Ecophysiological studies on the flood tolerance of common ...

Ecophysiological studies on the flood tolerance ofcommon ash (Fraxinus excelsior L.) — impact of

root-zone hypoxia on central parameters of Cmetabolism

Thesis submitted in partial fulfilment of the requirements of thedegree Doctor rer. nat. of the

Faculty of Forest and Environmental Sciences,Albert-Ludwigs-Universitat Freiburg im Breisgau, Germany

by

Carsten Jaeger

Freiburg im Breisgau, Germany2008

Dean: Prof. Dr. Heinz Rennenberg

Supervisor: Prof. Dr. Heinz Rennenberg

Second Reviewer: Prof. Dr. Siegfried Fink

Date of thesis’ defence: 11 July 2008

iii

The present study was financially supported by the European Community, ProgrammeInterreg IIIB, NorthWest Europe; Project FOWARA (Problems in the Realization ofForested Water Retention Areas); Project Number B039

Contents

List of Figures xi

List of Tables xiii

List of abbreviations xvi

1 Introduction 1

2 Materials and Methods 11

2.1 Plant material and growth conditions . . . . . . . . . . . . . . . . . . . . . 11

2.1.1 Ash provenances . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.1.2 Seedlings of other species . . . . . . . . . . . . . . . . . . . . . . . . 13

2.2 Design, location and ambient conditions of the experiments . . . . . . . . . 14

2.2.1 Experiment I: Effect of flooding on the C metabolism of commonash provenances “Alb”, “Rhine” and “BFor” . . . . . . . . . . . . . 16

2.2.2 Experiment II: Effect of flooding on the C metabolism of commonash provenances “Alb”, “Ras” as well as F. angustifolia . . . . . . . 17

2.2.3 Experiment III: Effect of flooding on the photosynthetic perfor-mance of common ash and three other tree species of varying floodtolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2.2.4 Experiment IV: Effect of flooding on phloem transport of leaf-fed13C-glucose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2.2.5 Experiment V: Effect of flooding on stem-internal oxygen concen-trations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3 Sampling procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3.1 Collection of leaf and root material . . . . . . . . . . . . . . . . . . 20

vi CONTENTS

2.3.2 Collection of xylem sap . . . . . . . . . . . . . . . . . . . . . . . . . 20

2.3.3 Collection of phloem exudates . . . . . . . . . . . . . . . . . . . . . 21

2.4 Physiological and analytical methods . . . . . . . . . . . . . . . . . . . . . 22

2.4.1 Gas exchange measurements . . . . . . . . . . . . . . . . . . . . . . 22

2.4.2 Acetaldehyde exchange . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.4.3 Sapflow rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.4.4 Chlorophyll contents . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.4.5 Soluble carbohydrates . . . . . . . . . . . . . . . . . . . . . . . . . 30

2.4.6 Starch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.4.7 ADH activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

2.4.8 Soluble leaf proteins . . . . . . . . . . . . . . . . . . . . . . . . . . 36

2.4.9 Ethanol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

2.5 Flap-feeding of U-13C-glucose . . . . . . . . . . . . . . . . . . . . . . . . . 39

2.5.1 Feeding procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

2.5.2 Determination of 13C derived . . . . . . . . . . . . . . . . . . . . . 40

2.5.3 Calculation of the amount of 13C derived . . . . . . . . . . . . . . . 42

2.6 Oxygen measurements within the stem . . . . . . . . . . . . . . . . . . . . 44

2.6.1 Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

2.6.2 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

2.6.3 Manual calculation of the O2 concentration from raw data . . . . . 46

2.7 Biometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

2.7.1 Stem height and diameter . . . . . . . . . . . . . . . . . . . . . . . 48

2.7.2 Fresh and dry weight . . . . . . . . . . . . . . . . . . . . . . . . . . 48

2.7.3 Leaf area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

2.7.4 Leaf number . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

2.8 Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

2.8.1 General data analysis and statistics . . . . . . . . . . . . . . . . . . 49

2.8.2 Analysis of light and CO2 response curves . . . . . . . . . . . . . . 50

CONTENTS vii

3 Results 53

3.1 Experiment I: Effect of flooding on the C metabolism of ash provenances“Alb”, “Rhine” and “BFor” . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3.1.1 Leaf gas exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3.1.2 Soluble carbohydrates . . . . . . . . . . . . . . . . . . . . . . . . . 57

3.1.3 ADH activity, ethanol contents and acetaldehyde exchange . . . . . 64

3.1.4 Water content of leaf, root and stem . . . . . . . . . . . . . . . . . 72

3.1.5 Stem height and diameter . . . . . . . . . . . . . . . . . . . . . . . 73

3.1.6 Flood injuries and morphological adaptations . . . . . . . . . . . . 75

3.2 Experiment II: Effect of flooding on C metabolism of F. excelsior prove-nances “Alb” and “Rhine” as well as F. angustifolia . . . . . . . . . . . . . 79

3.2.1 Leaf gas exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

3.2.2 Pigment contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

3.2.3 Contents of soluble leaf proteins . . . . . . . . . . . . . . . . . . . . 83

3.2.4 Soluble carbohydrates and starch . . . . . . . . . . . . . . . . . . . 83

3.2.5 ADH activity, ethanol contents and acetaldehyde exchange . . . . . 90

3.3 Experiment III: Effect of flooding on the photosynthetic performance ofcommon ash and three other species of varying flood tolerance . . . . . . . 95

3.3.1 Light response curves . . . . . . . . . . . . . . . . . . . . . . . . . . 95

3.3.2 CO2 response curves . . . . . . . . . . . . . . . . . . . . . . . . . . 96

3.4 Experiment IV: Effect of flooding on phloem transport of leaf-fed 13C-glucose101

3.4.1 Feeding-derived 13C in the application leaf . . . . . . . . . . . . . . 101

3.4.2 Feeding-derived 13C in phloem exudates . . . . . . . . . . . . . . . 101

3.5 Experiment V: Effect of flooding on stem-internal oxygen concentrations . 105

3.5.1 O2 concentrations before flooding . . . . . . . . . . . . . . . . . . . 105

3.5.2 Response to flooding . . . . . . . . . . . . . . . . . . . . . . . . . . 105

3.5.3 Response to reaeration . . . . . . . . . . . . . . . . . . . . . . . . . 107

3.5.4 Determination of sapflow . . . . . . . . . . . . . . . . . . . . . . . . 107

3.5.5 ADH activity in bark tissue . . . . . . . . . . . . . . . . . . . . . . 108

viii CONTENTS

4 Discussion 117

4.1 Anaerobic root metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

4.2 Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

4.3 Carbohydrate metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

4.4 Stem-internal O2 concentrations . . . . . . . . . . . . . . . . . . . . . . . . 135

4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138

Summary 143

German Summary 147

Bibliography 151

Acknowledgements 167

List of Figures

1.1 Polder Erstein (France) as an example of forested water retention basinsat the Upper Rhine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Identifying characteristics of common ash . . . . . . . . . . . . . . . . . . . 6

2.1 Studied provenances of common ash (F. excelsior L.) . . . . . . . . . . . . 12

2.2 Provenance area HKG 81107 . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.3 Sampling scheme for experiments I and II . . . . . . . . . . . . . . . . . . 17

2.4 Ash experiment I - picture showing greenhouse with flooding basin . . . . . 18

2.5 Calibration curve for acetaldehyde . . . . . . . . . . . . . . . . . . . . . . . 28

2.6 Analysis of soluble carbohydrates by HPLC (chromatogram and standardcurves) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.7 ADH assay: determination of slopes for blind and main reaction . . . . . . 35

2.8 Calibration curve for Bradford protein assay . . . . . . . . . . . . . . . . . 37

2.9 Illustration of flap-feeding method and chemical structure of U-13C-glucose 40

2.10 Position of feeding leaf and sampled stem segments . . . . . . . . . . . . . 41

2.11 Stem-internal oxygen measurements . . . . . . . . . . . . . . . . . . . . . . 45

2.12 Oxygen measurements with needle-type micro-optode sensors (time of in-sertion marked by arrow). Approx. 30 min were required for the measuredconcentration to settle down to a stable level. Data were recorded every 5min. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3.1 Effect of flooding on net assimilation and stomatal conductance of threeF. excelsior provenances (experiment I) . . . . . . . . . . . . . . . . . . . . 54

3.2 Effect of flooding on net assimilation and stomatal conductance of threeF. excelsior provenances, expressed as percent of the controls (experiment I) 55

3.3 Analysis of the relationship between Amax and gs for experiment I . . . . . 57

x LIST OF FIGURES

3.4 Effect of flooding on contents of soluble carbohydrates in leaves of threeprovenances of F. excelsior (experiment I) . . . . . . . . . . . . . . . . . . 59

3.5 Effect of flooding on contents of soluble carbohydrates in leaves of threeprovenances of F. excelsior , expressed as % of the control (experiment I) . 60

3.6 Effect of flooding on contents of soluble carbohydrates in roots of threeprovenances of F. excelsior (experiment I) . . . . . . . . . . . . . . . . . . 62

3.7 Effect of flooding on contents of soluble carbohydrates in roots of threeprovenances of F. excelsior , expressed as % of the control (experiment I) . 63

3.8 Effect of flooding on contents of soluble carbohydrates in phloem exudatesof three provenances of F. excelsior (experiment I) . . . . . . . . . . . . . . 65

3.9 Effect of flooding on contents of soluble carbohydrates in phloem exudatesof three provenances of F. excelsior , expressed as % of the control (exper-iment I) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.10 Effect of flooding on contents of soluble carbohydrates in xylem sap of threeprovenances of F. excelsior (experiment I) . . . . . . . . . . . . . . . . . . 67

3.11 Effect of flooding on contents of soluble carbohydrates in xylem sap of threeprovenances of F. excelsior , expressed as % of the control (experiment I) . 68

3.12 Effect of flooding on alcohol dehydrogenase (ADH) activity in roots of threeprovenances of F. excelsior (experiment I) . . . . . . . . . . . . . . . . . . 69

3.13 Effect of flooding on leaf and xylem ethanol contents of three provenancesof F. excelsior (experiment I) . . . . . . . . . . . . . . . . . . . . . . . . . 70

3.14 Effect of flooding on leaf acetaldehyde exchange of three provenances ofF. excelsior (experiment I) . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

3.15 Effect of flooding on the water content of leaves, roots and stems of threeprovenances of F. excelsior (experiment I) . . . . . . . . . . . . . . . . . . 73

3.16 Effect of flooding on stem diameter and height of three provenances ofF. excelsior (experiment I) . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

3.17 Effect of flooding on leaf number and on the percentage of trees developingfresh leaves for three provenances of F. excelsior (experiment I) . . . . . . 75

3.18 Leaf loss after flooding and development of fresh leaves (experiment I) . . . 76

3.19 Decay of fine roots in the provenance “Alb” . . . . . . . . . . . . . . . . . 77

3.20 Effect of flooding on the dry weight of roots in three provenances of F. ex-celsior (experiment I) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

3.21 Formation of hypertrophied lenticels in flooded ash seedlings (experiment I) 78

3.22 Adventitious roots in ash and willow seedlings . . . . . . . . . . . . . . . . 78

LIST OF FIGURES xi

3.23 Effect of flooding on net assimilation and stomatal conductance of “Alb”,“Rhine” and F. angustifolia (experiment II) . . . . . . . . . . . . . . . . . 80

3.24 Effect of flooding on net assimilation (A) and stomatal conductance (B) of“Alb”, “Rhine” and F. angustifolia, expressed as percent of the controls(experiment II) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

3.25 Effect of flooding on leaf pigment content of “Alb”, “Rhine” and F. angus-tifolia (experiment II) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

3.26 Effect of flooding on soluble leaf protein contents of “Alb”, “Rhine” andF. angustifolia (experiment II) . . . . . . . . . . . . . . . . . . . . . . . . . 83

3.27 Effect of flooding on contents of soluble carbohydrates in leaf and root of“Alb”, “Rhine” and F. angustifolia (experiment II) . . . . . . . . . . . . . 85

3.28 Effect of flooding on contents of soluble carbohydrates in phloem exudatesand xylem sap of “Alb”, “Rhine” and F. angustifolia (experiment II) . . . 88

3.29 Effect of flooding on leaf (A) and root (B) starch contents of two prove-nances of F. excelsior and of F. angustifolia (experiment II) . . . . . . . . 90

3.30 Effect of flooding on leaf (A) and root (B) ADH activity in two provenancesof F. excelsior and in F. angustifolia (experiment II) . . . . . . . . . . . . 91

3.31 Effect of flooding on ethanol contents in leaf, root and xylem sap of twoprovenances of F. excelsior and F. angustifolia (experiment II) . . . . . . . 92

3.32 Effect of flooding on light response curves in ash, lime, oak and willow . . . 97

3.33 Effect of flooding on CO2 response curves in ash, lime, oak and willow . . . 99

3.34 Effect of flooding on the translocation of 13C in the phloem of ash, mapleand poplar seedlings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

3.35 Response of stem-internal O2 concentrations in ash, oak and poplar seedlingsto flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

3.36 Responses of stem-internal O2 concentrations to flooding and reaeration . . 110

3.37 Stem-internal O2 concentration vs. sensor implantation height . . . . . . . 111

3.38 Change of O2 concentration in response to flooding vs. sensor distance fromwater surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

3.39 Effect of flooding on stem-internal O2 and sapflow in oak . . . . . . . . . . 113

3.40 Effect of flooding on stem-internal O2 and sapflow in poplar . . . . . . . . 114

3.41 Effect of flooding on ADH activity in bark of ash, maple, oak and poplarseedlings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

4.1 Alteration of carbohydrate contents by flooding . . . . . . . . . . . . . . . 126

List of Tables

2.1 Stand geographic coordinates and pedoclimatic characteristics of the ashprovenances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.2 Provenance, age and size of other seedlings . . . . . . . . . . . . . . . . . . 14

2.3 Ambient conditions at the different locations of the experiments . . . . . . 15

2.4 Device settings used for photosynthesis measurements . . . . . . . . . . . . 24

2.5 Protocol used for sequential recording of light and CO2 response curves . . 25

2.6 Custom GFS-3000 program used for sequential recording of light and CO2

response curves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.7 HPLC gradient used for separation of carbonyl compounds . . . . . . . . . 27

2.8 Natural carbon isotope ratios used for computation of excess 13C derivedfrom feeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.1 Statistical analysis of ADH activity in roots of flooded ash seedlings (ex-periment I) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

3.2 Comparison of leaf gas exchange results between experiments I and II . . . 82

3.3 Statistical analysis of soluble carbohydrate contents in flooded seedlings of“Alb”, “Rhine” and F. angustifolia (experiment II) . . . . . . . . . . . . . 86

3.4 Summary of parameters obtained from light and CO2 curve analysis . . . . 96

3.5 Molar amounts of 13C derived from feeding . . . . . . . . . . . . . . . . . . 102

3.6 Stem-internal O2 concentrations in ash, oak and poplar seedlings in re-sponse to flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

List of abbreviations

Amax CO2 CO2-saturated net assimilation rateAmax light-saturated net assimilation rate at ambient CO2

Aqe apparent quantum yielde.g. for exampleε apparent carboxylation efficiencyE transpiration rategs stomatal conductance to water vapour“Alb” F. excelsior provenance “Schwabische Alb” (Swabian Jura)“BFor” F. excelsior provenance “Black Forest”“Rhine” F. excelsior provenance from an alluvial forest of the river Rhinea.s. air saturationa.s.l. above sea levelADH alcohol dehydrogenaseAGS amyloglucosidaseALDH acetaldehyde dehydrogenaseANOVA analysis of varianceANP anaerobic proteinATP adenosine triphosphateBSA bovine serum albuminC carbonCAP chloramphenicolCCP CO2 compensation pointChl chlorophyllCO control (treatment, plant, . . . )ddH2O double-distilled waterDNPH 2,4-dinitrophenylhydrazineDW dry weightEDTA ethylenediaminetetraacetic acidEtOH ethanolfig. figureFL flooded (treatment, plant, . . . )FW fresh weightHKG “Herkunftsgebiet”, (certified) provenance areaHPAE-PAD high pressure anion exchange chromatography with pulsed amperometric

detectionHPLC high performance liquid chromatographyHSD honest significant difference

xvi LIST OF ABBREVIATIONS

IRGA infrared gas analyzerIRMS isotope ratio mass spectrometerLCP light compensation pointMS mass spectrometerna not availableNAD+ nicotinamide adenine dinucleotide, oxidised formNADH nicotinamide adenine dinucleotide, reduced formnd no dataNLME non-linear mixed effects modelPAR photosynthetically active radiationPCR polymerase chain reactionPDB Pee Dee Belemnite (C isotope standard)PDC pyruvate decarboxylasePFA perfluoroalkoxyPPFD photosynthetic photon flux densityPVPP polyvinylpolypyrrolidoneRH relative humidityrpm rotations per minuteRubisco ribulose-1,5-bisphosphate carboxylase/oxygenaseSD standard deviationsec. sectiontab. tableteflon tetrafluorethyleneTSC total soluble carbohydratesU enzyme unitUV ultraviolet lightVIS visible light

Chapter 1

Introduction

Flooding — ecological factor and natural hazard

Inundations of varying temporal and spatial extents occur in almost all regions of the

world. These are in most cases due to natural causes. Heavy precipitation can pro-

duce large water masses that exceed the absorption capacity of soils and cause small or

large-scale waterlogging of land areas. Rivers overflow their banks, drowning surrounding

regions, as a consequence of intense rainfall or rapid snowmelt in springtime. The sea can

deluge large coastal areas in the wake of storm surges or spring tides. Extensive floodings

also occur in urban areas, which, however, is often exacerbated by large-scale soil sealing

and thus influenced by human activities.

Flooding is an ecologically important factor for wetlands, under whose influence manifold

habitats are shaped. Mires, for example, often form in plain tracts or in the neigh-

bourhood of lake banks and are characterised by permanent, stagnant flooding. Bogs,

widespread in cold temperate climes of the northern hemisphere, resemble mires in terms

of hydrological conditions but accumulate acidic peat, arising from dead plant material.

Other wetland systems such as mangrove forests, by contrast, exhibit periodical flooding,

in this particular case as a result of the diurnal turn of the tides. Temporary, but regular

inundation is also representative of alluvial forests which connect aquatic and terrestrial

environments along rivers and streams. In Central Europe, alluvial forests rate among

the most productive and species-rich ecosystems (Schnitzler, 1994), due to the positive

effects of flooding on soil fertility on the one hand, and flood-caused formation of diverse

small-scale habitats on the other hand (e.g. Carbiener and Schnitzler, 1990). Each of

these wetland types harbours a varied flora and fauna, which is often specifically adapted

to the prevailing flooding regimes and not seldomly includes endemic species (Cronk and

2 Introduction

Fennessy, 2001).

Wetlands cover 6 % of the world’s land surface (WWF-International, 2004). Due to human

land use change, however, their continued existence is severely endangered, in fact on a

global scale. In Asia, 50 % of mangrove forests have been lost already, and conversion

into other land use forms, e.g. ponds for shrimp farming, takes place at an increasing pace

(Naylor et al., 1998). In North America, about half of the forested wetlands were, due to

highly fertile soils, converted into cropland as early as by the 1930s (Conner, 2001), leaving

locally only 25 % of the original wetland cover (e.g. in the Mississippi River floodplains;

Battaglia et al., 1995). In Central Europe, wetland loss is similarly serious, affecting most

notably alluvial forests (UNEP, 2000; Halkka and Lappalainen, 2001). These were already

decimated by measures of river regulation in the 19th and 20th centuries (FOWARA, 2006),

and are still converted into agricultural, urban and industrial areas (WWF-International,

2004). European alluvial forests presently span 670 km2, equating to merely 12 % of their

original distribution.

Floodings represent an important ecological factor, however, they also represent a nat-

ural hazard that costs many peoples’ lives and causes huge economic losses in terms of

crop production. In low-lying countries such as Bangladesh, floodings can reach catas-

trophic dimensions, with often two thirds of its land inundated during monsoon season

Figure 1.1: Polder Erstein (France) as an exam-

ple of forested water retention basins at the river

Rhine. At high water, such flood protection facilities

along the Upper Rhine are flooded, mitigating runoff

peaks and thereby reducing downstream hazards of

inundation.

(Brammer, 1990a). The economic impact

of flooding on these and other develop-

ing countries is immense, not least because

technical flood protection measures such

as river embankments are often lacking

(Brammer, 1990b). In developed countries,

by contrast, the most severe consequences

of inundations can often be mitigated, ow-

ing to enormous resources invested in tech-

nical flood protection. However, excep-

tional inundation events in the 1990s and

at the beginning of the 21th century at

the rivers Rhine and Elbe have demon-

strated that these technical solutions may

also meet their limit. This may particu-

larly apply for the future, since Central Eu-

rope will likely face increased winter rain-

fall frequency and intensity (IPCC, 2007),

resulting in increased flooding probabili-

ties in the Rhine basin (Middelkoop et al.,

3

2001; Pfister et al., 2004). Modern flood management efforts at big stream systems such

as the Rhine therefore focus on restoring lost retention space rather than further increas-

ing embankment height (FOWARA, 2006). This has the intended side-effect that former

riparian forests are reconnected to the flood dynamics of the river (Klein et al., 1994),

thereby restoring valuable floodplain habitats. As one of these measures, water retention

basins are built upstream with the purpose of absorbing exuberant water masses at ex-

treme flooding events, thereby reducing downstream risks of inundation. In some of these

basins, which are often forested (fig. 1.1), additional “ecological floodings” are carried out

at regular intervals to favour near-natural vegetation and “train” trees towards higher

flood resistance (Siepe, 1994, 2006; FOWARA, 2006).

Impact of flooding on soil and plant

Soil

Any adverse effect of flooding on non-adapted plants is primarily due to rapid elimination

of oxygen from flooded soils (Armstrong et al., 1994). Air in soil pores is replaced by water,

resulting in 30 times lower oxygen concentrations as compared to aerated soils (Armstrong

et al., 1994). Oxygen diffusion into water-saturated soils is decelerated by a factor of 104.

Residual oxygen pockets are consumed by plant root respiration and aerobic microorgan-

isms within hours or days (Drew, 1992). Thereby, an ideal environment for anaerobic

microorganisms is established, whose metabolic activity results in the accumulation of

carbon dioxide, ammonium and sulfide (Ponnamperuma, 1972, 1984). Micro-nutrients

such as phosphorous, iron and manganese are chemically reduced, thereby decreasing

their availability for plant growth and development. In addition, heavy metals (cadmium,

nickle and zinc) may become soluble and cause contamination of anoxic soils (Kashem

and Singh, 2001).

Plant physiological response

With oxygen increasingly depleted in the soil, plant roots are more and more deprived of

the possibility to continue aerobic energy metabolism. Most organisms, including higher

plants, possess anaerobic pathways (Kennedy et al., 1992) which can in part substitute

ATP and NAD+ regeneration under hypoxia. However, energy efficiency of these path-

ways is drastically lower compared to aerobic respiration. Alcoholic fermentation, for

example, the most important fermentative pathway in hypoxic plant roots (Good and

Muench, 1993), yields only 2 mol ATP per mol glucose consumed, as opposed to 36 mol

4 Introduction

ATP per mol glucose gained by aerobic respiration (Stryer, 1996). As a consequence,

carbohydrate consumption can be strongly increased (“Pasteur effect”), resulting in sub-

strate depletion in hypoxic roots of several tree species (reviewed in Kreuzwieser et al.,

2004). In other species, however, soluble carbohydrate contents increase under flooding

(Albrecht and Biemelt, 1998; Geigenberger, 2003, e.g. ), possibly due to decreased con-

sumption for growth (Albrecht et al., 2004) or decreased carbohydrate partitioning into

structural compounds (Barta, 1987; Kogawara et al., 2006). Moreover, high fermentation

rates may result in self-poisoning with the fermentative end product ethanol (McManmon

and Crawford, 1971), or the more toxic acetaldehyde, which can build up in the roots from

ethanol after reaeration of the soil (Crawford and Braendle, 1996).

One of the earliest symptoms of hypoxia-stressed plants is a marked closure of leaf stom-

ata, measurable within few hours of inundation (Jackson, 2002) even in highly flood-

tolerant tree species such as bald cypress (Nyssa sylvatica; Pezeshki et al., 1996). The

response is associated with hormonal signals originating from the flooded roots (Else et al.,

1995; Jackson, 2002). Stomatal closure can contribute to the preservation of high leaf wa-

ter potentials, which would otherwise decrease due to reduced hydraulic conductivity of

the roots (Else et al., 2001; Tournaire-Roux et al., 2003; Kreuzwieser et al., 2004). On the

other hand, it also causes leaf-internal CO2 to decrease (Farquhar et al., 1980), thereby

reducing carbon fixation rates in most plant species investigated (Kozlowski, 1997). De-

spite reduced assimilation, concentrations of photoassimilates have been found to increase

in leaves of flooded herbaceous and tree species (e.g. Wample and Davis, 1983; Vu and Ye-

lenosky, 1991; Gravatt and Kirby, 1998), as well as in whole shoots of seedlings (Islam and

Macdonald, 2004). This accumulation has been connected to disturbed assimilate translo-

cation to sink tissues (Saglio, 1985; Barta, 1987; Kreuzwieser et al., 2004; Kogawara et al.,

2006).

As a consequence of disturbed physiological functioning, vegetative and reproductive

growth of non-adapted plants are negatively affected by flooding (Kozlowski, 1984; Gibbs

and Greenway, 2003). Overall viability decreases, resulting in increased mortality rates

(Kozlowski, 1997). Bark and roots may suffer structural damage, which increases their

susceptibility to fungal infestations, e.g. by Phytophthora zoospores which are spread

with the flood water (Kozlowski, 1997; Jung and Blaschke, 2004). Seed germination and

seedling development are partially or entirely retarded by hypoxia (e.g. Perata and Alpi,

1993). As a result of these effects, regular floodings alter species frequency and composi-

tion of a given area (Crawford, 1992).

5

Plant adaptations to flooding

Flood-tolerant species possess different adaptations that enable them to withstand peri-

ods of soil anoxia. Morphological and anatomical features like hypertrophied lenticels and

aerenchyma in stem and roots allow for enhanced internal aeration, supplying oxygen to

the flooded roots (Colmer, 2003; Voesenek et al., 2006). Formation of these adaptations is

induced by a hormonal signal (e.g. ethylene) originating from the flooded roots (Jackson,

2002). Oxygen arriving at the roots facilitates aerobic metabolism, but also oxidation of

the surrounding rhizosphere, thereby enabling the uptake of minerals (Kozlowski, 1997).

Adventitious roots are developed within the flooded stem section to increase water as well

as mineral uptake and compensate for loss of original roots (Gomes and Kozlowski, 1980;

Voesenek et al., 2006). Furthermore, accelerated shoot elongation can represent an escape

reaction to avoid complete submergence (Siebel and Bouwma, 1998; Voesenek et al., 2003;

Visser et al., 2003). All these responses have in common that direct consequences of hy-

poxia are mitigated by improved access to oxygen (“tolerance by avoidance”). Metabolic

adaptations, by contrast, comprise those abilities that convey “true” hypoxia tolerance tis-

sues. Features required for sustained anaerobic energy metabolism include (1) the ability

to switch to anaerobic fermentation pathways, involving expression of anaerobic proteins

(ANPs; Sachs et al., 1996); (2) the provision of extensive energy resources and their re-

plenishment by sustained assimilate transport (Greenway and Gibbs, 2003; Kreuzwieser

et al., 2004; Kogawara et al., 2006); (3) the elimination of potential cell toxins which

occur as intermediate or end products of the fermentation processes (Armstrong et al.,

1994); (4) down-regulation of metabolic activities that are not required or essential under

anaerobic conditions (Drew, 1997; Albrecht and Biemelt, 1998; Albrecht et al., 2004).

Common ash

Distribution and ecology

Common ash (F. excelsior), a deciduous tree reaching heights of 40 meters, abundantly

occurs in Northern, Central and parts of Southern Europe. The distribution area is

characterised by mean annual temperatures of 4–12 ◦C and reaches from 60th degree

of latitude in Norway to Northern Spain and Central Italy (Marigo et al., 2000)1. The

climatic limit is due to cold winters in the north and to hot summers in the south (Wardle,

1961). The altitudinal limit amounts to ca. 1650 m a.s.l. in Central Europe (Wardle, 1961).

1A recent distribution map has been made available by the FRAXIGEN project (FRAXIGEN 2005;www.fraxigen.net)

6 Introduction

Figure 1.2: Identifying characteristics of common

ash. Source: “Baume”. Verlag Werner Dausien,

Hanau (1986).

Common ash is a member of the Oleaceae

family of plants, which comprises 25 gen-

era and approx. 600 species (Wallander and

Albert, 2000). The eponymous species of

the Oleaceae, Olea europea (olive tree), is

widespread in in Southern Europe. The

genus Fraxinus includes 65 deciduous tree

and shrub species, distributed in all cli-

mates of the earth (Hane, 2001). Apart

from F. excelsior , three Fraxinus species

are autochthonous in Europe, namely

narrow-leaved ash (F. angustifolia Vahl),

flowering ash (manna ash, F. ornus L.) and

moraine ash (F. holotricha Koehne). The

present thesis was focused on F. excelsior ,

but also included studies on the flood tol-

erance of F. angustifolia.

F. excelsior occurs on alluvial stands with

fresh to wet soils, but also on the rather

dry calcareous soils of mountainous sites,

e.g. the Swabian Jura. It is described as

a site-demanding species, requiring base-

saturated, nutrient-rich and fresh to very

moist but well-drained soils (Kerr and Ca-

halan, 2004; Kerr, 1995; Scheller, 1977; El-

lenberg, 1996). Its high requirements for calcium are fulfilled on calcareous as well as

on alluvial soils, with the latter regularly fertilised by floodwater (Rittershofer, 2001).

Common ash is practically absent on nutrient-poor soils, underlining that soil fertility is

clearly a limiting factor (Binner et al., 2000).

In riparian forests, F. excelsior is often associated with alder Alnus glutinosa, oak Quercus

robur and elm Ulmus spec., forming Alno-Padion and Querco-Ulmetum communities,

respectively (Schnitzler, 1994; Marigo et al., 2000). Moreover, F. excelsior is part of

numerous non-alluvial communities, reflecting its large ecological amplitude (reviewed in

Marigo et al., 2000).

7

Flood tolerance of common ash

As a main representative of hardwood alluvial forests of temperate Europe, common

ash must cope with moderate, but regular inundation. At the river Rhine, for instance,

flooding periods in this habitat on average amount to 1–4 days during the vegetation

period, although they can extend to 35 days in years with a high runoff (Michiels and

Aldinger, 2002). While ash is a dominating species in this zone of the riparian forest,

lower lying zones with higher inundation periods (15–30 days) are dominated by elm and

oak, featuring ash only as a transgressing tree species (Michiels and Aldinger, 2002). This

distribution pattern gives a first indication of the maximum duration that ash is able to

endure in oxygen-depleted soil. In agreement with this estimate, the critical threshold for

damage development in adult ash was assessed at 35 days of waterlogging, while 60 days

resulted in widespread dieback of trees (Spath, 1988; FOWARA, 2006). For common ash,

stagnant (as opposed to flowing) water seems to be particularly harmful (Ubysz, 2001;

FOWARA, 2006).

Growth and mortality rates of juvenile ash under flooding was studied by Siebel and

Bouwma (1998) who found that one-year-old seedlings survived shallow flooding for at

least three months, with similar results obtained for pedunculate oak (Quercus robur).

Consistently, two-year-old seedlings of common ash showed unaffected survival rates after

120 days of root-zone flooding and even increased diameter, but no height growth (Frye

and Grosse, 1992). Iremonger and Kelly (1988) compared survival rate, height growth

and dry weight of common ash seedlings subjected to waterlogging for the whole growing

season with other species. Survival rate was unaffected in ash, alder (Alnus glutinosa) and

willow (Salix cinerea ssp. oleifolia), whereas birch (Betula pubescens) showed increased

mortality. Height growth was not reduced, however, the dry weight of seedlings harvested

at the end of the growing season was significantly lower than in the unflooded plants.

The flood tolerance of ash seedlings has been attributed, among others, to morphogenetic

features like adventitious rooting (Marigo et al., 2000). Thus, literature indicates a con-

siderable flood resistance for common ash seedlings which may, astonishingly, surpass the

one of mature trees (cf. Gill, 1970).

Ecotypes of common ash

The observation that ash is distributed in floodplains as well as on hill slopes, has led to

the assumption that different ecotypes have evolved in the two environments of contrasting

water availability. Speculations about “soil ecotypes” or “soil races” date back to 1925,

where a distinction between moist-adapted “water ash” and drought-adapted “limestone

8 Introduction

ash” was made (Munch and Dieterich, 1925). In a common garden experiment, growth

and biomass production differed between alluvial and “limestone” provenances, with the

mountainous provenance growing faster and producing more fresh weight on a dry soil

than the floodplain provenance. In addition, there were indications of morphological

differences such as leaf hairiness, characteristic of many drought-adapted plants. However,

a similar investigation with one “limestone” provenance and two “water” provenances from

Switzerland did not indicate differences in growth or phenological variables (Leibundgut,

1956). Weiser (1995) came to the same conclusion after a 33-year growth trial with two

floodplain and two limestone provenances.

Other provenance trials with ash revealed differences in growth and viability between

provenances, interacting with the study site or soil type tested (Cundall et al., 2003;

Kleinschmit et al., 1996; Savill et al., 1999). However, none of these studies specifically

tested for variables of flood tolerance. Thus, while the terms “limestone ash” and “water

ash” are still used in more recent publications (Landolt, 1977), it is still not clear if they

represent different ecotypes or the large ecological amplitude of common ash (Marigo

et al., 2000). In particular, it is not clear whether “floodplain ash” is adapted to flooding

and “limestone ash” is not.

Aims of the thesis

Although a number of studies investigated the growth and survival rate of ash seedlings

under flooding (see above), none of these investigations included physiological aspects

such as leaf gas exchange, carbohydrate contents or alcoholic fermentation in the roots.

While some of these aspects were studied intensively in the American ash species Fraxi-

nus pennsylvanica (Gomes and Kozlowski, 1980; Gravatt and Kirby, 1998; Kozlowski and

Pallardy, 1979; Pereira and Kozlowski, 1977), comparable investigations for F. excelsior,

one of the most abundant species of the European alluvial hardwood forest, are lacking.

The central aim of the present study was to characterise the physiological response of

common ash to flooding. For this purpose, different controlled flooding experiments with

three-year-old common ash seedlings were carried out. The particular aims of these ex-

periments were to test the following hypotheses:

1. Common ash is physiologically well adapted to flooding periods, and cycles repre-

sentative of the hardwood alluvial forest.

To test this hypothesis, the seedlings’ response to an inundation period of 28 days,

including intermittent 7-day reaeration was tested. Leaf gas exchange, carbohydrate

9

contents as well as ADH activities and ethanol contents were determined at multiple

time points within this treatment scheme to describe hypoxia-related changes in C

metabolism.

2. Seedlings originating from an alluvial site represent a flood-adapted ecotype that

tolerates soil hypoxia better than seedlings of mountainous provenance.

It was speculated that seedlings of alluvial provenance may possess genetic adapta-

tions to flooding, allowing them to better cope with root-zone hypoxia than seedlings

originating from low flood risk areas. Such a genetic difference may be reflected by

differences on the physiological level. To test this hypothesis, the physiological re-

sponse of a potentially adapted provenance from the river Rhine floodplain was

compared to that of two potentially flood-sensitive provenances from the Black For-

est and Swabian Jura, respectively.

3. The high flood tolerance of closely related narrow-leaved ash (F. angustifolia) in

comparison with common ash is similarly reflected by differences in C metabolism

under hypoxia.

Narrow-leaved ash is a widespread tree species in Central and Eastern European

lowland forests (Kremer and Cavlovic, 2005). It was speculated that this high flood

tolerance is in part due to efficient carbon assimilation and utilisation under hypoxic

conditions. To test this conjecture, narrow-leaved ash seedlings were included in the

present experiments, yielding the possibility to directly compare their physiological

behaviour under flooding to that of F. excelsior seedlings.

4. The photosynthetic performance of common ash under flooding reflects its position

as a moderately flood-tolerant species within a spectrum of differently tolerant,

competing tree species of floodplain forests.

Photosynthetic performance of common ash in response to 14 days of flooding was

compared to that of flood-sensitive small-leaved lime (Tilia cordata Mill.), moder-

ately tolerant pedunculate oak (Quercus robur L.) and highly flood-tolerant purple

willow (Salix purpurea L.) by recording light and CO2 response curves of photosyn-

thesis. It was speculated that the order of flood tolerance of the species is reflected

by corresponding changes in parameters such photosynthetic capacity, apparent

quantum yield and apparent carboxylation efficiency in response to flooding.

5. Photoassimilate translocation in common ash from shoot to root is inhibited by

root-zone hypoxia.

It was supposed that continued supply of energy-rich carbon substrate to flooded

roots is an important prerequisite of flood tolerance (Gravatt and Kirby, 1998;

Kogawara et al., 2006). In order to test if assimilate translocation in common

10 Introduction

ash seedlings is affected by root-zone inundation, export of isotopically labelled

sugar from leaves and its basipetal translocation in the phloem was studied. For

comparison, the same investigation was carried out in a flood-sensitive (sycamore

maple; Acer pseudoplatanus L.), and in a highly tolerant (American aspen; Populus

tremula L.) tree species.

6. Stem-internal oxygen concentrations in common ash are severely affected by root-

zone flooding.

After prolonged inundation events, common ash (among other species) in the field

shows severe bark injuries, including pronounced dieback of the vascular cambium

at the respective positions (FOWARA, 2006). It was speculated that this damage to

the cambium may be caused by restricted oxygen supply from surrounding tissues,

including the wood. As a first approach to this problem, stem-internal oxygen con-

centrations in stems of common ash seedlings were followed before, during and after

flooding events. It was also tested how moderately flood-tolerant pedunculate oak

Q. robur and highly tolerant Populus tremula × alba responded to this treatment.

Chapter 2

Materials and Methods

2.1 Plant material and growth conditions

2.1.1 Ash provenances

Seeds of Fraxinus excelsior L. were collected from three natural stands in the federal

state of Baden-Wuerttemberg (South Germany) (fig. 2.1). The stand near Rastatt (in the

following, “Rhine”) is located in a natural riparian forest at the river Rhine with regular

flooding of high intensities. The stands on the Swabian Jura (Schwabische Alb, “Alb”)

and in the Black Forest (“BFor”) are located in mountainous regions (470 and 880 m

a.s.l., respectively) which are not affected by flooding events. The climate at the Black

Forest site is characterised by a lower annual average temperature (5.93 ◦C) and higher

annual precipitation (1449 mm) as compared to the Rhine site (10.48 ◦C, 857 mm). The

Swabian Jura site is intermediate in both parameters (8.61 ◦C, 964 mm). Geographical

coordinates and other pedoclimatic properties of the stands are given in table 2.1.

