Abstract
Fish consumption advisories for mercury (Hg) are common in rivers, highlighting connections between landscape sources of Hg and downstream fluvial ecosystems. Though watershed conditions can influence concentrations of Hg in smaller streams, how Hg changes downstream through larger rivers and how these changes associate with Hg concentrations in fish is not well understood. Here we present a continuum of concentrations and yields of total mercury (THg) and methylmercury (MeHg) from small tributary systems draining diverse western Canadian headwater landscapes through to major transboundary rivers. We associate these downstream patterns with THg concentrations in tissues of resident fish in major rivers. Mean concentrations and yields of unfiltered THg from over 80 monitored tributaries and major rivers were highly variable in space ranging from 0.28 to 120 ng L−1 and 0.39 to 170 µg ha−1 d−1, respectively. Using spatial data and a hierarchical cluster analysis, we identified three broad categories of tributary catchment conditions. Linear mixed modeling analysis with water quality variables revealed significantly lower THg concentrations in tributaries draining cordillera-foothills (geometric mean: 0.76 ng L−1) regions relative to those draining forested (1.5 ng L−1) and agriculturalized landscapes (2.4 ng L−1), suggesting that sources and mobility of THg in soils and surface waters were different between landscapes. However, these concentration differences were not sustained downstream in major rivers as local sources and sinks of THg in river channels smoothed differences between landscape types. Extensive fish tissue monitoring in major rivers and ANCOVA analysis found that site-specific, river water THg and MeHg concentrations and local catchment conditions were stronger associates of THg concentrations in fish than broader trends in rivers within and across landscape classes. Consequently, site-specific, targeted monitoring of THg and MeHg concentrations in water and fish is a preferred study design when assessing regional-level patterns in fish tissue concentrations.
Highlights
-
Mercury concentrations in rivers draining diverse headwater landscapes were different
-
Concentration differences were not sustained downstream in large rivers
-
Local conditions in rivers best associated with mercury concentrations in fish.
Introduction
Rivers serve as primary conduits of erodible and soluble terrestrial material to downstream lacustrine and marine environments. During riverine transit, this material may be deposited, re-suspended, biochemically transformed, supplemented or diluted by external sources, or simply delivered downstream (Schlesinger and others 2006). Mercury (Hg) is subjected to these fluvial processes and may be transformed to its toxic organic form methylmercury (MeHg) in aqueous environments and biomagnify up food chains (Liu and others 2011). Despite focus on Hg delivery, cycling, and toxicity within lacustrine, wetland, and estuarine receiving environments (Watras and others 1995; Branfireun and others 2001; Jiang and others 2018; Rudd and others 2018), Hg concentrations in fish collected from lotic ecosystems can be higher than in those ecosystems (Kamman and others 2005). In some cases, concentrations are high enough to warrant public health advice to limit consumption of fish tissues (Kinghorn and others 2007; Bookman and others 2008; Government of Alberta 2019; U.S. Environmental Protection Agency 2020). Because Hg inputs to and concentrations in aquatic systems are influenced by upstream sources and landscape characteristics (Hurley and others 1995), but also affect MeHg concentrations in fish tissues (Harris and others 2007; Orihel and others 2007), these river-based advisories highlight biogeochemical connections along this continuum.
Mercury delivered to river systems originates from sources external and internal to upstream watersheds and may mobilize downstream. External Hg sources include atmospheric deposition of anthropogenic (for example, coal combustion) and natural (for example, wildfires) material onto terrestrial landscapes and water bodies (Grigal 2002; Eckley and others 2013). Internal Hg sources include ore deposits (Kerfoot and others 2002), and Hg can be imported to watersheds via industrial releases (Bravo and others 2013). Organic soils and other biomass serve as important reservoirs of contemporary and legacy Hg from these internal and external sources (Grigal 2002; Steffen and Morrison 2016). Mobility of Hg throughout watersheds depends on many factors including climate, hydrologic connectivity, topography, erodibility of soils, vegetation cover, and land management practices, among others (Balogh and others 2003; Haynes and Mitchell 2012; Oswald and Branfireun 2014; Liu and others 2018). Previous assessments established associations between Hg in rivers with catchment extents of agricultural and industrial development (Hurley and others 1995; Babiarz and others 1998; Lyons and others 2006), wetlands (St Louis and others 1994; Shanley and others 2005; Schuster and others 2011; Bradley and others 2013), forest coverage and associated logging and wildfire events (Kelly and others 2006; Kronberg and others 2016), and erosive landforms (Kerr and Cooke 2017; Vermilyea and others 2017). Though these landscape–river connections are evident, particularly in smaller river systems, important physical and chemical changes within rivers may occur as these waters travel downstream (Harvey and Gooseff 2015).
As lotic systems progress downstream from headwaters to higher-order rivers, these waters become less reflective of landscape biogeochemistry as runoff is aggregated from larger diverse areas, erosion and deposition patterns change, basin geomorphology flattens, and groundwater influences increase (Temnerud and Bishop 2005). These downstream changes can enhance or depress concentrations of suspended material, dissolved organic matter, and ions in river water and may influence concentrations of Hg by association. These spatial changes can be confounded by difficulties quantifying Hg concentrations and yields in rivers considering: 1. rapid changes in flow and sediment transport occur often and associate closely with Hg (Babiarz and others 1998; Riscassi and others 2011; Haynes and Mitchell 2012); 2. ultraclean sampling requirements are not easily incorporated into automated sampling systems (Bradley and others 2013); 3. regression-type surrogate approaches (for example, turbidity) can be problematic during high flows (Wall and others 2005); and 4. high analytical costs limit the frequency, duration and locations of Hg sampling. As such, many previous studies of Hg in rivers have been of short duration, low sampling frequency, and limited spatial replication within and between river systems. Longer-term replicated sampling in rivers may improve our understanding of how landscapes impact Hg delivery to river systems, and if they can be associated with Hg concentrations in resident fish tissues.
Here, we present an integrated downstream spatial assessment of Hg in rivers from headwater tributaries, through passage into major rivers, to accumulation in resident fish tissues across Alberta, Canada. Specifically, we associate concentrations and watershed yields of unfiltered (UF) and filtered (F) total Hg (THg; all forms of Hg in a sample) and MeHg in tributaries and major rivers with different catchment landscape characteristics. We then use fish tissue monitoring from major Alberta rivers to provide insights into connections between THg in fish, river water Hg concentrations, and upstream catchment characteristics. We hypothesized that intact, forested landscapes would produce lower Hg yields and river water concentrations relative to those draining developed catchments. By extension, we expected to observe lower THg concentrations in fish tissues collected from rivers with lower river water THg concentrations and THg loading from catchments.
Methods
Study Region
Alberta is an ecologically diverse Canadian province. Landscapes vary from high elevation Rocky Mountain cordillera landscapes (> 3,000 m a.s.l.) in the west, through adjacent forested Foothills, to lower-relief Boreal Plains forests and wetlands, parkland forests, and prairie grasslands/shrublands toward the north, east, and south, respectively (Figure 1a). Glacial till characterizes much of the province’s surficial geology downstream from the Rocky Mountains. Approximately 55% of the province is covered with intact and fragmented/logged forests, followed by agricultural lands (28%), wetlands (~ 10%) and surface waters (~ 5%), barren/rocky lands (2%), and urban, industrial, and road land uses (1.5%) (ABMI 2019). Precipitation decreases from cordillera environments (> 600 mm y−1), northeastward though Boreal Plains (350–500 mm y−1) and southeastward to agricultural prairie grasslands (< 350 mm y−1; 1970–2000 normals) (Environment and Climate Change Canada 2018). Catchment water yields associate closely with precipitation patterns in Alberta (Kienzle 2012). Mean daily air temperature across the province reflects a continental climate with most of the province colder than −10 °C in January and not warmer than 18 °C in July.
a Land cover and mercury sampling stations on tributaries of major rivers of Alberta, western Canada, including drainage areas; b land cover and mercury sampling stations on major rivers of Alberta, including drainage areas; and c hierarchical cluster classification of tributary drainage areas using land cover, topographic slope, and climate variables. The Athabasca and Peace rivers contribute water to the Mackenzie River system to the north, the Milk River to the Mississippi system to the south, and all others to the Nelson-Churchill system to the east.
