soil microbiology of bushland saqib mumtaz master of ...44831/thesis_cdu_44831_mum… · soil...

SOIL MICROBIOLOGY OF BUSHLAND

SUBJECT TO POND WATER IRRIGATION AT

RANGER URANIUM MINE

Saqib Mumtaz

Master of Philosophy

Faculty of Education, Health, Science and the

Environment

Charles Darwin University

A thesis submitted to Charles Darwin University for the

degree of

Doctor of Philosophy

August 2013

ii

Declaration

I hereby declare that the work herein, now submitted as a thesis for the degree of

Doctor of Philosophy of the Charles Darwin University, is the result of my own

investigations, and all references to ideas and work of other researchers have been

specifically acknowledged. I hereby certify that the work embodied in this thesis has

not already been accepted in substance for any degree, and is not currently submitted

in candidature for any other degree.

Saqib Mumtaz

August 2013

iii

Acknowledgements

First of all, I am grateful to my supervisor Karen Gibb for all the fruitful discussions,

knowledge sharing and healthy criticism that enabled me think critically. I also thank

her for generously giving her time throughout the research work and especially in the

writing process. I am thankful to my co-supervisor David Parry for chemistry advice,

Keith McGuinness for statistical analyses and their interpretations, Ping Lu for

making the field work possible and Claire Streten-Joyce for her advice in planning

the lab experiments and patiently answering my questions. I also acknowledge my

co-supervisors for valuable comments and suggestions throughout the PhD process.

I would also like to thank all the other members of the Gibblab and the chemistry lab

for their help and a healthy working environment. I particularly thank Matthew

Neave for his help in sequencing. I thank Judy Manning for her help and advice in

chemistry lab. I am also thankful to Dylan Campbell, Dionisia Lambrinidis and

Francoise Foti for their help in chemical analyses. I am thankful to Zairinah Sani for

looking after the financial matters and managing the lab and making sure that lab is

well-stocked. I would like to thank Graeme Passmore for his assistance in field work.

I am thankful to my friend Wajid Javed for his support, healthy criticism and

discussions, John Sarev and his family for their support, enjoyable times and proof

reading my writing, Khalid Mehmood Shaheen, Salman Quddus and Wajahat

Mahmood, for their company and recreational activities and Rabia Tabassum for

sharing all the nice meals.

I would like to express my heartiest gratitude for the moral support, encouragement

and love that I received from my parents, brothers and sister.

I would also like to acknowledge Energy Resources of Australia Ltd. and Charles

Darwin University for funding my research project.

Last but not the least, I am extremely grateful to Higher Education Commission of

Pakistan as my PhD studies were not possible without the scholarship granted to me.

iv

Table of Contents

Declaration ................................................................................................................... ii

Acknowledgements ..................................................................................................... iii

Table of contents ......................................................................................................... iv

Abbreviations ............................................................................................................ viii

List of Figure ................................................................................................................ x

List of Tables............................................................................................................... xi

Abstract ..................................................................................................................... xiii

Chapter 1: General introduction

1.1: Uranium mining in Australia ......................................................................... 2

1.1.1: Ranger Uranium Mine ......................................................................... 2

1.2: Uranium geochemistry ................................................................................... 3

1.2.1: Uranium geochemistry in water ........................................................... 4

1.2.1.1: Uranium speciation in the absence of complexing agent

except hydroxide .................................................................. 4

1.2.1.2: Uranium speciation in the presence of carbonate, phosphate,

sulfate, fluoride and chloride ............................................... 6

1.2.2: Uranium geochemistry in soil .............................................................. 9

1.3: Microorganisms and uranium geochemistry ................................................ 10

1.3.1: Biotransformation .............................................................................. 10

1.3.2: Biomineralization............................................................................... 13

1.3.3: Biosorption......................................................................................... 15

1.3.4: Bioaccumulation ................................................................................ 16

1.4: Biomining .................................................................................................... 18

1.5: Bioremediation ............................................................................................. 19

1.6: Microorganisms as indicator of soil health .................................................. 20

1.7: Knowledge gaps ........................................................................................... 22

1.8: Research hypotheses .................................................................................... 23

Chapter 2: Fungi outcompete bacteria under high uranium concentration in

culture media

2.1: Introduction .................................................................................................. 28

2.2: Materials and methods ................................................................................. 30

v

2.2.1: Selection of sampling sites and soil uranium concentrations ............ 30

2.2.2: Culturing microbes from soil samples ............................................... 33

2.2.3: Identification of cultured isolates ...................................................... 33

2.2.4: Statistical analysis .............................................................................. 35

2.3: Results .......................................................................................................... 36

2.3.1: Soil uranium concentrations .............................................................. 36

2.3.2: Soil microbes and the effect of uranium concentrations in soil ......... 36

2.3.3: Identification of bacteria and fungi isolated from soil extracts ......... 37

2.3.4: Soil microbes and response to uranium in LB media ........................ 38

2.4: Discussion .................................................................................................... 38

2.5: Conclusions .................................................................................................. 42

Chapter 3: Physicochemical characteristics at Ranger Uranium Mine Land

Application Areas show significant seasonal, temporal and spatial

differences

3.1: Introduction .................................................................................................. 44

3.1.1: Soil characteristics at Ranger Uranium Mine Land Application Areas

............................................................................................................ 45

3.1.2: Uranium geochemistry at the Land Application Areas ..................... 46


3.2.1: Selection of sample sites .................................................................. 48

3.2.2: Analysis of soil physicochemical parameters at Ranger Uranium

Mine Land Application Areas .......................................................... 51

3.2.2.1: Acid extractible metal and sulfur analysis ......................... 51

3.2.2.2: Soil total organic carbon analysis ...................................... 51

3.2.2.3: Measurement of soil pH ..................................................... 52

3.2.2.3: Measurement of soil bulk density ...................................... 52

3.2.2.4: Measurement of soil moisture ............................................ 52

3.2.3: Statistical analysis .............................................................................. 53

3.3: Results .......................................................................................................... 54

3.3.1: Comparison of year 1 and year 2 soil samples based on

physicochemical variables ............................................................... 54

3.3.2: Comparisons of the dry and the wet seasons soil samples based on

physicochemistry.............................................................................. 54

vi

3.3.3: Comparison of low, medium, high and very high uranium categories

sites based on physicochemistry ...................................................... 58

3.3.4: Soil uranium concentrations between year 1 and year 2 .................. 60

3.3.5: Seasonal effect on soil uranium concentrations ............................... 61

3.3.6: Changes in soil sulfur, iron, calcium, aluminium, manganese and

copper concentrations between year 1 and year 2 ............................ 65

3.3.7: Seasonal change in soil sulfur, iron, calcium, aluminium, manganese

and copper concentrations between year 1 and year 2 ..................... 66

3.4: Discussion .................................................................................................... 66

3.4.1: Difference between dry season 1 and dry season 2 physicochemical

variables ........................................................................................... 68

3.4.2: Difference between wet season 1 and wet season 2 physicochemical

variables .......................................................................................... 70

3.4.3: Difference in soil physicochemistry between dry season 1 and wet

season 1 ............................................................................................ 70

3.4.4: Difference in soil physicochemistry between dry season 2 and wet

season 2 ............................................................................................ 72

3.4.5: Inter-site variation in soil physicochemistry .................................... 73

3.5: Conclusions .................................................................................................. 75

Chapter 4: Soil uranium concentration at Ranger Uranium Mine Land

Application Areas drives changes in the bacterial community

4.1: Introduction .................................................................................................. 77


4.2.1: Sampling sites and collection of soil samples .................................. 83

4.2.2: Analysis of soil physicochemical parameters at Ranger Uranium

Mine Land Application Areas .......................................................... 84

4.2.3: Bacterial community analysis of soil samples ................................. 85

4.2.3.1: Amplification and sequencing of the 16S ribosomal RNA

gene hypervariable V6 region ............................................ 85

4.2.3.2: Analysis of sequence data .................................................. 86

4.2.3.3: Statistical analysis of soil bacterial community and

physicochemical variables ................................................. 87

4.3: Results .......................................................................................................... 89

4.3.1: Soil physicochemistry at Ranger Uranium Mine LAAs and

associations with the bacterial community ...................................... 89

vii

4.3.1.1: Soil uranium concentration and physicochemical

parameters ......................................................................... 89

4.3.1.2: Correlation of soil uranium concentration and

physicochemical variables with the bacterial community . 93

4.3.2: An overview of the bacterial community composition at Ranger

Uranium Mine Land Application Areas ........................................... 97

4.3.3: Differences in the bacterial community between low and medium,

high and very high uranium sites at phyla level ............................. 102

4.3.4: Species indicative of medium, high and very high uranium sites at

phyla level ...................................................................................... 107

4.4: Discussion .................................................................................................. 107

4.4.1: Association between the bacterial community and soil uranium

Concentrations................................................................................ 107

4.4.2: Bacteria indicative of high uranium concentration ........................ 109

4.4.3: Bacterial community at Ranger Uranium Mine Land Application

Areas and its potential role ............................................................ 111

2.3: Conclusion ................................................................................................. 114

Chapter 5: General Discussion and Conclusions

5.1: Uranium resistant microbes ....................................................................... 120

5.2: Competition between bacteria and fungi ................................................... 123

5.3: Correlation between soil uranium concentrations and the bacterial

community ................................................................................................ 125

5.4: Bacteria indicator of high uranium at Ranger Uranium mine Land

Application Areas ...................................................................................... 126

5.5: Bacterial Community at Ranger Uranium Mine Land Application Areas 129

References ............................................................................................................... 134

Appendices

Appendix A .............................................................................................................. 170

Appendix B .............................................................................................................. 178

Appendix C .............................................................................................................. 185

Appendix D .............................................................................................................. 191

Appendix E .............................................................................................................. 192

viii

Abbreviations

μg microgram

μL microlitre

μM micromolar

°C degrees Celcius

AGAL Australian Government Analytical Laboratories

AGRF Australian Genome Research Facility

AIMS Australian Institute of Marine Sciences

AR analytical reagent

BLAST basic local alignment search tool

bp base pairs

CA California

CAP canonical analysis of principal coordinates

CEC cation exchange capacity

CLD Chemiluminescene

cm centimeter

dH2O distilled water

DNA deoxyribonucleic acid

dNTP deoxyribonucleoside triphosphate

e.g. for example

EDTA ethylenediaminetetraacetic acid

ERA Energy Resources of Australia Ltd.

et al. and others

g gram

ha hectare

H2S hydrogen sulphide

IAEA International Atomic Energy Agency

ICP-MS inductively coupled plasma-mass spectrometry

ICP-OES inductively coupled plasma optical emission spectrometry

kbp kilo base pairs

L litre

LAA Land Application Area

LB Luria-Bertani

m metre

M molar

MDS multi-dimensional scaling

mg milligram

MgCl2 magnesium chloride

ML Megalitre

mL millilitre

mM millimolar

MS mass spectrometry

NCBI National Centre for Biotechnology Information

NDIR non-dispersive infra-red

ng nanogram

NJ New Jersey

NSW New South Wales

OUT operational taxanomic unit

PCA principle component analysis

ix

PCR polymerase chain reaction

ppm parts per million/mg/kg

PRIMER Plymouth Routines in Multivariate Ecological Research

QLD Queensland

rcf relative centrifugal force

RNA ribonucleic acid

rRNA ribosomal ribonucleic acid

RP retention pond

RUM Ranger Uranium Mine

SA South Australia

SDS sodium dodecylsulfate

SDW sterilized distilled water

sp. species

SRM standard reference material

UV ultraviolet

x

List of Figures

Figure Title ................................................................................................ page

1.1 Eh-pH Diagram showing the hydrolysis of U(VI) and U(IV) in the

absence of complexing ligands except hydroxide ............................... 5

1.2 Estimated U speciation in the system UO2–PO4–CO3–OH–H2O at

over saturation at t= 25 ºC ................................................................... 6

1.3 Eh-pH diagram of aqueous U complexes at 25◦ C in the presence of

dissolved chloride, nitrate, carbonate, and sulfate .............................. 7

1.4 Eh–pH diagram of U speciation in the presence of sulfates at 25◦ C ... 8

2.1 A layout of Ranger Uranium Mine .................................................... 32

3.1 Multi-dimensional scaling (MDS) plots based on physicochemical

variables ............................................................................................ 56

3.2 Principal coordinate analysis plot generated from physicochemistry

resemblance matrix ........................................................................... 60

3.3 Average soil uranium concentrations at Ranger Uranium Mine Land

Application Areas on a dry weight basis .......................................... 63

3.4 Average soil uranium concentrations on a dry weight basis at low,

medium, high and very high uranium sites at Ranger Uranium Mine

Land Application Areas .................................................................... 65

4.1 Multi-dimensional scaling (MDS) plot of soil samples collected

during all the four sampling times at Ranger Uranium Mine Land

Application Areas based on OTUs .................................................... 96

4.2 Relative abundance of bacterial phyla at Ranger Uranium Mine Land

Application Areas during dry season 1 ............................................ 103


Application Areas during wet season 1 ............................................ 104


Application Areas during dry season 2 ............................................ 105


Application Areas during wet season 2 ............................................ 106

xi

List of Tables

Table Title ................................................................................................ page

2.1 A description of study sites at Ranger Uranium Mine Land

Application Areas and measured uranium concentrations ................. 31

2.2 Mean colony counts for bacterial genera growing on LB media ....... 37

3.1 Ranger Uranium Mine Land Application Areas ............................... 45

3.2 Study sites at Ranger Uranium Mine Land Application Areas ......... 49

3.3 Approximate monthly pond water disposal volumes (ML) at Ranger

Uranium Mine Land Application Areas ............................................ 49

3.4 Average total solute concentration (µg/L) applied in Retention Pond 2

irrigation water ................................................................................... 50

3.5 Total solutes (g/ha) applied in Retention Pond 2 irrigation water at

Ranger Uranium Mine Land Application Areas ................................ 50

3.6 PERMANOVA table of results based on soil physicochemical

parameters at Ranger Uranium Mine Land Application Areas ......... 55

3.7 Pairwise tests of all the combinations of low, medium, high and very

high U sites based on physicochemical parameters at Ranger Uranium

Mine Land Application Areas ............................................................ 59

3.8 PERMANOVA based on soil U concentrations at Ranger Uranium

Mine Land Application Areas ........................................................... 62

3.9 Pairwise tests of all the combinations of low, medium, high and very

high U sites at Ranger Uranium Mine Land Application Areas based

on soil U concentrations ..................................................................... 62

4.1 Ranger Uranium Mine Land Application Areas ................................ 81

4.2 Study sites at Ranger Uranium Mine Land Application Areas ......... 84

4.3 PERMANOVA table of results based on soil U concentration at

Ranger Uranium Mine Land Application Areas ................................ 91

4.4 PERMANOVA table of results based on soil physicochemical

parameters at Ranger Uranium Mine Land Application Areas ......... 92

4.5 P value and rho for Spearman’s rank correlation between soil U

concentration and the bacterial community at Ranger Uranium Mine

Land Application Areas during individual sampling time ................ 93

xii

4.6 PERMANOVA table of results based on OTUs (bacterial community)

............................................................................................................ 95

4.7 P value and rho for Spearman’s rank correlation between soil

physicochemical parameters and bacterial community during

individual sampling time at Ranger Uranium Mine Land Application

Areas ................................................................................................. 97

4.8 Sequences results of bacterial community at low, medium, high and

very high U sites at Ranger Uranium Mine Land Application Areas 98

4.9 Bacterial species richness and evenness at low, medium, high and

very high U sites at Ranger Uranium Mine Land Application Areas 99

4.10 Bacterial species Good’s coverage at low, medium, high and very

high U sites at Ranger Uranium Mine Land Application Areas ..... 100

4.11 Relative abundance of bacterial phyla and their classes in soil samples

at Ranger Uranium Mine Land Application Areas .......................... 101

xiii

ABSTRACT

Soil microorganisms may respond to metal stress by a shift in microbial community

from metal sensitive to metal resistant microorganisms. In this study microbes

isolated from soils irrigated with wastewater from Ranger Uranium Mine in northern

Australia were tested both for their resistance to uranium (U), and their community

level responses to variations in soil U and physicochemical parameters. Microbes

isolated from soil by culturing grew under different (field) concentrations of U added

to culture media in the form of uranyl nitrate and fungi out-competed the bacteria in

media with very high U concentrations. However, this shift from bacteria to fungi

that occurred in culture was not observed in soils with very high U concentrations

under field conditions. This suggests that the U present in the field may be less

bioavailable than U added to the culture media. Moreover, there was no difference in

the cultured microbial community isolated from soils with different U concentrations

which may be due to the fact that culturing technique captures only less than 1% of

the soil microbial community. To explore this further, the soil microbial community

was measured by culture-independent next generation sequencing using the 454

platform or pyrosequencing. One hundred and forty four soil samples were

pyrosequenced and 183,317 bacterial V6 sequences were obtained.

Using pyrosequencing, the bacterial community in soil with background levels of U

was different from those in soil with elevated U. Indicator species analysis showed

that bacterial OTUs closely related to members of Kitasatospora, Sphingobacteria,

Candidate_division_WS3 and Rhodobium were only present at medium, high and

very high U sites during all the sampling times. A significant seasonal and temporal

change in bacterial community was also measured as a result of seasonal and

xiv

temporal change in soil U and other physicochemical variables. Uranium resistant

microbes isolated in this study could be used to study resistance mechanisms and

bioremediation potential. Furthermore, bacterial species associated with higher U

concentrations may serve as useful indicators of U contamination in the wet-dry

tropics.

CHAPTER 1

GENERAL INTRODUCTION

Chapter 1. General Introduction

2

1.1 Uranium mining in Australia

Australia has the world’s largest Uranium (U) reserves (31% of the total world) and

it is the third largest producer of U behind Kazakhstan and Canada (WNA, 2012).

Currently, there are three U mines commercially operating in Australia: Ranger

Uranium Mine (RUM) in Northern Territory (NT), Olympic Dam (Roxby) Mine in

northern South Australia (SA), and Beverley Mine, also in SA. Honeymoon is an

approved mine located near Beverley in SA. The mine has started production but not

full commercial operations. Two new U recovery projects in SA at Beverley North

and Four Mile also have government approvals and are expected to commence

production in the near future (ACF, 2013; Geoscience Australia, 2013).

1.1.1 Ranger Uranium Mine

Ranger Uranium Mine, currently operated by Energy Resources of Australia Ltd.

(ERA) is located 250 km east of Darwin, NT. Uranium has been mined at RUM for

three decades and it is one of only three mines in the world to produce in excess of

100,000 tonnes of uranium oxide (U3O8) (ERA, 2013a).

Vegetation at RUM LAAs is comprised of open eucalypt forest dominated by E.

tetradonta, E. miniata, E. bleeseri and E. porrecta. The understory is characterised

by Acacia sp., Livistona humilis and Gardenia megasperma with a variable grass

cover of Sorghum sp., Themeda triandra and Eriachne triseta (Chartres et al., 1991).

Ranger Uranium Mine is situated in the wet-dry tropics and experiences monsoonal

rainfall. It receives 700–2200 mm (average 1540 mm) of rain in the wet season

(November–April). Rainfall received by the active pit catchment and stockpile


3

(waste and ore) catchments produces large volumes of water which need active

management (ERA, 2013b) as mine is also surrounded by Kakadu National Park,

which has a world heritage listing. Release of water from the site into the

downstream environment is minimised by the use of retention ponds (RP1, RP2).

Land application (irrigation) of excess waters from RP2 to natural woodland on the

mine lease is one mechanism used for water management on site (ERA, 2013b).

Soils at the Land Application Areas (LAAs) have strong tendency to adsorb

radionuclides and most metals applied in irrigation water (Akber and Marten, 1992;

Hollingsworth et al., 2005; Willett et al., 1993). Thus, bound metals and

radionuclides are unlikely to leach down the soil profile and affect the ground water

or aquatic environment downstream of RUM. However, there are concerns about the

radiological status of RUM LAAs and the concentration of radionuclides adsorbed in

the soil may require some RUM LAAs to be rehabilitated at mine closure (Akber et

al., 2011a), based on 1 milli Sievert (mSv) dose limit for public, recommended by

the ICRP (2007).

1.2 Uranium geochemistry

Uranium, in nature, generally exists in an oxide form, such as pitchblende (U3O8)

(US DOE, 2001). In ores it occurs as uranite (UO22+

), pitchblende (U3O82+

) or as

secondary minerals such as complex oxides, silicates, phosphates and vanadates

(Bleise et al., 2003; US DOE, 2001). In water, U is typically found as a uranyl

hydroxyl carbonate complex and in soil, it is usually present in an oxidized form

(Hopkins, 1923; Roh et al., 2000; Vochten, et al., 1990).


4

1.2.1 Uranium geochemistry in water

In aqueous environments, U can occur in the +3, +4, +5, and +6, oxidation states.

Dissolved U(III) easily oxidizes to U(IV) and the U(V) aqueous species readily

disproportionates to U(IV) and U(VI). Thus, U(IV) and U(VI) (i.e., uranyl) are the

most common oxidation states of U in natural environments (Krupka and Serne,

2002; Meinrath, 1998; Schoner et al., 2009). The solubility and the speciation of U

can be estimated from thermodynamic data, considering the concentration of U, pH,

presence of inorganic ligands such as (OH)−, (HCO3)

−, (CO3)

2−, (H2PO4)

−, (HPO4)

2−,

(PO4)3−

, (SO4)2−

in the ground waters, redox potential of waters and the equilibrium

or stability constants for the product species (Dozol and Hagemann, 1993; Siegel and

Bryan, 2003; Zachara et al., 2007). Areas of thermodynamic stability of various

species in an aqueous solution are presented by Eh–pH-diagrams. These Eh–pH-

diagrams show areas of stability as a function of electrochemical potential scales and

pH. Dashed lines in the diagrams show the upper and lower stability limits of water

(Figure 1.1, 1.3, 1.4). Diagonally drawn upper dashed line presents the superior limit

of water stability under oxidizing conditions, while the inferior stability limit of

water under reducing conditions is shown by the lower diagonal dashed line

(Meinrath, 1998; Robertson et al., 2003; Roine and Anttila, 2006).

1.2.1.1 Uranium speciation in the absence of complexing ligands except hydroxide

The significant uncomplexed hydrolytic species of U(VI) and U(IV) as a function of

Eh and pH are shown in Figure 1.1. Uranium(VI) species is dominant over the entire

pH range, under oxidizing to mildly reducing conditions. The hydrolysis of U(VI)

becomes significant at pH values greater than 5. In the absence of complexing


5

ligands other than hydroxide, UO22+

is the dominant aqueous U(VI) species at pH

values less than 5, UO2(OH)20 (aq) is favoured when pH is between 5 and 9, and at

pH values between 9 and 14 UO2(OH)3 is significant. At higher than approximately

1,000 μg/L dissolved U(VI), polynuclear species, like (UO2)3(OH)5+

and

(UO2)2(OH)22+

, start dominating the hydrolysis of U(VI) with increasing

concentrations of U(VI) when pH value is 5 or higher. Under reducing conditions,

U(IV) is stable and the hydrolysis of U(IV) is dominated by the neutral species

U(OH)40

(aq) at pH > 2 (Krupka and Serne, 2002; Markich, 2002).

Figure 1.1 Eh-pH Diagram representing the hydrolysis of U(VI) and U(IV) in the

absence of complexing ligands except hydroxide at 25 ºC and under 24

μg/L of total dissolved U concentration (Krupka and Serne, 2002).


6

1.2.1.2 Uranium speciation in the presence of carbonate, phosphate, sulfate,

fluoride and chloride

Uranium tends to form stable complexes with naturally occurring ligands such as

carbonate and phosphate (Figure 1.2) (Gavrilescu et al., 2009). Sulfate, fluoride and

possibly chloride complexes are also formed under elevated concentration of these

anions (Figure 1.3 and 1.4) (Gavrilescu et al., 2009; Krupka and Serne, 2002).

However, sulfate, fluoride and chloride complexes are less stable than carbonate and

phosphate complexes (Grenthe et al., 1992).

Figure 1.2 Estimated U speciation in the system UO2–PO4–CO3–OH–H2O at over-

saturation at t= 25 ºC (Gavrilescu et al., 2009).

Eh-pH diagram of the dominant U aqueous species calculated for total

concentrations of dissolved U, chloride, nitrate, carbonate, and sulfate of 0.024 (10-7

mol/L), 22, 1.7, 67.5, and 108 mg/L, respectively is presented in Figure 1.3. These


7

concentrations are based on a composition for uncontaminated groundwater from the

Hanford Site listed by Kaplan et al. (1996). Sulfate complexes of U would be

significant at pH values less than 3 while at pH values greater than 6, a range of

stable aqueous carbonate complexes such as UO2CO30 (aq), UO2(CO3)2

2− and

UO2(CO3)34−

dominate U(VI) speciation (Figure 1.3) which increases the solubility

of U under these environmental conditions (Langmuir, 1997). Under oxidizing

conditions, UO2(CO3)22−

is the dominant species found between pH 7 and 8. At pH

values greater than 2 and under reducing conditions, the speciation of U(IV) is

dominated by U(OH)40 (aq) in the presence of the dissolved chloride, nitrate,

carbonate, and sulfate (Krupka and Serne, 2002).

Figure 1.3 Eh-pH diagram of dominant aqueous U complexes estimated at a

concentration of 10-7

mol/L total dissolved U at 25 ºC in the presence of

dissolved chloride, nitrate, carbonate, and sulfate (Krupka and Serne,

2002)


8

The speciation of U in the presence of sulfates (Gavrilescu et al., 2009) which is a

major complexing agent present in RUM RP2 water is presented in Figure 1.4. At a

common ground water sulfate level of 100 ppm, UO2SO40 may be a significant

species up to pH 7. Sulfate complexing predominates in U solution mining

operations that use sulfuric acid in mill process such as RUM (Langmuir, 1978).

Sulfate concentration in RUM RP2 water is much higher than 100 ppm (Approx.

700–850 ppm) but the pH range 7–9 may not favour sulfate complexation of U. So U

may predominantly be present as uranyl hydroxy complexes such as UO2(OH)2+

and

(UO2)3(OH)5+

in RP2 water because these species predominate under U

concentration greater than 1000 µg/L (concentration present in RP2 water) and pH

value greater than 5 (Krupka and Serne, 2002; Markich, 2002). However, no models

were run to predict metal speciation in RP2 water in the present study.

Figure 1.4 Eh–pH diagram of U speciation in the presence of sulfates at 25 ºC

(conc. of U-ions: 0.01mg/L; sulfate-ions: 0.1mg/L). (1) UO22+

; (2)

U(SO4)2+

; (3) U4+

; (4) UO2(SO4)0; (5) U(SO4)2

0; (6) UO2; (7)

UO2(SO4)2−

; (8) UO2(OH)2H2O; (9) U3O8; (10) U4O9 (Gavrilescu et al.,

2009).


9

1.2.2 Uranium geochemistry in soil

Uranium in soil, can be adsorbed to the soil particles and in pore water it can be

found in complexed, reduced and precipitated forms. It can occur in various chemical

forms (Bertsch and Hunter, 1994; Hopkins, 1923; Todorov and Ilieva, 2006). The

primary processes that transform U in soil are biotic and abiotic redox reactions that

convert soluble U(VI) to insoluble U(IV) (Campbell and Biddle, 1977). Other abiotic

and biotic processes that can determine the speciation of U in the environment are

the formation of complexes with inorganic and organic ligands. Various soil

properties such as soil pH, redox potential, soil porosity, soil particle size and

adsorption potential, concentration of complex forming anions and the amount of

available water control the mobility of U in soil and its leaching to groundwater

(Allard, 1982; Bibler and Marson, 1992; Langmuir, 1978). Uranium is retained in the

soil due to adsorption, ion exchange, chemisorption or a combination of these

processes (Allard, 1982).

Adsorption of U to a large variety of soil minerals, organic surfaces, and other

sorbing agents has been documented (Arai et al., 2006; Baik et al., 2004; Baumann et

al., 2005; Fox et al., 2006; Fuller et al., 2002; Fuller et al., 2003; Giammar and

Hering, 2001; Livens et al., 2004; Noubactep et al., 2005; Prikryl et al., 2001; Reich

et al., 1998; Sylwester et al., 2000; Um et al., 2007; Wazne et al., 2006; Webb et al.,

2006). Uranium is also extensively adsorbed to iron oxides (hematite, goethite)

(Bargar et al., 1999; Combes et al., 1992; Kohler et al., 1992; Ticknor, 1994) and

ferrihydrite (Allard et al., 1999; Moyes et al., 2000; Waite et al., 1994). The

formation of U complexes in RUM RP2 water will affect its adsorption to the soil

particles in the LAAs. Soils have greater affinity for positively charged uranyl


10

hydroxy complexes (Echevarria et al., 2001), the complexes which are expected in

RP2 water. Thus, U is efficiently adsorbed in soils at RUM LAAs and it is assumed

that iron oxide component of LAAs soils is mainly responsible for this adsorption

and limitation of U mobility (Brown et al., 1998).

1.3 Microorganisms and uranium geochemistry

In addition to abiotic factors mentioned above, microorganisms interact with U in

multiple ways and thus significantly affect U geochemistry. These interactions may

include redox state biotransformation, bioaccumulation, biosorption and

biomineralization of U (Lloyd and Macaskie, 2002).

1.3.1 Biotransformation

Chemical changes in a substance due to metabolic activity of living organisms are

generally termed as biotransformation. In case of U, these changes mainly include

microbial oxidation and reduction processes (Reitz, 2011). Reductive immobilization

of U has been observed among diverse groups of respiratory and fermentative

microorganisms (Llorens et al., 2012; Reitz, 2011). The majority of Fe(III)-reducing

bacteria particularly, members of the δ-Proteobacteria and sulfate-reducing bacteria

such as Desulfovibrio desulfuricans, Desulfovibrio vulgaris (Lovley and Phillips,

1992; Lovley et al., 1993) and Desulfotomaculum reducens (Tebo and Obraztsova,

1998), can biotransform and immobilize U by direct enzymatic reduction of the

soluble uranyl ion (UO22+

) in which U is in U(VI) oxidation state and convert it into

U(IV) in the form of insoluble and less mobile uraninite (UO2) under anaerobic

conditions (Lovley, 1995; Wall and Krumholz, 2006). In addition, some sulfate-

reducing and Fe(III) reducing bacteria can also carry out the indirect reduction of


11

U(VI). For example, hydrogen sulfide (H2S), a by-product of sulfate reduction by

sulfate-reducing bacteria, can reduce U(VI) (Cardenas et al, 2008; Hua et al., 2006;

Liger et al., 1999; Lovley and Anderson, 2000). Ferrous iron Fe(II), produced by

Fe(III) reducing bacteria, may also take part in U(VI) reduction as Fe(II) can be re-

oxidized and provide electrons for the reduction of U(VI). Conversely, certain

microorganisms are able to oxidise U(IV) to U(VI). For example, bacterial species

like Acidithiobacillus ferrooxidans (DiSpirito and Tuovinen, 1982) as well as some

archaeal strains such as Sulfolobus metallicus (Huber and Stetter, 1991) and

Metallosphaera sedula (Huber et al., 1989) can carry out U oxidation under aerobic

conditions. Under anaerobic conditions nitrate, rather than oxygen, can serve as an

electron acceptor. This anaerobic, nitrate-dependent U(IV) oxidation has been

observed for Geobacter metallireducens (Finneran et al., 2002), Thiobacillus

denitrificans (Beller, 2005), and nitrate reducing Klebsiella sp. (Senko et al., 2005).

