Mercury Bioaccumulation and Effects in the Brown

MERCURY BIOACCUMULATION AND EFFECTS IN THE BROWN

WATERSNAKE (NERODIA TAXISPILOTA)

DAVID LEE HASKINS

(Under the Direction of Tracey D. Tuberville and Robert B. Bringolf)

ABSTRACT

Mercury (Hg) is a global pollutant of concern capable of contaminating aquatic and terrestrial environments. Unlike many other pollutants, Hg is well-known due to its propensity to bioaccumulate, biomagnify, and maternally transfer in vertebrates. The detrimental effects of Hg exposure in vertebrates include impaired growth, decreased survival and reproductive success, and altered behavior. Although these effects have been described in mammals and birds, little is known about the bioaccumulation and effects of

Hg in reptiles, especially snakes. All snakes are predators, typically occupy upper-level trophic positions in their respective food webs, and many are long-lived. These charateristics suggest snakes may be effective biomonitors for Hg contamination. In this dissertation, I explored how a common watersnake species, the brown watersnake

(Nerodia taxispilota), may be used to evaluate spatial and temporal trends in Hg contamination in a major riverine system in the southeastern United States. Next, I optimized an in vitro immune-based assay in N. taxispilota, providing a framework for the investigation of how mitogens, contmainants, and other stressors may impact their immune response. Using Hg data from previous studies, I then examined how in vitro exposure to Hg affected lymphocyte proliferation in N. taxispilota. Overall, my results demonstrate that N. taxispilota are effective biomonitors for Hg contamination in a riverine system, providing risk assessors with novel data that will aid in future investigations of snake ecotoxicology. In addition, my results suggest that N. taxispilota in my study system are at low risk of Hg immunotoxicity. However, Nerodia spp. in heavily contaminated systems in other areas of the United States could be subject to negative impacts due to Hg exposure.

INDEX WORDS: Squamate, Bioindicator, Pollution, Immunology, Toxicology,

Snake

MERCURY BIOACCUMULATION AND EFFECTS IN THE BROWN

WATERSNAKE (NERODIA TAXISPILOTA)

DAVID LEE HASKINS

B.S., Maryville College, 2014

M.S., University of Georgia, 2016

A Dissertation Submitted to the Graduate Faculty of The University of Georgia in Partial

Fulfillment of the Requirements for the Degree

DOCTOR OF PHILOSOPHY

ATHENS, GEORGIA

2021

David Lee Haskins

MERCURY BIOACCUMULATION AND EFFECTS IN THE BROWN

WATERSNAKE (NERODIA TAXISPILOTA)

DAVID LEE HASKINS

Major Professors: Tracey D. Tuberville Robert B. Bringolf Committee: Robert M. Gogal, Jr. Travis C. Glenn Melissa A. Pilgrim

Electronic Version Approved:

Ron Walcott Vice Provost for Graduate Education and Dean of the Graduate School The University of Georgia May 2021

DEDICATION

This dissertation is dedicated to all the loved ones I have lost along the way.

ACKNOWLEDGEMENTS

I am incredibly grateful to Tracey Tuberville for serving as my major advisor

during my doctoral program. I am thankful for her support, wisdom, and patience, as I

know I stopped in her office countless times with so many random thoughts (especially early on in my master’s program). Tracey leads by example, is a phenomenal scientist

(her passion for herpetofauna is infectious) and is a fantastic person. Throughout my time as her student, her advice and support always encouraged me to be a better scientist. I am going to miss going to her and Kurt’s place for pizza nights. Thank you and Kurt for always supporting me in and outside of the lab.

I am extremely thankful for my co-advisor, Robert Bringolf, for his invaluable contributions to my time at the University of Georgia. As a student that was stationed at

the Savannah River Ecology Laboratory (SREL; Aiken, SC), it is often hard to stay

connected to campus. From the beginning, Robert made it easy to do this and always

made time for me. While Robert is a fantastic, well-accomplished scientist, what always

struck me is how humble and open he is with his students and colleagues. His

mentorship, kindness, and wisdom have helped me make great strides as a scientist and as

a person. His examples of kindness, work-life balance, and faith have been invaluable. I am proud to call him a mentor, colleague, and true friend.

I am indebted to the other members of my advisory committee, including Robert

‘Bob’ Gogal, Melissa Pilgrim, and Travis Glenn. I am extremely lucky that John Finger

recommended that I connect with Bob prior to the beginning of my PhD program. Bob is

exactly the kind of scientist that you want on your committee as a graduate student. He always is willing to working in new systems or with new species. His expertise (and patience) in the laboratory, inquisitive nature, and passion truly made it so much enjoyable to conduct our research. Bob taught me much (in and outside of the lab) that will serve me well as I move forward into a postdoctoral position. I thank him profusely for his willingness to work with a loud, young man catching wild snakes for his dissertation. I am thankful that my research with Tracey allowed me to work with

Melissa and for her agreeing to be on my committee. Melissa always has challenged me to remember to think about all of our work in a broad context. This one piece of advice has helped me tremendously. While Melissa is well-versed in snake physiology and was a valuable academic mentor, I also really appreciate her taking the time to chat with me about life outside work. Finally, I would like to thank Travis for sticking with me as a committee member (master’s and doctoral). I have learned from Travis in the classroom and in meetings. Travis is a brilliant but shows humility, and his willingness to help students understand topics is something I truly admire. I am very excited about our RNA- seq and microbiome side projects and working together in the coming years.

I would also like to take the opportunity to thank Mark Mills for all his help during my doctoral program. I am fortunate that Mark was so willing to share his expertise on brown watersnakes with me. The field sampling for this species is unique, and I thank Mark for coming to the lab multiple times to help us remember to just “take the bite.” I am also indebted to Sue Blas, who took the time to hear our watersnake research proposal and support our project. Thank you for helping with my numerous

requests for fish data and for sending pictures of all the snakes you see on the Savannah

River Site!

I am thankful to the entire SREL community and the folks there that made it a wonderful place to learn and grow as a scientist. First, I would like to thank Gene Rhodes for agreeing to help support me financially as a doctoral student during my time at SREL.

I also thank him for coordinating our basketball group while at the lab—this was a much- needed outlet for many of us and I enjoyed getting to know everyone. I would like to thank Larry Bryan for allowing me to work as a technician in his lab the summer before my doctoral program started. Larry always made me feel welcome at the lab and I thoroughly enjoyed working with him in the field and the lab. I also thank Angela Lindell for providing help with our lab’s mercury analyses. I want to thank the entire SREL maintenance crew for their help over the last few years, and I’d especially like to thank

Dennis Frasier for helping us make sure we always had a working boat.

Thanks to my friends and lab mates that I spent so much time with at SREL and on campus, especially Austin Coleman, Kyle Brown, Matthew Hale, Amelia Russell,

Alexis Korotasz, Pearson McGovern, Rebecca McKee, Becca Cozad, Carmen Candal,

Lonnie Helton, Wes Flynn, Ben Thesing, Tyler Carter, Heather Gaya, Chris Leaphart,

Sarah Chinn, Laura Kojima, Jackie Newbold, and Emma Browning. A very special shout out to Kyle Brown for spending so many hours with me in the field and snagging as many watersnakes as possible.

I would like to thank University of Georgia’s Interdisciplinary Toxicology

Program and the U.S. Department of Energy for supporting my research at SREL. In addition, I thank the University of Georgia’s Graduate School for supporting my research

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and travel during my program. (the Dissertation Completion Award, annual travel grants,

Interdisciplinary Research awards). I also thank Riverbanks Zoo and Garden and the

American Society of Herpetologists for their support to our numerous projects. Lastly,

thank you to the numerous conferences (e.g., TWS, SICB, SETAC, SEPARC, TSA) that

supported my travel as a graduate student to present my research at their meetings. This

project was partially funded by the Department of Energy under award number DE-

EM0004391 to the University of Georgia Research Foundation and by Savannah River

Nuclear Solutions – Area Completions Project.

A special thanks to the professors at Maryville College that prepared me for

graduate school. I thank Dr. Dave Unger for taking a chance on a wild, curious

undergraduate student. To Drs. Drew Crain, Jerilyn Swann, and Josh Ennen, thank you

for mentoring and supporting me during my time at MC.

I would like to thank my family and close friends for all their support throughout

my program. I especially would like to thank my parents for always pushing me to work

hard. To my father, thank you for leading by example, teaching me that things can always be improved, and the wisdom of “all things are finite.” I thank my mother for always fostering my inquisitive nature and supporting me even when I did not believe in myself.

To my sisters, thank you both for our phone calls and for always keeping me on my toes.

Thank you to my best friends, David Marrow and Nick Wade, for keeping me sane through long chats about the most random things and our time online.

Of course—none of this would be possible without the brown watersnakes

(Nerodia taxispilota). Although they always make it clear that they would rather be anywhere else than in my hand, I have to say thank you to such great study subjects. You

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all lived up to my favorite quote used by Mark Mills in his dissertation that I would also like to provide here:

“… whoever… had experiences with this species in its wild states knows they are vicious and belligerent… The natives were not anxious to help us in the captures of this species.” – (Wright and Bishop 1915).

Finally, I would like to thank my wife and best friend, LeeAnn, for supporting me throughout this entire process. You are an incredible woman. I am so thankful for our loving cats, long walks, and our family. Your love, knowledge, and patience all continue to make me a better person and scientist.

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS ...... v

LIST OF TABLES ...... xiv

LIST OF FIGURES ...... xvii

CHAPTER

1 INTRODUCTION ...... 1

Wildlife as Bioindicators ...... 1

Mercury ...... 2

Mercury and Reptiles ...... 3

Objectives and Outline of Dissertation Research ...... 4

References ...... 4

2 LITERATURE REVIEW: SNAKES AS NOVEL BIOMARKERS OF

MERCURY CONTAMINATION ...... 11

Abstract ...... 12

Introduction ...... 12

Mercury ...... 15

Snakes as Biomarkers of Mercury Exposure ...... 17

Mercury Bioaccumulation in Snakes ...... 19

Effects of Mercury on Snake Health and Immune Status ...... 21

Snakes and Mercury Transfer ...... 24

Conclusions ...... 25

Summary ...... 26

Acknowledgements ...... 27

References ...... 27

Tables ...... 41

3 MULTI-DECADAL TRENDS IN MERCURY AND METHYLMERCURY

CONCENTRATIONS IN THE BROWN WATERSNAKE (NERODIA

TAXISPILOTA) ...... 46

Abstract ...... 47

Introduction ...... 48

Methods...... 50

Results ...... 56

Discussion ...... 58

Conclusions ...... 64

Acknowledgements ...... 65

Disclaimer ...... 66

References ...... 67

Tables ...... 79

Figures...... 81

4 BROWN WATERSNAKES (NERODIA TAXISPILOTA) AS

BIOINDICATORS OF MERCURY CONTAMINATION IN A RIVERINE

SYSTEM ...... 88

Abstract ...... 89

Introduction ...... 90

Methods...... 92

Results ...... 98

Discussion ...... 100

Conclusions ...... 106

Acknowledgements ...... 107

Disclaimer ...... 108

References ...... 108

Tables ...... 117

Figures...... 118

5 PERIPHERAL BLOOD HEMATOLOGY, PLASMA BIOCHEMISTRY,

AND THE OPTIMIZATION OF AN IN VITRO IMMUNE-BASED ASSAY

IN THE BROWN WATERSNAKE (NERODIA TAXISPILOTA) ...... 125

Abstract ...... 126

Introduction ...... 126

Methods...... 128

Results ...... 133

Discussion ...... 135

Acknowledgements ...... 138

Disclaimer ...... 139

References ...... 139

Tables ...... 145

Figures...... 149

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6 MERCURY IMMUNOTOXICITY IN THE BROWN WATERSNAKE

(NERODIA TAXISPILOTA), AN IN VITRO STUDY ...... 152

Abstract ...... 153

Introduction ...... 154

Methods...... 155

Results ...... 162

Discussion ...... 164

Acknowledgements ...... 167

Disclaimer ...... 168

References ...... 168

Tables ...... 175

Figures...... 178

7 CONCLUSION ...... 181

APPENDICES

A CHAPTER 3 APPENDIX ...... 86

B CHAPTER 4 APPENDIX ...... 124

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LIST OF TABLES

Page

Table 2.1: Mean ± SEM (followed by range, when provided in corresponding study)

mercury (Hg) concentrations (mg/kg) by snake species and tissue type (blood,

brain, egg, liver, kidney, muscle, whole body). Table is based on 23 published

studies in the literature (year range 1980-2018). We performed a literature search

for publications that focused on snakes, mercury, ecological risk assessments, and

biomarkers. We searched for these papers in multiple databases including Web of

Science and Google Scholar. We also used references cited in publications from

our literature search to thoroughly search for relevant studies...... 41

Table 3.1: Differences in total mercury (THg; mg/kg dw unless otherwise noted)

concentrations in destructive (liver, muscle, kidney) and nondestructive (blood,

tail) tissues in brown watersnakes (Nerodia taxispilota) collected from Steel

Creek on the Savannah River Site, South Carolina during two time periods

(1980s, 2019). Values are reported as means ± 1 SE (ranges are reported below

respective means in parentheses). ANCOVAs were used to determine significant

differences based on group (year). Significant differences are noted by bold text

(α = 0.05). Snout-vent length (SVL) was used as a covariate. ANCOVA outputs

2 (F-value, p) are reported along with calculated partial eta-squared (ηp ) and 90%

confidence intervals (CI; based on group effect). Snakes were collected in the

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1980s (1983 – 1986) and 2019. Note that blood tissues were not available for

analysis from archived 1980s samples...... 79

Table 3.2: Differences in methylmercury (MeHg; mg/kg dw) concentrations in liver,

muscle, and kidney tissues from brown watersnakes (Nerodia taxispilota)

collected at Steel Creek on the Savannah River Site, South Carolina during two

time periods (1980s, 2019). Percentage MeHg is also reported for each tissue

type. Values are reported as means ± 1 SE (ranges are reported below respective

means in parentheses). ANCOVAs were used to determine significant differences

based on group (year). Significant differences are noted by bold text (α = 0.05).

Snout-vent length (SVL) was used as a covariate. ANCOVA outputs (F-value, p)

2 are reported along with calculated partial eta-squared (ηp ) and 90% confidence

intervals (CI; based on group effect)...... 80

Table 4.1: Total mercury concentrations (THg) in blood and tail tips (mg/kg, wet wt)

from brown watersnakes (Nerodia taxispilota) from four sites on the Savannah

River in the vicinity of the Savannah River Site, SC. Values are reported as means

± 1 SE. Ranges of all values are reported in parentheses below respective means.

Samples were collected during late spring and summer (April – August) of 2017 –

2018...... 117

Table 5.1: Wild brown watersnake (Nerodia taxispilota) whole blood hematology...... 145

Table 5.2: Peripheral blood leukocyte count and differential data from wild brown

watersnakes (Nerodia taxispilota) ...... 146

Table 5.3: Wild brown watersnake (Nerodia taxispilota) enriched cytospin

leukocytes ......

...... 147

Table 5.4: Wild brown watersnake (Nerodia taxispilota) plasma biochemistry values

measured via a VetScan VS2 (Avian-Reptile Profile Plus rotor). Values outside of

the instrument’s range were not reported...... 148

Table 6.1: Morphometrics, total mercury concentrations (THg) in blood (mg/kg, dry wt

and wet wt), packed cell volume (PCV), and total solids (g/dL) from brown

watersnakes (Nerodia taxispilota) collected from the Savannah River in Augusta,

Georgia. Values are reported as mean ± 1 SE. Ranges of values are reported in

parentheses following the respective means. Samples were collected in June and

July of 2019-2020...... 175

Table 6.2: Peripheral blood leukocyte count and differential data from brown watersnakes

(Nerodia taxispilota) collected from the Savannah River in Augusta, Georgia.

Values are reported as mean ± 1 SE. Samples were collected in June and July of

2019-2020 ...... 176

Table 6.3: Enriched cytospin leukocytes from brown watersnake (Nerodia taxispilota)

collected from the Savannah River in Augusta, Georgia. Values are reported as

mean ± 1 SE. Samples were collected in June and July of 2019-2020...... 177

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LIST OF FIGURES

Page

Figure 3.1: Location of brown watersnake (Nerodia taxispilota) sampling on the

Savannah River Site (SRS) in west-central South Carolina, USA (inset). Snakes

were collected from a section of the Steel Creek system (hollow black box)...... 81

Figure 3.2: Correlations between tail and destructive (kidney [Figure 2A], liver [Figure

2B], and muscle [Figure 2C]) tissue total mercury (THg) concentrations in brown

watersnakes (Nerodia taxispilota) captured at Steel Creek on the Savannah River

Site (Aiken, South Carolina, USA). Snakes were collected in two time periods –

the 1980s (1983 – 1986, red circles) and 2019 (black circles) ...... 82

Figure 3.3: Correlations among liver, muscle, and kidney, tissue total mercury (THg)

concentrations in brown watersnakes (Nerodia taxispilota) captured at Steel

Creek on the Savannah River Site (near Aiken, South Carolina, USA). Snakes

were collected in two time periods – the 1980s (1983 – 1986, red circles) and

2019 (black circles). Figure 3C did not fit the assumptions of normality and a

Spearman rank correlation approach was used...... 83

Figure 3.4: Relationship between snout-vent length (SVL) and liver (Figure 4A; analysis

2 of covariance, n = 28; SVL: F1,25 = 14.04, r = 0.391, p = 0.03; group [year]: F1,25

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= 5.26, p < 0.001) and tail (Figure 4B; analysis of covariance, n = 38; SVL: F1,35

2 = 7.73, r = 0.560, p = 0.009; group: F1,35 = 41.38, p < 0.001) total mercury (THg)

concentrations in brown watersnakes (Nerodia taxispilota) collected from Steel

Creek on the Savannah River Site (near Aiken, South Carolina)...... 84

Figure 3.5: Correlations between methylmercury (MeHg) and total mercury (THg)

concentrations in kidney (Figure 5A), liver (Figure 5B), and muscle (Figure 5C)

tissues from brown watersnakes (Nerodia taxispilota) captured at Steel Creek on

the Savannah River Site (Aiken, South Carolina, USA). Snakes were collected in

two time periods – the 1980s (1983 – 1986, red circles) and 2019 (black

circles) ......