Albertan landscapes contain the headwaters of some of Canada’s largest rivers including the Mackenzie, Churchill, and Nelson rivers. A tributary of America’s Missouri-Mississippi river system, the Milk River, also passes through southern Alberta. Flow of most major central and southern Albertan rivers is low, consisting of glacier-fed mountain headwater rivers (for example, Bow at Calgary: 2–5 km3 y−1 [full records]; North Saskatchewan at Edmonton: 4–12 km3 y−1; South Saskatchewan upstream of Medicine Hat: 2–13 km3 y−1) (Water Survey of Canada 2021). Larger Boreal rivers occur in the north, including the glacier-sourced Athabasca (at Fort McMurray: 11–32 km3 y−1) and Peace (at Peace River: 29–91 km3 y−1) rivers. Annual flow of most rivers is highest during spring freshet, is supplemented by summer rainfalls, and decreases substantially through autumn and winter. Most major Alberta rivers (not Athabasca or Beaver) are regulated with flows higher in winter and lower during freshet than would occur naturally, though broad expected seasonal patterns of flow still exist. Certain rivers pass through major urban areas downstream of the Rockies including the Bow (Calgary metro population: ~ 1.4 M), North Saskatchewan (Edmonton: ~ 1.3 M), Oldman (Lethbridge: ~ 0.1 M), and Red Deer (Red Deer: ~ 0.1 M).
Sample Collection
River Water Quality Monitoring and Analysis
The Government of Alberta has monitored water quality monthly at several stations on its major rivers (draining ~ 82% of provincial area) for decades (Figure 1b). Tributaries of major rivers have been monitored sporadically over time, including annual and seasonal (March – October) monthly sampling (Figure 1a; Table S1). At each station, water was collected as near surface grab samples and analyzed for general water quality (major ions, nutrients, trace metals) at accredited laboratories. Monitoring for concentrations of trace-level THg at tributary and major river stations began in rivers as early as 2007. MeHg samples were taken from only selected tributaries and major rivers starting in 2013. During open water, most THg and MeHg samples were obtained by wading waist-deep and collecting water as surface grab samples at approximately 30 cm depth into new amber glass bottles (Environmental Sampling Supply). On larger rivers (for example, Athabasca, Peace rivers), samples were often collected at 30 cm depth at the thalweg from a boat. Winter samples, where open leads on rivers were not present, were collected by drilling a hole through river ice, clearing slush, and collecting water below the ice by hand or using a glass bottle attached to a plastic-lined sampling rod. All samples were collected using the “clean-hands, dirty-hands” USEPA Method 1669 for trace metals sampling (U.S. Environmental Protection Agency 1996) with some modifications for single-person sampling in smaller rivers of central and southern Alberta. An extensive quality control program consisting of distilled–deionize water blanks and replicate samples was included in regular sampling (see Supporting Information, Table S2). After collection, THg and MeHg samples were field-preserved with HCl to 0.2% and 0.4% volume, respectively, and stored at 4 °C until analysis. Samples for filtered measurements were filtered using 0.45 µm cellulose nitrate filters within 24 h of collection.
All water THg analyses were performed using oxidation, purge and trap, and cold vapour atomic fluorescence spectrometry (CVAFS) via USEPA Method 1631E (U.S. Environmental Protection Agency 2002) (see Supporting Information). THg analyses were performed by two different laboratories with a method detection limit of 0.04 ng L−1 for Innotech Alberta and a reportable detection limit (RDL) of 0.06 ng L−1 for the Biogeochemical Analytical Service Laboratory at the University of Alberta (BASL; 2012–2018) (see Figure S1 for lab comparison). Innotech Alberta analyzed only THgUF samples while BASL analyzed both THgUF and THgF (RDL: 0.08 ng L−1). MeHg analyses were performed only at BASL using isotope dilution, distillation, aqueous ethylation, purge and trap (via Tekran 2700) with inductively coupled plasma mass spectrometry via USEPA Method 1630 (U.S. Environmental Protection Agency 1998) with minor modifications (see Supporting Information). RDLs for MeHgUF and MeHgF were each 0.01 ng L−1. General water quality parameters analyzed from samples collected concurrently with THg were nutrients (nitrate [NO3−], total Kjeldahl nitrogen [TKN], sulfate [SO42−]), organic matter (dissolved organic carbon [DOC]), suspended material (total suspended solids [TSS]), trace metals (total recoverable aluminium [TAl]), and in-river measurements (pH, specific conductivity [COND]). These supporting parameters were selected based on typical associations with Hg reported in literature (for example, Babiarz and others 2012).
Fish Collection and Analysis
THg concentrations in fish tissues from major Alberta rivers were sourced from monitoring programs operated by the Government of Alberta (province-wide), the Oil Sands Monitoring Program (Athabasca and Peace rivers), and Environment and Climate Change Canada (North and South Saskatchewan rivers). These monitoring programs spanned different years between 2006 and 2016, which overlapped in time with river water Hg sampling (Table S3). Generally, fish collection methods consisted of gill netting, angling, electrofishing, or other means. Biometric information from each fish was recorded including species, whole-fish wet weight, total and/or fork length, and sex. Fillets or whole fish (filleted later) were frozen and submitted to accredited laboratories for THg determination using USEPA 1631E and USEPA 7473 (see Supporting Information).
Numerical and Spatial Analyses
River Water Mercury Concentrations and Yields
Data used for numerical assessments included all monthly THg samples from tributaries with more than 16 THgUF samples over three years and five separate months (2007–2018; n = 47; Table S1), and all monthly samples from major rivers (2007–2018; n = 35 stations). At all stations, mean concentrations and other descriptive statistics were calculated, as well as F:UF and MeHg:THg concentration ratios, where available. Watershed yields were calculated at all stations for each sample by quantifying the product of THg concentrations and mean daily flow measured on the sample day at the nearest flow station (Table S4) and dividing by the catchment area upstream of the sample location (see next section). Since MeHg sampling was much less widespread amongst river stations than THg, MeHgUF and MeHgF concentrations and yields were used to support THg analyses and interpretations.
Watershed Associations with Mercury in River Water
For all catchments upstream of water quality stations, watershed characteristics were compiled using spatial data within a Geographical Information System (ArcGIS; v.10.7.1; ESRI, Redlands, USA). ArcGIS Hydro Tools and an interpolated 100 m digital elevation model were used to delineate catchment areas upstream of water quality stations. Land cover data from the Landsat 5 Thematic Mapper (30 m resolution) for Alberta and surrounding jurisdictions were obtained from Canadian and US governments (Agriculture and Agri-Food Canada 2015; Homer and others 2015). Relative catchment areas of each land cover type were calculated. Mean topographic slope was quantified for each watershed using national digital elevation models (Gesch and others 2002; Natural Resources Canada 2013). Mean annual precipitation and air temperature within each catchment were taken from climate model interpolations of western North America (ABMI 2021). Stream density, used as a supporting measure of hydrologic connectivity, was calculated using total stream lengths from 1:50,000 digital topographic maps and dividing by upstream catchment area.
To group watersheds by landscape characteristics for comparisons of Hg concentrations and yields in rivers, we entered all spatial data (described above) of 47 independent tributary catchments into a hierarchical clustering analysis (HCA) using standardized scores, Euclidean distances, and Ward’s clustering method (manual cluster selection) using SPSS (v26; IBM, New York, USA). Absolute ranges of spatial data within each cluster were used to similarly classify the larger, more integrated major river watersheds post-HCA (Table S5). We then used log10-transformed THg concentration and yield data from all stations to assess differences between landscape types using linear mixed-effects models in SPSS. Mixed-models statistically account for model variability from repeated sampling (non-independence) at each station while still assessing fixed effects (that is, differences between landscape clusters). In the models, we used autoregressive covariance structures for repeated data, random effects modeling of regression intercepts, and Sidak multiple comparisons to distinguish significance in Hg among landscape types. Statistical similarity and differences in geometric means between landscape types for THg concentrations and yields were subsequently reported (α = 0.05). Different linear mixed models were developed for tributaries and major rivers to assess relative changes in Hg concentrations and yields between landscapes of these smaller and larger systems. Principal components analysis (PCA) was used (Canoco v. 5.03; Biometris, The Netherlands) to group THg concentrations with general chemistry and river flow for further biogeochemical insights between river and landscape types.
Mercury in Fish of Major Rivers
Analyses of fish THg data focused on two taxonomic groups that afforded robust spatial comparisons: walleye (Sander vitreus) and suckers (family Catostomidae). Walleye were collected from all major rivers in Alberta, but were absent from upper (mountain) reaches. Using THg concentrations and wet weights, we grouped walleye data (n ≥ 5 individuals) by broad geographic region in major rivers (Table S3) and applied landscape type classifications to these groups based on the closest major river water quality station to the grouping geography. In the sucker family, species represented included longnose sucker (Catostomus catostomus), shorthead redhorse (Moxostoma macrolepidotum), and white sucker (Catostomus commersoni). Longnose sucker and white sucker have similar broad distributions in Alberta, although the former can inhabit mountain reaches of rivers more successfully than the latter. Shorthead redhorse occur in major rivers and tributaries of central and southern Alberta, but are absent from northern basins. The taxonomic grouping of these species is justified, based on comparisons among species and within distinct locations (geographic groupings) for wet weight, THg concentration, and the relationship between weight and THg concentration. As for walleye, geographic groupings were constructed for suckers (Table S3) and major river landscape classifications were coded to those groups.