Seed collection was carried out in August 2001 (“Alb”, “Rhine”) and October 2001

(“BFor”). After harvest, the seeds were transferred to a soil/turf mixture (7-L pots)

and grown in the garden of the Forest Research Institute Baden Wurttemberg (FVA,

Freiburg, Germany) under ambient light and temperature conditions. Protection against

frost was provided by a plastic foil cover. Irrigation was carried out with tap water. Due

to the different collection times, the “BFor” plants germinated one year later and were

therefore one year younger than “Alb” and “Rhine”.

12 Materials and Methods

Rhine

Alb

BFor

Figure 2.1: Studied provenances of common ash (F. excelsior L.). “Rhine” is a population froma regularly flooded alluvial stand near Rastatt, Baden-Wurttemberg, Germany, while “Alb” and“BFor” represent mountainous regions with low risk of flooding. See text and tab. 2.1 for details.Maps modified from the Library of University of Texas, USA (http://www.lib.utexas.edu) andhttp://www.wikipedia.de, respectively.

Table 2.1: Geographic coordinates (GC) and pedoclimatic characteristics of the stands from which ashseeds were collected. The “Alb” stand is located near Bad Urach in the Swabian Jura, the “Rhine” standclose to the river of the same name near the city of Rastatt (Upper Rhine Valley) and the “BFor” standnear Oberrimsingen/Zastlertal in the Black Forest. Alt., altitude (m a.s.l.); T*, annual averages of dailymaximum (Tx), daily minimum (Tn), daily mean at 2 m above the ground (Tm), daily minimum at groundlevel (Tg); Rd, daily precipitation (mm); Ry, annual precipitation (mm); SMR, soil moisture regime andFF, flooding frequency after the USDA Soil Taxonomy System. N, none; FQ, frequent. Modified fromDacasa-Rudinger and Dounavi (2008).

Stand GC Alt. Tx Tn Tm Tg Rd Ry ST SMR FF“Alb” 48 ◦ 29’ 24” N

9 ◦ 24’ 0” E471 13.67 4.38 8.61 3.45 26.4 964 rendzic

leptosol/calcaricregosol

udic-aquic N

“Rhine” 48 ◦ 51’ 35” N8 ◦ 7’ 48” E

155 14.98 6.27 10.48 3.82 23.5 857 gleysol/fluvisol

xeric FQ

“BFor” 47 ◦ 55’ 47” N7 ◦ 56’ 24” E

883 11.26 1.32 5.93 −8.5 39.7 1449 cambisol udic-mesic N

2.1 Plant material and growth conditions 13

Figure 2.2: Provenance area HKG 81107. Ash seedlings from this provenance area were used inexperiments III, IV and V. The area comprises a large part of Baden-Wurttemberg, Germany, includingthe stands “Alb” and “BFor”. Source: “Herkunftsempfehlungen fur forstliches Vermehrungsgut in Baden-Wurttemberg”. FVA, Freiburg, Germany.

2.1.2 Seedlings of other species

In addition to the different F. excelsior provenances, seedlings of pedunculate oak (Quer-

cus robur L.), sycamore maple (Acer pseudoplatanus L.), small-leaved lime (Tilia cor-

data Mill.), American aspen (Populus tremula L.) and purple willow (Salix purpurea L.)

were investigated. These were obtained from a tree nursery in South Germany (Baum-

schule Sellner, Hohenstein-Oberstetten, Germany) (table 2.2). Additional ash seedlings

of the provenance region HKG 81107 (“Suddeutsches Hugel- und Bergland”; fig. 2.1)

were purchased from the same tree nursery. Seedlings of narrow-leaved ash (F. angus-

tifolia Vahl.), originating from Portugal, were purchased from a French tree nursery

(Pepinieres Naudet, Leuglay/Cote d’Or, France). Seedlings of Populus tremula × alba

were produced by micro-propagation as described by Hauberg (2008).

The seedlings from the German tree nursery were raised and delivered in soft-walled con-

tainers, reducing root loss during excavation and transport. F. angustifolia was delivered

with naked roots. After arrival in February or March (before bud break), the seedlings

were transferred to 7 L-pots containing a soil-sand mixture of 30 % soil (Floradur; Flor-


Table 2.2: Provenance, age and size of the ash, maple, lime, oak, poplar and willow seedlings. Allseedlings were obtained from tree nursery Sellner (Hohenstein-Oberstetten, Germany), with the excep-tion of F. angustifolia which was purchased from a french tree nursery (Pepinieres Naudet, Leuglay/Coted’Or, France). Age is specified as “x+y” where “x” is the number of seasons the seedling was grown in aseedbed and “y” is the number of seasons the seedling was grown in a transplant bed. Height classesare given according to standard tree nursery sorting.

Species Provenance Age (yrs) Height (cm) Stem diameter atstem basis (cm)

Pedunculate oak(Quercus robur L.)

Provenance area81709: SuddeutschesHugel- und Bergland

sowie Alpen

2+1 60–100 1–2

Small-leaved lime(Tilia cordata Mill.)

Germany 2+1 60–100 1–1.5

American aspen(Populus tremula L.)

Germany 2+1 80–120 1–1.5

Purple willow(Salix purpurea L.)

Germany 2+1 80–120 1–1.5

Sycamore maple(Acer pseudopla-tanus L.)

Germany 2+1 60–100 1–1.5

European ash(Fraxinus excel-sior L.)

Provenance areaHKG 81107:

Suddeutsches Hugel-und Bergland

2+1 60–100 1–1.5

Narrow-leaved ash(Fraxinus angustifo-lia Vahl.)

Portugal 2+1 80–100 1–1.5

agard, Oldenburg, Germany), 30 % rough-grained sand (1–2.2 mm), 30 % fine-grained

sand (0.7–1.22), 10 % perlite (Knauf, Dortmund, Germany) and 3 g L-1 long-term fer-

tiliser (Basacote Plus 12M; Compo, Munster, Germany). Before use in experiments, the

plants were grown for at least three months under long-day conditions (16/8 h) at a light

intensity of approx. 200 µmol m-2 s-1 at the highest leaf. Irrigation was performed every

other day with tap water. Only healthy trees with intense root growth were used.

2.2 Design, location and ambient conditions of the experi-

ments

In the following sections, the different experiments of the present study, carried out be-

tween 2003 and 2006, are described. An overview of location and ambient conditions is

given in table 2.3.

2.2 Design, location and ambient conditions of the experiments 15

Table 2.3: Ambient conditions and locations of the different experiments. CTP, Chair of Tree Physiology,Freiburg, Germany; FVA, Forest Research Institute Baden-Wuerttemberg, Freiburg, Germany.

Name of experiment(s) Ambient conditions LocationExperiment I Light: shaded daylight, no

supplemental lighting supplied,100–300 µmol m-2 s-1 at the heightof the highest leaves

Day/night cycle: as natural inMay-July, i.e. 14–16 h daylight

Temperature: uncontrolled- Range (day): 18–30 (max. 36 ◦C)- Range (night): 15–20 ◦C

Humidity: uncontrolled(40–90 % RH)

Greenhouse (FVA)

Experiment IIExperiment IVExperiment V (ash)

Light: shaded daylight,supplemental lighting supplied byOSRAM HQL 400 bulbs, ≈500µmol m-2 s-1 at the highest leaves

Day/night cycle: 16/8 h

Temperature: controlled- during day: 25 ± 2 ◦C- at night: 20 ± 2 ◦C


Greenhouse (CTP)

Experiment IIIExperiment V (oaks 1–3)

Light: no direct daylight, ≈200µmol m-2 s-1 supplied at thehighest leaves

Day/night cycle: 16/8 h

Temperature: uncontrolled- during day: 22–28 ◦C- at night: 15–20 ◦C


Hall (CTP)

Experiment V (oak 4 and allpoplar seedlings)

Climate program:- Day/night cycle: 16/8 h- Light: approx. 200 µmol m-2 s-1

at the highest leaves (OSRAML58W/77 universal white halogenlamps and OSRAM violet halogenlamps)- Temperature: 20/15 ◦C- Humidity: 60/40 % RH

Climate Chamber (CTP)


2.2.1 Experiment I: Effect of flooding on the C metabolism of common

ash provenances “Alb”, “Rhine” and “BFor”

The first flooding experiment took place in 2004 and included the F. excelsior provenances

“Alb”, “Rhine” and “BFor”. 45 plants of each provenance were placed in a basin of 2 ×4 m (fig. 2.4) and flooded with tap water on day 0 of the experiment (fig. 2.3). The flood

height was approx. 10 cm above the upper pot rim. After 1, 3, 7 and 14 days of flooding,

four plants of each provenance were harvested. On day 15, all plants were taken out of the

basin. One week later (day 21), four plants of each provenance were harvested in order

to study the recovery from flooding. On day 22, the remaining plants were put again

into the basin and flooded for another two weeks, with four plants of each provenance

harvested after 3, 7 and 14 days of second flooding (= days 24, 28 and 35). The remaining

plants were withdrawn from the basin on day 36 and harvested after one week of recovery

(day 42). Four non-flooded plants which had been placed next to the basin (fig. 2.4) were

harvested as controls on each of the days of the experiment. The water in the basin was

permanently circulated by a pump to establish homogeneous water conditions. By this

means, local fluctuations in oxygen content or temperature were intended to be avoided.

The harvest procedure consisted of the following steps. First, photosynthesis was mea-

sured with a portable photosynthesis system (section 2.4.1.2). For this purpose, one plant

at a time was taken out of the basin and temporarily placed into a water-filled bucket for

easier access. After measuring photosynthesis of three leaves taking approx. 15–20 min,

acetaldehyde emission was determined for one leaf (section 2.4.2). This measurement was

carried out for 45 min. Next, diverse tissue samples were taken for metabolic analyses: (1)

young white fine roots were detached and immediately stored on ice for the determination

of ADH activity (section 2.4.7); (2) bark pieces were removed from the stem by means

of a razor blade for the collection of phloem sap (section 2.3.3.1) in which the content of

carbohydrates was determined (section 2.4.5); (3) the root was detached from the stem

and cleaned with tap water. Tissue samples of root and (4) leaves were frozen in liquid

N2 for the determination of soluble carbohydrate, starch and ethanol concentrations. (5)

Xylem sap was collected from the stem by means of the Scholander pressure technique

(section 2.3.2). Finally, leaves, stem and roots were weighed (FW) and separately stored

in paper bags for the later determination of dry weight (DW).

A number of extra plants was submitted to the flooding treatment and used for biometric

measurements at the end of the experiment (day 42), including determination of stem

height and diameter, leaf number and leaf damages (see section 2.7). A comparable

number of control plants was reserved for the same purpose.

The experiment took place from 2004-05-17 to 2004-06-30 in the greenhouse of the Forest


Research Institute Baden-Wuerttemberg (FVA), Freiburg, Germany (47 ◦ 58’ 29” N, 7 ◦

50’ 35” E). Temperature was controlled by automatic opening or closure of roof windows,

limiting its variation to 18–30 (max. 36 ◦C) during day and 15–20 ◦C at night. Humidity

was identical to ambient air (approx. 40–90 % RH). Exposure of the plants to direct

sunlight was avoided by roof shades, resulting in a PAR of 100 to 300 µmol m-2 s-1 at the

highest leaves.

Day of experiment

1 7 10 14 21 28 35 42

Exp

erim

ent I

IE

xper

imen

t I

5 flo

oded

plan

ts/p

rov.

5 co

ntro

lpl

ants

/pro

v.4

flood

edpl

ants

/pro

v.4

cont

rol

plan

ts/p

rov.

Figure 2.3: Sampling scheme for experiments I and II. At the beginning of the experiments, 45 (ex-periment I) or 10 (experiment II) plants per provenance, respectively, were subjected to the floodingtreatment (indicated by blue rectangles). After the durations indicated by arrows, n plants were har-vested with n = 4 in experiment I, and n = 5 in experiment II.

2.2.2 Experiment II: Effect of flooding on the C metabolism of common

ash provenances “Alb”, “Ras” as well as F. angustifolia

The second flooding experiment with different ash provenances was carried out in 2005.

Like in 2004, seedlings of the two F. excelsior provenances “Alb” and “Rhine” were

investigated. The provenance “BFor” was omitted, instead, plants of narrow-leaved ash

(F. angustifolia) were included. The plants of the two F. excelsior provenances were from


Figure 2.4: Ash experiment I. A basin of 2× 4 m was constructed from wooden planks and heavy pondfoil. A water pump was used for circulating the water, assuring homogeneous oxygen and temperatureconditions. Seedlings of the three F. excelsior provenances “Alb”, “Rhine” and “BFor” were randomlydistributed in the basin. The control plants are visible in the background.

the same charge as the plants in 2004, i.e. they were now four years old. F. angustifolia

was obtained from a tree nursery (Pepinieres Naudet, Leuglay/Cote d’Or, France) as

four-year-old seedlings.

10 plants of each group were placed into 100-L plastic tanks and flooded with tap water

up to a height of approx. 10 cm above the pot rim. After three and ten days of flooding,

five plants each were harvested. 2 × 5 unflooded control plants were harvested one day

later. Measurements and sampling procedure were similar to 2004, however, more care

was taken to sample all plants at the same time of the day in order to avoid diurnal

variation of photosynthesis, carbohydrate content etc. Therefore, the harvest was carried

out equally for all plants between 08:00 and 11:00 h. This was possible due to the overall

reduced number of plants in the experiment and by distributing the harvest of the different

provenances over multiple days. By contrast, the harvest in 2004 spanned the whole day

between 08:00 and 18:00 h.

As a further difference to 2004, the experiment was carried out in the greenhouse of the


Chair of Tree Physiology, Freiburg, Germany (48 ◦ 0’ 49” N, 7 ◦ 49’ 59” E). Temperatures

were adjusted to 25 ± 2 ◦C during day, and 20 ± 2 ◦C at night. Humidity was not

controlled and varied between 60 and 80 % RH. Incidence of direct sunlight was avoided

by roof shades. Supplemental lighting was supplied by OSRAM HQL 400 bulbs (Osram

GmbH, Munich, Germany). A day/night cycle of 16/8 h was used. Resulting PAR from

natural and artificial light sources was ≈400 µmol m-2 s-1 at the highest leaves.

2.2.3 Experiment III: Effect of flooding on the photosynthetic perfor-

mance of common ash and three other tree species of varying

flood tolerance

The effect of flooding on the trees’ gas exchange was studied in detail by recording light

and CO2 response curves of photosynthesis. In addition to F. excelsior , three-year-old

seedlings of lime (Tilia cordata), oak (Quercus robur) and willow (Salix purpurea) were

studied. Four to five plants of each species were placed into plastic tanks as already

described for the ash experiment in 2005 (section 2.2.2). Before flooding, a first set of

response curves was recorded (“day 0”), followed by second set after 14 days of flooding.

The same leaves were used on both days and for both types of measurements. As control,

four to five non-flooded plants were studied. The recording procedure is detailed in

section 2.4.1.3.

The experiment was carried out in the hangar of the Chair of Tree Physiology. Trees were

kept under long-day conditions (16/8 h). During day, a light intensity of approx. 200 µmol

m-2 s-1 was supplied at the highest leaf. The plants were adapted to these conditions for

three months before starting the experiment. Temperature and humidity ranged between

22 and 28 ◦C and 30 to 60 % RH, respectively. The measurements were made between

08:00 and 16:00 h, with the same time of the day used for each plant and measurement

day. As one set of response curves took approx. 2 h to record, plants were split into groups

of two to three individuals and measured on consecutive days.

2.2.4 Experiment IV: Effect of flooding on phloem transport of leaf-fed13C-glucose

Six to eight seedlings of ash, maple and poplar were submitted to the flooding treatment

as described above (section 2.2.2). After ten days of flooding, plants were fed with U-13C-glucose and harvested afterwards (see section 2.5). The experiment was carried out

in August 2006 in the greenhouse of the Chair of Tree Physiology under the conditions


described above for experiment II.

2.2.5 Experiment V: Effect of flooding on stem-internal oxygen concen-

trations

A series of experiments on the effect of flooding on stem oxygen concentrations was carried

out between October 2003 and November 2006. Three-year-old seedlings of ash, oak and

poplar (section 2.1.2) were placed into plastic tanks as already described. Oxygen sensors

were implanted into the stem (section 2.6.2), and oxygen was measured for three to four

days before starting the flooding treatment. The tanks were then filled with tap water,

and oxygen measurement was continued for four to six days. After this period, the water

was removed and the oxygen concentrations were recorded for another four to six days.

The experiments were performed at varying locations with different ambient conditions.

Ash was studied in the greenhouse of the Chair of Tree Physiology, with climate conditions

as already described for ash experiment 2005 (section 2.2.2). Oaks nos. 1–3 were measured

in the hangar of the Chair of Tree Physiology, oak 4 as well as poplars nos. 1–4 in a climate

chamber (Heraeus-Votsch, Hanau, Germany) under controlled environmental conditions

(table 2.3).

2.3 Sampling procedures

2.3.1 Collection of leaf and root material

Leaves from the second or third branch from the top were cut with a razor blade, put into

7-mL screw top tubes (Sarstedt, Nurnberg, Germany) and frozen in liquid N2. Fine roots

were cleaned under tap water, dried on paper tissue and frozen. Storage until analysis

was at −80 ◦C.

2.3.2 Collection of xylem sap

Xylem sap was collected from whole tree seedlings using the gas pressure technique by

Scholander et al. (1965). The upper 40–50 cm of the stem of seedlings were cut with

garden shears. At the cutting site, approx. 5 cm of the bark were removed to prevent

contamination with cellular constituents. The uncovered wood was cleaned with a few

mL ddH2O to remove remains of phloem sap and dried with paper. The plant was then

2.3 Sampling procedures 21

inserted into the pressure vessel (Soilmoisture, Santa Barbara, USA) with its top first.

The cut end of the stem was mounted on the screw top of the vessel which was sealed with

a teflon collar put over the peeled end of the stem. Approx. 2 cm of the peeled end were

left protruding to the outside. The vessel was then pressured with nitrogen gas (SWF

GmbH, Friedrichshafen, Germany). For this purpose, the pressure was slowly raised at

rates of max. 0.25 MPa min-1 until a first drop of xylem sap appeared at the cutting site.

This first drop was discarded by dabbing off the cutting site with paper tissue. For the

following 2 min, the pressure was kept constant and escaping xylem sap was collected

with a Pasteur pipette. The collected sap was transferred to a reaction rube, frozen in

liquid N2, and stored at −80 ◦C until analysis.

Previous studies showed that xylem sap obtained by this method was virtually free of

cellular contaminants (e.g. Schulte, 1998; Bartels, 2001). In the latter study, this was

shown in particular for ash seedlings. Both authors used ATP as a contamination marker

since this compound should not be present in pure xylem sap. As no significant amounts

of ATP were found in either of the studies, the authors considered the xylem sap samples

to be free of cytoplasmic contaminants.

2.3.3 Collection of phloem exudates

2.3.3.1 EDTA technique

As the phloem sap of most tree species cannot easily be accessed directly, it has to

be exudated from isolated bark pieces. An effective exudation method is the so-called

“EDTA technique” which was introduced by King and Zeevaart (1974) and modified by

Rennenberg et al. (1996). EDTA is an effective chelating agent for bivalent cations such as

Ca2+. Sieve tube elements that are wounded prevent leakage by sealing sieve plates with

the polysaccharide callose. As the formation of callose is a Ca2+-dependent process, the

sieve plate sealing can be inhibited by removing Ca2+ from the medium or by making it

inaccessible to biological processes. Therefore, sieve tube elements can be quantitatively

exudated despite the injuries due to the cutting.

For phloem exudation, a small piece of bark (≈200 mg) was removed from the stem and

washed with H2O to remove xylary contaminants. After drying the bark piece on a paper

tissue, it was weighed (FW) and transferred to a 7-mL screw cap tube containing 2 mL of

10 mM EDTA (Sigma, Munich, Germany), pH 7.0 (NaOH) and 15 µM of chloramphenicol

(CAP; Merck, Darmstadt, Germany). CAP, a bacteriostatic antimicrobial, was added to

inhibit microbial degradation of the exudated compounds. The exudation was carried out

for 5 h on ice. Finally, aliquots of the exudate were transferred to two reaction tubes (2


× 1 mL) and frozen in liquid N2. Storage was at −80 ◦C until analysis.

Contamination of phloem exudates was already investigated in other studies for ash (Bar-

tels, 2001) and oak (Schulte, 1998). In these studies, the activity of acid invertase was

quantified as a measure for contamination of the exudates with apoplastic and cyto-

plasmic constituents. None of the studies found significant activities of the enzyme and

therefore no signs of contamination. As the same technique was applied in the present

study, phloem exudates were assumed to be uncontaminated as well.

2.3.3.2 H2O technique

This method of phloem sap collection was used when samples were needed for C isotope

analysis (sec. 2.5). The EDTA technique could not be used for this purpose because

EDTA and CAP contain C atoms which alter the C isotope signature of the sample. This

was experimentally shown by Geßler et al. (2004) who found significantly higher δ13C

values for EDTA-exudated samples in comparison to H2O-exudated assays. In the H2O

technique, bark pieces are simply exudated in H2O which avoids affecting the isotope sig-

nature. However, the amount of exudated compounds is lower than in EDTA due to the

formation of callose (Geßler et al., 2004). In a preliminary experiment with “standard”

conditions (200 mg FW bark in 2 mL H2O), this was a problem because the amount of

C and N exudated was not sufficient for elemental analysis. To overcome this problem,

bigger bark pieces (500–1000 mg FW) were used, which were exudated in 5 mL of ddH2O.

Furthermore, the obtained exudate was completely evaporated in a speed vac (Christ,

Osterode, Germany) and resolved back in a lower volume of ddH2O (25 µL). Moreover,

the exudation period was extended to 18 h (default: 5 h). Microbial degradation of the

exudates during this period was prevented by keeping the samples at 4 ◦C. Possible enzy-

matic breakdown of sugars, e.g. hydrolysis of sucrose by released invertase, was irrelevant

for the present objective since the C isotope signature is not changed by this conversion.

The concentrated exudate finally yielded sufficiently high signals in C isotope analysis.

2.4 Physiological and analytical methods

2.4.1 Gas exchange measurements

Leaf gas exchange was measured with a portable photosynthesis system (GFS-3000, Walz,

Effeltrich, Germany). Two types of measurements were made: (1) determination of light-

saturated photosynthesis, and (2) recording of light and CO2 response curves. The pro-

2.4 Physiological and analytical methods 23

tocols used for these two types of measurements are described below. Subsequently, the

operation principle of the system is outlined.

2.4.1.1 Principle of operation of the photosynthesis system

The GFS-3000 is an open system, i.e. it operates with an open air stream. Air is sucked

in from the outside, flushed through the leaf cuvette and emitted to the environment

again. Before entering the cuvette, the air is analyzed by an infrared gas analyzer (IRGA)

which determines the concentration of CO2 and H2O. After leaving the cuvette, the air is

analyzed again, and from the difference in CO2 and H2O, A, E , gs and other parameters

are calculated by accounting for leaf area and air flow. Analysis of CO2 and H2O is realised

by two CO2 and two H2O channels.

In operation mode, the air is split into two airstreams. 50 % are flushed through the leaf

cuvette and analyzed at the outlet of the cuvette. The other half is analyzed directly by

the other two channels. The difference between “cuvette channel” and “reference channel”

is equivalent to the difference between input and output of the cuvette. However, for this

parallel measurement, it is essential that both channels are synchronised (calibrated) on

a regular basis. For this purpose, the air that is normally directed through the cuvette

is shortcut directly through the “cuvette channel”. Any offset between the two channels

measured in this situation can only be due to technical differences and is set to zero. These

zero points (ZPs) were recorded at start-up time, approx. every two hours of operation

and upon changing the CO2 concentration.

CO2 and H2O vapor concentration of the input air were regulated in a two-step procedure.

First, CO2 and H2O vapor were completely removed by a passage through soda lime (CO2

removal) and silica gel (H2O removal). Then, the two gases are re-added at defined

concentrations from a CO2 cartridge (Liss, Repcelak, Hungary) and humidifying granules

(“Stuttgarter Masse”), respectively.

2.4.1.2 Determination of light-saturated photosynthesis

A healthy fully developed leaf was chosen and inserted into the leaf cuvette. The leaf was

allowed to adapt to cuvette settings (humidity 12000 ppm ≈ 45 % RH, CO2 375 ppm,

PPFD 1000 µmol m-2 s-1, leaf temperature 25 ◦C; see table 2.4 for other device settings)

until stable readings of light-saturated net assimilation rate (Amax) and transpiration rate

(E ) were established. This was usually obtained within five to ten minutes. Leaf gas

exchange was then recorded for 2 min at an interval of 10 s, yielding 12 data points.

The recorded data were stored on the system and later transferred to a PC. The data


Table 2.4: Device settings used for “standard” photosynthesis measurements with the Walz GFS-3000system.

Parameter ValueHumidity 12000 ppm (≈45 % RH)CO2 375 ppmTemperature mode Leaf temperature controlSet temperature 25 ◦CIncident PPFD (“PAR top”) 1000 µmol m-2 s-1

Impeller speed 5, on a scale from 1 (lowest) to 9 (highest)Air flow rate 700 µmol s-1 (possible range 600–900 µmol s-1)Leaf adapter 4 cm2 (ash, willow), 8 cm2 (oak, lime)

included CO2 and H2O concentrations at the input and output of the leaf cuvette and

derived parameters. The 12 data points were averaged (= leaf mean). Three leaves were

measured per plant. Leaf means were averaged, giving the plant mean.

Suitable leaf area adapters were chosen for each species. These adapters were installed

in the leaf cuvette and defined the leaf area to be measured. For species with relatively

narrow leaves (ash, willow), the 4-cm2 adapter was used whereas for broader leaves (lime,

oak) the 8-cm2 adapter was applied.

The system was turned on one hour before usage following the manufacturer’s instructions

in order to assure stable readings of the infrared gas analyzers (IRGAs). Cuvette con-

ditions (see above) were activated directly after power-on. Zero points (synchronisation

of both CO2 and both H2O channels; see below) were recorded at the beginning of the

measurement and then after every hour. Chemicals (soda lime, silica gel, CO2 cartridges)

were exchanged as required.

2.4.1.3 Light and CO2 response curves

Light response curves were recorded by subjecting the same leaf to increasing light inten-

sities (PPFD) of 0, 50, 100, 200, 500, 1000 µmol m-2 s-1. Complete darkness was ensured

by wrapping the cuvette in black cloth which was removed during measurement of the

other light steps. One leaf per plant was allowed to adapt to each light level for 5 to

10 min. At each light level, six data points were recorded within 1 min. The recorded

values were averaged per light level and plant.

For CO2 response curves, the same leaf was sequentially exposed to increasing CO2 con-

centrations: 140 ppm, 250 ppm, 375 ppm, 700 ppm, 1400 ppm, 2000 ppm CO2 which were

automatically applied using a GFS-3000 program (table 2.6). Adaptation times were dif-

ferent for each CO2 level and ranged between 5 and 15 min (table 2.5). Zero points (ZPs)

were recorded after each change of CO2 concentration. If possible, CO2 curves were de-


Table 2.5: Protocol used for sequential recording of light and CO2 response curves.

Step Adaptationtime (min)

PPFD (µmolm-2 s-1)

CO2 (ppm) Comment

1 5 0 375 Start of lightcurve

2 5 50 ”3 7.5 100 ”4 7.5 200 ”5 12.5 500 ”6 12.5 1000 ”7 7 ” 140 Start of CO2

curve8 7 ” 250

(9) (8) (”) (375) omitted becauseidentical to step 6

10 8 ” 70011 8 ” 140012 8 ” 2000

Total duration:≈83 min

termined directly after the light curves on the same leaf. Other device settings (humidity,

air flow rate, etc.) were the same as already given for the “standard” measurements

(table 2.4).

2.4.2 Acetaldehyde exchange

2.4.2.1 Cuvette system

Emission of acetaldehyde from leaves of flooded ash seedlings was determined with a

purpose-built cuvette system. The cuvettes with a shape of a flat circular cylinder (height

≈ 3 cm, diameter ≈ 12 cm) were constructed from chemically inert teflon plates (Dyneon

GmbH, Burgkirchen, Germany). Teflon was used to inhibit adhesion and reaction of

acetaldehyde with the walls of the cuvette. The top cover was made of transparent PFA

foil to facilitate positioning of the leaf in the cuvette. A small fan within the cuvette

assured proper stirring of the air volume of 0.5 L. The leaf was introduced into the

cuvette through a slit in the wall of the cylinder which was sealed with a piece of teflon

tape.

During the experiment, the cuvettes were flushed with ambient air using teflon-coated

pumps (KNF Neuberger, Laboport, Freiburg, Germany). A constant flow rate of 1 L

min-1 was regulated by flow sensors (MAS, Kobold, Germany).


Table 2.6: Custom GFS-3000 program used for sequential recording of light and CO2 response curves.The program is a simple list of directives that are processed by the system line by line. Temporal controlis achieved by “Interval” directives (given in s).

"Remark ="," "

"Remark =","********************************"

"Remark =","***** General settings *****"

"Remark =","********************************"

"Remark ="," "

"Mode =","MP"

"Set value(Flow) =","750"

"Set H2O(ppm) =","12000"

"Impeller =","5"

"Set value(Tleaf) =","25.0"

"Set Light Control =","PARtop"

"Set value(CO2) =","375"

"Storing interval =","001/010"

"Remark ="," "

"Remark =","********************************"

"Remark =","***** Light curve *****"

"Remark =","********************************"

"Remark ="," "

"Comment =","*** LC: Light 0 ***"

"Set value(Light) =","0"

"Interval =","300"



"Interval =","300"



"Interval =","300"



"Interval =","450"



"Interval =","450"



"Interval =","750"

"Comment =","*** LC: Light 1000 ***"


"Interval =","750"

"Remark ="," "

"Remark =","********************************"

"Remark =","***** CO2 curve *****"

"Remark =","********************************"

"Remark ="," "

"Stop storing",""

"AutoZPirga =","0001/0060"

"Remark ="," "

"Remark =","*** start A/ci ***"

"Remark ="," "

"Start storing",""

"Remark =","******- Aci: CO2 140 ******-"


"Interval =","300"

"AutoZPirga =","0001/0060"

"Interval =","120"

"Remark =","******- Aci: CO2 250 ******-"


"Interval =","300"

"AutoZPirga =","0001/0060"

"Interval =","120"

"Remark =","******- Aci: CO2 700 ******-"


"Interval =","300"

"AutoZPirga =","0001/0060"

"Interval =","180"

"Remark =","******- Aci: CO2 1400 ******-"


"Interval =","300"

"AutoZPirga =","0001/0060"

"Interval =","180"

"Remark =","******- Aci: CO2 2000 ******-"


"Interval =","300"

"AutoZPirga =","0001/0060"

"Interval =","180"

"Remark ="," "

"Remark =","*** stop Aci & "

"Remark =","restore standard conditions ***"

"Remark ="," "

"Stop storing",""



2.4.2.2 Absorption of acetaldehyde to DNPH cartridges

Emitted acetaldehyde was collected on 2,4-dinitrophenylhydrazine (DNPH) cartridges

(Supelco, Munich, Germany) which were interconnected in the tubing system between

the cuvette and a pump. Air was sucked through the cartridge for 45 min at a flow

rate of 1 L min-1, binding all acetaldehyde emitted by the leaf within this period to the

DNPH matrix. This absorption is based on the reaction of acetaldehyde with DNPH to

acetaldehyde hydrazone.

As an alternative to the cuvette system, DNPH cartridges were connected to the photo-

synthesis system (section 2.4.1). In this setup, photosynthesis and acetaldehyde emission

were measured simultaneously for the same leaf. The cartridge was connected to the out-

let of the leaf cuvette using teflon tubing. Acetaldehyde emission rates were calculated

considering the leaf area and the flow rate (see below).

2.4.2.3 Quantification of acetaldehyde

The acetaldehyde hydrazone produced was eluted from the DNPH cartridges and quanti-

fied by HPLC analysis. The elution was carried out with 2 mL of ultra-pure acetonitrile

(ACN; Sigma, Munich, Germany) and 1 mL of ddH2O. The cartridge was mounted on a

plastic syringe and flushed three times with the solution. By this step, the bound acetalde-

hyde hydrazone was quantitatively transferred to the liquid phase. 100 µL of the eluent

were injected into a HPLC system (System Gold, Beckman, Munich, Germany). Separa-

tion of carbonyl compounds was carried out on reversed-phase octadecyl-silicium-column

(SUPELCOSIL, Supelco, Munich, Germany) using a ACN-H2O gradient (tab. 2.7), at a

flow rate of 1 mL min-1. Detection of acetaldehyde hydrazone was performed by a UV/VIS

detector (Beckman Munich, Germany) at a wavelength of 354 nm.

Table 2.7: HPLC gradient used for separation of carbonyl compounds. Acetonitrile (ACN) and ddH2Owere mixed by a gradient pump at the given percentages. Acetaldehyde was eluted after approx. 23 min.

Time (min) % H2O % ACN0 35 65

13 35 6524 0 10027 0 10030 0 10030.5 70 3040 70 30

Identification of acetaldehyde was carried out using a mixture of standard solutions

(DNPH mix, Supelco, Munich, Germany) which were run at the beginning of each sample

series. For quantification of acetaldehyde, a series of acetaldehyde standards (0, 5, 10, 20,


30 µL of a 15.01 µg mL-1 acetaldehyde standard solution [Supelco, Munich, Germany],

each in 1 mL of 70 % acetonitrile) was prepared and aliquots of 100 µL were injected

into the HPLC system. Calibration curves were obtained by plotting peak area against

concentration and calculating a linear regression through the data points (fig. 2.5).

●

●

●

●

●

●

0.00 0.01 0.02 0.03 0.04

05

1015

20

Acetaldehyde (µg)

Pea

k ar

ea

y == 411.237x ++ 0.047 r2 = 0.97

Figure 2.5: Calibration curve for acetaldehyde. A dilution series of an acetaldehyde standard solutionwas prepared and injected into the HPLC system. The relationship between peak area and acetalde-hyde concentration was determined by linear regression analysis (r2 = 0.97) and used to calculate theacetaldehyde concentrations of the samples. Mean ± SD. n = 5.

2.4.2.4 Calculation of acetaldehyde emission rates

Acetaldehyde emission rates (JAcH) were calculated from the acetaldehyde concentration

of the sample (c), the volumetric flow rate through the cuvette (V ) and the leaf area (A)

(eq. 2.1).

JAcH [nmol m-2 min-1] =∆c [ppb] · V [L min-1]

vmol [L mol-1] · A [m-2](2.1)

where ∆c is the difference between leaf cuvette and blank cuvette (the background con-


centration of acetaldehyde was regularly determined using an empty cuvette). vmol is the

molar volume of an ideal gas (22.41 L mol-1).

2.4.3 Sapflow rate

Xylem sapflow of seedlings was determined in the frame of the measurements of oxygen

concentration in the stem (section 2.6). The heat balance method was applied. The

sapflow sensors used (sapflow “baby” gauges, EMS, Brno, Czech Republic) consisted

of two thin needles which were pinched into the stem. One needle was then heated.

The heating power (max. 1.6 W) was electronically controlled to maintain a constant

temperature difference between the heated and the reference needle. The more water

passed through the xylem along the heated needle, the more power had to be invested,

i.e. the xylem sap flow (Q) was proportional to the consumed power (P ). Together with

the constant temperature difference (dT ) and a coefficient z which represents heat losses

from the measuring point, eq. 2.2 can be formulated (T4.2 user manual; EMS, Brno,

Czech Republic).

Q [kg s-1] =P [W]

cw [J g-1 ◦C-1] · dT [ ◦C]− z [W ◦C-1]

cw [J g-1 ◦C-1](2.2)

where cw is the specific heat of water (4.186 J g-1 ◦C-1).

Heating and recording of sap flow was performed by a connected sap flow meter (T4.2,

EMS, Brno, Czech Republic). Up to 12 sensors could be operated at the same time.

Recorded data were transferred to a PC after the experiment. In order to prevent arti-

facts by external temperature fluctuations (e.g. light or wind), the attached sensors were

insulated by wrapping them in foamed material and aluminium foil, according to the

instructions of the manufacturer.

2.4.4 Chlorophyll contents

The chlorophyll content was determined using acetone extraction as described by Licht-

enthaler and Wellburn (1983). 20 mg of homogenised leaf tissue was transferred into a

2 mL reaction tube containing 1.5 mL of 80 % acetone. For extraction, the mixture was

incubated for 10 min at 4 ◦C in the dark to inhibit photooxidation of the pigments. The

sample was centrifuged for 10 min (12000 × g , 4 ◦C) and the supernatant was transferred

to a new tube. Extinction at wavelengths 470, 646 and 663 nm was then determined

with a spectrophotometer (model DU 650, Beckman Coulter, Fullerton, California, USA)


against 80 % acetone (E470, E646, E663). In case of extinctions > 1.5, the supernatant

was diluted 1:2 with 80 % acetone. The contents of chlorophyll a, chlorophyll b and

carotinoids was calculated according to Lichtenthaler and Wellburn (1983):

Chla [µg mL-1] = 12.21 E663 − 2.81 E646

Chlb [µg mL-1] = 20.13 E646 − 5.03 E663

Cr [µg mL-1] = (1000 E470 − 3.27 Chla − 104 Cb) / 229

where Chla, Chlb and Cr are the concentrations of chlorophyll a, chlorophyll b and caroti-

noids, respectively.

