Mercury Methylation in Riparian Areas Across Minnesota

by

Kevin Kai Fung Ng

A thesis submitted in conformity with the requirements for the degree of Master of Science

Department of Geography University of Toronto

© Copyright by Kevin Ng 2017

ii

Mercury Methylation in Riparian Areas Across

Minnesota

Kevin Kai Fung Ng

Master of Science

Department of Geography University of Toronto

2017

Abstract

Five rivers in Minnesota have been identified to have particularly elevated mercury

concentrations in fish despite relatively low total mercury concentrations in water and sediment.

One hypothesis is that methylmercury production in riparian areas and hydrological connectivity

of riparian areas to streams are important contributors to river methylmercury loads and

bioaccumulation. We conducted methylation (Kmeth) assays, using enriched mercury isotopes,

across two geomorphically distinct riparian zones in each of five Minnesota watersheds and

across seasons from 2015 through 2016. Kmeth was generally higher in-stream and lower with

increasing distance away from the stream. Results show that although methylation does occur in

riparian areas, it is not likely that these areas are the primary source of MeHg found in fish due to

hydrological flow patterns observed at these sites. More research is needed to determine the

source of elevated MeHg concentrations found in the fish of these “high-5” watersheds.

iii

Acknowledgments

Firstly, I would like to thank my supervisor and mentor, Dr. Carl Mitchell, for his patience,

guidance, and advice over the last few years. Thank you for providing me the opportunity to

pursue my academic dreams in a way that I would have otherwise never imagined. I would also

like to sincerely thank my committee members, Dr. Adam Martin and Dr. Sarah Finkelstein for

their time, input, and willingness to help in all circumstances. I would like to acknowledge

Planck Huang for his invaluable knowledge and assistance in the lab, as well as Raymond Co

and Steve Chang for field assistance. I thank Dr. Nathan Johnson and Dr. Jeff Jeremiason and

their respective students in this collaborative “High-5” research project. I thank Andrew

Alagaratnam, Roland Law, and Dave Rombough for their ongoing friendship and support. I

sincerely thank my family, Donny Ng, Rebecca Ng, and Carmen Ng, for their support in both my

academic journey and in life as I would have not gone far without them. Thank you for always

being there whether I am at home or a few thousand kilometers away. Finally, I thank God for all

the blessings thus far and regardless of the hardships in life, I know He’s still faithful till the end.

iv

Table of Contents

Acknowledgments.................................................................................................................iii

TableofContents...................................................................................................................iv

ListofTables..........................................................................................................................vi

ListofFigures........................................................................................................................vii

ListofAppendices..................................................................................................................ix

Chapter1:LiteratureReviewonMercuryMethylationandResearchObjectives.....................1

1.1 MercuryintheEnvironment.......................................................................................................1

1.2 MercuryMethylationinWetlands..............................................................................................3

1.3 MercuryinRiparianZones..........................................................................................................5

1.4 RiparianZoneHydrology.............................................................................................................6

1.5 StableMercuryIsotopes.............................................................................................................7

1.6 ResearchObjectives....................................................................................................................8

1.7 Hypotheses.................................................................................................................................9

1.8 References................................................................................................................................11

Chapter2:MercuryMethylationinRiparianAreasAcrossMinnesota..................................17

2.1 Introduction..............................................................................................................................17

2.2 Methods....................................................................................................................................21

2.2.1 ExperimentalDesign.............................................................................................................21

2.2.2 StudySite..............................................................................................................................23

2.2.3 SamplingMethods................................................................................................................25

2.2.4 AnalyticalMethods...............................................................................................................26

2.2.5 CalculationsandStatistics....................................................................................................27

2.3 Results.......................................................................................................................................28

2.3.1 Kmeth:MethylationRateConstants........................................................................................28

2.3.2 MeHgConcentrations...........................................................................................................30

2.3.3 PercentMeHg(%MeHg).......................................................................................................32

2.3.4 DissolvedOrganicCarbon(DOC)andSulphide.....................................................................33

v

2.3.5 MeHginSurfaceWater(SW)andGroundwater(GW).........................................................34

2.3.6 HydrologyofStudySites.......................................................................................................36

2.4 Discussion.................................................................................................................................46

2.5 Conclusion.................................................................................................................................51

2.6 References................................................................................................................................53

Appendix1:RiparianAreaStratigraphicLogs........................................................................60

Appendix2:SignificantStatisticalDifferences.......................................................................67

Appendix3:FieldandSamplingPhotography.......................................................................78

vi

List of Tables

Table 1: Site names for and abbreviations for each site in “High-5” study….………………….24

vii

List of Figures

Figure 1: Google Earth Landsat imagery, showing geographical location of study sites (Source:

Google Earth, 2016). ..................................................................................................................... 22

Figure 2: Bar graphs showing methylation rate constants (Kmeth) at each plot during all four

sampling events. Error bars show standard deviation of Kmeth between triplicate cores at each

plot. ............................................................................................................................................... 28

Figure 3: Bar graphs showing methylation rate constants (Kmeth) comparing different types of

riparian landscapes during all four sampling events. Error bars show standard deviation of

aggregated Kmeth in sediment cores for each of the riparian landscape types. .............................. 29

Figure 4: Scatterplot showing Kmeth against [MeHg] across all four sampling events. Both Kmeth

and [MeHg] are plotted on a logarithmic scale. ............................................................................ 30

Figure 5: Bar graphs showing [MeHg] at each plot during all four sampling events. Error bars

show standard deviation of [MeHg] between triplicate cores at each plot. .................................. 31

Figure 6: Bar graphs showing percent MeHg (%MeHg) at each plot during all four sampling

events. Error bars show standard deviation of %MeHg between triplicate cores at each plot. .... 32

Figure 7: (Left) Graph showing a weak, but positive significant relationship between DOC

against Kmeth. Note that the axis for both DOC and Kmeth are on a log scale. (Right) Graph

showing no significant relationship between sulphide concentrations against Kmeth. Both

regressions use data only from the in-stream plot. Note that the axis for both sulphide and Kmeth

are on a log scale. .......................................................................................................................... 34

Figure 8: Compiled surface water and groundwater MeHg concentrations across all study sites.

....................................................................................................................................................... 35

Figure 9: Time series of water levels at each instrumented plot all relative to a common datum at

RRWMA during 2016 sampling season. ...................................................................................... 36

Figure 10: Time series of water levels at each instrumented plot all relative to a common datum

at RRMH during 2016 sampling season. ...................................................................................... 37

viii

Figure 11: Time series of water levels at each instrumented plot all relative to a common datum

at MUS260 during 2016 sampling season. ................................................................................... 38

Figure 12: Time series of water levels at each instrumented plot all relative to a common datum

at MUSBB during 2016 sampling season. .................................................................................... 39

Figure 13: Time series of water levels at each instrumented plot all relative to a common datum

at THIEKV during 2016 sampling season. ................................................................................... 40

Figure 14: Time series of water levels at each instrumented plot all relative to a common datum

at THIMR during 2016 sampling season. ..................................................................................... 41

Figure 15: Time series of water levels at each instrumented plot all relative to a common datum

at KETBAN during 2016 sampling season. .................................................................................. 42

Figure 16: Time series of water levels at each instrumented plot all relative to a common datum

at KETRIF during 2016 sampling season. .................................................................................... 43

Figure 17: Time series of water levels at each instrumented plot all relative to a common datum

at VERBYK during 2016 sampling season. ................................................................................. 44

Figure 18: Time series of water levels at each instrumented plot all relative to a common datum

at VERGLD during 2016 sampling season. .................................................................................. 45

Figure 19: Vermillion site VERGLD just after snowmelt. .......................................................... 78

Figure 20: THIEKV site with drone photography. ...................................................................... 78

Figure 21: Installation of wells and piezometer nests at KETBAN. ........................................... 79

Figure 22: Sampling groundwater and measuring water levels at each plot at RRMH. .............. 79

Figure 23: Collecting Kmeth sediment cores at RRWMA site. .................................................. 80

Figure 24: Injecting stable isotope solution into sediment cores at the University of Minnesota

Duluth. .......................................................................................................................................... 80

ix

List of Appendices

Appendix 1: Riparian Area Stratigraphic Logs………………………………………………….53

Appendix 2: Statistical Significant Differences……………………………..…………………..60

Appendix 3: Field and Sampling Photography…...………………………………………..……74

1

Chapter 1: Literature Review on Mercury Methylation and Research

Objectives

1

1.1 Mercury in the Environment

Mercury (Hg) is a naturally occurring heavy metal element and is commonly found geologically

as cinnabar (HgS). Due to its low melting point, Hg exists in liquid state at standard ambient

temperature (25°C) and pressure (101.3kPa). Hg commonly exists in 3 species, elemental

mercury (Hg0), inorganic Hg (IHg), and organic Hg (MeHg or Me2Hg) and can form amalgams

with other metals such as gold, copper, and tin. These amalgams can be used in many

applications, from gold extraction in small scale artisanal gold mining to fillings in dental

procedures (Lacerda and Marins, 1997). Hg is also used in many household products, such as

compact fluorescent light bulbs and thermometers, however, these uses are slowly being phased

out and replaced with newer and more efficient technologies.

Hg0 is highly volatile due to its high vapour pressure, leading to large and effective fluxes into

the atmosphere either in natural or anthropogenic releases. Annually, natural sources account for

approximately 5307Mg and anthropogenic sources account for roughly 2320Mg of Hg emissions

into the global atmosphere (Pirrone et al., 2010). This substantial increase in Hg emission was

very prevalent during the industrial revolution and can be traced to a large number of point

sources (Lindberg and Stratton, 1998; Pirrone et al., 2010; Lamborg et al., 2002). Many of the

anthropogenic sources of Hg to the atmosphere are from burning fossil fuels, such as coal-fired

power plants, and from small scale artisanal gold mining operations (Pacyna et al., 2010; Pirrone

et al., 2010; Streets et al., 2011). The source of Hg to the environment is crucial in understanding

2

why Hg pollution occurs in non-source regions of the world, hence, Hg is considered a global

pollutant (Driscoll et al., 2013; Pacyna et al., 2016).

Elemental Hg has a relatively long residence times in the atmosphere and due to its stability,

long range atmospheric transport commonly occurs (Steffen et al., 2016; Schroeder and Munthe,

1998). When oxidized to gaseous Hg(II) or adsorbed into atmospheric particulate matter forming

Hg(p), Hg0 can be deposited onto terrestrial environments, either by wet or dry deposition

respectively (Greydon et al., 2008; Zhang et al., 2009; Lindberg et al.; 2007). Deposited

inorganic Hg can be methylated into MeHg through a wide group of microbial communities such

as methanogens, sulphate and iron reducing bacteria under favourable biogeochemical conditions

(Gilmour et al., 2013).

MeHg is one of the species that is most relevant to biological implications due to its capability to

bioaccumulate within organisms and biomagnify up to tropic levels in the food chain. As a

potent neurotoxin, wildlife and humans can be adversely affected even at relatively low

concentrations (Driscoll et al., 2013; Mergler et al., 2007; Scheulhammer et al., 2007). It

accumulates in muscle and fatty tissues of biota and is not easily excreted nor degraded. A main

source of exposure is through human consumption of contaminated food sources such as high

trophic level fish like shark and tuna (Li et al., 2014; Bosch et al., 2016; O'Bryhim et al., 2017).

Being able to cross the blood-brain barrier, Hg is damaging to the neurological system and can

be of grave concern to at risk individuals.

As such, there is precedence in studying Hg as a global pollutant. Hg is not limited to a local

region and due to the stability of elemental Hg, it may travel long distances before it gets

deposited in areas with previously thought low concentrations of Hg.

3

1.2 Mercury Methylation in Wetlands

Wetlands as sources of Hg to the aquatic environment are well studied in the scientific literature.

In wetlands, atmospherically deposited inorganic Hg can be methylated and transported to

nearby aquatic environments through shallow groundwater flows (Branfireun et al., 2005; St.

Louis et al., 1994). Since the process of Hg methylation is microbially mediated, the rate of

methylation and the amount of MeHg produced is a function of three major factors: (1) microbial

community, (2) biogeochemistry of environment, and (3) bioavailability of inorganic Hg. In the

case of wetlands as a source of MeHg, all three major factors have allowed microbial

communities to thrive and significantly methylate Hg.

It was previously thought that anaerobic sulphate reducing bacteria (SRB) and iron reducing

bacteria (FeRB) were solely responsible for the methylation of inorganic Hg to MeHg (Berman

and Bartha, 1986; Compeau and Bartha, 1985). Recent breakthroughs in gene sequencing have

demonstrated that the microbial communities responsible for Hg methylation are much wider

than this. Specifically, the presence of the hgcAB genetic markers allows microbes to methylate

Hg (Gilmour et al., 2013, Parks et al., 2013). Methanogens and firmicutes have since been added

to the list of microbial communities that methylate mercury in the environment (Hamelin et al.,

2011; Gilmour et al., 2013). Methanogens thrive in frequently inundated anaerobic

environments and the discovery of them can explain the large amounts of methylation in

frequently inundated wetland ecosystems (DeLaune et al. 2004; Du et al., 2017).

For microbial methylation of Hg to occur, favourable biogeochemical conditions are necessary

for the microbes, which are anaerobic and highly redox sensitive (Mitchell and Gilmour, 2008,

Marvin-DiPasquale and Agee, 2003; DeLaune et al. 2004; Grigal, 2003). Sulphate has been well

studied and known to be a limiting factor for Hg methylation, as it is seen to enhance MeHg

4

production when loading increases (Wasik et al., 2012; Jeremiason et al. 2006; Mitchell et al.,

2008). As sulphate gets reduced to sulphide by SRB, inorganic Hg is methylated to MeHg

(Gilmour et al., 1992). The depletion of sulphate and the increase of sulphide can be indicative of

activity by SRB, however, excess amounts of sulphide may in fact inhibit production of MeHg.

Excess sulphide may allow inorganic Hg to bind with the sulphide, forming HgS and decreasing

the amount of available inorganic bioavailable Hg. Hence, this may slow down Hg methylation

due to partitioning effects. Organic matter is thought to have similar effects, with complexation

reactions reducing the amount of free inorganic Hg in the environment available for methylation.

It has more recently been explored that under sulfidic conditions, organic matter may actually

enhance microbial methylation. The sulphide and organic matter may work synergistically as it

can reduce the effects of sulphide inhibition (Graham et al., 2012). MeHg production is often

linked to areas of high organic material, as organic material can act as an electron donor and the

recent work by Graham and colleagues can explain this linkage (Mitchell et al., 2008).

Thirdly, it is crucial to have bioavailable inorganic Hg for the methylation process to occur.

Newer inorganic Hg depositions have much greater rates of methylation than those that are older

and strongly sorbed to other substrates. As discussed earlier, high amounts of sulphide may be

indicative of productive methylating microbes, however, excess sulphide may lead to Hg

complexes such as HgS. This decreases the bioavailable fraction of inorganic Hg to be

methylated by microbes (Benoit et al., 1999). Similarly to sulphide, high amounts of humic

substances may lead to decreased bioavailability and therefore methylation, as complexation will

occur with inorganic Hg (Driscoll et al., 1995).

5

1.3 Mercury in Riparian Zones

As the ecotone between terrestrial and aquatic riverine environments, riparian zones are diverse

areas with a breadth of hydrological and sediment characteristics. They provide numerous

beneficial ecosystem services and are important habitat for numerous species of plants and other

organisms (Semlitsch and Bodie, 2003). Hydrologically, riparian areas are dynamic, with high

dependence on watershed drainage as well as shallow groundwater flows. Groundwater riparian

flows are a function of the geologic setting, governed by the sediment that lays between different

aquifer and aquitard layers (Vidon et al., 2004). In studying any form of aquatic contaminant

transport, one needs to address the hydrologic characteristics of the study area. The riparian zone

is an important convergence zone linking the hillslope and channel systems, not only for

contaminants, but also for nutrient dynamics (Burt and Pinay, 2005).