Figure 4.1: Brown watersnake (Nerodia taxispilota) sampling sites on the Savannah

River that borders the Department of Energy’s Savannah River Site in west-

central South Carolina, USA. Sites sampled (all labeled with black circles)

include Augusta, Jackson, Ellenton Bay (EBay), and Lower Three Runs ...... 118

Figure 4.2: Spearman rank correlation (rs) between blood and tail tip total mercury (THg)

concentrations in brown watersnakes (Nerodia taxispilota) captured in the

Savannah River. All THg values are reported on a wet weight basis...... 119

Figure 4.3: Relationship between tail tip total mercury (THg) concentrations and snout-

vent length in brown watersnakes (Nerodia taxispilota) captured in the Savannah

River. Tail tip THg values are reported on a wet weight basis...... 120

Figure 4.4: Predicted relationship between tail tip total mercury (THg) and snout vent

length in brown watersnakes (Nerodia taxispilota) at four different sites on the

xviii

Savannah River. Plots depict predicted fit (solid line) and 95% confidence

intervals (dotted lines). Sites include Augusta, Jackson, Ellenton Bay (EBay), and

Lower Three Runs (LTR). A significant interaction was observed between snout-

vent length (SVL) and site (Figure 4A; F7,113 = 15.57, p < 0.001). A spotlight

analysis was performed to examine differences in tail tip THg based on site at

three focal snake sizes (375, 600, and 900mm). Significant differences in tail tip

THg were observed between snakes from Augusta and Jackson at 375 and 600mm

SVL (Figure 4B; at 375mm: t113 = -3.72, p < 0.001; at 600mm: t113 = -3.35, p =

0.001). Larger snakes (900mm) had significantly higher tail tip THg at EBay and

LTR compared to Augusta (Figure 4C; Augusta to EBay: t113 = 3.41, p < 0.001;

t113 = 2.94, p = 0.004)...... 121

Figure 4.5: Average (± 1 SE) total mercury (THg) concentrations in all sampled brown

watersnakes (Nerodia taxispilota; n = 121), catfish (n = 89), panfish (n = 63), and

bass (n = 87) from three different sites on the Savannah River (Factorial ANOVA;

Species: F3,344 = 63.73, p < 0.001; Site: F2,344 = 39.88, p < 0.001). Both tail THg

and predicted snake muscle THg are reported for N. taxispilota (p < 0.0001, R2 =

0.872, n = 27; y [log10 muscle THg] = 0.81611x [log10 tail THg] + 0.83322;

Haskins et al., unpublished data). Pairwise comparisons revealed significant

differences among species across sites (denoted by letters). Note that tail THg

concentrations in N. taxispilota (*) were not used in this analysis. In addition, fish

were not sampled at the Jackson site; therefore, we do not provide any snake data

from Jackson in this figure...... 122

xix

Figure 4.6: Average (± 1 SE) total mercury (THg) concentrations in fish of consumable

size and brown watersnakes (Nerodia taxispilota) at three sites on the Savannah

River. Both tail THg and predicted snake muscle THg are reported for N.

2 taxispilota (p < 0.0001, r = 0.872, n = 27; y [log10 muscle THg] = 0.81611x

[log10 tail THg] + 0.83322; Haskins et al., unpublished data). To examine

potential biomagnification, we compared THg values in catfish (Figure 6A; N =

52) and panfish (Figure 6B; N = 62) that were 37 – 50% of the largest adult

snakes (N = 14) at each site. The average biomagnification factors for THg in N.

taxispilota were 5.4 (catfish) and 3.1 (panfish). Note that fish were not sampled at

the Jackson site, therefore, we do not provide any snake data from Jackson in this

figure… ...... 123

Figure 5.1: Images taken from brown watersnake (Nerodia taxispilota) blood smears

(panels A-D) and an enriched leukocyte cytospin (panel E). Examples of

azurophils (A), basophils (B), heterophils (H), lymphocytes (L), monocytes (M),

and reactive monocyte (Mr) are pictured. Examples of thrombocytes (T) are also

provided ...... 149

Figure 5.2: LPS mitogen stimulation. Enriched snake peripheral blood lymphocytes (4 x

105 cells/ 100 μL/well) were cultured with 100 μL LPS (0, 5, 50 μg/mL). At 48 or

72 hr, alamarBlueTM (20 μL) was added to each well, incubated, and then read 24

hr later, after a total incubation time of 72 hr (Figure 2A, grey bars) or 96 hr

(Figure 2B, dark grey bars), respectively. Values are reported as optical

absorbance (Δ570-600), mean ± 1 SE, n = 12. No significant differences were

found between baseline proliferation values and LPS-treated lymphocytes

(independent analysis for each incubation treatment – 72 or 96 hr). Significance is

based on p < 0.05...... 150

Figure 5.3: Con A Mitogen stimulation. Enriched snake peripheral blood lymphocytes (4

x 105 cells/ 100 μL/well) were cultured with 100 μL of Con A (0, 1, 10, 50, 100

μg/mL). At 48 or 72 hr, AlamarBlueTM (20 μL) was added to each well,

incubated, and then read 24 hr later, after a total incubation time of at 72 hr

(Figure 3A, grey bars) or 96 hr (Figure 3B, dark grey bars), respectively.

Values are reported as optical absorbance (570-600), mean ± 1 SE, n = 12.

Significant differences among proliferation treatments (Post hoc Tukey’s

analysis) are categorized by letter (independent analysis for each incubation

treatment – 72 or 96 hr). Significance is based on p < 0.05...... 151

Figure 6.1: Images taken from brown watersnake (Nerodia taxispilota) blood smears and

enriched leukocyte cytospins. All photos were taken at 100x oil objective (1000x

magnification). Cytospins from reference treatment (panel A) show lymphocytes

(L) and cells from the 75 µM HgCl2 treatment (panel B) show severe loss of

cellular details (lysis). Blood smears (panel C) show examples of azurophils (A),

lymphocytes (L), thrombocytes (T), and one heterophil (H). Multiple Hepatozoon

spp. (Apicomplexa:Haemogregarinidae) (arrows) were observed in one male

individual sampled (panel D)...... 178

Figure 6.2: Multivariate analysis of associations between immunological variables and

total mercury (THg) in brown watersnakes (Nerodia taxispilota). (2A) Biplot of

the first two principal components on seven measures of health, including: body

condition index (BCI), absolute azurophils (Abs A), absolute basophils (Abs B),

xxi

absolute heterophils (Abs H), absolute lymphocytes (Abs L), absolute monocytes

(Abs M), and heterophil:lymphocyte ratios (HL ratio). Red arrows depict

principal component loadings. (2B) Spearman rank correlation between principal

component 2 and blood total mercury (THg) in N. taxispilota. In both figures,

females are shown in red and males are shown in black ...... 179

Figure 6.3: Effects of mercury chloride (HgCl2) on snake lymphocyte proliferation.

Enriched snake peripheral blood lymphocytes (4 x 105 cells/100 µL/well) were

cultured with 100 µL of HgCl2 (3.75, 37.5, 75 µM) or 100 µL of Con A (50

µg/mL). At 48 hr, AlamarBlueTM (20 µL) was added to each well, incubated, and

read 24 hr later. Values are reported as optical absorbance (ΔOD570-600), mean

± 1 SE, n = 11. Significant differences among proliferation treatments (Tukey’s

HSD post-hoc analysis) are categorized by letter). Significant differences are

based on Bonferroni-adjusted significance values (p < 0.05) ...... 180

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CHAPTER 1

INTRODUCTION

Anthropogenic activities have led to the release of contaminants since humans began using fire for warmth and preparing food. Examples of alterations to the environment that lead to contaminant release vary greatly, and humans have dramatically altered baseline contaminant levels throughout the globe (Férard 2013). Some of the earliest published ecotoxicological studies in the mid-nineteenth century (Penny and

Adams 1863), demonstrate that humans have long recognized that exposure to pollutants may lead to unfavorable biological outcomes in humans and wildlife. While extensive habitat alterations undoubtedly impact wildlife populations, multiple large-scale environmental disasters in the last two decades (e.g., Deepwater Horizon Oil Spill in

2010, Fukushima Daiichi nuclear disaster in 2011), has again brought pollution to the forefront of public concern.

Wildlife as Bioindicators

The desire for quality control, through monitoring species native to impacted ecosystems, has led to the use of wildlife to monitor the presence and effects of pollution in the environment. Wildlife have long been used to evaluate conditions of their respective environments. For example, during the Industrial Revolution, canaries were

brought into coal mines to warn miners of hazardous conditions (Cairns and Pratt 1993).

In the realm of ecotoxicology, it is common for researchers to monitor the

bioaccumulation and effects of contaminants through “bioindicator” species (Asif et al.

2018). Broadly, bioindicators are considered any entity or group of organisms that

provide information based on the environment that they inhabit (Asif et al. 2018). The

use of wildlife to monitor pollution is not beholden to a single taxon, as there are examples of amphibians (Townsend and Driscoll 2013; Pfleeger et al. 2016; Faccio et al.

2019), birds (Vo et al. 2011; Espín et al. 2012; Cooper et al. 2017), mammals (Lord et al.

2002; Kalisinska et al. 2012; Lazarus et al. 2017), fish (Paller and Littrell 2007; Gentès et al. 2019; Maury-Brachet et al. 2020), invertebrates (Longo et al. 2013; Jelaska et al.

2014), and reptiles (Drewett et al. 2013; Lemaire et al. 2018; Rumbold and Bartoszek

2019; Lettoof et al. 2020; Lemaire et al. 2021) all serving as pollution bioindicators.

However, relative to other wildlife, amphibians and reptiles account for a significantly

lower percentage of these studies (Burger 2006). For this dissertation, we will focus on

the use of a bioindicator to evaluate the presence and effects of a pervasive heavy metal,

mercury (Hg), in the environment.

Mercury

Although Hg is a naturally-occurring, toxic heavy metal, anthropogenic activities have led to a significant increase of this contaminant in the environment. For several decades, Hg has been acknowledged as a global contaminant of concern. In the 1950s, extensive Hg pollution in Minamata Bay, Japan, led to more than 3,000 in the local population suffering Hg toxicity (Frederick et al. 2005). Global disasters such as the one in Minamata Bay led to a stronger focus on the monitoring of such contaminants by industrialized nations (Wiener et al. 2003). Sources of Hg present in the environment vary significantly and include power plants, mining, water treatment facilities, and other

industries (e.g., waste from chlor-alkali plants or medical facilities; Selin 2009). Once Hg

is released into the environment, bacteria can transform it into a bioavailable, more toxic form (methylmercury) that readily biomagnifies throughout food webs (Klaus et al.

2016). An improved understanding of how Hg accumulates and impacts wildlife is important, as it is well-documented that Hg exposure may lead to toxic effects on multiple organ systems (Eagles-Smith et al. 2018). Perhaps the most well-known impact of Hg exposure is the development of adverse neurological effects, such as limb paralysis, seizures, and death (Sleeman et al. 2010). However, Hg also may cause reproductive toxicity (Hopkins et al. 2013), immunotoxicity (Hawley et al. 2009; Lewis et al. 2013), and disruption of the endocrine system (Tan et al. 2009).

Mercury and Reptiles

Reptiles possess many characteristics that make them ideal candidates for monitoring contaminants in the environment that bioaccumulate and biomagnify in food webs. Many reptiles are long-lived (Vitt and Caldwell 2014), have a high position on trophic food webs (Chumchal et al. 2011; Aresco et al. 2015), and are relatively sedentary (e.g., Mills et al. 1995) compared to other more commonly studied taxa in ecotoxicology (e.g., birds and mammals). Recent studies demonstrate that carnivorous reptiles, such as alligators and snakes, may accumulate significant concentrations of Hg

(Axelrad et al. 2011; Krabbenhoft et al. 2012; Drewett et al. 2013) in polluted aquatic ecosystems. However, we know little regarding how Hg may negatively impact reptilian health. In the last three decades, studies focused on using reptiles as bioindicators of Hg have increased (Schneider et al. 2013). However, relative to other species, reptiles are among the least studied vertebrates in ecotoxicology (Hopkins 2000; Grillitsch and

Schiesari 2010). This, combined with global declines in reptilian populations, calls for a

more thorough investigation of contaminants’ potential impacts on these species

(Gibbons et al. 2000; Schneider et al. 2013).

Objectives and Outline of Dissertation Research

My research aims to reduce sizable knowledge gaps in reptile ecotoxicology by

focusing on the bioaccumulation and effects of Hg in a common watersnake species

endemic to the southeastern United States. In Chapter 2, I will review the use of snakes as

bioindicators of mercury contamination in the environment and identify knowledge gaps.

Chapter 3 explores temporal effects on Hg distribution and speciation in a watersnake, as

well as the validity of using non-destructive tissue types for monitoring Hg in destructive

tissues (e.g., kidney, liver, muscles). In Chapter 4, I investigate the potential utility of the

brown watersnake (Nerodia taxispilota) as serve as a bioindicator for monitoring Hg in a

riverine system. In Chapter 5, in a watersnake, I evaluate the optimization of an in vitro

technique commonly used in other taxa to examine immune function. In Chapter 6, I use

the optimized in vitro technique from the fourth chapter to determine how Hg may affect

the snake immune system. Collectively, these research chapters aim to increase our knowledge of how common watersnakes may be used to monitor Hg in aquatic systems, as well as provide a foundation for further investigations into how Hg and other contaminants may impact the snake immune response.

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CHAPTER 2

LITERATURE REVIEW: SNAKES AS NOVEL BIOMARKERS OF MERCURY

CONTAMINATION1

1 Haskins, D.L., R.M. Gogal, Jr., and T.D. Tuberville. 2019. Reviews of Environmental Contamination and Toxicology. Reprinted here with permission of the publisher.

Abstract

Mercury (Hg) is an environmental contaminant that has been reported in many

wildlife species worldwide. The organic form of Hg bioaccumulates in higher trophic

levels, and thus, long-lived predators are at risk for higher Hg exposure. Although

ecological risk assessments for contaminants such as Hg include pertinent receptor

species, snakes are rarely considered, despite their high trophic status and potential to accumulate high levels of Hg. Our current knowledge of these reptiles suggests that snakes may be useful novel biomarkers to monitor contaminated environments. The few available studies show that snakes can bioaccumulate significant amounts of Hg.

However, little is known about the role of snakes in Hg transport in the environment or the individual-level effects of Hg exposure in this group of reptiles. This is a major concern, as snakes often serve as important prey for a variety of taxa within ecosystems

(including humans). In this review, we compiled and analyzed the results of over 30 studies to discuss the impact of Hg on snakes, specifically sources of exposure, bioaccumulation, health consequences, and specific scientific knowledge gaps regarding these moderate to high trophic predators.

Introduction

Snakes, Ecotoxicology, and Mercury

Ecological risk assessments are a tool used by regulatory agencies to determine

how the environment and associated wildlife might be impacted by proposed or ongoing

anthropogenic activities (Newman 2015). In the last two decades, researchers have

highlighted the absence of reptiles in these assessments (Campbell and Campbell 2001;

Grillitsch and Schiesari 2010; Weir et al. 2010). Reptiles are often underrepresented or

excluded from ecological risk assessments even though they serve important roles in their

ecosystems and can be both predators and prey of terrestrial and aquatic species.

Furthermore, reptiles often inhabit environments that are conducive to long-term retention of contaminants (e.g., methylation of mercury in isolated wetlands), increasing

the likelihood that they will be exposed to and accumulate pollutants. Physiological characteristics found in reptiles also make them ideal study candidates for risk assessments. Their metabolic mode (ectothermy) allows high tissue conversion rates and low tissue turnover rates, which may promote processes associated with bioaccumulation

(Hopkins 2006). Many of these organisms also exhibit indeterminate growth, and this may allow researchers to quantify bioaccumulation rates over their entire lifespan.

Although interest in reptile ecotoxicology has increased in recent years, snakes

are still widely excluded from such studies, even though their life history characteristics

make them useful candidate receptor species (Hopkins 2000; Campbell and Campbell

2001; Drewett et al. 2013). This is likely due to a combination of factors. For instance,

snake studies have historically been plagued by small sample sizes, and thus, accumulation of information regarding their life history and ecological traits has lagged behind other reptiles. Many species are also secretive, limiting their detection or capture

(Durso et al. 2011; Willson and Winne 2016; Willson et al. 2011). Because of these issues, research involving these species may be more difficult to conduct and interpret.

Cultural biases toward snakes are also often extreme, and people tend to either worship or loathe these reptiles (Pough et al. 1998; Campbell and Campbell 2001). Further, it is often difficult to convince funding agencies and the general public that results from snake studies positively impact humans, although environmental education efforts may be

helping in this regard (Shine and Bonnet 2000). Overall, it is no surprise that research in

reptile ecotoxicology has significantly lagged behind that of other taxonomic groups

(Hopkins 2000; Weir et al. 2010).

