Anoxic conditions within reservoirs related to thermal stratification and oxygen depletion lead to methylmercury (MeHg) production, a key process governing the uptake of mercury in aquatic food webs. Once formed within a reservoir, the timing and magnitude of the biological uptake of MeHg and the relative importance of MeHg export in water versus biological compartments remain poorly understood. We examined the relations between the reservoir stratification state, anoxia, and the concentrations and export loads of MeHg in aqueous and biological compartments at the outflow locations of two reservoirs of the Hells Canyon Complex (Snake River, Idaho-Oregon). Results show that (1) MeHg concentrations in filter-passing water, zooplankton, suspended particles, and detritus increased in response to reservoir destratification; (2) zooplankton MeHg strongly correlated with MeHg in filter-passing water during destratification; (3) reservoir anoxia appeared to be a key control on MeHg export; and (4) biological MeHg, primarily in zooplankton, accounted for only 5% of total MeHg export from the reservoirs (the remainder being aqueous compartments). These results improve our understanding of the role of biological incorporation of MeHg and the subsequent downstream release from seasonally stratified reservoirs and demonstrate that in-reservoir physical processes strongly influence MeHg incorporation at the base of the aquatic food web.
Anoxic conditions within reservoirs related to thermal stratification and oxygen depletion lead to methylmercury (MeHg) production, a key process governing the uptake of mercury in aquatic food webs. Once formed within a reservoir, the timing and magnitude of the biological uptake of MeHg and the relative importance of MeHg export in water versus biological compartments remain poorly understood. We examined the relations between the reservoir stratification state, anoxia, and the concentrations and export loads of MeHg in aqueous and biological compartments at the outflow locations of two reservoirs of the Hells Canyon Complex (Snake River, Idaho-Oregon). Results show that (1) MeHg concentrations in filter-passing water, zooplankton, suspended particles, and detritus increased in response to reservoir destratification; (2) zooplankton MeHg strongly correlated with MeHg in filter-passing water during destratification; (3) reservoir anoxia appeared to be a key control on MeHg export; and (4) biological MeHg, primarily in zooplankton, accounted for only 5% of total MeHg export from the reservoirs (the remainder being aqueous compartments). These results improve our understanding of the role of biological incorporation of MeHg and the subsequent downstream release from seasonally stratified reservoirs and demonstrate that in-reservoir physical processes strongly influence MeHg incorporation at the base of the aquatic food web.
Reservoirs are critical infrastructure
in both developed and developing
nations, comprising a global surface area roughly equivalent to that
of natural lakes[1] and providing renewable
energy, water storage, flood control, and other services. Global construction
of reservoirs is expected to increase in the coming decades to meet
the water supply and renewable energy needs of a growing and economically
developing human population.[2] However,
while the socioeconomic benefits of reservoirs are clear, reservoirs
also dramatically alter natural flows and the ecosystem structure.[3,4]Seasonal anoxia from decomposing organic matter is common
in reservoirs
around the world and is expected to increase with climate and land-use
change.[5−8] Anoxia is a key driver of (MeHg) production and increased concentrations
in metalimnion and hypolimnion.[9] Upon seasonal
thermal destratification (i.e., mixing), MeHg stored in anoxic waters
at depth may become available for biological uptake.[10,11] MeHg is incorporated into the food web via bioconcentration by phytoplankton
and subsequent biomagnification in higher trophic levels,[12] which can result in a >1 million-fold increase
in MeHg levels from water to top predator fish.[13] As a potent neurotoxin and endocrine disruptor, MeHg causes
adverse health effects in both wildlife and humans.[14−16] Consequently,
MeHg contamination is the leading reason for issuing fish consumption
advisories in the United States.[13]Although MeHg produced and retained in reservoirs can influence
in-reservoir biological exposure, and destratification mobilizes those
stored pools of MeHg for downstream export,[10,17−19] the timing and relative magnitude and contributions
of MeHg export in aqueous versus biological compartments remain poorly
understood. This is an important information gap because of its implications
on MeHg uptake by downstream biota because fish primarily assimilate
MeHg through their diet rather than through aqueous exposure.[20,21]We examined the downstream export of MeHg in aqueous (filter-passing
and particulate) and biological compartments (zooplankton, other invertebrates,
fish, and coarse and fine detritus) from two reservoirs in the Hells
Canyon Complex (HCC) along the Snake River (USA) over a 16-month period.
We relate the outflow aqueous and biological MeHg concentrations to
the reservoir stratification status and anoxic volume. We also compare
the MeHg export loads in aqueous and biological compartments to understand
the relative importance of each compartment in transferring MeHg downstream.