Since the U cycle at the earth’s surface is mainly controlled by redox reactions,

bacteria can affect the distribution of U by catalyzing these reactions. Moreover,

because uraninite is the most abundant form of mineral associated with U ore

deposits, microorganisms may have a role in ore formation (Suzuki and Banfield,

1999). Sandstone deposits, quartz-pebble conglomerates and unconformity type

deposits constitute about 70% of economically important ore deposits of U (Nash et

al., 1981). In all of these deposits, U is generally present in the reduced U(IV) form

and microorganisms may have contributed to the formation of these deposits (Suzuki

and Banfield, 1999).

Sandstone deposits were formed by the reduction of U(VI) to U(IV) in the form of

uraninite and coffinite below 50 oC. (Langmuir, 1997). As U ore bodies are


12

associated with pyrite and organic matter, U precipitation has generally been

attributed to organic U(VI) reduction by aqueous humic acids, hydrogen sulphide

generated by sulfate-reducing bacteria or H2S-rich natural gas (Nash et al., 1981).

Thus, sulfate-reducing bacteria may have played a vital role in the formation of

sandstone deposits (Bargar et al., 2013; Maozhong et al., 2005). Moreover, many

important sediment-hosted U ore deposits are thought to have been formed from the

reduction of U(VI) to U(IV) oxides and silicates by aqueous sulfide species. Detailed

studies using sulfate reducing bacteria Desulfovibrio desulfuricans (ATCC 7757)

have suggested that sulfate reducing and other bacteria may play a significant role in

the formation of sediment-hosted U ore deposits by adsorption of U to the bacterial

cell surfaces and subsequently reducing it by producing aqueous sulfide reductant

(Mohagheghi et al., 1985).

Quartz-pebble conglomerate deposits were formed by the mineralization of U in

strata rich in organic material, mostly kerogen. It is suggested that the stratiform

kerogen originated from cyanobacteria (Willingham et al., 1985); however, the

mechanism by which organic matter or microorganisms contributed to U

mineralization remains unknown.

Uranium ore deposits at RUM are classified as unconformity-related deposits

(Douglas et al., 2009; Lambert et al., 2005). These deposits were formed by the

movement of oxidation solution up through faults. Reduction and precipitation of

aqueous U(VI) then took place in carbon containing marginal marine sediments.

Most of the ore bodies are found within graphitic layers. Estimated temperature of

ore-formation is 100 oC to 250

oC, which is beyond the optimum temperature for

most microorganisms. Therefore it is unlikely that living microorganisms played a


13

significant role in U(VI) reduction and hence microorganisms may not have

significantly contributed to the formation of unconformity-related deposits at RUM

(Suzuki and Banfield, 1999).

Microbially-mediated redox transformations also drive U aqueous geochemistry.

Anoxic marine sediments are the most important sink for U on the earth’s surface,

where mineral precipitation takes place due to reduction of U(VI) to U(IV).

(Anderson et al., 1989; Church et al., 1996; Klinkhammer and Palmer, 1991; Lovley

et al., 1993). Marine sediments are typically stratified with regard to redox reactions.

Uranium(VI) is reduced within the Fe(III) reduction zone (Cochran et al., 1986;

Lovley et al., 1991). Therefore Fe(III) reducing microorganisms may play vital roles

in the U cycle in marine sediments (Lovley and Phillips, 1992; Lovley et al., 1993;

Lovley et al., 1991). In estuarine sediments, U(VI) reduction takes place in the

sulfate-reducing zone. In near shore and estuarine sediments, where relatively

abundant organic matter is present, bacteria may control U(VI) reduction (Barnes

and Cochran, 1993). Microbially-mediated U reduction has also been reported in

shallow freshwater sediments at an open pit such as found at RUM (Suzuki et al.,

2005).

1.3.2 Biomineralization

In addition to redox biotransformation of U, microorganisms can also transform U by

forming its complexes with inorganic and organic compounds generated by

microbial cells which may either enhance or reduce solubility and mobility of U.

Usually microbial generated inorganic ligands, such as phosphates, sulphides, and

carbonates, precipitate U by forming insoluble mineral complexes resulting in


14

biomineralization of U. Biomineralization is the precipitation of U due to the

formation of insoluble mineral complexes of U with microbially generated ligands.

(Reitz, 2011). A well-known example of biomineralization is the precipitation of U

as U phosphate mineral phases ‒ such as H-autunite (Macaskie et al., 2000) and

autunite/meta-autunite (Jroundi et al., 2007; Martinez et al., 2007; Nedelkova et al.,

2007) ‒ due to complexation of U by orthophosphate. Orthophosphate is liberated

due to the activity of various enzymes, classified as phosphatases, which release

inorganic phosphate (PO43-

) from organic phosphate compounds. Not only anaerobic

and aerobic bacteria but some archaea also show phosphatase enzyme activities.

(Dassa et al., 1982; Kurosawa et al., 2000; Porschen and Spaulding, 1974; Satta et

al., 1979, Torriani, 1960). For example, strains belonging to the genera Bacillus and

Rahnella have been involved in the precipitation of U through phosphatase activity

(Martinez et al., 2007). Similarly, Citrobacter sp. precipitate HUO2PO4 and

NaUO2PO4 phases of U around its cells (Macaskie et al., 2000) and

Stenotrophomonas maltophilia JG-2 and Microbacterium oxydans SW-3 strains,

precipitate U phosphate mineral phase belonging to the meta-autunite group. Such U

precipitation was also found in other Gram-positive or Gram-negative bacterial

strains, like Bacillus sphaericus JG-7B and Sphingomonas sp. SW366- 3 (Merroun

and Selenska-Pobell., 2008).

In addition to inorganic ligands that are able to form U complexes, microorganisms

may also produce organic compounds such as humic substances by biodegradation of

complex organic matter (Allard et al., 1994). Humic substances particularly humic

acid and fulvic acid are known to efficiently interact with U (Lenhart et al., 2000;

Wei et al., 2007) and, thus, can increase or decrease U mobility depending upon soil

pH and other geochemical conditions (Bednar et al., 2007; Crancon and van der Lee,


15

2003; Ivanov et al., 2012). Humics may also reduce U(VI) by serving as terminal

electron acceptor in microbial respiration pathways and subsequently donating these

electrons to U(VI) (Lovley et al., 1998). This mechanism is most likely responsible

for U(VI) reduction by Deinococcus radiodurans, which is unable to reduce U(VI)

directly but it can reduce U(VI) in the presence of humic acids (Fredrickson et al.,

2000).

Other microgenic compounds which interact with U are siderophores. Siderophores

are chelating agents that are usually secreted by microbes due to intracellular iron

deficiency to increase iron solubility and bioavailability in the environment by

forming iron complexes with functional groups, particularly catechol and

hydroxamate (Neilands, 1995; Saha et al., 2013). However, siderophores are usually

not iron specific (Saha et al., 2013). Therefore, they may also increase the solubility

and thus the bioavailability of other metals including U. Siderophores such as

pyoverdin and desferrioxamine-B are reported to increase U mobility (Frazier et al.,

2005; Kalinowski et al., 2004).

1.3.3 Biosorption

In addition to above mentioned metabolism dependent (active) interactions of

microorganisms with U, microorganisms also have the ability to biosorb U to their

cell surface structures. Metabolism independent (passive) sorption of metals to

biomass is termed as “biosorption”. It includes both adsorption (the accumulation of

substances at a surface or interface) and absorption (nearly uniform penetration of

atoms or molecules of one phase to form a solution with second phase) (Merroun and

Selenska-Pobell., 2008). As the microbial cell wall is directly in contact with the


16

environment, it serves as a highly efficient matrix for metal complex formation due

to the high surface to volume ratio of microbial cells and the charged groups present

in the cell wall. Metals are primarily bound by negatively charged functional groups

such as deprotonated phosphate, carboxyl, hydroxyl and sulfhydryl groups located in

organic cell surface polymers such as lipopolysaccharides, peptidoglycan, proteins,

and glycolipids. Some studies have shown that microbial cell surfaces can even be

more efficient in binding U than inorganic soil minerals (Choi and Park, 2005;

Llorens et al., 2012; Ohnuki et al., 2005; Walker et al., 1989).

1.3.4 Bioaccumulation

Finally, microorganisms may also accumulate U intracellularly, a phenomenon

known as bioaccumulation. Unlike metabolically essential metals ‒ such as Fe, Cu,

Zn, Co, and Mn ‒ which are transported into the cells through energy dependent or

metabolism dependent transport systems, U is accumulated in the cells only due to

increased membrane permeability as a result of U toxicity (Suzuki and Banfield,

1999) as U has no essential biological function. Moreover, no U transporters have

been found in microorganisms. Therefore, U accumulation within microbial cells is

considered a metabolism-independent process (DiSpirito et al., 1983; Suzuki and

Banfield, 2004).

Once accumulated intracellularly, microorganisms have developed several

mechanisms to immobilize U to avoid its toxicity. One such tolerance mechanism is

U chelation by inorganic polyphosphate bodies, as observed in different bacterial

strains such as A. ferroxidans (Merroun et al., 2003) and Sphingomonas sp. S15-S1

(Merroun et al., 2006). In addition, U can also accumulate as needle-like fibrils of


17

different sizes, which has been observed in the cytoplasm of Arthrobacter sp.,

Desulfovibrio asponensis and Sphingomonas sp. S15–S1 (Merroun et al., 2006).

If microbes are planktonic, they may enhance migration of biosorbed or

bioaccumulated U. If microbes are sessile and form part of a biofilm, they may

immobilize U (Merroun and Selenska-Pobell., 2008). In nutrient deficient natural

environments, including rocks and soils, microorganisms are often attached to solid

surfaces and frequently form biofilms. Bacteria attached to solid surfaces can

decrease U transport in geological settings. However under harsh environmental

conditions (poor availability of nutrients, extreme temperature or pH), microbes

respond by reducing their cell size or their attachment abilities. These responses

enhance the movement of microbes and hence biosorbed and/or bioaccumulated U in

soils and subsurface strata (Suzuki and Banfield, 1999).

Most microbes are colloid-sized (particles having 0.005–5 µm diameter) ‒ refered to

as biocolloid, and they can increase or decrease the rate of U transportation.

Suspended colloids can migrate in solutions through porous or fractured subsurface

rocks. Thus, biocolloidal movement can facilitate the transport of biosorbed and/or

bioaccumulated U if microbial cells are not attached to large mineral particles

(McCarthy and Zachara, 1989; Richards et al., 2007).

In addition to bacterial cells, small mineral particles can be transported as colloids.

Microbes can form colloidal U precipitates. If these precipitates are detached from

microbial cell surfaces, they can migrate in ground water (McCarthy and Zachara,

1989). Thus, microorganisms efficiently interact with U and play important roles in


18

U geochemistry in nature. These microbial-U interactions also have other

applications such as biomining of U and bioremediation of U contaminated sites.

1.4 Biomining

Biomining is a technique used to recover the various types of minerals from ore

using microorganisms and is successfully used to extract a range of metals including

copper, gold and uranium (Rawlings, 2002; Watling, 2006).

Biomining may involve two processes: solubilization or bioleaching of minerals

from ores by microbial metabolic activities (Brierley, 1978), and biosorption of

metals from mine waste waters. There are bacteria, algae, yeasts and molds with this

capability.

Leaching reactions generally involve the conversion of insoluble metal ores (often

sulfides) to soluble compounds from which the desired metal can be more readily

recovered. The leaching bacteria may achieve this conversion directly by oxidizing

the metal sulfides. Alternatively, bacterial leaching of minerals can be indirect. The

ferric iron and sulfuric acid produced by the direct oxidation of metal sulfides are

themselves capable of oxidizing certain ores to form oxides and sulfates that are

soluble in acid solutions (Hutchins et al., 1986; Seifelnassr and Abouzeid, 2013).

Uranium leaching is an indirect process. A. ferrooxidans does not attack the U ore

directly, rather it acts on the iron oxidant. The pyrite reaction is used for the initial

production of Fe(III) leach solution (Hutchins et al., 1986; McCready and Gould,

1990). Uranium is recovered by the conversion of insoluble tetravalent U oxides to

soluble hexavalent U sulfates with hot H2SO4/Fe3+

solution generated by


19

microorganisms (Hutchins et al., 1986; Seifelnassr and Abouzeid, 2013).

( ) ( )

( )

Biomining has been successfully used to obtain U from waste gold ore. Biomining

has been receiving increased attention because this technology is more cost effective

and environmental friendly than conventional mining procedures (Rawlings, 2002;

Woods and Rawlings, 1989).

1.5 Bioremediation

Bioremediation is the process of detoxification, degradation or removal of

environmental pollutants using microorganisms. Microorganisms may be added

directly to the contaminated site, or their growth can be activated by addition of

nutrient(s) (Wall and Krumholz, 2006). Uranium bioremediation is generally based

on the reduction of soluble U(VI) to sparingly soluble U(IV), or on biosorption of

U(VI) in microbial biomass. This process does not change the half-life of the metal

but helps reduce the mobility of U, and prevents it from leaching and contaminating

the groundwater (Wall and Krumholz, 2006).

Uranium may be bioremediated by at least three immobilization-based processes: (1)

enzymatic dissimilatory metal bioreduction of soluble U(VI) to sparingly soluble

U(IV), (2) chemical reduction by microbially-generated by-products, and (3)

biosorption on cell surface, biopolymers or dead organisms (Seyrig, 2010; Wall and


20

Krumholz, 2006). Microbial based technology offers a low cost and environmentally

safe alternative for wastewater treatment and rehabilitation of contaminated sites

(Hutchins et al., 1986; Lovley, 2003).

Microorganisms also have a role in phytoremediation (environmental clean-up using

plants) of soil. Success of phytoremediation depends upon the uptake and removal of

bioavailable heavy metals from soil by plant roots. Since solubility and hence

bioavailability of metals to plant root system is largely determined by the soil

microbial activities, microbes may greatly influence the process of phytoextraction

(Haferburg et al., 2007). Microbes can also increase the efficiency of

phytoremediation by increasing the root absorption area (Lasat, 2002; Sessitsch et

al., 2013).

1.6 Microbes as an indicator of soil health

Chemical analysis is the most direct approach to reveal the status of heavy metal

pollution in the environment but it cannot provide evidence on the integrated

influence, and possible toxicity, of such pollution on the organisms and ecosystem

(Smejkalova et al., 2003; Zhou et al., 2008). Biological analyses can measure the

actual impact of contaminants on soil organisms, as they show the growth and

activity inhibition under stress conditions (Smejkalova et al., 2003; Zhou et al.,

2008). Among soil biota, microorganisms respond quickly to environmental stress,

as they have short generation time and have close interaction with their surroundings

due to their high surface to volume ratio. These unique features of microorganisms

make them ideal to study the effect of elevated metals on living organisms (Nielsen

and Winding, 2002). Changes in biomass, community structure, and specific


21

functions of soil microorganisms ‒ such as organic matter decomposition, soil

respiration, enzymatic activity and nitrogen mineralization ‒ serve as a useful

indicator of the alterations in soil physical and chemical properties (Nazaret et al.,

2003; Sardar et al., 2007).

Microbial activity also plays a vital role in determining the bioavailability of metals

in soils. The impact of such metals on soil health is dependent on microbial

activities. For instance, the concentration of heavy metals in soil will not change over

small time periods, but their bioavailability may. Therefore, the total content of

chemicals in soil is not a reliable indicator of its bioavailability (Logan, 2000) and

thereby of soil health. Instead, bioavailability has to be measured in relation to

bioassays and specific microbial processes. In this context, microbial responses also

integrate the effect of chemical mixtures, information not obtained by studying the

chemical mixtures themselves (Nielsen and Winding, 2002).

It is also difficult to predict the behavior of metals in the subsurface. Understanding

the processes controlling the fate and transport of metals in the environment is a

fundamental requirement in the development and evaluation of effective remediation

strategies. Microorganisms, and the extracellular material associated with them, are

thought to play key roles in determining the chemical speciation of a contaminant

and its mobility in the environment. Therefore, in order to fully understand mine

waste disposal environments, microbial processes should be included in models,

theories and interpretation of results (Ledin and Pedersen, 1996).


22

1.7 Knowledge gaps

Due to the above mentioned significance of microorganisms, there have been a

number of studies at U contaminated environments during the past decade to study

the microbial community structure, its role in the biogeochemistry of U and potential

for bioremediation and biomonitoring (Akob et al., 2007; Brodie et al., 2006; Chen et

al., 2012; Elias et al., 2003; Fields et al., 2005; Hwang et al., 2009; Martins et al.,

2010; Mondani et al., 2011; Petrie et al., 2003; Rastogi et al., 2010; Reardon et al.,

2004; Satchanska et al., 2004; Satchanska and Selenska-Pobell, 2005; Selenska-

Pobell et al., 2001; Suzuki et al., 2003, 2005; Xu et al., 2010). However, soil

microbiology has not been studied in detail at RUM LAAs. An understanding of soil

microbiology at RUM LAAs is not only important for adopting sustainable

management and rehabilitation practices but it may also be a step towards filling the

knowledge gaps related to soil microbiology at the U contaminated sites. RUM

LAAs are subjected to distinct wet and dry seasons. Irrigation with pond water

during dry seasons may increase the concentration of U and other metals in the soil

while rainfall during subsequent wet seasons may leach some metals from the soil

profile thus reducing their concentration. This seasonal change in U and metal

concentration may affect the indigenous microbial community, an effect which has

been poorly investigated at U contaminated sites. Studies of microbial community at

RUM LAAs would allow us to understand how seasonal changes in the wet-dry

tropics affect the bacterial community.

Moreover, to my knowledge, changes in the bacterial community structure as well as

the level of U resistance under increasing U concentrations in the soil has not been

investigated. Ranger Uranium Mine LAAs also provide an opportunity to investigate


23

this because sites at RUM LAAs present a range of U and other metal

concentrations.

Very few investigations have used culture independent pyrosequencing technique to

study microbial communities at U contaminated sites. Pyrosequencing technology

provides a large number of sequence reads per sample in a single run, that allows the

detection of not only the most dominant microbial community members but also of

the low-abundance (rare) taxa which is important for ecological studies (Siqueira et

al., 2012; Sogin et al., 2006). Pyrosequencing of the 16S rRNA gene from diverse

environments has demonstrated that the microbial diversity can be orders of

magnitude higher than revealed by previous technologies (Siqueira et al., 2012;

Sogin et al., 2006;). Pyrosequencing also enables the analysis of a large number of

samples, providing results that are more robust for comparisons. Moreover, the cost

per base is much lower for pyrosequencing when compared with the Sanger

sequencing method. Another advantage of the pyrosequencing technique is that it

also avoids the biases inherent to the cloning procedure. I studied the soil microbial

community at RUM LAAs using culture dependent and culture independent

(pyrosequencing) microbiology and molecular techniques to identify and compare

the microbes associated with low and high U levels, and to measure changes with

season and time.

1.8 Research hypotheses

1. Soil containing elevated metals can support a high diversity of

microorganisms (Ellis et al., 2003; Konstantinidis et al., 2003) and these

microbes are well adapted to metal contaminated environments (Haq and


24

Shakoori, 2000; Roane and Pepper, 2000) because they possess a variety of

mechanisms to tolerate high concentrations of metals and radionuclides

(Nies, 2003; Piddock, 2006). Since some microbial isolates recovered from

U-polluted environments are resistant to severe oligotrophic conditions

(Suzuki and Banfield, 2004) and the number of resistant microbes as well as

their level of resistance is increased with increasing loads of metals (Ryan et

al., 2005), I hypothesized that some microbes present at RUM LAAs would

be resistant to U. Moreover, microbes retrieved from soil with high ‘field

concentrations’ of U will be more resistant to U than microbes isolated from

soil with low field concentrations of U and the number of resistant microbes

isolated from soils with high field concentrations of U will be higher than the

number of resistant microbes isolated from low U soils.

2. Previous studies indicate that radionuclides and most metals applied in

irrigation water are efficiently retained by the soils at RUM LAAs, and the

loss of these radionuclides and metals after the wet season rainfall is minimal

(Chartres et al., 1991; Hollingsworth et al., 2005; Willett and Bond, 1998).

Therefore, I predicted that there would not be a significant change in soil

physicochemical properties between years and between wet and dry seasons.

Similarly, I also hypothesized that U concentrations would not differ

significantly between years or seasons.

3. Metal contamination may cause inhibition of specific functions of soil

microorganisms and changes in their biomass and community structure

(Nazaret et al., 2003; Sardar et al., 2007). Under metal stress the microbial

community may shift to microorganisms that can cope with the new


25

environments. Such community level changes in bacteria have been measured

in response to U stress (Akob et al., 2007; Islam et al., 2011; Joner et al.,

2007). Therefore, if the hypothesis in paragraph two above is rejected and

there is a significant seasonal and temporal change in soil U and other

physicochemical variables, I hypothesize that there will be a seasonal and

temporal change in the composition of the bacterial community. Moreover,

the bacterial community at low U sites will be significantly different from

medium, high and very high U sites.

4. Microorganisms adopt a variety of resistance mechanisms under U stress.

One such mechanism may involve reduction of highly soluble U(VI) to

sparingly soluble U(IV) species (Khijniak et al., 2005; Lloyd, 2003; Lovley et

al., 1991; Wu et al., 2006). Less soluble species may be less bioavailable and

hence less toxic to microorganisms (Gadd, 2004; Salbu et al., 1998). In these

conditions, U reducing bacteria may have a better chance of survival thus

increasing their population. This does appear to be borne out by the fact that

U reducing bacteria have been frequently isolated from uraniferous

environments (Cardenas et al., 2006; Mondani et al., 2011). Since sulfate

reducing bacteria are a major group of bacteria capable of U reduction

(Lovley and Phillips, 1992; Lovley et al., 1993), I hypothesized that sulfate or

U reducing bacteria will be more abundant at

medium, high and very high U

sites as compared to low U sites due to increased U and sulfate concentration.

5. The bacterial community present at one U contaminated location may differ

from other U contaminated locations due to differences in the level of U

contamination, differences in geographic and geologic origin of U, and


26

differences in climatic conditions or site history (Selenska-Pobell et al.,

2002). Reports indicate that throughout the world different U sites have

different complements of bacteria (Chen et al., 2012; Martins et al., 2010;

Mondani et al., 2011; Rastogi et al., 2010; Suzuki et al., 2005; Xu et al.,

2010). Thus, I also hypothesized that the bacterial community at RUM LAAs

will be different from other U contaminated locations due to its unique

climatic conditions.

I addressed the first hypothesis in chapter 2. I plated soil extracts from each uranium

concentration category onto culture media spiked with a range of U concentrations

that reflected the ‘field concentrations’ of U. By challenging each soil U category

with an increasing concentration of U in the culture media, I determined if microbes

cultured from soil with high ‘field concentrations’ of U were more resistant to

uranium than microbes cultured from soil with low field concentrations of U. In

chapter 3, the second hypothesis was tested by analyzing soil U and physicochemical

variables at RUM LAAs after wet and dry seasons for two consecutive years to study

the seasonal and temporal change in soil U and physicochemical variables. The third,

fourth and the fifth hypotheses were addressed in chapter 4. I used the 454

pyrosequencing platform to measure the soil bacterial community at RUM LAAs

with low, medium, high and very high U concentration after wet and dry seasons for

two consecutive years. The correlation of the bacterial community with the measured

soil U and other physicochemical variables was measured through multivariate

statistical analysis. Finally, in chapter 5, I discussed the significance of the results

obtained in this study....………………………………………………………………..

CHAPTER 2

FUNGI OUTCOMPETE BACTERIA UNDER

INCREASED URANIUM CONCENTRATION IN

CULTURE MEDIA

This chapter is an adapted version of a paper published in Journal of Environmental

Radioactivity

Mumtaz, S., Streten-Joyce, C., Parry, D.L., McGuinness, K.A., Lu, P., Gibb, K.S.,

2013. Fungi outcompete bacteria under increased uranium concentration in culture

media. J. Environ. Radioactiv. 120, 39–44.

Chapter 2. Uranium resistant microbes

28

2.1 Introduction

Ranger Uranium Mine (RUM) is one of the world’s largest uranium (U) producers.

The mine is located near the township of Jabiru, about 250 km east of Darwin in the

wet-dry tropics of northern Australia. Rainfall is monsoonal, with 700–2200 mm

(average 1540 mm) falling in the wet season (November–April), which requires

active water management. A key part of water management at RUM is land

application of surplus pond water from one of its retention ponds (RP2) to natural

woodland on the mine lease during each dry season (May–October) in accordance

with regulatory requirements. Pond water is defined as rainfall that falls on the active

pit catchment and stockpile (waste and ore) catchments. Uranium radioisotopes are

present in RP2 water (Akber et al., 2011a). About 30% of the RP2 water is directed

through a treatment wetland, and is polished by passing through a series of discrete

cells formed by earthen embankments. Upon entering the wetland, water flows

through each of the cells and reacts with the well-developed wetland ecosystem

dominated by water lilies and native reeds (Eleocharis sp.). The main purpose of the

treatment wetland is to remove U from RP2 water through biogeochemical

processes. As a result the polished RP2 water has less U compared to unpolished

water (Overall and Parry 2004; Zimmermann and Lu, 2011). The concentration of

radionuclides absorbed in the soil as a result of land application of water could

potentially require the Land Application Areas (LAAs) to be rehabilitated at the mine

closure (Akber et al., 2011a). Consequently, a rehabilitation plan for RUM LAAs is

being developed.

Microorganisms have a potential role in this rehabilitation plan because they

solubilise, transport, accumulate and precipitate metals and radionuclides in the


29

environment (Hutchins et al., 1986). Microorganisms immobilize radionuclides and

toxic metals by enzymatic reductive precipitation, biosorption, bioaccumulation and

biomineralization. These properties of microbes can be exploited for U

bioremediation (Francis, 1990; Nevin et al., 2003). Microbial based remediation

presents an economical, environment friendly and effective alternative to

conventional technologies for the treatment of contaminated environments (Hutchins

et al., 1986; Lovley, 2003). Thus, microorganisms, including bacteria (Andres et al.,

1994; Roig et al., 1997; Tsuruta, 2002; Pollmann et al., 2006), actinomycetes (Golab

et al., 1991; Tsuruta, 2006; Tsuruta, 2004), fungi (White and Gadds, 1990; Ding et

al., 2012), yeasts (Shumate II et al., 1978; Strandberg et al., 1981), and algae (Kalin

et al., 2005) have been the focus of studies to remove U from contaminated sites.

Soil containing elevated metals can support a high diversity of microorganisms (Ellis

et al., 2003; Konstantinidis et al., 2003). These native microorganisms have not only

adapted to the new environments but some species flourish (Haq and Shakoori, 2000;

Roane and Pepper, 2000). Microorganisms possess a variety of mechanisms to

tolerate high concentrations of heavy metals and radionuclides and are often

associated with particular metals (Nies, 2003; Piddock, 2006). Microbes have the

ability to tolerate U stress, to bioaccumulate (Ohnuki et al., 2005), precipitate

(Beazley et al., 2007; Nedelkova et al., 2005) and biotransform U (DiSpirito and

Tuovinen, 1982; Lovley et al., 1991). Therefore, microorganisms can be used to

bioremediate U-contaminated sites by in situ biostimulation (North et al., 2004;

Suzuki et al., 2005) or to decontaminate U polluted waters by using bioceramic

filters (Raff et al., 2003). Since some microbial isolates recovered from U-polluted

environments have adapted to severe oligotrophic conditions (Suzuki and Banfield,

2004), and the number of resistant microbes as well as their level of resistance is


30

increased with increasing loads of metals (Ryan et al., 2005), I hypothesized that

some microbes present at RUM LAAs would be resistant to U. Moreover, microbes

retrieved from soil with high ‘field concentrations’ of U will be more resistant to U

than microbes isolated from soil with low field concentrations of U and the number

of resistant microbes isolated from soils with high field concentrations of U will be

higher than the number of resistant microbes isolated from low U soils.

To address these hypotheses, I plated soil extracts from each U concentration

category onto culture media spiked with a range of U concentrations that reflected

the ‘field concentrations’ of U. By challenging each soil U category with an

increasing concentration of U in the culture media, I could determine if microbes

cultured from soil with high ‘field concentrations’ of U were more resistant to U than

microbes cultured from soil with low field concentrations of U.

2.2 Materials and methods

2.2.1 Selection of sampling sites and soil uranium concentrations

Historical soil chemistry data were used to categorise sites at RUM LAAs as low,

medium, high and very high U (Akber et al., 2011b). The differences in soil U were

largely due to their distance from the source of irrigation, year commissioned,

irrigation water quality (polished vs unpolished) and method of irrigation (Table 2.1).

Soil samples were collected using a core sampler with diameter 5 cm and depth 10

cm (Chan et al., 2006) from 18 sites at RUM LAAs (Table 2.1, Figure 2.1). Five

independent field replicates were collected from each of the low (control), medium,

high and very high U sites within each LAA. Ninety samples were collected and

transported to laboratory on ice..………………………………………………………

Ch

ap

ter

2.

Ura

niu

m r

esis

tan

t m

icro

bes

31

T

ab

le 2

.1

A d

escr

ipti

on

of

stu

dy s

ites

at

Ran

ger

Ura

niu

m M

ine

Lan

d A

pp

lica

tio

n A

reas

(R

UM

LA

As)

an

d m

easu

red

ura

niu

m c

on

cen

trat

ion

s

(mea

n o

f fi

ve

sub

-sam

ple

s).

Ura

niu

m

cate

gory

S

tud

y S

ites

Mean

U C

onc.

(ppm

dry

w

t.±

SD

)

Year

com

mis

sio

ned

Ir

rigation

meth

od

Wate

r qualit

y

Dis

tance

from

sprinkle

r

Lo

w(c

ontr

ol)

C

CLA

A-0

76

2 ±

0.2

2007

spra

y

unpo

lish

ed R

P2

wate

r

8

D

LA

A-1

77 E

XT

3 ±

0.7

1999

flood

w

etland p

olis

hed R

P2 w

ate

r 50

DLA

A-1

85

3 ±

0.7

1997

flood

w

etland p

olis

hed R

P2 w

ate

r 50

RP

1-1

44

5 ±

1.0

1995

flood

w

etland p

olis

hed R

P2 w

ate

r 50

MLA

A-E

XT

-121

11 ±

3.5

1994

spra

y

unpo

lish

ed R

P2

wate

r 50

JE

LA

A-0

20

14 ±

11

.1

2006

spra

y

unpo

lish

ed R

P2

wate

r 10

DLA

A-1

70 E

XT

20 ±

10

.2

1999

flood

w

etland p

olis

hed R

P2 w

ate

r 10

M

ed

ium

D

LA

A-2

22

222 ±

98.1

1997

flood

w

etland p

olis

hed R

P2 w

ate

r 1

.5

C

CLA

A-0

36

280 ±

303.8

2007

spra

y

unpo

lish

ed R

P2

wate

r 0

RP

1-1

38

344 ±

223.8

1995

flood

w

etland p

olis

hed R

P2 w

ate

r 1

0

JE

LA

A-0

01

407 ±

250.9

2006

spra

y

unpo

lish

ed R

P2

wate

r 1

H

igh

R

P1-1

34

521 ±

145.2

1995

flood

w

etland p

olis

hed R

P2 w

ate

r 2

DLA

A-1

57 E

XT

634 ±

93.9

1999

flood

w

etland p

olis

hed R

P2 w

ate

r 0.5

DLA

A-2

28

665 ±

334.3

1997

flood

w

etland p

olis

hed R

P2 w

ate

r 1

2.5

DLA

A-2

27

858 ±

229.7

1997

flood

w

etland p

olis

hed R

P2 w

ate

r 1

0

M

LA

A-E

XT

-101

820 ±

492.6

1994

spra

y

unpo

lish

ed R

P2

wate

r 3

V

ery

hig

h

M

LA

A-E

XT

-106

985 ±

488.6

1994

spra

y

unpo

lish

ed R

P2

wate

r 0

MLA

A-0

32

1728

± 5

21

.4

1985

spra

y

unpo

lish

ed R

P2

wate

r 0


32

Figure 2.1 A layout of Ranger Uranium Mine (RUM) Northern Territory (NT)

Australia. Approximate boundaries of different Land Application Areas

(LAAs) have been shaded (Akber et al., 2011c)

For total soil U analysis, samples were sieved to < 2 mm size fraction and oven dried

at 60 °C overnight. Dried soil samples were pulverised using a Labtechnics Ring

Mill. About 0.5 g of pulverised soil samples were digested with concentrated AR

grade nitric and perchloric acid at 100 °C for 30 min, 130 °C for 30 min and 200 °C

for 30 min in a block digester (Munksgaard and Parry, 2002) and analysed for total U

by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) using an Agilent


33

7500ce ICP-MS. Quality control samples included field duplicates, metal-spiked

field duplicates and lab blanks. Certified reference materials, AGAL-12 Biosoil,

Montana Soil (SRM 2710) and IAEA-Soil-7, were used to determine the percentage

recovery of U using this analytical method.

