Salt Marsh Sediment Biogeochemical Response to the BP Deepwater Horizon Blowout (Skiff Island, LA, and Cat Island, Marsh Point and Saltpan Island, MS)

Mississippi State University Scholars Junction

Theses and Dissertations Theses and Dissertations

1-1-2013

Salt Marsh Sediment Biogeochemical Response to the BP Deepwater Horizon blowout (Skiff Island, LA, and Cat Island, Marsh Point and Saltpan Island, MS)

Calista Lee Guthrie

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Salt marsh sediment biogeochemical response to the BP Deepwater Horizon blowout

(Skiff Island, LA, and Cat Island, Marsh Point and Saltpan Island, MS)

Calista Lee Guthrie

A Thesis Submitted to the Faculty of Mississippi State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Geoscience in the Department of Geosciences

Mississippi State, Mississippi

May 2013

Calista Lee Guthrie

2013

Salt marsh sediment biogeochemical response to the BP Deepwater Horizon blowout

(Skiff Island, LA, and Cat Island, Marsh Point and Saltpan Island, MS)

Calista Lee Guthrie

Approved:

______Karen S. McNeal Brenda Kirkland Associate Professor of Geoscience Associate Professor of Geoscience (Committee Chair) (Committee Member)

______Darrel Schmitz Deepak Mishra Professor of Geoscience Committee Participant Department of (Committee Member) Geosciences (Committee Participant)

______Mike Brown R. Gregory Dunaway Associate Professor of Geoscience Professor and Interim Dean (Graduate Coordinator) College of Arts & Sciences

Name: Calista Lee Guthrie

Date of Degree: May 11, 2013

Institution: Mississippi State University

Major Field: Geoscience

Major Professor: Karen S. McNeal

Title of Study: Salt marsh sediment biogeochemical response to the BP Deepwater Horizon blowout (Skiff Island, LA, and Cat Island, Marsh Point and Saltpan Island, MS)

Pages in Study: 188

Candidate for Degree of Master of Science

The impact of the Deepwater Horizon blowout on coastal wetlands can be understood through investigating carbon loading and microbial activity in salt marsh sediments. Carbon influx causes pore water sulfide to increase in wetland sediment, making it toxic and inhospitable to marsh vegetation. High sulfide levels due to increased microbial activity can lead to plant browning and mortality. Preliminary analyses at Marsh Point, Mississippi indicated that sulfate reducing bacteria are more active in contaminated marsh, producing sulfide concentrations 100x higher than in non- contaminated marsh. Sediment electrode profiles, hydrocarbon contamination, and microbial community profiles were measured at three additional locations to capture the spatial sedimentary geochemical processes impacting salt marsh dieback. Findings indicate that response to contamination is variable due to physical and biogeochemical processes specific to each marsh. Temporal evaluation indicates that there is a lag in maximum response to contamination due to seasonal effects on microbial activity.

DEDICATION

To my Lord, my family, Funnyface, Austin, and my friends.

ACKNOWLEDGEMENTS

First and foremost, I want to acknowledge Dr. Karen McNeal for supporting me in my research and all other endeavors. Though I may complain, I really appreciate her pushing me to do my best. An extra special thanks to Alon Blakeney for his hard work, long hours and dealing with my bossy nature in the field and the lab. Research would have been more difficult and less enjoyable without him. Thanks to Chris Downs for getting us safely to all our destinations and for his eagerness to help in any way. Also, to

Henry Stauffenburg, Jonathon Geroux, Kendra Wright, Erin Anderson, and Curry

Templeton for the extra hands in the field and the lab. I appreciate all the support I have received from my professors and the Department of Geosciences at Mississippi State

University since I became a student here. I want to acknowledge INSPIRE, CLiPSE, BP-

America Grant No. 013145-008 and Geosystems Research Institute Grant No. 0012 at

Mississippi State University for funding my research and schooling over the last two years.

This material is based upon work supported by the National Science Foundation

(NSF) under Grant No. DGE-0947419. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of NSF.

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TABLE OF CONTENTS

DEDICATION...... ii

ACKNOWLEDGEMENTS...... iii

LIST OF TABLES...... vi

LIST OF FIGURES ...... x

I. INTRODUCTION TO SALT MARSH SIGNIFICANCE AND BIOGEOCHEMISTRY ...... 1

Introduction...... 1 Hypotheses:...... 2 Literature Review...... 2 Concern for salt marshes ...... 3 Carbon and sulfur cycling...... 5 Sulfur and microbes ...... 7 Redox potential and pH ...... 8 Sulfur and metals ...... 11 Sulfur and salt marsh ...... 11 Hydrocarbon contamination in salt marshes ...... 13 Marshes in the Gulf of Mexico ...... 15

II. SPATIAL SALT MARSH SEDIMENT RESPONSE TO DWH OIL SPILL...... 17

Introduction...... 17 Research Questions ...... 20 Methodology...... 20 Study locations...... 20 Sample collection and field laboratory methods ...... 22 Laboratory methods ...... 23 Preliminary study method deviations ...... 25 Spatial study method deviations ...... 26 Statistical analyses ...... 27 Results...... 28 Preliminary study ...... 28 Preliminary electrode results ...... 28

Preliminary Biolog results ...... 31 Contamination results ...... 36 Spatial study...... 36 Spatial electrode results ...... 37 Spatial Biolog results ...... 43 Contamination results ...... 46 Particle size results...... 47 Discussion...... 49

III. TEMPORAL SALT MARSH SEDIMENT RESPONSE TO DWH BLOWOUT...... 54

Introduction...... 54 Research Question ...... 57 Methodology...... 57 Methodology applied all three years...... 57 Deviations in methodology among years ...... 58 Statistical analysis...... 58 Results...... 59 Discussion...... 61

IV. SUMMARY...... 63

Hypotheses:...... 64

REFERENCES ...... 65

A. PRELIMINARY STUDY: MARSH POINT 2010...... 70

Electrode Profiles...... 71 October electrode data ...... 72 Biolog data...... 105 Total petroleum hydrocarbons ...... 119

B. SPATIAL STUDY 2011 ...... 120

Guide ...... 121 August electrode profiles ...... 122 September electrode profiles ...... 138 Electrode statistical analysis ...... 154 Biolog statistical analysis...... 162 ECO microplates ...... 162 AN microplates ...... 167

C. TEMPORAL STUDY: MARSH POINT 2010, 2011, & 2012 ...... 180

LIST OF TABLES

2.1 Kruskal-Wallis and Mann-Whitney results for comparison of H2S and O2 by site...... 30

2.2 Kruskal-Wallis and Mann-Whitney results for October site comparison...... 33

2.3 Kruskal-Wallis and Mann-Whitney results for aerobic and anaerobic Biolog for November samples...... 35

2.4 TPH 2010 ...... 36

2.5 Location parameters...... 37

2.6 Kruskal-Wallis and Mann-Whitney results for comparison of H2S and O2 by location...... 42

2.7 Kruskal-Wallis and Mann-Whitney results for comparison of pH and Eh by location...... 42

2.8 ECO plate statistical results...... 44

2.9 AN plate statistical results...... 46

2.10 TPH 2011 ...... 46

3.1 Past oil spills and environment recovery periods ...... 55

3.2 Temporal electrode statistics...... 60

3.3 TPH values for Marsh Point in 2010 and 2011...... 61

A.1 H2S profiles ...... 72

A.2 O2 profiles ...... 83

A.3 Descriptive statistics for electrodes...... 97

A.4 Kruskal- Wallis test for electrodes...... 98

A.5 Mann-Whitney U test for electrodes comparing contaminated sediment and contaminated grass...... 99 vi

A.6 Mann-Whitney U test for electrodes comparing contaminated sediment and non-contaminated sediment...... 100

A.7 Mann-Whitney U test for electrodes comparing contaminated sediment and non-contaminated grass...... 101

A.8 Mann-Whitney U test for electrodes comparing contaminated grass and non-contaminated sediment...... 102

A.9 Mann-Whitney U test for electrodes comparing contaminated grass and non-contaminated grass...... 103

A.10 Mann-Whitney U test for electrodes comparing non-contaminated sediment and non-contaminated grass...... 104

A.11 Biolog ACWD...... 105

A.12 Kruskal-Wallis test for AN microplates...... 105

A.13 Mann-Whitney U test for AN microplates comparing contaminated sediment vs contaminated grass...... 106

A.14 Mann-Whitney U test for AN microplates comparing contaminated sediment vs non-contaminated sediment...... 107

A.15 Mann-Whitney U test for AN microplates comparing contaminated sediment vs non-contaminated grass...... 108

A.16 Mann-Whitney U test for AN microplates comparing contaminated grass vs non-contaminated sediment...... 109

A.17 Mann-Whitney U test for AN microplates comparing contaminated grass vs non-contaminated grass...... 110

A.18 Mann-Whitney U test for AN microplates comparing non-contaminated sediment vs non-contaminated grass...... 111

A.19 Kruskal-Wallis test for ECO microplates comparing contaminated sediment vs contaminated grass...... 112

A.20 Mann-Whitney U test for ECO microplates comparing contaminated sediment vs contaminated grass...... 113

A.21 Mann-Whitney U test for ECO microplates comparing contaminated sediment vs non-contaminated sediment...... 114

A.22 Mann-Whitney U test for ECO microplates comparing contaminated sediment vs non-contaminated grass...... 115 vii

A.23 Mann-Whitney U test for ECO microplates comparing contaminated grass vs non-contaminated sediment...... 116

A.24 Mann-Whitney U test for ECO microplates comparing contaminated grass vs non-contaminated grass...... 117

A.25 Mann-Whitney U test for ECO microplates comparing non- contaminated sediment vs non-contaminated grass...... 118

A.26 TPH data...... 119

B.2 Descriptive statistics for electrodes for all locations...... 154

B.3 Kruskal-Wallis test for the four locations...... 155

B.4 Mann-Whitney U test comparing electrode data for Saltpan Island and Marsh Point...... 156

B.5 Mann-Whitney U test comparing electrode data for Saltpan Island and Cat Island...... 157

B.6 Mann-Whitney U test comparing electrode data for Saltpan Island and Skiff Island...... 158

B.7 Mann-Whitney U test comparing electrode data for Marsh Point and Cat Island...... 159

B.8 Mann-Whitney U test comparing electrode data for Marsh Point and Skiff Island...... 160

B.9 Mann-Whitney U test comparing electrode data for Cat Island and Skiff Island...... 161

B.10 Biolog ECO microplate data for the four locations...... 162

B.11 Descriptive statistics for ECO microplates grouped by depth...... 163

B.12 Kruskal-Wallis test for ECO microlates grouped by depth...... 163

B.13 Mann-Whitney U test for ECO microplates comparing 0-2cm and 2- 4cm depths...... 164

B.14 Mann-Whitney U test for ECO microplates comparing 0-2cm and 4- 6cm depths...... 165

B.15 Mann-Whitney U test for ECO microplates comparing 2-4cm and 4- 6cm depths...... 166

viii

B.16 Biolog AN microplate data for the four locations...... 167

B.17 Descriptive statistics for AN microplates...... 169

B.18 Kruskal-Wallis test for AN microplates comparing four locations...... 169

B.19 Mann-Whitney U test comparing Saltpan Island and Marsh Point AN microplates...... 170

B.20 Mann-Whitney U test comparing Saltpan Island and Cat Island AN microplates...... 170

B.21 Mann-Whitney U test comparing Saltpan Island and Skiff Island AN microplates...... 171

B.22 Mann-Whitney U test comparing Marsh Point and Cat Island AN microplates...... 171

B.23 Mann-Whitney U test comparing Marsh Point and Skiff Island AN microplates...... 172

B.24 Mann-Whitney U test comparing Cat Island and Skiff Island AN microplates...... 172

B.25 Descriptive statistics for AN microplates grouped by depth...... 173

B.26 Kruskal-Wallis test for AN microlates grouped by depth...... 173

B.27 Mann-Whitney U test for AN microplates comparing 0-2cm and 2-4cm depths...... 174

B.28 Mann-Whitney U test for AN microplates comparing 0-2cm and 4-6cm depths...... 174

B.29 Mann-Whitney U test for AN microplates comparing 2-4cm and 4-6cm depths...... 175

4.1 Total petroleum hydrocarbons ...... 176

C.2 Descriptive statistics for electrode data for three years at Marsh Point...... 185

C.3 Kruskal-Wallis test for three years of electrode data at Marsh Point...... 185

C.4 Mann-Whitney U test comparing electrode data for 2010 and 2011...... 186

C.5 Mann-Whitney U test comparing electrode data for 2010 and 2012...... 187

C.6 Mann-Whitney U test comparing electrode data for 2011 and 2012...... 188 ix

LIST OF FIGURES

1.1 Map of global salt marsh distribution. (Hoekstra et al., 2010) ...... 3

1.2 Map showing heavy oiling along the Mississippi and Louisiana Gulf Coast (Spill and Offshore Drilling, 2011)...... 4

1.3 Typical aerobic and anaerobic zonation in a waterlogged system (Reddy and DeLaune, 2008)...... 6

1.4 Sulfur cycling in marshes (Reddy and DeLaune, 2008)...... 6

1.5 Aerobic and anaerobic degradation of organic matter...... 8

1.6 Relationship between root growth of Spartina patens and redox potential (Reddy and DeLaune, 2008)...... 9

1.7 Sulfur species present at varying pH and Eh (Reddy and DeLaune, 2008)...... 10

1.8 Cross- section of Spartina alterniflora roots showing aerenchyma...... 12

2.1 Map of locations included in the study...... 22

2.2 Sample collection and electrode profiling in 2010 and 2011...... 23

2.3 Electrode profiles for Marsh Point, Mississippi in Fall 2010...... 29

2.4 Aerobic Biolog results for October 2010 samples...... 32

2.5 Aerobic and anaerobic Biolog results for November 2010 samples...... 34

2.6 Electrode profiles for Skiff Island, Louisiana and Cat Island, Marsh Point, and Saltpan Island, Mississippi...... 38

2.7 ECO plate graphical results...... 44

2.8 AN plate graphical results...... 45

2.9 Cat Island chromatogram shows hydrocarbon signatures confirm contamination...... 47

2.10 Particle size variation among locations...... 48

3.1 Phenology plots for 2010 and 2011...... 57

3.2 Electrode profiles for Marsh Point, Mississippi for 2010, 2011, & 2012...... 60

A.1 Contaminated sediment H2S & O2 profiles...... 94

A.2 Contaminated grass H2S & O2 profiles...... 95

A.3 Non-contaminated sediment H2S & O2 profiles...... 96

A.4 Non-contaminated grass H2S & O2 profiles...... 97

B.1 Saltpan Island H2S electrode profiles. Aug. 2011...... 122

B.2 Marsh Point H2S electrode profiles. Aug. 2011...... 123

B.3 Cat Island H2S electrode profiles. Aug. 2011...... 124

B.4 Skiff Island H2S electrode profiles. Aug. 2011...... 125

B.5 Saltpan Island O2 electrode profile. Aug. 2011...... 126

B.6 Marsh Point O2 electrode profile. Aug. 2011...... 127

B.7 Cat Island O2 electrode profile. Aug. 2011...... 128

B.8 Skiff Island O2 electrode profile. Aug. 2011...... 129

B.9 Saltpan Island pH electrode profile. Aug. 2011...... 130

B.10 Marsh Point pH electrode profile. Aug. 2011...... 131

B.11 Cat Island pH electrode profile. Aug. 2011...... 132

B.12 Skiff Island pH electrode profile. Aug. 2011...... 133

B.13 Saltpan Island Eh electrode profile. Aug. 2011...... 134

B.14 Marsh Point Eh electrode profile. Aug. 2011...... 135

B.15 Cat Island Eh electrode profile. Aug. 2011...... 136

B.16 Skiff Island Eh electrode profile. Aug. 2011...... 137

B.17 Saltpan Island H2S electrode profiles. Sept. 2011...... 138

B.18 Marsh Point H2S electrode profiles. Sept. 2011...... 139 xi

B.19 Cat Island H2S electrode profiles. Sept. 2011...... 140

B.20 Skiff Island H2S electrode profiles. Sept. 2011...... 141

B.21 Saltpan Island O2 electrode profile. Sept. 2011...... 142

B.22 Marsh Point O2 electrode profile. Sept. 2011...... 143

B.23 Cat Island O2 electrode profile. Sept. 2011...... 144

B.24 Skiff Island O2 electrode profile. Sept. 2011...... 145

B.25 Saltpan Island pH electrode profile. Sept. 2011...... 146

B.26 Marsh Point pH electrode profile. Sept. 2011...... 147

B.27 Cat Island pH electrode profile. Sept. 2011...... 148

B.28 Skiff Island pH electrode profile. Sept. 2011...... 149

B.29 Saltpan Island Eh electrode profile. Sept. 2011...... 150

B.30 Marsh Point Eh electrode profile. Sept. 2011...... 151

B.31 Cat Island Eh electrode profile. Sept. 2011...... 152

B.32 Skiff Island Eh electrode profile. Sept. 2011...... 153

C.1 H2S electrode profile for Marsh Point in 2012...... 181

C.2 O2 electrode profile for Marsh Point in 2012...... 182

C.3 pH electrode profile for Marsh Point in 2012...... 183

C.4 Eh electrode profile for Marsh Point in 2012...... 184

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CHAPTER I

INTRODUCTION TO SALT MARSH SIGNIFICANCE AND BIOGEOCHEMISTRY

Introduction

The impact of the BP Deepwater Horizon (DWH) blowout can be characterized

by observing its effects on microbial and biological communities in salt marshes affected

by the spill. Sulfate reducers are very important in the degradation of hydrocarbons

because they make up a large portion of the biological community responsible for

degrading enriched carbon pools (Shin et al., 2000). Measuring the amount of sulfide in

contaminated marsh sediments, can shed some light on the potential risks and

consequences of oil spills on coastal environments.

As a result of carbon loading, pore water hydrogen sulfide (H2S) concentrations

have been documented to increase in anoxic wetland sediment, making the sediment

more toxic and inhospitable to marsh vegetation (Alber et al., 2008). Preliminary

analysis of the Marsh Point study area in the fall of 2010, after the DWH blowout, revealed that sulfate reducing bacteria are significantly more active in contaminated sediments, producing sulfide concentrations 100x higher than in non-contaminated sediments. The difference in the sediment biogeochemistry between the contaminated site and non-contaminated site at Marsh Point, Mississippi indicated that the effects of

hydrocarbon contamination on sulfur cycling in salt marshes should be more widely explored. In the fall of 2011, the study was expanded to include Skiff Island, Louisiana, 1

and Cat Island, and Salt Pan Island, Mississippi. A follow up trip in 2012 to Marsh Point,

Mississippi completed a three year data set for Marsh Point so that the marsh response over time could be observed. Through expansion of the study to four locations and monitoring one location over a three year period, the salt marsh biogeochemical response to contamination and implications for vegetation browning and dieback were observed.

Hypotheses:

1. There is a significant difference in sediment biogeochemistry in

contaminated and non-contaminated salt marsh areas.

2. Marshes closer in proximity to the well explosion experience a more

severe biogeochemical alteration due to higher likelihood of

contamination than marshes further from the spill.

3. Marshes will be most severely impacted during initial contamination but

sediment biogeochemistry will be restored to normal conditions as oil is

degraded over time.

Literature Review

The influx of organic matter due to hydrocarbon contamination stimulates microbial activity in contaminated salt marshes. Increased activity causes the biological demand of oxygen to increase, which can lead to the onset of reducing conditions in sediments. Under reduced conditions, sulfate reducing microbes can flourish and produce hydrogen sulfide. Depleted oxygen and high sulfide levels at plant rhizospheres can be detrimental for vegetation resulting in plant browning and dieback (Eldridge and

Morse, 2000).

Concern for salt marshes

Salt marshes cover approximately 1.9 million hectares of the Earth’s surface and are located along coastlines from middle to high latitudes (Figure 1.1) (Reddy and

DeLaune, 2008). Salt marshes are important ecological and sedimentological environments for several reasons. Marshes have high biotic productivity and are the spawning grounds for many marine species. Additionally, they act as a buffer for storm surge and a filter for contamination. Salt marshes play a role in maintaining nutrient balance within the marsh environment and in areas of outflow from the marsh (Wenner,

2010; White et al., 1978). Coastal marshes are an important carbon sink with a global carbon sequestration rate of ~0.025 to 0.05 Pg of carbon per year. Salt marshes can even affect climate since the amount of carbon dioxide stored in salt marshes is comparable to rainforests (Nellemann et al., 2009). Furthermore, the Mississippi Delta is home to ~10% of the world’s marshes (Reichle, 1999), however they are at risk with pre-spill marsh loss in Louisiana ranging from 50 km2 to 65 km2 per year (Mishra et al., 2012).

Figure 1.1 Map of global salt marsh distribution. (Hoekstra et al., 2010) 3

Salt marshes are among the many coastal habitats impacted by the DWH blowout

(Figure 1.2). Ecosystem level impacts of contamination are subtle, complex, and not well understood. Taking into account that large-scale spills such as these are unpredictable and uncommon, information on the effects of hydrocarbon contamination on coastal habitats is lacking (Peterson and Estes, 2001).

Figure 1.2 Map showing heavy oiling along the Mississippi and Louisiana Gulf Coast (Spill and Offshore Drilling, 2011).

Carbon and sulfur cycling

Carbon cycling of coastal sediments is largely driven by sulfur cycling (Holmer et al., 2003). Sulfate concentrations in seawater are generally around 2.7 g/kg, therefore, seawater continually brings sulfate into marshes (Schlesinger, 1997). Typically, salt marsh soils are permanently waterlogged and have high organic content. The accumulation of organic matter and aerobic and anaerobic zoning (Figure 1.3) in marshes allows sulfur cycling to play a dominant role in the sediment biogeochemistry (Figure

1.4) (Reddy and DeLaune, 2008). Sulfur can fluctuate between the oxidized state, sulfate, and the reduced state, sulfide where the reduction-oxidation dynamics indicate a change in the geochemical and biological environment (Mitsch and Gosselink, 2007).

Sulfide is a product of sulfate reduction and can cause sediments to become acidic.

Sediment acidification is toxic to salt marsh grasses and can be linked to salt marsh dieback events (King, 1988). Sulfur cycling through sulfate reduction and oxidation has large implications for the chemical environment in salt marsh sediments (Jorgensen,

1977) as enrichment of certain sulfur ions can be toxic to many plants and animals

(Reddy and DeLaune, 2008).

Figure 1.3 Typical aerobic and anaerobic zonation in a waterlogged system (Reddy and DeLaune, 2008).

Figure 1.4 Sulfur cycling in marshes (Reddy and DeLaune, 2008). 6

Sulfur and microbes

Sulfur is essential for cell synthesis in plants and microorganisms. As a

biofeedback system, cycling of different forms of sulfur in marshes both impacts, and is

controlled by, the microbial community in the marsh (Reddy and DeLaune, 2008).

Reduced conditions in coastal sediments tend to be maintained due to microbial processes

below the surface. In aerobic conditions, sulfides are electron donors and are oxidized to

sulfate. In anaerobic conditions, sulfate is reduced primarily through microbial catabolic

processes (Reddy and DeLaune, 2008). Redox processes allow for the transformation

sulfur compounds primarily through sulfate reduction. Sulfur geochemistry at the Earth’s

surface is dominated by anaerobic sulfate reducing bacteria (SRB). SRB oxidize organic

carbon, reduce sulfate, and produce sulfide (Equation 1.1). In the degradation of organic

matter, sulfide is produced when microbes use sulfate as a terminal electron acceptor

(TEA) during respiration. If sulfide remains in pore water, it may be oxidized back to

sulfate if sediments are re-oxygenated (Figure 1.5).