Our findings improve the understanding of how in-reservoir physical
processes influence MeHg incorporation into reservoir food webs and
its subsequent export to downstream habitats.
Methods
Study Area
The HCC comprises three successive reservoirs
on the Snake River along the Idaho-Oregon border (USA). Brownlee Reservoir
is the most upstream and largest of the reservoirs (Figure S1) and flows into Oxbow Reservoir, which in turn flows
into Hells Canyon Reservoir. During summer months, much of Brownlee
Reservoir thermally stratifies and becomes anoxic in portions of the
transition zone, metalimnion, and throughout the hypolimnion.[17,22] During late summer and fall, cool, inflowing water gradually erodes
the thermal stratification, mixing the anoxic waters with the overlying
oxic waters. This process, referred to hereafter as destratification,
occurs slowly over the course of several months (August to December),
after which the reservoir is thermally mixed and oxic and remains
so throughout the winter and early spring.[17] The forebay of the downstream Hells Canyon Reservoir also typically
stratifies during summer, whereas stratification is limited and inconsistent
in Oxbow Reservoir.[22]The Snake River
through the HCC is listed as impaired for mercury by the States of
Idaho and Oregon. Reservoir stratification is an important driver
of Hg cycling in the HCC.[17,23] During stratification
periods, aqueous methylmercury concentrations are elevated in the
anoxic and hypoxic areas of the transition zone, metalimnion, and
hypolimnion, relative to the epilimnion. This contrasts with nonstratified
(well-mixed) periods when concentrations are vertically uniform and
substantially lower.[23] Additionally, the
destratification period (August to December) coincides with the elevated
MeHg concentrations in water samples at the reservoir outflows, suggesting
that some portion of the metalimnetic and hypolimnetic MeHg is exported
downstream.[17]
Sample Collection
To quantify the role of reservoir
physical processes on the downstream export of aqueous and biological
MeHg, we collected aqueous and biological samples every 2 weeks between
June 2018 and September 2019 at the dam outflows of Brownlee and Oxbow
Reservoirs (Figure S1). Aqueous samples
collected at the Brownlee Inflow during the same period are also included
for comparison with the Brownlee Outflow. Additionally, to provide
greater temporal and spatial context for the results presented, aqueous
mercury concentrations and loads over a broader period (June 2014
to March 2021), and from two additional sites (near Melba, Idaho,
102 River Miles upstream of Brownlee Inflow and above the confluences
of five major tributaries; and at the dam outflow of Hells Canyon
Reservoir, the lowermost reservoir in the HCC), are available online
(concentrations)[24] and included in the Supporting Information (concentrations and loads).[24] Biological samples were limited to Brownlee
Outflow and Oxbow Outflow for logistical, safety, and (or) permitting
reasons and, in the case of the Melba and Brownlee Inflow sites, because
fish can travel both upstream and downstream, complicating load estimations.
The biological sample concentrations are available online.[25]
Water Samples
Water sample collection, processing,
and analytical methods are described elsewhere.[17,24] Briefly, water samples were collected using depth-integrated and
grab methods, depending on the access at different locations. Within
24 h of collection, water samples were filtered through a 0.7 μm
pore size quartz fiber filter (QFF; precombusted to 550 °C).
Particulate samples, which contained inorganic particles and particulate
organic carbon with some minor contributions of phytoplankton and
zooplankton,[24] were frozen (−20
°C) in the dark; filter-passing fractions were stored in Teflon
bottles and acidified to 1% volume-to-volume with ultraclean hydrochloric
acid. Samples were analyzed by the U.S. Geological Survey (USGS) Mercury
Research Laboratory (MRL; Madison, Wisconsin, USA) for filter-passing
THg and MeHg (THgF and MeHgF), particulate volumetric
THg and MeHg (THgPV and MeHgPV), and suspended
particulate material (SPM). THgF and THgPV analyses
followed USEPA Method 1631, Revision E,[26] with modifications by the MRL.[27] MeHgF and MeHgPV analyses followed USEPA Method 1630,[28] with modifications by the MRL.[29] SPM was collected on a preweighed QFF that was lyophilized
and weighed to determine the mass of particulates collected in comparison
to the volume of water filtered. Particulate gravimetric MeHg (MeHgPG, in ng/g) was calculated from the concentrations of MeHgPV (ng/L) and SPM. The results of the water sample field blanks
and field duplicates are summarized in Figure S2 and Table S1, respectively.