2.2.2 Culturing microbes from soil samples

To isolate U resistant microbes at RUM LAAs, all five replicate soil samples from

each site were cultured on solid Luria-Bertani (LB) – (Bacto-Tryptone, yeast extract

and sodium chloride) culture media plates. For each sample 10 g of soil was added to

5 mL of sterilized distilled water (SDW) and shaken to make slurry. One µL of this

slurry was then mixed with 100 µL of SDW and was poured and spread plated onto

the culture media plates spiked with uranyl nitrate (AR grade) resulting in low (3

ppm), medium (250 ppm), high (600 ppm) and very high (1500 ppm) concentrations

of U. These concentrations were similar to those found in previous studies at these

sites (Akber et al., 2011b). Media without any uranyl nitrate i.e., zero (0 ppm) U

concentration was also used. Plates were incubated at 37 °C for 48 hours and then

stored at 4°C. For each plate, colonies were counted and morphological data were

recorded for all microbial colonies.

2.2.3 Identification of cultured isolates

Each colony from mother plate was sub cultured in 2 ml of LB broth at 30 °C

overnight. Cultures were centrifuged at 10,000 rcf to get microbial pellets. Media

was poured off and Genomic DNA was isolated from pellets using a MoBio

UltraCleanTM

microbial DNA isolation kit (Geneworks, SA, Australia) and stored at

–20 °C till further use. DNA was extracted from one representative of each of the


34

morphologically different colonies. All steps were according to the manufacturer’s

protocol with the modification of heating the preps at 65 °C for 10 minutes in a water

bath for increased lysis before vortexing the MicroBead Tubes. Bacterial 16S

ribosomal RNA genes were amplified in the polymerase chain reaction (PCR) using

gene specific primers (Buchholz-Cleven et al., 1997). For amplification of

eukaryotes, the intergenic spacer region (ITS) was amplified using ITS1 and ITS4

primers (White et al., 1990). PCR reactions (50 µL) contained 10 ng of DNA

template, 0.4 µM of each primer, 0.2 mM (each) dNTP, 1.5 mM MgCl2 and 0.2 U of

Taq DNA polymerase (kappa Robust), in the buffer supplied by the manufacturer.

Amplifications were performed using a Labnet Multigene Thermal Cycler (Labnet

international, Inc. Edison, NJ, USA) and included an initial denaturation at 94 °C for

5 min, followed by 35 cycles of 92 °C/1 min, 57 °C/1 min, 72 °C/2 min and a final

extension at 72 °C for 10 min. Amplification products (4 µL) were separated by

electrophoresis in a 1% agarose gel in Tris–borate–EDTA buffer and visualized

under UV light after staining with ethidium bromide (0.5 mg/mL). A 1 kb plus DNA

ladder (Invitrogen, CA, USA) was used as a size standard for electrophoresis of PCR

products.

PCR products of approximately 1.5 kbp were purified using the QIAquick

PCR

purification kit (Qiagen, Hilden, Germany) to remove salts, polymerase and excess

primers and nucleotides following the manufacturer’s instructions. The DNA was

recovered in 30 µL of buffered sterile water, pH 7–8. Sequencing reactions for PCR

products were compiled using the Big Dye terminator version 3.1 sequencing Ready

Reaction kit (Applied Biosystems, Foster City, CA, USA). One representative of

each of the morphologically different colonies was sequenced. The sequencing

reactions contained 4 μl of either forward or reverse primer (0.8 pM/μl), 1 μl of big


35

dye terminator enzyme, 3.5 μl of 5x sequencing buffer and 5–10 ng of template DNA

in a 20 μl reaction. The sequencing reactions included an initial denaturation step of

94 °C for 5 min, followed by 35 cycles of 96 °C/10 sec, 50 °C/5 sec and 64 °C/4

min. Sequencing reaction products were then precipitated and sequenced in both

directions using a Genetic Analyzer 3130xl (Applied Biosystems, Foster City, CA,

USA). The consensus sequence for each individual was obtained by editing and

reconciling the forward and reverse sequences using MacVector, version 10.5

(MacVector, Inc., Cary, NC, USA). Close relatives and phylogenetic affiliation of

the sequences were checked using the BLAST search program (Altschul et al., 1997)

at the National Centre for Biotechnology Information (NCBI, http://www.ncbi.nlm.-

nih.gov/). Within a genus, microorganisms with 99% similarity in GAP analysis

were considered the same species (Stackebrandt and Ebers, 2006).

2.2.4 Statistical Analysis

Microbial communities that grew on media plates spiked with no U were compared

across field U concentration categories. Permutational analysis of variance was

calculated using PERMANOVA+ in PRIMER-E, (Plymouth Routines in

Multivariate Ecological Research, version 6) (Primer-E Ltd, United Kingdom). The

microbial community data were transformed (square-root) and resemblance among

samples was calculated using Bray Curtis similarity. This resemblance matrix was

then used for PERMANOVA+ analysis.


36

2.3 Results

2.3.1 Soil uranium concentrations

Soil U concentrations were measured to verify the choice of sites that had originally

been selected on the basis of historical chemistry data. Using our measured values

(Table 2.1), some of the sites originally designated as high or very high actually had

low concentrations of U. These sites were re-allocated on the basis of the U

concentrations in the present study. Sites categorised as low had U concentrations of

2–20 ppm, medium sites had 200–400 ppm, high had 500–900 ppm and very high

had > 900 ppm (Table 2.1). Uranium concentrations in duplicate samples had relative

standard deviation in the range of 0.1–0.2% and the U spike recovery was 92%. The

blanks showed U concentrations below the detection limit of 0.1 ppm and the percent

recovery of U from AGAL-12 Biosoil, Montana Soil (SRM 2710) and IAEA-Soil-7,

was 99%, 94%, and 87% respectively, indicating that the expected recovery of U in

soil samples was 87%–99%.

2.3.2 Soil microbes and the effect of uranium concentrations in soil

Bacteria were recovered on all the soil slurry culture plates except those spiked with

very high U (1500 ppm), regardless of the field soil U concentrations. That is, even

soil with very high field concentrations of U contained no bacteria that could grow at

U concentrations of 1500 ppm. Using data based on culture plates without added

uranium, there was no overall difference in the microbial community composition

despite the fact that these microbes were isolated from the soils with different field

concentrations of U based on number and type of colony forming units (CFU)

(PERMANOVA+, P = 0.695).


37

2.3.3 Identification of bacteria and fungi isolated from soil extracts

Bacillus was the most abundant bacterial genus isolated in this study. The genera

Lysinibacillus, Paenibacillus, Klebsiella and Chryseobacterium were consistently

cultured along with Bacillus, but at much lower levels (Table 2.2). There were nine

species of Bacillus, four of which were a 99–100% match to a species in the

database: B. cereus, B. mycoides, B. subtilis and B. megatarium. There were four

Lysinibacillus species with 100% similarity to more than one Lysinibacillus species

and hence could only be classified to genus. Four Klebsiella species with 99%

similarity and two Paenibacillus species with 100% similarity were isolated. Fungi

present were identified as Aspergillus terreus (100% similarity), Aspergillus flavus

(100% similarity), Cryptococcus laurentii (100% similarity), Penicillium

verruculosum (99% similarity), Curvularia sp. (100% similarity), Paecilomyces sp.

(100% similarity) and Alternaria sp. (100% similarity). For fungi, the most abundant

genus was Aspergillus. It was not known if the fungi in situ were vegetative or in

spore form.

Table 2.2 Mean colony counts for bacterial genera growing on Luria-Bertani (LB)

plates with different uranium concentrations. Data represents the mean of

90 samples (18 sites x 5 sub-samples) for each uranium concentration.

Bacterial genera

Uranium concentrations in media (ppm dry wt.)

No (0) Low (3) Medium

(250) High (600) Very High

(1500)

Mean colony counts ± SD





Bacillus 49 ± 22 50 ± 24 52 ± 31 39 ± 19 0

Paenibacillus 6 ± 19 9 ± 28 7 ± 25 2 ± 17 0

Lysinibacillus 4 ± 9 5 ± 9 3 ± 3 1 ± 3 0

Klebsiella 0 2 ± 1 0 0 0

Microbacterium 0 0 1 ± 8 0 0

Chryseobacterium 0 ± 1 1 ± 1 1 ± 1 1 ± 1 0


38

2.3.4 Soil microbes and response to uranium in Luria-Bertani (LB) media

Since there was no apparent effect of field soil U concentrations on the cultivable

microbial communities, the bacterial count data for low, medium, high and very high

soil U categories were pooled. For all these soil categories, the number of Bacillus

colonies was similar at no (0 ppm), low (3 ppm) and medium (250 ppm) U

concentration added to the culture media, with a decrease at high (600 ppm) and no

growth at very high (1500 ppm) U concentration in LB plates (Table 2.2).

Lysinibacillus and Paenibacillus species were most prevalent on LB plates

containing 3 ppm U and their colony count decreased as the U concentration rose to

600 ppm. Klebsiella species were only present on 3 ppm U plates (Table 2.2).

For all soil extracts, regardless of their field concentrations of U, LB plates spiked

with very high U concentrations (1500 ppm) supported the growth of fungi, but no

bacteria. Furthermore, fungi were not isolated from media plates with zero, low,

medium and high U concentrations.

2.4 Discussion

Microbes isolated from RUM LAAs grew in the presence of high concentrations of

soluble and hence potentially bioavailable U added to the culture plates. The

Bacillus species grew at U concentrations of 600 ppm and less. These findings are in

partial agreement with Ringelberg et al. (2004) who isolated Bacillus at U

concentrations of 200 to 20,000 ppm of “yellow cake” or U3O8. This difference

between the two studies may be because the uranyl nitrate I used in the culture media

is highly soluble and may therefore be more bioavailable than relatively insoluble


39

U3O8 (Bleise et al., 2003; Gadd and Fomina, 2011). Thus, bioavailability of U in

culture media may have a significant bearing on the microbes isolated.

Bacillus subtilis, B. sphaericus, B. cereus, B. megaterium and Lysinibacillus sp. grew

on plates containing U in the form of uranyl nitrate. However, the occurrence of

these genera decreased with increasing U concentration. Strains of Bacillus and

Lysinibacillus are known to survive at high U concentrations because they can

selectively accumulate and reversibly bind metals such as U, Al and Cd from

contaminated waters (Gorman-Lewis et al., 2005; Selenska-Pobell et al., 1999).

Resistance in Paenibacillus is conferred when U(VI) is precipitated to uranyl

phosphate within the cell wall (Reitz et al., 2008). The decrease in Bacillus,

Lysinibacillus and Paenibacillus species with increasing U suggests that not all

strains at RUM LAAs have U resistance. Those few colonies of Bacillus,

Lysinibacillus and Paenibacillus that persisted and grew at the high U concentrations

may represent resistant strains.

Though some species belonging to Bacillus, Paenibacillus and Lysinibacillus are

resistant to U contamination, these species are not specific to U-contaminated soils

rather they occur at a wide range of soil habitats (Gardener, 2004; Mohamed et al.,

2006)

At our study sites, the fungi Aspergillus, Cryptococcus and Penicillium were isolated

on plates containing 1500 ppm U. Aspergillus, Cryptococcus and Penicillium are

known to be U resistant (Hefnawy et al., 2002; Nakajima and Sakaguchi, 1986;

Wang et al., 2010a). These fungal genera can take-up and remove U from

uraniferous environments by binding uranyl ions to phosphate and carboxyl groups


40

in the cell wall, (Bhainsa and D’Souza, 1999; Gadd and Fomina, 2011; Wang et al.,

2010a) and hence may be suitable for bioremediation at RUM LAAs.

The recovery of only fungi at the very high U concentration indicates that fungi can

grow under extremely high concentrations of U and are more resistant than bacteria.

A number of studies have indicated that microbial community respond to heavy

metals such as Cd, Cu, Ni, Pb and Zn by a shift from bacteria to fungi (Khan and

Scullion, 2002; Wang et al., 2010b) and an increase in the ratio of fungi to that of

bacteria is reported with increasing metal concentrations such as Zn, Cu and Cr

(Akerblom et al., 2007; Rajapaksha et al., 2004). While these studies have reported a

shift in microbial community from bacteria to fungi in response to other heavy

metals, I have shown that this shift can also occur with U. However, growth of fungi

below 1500 ppm of U might have been prevented by the presence of bacteria as some

bacteria secrete fungicide (Thimon et al., 1992; Zhao et al., 2011) and fungi may

have outcompeted bacteria at 1500 ppm of U due to their resistance to U. Absence of

fungi below 1500 ppm of U may not be due to high pH (7–7.5) of the LB media

because fungi grew at 1500 ppm of U in the same high pH media when bacteria were

absent. The community shift from bacteria to fungi under very high U concentration

may disrupt vital processes carried out by soil bacteria like nitrification and nitrogen

fixing and transfer of nutrients to plant root system if fungi do not compensate for the

loss. This might affect plant growth and hence remediation of the site.

Our results indicate that regardless of the different field concentrations of U in soil at

RUM LAAs, there was no apparent difference in cultivable bacteria isolated from

these different soils. However, these same soils all harboured fungi that grew in

culture media spiked with U concentrations that were above the concentration that


41

would support bacterial growth. This shift from bacteria to fungi at high

concentrations of U that was observed in culture plates but not in the field, may

partially be explained by differences in bioavailability. It is possible that the soil

microbial communities were not different across different field acid extractable U

concentrations because the U present in RUM LAAs soils is not as readily

bioavailable as in the U spiked media. At RUM LAAs other workers have shown that

the U is tightly bound to soil components predominantly composed of mineralised

and crystalline material such as silicates and other refractory materials making it

relatively unavailable to biota (Medley, 2007). In Medley’s study, the total strong

acid extractable U concentration at the Magela Land Application Area (MLAA) was

463 ppm, but the bioavailable fraction extracted using 1 M magnesium chloride was

only 0.09 ppm, and the 1 M HCl extraction was only 0.15 ppm. Acid soils with low

adsorptive potential increase mobility and hence bioavailability of U (Shahandeh and

Hossner, 2002) but RUM LAAs soils have high adsorptive capacity for radionuclides

(Chartres et al., 1991) and the irrigated water is alkaline (Noller, 1991). Both of these

factors point to low U bioavailability at these sites, consistent with Medley’s 2007

data. Organic matter can influence U mobility and bioavailability in soils because

organic bound U is generally less bioavailable (Hogan, et al., 2005; Suzuki and

Banfield, 1999). On the other hand, organic matter may also increase U

bioavailability because soluble U complexes can form with organic compounds in

the presence of fulvic acid (Vandenhove et al., 2010). In this system however,

organic matter may not be a dominant factor because these soils are considered

deficient (< 1%) in organic matter (Chartres et al., 1991).

Lack of difference in the microbial community with changing soil U concentrations

may also be due to the fact that only about 1% of the microbial community can be


42

isolated from soil using conventional culturing methods (Bollmann et al., 2007;

Ferrari and Gillings 2009; Nichols et al., 2008). Therefore, there is a possibility that

certain bacterial species that respond to differences in soil U concentrations at RUM

LAAs may have been missed by culturing technique.

2.5 Conclusions

As predicted, microbes isolated from RUM LAAs showed resistance to the highly

soluble form of U added to culture media. These microbes might have the potential

to bioaccumulate, precipitate or bind U and therefore bioremediate U contaminated

soils and waters. My findings also suggest that when the U concentration exceeds the

binding capacity of the soil particles resulting in increased bioavailable U

concentration, fungi might outcompete bacteria leading to a fungi dominated

community that includes Aspergillus, Penicillium and bacterial sp. Bacillus. These

genera are known to bind U which may reduce its bioavailability to a level that is

tolerated by these organisms. In addition to lower bioavailability of soil U at RUM

LAAs, the absence of an effect with changing soil U concentration may also be due

to the limitation of culturing technique to isolate only < 1% of the microbial

community. Therefore, I analysed the soil bacterial community using the culture

independent pyrosequencing technique. To assess changes in the soil bacterial

community with varying soil U and physicochemical variables at RUM LAAs, I first

analysed the soil U concentration and physicochemical characteristics of the soil in

chapter 3 and measured the effect of these physicochemical parameters on the soil

bacterial community structure in chapter 4.

CHAPTER 3

PHYSICOCHEMICAL CHARACTERISTICS OF

RANGER URANIUM MINE LAND

APPLICATION AREAS SHOW SIGNIFICANT

SEASONAL, TEMPORAL AND SPATIAL

DIFFERENCE

Chapter 3. Physicochemistry of RUM LAAs

44

3.1 Introduction

Ranger Uranium Mine (RUM) receives monsoonal rainfall, with 700–2200 mm

(average 1540 mm) falling in the wet season (November–April) which makes water

management a major issue at the mine. Water from the site is stored in retention

ponds, RP1 and RP2. RP1 is a part of the sediment control system on the mine-site.

RP1 water is discharged into Magela Creek during most wet seasons. RP2 stores

runoff water from the low-grade ore and waste stockpiles and other areas on the

mine-site. Since 1985, water stored in RP2 during the wet season has been disposed

of onsite by irrigation on to Land Application Areas (LAAs) during subsequent dry

season. The Magela Land Application Area (MLAA) was the first to be established

using the spray irrigation method of unpolished (raw) pond water (Table 3.1). As a

result of the increasing area occupied by waste and low-grade ore stockpiles,

additional LAAs were developed over time to manage the rising volume of water

(Table 3.1). Presently there are eight LAAs being used for irrigation having a total

area of 338 ha (Table 3.1). Of these, Magela, Magela Extension, RP1 Extension,

Jabiru East and Corridor Creek areas receive spray irrigation of unpolished RP2 pond

water (Table 3.1). From 1995, RP1, Djalkmara and Djalkmara Extension LAAs have

received polished (wetlands filtered) water from RP1 and Djalkmara wetlands. The

concentration of metals and radionuclides varies between LAAs largely due to the

difference in length of time water has been applied (year it was commissioned) and

quality of the water being irrigated to these LAAs. Metals and radionuclides

concentrations at different LAAs are also variable due to the difference in distance of

these LAAs from the source of irrigation (e.g., distance from sprinkler head) and

method of irrigation. Due to the influence of water quality and year of commission


45

on metal and radionuclide concentration, Magela LAA is expected to contain the

highest concentrations of metals.

Table 3.1 Ranger Uranium Mine Land Application Areas (adapted from Akber et

al., 2011a)

Land Application Area and abbreviation

Water quality

Irrigation method

Total area (ha)

Year commissioned

Magela (MLAA) Unpolished RP2 water

Spray 33 1985

Magela Extension (MLAA-EXT))

Unpolished RP2 water

Spray 20 1994

RP1 Polished RP2 water Flood 46 1995

Djalkmara (DLAA) Polished RP2 water Flood 18 1997

Djalkmara Extension (DLAA EXT)

Polished RP2 water Flood 20 1999

Jabiru East (JELAA) Unpolished RP2 water

Spray 52 2006

RP1 Extension (RP1 EXT) Unpolished RP2 water

Spray 8 2006

Corridor Creek (CCLAA) Unpolished RP2 water

Spray 141 2007

Unpolished = raw RP2 water

Polished = water filtered through wetlands

3.1.1 Soil characteristics at Ranger Uranium Mine Land Application Areas

Generally the A horizon (0–20 cm) of soil profile at RUM LAAs consists of loose

sandy surface soils with ferruginous nodules and organic matter accumulation. The

B0/B1 horizon (20–50 cm) is composed of yellow sandy soils with ferruginous

nodules. The B2/B3 horizon (50–100 cm) is massive or nodular ferricate layer while

C horizon (50–150 cm) is extremely weathered lateritic clay-sand with the

proportion of schist increasing with depth (Hollingsworth et al., 2005). All sites are

classified as well drained to excessively drained soils; as mean values of hydraulic


46

conductivity of B and C horizons fall around 1 m/day and deeper strata around 0.5

m/day. The soils have low soluble salt contents, acidic pH and low concentration of

secondary iron and manganese oxides (Chartres et al., 1991). Soils at RUM LAAs

generally have high gravel content (20–50% of soil mass) composed of quartz and

ferruginous material. The soils are low in clay content, usually < 20% and deficient

in organic matter (< 1%) (Chartres et al., 1991).

The cation exchange capacities (CEC) of the soils are extremely low (< 10 cmol

[+]/kg) with no detectable anion exchange capacity (Willett et al., 1993). Although

the soil has limited capacity to assimilate major cations, manganese (Mn), uranium

(U) and radium (Ra) present in RP2 water are likely to be taken up in the soil

through high affinity and adsorption reactions possibly mediated by the ferruginous

gravels (Chartres et al., 1991; Willett and Bond 1995).

3.1.2 Uranium geochemistry at the Land Application Areas

Uranium in the RP2 water is under oxidising to mildly reducing conditions. Under

such conditions U exists in solution; predominantly as uranyl ion (UO2+2

) or as

soluble carbonate complexes (UO2)2CO3(OH)3−

, UO2CO3, UO2(CO3)22−

,

UO2(CO3)34−

and possibly (UO2)3(CO3)66−

in carbonate containing waters at near

neutral or basic higher pH (Ciavatta et al, 1981; Duff and Amrhein, 1996; Grenthe et

al., 1992). The uranyl species may also form complexes with sulfate, fluoride and

possibly chloride where concentrations of these anions are high (Grenthe et al.,

1992;). At a sulfate level of 100 ppm, UO2SO4 may be a significant species up to pH

7 (Langmuir, 1978). Uranyl hydroxy complexes such as UO2(OH)+

and

(UO2)3(OH)5+

are also formed in carbonate-depleted alkaline water. In RP2 water,


47

the sulfate concentration is approximately 700–850 ppm but the pH ranges from 7–9.

This suggests that the U may predominantly be present as the uranyl hydroxy

complexes such as UO2(OH)+

and (UO2)3(OH)5+

in RP2 water.

Soil U can be sorbed onto soil particles or it can occur in complexed, precipitated

and reduced forms. These different forms affect the mobility and fate of U in the soil

environment (Zhou and Gu, 2005). The formation of U complexes with ligands

present in the RP2 water will influence its ability to be adsorbed to the soil particles

in the LAAs. Carbonate complexing results in reduced adsorption of U leading to its

release from soils (Pabalan and Turne, 1997; Waite et al., 1994) while soils have

greater affinity for positively charged uranyl hydroxy complexes (Echevarria et al.,

2001) – the complexes which are expected in RP2 water. Chemical fractionations

showed that U is not in exchangeable forms in the soils at RUM LAAs but reacted to

produce less mobile forms (Willett and Bond, 1998). Consequently, U is retained in

the surface 10 cm and is preferentially adsorbed to the fine earth and iron oxides in

the soil thereby effectively immobilizing the U before it can reach the regional

aquifers (Brown et al., 1998, Hollingsworth et al., 2005). Uranium could be mobile

in the sandy soils present in the lower slope sites in the MLAA and RP1LAA, when

applied at high concentrations (Hollingsworth et al., 2005; Willett and Bond, 1995).

The aim of this study was to measure the effect of time and season on soil

physicochemical parameters, particularly U and other major solutes applied in

irrigation water. Data reported in the literature indicate that major radionuclides and

divalent cations present in irrigation water are efficiently retained by the soils at

RUM LAAs, and the loss of these radionuclide and divalent cations off site after the

wet season rainfall is minimal (Chartres et al., 1991; Hollingsworth et al., 2005;


48

Willett and Bond, 1998). In light of this, I predicted that there would not be a

significant change in soil physicochemical properties between years and between wet

and dry seasons. Similarly, I also hypothesized that U concentrations would not

differ significantly between years or seasons. To address these hypotheses, I

measured soil physicochemical parameters and U concentrations at the end of wet

and dry seasons for two consecutive years and analysed the temporal and seasonal

differences in soil physicochemical properties.


3.2.1 Selection of sampling sites

Soil samples were taken from 18 selected sites at RUM LAAs (Table 3.2, Figure

2.1). The selection was mainly based on the distance of these sites from the source of

irrigation, year commissioned, the quality of irrigated water and method of irrigation

(Table 3.1) so as to determine their effect on the U and other solute concentrations in

the soil. Historical soil chemistry data were used to categorise sites as low, medium,

high and very high U sites (Akber et al., 2011b). Approximate monthly pond water

disposal volumes (ML), average solute concentration (µg/L) applied in irrigation

water and total amount (g/ha) of solutes applied in irrigation water at RUM LAAs for

dry 2008 and dry 2009 is given in Tables 3.3, 3.4 and 3.5 respectively. Water Table

at RUM LAAs was on average 5 m (Hollingsworth et al., 2005). Soil sampling was

carried out using a core sampler with diameter 5 cm and depth 10 cm (Chan et al.,

2006) as U is known to be retained in the top 10 cm of the soil profile at RUM LAAs

(Hollingsworth et al., 2005). Five field replicates were collected within 1 m2 area

from 18 sites in RUM LAAs designated as low, medium, high and very high U


49

concentrations. An additional soil sample was taken from each study site to measure

soil moisture content and bulk density. Sampling was done at the end of wet and dry

seasons of 2008–09 (year 1) and 2009–10 (year 2). Ninety (18 sites x 5 subsamples)

samples were collected at each sampling time and transported to the laboratory for

physicochemical analyses.

Table 3.2 Study sites at Ranger Uranium Mine Land Application Areas

Table 3.3 Approximate monthly pond water disposal volumes (ML) for dry season

1 and dry season 2 at Ranger Uranium Mine Land Application areas.

Magela and Magela Extension Land Application Areas were not irrigated

during the study (ERA 2009; ERA 2010, ERA, 2011).

Land Application Areas

Dry 1

Dry 2

RP1 75 12 Jabiru East 15 87 Djalkmara 26 0 Corridor Creek 267 0

Dry 1 = April–October, 2008,

Dry 2 = April–October, 2009

Uranium category Land Application Area

Site Code

Low (2–20 ppm) Corridor Creek (CCLAA) CCLAA-076 Djalkmara Extension (DLAA EXT) DLAA-177 EXT Djalkmara (DLAA) DLAA-185 RP1 RP1-144 Magela Extension (MLAA-EXT) MLAA-EXT-121 Jabiru East (JELAA) JELAA-020 Djalkmara (DLAA EXT) DLAA-170 EXT Medium (200–400 ppm) Djalkmara (DLAA) DLAA-222 Corridor Creek (CCLAA) CCLAA-036 RP1 RP1-138 Jabiru East (JELAA) JELAA-001 High (500–900 ppm) RP1 RP1-134 Djalkmara Extension (DLAA EXT) DLAA-157 EXT Djalkmara (DLAA) DLAA-228 Djalkmara (DLAA) DLAA-227 Magela Extension (MLAA-EXT) MLAA-EXT-101 Very high (> 900 ppm) Magela Extension (MLAA-EXT) MLAA-EXT-106 Magela (MLAA) MLAA-032


50

Table 3.4 Average total solute concentration (µg/L) applied in Retention Pond 2

irrigation water during dry season 1 and dry season 2 (ERA 2009; ERA

2010, ERA, 2011)

Solutes

Dry 1

Dry 2

Al 33.6 29.6

Cu 2.46 3.22

Fe 173 200

Mn 25.7 50.4 Pb 0.33 0.26 U 4641 6410 SO4

2- 748000 1100000

Ca 30400 44600



Table 3.5 Total solutes (g/ha) applied in Retention Pond 2 irrigation water at

Ranger Uranium Mine Land Application Areas during dry season 1 and

dry season 2. Magela and Magela Extension Land Application Areas

were not irrigated during the study (ERA 2009; ERA 2010, ERA, 2011).

Solutes Season


RP1 Jabiru East Djalkmara Corridor Creek

Al Dry 1 54.8 9.7 23 63.6 Dry 2 7.7 49.5 0 0 Cu Dry 1 4.0 0.7 1.7 4.7 Dry 2 0.8 5.4 0 0 Fe Dry 1 283 50 119 328 Dry 2 52.2 335 0 0 Mn Dry 1 41.9 7.4 17.6 48.6 Dry 2 13.2 84.4 0 0 Pb Dry 1 0.5 0.1 0.2 0.6 Dry 2 0.1 0.4 0 0 U Dry 1 7570 1340 3180 8790 Dry 2 1670 10700 0 0 SO4

2-* Dry 1 1220000 216000 511000 142000

Dry 2 28700 1840000 0 0 Ca Dry 1 49600 8780 20800 57600 Dry 2 11600 74600 0 0

Dry 1 = April–October 2008, Dry 2 = April–October, 2009

0 = no irrigation

* Balance of SO4

2- is MgSO4 (Willet et al., 1993; van Dam et al., 2010)


51

3.2.2 Analysis of soil physicochemical parameters at Ranger Uranium Mine Land

Application Areas

Soil physicochemical parameters at RUM LAAs were analysed as follows:

3.2.2.1 Acid extractible metal and sulfur analysis of soil

For acid extractable metal analysis [Sulfur (S), iron (Fe), calcium (Ca), aluminium

(Al), copper (Cu), zinc (Zn), thorium (Th), nickel (Ni), lead (Pb), Mn and U],

samples were sieved to < 2 mm size fraction and oven dried overnight at 60 °C.

Dried soil samples were pulverised using a Labtechnics Ring Mill. About 0.5 g of

pulverised soil samples were digested with concentrated AR grade nitric and

perchloric acid at 100 °C for 30 min, 130 °C for 30 min and 200 °C for 30 min in a

block digestor (Munksgaard and Parry, 2002) and analysed for total metals by

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) using an Agilent 7500ce

ICP-MS. Sulfur was analysed by Inductively Coupled Plasma Optical Emission

Spectrometry (ICP-OES).

3.2.2.2 Soil total organic carbon analysis

Total organic carbon of soil samples was measured at the Australian Institute for

Marine Sciences (AIMS), Townsville, Australia. Samples were acidified with HCl

and heated gently to decompose any carbonate carbon (inorganic carbon) and the

residue was then analysed for total organic carbon (TOC) and total nitrogen (TN)

using a Shimadzu TOC-V Total Organic Carbon Analyser with a SSM-5000A Solid

Sample Module and TNM-1 Total Nitrogen Measuring Unit. Samples were


52

combusted at 950 °C, CO2 was detected by Non-Dispersive Infra-Red (NDIR) and

nitrogen by chemiluminescence (CLD).

3.2.2.3 Measurement of soil pH

Two g of soil samples were added to 15 ml falcon tubes. Ten ml of reverse osmosis

(RO) water was added to the samples and samples were shaken for an hour on a

shaker. Samples were left for half an hour for settling and pH was recorded with pH

meter.