Analysis of covariance (ANCOVA) was used to compare THg concentrations in walleye and sucker tissues within and among major river groupings (that is, landscape classes). ANCOVA was chosen a priori as the standard parametric test for comparing a characteristic (THg concentration) of groups (distinct population or location) while controlling for the effect of another variable (size) on that characteristic. The covariate used was wet weight, as that was the most consistently reported measure of size among and between programs. An ANCOVA with Type III sums of squares was performed for each of the walleye and sucker taxonomic groups, with JMP15 (SAS, Cary, USA; see Supporting Information).
Using linear regression, THg concentrations of fish groupings were compared to major river THg and MeHg concentrations in water. THg concentrations in walleye and suckers were represented by least-squares means of geographic groupings from the ANCOVAs. Least-squares means can be considered size-adjusted means, because the ANCOVA adjusts group means of the dependent variable (THg concentration) by controlling for the effect of the covariate (wet weight). THg and MeHg concentrations in water were represented by recorded arithmetic means (full records) from the nearest water quality monitoring stations to fish geographic groupings (Table S3).
Results
River Water Mercury Concentrations and Yields
Concentrations of unfiltered and filtered THg from 47 small tributary systems were highly variable within and between rivers (Figure 2). Mean THgUF concentrations of sites ranged from 0.28 to 120 ng L−1 with coefficients of variation between 43 and 315%. Filtered THg concentrations were about 47% of unfiltered concentrations across all tributary sites with mean concentrations ranging from 0.19 to 18 ng L−1. Tributaries of the lower Red Deer River basin reported the highest mean THg concentrations of all sites, including some sites beyond acute guidelines for protection of aquatic life (PAL; CCME 2003). Upstream tributaries in basins generally had lower THg concentrations than those downstream. MeHgUF concentrations were similarly highest in tributaries of the lower Red Deer River compared to those north or west, and MeHgF concentrations comprised about 53% of MeHgUF concentrations of all tributaries sampled for MeHg (Figure S2).
Mean concentrations (left panels) and watershed yields (right panels) of unfiltered (± 1 standard error) and filtered total mercury in tributaries (upper panels) and major rivers (lower panels) of Alberta. Canadian surface water quality guidelines for the protection of aquatic life are indicated in concentration graphs. Basins are organized north to south (P-Peace; A-Athabasca; V-Beaver; N-North Saskatchewan; B-Battle; R-Red Deer; S-South Saskatchewan; M-Milk) and in-basin tributaries upstream to downstream. Bars without a bi-color scheme indicate that only unfiltered THg sampling occurred.
Mean THgUF concentrations of a given major river were highest in the Red Deer (mean ± S.E.: 6.3 ± 1.1 ng L−1) and Peace (6.0 ± 1.2 ng L−1), and lowest in the Bow (1.8 ± 0.2 ng L−1) and Beaver (1.8 ± 0.1 ng L−1). Across individual stations (Figure 2), mean THgUF was below 6 ng L−1 except for two from the lower Red Deer (7.8, 17 ng L−1) and one from the Peace (7.7 ng L−1). Of all THgUF samples (n = 3189), only 1.2% were above PAL guidelines and were mostly from the Red Deer, Athabasca, and Peace rivers and collected during open water conditions. Plains-sourced rivers (Battle, Beaver) had the highest mean THgF:THgUF (39–46%) while mountain-sourced rivers had more THg bound to coarse suspended particles (THgF:THgUF: 13–26%). Concentrations of THg in major rivers generally increased downstream from west to east across the province. MeHgUF concentrations (Figure S2) were highest in the Red Deer River (0.14 ± 0.02 ng L−1) and lowest in the Peace River (0.061 ± 0.013 ng L−1), and all samples collected province-wide (n = 629; max: 1.4 ng L−1) were well below national guidelines (4 ng L−1) (CCME 2003). MeHgF concentrations comprised 41% of MeHgUF concentrations in major rivers. Province-wide, MeHgUF:THgUF (from 21 stations) was 0.6–12.1% (mean: 3.7%) and highest in the Beaver River. Overall, MeHg concentrations in tributaries and major rivers were positively correlated with THg concentrations (Figure S3).
Similar to concentrations, watershed yields of THgUF of tributary stations were highly variable in space ranging from 0.39 to 170 µg ha−1 d−1 with THgF comprising 41% of those yields (Figure 2). In contrast with concentrations, THgUF yields were typically highest in those tributaries draining high elevation catchments in the west and decreased toward eastern regions, though tributaries of the lower Red Deer River were an exception to this pattern. THgUF yields from major rivers (3.1–130 µg ha−1 d−1) were similar to those from tributaries and generally decreased from western stations toward eastern stations. Yields were lowest in plains-sourced rivers relative to mountain-sourced rivers, and only 22% of major river THgUF yields were attributed to THgF. Annual riverine THg yields of major rivers (0.09–1.3 µg m−2 y −1) were lower than province-wide total atmospheric deposition (~ 6–25 µg m−2 y −1) (Steffen and Morrison 2016) and rivers of other jurisdictions (Table 1).
Watershed Associations with Mercury in River Water
We distinguished three broad landscape classes across Alberta using climate, topography, and land cover geospatial data from 47 independent tributary catchments (Figures 1c, 3, S4). Cordillera-foothills catchments reside in western Alberta and are colder, wetter, and steeper than other landscapes and are predominantly covered in intact forests and barren rocky surfaces. Water quality of tributaries draining these catchments is dilute and sediment- and nutrient-poor. Forested catchments occur mostly within low-relief Boreal Plains forests of northern Alberta. These landscapes are drier than cordillera-foothills catchments and are predominantly forested with wetlands and few agricultural areas. Water quality in forested catchments is of low conductivity and pH, moderate suspended sediment concentrations, and high DOC concentrations compared to other tributaries. Finally, low-relief agriculturalized catchments are relatively warm, dry, and covered by crop and pasture lands with few forests compared to other catchments. Water quality in these smaller, sometimes ephemeral streams is concentrated with dissolved ions, DOC, nutrients, metals, and suspended sediments.
THgUF concentrations in tributaries draining cordillera-foothills regions (geometric mean: 0.76 ng L−1) were statically lower than those draining forested (1.5 ng L−1) and agriculturalized (2.4 ng L−1) catchments (Figure 4, Table S6). At the alpha 0.07 level, agriculturalized catchments had higher THgUF concentrations in river water than the other two landscape types, as also observed for arithmetic mean (± SE) MeHgUF concentrations between the landscapes (forested: 0.16 ± 0.01; agriculturalized: 0.29 ± 0.06 ng L−1). Filtered THg concentrations draining forested (0.95 ng L−1) and agriculturalized (0.89 ng L−1) catchments also were significantly higher than cordillera-foothills (0.37 ng L−1) rivers (Table S6). Notably, forested tributaries had much higher F:UF concentration ratios (65%) compared to agriculturalized (37%) or cordillera-foothills (49%) tributaries. Tributary concentrations of THg in cordillera-foothills and agriculturalized landscape class were decoupled from dilution-concentration flow patterns as THg PCA scores were toward right angles to a flow-conductivity gradient in ordination space (Figure 5). Typically larger forested tributaries showed THg concentrations associated closer to dilution-concentrations patterns in ordination space. In major rivers, THg concentrations were statistically similar between all landscape types (α = 0.05) as they increased in the cordillera-foothills regions and generally decreased in agricultural and forested regions, relative to tributaries. MeHgUF concentrations similarly decreased in agriculturalized major rivers from 0.28 to 0.16 ng L−1. However, THgF concentrations in forested major rivers (0.68 ng L−1) were higher than cordillera-foothills regions (0.43 ng L−1) at an alpha of 0.06. Cordillera-foothills and forested major rivers showed a coupling of THg concentrations with flow along the concentration-dilution gradient, but agriculturalized major rivers were decoupled from this pattern, similar to unforested tributary classes. THgUF and THgF were close in ordination space at all sites, similar to correlations between THg and MeHg (Figure S3).