Biological Samples
Biological samples were collected
from the same reservoir outflow locations as the aqueous samples and
typically within 5 days of aqueous sampling. During each sampling
event, biological samples were collected with a custom 1.5 ×
0.9 m (1.39 m2 sampling area) net with 5 mm mesh to capture
fish and coarse materials and a 30 cm diameter (0.07 m2 sampling area) Wisconsin-style plankton net with 125 μm mesh
used to capture plankton and other fine materials. The fish net was
designed to capture drifting, juvenile fish that had passed through
the dam turbines, rather than large fish which generally avoid the
turbine intakes. Floats attached to the nets ensured consistent sampling
depth near the water surface. At each site, the nets were deployed
in the main flowline for either 15–36 min (coarse net; median
31 min) or 3–21 min (plankton net; median 6 min) per sample
depending on the flows, which were quantified with a flow meter installed
on the sampling nets. The turbulence of flow below the dams kept the
water column well mixed at the sampling locations. Two or three replicate
samples were collected from each net per sampling event and site.
All biological samples were kept on ice in a cooler while in the field
(up to 6 h) and then frozen (−20 °C) until further processing.In the laboratory, the samples were thawed and quantitatively split
using either a Canton tray (coarse net samples) or a Folsom splitter
(plankton net samples) to a density that could be effectively sorted
and then sorted into five classes: fish, zooplankton, other invertebrates
(i.e., terrestrial and benthic invertebrates), coarse (≥5 mm)
detritus, and fine (≤5 mm) detritus. All samples were oven-dried
to a constant mass and weighed to either 0.001 g (large pieces of
coarse detritus) or 0.00001 g (all other samples) on a digital balance.
The biomass associated with each functional class in the entire sample
was calculated based on the proportion of the original sample that
was sorted and the volume of water filtered during each deployment
based on the flow meter readings. The biological samples were analyzed
for MeHg at the USGS Contaminant Ecology Research Laboratory (Corvallis,
OR, USA) following EPA method 1630,[28] and
the results are reported on a dry weight basis. Additional method
details are provided in the Supporting Information, and QAQC results are summarized in Tables S2 and S3.
Brownlee Reservoir Water Temperature and Dissolved Oxygen
Vertical profiles of water temperature and dissolved oxygen (DO)
were collected in Brownlee Reservoir to monitor the stratification
status and to estimate the volume of hypoxic and anoxic water in the
reservoir. Vertical profiles were collected using a SeaBird Electronics
SeaCat SBE 19-plus system every 3.2 km along the thalweg of Brownlee
Reservoir (22 locations) at 2 week intervals between April and late
December throughout the study period. In the distances between profiles,
water temperature and DO were estimated using the inverse distance
interpolation method in Tecplot 360, resulting in a continuous longitudinal
water temperature and DO profile of Brownlee Reservoir every 2 weeks.
The total reservoir volume of hypoxic (0.5 < DO < 2.0 mg/L)
and anoxic (DO < 0.5 mg/L) water corresponding to each profile
date was estimated using the longitudinal DO profiles and reservoir
stage and bathymetry data, following the assumption that DO along
the thalweg was horizontally uniform.
Data Analysis
All data analysis was done using R software.[30] Nonparametric statistical tests were used because
the data were non-normally distributed. Spatial, temporal, and matrix
comparisons of concentrations were done using either the Wilcoxon
rank sum test in the base R package stats(30) or the Kruskal–Wallis multiple comparison
test in the R package pgirmess.[31] Correlations
between different variables (e.g., MeHg concentrations in water and
zooplankton) were assessed using the Spearman rank test in the R package
Hmisc.[32] To examine the relations between
aqueous and biological MeHg, which were each sampled biweekly but
not on the same day, the time series of daily aqueous MeHg concentrations
were developed using the composite method in the R software package
loadflex.[33] The daily mercury loads in
aqueous and biological samples were estimated using the composite
method[34] in loadflex.[33] The composite method combines regression and interpolation
and has been shown to provide more accurate load estimates for a variety
of constituents compared to either regression or interpolation alone,
especially for high-frequency (i.e., biweekly) datasets.[35] The regression models used in the composite
method were developed using LOADEST model nine, which includes continuous
predictor variables related to streamflow and season.[36] The mean daily streamflow data used in load estimates were
from Idaho Power Company streamgages.[37] Additional details on data analysis are described in the Supporting Information.