3.2.2.4 Measurement of soil bulk density

Bulk density of soil was determined using core samples (surface cores), which were

collected by driving a metal corer into the soil at the desired depth and horizon. The

samples were then dried in an oven at 105 °C, weighed and the bulk density was

subsequently determined according to the following formula:

3.2.2.5 Measurement of soil moisture (volumetric soil water content)

Volumetric soil water content (q) was determined by weighing collected soil samples

of a known volume before and after drying. Samples were placed in a conventional

drying oven, at 105 °C (220 °F) for 24 hours. Volumetric soil water content (q) was

determined as follows:


53

Where:

3.2.3 Statistical analysis

The data were analysed using Primer 6 version 6.1.12 software (Primer-E Ltd,

United Kingdom). Mean value of 5 subsamples collected from each site was used for

statistical analysis. Prior to taking mean, the significance of differences were tested

statistically. Mean value was used because the results obtained were easy to interpret,

however, it did not affect the P value for test of significance. Data were normalized

and resemblance matrices were calculated using Euclidian distance. Resemblance

matrices were used for PERMANOVA+ analysis, and to generate Multi-

Dimensional Scaling (MDS) plots (Kruskal, 1964). PERMANOVA analysis was

used to test the significance of temporal and seasonal change in soil physicochemical

variables. PERMANOVA+ was also used for the analysis of seasonal and temporal

change in soil uranium concentrations because it makes less restrictive assumptions

about the data than analysis of variance (ANOVA) (Clarke and Warwick, 2001).

Significance of difference in physicochemical data between low and medium, low

and high, low and very high, medium and high, medium and very high and high and

very high U categories was tested using pairwise PERMANOVA+. Year 1 soil pH

was measured by a non-calibrated pH meter so the data was not reliable. However,

PRIMER analysis using Year 2 pH data showed that soil pH was not strongly

correlated with the changes in bacterial community structure. So soil pH was


54

excluded from the analysis because of above mentioned problems with the accuracy

of the data and weak correlation.

3.3 Results

3.3.1 Comparison of year 1 and year 2 soil samples based on physicochemical

variables

Soil physicochemical variables at RUM LAAs differed significantly between year 1

and year 2 (p < 0.05, Table 3.6) i.e., based on physicochemistry, soil samples

collected in dry season 1 were significantly different from those collected in dry

season 2 and soil samples collected in wet season 1 were significantly different from

soil samples collected in wet season 2. Moreover, sampling sites, within low,

medium, high and very high U categories were significantly different (p < 0.05,

Table 3.6). However, there was no interaction between years and U categories,

between years and seasons or between years and sites nested in U categories based

on soil physicochemistry (p > 0.05, Table 3.6). The significant difference between

year 1 and year 2 physicochemistry was evident in MDS plots as year 1 soil samples

scattered away from year 2 soil samples except for MLAA-032 (Figure 3.1a-d).

3.3.2 Comparison of the dry and the wet season soil samples based on

physicochemistry

In addition to significantly different year 1 and year 2 soil samples, there was also a

significant difference between the dry and the wet season soil samples (p < 0.05,

Table 3.6) based on soil physicochemistry. There was however, no interaction

between seasons and U categories, or between seasons and sites nested in U

categories (p > 0.05, Table 3.6). The dry season samples scattered away from the wet


55

season samples in the MDS plot showing their difference except for MLAA-032

(Figure 3.1a-d). As compared to other sites, a higher variation in physicochemistry at

EDJ-228 was due to the differences in TOC, Zn and Ca.

Table 3.6 PERMANOVA table of results based on soil physicochemical parameters

(S, Fe, Ca, Al, Mn, Cu, Zn, Th, Ni, Pb, U, TOC, TN, moisture and bulk

density) at Ranger Uranium Mine Land Application Areas showing p-

values for tests of significance of difference between year 1 and 2, wet and

dry seasons, U categories, site nested in U and interactions of these factors

(analysis was based on the mean of 5 sub samples from each Land

Application Area).

Source df SS MS Pseudo-F P(perm) Unique perms

U- 3 309.8 103.27 3.0714 0.001 998 Ye 1 9.6384 9.6384 2.3581 0.029 998 Se 1 19.57 19.57 4.1651 0.006 998 Si(U-) 14 470.71 33.622 6.5962 0.001 999 U-xYe 3 15.419 5.1398 1.2575 0.206 995 U-xSe 3 19.299 6.4328 1.3691 0.156 997 YexSe 1 10.67 10.67 2.0934 0.082 997 YexSi(U-) 14 57.223 4.0873 0.80188 0.88 998 SexSi(U-) 14 65.781 4.6986 0.9218 0.707 997 U-xYexSe 3 8.9048 2.9683 0.58233 0.917 999 Res 14 71.361 5.0972 Total 71 1065

U- = Low, medium, high and very high U categories

Ye = Year 1 and year 2

Se = Wet and dry seasons

Si(U-) = Sites nested in U categories

U-xYe = Interaction between U categories and years

YexSe = Interaction between years and seasons

YexSi(U-) = Interaction between years and sites nested in U categories

SexSi(U-) = Interaction between seasons and sites nested in U categories

U-xYexSe = Interaction between U categories, years and seasons


56

a)

b)

Figure 3.1 Multi-dimensional scaling (MDS) plots based on physicochemical

variables (Fe, Ca, Cu, Zn, Th, Al, Ni, Pb, S, U, Mn, TOC, TN, moisture

and bulk density) of soils at Ranger Uranium Mine Land Application

Areas. a) Low U level sites b) Medium U level sites c) High U level sites

and d) Vey high U level sites.


57

c)

d)

Figure 3.1 Multi-dimensional scaling (MDS) plots based on physicochemical

variables (Fe, Ca, Cu, Zn, Th, Al, Ni, Pb, S, U, Mn, TOC, TN, moisture

and bulk density) of soils at Ranger Uranium Mine Land Application

Areas. a) Low U level sites b) Medium U level sites c) High U level sites

and d) Vey high U level sites.


58

3.3.3 Comparison of low, medium, high and very high uranium categories sites

based on physicochemistry

Physicochemical parameters of soils at low, medium, high and very high U

categories were significantly different (p < 0.05, Table 3.6). This difference was

particularly significant between low U sites and all the other U categories sites. Low

and medium, low and high, and low and very high U categories differed significantly

(p < 0.05, table 3.7). But the difference between medium and high (p > 0.05, Table

3.7), medium and very high (p > 0.05, Table 3.7) and high and very high U sites was

not significant (p > 0.05, Table 3.7). Principal coordinate analysis plot of study sites

generated using physicochemical data showing different U categories also indicated

that most of the low U sites clustered together separately from the rest of the U

categories, while sites in the medium, high and very high U categories were

distributed randomly and there was no separation among samples based on U

categories (Figure 3.2). Some sampling sites within these different U categories were

also significantly different from each other (p < 0.05, Table 3.6).

Principal coordinate analysis of study sites showing the distribution of samples

collected at four sampling times (year 1 dry and wet season, year 2 dry and wet

season) indicated that the physicochemistry of these samples was different for study

sites DLAA-222, RP1-144, JELAA-020, DLAA-185, DLAA-170 EXT, DLAA-222,

RP1-138, JELAA-001, CCLAA-036, RP1-134, DLAA-228, MLAA-101-EXT,

MLAA-106-EXT, and MLAA-032. Study sites CCLAA-076, DLAA-177 EXT,

DLAA-157 EXT, DLAA-227 and MLAA-121-EXT were similar, since the samples

at these sites collected at four sampling times clustered together as compared to the

other sites (Figure 3.2).


59

Low U sites generally had higher moisture content as compared to medium, high and

very high U sites. Very high and some high U sites had higher U concentration,

TOC, TN, Mn and Ca. Medium U sites and some high U sites had higher values of

all the other physicochemical parameters like Fe, Cu, Zn, Th, Al, Ni, Pb, S and bulk

density. [Figure 3.2, Appendix A (Tables A-1–A-4)].

Table 3.7 Pairwise tests of all the combinations of low, medium, high and very

high U sites based on physicochemical parameters (S, Fe, Ca, Al, Mn,

Cu, Zn, Th, Ni, Pb, U, TOC, TN, moisture and bulk density) at Ranger

Uranium Mine Land Application Areas showing p-values for tests of

significance of difference between all pair combinations.

Unique Groups t P(perm) perms P(MC)

Low, Medium 1.9824 0.021 311 0.021 Low, High 2.1688 0.009 552 0.01 Low, Very High 2.0733 0.036 36 0.022 Medium, High 1.1924 0.179 126 0.24 Medium, Very High 1.3971 0.145 15 0.145 High, Very High 0.87685 0.705 21 0.574


60

Figure 3.2 Principal coordinate analysis plot generated from physicochemistry

resemblance matrix indicating the distribution of measured

physicochemical parameters among low, medium, high and very high U

sites at Ranger Uranium Mine Land Application Areas. Low U sites are

green, medium sites are black, high sites are yellow and very high U

sites are red.

3.3.4 Soil uranium concentrations between year 1 and year 2

Uranium concentrations at different sites at RUM LAAs also differed significantly

between year 1 and year 2 (p < 0.05, Table 3.8). Dry season 1 was significantly

different from dry season 2 (p < 0.05) but there was no significant difference

between wet season 1 and wet season 2 soil samples based on U concentrations (p >

0.05). Uranium concentrations at low U sites were similar in dry season 1 and dry

season 2 (Figures 3.3a and 3.4). At sites DLAA-170 EXT, CCLAA 036, RP1-138,

RP1-134, DLAA-157 EXT, MLAA-101-EXT, DLAA-227, MLAA-106-EXT and

MLAA-032 there was a decrease in U concentrations from dry season 1 to dry


61

season 2 (Figures 3.3b–d). In contrast, there was an increase in U concentration at

JELAA-001 from dry season 1 to dry season 2 (Figures 3.3b).

3.3.5 Seasonal effect on soil uranium concentrations

Based on soil U concentrations, the difference between dry season 1 and wet season

1 and dry season 2 and wet season 2 was non-significant (p > 0.05, Table 3.8).

However, U concentrations among low, medium, high and very high U categories

were significantly different. Specifically, there was a significant difference in U

concentrations between low and medium, low and high, and low and very high U

categories. But the difference was not significant between medium and high (p >

0.05, Table 3.9), medium and very high (p > 0.05, Table 3.9) and high and very high

U categories (p > 0.05, Table 3.9). Some sites within each U category were also

significantly different based on U concentrations (p < 0.05). Interactions between

years and seasons were also significant (p < 0.05, Table 3.8).


62

Table 3.8 PERMANOVA based on soil U concentrations at Ranger Uranium Mine

Land Application Areas showing p-values for tests of significance of

difference between year 1 and 2, wet and dry seasons, U categories, sites

nested in U and interactions of these factors (analysis was based on the

mean value of 5 sub-samples from each Land Application Area).

Unique Source df SS MS Pseudo-F P(perm) perms

U- 3 312.02 104.01 98.543 0.001 999 Ye 1 1.1023 1.1023 6.4439 0.021 996 Se 1 2.2005E-3 2.2005E-3 2.9613E-2 0.863 999 Si(U-) 14 14.776 1.0555 7.1372 0.001 999 U-xYe 3 7.4652E-2 2.4884E-2 0.14547 0.932 999 U-xSe 3 0.24698 8.2327E-2 1.1079 0.38 999 YexSe 1 0.72137 0.72137 4.878 0.031 997 YexSi(U-) 14 2.3948 0.17106 1.1567 0.408 997 SexSi(U-) 14 1.0403 7.4309E-2 0.50249 0.901 999 U-xYexSe 3 0.2346 7.82E-2 0.5288 0.706 999 Res 14 2.0703 0.14788 Total 71 334.86










Table 3.9 Pairwise tests of all the combinations of low, medium, high and very

high U sites at Ranger Uranium Mine Land Application Areas based on

soil U concentrations showing p-values for tests of significance of

difference between all pair combinations.

Unique Groups t P(perm) perms

Low, Medium 7.593 0.002 308 Low, High 16.005 0.003 562 Low, Very High 10.708 0.026 36 Medium, High 3.1382 0.052 126 Medium, Very High 3.2251 0.066 15 High, Very High 1.9631 0.144 21


63

a)

b)

Figure 3.3 Average soil uranium concentrations at Ranger Uranium Mine Land

Application Areas on a dry weight basis. Bars represent one standard

deviation a) Low uranium sites b) Medium uranium sites c) High

uranium sites d) Very high uranium sites.

0

5

10

15

20

25

30

35

40

45

CCLAA-076 DLAA-177EXT

DLAA-185 RP1-144 MLAA-121EXT

JELAA-020 DLAA-170EXT

Soil

ura

niu

m c

on

cen

trat

ion

s (p

pm

)

Study sites

Dry 1

Wet 1

Dry 2

Wet 2

0

100

200

300

400

500

600

700

800

900

1000

DLAA-222 CCLAA-036 RP1-138 JELAA-001

Soil

ura

niu

m c

on

cen

trat

ion

s (p

pm

)

Study sites

Dry 1

Wet 1

Dry 2

Wet 2


64

c)

d)

Figure 3.3 Average soil uranium concentrations at Ranger Uranium Mine Land

Application Areas on a dry weight basis. Bars represent one standard

deviation a) Low uranium sites b) Medium uranium sites c) High

uranium sites d) Very high uranium sites.

0

200

400

600

800

1000

1200

1400

RP1-134 DLAA-157EXT

DLAA-228 DLAA-227 MLAA-101EXT

Soil

ura

niu

m c

on

cen

trat

ion

(p

pm

)

Study sites

Dry 1

Wet 1

Dry 2

Wet 2

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

2400

MLAA-106 EXT MLAA-032

Soil

ura

niu

m c

on

cen

trat

ion

(p

pm

)

Study sites

Dry 1

Wet 1

Dry 2

Wet 2


65

Figure 3.4 Average soil uranium concentrations on a dry weight basis at low,

medium, high and very high uranium sites at Ranger Uranium Mine

Land Application Areas during different sampling times. Bars represent

one standard deviation.

3.3.6 Changes in soil sulfur, iron, calcium, aluminium, manganese and copper

concentrations between year 1 and year 2

Along with U, concentrations of some other solutes applied in the irrigation water

such as S, Fe, Ca, Al, Mn and Cu also differed significantly between year 1 and year

2 [p < 0.05, Appendix B (Table B-1–B-6)]. However, there was no significant

difference in soil Pb concentration [p > 0.05, Appendix B (Table B-7)]. There was a

decrease in the concentration of soil S, from dry season 1 to dry season 2 and wet

season 1 to wet season 2 at all the sites except JELAA-020, JELAA-001 and MLAA-

106 EXT [Appendix C (Figure C-1)]. Soil Fe and Ca concentration decreased from

dry season 1 to dry season 2 and wet season 1 to wet season 2 at all the sites except


66

JELAA-020 and JELAA-001 [Appendix C (Figure C-2 and C-3 respectively)].

Differences in soil Al, Mn and Cu between dry season 1 and dry season 2, and wet

season 1 and wet season 2 at different sites are presented in Appendix C (Figure C-4,

C-5 and C-6 respectively).

3.3.7 Seasonal change in soil sulfur, iron, calcium, aluminium, manganese and

copper concentrations

Concentrations of S, Fe, Ca, Al, Mn and Cu were also significantly different between

wet and dry seasons of both years [p < 0.05, Appendix-B (Table B-1–B-6)].

However, there was no significant difference in soil Pb concentration [p > 0.05,

Appendix B (Table B-7)]. There was a decrease in the concentration of soil S, Fe and

Ca from dry season 1 to wet season 1 and dry season 2 to wet season 2 at all the sites

[Appendix C (Figure C-1, C-2 and C-3 respectively)]. Differences in soil Al, Mn and

Cu from dry season 1 to wet season 1 and dry season 2 to wet season 2 at different

sites are shown in [Appendix C (Figure C-4, C-5 and C-6 respectively)].

3.4 Discussion

I predicted that soil U concentrations and other physicochemical variables (S, Fe, Ca,

Al, Mn, Cu, Zn, Th, Ni, Pb, U, TOC, TN, moisture and bulk density) of samples

collected in year 1 would not be significantly different from the samples collected in

year 2 at RUM LAAs. However, of the physicochemical variables applied in

irrigation water to soils at RUM LAAs, there was a significant difference in S, Fe,

Ca, Al, Cu, Mn and U concentration of soil samples collected in year 1 compared to

year 2, thus, my hypothesis was not supported.


67

One explanation for the measured differences in physicochemical nature of soil

between year 1 and year 2 may be changes in the amount of irrigation water applied

to RUM LAAs (ERA 2009; ERA 2010, ERA, 2011) and the variations in the amount

of rainfall during this study (Australian Bureau of Meteorology).

Irrigation water contains a range of solutes and these solutes have different fates in

RUM LAAs soils. Uranium, S in the form of SO42-

, Cu, Fe and Mn are the major

solutes present in the irrigation water. Lead and Ca are also present in small amounts.

Thus, Irrigation water may increase the concentrations of these solutes in RUM

LAAs soils. Uranium applied in the irrigation water can react to produce less mobile

forms when it reaches RUM LAAs soils and is not in exchangeable forms (Willett

and Bond, 1998). Lead is also generally immobilized in the soils possibly due to the

formation of PbSO4 because of the abundance of water-soluble SO42-

in RUM LAAs

soils (Willett and Bond, 1998). The soils at RUM LAAs have a relatively small

sorption capacity for other solutes applied in the irrigation water except Mn due to a

low clay content, low organic matter, acidic pH and low CEC (Chartres et al., 1991).

Therefore, with the exception of U, Mn and Pb, other solutes applied in irrigation

water are not retained in the soils and their leaching is maximum during the wet

season rainfall (Bond et al., 1994; Chartres et al., 1991; Holligsworth et al., 2005;

Willett et al., 1993).

Difference between year 1 and year 2 soil samples meant that dry season 1 soil

samples were significantly different from dry season 2 soil samples and wet season 1

soil samples differed significantly from wet season 2 soil samples. The difference in

dry season 1 and dry season 2 physicochemistry can be ascribed to the difference in

the amount of irrigation water. During year 1 dry season (April–October, 2008)


68

RUM LAAs had received far more irrigation water than during year 2 dry season

(April–October, 2009), except for Jabiru East (Table 3.3). However, the

concentration of solutes in irrigation water was higher during year 2 dry season as

compared to year 1 dry season (Table 3.4) but overall RUM LAAs received a higher

load of solutes during year 1 (Table 3.5) because more water was applied, with the

exception of Jabiru East. This means that the difference in soil physicochemistry

between dry 1 and dry 2 may be attributable to differences in the amount of irrigation

water applied.

As some of the solutes are not retained by RUM LAAs soils and are lost with the wet

season rainfall (Bond et al., 1994; Willet and Bond, 1998), the difference between

wet season 1 and wet season 2 physicochemistry can be attributed to the difference in

rainfall between wet season 1 and wet season 2 and to less irrigation water applied to

RUM LAAs before wet season 2 i.e., in dry season 2. Wet season 1 (2008/2009 wet

season) at RUM was a below average wet season with only 1184 mm of rainfall from

October 2008 to May 2009 while wet season 2 (2009/2010 wet season) received an

above average rainfall of 1569 mm during November 2009 to May 2010 (Australian

Bureau of Meteorology). The effect of irrigation water and rainfall on soil

physicochemical parameters at RUM LAAs is further discussed below:

3.4.1 Difference between dry season 1 and dry season 2 physicochemical

variables

The difference in dry season 1 and dry season 2 physicochemistry as a result of the

difference in the amount of irrigation water was due to a change in soil total S, Fe,

Ca and U concentration from dry season 1 to dry season 2 at all the sites. Soil U


69

concentration decreased from dry season 1 to dry season 2 at all sites except Jabiru

East. The decrease in the amount of irrigation water applied in dry season 2 as

compared to dry season 1, is likely to account for the overall decrease in soil U

concentration recorded in dry season 2 compared to dry season 1 at most of the sites

under irrigation. Although the average concentration of U in irrigation water

increased from dry season 1 to dry season 2, overall RUM LAAs received a lower

amount of U during dry season 2 (Table 3.5) due to the application of less water

except Jabiru East. At Jabiru East there was an increase in U concentration and the

amount of water applied to this LAA increased from 15 ML in dry season 1 to 87

ML in dry season 2 (Table 3.3). Among other major solutes applied in irrigation

water there was a decrease in soil S, Fe and Ca concentration from dry season 1 to

dry season 2 at all the sites except Jabiru East due to a decrease in the amount of

irrigation water from dry season 1 to dry season 2. Although the average

concentration of these solutes also increased in irrigation water in dry season 2,

overall RUM LAAs received higher amounts of these solutes during dry season 1

compared to dry season 2 because more irrigation water was applied to RUM LAAs

in dry season 1. At Jabiru east there was an increase in the concentration of soil S, Fe

and Ca concentration from dry season 1 to dry season 2. At this site higher amounts

of irrigation water were applied during dry season 2 compared to dry season 1.

Therefore, the difference in soil U, S, Fe, Ca concentrations between dry season 1

and dry season 2 can be attributed to differences in the amount of water being

applied through irrigation.


70

3.4.2 Difference between wet season 1 and wet season 2 physicochemical

variables

As mobility of leachable solutes in the irrigation water is maximum during the wet

season (Bond et al., 1994), the difference in rainfall from one wet season to the next

in this study may have had a different effect on the mobility of these solutes. This

may have resulted in different concentrations of leachable solutes between wet

season 1 and wet season 2. Higher rainfall during wet season 2 and less irrigated

water with the exception of Jabiru East may have caused a decrease in soil S, Fe and

Ca after wet season 2. Although there was a decrease in U concentration from dry

season 1 to dry season 2, the difference between wet season 1 and wet season 2 U

concentrations was not significant. This is because U is known to be localised in the

top 10 cm of the soil profile and hence can be redistributed by runoff water

(Hollingsworth et al., 2005; Willett and Bond, 1998). I recorded higher moisture

content at sites CCLAA-036, RP1-138, JELAA-001, RP1-134, DLAA-157 EXT,

DLAA-228 MLAA-101 EXT, DLAA-227 and MLAA-032 which suggests that

pooling of runoff at these sites after wet season 2 may have caused an increase in U

concentration resulting in a non-significant difference between wet season 1 and wet

season 2.

3.4.3 Difference in soil physicochemistry between dry season 1 and wet season 1

The difference in soil physicochemistry between dry season 1 and wet season 1 was

also significant. This may be because RUM LAAs are only irrigated during the dry

season and the wet season rainfall results in the loss of certain solutes like S, Fe, Ca

and U decreasing their concentration as compared to the dry season (Bond et al.,


71

1994; Willet and Bond, 1998). It has been shown by Bond et al. (1994) that

desorption of the solutes from soil particles is at its peak at the end of the wet season.

Therefore, the decrease in the concentration of S, Fe, Ca and U after the wet season

can be attributed to desorption and leaching of solutes from the soil with rainwater.

Although non-significant, there was a measurable decrease in U concentration

between dry season 1 and wet season 1. This decrease in U concentration after the

wet season is in agreement with Willett and Bond (1998), who also recorded as much

as 35% decrease in U concentration after the wet season. However, the decrease in U

concentration in Willett and Bond (1998) study was partly due to differences in

sampling and also the decrease was not significant due to a large standard error for

the data before the wet season. Different factors may be responsible for the decrease

in soil U concentrations at RUM LAAs in my study. At RUM LAAs, U sorption to

soil particles is expected to increase with increasing pH due to an increasing negative

charge associated with kaolinite and organic matter (Willett and Bond, 1995).

However, addition of U in the soil causes a decrease in soil pH, probably due to the

hydrolysis of uranyl ions (Willett and Bond, 1995) as illustrated below:

( )

( ) ( )

( ) ( )

This decrease in soil pH with the addition of U may decrease the sorption of U to the

soil particles at RUM LAAs and allow some mobilisation. Acidic rainwater at RUM

LAAs (Noller and Currey, 1990; Noller et al., 1990) is also capable of leaching U


72

and other metals from the soil. Moreover, Mn is used in the mill process (Baily,

1984; Noller, 1989) so it is present in RP2 irrigation water. Manganese is also

present in RUM surface soils naturally (Chartres et al., 1991). To some extent, Mn

can decrease the sorption of U to the soil (Willett and Bond, 1995) and may therefore

also play a role in U mobility. Uranium sorption may also be reduced if it forms

complexes with SO42-

present in the irrigation water (Davey and Scott, 1956). The

presence of U near the soil surface at RUM LAAs and little evidence that U is taken

up by vegetation (Akber and Marten, 1992) means that a major loss of U may be

ascribed to water and wind erosion of soil in particulate form rather than U being

leached down in the soil profile (Chartres et al., 1991; Hollingsworth et al., 2005;

Willett and Bond, 1998). Thus, the decrease in U at RUM LAAs is possibly due to

its loss through water and wind erosion. Direct measurement of runoff and its

suspended load could confirm this prediction (Willett and Bond, 1998). I also

measured a decrease in concentration of S, Fe and Ca from dry season 1 to wet

season 1 as a result of leaching of these solutes due to rainfall. These findings

confirm earlier studies that the wet season rainfall causes a loss of certain solutes

applied in the irrigation water from RUM LAAs soils.

3.4.4 Difference in soil physicochemistry between dry season 2 and wet season 2

There was a decrease in soil S, Fe and Ca concentration from dry season 2 to wet

season 2. However, there was an increase in U concentration during wet season 2 at

some of the sites like CCLAA-036, RP1-138, JELAA-001, RP1-134, DLAA-157

EXT, DLAA-228 MLAA-101 EXT, DLAA-227 and MLAA-032. Within the same

sampling site some samples had higher U concentration than other subsamples and

this high intra-site variation was evident by their high standard deviation. This means


73

that the measured increase in U concentration during year 2 wet season may have

been due to the redistribution of U at these sites by rainwater. These sites had higher

moisture content, which indicates that pooling of runoff might have occurred at these

sites resulting in an increase in the soil U concentrations. This suggests that U at

RUM LAAs is mobilized by surface water movement.

I did not measure a substantial change in the concentration of Al, Mn, Cu and Pb

between dry season 1 and dry season 2, wet season 1 and wet season 2 or between

wet and dry season seasons of both years. The concentrations of these solutes applied

in irrigation water are low and therefore may not have resulted in any major change

to the background concentrations (Table 3.5). So among solutes applied in irrigation

water, the difference in dry season 1 and dry season 2, wet season 1 and wet season 2

and the difference in dry and wet seasons of both years can be attributed to the

change in the soil S, Fe, Ca and U concentrations most likely due to differences in

the amounts of irrigation water and variations in the rainfall.

3.4.5 Inter-site variation in soil physicochemistry

In addition to seasonal and temporal changes in soil physicochemistry at RUM

LAAs, sites belonging to low, medium, high and very high U categories were

different from each other. This difference was particularly significant between low U

level sites and all other U categories sites. While these low U sites had lower

concentration of U compared to the other sites, they also had higher moisture levels

because these sites were either present in catchment areas, close to retention ponds or

were formerly billabongs. So there were two factors, lower concentration of U and


74

higher moisture content, that differentiated them from the sites belonging to medium,

high and very high U categories.

Very high and high U sites had higher Ca concentrations than did sites in the other U

categories. Very high and high U sites were commissioned earlier than other sites

and might have accumulated more Ca, which, unlike other elements in the irrigation

water such as Mg, Na, K, SO42-

and Cl, is preferentially retained by the soil (Bond et

al., 1994). Moreover, it has also been suggested that Ca might be taken up by the

vegetation cover at RUM LAAs as it is one of the essential plant nutrients (Bond et

al., 1994). So relatively undisturbed vegetation cover at low and medium U sites

might have taken up higher amounts of Ca resulting in its lower concentration in the

soil as compared to very high and high U sites. Very high U site MLAA-032 and one

of the high U sites (MLAA-101 EXT) had higher Mn concentration. This may be

because both of these sites are located within 1 m from the source of irrigation

(sprinkler) and have been irrigated for the longest period of time with unpolished

pond water (Zimmermann and Lu, 2011).

Sites at RUM LAAs were also different in terms of pattern of change in soil S, Ca

and Fe concentration. There was an increase in the concentration of soil S, Fe and Ca

at study sites RP1-134, RP1-138, RP1-144, JELAA-001 and JELAA-020 during dry

season 2 compared to wet season 1 as a result of irrigation during dry season 2.

However there was a decrease in the concentration of S, Fe and Ca at study sites

CCLAA-036, CCLAA-076, DLAA-185, DLAA-222, DLAA-227, DLAA-228,

DLAA-157 EXT, DLAA-170 EXT, DLAA-177 EXT, MLAA-101 EXT, MLAA-106

and MLAA-032 because these sites did not receive any irrigation water during dry

season 2. There was a seasonal effect on U concentrations evident by a decrease in


75

soil U concentrations at study sites JELAA-020, EDJ-222 after wet seasons. In

contrast, sites JELAA-001, CCLAA-036, RP1-138, JELAA-001, RP1-134, DLAA-

157 EXT, DLAA-228 MLAA-101 EXT, DLAA-227 and MLAA-032 showed an

increase in soil U concentration after wet season 2. This increase in U concentration

might be due to pooling of runoff at these sites. These findings suggest that

differences in physicochemical parameters among different sites at RUM LAAs

might be driven by their location, distance from the source of irrigation, year

commissioned, rate of irrigation of RP2 water, quality of irrigation water, vegetation

cover and surface water movement.

3.5 Conclusions

Contrary to the prediction, there was a seasonal and temporal change in soil

physicochemistry at RUM LAAs, which can be attributed to differences in the

amount of irrigation water and rainfall that these areas received between year 1 and

year 2. Differences in soil physicochemistry were due to changes in the

concentration of S largely in the form of MgSO4, Fe, Ca and U in soil from one year

to the next and between wet and dry seasons. These differences in the concentration

of S, Fe, Ca and U may drive a change in soil microbial communities present at

RUM LAAs. Such changes in microbial community composition may be useful

indicators of the effect of irrigation water on soil biota. Microbial community

composition at low U sites may differ from that present at medium, high and very

high U sites because low U sites were significantly different from other U categories

sites in terms of soil U concentrations and physicochemistry. Microbial community

composition at RUM LAAs and its correlation with soil U concentration and

physicochemical variables is presented in the following chapter.

CHAPTER 4

SOIL URANIUM CONCENTRATION AT

RANGER URANIUM MINE LAND

APPLICATION AREAS DRIVES CHANGES IN

THE BACTERIAL COMMUNITY

Chapter 4. Bacteria-uranium associations

77

4.1 Introduction

Microorganisms respond quickly to environmental stress compared to higher

organisms, as they have intimate interactions with their surroundings due to their

high surface to volume ratio (Nielsen and Winding, 2002). This unique characteristic

of microorganisms makes them ideal to study the effect of elevated metals on living

organisms (Nielsen and Winding, 2002). Biomass, community structure, and specific

functions of soil microorganisms may serve as a useful indicator of the changes in

soil physical and chemical properties, thereby providing an early sign of soil

improvement or an early warning of soil degradation (Pankhurst et al., 1995).

Changes in microbial community composition and its functions reflect the

environmental effects resulting from heavy metals and radionuclides contamination

(Hattori, 1992; Kelly et al., 2003; Smejkalova et al., 2003).

Speciation of heavy metals and radionuclides has an effect on microorganisms (Yu et

al., 2001). Soluble metal species tend to be mobile and bioavailable (Bosma and

Harms, 1996; Meharg, 1996) and they are therefore more likely to affect the

microbial community. Microorganisms, on the other hand, possess a variety of

mechanisms to resist high concentrations of heavy metals and radionuclides (Bruins

et al., 2000). These mechanisms may involve reduction (Khijniak et al., 2005; Lloyd,

2003; Lovley et al., 1991; Wu et al., 2006), bioaccumulation (Merroun et al., 2003;

2006), biosorption (Ohnuki et al., 2005) and/or biomineralization (Macaskie et al.,

2000; Martinez et al., 2007) of heavy metals and radionuclides into forms that are

less soluble and hence less bioavailable or less toxic. In this way, microorganisms

also play an important role in heavy metal speciation, which influences migration

and toxicity of heavy metals (Francis, 1998; Lloyd and Lovley, 2001; Merroun et al.,


78

2006; Merroun and Selenska-Pobell, 2001; Selenska-Pobell, 2002; Suzuki et al.,

2005).

