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
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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.
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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.
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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
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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
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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
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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
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List of Appendices
Appendix 1: Riparian Area Stratigraphic Logs………………………………………………….53
Appendix 2: Statistical Significant Differences……………………………..…………………..60
Appendix 3: Field and Sampling Photography…...………………………………………..……74
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Chapter 1: Literature Review on Mercury Methylation and Research
Objectives
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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.
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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).
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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.
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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”
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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.
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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
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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
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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
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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
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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;
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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
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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;
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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
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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
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(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
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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
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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
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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).
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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.
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Figure 21: Installation of wells and piezometer nests at KETBAN.
Figure 22: Sampling groundwater and measuring water levels at each plot at RRMH.
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Figure 23: Collecting Kmeth sediment cores at RRWMA site.
Figure 24: Injecting stable isotope solution into sediment cores at the University of
Minnesota Duluth.
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