Results and Discussion
Brownlee Stratification and Destratification
A temporal
analysis of the Brownlee Reservoir stratification status was conducted
using water temperature and DO profiles to aid the interpretation
of the MeHg export data. At the beginning of the study in June 2018,
Brownlee Reservoir was thermally stratified and anoxic or hypoxic
in portions of the transition zone, metalimnion, and throughout the
hypolimnion. Destratification began in August (between 7/31/2018 and
8/22/2018) with erosion and mixing of the anoxic and hypoxic water
in the transition zone (Figure A,B), reducing the total volume of hypoxic and anoxic water
in the reservoir (Figure C). By early- to mid-October (Figure A,B), approximately 65% of anoxic and 90%
of hypoxic water volumes present in late July had been eroded and
mixed into overlying oxic waters or flushed from the reservoir (Figure C), and the remaining
hypoxic and anoxic water was limited to the hypolimnion. A second
stage of destratification occurred between mid-November and early-
to mid-December (Figure C). By December 11, the reservoir was well mixed (as indicated by
a water temperature gradient of <1.5 °C for all depths between
River Miles 305 and 285; DO values not available due to freezing of
the sensor) and remained so for the remainder of the winter and early
spring. Thus, the 2018 destratification period spanned from August
to December, with most of the physical mixing occurring in August
to September (mixing of the transition zone and erosion of the metalimnion)
and November to December (the turnover of the hypolimnion). In 2019,
hypoxic and anoxic water gradually built up from April to the maxima
in early September, which then decreased again with the onset of destratification
(Figures C and S3).
Figure 1
Longitudinal cross sections of Brownlee Reservoir
(A) water temperature
and (B) DO concentrations on different dates during the 2018 destratification
period. River flow is from left to right. Gray triangles indicate
penstock centerline elevation. A companion set of plots for the 2019
destratification period is provided in Figure S3. (C) Volume of hypoxic and anoxic water in Brownlee Reservoir
during late May 2018 to November 2019, with the study period indicated
along the x-axis [°C, degrees Celsius; m3, cubic meters; mg/L, milligrams per liter].
Longitudinal cross sections of Brownlee Reservoir
(A) water temperature
and (B) DO concentrations on different dates during the 2018 destratification
period. River flow is from left to right. Gray triangles indicate
penstock centerline elevation. A companion set of plots for the 2019
destratification period is provided in Figure S3. (C) Volume of hypoxic and anoxic water in Brownlee Reservoir
during late May 2018 to November 2019, with the study period indicated
along the x-axis [°C, degrees Celsius; m3, cubic meters; mg/L, milligrams per liter].
Masses of Biological Material and SPM in Water
The
biomass density (mass of biological material per cubic meter of water)
in the samples at reservoir outflow locations varied considerably
across different biological compartments (Figure A). Fish and other invertebrates generally
had the lowest biomass density. In contrast, the biomass densities
of coarse and fine detritus and zooplankton were 1 and 2–3
orders of magnitude greater, respectively, than those of fish. Masses
of SPM per volume of water were approximately 2 orders of magnitude
greater than those of zooplankton. The biomass densities of coarse
and fine detritus and the masses of SPM per volume of water were significantly
and positively correlated with the streamflow (Figure S6).
Figure 2
(A) Biomass density and SPM in water and (B) MeHg concentration
in biological material and SPM in samples from Brownlee Outflow and
Oxbow Outflow, June 2018 to September 2019. Boxplots present median
and quartile ranges, and whiskers extend 1.5× the interquartile
ranges. Lower case letters (a–e) indicate statistical differences
between groups based on the Kruskal–Wallis multiple comparison
test, with p value of 0.05 [SPM, suspended particulate
material; ng/g, nanograms per gram; mg/m3, milligrams per
cubic meter].
(A) Biomass density and SPM in water and (B) MeHg concentration
in biological material and SPM in samples from Brownlee Outflow and
Oxbow Outflow, June 2018 to September 2019. Boxplots present median
and quartile ranges, and whiskers extend 1.5× the interquartile
ranges. Lower case letters (a–e) indicate statistical differences
between groups based on the Kruskal–Wallis multiple comparison
test, with p value of 0.05 [SPM, suspended particulate
material; ng/g, nanograms per gram; mg/m3, milligrams per
cubic meter].
MeHg Concentrations in Water
Aqueous MeHg concentrations
(MeHgF, MeHgPV, and MeHgPG) and the
percentages of filter-passing and particulate THg as MeHg (% MeHgF and % MeHgP) in Brownlee Outflow samples were
higher during August to December 2018 than during the months before
and after (Figure A–E and Table S5). We observed
two distinct peaks in aqueous MeHg concentrations during the August
to December 2018 period (Figure A–E), coinciding with the two stages of destratification
of Brownlee Reservoir. Profiles of Brownlee Reservoir DO (Figure B) suggest that the
first peak in aqueous MeHg (August to September) was associated with
the entrainment and downstream export of anoxic water in the transition
zone and metalimnion. Previous studies have identified the potential
importance of the oxic–anoxic boundary and metalimnion for
both methylation and biological uptake of Hg. Eckley and Hintelman[9] reported maximum methylation potentials at the
oxic–anoxic boundary in Canadian lakes, with decreasing methylation
potentials at greater depths. In Davis Creek Reservoir (California,
USA), Slotton et al.[19] reported a dense
seasonal lens of photosynthetic anaerobic bacteria in the lower metalimnion
immediately below the thermocline, and based on the entrainment of
this layer into the mixed layer coincident with the increases in THg
concentrations in juvenile bass hypothesized that this layer may be
a seasonally important source of bioavailable Hg.