The hydrology of the adjacent riverine environments can play a crucial role in Hg dynamics.

Some river floodplains are temporarily but periodically flooded, and these areas are important to

biogeochemical cycling of contaminants, including Hg. An increase in floodplain inundation

frequency and duration can lead to higher MeHg production potential (Singer et al., 2016).

Watershed characteristics have an overarching control on methylation and transport of Hg into

riverine environments (Mitchell et al., 2008). Watersheds with increased wetland abundance are

highly correlated with increased riverine MeHg concentrations (Brigham et al., 2009).

Agricultural watersheds with some forested regions in Minnesota were also identified to have

MeHg production (Balogh et al., 2002). Such studies show that riparian zones, regardless of

landscapes, can be sites of Hg methylation if conditions are suitable for the microbial activity.

6

1.4 Riparian Zone Hydrology

Riparian areas have high ecological significance and produce many ecosystem services that are

driven by hydrological functions. Vegetated riparian areas assist in sediment retention, slowing

the erosive forces originating from the riverine environment (Micheli and Kirchner, 2002). This

is necessary to maintain streambank stability, along with preservation of precious arable lands

for greater vegetative growth and regional biodiversity (Hupp and Osterkamp, 1996; Naiman et

al., 1993). The vegetation and sediment allow riparian areas to retain a natural filtering

capability, slowing and reducing contaminant transport and excess nutrient runoff (Cooper et al.,

1987; Barling and Moore, 1994). Mainly achieved through shallow groundwater flows, riparian

areas prevent the contaminant transport downstream in non-point source pollution environments.

These hydrological functions keep the watershed in a ‘healthy’ state and prevent the many

problems occurring from mismanagement of watershed resources (Finkenbine, Atwater and

Mavinic, 2000).

The riparian area is a highly dynamic, hydrological zone with complex interactions between both

surface water and groundwater (Vidon and Hill, 2004; Butturini et al., 2002). They can be

hydrologically diverse landscapes and can be visualized as a mosaic, combining both surface

water and shallow groundwater exchanges (Malard et al., 2002). In general, a healthy

functioning riparian area would allow infiltration of water in the uplands and shallow

groundwater flows would convey this water towards the riverine aquatic environment

(Finkenbine, Atwater, and Mavinic, 2000). The water may enter the river in a riparian wetland,

or it may enter through hyporheic flow if the water percolates deeper into the underlying

sediment. If the precipitation or input of water exceeds the infiltration rate, surface runoff will

result, where water may transit directly to the river without passing through the riparian sediment

7

(Niehoff, Fritsch, and Bronstert, 2002). The amount of infiltration is highly related to the gravity

and capillary forces, where sediment and soil composition can also play a key role in infiltration

capacity (McCauley et al., 2002). Riparian areas can serve as recharge sites for aquifers (Koreny

et al., 1999). The recharge can buffer water table fluctuations, dissipate large flows, and prevent

flashy stream responses in the adjacent riverine environment (Butturini et al., 2002).

Sediment stratigraphy and underlying geology both play a large role in determining flow paths

and hydrologic connectivity in riparian areas (Malard et al., 2002). The hydrologic connection

between the uplands and the riparian areas can be seasonal and dependent on the depth and

composition of permeable sediments (Vidon and Hill, 2004; Schilling, 2007). Sediments such as

sands and gravel allow for higher hydraulic connectivity, whereas silts and clays would yield

much slower groundwater flows (Van Genuchten, 1980). Landscapes with steeper slopes, larger

amounts permeable sediments would allow for: (1) greater connection between uplands and the

river, and (2) longer flow durations (Bracken and Croke, 2007; Vidon and Hill, 2004). It must be

noted that flatter riparian topography is more likely to be influenced by water level fluctuations

from the river, and during dryer seasons of the year, it is not uncommon to detect flow reversals,

resulting from little water contribution from the uplands (Burt et al., 2002; Vidon and Hill,

2004). Flow pulses that occur throughout the year are also dependent on landscape and

geomorphic controls which can contribute water to the river as hyporheic flow (Malard et al.,

2002).

1.5 Stable Mercury Isotopes

Stable isotopes are highly versatile tools, used across a breadth of environmental studies (e.g.,

Bowen et al., 2005; Tetzlaff et al., 2015). Stable isotopes applications can be used to explore

processes in environmental geochemistry, and specifically as a tracer in mercury

8

biogeochemistry. The advancement of mass spectrometry has allowed much of analytical

chemistry to advance greatly, allowing trace metal analysis even in low environmental

concentrations. The use of inductively coupled plasma mass spectroscopy (ICP-MS) allows

isotope determination of many elements with low detection limits and reliable results

(Hintelmann and Ogrinc, 2002; Hintelmann and Evans, 1997). By coupling the detection of trace

elements with that ICP-MS and addition of enriched (isotopes wherein mass abundances are

specifically altered) stable isotopes, researchers now utilize multiple stable isotope additions to

trace multiple biogeochemical processes, such as both methylation and demethylation, at the

same time (Hintelmann and Ogrinc, 2002; Hintelmann and Harris, 2004; Eckley and

Hintelmann, 2006). The technique of adding enriched stable isotope to an environmental sample

is known as isotope dilution and calculating the ratios between each isotope allows for

concentration determination with high accuracy and precision (Lambertsson et al., 2001; Smith,

1993; Hintelmann and Evans, 1997; Hintelmann et al., 1995). These techniques as outlined by

Hintelmann and colleagues are well known and still used today. It is advised, however, that high

enrichment isotopes be used in such experiments as this allows the use of multiple isotopes to

trace different environmental processes with high precision.

higher precision when measuring and calculating the dilution ratios.

1.6 Research Objectives

This project lies within the context of a larger scale study called the “Minnesota Hi-5 Project”.

The overall objective of the “Minnesota Hi-5” project is to determine why MeHg concentrations

in top predator fish such as walleye are especially high in five particular rivers in Minnesota.

This thesis specifically examined the likelihood that differences in riparian MeHg availability is

due to differences in riparian zone methylation and transport. Within the “Minnesota Hi-5”

9

project, a two-stage approach was used to conceptualize Hg dynamics and transport mechanisms

for riparian zone within three distinct landscapes - forested, wetland-dominated, and agricultural.

In the first stage, MeHg production potential in riparian areas was examined, specifically trying

to measure Hg methylation rates. This is important to determine the possibility and magnitude of

potential in-situ MeHg production. In the second stage, riparian groundwater exchange was

investigated, to assess the potential for MeHg produced in the riparian zones to be transported to

the riverine environment. It is necessary to consider hydraulic connectivity, ancillary chemical

data, and sediment type for this objective. By investigating methylation rates and the

hydrological gradients in these riparian zones, we hope to conceptualize the Hg methylation and

transport for the three riparian landscapes selected for this study.

1.7 Hypotheses

Since there are two primary objectives, there are two principal hypotheses associated with this

study. One of the hypotheses is related to MeHg production, and the other is related to the

hydrological connectivity of the riparian zones.

1) Watersheds that have higher methylation rates in riparian sediments will have higher than

normal MeHg concentrations in surface water and groundwater.

2) Riparian areas as a source of MeHg to the riverine environment is a function of

hydrological gradient and flow direction; areas with gradients that permit significant

riparian exchange will have for greater concentrations of MeHg in stream.

In the first hypothesis, it is predicted that higher Hg methylation rates are positively correlated

with the accumulation of MeHg in water. MeHg accumulation is likely to occur in areas with

organic content, sulphide concentrations, and hydraulic connectivity. Inorganic Hg is often

10

transformed into MeHg through sulphate reducing bacteria. The microbial communities need

certain nutrients for their metabolism, and organic matter partly serves this purpose – most

clearly as a source of electron donors, but also as a potential source of bound nutrients. As

sulphate gets taken up through this microbial methylation process, it becomes the reduced form

sulphide. A positive relationship could then be deduced: as sulphide concentrations increase, so

should MeHg production if it is indeed tied to the activity of sulphate reducing bacteria.

However, the relationship between sulphide and MeHg is complicated, as high concentrations of

sulphide can also act as an inhibitor for Hg methylation. When high concentrations of sulphide

are found, compounds such as Hg sulphide can form and precipitate out of solution; thereby

limiting the bioavailable inorganic Hg for this methylation process. Thus, one needs to exercise a

degree of caution when examining the relationship between sulphide and MeHg concentrations.

Overall, it is important to also consider the hydrologic conditions when studying MeHg

production. Sulphate reducing bacteria generally exhibit higher productivity under anaerobic

conditions, which can be governed by water level changes in the ecosystem.

The second hypothesis relates to the hydrological conditions in each of the riparian zones.

Hydraulic connectivity, a function of sediment characteristics, determines the transit time of

water between the riparian zone and riverine environments. As suggested earlier, wetlands have

been documented as MeHg hot spots, and recent studies suggest riparian areas floodplains can

act as important sites of Hg methylation due to inundation frequency and extent (Singer et al.,

2016). It is likely that the riparian zones in this study are producing MeHg; therefore, the

importance of riparian zones to aquatic Hg concentrations is also related to the connectivity

between the riparian zone and riverine environment. Increased hydraulic connectivity can lead to

an increase of nutrient fluxes into the riparian landscapes and MeHg fluxes out of the riparian

zone.

11

1.8 References Balogh, S. J., Nollet, Y. H., & Offerman, H. J. (2005). A comparison of total mercury and methylmercury

export from various Minnesota watersheds. Science of the Total Environment, 340(1-3), 261-270. doi:10.1016/j.scitotenv.2004.08.013

Barling, R. D., & Moore, I. D. (1994). Role of Buffer Strips in Management of Waterway Pollution – A Review. Environmental Management, 18(4), 543-558. doi:10.1007/bf02400858

Benoit, J. M., Gilmour, C. C., Mason, R. P., & Heyes, A. (1999). Sulfide controls on mercury speciation and bioavailability to methylating bacteria in sediment pore waters. Environmental Science & Technology, 33(6), 951-957. doi:10.1021/es9808200

Berman, M., & Bartha, R. (1986). Levels of Chemical Versus Biological Methylation of Mercury in Sediments. Bulletin of Environmental Contamination and Toxicology, 36(3), 401-404.

Bosch, A. C., O'Neill, B., Sigge, G. O., Kerwath, S. E., & Hoffman, L. C. (2016). Mercury accumulation in Yellowfin tuna (Thunnus albacares) with regards to muscle type, muscle position and fish size. Food Chemistry, 190, 351-356. doi:10.1016/j.foodchem.2015.05.109

Bowen, G. J., Wassenaar, L. I., & Hobson, K. A. (2005). Global application of stable hydrogen and oxygen isotopes to wildlife forensics. Oecologia, 143(3), 337-348. doi:10.1007/s00442-004-1813-y

Bracken, L. J., & Croke, J. (2007). The concept of hydrological connectivity and its contribution to understanding runoff-dominated geomorphic systems. Hydrological Processes, 21(13), 1749-1763. doi:10.1002/hyp.6313

Branfireun, B. A., Krabbenhoft, D. P., Hintelmann, H., Hunt, R. J., Hurley, J. P., & Rudd, J. W. M. (2005). Speciation and transport of newly deposited mercury in a boreal forest wetland: A stable mercury isotope approach. Water Resources Research, 41(6), 11. doi:10.1029/2004wr003219

Brigham, M. E., Wentz, D. A., Aiken, G. R., & Krabbenhoft, D. P. (2009). Mercury Cycling in Stream Ecosystems. 1. Water Column Chemistry and Transport. Environmental Science & Technology, 43(8), 2720-2725. doi:10.1021/es802694n

Burt, T. P., & Pinay, G. (2005). Linking hydrology and biogeochemistry in complex landscapes. Progress in Physical Geography, 29(3), 297-316. doi:10.1191/0309133305pp450ra

Burt, T. P., Pinay, G., Matheson, F. E., Haycock, N. E., Butturini, A., Clement, J. C., . . . Maitre, V. (2002). Water table fluctuations in the riparian zone: comparative results from a pan-European experiment. Journal of Hydrology, 265(1-4), 129-148. doi:10.1016/s0022-1694(02)00102-6

Butturini, A., Bernal, S., Sabater, S., & Sabater, F. (2002). The influence of riparian-hyporheic zone on the hydrological responses in an intermittent stream. Hydrology and Earth System Sciences, 6(3), 515-525.

12

Compeau, G. C., & Bartha, R. (1985). Sulfate-reducing Bacteria – Principal Methylators of Mercury in Anoxic Esturine Sediment. Applied and Environmental Microbiology, 50(2), 498-502.

Cooper, J. R., & Gilliam, J. W. (1987). Phosphorous Resdistribution from Cultivated Fields Into Riparian Areas. Soil Science Society of America Journal, 51(6), 1600-1604.

DeLaune, R. D., Jugsujinda, A., Devai, I., & Patrick, W. H. (2004). Relationship of sediment redox conditions to methyl mercury in surface sediment of Louisiana Lakes. Journal of Environmental Science and Health Part a-Toxic/Hazardous Substances & Environmental Engineering, 39(8), 1925-1933. doi:10.1081/ese-120039365

Driscoll, C. T., Blette, V., Yan, C., Schofield, C. L., Munson, R., & Holsapple, J. (1995). The Role of Dissolved Organic-Carbon in the Chemistry and Bioavailability of Mercury in Remote Adirondack Lakes. Water Air and Soil Pollution, 80(1-4), 499-508. doi:10.1007/bf01189700

Driscoll, C. T., Mason, R. P., Chan, H. M., Jacob, D. J., & Pirrone, N. (2013). Mercury as a Global Pollutant: Sources, Pathways, and Effects. Environmental Science & Technology, 47(10), 4967-4983. doi:10.1021/es305071v

Du, H. X., Ma, M., Sun, T., Dai, X. Z., Yang, C. Y., Luo, F., . . . Igarashi, Y. (2017). Mercury-methylating genes dsrB and hgcA in soils/sediments of the Three Gorges Reservoir. Environmental Science and Pollution Research, 24(5), 5001-5011. doi:10.1007/s11356-016-8213-9

Eckley, C. S., & Hintelmann, H. (2006). Determination of mercury methylation potentials in the water column of lakes across Canada. Science of the Total Environment, 368(1), 111-125. doi:10.1016/j.scitotenv.2005.09.042

Finkenbine, J. K., Atwater, J. W., & Mavinic, D. S. (2000). Stream health after urbanization. Journal of the American Water Resources Association, 36(5), 1149-1160. doi:10.1111/j.1752-1688.2000.tb05717.x

Gilmour, C. C., Podar, M., Bullock, A. L., Graham, A. M., Brown, S. D., Somenahally, A. C., . . . Elias, D. A. (2013). Mercury Methylation by Novel Microorganisms from New Environments. Environmental Science & Technology, 47(20), 11810-11820. doi:10.1021/es403075t

Gilmour, C.C., Henry, E.A., and Mitchell, R. (1992). Sulfate stimulation of mercury methylation in freshwater sediments, Environmental Science & Technology, 26 (11), 2281-2287. doi: 10.1021/es00035a029

Graham, A. M., Aiken, G. R., & Gilmour, C. C. (2012). Dissolved Organic Matter Enhances Microbial Mercury Methylation Under Sulfidic Conditions. Environmental Science & Technology, 46(5), 2715-2723. doi:10.1021/es203658f

Graydon, J. A., Louis, V. L. S., Hintelmann, H., Lindberg, S. E., Sandilands, K. A., Rudd, J. W. M., . . . Mowat, L. D. (2008). Long-Term Wet and Dry Deposition of Total and Methyl Mercury in the Remote Boreal Ecoregion of Canada. Environmental Science & Technology, 42(22), 8345-8351. doi:10.1021/es801056j

13

Grigal, D. F. (2003). Mercury sequestration in forests and peatlands: A review. Journal of Environmental Quality, 32(2), 393-405.