2.4.5 Soluble carbohydrates

2.4.5.1 Extraction from leaf and root material

Soluble carbohydrates were extracted from ground leaf and root tissue with water, taking

advantage of their high solubility in this solvent. 2-mL screwtop reaction tubes (Sarstedt,

Nuremberg, Germany) were filled with 100 mg of purified PVPP1(Sigma, Munich, Ger-

many) and 1 mL of pre-chilled ice-cold ddH2O. 50 mg of homogenised tissue were then

transferred to the prepared reaction tubes. Extraction was performed by continuously

shaking the tube for 1 h at 4 ◦C in a cold room. The reaction tubes were then boiled for

10 min in a water bath and afterwards cooled down for 5 min on ice. Two centrifugation

steps were used to sediment cell debris (each for 10 min at 12000 × g and 4 ◦C). The

supernatant was carefully removed and transferred into a new tube. Extracts were stored

at −80 ◦C until analysis.

For HPLC analysis, extracts were appropriately diluted with ddH2O. The empirically

determined dilutions were 1:100 for leaf extracts and 1:10 for root extracts.

2.4.5.2 Preparation of phloem exudates and xylem sap

Appropriate dilutions for phloem exudates were prepared with ddH2O (phloem: 1:20,

xylem sap: 1:100). The solutions were mixed with 20 mg of PVPP and shaken continu-

ously for 1 h at 4 ◦C in a cold room. PVPP and suspended matter were then removed

by centrifugation for 10 min at 12000 × g and 4 ◦C. The supernatant was subjected to

HPLC analysis.

1PVPP (polyvinylpolypyrrolidone) binds to polyphenols and thereby removes them from plant extracts


2.4.5.3 HPLC analysis

Identification and quantification of soluble carbohydrates were carried out by High Pres-

sure Anion Exchange Chromatography with Pulsed Amperometric Detection (HPAE-

PAD) on a Dionex DX 500 HPLC system (Dionex, Sunnyvale, California, USA). The

system consisted of a GP 50 gradient pump and an ED 40 electrochemical detector. The

samples were injected into the system by an auto-sampler (model AS 3500, Thermo Sep-

aration Products, Fremont, California, USA). A guard column (CarboPac guard, 4 × 50

mm, Dionex) was installed upstream the analytical column to prevent contamination of

the analytical column. Thereby, carbohydrate separation was enhanced and a higher peak

resolution was achieved. As analytical column, a CarboPac PA1 (4 × 250 mm, Dionex)

was used.

The carbohydrates were isocratically eluted from the column with 56 mM NaOH. The

eluent was produced by the gradient pump from 200 mM NaOH (previously prepared from

50 % ultra-pure, HPLC grade sodium hydroxide, J. T. Baker, Deventer, Netherlands) and

ddH2O (ratio 28:72). The system was permanently kept free of air bubbles by degassing

both eluents with helium. The eluted carbohydrates were detected in the amperometry

cell of the ED 40. Detection was based on the oxidation of carbohydrates at the surface

of a gold electrode. The current generated by the oxidation was proportional to the

concentration of carbohydrate present in the eluent/sample mixture. The current was

analyzed by the ED 40. Data were recorded by the PeakNet software (version 5.1, Dionex,

Sunnyvale, California, USA).

The CarboPac PA1 is a general purpose column suitable for the analysis of mono-, di-

and some oligosaccharides including sugar alcohols like mannitol (Dionex, 2000, 2004).

Reliable detection of mannitol was crucial for the present study as it was present in con-

siderable amounts in tissue extracts of Fraxinus. In general, sugar alcohols like mannitol

are more difficult to analyse by HPAE-PAD because they are poorly retained on the

PA1 column due to the lower acidity as compared to the respective sugar counterparts.

However, sufficient resolution could be obtained for mannitol and another sugar alcohol,

inositol, with the configuration used (fig. 2.6).

2.4.5.4 Identification and quantification of soluble carbohydrates

The detected carbohydrates were identified and quantified by comparison with a standard

sugar solution. The standard contained inositol, mannitol, glucose, fructose and sucrose,

each at 100 µM. It was injected into the system at five different concentrations (20, 40,

60, 80, 100 µM). A sample chromatogram for a 80 µM standard is shown in fig. 2.6. From


0 5 10 15 20

010

2030

4050

Retention time (min)

PA

D r

espo

nse

(nC

)

Inositol

MannitolGlucose

Fructose Sucrose

●

●

●

●

●

●

0 20 40 60 80 100

0e+

001e

+06

2e+

063e

+06

4e+

065e

+06

6e+

06

Concentration (mM)

Pea

k A

rea

●

●

●

●

●

●

● InositolMannitolGlucoseFructoseSucrose

Figure 2.6: Analysis of soluble carbohydrates by HPAE-PAD. Left graph: typical chromatogram of asugar standard (in this example, 80 µM) after separation on a Dionex CarboPac PA1 column. Rightgraph: typical calibration curves for inositol, mannitol, glucose, fructose and sucrose. 10-µL aliquots of20, 40, 60, 80 and 100 µM standard solutions were injected into the HPLC system, and the obtainedpeak areas plotted against the respective concentration. Inositol, y = 47970x + 171306, r2 = 0.994;mannitol, y = 31859x + 75651, r2 = 0.981; glucose, y = 32681x + 5700, r2 = 0.998; fructose, y =25330x + 4423, r2 = 0.998; sucrose, y = 44676x – 77433, r2 = 0.984).

the different peak areas at the different concentrations, calibration curves were plotted.

These were linear for the given concentration range, r2 was > 0.984 (fig. 2.6).

Peak areas for standards and samples were obtained by interactive analysis of the HPLC

data with the PeakNet software (version 5.1, Dionex, Sunnyvale, California, USA).

2.4.6 Starch

Starch concentrations were determined in the context of the extraction of soluble carbo-

hydrates from samples (section 2.4.5.1). The pellet obtained in the last centrifugation

step was washed twice with 1 mL ddH2O. 5 U mL-1 amyloglucosidase (AGS) from As-

pergillus niger (Sigma-Aldrich, Munich, Germany) were dissolved in H2O. Aliquots of

1 mL were added to the pellet, and the mixture was continuously shaken for 1 h at 37 ◦C

(Thermo-Shaker, Stratagene, La Jolla, California, USA) to completely digest starch to

glucose. The digestion was stopped by boiling the extracts for 10 min in a water bath. Af-

ter cooling the sample on ice for 5 min, the samples were centrifuged (12000 × g , 10 min,

4 ◦C). A 1:10 dilution of the supernatant in H2O was used for HPLC analysis as described

above (section 2.4.5.3). As AGS contained small amounts of glucose for stabilization of

the enzyme, an aliquot of the AGS solution was subjected to HPLC analysis as well. The


amount was subtracted from the samples’ glucose concentration. Starch concentration

was expressed as µmol glucose equivalents per g FW (µmol gluc. eq. g-1 FW).

2.4.7 ADH activity

The activity of alcohol dehydrogenase (ADH) was determined in fresh extracts of leaves,

roots and bark pieces. Extraction and enzyme assay were modified from Bouny and Saglio

(1996).

2.4.7.1 Total cell extracts from leaves

A healthy, fully developed leaf was removed from the tree (usually from a branch in the

upper third of the plant) using a razor blade. The petiole was discarded, and the leaf was

stored in a 7-mL screw top tube (Sarstedt, Nurnberg, Germany) on ice until all samples

were taken. A maximum of eight leaves were collected at a time in order to minimise

decay. 200 mg of the leaf were transferred to an ice-cold mortar. The plant material was

completely homogenised with a chilled pestle in 2 mL of ice-cold extraction buffer (50 mM

Tris-HCl pH 7.5, 10 mM Na2B4O7, 15 % v/v glycerol, 0.02 % triton, 1 mM PMSF, 5 mM

DTT, 5 % w/v PVPP). A spatula tip of fine quartz sand (Fluka, Buchs, Switzerland) was

added to enhance disintegration of tissue. The extract was transferred to a pre-chilled

2-mL reaction tube and centrifuged (12000 × g, 10 min, 4 ◦C). The supernatant was

transferred to a new reaction tube, and the centrifugation was repeated. The obtained

total cell extract was kept on ice and used fresh for the assay. An aliquot (10 µL) was

saved for the determination of soluble leaf proteins (section 2.4.8).

2.4.7.2 Total cell extracts from roots

The plant was carefully taken out of the pot in order to avoid injuries to the root system.

Fine roots of a diameter of up to 1 mm were collected from multiple points of the roots,

ensuring that the material was representative of the whole root system. The collected

roots were carefully cleaned under running tap water and quickly dried on paper tissue.

The roots were stored on ice in 2-mL reaction tubes (Eppendorf) until extraction. The

subsequent procedure was identical to the one described for leaves.


2.4.7.3 Total cell extracts of bark pieces

Bark sections including vascular cambium, phloem and periderm were excised from the

stem with a fresh scalpel. Remains of wood were discarded. The samples were stored on

ice in 2-mL Eppendorf tubes. The subsequent extraction procedure was identical as for

leaves except that 3 mL of extraction buffer were used for 100 mg of bark material.

2.4.7.4 Activity assay - principle

ADH catalyses the reversible oxidation of ethanol to acetaldehyde in the presence of

NAD+:

CH3CH2OH + NAD+ ADH /o CH3CHO + NADH + H+

In the assay used, ADH activity was monitored in the direction of ethanol oxidation.

Ethanol and NAD+ were added to an aliquot of the total cell extract, and the formation

of NADH was followed photometrically at 340 nm, representing the extinction maximum

of NADH. As the equilibrium of the reaction is shifted to the left side, it had to be

shifted completely to the right by using an excess of ethanol (100 mM). ADH activity is

expressed as µmol NADH formed min-1 which is equivalent to the definition of enzyme

units (U) for ADH. The specific ADH activity was thus calculated as:

ADH activity (U g-1 FW) =V[(∆E/∆t)sample − (∆E/∆t)blind

]v · d · ε · 10−6 · fdil · FW

(2.3)

where (∆E/∆t)sample is the change of extinction in the reaction with sample (min-1),

(∆E/∆t)blind is the change of extinction in the blind reaction (min-1), V is total assay

and v the sample volume (µL), d the light path (cm), ε the extinction coefficient of NADH

at the wavelength of 340 nm (6.3 · 10 -3 L mol-1 cm-1), fdil the dilution factor of the sample

and FW the fresh weight of the sample (g).

(∆E/∆t)sample and (∆E/∆t)blind were obtained from linear regression fits through the

data points of reaction and blind reaction, respectively (fig. 2.7).


0 5 10 15

0.0

0.1

0.2

0.3

0.4

0.5

Reaction time (min)

Ext

inct

ion

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

● sample 1sample 2y == 0.001 x + 0.243; r2 == 0.284y == 0.015 x + 0.182; r2 == 0.996y == 0 x + 0.228; r2 == 0.291y == 0.014 x + 0.169; r2 == 0.996

Ethanoladdition

Figure 2.7: ADH assay: determination of slopes for blind reaction (broken lines) and reaction (solidlines) for two arbitrary samples. The arrow marks the addition of ethanol after recording the blindreaction for 5 min. This procedure corresponds to the protocol described for the plate reader; when thephotometer was used, blind reaction and reaction were measured in two separate assays.

2.4.7.5 Activity assay - use of the photometer

975 µL of ice-cold assay buffer (100 mM tricine pH 7.5, 6.8 mM NAD, 100 mM ethanol)

were pipetted into a disposable semi-micro cuvette (polystyrene 10 × 4 mm; Sarstedt,

Nurnberg, Germany). The cuvette was heated to 25 ◦C by placing the cuvette in the

tempered photometer slot for 15 min. 25 µL of fresh cell extract were then added to the

assay and mixed by inverting the cuvette that had been previously sealed with a double

layer of parafilm. The parafilm was removed, and the reaction was recorded for 10 min at

340 nm. Extinction was recorded at intervals of 10 s. The blind reaction was determined

in a parallel assay, containing H2O instead of ethanol.


2.4.7.6 Activity assay - use of the plate reader

100 µL of 2 × assay buffer (100 mM tricine pH 7.5, 6.8 mM NAD) and 40 µL of ddH2O

were transferred to the wells of a 96-well plate (Sarstedt, Nurnberg, Germany). The plate

was brought to 25 ◦C by inserting it into an appropriately tempered plate reader (Spectra

Rainbow; Tecan, Mannedorf, Switzerland) 10 min before starting the assay. 30 µL of fresh

cell extract were added to each well, and the blind reaction was recorded for 5 min at an

interval of 10 s (fig. 2.7). 30 µL of 670 mM ethanol were then added to the reaction mix,

and the change in extinction at 340 nm was recorded for 10 min. The different light paths

of blind (d = 0.6 cm) and main reaction (d = 0.7 cm), caused by the different reaction

volumes, were considered by using appropriate d in the calculations.

2.4.8 Soluble leaf proteins

The content of soluble leaf proteins was determined in total cell extracts from leaf tissue

(section 2.4.7.1) according to the method of Bradford (1976). 5 µL of protein extract

were transferred to a 96-well plate (Sarstedt, Nurnberg, Germany) and mixed with 200 µL

of Bradford reagent (Bio-Rad Protein Assay, diluted 1:5 with ddH2O; Bio-Rad, Munich,

Germany). After incubation for 10 min at RT, the extinction of the samples at λ = 595 nm

was determined with a plate reader (Spectra Rainbow; Tecan, Mannedorf, Switzerland).

A calibration curve was obtained from the extinction of a dilution series of a protein

standard (fig. 2.8).

2.4.9 Ethanol

2.4.9.1 Extraction from leaf and root material

Ethanol was extracted from homogenised leaf or root tissue with water as solvent. Stan-

dard reaction tubes (Eppendorf) were filled with 50 mg of purified PVPP and 0.5 mL

of ice cold ddH2O. 50 mg of frozen homogenised leaf or root material, respectively, were

transferred to the prepared tubes and immediately mixed by vortexing. The tubes were

permanently kept on ice. Ethanol was then extracted from the tissue powder by continu-

ous shaking for 20 min at 4 ◦C (cold room). Cell debris were removed by centrifugation

for 10 min at 12000 × g and 4 ◦C. The supernatant was transferred to a fresh reaction

tube, frozen in liquid N2 and stored at −80 ◦C until analysis.


●

●

●

●

●

●

0 1 2 3 4 5

0.0

0.1

0.2

0.3

0.4

0.5

0.6

BSA concentration (µg µL−−1)

Net

ext

inct

ion

y == 0.123x −− 0.012; r2 = 0.994

Figure 2.8: Calibration curve for Bradford protein assay. A dilution series of a standard protein (bovineserum albumine, BSA; Sigma, Munich, Germany) at 0, 1, 2, 3, 4 and 5 µg µL-1 was prepared usingextraction buffer. After incubation of 5 µL of each dilution with 200 µL of Bradford reagent, the extinctionat λ = 595 nm was determined with a plate reader. Net extinction was obtained from extinction minuschemical blank (5 µL extraction buffer + 200 µL Bradford reagent). Results from linear regressionanalysis are shown. n = 3.

2.4.9.2 Preparation of xylem sap

Xylem sap samples were slowly thawed on ice in order to prevent evaporation of the con-

tained ethanol. Aliquots of 25 µL were transferred to standard reaction tubes (Eppendorf)

which had previously been filled with 20 mg of PVPP and 975 µL of ice cold ddH2O. Care

was taken to pipette the sample directly into the H2O, avoiding contact with the tube

wall. The mixture was then shaken for 20 min at 4 ◦C. After centrifugation (10 min,

12000 × g , 4 ◦C), the supernatant was pipetted into a new tube and stored at −80 ◦C

until analysis.


2.4.9.3 Enzymatic determination - principle

Ethanol concentrations were determined with a commercially available test kit (Roche,

Basel, Switzerland). Ethanol is oxidised to acetaldehyde in the presence of ADH and

NAD as an electron acceptor:

CH3CH2OH + NAD+ ADH /o CH3CHO + NADH + H+

The equilibrium of the reaction is quantitatively shifted towards acetaldehyde and NADH

by coupling the reaction to the ALDH-mediated oxidation of acetaldehyde to acetate:

CH3CHO + NAD+ ALDH /o CH3COOH + NADH + H+

The amount of ethanol is proportional to the amount of NADH produced in the reaction.

NADH (but not NAD) shows a strong extinction of light at the wavelength of 340 nm

which can be detected photometrically. This property was used in the assay.

2.4.9.4 Enzymatic determination - assay

The protocol followed the specifications of the manufacturer of the kit but with reagent

volumes adjusted for use with 96-well microtiter plates instead of 1-mL cuvettes. The

reaction mix (buffer + cosubstrates + coupling enzyme) was prepared by mixing 3 mL

of ready-made potassium diphosphate buffer, pH 9.0 (bottle 1) with a tablet containing

4 mg of NAD and 0.8 U of acetaldehyde (bottle 2). This amount of reaction mix was

sufficient for 15 samples and was made freshly for each measuring series. A microtiter

plate (Sarstedt, Nurnberg, Germany) was prepared by transferring 200 µL of the reaction

mix into each required well. Depending on the amount of ethanol, 5–10 µL of xylem

sap were transferred to the plate which was then inserted into the plate reader (Spectra

Rainbow, Tecan, Mannedorf, Switzerland) and mixed using the “quick shake” function.

The extinction was read at 340 nm (E1). 5 µL (22 U) of ADH suspension (bottle 3)

were added to start the reaction. After 10 min, the extinction was read again (E2). The

amount of ethanol in the sample was proportional to the extinction difference E2 - E1 and

was calculated on the basis of the Lambert-Beer law:

Concentration of ethanol (g L-1) =V ·MW ·∆Eε · d · v · n · 1000

(2.4)

2.5 Flap-feeding of U-13C-glucose 39

where V was the reaction volume, MW the molecular weight of ethanol (46.07 g mol-1),

ε the extinction coefficient of NADH at 340 nm (6.3 · 10-3 L mol-1 cm-1), d the light path

through the sample (0.5 cm), v the sample volume (5–10 µL), n the number of moles

NADH produced per moles ethanol oxidised (2) and ∆E E2 - E1 minus (E2 - E1)blank. The

blank reaction was measured once per plate with 10 µL of ddH2O in place of sample.

As control, an aliquot of ethanol standard solution (bottle 4, 0.06 g L-1) was measured in

the same way as the samples. The result for n = 6 measurements was 0.0598 ± 0.0040 g

L-1 (99.7 ± 6.8 %).

Recovery rates were determined by adding a defined amount of ethanol to extraction

assays before the shaking step. The amount of ethanol added (1 mM) was in the range

of ethanol present in the extraction assays (i.e. 0.1–2 mM). Of the 1 mM ethanol added

to the solutions, 0.85 to 0.97 mM were recovered in leaf (93 ± 5 %, n = 5), and 0.83 to

0.98 mM in root assays (91 ± 6 %, n = 5).

2.5 Flap-feeding of U-13C-glucose

2.5.1 Feeding procedure

U-13C-glucose (Cambridge Isotope Laboratories; Andover, MA, USA) was introduced into

leaves using the flap-feeding technique of Biddulph and Markle (1944). For this purpose,

an application tube was prepared by removing lid and upper third from a 0.5 mL PCR

tube (Eppendorf, Hamburg, Germany). This tube was filled with 75 µL of 100 mM U-13C-glucose and sealed with parafilm. A secondary vein from the middle of a healthy leaf

was cut at both longitudinal sides over a length of approx. 1 cm using a fresh razor blade.

The vein segment was isolated from the leaf by making a third cut through the vein close

to its connection to the primary vein. These cuts were made under water using a petri

dish, in order to prevent air from entering the vessels. The leaf was taken out of the water,

dried on soft paper, and the vein flap was immediately immersed into the feeding solution

(fig. 2.9). After 4–6 h, the application tube was taken off. The leaf including the petiole

was removed and frozen in liquid N2. The flap was stored in a separate tube. For the

recovery of 13C from the phloem, bark samples were taken from five stem segments of equal

length (fig. 2.10) and submitted to phloem exudation as described above (section 2.3.3.2).

In order to increase the amount of incorporated 13C, two flaps were used per plant. In

P. tremula and A. pseudoplatanus , these flaps were placed on the same leaf, while they

were on opposing leaflets in F. excelsior . Material from two application leaves was pooled.

This procedure was similar to the one described by Trip et al. (1965) who used three flaps


per plant.

A series of preliminary experiments was carried out in order to find suitable harvesting

times after application of the pulse. These were defined as the time when increased 13C

levels, and preferably a clear basipetal gradient, was detected in phloem exudates from

different heights of the stem. Up to four seedlings of each species were tested as described

above. Results indicated that harvest should be carried out four hours after pulsing in

poplar, and six hours after pulsing in ash and maple.

OH

13CHOH

13CHOHHOH

13C

HOH13C

H13C

13CHOH

Figure 2.9: Left: Illustration of flap-feeding method. A segment of a secondary vein was prepared fromthe leaf and immersed in 100 mM U-13C-glucose. As application vial, a cut PCR tube was used whichwas light enough to be hold only by the vein segment. Right: Chemical structure of U13C-glucose.

2.5.2 Determination of 13C derived

2.5.2.1 Sample preparation for elemental analysis

Leaves were transferred from −80 ◦C to a drying cabinet and desiccated for 5 days at

60 ◦C. For this purpose, the lids of the plastic tubes were removed. After drying, samples

were ground to fine powder for 2 min at 90 Hz with a ball mill (Retsch MM 2000, Retsch,

Haan, Germany). Approx. 0.5 mg of powder were transferred to a tin capsule (Tin

Capsules, CE Instruments, Milan, Italy).

For phloem exudates, 2 mL of the total volume (5 mL) were centrifuged for 10 min at

12000 × g in order to remove particulate material. 1.8 mL of the supernatant were

transferred into a new tube, from which H2O was completely evaporated for 24 h at 50◦C using a speed vac (Christ RVC 2-25, Christ, Osterode, Germany). The dried exudate


segment 1

segment 2

segment 3

segment 4

segment 5

feeding leaf

Figure 2.10: Feeding experiment: Position of the fed leaf and the bark samples taken. U-13C-glucosewas incorporated into the leaf by flap-feeding. Bark samples were taken from five stem segments asindicated by arrows, and analysed for changes in δ13C. The total height of the plants was 80–120 cm,the height of each segment 15–20 cm. The flooding height was 15 cm above ground.

was resuspended in 50 µL of ddH2O, 10 µL of which were pipetted into a tin capsule (Tin

Capsules, CE Instruments, Milan, Italy).

2.5.2.2 13C/12C analysis

Total C and C isotope ratio (13C/12C) were determined on an isotope ratio mass spec-

trometer (IRMS; Delta Plus, ThermoQuest, Milan, Italy) connected to a C/N elemental

analyzer (NC 2500, ThermoQuest, Milan, Italy). Samples were placed on an auto-sampler

and successively injected into the C/N analyzer. At a temperature of approx. 1050 ◦C, the

material was quantitatively combusted in the presence of ultra-pure oxygen gas (99.995 %,

SWF, Fiedrichshafen, Germany). The oxidation products (H2O, CO2, N2 and NOx) were

transferred to the reduction reactor using ultra-pure helium (99.996 %, SWF) as a vec-

tor gas. In the reduction reactor, the NOx components were catalytically reduced to N2

(using pure copper as a catalyzer), combining all N molecules of the sample in the N2


fraction. H2O gas was eliminated from the gas mixture by absorption to a magnesium

perchlorate column. The gas mixture was then transferred to the gas chromatographic

separation column where N2 and CO2 were separated on the basis of different retention

time (N2 came off first). N2 and CO2 were then ionised by an ion source and accelerated

in a potential field of 3 kV. The beam of ions passed an electromagnetic field produced by

a single magnet in which ions were deflected depending on mass (as 13C has a higher mass

than 12C the two isotopes are separated). Detection of the ion beam was performed on

multiple Faraday cups (detectors) which converted particle impact into electric current.

Data acquisition and analysis was carried out with the Isodat software (Thermo Fisher

Scientific, Inc., Waltham, MA, USA). Between sample measurements, the 13C/12C ratio

of a carbon dioxide test gas (ultra-pure CO2, 99.995 %, SWF) was determined for control

purposes. Calibration was carried out at the beginning of each sample series (consist-

ing of 60–90 samples) with acetanilide (CH3COHNHC6H5, CE Instruments, Wigan, UK)

and glutamate (Sigma, Munich, Germany) as well as standards IAEA-N-1 (ammonium

sulfate) and IAEA-CH-6 (sucrose) on a regular basis.

2.5.3 Calculation of the amount of 13C derived

The amount of 13C derived from feeding was calculated according to Kogawara et al.

(2006):

Amount of 13C = Total amount of C · 13 · (13C atom %− natural 13C atom %)

13 · 13C atom % + 12 · 12C atom %(2.5)

where “13C atom %” is the percentage of 13C atoms of total C, “12C atom %” is the

percentage of 12C atoms of total C and “natural 13C atom %” is the percentage of 13C of

total C in untreated plants. In case of the control signature for phloem samples, it was

tested for differences in signature with sampling height. No such differences were found,

so averages were used for samples of all heights (tab. 2.8). For the control signature of

leaves, a median value for C3 plants was used (−27 h; Lajtha and Michener, 1994),

since possible deviations from actual control signatures were considered neglectable in

comparison with the large δ13C values of the fed leaves, which ranged between 100 and

1000 h.

δ13C values were converted into isotope signatures (13C/12C) by applying eq. 2.6 (Isebrands

and Dickson, 1991).


Table 2.8: Natural carbon isotope ratios used for computation of excess 13C derived from feeding.

Material / species Carbon isotope ratio (δ13C) (h) SourcePhloem exudate / ash −26.30 ± 0.37 Average of 6 samples from 2 plants

Phloem exudate / poplar −26.29 ± 0.51 Average of 6 samples from 2 plantsPhloem exudate / maple −29.35 ± 0.92 Average of 20 samples from 5 plants

Leaf / all species −27 Median value for leaves of C3 plants(Lajtha and Michener, 1994)

13C12C

= PDB +δ13C

1000· PDB (2.6)

where PDB is the Pee Dee Belemnite standard for δ13C (0.0112372).

“13C atom %” and “12C atom %”, required for eq. 2.5, were derived by eq. 2.7 (Isebrands

and Dickson, 1991).

13C atom % =13C12C· 100 12C atom % = 100− 13C atom % (2.7)

The total amount of C was calculated from the C mass percentage (obtained from MS

analysis), multiplied by the dry weight of the sample.

The following example demonstrates how the amount of 13C derived from feeding was

calculated for a leaf sample of 0.2 g DW. The C mass percentage and δ13C were determined

to be 55 % and +100 h, respectively. δ13C was converted to 13C atom % using eqs. 2.6

and 2.7. The result, 1.236, along with 12C atom % = 100–1.236 = 98.764 and natural 13C

atom % = 1.093 (corresponding to δ13C = −27 h; tab. 2.8), was used in eq. 2.5. The

amount of 13C derived from feeding was 0.170·10-3 g (0.013·10-3 mol). This amount was

related to the total amount of 13C incorporated by the plant which was known from the

volume of sugar solution taken up. 0.020·10-3 mol 13C were incorporated, thus 0.013·10-3

/ 0.020·10-3 = 0.655 = 65.5 % of incorporated 13C were found in the leaf.

For the phloem exudates, analogous calculations were carried out. The amount of 13C

derived from feeding was related to the DW of the bark piece and scaled to the dry

weight of the bark of the respective stem segment. Thereby, the amount of 13C derived

from feeding in the phloem sap of each stem segment was obtained.


2.6 Oxygen measurements within the stem

2.6.1 Principle

Oxygen within the stems of tree seedlings was determined with oxygen micro-optodes

(Presens GmbH, Regensburg, Germany). These miniaturised sensors have a tip diameter

of only 50 µm, allowing for measurements with high spatial resolution. The operation

principle is based on the quenching of luminescence of dye molecules in the presence of

molecular oxygen (Presens, 2002; Klimant et al., 1997). The dye molecules, a ruthenium

diimine complex, are applied on the tip of a fiber optic cable through which periodic (1

Hz) light signals of a wavelength of 505 nm are sent. The dye molecules are excited by

the light signal and emit some of the excitation energy as luminescence. The more oxygen

is present in the vicinity of the sensor tip, the greater is the portion of luminescence that

is quenched by the collision of oxygen molecules with dye molecules. The luminescence

signal is transferred back through the fiber cable and photometrically detected by an

oxygen meter (Microx TX2; Presens GmbH, Regensburg, Germany). The quenching

effect is quantified as the lifetime of luminescence which is shorter in the presence of

oxygen. The detection works equally well in gaseous and liquid phase and is independent

of pH, ions, salinity or viscosity (Presens, 2002).

2.6.2 Experimental setup

In the experiments, micro-optodes of the variant “needle-type” were used for O2 anal-

ysis (order no. NTH-L10-TF-NS120/0.8-Y). In this sensor type, the fragile sensor tip

is enclosed in the steel needle (length 120 mm, diameter 0.8 mm) of a plastic syringe

(fig. 2.11A). For the measurement in the wood, the tip was extended only to the end of

the diagonal cut of the cannula in order to avoid damage by contact with the wood.

In a preliminary experiment, it was tested if sufficient air convection occurred between

half-extended tip and environment to ensure a high temporal resolution of the measure-

ment. For this purpose, the sensor was transferred from air into a septum-sealed HPLC

vial filled with 1 M Na2SO3 (Na2SO3 was used to eliminate all oxygen from the solution

and the airspace above it). In this experiment, a reaction of the sensor was observed

within 30–60 s after insertion, compared to 5–10 s with the fully extended tip (data not

shown). This slightly larger response time was considered neglectable.

For insertion of the sensor, a hole of 0.9 mm diameter was drilled into the stem using a

drill machine. The hole was driven to a depth of approx. half of the stem diameter. After

2.6 Oxygen measurements within the stem 45

inserting the sensor, the hole was sealed with terostat (Teroson, Heidelberg, Germany;

fig. 2.11B). Externally, the sensor was fixed to a wooden staff (fig. 2.11A). Once inserted,

the tip of sensor was carefully extended, and recording was started after reaching steady

state concentrations (fig. 2.12). For data acquisition, the Oxyview software (version 4.16;

Presens, Regensburg, Germany) was used.

Stem-internal temperatures were required for temperature-corrected calculation of oxygen

concentrations. However, suitable sensors for this purpose were not available. Therefore,

temperatures were recorded using temperature sensors (Presens, Regensburg, Germany)

attached to the stem surface, which were assumed to approximate stem-internal temper-

atures (cf. Gansert, 2004).

Calibration of the sensors was performed using a two-point calibration according to the

manufacturer’s instructions.

A B

C

Figure 2.11: Stem-internal oxygen measurements. (A) syringes containing the sensor tip were fixatedon a scaffold made of bamboo sticks. (B) enlargement of (A) showing how the cannula was inserted intothe stem. The borehole was sealed with terostat (Teroson, Heidelberg, Germany). (C) oxygen meterMicrox TX2 (Presens, Regensburg, Germany). Oxygen sensor (left plug) and temperature sensor (rightplug) are connected to the device. For data acquisition, a notebook computer was used.


●

●● ●

● ● ●●

●● ● ● ● ● ● ● ● ● ● ●

● ● ●● ●

● ● ● ● ● ●● ● ● ●

● ● ● ● ●

4060

8010

012

0

Time (hh:mm)

[Oxy

gen]

(%

air

satu

ratio

n)

17:00 17:48 18:36 19:24

Sensor inserted

Figure 2.12: Oxygen measurements with needle-type micro-optode sensors (time of insertion markedby arrow). Approx. 30 min were required for the measured concentration to settle down to a stable level.Data were recorded every 5 min.

2.6.3 Manual calculation of the O2 concentration from raw data

The measured O2 concentrations were calculated directly by the Oxyview program. This

requires the calibration data for the respective sensor to be entered into the software

before measurements were started. However, this became impractical when sensors were

changed frequently, e.g. when measuring several trees in turn. In this case, it was more

convenient to use the raw data output, phase angle and temperature, and recalculate

the O2 concentrations manually. For this purpose, the formulas from the manufacturer’s

manual (Presens, 2002) were applied as specified in eq. 2.8.

O2 (% air saturation) =−b+

√b2 − 4ac

2a(2.8)

where a, b and c are defined as

2.6 Oxygen measurements within the stem 47

a =tan Φm,Tm

tan Φ0,Tm· 1

22.9·K2

SV,Tm

b =tan Φm,Tm

tan Φ0,Tm·KSV,Tm+

tan Φm,Tm

tan Φ0,Tm· 1

22.9·KSV,Tm−0.805· 1

22.9·KSV,Tm−KSV,Tm+0.805·KSV,Tm

c =tan Φm,Tm

tan Φ0,Tm− 1

tan Φm,Tm in these equations is the tangent of the phase angle Φ of the current measure-

ment (m) at the current temperature (Tm) and is defined as:

tan Φm,Tm = tan(Φ0,T0 ·Π

180) (2.9)

where tan Φ0,Tm is the tangent of the phase angle at 0 % oxygen as obtained from cali-

bration, extrapolated for Tm. Its definition is:

tan Φ0,Tm = tan(Φ0,T0 + (−0.08037 · (Tm − T0)) · Π

180(2.10)

KSV,Tm is the Stern-Vollmer constant for Tm which is derived from the Stern-Vollmer

constant for T100:

KSV,Tm = KSV,T100 + 3.83 · 10−4 · (Tm − T100) (2.11)

The Stern-Vollmer constant for T100, i.e. the temperature during calibration at 100 % O2

is derived as:

KSV,T100 =−B +

√B2 − 4AC

2A(2.12)

where A, B and C are defined as:

A =tan Φ100,T100

tan Φ0,T100· 1

22.9· [O2]

2

B =tan Φ100,T100

tan Φ0,T100· [O2] +

tan Φ100,T100

tan Φ0,T100· 1

22.9· [O2] + 0.805 · 1

22.9· [O2]− [O2] + 0.805 · [O2]

C =tan Φ100,T100

tan Φ0,T100− 1

In these equations, tan Φ100,T100 and tan Φ0,T100 are:

tan Φ100,T100 = tan(Φ100,T100 · Π180

)

tan Φ0,T100 = tan([Φ0,T0 + (−0.08037 · (T100 − T0))] · Π180

)


where Φ100,T100 and Φ0,T0 are phase angles at 100 % O2 and respective temperature and

at 0 % O2 and respective temperature, respectively.

Φ0,T0, Φ100,T100, T0 and T100 were obtained from calibration, Φm,Tm and Tm from the raw

data of the measurement.

2.7 Biometry

2.7.1 Stem height and diameter

Stem height was determined from the ground (upper pot rim) to the terminal bud of the

tree using a folding rule. The stem diameter was determined with a gauge, at a height

of 2 cm above the ground. Diameters at other heights were recorded as indicated in the

text.

2.7.2 Fresh and dry weight

Fresh weight of leaves, stems and roots was determined by weighing immediately after

harvest. For the determination of dry weight, the material was dried in paper bags at 60◦C until weight constancy (5–6 days).

2.7.3 Leaf area

Leaf area was determined using a leaf area meter (Delta T Devices Ltd, Cambridge, UK).

The contour of the leaf, which was positioned on a lightbox providing uniform background

illumination, was detected with a camera using the method of colour discrimination. The

detection threshold was manually adjusted as appropriate. From the area occupied by

the dark space, the leaf area was automatically calculated by the system. Calibration

was performed with paper rectangles of defined area at the beginning of each series of

measurements.

2.7.4 Leaf number

All living leaves were counted, irrespective of developmental stage or damages. Dead

leaves were not taken into account.

2.8 Statistical analysis 49

2.8 Statistical analysis

2.8.1 General data analysis and statistics

Unless otherwise stated, data of n multiple measurements (x) were expressed as mean (x)

± standard deviation based on a sample (SD, eq. 2.13).

SD =

√(x− x)2

n− 1(2.13)

Preparation of data for statistical analysis was performed with OpenOffice Calc (version

2.0 or higher, Sun Microsystems Inc., Santa Clara, California, USA). Large datasets

were stored in a MySQL database (version 5.0 or higher, MySQL AB, Uppsala, Sweden).

Statistical analyses as well as graphics were made with the software R, version 2.0 or higher

(R Development Core Team, 2006). Chemical structures were drawn with GChemPaint,

version 0.6.9 or higher (www.nongnu.org/gchempaint).

For testing statistical differences between two groups, Student’s two-sample t test was used

(R function t.test()). Differences between more than two groups were tested by analysis

of variance (ANOVA), using aov(). Multiple comparisons (post-hoc tests) were carried

out with Tukey’s Honest Significant Differences (HSD) test (TukeyHSD()). The latter

function possesses a compensation for mildly unbalanced data, making it applicable for

most of the datasets in the present study. Balanced designs were used in all experiments,

however, balance was lost in some cases due to missing observations.

Normal distribution and homogeneity of variances of data were tested using visual meth-

ods (index plots, histograms, QQ plots) as well as appropriate statistical tests (Pearson

χ2 test for normality, Bartlett test for homogeneity of variances). In case of violation of

any of these assumptions, data were either (1) transformed using an appropriate power

transformation or (2) subjected to non-parametric methods. (1) Transformation can

generally be applied to either predictor or response variable. However, as predictors

in the data of the present study were mostly categorical (e.g. treatment, species), the

only candidate for transformations was the response variable. For identifying suitable

power transformations, the suggestions of Fox (2002) were followed. Appropriate trans-

formations to normality and symmetry were identified using Box-Cox transformations

and related methods. (2) Non-parametric methods included the Wilcoxon rank sum test

(wilcox.test()) for testing differences between two groups and the Kruskal-Wallis rank

sum test (kruskal.test()) for more than two groups.


Unless otherwise specified, significant difference between two groups were marked with

asterisks, using standard significance codes, i.e. “*”, “**” or “***” for significant differ-

ences at the 5 %, 1 %, 0.1 % significance level, respectively. Letter notation (A, B, C,

. . . ) was used when more than two groups were compared, with different letters indicating

significant differences between the groups at the 5 % significance level. Letter output was

obtained using the R function multcompLetters() (package multcompView).

2.8.2 Analysis of light and CO2 response curves

Both light and CO2 response were fitted with the Mitscherlich model (eq. 2.14).

y = A[1− e−k(x−x0)] (2.14)

The use of the model was suggested by Potvin et al. (1990) as it includes three regression

coefficients, A, k and x0 which represent important physiological characteristics. In the

case of the light curves, A stands for the light-saturated assimilation rate, k for the

apparent quantum yield and x0 for the light compensation point. In the case of the CO2

curves, A represents CO2 saturated photosynthesis, k the increase of A with increasing

CO2 (A/CO2) and x0 the CO2 compensation point. x refers to the applied light or CO2

level, respectively. Thus, by fitting the model to the acquired light and CO2 curve data

(section 2.4.1.3), estimates for these physiological characteristics were obtained.