Figure 3
Aqueous and biological
methylmercury (MeHg) at Brownlee Inflow,
Brownlee Outflow, and Oxbow Outflow, June 2018 to September 2019.
Data gaps in fish and other invertebrates indicate dates when the
biomass was below detection. August through December of each year
are highlighted in yellow to indicate the approximate destratification
periods of Brownlee Reservoir. Data for the Brownlee Inflow location
were only available for plots A–E [THg, total mercury; ng/L,
nanograms per liter; ng/g, nanograms per gram dry weight].
Aqueous and biological
methylmercury (MeHg) at Brownlee Inflow,
Brownlee Outflow, and Oxbow Outflow, June 2018 to September 2019.
Data gaps in fish and other invertebrates indicate dates when the
biomass was below detection. August through December of each year
are highlighted in yellow to indicate the approximate destratification
periods of Brownlee Reservoir. Data for the Brownlee Inflow location
were only available for plots A–E [THg, total mercury; ng/L,
nanograms per liter; ng/g, nanograms per gram dry weight].Following the increase in aqueous MeHg concentrations
at Brownlee
Outflow in August to September 2018, concentrations decreased by 56%
in October 2018, coincident with the pause in destratification (Figure ). Concentrations
then rebounded in late November 2018 (Figure ), coincident with the entrainment and downstream
export of anoxic water in the hypolimnion (Figure B).Aqueous MeHg concentrations at
Oxbow Outflow were similar to (p > 0.05; MeHgF and MeHgPV) or less
than (p < 0.05; %MeHgP and MeHgPG) those at Brownlee Outflow, but in both cases followed a
similar temporal pattern to those at Brownlee Outflow (Figure A–E and Table S5). This temporal pattern of increased
aqueous MeHg concentrations at Brownlee and Oxbow Outflows during
the August to December destratification period has previously been
observed during 2015–2017 as well (Figure S7).[17] In contrast, aqueous MeHg
at Brownlee Inflow varied independently of this pattern (Figure A–E), suggesting
that the outflow MeHg concentrations were controlled by in-reservoir,
rather than upstream, processes. The importance of in-reservoir processes
on MeHg export from Brownlee Reservoir, originally discussed by Baldwin
et al.,[17] is further supported by the decoupling
of aqueous MeHg concentrations between Brownlee Inflow and Brownlee
Outflow from 2014 to 2021, as discussed in the Supporting Information and presented in Figures S7 and S8.Unlike in 2018, Brownlee Outflow
and Oxbow Outflow aqueous MeHg
concentrations showed little or no increase through the 2019 destratification
period (Figure S7). This coincided with
a smaller volume of anoxic + hypoxic water in Brownlee Reservoir in
2019 versus 2018 (Figure S7A). Analysis
of aqueous MeHg and DO data from 2014 to 2020 (Figure S7) showed the reservoir anoxic volume to be a good
predictor of aqueous MeHg concentrations at Brownlee Outflow during
the destratification period (MeHgFR2 of 0.79, Figure ; MeHgPVR2 of 0.66).
While anoxia is known to be a key factor in MeHg production in the
metalimnion and hypolimnion,[9] our results
indicate that the volume of reservoir anoxia prior to destratification
may be a key driver of MeHg export downstream during destratification.
This finding is especially relevant in light of recent global projections
of increasing anoxia in reservoirs driven by land use and climate
change.[5] A greater understanding of the
factors controlling the development and extent of reservoir anoxia
and how those factors can be mitigated in the face of land use and
climate change will support reservoir management decision-making.
Figure 4
Relationship
between the annual maximum volume of Brownlee Reservoir
hypoxic and anoxic water and concentrations of filter-passing methylmercury
(MeHgF) at Brownlee Outflow during the destratification
period (August to December) [ng/L, nanograms per liter; mg/L, milligrams
per liter; m3, cubic meters; DO, dissolved oxygen].
Relationship
between the annual maximum volume of Brownlee Reservoir
hypoxic and anoxic water and concentrations of filter-passing methylmercury
(MeHgF) at Brownlee Outflow during the destratification
period (August to December) [ng/L, nanograms per liter; mg/L, milligrams
per liter; m3, cubic meters; DO, dissolved oxygen].