30 6 → 6 36 (1.1)

Equation 1.1 Bacterial respiration using sulfate as the terminal electron acceptor. (Howarth and Teal, 1979)

Changes in the amount of organic matter have an impact on the sulfur processes in marshes. There are typically only a few millimeters of an aerobic zone in salt marshes making oxygen a limiting factor for aerobic microbial degradation of carbon. Organic matter is an energy source for heterotrophic microbes; so if organics increase, microbial degradation will increase, which consumes oxygen in the water. As oxygen is depleted,

reducing conditions take over and sulfate-reducing microbes become dominant (Reddy and DeLaune, 2008). Sulfate reduction in salt marshes primarily occurs a few centimeters below the sediment water interface (Faure, 1998). When anaerobic processes take over, sulfate reduction can yield increased amounts of sulfide and make sediments more toxic hindering plant growth. With increasing organics due to DWH, sulfide production will likely increase as oxygen is depleted (Reddy and DeLaune, 2008), thus dieback events could be the result of reduced conditions (Calleja et al., 2007).

Figure 1.5 Aerobic and anaerobic degradation of organic matter.

Redox potential and pH

Changes in redox potential and pH in sediments due to sulfuric acid in pore water

can be toxic to plants (Alber et al., 2008). During the degradation of organic matter,

microbes consume oxygen, which lowers the redox potential, making conditions

favorable for sulfide production. Reducing conditions in sediments can inhibit root

development in some marsh grasses (Figure 1.6) (Reddy and DeLaune, 2008). An

approximately neutral pH is favorable for most heterotrophic bacteria indicating that

extremes in pH would have adverse effects on the microbial community and its ability to

2- degrade hydrocarbons (Leahy and Colwell, 1990). In oxidizing conditions, SO4 is the main sulfur ion. In reducing conditions, pH usually determines the prominent sulfur

- species. If pH is less than 7, H2S is prominent, for pH greater than 7, HS is expected,

and the sulfide ion is not usually a major constituent in pore water (Figure 1.7) (Reddy

and DeLaune, 2008).

Figure 1.6 Relationship between root growth of Spartina patens and redox potential (Reddy and DeLaune, 2008).

Figure 1.7 Sulfur species present at varying pH and Eh (Reddy and DeLaune, 2008).

Flushing the marsh system through tidal flux and surface water run-off helps to

rejuvenate sediments (King, 1988). Flooded marsh soils have an approximately neutral

pH (Reddy and DeLaune, 2008). During times of drought or infrequent tidal flooding,

sediments can be exposed to the atmosphere and begin to oxidize sulfide precipitates.

Conversely, prolonged submergence of interior marsh areas can lead to reducing conditions where sulfide production increases as SRB degrade organic matter (Alber et al., 2008).

Sulfur and metals

Metals in the environment can also impact sulfide levels as they can remove

sulfide from pore water through the precipitation of metal sulfides (King, 1988). When

sediments are re-oxygenated, deposited metal sulfides can be broken down releasing

sulfide into pore water (Jorgensen, 1977). Re-oxygenating sediments increases the

bioavailability of previously bound metals to plants and frees sulfide to make sulfuric

acid (Alber et al., 2008). High iron content in marsh sediments paired with sulfate in

seawater allow for the production of pyrite during times of marsh flooding. If the marsh

is drained, pyrite may be oxidized and produce ferric hydroxide and sulfuric acid,

lowering the pH in marsh sediment (Reddy and DeLaune, 2008). Pyrite accumulation in

sediments is dependent on HS- and Fe2+ availability (Faure, 1998).

Sulfur and salt marsh

In order for vegetation to survive in wetlands, it must be able to survive in

waterlogged soils. Wetland plants have developed several adaptations in order to survive

the stresses of living in wetland soils. Oxygen diffusion from the water column to

sediment pores is very slow causing a thin oxidized area. Aerenchyma are tissues with

airspaces, an adaptation that plants growing in flooded wetland soil often possess (Figure

1.8). The aerenchyma allow plants to pump oxygen through leaves and stems that are exposed to the atmosphere down to submerged roots (Mitsch and Gosselink, 2007). The oxidized rhizosphere that is produced is host to a diverse microbial population.

Beggiatoa is one type of bacteria commonly found in the plant rhizosphere that oxidizes

H2S to elemental sulfur (Mitsch and Gosselink, 2007). These bacteria are aerobic

microorganisms and are present where H2S rises through the sediment (Reddy and 11

DeLaune, 2008). Beggiatoa is a member of the Thiotrichaceae family which were

detected in DWH contaminated sediments (Beazley et al., 2012).

Figure 1.8 Cross- section of Spartina alterniflora roots showing aerenchyma.

Aerenchyma is the extensive pore space shown in roots. Arrows represent ferric deposits indicative of oxidation (Mitsch and Gosselink, 2007).

Marsh grasses alter their surrounding sedimentary environment through biological

processes as well as in their post-mortem organic contributions (Eldridge and Morse,

2000). Vegetation zonation in salt marshes depends on a variety of abiotic factors

including sulfide (Reddy and DeLaune, 2008). Salt water wetlands have higher emission

of H2S than freshwater wetlands due to the presence of the sulfate ion in seawater at 2.7

g/L as compared to 0.01 g/L in freshwater (Mitsch and Gosselink, 2007). Rhizosphere geochemical activity can lower sulfide levels affecting sediment digenesis. Production of oxygen in sediments by rhizomes allows constituents in the rhizosphere to be re-oxidized, which makes it crucial for maintaining non-toxic sulfide levels conducive to marsh health

(Mitsch and Gosselink, 2007). Marshes are most threatened in times of low photosynthesis when oxygen production in the root zone is limited. H2S can be toxic to both vegetation and microbes especially in saltwater wetlands where sulfates are

abundant. High sulfide levels can therefore be linked to salt marsh dieback events as sulfide causes the sediments to become acidic generating toxic conditions for marsh grasses (Eldridge and Morse, 2000). Microbial production of sulfide during low oxygen events results in elevated sulfide levels in sediment, which aids in sustaining hypoxic conditions in the rhizosphere of surviving marsh grasses, further inhibiting plant growth in the area. The dieback area can continue to expand as dead grasses supply more organic matter to be degraded helping maintain low oxygen conditions. Depending on the degradation rate of dead grasses, high pore water sulfide levels can be maintained for up to a year after the dieback event (Carlson et al., 1994).

Hydrocarbon contamination in salt marshes

Salt marshes are considered at high risk for crude oil contamination due to their proximity to oil production, which has proven to be a valid consideration in the case of the DWH blowout. Hydrocarbon contamination in marsh sediments has been shown to stimulate microbial activity (Beazley et al., 2012). Microbes preferentially degrade crude oil components sequentially (linear alkanes, branched alkanes, small aromatic, cyclic alkanes, and last polycyclic aromatic hydrocarbons) shaping the microbial community as degradation progresses (Mendelssohn, 2012). Petroleum hydrocarbons are more readily degraded through aerobic biodegradation than anaerobic processes (Aitken et al., 2004;

Leahy and Colwell, 1990). Hydrocarbon degrading bacteria represent an additional oxygen demand in the event of crude oil contamination of marsh. With only a few millimeters of aerobic zone in marshes initially, contamination can rapidly result in reduced conditions leaving anaerobic biodegraders including sulfate reducers,

denitrifiers, and methanogens to degrade hydrocarbons (Anderson and Lovley, 2000;

Cervantes et al., 2001).

Oil persistence in sediments can cause chronic negative effects after oil spills

(Mendelssohn, 2012). Salt marsh die back and growth reduction is more likely in oil contaminated sediments due to higher amounts of sulfide, which can affect the underground growth directly at the rhizosphere and induce above ground browning and

dieback (Alber et al., 2008). Sediment oxygen demand in salt marsh increases between

1.5 and 5 times upon the addition of crude oil and sulfate reduction rate doubles (Shin et

al., 2000). Crude oil in particular has been found to stimulate sulfate reduction and

increase the demand for oxygen, thereby creating an oxygen-depleted environment (Shin

et al., 2000). Areas previously exposed to hydrocarbon contamination have adapted

microbial communities resulting in more efficient biodegradation of hydrocarbons

(Leahy and Colwell, 1990).

The microbial community, primarily responsible for the degradation of crude oil,

is affected by the flooding regime in the marsh. When sediments are exposed (e.g. at low

tide), crude oil will degrade more readily since oxygen is no longer a limiting factor. A

microbial community that can utilize a variety of terminal electron acceptors (TEAs) is

ideal for hydrocarbon degradation. Marsh flooding promotes anaerobic degradation of

hydrocarbons primarily through sulfate reduction (Shin et al., 2000). Second to a mixed

anaerobic community (i.e. nitrate reducers and sulfate reducers), sulfate reducing

communities are the next most effective for biodegradation of hydrocarbons (Boopathy et

al., 2012).

Marshes in the Gulf of Mexico

Vegetation response to oil contamination is largely dependent on contact and penetration of oil in sediments, present vegetative species, frequency of oiling, time of year and seasonality of location (Mendelssohn, 2012). Microbial communities in marshes along the Gulf Coast have some resistance to oil contamination due to chronic exposure from natural seeps and other smaller oil spills that they have been exposed to in the past (Martinez et al., 2006; MacDonald et al., 2002). Increasing organic matter content in sediments, even in small amounts, is known to cause an increase in sulfide pore water concentration but a decrease in vegetation population growth. The saline and anaerobic soils in salt marshes along the Louisiana coast result in a selective low diversity of vegetation dominated by Spartina alterniflora (smooth cord-grass), Juncus romarianus (black needle-rush), and Spartina patens (salt meadow cord-grass) (Weis,

2010). The DWH blowout began in April 2010 and oil washed ashore along the Gulf

Coast in the months following. The hurricanes that have come ashore since the DWH blowout, have brought oil ashore with them causing more contamination along the coast.

Genes associated with both hydrocarbon degradation and sulfate reduction were detected in MC-252 contaminated salt marsh sediments as well as sulfate reducing bacteria known to degrade hydrocarbon, including the families Geobacteraceae and

Desulfobacteraceae (Beazley et al., 2012). The presence of these genes and bacteria indicate that anaerobic degradation of hydrocarbon through sulfate reduction can occur in contaminated sediments. High amounts of sulfide in sediments create a more toxic environment and can hinder plant growth. Thus, dieback events, primarily in the interior of salt marshes, can most likely be attributed to reduced conditions enhancing sulfide

production (Alber et al., 2008). Mishra et al. (2012) found that stress from oil contamination in salt marshes was more persistent in the interior marsh towards the end of the growing season as compared to signs of recovery on the shoreline.

CHAPTER II

SPATIAL SALT MARSH SEDIMENT RESPONSE TO DWH OIL SPILL

Introduction

Over 4.9 million barrels of crude oil gushed into the Gulf of Mexico between

April 20th and July 15th 2010 making the BP Deepwater Horizon (DWH) blowout the largest oil spill in U.S. history (McNutt et al., 2011). The large scale impact of the DWH blowout on biological communities can be predicted by developing an understanding of how carbon loading from the spill is affecting the microbial and biological communities of salt marshes along the Mississippi and Louisiana Gulf Coast. Sediment biogeochemical processes that degrade enriched carbon pools through sulfate reduction are primarily responsible for the biodegradation of spilled hydrocarbons (Shin et al.,

2000). Determination of sulfide concentration in contaminated areas, allowed for an assessment of the oil spill impact on salt marsh at Skiff Island, Louisiana, and Cat Island,

Marsh Point, and Saltpan Island, Mississippi (Figure 2.1).

Coastal wetlands provide a variety of ecosystem services important to the function of human society (Engle, 2011). Ironically, one of these services is protecting the infrastructure that provides one-third of the United States’ oil and gas as well as 50% of the nation’s refining capability (Mendelssohn, 2012). Approximately 40% of coastal wetlands in the lower 48 states of the U.S. are located within the Mississippi River Delta

(Mendelssohn, 2012). Low tidal energy and the presence of vegetation cause coastal 17

wetlands to be extremely vulnerable to contamination since contaminants can remain sequestered in sediments for decades (Burns et al., 1993). Salt marshes are the most vulnerable of coastal environments to oil spills (Pezeshki et al., 2000).

Oil contamination in wetlands is primarily degraded through microbial processes

(Mendelssohn, 2012). Abundant microbial diversity in marsh waters and sediments maximizes marsh potential for efficient degradation of nutrient resources such as crude oil (Mendelssohn, 2012). Oil can cause damage to the environment through increased aerobic microbial degradation of hydrocarbons resulting in oxygen depleted environments (Mendelssohn, 2012). Oxygen has been found to be the major limiting factor in oil biodegradation (Tate et al., 2012). Conditions below the first few millimeters of oxidized zone in salt marshes are typically severely reduced even without oil contamination (Reddy and DeLaune, 2008). The reduced environment in marshes results in anaerobic microbial processes playing a significant role in the degradation of organic matter, including oil contaminants (Boopathy et al., 2012). Due to oxygen depletion from oil contamination, microbial diversity is lowered (Shin et al., 2000) and the microbial community shifts toward a greater abundance of microorganisms that can use a variety of terminal electron acceptors (TEAs) (Mendelssohn, 2012). The shift in microbial community can result in the alteration of nutrient cycling in oil contaminated marshes which can affect marsh vegetation (Mendelssohn, 2012).

Due to oil contamination, the microbial community largely experiences negative effects with the exception of sulfate-reduction being stimulated (Suárez‐Suárez et al.,

2011). Dissolved oxygen from overlying aerated waters only diffuses within the top few millimeters of sediment leaving reducing conditions below (Taillefert et al., 2007).

Sulfate reduction is dominant in soils when redox potential is low (≤ -100 mV) indicating

highly reduced conditions (Reddy and DeLaune, 2008). The presence of TEAs with

higher redox potentials, like nitrates, can inhibit sulfate reduction since TEAs with higher

redox potentials are usually depleted before switching to a TEA with a lower redox

potential (Reddy and DeLaune, 2008). Sulfate is typically not a limiting factor in coastal

wetlands as it is brought into the environment with seawater. In salt marsh sediments, a major form of microbial respiration is sulfate reduction (Equation 2.1) (Reddy and

DeLaune, 2008).

8 10 → 4 (2.1)

Spartina alterniflora and Juncas roemerianus are marsh grasses that have shown

capabilities of lowering oil concentration in sediments (Lin and Irving, 2009). This could

be due to plant uptake, release of plant exudates, and an oxidized root zone (Chaudhry et

al., 2005). Oiled marsh grasses showed progressively deteriorating conditions in the Fall

of 2010 beginning with coating of marsh grasses, reduction of photosynthetic pigments

and increased physiological stress as indicated by chlorosis (discoloration) eventually

resulting in cell damage and mortality (Mishra et al., 2012). During the 2010 growing

season, over 400 km2 of salt marshes along the Louisiana coast experienced reduced

biomass and canopy chlorophyll whereas, in the 2009 growing season only 50 km2 to 65

km2 exhibited reductions (Mishra et al., 2012). A reduction of biomass and canopy

chlorophyll can trigger marsh loss since physiological stress can escalate to weakened

root systems resulting in the loss of the contaminated marsh fringe to open water (Mishra

et al., 2012).

The increased plant mortality following contamination could be linked in part to

increased sulfate reduction in marsh sediments. Organic matter, like crude oil, can be

oxidized through sulfate reduction, which releases sulfide. Sulfide is toxic to wetland

plants and can limit root development (Reddy and DeLaune, 2008). As a survival

mechanism, aerenchyma allow some marsh grasses to pump oxygen from the atmosphere

down to their roots creating an aerated zone where reduced sulfides may be re-oxidized chemically or microbially (Reddy and DeLaune, 2008). Despite these defense mechanisms, high sulfide levels due to carbon loading in hydrocarbon contaminated salt

marshes have been shown to cause microbial activity to increase at the plant rhizosphere,

leading to plant browning and die back (Eldridge and Morse, 2000).

Research Questions

1. Is there a significant difference in sediment biogeochemistry between

contaminated and non-contaminated salt marsh areas?

2. Does the proximity to the DWH blowout control the severity of

biogeochemical alteration in contaminated marshes?

Methodology

Study locations

The locations for the spatial study were selected to capture the biogeochemical effects of oil contamination along the Gulf Coast while also considering travel time and accessibility. The locations chosen were, from east to west, Saltpan Island, Marsh Point,

Cat Island, and Skiff Island (Figure 2.1). Saltpan Island is the easternmost location included in the study. It is located near Pascagoula, Mississippi and was selected as a

presumably low impact site. Marsh Point is just west of Saltpan Island and was selected as a study location in 2010 for the preliminary biogeochemical study. Marsh Point was monitored closely in 2010 by the University of Southern Mississippi’s Gulf Coast

Research Lab (GCRL) and any sites that were contaminated were marked. For the 2010 study, one contaminated site was used and one unaffected site was used. Both Saltpan

Island and Marsh Point are located very near the Mississippi Coast in contrast to Cat

Island, which is one of the barrier islands of the Mississippi Sound. Cat Island is located off of the west end of the Mississippi coast and had moderate to severe contamination.

Skiff Island was also more detached from the mainland coastline and is southwest of Cat

Island. Skiff Island, Louisiana was selected as a presumable heavily contaminated location. Cat Island and Skiff Island are more exposed locations in comparison to

Saltpan Island and Marsh Point which are located just off of the coast and are guarded partly by the barrier islands.

Figure 2.1 Map of locations included in the study.

Sample collection and field laboratory methods

Upon arrival at a site, GPS coordinates along with water quality measurements were taken. Water quality measurements including dissolved oxygen (DO), temperature, and salinity were taken using a YSI 85 Handheld (Yellow Springs, Ohio). Cores at least

15 cm in depth, preferably with overlying water, were collected manually or by using a hand coring device (Figure 2.2). Sediment cores were taken to a 10-15 cm depth using core liners 9 cm in diameter and ~30-35 cm in length. Cores were then transported to a field laboratory for electrode analysis. Electrode profiles were collected using the

Unisense microelectrode profiling system, Sensor Trace Pro software, a micromanipulator for fine-scale measurements. The cores were then refrigerated and

transported back to Mississippi State University to be sliced under anaerobic conditions to preserve the biological community.

Figure 2.2 Sample collection and electrode profiling in 2010 and 2011.

Laboratory methods

Once at Mississippi State, the refrigerated core was sliced into five 2 cm subsections inside a nitrogen-filled glove bag. The 2 cm sub sections were placed inside whirl bags and refrigerated until analysis was completed for Biolog. Only the top 6 cm of samples was analyzed, so for each core there were three samples: 0-2 cm, 2-4 cm and

4-6 cm depth, zero being the surface. Samples were prepared following traditional

Biolog procedures where the sample was diluted 1:1,000 and pipetted into 96 well plates.

Plates were incubated for 96 hours with measurements taken in 24 hour increments.

Plates were read using a Fisher Scientific Original Multiskan MCC and data generated was statistically analyzed.

To determine if sites were contaminated, total petroleum hydrocarbons (TPH) were measured. Samples were prepared using a method for non-polar hydrocarbon 23

extraction modified from EPA Method 1664 (1995), in which, non-polar hydrocarbons are extracted from five to ten grams of sediment. Sediments were weighed into 40 mL vials and 20 mL of methylene chloride was added. Samples were vortex mixed for one minute then placed in a sonicator for ten minutes. Samples were then poured through 20 g of anhydrous sodium sulfate and filtered into a 50 mL pre-weighed beaker. The filter and sodium sulfate was then rinsed with 20 mL of methylene chloride to wash out any sample still in the filter. Beakers were placed in a fume hood until the methylene chloride evaporated and beakers were weighed again in order to calculate residual oil in the beaker. After finding the difference in the pre- and post- weight of the beaker TPH was calculated by dividing the residual by the weight of sediment it was extracted from.

In order to get a more precise measure of TPHs present in samples, gas chromatography-mass spectrometry (GC-MS) analysis was also done. Samples were extracted in the same way as for TPH however, after evaporation was complete, the residue left in the beaker was dissolved with 4 mL of methylene chloride. The ~1000-

2000 ppm concentrated sample was then transferred into a 4 mL vial to be kept until GC-

MS analysis. For GC-MS analysis, 1μL of sample was run through a 30 meter Perkin-

Elmer Elite 225 column. The column is a crossbond of 50% cyanopropylmethyl and

50% phenylmethyl polysiloxane with a 0.32 mm ID. The injector temperature was

300°C. The GC began at 100°C and temperature increased at 5°C per minute until reaching 250°C. Temperature was maintained at 250°C for twenty minutes. After analyzing 1μL of concentrated sample, the results were run through a library of compounds to identify compounds indicative of hydrocarbon contamination.

Particle size analysis was completed for the four locations using G.W. Gee and

J.W. Bauder’s method for particle-size analysis (Klute, 1986). Wet sieve analysis was

completed using U.S. Standard Sieve numbers 10, 18, 35, 60, and 230. To prepare

sediments hydrogen peroxide was added to remove organics from sediments. Next,

sediments were dried and weighed. Water was added to sediments to break up particles

dried together. Sediments were then sieved. Sediments remaining in the sieves was dried

and weighed and percent finer for samples was calculated. The hydrometer method was

used to determine the percent of smaller particles present in samples. An HMP solution

was added to sediments for dispersion and the mixtures were shaken overnight. The

mixtures were then transferred to a 1 L sedimentation cylinder and DI water was added

until the mixture was 1 L. Hydrometer readings were taken at 0.5, 1, 3, 10, 30, 60, 90,

120, and 1440 minutes.

Preliminary study method deviations

The focus of the preliminary study was to determine how sediment

biogeochemistry differs at contaminated and non-contaminated sites at Marsh Point in

Ocean Springs, Mississippi. In October and November of 2010, six cores were taken at a

contaminated site and six cores were taken at a non-contaminated site, three cores in

marsh grass and three cores in sediment. Cores were capped, sealed, and transported

back to the field lab where they were analyzed for pore water oxygen (O2) and hydrogen

sulfide (H2S) using microelectrodes. Once cores were transported to the field laboratory,

cores were analyzed for pore water hydrogen sulfide (H2S) and oxygen (O2) using a microelectrode profiling system. One profiled core from each site was refrigerated and

other cores were frozen and transported back to the laboratory at Mississippi State

University for further analysis.

In order to complete Biolog analysis the refrigerated 2 cm sub sections were used.

To analyze October 2010 samples, one ECO Microplate was used for each 2 cm sub-

section. Anaerobic Biolog analysis was not conducted in October 2010, however, both aerobic and anaerobic Biolog analysis was completed for November 2010. One ECO

MicroPlate was used to measure the aerobic community and two AN Microplates were

used to measure the anaerobic community. Only one ECO plate was used because ECO

plates have replication in the wells, however, two AN plates were used because anaerobic

plates do not have replication in the wells.

Spatial study method deviations

Cores were collected at four locations: Salt Pan Island, Marsh Point, and Cat

Island, Mississippi and Skiff Island, Louisiana (Figure 2.1). At each location three sites

were chosen and three cores were taken at each of the three sites; a total of nine cores

were taken per location. Cores were only taken in marsh grasses. Travel time to Marsh

Point from GCRL was less than 30 minutes so electrode profiling was done at the GCRL.

Traveling time back to a field laboratory to do electrode analysis was too long to prevent

the core from either getting disturbed or from altering its geochemical state for Saltpan

Island, Cat Island, and Skiff Island. Therefore, electrode analysis equipment was set up

on the beach at these locations for profiling in the field. Electrode data was collected

using H2S, O2, Eh, and pH microelectrodes. Electrode analysis was done on only one

core from each site totaling to three cores per location. The remaining two cores

collected at each site were sliced in the field and frozen for hydrocarbon analysis. 26

Biolog analysis was conducted using the refrigerated 2 cm subsections of sliced

cores. For each 2 cm depth, two ECO plates were used and two AN plates were used.

One ECO plate was incubated in aerobic conditions and the remaining ECO plate was

incubated in anaerobic conditions in order to compare color development for the same

carbon sources with replication. The two AN plates were incubated in anaerobic

conditions in order to better measure the anaerobic community based on anaerobic media.