Microorganisms present in heavy metals contaminated environments are often

associated with particular metals (Mejare and Bulow, 2001; Nies, 2003; Piddock,

2006), which make them useful bioindicators for that metal and for environmental

forensics (Haq and Shakoori, 2000; Zhou, 2003). For example, the population of U

associated bacteria may increase under high U concentration in soils.

Detailed studies of microbial communities in metal contaminated environments

provide insights into the role of microorganisms in metal speciation and mobility. It

also allows us to assess their potential as bioindicators. A number of such studies

have investigated microbial communities in radionuclide contaminated environments

(Akob et al., 2007; Brodie et al., 2006; Chen et al., 2012; Crozier et al., 1999; Elias

et al., 2003; Fields et al., 2005; Fredrickson et al., 2004; Hwang et al., 2009; Khan et

al., 2013; Mondani et al., 2011; Petrie et al., 2003; Rastogi et al., 2010; Reardon et

al., 2004; Satchanska et al., 2004; Satchanska and Selenska-Pobell, 2005; Selenska-

Pobell et al., 2001; Suzuki et al., 2003, 2005; Xu et al., 2010).

These studies show that extremely diverse groups of bacteria can exist in

radionuclide contaminated environments. For example, Proteobacteria distributed

over the Alpha-, Beta-, Gamma- and Deltaproteobacteria were dominant in uranium

(U) contaminated sediment collected from an inactive U mine pit (Suzuki et al.,

2003). In other reports, Alphaproteobacteria and Acidobacteria were dominant in

soil samples collected from different depths of a U mining waste pile (Selenska-

Pobell, 2002; Satchanska et al., 2004). In some reports, however, gram-positive


79

bacteria, especially Bacillus sp., green non-sulfur bacteria, and

Gammaproteobacteria, were dominant in soil samples from U mill tailings

(Selenska-Pobell et al., 2002). In yet another U contaminated subsurface sediment,

phylotypes related to Proteobacteria (Alpha-, Beta-, Gamma- and

Deltaproteobacteria), Bacteroidetes, Actinobacteria, Firmicutes and Planctomycetes

were detected in DNA- and RNA-derived clone libraries (Akob et al., 2007).

Similarly, in addition to Acidobacteria and Proteobacteria, Chloroflexi, Firmicutes,

Nitrospirae, Actinobacteria, Deinococcus-Thermus, Elusimicrobia and

Verrucomicrobia were isolated from U deposits (Mondani et al., 2011). Phylogenetic

analysis at other U deposits indicated that the bacterial community was affiliated

with Firmicutes, Gammaproteobacteria and Actinobacteria (Chen et al., 2012).

Among cultivable bacteria, Firmicutes and Betaproteobacteria were dominant at

uranium mine water-tailings interface while a control lake was dominated by

Bacteroidetes and Gammaproteobacteria. However, metagenomic analysis

demonstrated the dominance of Firmicutes in both of the systems (Khan et al., 2013).

Similarly, Proteobacteria, Acidobacteria, Verrucomicrobia, Cyanobacteria,

Bacteroidetes, Chloroflexi, Planctomycetes Gemmatimonadetes, WS3, OD1 and

TM7, Firmicutes, Actinobacteria and Chlamydia were present in both U

contaminated as well as control streams. However, Verrucomicrobia were less

abundant in uraniferous streams compared to control stream (Vishnivetskaya et al.,

2011). Thus bacteria found at uraniferous sites are ubiquitous in nature. However

differences in the abundances of certain bacterial groups are found between U

contaminated and control sites. Moreover, the differences in bacterial community

composition at different sites may be due to different degrees of U contamination,


80

different geographic and geologic origin of the U, climatic conditions and/or site

history (Selenska-Pobell et al., 2002).

Although bacterial communities have been analysed at different heavy metal

contaminated sites as described above, there have been no detailed investigations of

bacterial communities in radionuclide contaminated environments in the wet-dry

tropics of northern Australia. Moreover, there is very little knowledge about seasonal

and temporal changes in bacterial community composition in radionuclide

contaminated environments (Mondani et al, 2011). To my knowledge, studies of

bacterial communities across a range of radionuclide concentrations under field

conditions are also not available. Ranger Uranium Mine Land Application Areas

(RUM LAAs) in the wet-dry tropics provide an ideal study site to fill these

knowledge gaps. This site is subjected to extreme seasonal changes and possesses a

range of U and other metal concentrations in soils (Chapter 3).

Ranger Uranium Mine LAAs are irrigated by runoff water from low-grade ore and

waste stockpiles and other areas on the mine-site, stored in a retention pond 2 (RP2).

In addition to radionuclides [uranium (U), radium (Ra), thorium (Th)], the water also

contains sulfur (S) in the form of sulfate (SO42-

), calcium (Ca), iron (Fe) and

manganese (Mn) as major solutes, while minor amounts of copper (Cu) and lead (Pb)

are also present.

The soils in RUM LAAs have different concentration of metals and radionuclides,

not only because they receive water of different quality (unpolished vs polished), but

also because their locations vary in their distance from the source of irrigation (i.e.,


81

sprinkler heads), the method of irrigation varies and they have received irrigation

over different time periods (Table 4.1).

Table 4.1 Ranger Uranium Mine Land Application Areas (LAAs) (adapted from

Akber et al., 2011a)

Land Application Area and abbreviation

Water quality Irrigation method

Total area (ha)

Year commissioned

Magela (MLAA) Unpolished RP2 water

Spray 33 1985

Magela Extension (MLAA-EXT)


Spray 20 1994

RP1 Polished RP2 water Flood 46 1995

Djalkmara (DLAA) Polished RP2 water Flood 18 1997

Djalkmara Extension (DLAA EXT)

Polished RP2 water Flood 20 1999

Jabiru East (JELAA) Unpolished RP2 water

Spray 52 2006

RP1 Extension (RP1 EXT)


Spray 8 2006

Corridor Creek (CCLAA)


Spray 141 2007

To study the effect of U and other metal concentrations on the soil bacterial

community, I categorized the sites at these LAAs as low, medium, high and very

high U sites based on their historical U concentration data. These sites were re-

categorized on the basis of the actual U concentrations measured in the present study

(Chapter 3). Low (control) U sites had background levels of U and were significantly

different from medium, high and very high sites U based on soil U and other

physicochemical parameters like [sulfur (S), iron (Fe), calcium (Ca), aluminium (Al),

copper (Cu), zinc (Zn), thorium (Th), nickel (Ni), lead (Pb), Mn, U, moisture and

bulk density] (Chapter 3). These sites also showed a significant seasonal and


82

temporal change in soil U and physicochemical parameters (Chapter 3). Since

community level changes in bacteria have been reported in response to changes in

physicochemical parameters (Akob et al., 2007; Islam et al., 2011), I predicted that

the bacterial community at low U sites would be significantly different from

medium, high and very high U sites and there would also be a seasonal and temporal

change in the composition of the bacterial community. Reports have also shown that

metal and/or U reducing bacteria are more abundant at U contaminated sites

(Cardenas et al., 2006; Mondani et al., 2011); therefore, I predicted that U and/or

SO42-

reducing bacteria would be more abundant at medium, high and very high U

sites as compared to low U sites. I also predicted that the bacterial community at

RUM LAAs would be different from other U contaminated sites due to its unique

climatic conditions (Selenska-Pobell et al., 2002).

To test these predictions, I studied the microbial community composition at low

(control), medium, high and very high U sites. Studies of microbial communities

using standard cultivation techniques capture less than 1% of the cultivable

microorganisms (Merroun, 2007; Nichols et al., 2008). Moreover, estimates of

bacterial species per gram of soil may vary from 2000 to 8.3 million which are

practically impossible to assess even using culture independent techniques such as

16S ribosomal RNA gene clone sequencing from soil DNA (Roesch et al., 2007). To

help avoid these problems, I used high throughput DNA pyrosequencing to assess

the bacterial community composition (Margulies et al., 2005; Sogin et al., 2006).

One of the greatest advantages of pyrosequencing is that it generates hundreds of

thousands of sequence reads in a single run, providing sequence information data

that are orders of magnitude larger than Sanger method of sequencing


83

(Margulies et al., 2005; Roesch et al., 2007; Sogin et al., 2006). The high throughput

of the pyrosequencing method enables greater sampling depth (number of sequences

per sample) and breadth (number of samples or individuals analyzed). A greater

sampling depth allows a better coverage of individual samples, increasing the

chances of detecting rare species which is of extreme importance for ecological

studies. A greater sampling breadth permits one to examine more samples, providing

results that are more reliable for comparisons (Siqueira et al., 2012). This approach

allowed me to study the bacterial community present at radionuclide and metal

contaminated environments in RUM LAAs. Correlations between the bacterial

community and soil physicochemical parameters were measured using statistical

inference. These data provided a comprehensive assessment of the microbial

community diversity and community change across a range of U concentrations at

RUM LAAs study sites.


4.2.1 Sampling sites and collection of soil samples

Soil samples were collected over two years, 2008–09 (year 1) and 2009–10 (year 2).

During each of those years, samples were collected in the dry season

(September/October) and in the wet season (February/March). Five sub-samples

were taken from each of the 18 selected sites at RUM LAAs (Table 4.2) using a core

sampler with diameter 5 cm and depth 10 cm (Chan et al., 2006). Ninety samples

were collected each season and transported to the laboratory on ice. These soil

samples were the same as used for soil physicochemical analysis in chapter 3.


84

Table 4.2 Study sites at Ranger Uranium Mine Land Application Areas

Uranium category Land Application Area (LAA) Site Code

Low [control (2–20 ppm)] Corridor Creek (CCLAA) CCLAA-076 Djalkmara Extension (DLAA EXT) DLAA-177 EXT Djalkmara (DLAA) DLAA-185 RP1 RP1-144 Magela Extension (MLAA EXT) MLAA-EXT-121 Jabiru East (JELAA) JELAA-020 Djalkmara (DLAA EXT) DLAA-170 EXT Medium (200–400 ppm) Djalkmara (DLAA) DLAA-222 Corridor Creek (CCLAA) CCLAA-036 RP1 RP1-138 Jabiru East (JELAA) JELAA-001 High (500–900 ppm) RP1 RP1-134 Djalkmara Extension (DLAA EXT) DLAA-157 EXT Djalkmara (DLAA) DLAA-228 Djalkmara (DLAA) DLAA-227 Magela Extension (MLAA EXT) MLAA-EXT-101 Very high (> 900 ppm) Magela Extension (MLAA EXT) MLAA-EXT-106 Magela (MLAA) MLAA-032

4.2.2 Analysis of soil physicochemical parameters at Ranger Uranium Mine


To measure correlation between soil physicochemistry and the bacterial community,

the physicochemical parameters at RUM LAAs soils were first analysed as described

in chapter 3, section 3.2.2.


85

4.2.3 Bacterial community analysis of soil samples

The bacterial community at RUM LAAs was analysed as follows:

4.2.3.1 Amplification and sequencing of the 16S ribosomal RNA gene

hypervariable V6 region

Two sub samples per site one having lowest and the other having highest U

concentration were selected for DNA extraction and pyrosequencing. Sub-samples

with lowest and highest U concentration were selected so that the bacterial

community present under both minimum and maximum U concentration could be

captured. Total DNA was extracted from approximately 10 g of soil per sample using

the MoBio PowerMax Soil DNA Extraction kit (Geneworks, SA, Australia)

according to the manufacturer’s instructions. The A-967F and B-1046R (5’-

CCTATCCCCTGTGTGCCTTGGCAGTCTCAG-CGACAGCCATGCANCACCT-

3’) polymerase chain reaction (PCR) primers were used to amplify the V6

hypervariable region of the bacterial 16S ribosomal RNA gene (Sogin et al., 2006).

Primers were modified to use with the Roche Titanium system (Forward primer 5’-

CCATCTCATCCCTGCGTGTCTCCGACTCAG-X-

CAACGCGAAGAACCTTACC-3’), where the first segment comprises the 454

primer A adaptor, X denotes a unique 10-nucleotide barcode sequence for each

sample, and the last segment comprises 16S bacteria A-967F primer sequence.

Polymerase chain reactions were compiled according to the Roche FastStart High

Fidelity PCR System, dNTPack protocol (Roche Diagnostics, NSW, Australia). Each

PCR reaction contained 10 ng of template DNA, 1X buffer with 1.8 mM MgCl2, 0.2

mM dNTPs, 0.4 µM forward and reverse primers, 2.5 U FastStart High Fidelity


86

Enzyme Blend, and dH2O. Amplifications performed for all the samples using a

Labnet Multigene Thermal Cycler (Labnet International, Inc. Edison, NJ, USA)

included an initial denaturation at 92 °C for 2 min, followed by 30 cycles of 94 °C/1

min, 57 °C/45 sec, 72 °C/30 sec and a final extension at 72 °C for 2 min. Each

sample was subjected to a minimum of four amplification reactions. PCR products

from these four reactions were pooled and purified using QIAquick PCR Purification

kit (Qiagen, Hilden, Germany), and eluted with sterilized distilled water (SDW).

Polymerase chain reaction products were quantified by separation through 2%

agarose gel electrophoresis and were compared with low DNA mass ladder

(Invitrogen CA, USA). Purified samples were concentrated to > 100 ng/µL by

sodium acetate-ethanol precipitation. Polymerase chain reaction products were

sequenced at the Australian Genome Research Facility (AGRF), Brisbane, QLD,

Australia, using the 454 GS FLX Titanium Sequencing System (Roche).

4.2.3.2 Analysis of sequence data

Sequence data were sorted by barcode at the AGRF and barcode sequences were

removed. Sequences were pre-treated to remove poor-quality sequence with the RDP

pyrosequencing pipeline at http://rdp.cme.msu.edu/ (Cole et al., 2007; Cole et al.,

2009). Sequences containing more than one ambiguous base or returning a quality

score < 20 and/or comprising less than 70 nucleotides were removed using RDP’s

Pipeline Initial Processer (http:www.pyro.cme.msu.edu). Sequences were further

processed using MOTHUR V1.13.0 software package (Schloss et al., 2009). The

sequences were aligned with the SILVA database using align.seqs command in

MOTHUR (Pruesse et al., 2007). Sequences that did not align to the V6 region were

removed using screen.seqs and common gaps were removed using filter.seqs. The


87

Chimeraslayer and SILVA database, accessed through MOTHUR, were used to

identify chimera sequences (Pruesse et al., 2007). Sequences were clustered into

operational taxonomic units (OTUs) using average distance method with a 3%

distance cut-off criterion. OTUs were classified using classify.seqs at the 0.03 level

using the SILVA database (Pruesse et al., 2007). Chao1 richness estimate and

Shannon Index were calculated at the 0.03 level using summary.single command in

MOTHUR (Schloss et al., 2009). The evenness of the representation of OTUs in

each sample was calculated by dividing the Shannon index by the natural log of the

number of OTUs. The richness of the species was calculated by dividing the

observed number of OTUs by the expected number of OTUs. Species richness

estimates were not normalized due to high evenness. Moreover, sequences obtained

and analysed were indicative of bacteria only and original bacteria (i.e., isolates)

were not obtained in this study.

4.2.4 Statistical analysis of soil bacterial community and physicochemical

variables

Data were analysed using PRIMER (Plymouth Routines in Multivariate Ecological

Research, version 6.1.12, Primer-E Ltd, United Kingdom) (Clarke and Warwick,

2001). Mean value of physicochemical data from the same 2 sub-samples on which

pyrosequencing was carried out were included in statistical analysis.

Physicochemical data were normalized, log (x+1) transformed and resemblance

matrices was calculated using Euclidian distance. Mean value of Operational

taxonomic units (OTUs) counts from 2 sub-samples were standardised to account for

variation in total counts between samples and were then square root transformed to

minimise some of the effect of highly abundant OTUs. A resemblance matrix was


88

calculated using Bray Curtis similarity. Resemblance matrices of both biological and

physicochemical data were analysed by permutational analysis of variance

(PERMANOVA+) to determine if the samples collected during different sampling

times were significantly different in terms of biological (bacterial community) and

physicochemical variables. Bacterial and physicochemical data were compared

between paired soil U categories (i.e., low and medium, low and high, low and very

high, medium and high, medium and very high and high and very high) using

pairwise PERMANOVA. The RELATE (Spearman rank correlation method) was

used on resemblance matrices to measure the correlation between biological and

physicochemical data. BEST (BIOENV) was used to determine which

physicochemical variables were best correlated with changes in the bacterial

community. An OTU resemblance matrix was used to generate Non-metric Multi-

Dimensional Scaling (MDS) plots for biological data.

An indicator species approach (Cardenas et al., 2010) was used to find the OTUs

which represented the low and medium, high and very high U sites. An indicator

value ranging from 0 to 1 was calculated for OTUs using both frequency of

occurrence and relative abundance information. A value closer to 1 represents the

stronger indicator value and vice versa. A 1,000-bootstrap test was used to calculate

p value for each indicator value. Indicator species analysis was carried out using

software R (version 2.12.1; http://www.R-project.org) with Labdsv (Cardenas et al.,

2010). It was not analysed if there were distinctive sequence signatures between

groups.


89

4.3 Results

4.3.1 Soil physicochemistry at Ranger Uranium Mine Land Application Areas

and associations with the bacterial community

4.3.1.1 Soil uranium concentration and physicochemical parameters

Soil U concentrations (p < 0.05, Table 4.3) and physicochemical variables (S, Fe, Ca,

Al, Mn, Cu, Zn, Th, Ni, Pb, U, TOC, TN, moisture and bulk density) (p < 0.05,

Table 4.4) were significantly different among low, medium, high and very high U

sites at RUM LAAs. More specifically, soil U concentrations and physicochemical

variables at low U sites differed significantly from medium, high and very high U

sites (p < 0.05). However, the differences in soil U concentration and

physicochemical variables between medium and high, medium and very high and

high and very high U sites were not significant (p > 0.05). The significant difference

at low U sites compared to all other soil U categories was driven by both low soil U,

and lower concentration of Ca, Cu, Fe and Al (Chapter 3). Study sites within each U

category were also significantly different from each other based on soil U

concentration (p < 0.05, Table 4.3) and physicochemistry (p < 0.05, Table 4.4).

Soil U and physicochemical variables at RUM LAAs study sites also differed

significantly between seasons and times. There was a significant change in RUM

LAAs soil U concentration (p < 0.05, Table 4.3) and physicochemical variables (p <

0.05, Table 4.4) from year 1 to year 2. That is, soil samples collected in year 1 dry

season were significantly different from year 2 dry season, and samples collected in

year 1 wet season were significantly different from those collected in year 2 wet

season. Moreover, U concentration and the physicochemical variables of the dry


90

season RUM LAAs soils differed significantly from the wet season for both years. In

addition to U, changes in the concentrations of S, Fe and Ca were responsible for the

temporal and seasonal change in soil chemistry (Chapter 3). There was however, no

interaction between year and season. There was also no interaction between low,

medium, high and very high U category sites and year or season. No interaction was

found between sites present in each uranium category and year or season based on

soil U concentration (p > 0.05, Table 4.3) and physicochemical variables (p > 0.05,

Table 4.4).


91

Table 4.3 PERMANOVA table of results based on soil U concentration at Ranger

Uranium Mine Land Application Areas showing p-values for tests of

significance of difference between U categories, year 1 and 2, wet and

dry seasons, site nested in U and interactions of these factors (analysis

was based on mean of 2 sub-samples from each Land Application Area).


U- 3 305.94 101.98 84.514 0.001 999 Ye 1 1.1566 1.1566 5.1493 0.049 997 Se 1 2.0793E-2 2.0793E-2 0.15767 0.042 997 Si(U-) 14 16.893 1.2066 5.6252 0.001 997 U-xYe 3 9.9472E-2 3.3157E-2 0.14762 0.942 999 U-xSe 3 0.3333 0.1111 0.84246 0.487 999 YexSe 1 1.066 1.066 4.9697 0.066 997 YexSi(U-) 14 3.1447 0.22462 1.0471 0.46 999 SexSi(U-) 14 1.8463 0.13188 0.61478 0.829 999 U-xYexSe 3 0.3409 0.11363 0.52973 0.666 999 Res 14 3.0031 0.21451 Total 71 334.05






U-x Se = YexSe = Interaction between years and seasons

Interaction between U categories and seasons





92

Table 4.4 PERMANOVA table of results based on soil physicochemical

parameters (S, Fe, Ca, Al, Mn, Cu, Zn, Th, Ni, Pb, U, TOC, TN,

moisture and bulk density) at Ranger Uranium Mine Land Application

Areas showing p-values for tests of significance of difference between U

categories, year 1 and 2, wet and dry seasons, site nested in U and

interactions of these factors (analysis was based on mean of 2 sub-

samples from each Land Application Area).


U- 3 368.13 122.71 3.3839 0.008 994 Ye 1 5.4804 5.4804 2.2679 0.044 998 Se 1 16.487 16.487 5.8558 0.001 997 Si(U-) 14 507.68 36.263 11.411 0.001 998 U-xYe 3 14.671 4.8902 2.0237 0.116 999 U-xSe 3 13.34 4.4467 1.5794 0.101 998 YexSe 1 8.7319 8.7319 2.7476 0.141 999 YexSi(U-) 14 33.831 2.4165 0.76039 0.907 998 SexSi(U-) 14 39.417 2.8155 0.88594 0.719 997 U-xYexSe 3 6.123 2.041 0.64223 0.839 999 Res 14 44.491 3.178 Total 71 1065






U-x Se = Interaction between U categories and seasons






93

4.3.1.2 Correlation of soil uranium concentration and physicochemical variables

with the bacterial community

Of all the measured soil physicochemical parameters, changes in the bacterial

community diversity at RUM LAAs were best correlated with soil U concentration

(Spearman’s rho = 0.67, Appendix D). In addition to an overall strong correlation

between soil U concentration and the bacterial community, U also showed a

significant and strong correlation with the bacterial community during each

individual sampling time (i.e., dry season 1, wet season 1, dry season 2 and wet

season 2) (Table 4.5).

Table 4.5 P value and rho for Spearman’s rank correlation between soil U

concentration and the bacterial community at Ranger Uranium Mine

Land Application Areas during individual sampling time

Sampling time

p-Value

Spearman’s rho

Dry season 1 < 0.05 0.71

Wet season 1 < 0.05 0.68

Dry season 2 < 0.05 0.76

Wet season 2 < 0.05 0.63

There was a significant difference in the bacterial community diversity among low,

medium, high and very high U sites (p < 0.05, Table 4.6). Specifically, the bacterial

community at sites with low U was significantly different from medium, high and

very high U sites (p < 0.05). However, there was no significant difference in the

bacterial community diversity among medium, high and very high U sites (p > 0.05).

This result was also reflected in the MDS spatial arrangement of the bacterial


94

community diversity represented by OTUs. That is, OTUs at the low U sites were

present in a cluster located at a distance from the cluster of OTUs from medium, high

and very high U sites (Figure 4.1). Medium, high and very high U sites had higher U,

Ca, Cu, Fe and Al concentrations and the bacterial community present at these U

sites were associated with the higher levels of these elements compared to the low U

sites (Figure 1, Appendix D).

There was also a significant change in the soil bacterial community between year 1

and year 2 (p < 0.05, Table 4.6). Specifically, in dry season 1, the bacterial

community differed significantly from that in dry season 2. Similarly, the bacterial

community in wet season 1 was significantly different from wet season 2. Moreover,

the dry season soil bacterial community was significantly different from wet season

during both the years (p < 0.05, Table 4.6). There was however, no interaction

between year and season in terms of the soil bacterial community. There was also no

interaction between the bacterial community present at low, medium, high and very

high U category sites and year or season. Moreover, no interaction was found

between sites present in each U category and year or season based on the bacterial

community (p > 0.05, Table 4.6).


95

Table 4.6 PERMANOVA table of results based on OTUs (bacterial community)

showing p-values for tests of significance of difference between U

categories, year 1 and 2, wet and dry seasons, site nested in U and

interactions of these factors at Ranger Uranium Mine Land Application

Areas (analysis was based on mean of 2 sub-samples from each Land

Application Area)


U- 3 24823 8274.4 4.1139 0.001 998 Ye 1 4519.2 4519.2 10.379 0.001 998 Se 1 4504 4504 10.255 0.001 998 Si(U-) 14 28159 2011.3 4.9657 0.001 997 U-xYe 3 1976.2 658.73 1.5128 0.113 999 U-xSe 3 1787.9 595.97 1.3569 0.063 997 YexSe 1 3822 3822 9.4362 0.201 999 YexSi(U-) 14 6096.1 435.44 1.075 0.205 997 SexSi(U-) 14 6148.8 439.2 1.0843 0.208 997 U-xYexSe 3 1838.4 612.81 1.513 0.204 999 Res 14 5670.6 405.04 Total 71 91782






U-x Se = Interaction between U categories and seasons






96

Figure 4.1 Multi-dimensional scaling (MDS) plot of soil samples collected during

all the four sampling times at Ranger Uranium Mine Land Application

Areas based on OTUs. Correlations of Al, Fe, Ca, Cu, U and moisture

content with the OTUs patterns were overlaid onto the plot. Low U

level sites are represented by green symbols, medium by black, high by

yellow and very high with red symbols.

Although, the bacterial community showed a strong correlation with soil U, there

was a moderate, but significant, correlation between the bacterial community

diversity and soil physicochemistry, when all the physicochemical variables were

included in the analysis (p < 0.05, Spearman’s rho = 0.42). The bacterial community

was moderately correlated with soil physicochemical variables during all the

sampling times (Table 4.7).


97

Table 4.7 P value and rho for Spearman’s rank correlation between soil

physicochemical parameters and the bacterial community during

individual sampling time at Ranger Uranium Mine Land Application

Areas

Sampling time

p-Value

Spearman’s rho

Dry season 1 < 0.05 0.31

Wet season 1 < 0.05 0.37

Dry season 2 < 0.05 0.48

Wet season 2 < 0.05 0.42

4.3.2 An overview of bacterial community composition at Ranger Uranium Mine


From 183,317 bacterial V6 sequences, 122,936 passed the quality tests and clustered

into 20,895 unique OTUs at a 3% distance threshold (Table 4.8). Species richness

ranged between 0.77 and 0.92, with most of the samples having species richness

values above 0.85 indicating that the number of observed OTUs was 85% of the

expected number of OTUs (Table 4.9). This means that the present study captured

about 85% of the bacterial diversity present at the study sites. Evenness values

ranged from 0.74 to 0.88 indicating that OTUs were evenly represented and the

population was not dominated by a few OTUs (Table 4.9). Good’s Coverage ranged

from 0.85-0.97 (Table 4.10). Although, the bacterial community present at the low U

sites was significantly different from medium, high and very high U sites, number of

sequences, number of OTUs, species richness, evenness or coverage at different sites

did not show any association with low, medium, high and very high U concentrations

(Tables 4.8, 4.9, 4.10).

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100

Table 4.10 Bacterial species Good’s coverage at low, medium, high and very high

U sites at Ranger Uranium Mine Land Application Areas

Uranium category

Study Sites

Good’s Coverage

Dry season 1

Wet season 1

Dry season 2

Wet season 2

Low CCLAA-076 0.87 0.91 0.90 0.90 WDJ-177 0.88 0.91 0.92 0.92 RP1-144 0.92 0.88 0.90 0.93 JELAA-020 0.88 0.91 0.91 0.90 EDJ-185 0.89 0.92 0.93 0.92 MBLAA-121 0.86 0.88 0.91 0.90 WDJ-170 0.85 0.85 0.91 0.91 Medium EDJ-222 0.90 0.91 0.90 0.91 RP1-138 0.91 0.93 0.92 0.90 JELAA-001 0.97 0.91 0.91 0.92 CCLAA-036 0.90 0.91 0.90 0.90 High RP1-134 0.94 0.94 0.92 0.93 WDJ-157 0.88 0.91 0.93 0.91 EDJ-228 0.89 0.92 0.92 0.93 EDJ-227 0.92 0.93 0.93 0.93 MBLAA-101 0.90 0.94 0.93 0.95 Very high MBLAA-106 0.89 0.89 0.90 0.93 MBLAA-032 0.91 0.91 0.94 0.93

Among the bacterial 16S ribosomal RNA gene sequences that could be classified,

Proteobacteria was the most abundant phylum contributing 28.9 % to the total OTUs

counts across all the sites. The second most abundant phylum was Actinobacteria

with 9.3 % of the total OTUs. Acidobacteria was the third largest phylum with 7.3%

of the OTUs belonging to this phylum (Table 4.11).


101

Table 4.11 Relative abundance of bacterial phyla and their classes in soil samples

at Ranger Uranium Mine Land Application Areas

Bacterial Phyla Relative Abundance

Class present within each phylum

Relative Abundance

Unclassified 46.8% Proteobacteria 28.9% Alphaproteobacteria 41.2%

Deltaproteobacteria 9.7% Betaproteobacteria 9.2%

Gammaproteobacteria 3.8% Unclassified 36.1%

Actinobacteria 9.3% Actinobacteria 100%

Acidobacteria 7.3% Acidobacteria 95.5%

Holophagae 0.5%

Verrucomicrobia 2.2% OPB35 54% Spartobacteria 29%

Verrucomicrobiae 0.2% Unclassified 16.7%

Firmicutes 2.1% Bacilli 88.8%

Clostridia 6.5% unclassified 4.6%

Chloroflexi 1.1% Caldilineae 33.8%

S085 31.7% Anaerolineae 14.4%

KD4-96 2.2% Thermomicrobia 1%

Chloroflexi 0.7% Unclassified 16.2%

Cyanobacteria 0.9% WD272 20.8%

SubsectionV 14.3% Chloroplast 2.6%

SubsectionI 1.5% unclassified 60.7%

Planctomycetes 0.8% OM190 2.2%

Pla4 1.7% Unclassified 96.1%

Bacteroidetes 0.4% Sphingobacteria 96.1%

Unclassified 3.9%

Candidate_division_ WS3

0.2% Unclassified 100%


102

4.3.3 Differences in the bacterial community between low and medium, high and

very high uranium sites at phyla level

Differences in the abundance of Acidobacteria, Verrucomicrobia and Firmicutes

distinguished the low U sites from medium, high and very high U sites.

Acidobacteria and Verrucomicrobia were more abundant at low U sites compared to

all other U sites during dry season 1 (Figure 4.2) and wet season 2 (Figure 4.5).

During wet season 1, Verrucomicrobia was higher at low U site CCLAA-076

compared to the other sites and Acidobacteria were higher at most of the low U sites

compared to all other U sites except CCLAA-036, EDJ-222 and JELAA-001, which

also had higher Acidobacteria (Figure 4.3). During dry season 2, Verrucomicrobia

were more prevalent at low U sites compared to all other U sites (Figure 4.4). Thus,

Acidobacteria were more prevalent at low U sites during dry season 1, wet season 1

and wet season 2 while Verrucomicrobia were more prevalent at low U sites during

all the seasons. In contrast, Firmicutes were more abundant at very high U sites like

MLAA-106 EXT and MLAA-032 and a high site WDJ-157 during wet season 1

compared to all the other sites (Figure 4.3). Firmicutes were also higher at most of

the medium, high and very high U sites compared to the low U sites during dry

season 2 (Figure 4.4). However, Firmicutes were not abundant at medium, high or

very high U sites during dry season 1 (Figure 4.2) and wet season 2 (Figure 4.5).

Hence, differences in the bacterial communities between low and medium, high and

very high U sites were not consistent at all the sampling times.