MeHg Concentrations in Biota
Among the biological compartments,
MeHg concentrations were greatest in fish (36.6–488 ng/g),
zooplankton (6.60–495 ng/g), and other invertebrates (1.50–610
ng/g) (Figure B and Table S5). In contrast, MeHg concentrations in
coarse and fine detritus were generally the lowest (0.10–198
ng/g) and were comparable to those of SPM. The temporal pattern of
MeHg in zooplankton and both detritus categories at Brownlee Outflow
followed that of aqueous MeHg, indicating the rapid uptake (zooplankton)
and partitioning (detritus) of MeHg concurrent with the reservoir
destratification (Figure F–J and Table S5). MeHg
of invertebrates in the Brownlee Outflow samples followed the same
approximate pattern as that of zooplankton and detritus, but the data
gaps prevent the determination of the exact timing of those maxima
(Figure G). Temporal
patterns in fish MeHg concentrations were not discernible because
fish were predominately associated with a high flow at the reservoir
outflow locations and were absent from the samples throughout much
of the study period (Figure H).As was observed with aqueous MeHg concentrations,
biological MeHg concentrations appeared to be lower during the 2019
destratification period than during the 2018 destratification period,
although biological sampling concluded prior to complete destratification
(Figure ). Zooplankton,
invertebrate, and fish MeHg concentrations at Oxbow Outflow were similar
(p > 0.05) to those at Brownlee Outflow, whereas
detrital concentrations were slightly lower (p <
0.05). In both cases, biological MeHg concentrations at Oxbow Outflow
followed a similar temporal pattern, as observed at Brownlee Outflow.We evaluated the linkages between aqueous MeHg concentrations and
biological MeHg concentrations at each location using Spearman correlations
(Table S6). Across all sampling events,
regardless of reservoir stratification, zooplankton MeHg concentrations
were significantly correlated with MeHgF at both Brownlee
Outflow (r = 0.70, p < 0.0001)
and Oxbow Outflow (r = 0.49, p =
0.0049) (Figure A).
However, when data were binned by the Brownlee Reservoir stratification
status (i.e., mixed, stratifying and stratified, destratifying), we
found that the relationship was only significant during the destratifying
period (Brownlee Outflow: r = 0.92, p < 0.0001; Oxbow Outflow: r = 0.91, p < 0.0001; Figure B–D). This suggests that the destratification period is a
critical time for MeHg formed in the metalimnion and hypolimnion to
become incorporated at the base of the aquatic food web. Zooplankton
MeHg concentrations were also correlated with MeHgPG at
both sites, although the relationships were not as strong as with
MeHgF (Table S6). Neither fish
nor invertebrate MeHg concentrations were significantly correlated
with MeHgF (Table S6). While
this could be related to gaps in our fish and other invertebrate data,
a similar lack of correlation has been observed elsewhere[20] and is likely attributed to a combination of
food web complexity and spatial/temporal scale differences for MeHg
incorporation among the different biological matrices. Fish MeHg was
weakly correlated with zooplankton MeHg at Brownlee Outflow (r = 0.49, p = 0.078) and more strongly
correlated with Oxbow Outflow (r = 0.56, p = 0.046) (Table S6), supporting
the idea that plankton MeHg is an important determinant of MeHg in
fish within the reservoirs.[20,38,39]
Figure 5
Relationship
between methylmercury (MeHg) in filter-passing water
and zooplankton samples from Brownlee Outflow and Oxbow Outflow. (A)
Samples from the entire study period June 2018 to September 2019;
(B–D) samples binned based on the stratification state of Brownlee
Reservoir. Linear regressions are shown as solid lines, and confidence
intervals of the fit are shaded [ng/L, nanograms per liter; ng/g,
nanograms per gram dry weight; r = Spearman correlation; p = p value on the Spearman correlation].
Relationship
between methylmercury (MeHg) in filter-passing water
and zooplankton samples from Brownlee Outflow and Oxbow Outflow. (A)
Samples from the entire study period June 2018 to September 2019;
(B–D) samples binned based on the stratification state of Brownlee
Reservoir. Linear regressions are shown as solid lines, and confidence
intervals of the fit are shaded [ng/L, nanograms per liter; ng/g,
nanograms per gram dry weight; r = Spearman correlation; p = p value on the Spearman correlation].A limited number of studies have reported the rapid
increase in
MeHg concentrations on SPM and in biota concurrent with the reservoir
destratification that we observed in this study. Herrin et al.[11] reported rapid increases in particle-associated
and Daphnia MeHg, concurrent with the thermal destratification and
mixing of anoxic hypolimnetic water in Devils Lake, Wisconsin (USA);
they concluded that much of the mass of MeHg built up in the hypolimnion
was rapidly taken up by particulate matter in the mixed zone during
turnover. Similarly, Slotton et al.[19] reported
rapid increases in THg (MeHg was not analyzed) in zooplankton and
juvenile fish, concurrent with the thermal destratification and mixing
of anoxic hypolimnetic water in Davis Creek Reservoir. Whereas Herrin
et al. and Slotton et al. focused on in-lake and in-reservoir processes,
the current study fills an important knowledge gap by showing with
the high temporal resolution that these processes also influence downstream
MeHg export from reservoirs.