Hamelin, S., Amyot, M., Barkay, T., Wang, Y. P., & Planas, D. (2011). Methanogens: Principal Methylators of Mercury in Lake Periphyton. Environmental Science & Technology, 45(18), 7693-7700. doi:10.1021/es2010072

Hintelmann, H., & Evans, R. D. (1997). Application of stable isotopes in environmental tracer studies - Measurement of monomethylmercury (CH3Hg+) by isotope dilution ICP-MS and detection of species transformation. Fresenius Journal of Analytical Chemistry, 358(3), 378-385. doi:10.1007/s002160050433

Hintelmann, H., Evans, R. D., & Villeneuve, J. Y. (1995). Measurement of Mercury Methylation in Sediments by using Enriched Stable Mercury Isotopes Combined with Methylmercury Determination by Gas-Chromatography Inductively-Coupled Plasma-Mass Spectroscopy. Journal of Analytical Atomic Spectrometry, 10(9), 619-624. doi:10.1039/ja9951000619

Hintelmann, H., & Harris, R. (2004). Application of multiple stable mercury isotopes to determine the adsorption and desorption dynamics of Hg(II) and MeHg to sediments. Marine Chemistry, 90(1-4), 165-173. doi:10.1016/j.marchem.2004.03.015

Hintelmann, H., & Ogrinc, N. (2003). Determination of stable mercury isotopes by ICP/MS and their application in environmental studies. Biogeochemistry of Environmentally Important Trace Elements, 835, 321-338.

Hupp, C. R., & Osterkamp, W. R. (1996). Riparian vegetation and fluvial geomorphic processes. Geomorphology, 14(4), 277-295. doi:10.1016/0169-555x(95)00042-4

Jeremiason, J. D., Engstrom, D. R., Swain, E. B., Nater, E. A., Johnson, B. M., Almendinger, J. E., . . . Kolka, R. K. (2006). Sulfate addition increases methylmercury production in an experimental wetland. Environmental Science & Technology, 40(12), 3800-3806. doi:10.1021/es0524144

Koreny, J. S., Mitsch, W. J., Bair, E. S., & Wu, X. Y. (1999). Regional and local hydrology of a created riparian wetland system. Wetlands, 19(1), 182-193.

Lacerda, L. D., & Marins, R. V. (1997). Anthropogenic mercury emissions to the atmosphere in Brazil: The impact of gold mining. Journal of Geochemical Exploration, 58(2-3), 223-229. doi:10.1016/s0375-6742(96)00068-4

Lambertsson, L., Lundberg, E., Nilsson, M., & Frech, W. (2001). Applications of enriched stable isotope tracers in combination with isotope dilution GC-ICP-MS to study mercury species transformation in sea sediments during in situ ethylation and determination. Journal of Analytical Atomic Spectrometry, 16(11), 1296-1301. doi:10.1039/b106878b

14

Lamborg, C. H., Fitzgerald, W. F., O'Donnell, J., & Torgersen, T. (2002). A non-steady-state compartmental model of global-scale mercury biogeochemistry with interhemispheric atmospheric gradients. Geochimica Et Cosmochimica Acta, 66(7), 1105-1118. doi:10.1016/s0016-7037(01)00841-9

Li, M. L., Sherman, L. S., Blum, J. D., Grandjean, P., Mikkelsen, B., Weihe, P., . . . Shine, J. P. (2014). Assessing Sources of Human Methylmercury Exposure Using Stable Mercury Isotopes. Environmental Science & Technology, 48(15), 8800-8806. doi:10.1021/es500340r

Lindberg, S., Bullock, R., Ebinghaus, R., Engstrom, D., Feng, X. B., Fitzgerald, W., . . . Seigneur, C. (2007). A synthesis of progress and uncertainties in attributing the sources of mercury in deposition. Ambio, 36(1), 19-32.

Lindberg, S. E., & Stratton, W. J. (1998). Atmospheric mercury speciation: Concentrations and behavior of reactive gaseous mercury in ambient air. Environmental Science & Technology, 32(1), 49-57. doi:10.1021/es970546u

Malard, F., Tockner, K., Dole-Olivier, M. J., & Ward, J. V. (2002). A landscape perspective of surface-subsurface hydrological exchanges in river corridors. Freshwater Biology, 47(4), 621-640. doi:10.1046/j.1365-2427.2002.00906.x

Marvin-DiPasquale, M., & Agee, J. L. (2003). Microbial mercury cycling in sediments of the San Francisco Bay-Delta. Estuaries, 26(6), 1517-1528. doi:10.1007/bf02803660

Mergler, D., Anderson, H. A., Chan, L. H. M., Mahaffey, K. R., Murray, M., Sakamoto, M., & Stern, A. H. (2007). Methylmercury exposure and health effects in humans: A worldwide concern. Ambio, 36(1), 3-11.

Micheli, E. R., & Kirchner, J. W. (2002). Effects of wet meadow riparian vegetation on streambank erosion. 2. Measurements of vegetated bank strength and consequences for failure mechanics. Earth Surface Processes and Landforms, 27(7), 687-697. doi:10.1002/esp.340

Mitchell, C. P. J., Branfireun, B. A., & Kolka, R. K. (2008a). Assessing sulfate and carbon controls on net methylmercury production in peatlands: An in situ mesocosm approach. Applied Geochemistry, 23(3), 503-518. doi:10.1016/j.apgeocliem.2007.12.020

Mitchell, C. P. J., Branfireun, B. A., & Kolka, R. K. (2008b). Spatial characteristics of net methylmercury production hot spots in peatlands. Environmental Science & Technology, 42(4), 1010-1016. doi:10.1021/es0704986

Mitchell, C. P. J., & Gilmour, C. C. (2008). Methylmercury production in a Chesapeake Bay salt marsh. Journal of Geophysical Research-Biogeosciences, 113, 14. doi:10.1029/2008jg000765

Naiman, R. J., Decamps, H., & Pollock, M. (1993). The Role of Riparian Corridors in Maintaining Regional Biodiversity. Ecological Applications, 3(2), 209-212. doi:10.2307/1941822

15

Niehoff, D., Fritsch, U., & Bronstert, A. (2002). Land-use impacts on storm-runoff generation: scenarios of land-use change and simulation of hydrological response in a meso-scale catchment in SW-Germany. Journal of Hydrology, 267(1-2), 80-93. doi:10.1016/s0022-1694(02)00142-7

O'Bryhim, J. R., Adams, D. H., Spaet, J. L. Y., Mills, G., & Lance, S. L. (2017). Relationships of mercury concentrations across tissue types, muscle regions and fins for two shark species. Environmental Pollution, 223, 323-333. doi:10.1016/j.envpol.2017.01.029

Pacyna, E. G., Pacyna, J. M., Sundseth, K., Munthe, J., Kindbom, K., Wilson, S., . . . Maxson, P. (2010). Global emission of mercury to the atmosphere from anthropogenic sources in 2005 and projections to 2020. Atmospheric Environment, 44(20), 2487-2499. doi:10.1016/j.atmosenv.2009.06.009

Pacyna, J. M., Travnikov, O., De Simone, F., Hedgecock, I. M., Sundseth, K., Pacyna, E. G., . . . Kindbom, K. (2016). Current and future levels of mercury atmospheric pollution on a global scale. Atmospheric Chemistry and Physics, 16(19), 12495-12511. doi:10.5194/acp-16-12495-2016

Parks, J. M., Johs, A., Podar, M., Bridou, R., Hurt, R. A., Smith, S. D., . . . Liang, L. Y. (2013). The Genetic Basis for Bacterial Mercury Methylation. Science, 339(6125), 1332-1335. doi:10.1126/science.1230667

Pirrone, N., Cinnirella, S., Feng, X., Finkelman, R. B., Friedli, H. R., Leaner, J., . . . Telmer, K. (2010). Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmospheric Chemistry and Physics, 10(13), 5951-5964. doi:10.5194/acp-10-5951-2010

Scheulhammer, A. M., Meyer, M. W., Sandheinrich, M. B., & Murray, M. W. (2007). Effects of environmental methylmercury on the health of wild birds, mammals, and fish. Ambio, 36(1), 12-18. doi:10.1579/0044-7447(2007)36[12:eoemot]2.0.co;2

Schilling, K. E. (2007). Water table fluctuations under three riparian land covers, Iowa (USA). Hydrological Processes, 21(18), 2415-2424. doi:10.1002/hyp.6393

Schroeder, W. H., & Munthe, J. (1998). Atmospheric mercury - An overview. Atmospheric Environment, 32(5), 809-822. doi:10.1016/s1352-2310(97)00293-8

Semlitsch, R. D., & Bodie, J. R. (2003). Biological criteria for buffer zones around wetlands and riparian habitats for amphibians and reptiles. Conservation Biology, 17(5), 1219-1228. doi:10.1046/j.1523-1739.2003.02177.x

Singer, M. B., Harrison, L. R., Donovan, P. M., Blum, J. D., & Marvin-DiPasquale, M. (2016). Hydrologic indicators of hot spots and hot moments of mercury methylation potential along river corridors. Science of the Total Environment, 568, 697-711. doi:10.1016/j.scitotenv.2016.03.005

Smith, R. G. (1993). Determination of Mercury in Environmental-Samples by Isotope Dilusion/ICPMS. Analytical Chemistry, 65(18), 2485-2488. doi:10.1021/ac00066a014

16

Soerensen, A. L., Jacob, D. J., Schartup, A. T., Fisher, J. A., Lehnherr, I., St Louis, V. L., . . . Sunderland, E. M. (2016). A mass budget for mercury and methylmercury in the Arctic Ocean. Global Biogeochemical Cycles, 30(4), 560-575. doi:10.1002/2015gb005280

Stlouis, V. L., Rudd, J. W. M., Kelly, C. A., Beaty, K. G., Bloom, N. S., & Flett, R. J. (1994). Importance of Wetlands as Sources of Methyl Mercury to Boreal Forest Ecosystems. Canadian Journal of Fisheries and Aquatic Sciences, 51(5), 1065-1076. doi:10.1139/f94-106

Streets, D. G., Devane, M. K., Lu, Z. F., Bond, T. C., Sunderland, E. M., & Jacob, D. J. (2011). All-Time Releases of Mercury to the Atmosphere from Human Activities. Environmental Science & Technology, 45(24), 10485-10491. doi:10.1021/es202765m

Tetzlaff, D., Buttle, J., Carey, S. K., McGuire, K., Laudon, H., & Soulsby, C. (2015). Tracer-based assessment of flow paths, storage and runoff generation in northern catchments: a review. Hydrological Processes, 29(16), 3475-3490. doi:10.1002/hyp.10412

Vangenuchten, M. T. (1980). A Closed-Form Equation for Prediction the Hydraulic Conductivity of Unsaturated Soils. Soil Science Society of America Journal, 44(5), 892-898.

Vidon, P. G. F., & Hill, A. R. (2004). Landscape controls on the hydrology of stream riparian zones. Journal of Hydrology, 292(1-4), 210-228. doi:10.1016/j.jhydrol.2004.01.005

Wasik, J. K. C., Mitchell, C. P. J., Engstrom, D. R., Swain, E. B., Monson, B. A., Balogh, S. J., . . . Almendinger, J. E. (2012). Methylmercury Declines in a Boreal Peatland When Experimental Sulfate Deposition Decreases. Environmental Science & Technology, 46(12), 6663-6671. doi:10.1021/es300865f

Zhang, L. M., Wright, L. P., & Blanchard, P. (2009). A review of current knowledge concerning dry deposition of atmospheric mercury. Atmospheric Environment, 43(37), 5853-5864. doi:10.1016/j.atmosenv.2009.08.019

17

Chapter 2: Mercury Methylation in Riparian Areas Across Minnesota

2

2.1 Introduction

Mercury (Hg) is a global pollutant and bioaccumulative neurotoxin that can adversely affect both

human and wildlife health at relatively low environmental concentrations (Driscoll et al., 2013;

Mergler et al., 2007; Scheulhammer et al., 2007). Atmospheric deposition of inorganic Hg from

diverse global sources is the main input of Hg to Minnesota watersheds and aquatic ecosystems

(Swain et al., 1992; Hines and Brezonik, 2007). Wet atmospheric deposition of Hg peaked in

Minnesota in the 1970’s with emissions having declined across the upper Midwest in more

recent decades (Engstrom and Swain, 1997). It is presumed that in-situ methylation of inorganic

Hg is the source of methylmercury (MeHg) to these environments in Midwest United States. In

Minnesota, sediments are observed to be possible sources of MeHg and have shown to have

significant substrate for methylation (Hines et al., 2007; Hines and Brezonik, 2007). With

production of MeHg and the bioaccumulative effects, it is therefore important to understand its

sources and fate from its deposition into the watershed.

MeHg is the most biologically relevant Hg species because most exposure is through diet and the

total Hg in most relatively high trophic level organisms (e.g., piscivorous fish) that compose the

diet of wildlife and humans is almost always nearly all MeHg (Bloom, 1992; Clayden et al.,

2017; Cipro et al., 2017; Zhang et al., 2014). Thus, the transformation of atmospherically

deposited inorganic Hg into MeHg is a key environmental control, in addition to food web

dynamics, on the accumulation of Hg in organisms (Bloom et al., 2003; Bloom, 1992; Pollman

and Axelrad, 2014; Lehnherr, 2014). Hg methylation is a microbially mediated process and many

18

advances have been made understanding the genetics behind Hg methylation. Recently, the

discovery of the presence of gene cluster hgcAB, demonstrated that this genetic marker is

required for Hg methylation to occur (Parks et al., 2013; Gilmour et al., 2013). This

breakthrough was significant, as it was previously thought that Hg methylation only occurred

through sulphate reducing bacteria (Desulfovibrionales and Desulfobacterales) and iron reducing

bacteria (Geobacter) (Compeau and Bartha, 1985; Gilmour et al., 1992; Kerin et al., 2006; King

et al., 2001). Through identification of the hgcAB gene, Hg methylation has been found to

include a much broader spectrum of microbial communities which include methanogens and

Firmicutes (Gilmour et al., 2013). Since methanogens are found in frequently inundated areas,

methylation in these areas is possibly more a function of the activity of these microbes than

previously believed (Hamelin et al., 2011; Gilmour et al., 2013).

Under favourable biogeochemical conditions, the microbial communities with the hgcAB genes

are highly active. Increased sulphate and organic carbon have been linked to synergistically

increase net MeHg production (Mitchell et al., 2008; Barkay et al., 1997). In addition, dissolved

porewater iron and sulphide are also known to be controls on MeHg production through controls

on Hg speciation (Creswell et al., 2017; Benoit et al., 1999). In general, addition of sulphate

increases net MeHg production; however, only to a certain threshold where high levels of

sulphide may inhibit methylation (Hsu-Kim et al., 2013; Benoit et al., 1999; Liu et al., 2009). It

is necessary for microbial communities to not only be in the optimal biogeochemical conditions,

but the bioavailable fraction of inorganic Hg must be present for the microbes to methylate Hg

(Benoit et al., 2001; Sunderland et al., 2009; Baptista-Salazar et al., 2017; Kadhum et al., 2017).

Microbial Hg methylation is present in a diverse number of environments, from wetlands and

rivers to water columns in both lakes and arctic marine environments (Mitchell et al., 2008;

19

Mitchell and Gilmour, 2008; Jeremiason et al., 2006; Eckley and Hintelmann, 2006; Lehnherr et

al., 2011; Brigham et al., 2009).

Riparian zones, the areas adjacent to streams, serve as a transitional environment between

riverine and terrestrial environments, with important ecological diversity (Naiman and Decamps,

1997). Riparian areas are often highly dynamic hydrological zones with complex interactions

between surface water and groundwater (Vidon and Hill, 2004; Butturini et al., 2002). The

sedimentology underlying riparian corridors is a significant influencing factor on both the local

and regional hydrology with more permeable sediments allowing for further and faster

hydrological conductivity (Schilling, 2007). Permeable sediments in riparian areas are commonly

linked to hyporheic flows in streams, where shallow groundwater transits beneath the river bed

and remerges in-stream close to riverbanks (Lawrence et al., 2013). The flow patterns in riparian

areas are not limited to the contribution of water from terrestrial areas into the river. Flow

reversals may occur where water from the riverine environment contributes and flows towards

terrestrial areas. These reversals are a function of both the hydrological input into the riparian

area, as well as the connectivity due to underlying geology and thus important to consider both

factors for magnitude and direction of riparian flow (Malard et al., 2002; Vidon and Hill, 2004).