Statistical analyses

Statistical analysis was conducted on microelectrode data and Biolog data. All

data, excluding the comparison of aerobic vs anaerobic ECO plates, was homogeneous according to Levene’s test for homogeneity, however, data were not normally distributed based on the Kolmogorov-Smirnov test (p < 0.05). Transformations performed on the

data in an attempt to meet the assumptions were unsuccessful therefore a non-parametric

test was used. The Kruskal-Wallis test is a non-parametric analogue of the one-way

ANOVA. The Kruskal-Wallis test is a rank test, meaning that values are converted into ranks before tests are carried out. For the Kruskal-Wallis test, the null hypothesis is that samples were taken from populations with the same median. While the Kruskal-Wallis

test is slightly less powerful than a one-way ANOVA, it is less likely to report a

significant result when there is not one. Like a one-way ANOVA, a significant difference

in a Kruskal-Wallis test indicates that at least one pair is significantly different but does not indicate which pair is different. To determine which pairs are different, the Kruskal-

Wallis test was followed by a Mann-Whitney U test. The Mann-Whitney U test only allows a comparison between two groups and the null hypothesis is that the two groups

being tested come from the same distribution. The Kruskal-Wallis and Mann-Whitney U tests were conducted on electrode readings and biological community.

In order to analyze electrode results, sites at each location were averaged to reduce error caused by ranking repeated values. For example, data collected in August

2011 from Site 1 at Cat Island was averaged with data collected in September of 2011 from Site 1 at Cat Island. For Biolog, tests were conducted on ECO plates comparing aerobic results to anaerobic results as a whole, aerobic verses anaerobic data based on depth and aerobic verses anaerobic data based on location. When comparing aerobic

ECO plates to anaerobic ECO plates, assumptions for a parametric test were satisfied as determined by the Kolmogorov-Smirnov test (p > 0.05) and Levene’s Test for

Homogeneity, so a paired t-test was used.

Results

Preliminary study

Preliminary data collected in October of 2010 on contaminated marsh grass and sediment and non-contaminated marsh grass and sediment revealed significantly higher sulfide concentrations for contaminated marsh grasses compared to contaminated sediments and non-contaminated marsh grass compared to sediment. The highest amount of anaerobic microbial activity was also observed at contaminated marsh grass.

Preliminary electrode results

Since the November sampling period was during a cold snap and when activity in the marsh is beginning to slow down for winter months, electrode profiling for November was not considered during data analysis. For October 2010, electrode measurements for

H2S ranged from 0 μM to 4034 μM, and O2 concentrations were between 0 μM and 117

μM (Figure 2.3). H2S and O2 concentrations were significantly different for

contaminated marsh grass compared to the three other sites (Table 2.1). Oxygen

concentrations were significantly different among all sites.

Figure 2.3 Electrode profiles for Marsh Point, Mississippi in Fall 2010.

Table 2.1 Kruskal-Wallis and Mann-Whitney results for comparison of H2S and O2 by site.

H2S O2 Core Core Core Significance Core Significance (Mean Rank) (Mean Rank)

Contaminated Contaminated Contaminated Contaminated Sediment Marsh Grass 0.00 Sediment Marsh Grass 0.00 (53.74) Non- (48.66) Non- Contaminated 0.97 Contaminated 0.05 Sediment Sediment Non- Non- Contaminated 0.25 Contaminated 0.00 Marsh Grass Marsh Grass Contaminated Contaminated Contaminated Contaminated Marsh Grass Sediment 0.00 Marsh Grass Sediment 0.00 (129.64) Non- (110.24) Non- Contaminated 0.00 Contaminated 0.00 Sediment Sediment Non- Non- Contaminated 0.00 Contaminated 0.02 Marsh Grass Marsh Grass Non- Non- Contaminated Contaminated Contaminated 0.97 Contaminated Sediment Sediment 0.05 Sediment Sediment (53.83) Contaminated (47.33) Contaminated 0.00 0.00 Marsh Grass Marsh Grass Non- Non- Contaminated 0.19 Contaminated 0.00 Marsh Grass Marsh Grass Non- Non- Contaminated Contaminated Contaminated 0.25 Contaminated Sediment Sediment 0.00 Marsh Grass Marsh Grass (62.61) Contaminated (94.29) Contaminated 0.00 0.02 Marsh Grass Marsh Grass Non- Non- Contaminated 0.19 Contaminated 0.00 Sediment Sediment Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Contaminated marsh grasses had the largest range in H2S and O2. Contaminated marsh grasses had the highest H2S concentrations, up to 4034 μM, among samples. The lowest concentration of H2S was at the sediment water interface with a concentration of

54 μM. H2S concentration increased with depth until reaching a maximum of 4034 μM at 2.4 cm depth. Oxygen concentrations were highest at the surface with a concentration of 117 μM. Oxygen decreased with depth until reaching a minimum of 1 μM at 2.2 cm depth. The profile for contaminated marsh grass illustrates the relationship between H2S and O2. As O2 decreases in the sediments, H2S increases.

H2S concentrations were similar for the contaminated sediment, non- contaminated sediment, and non-contaminated marsh grass sites. The pore water concentration of H2S and O2 in non-contaminated marsh grass did not vary much with depth. H2S concentrations hovered near 19 μM and O2 concentrations stayed around 26

μM. Non-contaminated marsh grasses had the least variable concentrations of sulfide and oxygen with depth compared with other samples. For contaminated sediments and non- contaminated sediments, H2S was highest at the surface and decreased with depth.

Preliminary Biolog results

The November sampling period was at the start of winter months when vegetation enters dormancy and microbial activity is lowered. Microbial results are presented for

November 2010 in order to observe anaerobic microbial activity. The highest amount of aerobic microbial activity in October 2010 was measured in non-contaminated marsh grass with the average well color development (ACWD) reaching 0.80 absorbance

(Figure 2.4). Contaminated marsh grass was significantly different than non- contaminated sediment (p=0.00) and non-contaminated marsh grass (p=0.00) (Table 2.2). 31

During the November sampling period, microbial activity was low for all four sites

(ACWD < 0.25) but it is important to note that the highest values observed both aerobically (ACWDECO=0.24) and anaerobically (ACWDAN=0.09) were at the contaminated marsh grass site (Figure 2.5). Aerobic and anaerobic Biolog results were only significantly different for contaminated marsh grass and contaminated sediment

(pECO=0.02, pAN=0.01) (Table 2.3).

Figure 2.4 Aerobic Biolog results for October 2010 samples.

Table 2.2 Kruskal-Wallis and Mann-Whitney results for October site comparison.

Core Core Significance (Mean Rank)

Contaminated Sediment Contaminated Marsh Grass 0.11 (6.80) Non-Contaminated Sediment 0.09

Non-Contaminated Marsh Grass 0.00 Contaminated Marsh Grass Contaminated Sediment 0.11 (15.60) Non-Contaminated Sediment 0.00

Non-Contaminated Marsh Grass 0.00 Non-Contaminated Sediment Contaminated Sediment 0.09 (8.80) Contaminated Marsh Grass 0.00

Non-Contaminated Marsh Grass 0.00 Non-Contaminated Marsh Grass Contaminated Sediment 0.00 (10.80) Contaminated Marsh Grass 0.00

Non-Contaminated Sediment 0.00 Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Figure 2.5 Aerobic and anaerobic Biolog results for November 2010 samples.

Table 2.3 Kruskal-Wallis and Mann-Whitney results for aerobic and anaerobic Biolog for November samples.

Aerobic ECO Plate Biolog Anaerobic AN Plate Biolog Core Core Core Significance Core Significance (Mean Rank) (Mean Rank) Contaminated Contaminated Contaminated Contaminated Sediment Marsh Grass 0.02 Sediment Marsh Grass 0.01 (6.80) Non- (5.60) Non- Contaminated 0.75 Contaminated 0.17 Sediment Sediment Non- Non- Contaminated 0.25 Contaminated 0.25 Marsh Grass Marsh Grass Contaminated Contaminated Contaminated Contaminated Marsh Grass Sediment 0.02 Marsh Grass Sediment 0.01 (15.60) Non- (16.00) Non- Contaminated 0.12 Contaminated 0.12 Sediment Sediment Non- Non- Contaminated 0.17 Contaminated 0.12 Marsh Grass Marsh Grass Non- Non- Contaminated Contaminated Contaminated 0.75 Contaminated 0.17 Sediment Sediment Sediment Sediment (8.80) Contaminated (10.00) Contaminated 0.12 0.12 Marsh Grass Marsh Grass Non- Non- Contaminated 0.60 Contaminated 0.75 Marsh Grass Marsh Grass Non- Non- Contaminated Contaminated Contaminated 0.25 Contaminated 0.25 Sediment Sediment Marsh Grass Marsh Grass (10.80) Contaminated (10.40) Contaminated 0.17 0.12 Marsh Grass Marsh Grass Non- Non- Contaminated 0.60 Contaminated 0.75 Sediment Sediment Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Contamination results

Total petroleum hydrocarbon analysis confirmed our selection of contaminated

and non-contaminated sites. The contaminated sediment and marsh grass had 30 and 20

times higher TPH than non-contaminated sediment and marsh grass (Table 2.4).

Table 2.4 TPH 2010

Site Maximum (mg/kg) Total (mg/kg) Contaminated Sediment 22,150 31,944 Contaminated Marsh Grass 21,588 21,588 Non-Contaminated Sediment 620 1,269 Non-Contaminated Marsh Grass 0 0

Spatial study

The expanded field and laboratory work, completed in August and September of

2011, focused on contaminated marsh grasses only and results show elevated sulfide

concentrations (H2S > 4000µM) for all sites. Location parameters taken during sample collection may be found in (Table 2.5). As oxygen concentrations decrease, redox potential moves toward the range ideal for sulfate reduction (~ 0mV to -200mV), sulfide

concentrations increase, and pH becomes more acidic (Figure 2.6).

Table 2.5 Location parameters.

Location Temperature (°C) DO (mg/ L) Salinity (‰) Tidal Flux (ft)

Saltpan Island 29.33 4.71 23.10 1.3

Marsh Point 29.88 6.24 6.24 1.2

Cat Island 30.22 7.05 7.05 1.3

Skiff Island 31.15 6.00 10.45 1.3

Tidal data averaged for August 2011 from (2011)

Spatial electrode results

Electrode profiles show average H2S concentrations between 0 μM to 6784 μM,

average O2 concentrations between 0 μM and 369 μM, average pH between 6.6 and 8.6,

and average Eh between -189 mV and 248 mV (Figure 2.6). Significant differences were

observed for all four electrode parameters measured (Tables 2.6 & 2.7).

Figure 2.6 Electrode profiles for Skiff Island, Louisiana and Cat Island, Marsh Point, and Saltpan Island, Mississippi.

Profiles presented are an average between August and September sampling periods.

Saltpan Island, Mississippi was the eastern most of the four locations included in the study. Sulfide concentrations at Saltpan Island increased consistently with depth with the largest jump between 3.2 cm and 3.3 cm depth from 1716.9 μM to 3766.8 μM respectively. Sulfide reached a maximum of 4389.3 μM at 3.6 cm below the sediment

surface. The lowest sulfide concentration was 344.8 μM measured at 0.6 cm below the sediment surface. Oxygen concentrations were highest at 0.5 cm above the sediment surface with a value of 188.0 μM. The largest millimeter decrease in oxygen concentrations occurred between 0.1 cm above the sediment and the sediment water interface where concentrations decreased from 120.8 μM to 23.6 μM respectively.

Oxygen concentrations decreased with depth reaching concentrations <0 μM at 0.2 cm below the sediment surface and continued to decrease until reaching 0 μM at 2.5 cm below the sediment surface. The pH was highest 0.3 cm above the sediment surface with a value of 8.0. The largest pH change occurred between 0.1 cm above the sediment surface and 0.3 cm below the sediment surface jumping from 7.9 to 7.2 respectively. The most acidic pH occurred at 2.0 cm below the sediment surface with a value of 6.9. Redox potential was highest as 0.2 cm above the sediment surface as indicated by and Eh value of 192.4 mV. Following the maximum value, Eh decreased with depth reaching a minimum of -118.5 mV at 3.7 cm below the sediment surface.

Marsh Point, Mississippi, just west of Saltpan Island, had the highest sulfide levels of all four sites. Sulfide concentrations peaked at 6784.3 μM only 0.8 cm below the sediment surface. Sulfide levels were lowest 0.3 cm above the sediment at 46.3 μM.

The most dramatic leap in sulfide concentrations occurred from 0.2 cm above the sediment surface to 0.6 cm below the sediment surface with concentrations from 69.8 μM to 6174.4 μM respectively. Though sulfide concentrations decreased after reaching the maximum at a 0.8 cm depth, the lowest sulfide concentration in the sediment was 1445.6

μM at 4.1 cm depth. Out of the four locations, Marsh Point had the overall lowest oxygen concentrations. Oxygen levels were highest at 0.4 cm above the sediment surface

with a concentration of 147.7 μM. Oxygen decreased most dramatically between 0.2 cm above the sediment surface and 0.1 cm below the sediment surface with concentrations of

95.9 μM and 16.8 μM respectively. Oxygen concentrations reached 0 μM at 0.8 cm depth when sulfide concentrations peaked. Of the four locations in the study, sediment pH was most acidic at Marsh Point. Above the sediment pH was slightly alkaline at 7.8, dropped below 7.0 at 0.8 cm depth, and reached a low of 6.6 at 1.5 cm depth. Marsh

Point had the lowest recorded Eh values of the four locations in the study. Redox potential was highest at 0.5 cm above the sediment as indicated by an Eh value of 222.9 mV. Eh deceased with depth with the largest millimeter increment drop of -63.0 mV occurring between 0.8 cm and 0.9 cm from -103.8 mV to 40.8 mV respectively. Eh continued to decrease with depth reaching its lowest value of -189.3 at 3.8 cm depth.

Farther to the west is Cat Island, Mississippi. Sulfide levels at Cat Island were the lowest out of the four locations. Sulfide concentrations were 591.0 μM at 0.5 cm above the sediment and actually decreased upon entering the sediment reaching a low of 0.0 μM at 0.6 cm below the sediment surface. Sulfide concentrations began to increase again at

1.0 cm below the sediment surface and reach a maximum of 3002.5 μM at 4.1 cm below the sediment surface. Cat Island had the highest oxygen concentrations of the four locations in the study. Oxygen concentrations were highest at the sediment water interface with a value of 369.1 μM. Oxygen concentrations decreased after entering the sediment with the most dramatic decrease occurring between 0.5 cm below the sediment surface and 0.7 cm below the sediment surface with values from 314.9 μM to 153.5 μM respectively. Oxygen concentrations did not reach 0 μM until 2.0 cm below the sediment surface. Cat Island had the most alkaline pH of the four locations in the study. The

highest value reached was 8.6 which occurred at 0.3 cm below the sediment surface.

After reaching the maximum value at 0.3 cm depth, values decreased until reaching a minimum of 6.7 at 3.4 cm below the surface. Eh values were highest at the sediment

water interface with a value of 247.9 mV. Recall that oxygen levels also peaked at the

sediment water interface. Eh values decreased continually with depth in the sediment

reaching a minimum of -104.4 mV at 4.2 cm below the sediment surface.

The eastern-most location included in the study was Skiff Island, Louisiana. Skiff

Island had the second highest sulfide concentrations; exceeded only by Marsh Point.

Marsh Point sulfide levels peaked at the shallow depth of 0.8 cm below the sediment

surface with a value of 6784.3 μM. Skiff Island sulfide concentration peaked with a value of 6003.3 μM, much deeper in the sediment at 3.5 cm below the sediment surface.

The sulfide concentration at 0.5 cm above the sediment surface was 275.4 μM and decreased until reaching a minimum at 1.6 cm below the surface with a value of 195.5

μM. Sulfide concentration fluctuated with depth showing an overall increase with depth between 1.6 cm and 3.5 cm where the maximum sulfide concentration was recorded.

Oxygen concentrations constantly decreased with depth. The highest concentration measured was 188.4 μM at 0.4 cm above the sediment surface and values decreased until reaching < 1.0 μM at 1.3 cm depth. The most alkaline pH recorded occurred at 0.1 cm

above the sediment surface with a value of 8.1. Values decreased until reaching a

minimum value of 7.0 at 4.1 cm below the sediment surface. Out of the four locations,

redox potential was highest at Skiff Island. The highest Eh value recorded was 156.4 mV

at 0.2 cm above the sediment surface. Eh decreased until reaching a minimum of -4.5

mV at 4.2 cm below the sediment surface.

Table 2.6 Kruskal-Wallis and Mann-Whitney results for comparison of H2S and O2 by location.

H2S O2 Location Location Location Significance Location Significance (Mean Rank) (Mean Rank) Saltpan Island Marsh Point 0.00 Saltpan Island Marsh Point 0.10 (278.11) Cat Island 0.48 (268.33) Cat Island 0.00 Skiff Island 0.00 Skiff Island 0.02 Marsh Point Saltpan Island 0.00 Marsh Point Saltpan Island 0.10 (330.05) Cat Island 0.00 (245.12) Cat Island 0.00 Skiff Island 0.00 Skiff Island 0.00 Cat Island Saltpan Island 0.48 Cat Island Saltpan Island 0.00 (282.74) Marsh Point 0.00 (343.67) Marsh Point 0.00 Skiff Island 0.00 Skiff Island 0.02 Skiff Island Saltpan Island 0.00 Skiff Island Saltpan Island 0.02 (219.67) Marsh Point 0.00 (303.96) Marsh Point 0.00 Cat Island 0.00 Cat Island 0.02 Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Table 2.7 Kruskal-Wallis and Mann-Whitney results for comparison of pH and Eh by location.

pH Eh Location Location Location Significance Location Significance (Mean Rank) (Mean Rank) Saltpan Island Marsh Point 0.00 Saltpan Island Marsh Point 0.00 (269.64) Cat Island 0.00 (307.49) Cat Island 0.05 Skiff Island 0.00 Skiff Island 0.23 Marsh Point Saltpan Island 0.00 Marsh Point Saltpan Island 0.00 (217.17) Cat Island 0.00 (197.80) Cat Island 0.00 Skiff Island 0.00 Skiff Island 0.00 Cat Island Saltpan Island 0.00 Cat Island Saltpan Island 0.05 (339.07) Marsh Point 0.00 (269.76) Marsh Point 0.00 Skiff Island 0.51 Skiff Island 0.00 Skiff Island Saltpan Island 0.00 Skiff Island Saltpan Island 0.23 (334.83) Marsh Point 0.00 (332.12) Marsh Point 0.00 Cat Island 0.51 Cat Island 0.00 Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Spatial Biolog results

Biolog ECO plate data showed that the aerobic and anaerobic communities had significantly different distributions at Cat Island compared to all other sites (Table 2.8 &

Figure 2.7). Saltpan Island, Marsh Point and Skiff Island did not have significantly different distributions from each other with reference to biological community as determined by Mann Whitney U tests. A paired t-test determined that the combined aerobic data for all sites was not significantly different from the combined anaerobic data for all sites (t(68) = 0.42, p=0.67). The Mann Whitney U test showed no significant difference in distributions between communities at 2-4 cm depth and 4-6 cm depth for aerobic or anaerobic communities (p=0.45) . Aerobic communities did have significantly different distributions for 0-2 cm and 2-4 cm depths (p=0.02) and 0-2 cm and 4-6 cm depths (p=0.00), however anaerobic communities showed no significant difference in distributions with depths (p=0.29).

Table 2.8 ECO plate statistical results.

Aerobic ECO Plate Biolog Anaerobic ECO Plate Biolog Location Location Location Significance Location Significance (Mean Rank) (Mean Rank) Saltpan Island Marsh Point 0.29 Saltpan Island Marsh Point 0.91 (36.67) Cat Island 0.00 (42.33) Cat Island 0.00 Skiff Island 0.31 Skiff Island 0.61 Marsh Point Saltpan Island 0.29 Marsh Point Saltpan Island 0.91 (42.53) Cat Island 0.00 (41.00) Cat Island 0.00 Skiff Island 0.66 Skiff Island 0.97 Cat Island Saltpan Island 0.00 Cat Island Saltpan Island 0.00 (17.33) Marsh Point 0.00 (17.44) Marsh Point 0.00 Skiff Island 0.00 Skiff Island 0.00 Skiff Island Saltpan Island 0.31 Skiff Island Saltpan Island 0.61 (44.72) Marsh Point 0.66 (40.22) Marsh Point 0.97 Cat Island 0.00 Cat Island 0.00 Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Figure 2.7 ECO plate graphical results.

Biolog AN plate data showed a significant difference in the anaerobic community between all locations excluding Saltpan Island and Marsh Point (Figure 2.8 &Table 2.9).

The Mann- Whitney U test determined that there was a significant difference between the anaerobic community present at a 0-2 cm depth and a 4-6 cm depth (p=0.00) as well as a

2-4 cm depth and a 4-6 cm depth (p=0.00). Anaerobic community was not statistically different between 0-2 cm and 2-4 cm depth (p=0.74).

Figure 2.8 AN plate graphical results.

Table 2.9 AN plate statistical results.

AN Biolog Location Location Significance (Mean Rank) Saltpan Island Marsh Point 0.74 (69.94) Cat Island 0.00 Skiff Island 0.01 Marsh Point Saltpan Island 0.74 (66.93) Cat Island 0.00 Skiff Island 0.00 Cat Island Saltpan Island 0.00 (35.06) Marsh Point 0.00 Skiff Island 0.00 Skiff Island Saltpan Island 0.01 (92.40) Marsh Point 0.00 Cat Island 0.00 Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

Contamination results

Total non-polar hydrocarbon results show higher non-polar hydrocarbons for the western-most sites, Skiff Island and Cat Island, compared to the eastern most sites (Table

2.10). GC-MS analysis for Cat Island confirmed that TPH measured contained at least 24 crude oil hydrocarbon compounds all of which have been previously identified in oil mousses and contaminated sediments (Figure 2.9) (Liu et al., 2012; Beazley et al., 2012).

Table 2.10 TPH 2011

Location Maximum (mg/kg) Average Sites (mg/kg) Saltpan Island 1,717 1,201 Marsh Point 1,570 693 Cat Island 8,631 2,183 Skiff Island 7,305 2,996

Figure 2.9 Cat Island chromatogram shows hydrocarbon signatures confirm contamination.

Particle size results

Particle size varied among locations (Figure 2.10). The finest grained location

was Skiff Island, Louisiana which also had a significantly more active anaerobic

community than other locations. Marsh Point and Saltpan Island, Mississippi had very

similar particle sizes, similarly active anaerobic community, and were not significantly

different in O2 concentrations. Cat Island was the coarsest grained site which had significantly more oxygen than the other locations and had the most oxygen penetration with depth as indicated by electrode profiles. H2S concentrations at Cat Island were not

significantly different from Saltpan Island even though Cat Island had a higher TPH than

Saltpan Island. One explanation for that is that Saltpan Island has finer grained sediment

so there was less oxygen diffusion in sediments for aerobes to utilize as compared to Cat

Island. Even though Cat Island had the highest TPH observed, it had the lowest pore

water H2S, and a significantly less active microbial community. Lower H2S may be attributed to the oxygen in sediments allowing for aerobic degradation of hydrocarbons.

Figure 2.10 Particle size variation among locations.