MeHg Loads
Daily loads were estimated for (1) biomasses
(zooplankton, other invertebrates, fish, and fine and coarse detritus),
(2) SPM, (3) biological MeHg, and (4) aqueous MeHg (MeHgF and MeHgPV) at Brownlee Outflow and Oxbow Outflow. Here,
we present load estimates for the June 2018 to September 2019 study
period. For comparison over a wider range of hydrological conditions,
the annual load estimates of aqueous MeHg and inorganic divalent Hg
for the period 2015–2020 are provided in Figures S9 and 10 and Table S7.Daily loads of total biomass ranged from 0.0735 to 18.3 megagrams/day
(Mg/day; mean 2.04 Mg/day) at Brownlee Outflow and 0.0907 to 17.5
Mg/day (mean 1.75 Mg/day) at Oxbow Outflow (Figures A and S13A and Table S8). At both locations, the biomass loads
were greater in spring and summer months, when streamflows were the
greatest, compared to fall and winter. Zooplankton dominated biomass
loads at both locations, comprising, on average, 94.8 and 88.2% of
the total biomass loads at Brownlee Outflow at Oxbow Outflow, respectively
(Figures B and S13B and Table S8).
Coarse and fine detritus together comprised 4.91 and 11.7%, respectively,
of the total biomass loads at the two locations. The export of detritus
biomass was primarily observed during the March to June (2019) spring
snowmelt period, during which they made up half or more of the total
biomass loads (Figures B and S13B). Fish made up only 0.190 and
0.034% of the total biomass load at Brownlee Outflow and Oxbow Outflow,
respectively. Similarly, other invertebrates made up only 0.150 and
0.070% of the total biomass load at Brownlee Outflow and Oxbow Outflow,
respectively. The loads of SPM exceeded the loads of biomass by several
orders of magnitude, ranging from 14,800 to 943,000 Mg/day (mean 144,000
Mg/day) at Brownlee Outflow and 14,200 to 1,330,000 Mg/day (mean 182,000
Mg/day) at Oxbow Outflow (Table S8).
Figure 6
Brownlee Outflow
(A,B) biomass and (C,D) biological (bio) methylmercury
(MeHg) loads in individual biological compartments, and (E,F) total
biological MeHg load compared with aqueous (filter-passing and particulate)
MeHg loads. Load estimates based on biweekly samples, June 2018 to
September 2019. A companion figure for Oxbow Outflow is provided in Figure S13 [Mg, megagrams; g, grams].
Brownlee Outflow
(A,B) biomass and (C,D) biological (bio) methylmercury
(MeHg) loads in individual biological compartments, and (E,F) total
biological MeHg load compared with aqueous (filter-passing and particulate)
MeHg loads. Load estimates based on biweekly samples, June 2018 to
September 2019. A companion figure for Oxbow Outflow is provided in Figure S13 [Mg, megagrams; g, grams].The total biological MeHg loads ranged from 0.00906
to 0.677 g/day
(mean 0.111 g/day) at Brownlee Outflow and 0.00674 to 0.345 g/day
(mean 0.0945 g/day) at Oxbow Outflow (Figures C and S13C and Table S9). Biological MeHg loads were almost
entirely associated with zooplankton, which accounted for 98.9 and
96.7% of the total biological MeHg load at each location, on average
(Figures D and S13D and Table S9).