The model was used for two types of analyses. The purpose of the first type of analysis

was to fit individual response curves for each plant and treatment. Thereby, estimates

of the regression coefficients for each single response curve were obtained. On the basis

of the regression coefficients, regression lines could be drawn through the data points.

Confidence intervals of the three regression coefficients were also calculated, allowing for

pair-wise comparison of the parameters of two or more curves.

Functions used for this first type of analysis included nls() for fitting, nlsList() for fit-

ting multiple curves in one step, predict() to calculate regression lines and intervals()

for calculating confidence intervals of the regression parameters (all functions from the

package nlme).

As a criterion for the goodness of fit, the coefficient of determination for non-linear regres-

sions (r2nl) was calculated. The formula given by Sachs and Hedderich (2006) was used

(eq. 2.15).

2.8 Statistical analysis 51

r2nl =

1− ss∑y2 − 1

n(∑y)2

(2.15)

where ss is the residual sum of squares of the fit (obtained from nls()), y is the response

variable and n is the sample size.

Good fits were obtained for the photosynthetic response curves of ash, lime and wil-

low (figs. 3.32, 3.33). For oak, however, only low coefficients of determination were

yielded. Therefore, other models often used in physiological response curve analysis,

e.g. the Michaelis-Menten model (He et al., 1999), rectangular (Krauss et al., 2006) or

non-rectangular hyperbola (Ogren and Evans, 1993; Leverenz et al., 1990), were tested

alternatively but did not yield considerably better results.

In the second type of analysis, the Mitscherlich equation was used for setting up a non-

linear mixed effects model (NLME). The general approach was adopted from Peek et al.

(2002) but modified in several points to account for the different experimental design of

the present experiments. The model, as used by Peek et al. (2002), is given in eq. 2.16:

yij = f(φij, xij) + eij (2.16)

where f is a nonlinear function of an individual-specific parameter vector φij and the

predictor vector xij for the jth observation on the ith subject. eij is a vector of unknown

random errors. phiij was given by:

φij = Aijβ +Bijbi

where β is a vector of fixed population parameters and bi is a vector of random effects

of the ith individual (not varying with j). Aij and Bij are design matrices for the fixed

and random effects, respectively (notation according to Pinheiro and Bates (2000)). The

fixed effect design matrix (Aij) was specified by Peek et al. (2002) in accordance with

their experimental design which was 2x2 factorial (two species which were subjected to

two treatments). The random component Bij was specified in order to take into account

repeated measurements on the same leaves at different light levels. For f , Peek et al.

(2002) used the Mitscherlich model equation as already given above (eq. 2.14).

In the present experiments, two groups of plants, a control and a flooded group, were

measured at two dates (day 0 and day 14). Thus, two levels of repeated measurements

were present in the experiment: (1) multiple measurements on the same leaf of each plant


at different light (or CO2) levels, and (2) measurements of the same plants on day 0 and

day 14. In order to account for this two level grouping, model 2.16 was modified (eq. 2.17).

yijk = f(φijk, xijk) + eijk (2.17)

where i refers to the plant number, j to the day and k to the light (or CO2) level.

Accordingly, φijk was defined as:

φijk = Aijkβ +Bijkbi + Cijkcij

where Aijkβ and Bijkbi are defined analogously to the above terms, however, cij is a

random effects vector associated with the ith individual on the jth day, and Cijk is a

design matrix for the random effects of the second level.

Model 2.17 was fitted separately to the light and CO2 curve data of each species inves-

tigated (ash, lime, oak, willow), using the function nlme(). According to the model,

light (or CO2) level (x) was specified as primary covariate, treatment and day, and their

interaction, as covariates. Random effects were first included for all regression coefficients

(A, k and x0) but eliminated when there was no or little variation between individuals in

order to simplify the model (Pinheiro and Bates, 2000).

The results of nlme() included estimates for the 12 parameters (2 treatments × 2 days

× 3 parameters). In order to test if treatment, day or their interaction had a significant

effect on the parameters (A, k, or x0), Wald’s F test was carried out using the function

anova() with an appropriate specification of the model terms to be tested. For example,

a test for a significant effect of treat on A was specified as anova(model, test="F",

Terms="treat"). Accordingly, all other combinations of factors and parameters were

tested.

Multiple comparisons of the parameter estimates were performed by obtaining confi-

dence intervals for the parameters on the 95 % confidence levels using the function

intervals.lme(). Two groups were marked as significantly different when their con-

fidence intervals of the respective parameter did not overlap. Different letters were used

to denote these differences.

Chapter 3

Results

3.1 Experiment I: Effect of flooding on the C metabolism of

ash provenances “Alb”, “Rhine” and “BFor”

In order to characterise the impact of flooding on common ash, flooding experiments

with three-year-old seedlings were performed under semi-controlled conditions. In this

experiment, three provenances of common ash, “Alb”, “Rhine” and “BFor” were com-

pared regarding major features of C metabolism: photosynthesis, carbohydrate contents

of various tissues, and alcoholic fermentation in the roots.

3.1.1 Leaf gas exchange

3.1.1.1 Assimilation

Control plants showed light-saturated net assimilation rates (Amax) between 1.8 and 3.2

µmol m-2 s-1 (day 1) which increased from day 3 to 7 (4–6 µmol m-2 s-1) and thereafter

decreased again to values similar to day 1 (fig. 3.1). In contrast, Amax was initially

relatively high (7–7.5 µmol m-2 s-1) in flooded plants of all provenances and then showed

a decreasing trend with increasing flooding duration. As a consequence, Amax amounted

to only 1.5 to 2.4 µmol m-2 s-1 at the end of the experiment (day 42).

For better comparability, Amax of the flooded plants were expressed as percent of the

control (fig. 3.2). Generally, Amax on day 1 was 2 (“Rhine”) to 4 (“Alb”) times higher in

the flooded plants than in the controls, whereas on all other days Amax was lower or in

54 Results

Am

ax (µµ

mol

m−−2

s−−1

)

02

46

810

●

● ●

●

●

●

●

●

●

●● ● ●

● ●

* *

**

Alb

●

●●

●

● ●●

●

●●

●

● ●●

●●

*

*

Rhine

●

●

●

●

●

●

●

●

●

●

● ●●

●

*

**

BFor

ControlFlooded

●

●

Day of experiment

g s (m

mol

m−−2

s−−1

)

020

4060

8010

012

0

0 10 20 30 40

●

●●

●

●●

●

●

●

● ●

●

●

●

●

* *

* * *

0 10 20 30 40

● ●

●

●

●

●

●

●

●●

●

●

●

●

●

●

*

0 10 20 30 40

●●

● ●

●

●

●

●

●

●

●

●●

●

*

*

A

B

Figure 3.1: Effect of flooding on net assimilation (A) and stomatal conductance (B). Ash seedlingsof three provenances (“Alb”, “Rhine”, “BFor”) were flooded for the times indicated by horizontal barsand gas exchange was analysed as described in Materials and Methods. Points represent means offour plants (± SD). Asterisks indicate significant differences between the treatments as calculated byWilcoxon rank sum tests, using standard significance codes. In case of the omitted control measure-ments (days 28 and 42), results for the flooded plants were tested against the respective precedingcontrol day.

the same range as the controls. The difference on day 1 between “Alb” and “Rhine” was

statistically significant.

Continued flooding caused lower Amax in all provenances. For example, after three days of

flooding, “Alb” and “BFor” exhibited lower assimilation rates than the controls (71 and

41 % respectively) while “Rhine” (108 %) remained similar to the control. After 14 days

of treatment, Amax was significantly reduced in the flooded plants of “Alb” (35 % of the

control) and also reduced, albeit less pronounced, in “Rhine” (64 %) and “BFor” (80 %).

One week of recovery did not cause Amax to regenerate in “Alb” and “Rhine” as compared

to the controls, which remained on approximately the same low level of the last day of

the flooding treatment (59 and 66 %, respectively). “BFor”, however, showed a relatively

high A (215 %) after the recovery phase. The difference between “Alb”, “Rhine” and

“BFor” was statistically significant.

3.1 Experiment I: Effect of flooding on ash provenances “Alb”, “Rhine” and “BFor” 55

Day of experiment

g s (%

of c

ontr

ol)

Am

ax (%

of c

ontr

ol)

020

040

060

080

010

00

1 3 7 14 21 24 28 35 42

aab

b

a abb

a abb

ab ab

010

020

030

0

a

ab

b

a a

bAlbRhineBFor

A

B

Figure 3.2: Effect of flooding on net assimilation (A) and stomatal conductance (B) of ash seedlings.Trees were flooded for the times indicated by horizontal bars, and results for flooded seedlings wereexpressed as percent of the controls. Bars represent means of four plants (± SD). Different lettersindicate significant differences between the provenances as calculated by a one-way ANOVA, applyingTukey’s HSD post-hoc test at p < 0.05. In case of the omitted control measurements on days 28 and42 the preceding days were used for calculations.

Re-flooding caused a reduction of Amax for “Alb” (33 %) and “BFor” (61 %) whereas

“Rhine” remained unchanged (65 %). Surprisingly, prolonged flooding led to a slight

recovery of Amax in “Alb” (70 %) and “Rhine” (107 %) while “BFor” still remained at

65 % of the control levels. Seven days of a second recovery did not cause noticeably

changes to the previous measuring days in “Alb” (61 %) and “Rhine” (85 %), however,

in “BFor” a slight recovery to 117 % of the control level was observed. This increase in

“BFor”, even though on a smaller scale, resembled the increase after the first recovery

56 Results

period.

3.1.1.2 Stomatal conductance

Reduced Amax in response to flooding has been connected, among others, to reduced stom-

atal conductance (gs). Therefore, this parameter was studied in the flooding experiment

besides Amax. gs showed a high degree of variability, with relatively low values of 4 to

8 mmol m-2 s-1 in both controls and flooded trees on day 1, and higher values of 10–60

mmol m-2 s-1 in the further course of the experiment (fig. 3.1). Statistically significant

differences between the treatments were observed on days 1 and 3 in “Alb”, only on day 3

in “Rhine” and only on day 1 in “BFor” (in all cases, gs was higher in the flooded plants).

By contrast, significantly reduced gs values were found in the flooded plants of day 42 in

“Alb” and “BFor”.

Expressed as relative values (fig. 3.2), gs of the flooded plants amounted to 230–300 % of

the control plants on day 1 and even to 500–840 % on day 3. These high gs values were in

contrast to the relatively low assimilation rates on that day (same figure). After 14 days

of flooding, gs in the flooded plants was slightly increased in “BFor” (141 %) but lower in

“Alb” (52 %) and “Rhine” (86 %), with the difference between “Alb” and “BFor” being

statistically significant (p < 0.05). The recovery period did neither bring about a change

in gs of “Alb” (51 %) nor “Rhine” (66 %).

Re-flooding caused a slight, but not significant increase in gs in all provenances (122–

171 %), resembling the increase at the beginning of the first flooding period. After

prolonged flooding (day 35) as well as after the second recovery (day 42), however, gs

dropped again to values equal to or lower than the controls. On day 42, gs of the flooded

plants was significantly higher in “BFor” (92 %) as compared to “Rhine” (62 %).

3.1.1.3 Relationship between Amax and gs

Since assimilation rates under flood stress are often limited by a low stomatal aperture,

the relationship between Amax and gs was investigated by linear regression analysis. On

the basis of the data for the whole experiment, Amax showed only a poor connection to

gs, with r2 < 0.23 for all three provenances (fig. 3.3).


gs (mmol m−−2 s−−1)

Am

ax (µµ

mol

m−−2

s−−1

)

0

2

4

6

8

10

0 20 40 60 80

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●●

●

●

●●

●

●●

●

●

●

●

●

●

●●

●

●

● ●●

●

●

●

●●

●

●●

●

●

●

●●

●

●●

● ●

Alb

0 20 40 60 80

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

● ●●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●●

Rhine

0 20 40 60 80

●●

●

●●

●

●

●

●

● ●

●●●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

● ●

●

● ●

●

●

●●

●

●●

●●

● ●●

●

●

●

●

●●

●

●●

●

●●

●

●

BForControlFlooded

●

●

Figure 3.3: Analysis of the relationship between Amax and gs for experiment I. Data represent the leafgas exchange results of the whole experiment as previously shown (fig. 3.1). Linear regression linesare indicated for control (broken lines) and flooded plants (solid lines). “Alb” control: y = 0.0438x +1.4800, r2 = 0.163; “Alb” flooded: y = 0.0088x + 2.0948, r2 < 0.01; “Rhine” control: y = 0.0279x +2.4028, r2 = 0.098; “Rhine” flooded: y = 0.0511x + 1.3742, r2 = 0.226; “BFor” control: y = 0.0042x +2.2103, r2 < 0.01; “BFor” flooded: y = −0.0380x + 3.6962, r2 = 0.043.

3.1.2 Soluble carbohydrates

For a more comprehensive characterisation of flooding effects on C metabolism, contents

of soluble carbohydrates were determined for leaves, roots, phloem exudates and xylem

sap.

3.1.2.1 Leaves

The main soluble carbohydrates in leaves were mannitol, glucose, sucrose and fructose. In

the non-flooded trees, mannitol and glucose amounted to 11–16 and 11–23 µmol g-1 FW,

respectively, each contributing ≈45 % to total soluble carbohydrates (TSC, defined as the

sum of mannitol, fructose, glucose and sucrose). Sucrose and fructose contents amounted

to 0.9–4 µmol g-1 FW, each constituting ≈5 % of TSC. The TSC contents amounted to

15–45 µmol g-1 FW.

Flooding did not consistently change the TSC contents in comparison to the controls.

While decreased TSC concentrations were observed for some of the flooding durations

tested, e.g. on days 7 (48 %) and 21 (78 %) in “Rhine”, or on day 24 in “Alb” (58 %),

even prolonged flooding did not result in altered TSC concentrations, visible e.g. on day 35

for both “Rhine” (113 %) and “Alb” (96 %) (fig. 3.4). Similar results were obtained for the

58 Results

provenance “BFor”: three days after re-flooding, TSC contents were reduced significantly

(68 %), however, the two 14-day flooding periods did not result in a similar reduction

(102 %).

The observed reductions in TSC contents were in part not due to a uniform decrease of

all individual carbohydrate compounds, but to a differential reduction of its components.

For example, glucose and fructose contents on day 24 were significantly reduced in “Alb”

whereas mannitol and sucrose contents were not. Mannitol contents were not affected on

days 7 and 14 in “Rhine”, in contrast to sucrose and glucose which showed significant

reductions. On the contrary, the mannitol content was significantly reduced on day 21 in

the same provenance while contents of other carbohydrates were not affected.

In order to test if the flood-induced changes to TSC contents were different between the

provenances, TSC contents of the flooded plants were expressed as percent of the non-

flooded controls (fig. 3.5D). Differences between the provenances were only found for the

TSC contents on day 21 where TSC contents were somewhat increased in “Alb” (118 %)

and lower than the control in “Rhine” (78 %), with “BFor” being intermediate (99 %). On

all other days, changes, if present, did not differ between provenances. The analysis was

extended to glucose and fructose, summarised as “hexose” (fig. 3.5A), mannitol (fig. 3.5B)

and sucrose (fig. 3.5C). Provenance-specific differences were observed sporadically, how-

ever, without a clear connection to the flooding duration. For example, the relative hexose

content differed between provenances on day 24, whereas the relative mannitol content

differed on day 21.

3.1.2.2 Roots

Like in leaves, the primary carbohydrates in roots were mannitol, glucose, fructose and

sucrose. In unflooded roots, the TSC content amounted to 2.1 to 10.4 µmol g-1 FW.

Mannitol contents varied from 0.3 to 3.1 µmol g-1 FW, constituting up to 30 % of TSC.

Glucose contents varied from 0.5 to 2.7 µmol g-1 FW (18–41 %), sucrose contents from

0.7 to 3.4 µmol g-1 FW and fructose contents from 0.1–1.3 µmol g-1 FW (3–15 %).

The TSC content of the control plants of “Alb” and “Rhine” showed a remarkable decreas-

ing trend in the course of the experiment. For example, TSC contents in “Alb” decreased

from 6.0 on day 3 to 2.3 µmol g-1 FW on day 42. Such a decreasing tendency was not

observed in the flooded plants. Instead, TSC contents remained on the high initial level

or even increased, resulting in significant differences from the controls for many of the

flooding treatments studied (fig. 3.6). These increases amounted to 150–350 %. In the

provenance “BFor”, TSC contents remained constant in the control plants but increased

in the submerged trees. Statistically significant effects were observed after three and 14


Alb CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

nd

0102030405060

Carbohydrate content (µµmol g−−1

FW)

Rhine CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

BFor CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

nd

nd

Suc

rose

Fru

ctos

eG

luco

seM

anni

tol

Tre

atm

ent /

Day

of e

xper

imen

t

13

714

2124

2835

421

37

1421

2428

3542

13

714

2124

2835

42Su

cr.

-*

*-

-*

--

Fruc

.**

--

--

-G

luc.

***

-*

*-

--

-M

ann.

-**

--

--

Tot

al*

-**

*-

-*

--

Figu

re3.

4:E

ffect

offlo

odin

gon

cont

ents

ofso

lubl

eca

rboh

ydra

tes

inle

aves

ofth

ree

prov

enan

ces

ofF.

exce

lsio

r.Tr

ees

wer

eflo

oded

fort

hetim

esin

dica

ted

byho

rizon

talb

ars,

and

carb

ohyd

rate

cont

ents

wer

ede

term

ined

inaq

ueou

sex

tract

sof

leav

esby

HP

LCan

alys

is.

Bar

sre

pres

entm

eans

(±S

D)

offo

urpl

ants

(nw

assm

alle

rin

afe

wca

ses

due

tosa

mpl

elo

ss).

Ast

eris

ks(*

)ind

icat

esi

gnifi

cant

diffe

renc

esbe

twee

ntre

atm

ents

fort

otal

and

sing

leca

rboh

ydra

tes,

resp

ectiv

ely,

asca

lcul

ated

byt

test

s,us

ing

stan

dard

sign

ifica

nce

code

s.C

,con

trol;

F,flo

oded

;nd,

noda

ta.

60 Results

Day of experiment

Car

bohy

drat

e co

nten

t (%

of C

O)

010

020

030

0

b

a

ab

Hexose

b

a

ab

Mannitol

1 3 7 14 21 24 28 35 42

b

a

a

Sucrose

1 3 7 14 21 24 28 35 42

010

020

030

0

b

a

ab

Total

AlbRhineBFor

A B

C D

Figure 3.5: Effect of flooding on contents of soluble carbohydrates in leaves of three provenancesof F. excelsior . Trees were flooded for the times indicated by horizontal bars, and leaf carbohydratecontents of flooded trees were expressed on a percent basis of controls. Results are shown for thesum of glucose and fructose (hexose, A), mannitol (B), sucrose (C) and total soluble carbohydrates(D). Bars represent means (± SD) for four plants. n was smaller in a few cases due to sample loss.Different letters indicate significant differences between provenances within each flooding duration andcarbohydrate type, as calculated by ANOVA with Tukey’s HSD (p < 0.05). Bars are missing when nodata were available.


days of flooding. Moreover, TSC contents remained tendentially increased after the first

recovery period (day 21).

The extent of TSC increase in response to flooding was significantly different between

the provenances. After 14 days of flooding, for example, the increase in “BFor” was

significantly higher than in “Alb”, and on day 28 the increase in the “Rhine” provenance

was significantly higher than in “Alb” (fig. 3.7D). On the other days, a clear temporal or

provenance-specific pattern was not observed.

In response to flooding, the provenances showed interesting differences in the accumulation

of mannitol. In the provenance “Alb”, mannitol increased continuously during the first

flooding period, dropped after reaeration and increased again in the course of the second

flooding period (fig. 3.7B). In contrast, the accumulation in “Rhine” was strongest during

the first days of flooding (3–7 days) and then decreased, a course observed for both flooding

periods. The diverging patterns in the two provenances led to a significant difference in

relative mannitol concentrations on day 42.

Provenance-specific differences were also indicated by different accumulations of sucrose.

Prolonged flooding resulted in a significantly stronger accumulation in the “Rhine” prove-

nance as compared to “Alb”, a phenomenon observed on days 14, 28 and 42 (fig. 3.7C).

By contrast, no clear differences between provenances were observed for the accumulation

of hexoses (fig. 3.7A).

3.1.2.3 Phloem exudates

TSC contents in phloem exudates of unflooded trees amounted to 0.7–2.3 (max. 4.6)

µmol g-1 bark FW and consisted of 40–60 % mannitol, 20–30 % glucose and 8–20 %

sucrose.

After three days of flooding, TSC contents were still unchanged (90 % in “Alb”) or lower

(61–65 % in both “Rhine” and “BFor”) than in the controls. Prolonged flooding for 14

days, however, resulted in an increase of TSC contents of 144–233 % of controls in all

provenances, though this effect was not in all cases statistically significant (fig. 3.8). Ten-

dentially elevated levels were measured on almost all subsequent days of the experiment,

mostly ranging between 130 and 190 % of controls. These increases were relatively homo-

geneous among provenances (fig. 3.9D); a significant difference was only present after day

7, with the increase in “Alb” (176 %) being significantly higher than in “Rhine” (106 %).

This significant difference applied for all individual carbohydrates, with the strongest dif-

ference observed for sucrose (600 % in “Alb” vs. 144 % in “Rhine”). In general, sucrose

seemed to accumulate stronger than hexoses (glucose, fructose) or mannitol (fig. 3.9A-C)

62 Results

AlbCF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

0 2 4 6 8 10 12

Carbohydrate content (µµmol g−−1 FW)

RhineCF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

BForCF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

nd

nd

nd

nd

Sucrose

Fructose

Glucose

Mannitol

Treatm

ent / Day of experim

ent

13

714

2124

2835

421

37

1421

2428

3542

13

714

2124

2835

42Sucr.

****

***

***

Fruc.*

**

***

*G

luc.*

**

**M

ann.*

**

**

**T

otal**

**

***

****

Figure3.6:

Effectofflooding

oncontents

ofsolublecarbohydrates

inroots

ofthreeprovenances

ofF.excelsior.Trees

were

floodedfor

thetim

esindicated

(horizontalbars),andcarbohydrate

contentsw

eredeterm

inedin

aqueousextracts

ofrootsusing

HP

LCanalysis.B

arsrepresentm

eans(±

SD

)offourplants(n

was

smallerin

afew

casesdue

tosam

pleloss).A

sterisks(*)indicate

significantdifferencesbetw

eentreatm

entsfortotaland

singlecarbohydrates,respectively,

ascalculated

byt

tests,usingstandard

significancecodes.

C,control;F,flooded;nd,no

data.


Day of experiment

Car

bohy

drat

e co

nten

t (%

of C

O)

020

040

060

080

010

00

a

abb

Hexose

a

b

Mannitol

1 3 7 14 21 24 28 35 42

a

bb

a

b

a

b

Sucrose

1 3 7 14 21 24 28 35 42

020

040

060

080

010

00a

aba a

b

Total

AlbRhineBFor

A B

C D

Figure 3.7: Effect of flooding on contents of soluble carbohydrates in roots of three provenances ofF. excelsior . Trees were flooded for the times indicated (horizontal bars), and root carbohydrate con-tents of flooded trees were expressed on a percent basis of controls. Results are shown for the sum ofglucose and fructose (hexose, A), mannitol (B), sucrose (C) and total soluble carbohydrates (D). Barsrepresent means (± SD) of four plants (n was smaller in a few cases due to sample loss). Differentletters indicate significant differences between provenances within each flooding duration and carbohy-drate type, as calculated by ANOVA with Tukey’s HSD (p < 0.05). Bars are missing when no data wereavailable.

64 Results

in response to flooding.

3.1.2.4 In xylem sap

TSC concentrations in the unflooded trees were relatively high at the beginning of the

experiment (2.5–4 mM) and decreased in the course of the experiment to much smaller

values (0.1–0.2 mM). In contrast, the decrease was less distinct in the flooded plants,

resulting in significantly increased concentrations compared to controls toward the end of

the experiment (fig. 3.10). For example, TSC concentrations on day 35 were increased in

the flooded plants by factors of 2.5 (“BFor”) to 4.3 (“Alb”).

Significant differences were observed between provenances, with “Alb” showing stronger

accumulations than “Rhine” and/or “BFor” after prolonged flooding (fig. 3.11D). Hex-

oses, mannitol and sucrose accumulated to a similar extent (fig. 3.11A–C).

3.1.3 ADH activity, ethanol contents and acetaldehyde exchange

3.1.3.1 Root ADH activity

Under normoxic conditions, activities of ADH in roots were relatively low with values

between 0.08 and 1.01 U g-1 FW in seedlings of the provenances “Alb” and “BFor”. For

the “Rhine” provenance, somewhat higher activities of up to 2.83 U g-1 FW were measured

in the non-flooded trees. Flooding caused a strong induction in ADH activity, reaching

values between 3 and 13 U g-1 FW (fig. 3.12). This corresponded to increases by factors

of 4–25.

The extent of increase was different for short and prolonged flooding durations. In “Alb”,

for example, 1-day flooding did not result in significantly increased activities (2.04 ± 0.86

U g-1 FW) whereas 3-day flooding caused a pronounced increase (4.87 ± 1.39 U g-1 FW).

Longer flooding periods did sometimes but not necessarily lead to further rises of ADH

activity. On day 28, for example, very high activities were observed (12.99 ± 0.92

U g-1 FW), being significantly higher than on day 3 (fig. 3.12). On day 35, however,

activities (6.93 ± 0.11 U g-1 FW) were in the same range as on day 3 and did not differ

statistically.

The course of ADH activity in the other provenances was generally similar as described

for “Alb”: flooding periods of longer than one day resulted in distinct, in most cases

statistically significant increases in activity. For the “Rhine” provenance, the increase

was in some cases statistically not significant, due to the relatively high activities of the


Alb CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

0123456

Carbohydrate content (µµmol g−−1

FW)

Rhine CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

BFor CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

Suc

rose

Fru

ctos

eG

luco

seM

anni

tol

Tre

atm

ent /

Day

of e

xper

imen

t

13

714

2124

2835

421

37

1421

2428

3542

13

714

2124

2835

42Su

cr.

**

***

**

Fruc

.*

Glu

c.*

***

Man

n.*

**

Tot

al**

***

Figu

re3.

8:E

ffect

offlo

odin

gon

cont

ents

ofso

lubl

eca

rboh

ydra

tes

inph

loem

exud

ates

ofth

ree

prov

enan

ces

ofF.

exce

lsio

r.Tr

ees

wer

eflo

oded

for

the

times

indi

cate

d(h

oriz

onta

lbar

s),a

ndph

loem

exud

ates

wer

eco

llect

edan

dus

edfo

rcar

bohy

drat

ede

term

inat

ion

byH

PLC

anal

ysis

.B

ars

repr

esen

tmea

ns(±

SD

)of

four

plan

ts.n

was

smal

leri

na

few

case

sdu

eto

sam

ple

loss

.Ast

eris

ks(*

)ind

icat

esi

gnifi

cant

diffe

renc

esbe

twee

ntre

atm

ents

fort

otal

and

sing

leca

rboh

ydra

tes,

resp

ectiv

ely,

asca

lcul

ated

byt

test

s,us

ing

stan

dard

sign

ifica

nce

code

s.C

,con

trol;

F,flo

oded

;nd,

noda

ta.

66 Results

Day of experiment

Car

bohy

drat

e co

nten

t (%

of C

O)

020

040

060

080

010

00

a

b

Hexose

ab

Mannitol

1 3 7 14 21 24 28 35 42

a

b

Sucrose

1 3 7 14 21 24 28 35 42

020

040

060

080

010

00a

b

Total

AlbRhineBFor

A B

C D

Figure 3.9: Effect of flooding on contents of soluble carbohydrates in phloem exudates of three prove-nances of F. excelsior . Trees were flooded for the times indicated (horizontal bars), and carbohydratecontents of phloem exudates of flooded trees were expressed on a percent basis of controls. Resultsare shown for the sum of glucose and fructose (hexose, A), mannitol (B), sucrose (C) and total solublecarbohydrates (D). Bars represent means (± SD) of four plants. n was smaller in a few cases due tosample loss. Different letters indicate significant differences between provenances within each floodingduration and carbohydrate type, as calculated by ANOVA with Tukey’s HSD (p < 0.05). Missing bars:no data available.


Alb CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

nd

nd

nd

nd

nd

0123456

Carbohydrate concentration (mM)

Rhine CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

nd

nd

nd

nd

nd

BFor CF

CF

CF

CF

CF

CF

CF

CF

CF

13

714

2124

2835

42

nd

nd

nd

nd

nd

nd

nd

nd

nd

nd

Suc

rose

Fru

ctos

eG

luco

seM

anni

tol

Tre

atm

ent /

Day

of e

xper

imen

t

13

714

2124

2835

421

37

1421

2428

3542

13

714

2124

2835

42Su

cr.

***

***

****

Fruc

.*

**G

luc.

***

*M

ann.

***

***

*T

otal

****

***

*

Figu

re3.

10:

Effe

ctof

flood

ing

onco

nten

tsof

solu

ble

carb

ohyd

rate

sin

xyle

msa

pof

thre

epr

oven

ance

sof

F.ex

cels

ior.

Tree

sw

ere

flood

edfo

rth

etim

esin

dica

ted

(hor

izon

talb

ars)

and

xyle

msa

pw

aspr

epar

edby

the

Sch

olan

der

pres

sure

tech

niqu

e.X

ylem

sap

sam

ples

wer

esu

bmitt

edto

carb

ohyd

rate

anal

ysis

byH

PLC

.B

ars

repr

esen

tmea

ns(±

SD

)of

four

plan

ts.

nw

assm

alle

rin

afe

wca

ses

due

tosa

mpl

elo

ss.

Ast

eris

ks(*

)in

dica

tesi

gnifi

cant

diffe

renc

esbe

twee

ntre

atm

ents

fort

otal

and

sing

leca

rboh

ydra

tes,

resp

ectiv

ely,

asca

lcul

ated

byt

test

s,us

ing

stan

dard

sign

ifica

nce

code

s.C

,con

trol;

F,flo

oded

;nd,

noda

ta.

68 Results

Day of experiment

Car

bohy

drat

e co

nten

t (%

of C

O)

050

010

0015

00

Hexose

b

aa

b

a

ab

b b

a

Mannitol

1 3 7 14 21 24 28 35 42

b

a

a

b

a

ab

Sucrose

1 3 7 14 21 24 28 35 42

050

010

0015

00

b

aa

b

a

ab

b

aba

Total

AlbRhineBFor

A B

C D

Figure 3.11: Effect of flooding on contents of soluble carbohydrates in xylem sap of three provenancesof F. excelsior . Trees were flooded for the times indicated (horizontal bars), and carbohydrate contentsof xylem sap of flooded trees were expressed on a percent basis of controls. Results are shown for thesum of glucose and fructose (hexose, A), mannitol (B), sucrose (C) and total SC (D). Bars representmeans (± SD) for four plants. n was smaller in a few cases due to sample loss. Different letters indicatesignificant differences between provenances within each flooding duration and carbohydrate type, ascalculated by ANOVA with Tukey’s HSD (p < 0.05). Missing bars: no data available.


Day of experiment

AD

H a

ctiv

ity (

U g

−−1 F

W)

05

1015

20

0 10 20 30 40

●●

●● ● ●

●

●

●

●

●

●

●

●

●

●

a*

ac***

abc***

a

abc**

bc***

b**

abc*** ac

**

Alb

0 10 20 30 40

● ●

●●

●●

●

●

● ●

●●

●

●

●●

b

ab***

ab*

abab**

ab*

a**

ab

ab

Rhine

0 10 20 30 40

● ●● ●

●●

● ●

●

●

●

●

●

●

aa

ab*

b***

ab**ab

**

b***

ab***

BForControlFlooded

●

●

Figure 3.12: Effect of flooding on alcohol dehydrogenase (ADH) activity in roots of three provenancesof F. excelsior . Three-year-old seedlings were flooded for the times indicated (horizontal bars) andADH activity was biochemically determined as described in Materials and Methods. Points representmeans (± SD) of four plants each. Asterisks (*) indicate significant differences between flooded andcontrol treatments as calculated by t tests, using standard significance codes. Different letters denotesignificant differences between days of the flooded treatment within each provenance (ANOVA withTukey’s HSD test, p < 0.05).

controls. Statistically significant differences between the provenances were only observed

for “Alb” and “BFor” on days 3 and 28, when “BFor” exhibited lower activities than

“Alb” (tab. 3.1). Activities of the provenances “Alb” and “Rhine” did not differ in a

statistically firm manner on any of the days investigated.

Re-aeration for one week did not affect ADH activities. After the first recovery period,

for example, activities were unchanged (“Rhine”) or even higher (“Alb”, “BFor”) than at

the end of the flooding treatment. Similarly, the second reaeration period did not result

in a return of activities to the low levels observed for aerated plants.

3.1.3.2 Ethanol contents in roots

Concentrations of ethanol, the end product of alcoholic fermentation, were mostly below

the detection limit (≈10 µg g-1 FW) in normoxic as well as hypoxic roots (results not

shown).

70 Results

Table 3.1: Statistical analysis of ADH activity in roots of flooded ash seedlings. One-way ANOVAs withthe independent variable “provenance” (levels “Alb”, “Rhine”, “BFor”), were run separately for each dayof the experiment. Tukey’s HSD test was used to test for differences between the groups. Differentletters indicate significant differences between the provenances at p < 0.05.

Day df F p Multiple comparisonsAlb Rhine BFor

1 2 0.18 0.84 a a a3 2 6.48 0.02 ab a b7 1 0.74 0.42 - - -14 2 1.12 0.37 a a a21 2 1.68 0.24 a a a24 2 2.04 0.19 a a a28 2 4.05 0.06 b ab a35 2 0.62 0.56 a a a42 2 1.49 0.28 a a a

Leaf

EtO

H (

µµg g

−−1 F

W)

050

100

150

200

250

● ●

●

●

●

●

●

●

●

●●

●

Alb

●

●

●●

●●

●

●

●

●

●●

●

●

Rhine

●

●

●

●

●

● ●●

●

●

●●

●

BForControlFlooded

●

●

Day of experiment

Xyl

em E

tOH

(m

M)

0.0

0.5

1.0

0 10 20 30 40

●● ● ● ● ● ● ●

●

●

●

●

● ● ● ●●

**

*

*

* *

0 10 20 30 40

●

●

● ● ● ● ● ●

●

●●

●

● ●●

●

*

0 10 20 30 40

●

● ● ● ● ● ●

●

●●

● ●●

●

*

*

* *

A

B

Figure 3.13: Effect of flooding on leaf (A) and xylem (B) ethanol contents of three provenances ofF. excelsior . Trees were submerged for the times indicated by horizontal bars and ethanol content wasenzymatically determined as described in Materials and Methods. Points represent means (± SD) offour plants. Asterisks (*) indicate significant differences between flooded and control treatments forxylem ethanol as calculated by t tests, using standard significance codes. No statistical analysis wasperformed for leaf ethanol contents.


3.1.3.3 Ethanol contents in leaves

In contrast to the ethanol contents in roots, ethanol in leaves was present in well detectable

amounts between 50 and 230 µg g-1 FW in the non-flooded controls. In all provenances,

the content varied widely between individual plants. Flooding caused no changes in leaf

ethanol contents (fig. 3.13A), even on the days where increased contents might have been

expected due to the large amounts of ethanol transported in the xylem sap, e.g. day 1 in

“BFor”.

3.1.3.4 Ethanol concentrations in the xylem sap

Virtually no ethanol was detected in the xylem sap of normoxic controls. By contrast,

ethanol amounts of up to 1.2 mM were found after the trees had been subjected to

flooding (fig. 3.13B). In contrast to the pattern of ADH activity in the roots, ethanol

concentrations were significantly increased in all provenances immediately after initiation

of the flooding treatment, with concentrations between 0.1 (“Rhine”) and 0.5–0.6 mM

(“Alb”, “BFor”). Concentration remained increased in “Alb” and only dropped after

reaeration. By contrast, ethanol contents dropped already after three days in “Rhine”

and “BFor”. Surprisingly, re-flooding did not result in increased ethanol concentrations

which was in contrast to the response during the first flooding period.

3.1.3.5 Acetaldehyde exchange with the atmosphere

Acetaldehyde exchange was investigated in order to test if some of the xylem-transported

ethanol was converted to acetaldehyde and emitted into the atmosphere. Acetalde-

hyde exchange rates of non-flooded controls were generally low with values of max. 30

nmol m-2 min-1. Negative exchange rates, i.e. acetaldehyde uptake, of −50 nmol m-2 min-1

were also occasionally observed in the course of the experiment. In the flooded plants of

provenance “Alb”, exchange rates did not differ from the controls (fig. 3.14). In prove-

nance “Rhine”, emission rates increased slightly, though in a statistically not significant

manner, after two weeks of flooding (72.48 ± 96.06 nmol m-2 min-1) but not at longer

flooding periods. Emission rates in “BFor” were characterised by a single peak in re-

sponse to one day of flooding (281.74 ± 475.45 nmol m-2 min-1). This peak, however, did

not differ significantly from control levels either.

72 Results

Day of experiment

Exc

hang

e ra

te (

nmol

m−−2

min

−−1)

−20

0−

100

010

020

030

0

0 10 20 30 40

●

●

●● ●

●●

●●

●

●●

●●

●

●●

●

Alb

0 10 20 30 40

●

●

●●

● ●● ●

●

●

●

●

●

● ● ● ● ●

Rhine

0 10 20 30 40

●

●

●●

● ● ●

●

●

● ●●

●●

●●

BForControlFlooded

●

●

Figure 3.14: Effect of flooding on leaf acetaldehyde exchange of three provenances of F. excelsior .Trees were subjected to flooding for the times indicated (horizontal bars) and leaf acetaldehyde ex-change was determined using an open cuvette system with attached DNPH cartridges (Supelco, Mu-nich, Germany) in which leaf-emitted acetaldehyde was trapped (see Materials and Methods for de-tails). Points represent means (± SD) of four plants. A statistical analysis using Wilcoxon rank sumtests revealed no significant differences between flooding and control treatments.

3.1.4 Water content of leaf, root and stem

The water content of leaves of the non-flooded trees amounted to ≈80 % at the beginning

of the experiment, and decreased to ≈60 % towards the end of the experiment. This

decrease was likely due to leaf maturation during the experiment (mid May to end of

June). The flooding treatment caused no clear change to this general trend (fig. 3.15A).