Ch

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80

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%

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CCLAA-076

WDJ-177

RP1-144

JELAA-020

EDJ-185

MLAA-121-EXT

WDJ-170

EDJ-222

RP1-138

JELAA-001

CCLAA-036

RP1-134

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107

4.3.4 Species indicative of medium, high and very high uranium concentrations

As low U sites were significantly different from medium, high and very high U sites,

an indicator species approach was used to find the OTUs which consistently

represented the medium, high and very high U sites. Indicator species analysis

showed that bacterial OTUs closely related to members of Kitasatospora,

Sphingobacteria, Candidate_division_WS3 and Rhodobium were only present at

medium, high and very high U sites during all the sampling times. These

bioindicators of medium, high and very high U concentration at RUM LAAs had an

indicator value of more than 0.65 and were significant at the 0.05 level (Appendix

E).

4.4 Discussion

I predicted that the bacterial community present at low U concentration sites at RUM

LAAs would be significantly different from medium, high and very high U sites and

there would also be a seasonal and temporal change in the bacterial community as a

result of changes in soil U concentrations and physicochemical parameters. This

hypothesis was in fact supported because there was a significant association between

bacterial community and soil U concentrations.

4.4.1 Association between the bacterial community and soil uranium

concentration at Ranger Uranium Mine Land Application Areas

The bacterial community present in low U soils differed significantly from that

present in the medium, high and very high U soils. However, there was no significant

difference among bacterial communities present in medium, high and very high U


108

soils. One explanation for the lack of differences is that the community structure was

best correlated with soil U concentrations, and the relative differences in soil U

concentration at medium (200–400 ppm), high (500–900 ppm) and very high (> 900

ppm) U sites were non-significant. Higher intra-site variations in soil U

concentrations at medium, high and very high U sites also made this difference non-

significant (Chapter 3). On the other hand, at the low U sites the U concentration (2–

20 ppm) was 10–100 times lower than all the other sites. Therefore, U was a logical

driver of the measured difference in the bacterial community structure between low

U site and all the other sites. These findings also suggest that under the

environmental conditions at the LAAs, a U concentration of 200 ppm is a threshold

level at which the bacterial community may change from U sensitive to U resistant

bacteria. Therefore, beyond 200 ppm, the bacterial community may not have

responded to increasing U concentrations at medium, high and very high U sites due

to their acquired resistance (Joner et al., 2007; Mondani et al., 2011). Future studies

should measure bacterial community responses in situ in the range between > 20 and

< 200 ppm U to measure this threshold more precisely.

It is possible that the higher Ca, Al, and Cu concentration at the medium, high and

very high U sites may also be responsible for a difference in microbial community

between low and all the other sites (Chapter 3) as these metals were also strongly

correlated with the bacterial community in the present study and in the literature

(Banu et al., 2004; He et al., 2012; Sridevi et al., 2012). Higher Ca, Al and Cu

concentrations may change bacterial community membership and my decrease

species richness. Moreover, these contaminants may adversely affect microbial

biomass and soil respiration (Banu et al., 2004; He et al., 2012; Sridevi et al., 2012).


109

Changes in populations of Verrucomicrobia, Acidobacteria, and Firmicutes drove

the differences in the bacterial community between sites with low U and sites with

medium, high and very high U concentrations. Acidobacteria and Verrucomicrobia

were generally more abundant at low U sites. A decrease in the abundance of

Acidobacteria and Verrucomicrobia with increasing U and other metals has been

reported elsewhere (Barns et al., 2007; George et al., 2009; Vishnivetskaya et al.,

2011). My data agree with these reports and suggest that Acidobacteria and

Verrucomicrobia are sensitive to U and other metals such as Ca, Al and Cu at RUM

LAAs. It is possible that members of these bacterial phyla may be suitable indicators

for monitoring U concentrations > 200 ppm. Based on the findings from this study

another potential indicator group was Firmicutes because members of this bacterial

phylum were higher at most of the medium, high and very high U sites as compared

to the low U sites during dry season 2. Firmicutes were also more abundant at high U

site WDJ-157 and very high U sites like MLAA-106 EXT and MLAA-032 during

wet season 1. Presence of Firmicutes at other U contaminated sites is also well

documented (Akob et al., 2007; Cardenas et al., 2010; Hwang et al., 2009; Mondani

et al., 2011; Rastogi et al., 2010; Vishnivetskaya et al., 2011).

4.4.2 Bacteria indicative of high uranium concentration

Although Firmicutes were identified as a potential indicator of U contamination,

indicator species analysis showed that bacterial OTUs closely related to members of

Sphingobacteria, Kitasatospora, Candidate_division_WS3 and Rhodobium, were

more suitable indicators of U contamination as these groups were only present at U

concentration of > 200. Members of Firmicutes were most likely not identified as

potential indicators species because their prevalence changed with season and time.


110

These findings demonstrate the importance of conducting bacterial assessment over

temporal and seasonal periods when identifying potential indicator species.

Some of the species identified in this study as potential indicators of U

contamination of > 200 ppm have been retrieved from other U contaminated sites

(Brodie et al., 2006; Radeva and selenska-Pobell, 2004; Satchanska et al., 2004;

Selenska-Pobell, 2002; Van Nostrand et al., 2007). For example, Sphingobacteria

were isolated from lower U concentration (51 ppm) in acidic water and sediments

which might be more bioavailable due to lower pH (Cardenas et al., 2006). Similarly,

Sphingobacteria have been found in U ore deposits with a concentration of 138 and

182 ppm while they were not found from soil samples collected from outer perimeter

of the mine pit with U concentration of < 42 ppm (Islam et al., 2011). However,

organisms belonging to Sphingobacteria have also been isolated from a U mine site

having U concentration as low as 2 ppm (Rastogi et al., 2010). Other potential

bioindicators of U contamination at RUM LAAs like Kitasatospora and

Candidate_division_WS3 have also been found at other sites with elevated U.

Kitasatospora have been isolated from samples having U concentrations ranging

from 2.1–4900 mg/kg from riparian sediments (Van Nostrand et al., 2007). Similarly,

Candidate_division_WS3 was found in soil having U concentration of 108 ppm and

206 ppm at a U waste pile and in stream sediment samples having U concentration of

0.2–268 ppm (Vishnivetskaya et al., 2011). These bacteria are potentially good

indicators of U concentrations of 200 – > 900 ppm at RUM LAAs. However, as

these bacteria have been isolated at < 200 ppm of U at other sites, further work is

required to determine their suitability as indicator species.


111

The indicator species identified at RUM LAAs may possess different metal and U

resistance mechanisms. For example, Rhodobium sp. are able to reduce sulfate

(Caumette et al., 2007) which is a major ion present in irrigation water at the LAAs.

As sulfate reducers are a major group of bacteria having the potential of U(VI)

reduction (Wall and KrumholzSp, 2006), Rhodobium might be involved in U

reduction from U(VI) to U(IV) at RUM LAAs. Similarly, members of

Sphingobacteria also possess metal reducing properties (Holmes, 2006; Madden et

al., 2009). So, indicator species isolated in the study may have the ability to reduce

U, SO4 and other metals like Cr(VI), Mn(IV), Fe(III) and technetium(VII) which

supported my prediction that U and/or SO4 reducing bacteria would be more

abundant at medium, high and very high U sites as compared to low U sites. Some

metals in their reduced form are less soluble (Gadd, 2004) and therefore may have

lower bioavailability (Salbu et al., 1998). Thus, metal reduction by these microbes

may decrease the solubility and/or bioavailability of metals and hence these microbes

might be able to survive under elevated metal and U concentrations. The genes

associated with U, SO4 and metal reduction pathways may be better targets for

developing U contamination assessment tools because these genes would be up-

regulated at higher U conditions (Akob et al., 2012).

4.4.3 Bacterial community at Ranger Uranium Mine Land application Areas and

its potential role

Proteobacteria, Actinobacteria, Acidobacteria, Firmicutes and Bacteroidetes were

prevalent at RUM LAAs and these bacterial phyla have been previously identified at

U contaminated sites (Akob et al., 2007; Brodie et al., 2006; Cardenas et al., 2006,

2010, Chen et al., 2012; Geissler and Selenska-Pobell, 2005; Hwang et al., 2009;


112

Islam et al., 2011; Mondani et al., 2011; Moreels et al., 2008; Petrie et al., 2003;

Rastogi et al., 2010; Satchanska et al., 2004; Vishnivetskaya et al., 2011). These

bacteria use a range of mechanisms to survive under uraniferous environments. For

example, phylotypes belonging to Proteobacteria can reduce a variety of electron

acceptors, such as sulfate, nitrate, and nitrite, for growth and respiration and have

been shown to enzymatically reduce metals such as Cr(VI), Mn(IV), Fe(III) and

technetium(VII) (Wall and Krumholz, 2006). As dissimilatory iron(III)-reducing

bacteria and sulfate-reducing bacteria are the two major groups of microorganisms

capable of U(VI) reduction, Proteobacteria with metal and sulfate-reducing

capabilities are also involved in either direct enzymatic reduction of U to an

insoluble form (Lovley, 2000; Lovley, 1995; Lovley and Anderson, 2000; Wall and

Krumholz, 2006), or indirectly via production of reducing agents, such as Fe(II) and

sulfide (Hua et al., 2006; Liger et al., 1999). Moreover, certain members of

Protobacteria also biosorp U (Gonzilez-Muiioz et al., 1997).

Actinobacteria and Firmicutes can carry out phosphate precipitation and enzymatic

reduction of U based on environmental conditions (Martinez et al., 2007; Sani et al.,

2002; Suzuki et al., 2004, 2003; Wall and Krumholz, 2006). Moreover, Firmicutes

are involved in biosorption and bioaccumulation of U and cell wall of certain species

of Firmicutes also has the ability to bind uranium (Merroun et al., 2005).

Acidobacteria, on the other hand, contain only a few cultivable members. Therefore,

the physiological roles that these bacteria play in U contaminated sites, or in any

other environment, are still not well known (Barns et al., 2007; Jones et al., 2009).

However, some members of Acidobacteria are known to reduce nitrate, Mn(IV),

Fe(III) and humic acids (Coates et al., 1999). These Acidobacteria may indirectly

promote U(VI) reduction by producing compounds capable of reducing U(VI) to


113

U(IV) abiotically, such as microbially reduced iron compounds and humic acids

(Coates et al., 1999; Nevin and Lovley, 2000; O’Loughlin et al., 2003).

The survival mechanisms used by these bacterial phyla means that like the indicator

species, Sphingobacteria and Rhodobium, they possibly play an important role in

reducing the solubility and hence bioavailability and toxicity of U at RUM LAAs.

Less soluble species are also less mobile which means that they are not readily

leached from the soil which might limit the migration of U and prevent the

contamination of nearby soils and/or ground water. Therefore, bacterial phyla present

at RUM LAAs may play a vital role in determining the solubility, bioavailability and

mobility of U.

Chloroflexi, Cyanobacteria, Verrucomicrobia and Planctomycetes isolated at the

study sites are also known to occur at U contaminated sites (Akob et al., 2007; Barns,

et al., 2007; Brodie et al., 2006; Cardenas et al., 2006, 2008, 2010; Fields et al.,

2005; Mondani et al., 2011; Rastogi et al, 2010; Vishnivetskaya et al., 2011).

However, to my knowledge, classes of these phyla found at the study sites have not

been reported in the literature. Chloroflexi and Planctomycetes may be involved in

the digestion or decomposition of dead microbial cells and soil humic substances

(Cardenas et al., 2008; Yamada et al., 2006). Moreover, members belonging to

Chloroflexi are known to form filaments and produce hydrogen (Yamada et al.,

2006). Therefore, Chloroflexi may contribute to the stability of the bacterial

community by forming biofilms and can promote U reduction by transferring

electrons in the form of hydrogen to other phyla responsible for U reduction

(Cardenas et al., 2008). Cyanobacteria can act as a biosorbent of heavy metals (El-


114

Enany and Issa, 2000). Verrucomicrobia have few cultivable isolates so their

physiological role in natural environments is not well explored (Galperin, 2008).

These results show that contrary to the prediction that the bacterial community at

RUM LAAs would be different from other U contaminated sites due to its unique

climatic conditions, major classifiable bacterial phyla and classes present at RUM

LAAs were similar to those found at other U contaminated sites worldwide. This

means that these phyla are able to survive under a wide range of climatic conditions

and U contaminated environments and may represent important phyla at these

environments. These phyla possess multiple mechanisms to interact with and convert

U into less soluble species. Species having low solubility are generally less

bioavailable and hence less toxic. This might enable these phyla to survive under

high U concentrations at RUM LAAs. The occurrence of classes at RUM LAAs

which are not reported earlier may be due to their association with the unique wet-

dry tropical conditions of the Northern Territory, Australia. However these classes

were not abundant and only contributed less than 3% of the bacterial communities

present at RUM LAAs.

5 Conclusions

As predicted, the bacterial community present at low U sites at RUM LAAs was

significantly different from the bacterial community present at medium, high and

very high U sites. There was also a significant seasonal and temporal change in the

bacterial community. Uranium might be a key driver of these changes in the bacterial

community. Bacterial species associated with U concentration of > 200 ppm may

serve as good bioindicators of U contamination resulting from waste water irrigation


115

at RUM LAAs and as predicted might be involved in U reduction, bioaccumulation,

biosorption or biomineralization of U thus reducing its solubility and bioavailability

as a survival mechanism. However, contrary to the prediction, classifiable bacterial

groups present at RUM LAAs were similar to those present at other U-contaminated

sites worldwide suggesting that they are important phyla present in uraniferous

environments.

CHAPTER 5

GENERAL DISCUSSION AND CONCLUSIONS

Chapter 5. General discussion

117

Waste water management is a major issue at Ranger Uranium Mine (RUM) because

the mine is located in the wet-dry tropics of northern Australia where up to 2 m of

rain can fall in a single wet season. The release of water from the site into the

downstream environment is minimised by the use of retention ponds (RP1, RP2).

From 1985 to 2008–09, water stored in RP2 during the wet season has been managed

through land application (irrigation) to natural bushland on the mine lease during

each dry season (May–October). In addition to radionuclides [uranium (U), radium

(Ra), thorium (Th)], the water also contains sulfur (S) in the form of sulfate (SO42-

),

calcium (Ca), iron (Fe) and manganese (Mn) as major solutes, while copper (Cu) and

lead (Pb) are present in minor amounts (Akber et al., 2011a). The sites at RUM Land

Application Areas (LAAs) have different concentrations of U and other

physicochemical variables [sulfur (S), iron (Fe), calcium (Ca), aluminium (Al),

copper (Cu), zinc (Zn), thorium (Th), nickel (Ni), lead (Pb), Mn, U, moisture and

bulk density] due to differences in the quality of irrigation water (wetland treated vs

untreated), method of irrigation (spray vs flood irrigation), distance from the source

of irrigation (i.e., sprinkler heads), and time period over which these site have been

irrigated. For the purpose of this study, the sites were categorized as low U (2–20

ppm), medium U (200–400 ppm), high U (500–900 ppm) and very high U (> 900

ppm). Low U sites were significantly different from all other sites in that they also

had lower concentration of Ca, Cu, Fe and Al. Study sites at LAAs also showed a

significant seasonal and temporal change in soil U and physicochemical variables

due to differences in the amount of irrigation water applied, and preceding wet

season rainfall.

The use of land application as a water management method relies on the fact that the

LAAs have the tendency to bind U and most of the applied metals to the organic rich


118

surface horizons of soil profiles (Akber and Marten, 1992; Willett et al., 1993;

Hollingsworth et al., 2005). It is reported that these bound metals have low

leachability and will therefore be unlikely to impact the aquatic environment

downstream of RUM LAAs (Akber et al., 2011a). However, a full understanding of

the fate and transport of metals in and outside of the mine LAAs cannot be achieved

unless microbial-metal interactions and processes are included in models, theories

and interpretation of results (Ledin and Pedersen, 1996). This is because metals

contaminated environments are a reservoir of well adapted microorganisms which

possess multiple mechanisms to interact with, and resist toxic metals. Microbial-

metal interactions include direct or indirect oxidation and/or reduction of metals

which either increases or decreases metal solubility (DiSpirito and Tuovinen, 1982;

Lovley, 1993); direct or indirect oxidation of metal sulphides and leaching of certain

metals (Bosecker, 1997); indirect alterations in metal ionic states caused by Eh-pH

changes in the medium due to bacterial activities (Bosecker, 1997; Bacelar-Nicolau

and Johnson, 1999); biosorption of metals by microbial cell surface ligands

(DiSpirito et al., 1983; Selenska-Pobell et al., 1999); intracellular bioaccumulation

(Marques et al., 1991; Purchase et al., 1997); biomineralization by microbial

phosphatase activity (Macaskie et al., 2000; Martinez et al., 2007) and release of

metals by chelation or decomposition (Francis, 1990; Bosecker, 1997). Thus,

microbial-metal interactions have the potential to play a key role in fate and transport

of metals. Understanding microbial community composition at U contaminated sites

is a step towards understanding key biogeochemical processes at impacted sites,

which can inform management of these sites. Moreover, U resistant microbes that

can decrease the solubility, and hence bioavailability and mobility of U, can also be

used in bioremediation (Barlett et al., 2012; Ledin and Pedersen, 1996).


119

Impacts associated with metals are routinely assessed by their effects on living

organisms, because chemical analysis of the total metals in an environmental sample

is not sufficient to predict its toxicity in situ. Ecosystem-level interactions between

metals and living organisms are complicated and the “biological” concentration of

the metals cannot be calculated from the absolute, or “chemical”, concentration

(Nies, 2000). Thus, bioavailability and ecotoxicity must also be determined using

organisms (Kong et al., 1995) or parts of organisms (Nies, 2000). Indigenous soil

microorganisms are the most obvious group of soil biota to study as they are

ubiquitous, respond rapidly to changing conditions (Nannipieri et al., 2003) and are

thus ideal indicators of ecosystem-level change caused by metals contamination in

soil. There is a growing view that analysis of microbial communities should be

included in determining the bioavailability and toxicity of metals, and as a routine

component of ecological risk assessments (White et al., 1998).

In spite of the vital role of microorganisms in biogeochemical cycles of metals, their

potential in bioremediation and as bioindicators of environmental health, soil

microbiology has not been thoroughly investigated at RUM LAAs. Therefore, this

study was undertaken to test microbial resistance to U, to study the microbial

community diversity and to determine if specific microbes were potential

bioindicators of environmental health.

Since some microbial isolates recovered from metal contaminated environments

have adapted to stress conditions (Suzuki and Banfield, 2004), I hypothesized that

some microbes present at RUM LAAs would be resistant to U. Moreover, the

number of resistant microbes as well as their level of resistance is increased with

increasing loads of metals (Ryan et al., 2005). Therefore, I also hypothesized that


120

microbes retrieved from soil with high ‘field concentrations’ of U would be more

resistant to U than microbes isolated from soil with low field concentrations of U,

and the number of resistant microbes isolated from soils with high field

concentrations of U would be higher than the number of resistant microbes isolated

from low U soils.

To test these hypotheses, I cultured soil extracts from different soil U concentration

sites onto solid Luria-Bertani (LB) media plates spiked with uranyl nitrate, resulting

in zero (0 ppm), low (3 ppm), medium (250 ppm), high (600 ppm) and very high

(1500 ppm) concentration of U. These concentrations were similar to those found in

previous studies at these sites (Akber et al., 2011b). I used uranyl nitrate because it is

highly soluble and hence potentially bioavailable (Bleise et al., 2003; Gadd and

Fomina, 2011). Therefore, microbes growing in the presence of uranyl nitrate should

be resistant to the form of U (UO22+

) that is bioavailable and hence toxic to

microorganisms. Microbes from each soil U category were challenged with an

increasing concentration of U in the culture media, to determine if microbes cultured

from soil with high ‘field concentrations’ of U were more resistant or the number of

resistant microbes were higher than microbes cultured from soil with low field

concentrations of U.

5.1 Uranium resistant microbes

My results showed that microbes isolated from RUM LAAs were resistant to the

highly bioavailable form of U. Bacterial species including Bacillus, Paenibacillus,

Lysinibacillus, Klebsiella and Chryseobacterium were prevalent on media plates with

zero, low, medium and high concentration of U, but fungi outcompeted (rather than


121

inhibited) bacteria when the U concentration in the plate was very high. These data

supported my hypothesis that some microbes isolated from RUM LAAs would be

resistant to U. However, results showed no evidence that the microbes isolated from

high U soils were more resistant or that the number of resistant microbes at high U

soils was higher than number of resistant microbes isolated from low U soils.

Similarly, the community shift from bacteria to fungi under very high U treatment in

culture media occurred for all study sites irrespective of the soil U concentration

from which the microbes were isolated.

The bacteria and fungi isolated from U spiked culture plates were similar to those

isolated from other U contaminated sites, and some species have known mechanisms

to detoxify and resist U. For example, Bacillus sp. are involved in biomineralisation

(Martinez et al., 2007) and bioaccumulation of U (Tsuruta, 2006; Selenska-Pobell, et

al., 1999; Pollmann et al., 2006; Gorman-Lewis et al., 2005; Hennig et al., 2001) and

Paenibacillus sp. have been reported to precipitate and reduce U(VI) ions (Ahmed et

al., 2012; Reitz et al., 2008) into less soluble and hence less bioavailable or less toxic

U(IV) forms. Similarly, fungal genera Aspergillus, Cryptococcus and Penicillium are

U resistant (Hefnawy et al., 2002; Nakajima and Sakaguchi, 1986; Wang et al.,

2010a). These fungal genera can take up and remove U from contaminated sites by

binding uranyl ions to phosphate and carboxyl groups in the cell wall (Bhainsa and

D’Souza, 1999; Gadd and Fomina, 2011; Wang et al., 2010a). Thus, U resistant

bacteria and fungi isolated from RUM LAAs soils may have the potential to

bioaccumulate, precipitate, biomineralise, reduce or bind U. These microbial

processes are involved in decreasing the solubility, and hence bioavailability and

mobility, of some metals, such as U, and have thus received considerable attention

because of their potential for bioremediating U contaminated sites and waste streams


122

(Macaskie et al., 1996). Therefore, bacteria and fungi isolated from RUM LAAs may

have the potential for bioremediating U contaminated soils and waters. Moreover,

these highly resistant isolates also represent important organisms to study for

valuable insights into mechanisms of resistance.

The capacity of fungi to grow in the presence of high levels of U and out-compete

bacteria is also in line with previous findings. In the literature there is evidence that

fungi are more resistant to metals (such as Zn, Cu, Cd, Ni and Pb) than bacteria. A

laboratory study conducted on a forest soil polluted with Zn showed higher fungal

activity in the contaminated soil than in the control soil and an increasing relative

fungal/bacterial ratio with increasing Zn concentration (Rajapaksha et al., 2004).

Another study, carried out on a fallow paddy field contaminated with Zn, Cu and Cd,

also showed higher sensitivity of bacteria to metal contamination than fungi and it

was concluded that bacterial communities were affected by metal contamination,

whereas a correlation between metal contamination and fungal community was not

found (Hiroki, 1992). Many other studies have shown that microbial populations

respond to metals like Zn, Cu, Cd, Ni and Pb by a shift from bacteria to fungi

(Chander et al., 2001; Khan and Scullion, 2002; Kostov and van Cleemput, 2001;

Olayinka and Babalola, 2001; Wang et al., 2010b). Although my culture studies

confirmed these published reports, the community shift from bacteria to fungi under

very high U concentrations was not detected in the field. Furthermore, fungi did not

grow in culture plates spiked with zero, low, medium and high U concentrations

even though fungi were recovered from these same U concentration soils in the very

high U spiked culture plates.


123

5.2 Competition between cultured bacteria and fungi

The absence of fungi in the culture plates with zero, low, medium and high U

concentration and their presence in the field with similar U concentrations may be

due to secretion of antifungal compounds, secondary metabolites and antibiotics by

bacteria present in the culture plates (De Boer et al., 2007). In soils, the effect of

these antimicrobials may be minimized by sorption onto the soil particles (Marshall,

1975) or by the presence of helper microbial strains (Vartoukian et al., 2010) thus

enabling fungi to grow in the presence of bacteria in situ. Moreover, soil microbial

communities are rarely as dense as in laboratory experiments. Therefore, potential

dilution effects must also be considered both for the microbes and for the excreted

antimicrobials (Mille-Lindblom et al., 2006). In future studies it would be possible to

assess the antifungal capacity of cultured bacteria using established methods (Qazi et

al., 2009; Petatan-Sagahon et al., 2011).

Moreover, faster growing bacteria may prevent the growth of fungi by consuming

nutrients in culture media (Mille-Lindblom et al., 2006) and this may also account

for my results of no fungi on the zero, low, medium and high U concentration plates.

Alternatively, fungi may have outcompeted bacteria under very high U concentration

in culture media due to their higher resistance (Khan and Scullion 2002; Wang et al.,

2010b). Those same ‘outcompeted bacteria’ may survive very high U concentrations

in the field because field U at RUM LAAs has lower solubility (Medley, 2007) and

hence lower bioavailability compared to the U used in the spiked culture media

experiments. One way to test a competition hypothesis (as opposed to resistance)

would be to run two sets of parallel experiments, using the same U spiking regime,

but with both bacteria-specific and fungal-specific culture media (Mille-Lindblom et


124

al., 2006) ‒ in other words, attempt to remove the potential for competition. The

ability of bacteria and eukaryotes to compete in this way, raises questions about the

capacity of culture based assays to truly represent in situ microbial communities.

Due to the questions regarding the suitability of culturing to assess bacteria

community diversity, I also applied a culture independent approach to study the

bacterial community in soil at RUM LAAs. Since community level changes in

bacteria have been reported in response to changes in physicochemical variables

(Akob et al., 2007; Islam et al., 2011), I hypothesized that the bacterial community at

low U sites would be significantly different from medium, high and very high U sites

and there would also be seasonal and temporal changes in the composition of the

bacterial community due to seasonal and temporal changes in soil U concentration

and other physicochemical variables. I also hypothesized that U and/or SO42-

reducing bacteria would be more abundant at medium, high and very high U sites,

compared to low U sites, and that the bacterial community at RUM LAAs would be

different from other U contaminated sites due to its unique climatic conditions

(Selenska-Pobell, et al., 2002; Suzuki et al., 2003).

I measured bacterial community-level responses to the spatial, temporal, and

seasonal changes in soil U concentration and physicochemical variables (S, Fe, Ca,

Al, Cu, Zn, Th, Ni, Pb, Mn, U, moisture and bulk density). The soil bacterial

community changes were assessed using next generation 454 pyrosequencing during

the dry and the wet seasons for two consecutive years at low, medium, high and very

high U sites. Changes in the bacterial community and their associations with

environmental variables were measured using multivariate analysis. One of the

advantages of pyrosequencing is that it generates hundreds of thousands of sequence


125

reads in a single run, thus enabling the detection of rare species which is of

importance in ecological studies (Margulies et al., 2005; Roesch et al., 2007;

Siqueira et al., 2012; Sogin et al., 2006).

Multivariate analysis is commonly used in ecology to correlate plants and animals

diversity with environmental variations. These tools are equally useful for microbial

ecology now that high throughput microbial assessment is available through next

generation sequencing technologies such as pyrosequencing (Ramette, 2007). In fact,

microbial ecology has increasingly benefited from multivariate analyses to measure

the correlation between bacterial community composition and environmental

variables, to study temporal and seasonal dynamics exhibited by bacterial

community, as well as to identify microbial species as indicators of metal stress

(Hwang et al., 2009).

5.3 Correlation between soil uranium concentrations and the bacterial

community

There was no significant difference among the bacterial communities of soil with

medium, high and very high uranium based on pyrosequencing of the bacteria 16S

rRNA gene and culture based approach. However, pyrosequencing showed that the

bacterial community in soil with low U was significantly different from those in soil

with medium, high or very high U. This difference was not detected using the

culturing approach. Thus my hypothesis that the bacterial community at low U sites

would be significantly different from medium, high and very high U sites was

supported by pyrosequencing results. Analyses showed that the community structure

was best correlated with soil U concentrations. Therefore, bacterial community at


126

low U sites may have significantly differed from all other sites because low U sites

had 2–20 ppm U that was 10–100 times lower than the other sites. However, there

was no significant difference among bacterial communities present at medium, high

and very high U sites as the relative differences in soil U concentration at medium

(200 – 400 ppm), high (500–900 ppm) and very high (> 900 ppm) U sites were non-

significant. I speculate that a U concentration of 200 ppm at the LAAs may be a

threshold level at which the bacterial community changes from U sensitive to U

resistant bacteria. A further speculation is that the bacterial community may not have

changed by a further increase in U concentration beyond 200 ppm at medium, high

and very high U sites due to their acquired resistance (Mondani, 2011; Joner et al.,

2007). I recommend that future studies should measure this threshold level more

precisely in the range between > 20 ppm and < 200 ppm U.

In addition to U, the significant change in bacterial community structure between

low and all other (medium, high and very high U) sites may have also been driven by

differences in the Ca, Al and Cu concentrations. This is because Ca, Al and Cu had

higher concentration at medium, high and very high U sites compared to low U sites

and analysis indicated that these metals were also strongly correlated with the

bacterial community in this study; an outcome which has also been seen elsewhere

(Banu et al., 2004; Sridevi et al., 2012; He et al., 2012).

5.4 Bacterial indicator of high uranium at Ranger Uranium Mine Land

Application Areas

Since the bacterial community at low U sites was significantly different from that

present at medium, high and very high U sites, an indicator species approach


127

(Cardenas et al., 2010) was used to identify the bacterial species that were associated

with > 200 ppm U at medium, high and very high U sites. This found that bacterial

OTUs closely related to members of Sphingobacteria, Kitasatospora,

Candidate_division_WS3 and Rhodobium, were consistently present only at sites

with > 200 ppm U and hence may serve as useful indicators of U contamination >

200 ppm at RUM LAAs. However, these bacterial phylotypes have been isolated at <

200 ppm U from other sites (Brodie et al., 2006; Van Nostrand et al., 2007; Radeva

and Selenska-Pobell, 2004; Satchanska et al., 2004; Selenska-Pobell, 2002). These

results show that bioindicators of U contamination identified at one site may not be

suitable for other sites due to differences in climate, geography, concentration and

bioavailability of metal contaminants, and this highlights the need for identifying

site-specific indicator species.

Indicator species such as Sphingobacteria and Rhodobium sp. specific to > 200 ppm

U at medium, high and very high U sites at RUM LAAs may reduce uranium(VI),

sulfate, chromium(VI), manganese(IV), iron(III), and technetium(VII) (Caumette et

al., 2007; Holmes, 2006; Madden et al., 2009). Thus, the hypothesis that U and/or

SO42-

reducing bacteria would be more abundant at medium, high and very high U

sites as compared to low U sites was supported by the results.

In addition to Sphingobacteria, Kitasatospora, Candidate_division_WS3 and

Rhodobium that were consistently associated with > 200 ppm U at RUM LAAs sites,

Firmicutes were also more abundant at most of the sites with > 200 ppm U during

wet season year 1 and dry season year 2. Similarly, Firmicutes (Bacillus sp.) were

also slightly more abundant in culture plates spiked with 250 ppm U compared to

zero and 3 ppm U plates thus both pyrosequencing and culturing techniques


128

identified Firmicutes as being more prevalent under U concentrations > 200 ppm.

Firmicutes have also been reported at other U contaminated environments (Akob et

al., 2007; Cardenas, 2010; Hwang et al., 2009; Mondani et al., 2011; Rastogi et al,

2010; Vishnivetskaya et al., 2011). Based on these results it is logical to consider

Firmicutes as a potential indicator of U contamination. However, Firmicutes were

not identified as suitable indicators of U contamination using indicator species

analysis because their prevalence at sites with > 200 ppm U changed with season and

time and they were not consistently abundant at these sites. These data reinforce the

value of measuring the response of potential indicator species at multiple time points.

Moreover, Firmicutes as a large group of bacteria may not be useful bioindicators of

U contamination because it would be difficult to identify signature specific

sequences from which to develop detection probes.