Geometric means (± 95% confidence intervals) of unfiltered (upper panels) and filtered (lower panels) total mercury concentrations (left panels) and yields (right panels) for rivers within each of the three hierarchical clusters. Consecutive letters within each landscape grouping denote statistical differences at α = 0.05 and *denotes statistical differences at α = 0.06–0.07 with the preceding category.
Principal components analysis biplots of general water quality parameter concentrations (see Methods for acronym definitions), river flow (Q), and concentrations of unfiltered (UF) and filtered (F) total mercury from tributaries and major rivers. Variability explained by the first two principal components for each biplot shown in parentheses.
THg yields of tributaries showed much different patterns between landscape types relative to concentrations. Both THgUF and THgF yields of cordillera-foothills and forested tributaries were statistically greater than agriculturalized catchments (Figure 4). Nearly three-quarters of THg yields from forested catchments were due to THgF compared to the other landscape types (33–43%). Interestingly, THgUF yields of cordillera-foothills major rivers (7.6 µg ha−1 d−1) were significantly higher than both forested and agriculturalized major rivers (1.3–2.6 µg ha−1 d−1) while major rivers showed similar relative landscape differences in THgF yields as tributaries, with agriculturalized catchments having lower yields than the other landscapes.
Mercury in Fish of Major Rivers
The ANCOVAs for walleye and suckers produced similar results indicating significant variation in size-adjusted THg concentrations among major rivers. For walleye and suckers, six geographical groupings met the assumption of linearity for THg-wet weight regressions and had slopes significantly different from zero (Table S7). For walleye, slopes of the regression lines were not statistically different among the six geographical groupings (F5,382 = 1.52; p = 0.182), but corresponding intercepts were statistically different among groupings (F5,387 = 14.37; p < 0.001). A Tukey’s HSD test found that the least-squares mean (± S.E.) of THg concentrations in walleye from the Peace-middle grouping (0.24 ± 0.01 µg g−1 ww; cordillera-foothills class) was significantly lower than other forested locations (Figure 6).
Least squares means (± 1 standard error) of total mercury concentrations from geographical groupings (that is, landscape classes) of fish from major Alberta rivers (left panels). Mean unfiltered and filtered total mercury and methylmercury concentrations (± SE) of nearby water quality monitoring stations relative to fish tissue concentrations of total mercury in geographical groupings of fish collected from major Alberta rivers (right panels). Regression symbol coloring matches the landscape classes in the left panel legend.
For suckers, slopes of the regression lines were statistically different among the six geographical groupings (F5,390 = 2.77; p = 0.018) and upon removal of the slope with the lowest r2 (Athabasca-lower), resulted in no difference in slopes among the remaining five groupings (F4,188 = 1.57; p = 0.185). Accordingly, we found statistical differences in intercepts among groupings (F4,192 = 8.24; p < 0.001) and found least-squares means of THg concentration increased in fish from the Bow-upper (0.10 ± 0.02 µg g−1 ww) to the Athabasca-middle (0.18 ± 0.01 µg g−1 ww) to Red Deer-lower (0.28 ± 0.03 µg g−1 ww; Figure 6). This pattern represented a transition from a cordillera-foothills dominated station to two forested stations. A lone agriculturalized grouping in the lower South Saskatchewan River was similar in fish tissue concentrations to both forested groupings, while the cordillera-foothills Oldman R. middle site had fish Hg tissue concentrations similar to other forested and agriculturalized sites.
Linear regressions between least-squares mean fish tissue THg concentrations and Hg concentrations in river water (THg, MeHg) showed variation among rivers in the former can be described by the latter, particularly by MeHg. For walleye, there was no significant relationship between THg concentrations in fish and in water, but there were strong relationships with mean MeHg concentrations in unfiltered (n = 5; r2 = 0.920; p = 0.010) and filtered (n = 5; r2 = 0.655; p = 0.097) water. For suckers, there were strong relationships between least-squares means of THg concentrations and mean THg concentrations in unfiltered (n = 5; r2 = 0.784; p = 0.046) and filtered (n = 5; r2 = 0.585; p = 0.132) water and mean MeHg concentrations in unfiltered water (n = 4; r2 = 0.992; p = 0.004).
Discussion
Landscape Connections to Mercury Concentrations in Headwater Tributaries
The biogeochemistry of small, headwater tributaries reflects their close connections to landscapes (Alexander and others 2007). Our PCA results from tributaries support this connection as close groupings of THgUF, THgF, t-Al, and TKN in ordinal space suggests co-mobilization of particle-bound nutrients, THg, and metal oxy-hydroxides from soils and surface waters via erosion and soil flushing (Grigal 2002; Park and others 2018). Particularly in smaller headwater streams (that is, cordillera-foothills, agriculturalized) with limited in-channel sinks and sources of landscape material, these associations were de-coupled with flow, which is consistent with hysteresis-type patterns indicating off-channel, landscape contributions of chemicals to rivers (Buendia and others 2016). Considering broad seasonal changes of Hg concentrations with flow in rivers (Figures S5–S8), inconsistent monitoring locations relative to cities (Figure 1) and industrial effluents (not shown), and human impacts on landscapes dominated by agriculture (ABMI 2019), we suggest that THg and MeHg sources and mobility at our scale of monitoring are related much more to landscape conditions, rather than local urban or industrial activities. As such, we expected broad landscape differences to be a key driver of THg mobility downstream in tributary and major river systems.
Alberta’s high-relief regions present climate and topographic conditions ideal to erosively mobilize THg due to high precipitation rates upon steep, dendritic landscapes (Figure 3; Riscassi and others 2011). However, throughout the Rockies, sediment and organic matter supply to rivers is poor due to predominance of unvegetated mountains, coarse gravels and boulders, thin or patchy soils, lack of wetland development, and national protection of landscapes from widespread development. Though foothills rivers drain rolling landscapes with more developed soils, forest cover fortifies soils and reduces erosive mobilization of THgUF (Gamby and others 2015). The general absence of lakes or wetlands on higher-relief topography likely reduces export of dissolved organic material and THgF downstream (Guentzel 2009; St Pierre and others 2019; Staniszewska and others 2021); thus, most Hg mobility in these systems is particle-bound. Together, these conditions support the observed lower THg concentrations in cordillera-foothills tributaries relative to other landscape types. Mass-wasting events, however, are common in these regions and can produce pulses of sediment to rivers that are offset from flow changes (Lee and others 2013).
In agriculturalized tributary catchments, which are dominated by drier climates with convective storms, rich organic chernozemic soils (CSC 1998) are exposed to storm-related gulley erosion and downstream mobilization of soils, nutrients and organic matter (Figure 3). This process is aided by row crop management that typically results in greater mechanical interventions of soils (for example, disking, seeding) and periods when erosive runoff moves across and through soils without established vegetation cover or soil cohesiveness (Kort and others 1998; Sherriff and others 2016). Often this material carries bound Hg in coarse and colloidal forms (passing through filters) and subsequently results in relatively high THgUF and THgF concentration in rivers (Hurley and others 1995; Babiarz and others 1998, 2012; Balogh and others 2003; Warner and others 2005a; Naik and Hammerschmidt 2011; Riscassi and others 2011; Ruzycki and others 2011; Kerr and Cooke 2017; Lim and others 2019). This sediment-rich load includes bound MeHg likely produced in methylating agricultural environments such as riparian corridors, beaver-induced flooded areas, and shallow wetlands and lakes (Ullrich and others 2001). Though intense storm-driven erosion of agricultural soils can increase THg concentrations in rivers, we also observed agriculturalized landscapes with lower river water THg concentrations that are associated closely with catchments of perennial pastures and grassland cover (Figure 3). This relationship can be attributed to fortification of soils by grasses that could limit soil detachment events (Kort and others 1998) and likely partly explains the mere statistical similarity between forested and agriculturalized THg concentrations in tributaries (Figure 4).
In the low-relief Boreal Forest, landscapes store water in organic soils and wetlands that typically results in surface waters high in DOC concentrations that can bind THgF (Figures 3, 5) (St Louis and others 1994; Wasiuta and others 2019). As such, we observed the highest DOC concentrations and THgF:THgUF concentration ratios from forested tributaries compared to others. Many of these wetlands and organic soils are adjacent to tributary channels and during hydrological events may result in efficient surface and subsurface flushing and transport of DOC and THg downstream (Bushey and others 2008; Devito and others 2012). Larger tributaries of forested regions may also mean a greater role of in-channel and river bank contributions of legacy material from landscapes, including particulate material and bound THg, during high flows. Together, these characteristics and processes of forested tributary landscapes may explain the lack of hysteresis observed and suggests potential changes in sources and mobilization of Hg as river sizes increase. Using data from major rivers, consequently, we tested the broader question if larger rivers downstream modify these landscape differences (that is, signals) as their geomorphologies and water compositions change.