Though significant differences were found for some treatment days, e.g. for “Alb” on

day 28 or for “BFor” on day 3, it was unclear if these differences reflected physiological

changes.

The water content of the stem including wood and bark also showed a decreasing tendency

in the course of the experiment. In the control plants, it decreased from ≈75 % to ≈50 %

in the provenance “Rhine” and “BFor”, whereas it was 5–10 % lower throughout the

whole experiment in the provenance “Alb”. Again, the flooded plants showed no clear

difference from their non-flooded counterparts (fig. 3.15B).

The water content of roots varied between 62 % and 83 % in the provenances “Rhine” and

“BFor”, while it was generally 5–10 % lower in the provenance “Alb”. As for leaves and

stems, there was a decreasing tendency in the roots during the course of the experiment,

though less pronounced than in the former. For “Rhine” and “BFor”, no statistical


differences were observed between flooded and control plants throughout the experiment

(fig. 3.15C). In “Alb”, statistically significant differences were observed on days 7 (flooded

trees higher) and 24 (control higher).

6070

80 ●

●

●

● ●●

●

●

●●

● ●

●●

●

●

**

Alb

●●

●

●

●

●

●●

●

●

●●

●●

●

●

*

Rhine

●

●

● ●

●

●

●

●

●

●

● ●

●●

*

**

BForControlFlooded

●

●

Wat

er c

onte

nt (

%)

4050

6070

80

●

● ●

●

●●

●

●

● ●

● ●

●● ●

●*

****

● ●

●●

●●

●

●

●●

●

●● ●

●

●

●

●

●

●●

●

●

●

●

●

●

●● ●

*

Day of experiment

6070

8090

0 10 20 30 40

● ●●

●

●

●

●

●

●● ●

●

● ●

●

**

0 10 20 30 40

●

● ●

●

●

●

●

●●

●

●

●

●●

●

0 10 20 30 40

● ●●

●

●

●

●

●

●

●

●●

●

A

B

C

Figure 3.15: Effect of flooding on the water content of leaves (A), stems (B) and roots (C) of threeprovenances of F. excelsior . Trees were subjected to flooding for the times indicated (horizontal bars)and water contents were calculated from the difference in FW and DW. Points represent means (± SD)of 4–5 plants. Asterisks denote significant differences between the treatments as determined by t testsat p < 0.05, using standard significance codes.

3.1.5 Stem height and diameter

Stem height and diameter were determined in additional plants that had been subjected

to both 2-week flooding periods. The measurements were made one week after removal

74 Results

of flooding water and included 31 flooded and 18 control plants of “Alb”, 77 flooded and

52 control plants of “Rhine” as well as 8 flooded and 11 control plants of “BFor”.

The mean diameter at the stem basis, 2 cm above the soil, was significantly increased

by the flooding treatment in the provenance “Rhine” (0.96 cm vs. 0.90 cm) (fig. 3.16,

A1). In contrast, no such change was observed for “Alb” or “BFor”. The comparatively

low diameter in “BFor” (0.69 cm and 0.75 cm, resp.) was due to lower age of the plants

compared to “Alb” and “Rhine” (see section 2.1.1). The diameter at a higher stem

position (approx. one third from the top) was also significantly increased in the provenance

“Rhine” (fig. 3.16, A2), an effect not observed in “Alb” or “BFor”.

Stem height did not differ between flooded and control plants (fig. 3.16, B1 and B2).

Diameter (cm)

0

0.2

0.4

0.6

0.8

1

1.2 *

0

0.2

0.4

0.6

0.8

1

1.2

Control

Flooded

*

Height (cm)

0

20

40

60

80

100

Alb Rhine BFor

0

20

40

60

80

100

Alb Rhine BFor

A1 A2

B1 B2

Figure 3.16: Effect of flooding on stem diameter (A1, A2) and stem height (B1, B2) of three prove-nances of F. excelsior . Tree seedlings were subjected to 2 × 2 weeks of flooding, and stem height anddiameter were determined. Stem diameter was determined at two positions, at the stem basis (A1) andat the lower end of the most recent stem segment (A2). The latter determination was carried out in orderto compensate for possible swelling/hypertrophied growth at the stem basis due to flooding. Besidestotal stem height (B1), the length of the most recent stem segment was determined. Bars representmeans (± SD). Asterisks (*) denote significant differences between treatments as calculated by t tests(p < 0.05).


3.1.6 Flood injuries and morphological adaptations

3.1.6.1 Leaf number

Partial or complete leaf loss in response to flooding was observed in many individual

plants. First signs of leaf loss were visible after 14 days of flooding, with more severe

effects becoming evident during the second flooding period. The average leaf number was

reduced from 33 to 15 in “Alb”, whereas no such reduction was observed in the provenances

“Rhine” or “BFor” (fig. 3.17A). Many plants of the provenance “Alb” exhibited complete

defoliation at the end of the experiment (fig. 3.18A).

After complete or partial defoliation, most plants were able to develop fresh leaves. These

fresh green leaves predominantly originated from terminal leaf buds (fig. 3.18, B+C).

However, the capacity to form fresh leaves was strongly reduced by the flooding treatment.

In “Alb”, only 2 % of the flooded plants had freshly budded leaves, as compared to 34 %

of the control plants. Similar (“BFor”) or less pronounced (“Rhine”) reductions were also

observed in the other provenances (fig. 3.17B).

Leaf number

0

5

10

15

20

25

30

35

40

45

50

Alb Rhine BFor

Control

Flooded

*

Percent

0

10

20

30

40

50

60

70

Alb Rhine BFor

A B

Figure 3.17: Effect of flooding on leaf number (A) and on the percentage of trees developing freshleaves (B) for three provenances of F. excelsior . Trees were subjected to 2 × 2 weeks flooding, andthe remaining number of leaves were counted. Furthermore, the percentage of trees developing freshleaves was determined. Bars in (A) represent means (± SD). The relatively high number of leaves inthe control plants of “Alb” was due to the fact that this provenance had more but smaller leaves. Therelatively low number in “BFor” was due to the lower age of these plants as compared to “Alb” and“Rhine”.

76 Results

A B

C

Figure 3.18: Leaf loss after flooding (A) and development of fresh leaves (B, C). The plants shown, allbelonging to the provenance “Alb”, had been subjected to 2 × 2 weeks of flooding.

3.1.6.2 Decay of fine roots

After 14 days of submergence, fine roots often showed a pronounced decay. Their colour

changed from bright white to gray. Particularly affected were the plants of the provenance

“Alb” which displayed much stronger root decay than “Rhine” or “BFor”, as shown in

fig. 3.19. However, the overall dry weight of the root system was not decreased in the

flooded plants (fig. 3.20).

A foul, sulfurous smell was often noted when harvesting the roots. It was particularly

noticeable after prolonged flooding.

3.1.6.3 Hypertrophied lenticels and adventitious roots

Development of hypertrophied lenticels (HL) was observed in the flooded portion of the

stem within approx. five days of flooding. HL appeared as white, mostly point-shaped

cell clusters (fig. 3.21, A) with diameters of approx. 0.5–1 mm. At wounded bark spots,

more extended growth was observed (fig. 3.21, B). Between the three provenances, there

were no differences in number or size of HL visible to the naked eye.

The formation of adventitious roots (AR) was not observed within the duration of the

experiment. However, in ash seedlings flooded for more than six weeks, AR formation

was observed. They were relatively few in numbers (3–5 roots per stem) and quite thick


Figure 3.19: Decay of fine roots after 14 days of flooding in the provenance “Alb” (right). By contrast,roots of the provenance “Rhine” were mostly considerably less affected (left).

Day of experiment

Dry

wei

ght (

g)

010

2030

0 10 20 30 40

●●

●

●

●

● ●

● ●●

●

●●

●●

Alb

0 10 20 30 40

●

● ●

●

●●

●

●

●

●

●●

●

●

●

Rhine

0 10 20 30 40

●●

●

●

●

●

●

●

●●

● ●

●

BForControlFlooded

●

●

Figure 3.20: Effect of flooding on the dry weight of roots in three provenances of F. excelsior . Treeswere flooded for the times indicated (horizontal bars) and dry weights of total roots were determined.Points represent means (± SD) of four plants. There were no statistical differences between floodedand control treatments, as calculated by Wilcoxon rank sum tests at p < 0.05.

78 Results

(diameter 2–3 mm) (fig. 3.22).

A B

Figure 3.21: Formation of hypertrophied lenticels. (A): Point-shaped hypertrophied lenticels in theflooded portion of the stem. (B): Hypertrophied cell growth along the edge of a bark wound (whitevertical stripe). A bark strip of approx. 2x0.5x0.1 cm was removed from the shown location for collectingcambial tissue.

Figure 3.22: Formation of adventitious roots (AR) in F. excelsior . The pictured plant of South Germanmountainous provenance area 81107 had been flooded continuously for six weeks until AR formationstarted.

3.2 Experiment II: Effect of flooding on C metabolism of

F. excelsior provenances “Alb” and “Rhine” as well as

F. angustifolia

3.2.1 Leaf gas exchange

3.2.1.1 Assimilation

Amax varied considerably between the provenances and between measurements within each

provenance. The control plants of “Alb” showed moderate Amax on day 3 (1.84 ± 1.10

µmol m-2 s-1) which decreased to 0.53 ± 0.42 µmol m-2 s-1 on day 10 (fig. 3.23). Similarly,

low values were observed on both days in the “Rhine” provenance (0.19–0.53 µmol m-2 s-1).

By contrast, F. angustifolia displayed considerably higher Amax than F. excelsior (4.95 ±2.82 µmol m-2 s-1). While short-term flooding caused no (“Alb”) or only little (“Rhine”)

reduction in Amax in F. excelsior , prolonged flooding reduced Amax by 87 % and 64 %

in comparison to the controls, respectively. The reduction in Amax was also observed in

F. angustifolia but it was less pronounced (38 %) than in F. excelsior . The differences

in reduction between the two F. excelsior provenances and F. angustifolia were, however,

statistically not significant (fig. 3.24).

3.2.1.2 Stomatal conductance

gs displayed a similar pattern as Amax (fig. 3.23). For “Alb”, relatively high values (25.29

± 10.45 mmol m-2 s-1) were observed in the control plants on day 3 and much lower

values on day 10 (7.69 ± 4.04 mmol m-2 s-1). In “Rhine”, gs was low on both days

(7.42–9.54 mmol m-2 s-1). F. angustifolia displayed considerably higher gs (41.66 ± 22.77

mmol m-2 s-1). Flooding caused a significant decrease in gs in both F. excelsior prove-

nances, but not in F. angustifolia. This reduction was strongest in “Alb” (66 %), com-

pared to 50 % in “Rhine” and 40 % in F. angustifolia (fig. 3.24). However, there were no

statistically firm differences between the F. excelsior provenances and F. angustifolia.

3.2.1.3 Comparison of Amax and gs between experiment I and II

A summary of the overlapping data of the two experiments is presented in tab. 3.2. The

three-day flooding treatment was carried in both years, allowing for a direct comparison.

The 14-day treatment in experiment I, however, was compared to the 10-day treatment

80 Results

Day of experiment

g s (m

mol

m−−2

s−−1

)A

max

(µµm

ol m

−−2 s

−−1)

02

46

8Alb Rhine Ang

020

4060

3 10 3 10 3 10

ControlFlooded

p=0.055

n.d.

n.d.

* **

A

B

Figure 3.23: Effect of flooding on net assimilation (A) and stomatal conductance (B) of “Alb”, “Rhine”and F. angustifolia. Trees were flooded for the time indicated and leaf gas exchange was measuredwith a portable photosynthesis system. Bars represent means of five different plants on each day (±SD). Asterisks indicate significant differences between flooding and control treatment as calculated byt tests, using standard significance codes. n.d., no data.

in experiment II.

For “Alb” and “Rhine”, three general trends were identified regarding Amax. (1) A strong

reduction in Amax was observed after 10/14 days of submergence. By contrast, short-

term flooding of three days caused no or only small decreases in Amax. (2) The reduction

in “Alb” was more pronounced than in “Rhine”, when compared within each experiment

(65 % in “Alb” vs. 36 % in “Rhine” in experiment I; 87 % in “Alb” vs. 64 % in “Rhine” in

experiment II). (3) The plants were more heavily affected by the long flooding treatment

in experiment II than in experiment I (“Alb”: 87 % in experiment II vs. 65 % in experiment

I; “Rhine”: 64 % in experiment II vs. 36 % in experiment I). A difference between the

experiments was observed regarding the reaction to short-term flooding: in “Alb”, there

was a reduction in Amax in experiment I but not in experiment II. “Rhine” contrarily

showed such a reduction in experiment II but not in experiment I.

Some general trends were also noticed for gs. (1) 10 or 14 days of flooding resulted in

3.2 Experiment II: Effect of flooding on “Alb”, “Rhine” and F. angustifolia 81

Day of experiment

Am

ax (%

of c

ontr

ol)

050

100

150

3 10

Day of experiment3 10

050

100

150Alb

RhineAng

g s (%

of c

ontr

ol)

a

a

a

A

A A

a

a a

A

A

A

A B

Figure 3.24: Effect of flooding on net assimilation (A) and stomatal conductance (B) of “Alb”, “Rhine”and F. angustifolia. Trees were flooded for the time indicated and Amax and gs were calculated on apercent basis of the controls. Bars represent means of five different plants per day (± SD). Differentletters indicate significant differences between provenances within each day and parameter (ANOVAwith Tukey’s HSD, p < 0.05). Results for F. angustifolia on day 3 were calculated on the basis of thecontrol plants of day 10.

reduced gs values whereas 3-day flooding did not. (2) The reduction on day 10 or 14,

respectively, was more distinct in “Alb” than in “Rhine” when compared within each

experiment (experiment I: 48 % in “Alb” vs. 14 % in “Rhine”; experiment II: 66 % in

“Alb” vs. 50 % in “Rhine”). The response of gs to the short flooding treatment, however,

was different between the experiments. While no change from control levels was observed

in experiment II, there was a significant increase in experiment I (“Alb”: 840 %, “Rhine”:

594 %).

3.2.2 Pigment contents

The content of total leaf pigments in unflooded control plants ranged from 2.65 to 3.19

mg g-1 FW for F. excelsior and from 3.07 to 3.84 mg g-1 FW for F. angustifolia. The

pigments were composed of approx. 63–69 % chlorophyll a, 15–18 % chlorophyll b and

16–21 % carotinoids (fig. 3.25). In the control plants, the total pigment content increased

from day 3 to day 10 by 10 % (“Alb”), 47 % (“Rhine”) and 25 % (F. angustifolia),

respectively. Such increases were not observed in the flooded trees. As a consequence, the

total pigment content on day 10 was tendentially (“Rhine”, F. angustifolia) or significantly

(“Alb”) reduced as compared to the controls. The reduction in “Alb” amounted to approx.

33 % and was due to decreased contents of both chlorophyll a (−34 %) and chlorophyll b

82 Results

Table 3.2: Comparison of leaf gas exchange results between experiments I and II. Data representmean assimilation rate (Amax) and stomatal conductance (gs) of four or five flooded plants per treatmentday, expressed as percent of the respective controls. Data compiled from figures 3.2 and 3.24. SD inbrackets.

Alb Rhine BFor F. ang.

exp. I exp. II exp. I exp. II exp. I exp. IIAmax (%) Day 3 71 106 108 63 46 82

(±25) (±51) (±57) (±15) (±22) (±29)Day 10/14 35 13 64 36 80 62

(±12) (±20) (±25) (±42) (±56) (±27)gs (%) Day 3 840 119 594 88 472 77

(±224) (±34) (±435) (±20) (±300) (±32)Day 10/14 52 34 86 50 141 60

(±20) (±2) (±39) (±10) (±39) (±30)

(−29 %).

01

23

4

CO FL CO FL CO FL CO FL CO FL CO FL

Day 3 Day 10 Day 3 Day 10 Day 3 Day 10

Alb Rhine Ang

Pig

men

t con

tent

(m

g g−−1

FW

)

Treatment / Day of experiment

Chl aChl bCr

*

*

*

Figure 3.25: Effect of flooding on leaf pigment content in “Alb”, “Rhine” and F. angustifolia. Trees weresubjected to flooding for the times indicated and leaf pigment content was determined photometricallyas described in Materials and Methods. Bars represent means (± SD) of five plants, with three leavesanalysed in each plant. Asterisks (*) indicate significant differences between flooded and control treat-ment (t test, p < 0.05). Chl a, chlorophyll a; Chl b, chlorophyll b; Cr, carotinoids; CO, Control; FL,Flooded.


3.2.3 Contents of soluble leaf proteins

In unflooded plants, contents of soluble leaf proteins amounted to 37.32 to 41.02 mg g-1 FW

in F. excelsior and to considerably higher values (≈56 mg g-1 FW) in F. angustifolia.

While no changes to these concentrations were observed after three days of flooding in

F. angustifolia, the 10-day flooding treatment caused statistically significant reductions

of leaf protein contents in both F. excelsior and F. angustifolia (fig. 3.26). Among the

F. excelsior provenances, “Rhine” was more heavily affected (−59 %) than “Alb” (−35 %).

The effect on F. angustifolia was less distinct (−17 %). An analysis of variance revealed

significant differences in the relative protein content between the provenance “Rhine” on

the one hand, and “Alb” and F. angustifolia on the other hand (fig. 3.26).

Day of experiment

Pro

tein

con

tent

(m

g g−−1

FW

)

020

4060

3 10

Alb

3 10

Rhine

3 10

AngControlFlooded

****

*

n.d. n.d.

A

B

A

Figure 3.26: Effect of flooding on soluble leaf protein contents of two provenances of F. excelsior and ofF. angustifolia. Trees were submerged for the times indicated and leaf protein content was determinedusing the Bradford assay as described in Materials and Methods. Bars represent means (± SD) offive plants from each of which two leaves were sampled. Asterisks (*) above bars indicate significantdifferences between the treatments as calculated by t tests, using standard significance codes. Differentletters represent significant differences between the respective treatments as calculated by a one-wayANOVA with Tukey’s HSD at p < 0.05. n.d., no data.

3.2.4 Soluble carbohydrates and starch

3.2.4.1 Leaves

Like in 2004, the main soluble carbohydrates in leaf tissue were mannitol, glucose and su-

crose. In the non-flooded plants, mannitol contents amounted to 72.33 ± 9.6 µmol g-1 FW,

84 Results

constituting 54 ± 3 % of total soluble carbohydrates (TSC). Glucose contents amounted

to 49.30 ± 4.33 µmol g-1 FW (37 ± 4 %), sucrose to 11.1 ± 3.96 (8 ± 2 %). Fructose was

only present in minor amounts of max. 5 µmol g-1 FW (≈5 % of TSC). TSC amounted

to concentrations of 114 to 155 µmol g-1 FW, which was significantly higher than in ex-

periment I. This increase indicated a considerable difference in the C status of the plants

as compared to experiment I (see discussion).

Flooding caused a remarkable increase of leaf sugar contents in all provenances/species

(fig. 3.27A). This effect was visible already after three days of flooding, resulting, for

example, in an accumulation of TSC at 188 % of the control in F. angustifolia. Prolonged

flooding led to a similar increase, e.g. to 175 % of the control in the provenance “Rhine”.

Interestingly, provenances “Alb” and “Rhine” differed in their response to short-term

flooding: while no increase in TSC contents was observed in “Alb”, TSC contents sig-

nificantly increased in “Rhine” to 145 % of the control. F. angustifolia differed from

F. excelsior in its response to the long-term flooding as no difference in TSC contents

from the control (≈105 %) was observed.

Regarding individual carbohydrates, the contents of mannitol increased to 163–203 %

of the respective control group in response to flooding (tab. 3.3). This increase was

statistically significant when also a significant increase in TSC contents was observed.

Glucose contents increased to a similar extent as mannitol (151–173 %), however, with

fewer significant effects. Sucrose concentrations were tendentially increased on day 3 in all

plants (162–184 %) with the increase in F. angustifolia being statistically significant. On

day 10, however, sucrose contents were only increased in “Alb” (152 %) but significantly

decreased in “Rhine” (68 %) and tendentially decreased in F. angustifolia (77 %).

In order to test if the changes in carbohydrate contents of the flooded plants differed be-

tween provenances or species, respectively, analyses of variance were carried out with the

relative TSC concentrations. The results showed that the contents of TSC did not statis-

tically differ between provenances/species for any of the two flooding periods (tab. 3.3).

Mannitol on day 3 was significantly stronger increased in F. angustifolia than in “Alb”,

whereas the opposite was observed for day 10. The increase in glucose contents was signif-

icantly higher on day 3 in F. angustifolia as compared to both F. excelsior provenances,

whereas no significant differences were found for day 10. The relative sucrose contents

did not differ between groups.

3.2.4.2 Roots

TSC contents in unflooded roots ranged between 18 and 28 µmol g-1 FW. Mannitol and

glucose represented the biggest percentages with 34–49 % of TSC each. Sucrose was


050

100

150

200

250

300

350

Alb Rhine Ang

*

*

**

*

*

*

*

**

**

**

**

nd

SucroseFructose

GlucoseMannitol

010

2030

4050

60



Alb Rhine Ang

*

*

*

**

**

*

**

**

****

***nd


Car

bohy

drat

e co

nten

t (µµm

ol g

−−1 F

W)

A

B

Figure 3.27: Effect of flooding on contents of soluble carbohydrates in leaf (A) and root (B) of “Alb”,“Rhine” and F. angustifolia. Trees were flooded for the times indicated, and soluble carbohydrateswere extracted were from leaf and root tissues for determination by HPLC analysis (see Materials andMethods). Bars represent means (± SD) of five plants. Asterisks (*) indicate significant differencesbetween treatments for individual carbohydrates (* within bar segments) or total carbohydrate contents(* above bars), as calculated by (t test). Ang, F. angustifolia; CO, control; FL, flooded; nd, no data.

present in smaller amounts (16–25 %), fructose mostly constituted less than 4 % of TSC.

Like for the leaves, the TSC content was noticeably (up to four times) higher in experiment

II than in experiment I.

The effect of flooding on TSC contents differed for the two flooding durations studied and

also between provenances and species, respectively. Short-term flooding caused increases

in TSC contents in all plants, with statistically significant effects in “Alb” (193 % of con-

trol) and F. angustifolia (237 %) (fig. 3.27B). Ten-day flooding, however, did not change

86 Results

Table 3.3: Statistical analysis of soluble carbohydrate contents in flooded seedlings of “Alb”, “Rhine”and F. angustifolia. The percent values represent mean carbohydrate contents of flooded plants, ex-pressed as percent of the respective controls. Asterisks (*) indicate significant differences from therespective controls as calculated by t test, using standard significance codes; these are identical tothe ones shown in figs. 3.27 and 3.28. Different letters denote significant differences between prove-nance/treatment combinations within the different carbohydrates (ANOVA with Tukey’s HSD, p < 0.05).

Type Carbohydrate Day Alb (%) Rhine (%) F. ang. (%)Leaf Total 3 112.46 a 145.21 * ab 188.66 * a

10 175.02 * ab 153.38 * b 105.84 abMannitol 3 105.36 bc 170.71 ** ab 203.49 ** a

10 188.42 * a 163.13 * ab 83.19 cGlucose 3 101.16 a 105.12 a 172.98 * b

10 157.50 b 151.49 * ab 139.91 abSucrose 3 162.30 a 184.26 a 162.52 ** a

10 152.64 a 68.33 * a 76.83 a

Root Total 3 193.42 * ab 145.65 ab 237.14 * a10 101.04 b 140.78 ab 237.76 ** ab

Mannitol 3 326.81 ** a 295.10 * a 321.59 * a10 214.75 a 238.50 * a 286.32 * a

Glucose 3 127.74 a 65.85 * ab 133.62 a10 50.77 b 22.04 ** b 143.28 ** a

Sucrose 3 133.16 ab 82.84 a 217.83 * b10 58.62 a 131.25 ab 217.61 ** b

Phloem Total 3 126.52 a 146.34 a 150.93 * a10 325.51 *** b 241.28 ** ab 251.29 ** ab

Mannitol 3 108.47 b 162.41 ab 152.21 * ab10 241.00 *** a 241.09 ** a 208.59 * a

Glucose 3 210.53 − −10 − 143.81 458.24

Sucrose 3 205.74 a 320.11 a 141.63 a10 697.15 * ab 323.15 *** a 963.95 ** b

Xylem Total 3 296.39 a 101.94 a 177.54 a10 − 244.17 * a 186.69 * a

Mannitol 3 270.27 a 102.70 a 170.48 a10 − a 238.31 a 151.64 * a

Glucose 3 468.65 a 86.14 a 238.65 a10 − a 213.33 a 406.52 * a

Sucrose 3 349.6 * a 118.76 a 176.19 a10 − 421.75 ** a 404.35 *** a

TSC contents in “Alb” whereas otherwise slight (“Rhine”) and significant (F. angustifolia)

increases were observed.

A closer look at individual carbohydrates revealed differential responses of different com-

pounds to flooding. Prolonged flooding led to a remarkable increase in mannitol in both

F. excelsior (215–239 % of control) and F. angustifolia (286 %). By contrast, glucose

and sucrose in F. excelsior were decreased or unchanged as compared to the controls in


response to flooding (tab. 3.3). In F. angustifolia, however, glucose and sucrose accumu-

lated significantly to 143 (glucose) and 218 % (sucrose) of the controls.

As a consequence, TSC contents in F. excelsior roots, flooded for ten days, changed in

favour of mannitol. The percentage of the latter rose from 39 % to 72 % in “Alb” and from

47 % to 79 % in “Rhine”. Accordingly, percentages of glucose and sucrose dropped from

together 61 % to 28 % in “Alb” and from 53 % to 21 % in “Rhine”. Due to the different

response pattern described for F. angustifolia, the change in carbohydrate composition

was less pronounced (see fig. 3.27B).

3.2.4.3 Phloem exudates

TSC contents in the phloem exudates of non-flooded plants ranged from 4.9 to 14.0

µmol g-1 FW. Mannitol constituted the major fraction (76–93 % of TSC), followed by

sucrose (5–18 %) and glucose (0–8 %). Flooding caused a dramatic increase of TSC

contents in all plants investigated. While the effect of short-term flooding was relatively

mild and only affected the TSC content of F. angustifolia in a statistically significant

manner (151 % of control), prolonged flooding affected all plants significantly (fig. 3.28A).

It resulted in increases by factors of 2.4 (“Rhine”, F. angustifolia) to 3.3 (“Alb”). These

relative TSC concentrations of the flooded plants, however, did not differ statistically

between the three groups (tab. 3.3).

Regarding the individual carbohydrates, mannitol contents increased on day 10 by factors

of 2.1 (F. angustifolia) to 2.4 (“Alb”, “Rhine”), with no statistical differences between the

three groups. In contrast, the increase of sucrose contents was much higher as compared

to that of mannitol in “Alb” (697 %) and F. angustifolia (963 %) but approx. equal in

“Rhine” (323 %). The difference between F. angustifolia and “Rhine” was statistically

significant (tab. 3.3).

3.2.4.4 Xylem sap

In xylem sap, TSC contents in non-flooded plants amounted to 6.1–15 mM in “Rhine”

and F. angustifolia, but was sometimes higher in “Alb” (up to 28.5 mM). Mannitol

constituted the major fraction (70–86 %), while glucose and sucrose each contributed

1–15 % to TSC. In comparison to experiment I, TSC contents were approx. 1.5 to 3-fold

higher in experiment II.

For “Alb”, the three-day flooding treatment caused a considerable (296 %), yet statisti-

cally insignificant increase in TSC contents. In contrast, no or only marginal increases

88 Results

010

2030

4050

60Alb Rhine Ang

Car

bohy

drat

e co

nten

t (µµm

ol g

−−1 F

W)

*

*

*

***

**

****

***

***

***

SucroseFructose

GlucoseMannitol

020

4060

8010

0



Alb Rhine Ang

Car

bohy

drat

e co

ncen

trat

ion

(mM

)

*

**

***nd nd


A

B

Figure 3.28: Effect of flooding on contents of soluble carbohydrates in phloem exudates (A) and xylemsap (B) of “Alb”, “Rhine” and F. angustifolia. Trees were flooded for the times indicated, and solublecarbohydrates were extracted were from phloem exudates and xylem sap for determination by HPLCanalysis (see Materials and Methods). Bars represent means (± SD) of five plants. Asterisks (*)indicate significant differences between treatments for individual carbohydrates (* within bar segments)or total carbohydrate contents (* above bars), as calculated by (t test). Xylem sap data for “Alb”, day 10,are missing because xylem sap could not be obtained due to extremely negative stem water potentials(below −30 bars). Ang, F. angustifolia; CO, control; FL, flooded; nd, no data.

were observed in “Rhine” and F. angustifolia, respectively (fig. 3.28B). Prolonged flood-

ing, however, caused significantly increased TSC concentrations in both “Rhine” (244 %)

and F. angustifolia (187 %). For “Alb”, no results were available as xylem sap could not

be harvested due to extremely negative stem water potentials after 10 days of flooding

(below −30 bars).


The accumulation effect on xylem sap TSC contents by flooding was similar for all com-

pounds studied. In response to 10-day flooding, mannitol increased by factors of 1.5

(F. angustifolia) to 2.4 (“Rhine”). Glucose increased by factors of 2.1 (“Rhine”) to 4.1

(F. angustifolia) and sucrose by factors of 4.0 (F. angustifolia) to 4.2 (“Rhine”). The

statistical comparison did not indicate differences between provenances and species, re-

spectively, for TSC and its components (tab. 3.3).

3.2.4.5 Starch in leaves

The starch content in leaves of unflooded control plants ranged between 24.18 and 48.83

µmol gluc. eq. g-1 FW, with the exception of “Alb” where considerably higher values were

found on day 10 (142.44 ± 78.90 µmol gluc. eq. g-1 FW). In flooded plants, starch contents

significantly increased at three days of flooding in “Alb” (223 % of the control) and

F. angustifolia (189 %) (fig. 3.29A). By contrast, there was no change compared to control

levels in “Rhine”. Prolonged flooding still maintained elevated starch levels in “Alb”

(215 %) but not in the other groups. Significant differences between the provenances and

species were only evident between the relatively high contents of “Alb” and F. angustifolia

on day 3 on the one hand, and the relatively low content of “Rhine” on day 10 on the

other hand (ANOVA with Tukey’s HSD at p < 0.05). At identical flooding durations, no

statistical differences were observed between provenances or species, respectively.

3.2.4.6 Starch in roots

In unflooded roots, starch contents ranged between 3.65 and 11.48 µmol gluc. eq. g-1

FW. In contrast to short-term flooding, which resulted in no significant changes in root

starch contents, prolonged flooding caused considerable decreases in starch contents in

“Alb” and F. angustifolia (fig. 3.29B). By contrast, the provenance “Rhine” showed a

significant increase in starch contents (283 % of the control). Within each provenance,

the relative starch contents of the flooded plants in comparison to the controls, did not

differ statistically between flooding durations (ANOVA with Tukey’s HSD at p < 0.05).

There were also no statistical differences between provenances at each flooding duration

(ANOVA with Tukey’s HSD at p < 0.05).

90 Results

Day of experiment

Sta

rch

cont

ent (

µµmol

glu

c. e

q. g

−−1 F

W)

010

020

030

0Alb Rhine Ang

05

1015

3 10 3 10 3 10

ControlFlooded

**

***

**

n.d.

n.d.

A

B

Figure 3.29: Effect of flooding on leaf (A) and root (B) starch contents of “Alb”, “Rhine” and F. angus-tifolia. Trees were flooded for three or ten days as indicated and starch contents were determined byenzymatic conversion to glucose and subsequent analysis by HPLC (see Materials and Methods). Barsrepresent means (± SD) of five plants. Asterisks (*) indicate significant differences between treatmentsas calculated by t tests, using standard significance codes. Ang, F. angustifolia; n.d., no data.

3.2.5 ADH activity, ethanol contents and acetaldehyde exchange

3.2.5.1 Root ADH activity

Similar to experiment I, ADH activities in roots of normoxic controls were low in all

plants investigated in experiment II (0.13–1.48 U g-1 FW). Activities increased in response

to flooding by a factor of up to 15 (fig. 3.30B). For F. excelsior provenance “Rhine”

and F. angustifolia, ADH activities were higher after prolonged flooding than after the

short, 3-day treatment. The contrary was observed for provenance “Alb”, which exhibited

relatively high activities after short (8.02 ± 6.89 U g-1 FW), but lower activities after

prolonged flooding (2.82 ± 2.05 U g-1 FW). Due to high variation between the individual

plants, however, there were no statistically firm differences among the flooded plants of

the three groups (fig. 3.30B).


Day of experiment

AD

H a

ctiv

ity (

U g

−−1 F

W)

AD

H a

ctiv

ity (

U g

−−1 F

W)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Alb Rhine Ang0

510

15

3 10 3 10 3 10

ControlFlooded

n.d. n.d.

**

*

***

*

**

***A

AA

AA

A

A

B

Figure 3.30: Effect of flooding on leaf (A) and root (B) ADH activity in “Alb”, “Rhine” and F. angustifolia.Trees were subjected to three or ten days of flooding and ADH activity was determined biochemicallyin fresh leaf and root tissue, as described in Materials and Methods. Bars represent means (± SD)of five plants. Asterisks (*) indicate significant differences between treatments as calculated by t tests,using standard significance codes. Different letters for root ADH indicate significant differences betweenprovenances within the flooding treatment, as calculated by analysis of variance with Tukey’s HSD (p <0.05). n.d., no data.

3.2.5.2 Root ethanol content

Ethanol contents in non-flooded roots in experiment II were in the range of 10–60 µg g-1 FW

(fig. 3.31B) which was similar to the range of concentrations measured in experiment I.

Flooding caused no significant increase in root ethanol in provenance “Alb” and F. an-

gustifolia. In “Rhine”, however, significantly (approx. 5 times) more ethanol was present

in the submerged roots than in controls (57.54 ± 29.36 vs. 10.38 ± 15.94 µg g-1 FW). This

finding was in contrast to 2004 where no accumulation of ethanol in roots was observed.

92 Results

EtO

H c

onte

nt (

µµg g

−−1 F

W)

200

400

600

800

1000

Alb Rhine Ang

ControlFlooded

EtO

H c

onte

nt (

µµg g

−−1 F

W)

2040

6080

100

120

Day of experiment

EtO

H c

once

ntra

tion

(mM

)1

23

45

6

3 10 3 10 3 10

n.d. n.d. n.d.

n.d. n.d. n.d.

n.d.

*

*

***

**** *

A

B

C

Figure 3.31: Effect of flooding on ethanol contents in leaf (A), root (B) and xylem sap (C) in twoprovenances of F. excelsior and F. angustifolia. Trees were flooded for three or ten days, respectively,and ethanol concentration were enzymatically determined as described in Materials and Methods. Barsrepresent means (± SD) of five plants. Asterisks indicate significant differences between treatments,as calculated by t tests, using standard significance codes. Ang, F. angustifolia; n.d., no data.


3.2.5.3 Leaf ADH activity

ADH activities in leaves of non-flooded plants ranged between 0.2 and 0.9 U g-1 FW.

Flooding did not cause an increase in activities in F. excelsior (fig. 3.12A). Prolonged

flooding even resulted in a significantly decreased ADH activity in the provenance “Alb”

(0.19 ± 0.04 U g-1 FW). By contrast, significantly increased activities were observed for

F. angustifolia in response to short-term (3 d) flooding (0.63 ± 0.12 U g-1 FW).

3.2.5.4 Leaf ethanol content

The amounts of ethanol in leaves of non-flooded trees were similar to the concentrations

measured in experiment I (190–315 µg g-1 FW). Concentrations were not altered in the

flooded trees, irrespective of the flooding duration (fig. 3.13A), thereby supporting the

findings of experiment I.

3.2.5.5 Ethanol concentrations in the xylem sap

While concentrations of ethanol in the xylem sap of control trees were very low (≤ 0.06

mM), flooding caused a strong increase of the concentrations (fig. 3.31C). After short-

term flooding, the concentration was relatively high in “Alb” (3.44 ± 2.46 mM) and

“Rhine” (2.36 ± 1.02 mM), while F. angustifolia showed a weaker increase (0.7 ± 0.46

mM). For the 10-day treatment, no data are available for “Alb” (see above). In “Rhine”

and F. angustifolia, 10-day flooding caused a similar increase of xylem ethanol contents

as on day 3 (1.34 ± 0.68 and 0.47 ± 0.24 mM, respectively).

3.2.5.6 Acetaldehyde exchange with the atmosphere

As no significant acetaldehyde emission rates were found in experiment I, emission rates

were exemplarily checked for only one of the F. excelsior provenances in experiment II

(“Rhine”). The measured emission rates were in the range of the blank controls (not

shown), supporting the low emission rates of experiment II. Consequently, measurements

for the remaining plants were omitted.

3.2 Photosynthetic performance of ash and three other species 95

3.3 Experiment III: Effect of flooding on the photosynthetic

performance of common ash and three other species of

varying flood tolerance

The previous experiments with different provenances of F. excelsior and with F. angusti-

folia showed differences in the response of CO2 assimilation to flooding. This experiment

was aimed at testing the photosynthetic performance of ash under flooding compared

to other species. For this purpose, the photosynthetic performance of three-year-old

seedlings of common ash, small-leaved lime (Tilia cordata Mill.), pedunculate oak (Quer-

cus robur L.) and purple willow (Salix purpurea L.) was investigated. The ash seedlings

in this experiment were from a South German mountainous area (HKG 81107), a region

including the previously characterised provenance areas “Alb” and “BFor”. Trees from

this region were assumed to represent a flood-sensitive ecotype.

Photosynthesis depends on numerous environmental conditions, including light intensity

and ambient CO2 concentration. The response of assimilation rates to varying ambient

conditions can be studied by recording photosynthetic light and CO2 response curves.

From the analysis of these curves, important photosynthetic parameters can be deduced,

which provide information about the processes limiting photosynthesis. These parameters

include light and CO2 saturated assimilation rates, apparent quantum yield and apparent

carboxylation efficiency as well as light and CO2 compensation points. The influence of a

14-day flooding treatment on these parameters was studied in the species indicated above.