Discussion

Anaerobic sulfate reduction may be enhanced due to contamination as indicated

by an abundance of sulfate reducing bacteria (SRB) in oil contaminated sediments along

with elevated sulfide levels up to 82.4 mg/kg (2,478µM) previously reported in heavily oiled Louisiana marshes (Natter et al., 2012). Preliminary analysis completed in October

of 2010 indicated that SRB were significantly more active in areas with contaminated

marsh grass, producing sulfide concentrations more than 100x higher than areas with

non-contaminated marsh grass. Contaminated marsh grass had sulfide levels

significantly higher than contaminated sediments as well. High productivity in salt

marshes is linked to the roots and rhizomes belowground (Schubauer and Hopkinson,

1984). Higher sulfide levels in contaminated marsh grasses compared to contaminated sediments may be attributed to a more abundant or diverse microbial population in the plant rhizosphere. Also, lower TPH in contaminated marsh grass (21,588 mg/kg)

compared to contaminated sediment (31,944 mg/kg) may reflect a more active microbial

community resulting in more efficient biodegradation of hydrocarbons in marsh grasses

than sediments. A study done by Mishra et al. (2012) reveals that significantly lower

photosynthetic activity was recorded at the peak of the 2010 growing season as compared

with other years. Reduced plant activity could be attributed to the high sulfide levels

recorded in 2010 (up to 4034 µM). Comparatively, at the non-contaminated site, aerobic

microbial communities were more active and abundant exhibiting the dominance of

aerobic processes meaning higher oxygen levels and decreased sulfide levels.

By the fall of 2011, heavily oiled locations still showed little to no recovery

(Mendelssohn, 2012) and photosynthesis began to decrease a month earlier (Wu et al.,

2012). Data collected from four locations along the Mississippi and Louisiana Gulf

Coast showed that there was no consistent trend of sulfide levels and proximity to the

DWH blowout. TPH results did decrease moving east from Skiff Island to Saltpan

Island, excluding Marsh Point though it is important to acknowledge that TPH at Marsh

Point in 2010 was over 20,000 mg/kg.. Beazely et al. (2012) reported TPH in

contaminated marsh at Weeks Bay, Alabama, East of Saltpan Island, as high as 189

mg/kg which continues the TPH decrease eastward. Higher sulfide concentrations in the

upper centimeters of the sediment profile at Marsh Point may be attributed to the lower

energy shoreline as compared to Skiff Island and Cat Island and higher degree of

contamination as compared to Saltpan Island. TPH at Marsh Point in 2010 (21,588

mg/kg) was reduced by more than 95% by 2011 (693 mg/kg) indicating rapid degradation

likely due to an abundant and diverse microbial community. The very high sulfide levels

(2010 H2S up to 4034 µM and 2011 H2S up to 6784.3 μM) indicate that the microbial

community is likely dominated by sulfate reducing bacteria, which are the most efficient

anaerobic hydrocarbon degrading microbes (Boopathy et al., 2012). The depth profile for

H2S at Skiff Island, Cat Island, and Saltpan Island was the inverse of the Marsh Point

profile with the three other locations having the highest concentrations of H2S deeper in

the sediment. Increase in H2S with depth in the upper few centimeters is typical of

wetland sediments however, the trend seen at these three sites have three different

explanations. Considering Marsh Point’s 2010 measurements, Saltpan Island was the

least contaminated site and shows the expected wetland trend for increasing H2S with

depth reaching 4389.3 μM at 3.6 cm below the surface. Due to coarser grainsize, Cat

Island had the most oxygen penetration with depth, so even though it was still a heavily

contaminated site in the 2011 sampling period, it is likely dominated by aerobic and

higher TEA processes shallow in the sediment. H2S slowly increased with depth as

oxygen was depleted and reached 3002.5 μM at 4.1 cm below the surface at Cat Island.

The nearest concentrations of H2S to Marsh Point were observed at 3.5 cm depth at Skiff

Island, Louisiana where H2S reached 6003.3 μM. Sulfide reaching a maximum deeper in

sediments at Skiff Island is likely due to an abundance of higher TEAs (e.g. phosphates,

nitrates) from the Mississippi River nutrient-rich discharge.

The trend in pH at the four locations varies with the sulfide concentrations. At

Skiff Island, Cat Island, and Saltpan Island pH becomes more acidic with depth as sulfide

concentrations increase. At Marsh Point, pH becomes more acidic higher in the sediment

when sulfide concentrations reach a maximum and pH gets slightly more basic as sulfide

concentrations decrease penetrating the sediment further. For all sites the mean pH was

close to 7 (Saltpan Island = 7.1, Marsh Point pH = 7.0, Cat Island = 7.6, Skiff Island =

7.2), which is ideal for assimilatory sulfate reduction by microbes such as Desulfovibrio

(Mitsch and Gosselink, 2007). Assimilatory sulfate reducers including Desulfovibrio, are

members of the sub-phylum Deltaproteobacteria and have been found in contaminated

marsh sediments. Other phylums identified that contain sulfate reducers include:

Acidobacteria, Firmicutes, and Nitrospirae (Beazley et al., 2012).

Higher redox potentials at Skiff Island, Cat Island, and Saltpan Island may promote a mixed microbial community where a combination of TEAs can be used including sulfate reducers to degrade hydrocarbons. Mixed electron acceptor conditions yield higher degradation rates of hydrocarbon contaminants (Boopathy et al., 2012).

Skiff Island may be influenced by an abundance of nitrates and phosphates that act as

TEAs since the Mississippi River discharge brings agricultural runoff into the Mississippi

River Delta ecosystem. Cat Island had the coarsest grained sediments allowing better

water flow through sediments and more oxygen diffusion into sediments. More oxygen

in Cat Island sediments would speed up degradation of hydrocarbons, and likely the

recovery process, in contaminated Cat Island areas.

Another factor contributing to sulfide presence in marshes is the iron content.

High iron concentrations in sediments can help to reduce the toxicity of sulfide in soils.

Ferrous iron (Fe2+) can bind with sulfides to form insoluble iron sulfide minerals (Mitsch

and Gosselink, 2007). Perhaps differing concentrations of iron among sites can account

for some of the difference in sulfide concentrations. Natter et al. (2012) reported low

iron concentrations in Louisiana contaminated marshes and high sulfide concentrations

indicating iron fixation through the mineralization of iron sulfides. If there were initially high iron concentrations at a site, sulfides could be precipitated to form ferrous sulfides

thus removing the sulfide from pore water and reducing toxicity of sediment.

Chronic severity of contamination is influenced by the energy of the coastline among other things. The influence that physical environments have on the biogeochemistry of sediments is unclear (Natter et al., 2012). The variation in the energy

of the shorelines at different locations can influence the severity of oil contamination and persistence in sediments. Higher energy shorelines can have sediments reworked and bring fresh seawater into the sediments. Perhaps this can explain less severely reduced environments of Skiff Island and Cat Island, which are more directly exposed to open ocean waves, as compared to Marsh Point and Saltpan Island, which are within the

Mississippi Sound. Tidal forcing significantly influences the first few centimeters below

the sediment-water interface by shifting the location of reducing conditions and sulfide

production (Taillefert et al., 2007). Thus, the tidal cycle during which sediments were

collected could also play a role in the vertical location of highest sulfide concentrations in

a depth profile. The lower energy and possibly tidal forcing at Marsh Point would likely

be a factor in the more reduced environment and high sulfide concentrations shallow in

sediments observed in comparison to Skiff Island.

Data collected from Saltpan Island, Marsh Point, Cat Island, and Skiff Island indicate that sulfate reduction is important for the degradation of hydrocarbons in salt

marshes along the Gulf Coast. The effect of contamination in marshes along the Gulf

Coast is not solely a function of the amount of contamination a location received. In

order to observe the full effects of contamination one must instead consider the

variability in marsh response to contamination due to physical processes,

biogeochemistry, and sediment dynamics in different marshes along the coast.

CHAPTER III

TEMPORAL SALT MARSH SEDIMENT RESPONSE TO DWH BLOWOUT

Introduction

The 2010 BP Deepwater Horizon blowout is the largest oil spill in U.S history to date (McNutt et al., 2011). Over 4.9 million barrels of oil gushed into the Gulf of Mexico placing habitats of the Gulf Coast in a vulnerable position. Among the coastal environments affected by the spill, salt marshes may be the most vulnerable (Pezeshki et al., 2000). Salt marshes provide a variety of services including some of the most valuable services among natural ecosystems (Gedan et al., 2009). Weathered oil was primarily what contaminated the shoreline of marshes along the Gulf Coast. An estimated 430 miles of marsh fringe was oiled, 176 miles of which was heavily to moderately contaminated (Zengel and Michel, 2011).

A variety of physical, biological, and chemical processes play a role in determining the fate of oil in contaminated coastal ecosystems (Leahy and Colwell,

1990). Residence time of oil in salt marshes is thought to be ten or more years (Pezeshki et al., 2000). However, degradation rates of hydrocarbons increase with temperature

(Leahy and Colwell, 1990) indicating that the sub-tropical climate of the Gulf Coast region is advantageous to combatting the spill as chronic effects of oil spill contamination in tropical environments tends to be less persistent (Table 3.1) (Mendelssohn, 2012).

Table 3.1 Past oil spills and environment recovery periods

Spill Location Date Volume (gallons) Recovery Climate West Falmouth, MA September 1969 184,900.00 > 40 years Temperate Brittany, France March 1978 67,200,000.00 > 8 years Temperate Arthur Kill, NY January 1990 660,450.00 > 7 years Temperate Swanson Creek, MD April 2000 140,000.00 >7 years Temperate Nairn, LA April 1985 12,600.00 > 4 years Sub-Tropical Bahia Las Minas, Panama April 1986 2,100,000.00 >3 years Tropical Tampa Bay, FL August 1993 300,000.00 >2years Sub-Tropical Modified from (Mendelssohn, 2012).

Hydrocarbon contamination in coastal environments stimulates the sulfur cycle

(Kleikemper et al., 2002). Anaerobic biodegradation through sulfate-reducing bacteria that also degrade hydrocarbon in reduced sediments is among the most important anaerobic processes in contaminated sediments (Rothermich et al., 2002). Fortunately, salt marshes are typically not limited in sulfate ions as seawater is a constant source for sulfate with ~2.7 g/L (Mitsch and Gosselink, 2007). Sulfur oxidizing and sulfate reducing bacteria have been found to represent up to 40% of the bacterial community in oil contaminated coastal sediments (Paisse et al., 2008). Anaerobic sulfate reducing bacteria, like Desulfovibrio desulfuricans, reduce sulfate by stripping the sulfate ion of oxygen and leaving H2S (Reddy and DeLaune, 2008).

The distribution of marsh vegetation can be affected by the presence of sulfide

(DeLaune and Wright, 2011). Spartina alterniflora and Juncas roemerianus are dominant fringing salt marsh grass species and experienced nearly complete mortality at heavily oiled locations (Mendelssohn, 2012). Little to no recovery in heavily oiled locations causes them to be more susceptible to erosion (Mendelssohn, 2012).

Contaminated sites at Marsh Point, Mississippi experienced low photosynthetic activity through the peak of the 2010 growing season. Rates were beginning to increase by August 2010 but decreased by October 2010 (Wu et al., 2012). Similarly, chlorophyll and green biomass was low in May 2010, increased by September, and plummeted by

October (Figure 3.1) (Mishra and Ghosh, 2012). During the dormant season, marsh grasses are less sensitive to oiling (Pezeshki et al., 2000; Mishra et al., 2012) which was reflected through the 2010-2011 winter months when there was no difference in photosynthetic activity between contaminated and non-contaminated sites at Marsh Point

(Wu et al., 2012). Chlorophyll and green biomass increased slightly through the spring and start of summer 2011 reaching a very low maximum in August before decreasing again (Figure 3.1) (Mishra and Ghosh, 2012). Photosynthesis rates seem to follow the same trend, increasing through the spring and early summer but decreasing by September in contaminated areas (Wu et al., 2012).

Figure 3.1 Phenology plots for 2010 and 2011.

CHL stands for chlorophyll and GBM stands for green biomass (Mishra and Ghosh, 2012).

Research Question

With reference to hydrocarbon contamination, what will the initial response of salt

marshes be and how will salt marshes recover over time?

Methodology

Methodology applied all three years

Upon arrival at a site, GPS coordinates were recorded and water quality measurements including dissolved oxygen (DO), salinity, temperature, and conductivity, was taken using a YSI 85 (Yellowsprings, Ohio). Cores were taken using plastic core liners ~30-35 cm long and 9 cm in diameter. Once cores were extracted, the liner was capped, sealed, and brought to the field laboratory for analysis. In the field laboratory cores were analyzed using microelectrodes. The electrode set up requires the Unisense

microelectrode profiling system (Brendstrup, Denmark), Sensor Trace Pro software

program, a micromanipulator that allows for fine-scale measurements with depth, and the

electrodes that measure the desired chemical parameters. Vertical profiles were generated beginning 5 mm above the sediment water interface and penetrating the sediment up to 4 cm. Triplicate readings were taken in millimeter increments. Depth profiles were generated with electrode measurements and a statistical analysis was conducted.

Deviations in methodology among years

In 2010 cores were taken at contaminated sediment and marsh grass and non-

contaminated sediment and marsh grass (see Chapter II). Therefore, the only data

comparable to 2011 and 2012 is the core taken in contaminated marsh grass. In 2011 and

2012 cores were taken at three contaminated marsh grass sites at the Marsh Point

location.

Statistical analysis

Electrode data did not meet the assumptions for parametric testing so a non-

parametric approach was taken. The Kruskal-Wallis test is a non-parametric equivalent

to the one way ANOVA. Like the ANOVA, the Kruskal-Wallis test tells if there is a

difference between any groups in the study and a post hoc analysis is required to identify

which groups are significantly different. The Mann-Whitney was used to identify which

groups were statistically different from one another.

Results

In the fall of 2010, electrode profiling revealed sulfide levels as high as 4034 μM

in contaminated marsh grass at Marsh Point, Mississippi. The location was revisited in

2011 and 2012 in order to monitor H2S in marsh grass sediments during the recovery from contamination. Sulfide concentrations were high in 2010 and even higher in 2011.

By 2012, sulfide concentrations decreased dramatically from a maximum of 6784 μM in

2011 to a maximum of 562 μM (Figure 3.2).

In October of 2010, electrode measurements for H2S ranged from 54 μM to 4034

μM and O2 concentrations were between 0 μM and 117 μM in 2010 in contaminated

marsh grasses. By August and September of 2011, sulfide measurements significantly

increased (p=0.00), ranging from 46 μM to 6784 μM and O2 concentrations ranged from

0 μM to 148 μM. In July of 2012, sulfide concentrations were significantly lower

(p=0.00) ranging from 17 μM to only 562 μM while O2 concentrations ranged from 12

μM to 145 μM. Sulfide concentrations for the three sampling periods were significantly

different (p=0.00). Oxygen concentrations were significantly different for 2010 versus

2011 (p=0.00) and 2011 versus 2012 (p=0.00). Oxygen however, was not significantly different for 2010 versus 2012 (p=0.10) (Table 3.2).

Figure 3.2 Electrode profiles for Marsh Point, Mississippi for 2010, 2011, & 2012.

Table 3.2 Temporal electrode statistics.

H2S O2 Year Year Location Significance Location Significance (Mean Rank) (Mean Rank) 2010 2011 0.00 2010 2011 0.00 (68.75) 2012 0.00 (90.34) 2012 0.10 2011 2010 0.00 2011 2010 0.00 (99.60) 2012 0.00 (35.04) 2012 0.00 2012 2010 0.00 2012 2010 0.10 (33.78) 2011 0.00 (81.88) 2011 0.00 Bold indicates significant difference according to the Mann-Whitney U test (p < 0.05)

In 2010 TPH for Marsh Point was extremely high as was H2S. By 2011, TPH had drastically decreased however, H2S was even higher than in 2010 (Table 3.3).

Table 3.3 TPH values for Marsh Point in 2010 and 2011.

Year Maximum (mg/kg) TPH (mg/kg) 2010 21,588 21,588 2011 1,570 693

Discussion

Elevated sulfide levels in 2010 indicated that there was a possibility that sulfide levels were a factor in marsh stress after contamination. Photosynthetic activity was greatly reduced at the peak of the 2010 growing season (Mishra et al., 2012). Oiling along the coastline continued through the winter months when vegetation is dormant and microbial processes slow down (Mitsch and Gosselink, 2007). Vegetation is less vulnerable to oil contamination during the dormant season (Pezeshki et al., 2000). In

2011, sulfide concentrations reached a maximum with concentrations as high as 6,784

μM. The concentrations that reached a maximum one year after the spill may be representatives of a lag time for the microbial response to the contamination. In 2012, sulfide concentrations in salt marsh sediments were much lower only reaching 562 μM.

Lower concentrations of H2S observed in 2012 may indicate that salt marsh at Marsh

Point, Mississippi is beginning to re-equilibrate. Salt marsh hydrocarbon contamination likely caused elevated sulfide concentrations in marsh sediments in 2010, sulfide concentrations reached a maximum in 2011 and the marsh seems to be recovering as indicated by reduced sulfide concentrations observed in 2012. The lag time in maximum

sulfide concentrations is likely due to decreased microbial activity in colder months postponing efficient degradation of hydrocarbons until the following growing season. In

2011, microbes were likely extremely active and efficient at degrading hydrocarbons as reflected by the change in TPH from 2010 to 2011 and higher sulfide concentrations in sediments. The end of July 2012 marked two full spring/summer periods in which hydrocarbons could efficiently be degraded. Much lower sulfide concentrations in 2012 compared to 2010 or 2011 represent great potential for biogeochemical recovery in sediments. Marsh re-exposure to contamination as a result of storm events washing oil ashore could prolong recovery. Biogeochemical observations from 2012 are a hopeful indication that marshes along the Gulf Coast may recover sooner than anticipated, however, the amount of dieback observed due to contamination, will be a major factor in the recovery of marshes if shorelines are eroded before vegetation recovers (Alber et al.,

2008).

CHAPTER IV

SUMMARY

Salt marsh sediment response to oil contamination has serious implications for the microbial and biological communities in contaminated areas. Increased microbial activity in salt marshes as a result of hydrocarbon contamination altered the sediment biogeochemistry. Elevated sulfide levels in Gulf Coast salt marshes have negative effects on marsh vegetation. Studies on salt marsh vegetation show that vegetation health has deteriorated since the blowout (Mishra et al., 2012; Wu et al., 2012). Sulfide concentrations in pore water at four locations along the Mississippi and Louisiana Gulf

Coast are high enough to cause detrimental effects on vegetation. Marsh Point,

Mississippi showed elevated sulfide levels in 2010 and even higher sulfide concentrations in 2011. Sulfide levels seem to have peaked in 2011 and by 2012, sulfide concentrations had greatly decreased. Considering the spatial and temporal data collectively, salt marshes along the Gulf Coast have experienced extremely elevated sulfide levels in their sediments. The damage done to marshes in the first year following the spill will play a major role in the marsh recovery capability since the years immediately following the spill are critical as high vegetation mortality at the marsh fringe can cause marsh loss to open water.

Hypotheses:

1. ACCEPTED. There was significantly more sulfide production in

contaminated marsh grasses than contaminated sediments, non-

contaminated sediments, and non-contaminated marsh grasses.

2. REJECTED. While on the grand scale this may hold true, variations in

the physical environment and biogeochemistry specific to locations along

the Gulf Coast prevent the application of such a generalization on the

small scale.

3. ACCEPTED. There is some lag time in maximum biogeochemical

changes in sediments and time of contamination that could be due to lower

microbial activity in winter months preventing efficient biodegradation of

oil as it washed ashore. In 2012 sulfide concentrations were one tenth of

what they were in 2011 indicating that sediments are beginning to re-

equilibrate.

REFERENCES

"National Oceanic and Atmospheric Administration Tides & Currents." NOAA Tide Predictions. 2011.

"Report of the Method 1664 Validation Studies." Washington, D.C.: U.S. Environmental Protection Agency, 1995. Print.

Aitken, Carolyn M., D. Martin Jones, and S. R. Larter. "Anaerobic Hydrocarbon Biodegradation in Deep Subsurface Oil Reservoirs." Nature [London] 431.7006 (2004): 291-94. Print.

Alber, Merryl, et al. "Salt Marsh Dieback: An Overview of Recent Events in the Us." Estuarine, Coastal and Shelf Science 80.1 (2008): 1-11. Print.

Anderson, Robert T., and Derek R. Lovley. "Anaerobic Bioremediation of Benzene under Sulfate-Reducing Conditions in a Petroleum-Contaminated Aquifer." Environmental Science & Technology, ES & T 34.11 (2000): 2261-66. Print.

Beazley, Melanie J., et al. "Microbial Community Analysis of a Coastal Salt Marsh Affected by the Deepwater Horizon Oil Spill." PLoS ONE 7.7 (2012): 1-13. Print.

Boopathy, Raj, Sara Shields, and Siva Nunna. "Biodegradation of Crude Oil from the Bp Oil Spill in the Marsh Sediments of Southeast Louisiana, USA." Applied Biochemistry and Biotechnology 167.6 (2012): 1560-68. Print.

Burns, K.A., S.D. Garrity, and S.C. Levings. "How Many Years until Mangrove Ecosystems Recover from Catastrophic Oil Spills?" Marine Pollution Bulletin 26.5 (1993): 239-48. Print.

Calleja, Maria Ll, Núria Marbà, and Carlos M. Duarte. "The Relationship between Seagrass (Posidonia Oceanica) Decline and Sulfide Porewater Concentration in Carbonate Sediments." Estuarine, Coastal and Shelf Science 73.3-4 (2007): 583- 88. Print.

Carlson, J., et al. "Relationship of Sediment Sulfide to Mortality of Thalassia Testudinum in Florida Bay." Bulletin of Marine Science 54.3 (1994): 733-46. Print.

Cervantes, F. J., et al. "Anaerobic Mineralization of Toluene by Enriched Sediments with Quinones and Humus as Terminal Electron Acceptors." Applied and Environmental Microbiology.10 (2001): 4471. Print. 65

Chaudhry, Qasim, et al. "Utilising the Synergy between Plants and Rhizosphere Microorganisms to Enhance Breakdown of Organic Pollutants in the Environment." Environmental Science and Pollution Research 12.1 (2005): 34- 48. Print.

DeLaune, R. D., and Alan L. Wright. "Projected Impact of Deepwater Horizon Oil Spill on Us Gulf Coast Wetlands." Soil Science Society of America Journal 75.5 (2011): 1602-12. Print.

Eldridge, Peter M., and John W. Morse. "A Diagenetic Model for Sediment–Seagrass Interactions." Marine Chemistry 70.1–3 (2000): 89-103. Print.

Engle, V. D. "Estimating the Provision of Ecosystem Services by Gulf of Mexico Coastal Wetlands." Wetlands 31.1 (2011): 179-93. Print.

Faure, Gunter. Principles and Applications of Geochemistry : A Comprehensive Textbook for Geology Students. Upper Saddle River, N.J. : Prentice Hall, c1998. 2nd ed., 1998. Print.

Gedan, K. Bromberg, B. R. Silliman, and M. D. Bertness. "Centuries of Human-Driven Change in Salt Marsh Ecosystems." Annual Review of Marine Science 1.1 (2009): 117-41. Print.

Hoekstra, J.M., et al. The Atlas of Global Conservation: Changes, Challenges and Opportunities to Make a Difference. University of California Press Berkeley, California, USA, 2010. Print.

Holmer, M., C.M. Duarte, and N. Marbá. "Sulfur Cycling and Seagrass (Posidonia Oceanica) Status in Carbonate Sediments." Biogeochemistry 66.3 (2003): 223-39. Print.

Howarth, R.W., and J.M. Teal. "Sulfate Reduction in a New England Salt Marsh." Limnology and Oceanography (1979): 999-1013. Print.

Jorgensen, B.B. "The Sulfur Cycle of a Coastal Marine Sediment (Limfjorden, Denmark)." Limnology and Oceanography (1977): 814-32. Print.

King, G.M. "Patterns of Sulfate Reduction and the Sulfur Cycle in a South Carolina Salt Marsh." Limnology and Oceanography (1988): 376-90. Print.

Kleikemper, J., et al. "Activity and Diversity of Sulfate-Reducing Bacteria in a Petroleum Hydrocarbon-Contaminated Aquifer." Applied and Environmental Microbiology 68.4 (2002): 1516-23. Print.