The approach for studying Hg methylation in riparian ecotones can be intricate and perplexing as

it is a balance between the niche biogeochemical conditions, bioavailable inorganic Hg, and the

correct microbial communities with the hgcAB gene. A few studies have found that riparian

zones are sources of MeHg production and that hydrological flow conditions can be mechanisms

which explain the Hg found in fluvial environments (Vidon et al., 2013; Singer et al., 2016). Hg

dynamics in differing hydro-geomorphic riparian areas have been investigated in the US

Midwest and found to be heavily dependent on organic content, hydrological connectivity, and

20

location from Hg sources (Vidon et al., 2013). Geomorphic setting as it relates to flooding

potential is also important, in that frequent inundation can create “hot spots” and temporary “hot

moments” of Hg methylation potential (Singer et al., 2016). Both these recent studies show that

hydrological connectivity in conjunction with favourable biogeochemcial conditions for

microbial communities can allow for Hg methylation in riparian sediments.

The fluctuation of the water table is known to affect Hg dynamics in many landscapes, most

likely as a mechanism for recycling important redox elements that fuel microbial activity

(Coleman et al., 2015; Haynes et al., 2017; Eckley et al., 2017). Riparian landscapes constantly

undergo wetting and drying cycles, with complex surface and groundwater interactions (Vidon

and Hill, 2004; Butturini et al., 2002). In many cases, the hydrology of such environments may

contribute to increased Hg methylation, as increased inundation effects maintain anoxic zones

necessary for microbial methylating bacteria to speciate inorganic Hg to MeHg (Branfireun and

Roulet, 2002). Anoxic conditions due to inundation allow for greater reduction potential, as

oxygen is not present as the primary election acceptor. All of the microbes rely on the absence of

oxygen to be productive in Hg methylation (Pak and Bartha, 1998). With fluctuation water tables

in riparian systems, it can be hypothesized that this allows for temporary hypoxia, allowing all of

the microbes from the sulphate reducing, iron reducing, and methanogens communities to be

active in Hg methylation.

The overall objective of this study is to determine and characterize Hg methylation potential in

riparian areas across different landscape types and to determine if in-situ production from

riparian zones should be of concern to the adjacent riverine environments. Primarily, using

enriched Hg isotope incubations, we assess MeHg production potentials in sediments across a

range of riparian environments. We also investigate shallow groundwater exchange flow patterns

21

and hydrological gradients to assess the extent of possible contributions of riparian MeHg

production to loads in the adjacent riverine systems. In this study, we hypothesize that: (1)

watersheds that have higher methylation rates in riparian sediments will have higher than normal

MeHg concentrations in surface water and groundwater, and (2) riparian areas as a source of

MeHg to the riverine environment is a function of hydrological gradient and flow direction, as

areas with gradients that permit significant riparian exchange will have for greater concentrations

of MeHg in stream. This work fits within a larger project, named the “Minnesota Hi-5”, which

attempts to determine why Hg concentrations in riverine fish are significantly elevated in five

specific Minnesota rivers.

2.2 Methods

2.2.1 Experimental Design

Minnesota is a state with abundant freshwater and has one of the most extensive pollution

monitoring programs in the United States. Contaminant monitoring has identified five rivers,

where large predator sportfish, such as walleye, have relatively high Hg concentrations compared

to other rivers in the state. Only four of the original five watersheds were used in this study.

These included the Kettle (KET), Roseau (RR), Thief (THI), and Vermillion (VER) watersheds.

The fifth watershed in our study, Mustinka (MUS), was the control watershed where MeHg

concentrations in the fish were not particularly elevated. Collectively, these watersheds were

named “High-5” and include a mix of agricultural, forested, or wetland environments. Within

each watershed, two sites were selected each with differing riparian and geomorphological

characteristics (Figure 1). Each paired site is located on the same stretch of river and within 100

km of each other.

22

Figure 1: Google Earth Landsat imagery, showing geographical location of study sites (Source: Google Earth, 2016).

At each of the ten study sites, a perpendicular transect away from the river was delineated.

Within each transect, three plots were created spaced roughly 5 meters apart. The three plots in

this study are designated as the in-stream plot (Plot A), streamside plot (Plot B), and outer

riparian edge plot (Plot C), each with increasing distance away from the river channel.

Methylation sediment cores were retrieved at each of the sites in a triplicate by plot design across

one sampling event in 2015 (August) and three sampling events in 2016 (May, August, and

October). It should be noted that only the Roseau, Thief, and Mustinka watersheds were sampled

in the lone 2015 sampling event as the Kettle and Vermillion watersheds were not installed until

May 2016. The three sampling events in 2016 were chosen to capture the impacts of changing

hydrological flow patterns due to changes in seasonality and its possible impact on Hg

methylation. A total of 258 cores were retrieved during the entire experiment, with 42 cores in

August 2015, 85 cores in May 2016, 79 cores in August 2016, and 52 cores in October 2016.

23

2.2.2 Study Site

While this research is conducted in Minnesota, the environments selected for this study are

highly applicable to Canadian landscapes. For example, these landscapes include the agricultural

prairies of southern Manitoba and Saskatchewan, and the southern boreal forest of northwestern

Ontario.

The eastern watershed sites considered for this study are the Kettle and Vermillion rivers and are

part of the coniferous forest biome. The Roseau, Thief, and Mustinka sites are the western

watersheds in our study. The Roseau and Thief River sites are nestled in northern Minnesota’s

tallgrass aspen parkland biome and the Mustinka sites are in the prairie grassland biome. In each

of the Roseau and Thief watersheds, an agricultural and forested riparian area was selected for

the study. The Mustinka, control watershed, had one wetland site, along with the Kettle

watershed. The other Mustinka site is located in agricultural lands and other Kettle site in

forested landscapes. The Vermillion watershed had both sites in forested riparian landscapes

(Minnesota DNR, 2017).

Within each plot, a well was installed, each with a pressure transducer water level logger (Onset

HOBO Model U20) to record near surface groundwater levels. An additional pressure transducer

was installed but not submerged to compensate for atmospheric barometric pressure. In addition

to the wells, each plot was instrumented with a nest of shallow groundwater piezometers,

installed to various depths dependant on the sedimentology of each site. Each of the plots were

surveyed using a total station and all hydrological measurements used in this study were

compared using a common survey datum.

24

Table 1: Site names for and abbreviations for each site in “High-5” study. KettleWatershed(KET)Site RifleRange BanningStateParkAbbreviation KETRIF KETBAN

MustinkaWatershed(MUS)Site Highway260 BrokenBridgeAbbreviation MUS260 MUSBB

RoseauWatershed(RR)Site MoorhouseRd Wildlife

ManagementAreaAbbreviation RRMH RRWMA

ThiefWatershed(THI)Site Ekvoll MooseRiverAbbreviation THIEKV THIMR

VermillionWatershed(VER)Site Buyck GoldMineRdAbbreviation VERBYK VERGLD

25

2.2.3 Sampling Methods

Sediment cores were taken with 5 cm diameter polycarbonate core tubes with pre-drilled holes at

1 cm intervals. The holes were covered with clear silicone caulking to prevent leaks when the

isotope spike was injected. Triplicate sediment cores were retrieved in the channel at the in-

stream plot, and at or just below the water table for the streamside and outer-riparian plots. A

minimum of 10 centimeters of sediment were retrieved for each core. The sediment cores were

kept in coolers on ice until they were returned to the lab. An injection solution for each site was

prepared using surface water from each site and mixed with both inorganic 200Hg and Me201Hg

enriched stable isotopes. Each solution was equilibrated at room temperature for one hour and

kept in the dark. The sediment cores were injected with the equilibrated stable Hg isotope

solution at one centimeter intervals and incubated for 5 hours and at the ambient temperatures at

which the cores were retrieved. To prevent photodemethylation, the cores were kept in the dark

during this time. The sediment cores were then extruded, sectioned into three depth intervals (0-

2cm, 2-4cm, and 4-8cm) and flash frozen to prevent further methylation and demethylation.

Water samples were retrieved from both surface water and ground water and collected using the

EPA Method 1669 for trace metal sampling. All the water samples were collected using double

bagged Nalgene PETG bottles, and later partitioned for separate analysis. Groundwater was

retrieved from each piezometer and well using a Geotech GeoPump2 peristaltic pump with

Teflon® lines. The groundwater was partitioned for total Hg, MeHg, anions, cations, total

organic carbon, and preserved for the respective analysis. A separate glass vial was pre-loaded

with ZnAc for sulphide preservation and later analysis. Pore waters were extracted from

composited jars of in-stream sediment using Rhizons®.

26

2.2.4 Analytical Methods

Methylation potential (Kmeth) was assessed using isotope dilution methods from Hintelmann et al.

(2000), Mitchell and Gilmour (2008) and Hintelmann and Evans (1997). To prepare the samples

for analysis, the samples were freeze dried and homogenized. MeHg was analyzed using a

method based on aqueous phase ethylation. The sediment samples were distilled on a hot plate

and the distillate was ethylated in a glass bubbler with nitrogen and sodium tetraethyl borate

(NaTEB). The MeHg was accumulated on Tenax® traps and introduced into a gas

chromatograph-inductively coupled plasma mass spectrometer (ICP-MS) Model 7700x from

Agilent Technologies. MeHg analysis included an addition of Me199Hg as an internal tracer. The

standard reference material used for MeHg was ERM® estuarine sediment (CC580) and

International Atomic Energy Agency sediment (IAEA-158) with SRM recovery of 110.4±11.6%

(n=62). Replicate percent relative standard deviations (%RSD) was calculated for each isotope.

For ambient MeHg, Me200Hg, and Me201Hg, the %RSD was 12.2±13.7% (n=47), 7.1±6.0%

(n=67), and 4.8±3.9% (n=67) respectively. The method detection limit (MDL) for MeHg

analyses was 0.03 ng/g and calculated using 3 times the standard deviation of the blanks (n=69).

Sediment samples were digested in 70% ACS grade nitric acid and diluted with deionized water

prior to total Hg analysis. BrCl was added to the digestate at 0.5% v/v to oxidize all Hg into

Hg2+. Total Hg concentrations were determined on a Total Mercury Analyzer Model 2600 from

Tekran Instruments using cold vapour atomic fluorescence spectroscopy (CVAFS) hyphenated

with the same ICP-MS used for MeHg. The certified reference material used for total Hg was

MESS-3, Marine Sediment Reference Material from National Research Council Canada, with

recovery 104.1±3.3% (n=48). The spike recovery for total Hg was 105.5±5.5% (n=47). For

202THg, 200THg, and 201THg, the %RSD was 3.0±3.0% (n=47), 4.3±3.3% (n=47) and 6.1±5.5%

27

(n=47), respectively. The method detection limit (MDL) for THg analyses was 0.808 ng/g and

calculated using 3 times the standard deviation of the blanks (n=52).

Ancillary chemical data, dissolved organic carbon (DOC) and sulphide, was assessed by

colleagues at the University of Minnesota – Duluth. DOC was analyzed on a Total Organic

Carbon Analyzer from Shimadzu corporation. Sulphide was assessed using the Hach methylene

blue sulphide reagent kit, and subsequently run on a spectrophotometer at 664nm wavelength.

2.2.5 Calculations and Statistics

The statistical analyses were completed on Microsoft Excel and R, using the R Studio graphical

interface. Histograms and QQ plots were used to determine normality, and log transformations

were applied to select variables where needed. Statistica by Dell was also used in some

preliminary trend analyses. Water-level pressure data was barometrically compensated using

HOBOware® Pro, proprietary software by Onset® Computer Corporation and compiled using

Microsoft Excel.

Repeated measures ANOVA was performed on Kmeth, [MeHg], and %MeHg to determine

significant differences across all the sampling sites, significant differences across plots, and

interactive effects between site and plot. Although samples were sectioned by depth, values were

averaged for each sediment core to exclude issues with pseudo-replication, as depth was not

consistently significant and no discernable patterns were apparent. A separate ANOVA was used

for each sampling event and all statistical significance comparisons were set at α < 0.05. The

Tukey post-hoc test was used to identify sites and plots with significant differences.

28

2.3 Results

2.3.1 Kmeth: Methylation Rate Constants

Significant differences in Kmeth were observed across both site (p<0.001) and plot (p<0.0001) for

all 4 sampling events. Depth was only significant for the October 2016 and the lone 2015

sampling periods; however, no consistencies or patterns were discernable during these sampling

events. The interaction between site and plot was also significant (p<0.001), suggesting that the

effects are not mutually exclusive. Kmeth was observed to be significantly different across

different sites at the same plot.

Figure 2: Bar graphs showing methylation rate constants (Kmeth) at each plot during all

four sampling events. Error bars show standard deviation of Kmeth between triplicate cores at each plot.

Across most watersheds (Thief, Kettle, Roseau and Vermillion), Kmeth at the in-stream plot was

consistently significantly greater than at the near-stream or outer riparian edge. This was

observed in both Kettle watershed sites in August and October 2016, in both Roseau watershed

29

sites in 2015 and August 2016, Vermillion watershed sites in October 2016, and Thief watershed

sites in October 2016. The only watershed inconsistent with significantly elevated Kmeth in-

stream was the Mustinka watershed (our control watershed) where no within-site significant

variability was observed, except for site MUS260 during only May 2016, wherein Kmeth

significantly declined from the riparian edge toward in-stream. Most observations across seasons

show that Kmeth in forested riparian areas are consistently lower than wetland or agricultural

riparian landscapes (Figure 3). A more detailed explanation of statistical findings for Kmeth across

sites and by plot is found in appendix A2.1.1-A2.1.3.

Figure 3: Bar graphs showing methylation rate constants (Kmeth) comparing different types of riparian landscapes during all four sampling events. Error bars show standard deviation

of aggregated Kmeth in sediment cores for each of the riparian landscape types.

30

No relationships were observed when plotting MeHg concentrations against Kmeth across all four

sampling events (Figure 4).

Figure 4:Scatterplot showing Kmeth against [MeHg] across all four sampling events. Both

Kmeth and [MeHg] are plotted on a logarithmic scale.

2.3.2 MeHg Concentrations

Significant differences were observed in methylmercury (MeHg) concentrations across each site

(p<0.001) during each sampling event in 2015 and 2016. MeHg concentrations across plot was

significantly different across all sampling events in 2016 (p<0.001); however, this was not the

case in 2015. The interaction between site and plot was also observed to be significant,

suggesting that the effects of site and plot are not mutually exclusive. Depth was significant

across all sampling events (p < 0.001), except in October 2016 where it was insignificant. The

interaction between site and depth was observed to be significant during the August and October

2016 sampling periods (p < 0.01). Furthermore, the interaction between site, plot, and depth was

only observed to be significant during the August 2016, and 2015 sampling periods (p < 0.01).

31

Figure 5: Bar graphs showing [MeHg] at each plot during all four sampling events. Error bars show standard deviation of [MeHg] between triplicate cores at each plot.

Across most watersheds (Kettle, Mustinka, Roseau, and Thief), it was frequently observed that

ambient MeHg concentrations at the in-stream plot were significantly lower than at the

streamside or outer riparian plots. This was observed in both Roseau sites, RRWMA in May and

August 2016, and RRMH in August 2016 and 2015; both Mustinka sites during each sampling

event except in October 2016. At least one site at each the following watersheds (Kettle, Thief,

and Vermillion), were also consistent with the lower MeHg at the in-stream sediment, KETRIF

during May 2016 and August 2016, THIMR in May and August 2016, and VERBYK in May

2016. Only three sites had observations opposing this trend, which was the other Kettle site,

KETBAN in May 2016; Roseau site RRWMA during October 2016 and 2015; and Vermillion

site VERBYK in October 2016, wherein MeHg was significantly higher in-stream and lower at

the outer-riparian edge. A more detailed explanation of statistical findings for Kmeth across sites

and by plot is found in appendix A2.1.4-A2.1.6.