Mercury Comparisons Between Tributaries and Major Rivers
Relative to tributaries, major river environments flattened differences in THg concentrations between landscape types and effectively reduced discernable upstream landscape influences on THg. We attribute this pattern to differences in how tributaries and larger rivers process sediments and dissolved material (and hence Hg) across different landscape types. In cordillera regions dominated by particle-bound transport of THg (Figure 2), hydrological energies can be vastly different between headwater regions and major river systems due to sharp slope transitions in connected river systems. This gradient promotes sediment entrainment in tributaries (albeit in low concentrations) but long-term sediment deposition in major rivers; notably observed as braided geomorphologies in high elevation environments (Knighton 2014). In cordilleran major rivers of Alberta, these deposits would likely include glacial flour and metal oxide material from upstream headwaters, which can bind significant concentrations of THgF (Hawkings and others 2021). Thus, upon high water events, these channel deposits would represent a steady source of local suspended material and bound THg to major rivers compared to scant sediment supplies in tributaries. Our PCA results support an in-channel source of sediments and THg in cordillera-foothills major rivers as it reported ordinal space clustering of flow, THg, TSS, and t-Al concentrations.
Agriculturalized regions, alternatively, are low-relief with impacted soils, intensive gulley erosion, and high sediment and THg concentrations in headwater rivers. Slope transitions there are less severe downstream relative to high-relief regions, thus promoting sedimentation at tributary confluences or continued entrainment of sediment, colloids, and THg downstream, particularly during high water in major rivers. Groundwater in these relatively small arid plains rivers is an important proportion of in-channel water that is often dilute in particle-bound THg during baseflow (Figures S5–S8). Therefore, pulses of high THgUF and THgF concentrations in tributaries during storms likely mix with major river waters more dilute in THg and depress concentrations. These arguments are supported by our PCA results that showed agriculturalized major rivers with no near-field associations between flow, suspended sediment or THg, similar to observations from agriculturalized tributaries.
Forested regions showed more consistent THgUF concentrations between tributaries and major rivers, likely due to a combination of processes. Similar to tributaries, major forested rivers reported relatively high THgF:THgUF and DOC concentrations that likely reflected sustained inputs of DOC-bound THg from adjacent wetland landscapes and upstream tributaries. For example, the fully Boreal-sourced Beaver River showed the highest THgF and DOC concentrations of all major rivers. PCA results from both river types also suggested in-channel sources of soil material and THg within these systems (Figure 5). Major Boreal rivers (for example, Peace, Athabasca) and tributaries flow across legacy glacial till deposits and source sediment in channels and river banks that are erodible during high water events (Shrestha and Wang 2018) likely mobilizing particle-bound THg. Finally, large groundwater proportions of river flow are a key characteristic of large Boreal tributaries and rivers (Gibson and others 2016) and are typically poor in particle-bound THg concentrations (Figure S5–S8). Low-relief topography and extensive surface water stores typical of Boreal landscapes also likely promotes storage of sediment and bound THg. Together, these synergies between river types likely explain the relatively few differences observed in Hg concentrations and associated water quality parameters downstream in forested regions.
Overall, downstream modification of THg concentrations from tributary to major river ecosystems suggests a weaker connection between landscapes and water in major rivers, due to in-channel processes that become relatively more important in larger rivers (Harvey and Gooseff 2015). Fish tissue THg concentrations collected from these rivers, alternatively, showed mixed results relative to this downstream continuum, suggesting an importance of local inputs of THg and MeHg relative to basin-scale conditions.
Landscape and Major River Connections to Mercury in Fish Tissues
Several studies have reported positive associations between habitat surface water THg and MeHg concentrations and THg concentrations in fish tissues (for example, Mason and others 1996). In small catchments, associations have been established between watershed characteristics and fish tissue concentrations (Warner and others 2005b; Rypel 2010; Marusczak and others 2011; Mattieu and others 2013). Using this hypothesis, we would expect few differences in THg fish tissue concentrations between fish caught in major rivers of cordillera-foothills, forested, and agriculturalized watersheds. However, we observed THg concentrations in fish varied significantly within and across different landscape types (Figure 6), suggesting site-specific, river water concentrations may be of greater importance than broad trends across landscape and river types. For example, both walleye and suckers showed close positive associations between THg tissue concentrations and MeHg concentrations in river water, despite varying differences in landscape type within regressions (Figure 6). This pattern supports MeHg concentrations and production rates in water being a key driver of bioconcentration and subsequent biomagnification of MeHg foodwebs (Mason and others 1996). For omnivorous suckers, river water THg concentrations also associated closely with tissue concentrations, which may reflect its bottom-feeding trophic position and greater non-diet exposure to THg in sediments (Rose and others 1999). Walleye, alternatively, are piscivorous species that primarily gain Hg via diet, rather than environmental exposure, and thus reported poor associations between tissue and river water THg concentrations, but higher tissue concentrations overall. Regardless, observations of THg concentrations in fish that were significantly different between landscape types (walleye and suckers), or significantly different within landscape types (suckers), point to site-specific differences driving Hg uptake in fish rather than broad regional differences (Rose and others 1999).
Several unique characteristics of specific river reaches where fish were collected may explain why THg concentrations in fish varied within and between major rivers. First, sites in the lower Red Deer River, though classed as forested in this study (Table S5), receive local runoff from exposed badlands and agriculturalized areas that can produce substantially high concentrations of THg and MeHg, particularly during summer storm events (Figure 2; S5–S8; Kerr and Cooke 2017). Donadt and others (2021) reported fish tissue concentrations in this region of the Red Deer River, consequently, are likely higher than surrounding regions. This helps explain statistically higher THg concentrations in suckers in the lower Red Deer relative to fish collected from other forested and cordillera-foothills groupings. Second, the Oldman-middle site reported fish with significantly higher THg concentrations than the Bow-upper site despite both groupings classified as cordillera-foothills. This difference reflects the high variability of THg concentrations within classifications as the Bow River site reported THg concentrations of only 0.51 ± 0.5 ng L−1 relative to the more locally-agriculturalized Oldman River site (2.8 ± 0.6 ng L−1; Table S5). This finding matches the work of Brinkmann and Rasmussen (Brinkmann and Rasmussen 2012) that reported increases in THg concentrations in aquatic biota (including suckers) along a continuum of the Oldman River from cordillera/foothills landscapes to more locally agricultural landscapes. Finally, walleye THg concentrations at the cordillera-foothills Peace R. Middle site were statistically lower than forested sites, despite reporting relatively high river water concentrations of THg. However, MeHg concentrations were very low at this site, possibly reflecting its water source from a large, cold, DOC-poor, mountain-fed oligotrophic reservoir likely limited in methylation sites (Bodaly and others 1993; Hsu-Kim and others 2018). Together, our results suggest that site-specific THg and MeHg concentrations and local characteristics associate better with fish tissue THg concentrations rather than broad catchment characteristics, whose signals diminish from headwaters to major rivers. Similarly, mercury loads carried by rivers that are largely influenced by river and catchment size differences between stations showed poor associations with fish tissue mercury concentrations (Figure S9). These findings are supported by results from Eagles-Smith and others (Eagles-Smith and others 2016) that showed site-specific THg and MeHg concentrations in rivers may be an important covariate of observed fish tissue concentrations. Consequently, our study suggests that site-specific, targeted monitoring of THg concentrations in water and fish, rather than landscape binning of collected fish, is a more important consideration in study designs when assessing regional-level patterns in fish tissue concentrations. This finding, in part, is likely due to downstream modification of landscape signals and water quality by large rivers relative to smaller tributary systems.
Mercury Yields and Connections to Landscape and Climate Change
In contrast with concentrations and our hypothesis, THg yields from intact tributaries were larger as they received more rainfall and had more widespread surface and subsurface hydrological connections than agriculturalized regions (Figure 4). Cordillera-foothills and forested regions are characterized by relatively frequent precipitation and large snow packs, widespread hydrological connectivity, ample coverage of surface waters, and large rivers. In contrast, drier agriculturalized regions dominated by net evaporation have smaller, lower-relief rivers subject to beaver activity, stagnation and drying. Short storm events drive much of Hg transport downstream and represent only short, intensive periods of hydrological connectivity that are buffered over annual scales. This seasonal pattern may sustain high mean concentrations in these rivers, but it does not equate to maintained export of Hg downstream.