Klute, A. Methods of Soil Analysis. Part 1. Physical and Mineralogical Methods. American Society of Agronomy, Inc., 1986. Print.

Leahy, J.G., and R.R. Colwell. "Microbial Degradation of Hydrocarbons in the Environment." Microbiological Reviews 54.3 (1990): 305-15. Print.

Lin, Qianxin, and A. Mendelssohn Irving. "Potential of Restoration and Phytoremediation with Juncus Roemerianus for Diesel-Contaminated Coastal Wetlands." Ecological Engineering 35 (2009): 85-91. Print.

Liu, ZhanFei, et al. "The Weathering of Oil after the Deepwater Horizon Oil Spill: Insights from the Chemical Composition of the Oil from the Sea Surface, Salt Marshes and Sediments." Environmental Research Letters 7.3 (2012): 035302-02. Print.

MacDonald, I. R., et al. "Transfer of Hydrocarbons from Natural Seeps to the Water Column and Atmosphere." Geofluids 2.2 (2002): 95-107. Print.

Martinez, R. J., et al. "Prokaryotic Diversity and Metabolically Active Microbial Populations in Sediments from an Active Mud Volcano in the Gulf of Mexico." Environmental Microbiology 8.10 (2006): 1783-96. Print.

McNutt, M., et al. "Assessment of Flow Rate Estimates for the Deepwater Horizon/Macondo Well Oil Spill." Flow rate technical group report to the national incident command, interagency solutions group (2011): 1-22. Print.

Mendelssohn, Irving A. Andersen Gary L. Baltz Donald M. Caffey Rex H. Carman Kevin R. Fleeger John W. Joye Samantha B. Lin Qianxinmaltby Edwardoverton Edward B. Rozas Lawrence P. "Oil Impacts on Coastal Wetlands: Implications for the Mississippi River Delta Ecosystem after the Deepwater Horizon Oil Spill." BioScience 62.6 (2012): 562. Print.

Mishra, Deepak R., et al. "Post-Spill State of the Marsh: Remote Estimation of the Ecological Impact of the Gulf of Mexico Oil Spill on Louisiana Salt Marshes." Remote Sensing of Environment 118 (2012): 176-85. Print.

Mishra, Deepak R., and Shuvankar Ghosh. "Unpublished Data on Remote Estimation of the Ecological Impact of the Gulf of Mexico Oil Spill at Marsh Point, Ms." Mississippi State University, 2012 of Geosciences. Print.

Mitsch, William J., and James G. Gosselink. Wetlands / William J. Mitsch, James G. Gosselink. 4th ed: Hoboken, N.J. : Wiley, c2007., 2007. Print.

Natter, M., et al. "Level and Degradation of Deepwater Horizon Spilled Oil in Coastal Marsh Sediments and Pore-Water." Environ Sci Technol 46.11 (2012): 5744-55. Print.

Nellemann, C., E. Corcoran, and C.M. Duarte. Blue Carbon: The Role of Healthy Oceans in Binding Carbon: A Rapid Response Assessment. Earthprint, 2009. Print.

Paisse, S., et al. "Structure of Bacterial Communities Along a Hydrocarbon Contamination Gradient in a Coastal Sediment." Fems Microbiology Ecology 66.2 (2008): 295-305. Print.

Peterson, C.H., and J.A. Estes. "Conservation and Management of Marine Communities." Sinauer Associates, Inc. Sunderland, Massachusetts, 2001. 469-507. Print.

Pezeshki, S. R., et al. "The Effects of Oil Spill and Clean-up on Dominant Us Gulf Coast Marsh Macrophytes: A Review." Environ Pollut 108.2 (2000): 129-39. Print.

Reddy, K. R., and R. D. DeLaune. "Biogeochemistry of Wetlands: Science and Applications." Biogeochemistry of wetlands: science and applications. Eds. Reddy, K. R. and R. D. DeLaune. Boca Raton; USA: CRC Press Inc., 2008. Print.

Reichle, D. "Carbon Sequestration State of the Science: Working Paper on Carbon Sequestration Science and Technology." US Department of Energy, Office of Science and Fossil Energy (1999). Print.

Rothermich, M. M., L. A. Hayes, and D. R. Lovley. "Anaerobic, Sulfate-Dependent Degradation of Polycyclic Aromatic Hydrocarbons in Petroleum-Contaminated Harbor Sediment." Environmental Science and Technology 36.22 (2002): 4811- 17. Print.

Schlesinger, W.H. Biogeochemistry: An Analysis of Global Change. Academic press, 1997. Print.

Schubauer, J. P., and C. S. Hopkinson. "Above- and Belowground Emergent Macrophyte Production and Turnover in a Coastal Marsh Ecosystem, Georgia." Limnology and oceanography 29.5 (1984): 1052-65. Print.

Shin, W.S., J.H. Pardue, and W.A. Jackson. "Oxygen Demand and Sulfate Reduction in Petroleum Hydrocarbon Contaminated Salt Marsh Soils." Water research 34.4 (2000): 1345-53. Print.

Spill, National Commission on the BP Deepwater Horizon Oil, and Offshore Drilling. "Report to the President." Eds. Graham, Bob, et al.2011. Print.

Suárez‐Suárez, A., et al. "Response of Sulfate‐Reducing Bacteria to an Artificial Oil‐Spill in a Coastal Marine Sediment." Environmental microbiology 13.6 (2011): 1488- 99. Print.

Taillefert, M., S. Neuhuber, and G. Bristow. "The Effect of Tidal Forcing on Biogeochemical Processes in Intertidal Salt Marsh Sediments." Geochem Trans 8 (2007): 6. Print.

Tate, P. Timothy, et al. "Bioremediation of an Experimental Oil Spill in a Coastal Louisiana Salt Marsh." Water Air and Soil Pollution 223.3 (2012): 1115-23. Print. 68

Weis, J.S. "Salt Marsh." Encyclopedia of earth. Ed. Duffy, J. E., Cleveland, C.J. Washington, DC: Environmental2010. Print.

Wenner, Elizabeth. "Dynamics of the Salt Marsh." Marine Resources Research Institute (2010). Print.

White, D.A., et al. "Productivity and Decomposition of the Dominant Salt Marsh Plants in Louisiana." Ecology (1978): 751-59. Print.

Wu, W., et al. "Modeling Photosynthesis of Spartina Alterniflora (Smooth Cordgrass) Impacted by the Deepwater Horizon Oil Spill Using Bayesian Inference." Environmental Research Letters 7.4 (2012): 045302. Print.

Testing and Implementation of Treatment Methods for Marshes Heavily Oiled During the Deepwater Horizon Spill. Gulf Oil Spill SETAC Focused Meeting, 26-28 April 2011. 2011. Print.

PRELIMINARY STUDY: MARSH POINT 2010

Electrode Profiles

Throughout this section, site abbreviations are as follows:

 OS1-1 represents contaminated sediment

 OS1-2 represents contaminated grass

 OS2-1 represents non-contaminated sediment

 OS2-2 represents non-contaminated grass

October electrode data

Table A.1 H2S profiles

OS1-1

Sensor 1 :H2S Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/4/2010 -5000 55.87 1.20 -5000 54.99 14:20:59 -5000 54.13 1.31 -4000 47.66 Slope -5000 54.98 1.25 -3000 42.19 (µmol/l/mV) -0.06 -4000 48.05 1.70 -2000 37.53 -4000 48.38 1.68 -1000 34.27 Intercept (mV) -4000 46.54 1.80 0 27.77 -86.50 -3000 41.27 2.14 1000 27.52 -3000 42.20 2.08 2000 26.35 -3000 43.09 2.02 3000 25.18 -2000 37.13 2.41 4000 25.22 -2000 37.83 2.37 5000 25.41 -2000 37.63 2.38 6000 22.65 -1000 32.88 2.69 7000 23.65 -1000 34.10 2.61 8000 22.95 -1000 35.84 2.49 9000 21.74 0 30.73 2.83 10000 20.71 0 32.15 2.73 11000 19.42 0 20.43 3.49 12000 18.11 1000 27.19 3.05 13000 16.56 1000 27.68 3.02 14000 15.04 1000 27.67 3.02 15000 13.89 2000 27.30 3.05 16000 11.99 2000 26.60 3.09 17000 11.10 2000 25.15 3.19 18000 10.61 3000 25.06 3.19 19000 10.62 3000 24.74 3.21 20000 10.46 3000 25.73 3.15 21000 10.17 4000 24.78 3.21 22000 8.45 4000 25.51 3.16 23000 6.19 4000 25.39 3.17 24000 4.71 5000 26.34 3.11 25000 2.82 5000 25.23 3.18 26000 2.63 5000 24.65 3.22 27000 1.66 6000 22.86 3.33 28000 0.73 6000 22.59 3.35 29000 1.68 6000 22.51 3.36 30000 2.47 7000 24.53 3.23 31000 3.89 7000 23.79 3.27 32000 5.61 7000 22.64 3.35

Table A.1 (Continued)

8000 23.11 3.32 8000 23.11 3.32 8000 22.63 3.35 9000 21.97 3.39 9000 21.48 3.42 9000 21.77 3.40 10000 20.80 3.47 10000 21.28 3.44 10000 20.07 3.52 11000 19.98 3.52 11000 19.46 3.55 11000 18.84 3.60 12000 18.25 3.63 12000 18.26 3.63 12000 17.82 3.66 13000 16.16 3.77 13000 17.10 3.71 13000 16.40 3.75 14000 16.23 3.76 14000 14.83 3.85 14000 14.05 3.91 15000 14.33 3.89 15000 14.35 3.89 15000 12.99 3.97 16000 11.94 4.04 16000 12.58 4.00 16000 11.45 4.07 17000 10.81 4.11 17000 11.20 4.09 17000 11.28 4.08 18000 10.19 4.16 18000 11.66 4.06 18000 9.99 4.17 19000 11.36 4.08 19000 10.14 4.16 19000 10.36 4.14 20000 10.67 4.12 20000 10.68 4.12 20000 10.02 4.17 21000 10.23 4.15 21000 10.03 4.17 21000 10.24 4.15 22000 8.51 4.26 22000 8.54 4.26 22000 8.29 4.28

Table A.1 (Continued)

23000 6.39 4.40 23000 6.29 4.41 23000 5.88 4.43 24000 4.68 4.51 24000 5.02 4.49 24000 4.44 4.53 25000 2.11 4.68 25000 2.94 4.62 25000 3.42 4.59 26000 1.99 4.69 26000 3.70 4.58 26000 2.19 4.67 27000 1.63 4.71 27000 1.24 4.73 27000 2.12 4.68 28000 0.18 4.80 28000 1.47 4.72 28000 0.53 4.78 29000 1.57 4.71 29000 1.86 4.69 29000 1.62 4.71 30000 3.00 4.62 30000 3.83 4.57 30000 0.59 4.78 31000 4.09 4.55 31000 3.96 4.56 31000 3.63 4.58 32000 4.58 4.52 32000 5.83 4.44 32000 6.43 4.40 OS1-2

Sensor 1 :H2S Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/4/2010 -5000 78.92245215 2.03521729 -5000 78.28944891 15:40:40 -5000 78.17792724 2.08343506 -4000 76.40667044 Slope -5000 77.76796733 2.10998535 -3000 74.26576865 (µmol/l/mV) -0.064763144 -4000 77.23235042 2.14467359 -2000 70.99970188 -4000 76.22237132 2.21008301 -1000 65.91630322 Intercept (mV) -4000 75.76528957 2.23968506 0 59.04751244 -86.50102234 -3000 74.63593762 2.31282544 1000 54.52224486 -3000 74.14429864 2.34466553 2000 54.19500952 -3000 74.0170697 2.35290527 3000 54.21438224 -2000 72.22958041 2.4686687 4000 65.87389481 -2000 70.96828733 2.550354 5000 77.04071981 74

Table A.1 (Continued)

-2000 69.80123791 2.62593579 6000 144.6898665 -1000 67.45299885 2.77801514 7000 227.9698468 -1000 65.70949116 2.89093018 8000 380.9744247 -1000 64.58641966 2.96366382 9000 565.8569374 0 60.35173915 3.23791504 10000 780.1151642 0 58.84541256 3.33546948 11000 996.9368383 0 57.94538562 3.39375806 12000 1397.046741 1000 54.64999778 3.60717773 13000 1408.858064 1000 54.3672668 3.62548828 14000 1769.520222 1000 54.54946998 3.61368823 15000 2541.650627 2000 53.46095572 3.68418384 16000 3111.852016 2000 54.24946223 3.63311768 17000 3448.287192 2000 54.87461061 3.5926311 18000 3734.432381 3000 54.56203826 3.61287427 19000 3602.407538 3000 53.97458366 3.65091968 20000 2957.830153 3000 54.10652479 3.64237475 21000 3168.906577 4000 53.33529874 3.69232178 22000 3654.189167 4000 72.82645937 2.43001294 23000 3880.874461 4000 71.45992631 2.51851392 24000 4034.246592 5000 70.18449301 2.60111499 25000 3804.004699 5000 78.1355176 2.08618164 26000 3523.499993 5000 82.80214883 1.78395593 27000 3235.479277 6000 119.0294123 -0.5622355 28000 2724.59948 6000 149.4041445 -2.5293987 29000 2354.191114 6000 165.6360428 -3.5806274 30000 2138.220186 7000 200.6805474 -5.8502197 7000 231.3395779 -7.8357949 7000 251.8894151 -9.166667 8000 322.6019933 -13.746236 8000 390.4134425 -18.137918 8000 429.9078382 -20.6957 9000 502.2115733 -25.378317 9000 574.9582537 -30.089621 9000 620.4009851 -33.032635 10000 715.9954503 -39.223633 10000 791.9369907 -44.141846 10000 832.4130518 -46.763203 11000 925.872957 -52.81596 11000 1010.510006 -58.297321 11000 1054.427551 -61.14156 12000 1239.148245 -73.104652 12000 1429.837802 -85.454308 12000 1522.154178 -91.433006 13000 1458.82397 -87.331543 13000 1388.961146 -82.807007

Table A.1 (Continued)

13000 1378.789074 -82.148232 14000 1534.443551 -92.228905 14000 1811.807351 -110.19186 14000 1962.309763 -119.93887 15000 2311.427504 -142.54883 15000 2591.307611 -160.67474 15000 2722.216765 -169.15283 16000 2958.444858 -184.45171 16000 3145.744706 -196.58183 16000 3231.366483 -202.12697 17000 3356.591332 -210.23692 17000 3468.893489 -217.50996 17000 3519.376754 -220.77942 18000 3640.052697 -228.59477 18000 3759.470251 -236.32863 18000 3803.774195 -239.19789 19000 3708.305368 -233.01503 19000 3579.911106 -224.69981 19000 3519.006141 -220.75542 20000 3184.997189 -199.12395 20000 2906.582572 -181.09294 20000 2781.910699 -173.0188 21000 2927.983658 -182.47894 21000 3215.631091 -201.10789 21000 3363.104982 -210.65877 22000 3540.328769 -222.13634 22000 3672.572885 -230.70088 22000 3749.665847 -235.69366 23000 3852.641181 -242.36267 23000 3888.496181 -244.68475 23000 3901.48602 -245.52602 24000 3982.716279 -250.78674 24000 4053.584448 -255.37639 24000 4066.439048 -256.20889 25000 3888.7742 -244.70276 25000 3793.118536 -238.5078 25000 3730.121362 -234.4279 26000 3609.484766 -226.6151 26000 3509.317893 -220.12798 26000 3451.69732 -216.39629 27000 3339.594488 -209.13615 27000 3225.14169 -201.72383 27000 3141.701653 -196.31999 28000 2924.245247 -182.23683 28000 2696.425338 -167.4825

Table A.1 (Continued)

28000 2553.127855 -158.2021 29000 2448.101308 -151.40025 29000 2355.811555 -145.42328 29000 2258.66048 -139.13147 30000 2251.12405 -138.64339 30000 2127.400974 -130.63069 30000 2036.135533 -124.72005 31000 -119.15395 31000 -114.84396 31000 -110.80465 32000 -102.00491 32000 -102.02799 32000 -101.44125 OS2-1

Sensor 1 :H2S Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/5/2010 -5000 63.70367318 3.02083325 -5000 62.6764173 18:06:32 -5000 62.19577464 3.1184895 -4000 52.30437864 Slope -5000 62.12980407 3.12276196 -3000 47.41103803 (µmol/l/mV) -0.064763144 -4000 50.01320976 3.9074707 -2000 43.21823949 -4000 54.12851743 3.64095044 -1000 37.64634822 Intercept (mV) -4000 52.77140874 3.72884107 0 36.6567898 -86.50102234 -3000 44.96174964 4.23461914 1000 34.14990847 -3000 48.42049192 4.01062012 2000 33.23888643 -3000 48.85087252 3.98274732 3000 25.12764639 -2000 42.22553962 4.4118247 4000 12.10003127 -2000 42.69675791 4.38130713 5000 13.91998186 -2000 44.73242095 4.24947119 6000 16.99546905 -1000 36.67145156 4.77152491 7000 18.55677233 -1000 37.18979168 4.73795557 8000 23.27314471 -1000 39.07780141 4.61568213 9000 19.97984913 0 35.58764948 4.84171534 10000 19.91597205 0 37.02643355 4.74853516 11000 21.19245333 0 37.35628636 4.72717285 12000 18.05937443 1000 34.18969942 4.93225098 13000 14.52837622 1000 36.83794623 4.76074219 14000 8.105148098 1000 31.42207975 5.11149073 15000 5.29354806 2000 30.89117135 5.14587402 16000 3.901880908 2000 33.84099788 4.95483398 17000 4.533313423 2000 34.98449006 4.88077784 18000 2.71860023 3000 26.03447901 5.46040869 19000 2.918605399 3000 24.72449215 5.54524755 20000 2.125910694 3000 24.62396803 5.55175781 21000 3.035887215 4000 11.62462355 6.39363623 22000 1.889256031 77

Table A.1 (Continued)

4000 12.61418197 6.32954931 23000 2.655771124 4000 12.06128829 6.36535645 24000 2.8704356 5000 10.73873315 6.45100927 25000 3.525954242 5000 13.71683278 6.25813818 26000 2.192929225 5000 17.30437964 6.02579737 27000 1.945802227 6000 12.85293503 6.31408691 28000 10.0308602 6000 18.49184974 5.94889307 29000 92.94957374 6000 19.64162238 5.87443018 30000 278.7708456 7000 14.4959186 6.20768213 7000 19.18610891 5.90393066 7000 21.98828949 5.72245264 8000 20.49923968 5.81888819 8000 24.50459518 5.55948877 8000 24.81559926 5.53934717 9000 17.27296263 6.02783203 9000 20.05315057 5.84777832 9000 22.61343419 5.6819663 10000 18.17455785 5.96944189 10000 19.70130512 5.87056494 10000 21.87205319 5.72998047 11000 17.74732484 5.99711084 11000 21.53591993 5.75174952 11000 24.29411522 5.57312012 12000 15.11478284 6.16760254 12000 19.44056679 5.88745117 12000 19.62277365 5.87565088 13000 14.47392596 6.20910645 13000 15.68652525 6.1305747 13000 13.42467744 6.27705908 14000 7.713511701 6.64693213 14000 7.69466297 6.64815283 14000 8.907269624 6.56962061 15000 3.818112039 6.89921045 15000 5.671568211 6.7791748 15000 6.390963929 6.73258448 16000 1.374057362 7.05749512 16000 4.782533907 6.83675146 16000 5.549051455 6.78710938 17000 2.841114533 6.96248388 17000 5.332291039 6.80114746 17000 5.426534698 6.79504395 18000 1.612810419 7.04203272 18000 2.938502101 6.95617676 18000 3.60448817 6.91304541 19000 1.044204556 7.07885742

Table A.1 (Continued)

19000 3.230657444 6.93725586 19000 4.480954199 6.85628271 20000 1.55940077 7.0454917 20000 2.275652579 6.99910498 20000 2.542678733 6.98181152 21000 1.703910168 7.03613281 21000 3.686170916 6.90775537 21000 3.717580561 6.90572119 22000 -0.196667833 7.15922022 22000 1.860980479 7.02596045 22000 4.003455447 6.88720703 23000 1.235835783 7.06644678 23000 2.831690167 6.96309423 23000 3.899787423 6.8939209 24000 1.647363973 7.03979492 24000 2.303925676 6.99727392 24000 4.660017151 6.84468603 25000 2.272516032 6.99930811 25000 3.258930542 6.9354248 25000 5.046416152 6.81966162 26000 0.676654286 7.10266113 26000 2.750014783 6.96838379 26000 3.152118607 6.94234228 27000 0.657805554 7.10388184 27000 1.19813832 7.06888819 27000 3.981462806 6.88863134 28000 3.350030291 6.9295249 28000 8.282117565 6.61010742 28000 18.46043273 5.95092773 29000 64.05551495 2.99804688 29000 94.19777915 1.04593909 29000 120.5954271 -0.6636556 30000 229.4657047 -7.714437 30000 284.9438028 -11.307373 30000 321.9030293 -13.700969 OS2-2

Sensor 1 :H2S Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/5/2010 -5000 38.91933999 4.23736572 -5000 26.56242557 16:04:35 -5000 17.48047585 5.62581396 -4000 22.09946556 Slope -5000 23.28746088 5.24973536 -3000 17.50822864 (µmol/l/mV) -0.064763144 -4000 26.03937572 5.0715127 -2000 13.6086371 -4000 14.13640159 5.84238672 -1000 12.94369409 Intercept (mV) -4000 26.12261938 5.06612158 0 7.891186001 79

Table A.1 (Continued)

-86.50102234 -3000 14.14582596 5.84177637 1000 14.24739804 -3000 17.73022154 5.60963964 2000 21.58636038 -3000 20.64863843 5.42063379 3000 20.59680196 -2000 11.46930604 6.01511621 4000 20.47847463 -2000 15.32858388 5.76517725 5000 23.93197952 -2000 14.02802138 5.84940577 6000 24.45869849 -1000 0.873174863 6.70135498 7000 26.31477582 -1000 11.07348267 6.04075098 8000 21.43452255 -1000 26.88442474 5.01678467 9000 22.81362388 0 6.686440348 6.32486963 10000 21.53714261 0 4.239241762 6.48335791 11000 22.20365634 0 12.74787589 5.93231201 12000 21.33242526 1000 4.936644838 6.43819189 13000 19.53865673 1000 10.154607 6.10026026 14000 19.43394074 1000 27.65094229 4.96714258 15000 20.15123806 2000 16.64485119 5.67993164 16000 18.47579442 2000 11.03735348 6.04309082 17000 22.6214699 2000 37.07687646 4.35668945 18000 21.39787061 3000 16.3872494 5.69661474 19000 22.46910932 3000 15.54220038 5.75134277 20000 19.75384397 3000 29.86095609 4.82401514 21000 19.58420538 4000 27.58968391 4.97110987 22000 17.23753827 4000 15.8186509 5.73343897 23000 15.44586078 4000 18.02708907 5.59041357 24000 27.81115405 5000 24.4309457 5.17567968 25000 18.01138425 5000 24.3257094 5.18249512 26000 17.18204005 5000 23.03928345 5.26580811 27000 16.43699238 6000 28.12687276 4.93631983 28000 15.66733584 6000 23.78224009 5.2176919 29000 16.43542166 6000 21.46698262 5.36763525 30000 15.89613686 7000 35.89411854 4.43328857 31000 14.80762505 7000 22.67487709 5.28940821 32000 15.41339826 7000 20.37533181 5.43833399 8000 25.3969432 5.11311865 8000 20.47585593 5.43182373 8000 18.43076853 5.56427002 9000 22.33716819 5.3112793 9000 23.28274869 5.25004053 9000 22.82095476 5.27994776 10000 19.88368915 5.47017431 10000 20.48999248 5.4309082 10000 24.2377462 5.18819189 11000 27.60067655 4.97039795 11000 19.17686171 5.51595068 11000 19.83343078 5.4734292