There are more than 3,000 species of snakes recognized globally, and they exhibit

a wide diversity in their habitat associations. These limbless predators inhabit every

continent except Antarctica and have successfully colonized terrestrial, freshwater, and

marine habitats (Vitt and Caldwell 2014). Of the snake families, Colubridae is the most

speciose and is comprised of more than half of the world’s described snake species

(>1,700 species, Vitt and Caldwell 2014). Although the ICUN Red List of Threatened

Species does not indicate that large numbers of snake species are threatened (~185 at risk, IUCN 2017), it is notoriously difficult to study snake population dynamics, and recent research has suggested that snakes (like other reptiles) could be experiencing population declines likely due to an assortment of threats, including pollution (Gibbons et

al. 2000; Reading et al. 2010).

Mercury (Hg) is a major contaminant of concern around the globe, and its prevalence has increased markedly in both terrestrial and aquatic habitats over the last half a century (Tweedy et al. 2013; Lamborg et al. 2014). Anthropogenic activities such as mining, coal combustion, and other industrial processes have facilitated Hg’s release into the environment, where it is transformed into a bioavailable form (methylmercury,

MeHg) that can accumulate in wildlife (Schneider et al. 2013). Recent studies suggest that snakes can accumulate significant amounts of Hg, with snakes inhabiting aquatic environments often exhibiting the highest Hg burdens (Axelrad et al. 2011; Drewett et al.

2013). Indeed, most ecotoxicological studies of Hg bioaccumulation in snakes have

focused on aquatic or semiaquatic species such as cottonmouths (Agkistrodon

piscivorus), natricines (e.g., Nerodia and Thamnophis spp.), and a few other colubrids

(Campbell and Campbell 2001; Schneider et al. 2013; Lemaire et al. 2018).

In this review, we will examine the sources of Hg contamination and the factors that determine availability within aquatic and terrestrial environments. We will also

review the potential of snakes as biomarkers for Hg exposure, focusing on

bioaccumulation and known effects of exposure. We will then discuss the role snakes

play in nutrient and contaminant transfer. Finally, we will conclude by identifying

research gaps.

Mercury

Mercury Sources

Mercury is a highly toxic heavy metal that is released into the environment by

natural and anthropogenic sources. Unlike other heavy metals of concern (e.g., lead or

cadmium), Hg is unique not only because is it locally transformed to more bioavailable forms (e.g., Hg methylation), but because it also can be transported on a global scale via atmospheric cycling and deposition (Boening 2000; Zhang et al. 2009). In fact, distinct

atmospheric cycles may result in a system where regions can be impacted by Hg that

originates from both local and global inputs. Prior to the industrial revolution, Hg in the

environment mostly originated from the natural mobilization of Hg deposits in the earth’s crust and volcanoes (Selin 2009). Presently, environmental Hg originates from a variety of anthropogenic activities, including coal burning, mining, water treatment plants, and

other industrial facilities (Selin 2009). Thus, industrialization has significantly altered Hg

emissions and cycling. For example, one study recently suggested that Hg concentrations

in ocean surface waters have tripled compared to pre-anthropogenic conditions (Lamborg et al. 2014).

Forms of Mercury and Availability in the Environment

The major forms of Hg in the environment include elemental, ionic, or organic Hg

(e.g., methylmercury or MeHg). Atmospheric Hg is primarily comprised of elemental Hg, which has a long atmospheric lifespan (~1 year) and thus contributes to its global transport (Chen et al. 2014). Within aquatic and terrestrial habitats, Hg can be found in various forms, but most studies focus on inorganic Hg and MeHg. The most toxic form of

Hg, MeHg, is commonly produced by interactions between anaerobic sulfur-reducing bacteria and inorganic Hg (Klaus et al. 2016). Bioaccumulation of MeHg is facilitated by dietary exposure, with higher Hg burdens reported in top trophic predators

(Scheuhammer et al. 2007).

MeHg deposition in aquatic environments is dependent on the original Hg species present, as well as an assortment of environmental factors (e.g., pH, temperature, oxygen, dissolved organic carbon, sediment type, forest cover, forest fires) that influence Hg biotransformation (Kelly et al. 2006; Drenner et al. 2013; Klaus et al. 2016; Yang et al.

2016). Recent studies suggest that even fluctuations in weather, such as flooding events, can alter the availability and bioaccumulation of Hg in reptiles. Lázaro et al. (2015) observed that Brazilian caimans (Caiman yacare) had higher total mercury (THg) concentrations in their scutes and claws during flood periods than those sampled in drought conditions. Thus, when studying local Hg uptake and effects in biota, researchers must take care to consider all factors that can impact Hg biotransformation within their system.

Snakes as Biomarkers of Mercury Exposure

Studies of Hg in wildlife have mostly focused on mammals, fish, birds, and other

species of importance to human exposure (e.g., game species or species of immediate

economic value). Surprisingly, even though snakes are often important predators co-

inhabiting within the same ecosystems, studies of Hg bioaccumulation and its potential

impact on snake health are sparse (Drewett et al. 2013). All snakes are either secondary,

tertiary, or top predators within their respective ecosystems; thus, they play a crucial role

in the transfer of environmental contaminants (Campbell and Campbell 2001).

Snakes exhibit a variety of natural history traits that make them exceptional

candidates for ecotoxicological studies. One of the most important traits to consider is

their diet. While some snake species are dietary generalists, many are dietary specialists

that only consume a specific type of prey (Drewett et al. 2013). For instance, rough green

snakes (Opheodrys aestivus) and glossy crayfish snakes (Liodytes [Regina] rigida)

specialize on insects and crayfish, respectively (Gibbons and Dorcas 2008; Mason 2008).

Diets may also vary among populations within a single species, as has been demonstrated

in the viperine watersnake (Natrix maura; Lemaire et al. 2018). Some snake species also

undergo ontogenetic shifts in dietary preferences, which may impact how snakes at differing life stages accumulate specific contaminants. The brown watersnake (Nerodia taxispilota) is a great example of a species whose bioaccumulation potential likely hinges on its ontogenetic dietary shift. Although brown watersnakes are piscivorous throughout their lives, at approximately 60 cm snout-vent length, they shift from a diet that includes a variety of fish prey to a diet mainly comprised of catfish (Ictalurus spp.; Mills 2002).

Although dietary exposure is the focus of most contaminant studies, dermal contact with

contaminated soils may be an underappreciate source of exposure (Weir et al. 2010).

Thus, the proportion of time a snake spends buried or in contact with the soil and the

propensity of different contaminants to partition in soil layers would both influence

exposure and accumulation. Furthermore, because they have relatively small home ranges

and high site fidelity (Mills 2002; Beaupre and Douglas 2009), snakes may be

particularly valuable biomarkers of local contamination.

Life history traits of snakes also contribute to their potential as bioindicators of

Hg pollution. Many species of snakes are relatively long-lived and thus can accumulate high Hg burdens throughout their lifetime. Some large-bodied watersnakes (e.g., brown

watersnakes) can live for more than 10 years (Mills 2002). Pit vipers such as the timber rattlesnake (Crotalus horridus) are capable of even more impressive lifespans, with maximum estimates of more than 30 years (Brown 2016). Another important life history

trait potentially influencing Hg bioaccumulation and exposure routes is reproductive

strategy. Snake’ reproductive strategies vary but can be broadly categorized as oviparous

or viviparous. Furthermore, snakes also exhibit differences in how they invest their energy stores into their offspring. Capital breeders used stored energy, while income breeders use recently acquired energy (Bonnet et al. 1998; Gregory 2006). These variations dictate how contaminants and potentially the extent to which contaminants may be maternally transferred to offspring. For example, animals that are primarily capital breeders may concentrate contaminants in their body reserves, allowing

mobilization and circulation of high contaminant levels during vitellogenesis (Meijer and

Drent 1999; Rowe 2008).

Our overall understanding of snake ecology is still growing, but more studies are needed to determine what factors may impact their utility as biomarkers of Hg pollution.

As mentioned previously, Hopkins (2006) suggested that reptiles may accumulate higher

amounts of Hg than other taxa because of their high conversion efficiencies. Furthermore,

multiple studies show that snakes can occur at high densities, with substantial biomasses

(Houston and Shine 1994; Mills 2002; Willson and Winne 2016). As relatively sedentary,

obligate predators occupying a diversity of ecosystems, snakes have the potential to

accumulate high amounts of Hg and are likely important contributors to Hg transfer

within food webs.

Mercury Bioaccumulation in Snakes

As in other species, Hg partitioning in snakes is known to vary among tissue

types. Published values in snakes are often opportunistic and typically obtained from

destructively sampled individuals. However, in recent years, there has been an increased

use of nondestructively sampled tissues for quantifying contaminant burdens to allow for

repeated sampling of individuals and to provide the opportunity to investigate the potential sublethal impacts of contaminant exposure in snakes (Hopkins et al. 2001; Jones

and Holladay 2006). Thus, it is important for researchers to consider tissue types when

interpreting Hg exposure and its effects.

We reviewed the literature (year range 1980–2018) to compile tissue-specific Hg

concentration data from snakes (see Table 1). Studies of Hg bioaccumulation in snakes

have predominantly focused on taxa (e.g., Agkistrodon, Natrix, Nerodia, Python, and

Thamnophis spp.) that frequent aquatic environments, as these habitats are often associated with high rates of Hg methylation (Scheuhammer et al. 2007). Of the 18 snake

species with published studies, only seven species were not in the natricine subfamily of

colubrids. Nerodia (i.e., watersnakes) were the most commonly sampled genus for Hg

exposure (appearing in 12/23 of reviewed articles in Table 1). However, a few studies

reported Hg burdens for terrestrial species, including the pine snake (Pituophis melanoleucus), the rat snake (Pantherophis [Elaphe] obsoleta), and the big-eye rat snake

(Ptyas dhumnades; Burger 1992; Burger et al. 2017; Drewett et al. 2013; Abeysinghe et al. 2017). Our review also highlights a strong geographic bias in the availability of published studies focused on snakes in ecotoxicology, with most of the research occurring in North America (see Table 1).

One of the highest Hg burdens reported in any snake to date was from a northern watersnake (Nerodia sipedon) collected in Virginia (tail tip, 13.84 mg/kg dw; Drewett et al. 2013), surpassing values previously reported in snapping turtles (Chelydra serpentina) from the same site (Hopkins et al. 2013b). Another study in Taiwan reported that snakes had some of the highest Hg burdens found in biota from Kenting National Park

(maximum of 23.9 mg/kg dw Hg); however, they did not report the species of snake sampled in their study. Similarly, aquatic snakes from other study systems have also been documented to have higher Hg burdens than co-occurring top predators (Chumchal et al.

2011; Drewett et al. 2013). In Texas and Louisiana, Chumchal et al. (2011) found that cottonmouths (A. piscivorus) attained liver Hg concentrations of 7.46 mg/kg dw – three times that of American alligators (Alligator mississippiensis; 2.26 mg/kg dw) from the same site. In the Florida Everglades, invasive Burmese pythons (Python molurus bivittatus), which are reported to consume wading birds, mammals, and even alligators

(Snow et al. 2007; Dove et al. 2011; Dorcas et al. 2012), had higher muscle Hg

concentrations (10.75 mg/kg Hg; Axelrad et al. 2011) than sympatric alligators and fish

(Axelrad et al. 2011). Snakes that feed at lower trophic levels but occur near point sources of Hg contamination, however, can still attain high Hg levels, as illustrated by the

Hg levels in Virginia northern watersnakes, which were captured near a former acetate fiber production facility (13.84 mg/kg dw; Drewett et al. 2013). Collectively, these studies reveal the propensity for snakes to bioaccumulate high levels of Hg, thereby supporting their utility as biomarkers of Hg contamination.

Effects of Mercury on Snake Health and Immune Status

Mercury effects in wildlife

The effects of Hg on wildlife vary widely, but in birds and mammals, these effects

are generally characterized by aberrations in the endocrine, immune, neurological, and reproductive systems (Spalding et al. 2000; Tan et al. 2009; Fallacara et al. 2011). Many of the organ systems are similar across taxa. Thus, the biological effects of Hg exposure in reptiles may have similar consequences as reported for other taxa. It is important to note, however, that both exposure and sensitivity to contaminants can vary among taxa in the same study system (Weir et al. 2010). Unfortunately, relatively little is known about the toxicological significance of Hg exposure in snakes and other reptiles compared to birds, fish, and mammals. The few studies to date on the effects of Hg on reptiles, especially snakes, suggest that they may be more resilient to contaminants relative to other taxa (Wolfe et al. 1998; Bazar et al. 2002; Chin et al. 2013b). However, given the propensity of snakes to accumulate high levels of Hg coupled with the sublethal effects observed in other species, it is quite likely that snakes could be at risk for compromised health.

Maternally Transferred Mercury in Snakes

Maternal transfer of contaminants in wildlife is an important route of exposure to

consider in ecotoxicological research. There are only a handful of studies that examined

maternal transfer of contaminants in snakes, and the majority of them focused on Hg

(Hopkins et al. 2004; Chin et al. 2013a, b; Cusaac et al. 2016). Chin et al. (2013a) found that high levels of maternally transferred Hg did not significantly impact maternal reproductive output or embryonic survival in northern watersnakes collected in Virginia.

Neonates from the same study system were then subjected to tests that gauged their

foraging, learning, and locomotor abilities (Chin et al. 2013b). They found that food

motivation and striking efficiency in neonates were negatively correlated with Hg

burdens. If these behavioral deficits translate to a wild setting, they could lead to reduced

growth and fitness in neonates produced by highly contaminated mothers.

In a more recent study involving an artificial maternal Hg transfer technique in

which female northern watersnakes were force-fed pills with MeHg during pregnancy,

neither corticosterone (CORT) levels nor white blood cell counts in offspring were

affected when compared to control offspring (Cusaac et al. 2016). However, absolute

baseline level for CORT could not be obtained, as evidenced by control neonates also

having maternally transferred Hg even though their mothers were not exposed to MeHg

during the experimental trial. The most noteworthy observation from this study was that

three (3/17) Hg-exposed mothers died and all three were in either the low- (0.1 mg/kg) or

high-dose (10 mg/kg) MeHg groups. Furthermore, the single female mortality from the

high-dose group presented with symptoms that were consistent with acute Hg exposure

(e.g., lethargy, lack of coordination). Overall, the little information that exists for Hg

effects in snakes suggests that northern watersnakes, and perhaps other snake species,

may be more tolerant of Hg exposure compared to other taxa, but more research is needed (Chin et al. 2013a, b; Cusaac et al. 2016).

Mercury and Reptile Immunotoxicology

The vertebrate immune response is sensitive to Hg exposure, as many studies in

mammals and birds show that Hg may negatively affect cell proliferation and regulation

of cytokines and chemokines and potentially cause cell death (Lewis et al. 2013;

Desforges et al. 2016; Gardner and Nyland 2016). Studies examining the effects of

contaminants on the reptilian immune system are lacking. In fact, most literature reviews

in wildlife immunotoxicology do not include sections for reptiles due to a paucity of

research in this field (Keller et al. 2006). Of the two reported studies that examined Hg’s

impact on reptilian immunity, one study found that leukocyte counts in wild loggerhead

sea turtles (Caretta caretta) were negatively correlated with blood Hg, suggesting that Hg

exposure caused measurable immunosuppression (Day et al. 2007). Yet, in the other

study, northern watersnakes collected from a site contaminated with Hg exhibited no

differences in wound healing, an indirect measure of innate immunity, compared to

snakes from a reference site (Hopkins et al. 2013a). There are numerous host and

environmental factors that likely impacted the outcomes of these two studies. Still, based

on studies in other species, it is possible that Hg exposure can adversely modulate the

snake immune system leading to higher rates of disease and other health issues

(Scheuhammer et al. 2007). This is a relevant concern as some snake populations are

currently under threat due to emerging diseases, such as snake fungal disease (Lorch et al.

2016). Exposure to additional stressors such as contaminants that disrupt the snake

immune system could increase susceptibility to infection or disease. Further research is needed to elucidate the relationship between contaminants, immunity, and health and to better understand their potential individual- and population-level consequences in snakes.

Snakes and Mercury Transfer

Snakes and Mercury Transfer in Aquatic and Terrestrial Ecosystems

An increasingly important topic in ecotoxicological studies is the role of species in linking aquatic and terrestrial food webs (Cristol et al. 2008; Sullivan and Rodewald

2012; Leaphart 2017). Snakes facilitate the movement of energy and contaminants across ecosystems in their roles as both predators and prey. For example, banded watersnakes

(Nerodia fasciata) and black swamp snakes (Liodytes [Seminatrix] pygaea) consume large quantities of terrestrial amphibians returning to wetlands to breed (Willson and

Winne 2016), resulting in large transfers of energy to the aquatic habitat from the surrounding terrestrial environment (>150,000 kJ ha1 annually in an 10-ha isolated wetland in South Carolina, USA).

Watersnakes (Nerodia spp.) can also play an important role in contaminant transfer from the aquatic to the terrestrial environment. In addition to being subject to predation by aquatic species such as fish, watersnakes are also consumed by terrestrial predators, including other snakes (e.g., coachwhips, king snakes, and racers), mammals

(e.g., raccoons and armadillos), and birds (e.g., hawks and owls; Mushinsky and Miller

1993; Voris and Murphy 2002; Gibbons and Dorcas 2004; Willson and Winne 2016).

Thus, due to their small size, neonates in particular may be prone to predation. The brown watersnake and the diamondback watersnake (Nerodia rhombifer) are large-bodied, piscivorous watersnakes that inhabit rivers and permanent bodies of water in the USA

(Mills 2004; Keck 2004). Their strictly piscivorous diet likely puts them at risk for

bioaccumulation of high amounts of MeHg. In addition, these species are known to

reproduce annually, with the largest females capable of producing upward of 60 neonates

(Mills 2004; Keck 2004). If females maternally transfer Hg to their young, as reported in

northern watersnakes (Chin et al. 2013b), these neonates may potentially spread large

amounts of Hg from aquatic sources to terrestrial predators.