Though Hg concentrations in aquatic ecosystems are of great importance for uptake by biota, yields are important measurements when considering source water quality in rivers and how potential future changes in climate and land use may impact those concentrations. Water quantity and quality in large rivers reflects mixing of various atmospheric, catchment runoff, subsurface, and in-channel sources of water and chemicals and disturbances to these sources can impact downstream water quality. For example, the highest yields of runoff and THg occur in cordillera and forested regions that are relatively intact and present more pristine environments compared to agriculturalized catchments. Cordillera-foothills and forested regions produce typically lower Hg concentrations in runoff and comprise most of the flows in Alberta’s major rivers (Water Survey of Canada 2021), leading to among the lowest observed Hg concentrations and yields of major rivers compared to other jurisdictions (Table 1). However, these regions are experiencing notable changes to their climates and landscapes with potential downstream effects on Hg content in major rivers. Precipitation and streamflow has declined measurably across the Alberta climate in recent decades (Rood and others 2005; Newton and others 2021), in particular in cordillera-foothills and Boreal regions. Declining streamflow from intact regions may shift the relative importance of runoff and Hg yields from agriculturalized regions in some major rivers, with potential negative effects on river water quality. Shortening of winter periods and increasing air temperatures projected for the Alberta climate (Newton and others 2021) further increase the risk of more widespread methylation in surface waters and more frequent and intense wildfires that can impact Hg cycling in forested landscapes (Kelly and others 2006). Land use change such as land clearing for roads, forestry, and energy activities has proceeded quickly across Alberta in cordillera-foothills and forested regions (ABMI 2019) and such changes are known to increase Hg yields downstream (Hsu-Kim and others 2018). How these changes impact downstream Hg delivery and concentrations in major rivers is an important, ongoing question in Alberta and will serve as an important bellwether for other rivers systems worldwide. Source water protection, consequently, is an important consideration in water quality management of large river systems undergoing climate and land use change, and in the case of Hg likely has long-term implications for the ultimate uptake of Hg in food webs of large rivers.
Data availability
Raw water quality and fish tissue quality data are available from: https://www.alberta.ca/open-government-program.aspx#jumplinks-0
References
ABMI. 2019. Wall-to-Wall Human Footprint Inventory 2017. Edmonton, Alberta https://abmi.ca/home/data-analytics/da-top/da-product-overview/Human-Footprint-Products/HF-inventory.html
ABMI. 2021. Wall-to_Wall Climate variables 1961–1990. https://abmi.ca/home/data-analytics/da-top/da-product-overview/Other-Geospatial-Land-Surface-Data/Climate-Variables.html
Agriculture and Agri-Food Canada. 2015. Land Use 2010. https://www.agr.gc.ca/atlas/landu
Alexander RB, Boyer EW, Smith RA, Schwarz GE, Moore RB. 2007. The role of headwater streams in downstream water quality 1. JAWRA J Amer Water Resour Assoc 43(1):41–59.
Babiarz C, Hoffmann S, Wieben A, Hurley J, Andren A, Shafer M, Armstrong D. 2012. Watershed and discharge influences on the phase distribution and tributary loading of total mercury and methylmercury into Lake Superior. Environ Pollut 161:299–310. https://doi.org/10.1016/j.envpol.2011.09.026.
Babiarz CL, Hurley JP, Benoit JM, Shafer MM, Andren AW, Webb DA. 1998. Seasonal influences on partitioning and transport of total and methylmercury in rivers from contrasting watersheds. Biogeochemistry 41:237–257.
Balogh SJ, Huang Y, Offerman HJ, Meyer ML, Johnson DK. 2003. Methylmercury in rivers draining cultivated watersheds. Sci Total Environ 304:305–313.
Balogh SJ, Meyer ML, Johnson DK. 1998. Transport of mercury in three contrasting river basins. Environ Sci Technol 32:456–462.
Balogh SJ, Nollet YH, Offerman HJ. 2005. A comparison of total mercury and methylmercury export from various Minnesota watersheds. Sci Total Environ 340:261–270.
Bodaly RA, Rudd JWM, Fudge RJP, Kelly CA. 1993. Mercury concentrations in fish related to size of remote Canadian Shield lakes. Canadian J Fisheries Aquatic Sci 50(5):980–987.
Bookman R, Driscoll CT, Engstrom DR, Effler SW. 2008. Local to regional emission sources affecting mercury fluxes to New York lakes. Atmos Environ 42:6088–6097.
Bradley PM, Journey CA, Brigham ME, Burns DA, Button DT, Riva-Murray K. 2013. Intra- and inter-basin mercury comparisons: Importance of basin scale and time-weighted methylmercury estimates. Environ Pollut 172:42–52. https://doi.org/10.1016/j.envpol.2012.08.008.
Branfireun BA, Bishop K, Roulet NT, Granberg G, Nilsson M. 2001. Mercury cycling in boreal ecosystems: The long-term effect of acid rain constituents on peatland pore water methylmercury concentrations. Geophys Res Lett 28:1227–1230.
Bravo AG, Cosio C, Amouroux D, Zopfi J, Chevalley PA, Spangenberg JE, Ungureanu VG, Dominik J. 2014. Extremely elevated methyl mercury levels in water, sediment and organisms in a Romanian reservoir affected by release of mercury from a chlor-alkali plant. Water Research 49:391–405.
Brinkmann L, Rasmussen JB. 2012. Elevated mercury levels in biota along an agricultural land use gradient in the Oldman River basin, Alberta. Can J Fish Aquat Sci 69(7):1202-1213.
Buendia C, Vericat D, Batalla RJ, Gibbins CN. 2016. Temporal Dynamics of Sediment Transport and Transient In-channel Storage in a Highly Erodible Catchment. L Degrad Dev 27:1045–63. https://doi.org/10.1002/ldr.2348. Last accessed 30/05/2019
Bushey JT, Driscoll CT, Mitchell MJ, Selvendiran P, Montesdeoca MR. 2008. Mercury transport in response to storm events from a northern forest landscape. Hydrol Process Int J, 22(25):4813–4826.
CCME. 2003. Canadian water quality guidelines for the protection of aquatic life: Inorganic mercury and methylmercury. In: Environment. CC of M of the, editor. Canadian environmental quality guidelines, 1999. Winnipeg http://ceqg-rcqe.ccme.ca/download/en/191
Devito K, Mendoza C, Qualizza C. 2012. Conceptualizing water movement in the Boreal Plains. Implications for watershed reconstruction. Synthesis report preapred for the Canadian Oil Sands Network for Research and Developement. :164.
Donadt C, Cooke CA, Graydon JA, Poesch MS. 2021. Mercury bioaccumulation in stream fish from an agriculturally-dominated watershed. Chemosphere 262:128059.
Eagles-Smith CA, Ackerman JT, Willacker JJ, Tate MT, Lutz MA, Fleck JA, Stewart AR, Wiener JG, Evers DC, Lepak JM, Davis JA. 2016. Spatial and temporal patterns of mercury concentrations in freshwater fish across the Western United States and Canada. Sci Total Environ 568:1171–1184.
Eckley CS, Parsons MT, Mintz R, Lapalme M, Mazur M, Tordon R, Elleman R, Graydon JA, Blanchard P, St Louis V. 2013. Impact of closing Canada’s largest point-source of mercury emissions on local atmospheric mercury concentrations. Environ Sci Technol 47:10339–10348.
Environment and Climate Change Canada. 2018. Canadian Climate Normals 1981–2010. http://climate.weather.gc.ca/climate_normals/. Last accessed 14/02/2018
Gamby RL, Hammerschmidt CR, Costello DM, Lamborg CH, Runkle JR. 2015. Deforestation and cultivation mobilize mercury from topsoil. Sci Total Environ 532:467–473.
Gesch D, Oimoen M, Greenlee S, Nelson C, Steuck M, Tyler D. 2002. The national elevation dataset. Photogramm Eng Remote Sens 68(1):5–32.
Gibson JJ, Yi Y, Birks SJ. 2016. Isotope-based partitioning of streamflow in the oil sands region, northern Alberta: Towards a monitoring strategy for assessing flow sources and water quality controls. J Hydrol Reg Stud 5:131–48. https://linkinghub.elsevier.com/retrieve/pii/S2214581815002141. Last accessed 30/05/2019
Government of Alberta. 2019. Fish Consumption Guidance: mercury in Fish. Edmonton, Alberta
Grigal DF. 2002. Inputs and outputs of mercury from terrestrial watersheds: A review. Environ Rev 10:1–39.
Guentzel JL. 2009. Wetland influences on mercury transport and bioaccumulation in South Carolina. Sci Total Environ 407(4):1344–1353.