Table A.1 (Continued)

12000 24.98698328 5.13966894 12000 19.37163685 5.50333643 12000 19.63865564 5.48604345 13000 19.69206529 5.48258448 13000 19.07476932 5.5225625 13000 19.8491356 5.47241211 14000 20.25438333 5.44616699 14000 19.28681755 5.50882959 14000 18.76062134 5.54290771 15000 17.78205556 5.60628271 15000 20.39574882 5.43701172 15000 22.27590982 5.31524658 16000 18.11034009 5.58502197 16000 18.50301955 5.55959082 16000 18.81402362 5.53944921 17000 26.29697014 5.05483007 17000 21.44656562 5.36895752 17000 20.12087394 5.45481348 18000 22.46125322 5.30324316 18000 21.09472017 5.39174414 18000 20.63763842 5.42134619 19000 22.45497277 5.3036499 19000 22.48010196 5.30202246 19000 22.47225323 5.30253077 20000 19.8208625 5.47424316 20000 20.08631302 5.45705175 20000 19.35435639 5.50445557 21000 19.52085106 5.49367285 21000 19.22555917 5.51279688 21000 20.00620591 5.46223974 22000 16.34483976 5.69936132 22000 17.59356824 5.61848974 22000 17.77420683 5.60679102 23000 18.43704899 5.56386328 23000 11.98921444 5.98144531 23000 15.91131893 5.7274375 24000 37.99103995 4.29748535 24000 24.50948453 5.17059326 24000 20.93293768 5.40222168 25000 18.77161398 5.5421958 25000 17.99567943 5.59244776 25000 17.26685934 5.63964844 26000 16.47835652 5.69071436 26000 18.4401929 5.56365967 26000 16.62757073 5.68105078

Table A.1 (Continued)

27000 16.37940067 5.69712305 27000 16.61029764 5.68216944 27000 16.32127884 5.7008872 28000 15.4039788 5.76029444 28000 16.03383568 5.71950293 28000 15.56419302 5.74991846 29000 16.04169177 5.71899414 29000 16.86161161 5.66589355 29000 16.40296159 5.69559717 30000 16.92758217 5.66162109 30000 15.68827805 5.74188232 30000 15.07255036 5.78175879 31000 14.35787419 5.82804346 31000 15.44795672 5.75744629 31000 14.61704425 5.81125879 32000 15.02071635 5.78511572 32000 15.21862803 5.77229834 32000 16.0008504 5.72163916

Table A.2 O2 profiles

OS1-1

Sensor 2: O2 Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/4/2010 -5000 34.39 21.16 -5000 34.25 14:21:00 -5000 34.24 21.07 -4000 30.77 Slope -5000 34.10 20.98 -3000 28.87 (µmol/l/mV) 0.62 -4000 30.82 18.95 -2000 27.32 -4000 30.74 18.91 -1000 20.20 Intercept (mV) -4000 30.76 18.92 0 8.87 -0.09 -3000 29.55 18.17 1000 3.88 -3000 28.74 17.67 2000 1.74 -3000 28.32 17.41 3000 1.55 -2000 27.70 17.02 4000 1.44 -2000 27.34 16.80 5000 1.36 -2000 26.92 16.55 6000 1.33 -1000 23.16 14.22 7000 1.27 -1000 19.75 12.12 8000 1.24 -1000 17.70 10.85 9000 1.23 0 11.62 7.09 10000 1.20 0 8.47 5.14 11000 1.17 0 6.52 3.94 12000 1.14 1000 4.64 2.78 13000 1.11 1000 3.80 2.26 14000 1.08 1000 3.22 1.90 15000 1.10 2000 1.81 1.03 16000 1.06 2000 1.77 1.01 17000 1.02 2000 1.64 0.93 18000 0.99 3000 1.57 0.88 19000 0.93 3000 1.57 0.89 20000 0.88 3000 1.49 0.84 21000 0.87 4000 1.45 0.81 22000 0.86 4000 1.44 0.80 23000 0.90 4000 1.42 0.79 24000 0.86 5000 1.40 0.78 25000 0.81 5000 1.34 0.75 26000 0.86 5000 1.32 0.73 27000 0.79 6000 1.35 0.75 28000 0.71 6000 1.31 0.72 29000 0.67 6000 1.33 0.74 30000 0.62 7000 1.31 0.72 31000 0.64 7000 1.32 0.73 32000 0.61 7000 1.19 0.65 8000 1.24 0.68 8000 1.26 0.69

Table A.2 (Continued)

8000 1.23 0.67 9000 1.23 0.68 9000 1.27 0.70 9000 1.19 0.65 10000 1.21 0.66 10000 1.18 0.65 10000 1.19 0.65 11000 1.19 0.65 11000 1.17 0.63 11000 1.15 0.62 12000 1.15 0.62 12000 1.15 0.62 12000 1.13 0.61 13000 1.11 0.60 13000 1.14 0.62 13000 1.09 0.59 14000 1.10 0.59 14000 1.09 0.59 14000 1.06 0.57 15000 1.15 0.62 15000 1.10 0.60 15000 1.04 0.56 16000 1.05 0.56 16000 1.05 0.56 16000 1.08 0.58 17000 1.04 0.56 17000 1.01 0.54 17000 1.00 0.53 18000 1.02 0.55 18000 0.98 0.52 18000 0.98 0.52 19000 0.91 0.47 19000 0.96 0.50 19000 0.93 0.49 20000 0.89 0.46 20000 0.91 0.48 20000 0.85 0.44 21000 0.90 0.47 21000 0.88 0.46 21000 0.82 0.42 22000 0.87 0.45 22000 0.86 0.44 22000 0.86 0.44 23000 0.93 0.49 23000 0.91 0.48

Table A.2 (Continued)

23000 0.87 0.45 24000 0.85 0.44 24000 0.87 0.45 24000 0.86 0.44 25000 0.84 0.43 25000 0.78 0.40 25000 0.80 0.41 26000 0.82 0.42 26000 0.89 0.46 26000 0.89 0.47 27000 0.86 0.45 27000 0.77 0.39 27000 0.75 0.38 28000 0.68 0.33 28000 0.76 0.38 28000 0.68 0.33 29000 0.67 0.33 29000 0.67 0.33 29000 0.67 0.33 30000 0.64 0.31 30000 0.57 0.27 30000 0.64 0.31 31000 0.62 0.30 31000 0.62 0.30 31000 0.68 0.34 32000 0.64 0.31 32000 0.59 0.28 32000 0.61 0.29 OS1-2

Sensor 2: O2 Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/4/2010 -5000 116.6364901 16.3694248 -5000 116.6484574 15:06:22 -5000 116.6341868 16.3680019 -4000 116.6762319 Slope -5000 116.6746953 16.3930264 -3000 116.1081241 (µmol/l/mV) 0.617756844 -4000 116.7023597 16.4101162 -2000 111.6254007 -4000 116.6707432 16.3905849 -1000 99.45550032 Intercept (mV) -4000 116.6555927 16.3812256 0 94.04909529 -0.085449219 -3000 116.4079319 16.2282314 1000 90.57140064 -3000 116.1171258 16.048584 2000 90.02129716 -3000 115.7993146 15.8522539 3000 89.88736656 -2000 112.235553 13.6507158 4000 89.82709779 -2000 111.59598 13.2556152 5000 89.78834574 -2000 111.044669 12.9150391 6000 89.78724794 -1000 99.80569574 5.97208643 7000 89.72555205 85

Table A.2 (Continued)

-1000 99.42004199 5.73384619 8000 89.67538297 -1000 99.14076324 5.56131983 9000 89.15634702 0 95.28026869 3.1764729 10000 81.39956955 0 93.86675222 2.30326343 11000 72.8650066 0 93.00026495 1.76798499 12000 61.15541078 1000 90.80753567 0.41341147 13000 54.45251287 1000 90.54604163 0.25187173 14000 40.137307 1000 90.36062461 0.1373291 15000 27.61776159 2000 90.07179559 -0.041097 16000 19.9148858 2000 89.99538928 -0.0882975 17000 14.74022318 2000 89.99670662 -0.0874837 18000 9.736377647 3000 89.91009085 -0.1409912 19000 5.447305736 3000 89.87814512 -0.1607259 20000 2.400056605 3000 89.87386371 -0.1633708 21000 1.331574465 4000 89.84060064 -0.1839193 22000 0.505816152 4000 89.81557097 -0.1993815 23000 1.508428725 4000 89.82512176 -0.1934814 24000 2.944560656 5000 89.81326561 -0.2008057 25000 5.987968888 5000 89.76518232 -0.2305094 26000 11.48373561 5000 89.78658927 -0.2172852 27000 18.1844352 6000 89.7790145 -0.2219645 28000 23.16478867 6000 89.7948227 -0.2121989 29000 30.4514909 6000 89.78790661 -0.2164714 30000 38.19619255 7000 89.74838611 -0.2408854 31000 46.7724715 7000 89.71084165 -0.2640788 32000 55.85922364 7000 89.71742839 -0.2600098 8000 89.69997351 -0.2707926 8000 89.66901577 -0.289917 8000 89.65715962 -0.2972412 9000 89.64662083 -0.3037516 9000 89.34165424 -0.4921468 9000 88.48076598 -1.0239664 10000 82.97094857 -4.4276938 10000 81.16090943 -5.5458579 10000 80.06685063 -6.2217202 11000 74.36865221 -9.7418213 11000 72.54972096 -10.865479 11000 71.67664662 -11.404826 12000 62.95644871 -16.791788 12000 60.78413622 -18.133749 12000 59.72564742 -18.787638 13000 56.03508989 -21.067505 13000 54.16576999 -22.22229 13000 53.15667873 -22.845663 14000 42.86751523 -29.201864

Table A.2 (Continued)

14000 39.55207521 -31.25 14000 37.99233055 -32.213543 15000 29.16641375 -37.665813 15000 27.11464497 -38.933308 15000 26.57222604 -39.268391 16000 20.93692929 -42.749634 16000 19.67886193 -43.526814 16000 19.12886618 -43.866577 17000 15.19887922 -46.294353 17000 14.60903568 -46.658733 17000 14.41275463 -46.779987 18000 10.25881608 -49.346111 18000 9.5540358 -49.781494 18000 9.396281059 -49.878948 19000 5.64479711 -52.196453 19000 5.353994118 -52.376099 19000 5.343125979 -52.382813 20000 2.588546772 -54.084473 20000 2.272382731 -54.279785 20000 2.339240311 -54.238483 21000 1.421703859 -54.805298 21000 1.296226255 -54.882813 21000 1.276793282 -54.894817 22000 0.71494755 -55.241901 22000 0.402402106 -55.434978 22000 0.400098801 -55.436401 23000 1.450356225 -54.787598 23000 1.529724514 -54.738567 23000 1.545205437 -54.729004 24000 2.390944247 -54.206543 24000 3.029861138 -53.811848 24000 3.412876583 -53.575237 25000 5.006874407 -52.590534 25000 6.232664624 -51.833294 25000 6.724367633 -51.529541 26000 9.999302216 -49.506428 26000 11.81922148 -48.38216 26000 12.63268315 -47.879639 27000 16.91637862 -45.233356 27000 18.53440986 -44.233807 27000 19.10251712 -43.882854 28000 22.26251496 -41.930744 28000 23.4438446 -41.20097 28000 23.78800645 -40.988361 29000 28.73531296 -37.932129

Table A.2 (Continued)

29000 30.86612892 -36.615803 29000 31.75303081 -36.067913 30000 35.96262533 -33.467407 30000 38.67735367 -31.790365 30000 39.94859864 -31.005045 31000 44.74309356 -28.043213 31000 47.22201724 -26.511841 31000 48.35230369 -25.813599 32000 53.84104421 -22.422892 32000 56.40032419 -20.841879 32000 57.33630252 -20.263672 OS2-1

Sensor 2: O2 Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/5/2010 -5000 55.94540921 34.2281075 -5000 56.19351154 18:06:33 -5000 56.16211743 34.3619804 -4000 54.66692293 Slope -5000 56.47300796 34.5540352 -3000 52.05362953 (µmol/l/mV) 0.617756844 -4000 54.86024407 33.5577393 -2000 50.5138664 -4000 54.63530447 33.4187813 -1000 49.09738563 Intercept (mV) -4000 54.50522026 33.3384209 0 48.44727332 -0.085449219 -3000 52.2024901 31.9158936 1000 49.19432099 -3000 52.00258118 31.7923985 2000 55.16005033 -3000 51.95581731 31.7635098 3000 45.34436408 -2000 50.61738748 30.9366856 4000 11.14518614 -2000 50.47412565 30.8481846 5000 5.190434031 -2000 50.45008607 30.833334 6000 3.951685797 -1000 49.1086922 30.0046787 7000 2.146586789 -1000 49.07444212 29.9835205 8000 0.896311677 -1000 49.10902256 30.0048828 9000 0.550068141 0 48.42498746 29.5823154 10000 0.501655521 0 48.43289156 29.5871983 11000 0.487603787 0 48.48394094 29.6187344 12000 0.46828265 1000 48.9130657 29.8838291 13000 0.452254891 1000 49.19991972 30.0610352 14000 0.465208833 1000 49.46997754 30.2278652 15000 0.377714824 2000 54.8157835 33.5302734 16000 0.375409465 2000 55.27652467 33.8148994 17000 0.692781075 2000 55.38784281 33.883667 18000 0.612642272 3000 48.17502026 29.4278965 19000 0.585965933 3000 45.11810919 27.5394688 20000 1.054174166 3000 42.7399628 26.0703526 21000 0.523940696 4000 12.31049223 7.27233887 22000 0.414600628 4000 11.04451846 6.49027491 23000 0.407135649 4000 10.08054773 5.89477539 24000 0.34829401 88

Table A.2 (Continued)

5000 5.32557216 2.95735669 25000 0.285610088 5000 5.187909195 2.87231445 26000 0.275400624 5000 5.057820737 2.79195142 27000 0.249822081 6000 4.169597385 2.24324536 28000 0.241478865 6000 3.883732526 2.06665039 29000 0.235989904 6000 3.801727478 2.01599121 30000 0.31536026 7000 2.356265004 1.12304688 7000 2.11584863 0.97452801 7000 1.967646735 0.88297528 8000 0.76029528 0.13712566 8000 0.917389288 0.23417155 8000 1.011250463 0.29215494 9000 0.539309781 0.00061035 9000 0.543591168 0.00325521 9000 0.567303473 0.01790365 10000 0.509340063 -0.0179036 10000 0.513621452 -0.0152588 10000 0.482005048 -0.03479 11000 0.490897162 -0.0292969 11000 0.462903473 -0.0465902 11000 0.509010728 -0.0181071 12000 0.483322396 -0.0339762 12000 0.440179182 -0.0606283 12000 0.481346371 -0.0351969 13000 0.44314322 -0.0587972 13000 0.462903473 -0.0465902 13000 0.45071798 -0.0541178 14000 0.447095271 -0.0563558 14000 0.477394321 -0.0376383 14000 0.471136909 -0.0415039 15000 0.425358987 -0.0697835 15000 0.363114191 -0.1082357 15000 0.344671293 -0.1196289 16000 0.374311672 -0.1013184 16000 0.365419558 -0.1068115 16000 0.386497165 -0.0937907 17000 0.709906624 0.10599772 17000 0.692781079 0.0954183 17000 0.675655523 0.08483887 18000 0.632512303 0.05818685 18000 0.599907886 0.03804525 18000 0.605506627 0.04150391 19000 0.576524922 0.02360026 19000 0.598261203 0.037028 19000 0.583111675 0.02766927

Table A.2 (Continued)

20000 0.037728719 -0.3092448 20000 2.647070118 1.30269372 20000 0.477723662 -0.0374349 21000 0.525148267 -0.008138 21000 0.496166563 -0.0260417 21000 0.550507257 0.00752767 22000 0.458292745 -0.0494385 22000 0.400658671 -0.0850423 22000 0.384850469 -0.0948079 23000 0.423053632 -0.0712077 23000 0.397365304 -0.0870768 23000 0.400988013 -0.0848389 24000 0.352904735 -0.1145426 24000 0.35850347 -0.111084 24000 0.333473824 -0.1265462 25000 0.300540054 -0.1468913 25000 0.284402523 -0.1568604 25000 0.271887688 -0.1645915 26000 0.275839738 -0.1621501 26000 0.276498421 -0.1617432 26000 0.273863713 -0.1633708 27000 0.236648587 -0.1863607 27000 0.240271284 -0.1841227 27000 0.272546371 -0.1641846 28000 0.246528713 -0.1802572 28000 0.256079486 -0.1743571 28000 0.221828397 -0.1955159 29000 0.229403145 -0.1908366 29000 0.224792435 -0.1936849 29000 0.253774131 -0.1757813 30000 0.299881395 -0.1472982 30000 0.329521774 -0.1289876 30000 0.31667761 -0.1369222 OS2-2

Sensor 2: O2 Average Depth Concentration Signal Depth Concentration Time (µm) (µmol/l) (mV) (µm) (µmol/l) 10/5/2010 -5000 28.0677931 17.2536221 -5000 28.31995554 16:49:43 -5000 28.49823624 17.5195313 -4000 28.45597092 Slope -5000 28.39383727 17.4550381 -3000 28.73788385 (µmol/l/mV) 0.617756844 -4000 27.9989595 17.2110996 -2000 28.81044823 -4000 28.57530123 17.5671387 -1000 29.0049766 Intercept (mV) -4000 28.79365202 17.7020264 0 29.11969722 -0.085449219 -3000 28.62239547 17.5962315 1000 29.23002529 -3000 28.85622718 17.7406826 2000 29.32542203 90

Table A.2 (Continued)

-3000 28.73502891 17.6658115 3000 27.56862648 -2000 28.56575147 17.5612392 4000 23.13299834 -2000 28.82428041 17.7209473 5000 21.65229726 -2000 29.04131282 17.8550205 6000 22.06199265 -1000 28.97149429 17.8118896 7000 23.96721033 -1000 28.89311093 17.7634678 8000 26.71432438 -1000 29.15032458 17.9223633 9000 29.43037058 0 29.23760006 17.9762783 10000 29.39403436 0 29.23562403 17.9750576 11000 29.61018888 0 28.88586756 17.7589931 12000 29.77870061 1000 29.17634327 17.9384365 13000 29.62478985 1000 29.21981583 17.965292 14000 29.45671861 1000 29.29391678 18.0110683 15000 28.97687381 2000 29.31993238 18.0271397 16000 28.68442105 2000 29.33343728 18.0354824 17000 28.61866366 2000 29.32289642 18.0289707 18000 28.3784675 3000 28.63359397 17.6031494 19000 27.8688722 3000 27.45094286 16.8725586 20000 26.95067913 3000 26.62134262 16.3600674 21000 25.79744866 4000 24.36472023 14.9660234 22000 24.37635717 4000 22.89225259 14.0563965 23000 23.57848242 4000 22.14202218 13.5929365 24000 27.04432163 5000 21.77843354 13.3683271 25000 27.92156724 5000 21.64900388 13.2883711 26000 15.49675834 5000 21.52945435 13.2145185 27000 6.884691593 6000 21.74319391 13.3465576 28000 14.37734029 6000 22.01160452 13.5123701 29000 22.05441788 6000 22.43117952 13.7715654 30000 26.26917015 7000 23.44817488 14.3998213 31000 25.67987516 7000 24.04229929 14.7668457 32000 23.88344899 7000 24.41115682 14.99471 8000 25.83685905 15.8754473 8000 26.79984254 16.4703369 8000 27.50627156 16.9067383 9000 29.42301606 18.0908203 9000 29.48097844 18.126627 9000 29.38711724 18.0686436 10000 29.56298349 18.1772861 10000 29.2540659 17.9864502 10000 29.36505368 18.0550137 11000 29.70130526 18.2627354 11000 29.57813405 18.1866455 11000 29.55112734 18.1699619 12000 29.79846086 18.3227539 12000 29.77738223 18.3097324

Table A.2 (Continued)

12000 29.76025874 18.2991543 13000 29.50897316 18.1439209 13000 29.70262364 18.2635498 13000 29.66277276 18.2389317 14000 29.57253634 18.1831875 14000 29.38514122 18.0674229 14000 29.41247829 18.0843105 15000 29.19280912 17.9486084 15000 28.95568609 17.802124 15000 28.78212623 17.6949062 16000 28.66685604 17.6236973 16000 28.71230462 17.6517735 16000 28.67410249 17.6281738 17000 28.76796369 17.6861572 17000 28.57595887 17.5675449 17000 28.51206842 17.5280762 18000 28.36880659 17.4395752 18000 28.38692118 17.4507656 18000 28.37967473 17.4462891 19000 27.9581237 17.185873 19000 27.89554854 17.1472168 19000 27.75294435 17.0591221 20000 27.25729238 16.7529297 20000 26.91544001 16.541748 20000 26.67930499 16.395874 21000 26.08649742 16.0296631 21000 25.7723094 15.8355713 21000 25.53353917 15.6880693 22000 24.865973 15.2756758 22000 24.27382307 14.9098711 22000 23.98927543 14.7340899 23000 23.62107709 14.5066328 23000 23.62634597 14.5098877 23000 23.48802421 14.4244385 24000 25.98440329 15.9665937 24000 27.16079751 16.6933193 24000 27.98776408 17.2041836 25000 28.53215904 17.5404873 25000 27.81486187 17.0973721 25000 27.41768079 16.8520107 26000 19.90647843 12.2119141 26000 14.78890184 9.0504961 26000 11.79489475 7.20092773 27000 7.691348714 4.66593409 27000 6.798844488 4.11458349

Table A.2 (Continued)

27000 6.163881577 3.72233081 28000 10.75418786 6.55802393 28000 14.98584672 9.17216015 28000 17.39198629 10.6585693 29000 20.73015214 12.7207441 29000 22.23423618 13.6499023 29000 23.19886533 14.2458086 30000 25.36491938 15.5839033 30000 26.36643536 16.2025967 30000 27.0761557 16.6410313 31000 26.65427431 16.3804111 31000 25.55988669 15.7043457 31000 24.82546448 15.2506514 32000 23.92472579 14.6942139 32000 23.95436617 14.7125244 32000 23.77125501 14.5994062

Concentration with Depth

Concentration (umol/L) 0 204 06 0 -5000 0 5000 10000 H2S 15000 O2 20000

Depth (um) Depth 25000 30000 35000 40000

Figure A.1 Contaminated sediment H2S & O2 profiles.

Concentration with Depth

Concentration (umol/L) 0 1000 2000 3000 4000 5000 0 501 0015 0 -5000 0 5000 10000 O2 15000 H2S 20000

Depth (um) Depth 25000 30000 35000 40000

Figure A.2 Contaminated grass H2S & O2 profiles.

Concentration with Depth

Concentration (umol/L) 0 2040 60 80 100 -5000 0 5000 10000 H2S 15000 O2 20000

Depth (um) Depth 25000 30000 35000 40000

Figure A.3 Non-contaminated sediment H2S & O2 profiles.

Concentration with Depth

Concentration (umol/L) 0 10 20 30 40 -5000 0 5000 10000 H2S 15000 O2 20000

Depth (um) Depth 25000 30000 35000 40000

Figure A.4 Non-contaminated grass H2S & O2 profiles.

Table A.3 Descriptive statistics for electrodes.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum H2S 148 423.7010 1030.67833 .73 4034.25 O2 150 25.0375 30.16201 .24 116.68 GROUP 150 2.4933 1.12773 1.00 4.00

Table A.4 Kruskal- Wallis test for electrodes.

Ranks

GROUP N Mean Rank H2S ConSed 38 53.74 ConGrass 36 129.64 NonSed 36 53.83 NonGrass 38 62.61 Total 148 O2 ConSed 38 48.66 ConGrass 38 110.24 NonSed 36 47.33 NonGrass 38 94.29 Total 150

Test Statisticsa,b

H2S O2 Chi-Square 79.767 61.037 df 3 3 Asymp. Sig. .000 .000 a. Kruskal Wallis Test b. Grouping Variable: GROUP

Table A.5 Mann-Whitney U test for electrodes comparing contaminated sediment and contaminated grass.