While Firmicutes were more prevalent under higher U concentrations based on both

culturing and pyrosequencing results, low U sites were generally dominated by

Acidobacteria and Verrucomicrobia based on pyrosequencing. However

Acidobacteria and Verrucomicrobia were not recovered in culturing plates spiked

with low U concentration. This may be because Acidobacteria and Verrucomicrobia

are known to be recalcitrant to culturing using traditional media (Jones et al., 2009;

Kielak et al., 2010; Navarrete et al., 2013) while members of Firmicutes can easily

be cultured on traditional media such as LB. In addition, members of the

Acidobacteria are slow growing. So the incubation period of 48 hours used in this

study may not have been sufficient for these organisms and they would have been

outcompeted by the faster growing Firmicutes (Navarrete et al., 2013). Therefore,

the incongruence between the culture and pyrosequencing results for dry season 1

(when the culturing was conducted) was most likely due to culturing conditions used


129

in this study not being suitable for the Acidobacteria and Verrucomicrobia which

were the phyla that were more prevalent at U concentrations < 200 ppm.

Furthermore, the use of media and an incubation period suitable for Firmicutes

resulted in these organisms being identified as the dominant group in soil samples

based on culturing, a result not reflected in pyrosequencing findings. Hence, the

dominance of Firmicutes (Bacillus sp.) in culture does not reflect the field situation

because it is the result of culturing bias. This bias and limitation of culturing

technique to recover only a small number of bacterial community present in the soil

(Bollmann et al., 2007; Ferrari and Gillings 2009; Kaeberlein et al., 2002; Nichols et

al., 2008) may also be the reason why I did not detect a significant difference in

bacterial community between low U sites and all other (medium, high and very high)

U sites in culture plates. While culturing approach applied in this study was not

suitable for assessing bacterial community diversity in RUM LAAs soil samples it

facilitated the identification of easily cultivable bacteria species that are resistant to

high uranium concentrations and hence may be suitable for the development of

bioremediation technology.

5.5 Bacterial Community present at Ranger Uranium Mine Land Application

Areas

In addition to Firmicutes, Acidobacteria and Verrucomicrobia, I also retrieved

Proteobacteria, Actinobacteria and Bacteroidetes related lineages at RUM LAAs

using pyrosequencing. These bacterial phyla have previously been recovered from U

contaminated sites (Akob et al., 2007; Brodie et al, 2006; Cardenas et al., 2006,

2010; Chen et al., 2012; Geissler and Selenska-Pobell, 2005; Hwang et al., 2009;

Islam et al., 2011; Mondani et al., 2011; Moreels et al., 2008; Petrie et al., 2003;


130

Rastogi et al., 2010; Satchanska et al, 2004; Vishnivetskaya et al., 2011). Members

belonging to these bacterial phyla use a range of survival mechanisms under

uraniferous environments. These mechanisms include direct and indirect reduction,

phosphate precipitation, bioaccumulation, biosorption and binding U to cell wall

components (Sani et al., 2002; Suzuki et al., 2004; Martinez et al., 2007; Lovley,

2000; Lovley and Anderson, 2000; Wall and Krumholz, 2006). These survival

mechanisms play an important role in converting highly soluble U into less soluble U

forms thus reducing its bioavailability and toxicity (Wall and Krumholz, 2006). Less

soluble chemical species are also less mobile and this may limit the migration of U

and prevent the contamination of nearby soils and/or ground water (Charbonneau,

2009; Macaskie et al., 1996). It is therefore possible that bacterial phyla present at

RUM LAAs may play a role in U solubility, bioavailability and mobility.

Due to its unique climatic conditions, I predicted that the bacterial community

present at RUM LAAs would be different to other U contaminated environments

(Selenska-Pobell et al., 2002). However, this prediction was not supported, as

classifiable bacterial phyla and classes found at RUM LAAs were similar to those

reported at other U contaminated sites worldwide. This illustrates that these phyla

may flourish under a wide range of climatic conditions and U contaminated

environments and may represent important phyla which may be involved in

fundamental biogeochemical processes in these environments.

In summary, high throughput pyrosequencing approach allowed an extensive survey

of the microbial communities at RUM LAAs. Using this approach I was able to track

microbial community changes in comparison to analogue sites. A shift in the

bacterial community structure and membership was observed with increase in soil U


131

concentration. Moreover, pyrosequencing coupled with indicator species analysis

enabled the identification of statistically robust bioindicators of U contamination

(Cardenas et al., 2010) and I was able to detect bacteria significantly associated with

U concentration of > 200 ppm. Thus, this study provided useful soil microbiology

data at RUM Uranium Mine LAAs.

This project has also extended our understanding of U biogeochemistry at RUM

LAAs. LAAs soils are known to retain U within the soil profile (Akber et al., 2011a;

Hollingsworth et al., 2005; Willett et al., 1993). Microorganisms isolated from the

LAAs in my study may have a vital role in limiting the migration of U from LAA

soils as these microorganisms have been reported to reduce, bioaccumulate,

biomineralise or precipitate U (Sani et al., 2002; Suzuki et al., 2004; Martinez et al.,

2007; Lovley, 2000; Lovley and Anderson, 2000; Wall and Krumholz, 2006), thus

decreasing the solubility and hence mobility of U in LAAs soils (Charbonneau, 2009;

Macaskie et al., 1996).

Although, conventional culturing did not reveal a difference in microbial community

structure due to variations in soil U concentrations at RUM LAAs, the approach

afforded an opportunity to test U resistance of indigenous microbes at RUM LAAs.

Uranium resistant microbes isolated at RUM LAAs using culturing technique may

provide an important resource for studying U bioremediation (Martinez et al., 2007;

Selenska-Pobell, 1999; Pollmann et al., 2006; Gorman-Lewis et al., 2005) and

mechanisms of resistance to U. Moreover, data derived from culture experiments may

not always reflect in situ data, so any future laboratory studies would need to be

verified in the field.


132

This is the first microbiology study at RUM LAAs using culture dependent and

culture independent techniques coupled with multivariate and indicator species

statistical analysis. This work has laid a foundation for future microbiology studies at

this site to further explore soil-microbe-metal interactions and their effect on metals

(including U) transport and mobility which may be useful for developing sustainable

management and rehabilitation practices.

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APPENDICES

Ap

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hy

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Fe (

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Mn

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pm

) N

i (p

pm

) C

u (

pp

m)

Zn

(p

pm

)

CC

LA

A-0

76

1270

0±14

77.5

0

98.3

9±29.2

1

5410

±6

61.5

7

40.8

9±7.2

1

9.2

6±0.6

9

7.4

8±0.4

2

4.2

8±0.3

2

DLA

A-1

77 E

XT

1410

0±25

8.8

4

250.5

8±10.1

9

9090

±1

49

5.4

0

31.5

0±1.8

7

7.6

7±0.2

6

5.7

5±0.4

3

4.7

6±0.2

6

RP

1-1

44

1520

0±23

41.5

8

180.8

0±37.8

1

6580

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35

1.9

0

39.2

6±4.3

6

7.9

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1

6.1

4±0.6

0

6.1

3±0.6

5

JE

LA

A-0

20

2530

0±49

21.0

8

291.1

9±21

7.1

2

1590

0±41

25.8

9

108.1

6±27.8

3

14.0

4±1.7

5

13.3

4±1.2

7

6.9

7±0.6

8

DLA

A-1

85

2870±2

20.3

0

124.8

8±29.0

1

5170

±5

70.6

3

18.5

8±1.3

8

6.8

6±0.5

3

5.0

5±0.3

8

2.1

6±0.2

5

MLA

A-1

21 E

XT

1600

0±96

7.9

9

267.0

0±63.5

2

9870

±7

01.9

1

242±16

.08

17.6

3±1.0

3

17.2

5±1.0

3

6.6

5±0.4

4

DLA

A-1

70 E

XT

1330

0±56

70.3

6

187.6

0±36.8

6

6750

±2

00

9.5

5

39.9

6±10.0

4

7.3

3±2.1

2

5.9

7±2.5

4

4.3

7±4.0

7

DLA

A-2

22

2020

0±45

29.3

0

468.6

0±11

9.7

1440

0±21

82.2

33.6

4±10.4

19.4

0±3.8

26.9

1±3.7

11.7

8±4.0

R

P1-1

38

1420

0±76

59.8

3

454.0

0±25

2.9

7

1560

0±80

16.2

3

115±90

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13.4

0±5.0

1

9.7

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7

8.7

6±4.6

3

JE

LA

A-0

01

3340

0±11

956.0

9

558.9

7±49

2.0

2

2490

0±51

39.0

7

100.4

8±51.9

1

20.3

4±4.3

8

22.2

7±3.9

5

20.6

8±6.1

8

CC

LA

A-0

36

3410

0±71

88.6

7

558.0

0±14

6.8

7

3710

0±45

77.3

4

100.5

4±16.2

1

36.8

9±8.1

0

35.9

8±6.3

0

27.1

7±33.6

2

RP

1-1

34

2790

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73.5

8

685.4

8±19

7.5

6

2520

0±24

00.6

2

300±17

9.4

8

18.9

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0

17.5

5±1.3

9

13.6

2±2.5

9

DLA

A-1

57 E

XT

2340

0±33

82.3

1

485.8

0±13

3.3

4

1090

0±10

84.5

8

42.5

4±10.8

4

7.1

2±0.7

4

5.4

3±1.0

2

3.5

1±1.4

7

DLA

A-2

28

1920

0±35

23.7

8

794.8

0±31

0.6

1

1680

0±41

71.5

7

51.7

8±16.9

5

17.2

2±2.2

3

36.6

3±4.5

0

6.7

5±1.4

4

DLA

A-2

27

2640

0±46

05.7

6

628.8

0±21

5.0

9

1570

0±17

33.4

9

98.9

0±26.4

0

11.4

0±1.6

1

26.1

3±3.7

4

7.3

1±1.0

7

MLA

A-1

01 E

XT

2490

0±58

99.5

8

769.2

0±35

2.6

5

2270

0±34

04.4

1

901±25

5.3

9

22.3

0±3.8

0

35.8

2±6.9

1

7.7

8±2.7

5

MLA

A-1

06 E

XT

2070

0±47

72.5

3

695.2

0±31

3.7

4

2140

0±58

05.4

3

365.8

0±12

6.2

0

14.2

1±2.7

0

21.2

9±3.6

9

7.2

3±1.9

0

MLA

A-0

32

1690

0±47

65.7

1

781.6

5±28

9.0

3

1610

0±42

42.4

0

925.4

0±28

7.6

1

14.2

8±3.3

3

24.3

7±5.2

6

14.9

6±4.3

7

Ap

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Th

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Mo

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Bu

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CC

LA

A-0

76

4.4

6±0.3

9

26.0

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4

4.0

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5

2.3

6±0.1

6

0.6

3±0.1

8

0.0

4±0.0

1

0.0

1±0.0

0

1.6

7±0.0

0

DLA

A-1

77 E

XT

6.8

1±0.1

8

254.4

6±98.4

3

5.0

0±0.1

1

2.6

1±0.6

8

0.9

6±0.7

2

0.0

6±0.0

4

0.0

5±0.0

0

1.6

2±0.0

0

RP

1-1

44

8.8

4±1.0

0

174.1

9±67.8

6

18.5

4±1.4

2

4.6

7±0.9

8

0.9

9±0.4

3

0.0

5±0.0

2

0.1

8±0.0

0

1.6

1±0.0

0

JE

LA

A-0

20

10.6

9±2.6

6

104.6

5±56.1

1

7.9

8±0.4

7

13.6

7±11.0

7

3.0

1±1.8

3

2.5

5±0.0

7

0.0

8±0.0

0

1.7

4±0.0

0

DLA

A-1

85

1.8

1±0.0

9

253.1

7±89.6

0

1.6

9±0.1

9

2.7

7±0.7

0

0.5

6±0.2

8

0.0

3±0.0

1

0.0

6±0.0

0

1.6

7±0.0

0

MLA

A-1

21 E

XT

7.8

0±1.1

6

62.7

3±9.4

3

5.1

7±0.3

3

10.9

1±3.4

5

1.5

2±0.7

6

0.0

7±0.0

3

0.0

3±0.0

0

1.7

1±0.0

0

DLA

A-1

70 E

XT

7.1

2±2.0

7

183.5

7±34.0

1

12.9

3±4.3

3

20.4

0±10.2

3

0.9

0±0.0

4

0.0

6±0.0

0

0.0

0±0.0

0

1.6

0±0.0

0

DLA

A-2

22

4.0

6±3.6

135.0

5±18.2

10.3

1±1.8

222.4

9±98.1

0.9

7±0.1

3

0.0

7±0.0

1

0.0

5±0.0

1.7

3±0.0

0

RP

1-1

38

7.2

6±2.6

1

240.1

9±67.9

6

13.0

2±3.9

0

344.2

5±22

3.8

2

1.0

4±0.6

6

0.0

9±0.0

6

0.1

1±0.0

0

1.9

0±0.0

0

JE

LA

A-0

01

17.8

8±3.8

2

181.3

1±42.0

8

16.7

6±5.2

8

407.3

3±25

0.9

0

0.9

5±0.7

6

0.0

6±0.0

4

0.1

2±0.0

0

1.8

2±0.0

0

CC

LA

A-0

36

6.0

2±0.8

1

141.8

2±30.1

5

4.5

3±0.5

0

280.2

3±30

3.7

9

1.3

1±0.7

3

0.0

9±0.0

4

0.0

5±0.0

0

1.6

2±0.0

0

RP

1-1

34

12.9

0±1.3

3

232.8

1±75.8

9

14.4

7±0.5

0

520.9

7±14

5.2

0

1.9

3±0.4

0

0.1

3±0.0

3

0.0

9±0.0

0

1.7

0±0.0

0

DLA

A-1

57 E

XT

9.0

8±1.1

9

69.3

7±12.0

7

7.9

6±1.1

3

633.5

4±93.9

0

1.0

2±0.2

5

0.0

6±0.0

1

0.0

7±0.0

0

1.4

6±0.0

0

DLA

A-2

28

5.0

1±0.6

9

115.1

8±37.0

2

5.9

5±0.8

8

665.0

0±33

4.3

1

1.5

5±0.6

7

0.1

0±0.0

4

0.1

4±0.0

0

1.6

9±0.0

0

DLA

A-2

27

4.9

4±0.2

6

105.1

6±23.1

9

11.3

5±1.6

8

857.6

0±22

9.7

2

2.1

8±0.9

7

0.1

1±0.0

4

0.0

7±0.0

0

1.5

6±0.0

0

MLA

A-1

01 E

XT

12.0

4±2.3

7

99.2

2±28.2

2

9.2

3±1.4

4

819.8

5±49

2.5

6

3.1

9±1.2

2

0.1

3±0.0

5

0.0

4±0.0

0

1.6

7±0.0

0

MLA

A-1

06 E

XT

8.2

7±1.3

9

90.5

8±58.7

3

11.2

0±2.5

8

984.5

3±48

8.5

6

3.5

2±2.3

2

0.1

4±0.0

7

0.0

7±0.0

0

1.5

9±0.0

0

MLA

A-0

32

7.6

2±1.7

0

91.7

2±22.1

6

7.2

5±1.5

3

1730

.00±5

21.4

1

1.9

1±0.7

4

0.1

0±0.0

3

0.0

9±0.0

0

1.7

8±0.0

0

Ap

pen

dic

es

17

2

Ta

ble

A-2

S

oil

ph

ysi

coch

emic

al p

aram

eter

s o

f yea

r 1

wet

sea

son

sam

ple

s. V

alu

es r

epre

sen

t m

ean

of

5 s

ub

sam

ple

s ±

sta

nd

ard

dev

iati

on

.

Mo

istu

re a

nd

bu

lk d

ensi

ty w

as m

easu

red

on

1 a

dd

itio

nal

sam

ple

co

llec

ted

fro

m e

ach

sit

e

a) S

ite

A

l (p

pm

) C

a (

pp

m)

Fe (

pp

m)

Mn

(p

pm

) N

i (p

pm

) C

u (

pp

m)

Zn

(p

pm

)

CC

LA

A-0

76

1270

0±99

3.9

8

96.3

2±51.2

6

4980

±4

40.3

6

38.8

6±4.1

1

11.4

9±0.8

1

7.7

4±0.4

7

5.3

5±2.8

4

DLA

A-1

77 E

XT

1380

0±12

63.7

2

183.1

2±14.7

0

7030

±1

81

3.3

1

29.3

9±2.9

0

8.8

5±0.5

7

5.8

0±0.5

3

4.7

0±0.9

1

RP

1-1

44

1480

0±21

73.2

5

130.7

2±43.7

5

5210

±1

01

5.6

2

38.3

0±2.0

2

10.4

8±2.6

5

6.9

2±1.1

5

6.0

6±0.8

4

JE

LA

A-0

20

2480

0±27

38.9

8

256.9

6±15

6.0

2

1470

0±16

20.1

9

102.5

3±38.0

7

15.7

9±0.6

7

12.8

0±0.9

3

6.5

8±0.2

7

DLA

A-1

85

277

0±420

.56

98.6

7±16.4

3

4320

±1

04

6.1

4

19.1

1±1.0

8

10.3

3±2.3

0

5.1

1±0.9

8

2.1

4±0.2

6

MLA

A-1

21-E

XT

1640

0±57

2.7

1

201.5

9±32.7

1

9710

±4

58.8

0

239.1

3±9.1

0

19.1

8±1.0

0

18.0

4±0.9

1

7.5

1±0.6

4

DLA

A-1

70 E

XT

1280

0±60

5.8

1

161.3

0±12.7

0

5740

±3

19.6

6

36.6

3±2.9

1

8.2

1±0.7

3

5.1

4±0.9

3

4.5

1±0.6

3

DLA

A-2

22

2000

0±17

44.4

2

456.0

9±18.6

6

1070

0±15

92.5

2

32.8

6±3.8

2

14.6

9±1.7

7

26.7

2±4.1

4

9.4

1±1.9

4

RP

1-1

38

1370

0±11

00.9

1

287.4

9±40.8

2

1100

0±97

4.6

8

114.3

9±19.9

0

10.2

4±0.6

7

9.3

7±0.5

1

7.0

6±0.7

3

JE

LA

A-0

01

3300

0±62

81.9

6

469.6

7±77.9

3

2370

0±37

65.2

4

93.9

8±10.9

5

18.9

6±4.8

9

22.1

8±2.9

5

21.5

6±3.6

2

CC

LA

A-0

36

3450

0±76

01.1

8

421.9

9±74.8

4

3370

0±55

61.9

2

108.8

4±29.8

4

43.0

9±7.5

1

36.9

6±7.4

6

17.1

7±2.7

0

RP

1-1

34

2811

0±83

3.9

7

599.6

8±66.1

3

2390

0±12

07.0

6

278.0

0±3.0

2

20.4

7±0.9

9

18.6

0±0.5

2

15.5

5±5.5

2

DLA

A-1

57 E

XT

2356

0±17

55.8

5

416.4

7±89.5

6

9840

±2

86.3

6

44.0

9±8.0

7

9.0

8±0.3

2

5.4

9±0.7

9

5.0

0±0.7

1

DLA

A-2

28

1888

0±12

98.8

5

626.3

1±42

7.4

6

1630

0±11

61.6

8

59.5

4±17.6

8

22.0

2±7.1

2

35.9

9±5.1

0

9.9

4±0.8

6

DLA

A-2

27

2609

0±19

13.2

4

618.9

1±38.0

3

1490

0±10

23.7

2

77.2

4±18.6

5

13.1

5±0.9

3

27.5

0±2.5

9

11.6

7±1.2

0

MLA

A-1

01 E

XT

2430

0±74

6.3

2

747.0

2±79.2

6

2060

0±12

95.9

6

878.9

8±58.6

6

18.8

3±0.9

1

33.9

4±0.5

9

8.3

9±0.7

4

MLA

A-1

06 E

XT

2060

0±10

32.9

6

668.4

3±90.2

4

2050

0±12

73.5

8

325.9

4±62.0

9

14.2

6±0.2

9

20.3

7±1.9

4

8.7

4±1.4

0

MLA

A-0

32

1730

0±16

04.0

6

743.2

0±43

9.0

6

1570

0±16

76.9

0

918.5

6±52

5.8

1

14.3

2±2.7

7

24.5

1±4.1

9

21.6

8±8.7

6

Ap

pen

dic

es

17

3

Ta

ble

A-2

S

oil

ph

ysi

coch

emic

al p

aram

eter

s o

f yea

r 1

wet

sea

son

sam

ple

s. V

alu

es r

epre

sen

t m

ean

of

5 s

ub

sam

ple

s ±

sta

nd

ard

dev

iati

on

.

Mo

istu

re a

nd

bu

lk d

ensi

ty w

as m

easu

red

on

1 a

dd

itio

nal

sam

ple

co

llec

ted

fro

m e

ach

sit

e

b) S

ite

P

b (

pp

m)

S (

pp

m)

Th

(p

pm

) U

(p

pm

) T

OC

%

TN

%

Mo

istu

re

(g/c

m3)

Bu

lk d

en

sit

y

(g/c

m3)

CC

LA

A-0

76

4.4

5±0.4

1

23.5

5±11.7

4

4.0

2±0.2

7

2.5

5±0.2

8

0.9

6±0.6

4

0.0

5±0.0

2

0.1

2±0.0

0

1.6

8±0.0

0

DLA

A-1

77 E

XT

6.9

5±1.2

8

182.7

8±14

5.9

3

4.1

6±0.2

7

2.9

1±0.6

0

1.0

2±0.5

0

0.0

6±0.0

3

0.2

2±0.0

0

1.4

7±0.0

0

RP

1-1

44

8.8

4±0.8

2

159.9

2±57.6

2

15.0

6±0.8

0

15.9

6±24.3

6

0.7

3±0.3

0

0.0

5±0.0

2

0.0

8±0.0

0

1.5

3±0.0

0

JE

LA

A-0

20

11.0

1±1.7

5

86.5

1±25.5

5

7.8

6±0.1

7

6.0

8±1.5

8

2.1

5±0.8

9

0.1

1±0.0

4

0.0

6±0.0

0

1.6

4±0.0

0

DLA

A-1

85

1.8

3±0.5

1

203.8

5±35.5

6

1.5

3±0.1

9

2.9

9±0.9

7

0.5

1±0.2

9

0.0

4±0.0

1

0.3

3±0.0

0

1.5

7±0.0

0

MLA

A-1

21 E

XT

8.2

8±0.4

8

61.0

8±4.5

4

5.5

7±0.1

4

9.8

9±1.5

7

1.0

9±0.1

6

0.0

6±0.0

1

0.0

4±0.0

0

1.6

6±0.0

0

DLA

A-1

70 E

XT

7.1

0±0.1

8

183.1

8±37.1

2

10.0

9±1.1

4

12.8

9±8.0

6

0.7

7±0.1

6

0.0

5±0.0

1

0.3

3±0.0

0

1.6

9±0.0

0

DLA

A-2

22

3.8

3±0.6

9

118.7

4±22.7

6

6.7

9±0.3

4

195.8

3±43.7

3

1.0

5±0.0

2

0.0

7±0.0

0

0.0

5±0.0

0

1.7

2±0.0

0

RP

1-1

38

7.3

3±0.2

8

173.0

4±32.5

2

8.7

1±0.5

7

168.6

6±43.7

6

0.5

7±0.2

8

0.0

5±0.0

2

0.1

9±0.0

0

1.7

3±0.0

0

JE

LA

A-0

01

18.0

1±4.4

6

75.1

2±17.1

6

12.4

8±0.8

2

358.0

5±69.0

1

1.2

2±0.4

4

0.0

7±0.0

2

0.1

2±0.0

0

1.8

3±0.0

0

CC

LA

A-0

36

5.7

9±0.7

2

107.6

2±18.0

3

3.9

8±0.5

7

151.1

6±11

4.2

4

1.2

5±0.2

7

0.0

8±0.0

2

0.0

5±0.0

0

1.4

7±0.0

0

RP

1-1

34

13.3

0±0.6

0

166.2

6±14.0

4

13.0

8±0.5

6

400.7

4±56.2

2

1.3

6±0.2

2

0.1

0±0.0

1

0.2

3±0.0

0

1.7

7±0.0

0

DLA

A-1

57 E

XT

8.5

2±0.3

6

57.3

4±9.4

9

6.7

0±0.2

9

434.2

5±16

6.7

9

0.8

0±0.3

1

0.0

5±0.0

2

0.1

9±0.0

0

1.5

6±0.0

0

DLA

A-2

28

5.1

3±1.6

8

113.2

3±51.7

5

5.0

9±0.4

3

758.5

6±55

3.1

5

5.8

6±6.8

9

0.1

5±0.1

3

0.0

8±0.0

0

1.6

4±0.0

0

DLA

A-2

27

5.2

4±0.1

2

105.1

8±6.8

8

11.8

0±0.3

9

728.6

5±13

9.6

0

1.7

8±0.0

0

0.1

0±0.0

0

0.0

3±0.0

0

1.7

7±0.0

0

MLA

A-1

01 E

XT

11.7

2±3.5

5

80.7

7±14.0

9

6.8

1±0.2

5

460.4

9±18

6.1

6

2.1

0±0.0

2

0.0

9±0.0

0

0.0

5±0.0

0

1.7

4±0.0

0

MLA

A-1

06 E

XT

7.9

5±3.1

9

88.5

4±20.9

4

8.5

3±0.2

0

643.6

1±19

9.0

7

1.8

5±0.4

0

0.0

9±0.0

2

0.0

3±0.0

0

1.4

7±0.0

0

MLA

A-0

32

7.9

9±1.6

1

88.5

6±19.0

2

6.6

1±0.2

9

1460

.00±3

64.9

4

2.1

1±1.1

4

0.1

2±0.0

7

0.0

9±0.0

0

1.7

1±0.0

0

Ap

pen

dic

es

17

4

Ta

ble

A-3

S

oil

ph

ysi

coch

emic

al p

aram

eter

s o

f yea

r 2

dry

sea

son

sam

ple

s. V

alu

es r

epre

sen

t m

ean

of

5 s

ub

sam

ple

s ±

sta

nd

ard

dev

iati

on

.

Mo

istu

re a

nd

bu

lk d

ensi

ty w

as m

easu

red

on

1 a

dd

itio

nal

sam

ple

co

llec

ted

fro

m e

ach

sit

e

a) Sit

e

Al

(pp

m)

Ca (

pp

m)

Fe (

pp

m)

Mn

(p

pm

) N

i (p

pm

) C

u (

pp

m)

Zn

(p

pm

)

CC

LA

A-0

76

1310

0±15

10.9

6

98.1

9±31.3

5

520

0±610

.86

41.4

2±4.7

3

5.2

6±0.7

2

7.1

1±1.5

8

4.7

4±1.3

4

DLA

A-1

77 E

XT

1370

0±11

74.7

3

159.5

6±17.4

0

571

0±965

.13

30.5

9±1.6

3

3.5

4±0.2

8

4.9

0±0.9

4

5.3

4±0.5

7

RP

1-1

44

1490

0±17

49.2

9

145.8

2±12.1

3

603

0±485

.85

40.6

2±12.3

9

2.9

0±0.3

1

7.2

9±6.5

0

9.1

0±4.8

0

JE

LA

A-0

20

2510

0±28

82.1

9

324.8

0±32

9.6

2

1700

0±54

23.2

8

104.2

1±15.5

8

10.2

5±0.9

4

14.2

2±10.0

9

10.5

6±7.0

0

DLA

A-1

85

276

0±320

.11

74.6

3±17.9

9

263

0±459

.29

20.0

5±5.8

9

1.8

0±0.1

4

4.7

0±0.8

5

2.4

9±0.4

5

MLA

A-1

21 E

XT

1700

0±57

8.7

9

175.6

0±46.1

1

795

0±645

.55

235.7

2±5.8

5

14.7

1±0.4

3

18.8

4±2.2

6

8.6

4±1.6

4

DLA

A-1

70 E

XT

1300

0±41

4.7

3

137.5

4±16.6

8

451

0±760

.70

35.8

3±3.2

6

3.3

4±0.0

5

4.5

7±0.5

9

4.4

6±0.2

9

DLA

A-2

22

1910

0±11

99.1

7

398.3

7±92.1

2

1090

0±18

04.3

0

30.1

6±7.1

5

14.9

6±0.9

2

26.6

5±6.8

0

10.5

5±4.7

8

RP

1-1

38

1410

0±62

2.0

9

345.4

2±54.5

9

1350

0±75

9.6

1

112±25

.32

14.7

5±1.3

3

10.0

2±2.8

2

10.3

4±2.2

0

JE

LA

A-0

01

3230

0±49

56.0

6

630.0

0±95.1

3

2640

0±25

43.4

6

91.4

9±8.1

3

44.2

3±39.4

2

23.4

7±42.1

9

66.6

3±28.3

8

CC

LA

A-0

36

3400

0±74

89.1

9

498.9

4±67.8

5

3580

0±53

37.6

0

107.6

1±22.2

7

42.7

4±5.5

5

37.4

4±7.3

5

14.1

0±1.7

5

RP

1-1

34

2770

0±12

35.5

8

660.6

0±74.7

5

2500

0±11

55.6

9

304.2

9±66.4

5

20.1

9±1.1

7

17.6

8±28.9

3

36.3

0±19.9

3

DLA

A-1

57 E

XT

2290

0±15

58.2

0

409.3

0±59.0

7

929

0±104

1.9

8

52.1

6±16.2

0

11.5

6±1.0

3

6.2

3±7.0

2

5.7

9±2.7

0

DLA

A-2

28

1910

0±15

64.2

9

570.0

4±47

0.3

3

1520

0±29

30.0

2

60.1

1±30.7

8

20.0

5±0.7

4

37.0

0±3.4

6

10.0

6±1.5

3

DLA

A-2

27

2560

0±55

65.5

2

565.7

1±10

7.6

7

1470

0±30

62.1

9

91.7

0±7.1

2

14.7

1±2.0

2

27.1

1±7.5

6

12.3

8±4.4

5

MLA

A-1

01 E

XT

2380

0±90

1.6

7

706.3

0±13

4.6

7

1800

0±24

14.9

5

873.6

6±69.7

6

20.2

9±1.3

3

34.6

6±0.9

9

8.5

0±1.0

1

MLA

A-1

06 E

XT

2020

0±92

8.9

8

670.9

0±86.3

6

1930

0±73

17.9

2

345.1

2±76.7

9

17.1

5±2.0

5

22.1

1±2.9

2

9.4

5±1.6

8

MLA

A-0

32

1750

0±99

8.5

0

728.2

3±47

4.5

5

1380

0±34

86.0

4

890±24

8.6

7

16.7

7±2.5

6

25.8

3±6.4

7

24.3

0±17.2

2

Ap

pen

dic

es

17

5

Ta

ble

A-3

S

oil

ph

ysi

coch

emic

al p

aram

eter

s o

f yea

r 2

dry

sea

son

sam

ple

s. V

alu

es r

epre

sen

t m

ean

of

5 s

ub

sam

ple

s ±

sta

nd

ard

dev

iati

on

.