Harris RC, Rudd JWM, Amyot M, Babiarz CL, Beaty KG, Blanchfield PJ, Bodaly RA, Branfireun BA, Gilmour CC, Graydon JA, Heyes A, Hintelmann H, Hurley JP, Kelly CA, Krabbenhoft DP, Lindberg SE, Mason RP, Paterson MJ, Podemski CL, Robinson A, Sandilands KA, St. Southworthn GR, Louis VL, Tate MT. 2007. Whole-ecosystem study shows rapid fish-mercury response to changes in mercury deposition. Proc Natl Acad Sci USA 104:16586–91.
Harvey J, Gooseff M. 2015. River corridor science: Hydrologic exchange and ecological consequences from bedforms to basins. Water Res Research 51(9):6893–6922.
Hawkings JR, Linhoff BS, Wadham JL, Stibal M, Lamborg CH, Carling GT, Lamarche-Gagnon G, Kohler TJ, Ward R, Hendry KR, Falteisek L. 2021. Large subglacial source of mercury from the southwestern margin of the Greenland Ice Sheet. Nat Geosci 14(7):496–502.
Haynes KM, Mitchell CPJ. 2012. Inter-annual and spatial variability in hillslope runoff and mercury flux during spring snowmelt. J Environ Monit 14:2083–2091.
Homer C, Dewitz J, Yang L, Jin S, Danielson P, Xian G, Coulston J, Herold N, Wickham J, Megown K. 2015. Completion of the 2011 National Land Cover Database for the conterminous United States–representing a decade of land cover change information. Photogramm Eng Remote Sens 81(5):345–354.
Hsu-Kim H, Eckley CS, Achá D, Feng X, Gilmour CC, Jonsson S, Mitchell CP. 2018. Challenges and opportunities for managing aquatic mercury pollution in altered landscapes. Ambio 47(2):141–169.
Hurley JP, Benoit JM, Babiarz CL, Shafer MM, Andren AW, Van JRS, Hammond R, Webb DA. 1995. Influences of Watershed Characteristics on Mercury Levels in Wisconsin Rivers. Environ Sci Technol 29:1867–1875.
Jiang T, Bravo AG, Skyllberg U, Björn E, Wang D, Yan H, Green NW. 2018. Influence of dissolved organic matter (DOM) characteristics on dissolved mercury (Hg) species composition in sediment porewater of lakes from southwest China. Water Research 146:146–158.
Kamman NC, Burgess NM, Driscoll CT, Simonin HA, Goodale W, Linehan J, Estabrook R, Hutcheson M, Major A, Scheuhammer AM, Scruton DA. 2005. Mercury in freshwater fish of northeast North America–a geographic perspective based on fish tissue monitoring databases. Ecotoxicol 14(1):163–180.
Kasper D, Forsberg BR, Amaral JHF, Py-Daniel SS, Bastos WR, Malm O. 2017. Methylmercury Modulation in Amazon Rivers Linked to Basin Characteristics and Seasonal Flood-Pulse. Environ Sci Technol 51:14182–14191.
Kelly EN, Schindler DW, St. Louis VL, Donald DB, Vladicka KE. 2006. Forest fire increases mercury accumulation by fishes via food web restructuring and increased mercury inputs. Proc Natl Acad Sci 103:19380–5. https://doi.org/10.1073/pnas.0609798104. Last accessed 30/05/2019
Kerfoot WC, Harting SL, Rossmann R, Robbins JA. 2002. Elemental mercury in copper, silver and gold ores: an unexpected contribution to Lake Superior sediments with global implications. Geochem Explor Environ Anal 2(2):185–202.
Kerr JG, Cooke CA. 2017. Erosion of the Alberta badlands produces highly variable and elevated heavy metal concentrations in the Red Deer River, Alberta. Sci Total Environ 596–597:427–436. https://doi.org/10.1016/j.scitotenv.2017.04.037.
Kienzle SW. 2012. Water Yield and Streamflow Trend Analysis for Alberta Watersheds. https://albertawater.com/water-yield-streamflow-analysis
Kinghorn A, Solomon P, Chan HM. 2007. Temporal and spatial trends of mercury in fish collected in the English–Wabigoon river system in Ontario, Canada. Sci Total Environ 372(2–3):615–623.
Kirk, Jane L, Vincent L, St. Louis. 2009. Multiyear total and methyl mercury exports from two major sub-Arctic rivers draining into Hudson Bay, Canada. Environ Sci Technol 43(7):2254–2261.
Knighton D. 2014. Fluvial forms and processes: A new perspective.
Kort J, Collins M, Ditsch D. 1998. A review of soil erosion potential associated with biomass crops. Biomass and Bioener 14(4):351–359.
Kronberg RM, Drott A, Jiskra M, Wiederhold JG, Björn E, Skyllberg U. 2016. Forest harvest contribution to Boreal freshwater methyl mercury load. Global Biogeochem Cycles 30:825–843.
Lee G, Yu W, Jung K. 2013. Catchment-scale soil erosion and sediment yield simulation using a spatially distributed erosion model. Environ Earth Sci 70(1):33–47.
Lim AG, Sonke JE, Krickov IV, Manasypov RM, Loiko SV, Pokrovsky OS. 2019. Enhanced particulate Hg export at the permafrost boundary, western Siberia. Environ Pollut 254:113083. https://doi.org/10.1016/j.envpol.2019.113083.
Liu G, Cai Y, O’Driscoll N. 2011. Environmental Chemistry and Toxicology of Mercury.
Liu M, Zhang Q, Luo Y, Mason RP, Ge S, He Y, Yu C, Sa R, Cao H, Wang X, Chen L. 2018. Impact of water-induced soil erosion on the terrestrial transport and atmospheric emission of mercury in China. Environ Sci Technol 52(12):6945–6956.
Lyons WB, Fitzgibbon TO, Welch KA, Carey AE. 2006. Mercury geochemistry of the Scioto River, Ohio: Impact of agriculture and urbanization. Appl Geochemistry 21:1880–1888.
Marusczak N, Larose C, Dommergue A, Paquet S, Beaulne JS, Maury-Brachet R, Lucotte M, Nedjai R, Ferrari CP. 2011. Mercury and methylmercury concentrations in high altitude lakes and fish (Arctic charr) from the French Alps related to watershed characteristics. Sci Total Environ 409(10):1909–1915.
Mason RP, Reinfelder JR, Morel FMM. 1996. Uptake, toxicity, and trophic transfer of mercury in a coastal diatom. Environ Sci Technol.
Mattieu CA, Furl CV, Roberts TM, Friese M. 2013. Spatial trends and factors affecting mercury bioaccumulation in freshwater fishes of Washington State, USA. Archiv Environ Contamin Toxicol 65(1):122–131.
Naik AP, Hammerschmidt CR. 2011. Mercury and trace metal partitioning and fluxes in suburban Southwest Ohio watersheds. Water Res 45:5151–5160. https://doi.org/10.1016/j.watres.2011.07.023.
Natural Resources Canada. 2013. Canadian Digital Elevation Model. Ottawa https://open.canada.ca/data/en/dataset/7f245e4d-76c2-4caa-951a-45d1d2051333
Newton BW, Farjad B, Orwin JF. 2021. Spatial and temporal shifts in historic and future temperature and precipitation patterns related to snow accumulation and melt regimes in Alberta, Canada. Water 13(8):1013.
Orihel DM, Paterson MJ, Blanchfield PJ, Bodaly RA, Hintelmann H. 2007. Experimental evidence of a linear relationship between inorganic mercury loading and methylmercury accumulation by aquatic biota. Environ Sci Technol 41(14):4952–4958.
Oswald CJ, Branfireun BA. 2014. Antecedent moisture conditions control mercury and dissolved organic carbon concentration dynamics in a boreal headwater catchment. Water Resour Res 50(8):6610–6627.
Park JH, Wang JJ, Xiao R, Pensky SM, Kongchum M, DeLaune RD, Seo DC. 2018. Mercury adsorption in the Mississippi River deltaic plain freshwater marsh soil of Louisiana Gulf coastal wetlands. Chemos 195:455–462.
Riscassi AL, Hokanson KJ, Scanlon TM. 2011. Streamwater particulate mercury and suspended sediment dynamics in a forested headwater catchment. Water Air Soil Pollut 220:23–36.
Rood SB, Samuelson GM, Weber JK, Wywrot KA. 2005. Twentieth-century decline in streamflows from the hydrographic apex of North America. J Hydrol 306(1–4):215–233.