3.3.1 Light response curves

Assimilation rate plotted against increasing light intensity yielded typical saturation

curves (fig. 3.32). Curve shapes differed between species, e.g. regarding the saturation

level (Amax). While Amax light was reached at relatively high light intensities of ≥1000

µmol m-2 s-1 in ash and willow, the same parameter was reached at much lower light

intensities in lime (200–400 µmol m-2 s-1) and oak (100–300 µmol m-2 s-1). The magnitude

of Amax light varied between 1.54 µmol m-2 s-1 in oak and 11.86 µmol m-2 s-1 in willow. Sim-

ilarly large differences were observed regarding the initial slope of the curves, representing

the apparent quantum yield of photosynthesis (Aqe). Aqe varied from low values in ash

(3.07 · 10-3) to high values in oak (20.6 · 10-3), visible as a relatively flat or steep initial

slope of the curves, respectively (fig. 3.32).

Flooding decreased Amax light markedly by 48 % from 5.60 µmol m-2 s-1 in the controls to

96 Results

Table 3.4: Summary of parameters obtained from light and CO2 curve analysis. Different letters of thesame case indicate significant differences between treatments within each species. See text for furtherexplanations. DOE, day of experiment; T, treatment; CO, control; FL, flooded.

Species DOE T Amax light Aqe (·103) LCP Amax CO2 ε (·103) CCP

Ash 3 CO 4.46 a 3.07 A −7.47 α 14.10 a’ 1.81 A’ 140.40 α’FL 3.59 a 3.17 A −17.48 α 15.82 a’ 1.28 A’ 129.10 α’

10 CO 5.60 a 4.78 AB 10.54 α 10.54 a’ 3.21 B’ 114.60 α’FL 2.93 a 7.57 B −3.92 α 12.40 a’ 1.38 A’ 137.30 α’

Lime 3 CO 3.98 a 9.43 A 18.26 α 7.69 a’ 2.85 A’ 109.10 α’FL 2.42 ab 11.97 A 26.32 α 6.47 a’ 2.85 A’ 159.60 α’

10 CO 2.95 ab 9.81 A 21.38 α 7.15 a’ 2.92 A’ 161.10 α’FL 1.56 b 5.40 A 33.73 α 4.59 a’ 2.85 A’ 119.10 α’

Oak 3 CO 2.29 a 12.27 A 6.96 α 7.88 a’ 0.69 A’ −10.96 α’FL 2.01 a 19.64 A 2.17 α 3.48 b’ 1.78 A’ −27.25 α’

10 CO 1.54 a 20.55 A 14.48 α 5.81 ab’ 0.70 A’ −126.10 α’FL 1.21 a 14.28 A 31.47 α 3.62 b’ 2.98 A’ 75.46 α’

Willow 3 CO 9.46 a 4.82 A 5.36 α 21.54 a’ 3.31 A’ 112.90 α’FL 8.58 a 5.76 A 24.15 α 24.94 a’ 2.66 A’ 114.50 α’

10 CO 11.86 a 3.91 A −1.94 α 20.63 a’ 4.78 A’ 155.40 αβ’FL 9.50 a 6.21 A 6.76 α 18.95 a’ 4.95 A’ 244.30 β’

2.93 µmol m-2 s-1 in the flooded plants. This difference, however, was statistically not

significant (see letter notation in fig. 3.32 and tab. 3.4). A similar difference between

flooded and control group was found for lime, which, however, was already present before

the flooding treatment. Amax light was otherwise not (oak) or only marginally (willow)

decreased. Thus, significant effects of flooding on Amax light were not observed.

Aqe increased by 54–59 % in ash and willow, whereas it decreased by 31 and 45 % in oak

and lime, respectively. However, none of these effects were statistically significant. Light

compensation points (LCP) were in the range of 10–30 µmol m-2 s-1 for lime and oak, and

in the range 0–10 µmol m-2 s-1 for ash and willow. In none of the species, the LCP was

altered significantly by the flooding treatment.

3.3.2 CO2 response curves

Similar to the light response curves, CO2 response curves showed clear differences between

the species. In the non-flooded plants, saturation levels were reached at CO2 concentra-

tions of 1000–1500 ppm in willow and lime, and at higher concentration in ash and oak

(>2000 ppm) (fig. 3.33). The initial slope of the curves, representing the apparent car-

boxylation efficiency (ε), also differed between species. ε was strikingly lower in control

plants of oak (0.69–0.70 mol m-2 s-1) as compared to control plants of ash (1.81–3.21

mol m-2 s-1), lime (2.85–2.92 mol m-2 s-1) and willow (3.31–4.78 mol m-2 s-1).

Flooding did not result in a significant change in CO2-saturated photosynthesis (Amax CO2)


02

46

8

Day 0

●

●

●

●

●

●

●

●

● ● ●●

●

●

●

●

●

●

●

●●

●

●

●

02

46

8

y == 4.456 [1 −− e−−0.00307((x++7.466))]; r2 == 0.784y == 3.589 [1 −− e−−0.003169((x++17.48))]; r2 == 0.644

ash

Day 14

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●●

●

●

y == 5.601 [1 −− e−−0.004779((x−−10.54))]; r2 == 0.691y == 2.929 [1 −− e−−0.007571((x++3.918))]; r2 == 0.909

●

ControlFlooded

02

46

8

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●●

● ●

●

02

46

8

y == 3.976 [1 −− e−−0.009431((x−−18.26))]; r2 == 0.778y == 2.424 [1 −− e−−0.01197((x−−26.32))]; r2 == 0.901

lime

●●

●

●

●●

● ●

● ●● ●

● ● ●

●●

●

●● ●

●

● ●

y == 2.945 [1 −− e−−0.009808((x−−21.38))]; r2 == 0.975y == 1.559 [1 −− e−−0.005401((x−−33.73))]; r2 == 0.888

02

46

8

●

●

● ●

●●

●

●

● ● ● ●

●

●

●

●

●●

●

●

● ●

●●

●

●

●

● ●●

02

46

8

y == 2.29 [1 −− e−−0.01227((x−−6.961))]; r2 == 0.421y == 2.013 [1 −− e−−0.01964((x−−2.169))]; r2 == 0.686

oak

●●

● ●●

●

●

●

●●

● ●

●

●

●

●

● ●

●

●●

● ● ●●

● ●●

●●

y == 1.542 [1 −− e−−0.02055((x−−14.48))]; r2 == 0.248y == 1.206 [1 −− e−−0.01428((x−−31.47))]; r2 == 0.169

05

1015

●

●

●

●

●

●

●

●

●

●

●

●

05

1015 y == 9.455 [1 −− e−−0.004816((x−−5.362))]; r2 == 0.935

y == 8.581 [1 −− e−−0.005758((x−−24.15))]; r2 == 0.75

0 200 400 600 800 1000

will

ow

●

●

●

● ●

●

●

●

● ●

●

●

●

● ●

●

●

●

●●

y == 11.86 [1 −− e−−0.003911((x++1.936))]; r2 == 0.876y == 9.503 [1 −− e−−0.006212((x−−6.76))]; r2 == 0.798

0 200 400 600 800 1000

Ane

t (µµm

ol m

−−2 s

−−1)

Incident PPFD (µµmol m−−2 s−−1)

a

a

A

A

a’

a’a

a

AB

B

a’

a’

a

a

A

A

a’

ab’ a

a

A

A

ab’

b’

a

a

A

A

a’

a’

a’

a’A

A

a

a

aa

a

A

A

a’

a’

a

A

A

a’

a’

Figure 3.32: Effect of flooding on light response curves in three-year-old seedlings of ash,lime, oak and willow. Assimilation rates at PPFDs of 0, 100, 200, 500 and 1000 µmol m-2 s-1

were recorded a first time before any flooding treatment was applied (day 0). After 14 days offlooding, a second set of light curves was recorded (day 14). Measurements were conductedfor an equal number of control plants. In both flooded and control groups, the same plantsused on day 0 and day 14. Points represent means for individual plants. For curve fitting,the Mitscherlich equation, y = Amax[1 − e−Aqe(x−LCP )], was used, providing parameterestimates for light saturated photosynthesis (Amax), apparent quantum yield (Aqe) and lightcompensation point (LCP). Different letters of the same case indicate significant differencesfor Amax (primed), Aqe (upper case) and LCP (lower case) within species, as calculated fromthe output of a nonlinear mixed effects model (see Materials and Methods).

98 Results

for any of the four species, though slight reductions of Amax CO2 were observed for oak

(−36 %) (fig. 3.33, tab. 3.4). In willow, Amax CO2 in the flooded plants decreased from

24.94 µmol m-2 s-1 on day 0 to 18.95 µmol m-2 s-1 on day 14 (−24 %), while the control

plants maintained a high Amax CO2. A significant decrease by 57 % in ε was only observed

in ash (1.38 vs. 3.21 mol m-2 s-1).

The CO2 compensation point (CCP) was not significantly affected by flooding, with the

exception of willow, where a shift towards higher CO2 concentrations was detected (244

vs. 155 ppm; tab. 3.4). However, in the latter case, only few data were available for

the CO2 concentration range below 375 ppm, resulting in potential inaccuracies in CCP

estimation.


05

1015

20

Day 0

●

●

●

●

●

●

● ●

●

●

●

●

●

●

●

●

●●

●

●

05

1015

20 y == 14.1 [1 −− e−−0.001806((x−−140.4))]; r2 == 0.857y == 15.82 [1 −− e−−0.00128((x−−129.1))]; r2 == 0.946

ash

Day 14

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

y == 10.54 [1 −− e−−0.003208((x−−114.6))]; r2 == 0.884y == 12.4 [1 −− e−−0.001382((x−−137.3))]; r2 == 0.935

●

ControlFlooded

05

1015

20

●

●

● ● ●

●

●

●

●

● ●●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

05

1015

20 y == 7.694 [1 −− e−−0.002853((x−−109.1))]; r2 == 0.771y == 6.473 [1 −− e−−0.002859((x−−159.6))]; r2 == 0.721

lime

●

●

● ● ●●

●

●●

●●

●

●

●

●

●

●●

●

●

●

●

●●

y == 7.152 [1 −− e−−0.002915((x−−161.1))]; r2 == 0.792y == 4.589 [1 −− e−−0.002849((x−−119.1))]; r2 == 0.945

05

1015

20

● ● ●●

● ●● ●●

●●

●

●

●

●

●

●●

●

● ● ● ● ●

● ●●

●

●●

05

1015

20 y == 7.876 [1 −− e−−0.0006911((x++10.96))]; r2 == 0.719y == 3.483 [1 −− e−−0.001775((x++27.25))]; r2 == 0.243

oak

● ●● ● ●●

●

●

●

●●

●

●●

● ● ●

y == 5.81 [1 −− e−−0.000702((x++126.1))]; r2 == 0.796y == 3.622 [1 −− e−−0.002982((x−−75.46))]; r2 == 0.611

05

1015

2025

30

●

●

●

●

●

●

●

●

●

●

●

●

05

1015

2025

30 y == 21.54 [1 −− e−−0.003311((x−−112.9))]; r2 == 0.99y == 24.94 [1 −− e−−0.002658((x−−114.5))]; r2 == 0.917

0 500 1000 1500 2000

will

ow

●

●●

●

●

●

●

●●

●

● ●

y == 20.63 [1 −− e−−0.004779((x−−155.4))]; r2 == 0.823y == 18.95 [1 −− e−−0.004953((x−−244.3))]; r2 == 0.936

0 500 1000 1500 2000

Ane

t (µµm

ol m

−−2 s

−−1)

Ambient CO2 concentration (ppm)

a

a

A

A

a’

a’

a

a

B

A

a’

a’

a

a

A

A

a’

a’a

a

A

A

a’

a’

a

a

A

A

a’

b’

ab’

b’A

A

a

a

b

a

a

A

A

a’

a’

ab

A

A

a’

a’

Figure 3.33: Effect of flooding on CO2 response curves in ash, lime, oak and willow. Assimi-lation rates at CO2 concentrations of 140, 250, 375, 700, 1400 and 2000 ppm were recordeda first time before any flooding treatment was applied (day 0). After 14 days of flooding, asecond set of light curves was recorded (day 14). Measurements were conducted for anequal number of control plants. In both flooded and control groups, the same plants usedon day 0 and day 14. Points represent means for individual plants. For curve fitting, theMitscherlich equation, y = Amax[1−e−ε(x−CCP )], was used, providing parameter estimatesfor light saturated photosynthesis (Amax), apparent carboxylation efficiency (ε) and CO2 com-pensation point (CCP). Different letters of the same case indicate significant differences forAmax (primed), ε (upper case) and CCP (lower case) within species, as calculated from theoutput of a nonlinear mixed effects model (see Materials and Methods).

3.4 Experiment IV: Effect of flooding on phloem transport of leaf-fed 13C-glucose 101

3.4 Experiment IV: Effect of flooding on phloem transport

of leaf-fed 13C-glucose

The experiments with different ash provenances revealed considerable accumulation of

soluble carbohydrates in leaf as well as phloem tissue in response to flooding. These results

supported the idea of a reduced phloem transport of sugars in flooded trees. In this section,

results from a pulse-chase experiment are presented in which assimilate translocation

in flooded plants was studied in more detail. At the end of a 7-day flooding period,

isotopically labelled glucose (U-13C-glucose) was introduced into the leaves of different

species. The translocation of the label in the phloem was followed by collecting multiple

phloem exudate samples along the stem. The amount of 13C derived from feeding was

calculated from the 13C/12C isotope ratio of the phloem exudates. Non-flooded trees

served as controls. Besides ash, flood-sensitive sycamore maple (Acer pseudoplatanus L.)

and highly flood-tolerant American aspen (Populus tremula L.) were studied.

3.4.1 Feeding-derived 13C in the application leaf

In the control trees, the major portion of 13C derived from feeding remained in the ap-

plication leaves. In ash, the percentage amounted to 45.21 ± 30.98 %, in maple to

52.83 ± 46.44 % and in poplar to 69.75 ± 55.93 % (tab. 3.5). Seven-day flooding in-

creased the percentage of label retained in the application leaves. While in ash and maple

this increase amounted to only 20.5 and 20.2 %, respectively, as compared to the controls,

it was considerably more pronounced in poplar (52.3 %) (tab. 3.5).

3.4.2 Feeding-derived 13C in phloem exudates

The amount of label recovered from phloem exudates was much smaller in comparison

with the application leaves. Depending on species, max. 1 % of label was detected in

the phloem sap of the total stem section below the application leaf in non-flooded trees

(tab. 3.5, “Total bark”). A decreasing, basipetal gradient from stem segment 1 to segment

5 was found in all species. In the lowest segment (5), only very low amounts of feeding-

derived 13C of max. 0.05 % were detected. The remaining feeding-derived 13C, that was

neither detected in application leaves nor in phloem exudates, amounted to 29.41–54.57 %

(tab. 3.5, “Rest”).

Flooding resulted in a slight increase of the portions of fed 13C in the three middle stem

segments (2, 3 and 4) in ash and maple, in comparison to the respective controls (fig. 3.34).

102 Results

However, this effect was statistically significant only for segment 2 in ash (fig. 3.34). In

contrast to ash and maple, the amounts of label found in poplar in stem segments 2–4

were were not increased but tendentially lower than in the controls. Nevertheless, these

changes were not statistically significant either.

Table 3.5: Amounts of feeding solution and 13C taken up. A flap was cut into fully mature leaves of thespecies indicated. The table gives the total amount (µL) of solution taken up by the flap leaf from whichthe amount of 13C taken up was calculated. After 4–6 h of 13C application, five bark samples wereharvested along the stem and exudated. From the 13C signature of the phloem exudates, amounts of13C derived from feeding were calculated for five stem segments as described in Materials and Methods.Mean amounts (± SD) of feeding-derived 13C are indicated in µmol and in percent of total 13C takenup. Wilcoxon rank sum tests were carried to compare the feeding-derived amounts of 13C in applicationleaves and bark segments between treatments. Significant differences are indicated by asterisks (*),using standard significance codes. n = 6–8. T, treatment; CO, control; FL, flooded.

Species T Uptake13C-

glucose,mea-sured(µL)

Uptake13C,

calcu-lated(µmol)

13C derived from feeding

Appli-cation

leaf

Barkfromstemseg-ment

1


2


3


4


5

Totalbark

Rest

Ash CO 52.38 31.41 15.88 0.04 0.01 0.01 0.00 0.00 0.06 15.47

(±15.39) (±9.23) (±9.73) (±0.07) (±0.01) (±0.01) (±0.00) (±0.00) (±0.07) (±4.01)

=100% 45.21% 0.16% 0.02% 0.02% 0.01% 0.00% 0.22% 54.57%

FL 44.57 26.74 15.32 0.06 0.07** 0.01 0.00 0.00 0.14 11.28

(±14.11) (±8.45) (±8.07) (±0.10) (±0.13) (±0.01) (±0.00) (±0.00) (±0.16) (±4.56)

=100% 54.46% 0.17% 0.28% 0.05% 0.02% 0.00% 0.52% 45.02%

Maple CO 74.00 44.40 25.50 0.63 0.03 0.03 0.01 0.00 0.70 18.20

(±39.03) (±23.41) (±20.62) (±1.25) (±0.02) (±0.04) (±0.02) (±0.00) (±1.30) (±4.48)

=100% 52.83% 0.86% 0.06% 0.06% 0.02% 0.00% 1.00% 40.17%

FL 121.83 73.14 47.41 0.89 0.71 0.14 0.17 0.00 1.91 23.82

(±37.40) (±22.39) (±17.36) (±1.28) (±0.95) (±0.17) (±0.34) (±0.01) (±2.58) (±8.90)

=100% 63.48% 1.03% 0.82% 0.15% 0.20% 0.00% 2.20% 34.32%

Poplar CO 115.38 69.21 51.15 0.36 0.11 0.07 0.11 0.03 0.69 17.37

(±34.74) (±20.86) (±38.71) (±0.52) (±0.17) (±0.17) (±0.24) (±0.06) (±0.75) (±29.23)

=100% 69.75% 0.45% 0.13% 0.09% 0.13% 0.05% 0.84% 29.41%

FL 124.13 74.47 80.91 0.34 0.04 −0.01 −0.01 0.00 0.36 0

(±29.22) (±17.50) (±27.89) (±0.80) (±0.12) (±0.01) (±0.01) (±0.00) (±0.92) -

=100% 106.25% 0.40% 0.04% -0.01% -0.01% 0.00% 0.43% 0%

Average distance from feeding leaf (cm)

13C

allo

catio

n (%

of f

ed 13

C)

0.0

0.2

0.4

0.6

0.8

5 17 32 46 57

Ash

0.0

0.5

1.0

1.5

2.0

2.5

5 23 45 63 81

Maple

0.0

0.5

1.0

5 25 45 66 87

Poplar

ControlFlooded

**

Figure 3.34: Effect of flooding on the translocation of 13C in the phloem of ash, maple and poplarseedlings. Trees were flooded for seven days and fed with 13C-glucose via leaf flaps. Phloem transportof feeding-derived 13C was studied by sampling phloem sap from five different heights along the stem.From the 13C signature of the phloem exudates, the amount of 13C derived from feeding was calculatedfor five stem segments as described in Materials and Methods. The graph shows the amount of feeding-derived 13C present in the phloem sap of five equally spaced stem segments. The average distanceof each segment’s centre from the feeding leaf is indicated. Asterisks denote significant differencesbetween flooded and control treatments as calculated by Wilcoxon rank sum tests (**, p < 0.01).

104 Results

3.5 Experiment V: Effect of flooding on stem-internal oxygen concentrations 105

3.5 Experiment V: Effect of flooding on stem-internal oxy-

gen concentrations

The experiments described in this section were aimed at direct determination of O2 in

the stem as influenced by flooding. By means of miniaturized O2 sensors (micro-optodes)

implanted into the stem of tree seedlings, it was possible to track changes in O2 in real-

time. Measurements were carried out continuously over seven to ten days, involving a

flooding treatment of 3–4 days in the middle of this period. By this experimental design,

it was aimed to obtain information about the response of stem-internal O2 to flooding, the

status of O2 during flooding and the recovery from flooding. In addition to F. excelsior,

seedlings of two other species were investigated: pedunculate oak (Quercus robur) and

grey poplar (P. tremula × alba).

In a related experiment, ADH activities in bark samples were determined to test if changed

O2 concentrations in the stem affected the physiology of the trees.

3.5.1 O2 concentrations before flooding

Before the seedlings were subjected to the flooding treatment, stem-internal O2 was

recorded for 2–4 days under normoxic conditions. In ash seedlings, the average pre-

flooding O2 concentrations varied between 70 % and 86 % air saturation (% a.s.), in oak

between 75 % and 87 % a.s. and in poplar between 54 % and 81 % a.s. (tab. 3.6).

For ash and oak, it was tested if sensor implantation height had an influence on the pre-

flooding O2 concentrations. The results indicated a weak inverse-linear relationship for

ash (r2 = 0.73) whereas no such relationship was detected for oak (r2 = 0.02). However,

it is emphasised that these results are of preliminary character, since n was small (6 for

ash, 5 for oak). In poplar, all sensors were implanted at the same stem positions, so no

data were available for correlation analysis.

3.5.2 Response to flooding

Depending on tree species, seedlings showed a more less pronounced reduction of stem-

internal O2 concentrations in response to flooding. In ash and oak, stem-internal O2

concentrations decreased immediately after subjecting the plants to the flooding treatment

(fig. 3.35A+B). This drop took approx. 2 h until a new stable level was reached (fig. 3.36).

In ash, the reduction amounted to 23± 6 % a.s., or 6± 1 % a.s., respectively, depending on

106 Results

Table 3.6: Stem-internal O2 concentrations in ash, oak and poplar seedlings in response to flooding.Oxygen micro-optodes were implanted into the stems of three-year-old seedlings (stem diameter 1–2cm) to follow stem-internal O2 concentrations before, during and after flooding treatments of 5–8 days.Minimum (min), average (avg) and maximum (max) O2 concentrations during these phases (pre-flood,flood, post-flood) are given for each plant investigated. Bold figures additionally indicate average O2concentrations per species (±SD). All O2 concentrations in % air saturation (% a.s.). Depending onexperiment, trees were either equipped with one, or two different sensors at different stem heights, asindicated. In the particular case of ash trees 1 and 2, plants were first exposed to a flood height of 15cm (“full flood height”), that was reduced after four days to 5 cm (“reduced flood height”; cf. fig. 3.35A).Sens., sensor; hflood, flood height in cm above ground; hsens, sensor implantation height in cm aboveground; dsens, distance of sensor from water surface (=hsens−hflood); Reduction, difference between O2concentrations during, and before flooding (=[O2] flood)−([O2] pre-flood).

Plant/Sens.

hflood hsens dsens [O2] pre-flood [O2] flood Reduction [O2] post-flood

(cm) (cm) (cm) (% a.s.) (% a.s.) (% a.s.) (% a.s.)min avg max min avg max min avg max

Ash — below-water sensorsAsh 1/1 15 7 −8 71 77 82 2 6 16 −71 62 75 80Ash 2/1 15 5 −10 71 78 86 10 16 19 −62 77 79 84Ash 3/1 15 4 −11 82 86 92 7 11 16 −75 82 86 93Ash 4/1 15 3 −12 72 78 83 16 17 24 −61 67 73 80

80 13 −67 78(±4) (±5) (±7) (±6)

Ash — above-water sensors (full flood height)Ash 1/2 15 17 2 63 70 74 45 51 54 −19 67 75 83Ash 2/2 15 16 1 64 71 82 36 44 50 −27 69 81 84

71 48 −23 78(±1) (±5) (±6) (±4)

Ash — above-water sensors (reduced flood height)Ash 1/2 5 17 12 63 70 74 60 64 67 −6 67 75 83Ash 2/2 5 16 11 64 71 82 61 66 71 −5 69 81 84

71 65 −6 78(±1) (±1) (±1) (±4)

Oak (all sensors above water)Oak 1/1 5 8 3 81 87 90 68 72 77 −15 92 95 99Oak 1/2 5 17 12 73 80 81 75 76 78 −11 90 91 94Oak 2/1 4 10 6 80 83 86 64 68 71 −15 85 89 95Oak 3/1 2 11 9 76 80 81 75 77 78 −3 77 79 80Oak 3/2 2 27 25 70 75 77 66 69 72 −6 85 86 89Oak 4/1 4 8 4 78 80 82 58 60 61 −20 78 83 86

81 70 −11 87(±4) (±6) (±6) (±6)

Poplar (all sensors above water)Poplar 1/1 5 8 3 52 54 56 54 65 76 11 76 84 79Poplar 2/1 5 8 3 74 77 80 71 73 75 −4 75 85 90Poplar 3/1 5 8 3 76 79 81 73 78 85 −1 89 92 98Poplar 4/1 5 8 3 74 81 91 67 73 76 −8 78 85 95

73 72 −1 85(±13) (±5) (±8) (±5)


whether a full or a reduced flood height was applied (n = 2; tab. 3.6). In the flooded stem

section of ash, the decrease was considerably more pronounced, amounting to 67 ± 7 %

a.s. (n = 4; tab. 3.6). In oak, O2 concentrations were reduced by 11 ± 6 % a.s. (n =

6). In contrast to ash and oak, no clear response was observed in poplar (fig. 3.35C).

The concentrations during flooding (72 ± 5 % a.s., n = 4) were almost identical to those

before flooding (73 ± 13 % a.s.).

In ash and oak, the reduction in stem O2 concentrations was tendentially influenced by

the distance of the measuring position from the water surface, with tendentially larger

reductions near the surface (fig. 3.38). No such tendency was found for poplar.

3.5.3 Response to reaeration

O2 concentrations in ash and oak quickly recovered after termination of the flooding

treatment (fig. 3.36, A2+B2). Pre-flooded O2 concentrations were mostly restored within

2–3 h, i.e. in similar times as the preceding decline upon inundation. Poplar showed no

response to reaeration (fig. 3.36, C2).

In oak and poplar, higher O2 concentrations were detected after flooding compared to

pre-flooding values. O2 concentrations after flooding amounted to 87 ± 6 % a.s. in oak,

compared to 81 ± 4 % a.s. before inundation. In poplar, this response was more pro-

nounced than in oak, with O2 concentrations of 73 ± 13 % a.s. before, and 85 ± 5 % a.s.

after flooding (tab. 3.6).

3.5.4 Determination of sapflow

Sapflow densities were determined in parallel with O2 in all experiments in order to detect

a possible influence of sap stream on stem aeration. However, reliable data were only

obtained for two experiments, one with oak and one with poplar. In these two experiments,

no clear relationship between sapflow densities and stem-internal O2 concentrations were

observed. In oak, for example, sapflow densities decreased with progressing flooding

duration, whereas O2 concentrations remained on the same low level that was reached

at the beginning of the flooding treatment (fig. 3.39). A similar discrepancy between

O2 concentration, and sapflow course was found for poplar: O2 concentrations began to

increase approximately in the middle of the flooding treatment, however, the sapflow

pattern remained unchanged (fig. 3.40).

108 Results

3.5.5 ADH activity in bark tissue

ADH activity, determined as an indicator for anaerobiosis in the bark, was relatively

high in the controls, with specific activities in the range of 1 to 4 U g-1 FW (fig. 3.41).

These activities were comparable to those found for flooded ash roots (sections 3.1.3.1

and 3.2.5.1). Among the four tree species studied, the average activity was lowest in

pedunculate oak (1.6–1.9 U g-1 FW), intermediate in common ash (1.9–2.5 U g-1 FW)

and sycamore maple (2.1–2.5 U g-1 FW), and highest in gray poplar (2.9–3.3 U g-1 FW).

Flooding the trees for one week to a height of 15 cm above ground, did not significantly

increase ADH activities in any of the four species (fig. 3.41). This was true for bark

samples from the unflooded as well as from the flooded stem section. Only in sycamore

maple, activities in the flooded section showed a marked, albeit statistically not significant

increase (60 %).

FL (15 cm) FL (5 cm)0

2040

6080

100

Oxygen (7 cm)Oxygen (17 cm)Temp.

1020

3040

5060

FL (5 cm)

020

4060

8010

0

Oxy

gen

(% a

ir sa

tura

tion)

Oxygen (8 cm)Oxygen (17 cm)Temp.

1020

3040

5060

Tem

pera

ture

(°C

)

020

4060

8010

0

FL (5 cm)

020

4060

8010

0

0 2 4 6 8 10

Day of experiment

Oxygen (8 cm)Temp.

1015

2025

3035

40

A

B

C

Figure 3.35: Response of stem-internal O2 concentrations in ash (A), oak (B) and poplar (C) seedlingsto flooding. Three-year-old seedlings were flooded for the time indicated by dashed rectangles and O2concentration in the stem was recorded using implanted O2micro-optodes as described in Materialsand Methods. In ash and oak, two sensors were used each at the stem heights specified (see legends).The temperature course shown is that of the stem surface. Night periods from 22:00 to 07:00 h areshaded. For ash, the flooding height was reduced on day 7 from 15 to 5 cm. FL, flooding.

110 Results

●●

●

●

●

●

●

oxygen (7 cm)oxygen (17 cm)

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00

Day of experiment

020

4060

8010

0

Oxy

gen

(% a

ir sa

tura

tion)

● ●●

●●

●●

●

●


12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00

Day of experiment

020

4060

8010

0

Oxy

gen

(% a

ir sa

tura

tion)

●●

●●

●

●


5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00

Day of experiment

020

4060

8010

012

0

Oxy

gen

(% a

ir sa

tura

tion)

● ●● ●

●


5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00

Day of experiment

020

4060

8010

012

0

Oxy

gen

(% a

ir sa

tura

tion)

oxygen (8 cm)

10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Day of experiment

020

4060

8010

012

0

Oxy

gen

(% a

ir sa

tura

tion)

oxygen (8 cm)

10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Day of experiment

020

4060

8010

012

0

Oxy

gen

(% a

ir sa

tura

tion)

A1 A2

B1 B2

C1 C2

Figure 3.36: Responses of stem-internal O2 concentrations in ash (A1, A2), oak (B1, B2) and poplar(C1, C2) seedlings to flooding (left column) and reaeration (right column). Enlarged sections fromfig. 3.35. The flooding period is indicated by dashed lines. Sensor implantation heights are given in cmabove ground.


●

●

●

●

●

●

4 6 8 10 12 14 16

7075

8085

h

o2O

xyge

n (%

air

satu

ratio

n)

y == −0.79 x + 83.56 ; r2 == 0.7299

●

●

●

●

●

10 15 20 25

h76

7880

8284

86

Oxy

gen

(% a

ir sa

tura

tion)

y == 0.09 x + 79.71 ; r2 == 0.0238

Sensor implantation height (cm)

A B

Figure 3.37: Correlation between O2 concentration and sensor implantation height in ash (A) and oak(B). Data points represent average O2 concentrations before the flooding treatment on a per plantbasis (see tab. 3.6). Linear regression lines with corresponding regression equation and coefficient ofdetermination (r2) are shown. The results are of preliminary character, due to small n (6 for ash, 5 foroak).

112 Results

−10 0 10 20

−80

−60

−40

−20

020

Sensor distance from water surface (cm)

Cha

nge

in o

xyge

n co

ncen

trat

ion

(per

cent

age

poin

ts a

.s.)

●

●

●

●

●

●

●

●

●

●

●

●

●

●

AshOakPoplar

Figure 3.38: Change in O2 concentration in response to flooding vs. sensor distance from the wa-ter surface. Data represent the differences between average O2 concentrations before, and averageconcentrations during flooding on a per plant basis.


40

50

60

70

80

90

100O

xyge

n (%

air

satu

ratio

n)

FL

0

1

2

3

4

5

6

Sap

flow

(g

h−−1 s

tem

−−1 )

10

12

14

16

18

20

Air

tem

p. (

°C)

0 2 4 6 8 10

Day of experiment

A

B

C

12:00 14:00 16:00 18:00

4050

6070

8090

100

5:00 7:00 9:00 11:00

4050

6070

8090

100

A1 A2

Figure 3.39: Effect of flooding on stem-internal O2 (A) and sapflow (B) in oak. A three-year-old Q. roburseedling was flooded for the time indicated (dashed rectangle), and within-stem O2 as well as sapflowwere determined as described in Materials and Methods. The O2 concentration was measured ata height of 8 cm above ground, sapflow a few cm above this position. The flood height was 4 cmabove ground. A1, A2, enlarged views of the responses of O2 concentration to flooding and reaeration,respectively. C, temperature of the stem surface. See fig. 3.35 for further explanations.

114 Results

40

50

60

70

80

90

100

Oxy

gen

(% a

ir sa

tura

tion)

FL

0

5

10

15

20

25

Sap

flow

(g

h−−1 s

tem

−−1 )

10

12

14

16

18

20

Air

tem

p. (

°C)

0 2 4 6 8 10

Day of experiment

A

B

C

10:00 12:00 14:00 16:00

020

4060

8010

012

0

10:00 12:00 14:00 16:00

020

4060

8010

012

0

A1 A2

Figure 3.40: Effect of flooding on stem-internal O2 (A) and sapflow (B) in poplar. C, temperature of thestem surface. See fig. 3.39 for further explanations.


Day of experiment

AD

H a

ctiv

ity (

U g

−−1 F

W)

01

23

4

Ash Maple Oak Poplar

above water

Ash Maple Oak Poplar

below waterControlFlooded

A B

Figure 3.41: Effect of flooding on ADH activity in bark of ash, maple, oak and poplar seedlings. Three-year-old seedlings were subjected to a one-week flooding treatment and ADH activity was determinedin bark samples, as described in Materials and Methods. The bark samples were harvested from twostem positions: above the water (A) and below the water (B), or from comparable positions in the controltrees, respectively. Bars represent means (± SD) of four plants. None of the differences between theflooded and control groups were statistically significant as calculated by t tests (p < 0.05).

116 Results

Chapter 4

Discussion

Common ash (F. excelsior) is one of the most abundant species of the European hardwood

alluvial forest, a habitat that is characterised by regular inundation events. However, the

physiological response of common ash to submergence has received little attention. In

the present study, seedlings of common ash were subjected to various controlled flood-

ing treatments, and hence oxygen depletion of the soil, resembling duration and cycling

of natural flooding regimes. As known from numerous studies (reviewed in Kozlowski,

1997), C metabolism of plants is profoundly altered by oxygen depletion of the soil, which

is reflected by various physiological parameters such as photosynthesis rates and tissue

carbohydrate contents. A range of these sensitive parameters was included in the present

study.

From a fundamental point of view, any adverse effect on C metabolism does in the long

run also affect growth, since anabolic processes are impaired. In the ash investigated

seedlings of the provenances “Alb”, “BFor” and “Rhine”, height and diameter growth was

determined after a total of four weeks of flooding, interrupted by one week of reaeration

which was expected to additionally cause post-anoxic stress. Reduced growth as a result

of this treatment was anticipated, since it covered approx. 30 % of the growing season and

constituted a flooding period that occurs in exceptional years only in the hardwood alluvial

forest. However, neither height nor diameter growth were decreased by this treatment

(fig. 3.16), suggesting that the seedlings adapted well to inundation. Such a conclusion

was supported by other parameters (see below). By contrast, flooding ash seedlings for

the whole growing season (April–September) has been reported to significantly reduce

height growth and biomass increase (Frye and Grosse, 1992; Iremonger and Kelly, 1988).

In the provenance “Rhine”, flooding even led to a significantly increased growth in diam-

eter (fig. 3.16). This may indicate the development of stem hypertrophy, a morphological

118 Discussion

adaptation to flooding that enhances stem-internal aeration (Kawase, 1981), as also ob-

served for F. excelsior by Frye and Grosse (1992). Since this phenomenon was only

observed in the provenance “Rhine”, originating from an alluvial forest, and not in “Alb”

and “BFor”, it may indicate a provenance-specific adaptation to its habitat.

Despite unchanged growth and the development of morphological adaptations such as

hypertrophied lenticels (sec. 3.1.6.3), the seedlings’ vitality was clearly weakened by root-

zone oxygen depletion. Visible damage that became apparent after two times two weeks

of flooding interrupted by one week of reaeration, included chlorophyll degradation, leaf

wilting, reduced leaf number and inhibited formation of new leaves (figs. 3.25 and 3.17).

Similar stress symptoms have been described for many species in response to root hypoxia,

including relatively flood-tolerant species like Ulmus americana (Angeles et al., 1986) and

even Populus deltoides (Cao and Conner, 1999). 30 days of inundation were sufficient to

cause necrosis and leaf shed in the former, while 42 days of flooding resulted in reduced

leaf size, leaf area, leaf number and inhibition of formation of new leaves in the latter

species. In comparison, the degree of injury in common ash did not appear extraordinary,

in particular for “Rhine” and “BFor” (fig. 3.17). By contrast, the provenance “Alb”

was more heavily affected, being the only provenance that showed more than 50 % leaf

shed (fig. 3.17) and also significant chlorophyll loss (fig. 3.25). This provided additional

evidence of a different flood tolerance among the provenances. Chlorophyll degradation

has been connected to diminished Mg2+ uptake from the flooded soil (Talbot et al., 1987).

Leaf wilting has been linked to decreased water absorption by the roots (see Else et al.,

2001).

In addition to leaf damage, root injury was observed after prolonged inundation (fig. 3.19).

Decay of fine roots has mainly been associated with Phytophthora infestation, a hypoxia-

tolerant fungus (Kozlowski, 1997) whose zoospores can be attracted to roots by or-

ganic compounds including ethanol (Tyler, 2002), which can be exudated from flooded

roots. Moreover, root damage may have been aggravated by H2S formation in the soil

(cf. sec. 3.1.6.2), because sulphide is a potent root toxin (Mendelssohn et al., 1981; Koch

and Mendelssohn, 1989). The provenance “Alb” evidently suffered more damage than

“Rhine” or “BFor”, with the roots of this provenance often completely rotten (fig. 3.19).

This supports the conclusion about the differences in flood resistance between the prove-

nances analysed. However, on biomass (FW) basis, such a difference was not confirmed

(fig. 3.20).

Increased diameter growth of the provenance “Rhine” on the one hand, and marked

damage in “Alb” on the other hand, suggested that differences between provenances may

also be reflected by the physiological parameters studied.

4.1 Anaerobic root metabolism 119

4.1 Anaerobic root metabolism

As a measure for anaerobic metabolism of the root, the activity of the enzyme alcohol

dehydrogenase (ADH) was determined. ADH is involved in the biochemical pathway

of ethanolic fermentation which describes the anaerobic conversion of the glycolytic end

product pyruvate to ethanol. In hypoxic plant roots, ethanol is the main product of

pyruvate metabolism while other pathways such lactic fermentation have only minor sig-

nificance (Good and Muench, 1993). In agreement with this, ADH in the most intensely

studied enzyme of anaerobic metabolism (Kennedy et al., 1992).