Snakes and Risk of Human Exposure to Contaminants

Another often overlooked hazard of contaminants in snakes is the risk of human

exposure. Human consumption of snakes may be uncommon in the USA, but in other

countries, snakes are commonly collected for medicine or food and are even considered a

delicacy (Klemens and Thorbjarnarson 1995; Schneider et al. 2013). In Cambodia, some

records show that during the monsoon season, upward of 8,500 watersnakes can be collected per day for feeding alligators and for human consumption. In addition, estimates of snake consumption by humans in Svay Rieng, Cambodia, are approximately

0.19 kg/person/year (Hortle 2007). Although snakes are not commonly consumed in the

USA, reports of Florida residents eating “Everglades pizza” have worried state officials because this dish often includes American alligator, frog legs, and invasive Burmese python (Snyder 2012), which accumulate high amounts of Hg, thereby putting humans at risk (Axelrad et al. 2011).

Conclusions

Despite being one of the most well-studied contaminants around the globe, relatively little is known about Hg bioaccumulation in snakes. Snakes are middle to upper trophic level predators within ecosystems; thus, understanding their role in Hg transfer is

crucial when performing accurate risk assessments. Studies show that snakes that inhabit aquatic environments (e.g., Nerodia, Python, Agkistrodon spp.) can accumulate markedly high amounts of Hg relative to other taxa in the same system. Because viviparous watersnake species can also maternally transfer Hg to their offspring, it is also important to consider the multiple routes by which snakes can transfer and mobilize Hg within an ecosystem. Furthermore, countries with human populations that rely on snakes as a food source should seriously consider Hg bioaccumulation in snakes as a likely avenue for human exposure, particularly in areas where environmental Hg levels are known to be elevated.

Little is known about the impact of acute or chronic Hg exposure on snakes and their health (i.e., immunology, metabolism, and overall physiology). The limited studies available suggest at least some species (e.g., northern watersnakes) may be tolerant to high levels of Hg (Chin et al. 2013a, b; Cusaac et al. 2016). If widely applicable, their resilience bodes well for the snakes, but the implications are that snakes may readily transport high amounts of Hg and yet not show signs of clinical illness. However, it is also important to note that many aspects of snake health remain poorly known or even unexplored in the scientific literature (e.g., immunotoxicity). Thus, further research is needed to clarify the relationships between Hg body burdens and snake health.

Summary

In this review, we emphasize the utility of snakes as important biomarkers of Hg exposure and as critical links for Hg transfer in the environment. We also sought to stress the lack of studies that focus on Hg bioaccumulation and concomitant effects in snakes.

Though disdain for snakes persists throughout much of society, snakes are important to

biodiversity and overall ecosystem health. Snakes are facing threats from a variety of

sources including pollution, emerging diseases, invasive species, and habitat destruction.

Many snake species are listed as threatened or endangered, and their ultimate persistence will rely on a more comprehensive understanding of the potential impacts of widespread contaminants on their health.

Acknowledgements

Preparation of this manuscript was supported by an assistantship through the University

of Georgia’s Interdisciplinary Toxicology Program and the Savannah River Ecology

Laboratory, as well as the Department of Energy under award number DE-EM0004391 to

the University of Georgia Research Foundation and by the Savannah River Nuclear

Solutions – Area Completions Project.

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Table 1: Mean ± SEM (followed by range, when provided in corresponding study) mercury (Hg) concentrations (mg/kg) by snake species and tissue type (blood, brain, egg, liver, kidney, muscle, whole body). Table is based on 23 published studies in the literature (year range 1980-2018). We performed a literature search for publications that focused on snakes, mercury, ecological risk assessments, and biomarkers. We searched for these papers in multiple databases including Web of Science and Google Scholar. We also used references cited in publications from our literature search to thoroughly search for relevant studies.

Wet/ Mean Hg Tissue Dry Species (mg/kg) type wt Location Citation

Agkistrodon 0.9 ± 0.1 Savannah River piscivorous Muscle W Site, SC, USA Burger et al. 2006 Savannah River A. piscivorous 0.1 ± 0.04 Blood W Site, SC, USA Burger et al. 2006 Longhorn Army Ammunitions A. piscivorous 0.211 Kidney W Plant, TX, USA Rainwater et al. 2005a Longhorn Army Ammunitions A. piscivorous 0.739 Liver W Plant, TX, USA Rainwater et al. 2005a Longhorn Army Ammunitions A. piscivorous 0.163 Tail tip W Plant, TX, USA Rainwater et al. 2005a Savannah River A. piscivorous 0.117 ± 0.09 Blood D Site, SC, USA Murray et al. 2010b Savannah River A. piscivorous 1.204 ± 0.475 Muscle D Site, SC, USA Murray et al. 2010b Savannah River A. piscivorous 0.145 ± 0.05 Blood D Site, SC, USA Murray et al. 2010b Savannah River A. piscivorous 1.103 ± 0.167 Muscle D Site, SC, USA Murray et al. 2010b Old River Slough, A. piscivorous 0.0135 Blood W TX, USA Clark et al. 2000a Caddo Lake, A. piscivorous 3.292 Muscle D LA/TX, USA Chumchal et al. 2011 Caddo Lake, A. piscivorous 7.456 Liver D LA/TX, USA Chumchal et al. 2011 Natrix maura 0.145 ± 0.071 Skin D Brenne, France Lemaire et al. 2018 N. maura 0.289 ± 0.218 Skin D Cébron, France Lemaire et al. 2018 N. maura 0.439 ± 0.261 Skin D Fontenille, France Lemaire et al. 2018 N. maura 0.183 ± 0.159 Skin D Moëze, France Lemaire et al. 2018 Tour du Valat, N. maura 0.220 ± 0.153 Skin D France Lemaire et al. 2018 Tour de Valat, N. maura 0.719 ± 0.267 Blood D France Lemaire et al. 2018 N. maura 0.438 ± 0.241 Skin D Ons, Spain Lemaire et al. 2018

Wet/ Mean Hg Tissue Dry Species (mg/kg) type wt Location Citation Upper 0.18 Whole Apalachiola Nerodia spp. (0.13-0.21) body W River, FL, USA Winger et al. 1984 Lower 0.29 Whole Apalachiola Nerodia spp. (0.17-0.38) body W River, FL, USA Winger et al. 1984 Nerodia Savannah River fasciata 0.6 ± 0.05 Muscle W Site, SC, USA Burger et al. 2006 Savannah River N. fasciata 0.4 ± 0.05 Blood W Site, SC, USA Burger et al. 2006 Savannah River N. fasciata 0.4 ± 0.047 Blood W Site, SC, USA Burger et al. 2007 Savannah River N. fasciata 0.192 ± 0.014 Tail tip W Site, SC, USA Burger et al. 2007 Savannah River N. fasciata 0.379 ± 0.057 Blood D Site, SC, USA Murray et al. 2010b Savannah River N. fasciata 0.538 ± 0.047 Muscle D Site, SC, USA Murray et al. 2010b Savannah River N. fasciata 0.460 ± 0.084 Blood D Site, SC, USA Murray et al. 2010b Savannah River N. fasciata 0.860 ± 0.081 Muscle D Site, SC, USA Murray et al. 2010b Nerodia Savannah River floridana 0.327 ± 0.028 Tail tip D Site, SC, USA Russell et al. 2016 Nerodia Private Lake, TX, rhombifer 0.0613 Blood W USA Clark et al. 2000a Old River Slough, N. rhombifer 0.146 Blood W TX, USA Clark et al. 2000a Nerodia Walland, TN, sipedon 0.061 ± 0.001 Egg W USA Burger et al. 2005 Walland, TN, N. sipedon 0.289 ± 0.133 Testes W USA Burger et al. 2005 Walland, TN, N. sipedon 0.423 ± 0.028 Skin W USA Burger et al. 2005 1.121 ± 0.173 (0.209 – Oak Ridge, TN, N. sipedon 3.505) Kidney W USA Campbell et al. 2005 1.403 ± 0.214 (0.220 – Oak Ridge, TN, N. sipedon 3.795) Liver W USA Campbell et al. 2005 0.582 ± 0.047 (0.051 – Oak Ridge, TN, N. sipedon 1.015) Muscle W USA Campbell et al. 2005 0.372 ± 0.0461 Oak Ridge, TN, N. sipedon (0.141-0.816) Blood W USA Campbell et al. 2005 0.382 ± 0.032 (0.042 – Walland, TN, N. sipedon 0.784) Kidney W USA Campbell et al. 2005 0.75 ± 0.076 (0.090 – Walland, TN, N. sipedon 1.161) Liver W USA Campbell et al. 2005

Wet/ Mean Hg Tissue Dry Species (mg/kg) type wt Location Citation 0.741 ± 0.049 (0.224 – Walland, TN, N. sipedon 1.630) Muscle W USA Campbell et al. 2005 0.436 ± 0.064 (0.009 – Walland, TN, N. sipedon 1.420) Blood W USA Campbell et al. 2005 Whole Lake Michigan, N. sipedon 0.45 body W MI, USA Heinz et al. 1980 Raritan Canal, NJ, N. sipedon 0.128 ± 0.026 Blood W USA Burger et al. 2007 Raritan Canal, NJ, N. sipedon 0.136 ± 0.039 Kidney W USA Burger et al. 2007 Raritan Canal, NJ, N. sipedon 0.303 ± 0.091 Liver W USA Burger et al. 2007 Raritan Canal, NJ, N. sipedon 0.357 ± 0.049 Muscle W USA Burger et al. 2007 Raritan Canal, NJ, N. sipedon 0.159 ± 0.023 Skin W USA Burger et al. 2007 Oak Ridge, TN, N. sipedon 0.417 ± 0.042 Blood W USA Burger et al. 2007 Oak Ridge, TN, N. sipedon 0.671 ± 0.038 Muscle W USA Burger et al. 2007 Oak Ridge, TN, N. sipedon 1.024 ± 0.115 Liver W USA Burger et al. 2007 0.29 ± 0.01 Middle River, N. sipedon (0.23-0.37) Tail tip D VA, USA Drewett et al. 2013 0.49 ± 0.07 South River, VA, N. sipedon (0.16-0.92) Tail tip D USA Drewett et al. 2013 4.85 ± 0.29 South River, VA, N. sipedon (2.25-13.84) Tail tip D USA Drewett et al. 2013 2.24 ± 0.42 N. sipedon (0.03-7.04) Blood W Virginia, USA Drewett et al. 2013 0.2 ± 0.11 Whole Middle River, N. sipedon (0.06 – 1.09) body D VA, USA Chin et al. 2013b 3.42 ± 0.45 Whole South River, VA, N. sipedon (1.08 – 10.10) body D USA Chin et al. 2013b 0.0037 ± N. sipedon 0.0001 Fecal W MTSU, TN, USA Cusaac et al. 2016c 0.0070 ± N. sipedon 0.001 Fecal W MTSU, TN, USA Cusaac et al. 2016c

N. sipedon 2.87 ± 1.53 Fecal W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 0.112 ± 0.019 Muscle W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 0.199 ± 0.047 Muscle W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 13.2 ± 2.58 Muscle W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 0.116 ± 0.023 Liver W MTSU, TN, USA Cusaac et al. 2016c 0.0935 ± N. sipedon 0.021 Liver W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 13.5 ± 8.16 Liver W MTSU, TN, USA Cusaac et al. 2016c

Wet/ Mean Hg Tissue Dry Species (mg/kg) type wt Location Citation N. sipedon 0.286 ± 0.059 Skin W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 0.375 ± 0.032 Skin W MTSU, TN, USA Cusaac et al. 2016c N. sipedon 95.4 ± 21.1 Skin W MTSU, TN, USA Cusaac et al. 2016c Nerodia Savannah River taxispilota 0.7 ± 0.1 Muscle W Site, SC, USA Burger et al. 2006 Savannah River N. taxispilota 0.7 ± 0.15 Blood W Site, SC, USA Burger et al. 2006 Savannah River N. taxispilota 0.611 ± 0.180 Blood D Site, SC, USA Murray et al. 2010b Savannah River N. taxispilota 0.644 ± 0.100 Muscle D Site, SC, USA Murray et al. 2010b Savannah River N. taxispilota 0.923 ± 0.005 Blood D Site, SC, USA Murray et al. 2010b Savannah River N. taxispilota 0.971 ± 0.179 Muscle D Site, SC, USA Murray et al. 2010b Pantherophis (Elaphe) Virginia Tech, Jones and Holladay guttata 0.403 ± 0.089 Skin D VA, USA 2006c Pantherophis (Elaphe) 0.26 ± 0.09 South River, VA, obsoleta (0.05-0.89) Tail tip D USA Drewett et al. 2013 Pituophis Whole melanoleucus 0.13 ± 0.027 body D New Jersey, USA Burger 1992a P. melanoleucus 0.28 ± 0.047 Skin D New Jersey, USA Burger 1992a P. melanoleucus 0.46 ± 0.078 Liver W New Jersey, USA Burger et al. 2017 P. melanoleucus 0.12 ± 0.035 Kidney W New Jersey, USA Burger et al. 2017 P. melanoleucus 0.76 ± 0.012 Muscle W New Jersey, USA Burger et al. 2017 P. melanoleucus 0.42 ± 0.007 Skin W New Jersey, USA Burger et al. 2017 P. melanoleucus 0.41 ± 0.009 Heart W New Jersey, USA Burger et al. 2017 P. melanoleucus 0.27 ± 0.005 Blood W New Jersey, USA Burger et al. 2017 Ptyas dhumnades 9.77 ± 0.68 Tail tip D Guizhou, China Abeysinghe et al. 2017

P. dhumnades 2.36 ± 0.175 Tail tip D Guizhou, China Abeysinghe et al. 2017 Python molurus 3.6 Everglades, FL, bivittatus (0.14 – 10.75) Muscle W USA Axelrad et al. 2011 Regina 4.59 ± 0.38 South River, VA, septemvittata (1.90-6.00) Tail tip D USA Drewett et al. 2013 Thamnophis 0.571 ± 0.108 Sacramento gigas (0.08 – 1.64) Liver W Valley, CA, USA Wylie et al. 2009 0.077 ± 0.010 Sacramento T. gigas (0.01 – 0.18) Brain W Valley, CA, USA Wylie et al. 2009

Wet/ Mean Hg Tissue Dry Species (mg/kg) type wt Location Citation 0.083 ± 0.019 Sacramento T. gigas (0.02 – 0.32) Tail tip W Valley, CA, USA Wylie et al. 2009 Thamnophis Whole Mobile-Tensaw sauritus 0.58 ± 0.12 body D River, AL, USA Albrecht et al. 2007 Lake Michigan Thamnophis Whole Spider Island, sirtalis 0.303 body W USA Heinz et al. 1980 1.28 ± 0.32 South River, VA, T. sirtalis (0.08-2.53) Tail tip D USA Drewett et al. 2013 Unknown 5.41 ± 2.28 Kenting National spp. (0.16 – 23.9) Muscle D Park, Taiwan Hsu et al. 2006 a – Geometric means b – Dry vs. wet weight not explicitly listed c – Controlled exposure experiment

CHAPTER 3

MULTI-DECADAL TRENDS IN MERCURY AND METHYLMERCURY

CONCENTRATIONS IN THE BROWN WATERSNAKE (NERODIA TAXISPILOTA)2

2 Haskins, D.L., M.K. Brown, C. Qin, X. Xu, M.A. Pilgrim, and T.D. Tuberville. In revision to Environmental Pollution.

Abstract

Mercury (Hg) is an environmental contaminant that poses a threat to aquatic systems

globally. Temporal evaluations of Hg contamination have increased in recent years, with studies focusing on how anthropogenic activities impact Hg bioavailability in a variety of aquatic systems. While it is common for these studies and ecological risk assessments to evaluate Hg bioaccumulation and effects in wildlife, there is a paucity of information regarding Hg dynamics in reptiles. The goal of this study was to investigate temporal patterns in total mercury (THg) and methylmercury (MeHg) concentrations across a 36- year period, as well as evaluate relationships among and between destructive (kidney, liver, muscle) and non-destructive (blood, tail) tissue types in a common watersnake species. To accomplish this, we measured THg and MeHg concentrations in multiple tissues from brown watersnakes (Nerodia taxispilota) collected from Steel Creek on the

Savannah River Site (SRS; Aiken, SC, USA) from two time periods (1983 – 1986 and

2019). We found significant and positive relationships between tail tips and destructive tissues. In both time periods, THg concentrations varied significantly by tissue type, and destructive tissues exhibited higher but predictable THg values relative to tail tissue.

Methylmercury concentrations did not differ among tissues from the 1980s but was significantly higher in muscle compared to other tissues from snakes collected in 2019.

Percent MeHg of THg in N. taxispilota tissues mirrored patterns reported in other reptiles, although the range of % MeHg in liver and kidney differed between time periods. Both THg and MeHg concentrations in N. taxispilota declined significantly from the 1980s to 2019, with average values 1.6 to 4-fold lower in contemporary samples.

Overall, our data add further evidence to the utility of watersnakes to monitor Hg

pollution in aquatic environments and suggest attenuation of this contaminant in watersnakes in our study system.

Introduction

Mercury (Hg) is a ubiquitous heavy metal that enters the environment through a variety of processes. Both natural and anthropogenic processes contribute to the global

Hg budget, however, human activities have led to Hg levels 5.5 – 7.6 times higher than natural background levels (Amos et al. 2013). Once Hg enters the environment, its inorganic forms can be transformed into bioavailable methylmercury (MeHg), which readily bioaccumulates and biomagnifies in food webs. The impacts of Hg exposure in vertebrates are well-documented and varied, with reports of negative effects on endocrine, immune, neurological, and reproductive systems (Wolfe et al. 1998; Tan et al.