32

2.3.3 Percent MeHg (%MeHg)

Significant differences in percent methylmercury (%MeHg) were observed across all sites during

each sampling event in 2015 and 2016 (p < 0.001). %MeHg was also significantly different

across all sampling events at each plot (p < 0.01). The interaction between both site and plot

were significantly different across all sampling events (p < 0.001), suggesting that effects of site

and plot are not mutually exclusive. %MeHg was significant across all depths, during each

sampling event except October 2016 (p < 0.001). The interaction between site and depth for

%MeHg was only significant during August 2016, October 2016, and 2015 (p < 0.01). Finally,

the interaction between site, plot, and depth was only found to be significant for August 2016,

and 2015 (p < 0.001).

Figure 6: Bar graphs showing percent MeHg (%MeHg) at each plot during all four sampling events. Error bars show standard deviation of %MeHg between triplicate cores

at each plot.

33

Not surprisingly, %MeHg showed trends that were very similar to ambient MeHg

concentrations. Most watersheds (Kettle, Mustinka, Roseau, and Vermillion) each had one site

where %MeHg was significantly lower in-stream and higher at the outer-riparian edge. This was

observed at KETRIF and VERBYK in May 2016; MUS260 in May 2016, August 2016, and

2015; and RRWMA for all sampling events in 2016, however, 2015 was observed to have the

opposing trend. A few other sites had %MeHg that were lower in plots other than in-stream

which included KETBAN and THIEKV in May 2016, THIMR in August 2016, and VERBYK in

October 2016. RRWMA, MUS260, and VERBYK had higher %MeHg than the other sites in our

study. A more detailed explanation of statistical findings for Kmeth across sites and by plot is

found in appendix A2.1.7-A2.1.9.

2.3.4 Dissolved Organic Carbon (DOC) and Sulphide

DOC was weakly, but significantly correlated with Kmeth (r2 = 0.2411, p < 0.01), and

surprisingly, sulfide was not correlated with Kmeth (r2 = 0.008, p insignificant) at the in-stream

plots (Figure 7). Similarly, DOC moderately correlated with MeHg concentrations in pore water

observations.

34

Figure 7: (Left) Graph showing a weak, but positive significant relationship between DOC

against Kmeth. Note that the axis for both DOC and Kmeth are on a log scale. (Right) Graph

showing no significant relationship between sulphide concentrations against Kmeth. Both

regressions use data only from the in-stream plot. Note that the axis for both sulphide and

Kmeth are on a log scale.

Across all study sites, MUS260 had the highest sulphide concentrations, which were greater than

the other sites by three to four orders of magnitude (124.26-1440.85 µg/L in pore water at the in-

stream plot). The other Mustinka site, MUSBB, was also observed to have high sulphide

concentrations, however, was not as high as MUS260 (<300 µg/L). Excluding MUS260, the

mean sulfide concentrations in pore water across the other sites was 2.41 µg/L.

2.3.5 MeHg in Surface Water (SW) and Groundwater (GW)

MeHg concentrations were generally higher in surface water than in groundwater across a

majority of the study sites. This was the case for both of the sites in the Roseau and Vermillion

watersheds, and one site from each the Kettle, Mustinka, and Thief watersheds. KETRIF,

RRWMA, and THIEKV had the highest MeHg concentrations in surface water, whereas

MUSBB was consistently higher in groundwater. Other than MUSBB, Groundwater

concentrations of MeHg did not differ greatly among the other study sites and pore water

concentrations of MeHg were generally similar to that of surface water concentrations. Water

35

samples were analyzed by collaborators at Gustavus Augustus College in Minnesota. Although it

is apparent that this datum is from only one sampling event, water samples were collected on

many occasions. A compilation dataset was provided for the use of this thesis, therefore, no error

bars were included in the graphs (Figure 8).

Figure 8: Compiled surface water and groundwater MeHg concentrations across all study sites.

36

2.3.6 Hydrology of Study Sites

2.3.6.1 Roseau Watershed: RRWMA

Figure 9: Time series of water levels at each instrumented plot all relative to a common datum at RRWMA during 2016 sampling season.

Near-surface groundwater levels at RRWMA fluctuated significantly during the 2016 monitoring

period (Figure 9). During a large portion of the year, the water level at the outer-riparian plot is

higher than at the in-stream plot. This suggests that water predominantly moves from riparian

areas towards the stream. Towards the end of the year, there is an occasion where the in-stream

plot was slightly higher than the outer-riparian plot, indicating a short-term flow reversal. No

other flow reversals were detected at this site during 2016.

37

2.3.6.2 Roseau Watershed: RRMH

Figure 10: Time series of water levels at each instrumented plot all relative to a common datum at RRMH during 2016 sampling season.

Water level at the outer-riparian edge is consistently higher than at the streamside or in-stream

plots, however, on a few occasions during the year water levels deviated from this pattern

(Figure 10). This only occurred during lower groundwater drawdowns, where the outer-riparian

plot showed lower water levels compared to both the in-stream and streamside plots. Under

normal and higher than usual flow conditions, water flowed from the outer-riparian area to the

streams but during low flow conditions, however, the stream contributed water to the riparian

areas. The observed gradients were not particularly large across the transect, suggesting some but

not elevated riparian groundwater exchange. From field observations, the sediment was

predominantly silty at the surface, grading into finer sand at greater depths. The tightly packed

sediments likely explain the low gradients across the transect of plots. A couple of stratigraphic

logs showing the sedimentology for this site are found in appendix A1.3.

38

2.3.6.3 Mustinka Watershed: MUS260

Figure 11: Time series of water levels at each instrumented plot all relative to a common datum at MUS260 during 2016 sampling season.

The water level at outer-riparian edge is higher than the streamside plot, showing that the

hydrological gradient consistently flows towards the stream from the riparian area (Figure 11).

Field observations were noted that at this site, the water level at the streamside and in-stream

plots were both always above the ground surface. At this wetland site, water levels were very

consistent during the year with no large deviations in the river stage and no flow reversals were

detected at this site during 2016. At the streamside plot, a piezometer inserted at depth 160cm

was free flowing artisanal, but no other piezometers or wells at any other plot and site had

artisanal characteristics. During sampling, we found that the sediments found at this site were

very loose and unconsolidated, likely explaining the higher hydrological gradient at this site.

39

2.3.6.4 Mustinka Watershed: MUSBB

Figure 12: Time series of water levels at each instrumented plot all relative to a common datum at MUSBB during 2016 sampling season.

During 2016, many minor water level fluctuations were observed at all of the plots at this site,

however a generally decreasing trend was observed during most of the year. The in-stream plot

was consistently higher than the streamside and outer-riparian plots, resulting in contribution of

water from the stream to the riparian area (Figure 12). At MUSBB, flow reversals are common,

with a general hydrological gradient towards the riparian areas. The outer riparian plot and

streamside plot follow closely with each other, with slight deviations from the in-stream plot.

The surficial sediment was predominantly a mixture of silty sand but graded into gravel at

greater depth (~100cm). The sediment was more unconsolidated, allowing for greater

connectivity and riparian groundwater exchange. A couple of stratigraphic logs showing the

sedimentology for this site are found in appendix A1.2.

40

2.3.6.5 Thief Watershed: THIEKV

Figure 13: Time series of water levels at each instrumented plot all relative to a common datum at THIEKV during 2016 sampling season.

In 2016, water levels at the in-stream plot were always slightly higher than at the streamside plot,

showing a clear hydrological gradient from the stream towards the riparian area (Figure 13).

Although not consistently inundated, this site maintained wet sediment conditions throughout the

year as the streamside plot was occasionally inundated with water. The sediments at this site

were organic, silty, and unconsolidated at the surface, and became coarser as depth increased.

Wetter sediments were commonly observed at the surface with dryer sediments at depth. The

unconsolidated, loosely packed sediment at the surface along with the coarser sediments at depth

is likely to contribute to the higher hydrologic connectivity at this site. A couple of stratigraphic

logs showing the sedimentology for this site are found in appendix A1.4.

41

2.3.6.6 Thief Watershed: THIMR

Figure 14: Time series of water levels at each instrumented plot all relative to a common datum at THIMR during 2016 sampling season.

In 2016, the water levels observed at the THIMR site were frequently higher at the outer-riparian

edge than at the in-stream and streamside plots, in which these plots followed closely with each

other. The flow patterns at the in-stream plot were very flashy, mimicking patterns similar to a

very urbanized watershed, with very low lag times and short recession limbs (Figure 14). This is

due to the upstream impoundment releasing water into the river for agriculture flooding control,

explaining the flat portions of the graph in Figure 8. During large controlled, sustained releases

of water, the graph plateaus and stays flat until the gates of the impoundment are closed. When

the gates are shut, the water level recorded in the in-stream plot also drops rapidly, resulting in

the flat line adjacent to the x-axis. The in-stream plot recorded this event well and the outer-

riparian plot located farthest from the river has a more muted response when compared to the

streamside plot. The sediments are coarse and sandy at the surface, allowing for high

42

connectivity. A couple of stratigraphic logs showing the sedimentology for this site are found in

appendix A1.5.

2.3.6.7 Kettle Watershed: KETBAN

Figure 15: Time series of water levels at each instrumented plot all relative to a common datum at KETBAN during 2016 sampling season.

The water levels observed at the in-stream plot and the streamside plots were near identical,

showing that high hydrological connectivity has a significant role in these observations (Figure

15). The water levels in these plots were greater at both the in-stream and streamside plots than

at the outer-riparian plot, showing contribution of water from the riparian zone to the stream at

KETBAN. On a few occasions, water levels at all the plots changed significantly under a short

period of time which serves as further evidence supporting high hydrological connectivity

between plots.

43

2.3.6.8 Kettle Watershed: KETRIF

Figure 16: Time series of water levels at each instrumented plot all relative to a common datum at KETRIF during 2016 sampling season.

The water levels observed at KETRIF are consistently higher at the streamside plot than at the

in-stream plot, suggesting that flow is predominantly from the riparian areas to the stream

(Figure 16). There are no large and drastic changes in the water level at either plot except on a

few occasions. Tighter, silty organic sediment was found at the surface, grading into looser sand

and gravel at depth. The consistent water levels are likely a function of less consolidated

sediment at depth and the tight sediment at the surface allows for more muted responses in from

precipitation events. A couple of stratigraphic logs showing the sedimentology for this site are

found in appendix A1.1.

44

2.3.6.9 Vermillion Watershed: VERBYK

Figure 17: Time series of water levels at each instrumented plot all relative to a common datum at VERBYK during 2016 sampling season.

In 2016, water levels at the instream were consistently higher than at the streamside and outer-

riparian plots at this site, resulting in the stream is contributing water to the riparian areas (Figure

17). The water levels at the in-stream plot were significantly higher during the first half of the

year, and likely due to the large amounts of snowmelt observed late into the year. The water

levels are seen to follow closely with the streamside plot, where occasional surface flooding of

the streamside plot was observed during site visits. At the streamside plot, the sediments were

sandy and graded into gravel, however, at the outer-riparian plot, a majority of the sediments

were a silty-clay texture. The silty-clay is a confining layer in the outer-riparian plot, and

hydrological inputs to the riparian sediment is at depth. At the streamside plot, the coarser

sediment is likely to act as a recharge area for the outer-riparian plot. A couple of stratigraphic

logs showing the sedimentology for this site are found in appendix A1.6.

45

2.3.6.10 Vermillion Watershed: VERGLD

Figure 18: Time series of water levels at each instrumented plot all relative to a common datum at VERGLD during 2016 sampling season.

Similar to VERBYK, many of the water levels across the plots were higher at the beginning of

the year due to high amounts of snowmelt. The water levels at the in-stream plot were

consistently higher than the streamside and outer-riparian plot across the entire 2016 season,

indicative of flow from the stream to the riparian area (Figure 18). This was not surprising, as

again, the streamside plot was occasionally inundated with water during the high flow

conditions. Peat and organic matter were widely distributed at this site and extended to great

depths (137+ cm). A stratigraphic log showing the sedimentology for this site are found in

appendix A1.7.

46

2.4 Discussion

Kmeth measured across different riparian landscapes and seasons was not definitively different,

which suggests that riparian areas as a whole are not likely to be the primary source of MeHg to

fish in these “High-5” watersheds. Especially in the case for the Vermillion and Kettle eastern

Minnesota watersheds, Kmeth was similar to the Mustinka control watershed. Formation of MeHg

is likely to occur elsewhere in the watershed, possibly in hydrologically connected wetlands

since wetlands are known hotspots for Hg methylation (Mitchell et al., 2008). Minnesota is also

home to numerous freshwater lakes, and potential Hg methylation can occur in both the lake

sediments as well as the oxic water column (Diez et al., 2016; Pak and Bartha, 1998; Fleming et

al., 2006). Sediment have long been known to be sites of Hg methylation due to anoxic

conditions and with the correct biogeochemical conditions, they can be highly productive

(Gilmour et al., 1992; Gilmour and Henry, 1991; Fleming et al., 2006; Furutani and Rudd, 1980;

Pak and Bartha, 1998). Very recently, studies have shown that Hg methylation can occur even in

oxic water of freshwater lakes (Diez et al., 2016; Bravo et al., 2017). Although we did not

measure Kmeth beyond riparian areas, it is not without reason to believe methylation is likely to

occur in other regions of the watershed. The relatively low MeHg production capacity of most

riparian areas suggests that riparian MeHg production is not something that can or should be

managed at a watershed level in an attempt to impact fish MeHg concentrations in the Hi-5

watersheds.

Surface water MeHg concentrations were generally higher than the groundwater concentrations

regardless of hydrological flow patterns. Half of the study sites (RRMH, RRWMA, MUS260,

THIMR, and KETRIF) demonstrated hydrological gradients that move water from the stream to

the riparian area and the other half (VERBYK, VERGLD, MUSBB, THIEKV, and KETBAN)

47

demonstrated the opposite gradient. With some sites demonstrating hydrological gradients that

move water from the stream to the riparian areas, the flux of Hg also follows this pattern. The

dominant flow direction by itself is significant evidence that even if MeHg is produced in the

riparian areas, there is little opportunity for it to move into the stream; at least at these study

sites. At a few study areas, particularly both sites in the Kettle and Roseau watersheds, we find

that surface water MeHg concentrations are often greater than the groundwater concentrations on

several sampling occasions, indicative of an external source of MeHg upstream from the study

sites. On only a few occasions were concentrations of MeHg in pore waters retrieved from the

in-stream plots were similar to surface water concentrations. Thus, methylation in stream

sediments may contribute some MeHg to the rivers via diffusive or advective hyporheic fluxes,

but this is likely only a sporadic source given the predominance of higher surface water

concentrations. In addition to this, across a majority of sites, MeHg concentrations and %MeHg

are both more significantly elevated at the outer-riparian plot compared to the in-stream or

streamside plots, signifying evidence that MeHg may in fact be “trapped” within riparian

sediments. The sites that do, however, demonstrate hydrological gradients that move water from

the riparian area to the stream may not be a large and significant source of MeHg to the riverine

environment. Four out of the five sites that show this gradient still demonstrate elevated surface

water concentrations of MeHg than the groundwater, further indicative that groundwater

contributions from riparian areas are not the sole source of MeHg to the stream. The hydrological

connectivity is arguably important to determine fluxes of MeHg, however, coupling the

magnitude of MeHg measured in both surface and groundwater with the flow patterns can

determine relative importance of riparian areas as a source of MeHg. In this case, the dominant

pattern of higher surface water MeHg compared to riparian groundwater regardless of hydrologic

48

flow direction further suggests that riparian areas are not the only source of MeHg to fish in

these “High-5” streams and its relative importance is low.