In the ash seedlings studied, increased activities of ADH were observed as soon as 24 h

after initiation of the flooding treatment (fig. 3.12). This fast induction of the enzyme

indicates that the ash roots became rapidly hypoxic (Sachs et al., 1996; Subbaiah and

Sachs, 2003). The quick response is in agreement with studies for maize roots, which

showed ADH transcript synthesis within 6 h of hypoxia (Andrews et al., 1994a).

Prolonged flooding resulted in a further increase of enzyme activities, reaching values of

4–15 U g-1 FW (figs. 3.12, 3.30). These were comparable to other tree species under

hypoxia, such as flood-tolerant Nyssa sylvatica, Taxodium distichum and Populus spec.

(Pezeshki, 1991; Angelov et al., 1996; Hauberg, 2008) but also flood-intolerant Quercus

species (Angelov et al., 1996; Parelle et al., 2006). Surprisingly, however, ADH activities

remained on this high level even after one week of reaeration. This was in contrast to

rice (Xie and Wu, 1989), the coastal grass Spartina patens (Burdick and Mendelssohn,

1990) and also tree species such as T. distichum (Angelov et al., 1996), all showing a

return of activities to control levels within hours or few days. A retardation may be

caused by poor drainage of soil, however, this did not apply in the present case. Hence,

the maintenance of high activity levels over periods where oxygen is available may be of

ecophysiological significance. In alluvial forests, the fluctuating hydrology may produce

series of oxygen deprivation and availability (Anderson and Pezeshki, 2001). Maintaining

a high expression of anaerobic proteins (ANPs) over periods where oxygen is available

may have the advantage that (1) anaerobic metabolism could commence immediately,

eliminating shortages in energy metabolism, and (2) energy-consuming re-synthesis of

proteins is avoided. Biochemically, this response resembles the “hypoxic pretreatment”

effect, which describes the enhanced anoxic survival of roots after preceding hypoxic

incubation (Andrews et al., 1994a; Bouny and Saglio, 1996; Subbaiah and Sachs, 2003).

In these root tips, ADH activity under anoxia was considerably higher in hypoxically pre-

treated (HPT) tips than in anoxically shocked ones (Saglio et al., 1988; Johnson et al.,

1989). Similarly, ADH activities in flooded ash roots were in part considerably higher

during the second than during the first flooding period. In the provenance “Alb”, for

120 Discussion

instance, activities were almost twice as high as before (fig. 3.12). HPT root tips showed

an overall enhanced tolerance to anoxia, due to higher higher adenylate energy charge

and an enhanced regulation of cytoplasmic pH (Bouny and Saglio, 1996, and references

therein). It may be speculated that similar responses also allowed F. excelsior roots to

adapt to prolonged flooding. This is partly supported by the relatively mild effect of the

second 14-day flooding period on leaf gas exchange and carbohydrate levels which were

less, or not more affected than at the end of the first flooding period.

Absence of provenance-specific differences in ADH activity

Neither the initial increase in ADH activity in response to flooding nor the maintenance

of high activities under prolonged flooding differed significantly among the provenances of

F. excelsior (tab. 3.1) or between F. excelsior and F. angustifolia (fig. 3.30). Therefore,

ADH activity did not seem to be a marker for trees’ flooding tolerance. This is in agree-

ment with manifold ADH responses described in literature (Benz et al., 2007). Originally,

it was assumed that flood-sensitive species responded to hypoxia with higher ADH ac-

tivities than tolerant species (Crawford, 1967; McManmon and Crawford, 1971). Several

studies supported this relationship (Pezeshki, 1991; Naidoo and Naidoo, 1992; Baruch,

1994; De Simone et al., 2002). However, many authors came to the opposite conclusion

(Mendelssohn et al., 1981; Parelle et al., 2006; Keeley, 1979).

The discrepancy in the literature about the relationship between flood tolerance and ADH

activity seems to be, at least, partially due to different flooding durations considered.

Short-term flooding (several days) often causes similar increases in activities in both

flood-tolerant and sensitive species. However, after long-term flooding (several weeks),

the flood-tolerant species sometimes show decreasing activities which is not observed in the

intolerant species (Pezeshki, 1991; Naidoo and Naidoo, 1992; Baruch, 1994; De Simone

et al., 2002; Benz et al., 2007). This can be due to enhanced aeration of root system

by formation of aerenchyma (De Simone et al., 2002; Benz et al., 2007). This activity

pattern of many flood-tolerant species was not reflected by F. excelsior which showed

rather higher than lower activities with prolonged flooding (fig. 3.12). Differences in this

respect between “Alb”, “BFor” and “Rhine” were not suggested by the present findings.

Fate of ethanol

Despite high ADH activities, ethanol, the product of the reaction catalysed by ADH,

mostly remained below the detection limit in flooded ash roots (sec. 3.1.3.2). Low con-

centrations of ≈10 µg g-1 FW have also been reported for relatively flood-tolerant Quer-

4.1 Anaerobic root metabolism 121

cus robur seedlings, whereas ethanol levels increased to 75 µg g-1 FW in Fagus sylvatica

(Schmull and Thomas, 2000). In general, flood-tolerant species seem to avoid ethanol

accumulation in the roots, whereas flood-sensitive species sometimes accumulate this po-

tential cell toxin (Crawford, 1967; McManmon and Crawford, 1971; Monk et al., 1984).

Moreover, build-up of more toxic acetaldehyde after reaeration is prevented (Crawford

and Braendle, 1996). The present findings suggest that ash rates among ethanol-avoiding

species, which may be of particular importance with respect to regular reaeration in al-

luvial environments.

Since ethanol did not accumulate in the roots, it must have been transported to other

tissues or exudated into the water. The results indicated that ethanol, to some degree,

moved up the shoot with the transpiration stream (figs. 3.13B, 3.31B). The concentra-

tions in the xylem sap in some cases exceeded 2 mM (fig. 3.31B) but mostly remained

< 1 mM (fig. 3.13B). In comparison, much higher concentrations have been reported for

Populus deltoides (5 mM; MacDonald and Kimmerer, 1991) and Populus tremula × alba

(> 30 mM; Kreuzwieser et al., 2000). This indicates substantial differences in ethanol

utilisation between flood-tolerant poplar and F. excelsior . In previous studies with Pop-

ulus (MacDonald and Kimmerer, 1993; Kreuzwieser et al., 1999), it has been shown that

the majority of the shoot-transported ethanol (> 95 %) is recycled in leaf C metabolism,

a feature regarded as a flood tolerance mechanism in poplar (Kreuzwieser et al., 1999).

Common ash may lack this feature, suggesting less efficient carbon utilisation under hy-

poxia.

In agreement with its low acropetal transport rates, ethanol did not accumulate in the

leaves (figs. 3.13A, 3.31A), did not cause induction of leaf ADH over constitutive levels

(fig. 3.30A) and was emitted in only small amounts (<100 nmol m-2 min-1) as acetaldehyde

(fig. 3.14). By comparison, emission rates of 350 nmol m-2 min-1 have been reported for

poplar (Kreuzwieser et al., 2000). In agreement with Kimmerer and MacDonald (1987),

constitutive leaf ADH activity was likely sufficient to cope with ethanol arriving at the

leaves.

Interestingly, ethanol transport in the xylem ceased completely after reflooding despite

unchanged or even higher ADH activity (fig. 3.13). This suggested a shift of ethanol

utilisation with repeated flooding, possibly towards increased exudation. The latter has

been shown to be the major path of ethanol removal from the roots flood-tolerant Pi-

nus contarta, Nyssa sylvatica (Hook et al., 1983) and Lotus corniculatus (Barta, 1984).

In general, efficient ethanol exudation has been especially associated with flood-tolerant

species (Barta, 1984), avoiding self-poisoning (McManmon and Crawford, 1971). In-

creased ethanol exudation with repeated flooding may represent an adaptive response,

resembling a certain phenomenon in maize roots. These roots showed efficient efflux of

122 Discussion

lactic acid, another fermentative end product, after hypoxic pretreatment, but not when

anoxically shocked (Xia and Saglio, 1992).

4.2 Photosynthesis

In general, CO2 assimilation was increasingly affected with prolonged periods of flooding.

The critical flood duration to cause clear reductions in light-saturated assimilation (Amax)

appeared to be in the range of four to ten days (figs. 3.1, 3.23). Submergence for up to

three days did not significantly impact photosynthesis (fig. 3.23), or even caused 2 to 4-fold

increases in Amax in comparison with the normoxic controls, a response that coincided with

an up to 8.5-fold increased gs (fig. 3.1). Especially the latter finding was not expected, since

assimilation rates usually decrease within few hours or days of inundation, as reported

for numerous tree species (Gomes and Kozlowski, 1980; Dreyer et al., 1991; Gravatt and

Kirby, 1998; Anderson and Pezeshki, 1999). In highly flood-tolerant F. pennsylvanica,

for instance, stomatal conductance was reduced by 50–75 % within three days of flooding

(Gomes and Kozlowski, 1980; Tang and Kozlowski, 1984). Therefore, it is more likely that

the plants suffered from drought stress in the time before the flooding treatment. This

was implied by the very low gs of less than 10 mmol m-2 s-1 before flooding (fig. 3.1). Upon

supply of the flood water, the stomata may have re-opened, suggesting that the normal

watering frequency was not sufficient to fulfil the high water requirement of common ash

seedlings (Besnard and Carlier, 1990; Carlier et al., 1992).

Longer flooding periods of 10–14 days exacerbated the repression of CO2 assimilation in all

provenances studied. In the provenance “Rhine”, for example, Amax was reduced by 36 %

to 64 % (tab. 3.2). In general, leaf gas exchange is more affected by root-zone hypoxia in

flood-intolerant, than in tolerant species (Pezeshki et al., 1996; Anderson and Pezeshki,

1999). In good agreement with this assumption, leaf gas exchange was tendentially more

reduced in the provenance “Alb” than in “Rhine”. Whilst this difference was statistically

not significant, it is still consistent with the above findings for growth as well as leaf and

root damage, as is the observation that the provenance “BFor” was not more affected

than “Rhine” (tab. 3.2). Furthermore, F. angustifolia was the least affected species,

corresponding well to its reportedly higher flood tolerance in comparison with F. excelsior .

In comparison to other species, the response of leaf gas exchange of F. excelsior resembled

those of flood-tolerant rather than flood-sensitive species. Flood-tolerant species like

Fraxinus pennsylvanica and Quercus nigra, for example, showed reductions in assimilation

by 55–60 %, after comparable flooding periods as in the present study (Gravatt and Kirby,

1998). In Quercus lyrata, a more sensitive species, assimilation was reduced by 75 %

4.2 Photosynthesis 123

(Pezeshki et al., 1996), in moderately tolerant Acer rubrum by around 65 % (Anella and

Whitlow, 2000), but even in highly flood-tolerant Taxodium distichum, assimilation was

still reduced by 30 % after two weeks of submergence (Pezeshki et al., 1996). However, the

apparently low reduction of leaf gas exchange of ash in comparison to other species was

not supported by the findings for other species in the present study (figs. 3.32, 3.33). As

expected, 14-day flooding had no significant effect on the photosynthetic performance of S.

purpurea, the most flood-tolerant of the species tested, as indicated by unchanged light and

CO2 saturated assimilation rates (Amax light, Amax CO2), unchanged apparent quantum yield

(Aqe) and carboxylation efficiency (ε) as well as unchanged light (LCP) and CO2 (CCP)

compensation points (figs. 3.32 and 3.33). By contrast, F. excelsior showed strongly

decreased Amax light (−50 %) and even significantly decreased ε (−57 %). Unexpectedly,

T. cordata, a species described as only slightly tolerant to flooding (Glenz et al., 2006),

displayed less interference of flooding with photosynthesis than F. excelsior (figs. 3.32,

3.33). The reason for this difference between lime and ash remained unclear, and requires

further investigation. The tendentially higher flood tolerance of Q. robur compared to

F. excelsior , again, was in agreement with a previous study of the two species (Vreugdenhil

et al., 2006).

Responses to reaeration and reflooding

Studying the effects of reaeration and reflooding on photosynthesis is of great ecological

importance, since hydrology undergoes strong fluctuations in alluvial forests (cf. An-

derson and Pezeshki, 1999). Flood-tolerant species like F. pennsylvanica (Gomes and

Kozlowski, 1980) or Populus deltoides (Regehr et al., 1975) are capable of recovering

stomatal conductance to pre-flooding levels within 3–5 days after reaeration of the soil.

By contrast, moderately tolerant Q. robur showed no clear recovery within one week of

flooding (Dreyer et al., 1991), a phenomenon attributed to a lack of recovery of root hy-

draulic conductance (Davies and Flore, 1986). For common ash, whose flood tolerance

resembles that of Q. robur , similar results were expected. However, neither of the prove-

nances “Alb” and “Rhine” showed increasing Amax after the flooding treatment (fig. 3.1).

Surprisingly, the opposite was observed for “BFor” (fig. 3.1), which clearly contradicted

the initial hypothesis that the alluvial provenance (“Rhine”) is best adapted to flooding.

Given the absence of a clear recovery in “Alb” and “Rhine”, leaf gas exchange was ex-

pected to be increasingly affected by repeated flooding. However, three days after re-

flooding, gs increased over control levels, similar to the response during the first flooding

period. This suggested that the plants were still able to profit from the enhanced water

availability. Moreover, 14 days after reflooding, photosynthesis rates in “Alb” (70 % of

control), “Rhine” (107 %) and “BFor” (67 %) were even less affected than on day 14 of

124 Discussion

the first flooding period. This indicates a good adaptation of leaf gas exchange to pro-

longed flooding. It may be speculated that the first flooding period had a similar effect

as described by Anderson and Pezeshki (2001) for flood-tolerant bald cypress (Taxodium

distichum). Seedlings of this species, subjected to multiple, short flooding events, main-

tained higher levels of stomatal conductance during subsequent continuous flooding than

plants directly exposed to continuous flooding. This effect was termed “flood hardening”

following the terms for cold or drought hardening (Anderson and Pezeshki, 2001) and

may also be responsible for the present observations with ash seedlings.

Similarly, stomatal adaptation to continuous oxygen deprivation at the roots has been

described for other tolerant species such as F. pennsylvanica (Gomes and Kozlowski,

1980) and Populus deltoides (Regehr et al., 1975). These tree species exhibited initially

depressed gs, but stomata re-opened with prolonged flooding. It may be assumed that

F. excelsior behaved similarly, even though it did not develop adventitious roots, which

seemed to be required for stomatal reopening in F. pennsylvanica (Gomes and Kozlowski,

1980). Surprisingly, all provenances performed equally well during the second flooding

period. A stronger impact on “Alb”, as may have been anticipated after the previous

results, was not observed.

Marigo et al. (2000) described that F. excelsior exhibits generally little control over stom-

atal aperture, resulting in relatively high gs under severe drought stress. This stomatal

behaviour is typical of “tolerators” (as opposed to “avoiders”; Ludlow, 1989) and might

have contributed to the maintenance of relatively high gs under prolonged flooding. It

may retain high CO2 assimilation rates, even when water uptake is limited by decreased

hydraulic conductivity of the hypoxic root (Else et al., 2001; Tournaire-Roux et al., 2003).

Factors limiting assimilation

The mostly parallel course of Amax and gs (fig. 3.1) suggested that Amax was mainly limited

by stomatal conductance. However, a plot of Amax vs. gs revealed only low correlations

between the two parameters (fig. 3.3). Thus, non-stomatal factors such as (1) leaf chloro-

phyll degradation, (2) reduced Rubisco contents and/or activity, (3) decreased leaf water

potential and (4) disturbed photosynthate transport were most probably also involved

(see Pezeshki et al., 1996). Significant chlorophyll degradation by around 30 % was found

for “Alb” after 10 days of flooding, which might explain the particularly strong decrease

in Amax after this flooding duration (13 % of control; fig. 3.24). Decreased Rubisco activ-

ity can also be assumed, since soluble leaf protein levels were reduced by 35 % (“Alb”)

to 59 % (“Rhine”) and Rubisco constitutes up to 50 % of total soluble leaf protein (see

Larcher, 2001). This was supported by the lower saturation level of the light response

4.3 Carbohydrate metabolism 125

curve (fig. 3.32) and the significantly reduced apparent carboxylation efficiency (fig. 3.33)

(Larcher, 2001). Reduced leaf water potential (Ψl) was indicated by incipient wilting, in

particular for “Alb” (cf. section 3.1.6.1). Accumulation of photoassimilates in the leaves

was also observed and will be discussed below.

4.3 Carbohydrate metabolism

Plant carbohydrate metabolism is crucially determined by rates of photosynthetic carbon

assimilation (source) on the one hand, and carbohydrate consumption in sink tissues on

the other hand. The present results showed that carbon fixation was strongly depressed

by root-zone oxygen depletion, suggesting decreased amounts of carbohydrates available

for respiration, growth and reserve build-up. At the same time, strongly elevated root

ADH levels as in the ash seedlings investigated, may result in accelerated glycolytic flux

and thereby accelerated assimilate consumption (known as “Pasteur effect”; Drew, 1992).

Flooding was therefore expected to alter assimilate partitioning on the whole-plant level.

Root carbohydrate metabolism

In the roots, soil oxygen depletion for 10–14 days mainly caused accumulation of solu-

ble sugars, as well as in the other plant parts studied (fig. 4.1). Such increased soluble

carbohydrate levels in flooded roots may surprise since accelerated channelling of sug-

ars into glycolysis often results in depletion of respirable substrates (Drew, 1992; Saglio

and Pradet, 1980; Vartapetian and Jackson, 1997, see Introduction). For tree species,

decreasing carbohydrate contents in response to flooding have been reported for roots of

flood-tolerant Picea mariana and Larix laricina (Islam and Macdonald, 2004) as well as

of non-tolerant Fagus sylvatica (Kreuzwieser et al., 2004). Also, isolated (“excised”) root

tips of maize, as well as intact roots of wheat survived longer periods of anoxia when

the incubation medium was supplemented with glucose, suggesting that the supply of

carbohydrates was critical for survival (Drew, 1997).

The observed increase in soluble sugars contents in flooded ash roots may imply either

(1) increased sugar import from the phloem, (2) increased starch reserve mobilisation,

(3) globally reduced consumption rates (growth, respiration), (4) reduced export into the

xylem or any combination of these causes. Increased photoassimilate import from the

phloem seemed unlikely, due to strongly depressed net assimilation, as well as restricted

carbon export from leaves (see below) of flooded trees. Accelerated mobilisation of root

starch reserves was indicated for “Alb” and F. angustifolia by starch content reductions

126 Discussion

Assimilation: 80 %

BFor

Phloem:HexSuc 133 %Mann 154 %

Leaf:HexSuc 62 %Mann 71 %Starch n.d.

Root:HexSuc 223 %Mann 358 %Starch n.d.

Xylem:HexSuc 138 %Mann 122 %

Assimilation: 13-35 %

Alb

Phloem:HexSuc 201-721 %Mann 236-241 %

Leaf:HexSuc 63-170 %Mann 90-188 %Starch 215 %

Root:HexSuc 60-78 %Mann 215-232 %Starch 27 %


Assimilation: 62 %

F. angustifolia

Phloem:HexSuc 781 %Mann 209 %

Leaf:HexSuc 114 %Mann 83 %Starch 107 %

Root:HexSuc 222 %Mann 286 %Starch 27 %


Assimilation: 36-64 %

Rhine

Phloem:HexSuc 236-242 %Mann 210-241 %

Leaf:HexSuc 98-150 %Mann 93-163 %Starch 56 %

Root:HexSuc 111-178 %Mann 193-238 %Starch 284 %

Xylem:HexSuc 101-289 %Mann 86-238 %

Figure 4.1: Alteration of carbohydrate contents by flooding. 10–14 days of root-zone oxygen deple-tion resulted in depressed net assimilation rates, while carbohydrate contents in leaf and root, as wellphloem exudates and xylem sap remained unchanged or increased. HexSuc, hexose+sucrose contentof flooded plants, expressed as percent of normoxic controls; Mann, mannitol content of flooded plants,expressed as percent of normoxic controls. Data compiled from figs. 3.5, 3.7, 3.9, 3.11 and tab. 3.3.

by each 63 % (fig. 3.29). By contrast, the provenance “Rhine” showed an almost three-fold

increase in starch contents (fig. 3.29). This observation for both the most flood-sensitive

provenance of F. excelsior (“Alb”) and the flood-tolerant F. angustifolia indicated that


starch utilisation in flooded ash roots was not related to flood tolerance. This contradicts

findings for other tree species, which suggested more efficient starch utilisation under

hypoxia in flood-tolerant compared to non-tolerant species (Gravatt and Kirby, 1998;

Kreuzwieser et al., 2004).

Decreased substrate consumption may occur under circumstances of reduced resource

demand, e.g. with diminished growth rates. A well characterised effect of flooding is

the rapid inhibition of root elongation, as demonstrated for flood-sensitive economic

plants such as wheat (Huang et al., 1997) and potato (Biemelt et al., 1999), but also

for flood-tolerant trees, e.g. bald cypress (Taxodium distichum; Pezeshki, 1991). Reduc-

tion of energy-consuming processes in hypoxic roots, such as biosynthesis of proteins and

structural carbohydrates, have been demonstrated (Saglio and Pradet, 1980; Barta, 1987;

Kogawara et al., 2006) and interpreted as the cause for carbohydrate accumulation in

flooded roots of numerous different species (Albrecht et al., 1993; Albrecht and Biemelt,

1998; Biemelt et al., 1999; Schlueter and Crawford, 2001). Similarly, growth of flooded

F. excelsior roots may have slowed or ceased in oxygen-depleted soils, leading to reduced

substrate demand and thereby to the observed accumulation of soluble carbohydrates.

Decreased root growth was strongly suggested by fine root decay (sec. 3.1.6.2), therefore

supporting this hypothesis.

Highly increased ADH levels and simultaneously reduced carbohydrate consumption are

not necessarily contradictory, as demonstrated for maize (Andrews et al., 1994b), potato

(Biemelt et al., 1999) and wheat (Albrecht et al., 2004). These studies showed that high

expression and in vitro activity of fermentative enzymes are not automatically paralleled

by increased glycolytic fluxes, and that enzymes of glycolysis and ethanolic fermentation

are not induced in equal measures but differentially. Similarly, glycolytic sugar break-

down in flooded ash roots may have remained on a low level despite high in vitro ADH

activity. However, more detailed biochemical investigations are needed to substantiate

this assumption.

Since starch played an unclear role as reserve carbohydrate under flooding, other reserve

compounds may be more important for flooded ash roots. Such a role was indicated

for the sugar alcohol mannitol. Among the carbohydrates analysed, the concentrations

of mannitol increased the strongest under oxygen depletion, resulting in a significant

change in the composition of soluble carbohydrates in the roots. The ratio of mannitol

to combined hexose and sucrose contents changed markedly from 0.51 to 2.59 in the

provenance “Alb”, from 0.87 to 3.71 in “Rhine” and from 0.92 to 1.36 in F. angustifolia

(cf. tab. 3.3). This change suggested that mannitol utilisation differed clearly from that

of sucrose or hexoses in flooded ash roots.

A possible biochemical basis for such a differential regulation is suggested by insights into

128 Discussion

carbohydrate metabolism of other mannitol-synthesising species such as celery (Apium

graveolens). This agricultural plant shows a strong accumulation of mannitol as soon

as transferred to high salinity (Stoop and Pharr, 1994), an effect due to specific down-

regulation of mannitol dehydrogenase (MTD), the enzyme catalysing mannitol breakdown

(Stoop and Pharr, 1993; Pharr et al., 1995). Since MTD is repressed by high sugar

concentrations (Pharr et al., 1995), sucrose is preferentially metabolised under normal

conditions, leaving sufficient mannitol reserves for possible stress situations (Stoop et al.,

1996). This pays off advantageously for plants due to mannitol’s property as a compatible

solute, which allows for tissue adaptation to salt stress by osmotic adjustment (Stoop

et al., 1996). Due to this regulation, mannitol reserves are saved until sucrose reserves

become exhausted (Stoop et al., 1996). A preferential use of sucrose over mannitol may

explain why, in the present study, mannitol concentrations remained on a high level even

when sucrose contents were slightly reduced, as occasionally observed in the flooded ash

seedlings (e.g. after 10-day flooding in “Alb” and “Rhine”; tab. 3.3).

Mannitol’s osmotic properties may be important under flood stress, just as they are under

conditions of high salinity. Hypoxia causes drastically decreased hydraulic conductivity of

roots (Else et al., 2001; Tournaire-Roux et al., 2003). Roots accumulate other compatible

solutes (e.g. amino acids) not only under salt (Ogawa and Yamauchi, 2006) but also under

drought stress (Parker and Pallardy, 1988). Osmotic adjustment is a common adaptation

to these circumstances, preventing water loss from tissue by increasing the cellular con-

centrations of osmolytes. In addition, an important role of mannitol in this process has

been demonstrated in several drought stress studies with F. excelsior (Guicherd et al.,

1997; Patonnier et al., 1999; Peltier and Marigo, 1999; Oddo et al., 2002).

The observation that mannitol accumulated to a similar extent in all provenances of F. ex-

celsior indicated that this response was no particular feature of flood-adapted ecotypes.

This is in agreement with osmotic adjustment representing a general response to various

environmental stress types (salt stress, drought stress), rather than a specific adaptation

to a particular stress such as oxygen deprivation (cf. Stoop et al., 1996). It is therefore

not surprising that “Alb” and “BFor” showed similarly increased mannitol contents upon

flooding as “Rhine”.

Carbohydrate concentrations in the xylem sap

Flooding did not only cause increased carbohydrate contents within the root system,

but apparently also increased sugar export into the xylem sap. In the xylem sap of

flooded trees, up to 8× higher TSC concentrations were found in comparison to well-

drained plants (figs. 3.11, 3.28B). The general amount of carbohydrates in the xylem


sap (corresponding to C contents of approx. 50–200 mM; fig. 3.28B) was comparable to

findings for Quercus robur seedlings (50–500 mM C) (Heizmann et al., 2001). In oak, the

carbohydrate composition is dominated by sucrose (Heizmann et al., 2001), whereas the

high percentage of mannitol (70–86 % of TSC) seemed to be ash-specific. This high portion

of xylem mannitol is in accordance with previous reports for F. excelsior (Patonnier et al.,

1999).

The role of sugars in the xylem sap has received little attention in flood tolerance research

(cf. Kreuzwieser et al., 2004). Higher sugar concentrations increase the osmolality of the

xylem sap (Jackson et al., 1996). It is well-known that trees secrete sugars into the

xylem sap via the contact parenchyma under ambient conditions of limited transpiration

stream, e.g. high air humidity (see Sitte et al., 1991, p. 200). This secretion enhances

the osmotic force of the xylem sap and thereby facilitates acropetal water flow. Increased

osmolyte concentrations originating from flooded roots can enhance the xylem flux in

hypoxic tomato plants (Jackson et al., 1996). Thus, increased sugar concentrations in

the xylem sap of F. excelsior seedlings possibly contributed to the maintenance of a

high transpiration stream, counteracting decreased stomatal conductance (fig. 3.1), and

potentially decreased root hydraulic conductance.

Apart from osmotic properties, carbohydrate in the xylem sap may represent a significant

portion of the shoot’s C pool (Heizmann et al., 2001). In pedunculate oak (Quercus

robur), for example, 8–91 % of leaf C did not stem from photosynthesis but from xylem

delivery of carbohydrates (Heizmann et al., 2001). This percentage was highest when

photosynthesis was low, e.g. during midday depression of assimilation. According to

these authors, C from the transpiration stream may supply leaves with low CO2 fixation

rates with sufficient amounts of substrates for respiration. Similarly, ash leaves with low

CO2 fixation rates due to flood stress, may have been supplied with additional C from

the xylem sap.

The high portion of mannitol in the xylem sap of F. excelsior has led to the speculation

that mannitol may be involved in root-to-shoot signalling, exerting control over stomatal

aperture (Patonnier et al., 1999). However, such a function could, in contrast to malate,

another important xylary constituent in ash, not be substantiated (Patonnier et al., 1999).

Thus, mannitol in the xylem sap of flooded plants may contribute to whole-plant C cycling

similar to sucrose (Heizmann et al., 2001).

130 Discussion

Leaves

The described effect of inundation on carbohydrate levels in the roots was accompanied by

either unchanged (fig. 3.4) or increased (fig. 3.23A) carbohydrate contents in the leaves.

This accumulation is in agreement with the above hypothesis that the roots’ sink strength

was weakened by flooding. Accumulation of photoassimilates may reflect reduced phloem

translocation of leaf sugars to sink tissues (Wample and Davis, 1983; Gravatt and Kirby,

1998). This was indicated by different physiological responses concerning leaf carbohy-

drate contents on the one hand, and root growth on the other hand, among tree species of

different flood tolerance. In flood tolerant Nyssa aquatica, for example, the maintenance

of active root growth coincided with the maintenance of low leaf carbohydrate levels,

whereas flood-sensitive Quercus alba showed reduced root growth and a comparatively

stronger leaf carbohydrate accumulation (Gravatt and Kirby, 1998).

In the present study, reduced assimilate transport from source leaves to sinks was sup-

ported by the finding of 13C accumulation in 13C-glucose fed leaves (tab. 3.5). 13C-glucose,

fed into source leaves via secondary vein flaps (Biddulph and Markle, 1944), was assumed

to be incorporated into the cytoplasmic C pool and exported as 13C-sucrose (or other

translocated sugars). The detection of 13C label in phloem exudates (fig. 3.34) supported

this assumption. Hence, accumulation of 13C in the leaves indicated that leaf export of

photoassimilates was inhibited by root-zone inundation.

Unexpectedly, this inhibition of leaf export was most clearly seen in flood-tolerant poplar,

while in flood-sensitive Acer pseudoplatanus as well as in F. excelsior , export rates were

obviously less affected (tab. 3.5). This contradicted the assumption that phloem trans-

port is less affected in flood-tolerant as compared to sensitive species (Gravatt and Kirby,

1998). Moreover, the finding was in contrast to the results of Kogawara et al. (2006), who

observed a failure to export assimilates in a flood-sensitive species (Eucalyptus camaldu-

lensis) but not in tolerant Melaleuca cajuputi. Possibly, the unexpected finding for poplar

was due to species-specific differences in age or developmental stage of the leaves between

poplar on the one hand, and ash and maple on the other hand. This assumption is based

on the fact that leaf age determines whether leaves are net carbon sources or net sinks

(Turgeon, 2006). The transition of leaves from from sink to source status occurs when

they are about approximately half grown (Turgeon, 2006). Poplar had a high number of

relatively small leaves, which likely exported less assimilates than the large, mature leaves

of ash and maple. This was supported by the high amount of 13C label remaining in leaves

of well-drained poplar, compared to leaves of well-drained ash and maple (tab. 3.5).

In ash, additionally to reduced sink demand from the hypoxic roots, substrate consump-

tion in other parts of the plants was possibly also weakened. Formation of new leaves, for


example, a process claiming a considerable portion of seedlings’ resources (see e.g. Ko-

gawara et al., 2006), was clearly inhibited (fig. 3.17). By contrast, an effect of flooding

on height growth was not observed (fig. 3.16). Also, an effect of flooding on respiration

of source leaves was not detected, as indicated by unchanged dark respiration rates of

the leaves (fig. 3.33). If leaf growth or maintenance metabolism had been significantly

affected by root-zone inundation, decreased respiration rates due to overall reduced ATP

demand would have been a possible consequence.

Apart from the unexpected findings for leaf assimilate export in P. tremula × alba, the

differences in carbohydrate accumulation between the provenances of F. excelsior are

in agreement with the hypothesis that the maintenance of low leaf carbohydrate levels

is an indicator for flood tolerance (Vu and Yelenosky, 1991; Gravatt and Kirby, 1998).

The provenance “Alb”, at least under the test conditions of experiment II, showed the

strongest accumulation in leaf carbohydrates of the three provenances after 10 days of

flooding, while “Rhine” showed intermediate and F. angustifolia no accumulation of car-

bohydrates (fig. 3.27). In addition, a considerable increase in leaf starch was only detected

in “Alb” (fig. 3.29). Together, this suggested that phloem transport was most disturbed

in “Alb”, and to lesser degrees in “Rhine” and F. angustifolia, which is in accordance

with the assumed flood tolerance ranking “Alb” < “Rhine” < F. angustifolia. However,

this assertion was not matched by the observations for short-term (3-day) flooding, where

F. angustifolia showed an accumulation of carbohydrates that was similar to that of “Alb”

and “Rhine” (fig. 3.27). This unexpected effect of short-term flooding indicated that fac-

tors other than the described sink effects must play a role in leaf assimilate accumulation.

One of these factors might be increased sugar import from the xylem, as already pointed

out above.

As a consequence of increased leaf photoassimilate levels, photosynthesis may be depressed

through mechanisms of feedback inhibition (Paul and Foyer, 2001). The maintenance of

low leaf assimilate contents may therefore be an important prerequisite for continued

carbon assimilation at high rates. Increased levels of photoassimilates in the leaves of

the flooded ash plants may have contributed to diminished photosynthesis rates (figs. 3.1,

3.23; see above). For the same reason, the relatively low assimilate levels after 10 days

of flooding in F. angustifolia may have allowed this species to retain higher assimilation

rates than F. excelsior (fig. 3.23). This property of F. angustifolia possibly contributes

to its higher flood tolerance in comparison with F. excelsior .

132 Discussion

Phloem

In the phloem, carbohydrates assimilated in photosynthetically active source leaves are

translocated over long distances to heterotrophic tissues, such as roots and developing

leaves. In well-drained plants, CO2 fixation rates were high, and photoassimilates were

loaded into the phloem at normal rates. By contrast, decreased photoassimilate export

from leaves of flooded plants implied that phloem loading rates were reduced in comparison

to the normoxic controls. Surprisingly, phloem carbohydrate levels were found to be

strongly increased in response to root-zone inundation (figs. 3.8, 3.28B; fig. 4.1). Since

phloem carbohydrate concentrations are modulated by the rate of loading on the one

hand, and (1) unloading rates, (2) transport velocity and (3) consumption for growth as

well as respiration on the other hand (Giaquinta, 1983; Lalonde et al., 2003), this result

indicated that at least one of these factors was more affected by flooding than assimilate

export from leaves.

As pointed out above, sink strength of roots was assumed to be reduced by flooding. Rates

of unloading of phloem carbohydrates to roots may have therefore decreased. Symplastic

unloading of sucrose requires a high concentration gradient between phloem path and

roots tips, which is normally maintained by active root metabolism (Lalonde et al., 2003).

However, if root metabolism is decelerated by hypoxia, unloading may be significantly

affected (Barta, 1987). Moreover, the disturbance of unloading may be aggravated by

hypoxia-induced damage to cell structures such as plasmodesmata (Saglio, 1985).

As far as the translocation velocity is concerned, several studies indicated that this may

also be affected by flooding. In the flooded section of the stem, access to atmospheric

oxygen is eliminated by the surrounding flood water, resulting in increasingly hypoxic

conditions in the phloem (cf. Dongen et al., 2003). Under these conditions, translocation

of solutes in the phloem can be strongly inhibited, at least for temporary periods as

shown for squash (Cucurbita melopepo torticollis Bailey; Sij and Swanson, 1973), sugar

beet (Beta vulgaris ; Cataldo et al., 1972) and Ricinus (Dongen et al., 2003). Therefore,

in the present study, inhibition of sugar translocation by hypoxia may have occurred in

the flooded section of the stem which covered approx. its lower 15 cm. In agreement with

this, phloem translocation of 13C was obviously diminished as indicated by accumulation

of feeding-derived 13C in the upper stem segments of ash (fig. 3.34). As expected, this

effect was not ash-specific but also affected maple seedlings (fig. 3.34). The latter may

have been expected to exhibit more retarded 13C translocation than F. excelsior , due to

its higher sensitivity to flooding. However, such differences between species are probably

very small and, thus, were impossible to detect in the present study, given the large

fluctuation of 13C translocation among specimens (see fig. 3.34).


Unexpectedly, carbohydrate accumulation in the phloem did not differ clearly between

the F. excelsior provenances or F. angustifolia (fig. 4.1). This indicated that the de-

scribed effects of hypoxia on sink and phloem path did not substantially differ between

the ash provenances and species, despite varying flood tolerance. One might argue that

these differences in flood tolerance are gradual and are not reflected sensitively enough

by the parameters tested. However, this is in contrast to other studies (e.g. Kogawara

et al., 2006), which found substantially different patterns of assimilate translocation be-

tween flood-tolerant and sensitive tree species. Therefore, it is concluded that F. excelsior

provenances and F. angustifolia do only marginally differ in parameters related to C sup-

ply to flooded roots. This indicates that physiological aspects other than the investigated

ones may be more important for determining the different degrees of flood tolerance ob-

served (see “Future research”).

Carbohydrate metabolism — methodological considerations

Range of carbohydrate concentrations in phloem exudates In comparison to other

studies, the total concentration of sugars in the phloem exudates was relatively low. For

poplar and beech, for example, 2–3 times higher concentrations were found (Herschbach

et al., 2005; Geßler et al., 2004). This difference is likely due to the different composition

of sugars translocated in common ash. Members of the genus Fraxinus are known to

translocate oligosaccharides of the raffinose family (RFOs) which occur in similarly high

concentrations as mannitol and sucrose (Zimmermann, 1957; Trip et al., 1963). RFOs

were not included in the sugar analysis of the present study (cf. sec. 2.4.5.3). Therefore,

the total concentration of soluble carbohydrates might have been two to four times higher

than determined in the present study, explaining the difference to species like poplar and

beech.

Presence of reducing sugars in phloem exudates The presence of glucose in consid-

erable amounts (up to 15 % of TSC; fig. 3.8) was surprising, since reducing sugars are

usually not rated among the translocated sugars (Hall and Baker, 1972). Also, Zimmer-

mann (1957) did not find hexoses in the phloem sap of Fraxinus. Their presence might

be the result of invertase activity which, originating from injured adjacent cells of the

phloem (Giaquinta, 1983), degrades sucrose to glucose and fructose. Although invertase

activity was previously not found under the experimental conditions used (Bartels, 2001;

Schulte, 1998), reducing sugars in concentrations of up to 5 % of TSC were also detected

in phloem exudates of beech (Geßler et al., 2004). A recent publication pointed out that

translocation of hexose sugars may not be as unusual as previously thought (van Bel and

Hess, 2008).