2009; Chételat et al. 2020). Human populations and wildlife that consume fish as an integral part of their diet are at high risk for MeHg exposure (Chan et al. 2003; Jackson et al., 2016).

In wildlife, assimilation rates for MeHg and inorganic Hg can vary considerably depending on species (Oliveira Ribeiro et al. 1999; Pickhardt et al. 2006; Chumchal et al.

2011). Methylmercury readily binds to sulfur-containing amino acids and sulfhydryl groups, allowing for its efficient bioaccumulation in skeletal muscle and keratinized tissues (Newman 2014). It is valuable to know what proportion of total Hg (THg) in wildlife tissues is represented by MeHg, as MeHg is much more toxic relative to its inorganic form (Newman 2014). Mercury accumulation trends in vertebrates reveal significant variation across taxa in THg and MeHg tissue distribution (Chumchal et al.

2011). However, relative to birds, fish, and mammals there is a paucity of data available

regarding Hg speciation in tissues collected from reptiles (Scheuhammer et al. 2007),

especially in snakes (Haskins et al. 2019). To date, few studies have measured multiple

forms of Hg in snake tissues, and these studies were limited by sample sizes and types of

tissues examined (Chumchal et al. 2011; Chin et al. 2013b; Drewett et al. 2013). Non-

destructive tissue samples (e.g., blood, tail, dermis) are increasingly being used in reptile

ecotoxicology to effectively predict contaminant concentrations in major organs

(Hopkins et al. 2001; Grillitsch and Schiesari, 2010; Faust et al. 2014; Haskins et al.

2017). However, these predictive equations rarely consider MeHg, as the quantification

of MeHg is expensive and labor intensive. Overall, this limits our ability to effectively

estimate risk for these species. Furthering our understanding of Hg dynamics in reptiles

would be valuable to risk assessors, as these species can accumulate high levels of Hg in

contaminated environments (Drewett et al. 2013; Schneider et al. 2013).

The implementation of longitudinal studies designed to monitor environmental

contaminants are powerful tools to predict exposure and risk in humans and wildlife.

These studies are rare and some of the best examples are focused on fish (Paller and

Littrell 2007; Pelletier et al. 2017). In recent years, researchers have turned to archived

specimens or long-term datasets to examine temporal trends in environmental Hg

(Schmitt et al. 2018). Such studies have examined temporal trends in Hg and MeHg in a

variety of samples, including bird feathers (Vo et al. 2011; Hebert and Popp 2018),

mammal hair (Kumar et al. 2018), and soil sediments (Muir et al., 2009; Sharley et al.

2016). While temporal Hg data are available for a variety of taxa, we are not aware of

any studies that examine long-term Hg trends in snakes. As a group, reptiles have historically been overlooked in ecotoxicological studies (Grillitsch and Schiesari 2010;

Lemaire et al. 2018), despite being important components of ecosystems. Reptiles, such as crocodilians and snakes, are long-lived and can be top predators within their respective

food webs (Hopkins 2006). Thus, they play an integral role in the transfer of contaminants such as Hg (Campbell and Campbell 2001; Haskins et al. 2019).

The objectives of this study were three-fold. First, we used historical and contemporary samples to evaluate correlational relationships in THg among non- destructive (blood and tail tips) and destructive (kidney, liver, and muscle) tissues in the brown watersnake (Nerodia taxispilota). Secondly, we compared THg content among tissues and quantified MeHg in destructive tissues from N. taxispilota to determine Hg speciation trends. Finally, we compared all Hg concentrations between sampling periods

(1980s and 2019) to investigate a potential temporal trend in Hg burdens in N. taxispilota.

We predicted that (1) THg in tail tissues would be strongly correlated with THg in all destructive tissue types, (2) Hg speciation patterns would resemble the limited data available in reptiles, with the highest Hg concentrations being present in liver (THg) and muscle (MeHg) tissues, and (3) all Hg concentrations from historical snakes would be significantly higher than those in contemporary snakes. Overall, we aim to provide novel ecotoxicological data relevant to risk assessments that incorporate reptile species.

Methods

Study species

Brown watersnakes (Nerodia taxispilota) are large-bodied, obligate piscivores that can be found in high densities in riverine and stream ecosystems of the Coastal Plain of the southeastern United States (Mills 2004). Nerodia taxispilota consume a variety of fish species, but once snakes reach 600 mm in size, individuals exhibit an ontogenetic

diet shift to an almost exclusive catfish diet (Mills 2002; 2004). Like many other watersnakes (Nerodia spp.), N. taxispilota exhibit female-biased sexual dimorphism in

body size and high levels of philopatry (Mills et al. 1995; 2004), the latter making them

effective bioindicators of local contamination (Haskins et al., in press; Lettoof et al.

2020).

Study area

Our study was conducted on the Savannah River Site (SRS), an 800km2

Department of Energy (DOE)-operated superfund facility located in Aiken, Barnwell and

Allendale counties in west-central South Carolina. The SRS is a former nuclear weapons

production facility, and a variety of activities onsite led to the accidental release of contaminants, including Hg. A variety of additional anthropogenic sources contribute to

Hg contamination at this site, such as industrial activities upstream of the SRS (e.g., a now inactive chlor-alkali facility in Augusta, GA – decommissioned in 2012), formerly active coal combustion facilities and aquatic basins associated with SRS operations, and atmospheric deposition. Water was also drawn from the Savannah River downstream of the then-active chloro-alkali plant and used as a non-contact coolant for multiple reactors across the SRS, leading to an increase in Hg in associated tributaries on the SRS (Kvartek et al. 1994). The most recent data from the National Atmospheric Deposition Program

(NRSP-3) reports an average of 8.64 ng/L Hg deposition for the Savannah River Site area

(data from 2016 – 2017, Barnwell County, 33.2450, -81.6505; NADP 2019). The main source of contemporary Hg loads in the SRS area is atmospheric deposition (~ 99% of

Hg loading; USEPA 2000); recent research demonstrates that there has been a significant

decrease in atmospheric deposition of Hg in the eastern United States relative to other

regions (Olson et al. 2020).

Our research was conducted in Steel Creek, a 20-km long stream that arises in the

Aiken Plateau and is a tributary of the Savannah River (Figure 1). Steel Creek, along

with two other streams on the SRS, drain a 290-km2 watershed in Barnwell County,

South Carolina into the Savannah River. Steel Creek also receives approximately 20% of

its flow from Meyers Branch, a relatively unimpacted stream system on the SRS. The

Steel Creek system received thermal discharge from nuclear reactors from 1954 – 1968

(Kilgo and Blake 2005). Elevated water flow and temperatures destroyed a significant portion of the original water tupelo (Nyssa aquatica) - bald cypress (Taxodium distichum) forests in the area (Sharitz et al. 1974). The upper third of Steel Creek was also significantly altered by the construction of L-Lake (1984 – 1985) and its associated dam

~ 14.5 km south of its headwaters (Ziegler et al. 1985; Bowers et al. 1997).

Snake collections and sample processing

Historical samples were obtained from snakes (n = 18) collected from the Steel

Creek system in the 1980s (1983 – 1986; Figure 1) and stored in the freezer until dissection in 2015. Prior to dissection, we thawed, measured (snout-vent length [SVL] to the nearest 1 mm), and weighed (to the nearest 1 g) all snakes. We also recorded sex for each snake. We then dissected liver, kidney, muscle, and tail tips (~10 mm in length) tissues from each snake for THg and MeHg analysis.

Contemporary sampling was performed in March – June 2019. We collected all snakes (n = 21) by hand and recorded morphological measurements (as described above) for each snake. From each snake, we collected the distal 10 mm of the tail and a whole

blood sample (≤ 1% of the snake’s weight) from the caudal vein with a 25-gauge needle

for subsequent THg quantification. Across both sampling periods, for blood and tail tissues, we only quantified THg concentrations. We permanently marked all snakes that were not sacrificed with a passive integrated transponder (PIT) tag (AVID, Norco, CA,

USA; Camper and Dixon 1988; Gibbons and Andrews 2004). We humanely dispatched a

subset (n = 10) of sampled snakes following UGA IACUC-approved protocols (AUP#

A2019 01-012-Y2-A3) and in accordance with Scientific Collection Permits issued by

the Georgia Department of Natural Resources (CN#1000540516) and the South Carolina

Department of Natural Resources (#SC-08-2019). Because historical sampling focused

on the collection of female snakes, we only sacrificed female contemporary snakes of

similar size for in-depth temporal comparisons. We then collected liver, kidney, and

muscle tissues from contemporary snakes for THg and MeHg analysis.

Total mercury analyses

We lyophilized and homogenized blood, liver, kidney, and muscle prior to THg

analysis. Tail tips were oven-dried for 24 hrs at 50°C and run whole. We analyzed all samples using a DMA-80 (Milestone Inc., Shelton, Connecticut, USA), which uses thermal decompositions, catalytic conversion, amalgamation, and cold-vapor atomic absorption spectrophotometry for THg analysis. Our THg analysis used a modification of the USEPA method 7473 (USEPA 1998). We analyzed samples in batches containing a blank and standard reference material of known concentration (National Research

Council of Canada). We ran duplicates every 12 samples to ensure consistency during

THg analysis. Average percent recoveries (% ± 1 SE) of certified reference materials were 98.30 ± 2.03 and 112.70 ± 2.18 for PACS-2 and TORT-3 (both n = 13),

respectively. We report all THg data (excluding whole blood) in mg/kg on a dry weight basis (wet weight THg and moisture content for both historical and contemporary snake tissues are provided in Appendix 3A Table 1 [S1]).

Methylmercury analyses

We analyzed kidney, liver, and muscle tissues for MeHg using a MERX

Automated Methylmercury System (Brooks Rand, Seattle, Washington, USA). We did not perform MeHg analyses on tail tips, as prior research in Nerodia spp. reported that

87.1 – 95% of THg in tail tissues consists of MeHg (Drewett et al. 2013). Prior to analysis, we digested muscle samples using an alkaline solution (25% [w/v] KOH in methanol) at 75C in the oven for 3 hrs (Liang et al. 1994a). We buffered aliquots of prepared muscle samples with sodium acetate. Next, we ethylated these prepared muscle samples with sodium tetraethylborate (Liang et al. 1994a; Liang et al. 1994b). We quantified MeHg via gas chromatographic separation and pyrolysis following cold vapor atomic fluorescence. We used a liquid MeHg standard CH3HgCl (Brooks Rand, Seattle,

Washington USA) to establish calibration curves for each analytical session. We quantified precision and accuracy of our analysis using blanks, sample replicates, and standard reference materials (TORT-3, National Research Council of Canada; Ottawa,

Canada). Mean percent recovery was 98% ± 0.02 (n = 13) for TORT-3. Relative percent difference for replicated samples averaged 3% ± 0.01 (n = 9). The method detection limit was 0.013 ng/g. We report all MeHg data in mg/kg on a dry weight basis.

Statistics

For statistical comparisons between sampling periods, we placed snakes from historical sampling (1983 – 1986, n = 18) into one group for statistical comparisons to

contemporary samples (2019, n = 21). During dissections, we did not measure the SVL of

seven individuals from the 1980s period. Thus, we used a linear regression approach to

predict the SVL for these individuals based on their weight using a long-term mark- recapture database of morphometric measurements for female N. taxispilota collected on

the SRS (Supplemental Figure 1; n = 1088, r2 = 0.968, p < 0.001; 1967 – 2019; Mills

and Haskins, unpublished data).

We analyzed all data using RStudio (R Core Team 2020). We log-transformed data if they did not meet assumptions of normality or homogeneity of variances using the

Shapiro-Wilk and Levene statistics, respectively. We used an analysis of covariance

(ANCOVA) to evaluate differences in THg and MeHg concentrations in tissues

(excluding whole blood) between time periods (1980s vs. 2019), as well as determine

differences in THg or MeHg concentrations among tissue types. Time period or tissue type was used as a main effect in ANCOVA models and SVL was used as a covariate to determine the potential effect of snake size on contaminant concentrations. For our

ANCOVA model that considered tail THg concentrations, we included all individuals (n

= 38) sampled from both time periods (including 6 males and 5 immature females in

2019 dataset) because the relationship (i.e., slope) between SVL and tail was not predicted to change over time. If ANCOVA models were significant, we used Tukey

HSD tests for post-hoc comparisons. Effect sizes (partial eta-squared) and 90% confidence intervals were calculated for each ANCOVA to examine the proportion of variance explained by the fixed effect in our models (Richardson 2011). If data did not fit assumptions of normality or homogeneity of variances after transformations, we used

Kruskal-Wallis H tests. We followed any significant Kruskal-Wallis analyses with

Dunn’s post-hoc test with Bonferroni-corrected significance values. We evaluated correlations in THg between non-destructive (blood, tail) and destructive (kidney, liver, muscle) tissue types using simple linear regression. In addition, we used simple linear regression to evaluate correlations between MeHg and THg in kidney, liver, and muscle tissues.

Results

We sampled a total of 39 N. taxispilota – 18 from the 1980s and 21 from 2019.

Average SVL for snakes collected from the 1980s was 788 ± 44 mm (mean ± 1 SE; range

of 490 – 1178 mm). Mean SVL for snakes collected in 2019 was 784 ± 27 mm (565 –

1030 mm). Snake SVL did not vary significantly between time periods (t-test; t = 0.088,

p = 0.93). Sample sizes for each tissue type varied in the snakes collected in the 1980s, as we were not always able to collect each target tissue.

Total Hg concentrations ranged from 0.06 – 50.36 mg/kg across both time periods

and all tissue types, with the highest THg levels in liver, followed by kidney, muscle, tail,

and blood (Table 1). Concentrations of MeHg ranged from 0.19 – 12.76 mg/kg across

both sampling time periods and all tissue types (kidney, liver, and muscle tissues, Table

2).

THg correlations among tissue types

We found significant positive relationships between THg concentrations

measured in tail and destructive tissue types (Figure 2). Specifically, we observed that

THg concentrations in tail were significantly correlated with THg in kidney (r2 = 0.73, p

< 0.0001), liver (r2 = 0.85, p < 0.0001), and muscle (r2 = 0.82, p < 0.0001) tissues.

Similarly, we also found strong, significant, and positive correlations among all

destructive tissue types (Figure 3). Liver THg was positively associated with THg in

2 kidney (rs = 0.82, p < 0.0001) and muscle (r = 0.86, p < 0.0001). Kidney THg was also positively associated with muscle THg (r2 = 0.77, p < 0.0001). For snakes in 2019, we

calculated correlations between blood THg and other tissue types. We found significant

and positive correlations between blood THg and tail (r2 = 0.77, p = 0.007, n = 19),

kidney (r2 = 0.77, p = 0.003, n = 8), liver (r2 = 0.76, p = 0.003, n = 8), and muscle (r2 =

0.86, p < 0.001, n = 8) tissues. In addition, snake SVL was a significant covariate in the

2 2 liver (F1,25 = 5.26, r = 0.39, p = 0.03) and tail (F1,35 = 7.73, r = 0.56, p = 0.009) THg

ANCOVA models, explaining 39 and 56% of variation in liver and tail mercury,

respectively (Figure 4).

THg and MeHg: Speciation and temporal patterns

ANCOVA analyses revealed significant differences in THg concentrations from

liver (F1,25 = 14.04, p < 0.001), muscle (F1,25 = 9.40, p = 0.005), and tail (F1,24 = 16.12, p

< 0.001) in N. taxispilota from the 1980s relative to 2019 individuals (Table 1). We found that kidney THg concentrations did not differ significantly between time periods

(F1,24 = 3.57, p = 0.07).

Methylmercury was strongly correlated with THg concentrations in kidney (r2 =

0.941, p < 0.001), liver (r2 = 0.897, p < 0.001), and muscle tissues (r2 = 0.941, p < 0.001;

Figure 5). Our ANCOVA analyses found that MeHg concentrations in all tissues were

significantly higher in snakes captured in the 1980s relative to 2019 (kidney: F1,24 = 6.13, p = 0.021; liver: F1,25 = 17.51, p < 0.001; muscle: F1,25 = 10.32, p = 0.004; Table 2). In

contrast to our THg analyses, SVL was not a significant covariate in the any of the MeHg

models (kidney: F1,24 = 1.61, p = 0.217; liver: F1,25 = 2.87, p = 0.103; muscle: F1,25 = 1.46,

p = 0.238). The percentage of MeHg in THg in tissues varied considerably by tissue type, with the highest average percentage found in muscle (79.4 ± 1.7%, n = 28). Compared to muscle MeHg, the average percentages of MeHg in kidney (56.9 ± 2.5%, n = 27) and liver (46.4 ± 2.8%, n = 28) tissues were much lower. Our analyses also found that percentage MeHg in snake tissues did not significantly differ based on time period (t ≤

1.22, p ≥ 0.233 for all tissues).

Because THg and MeHg concentrations in tissues varied by time period, we performed separate ANCOVA analyses for each time period to evaluate differences in Hg among tissue types. However, differences in THg distribution among tissue types remained stable between the two time periods. In both sampling periods, THg

2 significantly varied by tissue type (1980s: X = 29.81, p < 0.0001; 2019: F3,35 = 2.86, p <

0.0001), was significantly lower in tail tissues relative to destructive tissues (both time

periods: all p < 0.0001), and did not vary significantly among kidney, liver, and muscle

(1980s: all p ≥ 0.07; 2019: all p ≥ 0.152). Methylmercury did not differ significantly

among destructive tissues in snakes captured in the 1980s (X2 = 5.28, p = 0.070).

However, MeHg concentrations in 2019 snakes significantly differed among tissue types

(F2,26 = 6.73, p = 0.004), with significantly higher MeHg concentrations in muscle

relative to liver and kidney tissues (both p ≤ 0.028).