It is expected that a positive linear relationship would exist with increased Hg methylation

leading to an increase in MeHg concentrations, however, this was not the case across all our

sampling events, likely indicative of demethylation that can occur simultaneously. No clear

relationship, either positive or negative, was observed between MeHg concentrations and Kmeth.

Methylation leads to an increase in MeHg concentrations, however, demethylation would lead to

decreased concentrations of MeHg, therefore, if demethylation exceeds methylation,

accumulation of MeHg would not occur. Higher rates of demethylation would also lead to lower

%MeHg as well, as this process would increase inorganic Hg concentrations and decrease

organic Hg concentrations. Although we did not measure Kdemeth, across most of our sites we find

that %MeHg is not significantly elevated, further supporting evidence that demethylation is

process that is likely occurring and should be investigated in further studies.

It was previously thought that seasonal variability would be present during our sampling events,

however, little seasonal variability was observed across Kmeth, [MeHg], and %MeHg. This is

likely due to relatively consistent hydrological gradients across plots at each site. Previous

studies have identified large water level fluctuations can heavily stimulate Hg methylation

(Eckley et al., 2015, Eckley at al., 2017). The studies have also identified that seasonally

inundated areas show higher methylation than permanently inundated areas. Hydrological flow

patterns can change the redox gradient of the sediment, with inundation allowing for anaerobic

conditions. The non-conformity to seasonality is reflected in most of our sites, with minor

fluctuations in the water levels, which is likely due to lower hydrological inputs and outputs in

49

the system. The relatively consistent hydrology throughout the year therefore allows for minimal

seasonal variability in Kmeth, [MeHg], and %MeHg.

Wetland and agricultural riparian landscapes were slightly higher in Kmeth, MeHg, and [MeHg]

than in forested landscapes, which may be a function of the quantity of available organic matter.

In agricultural and wetland landscapes, it is common to have greater amounts of organic

substrates (Dalzell et al., 2007; Bridgham et al., 1998). Past research has shown that a labile

carbon source alone does not significantly increase MeHg production, however, in conjunction

with the presence of sulphate, will yield higher MeHg production than only with sulphate

additions alone (Mitchell et al., 2008). A recent study discovered that having some dissolved

organic matter (DOM) may enhance methylation, as it can slow the formation of HgS and

prevent sulphide inhibition effects (Graham et al., 2012). Since DOC has a strong affinity of Hg,

too much can decrease bioavailability, however, it can also act as a possible transport vector. In

our study, the relationship between DOC and Kmeth is weakly but positively related. DOC was

also weakly correlated with MeHg concentrations in pore water. In both wetlands and

agricultural landscapes, the quality of organic carbon compounds is likely higher in abundance,

which can, but not definitively, explain the slightly elevated levels of Kmeth, MeHg, and [MeHg].

In contrast, forested riparian areas are not as likely to have as much organic rich sediment, and

mainly have mineral sediments. With the complex chemical relationship between organic carbon

compounds and sulphide, these confounding factors can both increase and decrease inorganic Hg

bioavailability.

Sulphide was not exceptionally high at most of our study sites and under low sulphide

environmental conditions, Hg forms complexes with DOC and other organic components,

thereby limiting the availability of inorganic Hg to be methylated (Schuster et al., 2008). In most

50

of the watersheds, except Mustinka, sulphide concentrations were generally low, and likely

explains the slightly lower Kmeth observed across most sites. It should be noted, however, that

sulphide accumulation is a function of sulphate reduction, indicative of activity by sulphate

reducing bacteria. Sulfide was high in the Mustinka wastershed, and more specifically at

MUS260, sulfide was the highest, up to 3 orders of magnitude higher than the rest of the sites.

Sulfide inhibition effects were evident especially at the instream plot, as highly sulfidic

environments decrease bioavailaibilty of inorganic Hg. The formation of HgS, inhibits microbial

Hg methylation removal of inorganic Hg limits the capacity of MeHg formation. In microbially

mediated Hg methylation, too little or too much sulfide can both decrease methylation and this

was likely the case in our study sites. Although we measured Kmeth and low sulphide

concentrations, it is possible that there may be other microbial communities that are methylating

Hg that are not sulphate reducers. Recent studies have found that methanogens are Hg

methylators in anaerobic environments, such as in rice paddies, and it is not without reason to

believe that methylation at our sites may be a contribution from such microbial communities

(Gilmour et al., 2013).

Although few studies have investigated riparian area Hg dynamics in the past, this study

specifically examines the potential for riparian zones as active Hg methylating landscapes.

Recent research has investigated Hg dynamics with water geochemistry and hydrological

indicators, but never have measured methylation rate constants directly (Vidon et al., 2013;

Singer et al., 2016). Singer and colleagues deduced rate constants through a mathematical

relationship with organic material using loss-on-ignition results. Although a good start, that was

the closest to measuring Hg methylation, that we know of, in riparian areas. Our study fills this

gap by directly performing methylation assays and calculating Kmeth using stable isotope

techniques. Overall, Kmeth is rather average compared to measurements in other environments,

51

such as arctic wetlands (0.029-0.071 d-1), fresh water wetlands in Florida everglades (<0.001–0.3

d-1), and saltmarshes (0.002 - 0.07 d-1) (Marvin-DiPasquale et al., 2003; Mitchell and Gilmour,

2008; Gilmour et al., 1998; Lehnherr et al., 2012).

It was originally predicted that riparian areas in these “High-5” watersheds were sources of

MeHg to the riverine environment, in which top-predator fish accumulated high levels of MeHg.

Although methylation was occurring, we find that riparian areas are not likely to be the primary

source of MeHg to the riverine environment, and consequently, top-predator fish. Within the

watersheds, many areas have potential in methylating Hg under the right conditions, but to

determine the source of MeHg to the “High-5” watersheds further studies are needed to

investigate other probable locations as being stronger MeHg sources to the streams. It must be

noted that no biotic component was integrated as a part of this paper, however, collaborators at

the University of Wisconsin – LaCrosse are continuing to investigate Hg in food webs of the

“High-5” watersheds. Other future research areas should include possible tributaries that may

seasonally link to areas of known high methylation such as wetlands. Surrounding lakes should

also be investigated, where methylation in both the water column as well as the sediment may be

a source of MeHg to the streams.

2.5 Conclusion

The original hypothesis was that watersheds that have higher methylation rates in riparian

sediments will also have higher MeHg concentrations in water. Our study found that this was not

always the case, as some of the sites that have higher methylation did not have higher than

normal MeHg concentrations in water. Within the riparian zone, we found that methylation was

generally highest at the instream environments and lower towards the riparian edge.

Groundwater concentrations were consistently lower in MeHg concentrations than surface water

52

or pore water. In addition, wetland riparian landscapes, with the exception of one site, had

relatively high Kmeth, and forested landscapes have relatively lower Kmeth.

We also hypothesized that riparian areas as a source of MeHg is strongly dependent on

hydrological connectivity of riparian areas. This study found that riparian areas do not methylate

as much as expected, but rather the stream may supply MeHg towards the riparian areas at some

sites. The highest measured MeHg concentrations were commonly in surface water, and coupled

with the hydrological gradient, it is possible that the influx of MeHg from surface water may be

greater than the Hg methylation in these areas. The sites demonstrate a hydrological gradient

from the outer riparian to the stream, still have higher concentrations of MeHg in surface water

than in groundwater, further supporting that MeHg contribution from the riparian areas are not

the sole source of MeHg in stream. With relation to the large scope of the “High-5” project, it is

not likely that riparian production of MeHg is responsible for the higher than normal

concentrations found in top-predator fish. It may be likely that sources of MeHg lie elsewhere

within each of the watershed and further studies are needed to identify such areas. Although Hg

methylation does occur in riparian areas, the production and transport of MeHg is not

significantly large and should not be a cause for concern at the watershed scale. We suggest

caution as not all riparian areas have similar flow patterns and methylation rates to that of the

“High-5” study sites. Other areas that have flow patterns from productive Hg methylating

riparian sites towards the stream may instead have a dominant flux towards the aquatic

environment.

53

2.6 References Baptista-Salazar, C., Richard, J. H., Horf, M., Rejc, M., Gosar, M., & Biester, H. (2017). Grain-size

dependence of mercury speciation in river suspended matter, sediments and soils in a mercury

mining area at varying hydrological conditions. Applied Geochemistry, 81, 132-142.

doi:10.1016/j.apgeochem.2017.04.006

Barkay, T., Gillman, M., & Turner, R. R. (1997). Effects of dissolved organic carbon and salinity on

bioavailability of mercury. Applied and Environmental Microbiology, 63(11), 4267-4271.

Benoit, J. M., Gilmour, C. C., & Mason, R. P. (2001). The influence of sulfide on solid phase mercury

bioavailability for methylation by pure cultures of Desulfobulbus propionicus (1pr3).

Environmental Science & Technology, 35(1), 127-132. doi:10.1021/es001415n

Benoit, J. M., Gilmour, C. C., Mason, R. P., & Heyes, A. (1999). Sulfide controls on mercury speciation

and bioavailability to methylating bacteria in sediment pore waters. Environmental Science &

Technology, 33(6), 951-957. doi:10.1021/es9808200

Bloom, N. S. (1992). On the Chemical Form of Mercury in Edible Fish and Marine Invertebrate Tissue.

Canadian Journal of Fisheries and Aquatic Sciences, 49(5), 1010-1017. doi:10.1139/f92-113

Bloom, N. S., Preus, E., Katon, J., & Hiltner, M. (2003). Selective extractions to assess the

biogeochemically relevant fractionation of inorganic mercury in sediments and soils. Analytica

Chimica Acta, 479(2), 233-248. doi:10.1016/s0003-2670(02)01550-7

Branfireun, B. A., & Roulet, N. T. (2002). Controls on the fate and transport of methylmercury in a boreal

headwater catchment, northwestern Ontario, Canada. Hydrology and Earth System Sciences, 6(4),

783-794.

Bravo, A. G., Bouchet, S., Tolu, J., Bjorn, E., Mateos-Rivera, A., & Bertilsson, S. (2017). Molecular

composition of organic matter controls methylmercury formation in boreal lakes. Nature

Communications, 8, 9. doi:10.1038/ncomms14255

Brigham, M. E., Wentz, D. A., Aiken, G. R., & Krabbenhoft, D. P. (2009). Mercury Cycling in Stream

Ecosystems. 1. Water Column Chemistry and Transport. Environmental Science & Technology,

43(8), 2720-2725. doi:10.1021/es802694n

54

Bridgham, S. D., Updegraff, K., & Pastor, J. (1998). Carbon, nitrogen, and phosphorus mineralization in

northern wetlands. Ecology, 79(5), 1545-1561.

Butturini, A., Bernal, S., Sabater, S., & Sabater, F. (2002). The influence of riparian-hyporheic zone on

the hydrological responses in an intermittent stream. Hydrology and Earth System Sciences, 6(3),

515-525.

Cipro, C. V. Z., Montone, R. C., & Bustamante, P. (2017). Mercury in the ecosystem of Admiralty Bay,

King George Island, Antarctica: Occurrence and trophic distribution. Marine Pollution Bulletin,

114(1), 564-570. doi:10.1016/j.marpolbul.2016.09.024

Clayden, M. G., Lescord, G. L., Kidd, K. A., Wang, X. W., Muir, D. C. G., & O'Driscollx, N. J. (2017).

Using Sulfur Stable Isotopes to Assess Mercury Bioaccumulation and Biomagnification in

Temperate Lake Food Webs. Environmental Toxicology and Chemistry, 36(3), 661-670.

doi:10.1002/etc.3615

Compeau, G. C., & Bartha, R. (1985). Sulfate-reducing Bacteria – Principal Methylators of Mercury in

Anoxic Estuarine Sediment. Applied and Environmental Microbiology, 50(2), 498-502.

Creswell, J. E., Shafer, M. M., Babiarz, C. L., Tan, S. Z., Musinsky, A. L., Schott, T. H., . . . Armstrong,

D. E. (2017). Biogeochemical controls on mercury methylation in the Allequash Creek wetland.

Environmental Science and Pollution Research, 24(18), 15325-15339. doi:10.1007/s11356-017-

9094-2

Dalzell, B. J., Filley, T. R., & Harbor, J. M. (2007). The role of hydrology in annual organic carbon loads

and terrestrial organic matter export from a midwestern agricultural watershed. Geochimica Et

Cosmochimica Acta, 71(6), 1448-1462. doi:10.1016/j.gca.2006.12.009

Diez, E. G., Loizeau, J. L., Cosio, C., Bouchet, S., Adatte, T., Amouroux, D., & Bravo, A. G. (2016).

Role of Settling Particles on Mercury Methylation in the Oxic Water Column of Freshwater

Systems. Environmental Science & Technology, 50(21), 11672-11679.

doi:10.1021/acs.est.6b03260

Driscoll, C. T., Mason, R. P., Chan, H. M., Jacob, D. J., & Pirrone, N. (2013). Mercury as a Global

Pollutant: Sources, Pathways, and Effects. Environmental Science & Technology, 47(10), 4967-

4983. doi:10.1021/es305071v

55

Eckley, C. S., & Hintelmann, H. (2006). Determination of mercury methylation potentials in the water

column of lakes across Canada. Science of the Total Environment, 368(1), 111-125.

doi:10.1016/j.scitotenv.2005.09.042

Eckley, C. S., Luxton, T. P., McKernan, J. L., Goetz, J., & Goulet, J. (2015). Influence of reservoir water

level fluctuations on sediment methylmercury concentrations downstream of the historical Black

Butte mercury mine, OR. Applied Geochemistry, 61, 284-293.

Eckley, C. S., Luxton, T. P., Goetz, J., & McKernan, J. (2017). Water-level fluctuations influence

sediment porewater chemistry and methylmercury production in a flood-control reservoir.

Environmental Pollution, 222, 32-41. doi:10.1016/j.envPo1.2017.01.010

Engstrom, D. R., & Swain, E. B. (1997). Recent declines in atmospheric mercury deposition in the upper

Midwest. Environmental Science & Technology, 31(4), 960-967. doi:10.1021/es9600892

Fleming, E. J., Mack, E. E., Green, P. G., & Nelson, D. C. (2006). Mercury methylation from unexpected

sources: Molybdate-inhibited freshwater sediments and an iron-reducing bacterium. Applied and

Environmental Microbiology, 72(1), 457-464. doi:10.1128/aem.72.1.457-464.2006

Furutani, A., & Rudd, J. W. M. (1980). Measurement of Mercury Methylation in Lake Water and

Sediment Samples. Applied and Environmental Microbiology, 40(4), 770-776.

Gilmour, C.C., et al. "Methylmercury concentrations and production rates across a trophic gradient in the

northern Everglades." Biogeochemistry40.2-3 (1998): 327-345.

Gilmour, C. C., & Henry, E. A. (1991). Mercury Methylation in Aquatic Systems Affected by Acid

Deposition. Environmental Pollution, 71(2-4), 131-169. doi:10.1016/0269-7491(91)90031-q

Gilmour, C. C., Podar, M., Bullock, A. L., Graham, A. M., Brown, S. D., Somenahally, A. C., . . . Elias,

D. A. (2013). Mercury Methylation by Novel Microorganisms from New Environments.

Environmental Science & Technology, 47(20), 11810-11820. doi:10.1021/es403075t

Hamelin, S., Amyot, M., Barkay, T., Wang, Y. P., & Planas, D. (2011). Methanogens: Principal

Methylators of Mercury in Lake Periphyton. Environmental Science & Technology, 45(18), 7693-

7700. doi:10.1021/es2010072

Haynes, K. M., Kane, E. S., Potvin, L., Lilleskov, E. A., Kolka, R. K., & Mitchell, C. P. J. (2017).

Mobility and transport of mercury and methylmercury in peat as a function of changes in water

56

table regime and plant functional groups. Global Biogeochemical Cycles, 31(2), 233-244.

doi:10.1002/2016gb005471

Hines, N. A., & Brezonik, P. L. (2007). Mercury inputs and outputs at a small lake in northern Minnesota.