134 Discussion

Diverging carbohydrate concentration ranges in experiments I and II Considerably dif-

ferences in carbohydrate concentrations measured in experiments I and II were observed.

These were not due to technical issues as re-examination by HPLC analysis confirmed

the differences. Thus, (1) the different age of the plants, three years in experiment I

and four years in experiment II, might have played a role, although this assumption is

not supported by other studies (Donaldson et al., 2006). (2) Seasonal variation might

explain a certain variation since experiment I began in mid-May, four weeks earlier than

experiment II (cf. Schaberg et al., 2000; Wong et al., 2003). (3) Different experimental

conditions might have had the largest impact. Poor light supply in experiment I possibly

resulted in reduced CO2 assimilation and thereby lower carbohydrate concentrations in

general.

Flap feeding of 13C-glucose Flap feeding, a technique introduced by Biddulph and

Markle (1944), has been used extensively in studies of metabolism and translocation

of isotopically labelled sugars (Trip et al., 1965; Trip and Gorham, 1968; Goldsmith et al.,

1974; Bieleski and Redgwell, 1985). As external application of sugars to the surface of

intact leaves (Nelson and Gorham, 1957) was not an option because sugar uptake through

the cuticle obviously does not work for ash leaves (Trip et al., 1965), 13C-glucose was fed

through a cut flap. Photosynthesis under a 13CO2 atmosphere, as used by (Kogawara

et al., 2006), for example, was a worthwhile, though technically sophisticated alternative.

Moreover, flap feeding and 14CO2 assimilation were shown to deliver comparable results

in terms of range, composition and translocation of labelled sugars (Trip et al., 1965).

13C-glucose, used in the present study to follow the fate of photoassimilates, was readily

taken up by the leaves. It was assumed that it was converted to sucrose (and/or other

translocated carbohydrates) and loaded into the sieve tubes. Experimental evidence for

the occurrence of these conversions came from a previous translocation study (Saglio,

1985, and references therein). The fact that F. excelsior does not only translocate su-

crose but also mannitol and RFOs, while both maple and poplar appear to translocate

mainly sucrose (Zimmermann, 1957), raised the question whether 13C-glucose might be

differently metabolised among the three species. Trip et al. (1965) showed that a large

numbers of sugars are interconverted within the leaf. In particular, 14C-fructose was

partly converted to 14C-mannitol as well as 14C-RFOs. Moreover, mannitol has been sug-

gested to be synthesised from the cytoplasmic triose-P pool (Rumpho and Kennedy, 1983;

Loescher, 1987; Loescher et al., 1992). Therefore, in F. excelsior , glucose conversion to

translocatable carbohydrates other than sucrose could be assumed.

4.4 Stem-internal O2 concentrations 135

4.4 Stem-internal O2 concentrations

Previous studies with different species showed that root anoxia caused decreased O2 con-

centrations in the stem (del Hierro et al., 2002; Gansert, 2003). Diminished aeration of

the stem may on the one hand become critical for energy metabolism of the sapwood,

with possible consequences for growth and vitality of the tree (see Gansert, 2003; Spicer

and Holbrook, 2005). On the other hand, O2 diffusion through the stem has been shown

to be an important characteristic of flood-tolerant species, as it allows for O2 supply to

the flooded roots and thereby for aerobic respiration in a hypoxic environment (Arm-

strong, 1968; Hook and Brown, 1972; Colmer, 2003). As shown in the present study,

ash roots flooded for prolonged periods retained high fermentation rates, suggesting low

root aeration and the absence of morphological adaptations enhancing root O2 supply.

Stem-internal O2 concentrations were therefore investigated in ash and compared to an

equally (Q. robur) and a more flood-tolerant (P. tremula × alba) species.

For O2 detection, the relatively modern technology of O2 micro-optodes (Holst et al.,

1997; Klimant et al., 1997) was deployed in the present study. This approach has been

successfully used in several stem O2 studies (Gansert et al., 2001; Gansert, 2003; del

Hierro et al., 2002; Dongen et al., 2003; Spicer and Holbrook, 2005; Sorz and Hietz, 2006).

Due to its sensitivity, the method permits a high spatial and temporal resolution. Unlike

Clark-type micro-electrodes with similar sensitivity (Aguilar et al., 2003), it does not

consume O2 during the measurement. The latter feature was an essential prerequisite

for the present study, because O2 determinations were carried out for up to 12 days at

identical measuring positions. With such long measurements, Clark-type electrodes may

have produced technical artefacts.

The relatively simple method of inserting the sensor into the stem (see Materials and

Methods, sec. 2.6) appeared appropriate, as indicated by short adaptation (figs. 2.12) and

response times upon environmental changes (fig. 3.36). Technically similar approaches

have been applied by Spicer and Holbrook (2005) and Mancuso and Marras (2003).

Range of O2 concentrations

O2 concentrations in unflooded stems amounted to 70–95 % air saturation (a.s.). This

was comparable to ranges for seedlings of 5-year-old Betula pubescens (Gansert, 2003)

and 7-year-old Laurus nobilis (del Hierro et al., 2002). Considerably lower values (9–

35 % a.s.), however, were found in 4-year-old Olea europea trees (Mancuso and Marras,

2003). In adult trees, stem-internal O2 varies between concentrations of 9 % a.s. to 100 %

136 Discussion

a.s. (Eklund, 1990, 1993, 2000; Gansert et al., 2001; del Hierro et al., 2002; Spicer and

Holbrook, 2005) and is strongly influenced by seasonal fluctuations. In Quercus robur

and Acer platanoides, for instance, summer O2 concentrations (25–30 % a.s.) were two to

three times lower than concentrations in spring or autumn (75–80 % a.s.), likely due to

more intense sapwood metabolism (Eklund, 1993).

Effect of flooding on stem-internal O2 concentrations

Root submergence resulted in decreased stem O2 concentrations in ash and maple, but

not in poplar (fig. 3.35, tab. 3.6). In the literature, only few studies have investigated

the influence of root anoxia on stem O2 concentrations. For example, Betula pubescens

saplings showed a reduction in sapwood O2 concentrations from ≈80 to ≈30 % a.s. in

response to root-zone oxygen depletion (Gansert, 2003). Similarly, del Hierro et al. (2002)

managed to manipulate stem-internal O2 concentrations in Laurus nobilis by varying soil

water contents, with concentrations ≈20 % lower at high soil moisture. Whilst similar

reductions were found for ash and oak seedlings in the present study, the results are

difficult to compare, due to different age of specimens and different experimental setups.

Several studies provided evidence that stem-internal O2 concentrations are closely corre-

lated with sapflow velocity (Eklund, 1990, 1993; Eklund and Lavigne, 1995; Eklund, 2000;

Gansert et al., 2001; Gansert, 2003; Mancuso and Marras, 2003). Flooding is known to

reduce sapflow rates, due to diminished transpiration and root water uptake (Else et al.,

1996, 2001; Tournaire-Roux et al., 2003). In addition, the water in flooded soils contains

considerably less O2 than in aerated soils (Spicer and Holbrook, 2005).

Thus, the reduced O2 concentrations in ash and oak may be explained by less intense

O2 supply with the sapstream. Nevertheless, several observations indicated that the

influence of sapflow was limited. (1) The diurnal O2 concentration patterns of all plants

exhibited lower concentrations at day and higher ones at night (fig. 3.35). If xylem sap

was the dominant source of O2, one would expect the opposite, as indeed observed by

del Hierro et al. (2002) and Mancuso and Marras (2003). (2) O2 levels in the xylem

sap decrease with increasing stem height due to the passage through respiring sapwood

(Eklund, 2000). Such a correlation was very weak in ash and absent in oak (fig. 3.37),

although more experiments on this subject are necessary. (3) Sapflow, as determined with

the heat-balance method, showed no clear correlation with O2 concentrations in oak and

poplar (figs. 3.39, 3.40). (4) O2 concentrations in the flooded portion of the stem were

substantially more decreased than in the stem section above the water surface (fig. 3.35A,

tab. 3.6). If O2 was mainly delivered by the sapstream, then the drop in the lower stem

should not be higher than in the upper stem. Thus, the difference between the two stem

4.4 Stem-internal O2 concentrations 137

positions can only be explained with a significant radial O2 influx from the atmosphere.

Given such a strong influence of radial O2 diffusion, how can the impact of soil flooding

on O2 concentrations in the upper, unflooded stem sections be explained? (1) Xylem sap

passing through the flooded stem could be increasingly depleted in O2 due to consumption

by the wood parenchyma. Since there is no O2 diffusion from the atmosphere, all O2

requirements in this section must be served by the xylem sap. (2) The strong reduction

in the flooded stem portion might pose a sink for O2, causing O2 to diffuse from locations

of high concentrations (unflooded stem) to those of low concentrations (flooded stem).

Such basipetal O2 diffusion has been demonstrated for various wetland species (Hook and

Scholtens, 1978; Armstrong, 1968; Philipson and Coutts, 1978).

A problem with radial O2 diffusion from the atmosphere is that it requires a low radial

barrier to gas flow (Sorz and Hietz, 2006). Resistance to lateral diffusion is imposed by

bark, cambium and wood (Hook and Brown, 1972; Sorz and Hietz, 2006). In particular,

a porous vascular cambium seems to be a important prerequisite for radial gas diffusion

(Hook and Brown, 1972). However, cambium pores in significant numbers and sizes

are only found in wetland tree species like Nyssa aquatica and F. pennsylvanica (Hook

and Brown, 1972). By contrast, mesophytes do not permit free gas exchange across

the vascular cambium (Hook and Brown, 1972). This view of a relatively impermeable

cambium was supported by later works (Eklund, 2000; del Hierro et al., 2002; Gansert

et al., 2001; Gansert, 2003). Thus, intense O2 exchange with the atmosphere is surprising

for ash and maple. Possibly, morphological features like lenticels (sec. 3.1.6.3) facilitated

gas exchange (Hook et al., 1971; Grosse et al., 1992). Also, relatively rough bark like the

one of oak can decrease the resistance to lateral gas interchange (Sorz and Hietz, 2006).

A relatively free radial gas exchange allows for stem-internal aeration and thereby O2 sup-

ply to flooded roots (Armstrong, 1968; Philipson and Coutts, 1978). Good and Patrick

(1987) found that flood-tolerant F. pennsylvanica maintained higher root O2 and lower

CO2 concentrations than sensitive Quercus nigra. In contrast to F. pennsylvanica, F. ex-

celsior may not be able transport significant amounts of O2 to the roots, given the low O2

concentrations in the flooded stem measured in the present study (10–20 % a.s.). Such

a difference between F. pennsylvanica and F. excelsior may contribute to their widely

diverging flood tolerance.

Moreover, the increasing O2 concentrations in poplar (fig. 3.35C) may suggest enhanced

aeration of the stem in response to inundation. This may be due to incipient aerenchyma

formation in stem and root neck. In maize roots, aerenchyma formation was observed

within 2.5 days of hypoxia (Gunawardena et al., 2001), which is comparable to the time

point where O2 concentrations began to rise in poplar. More evidence, that such anatom-

ical adaptations can occur after short periods of time, were provided by own experiments

138 Discussion

with flood-tolerant Salix purpurea. This species formed adventitious roots, which often oc-

cur simultaneously with aerenchyma development (Armstrong et al., 1994), was observed

within 2–3 days of flooding. Increasing O2 levels were also observed for oak, possibly

indicating similar anatomical changes (fig. 3.35B). In contrast, the findings for ash did

not suggest enhanced stem aeration.

In the field, adult ash trees often show marked injuries to bark and cambium after pro-

longed flooding periods (FOWARA, 2006). These injuries include bark lesions of a length

of several centimetres, which may increase the risk of Phytophthora and other fungal in-

festations (Jung and Blaschke, 2004). Parts of the vascular cambium in these trees show

dieback, as indicated by black spots on stem cross sections in the particular year ring

(FOWARA, 2006). It may be speculated that such damage to the cambium is induced by

oxygen deficiency in the bark. However, anaerobic metabolism in the bark did not seem to

be affected by flooding, as indicated by unchanged ADH activities in both the unflooded

and flooded sections of the stem (fig. 3.41). ADH exhibited high activities of up to 3.3

U g-1 FW under normoxia, and high constitutive levels of anaerobic metabolism have also

been reported for the vascular cambium of Populus deltoides (Kimmerer and Stringer,

1988), as well as for the phloem of Ricinus (Dongen et al., 2003). These ADH levels may

have been sufficient to cope with diminished O2 availability under flooding. However, the

strong reduction of stem-internal O2 in the flooded stem section of ash indicated, that

cambium vitality may be severely affected with prolonged flooding periods.

4.5 Conclusions

Flood tolerance strategy of common ash

True wetland species develop morphological and anatomical adaptations to flooding, such

as hypertrophied lenticels, aerenchyma and adventitious roots, which enable them to

sustain growth under conditions of prolonged or permanent flooding (Crawford, 1967;

Naidoo et al., 1992; Vartapetian et al., 2003; Benz et al., 2007). By contrast, moderately

flood-tolerant species often rely on metabolic rather than morphological features that

provide a certain, though smaller degree of hypoxia tolerance. The ash seedlings studied

showed development of hypertrophied lenticels, and possibly stem hypertrophy in case of

the “Rhine” provenance, however, adventitious roots formed relatively late and only in

small numbers. Hence, for the tolerance strategy of common ash, metabolic adaptations

may be more important. One of these metabolic adaptations was possibly represented by

the accumulation of mannitol. A strategy of tolerance rather than avoidance (Ludlow,

1989; Vartapetian et al., 2003) appears plausible, considering corresponding reports for

4.5 Conclusions 139

the response of common ash to drought stress (Guicherd et al., 1997; Oddo et al., 2002;

Patonnier et al., 1999; Marigo et al., 2000).

Intraspecific variation of flood tolerance?

Three provenances of F. excelsior were analysed, in order to test the hypothesis that flood

resistance is higher in riparian populations than in trees originating from mountainous

areas. The impact of flooding on leaf gas exchange was stronger on plants originating

from the Swabian Jura (“Alb”) than on plants of the alluvial provenance “Rhine”, as

were chlorophyll loss, leaf shed and other visible injuries. Thus, when only comparing

“Alb” and “Rhine”, one could conclude that “Rhine” represents a flood-adapted ecotype.

However, results for the second mountainous provenance, “BFor”, restricted this con-

clusion since none of the parameters tested indicated a higher sensitivity in comparison

with “Rhine”. This is consistent with the findings of Weiser (1995) who described similar

long-term growth for two alluvial and two mountainous populations of F. excelsior , in-

dependent of the soil moisture regime tested. In Weiser’s study, the observed differences

in growth tended to be larger within alluvial and mountainous provenances, respectively,

than between these opposite provenance areas. Similarly, the flood tolerance of the prove-

nances tested in the present work may differ in a manner that is unrelated to the flood

frequency of the seed source area.

The results are in contrast to studies with other species, in which clearer evidence for ge-

netic adaptation to flooding was found. Distinct “flooding ecotypes” were demonstrated,

amongst others, for Nyssa sylvatica (Keeley, 1979), Acer rubrum (Anella and Whitlow,

2000) and Piriqueta caroliniana (Benz et al., 2007). However, in agreement with the

current results is a recent study on the genetic diversity of alluvial and non-alluvial pop-

ulations, which found no indications for the occurrence of genetic adaption to flooding in

common ash provenances (Dacasa-Rudinger et al., 2008). Therefore, the large ecological

amplitude of common ash (Marigo et al., 2000) may be ascribed to phenotypic plastic-

ity rather than genetic differentiation. However, such a conclusion must be validated by

investigating a larger number of ash provenances.

Consequences for cultivation of ash on flood-prone sites

Ash has become an important forestry tree in Europe (Pliura, 1999) due to its valu-

able timber (Hane, 2001) and easy establishment (Kerr and Cahalan, 2004). Ongoing

restoration of alluvial forests, and establishment of new forested water retention basins

(FOWARA, 2006; IRP, 2007), imply an increasing demand for flood-tolerant as well as eco-

140 Discussion

nomically profitable species. On the basis of the present knowledge (Siebel and Bouwma,

1998; Frye and Grosse, 1992; Iremonger and Kelly, 1988) and natural abundance of com-

mon ash in European hardwood alluvial forests (Volk, 2002), this species seems suitable

for forestry on flood-prone sites, as long as stagnant flooding is avoided (FOWARA, 2006).

The findings of this study support the view of common ash as a moderately flood-tolerant

tree species, and therefore do not argue against increased silvicultural use of common ash

on flood-prone sites.

A potentially crucial aspect of forest management is the choice of the right provenance

or ecotype for a given site. Current guidelines recommend ash from the upper Rhine

valley (provenance area 81105) for the cultivation in floodplain areas (FVA, 2004), based

on the concept of “near-natural” forest management. In this concept, local adaptedness

and preservation of genetic diversity are major goals. Although a specific adaptedness to

flooding of the “Rhine” provenance was relativised by the findings for “BFor”, the results

for “Alb” indicated that less flood-resistant ecotypes of F. excelsior exist, and must be

taken into consideration. Therefore, field studies with different ash provenances should

clarify which one is particularly suited for the site conditions (soil type, flooding frequency

etc.) of interest.

Moreover, measures of “flood-hardening” (Anderson and Pezeshki, 2001) may be taken

into consideration for enhancing the response of common ash seedlings to flooding. These

could be carried out in the form of control floodings which allow seedlings to stepwise

adapt to typical inundation regimes of a site. First experiences with “ecological floodings”

suggest that this practice may be a worthwhile strategy for enhancing success of forest

management in forested water retention areas (FOWARA, 2006).

Future research

Future investigations in F. excelsior should focus on the mechanisms that conveys flood

tolerance to this tree species. The present findings indicate that osmotic adjustment plays

a prominent role in the tolerance strategy of F. excelsior . Besides investigations of com-

patible solutes other than mannitol, e.g. malate (see Peltier et al., 1997; Patonnier et al.,

1999), a molecular characterisation of mannitol dehydrogenase (MTD) (Stoop and Pharr,

1993; Pharr et al., 1995), for example, could clarify if and how mannitol accumulation is

regulated. Similarly, cellular mannitol transporters could be studied, whose expression

seems to be an important determinant of mannitol contents (Conde et al., 2007).

Relatively clear differences between “Alb” and the other provenances were observed re-

garding visible flood injuries which, however, were not paralleled by correspondingly large

4.5 Conclusions 141

changes in the C metabolic parameters studied. Therefore, metabolic aspects apart from

C metabolism should receive more attention. For instance, nitrogen uptake (Kreuzwieser

et al., 2002), amino acid metabolism (Reggiani et al., 1988), sulphur nutrition (Herschbach

et al., 2005) or phosphate acquisition/allocation (Topa and Cheeseman, 1992) were all

shown to vary greatly among flood-tolerant and sensitive species. Consideration of these

parameters in future studies may help to reveal the metabolic basis for the diverging flood

tolerance among F. excelsior provenances.

Large provenance-specific differences in flood tolerance can also be caused by morpho-

logical differences. Benz et al. (2007), for instance, found that constitutive as well as

hypoxia-induced aerenchyma formation differed widely among genotypes of a single species

(Piriqueta caroliniana, Turneraceae). Therefore, morphological aspects should also be re-

garded more closely in future studies on flood tolerance of the genus Fraxinus.

142 Discussion

Summary

Common ash (Fraxinus excelsior L.), an autochthonous and abundant representative of

the Oleacea family of plants in Central Europe, is a characteristic member of the hard-

wood alluvial forest and, as such, exposed to moderate, but repeated inundation. Growth

and survival studies indicated an adaptation to oxygen deficits in compliance with this

habitat, whose physiological basis, however, has received little attention. Aim of the

present work was to characterise the flooding tolerance of common ash with respect to

central parameters of carbon metabolism. For this purpose, three-year-old ash seedlings

were exposed to controlled flooding treatments of 1–28 days. Photosynthesis, carbohy-

drate contents and parameters of anaerobic root metabolism were determined. Growth

parameters, as well as flood-induced leaf injuries were also acquired. Plants of three prove-

nances — Rhine floodplain, Swabian Jura, Black Forest — were compared in order to test

if regular flooding of the alluvial forest has resulted in the evolution of a flood-tolerant

ecotype. In addition, more detailed studies were carried out to compare common ash’s

photosynthetic performance and assimilate transport under hypoxia with that of other

tree species of lower and higher flooding tolerance.

These investigations yielded the following key results:

1. Biometric parameters and visible flood damage:

Neither height growth nor biomass development of the seedlings were affected by

the longest flooding treatment of a total of four weeks tested. However, partial leaf

shed occurred after 10–14 days of flooding, often extending into complete defoliation

with prolonged flooding. Formation of new leaves was inhibited. The provenance

from the Swabian Jura (“Alb”) suffered appreciably more damage than provenances

“Rhine” and Black Forest (“BFor”).

2. Photosynthesis:

While short-term (3 d) flooding did not influence photosynthesis rates, typical

hypoxia-related stress symptoms were indeed observed after 10–14 days of inunda-

tion. Light-saturated assimilation rates (Amax) dropped to values of between 80 %

144 Summary

and 30 % of normoxic controls, depending on provenance. “Alb” tendentially showed

the largest reduction of the three provenances whereas “BFor” was even slightly less

affected than “Rhine”. In seedlings of narrow-leaved ash (F. angustifolia L.) investi-

gated in parallel to F. excelsior , flooding produced the least effects, supporting the

reportedly higher flood tolerance of this species in comparison with F. excelsior . Re-

duction of Amax was obviously due to partial stomatal closure, however non-stomatal

factors such as reduced leaf chlorophyll contents (e.g. decreased by 33 % in “Alb”)

and reduced leaf protein contents (e.g. decreased by 59 % in “Rhine”) also played

a role. Reduced leaf protein contents suggested reduced amounts of Rubisco. Such

a conclusion was supported by the analysis of light and CO2 response curves of

photosynthesis, which, apart from ash, were recorded for oak (Quercus robur L.),

lime (Tilia cordata Mill.) and willow (Salix purpurea L.). After 14 days of flooding,

results for ash indicated 50 % and 57 % reductions in light-saturated assimilation

(Amax light) and apparent carboxylation efficiency (ε), respectively. In comparison

with ash, the other investigated species were less affected regarding the different

parameters. This was expected in the case of moderately flood-tolerant oak and

highly tolerant willow, but contradicted expectations in the case of flood-sensitive

lime.

3. Anaerobic root metabolism:

Increased activities of the enzyme alcohol dehydrogenase (ADH) were detected as

soon as 24 h after flooding, indicating a rapid switch of root metabolism from

aerobic to anaerobic pathways. With prolonged inundation, specific ADH activities

raised further to 3–13 U g-1 FW, corresponding to 4 to 25-fold normoxic levels.

Surprisingly, ADH activities remained unchangedly high even after one week of

reaeration, possibly indicating a specific adaptation to the periodic flooding regimes

of alluvial forests. Ethanol, end product of alcoholic fermentation and potential

cell toxin, did not accumulate in root tissue, which is typical of many flood-tolerant

species. Since its concentrations also remained low in the transpiration stream (max.

3.5 mM), ethanol was obviously hardly fed into metabolic recycling in the shoot, but

predominantly exudated into the surrounding medium. This trend was reinforced

upon reaeration and subsequent reflooding.

Despite high fermentation activities, substrate depletion as a consequence of a possi-

ble Pasteur effect did not occur. On the contrary, flooded roots showed tendentially

increased carbohydrate contents, indicating substantially metabolic activity, e.g. as

a consequence of diminshed growth. This was in agreement with the observed decay

of fine roots after prolonged hypoxia. There was no clear relationship between ADH

activity or root carbohydrate contents on the one hand, and flooding tolerance of

the investigated F. excelsior provenances and F. angustifolia on the other hand,

Summary 145

indicating that fermentative root metabolism did not substantially influence flood

resistance.

4. Translocation of photoassimilates:

Distinctly (1.5 to 2-fold) increased contents of soluble leaf sugars in ash seedlings

indicated reduced assimilate export from leaves. This conclusion was supported by

accumulation of 13C after feeding of 13C-glucose into the leaf. Moreover, phloem

sucrose contents increased 2 to 10-fold, suggesting that phloem unloading and/or

transport velocity were affected to a larger extent by flooding than phloem load-

ing. Regarding leaf sugar export, flood-sensitive maple (Acer pseudoplatanus L.)

behaved similar to ash, whereas flood-tolerant poplar (Populus tremula L.) surpris-

ingly exhibited complete inhibition as assimilate export.

5. Accumulation of mannitol:

In leaf and root tissue, as well as phloem exudates and xylem sap of flooded plants,

strongly (up to 8-fold) increased contents of the sugar alcohol mannitol were de-

tected. As mannitol in common ash is involved in osmotic adjustment of tissues

to decreased water contents, e.g. under drought stress, it may also have this func-

tion during flooding. Such a physiological role was supported by the finding that

mannitol contents in the roots increased stronger than soluble sugars, indicating

differential carbohydrate consumption.

6. Stem-internal oxygen concentrations:

Due to the high sensitivity of C metabolism for changes in O2 availability, deter-

minations of stem-internal O2 concentrations were carried out in addition to the

aforementioned investigations. In response to root flooding, O2 concentrations in

the stem ash seedlings dropped markedly from averagely 71 % air saturation (a.s.)

to 48 % a.s. Similar reductions were observed for oak (Quercus robur). In the

flooded stem section of ash, concentrations decreased unequally stronger to 13 %

a.s., indicating an important role of radial gas diffusion for stem aeration on the

one hand, and considerably hypoxic conditions in the stem base of ash on the other

hand. In contrast to ash and oak, stem-internal O2 concentrations in poplar were

not influenced by flooding.

To sum up, the “Rhine” provenance expectably proved to be more flood-tolerant than

the provenance “Alb”. By contrast, the relatively mild impact of flooding on “BFor” in

comparison with “Alb” was surprising and possibly due to different soil moisture regimes

of the two mountainous provenance areas. The present results indicated that selection

of suitable provenances may decisively influence the success of ash cultivation in, e.g.,

restoration of alluvial forests or afforestation of water retention basins.

German Summary

Die Gemeine Esche (Fraxinus excelsior L.), ein in Mitteleuropa autochthoner und weit

verbreiteter Vertreter der Olbaumgewachse (Oleaceae), ist ein charakteristisches Mit-

glied der Hartholzaue und somit moderaten, aber regelmaßigen Uberflutungen ausge-

setzt. Wachstums- und Uberlebensstudien zeigten eine diesem Habitat entsprechende

Anpassung an Sauerstoffmangel, deren physiologische Grundlage bislang jedoch kaum

untersucht wurde. Ziel der vorliegenden Arbeit war es, die Uberflutungstoleranz der

Gemeinen Esche im Hinblick auf zentrale Parameter des Kohlenstoffhaushalts zu charak-

terisieren. Dazu wurden dreijahrige Eschensamlinge kontrollierten Uberflutungen von 1–

28 Tagen ausgesetzt und Bestimmungen von Photosyntheseraten, Kohlenhydratgehalten

und Parametern des anaeroben Wurzelmetabolismus unterworfen. Ebenso wurden Wach-

stumsparameter und durch Uberflutung verursachte Blattschaden erfasst. Pflanzen dreier

Herkunfte — Rheinaue, Schwabische Alb und Schwarzwald — wurden verglichen, um

die Hypothese zu uberprufen, ob regelmaßige Uberflutungen des Auenwalds zur Aus-

bildung eines uberflutungstoleranten Okotypen gefuhrt haben. In vertiefenden Unter-

suchungen wurden außerdem Photosyntheseleistung und Assimilattransport der Esche

unter Uberflutungsbedingungen mit denen anderer Arten von geringerer und hoherer

Uberflutungstoleranz verglichen.

Diese Untersuchungen fuhrten zu den folgenden Schlusselergebnissen:

1. Biometrische Parameter und sichtbare Uberflutungsschaden:

Auch nach der langsten Uberflutungsbehandlung von insgesamt vier Wochen waren

weder Hohen- und Dickenwachstum, noch Biomasseentwicklung der Samlinge beein-

trachtigt. Allerdings traten nach 10–14 Tagen erster, mit fortschreitender Uberflut-

ung teilweise auch vollstandiger Blattabwurf auf. Die Bildung neuer Blatter war

verringert. Von diesen Schaden war die Herkunft “Alb” eindeutig starker betroffen

als “Rhein” und “Schwarzwald”.

2. Photosynthese:

Wahrend bei kurzzeitiger (3 d) Uberflutung keine Reduktion der Photosyntheser-

148 German Summary

aten zu beobachten war, traten nach 10 bis 14 Tagen typische, hypoxiebedingte

Stresssymptome auf. Die lichtgesattigte Assimilationsrate (Amax) sank je nach Her-

kunft auf Werte zwischen 80 % und 13 % der normoxischen Kontrollpflanzen. Die

Provenienz “Alb” wies tendenziell die großte Reduktion der drei Herkunfte auf,

wahrend “Schwarzwald” sogar etwas weniger betroffen war als “Rhein”. Bei paral-

lel untersuchten Samlingen der Schmalblattrigen Esche (F. angustifolia L.) zeigten

sich die geringsten Effekte, was gut mit der hoheren Uberflutungstoleranz dieser

Art ubereinstimmte. Die Verringerung von Amax war offenbar auf partiellen Stom-

ataschluss zuruckzufuhren, allerdings spielten auch nicht-stomatare Faktoren wie

verringerter Blattchlorophyllgehalt (z.B. in “Alb” um 33 % reduziert) und Blattpro-

teingehalt (z.B. in “Rhein” um 59 % reduziert) eine Rolle, wobei letzterer vermut-

lich mit verringerten Mengen des Enzyms Rubisco einherging. Einen solchen Schluss

legte auch die Analyse von Licht- und CO2-Response-Kurven der Photosynthese na-

he, die außer fur Esche auch fur Eiche (Quercus robur L.), Linde (Tilia cordata Mill.)

und Weide (Salix purpurea L.) aufgenommen wurden. Nach 14 Tagen Uberflutung

zeigte sich bei der Esche ein um 50 % reduziertes Lichtsattigungsniveau der Assimila-

tion (Amax light) sowie eine um 57 % verringerte apparente Carboxylierungseffizienz

(ε). Im Vergleich zur Esche zeigten die anderen untersuchten Arten eine deutlich

geringere Beeintrachtigung der verschiedenen Parameter, was den Erwartungen im

Falle der moderat bzw. sehr toleranten Eiche und Weide entsprach, im Falle der als

uberflutungssensitiv beschriebenen Linde aber uberraschte.

3. Anaerober Wurzelstoffwechsel:

Erhohte Aktivitaten des Enzyms Alkoholdehydrogenase (ADH) waren bereits 24 h

nach Uberflutungsbeginn detektierbar, was auf ein rasches Umschalten von aerobe

auf anaerobe Stoffwechselwege schließen ließ. Mit zunehmender Uberflutungsdauer

steigerte sich die spezifische ADH-Aktivitat auf 3–13 U g-1 FW, was dem 4 bis 25-

fachen der normoxischen Kontrollen entsprach. Uberraschenderweise blieb die ADH-

Aktivitat auch eine Woche nach Wiederbeluftung auf unverandert hohem Niveau,

was moglicherweise als Anpassung an die periodischen Uberflutungsbedingungen

des Auenwalds zu interpretieren ist. Ethanol, Endprodukt der alkoholischen Garung

und potenzielles Zellgift, zeigte trotz hoher ADH-Aktivitat keine Akkumulation im

Wurzelgewebe, was typisch fur viele uberflutungstolerante Arten ist. Da auch im

Transpirationsstrom nur geringe Ethanolkonzentrationen von max. 3.5 mM gefun-

den wurden, wurde Ethanol offenbar kaum einer metabolischen Wiederverwertung

im Spross zugefuhrt, sondern wahrscheinlich vorwiegend ins umgebende Medium

exudiert. Nach Wiederbeluftung und -uberflutung verstarkte sich dieser Trend noch

einmal.

Trotz starker Fermentationsaktivitat war, wie eventuell aufgrund eines Pasteur-

German Summary 149

Effekts zu erwarten, keine Verarmung, sondern tendenziell sogar eine Erhohung

loslicher Kohlenhydrategehalte im Wurzelgewebe feststellbar. Dies deutete auf ver-

ringerte Stoffwechselaktivitat z.B. durch eingeschranktes Wurzelwachstum hin, was

im Einklang mit dem beobachteten Feinwurzelverlust stand. Ein Zusammenhang

zwischen ADH-Aktivitat oder Kohlenhydratgehalt der Wurzel einerseits, und der

Uberflutungstoleranz der untersuchten F. excelsior -Herkunfte sowie F. angustifolia

andererseits war nicht klar erkennbar. Dies deutete darauf hin, dass der Garungs-

stoffwechsel der Wurzel die Uberflutungstoleranz nicht maßgeblich beeinflusste.

4. Translokation von Photoassimilaten:

Deutlich (1,5- bis 2-fach) erhohte Gehalte loslicher Blattzucker in uberfluteten Esch-

ensamlingen deuteten auf einen verringerten Assimilatexport aus dem Blatt hin.

Dieser Ruckschluss wurde durch die Akkumulation von 13C nach Einfutterung von13C-Glukose ins Blatt unterstutzt. Desweiteren kam es im Phloem zu 2- bis 10-

facher Akkumulation von Saccharose, was darauf hindeutete, dass Phloementladung

und/oder -transportgeschwindigkeit durch Uberflutung noch starker verringert wa-

ren als die Phloembeladung. In Bezug auf den Blattzuckerexport ergab sich fur

uberflutungssensitive Ahornsamlinge (Acer pseudoplatanus L.) ein ahnliches Bild

wie fur Esche, wahrend in uberflutungstoleranter Zitterpappel (Populus tremula L.)

der Assimilatexport uberraschenderweise komplett inhibiert war.

5. Akkumulation von Mannitol:

In Blatt- und Wurzelgewebe sowie in Phloemexudaten und im Xylemsaft fanden

sich stark (bis zu 8-fach) erhohte Gehalte des Zuckeralkohols Mannitol. Da Man-

nitol u.a. bei F. excelsior an der osmotischen Anpassung von Geweben an ver-

ringerte Wassergehalte, z.B. bei Trockenstress, beteiligt ist, kam ihm diese Funk-

tion moglicherweise auch bei Uberflutung zu. Fur eine besondere Rolle sprach, dass

Mannitol in der Wurzel starker akkumulierte als die loslichen Zucker, was auf dif-

ferentielle Kohlenhydratverwertung hindeutete.

6. Stamminterne Sauerstoffkonzentrationen:

Aufgrund der hohen Sensitivitat des C-Haushalts fur Veranderungen der O2-Verfug-

barkeit, wurden erganzend Bestimmungen der stamminternen O2-Konzentrationen

vorgenommen. In Reaktion auf Wurzeluberflutung verringerte sich die O2-Konzen-

tration im Stamm von Eschensamlingen von durchschnittlich 71 % Luftsattigung

(LS) deutlich auf 48 % LS. Ahnliche Reduktionen traten in der Eiche auf. Im

uberfluteten Stammabschnitt der Esche fiel die Konzentration ungleich starker auf

13 % LS, was einerseits auf eine wichtige Rolle von radialer Gasdiffusion fur die

Stammbeluftung hindeutete und andererseits auf stark hypoxische Verhaltnisse im

unteren Stammbereich der Esche hindeutete. Im Gegensatz zu Esche und Eiche,

150 German Summary

wurde die stamminterne O2-Konzentration bei der Pappel nicht durch Uberflutung

beeinflusst.

Zusammenfassend betrachtet, erwies sich die “Rhein”- gegenuber der “Alb”-Herkunft er-

wartungsgemaß als uberflutungstoleranter, wohingegen die im Vergleich zu “Alb” geringen

Uberflutungsauswirkungen auf die Herkunft “Schwarzwald” uberraschten und moglicher-

weise auf unterschiedlich feuchte Bodenverhaltnisse der beiden Gebirgsherkunfte zuruck-

zufuhren sind. Die Ergebnisse deuteten an, dass der Wahl der richtigen Eschenherkun-

ft eine große Bedeutung fur die forstliche Praxis, z.B. bei Auwaldrestaurationen oder

Bepflanzungen von Hochwasserruckhaltebecken, zukommt.

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Acknowledgements

I am pleased to have the opportunity to express my gratitude to those people whose help

was indispensable for the success of the present thesis.

I would like to thank Prof. Rennenberg for the opportunity to work on an exciting stress-

physiological topic and for his guidance throughout the PhD project. To my supervisor,

Dr. Jurgen Kreuzwieser, I am deeply indebted for his advice and support. His insightful

comments and constructive criticism brought me to reconsider over and over the many

scientific questions and backgrounds relevant for the present work. This has undoubtedly

left its mark on the way I approach and judge scientific contexts. I also greatly appreciated

advice by Dr. Barbara Ehlting, Dr. Arthur Gessler and Dr. Andreas Peuke in manifold

scientific and statistical problems.

I am thankful to Monika Eiblmeier for readily sharing her professional lab knowledge and

her patience when work bench cleansing sometimes took a bit longer. . . I would also like

to thank Michael Rienks for his skillful technical support at numerous occasions. His help

with lifting those dreadful 25 kg-batteries onto stem heights of several meters is especially

acknowledged.

I am very grateful for the company of my great fellow PhD students, who never hesitated

to give a hand when needed. In particular, I thank Dr. Jost Hauberg for help with

countless small and big problems and his support in a special field mission (codename

“fine roots”). I thank Dr. Michael Nahm for interesting insights into climate change,

evolution theory and the music of Tom Waits.

I am also thankful to Dr. Peter Escher for his dedicated help with the mass spectrometer.

Thanks to Henriette Dietrich for providing me with (non-scientific) literature and music.

For their professional assistance with the “ash” experiments, I would like to thank the

following precious people (in alphabetical order): Dr. Cristian Cojocariu, Doris Fellner,

Ann-Kathrin Hofmann, Carmen Huglin, Ewa Lopacinska, Ursula Scheerer and Christiane

Steinki-Schwarz. Without your help, these experiments would have been simply unfeasi-

ble. To Carmen Huglin, Michael Nahm and Jost Hauberg I am additionally much obliged

168 Acknowledgements

for their support in seedling plantation in a thorny environment.

Moreover, I would like to say thank you to all partners of the FOWARA project. I greatly

enjoyed the friendly cooperation of the project, and the stimulating atmosphere at our

meetings.

Last but not least, I would like to thank my family and friends for their relentless support

and cheering during the last four years. There are no words to express my gratitude to

MariCarmen for her endless encouragement, patience and love.

April, 2008

Carsten Jaeger

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