Ranks

GROUP N Mean Rank Sum of Ranks H2S ConSed 38 19.58 744.00 ConGrass 36 56.42 2031.00 Total 74 O2 ConSed 38 22.61 859.00 ConGrass 38 54.39 2067.00 Total 76

Test Statisticsa

H2S O2 Mann-Whitney U 3.000 118.000 Wilcoxon W 744.000 859.000 Z -7.365 -6.275 Asymp. Sig. (2-tailed) .000 .000 a. Grouping Variable: GROUP

Table A.6 Mann-Whitney U test for electrodes comparing contaminated sediment and non-contaminated sediment.

Ranks

GROUP N Mean Rank Sum of Ranks H2S ConSed 38 37.58 1428.00 NonSed 36 37.42 1347.00 Total 74 O2 ConSed 38 42.29 1607.00 NonSed 36 32.44 1168.00 Total 74

Test Statisticsa

H2S O2 Mann-Whitney U 681.000 502.000 Wilcoxon W 1347.000 1168.000 Z -.032 -1.968 Asymp. Sig. (2-tailed) .974 .049 a. Grouping Variable: GROUP

100

Table A.7 Mann-Whitney U test for electrodes comparing contaminated sediment and non-contaminated grass.

Ranks

GROUP N Mean Rank Sum of Ranks H2S ConSed 38 35.58 1352.00 NonGrass 38 41.42 1574.00 Total 76 O2 ConSed 38 22.76 865.00 NonGrass 38 54.24 2061.00 Total 76

Test Statisticsa

H2S O2 Mann-Whitney U 611.000 124.000 Wilcoxon W 1352.000 865.000 Z -1.153 -6.212 Asymp. Sig. (2-tailed) .249 .000 a. Grouping Variable: GROUP

101

Table A.8 Mann-Whitney U test for electrodes comparing contaminated grass and non- contaminated sediment.

Ranks

GROUP N Mean Rank Sum of Ranks H2S ConGrass 36 53.72 1934.00 NonSed 36 19.28 694.00 Total 72 O2 ConGrass 38 50.42 1916.00 NonSed 36 23.86 859.00 Total 74

Test Statisticsa

H2S O2 Mann-Whitney U 28.000 193.000 Wilcoxon W 694.000 859.000 Z -6.983 -5.310 Asymp. Sig. (2-tailed) .000 .000 a. Grouping Variable: GROUP

102

Table A.9 Mann-Whitney U test for electrodes comparing contaminated grass and non- contaminated grass.

Ranks

GROUP N Mean Rank Sum of Ranks H2S ConGrass 36 56.50 2034.00 NonGrass 38 19.50 741.00 Total 74 O2 ConGrass 38 44.42 1688.00 NonGrass 38 32.58 1238.00 Total 76

Test Statisticsa

H2S O2 Mann-Whitney U .000 497.000 Wilcoxon W 741.000 1238.000 Z -7.397 -2.337 Asymp. Sig. (2-tailed) .000 .019 a. Grouping Variable: GROUP

103

Table A.10 Mann-Whitney U test for electrodes comparing non-contaminated sediment and non-contaminated grass.

Ranks

GROUP N Mean Rank Sum of Ranks H2S NonSed 36 34.14 1229.00 NonGrass 38 40.68 1546.00 Total 74 O2 NonSed 36 28.03 1009.00 NonGrass 38 46.47 1766.00 Total 74

Test Statisticsa

H2S O2 Mann-Whitney U 563.000 343.000 Wilcoxon W 1229.000 1009.000 Z -1.309 -3.688 Asymp. Sig. (2-tailed) .191 .000 a. Grouping Variable: GROUP

104

Biolog data

Table A.11 Biolog ACWD

ACWD Site October ECO November ECO November AN OS 1-1 0.14 0.04 0.02 OS 1-2 0.18 0.15 0.05 OS 2-1 0.05 0.10 0.03 OS 2-2 0.45 0.08 0.03

Table A.12 Kruskal-Wallis test for AN microplates.

Ranks

BIOGROUP N Mean Rank ACWD ConSed_AN 5 5.60 ConGrass_AN 5 16.00 NonSed_AN 5 10.00 NonGrass_AN 5 10.40 Total 20

Test Statisticsa,b

ACWD Chi-Square 7.789 df 3 Asymp. Sig. .051 a. Kruskal Wallis Test b. Grouping Variable: BIOGROUP

105

Table A.13 Mann-Whitney U test for AN microplates comparing contaminated sediment vs contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConSed_AN 5 3.00 15.00 ConGrass_AN 5 8.00 40.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U .000 Wilcoxon W 15.000 Z -2.611 Asymp. Sig. (2-tailed) .009 Exact Sig. [2*(1-tailed a .008 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

106

Table A.14 Mann-Whitney U test for AN microplates comparing contaminated sediment vs non-contaminated sediment.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConSed_AN 5 4.20 21.00 NonSed_AN 5 6.80 34.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 6.000 Wilcoxon W 21.000 Z -1.358 Asymp. Sig. (2-tailed) .175 Exact Sig. [2*(1-tailed a .222 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

107

Table A.15 Mann-Whitney U test for AN microplates comparing contaminated sediment vs non-contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConSed_AN 5 4.40 22.00 NonGrass_AN 5 6.60 33.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 7.000 Wilcoxon W 22.000 Z -1.149 Asymp. Sig. (2-tailed) .251 Exact Sig. [2*(1-tailed a .310 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

108

Table A.16 Mann-Whitney U test for AN microplates comparing contaminated grass vs non-contaminated sediment.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConGrass_AN 5 7.00 35.00 NonSed_AN 5 4.00 20.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 5.000 Wilcoxon W 20.000 Z -1.567 Asymp. Sig. (2-tailed) .117 Exact Sig. [2*(1-tailed a .151 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

109

Table A.17 Mann-Whitney U test for AN microplates comparing contaminated grass vs non-contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConGrass_AN 5 7.00 35.00 NonGrass_AN 5 4.00 20.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 5.000 Wilcoxon W 20.000 Z -1.567 Asymp. Sig. (2-tailed) .117 Exact Sig. [2*(1-tailed a .151 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

110

Table A.18 Mann-Whitney U test for AN microplates comparing non-contaminated sediment vs non-contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD NonSed_AN 5 5.20 26.00 NonGrass_AN 5 5.80 29.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 11.000 Wilcoxon W 26.000 Z -.313 Asymp. Sig. (2-tailed) .754 Exact Sig. [2*(1-tailed a .841 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

111

Table A.19 Kruskal-Wallis test for ECO microplates comparing contaminated sediment vs contaminated grass.

Ranks

BIOGROUP N Mean Rank ACWD ConSed_ECO 5 6.80 ConGrass_ECO 5 15.60 NonSed_ECO 5 8.80 NonGrass_ECO 5 10.80 Total 20

Test Statisticsa,b

ACWD Chi-Square 6.097 df 3 Asymp. Sig. .107 a. Kruskal Wallis Test b. Grouping Variable: BIOGROUP

112

Table A.20 Mann-Whitney U test for ECO microplates comparing contaminated sediment vs contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConSed_ECO 5 3.20 16.00 ConGrass_ECO 5 7.80 39.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 1.000 Wilcoxon W 16.000 Z -2.402 Asymp. Sig. (2-tailed) .016 Exact Sig. [2*(1-tailed a .016 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

113

Table A.21 Mann-Whitney U test for ECO microplates comparing contaminated sediment vs non-contaminated sediment.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConSed_ECO 5 5.20 26.00 NonSed_ECO 5 5.80 29.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 11.000 Wilcoxon W 26.000 Z -.313 Asymp. Sig. (2-tailed) .754 Exact Sig. [2*(1-tailed a .841 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

114

Table A.22 Mann-Whitney U test for ECO microplates comparing contaminated sediment vs non-contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConSed_ECO 5 4.40 22.00 NonGrass_ECO 5 6.60 33.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 7.000 Wilcoxon W 22.000 Z -1.149 Asymp. Sig. (2-tailed) .251 Exact Sig. [2*(1-tailed a .310 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

115

Table A.23 Mann-Whitney U test for ECO microplates comparing contaminated grass vs non-contaminated sediment.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConGrass_ECO 5 7.00 35.00 NonSed_ECO 5 4.00 20.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 5.000 Wilcoxon W 20.000 Z -1.567 Asymp. Sig. (2-tailed) .117 Exact Sig. [2*(1-tailed a .151 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

116

Table A.24 Mann-Whitney U test for ECO microplates comparing contaminated grass vs non-contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD ConGrass_ECO 5 6.80 34.00 NonGrass_ECO 5 4.20 21.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 6.000 Wilcoxon W 21.000 Z -1.358 Asymp. Sig. (2-tailed) .175 Exact Sig. [2*(1-tailed a .222 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

117

Table A.25 Mann-Whitney U test for ECO microplates comparing non-contaminated sediment vs non-contaminated grass.

Ranks

BIOGROUP N Mean Rank Sum of Ranks ACWD NonSed_ECO 5 5.00 25.00 NonGrass_ECO 5 6.00 30.00 Total 10

Test Statisticsb

ACWD Mann-Whitney U 10.000 Wilcoxon W 25.000 Z -.522 Asymp. Sig. (2-tailed) .602 Exact Sig. [2*(1-tailed a .690 Sig.)] a. Not corrected for ties. b. Grouping Variable: BIOGROUP

118

Total petroleum hydrocarbons

Table A.26 TPH data

TPH Method Analysis Total hydrocarbons Site Depth Soil (g) TPH (g) (g/kgsed) Ttl/site (g/kg) Avg. Location (g/kg) OS1_1 2 5.643 0.125 22.150 31.944 26.766 4 5.140 0.011 2.101 6 5.769 0.000 0.052 8 5.471 0.042 7.640 10 5.217 0.000 0.000 OS1_2 2 5.042 0.000 0.000 21.588 4 4.970 0.107 21.588 6 5.040 0.000 0.000 8 5.005 0.000 0.000 10 5.629 0.000 0.000 OS2_1 2 5.485 0.003 0.620 1.269 0.635 4 5.458 0.000 0.000 6 5.121 0.000 0.059 8 5.689 0.001 0.211 10 5.795 0.002 0.380 OS2_2 2 3.047 0.000 0.000 0.000 4 5.597 0.000 0.000 6 5.038 0.000 0.000 8 5.673 0.000 0.000 10 5.601 0.000 0.000

119

SPATIAL STUDY 2011

120

Guide

Throughout this section, site abbreviations are as follows:

 SP represents Saltpan Island

 MP represents Marsh Point

 CI represents Cat Island

 SI represents Skiff Island

121

August electrode profiles

H2S Concentration with Depth

Concentration (umol/L) 0 2000 4000 6000 8000 10000 -5000 0 5000 10000 SP1 15000 SP2 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.1 Saltpan Island H2S electrode profiles. Aug. 2011.

122

H2S Concentration with Depth

Concentration (umol/L) 0 10000 20000 30000 40000 50000 -5000 0 5000 10000 MP1 15000 MP2 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.2 Marsh Point H2S electrode profiles. Aug. 2011.

123

H2S Concentration with Depth

Concentration (umol/L) 0 2000 4000 6000 -5000 0 5000 10000 CI1 15000 CI2 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.3 Cat Island H2S electrode profiles. Aug. 2011.

124

H2S Concentration with Depth

Concentration (umol/L) 0 10000 20000 30000 40000 -5000 0 5000 10000 SI1 15000 SI2 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.4 Skiff Island H2S electrode profiles. Aug. 2011.

125

O2 Concentration with Depth

Concentration (umol/L) 0 50 100 150 200 250 -5000 0 5000 10000 SP1 15000 SP2 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.5 Saltpan Island O2 electrode profile. Aug. 2011.

126

O2 Concentration with Depth

Concentration (umol/L) 050 100 150 -5000 0 5000 10000 MP1 15000 MP2 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.6 Marsh Point O2 electrode profile. Aug. 2011.

127

O2 Concentration with Depth

Concentration (umol/L) 0 200 400 600 800 1000 -5000 0 5000 10000 CI1 15000 CI2 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.7 Cat Island O2 electrode profile. Aug. 2011.

128

O2 Concentration with Depth

Concentration (umol/L) 0 50 100 150 200 -5000 0 5000 10000 SI1 15000 SI2 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.8 Skiff Island O2 electrode profile. Aug. 2011.

129

pH with Depth

pH 56 78 9 10 -5000 0 5000 10000 SP1 15000 SP2 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.9 Saltpan Island pH electrode profile. Aug. 2011.

130

pH with Depth

pH 56 7 8 9 10 -5000 0 5000 10000 MP1 15000 MP2 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.10 Marsh Point pH electrode profile. Aug. 2011.

131

pH with Depth

pH 5 6 7 8 910 -5000 0 5000 10000 CI1 15000 CI2 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.11 Cat Island pH electrode profile. Aug. 2011.

132

pH with Depth

pH 56 7 8 9 10 -5000 0 5000 10000 SI1 15000 SI2 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.12 Skiff Island pH electrode profile. Aug. 2011.

133

Eh with Depth

Eh (mv) -300 -100 100 300 500 -5000 0 5000 10000 SP1 15000 SP2 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.13 Saltpan Island Eh electrode profile. Aug. 2011.

134

Eh with Depth Eh (mv) -300 -100 100 300 -5000 0 5000

10000 MP1 15000 MP2 20000 MP3

Depth (um) Depth 25000 30000 35000 40000

Figure B.14 Marsh Point Eh electrode profile. Aug. 2011.

135

Eh with Depth

Eh (mv) -50 150 350 550 -5000 0 5000

10000 CI1 15000 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.15 Cat Island Eh electrode profile. Aug. 2011.

Due to a storm coming in, there was not enough time to get the Eh profile done for CI2.

136

Eh with Depth

Eh (mv) -300 -100 100 300 500 -5000 0 5000 10000 SI1 SI2 15000 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.16 Skiff Island Eh electrode profile. Aug. 2011.

137

September electrode profiles

H2S Concentration with Depth Concentration (umol/L) 0 500 1000 1500 -5000 0 5000 10000 SP1 15000 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.17 Saltpan Island H2S electrode profiles. Sept. 2011.

Due to equipment malfunction, the H2S profile for SP2 was not recorded.

138

H2S Concentration with Depth

Concentration (umol/L) 0 500 1000 1500 -5000 0 5000 10000 MP1 15000 MP2 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.18 Marsh Point H2S electrode profiles. Sept. 2011.

139

H2S Concentration with Depth

Concentration (umol/L) 0 1000 2000 3000 -5000 0 5000 10000 CI1 15000 CI2 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.19 Cat Island H2S electrode profiles. Sept. 2011.

140

H2S Concentration with Depth

Concentration (umol/L) 0 500 1000 1500 2000 -5000 0 5000 10000 SI1 15000 SI2 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.20 Skiff Island H2S electrode profiles. Sept. 2011.

141

O2 Concentration with Depth

Concentration (umol/L) 0 100 200 300 400 -5000 0 5000 10000 SP1 15000 SP2 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.21 Saltpan Island O2 electrode profile. Sept. 2011.

142

O2 Concentration with Depth

Concentration (umol/L) 0 50 100 150 200 250 -5000 0 5000 10000 MP1 15000 MP2 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.22 Marsh Point O2 electrode profile. Sept. 2011.

143

O2 Concentration with Depth

Concentration (umol/L) 0 500 1000 1500 -5000 0 5000 10000 CI1 15000 CI2 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.23 Cat Island O2 electrode profile. Sept. 2011.

144

O2 Concentration with Depth

Concentration (umol/L) 0 500 1000 1500 2000 -5000 0 5000 10000 SI1 15000 SI2 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.24 Skiff Island O2 electrode profile. Sept. 2011.

145

pH with Depth

pH 56 78 9 10 -5000 0 5000 10000 SP1 15000 SP2 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.25 Saltpan Island pH electrode profile. Sept. 2011.

146

pH with Depth

pH 56 7 8 9 10 -5000 0 5000 10000 MP1 15000 MP2 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.26 Marsh Point pH electrode profile. Sept. 2011.

147

pH with Depth

pH 5 6 7 8 910 -5000 0 5000 10000 CI1 15000 CI2 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.27 Cat Island pH electrode profile. Sept. 2011.

148

pH with Depth

pH 56 7 8 9 10 -5000 0 5000 10000 SI1 15000 SI2 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.28 Skiff Island pH electrode profile. Sept. 2011.

149

Eh with Depth

Eh (mv) -300 -200 -100 0 100 200 -5000 0 5000 10000 SP1 15000 SP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.29 Saltpan Island Eh electrode profile. Sept. 2011.

Due to equipment malfunction, the Eh profile for SP2 was not recorded.

150

Eh with Depth

Eh (mv) -300 -100 100 300 500 -5000 0 5000 10000 MP1 MP2 15000 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.30 Marsh Point Eh electrode profile. Sept. 2011.

151

Eh with Depth

Eh (mv) -300 -100 100 300 -5000 0 5000 10000 CI1 CI2 15000 CI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.31 Cat Island Eh electrode profile. Sept. 2011.

152

Eh with Depth

Eh (mv) -100 -50 0 50 100 -5000 0 5000 10000 SI1 SI2 15000 SI3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure B.32 Skiff Island Eh electrode profile. Sept. 2011.

153

Electrode statistical analysis

Table B.2 Descriptive statistics for electrodes for all locations.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum H2S 553 2067.5574 3969.41326 .00 19421.46 O2 580 50.7111 264.07125 .00 5927.62 PH 580 7.2273 .84265 -3.80 9.08 EH 553 36.6994 143.61452 -254.67 321.74 LOCATION 582 2.5086 1.11896 1.00 4.00

154

Table B.3 Kruskal-Wallis test for the four locations.

Ranks

LOCATION N Mean Rank H2S SP 134 278.11 MP 142 330.05 CI 130 282.74 SI 147 219.67 Total 553 O2 SP 144 268.33 MP 144 245.12 CI 146 343.67 SI 146 303.96 Total 580 PH SP 144 269.64 MP 144 217.17 CI 146 339.07 SI 146 334.83 Total 580 EH SP 134 307.49 MP 142 197.80 CI 130 269.76 SI 147 332.12 Total 553

Test Statisticsa,b

H2S O2 PH EH Chi-Square 34.863 36.994 52.286 57.532 df 3 3 3 3 Asymp. Sig. .000 .000 .000 .000 a. Kruskal Wallis Test b. Grouping Variable: LOCATION

155

Table B.4 Mann-Whitney U test comparing electrode data for Saltpan Island and Marsh Point.

Ranks

LOCATION N Mean Rank Sum of Ranks H2S SP 134 123.43 16539.00 MP 142 152.73 21687.00 Total 276 O2 SP 144 151.03 21748.00 MP 144 137.97 19868.00 Total 288 PH SP 144 160.51 23113.50 MP 144 128.49 18502.50 Total 288 EH SP 134 166.15 22264.00 MP 142 112.41 15962.00 Total 276

Test Statisticsa

H2S O2 PH EH Mann-Whitney U 7494.000 9428.000 8062.500 5809.000 Wilcoxon W 16539.000 19868.000 18502.500 15962.000 Z -3.050 -1.657 -3.262 -5.590 Asymp. Sig. (2-tailed) .002 .098 .001 .000 a. Grouping Variable: LOCATION

156

Table B.5 Mann-Whitney U test comparing electrode data for Saltpan Island and Cat Island.

Ranks

LOCATION N Mean Rank Sum of Ranks H2S SP 134 129.20 17313.00 CI 130 135.90 17667.00 Total 264 O2 SP 144 126.81 18261.00 CI 146 163.93 23934.00 Total 290 PH SP 144 128.10 18447.00 CI 146 162.66 23748.00 Total 290 EH SP 134 141.41 18949.00 CI 130 123.32 16031.00 Total 264

Test Statisticsa

H2S O2 PH EH Mann-Whitney U 8268.000 7821.000 8007.000 7516.000 Wilcoxon W 17313.000 18261.000 18447.000 16031.000 Z -.713 -4.140 -3.508 -1.925 Asymp. Sig. (2-tailed) .476 .000 .000 .054 a. Grouping Variable: LOCATION

157

Table B.6 Mann-Whitney U test comparing electrode data for Saltpan Island and Skiff Island.

Ranks

LOCATION N Mean Rank Sum of Ranks H2S SP 134 160.49 21505.00 SI 147 123.24 18116.00 Total 281 O2 SP 144 135.49 19510.00 SI 146 155.38 22685.00 Total 290 PH SP 144 126.03 18148.00 SI 146 164.71 24047.00 Total 290 EH SP 134 134.93 18080.00 SI 147 146.54 21541.00 Total 281

Test Statisticsa

H2S O2 PH EH Mann-Whitney U 7238.000 9070.000 7708.000 9035.000 Wilcoxon W 18116.000 19510.000 18148.000 18080.000 Z -3.843 -2.286 -3.927 -1.196 Asymp. Sig. (2-tailed) .000 .022 .000 .232 a. Grouping Variable: LOCATION

158

Table B.7 Mann-Whitney U test comparing electrode data for Marsh Point and Cat Island.

Ranks

LOCATION N Mean Rank Sum of Ranks H2S MP 142 149.80 21272.00 CI 130 121.97 15856.00 Total 272 O2 MP 144 121.30 17467.00 CI 146 169.37 24728.00 Total 290 PH MP 144 116.99 16846.00 CI 146 173.62 25349.00 Total 290 EH MP 142 114.11 16204.00 CI 130 160.95 20924.00 Total 272

Test Statisticsa

H2S O2 PH EH Mann-Whitney U 7341.000 7027.000 6406.000 6051.000 Wilcoxon W 15856.000 17467.000 16846.000 16204.000 Z -2.920 -5.553 -5.750 -4.906 Asymp. Sig. (2-tailed) .003 .000 .000 .000 a. Grouping Variable: LOCATION

159

Table B.8 Mann-Whitney U test comparing electrode data for Marsh Point and Skiff Island.

Ranks

LOCATION N Mean Rank Sum of Ranks H2S MP 142 170.52 24214.00 SI 147 120.35 17691.00 Total 289 O2 MP 144 130.85 18842.00 SI 146 159.95 23353.00 Total 290 PH MP 144 116.69 16804.00 SI 146 173.91 25391.00 Total 290 EH MP 142 114.27 16227.00 SI 147 174.68 25678.00 Total 289

Test Statisticsa

H2S O2 PH EH Mann-Whitney U 6813.000 8402.000 6364.000 6074.000 Wilcoxon W 17691.000 18842.000 16804.000 16227.000 Z -5.119 -3.496 -5.809 -6.143 Asymp. Sig. (2-tailed) .000 .000 .000 .000 a. Grouping Variable: LOCATION

160

Table B.9 Mann-Whitney U test comparing electrode data for Cat Island and Skiff Island.

Ranks

LOCATION N Mean Rank Sum of Ranks H2S CI 130 155.87 20263.00 SI 147 124.08 18240.00 Total 277 O2 CI 146 157.37 22976.50 SI 146 135.63 19801.50 Total 292 PH CI 146 149.79 21869.00 SI 146 143.21 20909.00 Total 292 EH CI 130 116.49 15144.00 SI 147 158.90 23359.00 Total 277

Test Statisticsa

H2S O2 PH EH Mann-Whitney U 7362.000 9070.500 10178.000 6629.000 Wilcoxon W 18240.000 19801.500 20909.000 15144.000 Z -3.307 -2.359 -.665 -4.398 Asymp. Sig. (2-tailed) .001 .018 .506 .000 a. Grouping Variable: LOCATION

161

Biolog statistical analysis

ECO microplates

Table B.10 Biolog ECO microplate data for the four locations.