Mo

istu

re a

nd

bu

lk d

ensi

ty w

as m

easu

red

on

1 a

dd

itio

nal

sam

ple

co

llec

ted

fro

m e

ach

sit

e

b) S

ite

P

b (

pp

m)

S (

pp

m)

Th

(p

pm

) U

(p

pm

) T

OC

%

TN

%

Mo

istu

re

(g/c

m3)

Bu

lk d

en

sit

y

(g/c

m3)

CC

LA

A-0

76

4.5

8±4.3

9

22.0

0±9.0

4

4.1

1±0.8

2

2.2

3±0.3

0

0.6

1±0.1

4

0.0

4±0.0

0

0.0

4±0.0

0

1.7

2±0.0

0

DLA

A-1

77 E

XT

6.7

6±0.5

8

181.1

0±44.4

3

5.0

6±0.5

0

2.5

4±0.2

2

1.0

1±0.0

2

0.0

6±0.0

0

0.1

0±0.0

0

1.7

0±0.0

0

RP

1-1

44

8.3

9±1.0

7

166.7

7±22.1

1

16.7

5±0.9

6

4.9

0±0.6

0

0.6

4±0.0

1

0.0

5±0.0

0

0.0

5±0.0

0

1.5

8±0.0

0

JE

LA

A-0

20

10.5

9±1.5

1

112.0

3±30.4

0

8.3

8±0.2

3

11.5

6±15.6

7

3.4

2±2.6

3

0.1

4±0.0

8

0.0

5±0.0

0

1.7

1±0.0

0

DLA

A-1

85

2.0

1±0.2

0

144.8

5±86.6

3

1.6

4±0.1

5

3.4

0±0.7

0

0.5

8±0.0

3

0.0

3±0.0

0

0.2

4±0.0

0

1.1

5±0.0

0

MLA

A-1

21 E

XT

7.6

2±1.3

1

52.1

2±8.5

6

5.8

8±0.4

1

10.3

5±2.2

7

1.0

1±0.1

5

0.0

6±0.0

0

0.0

7±0.0

0

1.7

1±0.0

0

DLA

A-1

70 E

XT

6.9

1±1.0

7

141.9

8±38.4

1

4.4

6±0.2

2

2.2

7±0.2

2

0.9

5±0.0

3

0.0

6±0.0

0

0.0

5±0.0

0

1.6

3±0.0

0

DLA

A-2

22

3.7

2±0.6

2

126.3

3±6.9

2

7.7

1±0.9

6

161.0

7±30.8

5

1.1

3±0.1

6

0.0

7±0.0

1

0.0

6±0.0

0

1.6

9±0.0

0

RP

1-1

38

7.3

4±0.3

7

201.9

8±29.1

8

9.4

8±0.7

4

177.1

7±26.2

8

0.8

4±0.1

5

0.0

8±0.0

1

0.0

8±0.0

0

1.7

9±0.0

0

JE

LA

A-0

01

17.8

5±2.5

0

158.2

1±18.4

6

13.0

3±0.8

1

639.1

7±33

9.5

5

1.4

1±0.1

2

0.0

7±0.0

0

0.0

6±0.0

0

1.9

6±0.0

0

CC

LA

A-0

36

5.5

5±0.4

0

92.6

6±26.3

5

4.3

5±0.3

0

43.0

7±22.8

8

1.1

7±0.4

9

0.0

7±0.0

2

0.0

8±0.0

0

1.7

1±0.0

0

RP

1-1

34

12.1

2±1.5

6

212.1

8±55.5

1

14.0

1±1.2

8

191.5

7±55.2

8

1.1

9±0.0

9

0.0

9±0.0

0

0.1

0±0.0

0

1.6

6±0.0

0

DLA

A-1

57 E

XT

8.5

6±0.7

1

54.7

6±4.9

0

7.1

1±0.3

6

331.5

8±88.4

0

0.8

6±0.0

2

0.0

5±0.0

0

0.1

0±0.0

0

1.4

0±0.0

0

DLA

A-2

28

5.0

7±1.1

0

101.7

8±15.9

5

5.9

0±0.7

2

717.8

1±13

2.2

6

2.8

6±0.9

1

0.1

2±0.0

2

0.0

5±0.0

0

1.2

9±0.0

0

DLA

A-2

27

4.7

8±0.5

3

96.7

3±21.2

8

11.9

9±1.7

7

608.5

5±13

5.4

8

1.7

7±0.0

4

0.0

9±0.0

1

0.0

6±0.0

0

1.5

7±0.0

0

MLA

A-1

01 E

XT

12.1

1±0.5

7

84.7

5±14.9

1

7.7

3±0.4

7

241.2

8±11

6.4

2

2.2

8±0.4

8

0.1

0±0.0

2

0.0

8±0.0

0

1.4

2±0.0

0

MLA

A-1

06 E

XT

8.3

3±0.7

7

86.7

3±12.9

3

10.4

7±1.2

9

507.6

9±10

3.8

4

6.1

4±2.4

1

0.0

7±0.0

1

0.0

6±0.0

0

1.1

6±0.0

0

MLA

A-0

32

7.2

6±1.7

8

68.4

1±41.6

0

8.0

3±0.6

4

127

0.3

64±69

9.4

1

2.4

5±1.6

5

0.1

3±0.0

8

0.0

7±0.0

0

1.7

2±0.0

0

Ap

pen

dic

es

17

6

Ta

ble

A-4

S

oil

ph

ysi

coch

emic

al p

aram

eter

s o

f yea

r 2

wet

sea

son

sam

ple

s. V

alu

es r

epre

sen

t m

ean

of

5 s

ub

sam

ple

s ±

sta

nd

ard

dev

iati

on

.

Mo

istu

re a

nd

bu

lk d

ensi

ty w

as m

easu

red

on

1 a

dd

itio

nal

sam

ple

co

llec

ted

fro

m e

ach

sit

e

a)

Sit

e

Al

(pp

m)

Ca (

pp

m)

Fe (

pp

m)

Mn

(p

pm

) N

i (p

pm

) C

u (

pp

m)

Zn

(p

pm

)

CC

LA

A-0

76

1350

0±14

30.7

3

89.5

4±20.5

7

4670

±5

32

39.4

3±2.4

0

7.6

3±1.1

4

6.7

1±1.5

1

4.1

1±0.9

2

DLA

A-1

77 E

XT

1420

0±12

09.1

3

127.5

9±12.1

1

4670

±5

27

29.6

0±4.3

7

5.5

7±1.0

5

4.8

5±0.6

1

5.0

0±0.7

8

RP

1-1

44

1540

0±22

16.3

0

117.5

9±33.4

0

4710

±6

29

39.1

6±2.8

4

3.9

0±0.5

2

6.4

4±1.4

1

6.9

2±1.4

8

JE

LA

A-0

20

2490

0±27

27.0

9

271.2

8±41

5.8

6

1030

0±17

41

106.9

0±46.9

0

10.3

7±1.1

2

14.3

7±4.2

6

8.3

3±1.3

5

DLA

A-1

85

2680±4

15.8

7

74.2

5±16.3

7

2340

±3

33

19.4

7±1.9

2

1.8

0±0.2

6

4.0

9±0.3

7

1.8

1±0.3

0

MLA

A-1

21 E

XT

1800

0±15

08.3

1

135.9

2±17.2

9

7340

±1

09

5

240.0

8±17.7

2

15.8

5±1.4

7

19.5

1±3.3

2

8.6

3±1.5

0

DLA

A-1

70 E

XT

1340

0±18

96.8

4

104.7

0±28.7

4

3350

±5

05

34.6

4±3.9

8

2.9

0±0.4

7

4.6

5±0.8

8

4.0

5±0.9

1

DLA

A-2

22

1980

0±24

11.0

2

367.4

9±19.5

9

1070

0±13

50

32.0

9±3.0

4

17.9

5±2.1

9

27.3

6±5.3

7

16.7

1±3.0

3

RP

1-1

38

1360

0±43

9.3

2

213.3

1±44.1

9

9720

±4

53

109±11

.49

44.6

1±51.4

4

10.2

1±1.5

4

13.2

8±2.7

7

JE

LA

A-0

01

3210

0±63

42.9

5

453.0

7±81.8

8

2280

0±36

78

96.4

5±11.0

6

19.3

6±1.4

6

23.0

5±5.8

6

22.3

0±2.9

0

CC

LA

A-0

36

3310

0±18

92.8

8

345.0

8±91.7

5

2910

0±17

95

103.4

6±8.6

0

38.9

4±7.7

2

37.1

0±3.0

3

10.9

6±1.7

2

RP

1-1

34

2690

0±13

43.3

2

575.9

4±42.7

7

2170

0±98

4

288±21

.75

31.8

9±10.6

6

18.1

8±3.0

0

14.3

9±1.9

9

DLA

A-1

57 E

XT

2270

0±80

4.3

6

321.6

8±21.3

0

8290

±5

60

47.8

5±5.2

7

10.8

0±0.6

0

6.6

5±0.2

7

0.3

5±0.0

0

DLA

A-2

28

1830

0±16

29.2

6

427.5

2±13

2.4

8

1260

0±15

58

53.1

3±7.6

7

17.6

7±1.6

4

37.2

9±5.6

6

14.1

4±6.0

5

DLA

A-2

27

2480

0±31

81.2

7

524.0

0±86.0

5

1460

0±25

35

78.5

2±21.9

5

13.5

2±1.8

4

26.4

4±3.4

7

6.8

1±3.6

7

MLA

A-1

01 E

XT

2370

0±21

41.1

4

654.6

2±20

6.2

6

1780

0±20

40

888.9

0±11

0.2

6

22.3

6±1.6

3

35.7

1±2.6

7

16.3

1±2.5

8

MLA

A-1

06 E

XT

1970

0±12

86.6

6

648.5

5±22

6.1

1

1760

0±10

12

328.1

4±73.9

1

14.5

0±1.8

1

22.0

9±3.4

1

5.8

1±5.2

9

MLA

A-0

32

1690

0±80

1.8

7

658.3

4±97

.45

1380

0±13

22

880±11

3.5

8

18.9

3±10.7

4

25.2

1±3.1

8

15.7

5±2.9

3

Ap

pen

dic

es

17

7

Ta

ble

A-4

S

oil

ph

ysi

coch

emic

al p

aram

eter

s o

f yea

r 2

wet

sea

son

sam

ple

s. V

alu

es r

epre

sen

t m

ean

of

5 s

ub

sam

ple

s ±

sta

nd

ard

dev

iati

on

.

Mo

istu

re a

nd

bu

lk d

ensi

ty w

as m

easu

red

on

1 a

dd

itio

nal

sam

ple

co

llec

ted

fro

m e

ach

sit

e

b) S

ite

P

b (

pp

m)

S (

pp

m)

Th

(p

pm

) U

(p

pm

) T

OC

%

TN

%

Mo

istu

re

(g/c

m3)

Bu

lk d

en

sit

y

(g/c

m3)

CC

LA

A-0

76

4.3

0±0.3

5

21.3

5±3.5

3

3.9

7±0.3

7

2.2

6±0.1

9

0.6

2±0.1

7

0.0

4±0.0

1

0.1

8±0.0

0

1.6

3±0.0

0

DLA

A-1

77 E

XT

6.9

7±0.6

0

120.2

2±34.0

3

5.0

2±0.5

4

2.9

0±0.7

3

0.8

5±0.0

1

0.0

5±0.0

0

0.2

5±0.0

0

1.6

2±0.0

0

RP

1-1

44

8.9

0±3

5.9

4

141.9

6±63.5

5

17.3

2±1.7

0

5.6

4±1.6

1

1.0

2±0.5

9

0.0

7±0.0

3

0.1

8±0.0

0

1.6

9±0.0

0

JE

LA

A-0

20

10.4

2±2.4

6

72.5

7±5.6

6

8.1

1±0.4

9

9.0

5±9.8

8

3.2

2±3.0

1

0.1

5±0.1

2

0.0

6±0.0

0

1.7

7±0.0

0

DLA

A-1

85

1.7

9±0.2

8

131.8

9±33.4

3

1.5

1±0.3

2

2.4

7±0.7

7

0.5

2±0.2

1

0.0

3±0.0

0

0.3

6±0.0

0

1.5

3±0.0

0

MLA

A-1

21 E

XT

8.2

5±0.8

2

40.4

0±6.0

9

6.6

2±1.5

7

9.5

6±2.1

3

0.9

1±0.0

7

0.0

5±0.0

0

0.0

6±0.0

0

1.6

5±0.0

0

DLA

A-1

70 E

XT

7.0

1±0.4

6

103.5

1±36.1

6

12.2

8±0.8

6

16.5

2±7.2

8

1.0

6±0.7

3

0.0

7±0.0

3

0.2

8±0.0

0

1.6

1±0.0

0

DLA

A-2

22

3.9

2±0.3

6

103.3

0±26.0

0

7.7

9±0.8

4

142.9

2±78.3

5

0.9

6±0.2

0

0.0

6±0.0

1

0.0

8±0.0

0

1.7

9±0.0

0

RP

1-1

38

7.0

9±0.4

6

105.0

9±8.8

1

10.3

5±0.4

7

264.2

5±69.1

4

0.8

9±0.0

5

0.0

7±0.0

2

0.2

2±0.0

0

1.8

2±0.0

0

JE

LA

A-0

01

18.0

9±3.7

0

80.2

8±14.4

9

13.4

4±1.1

2

475.2

0±15

6.0

1

1.0

4±0.2

6

0.0

6±0.0

2

0.0

9±0.0

0

1.9

6±0.0

0

CC

LA

A-0

36

5.4

4±0.4

8

87.0

1±7.6

2

3.8

2±0.4

2

69.5

4±72.4

6

1.2

8±0.3

2

0.0

9±0.0

1

0.1

4±0.0

0

1.5

3±0.0

0

RP

1-1

34

13.3

2±0.4

1

135.9

0±37.9

9

14.1

4±0.5

0

514.7

9±15

5.0

5

1.8

5±0.6

0

0.1

2±0.0

6

0.2

9±0.0

0

1.7

3±0.0

0

DLA

A-1

57 E

XT

8.6

1±0.5

1

63.8

1±9.1

3

6.9

6±0.4

3

457.7

3±11

8.9

6

0.9

2±0.0

0

0.0

5±0.0

0

0.1

5±0.0

0

1.6

2±0.0

0

DLA

A-2

28

5.2

0±2

3.5

5

96.3

8±24.4

1

5.4

3±0.3

2

795.3

7±38

4.0

9

1.9

2±0.4

7

0.1

0±0.0

4

0.1

4±0.0

0

1.6

6±0.0

0

DLA

A-2

27

5.0

2±1.3

0

86.7

0±15.4

8

11.8

9±0.8

6

795.0

4±16

2.4

1

2.1

2±0.3

6

0.1

0±0.0

1

0.1

1±0.0

0

1.7

2±0.0

0

MLA

A-1

01 E

XT

11.8

5±1.1

8

91.9

2±41.5

7

7.3

2±0.7

1

537.8

4±31

6.9

9

2.8

7±1.9

2

0.1

2±0.0

8

0.1

3±0.0

0

1.5

8±0.0

0

MLA

A-1

06 E

XT

7.9

8±0.4

1

89.5

8±22.0

7

9.2

0±1.0

9

520.3

0±26

4.1

8

1.9

1±0.5

7

0.0

9±0.0

3

0.0

8±0.0

0

1.7

7±0.0

0

MLA

A-0

32

7.6

8±0.3

5

61.3

0±6.4

5

7.0

5±0.3

5

1330

.00±2

07.1

7

1.2

6±0.4

9

0.0

7±0.0

2

0.0

7±0.0

0

1.7

0±0.0

0

Appendices

178

Appendix B – PERMANOVA tables based on soil physicochemical

parameters at Ranger Uranium Mine Land Application Areas

Table B-1 PERMANOVA based on soil S concentrations at Ranger Uranium

Mine Land Application Areas indicating significance of difference

between year 1 and 2, wet and dry seasons, U categories, site nested in

U and interactions of these factors.


U- 3 3.5479 1.1826 0.31485 0.011 998 Ye 1 4.8093E-3 4.8093E-3 2.502E-2 0.003 993 Se 1 4.5045 4.5045 17.703 0.001 996 Si(U-) 14 52.586 3.7561 28.37 0.221 999 U-xYe 3 0.17607 5.8691E-2 0.30533 0.826 999 U-xSe 3 1.0973 0.36578 1.4375 0.271 999 YexSe 1 0.3421 0.3421 2.5839 0.133 996 YexSi(U-) 14 2.6911 0.19222 1.4518 0.223 999 SexSi(U-) 14 3.5623 0.25445 1.9219 0.105 999 U-xYexSe 3 0.35956 0.11985 0.90526 0.488 999 Res 14 1.8536 0.1324 Total 71 71










Appendices

179

Table B-2 PERMANOVA based on soil Fe concentrations at Ranger Uranium





U- 3 38.236 12.745 6.2037 0.009 999 Ye 1 0.42638 0.42638 14.267 0.004 994 Se 1 0.64618 0.64618 15.932 0.002 996 Si(U-) 14 28.762 2.0545 133.58 0.121 997 U-xYe 3 0.795 0.265 8.867 0.082 998 U-xSe 3 0.33702 0.11234 2.7698 0.078 999 YexSe 1 9.6997E-2 9.6997E-2 6.3068 0.052 995 YexSi(U-) 14 0.41841 2.9886E-2 1.9432 0.122 999 SexSi(U-) 14 0.56783 4.0559E-2 2.6372 0.059 999 U-xYexSe 3 5.7654E-2 1.9218E-2 1.2495 0.336 999 Res 14 0.21532 1.538E-2 Total 71 71










Appendices

180

Table B-3 PERMANOVA based on soil Ca concentrations at Ranger Uranium





U- 3 48.071 16.024 12.905 0.001 999 Ye 1 0.7995 0.7995 26.464 0.001 998 Se 1 1.5675 1.5675 65.345 0.001 999 Si(U-) 14 17.383 1.2416 9.5745 0.071 999 U-xYe 3 0.15056 5.0187E-2 1.6612 0.22 998 U-xSe 3 0.47301 0.15767 6.5727 0.059 999 YexSe 1 1.5743E-3 1.5743E-3 1.214E-2 0.895 997 YexSi(U-) 14 0.42295 3.0211E-2 0.23296 0.994 999 SexSi(U-) 14 0.33584 2.3988E-2 0.18498 0.998 999 U-xYexSe 3 0.1252 4.1735E-2 0.32182 0.8 999 Res 14 1.8156 0.12968 Total 71 71










Appendices

181

Table B-4 PERMANOVA based on soil Al concentrations at Ranger Uranium





U- 3 26.284 8.7612 2.9839 0.048 998 Ye 1 0.72035 0.72035 36.484 0.039 998 Se 1 0.38446 0.38446 23.15 0.021 999 Si(U-) 14 41.106 2.9362 52.536 0.061 997 U-xYe 3 0.80258 0.26753 13.55 0.061 999 U-xSe 3 0.22212 7.404E-2 4.4583 0.072 997 YexSe 1 2.3983E-2 2.3983E-2 0.42911 0.524 998 YexSi(U-) 14 0.27642 1.9744E-2 0.35327 0.97 998 SexSi(U-) 14 0.2325 1.6607E-2 0.29714 0.978 999 U-xYexSe 3 0.13048 4.3494E-2 0.77821 0.531 998 Res 14 0.78245 5.5889E-2 Total 71 71










Appendices

182

Table B-5 PERMANOVA based on soil Mn concentrations at Ranger Uranium





U- 3 32.367 10.789 3.9792 0.033 999 Ye 1 0.10545 0.10545 16.018 0.007 997 Se 1 9.9751E-2 9.9751E-2 8.9659 0.013 998 Si(U-) 14 37.959 2.7114 356.14 0.051 999 U-xYe 3 9.5155E-3 3.1718E-3 0.4818 0.717 998 U-xSe 3 8.6671E-2 2.889E-2 2.5967 0.086 997 YexSe 1 1.5584E-2 1.5584E-2 2.047 0.18 997 YexSi(U-) 14 9.2165E-2 6.5832E-3 0.86472 0.605 999 SexSi(U-) 14 0.15576 1.1126E-2 1.4614 0.252 999 U-xYexSe 3 7.2104E-3 2.4035E-3 0.3157 0.816 999 Res 14 0.10658 7.6131E-3 Total 71 71










Appendices

183

Table B-6 PERMANOVA based on soil Cu concentrations at Ranger Uranium





U- 3 30.086 10.029 4.9112 0.02 999 Ye 1 1.2105 1.2105 4.8235 0.049 998 Se 1 0.7714 0.7714 5.3001 0.039 997 Si(U-) 14 28.588 2.042 11.391 0.053 999 U-xYe 3 1.3614 0.45381 1.8083 0.193 999 U-xSe 3 0.53003 0.17668 1.2139 0.353 999 YexSe 1 0.25442 0.25442 1.4192 0.283 998 YexSi(U-) 14 3.5134 0.25096 1.3999 0.28 998 SexSi(U-) 14 2.0376 0.14554 0.81187 0.69 998 U-xYexSe 3 8.8831E-2 2.961E-2 0.16517 0.911 999 Res 14 2.5098 0.17927 Total 71 71










Appendices

184

Table B-7 PERMANOVA based on soil Pb concentrations at Ranger Uranium





U- 3 3.8199 1.2733 0.37679 0.745 998 Ye 1 0.34428 0.34428 0.76863 0.401 998 Se 1 8.7899E-2 8.7899E-2 0.26245 0.633 997 Si(U-) 14 47.31 3.3793 10.851 0.20 999 U-xYe 3 0.82998 0.27666 0.61765 0.646 999 U-xSe 3 1.2428 0.41427 1.2369 0.323 999 YexSe 1 0.65713 0.65713 2.11 0.183 999 YexSi(U-) 14 6.2708 0.44792 1.4382 0.225 999 SexSi(U-) 14 4.6889 0.33492 1.0754 0.436 999 U-xYexSe 3 0.41625 0.13875 0.4455 0.715 998 Res 14 4.3602 0.31144 Total 71 71










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Appendices

191

Appendix D – BEST Analysis between physicochemical parameters and the

bacterial community at Ranger Uranium Mine Land

Application Areas

BEST

Biota and/or Environment matching

Data worksheet

Name: Normalized log (x+1) transformed physicochemistry

Data type: Environmental

Sample selection: All

Variable selection: All

Resemblance worksheet

Name: OTUs

Data type: Similarity

Selection: All

Parameters

Rank correlation method: Spearman

Method: BIOENV

Maximum number of variables: 5

Resemblance:

Analyse between: Samples

Resemblance measure: D1 Euclidean distance

Variables

1 Al

2 Ca

3 Fe

4 Mn

5 Ni

6 Cu

7 Zn

8 Pb

9 S

10 Th

11 U

12 TOC %

13 TN %

14 Moisture

15 Bulk density

Best results

No.Vars Corr. Selections

1 0.678 11

2 0.653 2,11

2 0.644 1,11

2 0.637 6,11

3 0.637 2,11,14

3 0.636 1,2,11

2 0.634 3,11

3 0.634 2,6,11

3 0.632 2,9,11

3 0.631 2,3,11

Appendices

192

Appendix E – Indicator species at low and medium, high and very high U

sites at Ranger Uranium Mine Land Application Areas

Table E-1 Indicator species at low and medium, high and very high U sites at

Ranger Uranium Mine Land Application Areas during dry season 1

Classification Indicator of indval p-value

Detection frequency

Solirubrobacter L 0.76 0.001 18 Acidobacterium L 0.88 0.002 16 Candidatus_Koribacter L 0.81 0.001 18 Verrucomicrobia L 0.65 0.035 18 Rhodospirillales L 0.85 0.007 16 Acidobacteriaceae L 0.74 0.002 18 Acidobacterium L 0.77 0.001 18 Chloroflexi L 0.97 0.001 11 Rhodospirillales L 0.81 0.001 18 Candidatus_Koribacter L 0.97 0.001 13 Acidothermus L 0.79 0.002 18 Acidothermus L 0.79 0.002 18 Chloroflexi L 0.93 0.002 12 Actinobacteria L 0.76 0.022 18 Actinoallomurus L 0.91 0.003 15 Acidobacterium L 0.91 0.002 11 Saxeibacter L 0.79 0.048 15 Acidobacteriaceae L 0.93 0.004 14 Acidobacteriaceae M, H, VH 0.93 0.001 17 Streptomycetaceae M, H, VH 0.72 0.003 18 Sphingobacteria M, H, VH 0.98 0.001 14 Candidate_division_WS3 M, H, VH 0.67 0.043 18 Gemmatimonadetes M, H, VH 0.89 0.001 18 Acidobacteriaceae M, H, VH 0.77 0.001 18 Gemmatimonas M, H, VH 0.99 0.001 13 Kitasatospora M, H, VH 0.83 0.008 17 Acidobacteriaceae M, H, VH 0.91 0.001 17 Conexibacter M, H, VH 0.82 0.001 16 Rhodobium M, H, VH 0.84 0.002 13 Gemmatimonadaceae M, H, VH 0.72 0.03 18 Acidobacteriaceae M, H, VH 0.89 0.001 18 Nocardioides M, H, VH 0.75 0.022 18 Acidobacteriaceae M, H, VH 0.85 0.002 17 Phycisphaerae M, H, VH 0.73 0.009 18 Pseudonocardia M, H, VH 0.83 0.001 18 Sphingomonas M, H, VH 0.78 0.001 18 Polymorphospora M, H, VH 0.77 0.005 18 Hamadaea M, H, VH 0.9 0.009 17 Betaproteobacteria M, H, VH 0.68 0.031 18 Chitinimonas M, H, VH 0.82 0.001 17 Micromonospora M, H, VH 0.78 0.002 18 Actinobacteria M, H, VH 0.86 0.006 17 Actinobacteria M, H, VH 0.76 0.037 11 Actinobacteria M, H, VH 0.64 0.039 7

L = Low U sites

M, H, VH = Medium, high and very high U sites

Appendices

193


Ranger Uranium Mine Land Application Areas during wet season 1

Classification

Indicator of indval pvalue

Detection frequency

Solirubrobacter L 0.77 0.002 18 Acidobacterium L 0.84 0.001 16 Candidatus_Koribacter L 0.80 0.002 18 Candidatus_Koribacter L 0.78 0.019 14 Rhodospirillales L 0.77 0.008 16 Acidobacteriaceae L 0.68 0.003 18 Acidobacterium L 0.75 0.034 18 Rhodospirillales L 0.77 0.002 18 Conexibacter L 1.00 0.002 8 Candidatus_Koribacter L 0.96 0.001 12 Acidothermus L 0.66 0.043 18 Conexibacter L 0.71 0.003 6 Dyella L 0.95 0.006 17 Deinococcus-Thermus L 0.68 0.032 18 Sorangiineae L 0.76 0.001 18 Gemmatimonadaceae M, H, VH 0.90 0.002 18 Acidobacteriaceae M, H, VH 0.79 0.013 17 Sphingobacteria M, H, VH 0.80 0.038 15 Kitasatospora M, H, VH 0.74 0.011 18 Sphingobacteria M, H, VH 0.95 0.001 16 Candidate_division_WS3 M, H, VH 0.84 0.002 18 Gemmatimonadetes M, H, VH 0.88 0.001 17 Acidobacteriaceae M, H, VH 0.72 0.001 18 Acidobacteriaceae M, H, VH 0.78 0.008 18 Acidobacteriaceae M, H, VH 0.88 0.002 16 Acidobacteriaceae M, H, VH 0.91 0.001 18 Conexibacter M, H, VH 0.88 0.002 14 Rhodobium M, H, VH 0.92 0.002 16 Gemmatimonadaceae M, H, VH 0.80 0.001 18 Acidobacteriaceae M, H, VH 0.93 0.001 17 Candidatus_Chloroacidobacterium M, H, VH 0.95 0.003 14 Acidobacteriaceae M, H, VH 0.76 0.024 14 Candidatus_Chloroacidobacterium M, H, VH 0.71 0.029 18 Acidobacteriaceae M, H, VH 0.95 0.001 14 Phycisphaerae M, H, VH 0.73 0.009 18 Pseudonocardia M, H, VH 0.89 0.001 17 Nitrospira M, H, VH 0.81 0.003 18 Rhodospirillales M, H, VH 0.66 0.005 18 Chitinimonas M, H, VH 0.79 0.033 15 Acidobacteriaceae M, H, VH 0.74 0.009 17

L = Low U sites


Appendices

194


Ranger Uranium Mine Land Application Areas during dry season 2

Classification


Detection frequency

Solirubrobacter L 0.79 0.003 18 Acidobacterium L 0.85 0.002 18 Candidatus_Koribacter L 0.80 0.001 18 Candidatus_Koribacter L 0.87 0.004 13 Rhodospirillales L 0.79 0.013 18 Acidobacteriaceae L 0.70 0.001 18 Acidobacterium L 0.72 0.026 18 Deltaproteobacteria L 0.70 0.004 18 Rhodospirillales L 0.93 0.002 14 Actinopolyspora L 0.78 0.003 18 Nitrospira L 0.57 0.01 5 Acidobacteriaceae L 0.89 0.001 16 Acidobacteriaceae L 0.96 0.001 12 Candidatus_Solibacter L 0.83 0.003 17 Acidobacteriaceae M, H, VH 0.85 0.003 17 Thermonema M, H, VH 0.91 0.013 17 Streptomycetaceae M, H, VH 0.70 0.005 18 Sphingobacteria M, H, VH 0.92 0.001 16 Candidate_division_WS3 M, H, VH 0.83 0.001 18 Gemmatimonadetes M, H, VH 0.83 0.001 17 Kitasatospora M, H, VH 0.81 0.001 18 Gemmatimonas M, H, VH 0.89 0.003 12 Acidobacteriaceae M, H, VH 0.89 0.001 18 Acidobacteriaceae M, H, VH 0.85 0.012 18 Acidobacteriaceae M, H, VH 0.92 0.001 18 Verrucomicrobia M, H, VH 0.67 0.017 18 Conexibacter M, H, VH 0.86 0.002 17 Rhodobium M, H, VH 0.94 0.001 16 Chloroflexi M, H, VH 0.81 0.001 18 Rickettsiales M, H, VH 0.94 0.001 17 Candidatus_Solibacter M, H, VH 0.63 0.041 18 Acidobacteriaceae M, H, VH 0.79 0.003 18 Singularimonas M, H, VH 0.68 0.001 18 Deinococcus-Thermus M, H, VH 0.94 0.003 17 Kutzneria M, H, VH 0.83 0.001 16 Candidatus_Chloroacidobacterium M, H, VH 0.86 0.03 14

L = Low U sites


Appendices

195


Ranger Uranium Mine Land Application Areas during wet season 2

Classification


Detection frequency

Solirubrobacter L 0.79 0.005 18 Acidobacterium L 0.82 0.003 17 Candidatus_Koribacter L 0.72 0.002 18 Candidatus_Koribacter L 0.85 0.01 15 Rhodospirillales L 0.73 0.022 17 Acidobacteriaceae L 0.71 0.001 18 Acidobacterium L 0.68 0.026 18 Rhodospirillales L 0.69 0.004 18 Candidatus_Koribacter L 0.89 0.014 16 Sorangiineae L 0.75 0.002 18 Candidatus_Solibacter L 0.55 0.046 7 Gemmatimonadaceae M, H, VH 0.77 0.023 17 Acidobacteriaceae M, H, VH 0.84 0.008 17 Thermonema M, H, VH 0.82 0.01 16 Streptomycetaceae M, H, VH 0.78 0.001 18 Sphingobacteria M, H, VH 0.90 0.001 18 Candidate_division_WS3 M, H, VH 0.85 0.001 18 Kitasatospora M, H, VH 0.73 0.002 18 Actinobacteria M, H, VH 0.66 0.019 18 Gemmatimonas M, H, VH 0.98 0.001 14 Acidobacteriaceae M, H, VH 0.80 0.002 17 Acidobacteriaceae M, H, VH 0.75 0.043 16 Acidobacteriaceae M, H, VH 0.91 0.001 18 Conexibacter M, H, VH 0.87 0.001 17 Rhodobium M, H, VH 0.96 0.001 15 Deltaproteobacteria M, H, VH 0.78 0.007 18 Acidobacteriaceae M, H, VH 0.90 0.001 18 Candidatus_Chloroacidobacterium M, H, VH 0.84 0.002 16 Verrucomicrobia M, H, VH 0.86 0.01 17 Nitrospira M, H, VH 0.69 0.03 18 Rhodospirillales M, H, VH 0.68 0.002 18 Betaproteobacteria M, H, VH 0.92 0.001 18 Candidate_division_WS3 M, H, VH 0.81 0.03 17 Chitinimonas M, H, VH 0.71 0.024 18

L = Low U sites


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