Discussions

This study characterized both THg and MeHg content in multiple target tissues

from a watersnake species on a DOE Superfund Site over multiple decades (1980s –

2019). To our knowledge, this is the first study to examine long-term temporal trends (>

35 years) in Hg contamination using a reptile species as a bioindicator. Non-destructive

tissues were effective at predicting THg concentrations in major organs in N. taxispilota,

similar to other studies in aquatic snakes (Rainwater et al. 2005; Wylie et al. 2009).

Snake size was an important predictor of liver and tail THg concentrations, with higher

THg concentrations predicted in larger individuals. This study also represents the most

in-depth examination of Hg speciation (THg and MeHg) in a snake species to date, and

distribution of Hg among snake tissues resembled trends reported in other reptiles

(Schneider et al. 2013). As expected, all Hg concentrations were significantly elevated in

snakes from the 1980s relative to those sampled in 2019. Among all tissues, average

concentrations of Hg were 1.6 – 3.3 (THg) and 1.7 – 4.2 (MeHg) times higher in

historical snakes compared to contemporary snakes.

Tissue Hg correlations

As many reptile species are declining due to multiple anthropogenic causes (e.g.,

invasive species, habitat loss and degradation, pollution; Gibbons et al. 2000; Falaschi et

al. 2019), it is necessary for researchers to be able to effectively monitor contaminant

concentrations without having appreciable negative impacts on populations. To improve

environmental monitoring efforts in reptiles, several studies have examined correlations between non-destructive tissues and major organs in snakes (Burger 1992; Burger et al.

2005; 2007; 2017; Rainwater et al. 2005; Wylie et al. 2009). Developing these models

may allow other investigators to estimate internal tissue Hg concentrations without

sacrificing the animal. However, species-specific accumulation patterns may require

establishing predictive relationships among tissues for a target species (Pfleeger et al.

2016). Positive correlations between tail and destructive tissue types have been verified in other snake species residing in aquatic environments, including cottonmouths

(Agkistrodon piscivorous; Rainwater et al. 2005) and giant garter snakes (Thamnophis gigas; Wylie et al. 2009). In the present study, we observed significant and positive relationships between non-destructive tissues and kidney, liver, and muscle tissues in brown watersnakes (N. taxispilota). In fact, correlations between tail and major organs from our study were similar to or stronger than those reported in other aquatic snake species (Rainwater et al. 2005; Wylie et al. 2009). The observed differences in the strength of correlations among species could be due to a variety of factors, such as inherent species-specific life history traits (e.g., consumption patterns and diet), season, and sex. For example, Rainwater et al. (2005) reported that Hg concentrations in male cottonmouths were higher than those in females and that correlational relationships (tail and liver) were much stronger in males even after accounting for size. We did not measure Hg concentrations among all tissues in male N. taxispilota; thus, it was not possible for us to make sex-specific comparisons in this study. However, across both time periods, we observed a significant relationship between snake size and THg content for liver and tail tissues, similar to published data available for snakes (Rainwater et al. 2005;

Wylie et al. 2009; Drewett et al. 2013; Rumbold and Bartoszek 2019; Lettoof et al. 2020;

Haskins et al., in press).

Mercury distribution and speciation among tissues

Accumulation of THg in N. taxispilota tissues was similar to patterns reported in

other reptiles, including the little data available for snakes (Burger et al. 2005; 2007;

2017; Campbell et al. 2005; Rainwater et al. 2005; Wylie et al. 2009). A recent review of

Hg contamination studies in reptiles found that average THg concentrations are typically

highest in liver, followed by kidney, skin, muscle, and blood tissues (Schneider et al.

2013). Our THg results from snakes collected in the 1980s conform to these general

patterns, as THg concentrations in N. taxispilota were highest in liver, followed by

kidney, muscle, tail, and blood tissues. In contrast, the highest average THg

concentrations in snakes collected from 2019 were in muscle, followed by liver, kidney,

tail, and blood tissues. The differences observed in Hg distribution between liver and muscle tissues between time periods likely reflects temporal differences in bioavailability

of Hg (i.e., higher Hg contamination in the 1980s), as the kidney and liver are known to

be important sites of Hg detoxification in vertebrates, preventing high concentrations of

Hg from reaching other sensitive tissues; in addition, muscle is the major storage organ

for Hg when there is not a point source and trophic bioaccumulation is the primary

exposure pathway (Eagles-Smith et al. 2009; Grillitsch and Schiesari 2010; Evans et al.

2016; Chételat et al. 2020).

The physiological processes that control MeHg dynamics in vertebrates are well-

described in other taxa. Laboratory dosing experiments and toxicokinetic models

demonstrate how Hg and MeHg are absorbed, distributed, transferred, and eliminated in

fish and mammals (Rodgers and Beamish 1982; Nielsen and Andersen 1991; Dutton and

Fisher 2011). However, much less is known about MeHg toxicokinetics in reptiles,

though several studies have directly measured MeHg concentrations in this group.

Methylmercury concentrations have been reported in non-destructive tissues (e.g., blood,

carapace, scutes, tail tips; Bergeron et al. 2007; Blanvillain et al. 2007; Vieira et al. 2011;

Drewett et al. 2013; Rodriguez et al. 2019) and major organs (e.g., kidney, liver, and

muscle; Storelli et al. 1998; Chumchal et al. 2011; Perrault 2014; Eggins et al. 2015; Ng

et al. 2018; Rodriguez et al. 2020) of reptiles. As in other taxa, MeHg is the dominant

form of Hg in reptile muscle tissues (70 – 93% of THg). Percent MeHg of THg in reptile

liver tissues are more variable, ranging from 3.2 – 46%. To our knowledge, only one

study measured multiple forms of Hg in kidney tissues of a reptile, reporting a lower %

MeHg relative to other major organs sampled (8.8%, Rodriguez et al. 2020). In the

current study, average % MeHg in N. taxispilota tissues were highest in muscle (77.6%

from 1980s samples and 80.4% from 2019 samples), followed by kidney (52.0% and

59.7%) and liver (46.3% and 46.4%). Interestingly, as mentioned earlier, highest MeHg

concentrations in N. taxispilota from the 1980s were in the liver, whereas the highest

MeHg values in snakes from 2019 were in muscle tissue. In addition, the range of %

MeHg in liver tissue was much larger in snakes from the 1980s (19.7 – 90.3%) relative to

snakes from 2019 (31.2 – 65%). These results suggest that piscivorous watersnakes, like

waterbirds (Eagles-Smith et al. 2009), may use the liver as an important site of

demethylation of MeHg, but further studies are necessary to confirm this.

Temporal trends in Hg at Steel Creek

Snakes collected from the Steel Creek area in the early 1980s exhibited

significantly higher THg and MeHg concentrations in all tissues (excluding THg in

kidney) compared to individuals sampled in 2019. The higher Hg concentrations in the

1980s snakes are likely due to greater amounts of Hg contamination in the Savannah

River watershed during the mid-twentieth century compared to present. We suggest that

the declines in Hg concentrations observed in contemporary N. taxispilota are a result of

reduced Hg inputs into the Savannah River and the SRS area by a now inactive chlor-

alkali plant in Augusta, GA, which – between 1965 and 1970 – discharged > 8,000 kg of

Hg into the Savannah River upstream of the SRS (Kvartek et al. 1994). A similar decline

in Hg concentrations between 1971 – 2004 for fish collected from the Savannah River

adjacent to the SRS was reported by Paller and Littrell (2007), who also attributed the trend to significant reductions in Hg pollution from the chlor-alkali plant. However, the same study also determined that between the early 1990s and 2005, fish Hg concentrations steadily increased back to historical levels, contrasting with the trend we observed in N. taxispilota. However, their data combined Hg data patterns in fish from the entirety of the SRS and the adjacent Savannah River, while our data is from one site on the SRS (Steel Creek). Furthermore, a recent study in N. taxispilota along the SRS

lends support to the value of this species as a bioindicator for local Hg contamination, as

Hg concentrations measured in snakes from multiple sampling sites mirrored those in fish

sampled at the same locations in the Savannah River (Haskins et al., in press).

Nevertheless, a variety of factors could be responsible for the observed differences in

long-term temporal Hg trends when comparing N. taxispilota collected from Steel Creek

to fish sampled across the entire portion of the Savannah River adjacent to the SRS. For

example, differences in movement patterns and home range size (Mills et al. 1995),

fluctuations in river or local watershed conditions (e.g., drought, flow rates), and the

construction of L-Lake and the associated downstream release of contaminants within

sediments could all impact Hg bioaccumulation in these species. In addition, the use of

archived specimens for the earlier sampling period comes with limitations, especially in

regard to sample size, but provide important historical data that would not otherwise be

available. Thus, as Paller and Littrell (2007) stated in their temporal study, our data

remain valuable due to their uniqueness.

Mercury levels in snakes and potential health impacts

Little is known about how Hg exposure may impact reptile physiology; however, recent studies demonstrate that snakes may be more resilient to Hg compared to other taxa (Bazar 2002; Chin et al. 2013b; Hopkins et al. 2013a; Hopkins et al. 2013b; Cusaac et al. 2016). The only study available to date that reported negative effects of Hg in snakes found that striking efficiency in newborn northern watersnakes (Nerodia sipedon) negatively correlated with Hg concentrations (Chin et al. 2013a). Nerodia sipedon mothers from the same population had mean tail THg concentrations > 4-fold higher

(5.78 ± 0.55 mg/kg dw) than those in N. taxispilota in our study collected from the 1980s

(1.33 ± 0.17 mg/kg dw) and exhibited no adverse effects on reproduction (Chin et al.

2013b). The Hg concentrations measured in N. taxispilota from Steel Creek are well below the values reported to cause sublethal effects in N. sipedon but still provide novel data that will be useful for informing risk assessments. Overall, there are a lack of studies available that examine how physiological systems (e.g., endocrine, immune, neurological) in snakes may be affected by Hg exposure, and further research is necessary to determine risk thresholds for Hg in these species.

Conclusions

To our knowledge, this study represents the first long-term examination (i.e.,

across multiple decades) of contaminant concentrations in a snake species. Our dataset

characterizes THg and MeHg dynamics in a common, piscivorous watersnake on a DOE

facility across a 36-year period. Collectively, average Hg values were 1.6 – 4.2 (THg)

and 1.7 – 3.3 (MeHg) times higher in snake tissues collected from the 1980s than in

2019, possibly reflecting an attenuation of Hg contamination in the Steel Creek system.

These data have important implications for the environmental health of the Steel Creek

system. Mainly, our data agree with studies that highlight the decrease in Hg loading resulting from major point source pollution in the SRS area (Kvartek et al. 1994) and atmospheric deposition in the eastern United States over the last two decades (Olson et al.

2020). However, our study only considers one reptile species from one site. Additional data are necessary to determine if the trends we observed in N. taxispilota reflect temporal trends in Hg from the Steel Creek system as a whole. Nerodia taxispilota tail

THg concentrations were a powerful predictor of THg concentrations in blood, kidney, liver, and muscle tissues, providing useful predictive relationships based on nondestructively collected samples for future studies in this species. In addition, strong relationships were found for THg and MeHg concentrations among kidney, liver, and muscle tissues. These relationships are advantageous for future investigations of THg and

MeHg in N. taxispilota, as MeHg analyses are more expensive and labor intensive compared to THg analyses. The distribution of THg and MeHg among tissues was similar to patterns reported in other reptiles, although the range of % MeHg in liver and kidney differed between time periods. Overall, Hg distribution trends in this species highlight the potential value of reptiles as bioindicators of contaminant trends through time, but also the need for a better understanding of Hg toxicokinetics in reptiles – especially snakes.

Acknowledgments

The authors thank Mark Mills for training us to sample brown watersnakes on the

Savannah River, assisting with snake dissections, offering his expertise on the species' ecology, and providing access to capture records collected as part of his dissertation research. The authors would also like to thank Austin Coleman, Louise McCallie, and

Pearson McGovern for their assistance with contemporary sampling of snakes on the

river. Whit Gibbons and Ray Semlitsch contributed snakes collected and archived in the

1980s. We also thank Caitlin Kupar and Matt Hamilton for dissecting multiple snakes

that were used for this project. Angela Lindell and Chris Leaphart provided valuable

assistance with collection and interpretation of total mercury analyses. The authors would

also like to thank LeeAnn Haskins, Robert Gogal, Travis Glenn, and anonymous

reviewers who provided valuable feedback on this manuscript. This project was partially

funded by the Department of Energy under award number DE-EM0004391 to the

University of Georgia Research Foundation and by Savannah River Nuclear Solutions –

Area Completions Project. Preparation of this manuscript was supported by funding from the University of Georgia's Interdisciplinary Toxicology Program and the University of

Georgia's Graduate School.

Disclaimer

This report was prepared as an account of work sponsored by an agency of the United

States government. Neither the United States Government nor any agency thereof, nor

any of their employees, makes any warranty, express or implied, or assumes any legal

liability or responsibility for the accuracy, completeness, or usefulness of any

information, apparatus, product, or process disclosed, or represents that its use would not

infringe privately owned rights. Reference herein to any specific commercial product,

process, or service by trade name, trademark, manufacturer, or otherwise does not

necessarily constitute or imply its endorsement, recommendation, or favoring by the

United States Government or any agency thereof. The views and opinions of authors

expressed herein do not necessarily state or reflect those of the United States Government

or any agency thereof.

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Table 1: Differences in total mercury (THg; mg/kg dw unless otherwise noted)

concentrations in destructive (liver, muscle, kidney) and nondestructive (blood, tail)

tissues in brown watersnakes (Nerodia taxispilota) collected from Steel Creek on the

Savannah River Site, South Carolina during two time periods (1980s, 2019). Values are reported as means ± 1 SE (ranges are reported below respective means in parentheses).

ANCOVAs were used to determine significant differences based on group (year).

Significant differences are noted by bold text (α = 0.05). Snout-vent length (SVL) was

used as a covariate. ANCOVA outputs (F-value, p) are reported along with calculated

2 partial eta-squared (ηp ) and 90% confidence intervals (CI; based on group effect).

Snakes were collected in the 1980s (1983 – 1986) and 2019. Note that blood tissues were

not available for analysis from archived 1980s samples.

2 Tissue Group n THg (mg/kg) F, p (Group) F, p (SVL) ηp , CI

Blooda 1980s - - - - - 0.31 ± 0.05 2019 19 (0.03 – 0.85) 12.97 ± 3.13 0.36 Liver 1980s 18 14.04, < 0.001 5.26, 0.030 (1.88 – 50.36) (0.11 – 0.53) 3.08 ± 0.65 2019 10 (0.79 - 8.11) 5.16 ± 0.52 0.27 Muscle 1980s 18 9.40, 0.005 2.24, 0.147 (2.42 – 11.27) (0.05 – 0.46) 3.16 ± 0.28 2019 10 (1.65 – 4.32) 6.23 ± 1.75 0.13 Kidney 1980s 17 3.57, 0.07 1.72, 0.20 (0.56 – 29.51) (0 – 0.33) 2.22 ± 0.46 2019 10 (0.42 – 5.74) 1.33 ± 0.17 0.40 Tail 1980s 17 16.12, < 0.001 5.45, 0.028 (0.51 - 2.89) (0.14 – 0.57) 0.65 ± 0.07 2019 10 (0.32 - 1.18) 0.51 ± 0.05 2019b 21 (0.17 – 1.18) a Blood THg data are reported as mg/kg ww b All tail THg data including individuals that were not sacrificed for temporal comparisons.

Table 2: Differences in methylmercury (MeHg; mg/kg dw) concentrations in liver,

muscle, and kidney tissues from brown watersnakes (Nerodia taxispilota) collected at

Steel Creek on the Savannah River Site, South Carolina during two time periods (1980s,

2019). Percentage MeHg is also reported for each tissue type. Values are reported as means ± 1 SE (ranges are reported below respective means in parentheses). ANCOVAs were used to determine significant differences based on group (year). Significant differences are noted by bold text (α = 0.05). Snout-vent length (SVL) was used as a covariate. ANCOVA outputs (F-value, p) are reported along with calculated partial eta-

2 squared (ηp ) and 90% confidence intervals (CI; based on group effect).

F, p F, p Percentage 2 Tissue Group n MeHg ηp , CI (mg/kg) MeHg (Group) (SVL)

0.41 4.54 ± 0.71 46.3 ± 4.1 17.51, < 2.87, Liver 1980s 18 (0.16 – (0.91 – 12.76) (19.7 – 90.3) 0.001 0.103 0.58) 1.37 ± 0.24 46.4 ± 3.2 2019 10 (0.25 – 2.91) (31.2 – 65.0) 4.17 ± 0.44 0.29 80.4 ± 1.4 10.32, 1.46, Muscle 1980s 18 (1.79 – 9.27) (0.07 – (69.6 – 88.0) 0.003 0.238 0.48) 2.42 ± 0.21 77.6 ± 4.0 2019 10 (1.28 – 3.49) (64.0 – 103.0) 0.20 3.03 ± 0.60 59.7 ± 3.6 6.13, 1.72, Kidney 1980s 17 (0.02 – (0.35 – 10.46) (29.9 – 85.1) 0.021 0.217 0.40) 1.14 ± 0.22 52.0 ± 2.7 2019 10 (0.19 – 2.63) (39.1 – 70.0)

Figure 1: Location of brown watersnake (Nerodia taxispilota) sampling on the Savannah

River Site (SRS) in west-central South Carolina, USA (inset). Snakes were collected from a section of the Steel Creek system (hollow black box).

Figure 2: Correlations between tail and destructive (kidney [Figure 2A], liver [Figure

2B], and muscle [Figure 2C]) tissue total mercury (THg) concentrations in brown watersnakes (Nerodia taxispilota) captured at Steel Creek on the Savannah River Site

(Aiken, South Carolina, USA). Snakes were collected in two time periods – the 1980s

(1983 – 1986, red circles) and 2019 (black circles).