August Sampling ACWD September Sampling ACWD Site Depth Aerobic ECO Anaerobic ECO Aerobic ECO Anaerobic ECO SP1 0‐2cm 1.016 0.914 0.606 0.946 SP1 2‐4cm 0.849 0.970 0.503 0.980 SP1 4‐6cm 0.512 0.956 0.411 0.824 SP2 0‐2cm 0.890 0.921 0.879 0.973 SP2 2‐4cm 1.035 0.891 0.694 0.869 SP2 4‐6cm 0.896 0.889 0.270 0.623 SP3 0‐2cm 1.060 0.371 1.036 1.082 SP3 2‐4cm 0.856 0.440 0.480 0.634 SP3 4‐6cm 0.823 0.348 0.175 0.356 MP1 0‐2cm No Data No Data 0.736 0.732 MP1 2‐4cm No Data No Data 0.589 0.621 MP1 4‐6cm No Data No Data 0.513 0.445 MP2 0‐2cm 1.061 0.705 0.896 0.752 MP2 2‐4cm 1.101 1.115 0.595 0.652 MP2 4‐6cm 0.724 0.875 0.699 0.621 MP3 0‐2cm 0.961 1.052 0.941 0.880 MP3 2‐4cm 1.035 1.174 0.404 0.471 MP3 4‐6cm 1.079 1.026 0.797 0.802 CI1 0‐2cm 0.639 0.209 0.766 0.779 CI1 2‐4cm 0.376 0.387 0.220 0.203 CI1 4‐6cm 0.434 0.459 0.644 0.719 CI2 0‐2cm 0.724 0.781 0.231 0.119 CI2 2‐4cm 0.205 0.360 0.127 0.175 CI2 4‐6cm 0.310 0.238 0.086 0.140 CI3 0‐2cm 0.661 0.558 0.137 0.176 CI3 2‐4cm 0.939 0.884 0.013 0.061 CI3 4‐6cm 0.712 0.685 0.348 0.442 SI1 0‐2cm 1.032 0.983 0.779 0.240 SI1 2‐4cm 0.846 0.890 0.905 0.394 SI1 4‐6cm 0.679 0.768 0.822 1.064 SI2 0‐2cm 1.236 1.272 0.944 1.043 SI2 2‐4cm 0.869 0.883 0.736 0.777 SI2 4‐6cm 0.784 0.710 0.476 0.622 SI3 0‐2cm 1.037 0.885 1.116 0.788 SI3 2‐4cm 0.646 0.587 0.805 0.629 SI3 4‐6cm 0.647 0.658 0.935 0.751 162

Table B.11 Descriptive statistics for ECO microplates grouped by depth.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum ECO 69 .6955 .29366 .01 1.24 ANECO 69 .6844 .29173 .06 1.27 DEPTH 72 2.0000 .82223 1.00 3.00

Table B.12 Kruskal-Wallis test for ECO microlates grouped by depth.

Ranks

DEPTH N Mean Rank ECO 0-2 23 45.83 2-4 23 31.70 4-6 23 27.48 Total 69 ANECO 0-2 23 40.35 2-4 23 32.87 4-6 23 31.78 Total 69

Test Statisticsa,b

ECO ANECO Chi-Square 10.554 2.485 df 2 2 Asymp. Sig. .005 .289 a. Kruskal Wallis Test b. Grouping Variable: DEPTH

163

Table B.13 Mann-Whitney U test for ECO microplates comparing 0-2cm and 2-4cm depths.

Ranks

DEPTH N Mean Rank Sum of Ranks ECO 0-2 23 28.30 651.00 2-4 23 18.70 430.00 Total 46 ANECO 0-2 23 25.83 594.00 2-4 23 21.17 487.00 Total 46

Test Statisticsa

ECO ANECO Mann-Whitney U 154.000 211.000 Wilcoxon W 430.000 487.000 Z -2.428 -1.175 Asymp. Sig. (2-tailed) .015 .240 a. Grouping Variable: DEPTH

164

Table B.14 Mann-Whitney U test for ECO microplates comparing 0-2cm and 4-6cm depths.

Ranks

DEPTH N Mean Rank Sum of Ranks ECO 0-2 23 29.52 679.00 4-6 23 17.48 402.00 Total 46 ANECO 0-2 23 26.52 610.00 4-6 23 20.48 471.00 Total 46

Test Statisticsa

ECO ANECO Mann-Whitney U 126.000 195.000 Wilcoxon W 402.000 471.000 Z -3.043 -1.527 Asymp. Sig. (2-tailed) .002 .127 a. Grouping Variable: DEPTH

165

Table B.15 Mann-Whitney U test for ECO microplates comparing 2-4cm and 4-6cm depths.

Ranks

DEPTH N Mean Rank Sum of Ranks ECO 2-4 23 25.00 575.00 4-6 23 22.00 506.00 Total 46 ANECO 2-4 23 23.70 545.00 4-6 23 23.30 536.00 Total 46

Test Statisticsa

ECO ANECO Mann-Whitney U 230.000 260.000 Wilcoxon W 506.000 536.000 Z -.758 -.099 Asymp. Sig. (2-tailed) .448 .921 a. Grouping Variable: DEPTH

166

AN microplates

Table B.16 Biolog AN microplate data for the four locations.

Anaerobic AN Microplates Site Depth ACWD: August ACWD: September SP1 0‐2cm 0.569 0.550 SP1 2‐4cm 0.434 0.471 SP1 4‐6cm 0.538 0.496 SP1 0‐2cm 0.750 0.483 SP1 2‐4cm 0.590 0.303 SP1 4‐6cm 0.390 0.307 SP2 0‐2cm 0.688 0.696 SP2 2‐4cm 0.756 0.614 SP2 4‐6cm 0.542 0.327 SP2 0‐2cm 0.648 0.735 SP2 2‐4cm 0.668 0.524 SP2 4‐6cm 0.612 0.544 SP3 0‐2cm 0.509 0.753 SP3 2‐4cm 0.464 0.410 SP3 4‐6cm 0.450 0.111 SP3 0‐2cm 0.151 0.671 SP3 2‐4cm 0.469 0.349 SP3 4‐6cm 0.006 0.190 MP1 0‐2cm No Data 0.397 MP1 2‐4cm No Data 0.582 MP1 4‐6cm No Data 0.383 MP1 0‐2cm No Data 0.517 MP1 2‐4cm No Data 0.502 MP1 4‐6cm No Data 0.446 MP2 0‐2cm 0.755 0.525 MP2 2‐4cm 0.527 0.317 MP2 4‐6cm 0.368 0.488 MP2 0‐2cm No Data 0.666 MP2 2‐4cm No Data 0.250 MP2 4‐6cm No Data 0.533 MP3 0‐2cm 0.669 No Data MP3 2‐4cm 0.717 0.092 MP3 4‐6cm 0.687 0.436 MP3 0‐2cm No Data 0.603 MP3 2‐4cm No Data 0.067 MP3 4‐6cm No Data 0.559 CI1 0‐2cm 0.307 0.536 CI1 2‐4cm 0.352 0.188 167

Table B.16 (Continued)

168

Table B.17 Descriptive statistics for AN microplates.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum ANAN 131 .4708 .21396 .01 .91 GROUP_L 144 2.5000 1.12194 1.00 4.00

Table B.18 Kruskal-Wallis test for AN microplates comparing four locations.

Ranks

GROUP_L N Mean Rank ANAN Saltpan 36 69.94 MarshPoint 23 66.93 Cat 36 35.06 Skiff 36 92.40 Total 131

Test Statisticsa,b

ANAN Chi-Square 41.741 df 3 Asymp. Sig. .000 a. Kruskal Wallis Test b. Grouping Variable: GROUP_L

169

Table B.19 Mann-Whitney U test comparing Saltpan Island and Marsh Point AN microplates.

Ranks

GROUP_L N Mean Rank Sum of Ranks ANAN Saltpan 36 30.58 1101.00 MarshPoint 23 29.09 669.00 Total 59

Test Statisticsa

ANAN Mann-Whitney U 393.000 Wilcoxon W 669.000 Z -.326 Asymp. Sig. (2-tailed) .744 a. Grouping Variable: GROUP_L

Table B.20 Mann-Whitney U test comparing Saltpan Island and Cat Island AN microplates.

Ranks

GROUP_L N Mean Rank Sum of Ranks ANAN Saltpan 36 46.75 1683.00 Cat 36 26.25 945.00 Total 72

Test Statisticsa

ANAN Mann-Whitney U 279.000 Wilcoxon W 945.000 Z -4.156 Asymp. Sig. (2-tailed) .000 a. Grouping Variable: GROUP_L

170

Table B.21 Mann-Whitney U test comparing Saltpan Island and Skiff Island AN microplates.

Ranks

GROUP_L N Mean Rank Sum of Ranks ANAN Saltpan 36 29.61 1066.00 Skiff 36 43.39 1562.00 Total 72

Test Statisticsa

ANAN Mann-Whitney U 400.000 Wilcoxon W 1066.000 Z -2.793 Asymp. Sig. (2-tailed) .005 a. Grouping Variable: GROUP_L

Table B.22 Mann-Whitney U test comparing Marsh Point and Cat Island AN microplates.

Ranks

GROUP_L N Mean Rank Sum of Ranks ANAN MarshPoint 23 39.74 914.00 Cat 36 23.78 856.00 Total 59

Test Statisticsa

ANAN Mann-Whitney U 190.000 Wilcoxon W 856.000 Z -3.481 Asymp. Sig. (2-tailed) .000 a. Grouping Variable: GROUP_L

171

Table B.23 Mann-Whitney U test comparing Marsh Point and Skiff Island AN microplates.

Ranks

GROUP_L N Mean Rank Sum of Ranks ANAN MarshPoint 23 22.11 508.50 Skiff 36 35.04 1261.50 Total 59

Test Statisticsa

ANAN Mann-Whitney U 232.500 Wilcoxon W 508.500 Z -2.821 Asymp. Sig. (2-tailed) .005 a. Grouping Variable: GROUP_L

Table B.24 Mann-Whitney U test comparing Cat Island and Skiff Island AN microplates.

Ranks

GROUP_L N Mean Rank Sum of Ranks ANAN Cat 36 22.03 793.00 Skiff 36 50.97 1835.00 Total 72

Test Statisticsa

ANAN Mann-Whitney U 127.000 Wilcoxon W 793.000 Z -5.868 Asymp. Sig. (2-tailed) .000 a. Grouping Variable: GROUP_L

172

Table B.25 Descriptive statistics for AN microplates grouped by depth.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum ANANAN 131 .4708 .21396 .01 .91 GROUP_D 144 2.0000 .81935 1.00 3.00

Table B.26 Kruskal-Wallis test for AN microlates grouped by depth.

Ranks

GROUP_D N Mean Rank ANANAN 0-2 43 80.34 2-4 44 59.84 4-6 44 58.15 Total 131

Test Statisticsa,b

ANANAN Chi-Square 9.175 df 2 Asymp. Sig. .010 a. Kruskal Wallis Test b. Grouping Variable: GROUP_D

173

Table B.27 Mann-Whitney U test for AN microplates comparing 0-2cm and 2-4cm depths.

Ranks

GROUP_D N Mean Rank Sum of Ranks ANANAN 0-2 43 50.86 2187.00 2-4 44 37.30 1641.00 Total 87

Test Statisticsa

ANANAN Mann-Whitney U 651.000 Wilcoxon W 1641.000 Z -2.504 Asymp. Sig. (2-tailed) .012 a. Grouping Variable: GROUP_D

Table B.28 Mann-Whitney U test for AN microplates comparing 0-2cm and 4-6cm depths.

Ranks

GROUP_D N Mean Rank Sum of Ranks ANANAN 0-2 43 51.48 2213.50 4-6 44 36.69 1614.50 Total 87

Test Statisticsa

ANANAN Mann-Whitney U 624.500 Wilcoxon W 1614.500 Z -2.729 Asymp. Sig. (2-tailed) .006 a. Grouping Variable: GROUP_D

174

Table B.29 Mann-Whitney U test for AN microplates comparing 2-4cm and 4-6cm depths.

Ranks

GROUP_D N Mean Rank Sum of Ranks ANANAN 2-4 44 45.05 1982.00 4-6 44 43.95 1934.00 Total 88

Test Statisticsa

ANANAN Mann-Whitney U 944.000 Wilcoxon W 1934.000 Z -.200 Asymp. Sig. (2-tailed) .841 a. Grouping Variable: GROUP_D

175

Table 4.1 Total petroleum hydrocarbons

TPH Method Analysis Total hydrocarbons

Site Depth (cm) Soil (g) TPH (g) (g/kgsed) Ttl/site (g/kg) Avg. Location (g/kg) SP1 2 5.0654 0.0039 0.769929324 1.60045614 1.200559152 4 5.033 0.002 0.397 6 5.048 0.000 0.000 8 5.395 0.000 0.000 10 5.079 0.002 0.433 SP2 2 10.112 0.001 0.148 1.717 4 10.485 0.002 0.191 6 10.238 0.009 0.840 8 10.004 0.002 0.250 10 10.426 0.003 0.288 SP3 2 10.270 0.002 0.185 0.907 4 10.464 0.002 0.153 6 10.303 0.001 0.107 8 10.624 0.002 0.216 10 10.563 0.003 0.246 SP4 2 10.527 0.003 0.247 1.245 4 10.302 0.001 0.058 6 10.292 0.004 0.340 8 10.591 0.004 0.340 10 10.403 0.003 0.260 SP5 2 10.517 0.002 0.181 0.534 4 10.537 0.000 0.028 6 10.100 0.000 0.000 8 10.071 0.001 0.129 10 10.241 0.002 0.195 MP1a 2 10.389 0.001 0.116 0.818 0.693 4 10.129 0.005 0.474 6 10.380 0.005 0.472 8 10.302 0.001 0.058 10 10.446 0.005 0.450 MP1b 2 10.223 0.000 0.020 4 10.214 0.000 0.000 6 10.183 0.000 0.000 8 10.017 0.000 0.020 10 10.881 0.000 0.028 MP1c 2 10.641 0.000 0.000 4 10.448 0.000 0.000 6 10.111 0.000 0.000 8 10.540 0.000 0.000 10 10.574 0.000 0.000 MP2a 2 10.773 0.001 0.111 0.707 4 10.571 0.000 0.000 6 10.525 0.002 0.228

176

Table 4.1 (Continued)

8 1.018 0.000 0.000 10 10.093 0.007 0.684 MP2b 2 10.128 0.000 0.000 4 10.464 0.000 0.000 6 10.320 0.001 0.136 8 10.342 0.000 0.000 10 10.782 0.006 0.529 MP2c 2 10.561 0.002 0.161 4 10.720 0.001 0.084 6 10.015 0.000 0.000 8 10.108 0.002 0.188 10 10.693 0.000 0.000 MP3a 2 10.482 0.000 0.000 0.548 4 10.282 0.004 0.360 6 10.183 0.000 0.000 8 10.621 0.000 0.000 10 10.348 0.002 0.174 MP3b 2 10.330 0.000 0.000 4 10.670 0.000 0.000 6 10.509 0.000 0.000 8 10.841 0.006 0.563 10 10.393 0.000 0.000 MP3c 2 10.308 0.000 0.000 4 10.228 0.000 0.000 6 10.643 0.000 0.000 8 10.573 0.000 0.000 10 10.428 0.000 0.000 CI-1a 2 10.039 0.000 0.000 0.822 2.183 4 10.036 0.002 0.219 6 10.291 0.001 0.068 8 10.065 0.001 0.119 10 10.322 0.001 0.116 CI-1b 2 10.403 0.003 0.260 4 10.061 0.002 0.199 6 10.300 0.001 0.136 8 10.571 0.002 0.227 10 10.565 0.000 0.000 CI-1c 2 10.071 0.000 0.000 4 10.163 0.000 0.000 6 10.076 0.002 0.208 8 10.217 0.001 0.078 10 10.194 0.008 0.834 CI-2a 2 10.731 0.010 0.941 1.881 4 10.130 0.000 0.020 6 10.545 0.029 2.788

177

Table 4.1 (Continued)

8 10.146 0.004 0.375 10 10.374 0.000 0.000 CI-2b 2 10.049 0.000 0.000 4 10.691 0.000 0.000 6 10.264 0.002 0.205 8 10.449 0.000 0.000 10 10.542 0.000 0.047 CI-2c 2 10.362 0.011 1.110 4 10.071 0.002 0.159 6 10.380 0.000 0.000 8 10.699 0.000 0.000 10 10.680 0.000 0.000 CI-3a 2 10.286 0.001 0.087 3.448 4 10.323 0.002 0.184 6 10.423 0.003 0.326 8 10.514 0.000 0.000 10 10.779 0.003 0.260 CI-3b 2 10.203 0.001 0.118 4 10.284 0.003 0.282 6 10.094 0.003 0.287 8 10.241 0.000 0.020 10 10.780 0.002 0.148 CI-3c 2 10.343 0.037 3.539 4 10.149 0.049 4.799 6 10.196 0.003 0.294 8 10.004 0.000 0.000 10 10.168 0.000 0.000 CI 4a 2 10.825 0.001 0.074 3.700 4 10.298 0.000 0.049 6 10.578 0.000 0.000 8 10.193 0.000 0.000 10 10.595 0.007 0.689 CI 4b 2 10.028 0.008 0.748 4 10.535 0.012 1.120 6 10.634 0.001 0.075 8 10.585 0.002 0.227 10 10.609 0.014 1.357 CI 4c 2 10.383 0.035 3.361 4 10.326 0.015 1.414 6 10.550 0.007 0.654 8 10.558 0.012 1.137 10 10.249 0.002 0.195 CI 5a 2 10.729 0.000 0.000 1.062 4 10.287 0.000 0.000 6 10.217 0.001 0.069

178

Table 4.1 (Continued)

8 10.167 0.001 0.118 10 10.135 0.000 0.010 CI 5b 2 10.331 0.001 0.136 4 10.532 0.003 0.275 6 10.567 0.002 0.189 8 10.669 0.001 0.056 10 10.357 0.007 0.686 CI 5c 2 10.296 0.008 0.826 4 10.387 0.001 0.067 6 10.578 0.005 0.435 8 10.028 0.003 0.319 10 10.365 0.000 0.000 SI-1 2 5.359 0.000 0.000 5.065 2.996 4 5.422 0.024 4.445 6 5.163 0.003 0.600 8 5.101 0.000 0.000 10 5.066 0.000 0.020 SI-2 2 5.033 0.000 0.000 0.922 4 5.206 0.005 0.922 6 5.022 0.000 0.000 8 5.125 0.000 0.000 10 5.178 0.000 0.000 SI-3 2 5.010 0.000 0.000 0.000 4 5.143 0.000 0.000 6 5.127 0.000 0.000 8 5.243 0.000 0.000 10 5.080 0.000 0.000 SI-4 2 5.152 0.000 0.000 7.305 4 5.417 0.004 0.757 6 5.085 0.002 0.295 8 5.188 0.003 0.540 10 5.199 0.030 5.713 SI5 2 5.201 0.002 0.365 1.688 4 5.103 0.001 0.176 6 5.009 0.000 0.000 8 5.105 0.001 0.294 10 5.160 0.004 0.853

179

TEMPORAL STUDY: MARSH POINT 2010, 2011, & 2012

180

H2S Concentration with Depth

Concentration (umol/L) 0 100 200 300 400 500 -5000 0 5000 10000 MP1 15000 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure C.1 H2S electrode profile for Marsh Point in 2012.

181

O2 Concentration with Depth

Concentration (umol/L) 0 50 100 150 200 -5000 0 5000 10000 MP1 15000 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure C.2 O2 electrode profile for Marsh Point in 2012.

182

pH with Depth

pH 56 7 8 9 10 -5000 0 5000 10000 MP1 15000 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure C.3 pH electrode profile for Marsh Point in 2012.

183

Eh with Depth

Eh (mv) -400 -200 0 200 -5000 0 5000

10000 MP1 15000 MP3 20000

Depth (um) Depth 25000 30000 35000 40000

Figure C.4 Eh electrode profile for Marsh Point in 2012.

184

Table C.2 Descriptive statistics for electrode data for three years at Marsh Point.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum TEMPH2S 133 1898.7221 2166.41803 17.49 6784.30 TEMPO2 134 34.3060 42.49732 .00 147.73 TEMPPH 96 6.9962 .24236 6.63 7.78 TEMPEH 97 -100.8967 143.92944 -255.95 222.89 YEAR 135 2.0815 .80160 1.00 3.00

Table C.3 Kruskal-Wallis test for three years of electrode data at Marsh Point.

Ranks

YEAR N Mean Rank TEMPH2S 2010 36 68.75 2011 48 99.60 2012 49 33.78 Total 133 TEMPO2 2010 38 90.34 2011 48 35.04 2012 48 81.88 Total 134 TEMPPH 2011 48 47.98 2012 48 49.02 Total 96 TEMPEH 2011 48 63.94 2012 49 34.37 Total 97

Test Statisticsa,b

TEMPH2S TEMPO2 TEMPPH TEMPEH Chi-Square 70.851 54.244 .034 26.764 df 2 2 1 1 Asymp. Sig. .000 .000 .855 .000 a. Kruskal Wallis Test b. Grouping Variable: YEAR

185

Table C.4 Mann-Whitney U test comparing electrode data for 2010 and 2011.

Ranks

YEAR N Mean Rank Sum of Ranks TEMPH2S 2010 36 28.50 1026.00 2011 48 53.00 2544.00 Total 84 TEMPO2 2010 38 61.34 2331.00 2011 48 29.38 1410.00 Total 86 TEMPPH 2010 0a .00 .00 2011 48 24.50 1176.00 Total 48 TEMPEH 2010 0a .00 .00 2011 48 24.50 1176.00 Total 48 a. Mann-Whitney Test cannot be performed on empty groups.

Test Statisticsa

TEMPH2S TEMPO2 Mann-Whitney U 360.000 234.000 Wilcoxon W 1026.000 1410.000 Z -4.556 -6.105 Asymp. Sig. (2-tailed) .000 .000 a. Grouping Variable: YEAR

186

Table C.5 Mann-Whitney U test comparing electrode data for 2010 and 2012.

Ranks

YEAR N Mean Rank Sum of Ranks TEMPH2S 2010 36 58.75 2115.00 2012 49 31.43 1540.00 Total 85 TEMPO2 2010 38 48.50 1843.00 2012 48 39.54 1898.00 Total 86 TEMPPH 2010 0a .00 .00 2012 48 24.50 1176.00 Total 48 TEMPEH 2010 0a .00 .00 2012 49 25.00 1225.00 Total 49 a. Mann-Whitney Test cannot be performed on empty groups.

Test Statisticsa

TEMPH2S TEMPO2 Mann-Whitney U 315.000 722.000 Wilcoxon W 1540.000 1898.000 Z -5.043 -1.652 Asymp. Sig. (2-tailed) .000 .098 a. Grouping Variable: YEAR

187

Table C.6 Mann-Whitney U test comparing electrode data for 2011 and 2012.

Ranks

YEAR N Mean Rank Sum of Ranks TEMPH2S 2011 48 71.10 3413.00 2012 49 27.35 1340.00 Total 97 TEMPO2 2011 48 30.17 1448.00 2012 48 66.83 3208.00 Total 96 TEMPPH 2011 48 47.98 2303.00 2012 48 49.02 2353.00 Total 96 TEMPEH 2011 48 63.94 3069.00 2012 49 34.37 1684.00 Total 97

Test Statisticsa

TEMPH2S TEMPO2 TEMPPH TEMPEH Mann-Whitney U 115.000 272.000 1127.000 459.000 Wilcoxon W 1340.000 1448.000 2303.000 1684.000 Z -7.656 -6.610 -.183 -5.173 Asymp. Sig. (2-tailed) .000 .000 .855 .000 a. Grouping Variable: YEAR

188