Biogeochemistry, 84(3), 265-284. doi:10.1007/s10533-007-9114-2

Hintelmann, H., Keppel-Jones, K., & Evans, R. D. (2000). Constants of mercury methylation and

demethylation rates in sediments and comparison of tracer and ambient mercury availability.

Environmental Toxicology and Chemistry, 19(9), 2204-2211. doi:10.1897/1551-

5028(2000)019<2204:commad>2.3.co;2

Hsu-Kim, H., Kucharzyk, K. H., Zhang, T., & Deshusses, M. A. (2013). Mechanisms Regulating

Mercury Bioavailability for Methylating Microorganisms in the Aquatic Environment: A Critical

Review. Environmental Science & Technology, 47(6), 2441-2456. doi:10.1021/es304370g

Lehnherr, I., St. Louis, V. L., & Kirk, J. L. (2012). Methylmercury cycling in high arctic wetland ponds:

controls on sedimentary production. Environmental science & technology, 46(19), 10523-10531.

Jeremiason, J. D., Engstrom, D. R., Swain, E. B., Nater, E. A., Johnson, B. M., Almendinger, J. E., . . .

Kolka, R. K. (2006). Sulfate addition increases methylmercury production in an experimental

wetland. Environmental Science & Technology, 40(12), 3800-3806. doi:10.1021/es0524144

Kadhum, S. A., Ishak, M. Y., Zulkifli, S. Z., & Hashim, R. B. (2017). Investigating geochemical factors

affecting heavy metal bioaccessibility in surface sediment from Bernam River, Malaysia.

Environmental Science and Pollution Research, 24(14), 12991-13003. doi:10.1007/s11356-017-

8833-8

Kerin, E. J., Gilmour, C. C., Roden, E., Suzuki, M. T., Coates, J. D., & Mason, R. P. (2006). Mercury

methylation by dissimilatory iron-reducing bacteria. Applied and Environmental Microbiology,

72(12), 7919-7921. doi:10.1128/aem.01602-06

Lawrence, J. E., Skold, M. E., Hussain, F. A., Silverman, D. R., Resh, V. H., Sedlak, D. L., . . . McCray,

J. E. (2013). Hyporheic Zone in Urban Streams: A Review and Opportunities for Enhancing Water

Quality and Improving Aquatic Habitat by Active Management. Environmental Engineering

Science, 30(8), 480-501. doi:10.1089/ees.2012.0235

Lehnherr, I. (2014). Methylmercury biogeochemistry: a review with special reference to Arctic aquatic

ecosystems. Environmental Reviews, 22(3), 229-243. doi:10.1139/er-2013-0059

57

Liu, J. R., Valsaraj, K. T., & Delaune, R. D. (2009). Inhibition of Mercury Methylation by Iron Sulfides

in an Anoxic Sediment. Environmental Engineering Science, 26(4), 833-840.

doi:10.1089/ees.2008.0243

Malard, F., Tockner, K., Dole-Olivier, M. J., & Ward, J. V. (2002). A landscape perspective of surface-

subsurface hydrological exchanges in river corridors. Freshwater Biology, 47(4), 621-640.

doi:10.1046/j.1365-2427.2002.00906.x

Marvin-DiPasquale, M., Agee, J., Bouse, R., & Jaffe, B. (2003). Microbial cycling of mercury in

contaminated pelagic and wetland sediments of San Pablo Bay, California. Environmental

Geology, 43(3), 260-267.

Mergler, D., Anderson, H. A., Chan, L. H. M., Mahaffey, K. R., Murray, M., Sakamoto, M., & Stern, A.

H. (2007). Methylmercury exposure and health effects in humans: A worldwide concern. Ambio,

36(1), 3-11.

Minnesota Department of Natural Resources. (2017). Biomes of Minnesota. Retrieved from

http://www.dnr.state.mn.us/biomes/index.html

Mitchell, C. P. J., Branfireun, B. A., & Kolka, R. K. (2008a). Assessing sulfate and carbon controls on net

methylmercury production in peatlands: An in situ mesocosm approach. Applied Geochemistry,

23(3), 503-518. doi:10.1016/j.apgeocliem.2007.12.020

Mitchell, C. P. J., Branfireun, B. A., & Kolka, R. K. (2008b). Spatial characteristics of net methylmercury

production hot spots in peatlands. Environmental Science & Technology, 42(4), 1010-1016.

doi:10.1021/es0704986

Mitchell, C. P. J., & Gilmour, C. C. (2008). Methylmercury production in a Chesapeake Bay salt marsh.

Journal of Geophysical Research-Biogeosciences, 113, 14. doi:10.1029/2008jg000765

Naiman, R. J., & Decamps, H. (1997). The ecology of interfaces: Riparian zones. Annual Review of

Ecology and Systematics, 28, 621-658. doi:10.1146/annurev.ecolsys.28.1.621

Pak, K. R., & Bartha, R. (1998). Mercury methylation and demethylation in anoxic lake sediments and by

strictly anaerobic bacteria. Applied and Environmental Microbiology, 64(3), 1013-1017.

58

Parks, J. M., Johs, A., Podar, M., Bridou, R., Hurt, R. A., Smith, S. D., . . . Liang, L. Y. (2013). The

Genetic Basis for Bacterial Mercury Methylation. Science, 339(6125), 1332-1335.

doi:10.1126/science.1230667

Pollman, C. D., & Axelrad, D. M. (2014). Mercury bioaccumulation factors and spurious correlations.

Science of the Total Environment, 496, VI-XII. doi:10.1016/j.scitotenv.2014.07.050

Scheulhammer, A. M., Meyer, M. W., Sandheinrich, M. B., & Murray, M. W. (2007). Effects of

environmental methylmercury on the health of wild birds, mammals, and fish. Ambio, 36(1), 12-

18. doi:10.1579/0044-7447(2007)36[12:eoemot]2.0.co;2

Schilling, K. E. (2007). Water table fluctuations under three riparian land covers, Iowa (USA).

Hydrological Processes, 21(18), 2415-2424. doi:10.1002/hyp.6393

Schuster, P. F., Shanley, J. B., Marvin-Dipasquale, M., Reddy, M. M., Aiken, G. R., Roth, D. A., . . .

DeWild, J. F. (2008). Mercury and organic carbon dynamics during runoff episodes from a

northeastern USA watershed. Water Air and Soil Pollution, 187(1-4), 89-108. doi:10.1007/s11270-

007-9500-3

Singer, M. B., Harrison, L. R., Donovan, P. M., Blum, J. D., & Marvin-DiPasquale, M. (2016).

Hydrologic indicators of hot spots and hot moments of mercury methylation potential along river

corridors. Science of the Total Environment, 568, 697-711. doi:10.1016/j.scitotenv.2016.03.005

Sunderland, E. M., Krabbenhoft, D. P., Moreau, J. W., Strode, S. A., & Landing, W. M. (2009). Mercury

sources, distribution, and bioavailability in the North Pacific Ocean: Insights from data and models.

Global Biogeochemical Cycles, 23, 14. doi:10.1029/2008gb003425

Swain, E. B., Engstrom, D. R., Brigham, M. E., Henning, T. A., & Brezonik, P. L. (1992). Increasing

Rates of Atmospheric Mercury Deposition in Mid-continental North-America. Science, 257(5071),

784-787. doi:10.1126/science.257.5071.784

Vidon, P. G., Mitchell, C. P. J., Jacinthe, P. A., Baker, M. E., Liu, X. Q., & Fisher, K. R. (2013). Mercury

dynamics in groundwater across three distinct riparian zone types of the US Midwest.

Environmental Science-Processes & Impacts, 15(11), 2131-2141. doi:10.1039/c3em00254c

Vidon, P. G. F., & Hill, A. R. (2004). Landscape controls on the hydrology of stream riparian zones.

Journal of Hydrology, 292(1-4), 210-228. doi:10.1016/j.jhydrol.2004.01.005

59

Wasik, J. K. C., Engstrom, D. R., Mitchell, C. P. J., Swain, E. B., Monson, B. A., Balogh, S. J., . . .

Almendinger, J. E. (2015). The effects of hydrologic fluctuation and sulfate regeneration on

mercury cycling in an experimental peatland. Journal of Geophysical Research-Biogeosciences,

120(9), 1697-1715. doi:10.1002/2015jg002993

Zhang, H., Feng, X. B., Chan, H. M., & Larssen, T. (2014). New Insights into Traditional Health Risk

Assessments of Mercury Exposure: Implications of Selenium. Environmental Science &

Technology, 48(2), 1206-1212. doi:10.1021/es4051082

60

Appendix 1: Riparian Area Stratigraphic Logs

A1 A1.1 Kettle Watershed: KETRIF

61

A1.2 Mustinka Watershed: MUSBB

62

A1.3 Roseau Watershed: RRMH

63

A1.4 Thief Watershed: THIEKV

64

A1.5 Thief Watershed: THIMR

65

A1.6 Vermillion Watershed: VERBYK

66

A1.7 Vermillion Watershed: VERGLD

67

Appendix 2: Significant Statistical Differences

A2 A2.1.1 Significant Differences in Kmeth at Plot A: In-stream Plot

Kmeth at the in-stream sediment was significantly different across many study sites. At the

Mustinka site, MUS260, Kmeth was observed to be consistently lower than most sites (KETBAN,

KETRIF, MUSBB, RRMH, RRWMA, THIEKV, THIMR, and VERBYK in May 2016;

KETBAN, KETRIF, RRMH, RRWMA, THIEKV, and THIMR in August 2016). In contrast,

THIEKV showed significantly consistently greater Kmeth values (KETBAN, KETRIF, RRMH,

RRWMA, VERGLD, and MUS260 in May 2016; KETBAN, MUSBB, RRMH, RRWMA,

THIMR, and VERBYK in Aug 2016; MUSBB and MUS260 in 2015). THIMR was observed to

have similarly significantly lower Kmeth; however, this was only significant during May 2016

when comparing among the sites KETBAN, KETRIF, RRMH, RRWMA, MUS260, MUSBB

and VERGLD. The Vermillion site, VERGLD, only showed significantly lower Kmeth during

May 2016, among the sites KETRIF, MUSBB, RRMH, RRWMA, THIEKV, THIMR, and

VERBYK. In contrast, the other Vermillion site, VERBYK, was observed to have significantly

greater Kmeth among the sites RRWMA, and both Kettle watershed sites (KETBAN and

KETRIF). MUSBB showed significantly lower Kmeth than a few sites (KETBAN, KETRIF,

RRMH, THIEKV, THIMR in Aug 2016; THIEKV and THIMR in 2015). Both sites in the Kettle

watershed (KETBAN and KETRIF) were observed to have significantly greater Kmeth than

RRWMA, THIEKV, VERBYK, and VERGLD in Oct 2016.

A2.1.2 Significant Differences in Kmeth at Plot B: Streamside Plot

68

Kmeth at the streamside plot was significantly different among study sites. The Kettle watershed

site, KETRIF, was consistently significantly greater across all sampling periods in 2016

(KETBAN, THIEKV, VERBYK, and VERGLD in May 2016; KETBAN, MUSBB, RRMH,

RRWMA, THIMR, and VERBYK in Aug 2016; KETBAN, VERGLD, and RRWMA in Oct

2016). Similarly, THIEKV was observed to have significantly higher Kmeth; however, only

during the two sampling periods in late summer and early fall (KETBAN, MUSBB, RRMH,

RRWMA, THIMR, and VERBYK in Aug 2016; KETBAN, VERBYK, and VERGLD in

October 2016). Kmeth at the Vermillion site, VERGLD, was significantly lower than some sites

(RRWMA in May 2016; KETBAN, KETRIF, RRWMA, and THIEKV in Oct 2016). Other sites

that were observed to have significantly greater Kmeth; however, we only observed significant

differences on one sampling event. Kmeth at MUSBB was significantly greater than KETBAN,

THIEKV, VERBYK, and VERGLD in May 2016; THIEKV was significantly greater than

KETBAN, and VERBYK in Oct 2016; and MUS260 was significantly greater than RRMH,

RRWMA, and THIMR in 2015.

A2.1.3 Significant Differences in Kmeth at Plot C: Outer Riparian Edge

Kmeth at the outer riparian edge was significantly different across a large number of study sites.

The Kettle watershed sites (KETBAN and KETRIF) were observed to have significantly lower

Kmeth than some sites in May 2016 (MUS260, MUSBB, RRWMA); however, in October 2016,

KETRIF was observed to have significantly higher Kmeth than both KETBAN, RRWMA,

VERBYK, and VERGLD. MUS260 only showed significantly different Kmeth during May 2016,

with greater values than MUSBB, RRMH, THIEKV, KETRIF, KETBAN, VERBYK, VERGLD.

The Vermillion site, VERGLD, was observed to have significantly lower Kmeth during two

69

sampling events (KETBAN, KETRIF, MUSBB, RRMH, and RRWMA in May 2016; KETBAN,

KETRIF, and THIEKV in Oct 2016). Kmeth was observed to have similarly significantly lower

values at VERBYK (RRWMA in Aug 2016; KETBAN, KETRIF, and THIEKV in Oct 2016).

The site THIEKV showed significantly lower Kmeth during the May 2016 sampling (MUSBB,

RRMH, RRWMA); however, THIEKV was observed to have elevated Kmeth during Aug 2016

(KETBAN, MUS260, RRMH, RRMWA, and THIMR) and October 2016 (RRWMA,

VERBYK). In May 2016, Kmeth at RRWMA was only observed to be significantly greater than

VERBYK, KETBAN, and KETRIF; however, in August 2016, Kmeth at RRWMA was observed

to be significantly lower than KETBAN, KETRIF, MUSBB, THIEKV, and RRMH. Both sites,

THIMR and VERBYK, were significantly lower than the Kettle watershed sites (KETBAN and

KETRIF) during August 2016 and October 2016 respectively. Kmeth at THIMR was also

significantly lower than THEKV during August 2016. There were no significant differences

between the outer riparian plots across different sites in 2015.

A2.1.4 Significant Differences in MeHg at Plot A: Instream Plot

MeHg concentrations at the in-stream plot was frequently, significantly different across our

study sites. KETBAN showed significantly greater MeHg during the May 2016 sampling event

(KETRIF, MUSBB, RRMH, and THIMR) and some sites in August 2016 (RRMH and THIMR);

however; MeHg concentrations were significantly lower across other sites in August 2016

(KETRIF and RRWMA) and most sites in October 2016 (KETRIF, RRWMA, THIEKV,

VERBYK, and VERGLD). The other Kettle site, KETRIF, was observed to have significantly

lower MeHg during May 2016 (RRWMA, THIEKV, KETBAN, VERBYK, and VERGLD) and

significantly higher MeHg concentrations during the August 2016 sampling event (KETBAN,

70

MUS260, MUSBB, RRMH, and THIMR). The Roseau site, RRWMA, had significantly greater

concentrations of MeHg across most sites (KETRIF, MUS260, MUSBB, RRMH, and THIMR in

May 2016; KETBAN, MUS260, MUSBB, RRMH, and THIMR in August 2016; KETBAN in

October 2016; MUS260, MUSBB, RRMH, and THIMR in 2015). RRMH in contrast, had

significantly lower concentrations than some sites (KETBAN, RRWMA, THIEKV, VERBYK

and VERGLD in May 2016; KETBAN, KETRIF, MUS260, and THIEKV in August 2016;

MUS260 and MUSBB in 2015). THIEKV showed significantly greater MeHg concentrations

during most sampling events (KETRIF, MUS260, MUSBB, RRMH, and THIMR in May 2016;

MUSBB, RRMH, and THIMR in Aug 2016; KETBAN in October 2016; MUS260, MUSBB,

RRMH, and THIMR in 2015). In contrast, the other Thief watershed site THIMR had

significantly lower MeHg concentrations than many sites, (KETBAN, RRWMA, THIEKV,

VERBYK, and VERGLD in May 2016; KETBAN, KETRIF, MUS260, and THIEKV in August

2016; RRWMA and THIEKV in 2015). Both sites in the Vermillion watershed were observed to

have remarkably similar tends, with significantly elevated concentrations across a few sites

during May 2016 (MUSBB, RRMH, THIEKV, THIMR for VERBYK; MUSBB, RRMH,

THIEKV, THIMR for VERGLD). During the October sampling event, both Vermillion sites

were observed to have significantly elevated MeHg than KETBAN.