Rose J, Hutcheson MS, West CR, Pancorbo O, Hulme K, Cooperman A, Decesare G, Isaac R, Screpetis A. 1999. Fish mercury distribution in Massachusetts, USA lakes. Environ Toxicol Chem Inter J 18(7):1370–1379.
Rudd JW, Bodaly RA, Fisher NS, Kelly CA, Kopec D, Whipple C. 2018. Fifty years after its discharge, methylation of legacy mercury trapped in the Penobscot Estuary sustains high mercury in biota. Sci Total Environ 642:1340–1352.
Ruzycki EM, Axler RP, Henneck JR, Will NR, Host GE. 2011. Estimating mercury concentrations and loads from four western Lake Superior watersheds using continuous in-stream turbidity monitoring. Aquat Ecosyst Heal Manag 14:422–432.
Rypel AL. 2010. Mercury concentrations in lentic fish populations related to ecosystem and watershed characteristics. Ambio 39(1):14–19.
Schlesinger WH, Reckhow KH, Bernhardt ES. 2006. Global change: The nitrogen cycle and rivers. Water Resources Research, 42(3).
Schuster PF, Striegl RG, Aiken GR, Krabbenhoft DP, Dewild JF, Butler K, Kamark B, Dornblaser M. 2011. Mercury export from the Yukon River Basin and potential response to a changing climate. Environ Sci Technol 45:9262–9267.
Shanley JB, Kamman NC, Clair TA, Chalmers A. 2005. Physical controls on total and methylmercury concentrations in streams and lakes of the northeastern USA. ECOTOXICOLOGY 14:125–134.
Sherriff SC, Rowan JS, Fenton O, Jordan P, Melland AR, Mellander PE, Huallachain DO. 2016. Storm event suspended sediment-discharge hysteresis and controls in agricultural watersheds: implications for watershed scale sediment management. Environ Sci Technol 50(4):1769–1778.
Shrestha NK, Wang J. 2018. Predicting sediment yield and transport dynamics of a cold climate region watershed in changing climate. Sci Total Environ 625:1030–1045.
Soil Classification Working Group, 1998. The Canadian system of soil classification. Agriculture and agri-food Canada publication, 1646, p.187.
St Louis VL, Rudd JWM, Kelly CA, Beaty KG, Bloom NS, Flett RJ. 1994. Importance of wetlands as sources of methyl mercury to boreal forest ecosystems. Can J Fish Aquat Sci 51:1065–1076.
St Pierre KA, St Louis VL, Lehnherr I, Gardner AS, Serbu JA, Mortimer CA, Muir DCG, Wiklund JA, Lemire D, Szostek L, Talbot C. 2019. Drivers of Mercury Cycling in the Rapidly Changing Glacierized Watershed of the High Arctic’s Largest Lake by Volume (Lake Hazen, Nunavut, Canada). Environ Sci Technol 53:1175–1185.
Staniszewska KJ, Cooke CA, Reyes AV. 2020. Quantifying Meltwater Sources and Contaminant Fluxes from the Athabasca Glacier, Canada. ACS Earth Space Chem 5(1):23–32.
Steffen A, Morrison H. 2016. Canadian Mercury Science Assessment.
Temnerud J, Bishop K. 2005. Spatial variation of streamwater chemistry in two Swedish boreal catchments: Implications for environmental assessment. Environ Sci Technol 39:1463–1469.
U.S. Environmental Protection Agency. 1996. Method 1669, Sampling Ambient Water for Trace Metals at EPA Water Quality Criteria Levels. Washington, D.C.
U.S. Environmental Protection Agency. 1998. Method 1630, Methyl Mercury in Water by Distillations, Aqueoius Ethylation, Purge and Trap, and Cold Vapor Atomic Fluorescence Spectrometry. Washington, D.C.
U.S. Environmental Protection Agency. 2002. Method 1631, Revision E: Mercury in Water by Oxidation, Purge and Trap, and Cold Vapor Atomic Fluorescence Spectrometry. Washington, D.C.
U.S. Environmental Protection Agency. 2020. Fish and Shellfish Advisories and Safe Eating Guidelines. Environ Prot Agency. https://www.epa.gov/choose-fish-and-shellfish-wisely/fish-and-shellfish-advisories-and-safe-eating-guidelines. Last accessed 23/12/2020
Ullrich SM, Tanton TW, Abdrashitova SA. 2001. Mercury in the aquatic environment: a review of factors affecting methylation. Critical Rev Environ Sci Technol 31(3):241–293.
Vermilyea AW, Nagorski SA, Lamborg CH, Hood EW, Scott D, Swarr GJ. 2017. Continuous proxy measurements reveal large mercury fluxes from glacial and forested watersheds in Alaska. Sci Total Environ 599–600:145–155. https://doi.org/10.1016/j.scitotenv.2017.03.297.
Wall GR, Ingleston HH, Litten S. 2005. Calculating mercury loading to the tidal Hudson River, New York, using rating curve and surrogate methodologies. Water Air Soil Pollut 165:233–248.
Warner KA, Bonzongo JCJ, Roden EE, Ward GM, Green AC, Chaubey I, Lyons WB, Arrington DA. 2005. Effect of watershed parameters on mercury distribution in different environmental compartments in the Mobile Alabama River Basin, USA. Sci Total Environ 347(1–3):187–207.
Warner KA, Bonzongo JCJ, Roden EE, Ward GM, Green AC, Chaubey I, Lyons WB, Arrington DA. 2005. Effect of watershed parameters on mercury distribution in different environmental compartments in the Mobile Alabama River Basin, USA. Sci Total Environ 347:187–207.
Wasiuta V, Kirk JL, Chambers PA, Alexander AC, Wyatt FR, Rooney RC, Cooke CA. 2019. Accumulating Mercury and Methylmercury Burdens in Watersheds Impacted by Oil Sands Pollution. Environ Sci Technol 53:12856–12864.
Water Survey of Canada. 2021. Archived hydrometric data. http://www.wateroffice.ec.gc.ca/. Last accessed 01/07/2021
Watras CJ, Morrison KA, Host JS, Bloom NS. 1995. Concentration of mercury species in relationship to other site-specific factors in the surface waters of northern Wisconsin lakes. Limnol Oceanogr 40:556–565.
Zolkos S, Krabbenhoft DP, Suslova A, Tank SE, McClelland JW, Spencer RGM, Shiklomanov A, Zhulidov AV, Gurtovaya T, Zimov N, Zimov S, Mutter EA, Kutny L, Amos E, Holmes RM. 2020. Mercury Export from Arctic Great Rivers. Environ Sci Technol 54:4140–4148.
Acknowledgements
Funding for water quality and portions of the fish work was provided by the Government of Alberta through operational budgets and grants to partners. We would like to thank the numerous Alberta Environment and Parks (AEP) technicians and supervisors who collected mercury and other water quality samples since 2007. We appreciate the work of Water Survey of Canada and AEP, taking hours of manual flow measurements and data truthing annual flow records. We would also like to thank AEP and ECCC fisheries technicians for collecting and processing fish for mercury analyses. Research funding of the river water monitoring program was provided by the Government of Alberta and the Government of Canada. Funding for portions of the fish work was provided by the Oil Sands Monitoring Program co-led by the Governments of Canada and Alberta, but does not necessarily reflect the position of the Program. We acknowledge the laboratory staff from the Alberta Centre for Toxicology at the University of Calgary for analyses of the fish collected by AEP and from Innotech Alberta and the University of Alberta Biogeochemical Analytical Service Laboratory for mercury in water analyses. Also thanks to Bureau Veritas staff for analysis water samples for general chemistry. Finally, we appreciate the time and input from anonymous reviewers whose input improved our manuscript.
Author information
Authors and Affiliations
Corresponding author
Additional information
Author contributions
Author Contributions: CE conceived study, performed research, analyzed data, and wrote paper. PD conceived study, performed research, analyzed data, and wrote paper. JS conceived study, performed research, and analyzed data. CC conceived study, performed research, and analyzed data. JG conceived study, performed research, and analyzed data. MR conceived study, performed research, and analyzed data. ME performed research and analyzed data. MM performed research and analyzed data.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Emmerton, C.A., Drevnick, P.E., Serbu, J.A. et al. Downstream Modification of Mercury in Diverse River Systems Underscores the Role of Local Conditions in Fish Bioaccumulation. Ecosystems 26, 114–133 (2023). https://doi.org/10.1007/s10021-022-00745-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10021-022-00745-w
Keywords
- mercury
- methylmercury
- river
- bioaccumulation
- fish
- water quality
- land cover
- agriculture
- boreal
- mountain