Figure 3: Correlations among liver, muscle, and kidney, tissue total mercury (THg) concentrations in brown watersnakes (Nerodia taxispilota) captured at Steel Creek on the

Savannah River Site (near Aiken, South Carolina, USA). Snakes were collected in two time periods – the 1980s (1983 – 1986, red circles) and 2019 (black circles). Figure 3C did not fit the assumptions of normality and a Spearman rank correlation approach was used.

Figure 4: Relationship between snout-vent length (SVL) and liver (Figure 4A; analysis of

2 covariance, n = 28; SVL: F1,25 = 14.04, r = 0.391, p = 0.03; group [year]: F1,25 = 5.26, p

2 < 0.001) and tail (Figure 4B; analysis of covariance, n = 38; SVL: F1,35 = 7.73, r =

0.560, p = 0.009; group: F1,35 = 41.38, p < 0.001) total mercury (THg) concentrations in brown watersnakes (Nerodia taxispilota) collected from Steel Creek on the Savannah

River Site (near Aiken, South Carolina).

Figure 5: Correlations between methylmercury (MeHg) and total mercury (THg) concentrations in kidney (Figure 5A), liver (Figure 5B), and muscle (Figure 5C) tissues from brown watersnakes (Nerodia taxispilota) captured at Steel Creek on the Savannah

River Site (Aiken, South Carolina, USA). Snakes were collected in two time periods – the 1980s (1983 – 1986, red circles) and 2019 (black circles).

Appendix

3A. Table 1: Percent moisture content, wet:dry factor values, and total mercury (THg, mg/kg wet weight) for blood, liver, muscle, kidney, and tail tissues from brown watersnakes (Nerodia taxispilota) collected at Steel Creek on the Savannah River Site,

South Carolina during two time periods (1980s, 2019).

Tissue Group n Percent moisture Wet:Dry factor THg, mg/kg ww Blood 1980s ------2019 19 84.51 ± 0.42 6.54 ± 0.18 0.31 ± 0.06 (80.14 – 87.88) (5.03 – 8.25) (0.05 – 0.85) Liver 1980s 18 75.61 ± 0.43 4.12 ± 0.08 3.08 ± 0.69 (72.36 – 79.18) (3.62 – 4.80) (0.47 – 10.49) 2019 10 75.25 ± 0.50 4.06 ± 0.08 0.77 ± 0.17 (72.31 – 77.19) (3.61 – 4.38) (0.37 – 2.05)

Muscle 1980s 18 75.41 ± 0.90 4.21 ± 0.24 1.25 ± 0.12

(71.67 – 87.53) (3.53 – 8.02) (0.60 – 2.55) 2019 10 79.02 ± 0.28 4.77 ± 0.06 0.66 ± 0.05 (77.66 – 80.24) (4.48 – 5.06) (0.34 – 0.86)

Kidney 1980s 17 80.66 ± 0.86 5.35 ± 0.24 1.14 ± 0.29 (72.37 – 86.05) (3.62 – 7.04) (0.11 – 4.49) 2019 10 80.16 ± 1.49 5.21 ± 0.25 0.44 ± 0.09 (66.93 – 82.59) (3.02 – 5.74) (0.08 – 1.03) Tail 1980sa 17 - - 0.49 ± 0.06 - - (0.23 – 1.06) 2019 21 61.89 ± 0.48 2.64 ± 0.05 0.19 ± 0.02 (58.55 – 66.55) (2.41 – 2.99) (0.07 – 0.45) a Tail weights from 1980s snakes were not collected prior to desiccation.

3A. Figure 1: Relationship between log snout-vent length (SVL) and log mass in brown watersnakes (Nerodia taxispilota) captured in the Savannah River Site area, Aiken, South

Carolina. Snakes were collected from 1967 – 2019.

CHAPTER 4

BROWN WATERSNAKES (NERODIA TAXISPILOTA) AS BIOINDICATORS OF

MERCURY CONTAMINATION IN A RIVERINE SYSTEM 3

3 Haskins, D.L., M.K. Brown, R.B. Bringolf, and T.D. Tuberville. In press. Science of the Total Environment. Reprinted here with permission of the publisher.

Abstract

Mercury (Hg) is a contaminant that enters the environment through natural or anthropogenic means. Ecological risk assessments have examined Hg bioaccumulation and effects in many taxa, but little is known about Hg dynamics in reptiles, or their potential use as bioindicator species for monitoring Hg in aquatic systems. Numerous snake species, like North American watersnakes (Nerodia spp.), are piscivorous and are exposed to Hg through their diet. The purpose of this study was to identify factors associated with Hg accumulation in a common watersnake species and compare Hg concentrations of the snakes to those in fish occupying the same habitats. To this end, we sampled brown watersnakes (Nerodia taxispilota) from the Savannah River, a major river system in the southeastern U.S., and compared N. taxispilota Hg accumulation trends to those of bass (Micropterus salmoides), catfish (Ictalurus and Ameiurus spp.), and panfish

(Lepomis and Pomoxis spp.) collected from the same reach. Total Hg (THg) in N. taxispilota tail tips ranged from 0.020 to 0.431 mg/kg (wet weight; mean: 0.104 ± 0.008).

Snake tail THg was significantly correlated with blood THg, which ranged from 0.003 to

1.140 mg/kg (0.154 ± 0.019). Snake size and site of capture were significantly associated with tail THg. Snake tail THg increased at sites along and downstream of the area of historic Hg pollution, consistent with fish THg. Snake muscle THg was predicted based on tail THg and ranged from 0.095 to 1.160 (0.352 ± 0.022). To gauge Hg biomagnification in N. taxispilota, we compared predicted snake muscle THg concentrations to THg in fish of consumable size. Average biomagnification factors for

THg in N. taxispilota were 3.1 (panfish) and 5.4 (catfish), demonstrating N. taxispilota

likely biomagnify Hg through their diet. These results reveal N. taxispilota to be an

effective bioindicator species for monitoring Hg in aquatic environments.

Introduction

Mercury (Hg) is a contaminant of concern which enters the environment through

both natural and anthropogenic sources. Mercury in the environment has increased

significantly in the last century, largely due to anthropogenic activities such as mining,

coal combustion, and the production of non-ferrous metals (Selin, 2009). Once in the

environment, Hg is unique in its persistence and potential for long-distance atmospheric

transport (Chen et al., 2014). Aquatic environments provide conditions conducive for the

conversion of inorganic Hg to its more bioavailable and toxic organic form –

methylmercury (MeHg; Morel et al., 1998). Methylmercury bioaccumulates and

biomagnifies in food webs and is toxic to humans and wildlife. Numerous studies

demonstrate that MeHg may negatively impact reproduction, survival, and immune status

in a variety of species (Wolfe et al., 1998; Tan et al., 2009; Evers, 2018). Though much is known about MeHg bioaccumulation potential and its associated effects in birds, fish, and mammals, less is known about MeHg dynamics in reptiles (Schneider et al., 2013).

Reptiles, including alligators (Jagoe et al., 1998), turtles (Hopkins et al., 2013), and snakes (Burger et al., 2006; Drewett et al., 2013), can accumulate significant amounts of Hg in aquatic environments, suggesting that reptiles play an important role in Hg dynamics in their respective ecosystems. Snakes are typically underrepresented in ecotoxicological studies but more recently have been explored as potential bioindicators of contaminants, including Hg (Campbell and Campbell, 2001; Haskins et al., 2019;

Lettoof et al., 2020). For example, northern watersnakes (Nerodia sipedon) from a

contaminated river in Virginia had high Hg concentrations as a result of both dietary

exposure and maternal transfer (Chin et al., 2013a, 2013b; Drewett et al., 2013).

Although watersnakes (Nerodia spp.) may not always feed at the highest trophic level in an ecosystem, many of their characteristics (e.g., carnivorous diets, widespread distribution, high site fidelity, relatively long-life span) may make them suitable species for monitoring contamination in aquatic environments.

North American watersnakes vary significantly in dietary habits, and many species are likely at risk of contaminant exposure due to their strong affinity for wetlands and aquatic ecosystems (Drewett et al., 2013). Their high site fidelity (Mills et al., 1995) also provides a strong case that they may be useful for monitoring local patterns of Hg contamination, as has been shown for an Australian aquatic snake (Lettoof et al., 2020).

For example, Nerodia spp. that are obligate piscivores may be particularly useful for monitoring the flow of Hg in aquatic ecosystems in the United States. In large rivers, fish are often used to gauge risk for contaminant exposure in humans and wildlife, as many of these species are piscivorous and feed on the same fish that humans may consume

(Burger et al., 2001a, 2001b). Likewise, snakes that are predators of fish in these

environments may accumulate Hg in a similar manner and be useful indicators of

exposure.

Here we explore the potential utility of the brown watersnake (Nerodia taxispilota) as a bioindicator species for Hg contamination in riverine systems. We investigated Hg concentrations in brown watersnakes collected upstream, along, and downstream of an area of historic Hg pollution on the Savannah River. Fish collected from this same study system have previously been shown to increase in Hg

concentrations from upstream to downstream locations (Paller et al., 2004). Specifically,

the objectives of this study were to (1) validate the use of tail tips as an additional non-

lethal sampling alternative to blood in N. taxispilota, (2) examine the relationship

between body size and Hg bioaccumulation in N. taxispilota, (3) compare spatial trends

in Hg values from N. taxispilota relative to spatial trends for fish from the same locations,

and (4) evaluate the potential for Hg biomagnification in N. taxispilota. We predicted that

(1) tail tip Hg would be strongly correlated with blood Hg, (2) Hg concentrations would

increase with size in N. taxispilota, (3) spatial Hg trends in N. taxispilota would mirror

those seen in fish from the same sites on the Savannah River, and (4) N. taxispilota would

exhibit evidence suggestive of biomagnification by having higher Hg concentrations than

those of prey fish species.

Methods

Study area

The Savannah River serves as the border between the states of Georgia and South

Carolina in the southeastern U.S. Sampling sites were in the Upper Coastal Plain of the region and spanned approximately 87 river km from Augusta, Georgia to Martin, South

Carolina (excluding the 22.5 river km between Vogtle Point Landing and Little Hell

Landing; USACE, 2016). Delineation of the four sampling sites reported in this study

was based on city names or boat landings that were used for river access. The four sites

were (in order from upstream to downstream): Augusta (33.367859, −81.947096),

Jackson (33.279966, −81.843821), Ellenton Bay (EBay; 33.217950, −81.768346), and

Lower Three Runs (LTR; 32.999837, −81.489232; Fig. 1). The sampling area used for

snake collections is the same stretch of river for which historical and contemporary fish

Hg data are available (Burger et al., 2001a; Paller et al., 2004; Paller and Littrell, 2007).

A portion of the river length sampled was adjacent to the Savannah River Site

(SRS), a 800-km2 Department of Energy-operated National Environmental Research

Park. Historically, the SRS was a nuclear production facility, and activities onsite led to

the accidental release of radionuclides and heavy metals, including Hg. Multiple anthropogenic sources – both historical and contemporary – contribute to Hg contamination in this area of the Savannah River, including industrial activities upstream

of the SRS (e.g., a now inactive chlor-alkali facility in Augusta, Georgia decommissioned

in 2012), formerly active coal combustion facilities on the SRS, aquatic basins associated

with SRS industrial operations, and atmospheric deposition. The most recent calculations

of Hg loading in the region found that atmospheric deposition is the main source of Hg

contamination in the Savannah River watershed (~99% of Hg loading; EPA, 2000).

Recent data from the National Atmospheric Deposition Program (NRSP-3) reports an

average Hg deposition of 8.64 ng/L for the SRS area (data from 2016 to 2017, Barnwell

County, 33.2450, −81.6505; NADP, 2019).

Study species

Nerodia taxispilota inhabit primarily riverine and stream systems of the

southeastern U.S. Coastal Plain, rarely leaving the water except to bask (Mills et al.,

1995). They occur at high densities and are easily caught without trapping, facilitating

monitoring. Brown watersnakes are also long-lived (>10 years; Mills, 2002) and may

thus be prone to accumulate contaminants over long periods (Rowe, 2008). Finally, they

are obligate piscivores known to consume a variety of fish species. However, once

individuals reach a snout-vent length (SVL) of approximately 600 mm, they experience

an ontogenetic diet shift, with catfish (Ictaluridae spp.) comprising the largest portion of

their diet (Mills, 2002, 2004). Like other Nerodia, brown watersnakes are sexually

dimorphic with females growing to significantly greater sizes than males (Mills, 2004). In the SRS area, females had a maximum SVL of 1340 mm and males had a maximum SVL of 910 mm (Mills, 2002, 2004).

Sampling and processing of snakes

We hand-captured basking snakes by moving slowly in a boat approximately 5 to

15 m from the riverbank during daylight hours (approximately 0730 to 1830) from May–

August 2017 and April–August 2018. For each snake, we recorded morphological data including SVL (to the nearest 1 mm), weight (to the nearest 1 g), and sex. For snakes that were larger than 20 g, we collected blood samples (≤1% of the snake's weight) from the caudal vein. We also collected tail clips (~1 cm) from each snake, as previous studies in

other snake species demonstrate that tail clips may serve as an effective non-lethal

sampling tool for Hg (Hopkins et al., 2001; Burger et al., 2006; Drewett et al., 2013). We

permanently marked all snakes (>20 g in mass) with a passive integrated transponder

(PIT) tag (AVID, Norco, CA, USA) injected ventrally into the coelomic cavity

approximately one-third of the SVL anterior to the snakes' cloaca (Camper and Dixon,

1988; Gibbons and Andrews, 2004).We released all snakes at their original capture

location immediately following processing. We collected and handled snakes in

accordance with approved protocols from the University of Georgia's Institutional

Animal Care and Use Committee (AUP# A2019 05-024-Y1- A0). Scientific Collection

Permits for capture, handling, and sampling snakes were issued by Georgia Department

of Natural Resources (permit #1000540516) and South Carolina Department of Natural

Resources (permits #SC-08-2017; #SC-06-2018).

Quantifying total mercury in snakes

Although MeHg is the primary form of Hg that is a concern in vertebrates, few studies have directly measured MeHg in reptiles. However, a recent study in the northern watersnake (N. sipedon) found that 87.1 to 95% of the total Hg (THg) concentration in

tail tips was MeHg (Drewett et al., 2013). Thus, we opted to use THg as a proxy for

MeHg in N. taxispilota. We quantified total mercury (THg) concentrations in snake blood

and tail tissue on a Milestone DMA-80 Tri-Cell (Milestone Inc., Shelton, CT, USA)

using the Environmental Protection Agency method 7473 (USEPA, 1998). The DMA-80

uses a combination of thermal decomposition, catalytic conversion, amalgamation, and

cold vapor atomic absorption spectrophotometry for THg analysis. We conducted these

analyses over several runs. For quality control, each run of 20 samples incorporated a

blank, replicate, and two certified reference materials (TORT-3 and PACS-2; National

Research Council of Canada, Ottawa, Ontario). Average percent recoveries (% ± SE) of certified reference materials were 94.3% ± 0.73% and 102.9% ± 1.82% for PACS-2 and

TORT-3 (both n = 29), respectively. All blood and tail THg concentrations are reported

as mg/kg on a wet weight basis (Table 1; see Appendix 4A Table 1 for dry weight

values).

Monitoring of fish mercury

As part of the Nonradiological Environmental Monitoring Program, Savannah

River Nuclear Solutions (SRNS) samples multiple fish species annually from the

Savannah River and quantifies a variety of contaminants, including Hg. The SRNS fish

sampling sites directly overlap with snake sampling sites (excluding the Jackson site).

Sampled fish species include largemouth bass (Micropterus salmoides), channel catfish

(Ictalurus punctatus), white catfish (Ameiurus catus), bluegill (Lepomis macrochirus), redbreast sunfish (Lepomis auritus), redear sunfish (Lepomis microlophus), and crappie

(Pomoxis annularis). Muscle THg (mg/kg, wet weight) data are then reported by the

SRNS as three broad groups: bass (Micropterus salmoides), catfish (Ictalurus and

Ameiurus spp.), and panfish (Lepomis and Pomoxis spp.). We used Hg data from fish

collected from 2017 to 2019 (SRNS, 2017, 2018; SRNS, unpublished data).

Comparisons of mercury between fish and snakes

Biomagnification of Hg is well-documented in aquatic and terrestrial food webs.

Predators with a higher trophic position in the food web, such as watersnakes, may be

expected to accumulate significant amounts of Hg. We calculated biomagnification

factors (BMFs) to compare Hg concentrations between N. taxispilota (predicted muscle

THg) and potential fish prey (muscle THg) of consumable size using Gobas and

Morrison's (2000) interpretation of BMF (Eq. (1)):

BMF = CB/CD (1)

where CB is the concentration of Hg in the predator (N. taxispilota) and CD is the

concentration of Hg in the diet (fish). A calculated BMF > 1 suggests that the

contaminant of concern (Hg) is biomagnifying in the predator (Gobas et al., 2009).

Because captured snakes included all size classes (SVL range 275–1170 mm) but

the fish included in the SRNS data are restricted to large adults, we calculated BMFs for

snakes using a targeted approach. Mills (2002) reported that N. taxispilota may consume

prey items >35% of their body mass. The study found that the largest prey item (37% of

snake's mass) in a N. taxispilota was likely a low figure, as the snake had been digesting

the fish for at least a day (Mills, 2002). Thus, for each sampling site, we trimmed the

snake dataset to include only the largest adult snakes (snakes with mass > 1000 g) likely

to consume large fish. Because catfish and panfish are likely prey of large adult N.

taxispilota, we then trimmed the fish dataset at each sampling site to only include individuals that were 37–50% of the largest snakes' mass at that site. Using this approach,

we calculated BMFs for snakes relative to catfish and panfish at each sampling site on the

Savannah River.