The second greatest share of the total biological MeHg load was fish
at Brownlee Outflow (mean 0.584%) and fine detritus at Oxbow Outflow
(2.66%). At both locations, some of the highest biological MeHg loads
were in September 2018 (Figures C and S13C), a period when
the biomass loads were relatively low (Figures A and S13A) but
biological MeHg concentrations were high (Figure ), coincident with the first stage of destratification
of Brownlee Reservoir (Figure ).The total biological MeHg loads were far surpassed
by the loads
of MeHgP and MeHgF (Figures E and S13E). Loads
of MeHgP were nearly an order of magnitude greater than
the total biological MeHg loads, ranging between 0.197 and 4.22 g/day
(mean 0.912 g/day) at Brownlee Outflow and 0.0643–3.24 g/day
(mean 0.814 g/day) at Oxbow Outflow (Table S9). The greatest MeHgP loads occurred during the spring
snowmelt period, when streamflows were the greatest, despite low MeHg
concentrations in particles during that time (Figure E). MeHgF loads ranged between
0.270 and 5.24 g/day (mean 1.53 g/day) at Brownlee Outflow and 0.172–4.64
g/day (mean 1.60 g/day) at Oxbow Outflow (Table S9). The combined aqueous (MeHgF and MeHgP) plus biological MeHg load at Brownlee Outflow averaged 2.55 g/day
and comprised 5.22% biological, 59.1% MeHgF, and 35.7%
MeHgP (Figure E,F and Table S9). The combined
aqueous plus biological MeHg load at Oxbow Outflow was similar, averaging
2.51 g/day, and comprised 4.88% biological, 65.0% MeHgF, and 30.1% MeHgP (Figure S13E,F and Table S9).The relative distribution
of MeHg export among individual aqueous
and biological compartments in the current study is consistent with
the previous findings from Caniapiscau Reservoir (Quebec, Canada).[21] In Brownlee Reservoir, the distribution was
59.1% MeHgF, 35.7% MeHgP, 5.17% zooplankton,
0.03% fish, <0.01% other invertebrates, and 0.016% detritus. In
Caniapiscau Reservoir, the distribution was 64.3% MeHgF, 33.2% MeHgP, 1.54% zooplankton, 0.85% phytoplankton,
0.1% fish, <0.01% other invertebrates, and 0.01% detritus.[21] The relatively small proportion of biological
MeHg export (4.87–5.22% of the total MeHg export; Table S9) relative to particle-bound MeHg export
(30.1–35.7%) in the current study reflects the quantity of
biomass versus suspended particles in the water column. MeHg concentrations
in zooplankton, which made up the vast majority of the total biomass
(Figure B), were 10×
greater than MeHg concentrations on suspended particles (Figure B), but suspended
particles were 100× more abundant (Figure A). The suspended particles likely included
some phytoplankton and zooplankton, in addition to mineral particles,
but in relatively minor proportions: SPM data from Brownlee and Oxbow
Outflows averaged approximately 11% particulate organic carbon,[24] indicating that the majority of SPM was mineral.
We did not directly sample phytoplankton and zooplankton <125 μm,
but, based on the small proportion of particulate organic carbon in
SPM samples, we expect MeHg loads associated with phytoplankton and
zooplankton <125 μm to be small. In Caniapiscau Reservoir,
phytoplankton accounted for <1% of the total MeHg export.[21]Although our results show that the percentage
of total MeHg export
from the reservoirs as biological MeHg was small compared to that
of the aqueous compartments, we anticipate that the biological MeHg
disproportionately impacts MeHg concentrations in biota downstream
of the dams because fish are primarily exposed to MeHg through their
diet.[40] Thus, understanding the processes
driving MeHg production within reservoirs and MeHg uptake at the base
of the food web during and after destratification is critical to managing
mercury in fish within and downstream of reservoirs.
Authors: Daniele Kasper; Bruce R Forsberg; João H F Amaral; Rafael P Leitão; Sarah S Py-Daniel; Wanderley R Bastos; Olaf Malm Journal: Environ Sci Technol Date: 2014-01-10 Impact factor: 9.028
Authors: Austin K Baldwin; Brett A Poulin; Jesse Naymik; Charles Hoovestol; Gregory M Clark; David P Krabbenhoft Journal: Environ Sci Technol Date: 2020-07-15 Impact factor: 9.028
Authors: Stephen F Jane; Gretchen J A Hansen; Benjamin M Kraemer; Peter R Leavitt; Joshua L Mincer; Rebecca L North; Rachel M Pilla; Jonathan T Stetler; Craig E Williamson; R Iestyn Woolway; Lauri Arvola; Sudeep Chandra; Curtis L DeGasperi; Laura Diemer; Julita Dunalska; Oxana Erina; Giovanna Flaim; Hans-Peter Grossart; K David Hambright; Catherine Hein; Josef Hejzlar; Lorraine L Janus; Jean-Philippe Jenny; John R Jones; Lesley B Knoll; Barbara Leoni; Eleanor Mackay; Shin-Ichiro S Matsuzaki; Chris McBride; Dörthe C Müller-Navarra; Andrew M Paterson; Don Pierson; Michela Rogora; James A Rusak; Steven Sadro; Emilie Saulnier-Talbot; Martin Schmid; Ruben Sommaruga; Wim Thiery; Piet Verburg; Kathleen C Weathers; Gesa A Weyhenmeyer; Kiyoko Yokota; Kevin C Rose Journal: Nature Date: 2021-06-02 Impact factor: 49.962