A2.1.5 Significant Differences in MeHg at Plot B: Streamside Plot MeHg concentrations were significantly different across sites at the streamside plot. At the Kettle

watershed site KETBAN, MeHg concentrations were observed to be significantly lower across

most sampling events (KETRIF, RRWMA, VERBYK and VERGLD in May 2016; KETRIF,

THIMR, and VERGLD in August 2016; KETRIF and VERGLD in October 2016). The other

Kettle site, KETRIF, was consistently significantly higher across all sampling events in 2016

71

(KETBAN, MUSBB, MUS260, THIEKV, and THIMR in May 2016; KETBAN, MUS260,

MUSBB, RRMH and THIEKV in August 2016; KETBAN, RRWMA, THIEKV, and VERBYK

in October 2016). RRWMA was significantly greater among most sites only during the May

2016 sampling event (KETBAN, MUS260, RRMH, and THIEKV), and was significantly lower

during the October 2016 (KETRIF, VERGLD and THIEKV) and 2015 (MUS260 and THIEKV)

sampling events. The other Roseau site, RRMH, had consistently lower MeHg than most sites in

May 2016 (RRWMA, VERBYK, and VERGLD), August 2016 (KETBAN, KETRIF, MUSBB,

THIEKV, THIMR, VERBYK, and VERGLD) and just MUSBB in 2015. MeHg at the site

MUS260 was consistently lower during May 2016 (KETRIF, MUSBB, RRWMA, VERBYK,

and VERGLD) and August 2016 (KETRIF, MUSBB, THIEKV, THIMR, VERBYK, and

VERGLD); however, it was observed to be significantly higher during the 2015 sampling event

(MUSBB, RRMH, RRWMA, THIEKV, and THIMR). At MUSBB, similar trends were

observed, with significant MeHg concentrations lower than the sites compared (KETRIF,

VERBYK and VERGLD in May 2016; KETRIF and THIMR in August 2016). MeHg

concentrations were significantly lower at THIEKV than at KETRIF, RRWMA, VERBYK, and

VERGLD in May 2016, KETRIF in August 2016, KETRIF and VERGLD in October 2016.

THIEKV also was observed to have significantly higher MeHg during August 2016 (MUS260,

RRMH in August 2016; RRWMA in October 2016; RRMH, RRWMA and THIEKV in 2015).

At THIMR, MeHg concentrations were significantly lower than some sites earlier in 2015 and

2016 (MUS260, MUSBB, RRWMA, and THIEKV in 2015; KETRIF, VERBYK, VERGLD in

May 2016) but were observed to be higher later in 2016 (KETBAN, MUS260, and MUSBB in

August 2016). Both sites in the Vermillion watershed were observed to have significantly high

MeHg concentrations during most sampling periods. VERBYK had higher concentrations than

most sites (KETBAN, MUS260, MUSBB, RRMH, THIEKV, and THIMR in May 2016;

72

MUS260, RRMH in August 2016); however significantly lower MeHg concentrations were

observed in October 2016 (KETRIF and VERGLD). The other Vermillion site, VERGLD,

consistently had higher MeHg concentrations at the streamside plot (KETBAN, MUS260,

MUSBB, RRMH, THIEKV, and THIMR in May 2016; KETBAN. MUS260, and RRMH in

August 2016; KETBAN, RRWMA, THIEKV, and VERBYK in October 2016).

A2.1.6 Significant Differences in MeHg at Plot C: Outer Riparian Edge

At the outer-riparian edge, MeHg concentrations differ significantly across many sites. MeHg at

KETBAN was significantly higher during all sampling events in 2016 (KETRIF, MUSBB,

MUS260, RRWMA, THIEKV, VERBYK, and VERGLD in May; KETRIF, MUS260,

RRWMA, THIEKV, and VERGLD in August; KETRIF, THIEKV, and VERGLD in October).

The other Kettle site, KETRIF, had significantly higher MeHg than most sites during May 2016

(KETBAN, MUSBB, RRMH, THIEKV, and THIMR), August 2016 (KETBAN, MUSBB,

RRMH, and THIMR), and in October 2016 (KETBAN, RRWMA, THIEKV, and VERBYK).

MUS260 was observed to have significantly greater MeHg concentrations than most sites

(KETBAN, MUSBB, RRMH, THIEKV, and THIMR in May 2016; KETBAN, MUSBB,

RRMH, THIMR in August 2016; MUSBB, RRMH, and RRWMA in 2015). MUSBB was

observed to have significantly lower MeHg concentrations (KETRIF, MUS260, VERBYK, and

VERGLD in May 2016; KETRIF, MUS260, RRWMA, THIEKV, VERBYK, and VERGLD in

August 2016. During most sampling occasions, MeHg was observed to be significantly lower

than most sites at RRMH (KETRIF, MUS260, VERBYK, and VERGLD in May 2016;

KETBAN, KETRIF, MUS260, RRWMA, THIEKV, VERBYK, and VERGLD in August 2016;

MUS260, MUSBB, RRWMA, and THIEKV in 2015). At RRWMA, MeHg was significantly

73

higher than a few sites (KETBAN, KETRIF, THIEKV, and THIMR in May 2016; KETBAN,

MUSBB, RRMH, THIMR, and VERBYK in August 2016; RRMH in 2015). MeHg at RRWMA

was only significantly lower for KETRIF and VERGLD in October 2016, and MUS260 in 2015.

At THIEKV, had significantly lower MeHg concentrations in May 2016 (KETBAN, KETRIF,

MUS260, RRWMA, VERBYK, and VERGLD), but was seen to have significantly higher MeHg

concentrations in August 2016 (KETBAN, MUSBB, RRMH, and THIMR), October 2016

(KETBAN, VERBYK), and 2015 (RRMH). The other Thief River site, THIMR, MeHg

concentrations were significantly lower (KETRIF, MUS260, RRWMA, VERBYK, and

VERGLD in May 2016; KETBAN, KETRIF, MUS260, MUSBB, RRWMA, THIEKV,

VERBYK, and VERGLD in August 2016). The Vermillion watershed sites generally were

observed to have higher MeHg. At VERBYK, MeHg was significantly higher than KETBAN,

MUSBB, RRMH, THIEKV, and THIMR in May 2016, MUSBB, RRMH, THIMR in August

2016; but was also observed to be significantly lower than RRWMA in August 2016 and

KETRIF, THIEKV, and VERGLD in October 2016. The other Vermillion site VERGLD was

observed to have significantly higher MeHg than most sites during all sampling events in 2016

(KETBAN, MUSBB, RRMH, THIEKV, and THIMR in May 2016; KETBAN, MUSBB,

RRMH, and THIMR in August 2016; and KETBAN, RRWMA, THIEKV, and VERBYK in

October 2016).

A2.1.7 Significant Differences in %MeHg at Plot A: In-stream Plot

%MeHg was significantly different across sites at the in-stream plot. KETBAN was observed to

have significantly higher %MeHg (RRMH, RRWMA, and THIEKV) only for the August 2016

sampling event and subsequently lower %MeHg during the October 2016 sampling event

74

(KETRIF, RRWMA, THIEKV, VERBYK, and VERGLD). KETRIF was observed to have

significantly lower %MeHg during the May 2016 sampling period (KETBAN, RRWMA,

THIEKV, and VERBYK); however, it was observed to have significantly higher %MeHg during

August 2016 (MUSBB, and RRMH) and October 2016 (KETBAN). The Roseau site RRWMA,

had significantly higher %MeHg than most sites across all sampling events (MUS260, MUSBB,

THIMR, and VERGLD in May 2016; MUS260, MUSBB, and RRMH in August 2016;

KETBAN in October 2016; MUS260, RRMH, MUSBB, and THIMR in 2015). The other

Roseau site, RRMH, showed significantly lower %MeHg during August 2016 (KETBAN,

KETRIF, RRWMA, THIEKV, and THIMR) and in 2015 (RRWMA, THIEKV, and THIMR). In

the Thief watershed, THIEKV was observed to have significantly higher %MeHg on more than

one occasion (KETBAN, MUS260, MUSBB, RRMH, THIMR, and VERGLD in May 2016;

MUS260, MUSBB, RRMH, and THIMR in August 2016; KETBAN in October 2016). THIMR

was occasionally observed to have significantly different %MeHg, with lower values in May

2016 (RRWMA, THIEKV). In 2015, %MeHg at THIMR was significantly lower than RRWMA,

and THIEKV, but also significantly higher when compared to MUS260, and RRMH. Both sites

in the Mustinka watershed were observed to consistently have lower %MeHg among the

compared sites. At MUS260, %MeHg was significantly lower (RRWMA and THIEKV in both

May and August 2016; RRWMA, THIEKV, and THIMR in 2015). Similarly, %MeHg was

observed to be lower for MUSBB (RRWMA, and THIEKV in May 2016; KETRIF, RRWMA,

and THIEKV in August 2016; RRWMA, THIEKV, and THIMR in 2015). Both Vermillion sites,

VERBYK and VERGLD did not systematically show any significant differences among each of

the compared sites at the in-stream plot. VERGLD was only observed to have significantly lower

%MeHg during May 2016, where it was lower than RRWMA and THIEKV. VERBYK was only

75

observed to be significantly higher than KETRIF during the same sampling period. Both

Vermillion sites had significantly greater %MeHg than KETBAN in October 2016.

A2.1.8 Significant Differences in %MeHg at Plot B: Streamside Plot

At the streamside plot, significant differences were observed for %MeHg among sites. At

KETBAN, %MeHg was observed to be significantly lower than some sites in August 2016

(KETRIF, MUSBB, THIEKV, THIMR, and VERBYK) and October 2016 (KETRIF and

VERGLD). The other Kettle site, KETRIF, was observed to contrast this trend, with significantly

higher %MeHg (KETBAN, RRMH, THIEKV in May 2016; KETBAN, MUS260, and RRMH in

August 2016; KETBAN, VERBYK and RRWMA in October 2016). At the Mustinka watershed,

MUS260 was frequently observed to have lower %MeHg than other sites (KETRIF, MUSBB,

RRMH, RRWMA, THIEKV, THIMR, VERBYK, and VERGLD in May 2016; KETRIF,

MUSBB, RRWMA, THIMR, and VERBYK in August 2016). In 2015, the opposite was

observed for MUS260, where %MeHg was significantly greater than RRMH, RRWMA, and

THIMR. MUSBB was observed to have significantly higher %MeHg on several occasions

(MUS260 in May 2016; KETBAN, MUS260, and RRMH in August 2016; RRMH, RRWMA,

and THIMR in 2015). At RRMH, %MeHg was observed to be significantly lower than most sites

(KETRIF, and VERBYK in August 2016; KETRIF, MUSBB, RRWMA, THIEKV, THIMR, and

VERBYK in August 2016; MUS260, MUSBB, THIEKV, and THIMR in 2015). The other

Roseau site, RRWMA showed opposing trends, with significantly higher %MeHg across most

sites (KETBAN, MUS260, and THIEKV in May 2016; MUS260, and RRMH in August 2016;

MUS260, MUSBB, and THIEKV in 2015). At THIEKV, %MeHg was observed to be

significantly lower during May 2016 (KETRIF, RRWMA, and VERBYK), but significantly

76

higher in August 2016 (KETBAN and RRMH) and 2015 (RRMH, RRWMA and THIMR). The

other site in the Thief watershed, THIMR, were not observed to have many significant

differences among the compared sites, other than significantly higher %MeHg in August 2016

(KETBAN, MUS260 and RRMH), and in 2015 (MUS260, MUSBB, RRMH, and THIEKV). In

the Vermillion watershed, the VERBYK site consistently showed significantly higher %MeHg

during May 2016 (KETBAN, MUS260, RRMH, and THIEKV) and August 2016 (KETBAN,

MUS260, and RRMH), but significantly lower %MeHg in October 2016 (KETRIF and

VERGLD). The other Vermillion site, VERGLD, did not show many significant and consistent

differences during the sampling period. VERGLD was only observed to be significantly higher

than MUS260 in May 2016, and RRWMA in October 2016.

A2.1.9 Significant Differences in %MeHg at Plot C: Outer Riparian Edge

%MeHg concentrations differed significantly across sites at the outer-riparian edge. At site

KETBAN, %MeHg was observed to frequently be significantly lower than most sites in May

2016 (KETRIF, MUSBB, MUS260, MUSBB, RRWMA, THIEKV, VERBYK, and VERGLD),

August 2016 (MUS260 and THIEKV), and October 2016 (KETRIF, THIEKV, and VERGLD).

KETRIF showed similar trends, with significantly lower %MeHg (RRWMA and VERBYK in

May 2016; MUS260, RRWMA in August 2016), but was observed to be significantly higher

than some sites (RRMH, THIMR in August 2016; KETBAN and VERBYK in October 2016).

MUS260 generally showed significantly higher %MeHg at the outer-riparian edge (KETBAN,

MUSBB, RRMH, THIEKV, and THIMR in May 2016, KETRIF, MUSBB, RRMH, THIMR,

VERBYK, and KETBAN in August 2016; RRMH and RRWMA in 2015). The other Mustinka

site, MUSBB, contrasted this trend, with significantly lower %MeHg (MUS260, RRWMA, and

77

VERBYK in May 2016; MUS260 and RRWMA in August 2016). At the Roseau site RRMH,

%MeHg was consistently significantly lower during all the sampling events (MUS260,

RRWMA, VERBYK, and VERGLD in May 2016; KETRIF, MUS260, MUSBB, RRWMA,

THIEKV, VERBYK, and VERGLD in August 2016; MUS260, MUSBB, RRWMA, and

THIEKV in 2015). In contrast, the other paired Roseau site RRWMA consistently demonstrated

significantly higher %MeHg among all the compared sites (KETBAN, KETRIF, MUSBB,

RRMH, THIEKV, THIMR, and VERGLD in May 2016; KETBAN, KETRIF, RRMH, MUSBB,

THIMR, and VERBYK in August 2016, and RRMH in 2015). THIEKV was observed to have

significantly lower %MeHg than some sites in May 2016 (MUS260, RRWMA, and VERBYK),

but significantly higher in other sites in August 2016 (RRMH, MUSBB, KETBAN, and

THIMR), October 2016 (KETRIF, VERBYK), and 2015 (RRMH). The other Thief watershed

site, THIMR, had significantly lower %MeHg in May 2016 (MUS260, RRWMA, VERBYK)

and August 2016 (KETBAN, KETRIF, MUS260, MUSBB, RRWMA, THIEKV, VERBYK, and

VERGLD). Both Vermillion watershed sites were observed to have significantly higher %MeHg

among compared sites. At VERBYK, %MeHg was significantly higher during May 2016

(KETBAN, KETRIF, MUSBB, RRMH, THIEKV, and THIMR), August 2016 (RRMH and

THIMR), and October 2016 (KETRIF, THIEKV). The other Vermillion site, VERGLD, was

observed to have significantly higher %MeHg during August 2016 (RRMH and THIMR) and

October 2016 (KETBAN, VERBYK).

78

Appendix 3: Field and Sampling Photography

A3

A3.1 Field and Sampling Photos

Figure 19: Vermillion site VERGLD just after snowmelt.

Figure 20: THIEKV site with drone photography.

79

Figure 21: Installation of wells and piezometer nests at KETBAN.

Figure 22: Sampling groundwater and measuring water levels at each plot at RRMH.

80

Figure 23: Collecting Kmeth sediment cores at RRWMA site.

Figure 24: Injecting stable isotope solution into sediment cores at the University of

Minnesota Duluth.