Statistics

We analyzed data with program R (R Core Team, 2019) and set α at 0.05 to

assess significance across all analyses. We evaluated all data to ensure normality and

homogeneity of variance and log-transformed data when necessary to improve

distribution and to fit basic assumptions of the analyses. If assumptions were not met, we

used a nonparametric approach for analysis. We used correlational analyses to evaluate

potential relationships between snake size (SVL) and THg, as well as between snake blood and tail THg. Preliminary examination of data found that THg did not differ significantly based on sampling year or sex. Therefore, we pooled data from 2017 to

2018 and did not consider sex further in models. We evaluated site and size-specific differences in Hg concentrations in tissues of N. taxispilota using a multiple linear regression approach and detected a significant interaction between site of capture and snake size (SVL). Therefore, we evaluated site differences based on the covariate (snake

size) using a ‘spotlight analysis’ approach (Spiller et al., 2013). This statistical approach traditionally uses three arbitrary values (mean ± 1 SD) based on the covariate of interest.

Instead, we used three focal sizes of snake (375 mm, 600 mm, and 900 mm SVL) to examine potential site-specific differences. Based on previous data collected by Mills

(2002, 2004), 375 mm represents a one-year-old snake, 600 mm corresponds to the size at which a major ontogenetic diet shift is reported to occur, and 900 mm represents a large, sexually mature snake. If necessary, we used multiple comparisons to detect significant differences based on site via a Tukey-Kramer test (after accounting for the site*size interaction). We used a 4 (species) × 3 (site) factorial analysis of variance

(ANOVA) to compare THg concentrations among all species sampled at different sites

(fishes and N. taxispilota) followed by Tukey-Kramer tests for multiple comparisons when significant differences were detected. To facilitate comparisons of THg in all fish and snakes, we used snake tail and available predictive equations to approximate THg in snake muscle (p < 0.0001, r 2 = 0.872, n = 27; y (log10 muscle THg) = 0.81611 x (log10 tail THg) + 0.83322; Haskins et al., unpublished data).

Results

We collected a total of 121 N. taxispilota (61 females, 275–1170 mm SVL, 18 –

2290 g; 60 males, 290–870 mm SVL, 18–505 g) from the four sampling sites (Augusta, n

= 30; Jackson, n = 28; EBay, n = 29; LTR, n = 34; Table 1). Because we were not able to collect both blood and tail tips from every snake, the individuals used for each tissue type vary.

Mercury in snakes: size and site

THg concentrations in snakes ranged 0.003–1.140 mg/kg for blood (n = 117) and

0.020–0.430 mg/kg for tail (n = 121). We found a significant and positive correlation (p <

0.001, rs = 0.92, n = 117) between blood and tail THg concentrations in snakes (Fig. 2).

When including all individuals sampled, we also observed a significant and positive correlation (p < 0.001, r2 = 0.34, n = 121) between snake SVL and tail THg

concentrations, with approximately 34% of variation in tail THg explained by snake size

(Fig. 3). We found a significant interaction between snout-vent length (SVL) and site on

snake tail THg (F7,113 = 15.57, p < 0.001; Fig. 4A). In the two smaller snake size classes,

tail THg was significantly higher in snakes from Augusta relative to Jackson (at 375 mm:

t113 = −3.72, p < 0.001; at 600 mm: t113 = −3.35, p = 0.001; Fig. 4B). In contrast, tail THg at 900 mm was significantly higher further downstream (EBay and LTR) when compared to Augusta (Augusta to EBay: t113 = 3.41, p < 0.001; Augusta to LTR: t113 = 2.94, p =

0.004; Fig. 4C).

Mercury comparisons among species

Using tail concentrations, we predicted muscle THg concentrations in all snakes, which ranged 0.095–1.160 mg/kg (wet weight; mean: 0.352 ± 0.022). Spatial patterns of predicted THg in snake muscle mirrored patterns present in fish collected along the same stretch of the Savannah River. Mean muscle THg concentrations in all snakes increased as sampling moved downstream from the Augusta site to Lower Three Runs, where THg was the highest. A factorial ANOVA revealed significant differences in THg among bass, catfish, panfish, and snakes (F3,344 = 63.73, p < 0.001). Pairwise comparisons of muscle

THg based on species found that bass had significantly higher THg concentrations than

catfish (t344 = 10.72, p < 0.001) and panfish (t344 = 10.94, p < 0.001) but not snakes (t344 =

2.12, p = 0.150). Similarly, snakes had significantly higher muscle THg concentrations

relative to catfish (t344 = 8.92, p < 0.001) and panfish (t344 = 9.17, p < 0.001). Catfish and

panfish exhibited similar muscle THg concentrations (t344 = 0.30, p = 0.99; Fig. 5). Total

Hg concentrations also varied significantly among sites (F2,344 = 39.88, p < 0.001), with

muscle THg increasing as sampling moved downstream (all t344 > 2.48, all p < 0.036).

The main effects also presented with a significant interaction (F6,344 = 3.00, p = 0.007;

Fig. 5), such that at LTR, bass had significantly higher muscle THg than all other species

sampled (all t344 > 4.03, all p < 0.004). Also at LTR, snakes had significantly elevated

muscle THg compared to catfish (t344 = 3.55, p < 0.022) but not panfish (t344 = 2.98, p =

0.12).

Biomagnification factors

Based on comparison of muscle THg concentrations between the largest snakes

and the catfish they could consume, the average BMF was 5.4 in N. taxispilota when all

sites were combined. At individual sampling sites, average BMFs for muscle THg in

snakes relative to catfish were 6.6 (Augusta), 6.0 (EBay), and 3.5 (LTR; Fig. 6A).

Comparisons of THg concentrations between larger snakes and panfish yielded an

average BMF of 3.1 in N. taxispilota for all sites combined. At individual sampling sites, average BMFs for THg in snakes relative to panfish were 3.8 (Augusta), 2.9 (EBay), and

2.7 (LTR; Fig. 6B).

Discussion

Understanding Hg accumulation patterns in wildlife assists with ecological risk

assessment and is useful for monitoring spatial and temporal contamination trends in the

environment. Unlike other vertebrates, much less is known about accumulation of Hg and

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associated effects in snakes (Haskins et al., 2019). This study quantified THg

concentrations in N. taxispilota blood and tail tips from the Savannah River adjacent to a

former nuclear production site. As reported in other Nerodia spp., the two nondestructive

tissues were significantly correlated in N. taxispilota (Hopkins et al., 2001; Drewett et al.,

2013). Likewise, size was an important predictor of THg accumulation patterns, with

higher THg concentrations in larger snakes. Further, site-specific differences in THg

concentrations depended on snake size class. Spatial THg trends in N. taxispilota

matched those reported in fish, with THg generally increasing in snakes sampled

downstream of the SRS. Based on comparison of predicted muscle THg in all captured

snakes to all available fish data, average snake THg (all size classes) was significantly

higher than THg reported in adult catfish and panfish but not bass. Mean BMFs

calculated for the largest snakes (>1000 g in mass) relative to consumable prey fish

ranged 3.1–5.4, suggesting that Hg biomagnification does occur in N. taxispilota.

Mercury in Nerodia taxispilota based on non-destructive tissues

Over the last two decades, ecotoxicological studies of snakes have shifted towards the use of non-destructively collected tissues to monitor contaminants in this understudied group (Hopkins et al., 2001; Burger et al., 2006; Murray et al., 2010;

Drewett et al., 2013). Nondestructive tissues can be powerful predictors of contaminant exposure, but species-specific differences in Hg accumulation patterns may limit comparisons among species without proper validation (Pfleeger et al., 2016). As predicted, blood and tail THg in N. taxispilota were highly correlated, facilitating comparisons to Hg values reported in other studies. In the present study, correlation

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values between blood THg and tail THg in N. taxispilota were similar to those reported in

the northern watersnake (N. sipedon; r 2 = 0.84, p < 0.01; Drewett et al., 2013).

The range of tail THg concentrations for N. taxispilota in this study are comparable to the few THg data available for this species (Burger et al., 2006; Murray et al., 2010), which were based on a small number of individuals collected from a variety of other aquatic habitats on the SRS (0.611–0.971 mg/kg wet wt; Burger et al., 2006;

Murray et al., 2010). Other species of Nerodia recently collected on or adjacent to the

SRS exhibited similar THg concentrations. Across all sites, banded watersnakes (N. fasciata) had mean tail THg concentrations of 0.082 ± 0.007 mg/kg (wet wt; Brown,

2019), Florida green watersnakes (N. floridana) had mean tail THg concentrations of

0.054 ± 0.003 mg/kg (wet wt; Brown, 2019), and red-bellied watersnakes (N.

erythrogaster) had mean tail THg of 0.14 ± 0.03 mg/kg (wet wt; Haskins, Brown, and

Tuberville; unpublished data). While there are no toxicity reference values available for

Hg in reptiles, THg values in N. taxispilota and other Nerodia spp. on the SRS are much

lower than those from the only study to report sublethal impacts of Hg on snakes. Chin et

al. (2013a) found decreased striking and feeding efficiencies of N. sipedon offspring with

mean whole-body THg concentrations (3.42 ± 0.45 mg/kg, dry wt) more than ten times

higher than the average THg concentrations from N. taxispilota in this study (0.287 ±

0.021 mg/kg, dry wt).

Mercury in snakes based on size and site

Mercury is a heavy metal that bioaccumulates, typically resulting in higher

concentrations in larger conspecifics. Although growth rates vary among individuals and

snakes exhibit indeterminate growth (Bronikowski, 2008), one might expect THg to be

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greater in larger size classes due to longer potential exposure (i.e., age; Drewett et al.,

2013). As predicted, THg in N. taxispilota increased with snake size. Our results corroborate patterns reported for other snake species, indicating that body size is an important factor in Hg bioaccumulation. Banded watersnakes (N. fasciata) and Florida green watersnakes (N. floridana) collected from natural isolated wetlands and former nuclear cooling reservoirs on the SRS also exhibited a positive relationship between body size and tail THg (Brown, 2019). Likewise, northern watersnakes (N. sipedon) from a

Hg-contaminated river in Virginia also exhibited a significant positive relationship between snake size and tail THg concentrations (Drewett et al., 2013). Furthermore, snakes from other genera, including cottonmouths (Agkistrodon piscivorous), ribbon snakes (Thamnophis sauritus), and Burmese pythons (Python bivitattus) have all shown increasing Hg concentrations with increasing body size (Rainwater et al., 2005; Albrecht et al., 2007; Lemaire et al., 2018; Rumbold and Bartoszek, 2019; Lettoof et al., 2020).

As gape-limited predators, many watersnake species experience ontogenetic dietary shifts as they grow, resulting in differences in diet based on size (Mushinsky et al., 1982). Mills (2002) found that N. taxispilota, much like the closely related diamondback watersnake (N. rhombifer; Plummer and Goy, 1984), undergo a dietary shift to an almost exclusively catfish diet at approximately 600 mm SVL. We found that snake size influenced whether N. taxispilota exhibited significantly different THg values among sites. Nerodia taxispilota in the smaller size classes (375 and 600 mm) had higher

THg values at Augusta than those captured at Jackson. In contrast, the largest N. taxispilota from EBay and LTR sites had higher THg concentrations than conspecifics at

Augusta. Notably, the size range (SVL) of snakes captured in Augusta (318–978 mm)

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was not as large as those at other sampling sites (max SVL ≥ 1160 mm at all other sites),

which may have underestimated THg concentrations in 900 mm snakes. This potential

underestimation of THg in the 900 mm size class at Augusta could affect its slope of

regression, such that differences in THg among sites could become less significant if larger snakes were captured. However, snake THg values followed the expected trend

increasing from upstream to downstream sites along the Savannah River. It is interesting

that smaller N. taxispilota from Augusta have higher THg concentrations compared to

Jackson. There are a variety of factors that could be contributing to these differences. For

example, the sampling site at Augusta occurs downstream of the Augusta Lock and Dam, which constrains movement patterns of fish and may also alter Hg cycling at the Augusta site (Stanford et al., 1996; Wang et al., 2018). These unique attributes of the Augusta site could also potentially influence the fish prey that are available for consumption or Hg accumulation rates in prey.

Mercury in Nerodia taxispilota and fish

To evaluate the utility of using N. taxispilota to monitor spatial patterns in Hg in the Savannah River, we compared patterns between predicted muscle THg in N. taxispilota and muscle THg in fish collected from the same sites during the study period.

As expected, spatial trends in THg from upstream (Augusta) to downstream (LTR) were similar between fish and N. taxispilota. Muscle THg in all fish collected during 2017–

2019 increased from upstream to downstream. The contemporary patterns observed in

fish and N. taxispilota mirror historical mercury trends in fish from the same sites, where

muscle THg in all fish increased significantly as sampling moved further downstream

(Paller et al., 2004). The numerous wetlands and streams on the SRS that drain into the

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Savannah River and its associated floodplain are likely the source of increased mercury at the sampling sites along and downstream of the SRS, as wetlands are known to significantly increase bioavailability of mercury in associated rivers (Zillioux et al., 1993;

Paller et al., 2004). Indeed, studies from Canada and the U.S. (Wisconsin) demonstrate that wetlands export significant amounts of mercury into lakes and rivers (Hurley et al.,

1995; St. Louis et al., 1996; Krabbenhoft et al., 1995; Back et al., 2002). Furthermore,

Guentzel (2009) found that the percentage of wetlands and total organic carbon within a watershed were significantly and positively correlated with increased mercury concentrations in rivers and resident bass from the Coastal Plain of South Carolina. The

Hg patterns observed in this study are likely not associated with point source inputs from the SRS, but rather the drainage of water through an area with a higher concentration of intact wetlands relative to upstream sites.

Nerodia taxispilota had higher THg concentrations than prey fish species (catfish and panfish) at all sites sampled. However, bass had similar THg concentrations relative to snakes at two of the three sites sampled. An in-depth study on the diet of N. taxispilota found that largemouth bass (Micropterus salmoides) were not a preferred food item (one potential predation event; 0.004% rate; Mills, 2002). Because of this, we did not include bass in the BMF comparisons. As has been previously reported for the Savannah River system, bass had significantly higher THg concentrations than the other fish species sampled (Burger et al., 2001a, 2001b; Burger et al., 2002; Paller et al., 2004; Paller and

Littrell, 2007).

It is likely that the differences in THg between N. taxispilota and its prey fish are even greater than those observed in this study. The interspecies comparison of THg from

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this study includes all size classes of N. taxispilota (yearlings to large adult females) but

did not incorporate smaller fish which are not included in the annual monitoring data

reported by SRNS. As in other vertebrates, THg is positively and significantly associated

with fish body mass (Burger et al., 2001a, 2001b). Thus, to allow us to make biologically

relevant inferences regarding biomagnification in N. taxispilota, we compared THg in

large adult snakes to prey fish of a size snakes are likely to consume. In N. taxispilota, the

average BMFs for THg were 3.1 (panfish) and 5.4 (catfish) among all sites, which is

within the reported range of BMFs for Hg in aquatic systems (~2–10; Kidd et al., 2011).

It is important to note that because we trimmed the dataset to include only the snakes

large enough to consume fish of the size for which data were available, all BMF

calculations were based on large adult females. Sex-specific factors that influence Hg

bioaccumulation and offloading, such as maternal transfer from gravid females to

offspring (Chin et al., 2013a, 2013b), may impact BMF estimates and merit further investigation. Overall, these results indicate that biomagnification of THg occurs in N.

taxispilota.

Conclusions

Collectively, our work adds further support to the potential utility of watersnakes for monitoring Hg contamination in aquatic environments. Nerodia taxispilota sampled from a major river system with Hg pollution demonstrated Hg bioaccumulation, and both

blood and tail tips were useful tissues for monitoring THg in this species. Further,

bioaccumulation of Hg in N. taxispilota was strongly associated with snake size and site

of capture, with spatial trends in THg mirroring those documented in fish sampled at the

same sites. Average THg was higher in N. taxispilota when compared to most fish at the

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same sites but likely underestimates the difference – due to the absence of smaller size classes of fish from the available dataset. Total Hg concentrations across the full size ranges of fish would help elucidate patterns of THg observed in N. taxispilota. Estimating trophic positions of both N. taxispilota and potential fish prey with stable isotopes would provide additional valuable insight into biomagnification of Hg in this system.

Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2020.142545.

Acknowledgments

The authors thank Mark Mills for training us to sample brown watersnakes on the

Savannah River and offering his expertise on the species' ecology. The authors would also like to thank Austin Coleman, Alexis Korotasz, Kip Callahan, Matt Hamilton,

Matthew Hale, Pearson McGovern, Amelia Russell, Kurt Buhlmann, James Angley,

Kaiya Cain, Wes Flynn, LeeAnn Haskins, Melissa Lech, Phillip Lyons, Rebecca McKee,

Melissa Pilgrim, Caleigh Quick, and Heaven Tharp for their assistance with capturing snakes on the river. We are indebted to Susan Blas, who compiled and provided fish monitoring data from the Savannah River. Angela Lindell provided valuable assistance with collection and interpretation of total mercury analyses. Dean Fletcher aided with interpretation of fish mercury data. The authors would also like to thank LeeAnn

Haskins, Robert Gogal, Melissa Pilgrim, Travis Glenn, and anonymous reviewers who provided valuable feedback on this manuscript. This project was partially funded by the

Department of Energy under award number DE-EM0004391 to the University of Georgia

Research Foundation and by Savannah River Nuclear Solutions – Area Completions

Project. Preparation of this manuscript was supported by funding from the University of

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Georgia's Interdisciplinary Toxicology Program and the University of Georgia's Graduate

School.