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. 2024 Jul 30;58(32):14396–14409. doi: 10.1021/acs.est.4c00789

Wildfires Influence Mercury Transport, Methylation, and Bioaccumulation in Headwater Streams of the Pacific Northwest

Austin K Baldwin †,*, James J Willacker ‡, Branden L Johnson ‡, Sarah E Janssen §, Collin A Eagles-Smith ‡
PMCID: PMC11325654  PMID: 39078944

Abstract

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The increasing frequency and severity of wildfires are among the most visible impacts of climate change. However, the effects of wildfires on mercury (Hg) transformations and bioaccumulation in stream ecosystems are poorly understood. We sampled soils, water, sediment, in-stream leaf litter, periphyton, and aquatic invertebrates in 36 burned (one-year post fire) and 21 reference headwater streams across the northwestern U.S. to evaluate the effects of wildfire occurrence and severity on total Hg (THg) and methylmercury (MeHg) transport and bioaccumulation. Suspended particulate THg and MeHg concentrations were 89 and 178% greater in burned watersheds compared to unburned watersheds and increased with burn severity, likely associated with increased soil erosion. Concentrations of filter-passing THg were similar in burned and unburned watersheds, but filter-passing MeHg was 51% greater in burned watersheds, and suspended particles in burned watersheds were enriched in MeHg but not THg, suggesting higher MeHg production in burned watersheds. Among invertebrates, MeHg in grazers, filter-feeders, and collectors was 33, 48, and 251% greater in burned watersheds, respectively, but did not differ in shredders or predators. Thus, increasing wildfire frequency and severity may yield increased MeHg production, mobilization, and bioaccumulation in headwaters and increased transport of particulate THg and MeHg to downstream environments.

Keywords: mercury methylation, invertebrates, climate change, watershed, soil, sediment, ecosystem health, human health

Short abstract

This study demonstrates that wildfires are linked to greater mercury transport and bioaccumulation in some taxa, and may promote increased Hg methylation, in headwater streams of the northwestern United States, with implications for downstream ecosystems and human health.

Introduction

Climate change is increasing the frequency and severity of wildfires,1−5 leading to widespread ecosystem disruptions.6 Rising temperatures and persistent drought have resulted in conditions conducive to wildfires such as low fuel moisture and elevated vapor pressure deficits,7,8 and additional drivers such as changes in land cover, ignition patterns, and fire suppression have exacerbated these effects.9 As a result, larger, longer-lasting, and more intense wildfires are becoming common worldwide,10−12 affecting the structure and function of the burned ecosystems.6,13 Wildfires destroy ground cover and roots and can reduce water infiltration through development of hydrophobic ash layers in soil, leading to increased runoff and erosion of soil material to streams.14 Suspended solids loads often increase, potentially for years, after wildfires15 and can negatively impact downstream water quality by increasing turbidity; transporting nutrients, pathogens, and organic and inorganic contaminants; and increasing treatment costs for drinking water.16,17

Although many ecosystem alterations driven by climate change are self-evident, there can also be substantial indirect effects on a range of ecosystem processes that are more difficult to parse. For example, climate change-driven shifts in ecosystem biogeochemical processes can alter contaminant cycling, further exacerbating the degradation of high-quality habitat and the risks to ecosystem health. One such chemical of concern is mercury (Hg), which is ubiquitous in the environment and contributes to 81% of all fish consumption advisories within the United States (U.S.).18 Soils and plants sequester large amounts of atmospherically deposited Hg over time.19−21 Wildfires can re-emit this Hg back to the atmosphere through combustion of plant biomass and thermal volatilization from soils.22−25 Depending on burn intensity and other factors, up to 97% of Hg in the organic soil horizon may be volatilized to the atmosphere during wildfires.26−28 This soil Hg depletion may be expected to reduce Hg transport and bioaccumulation but is countered by increased erosion. Additionally, wildfires may affect watershed Hg cycling by altering soil properties (e.g., soil organic carbon concentrations and characteristics),22,29 hydrologic flow paths,14,30 and canopy loss.31 Little is known about the interactions among these competing mechanisms on the aqueous mobilization and transport of Hg within burned watersheds.32−34 Those few studies that have evaluated wildfire effects on aqueous Hg transport have been limited in geographic scope, lacking landscape replication necessary for broader inference, or focused on either immediate or decadal responses after fires.35−39 Similarly, little is known about how wildfire might alter Hg bioaccumulation in headwater streams.34 Recent laboratory studies have shown that although wildfire ash can strongly sequester inorganic Hg,40 it may also promote MeHg production and subsequent bioaccumulation when labile organic matter leaches from the ash and mobilizes inorganic Hg in sediments.29 Field studies on post wildfire Hg bioaccumulation are very limited and have focused on biota in a downstream lake, rather than in the headwater streams that are often most directly affected by wildfires.37,41−43 Such a lack of information is particularly problematic given the importance of coupling between in-stream and watershed ecological processes in forested headwaters.44 The linkages between headwater streams and their watersheds are strong,45,46 and fire-induced changes in vegetation, light levels, flows, and productivity are known to influence stream food webs47,48 and are therefore likely to also impact Hg bioaccumulation in the streams.

To address some of the knowledge gaps related to the effects of wildfires on Hg transport and bioaccumulation in headwater streams in the medium term (i.e., one-year post fire, after first flush rain events and a winter snowmelt), we conducted a comprehensive survey of 36 burned and 21 reference (unburned) watersheds associated with 12 wildfires from 2020 and 2021 across 3 states of the northwestern U.S. Medium-term conditions were targeted for this study and represent ecosystem recovery one-year post burn. These conditions fill an important data gap for understanding Hg exposure to headwater organisms in the period after the first flush/snowmelt post fire (i.e., short-term conditions). The study was designed to address the effects of wildfire occurrence and severity on (1) in-stream concentrations of aqueous filter-passing and particulate THg and MeHg, and sediment total Hg (THg); (2) Methylmercury (MeHg) bioaccumulation in different aquatic invertebrate guilds; and (3) the relationships between Hg concentrations in soil, streamwater, and aquatic invertebrates. Replication within and among watersheds and fires allowed us to robustly account for the variation among localities that was not associated with wildfire effects and enabled us to identify broad patterns that may not have been measurable by focusing on a small number of fire-affected watersheds. To date, this is the first comprehensive regional-scale assessment of wildfire effects on Hg cycling targeting watershed (soils) and instream (water, sediment, biota) impacts. These findings fill an important gap in the understanding of medium-term wildfire effects on Hg cycling and bioaccumulation in headwater streams and highlight potential downstream environmental impacts, which are particularly relevant with more frequent and intense wildfires and increasing pressures on quality water supplies worldwide.

Methods

Site Selection

Between 2021 and 2022, we sampled 57 streams associated with 12 separate wildfires or wildfire complexes (henceforth collectively referred to as wildfires) in Oregon, Washington, and Idaho, U.S.A. (Figure 1A; Table S1). Each stream was sampled in the summer or autumn approximately one year after its wildfire (fire and sampling dates are provided in Table S1). For each fire, we sampled 1–5 watersheds within the burn perimeter (36 total) and 1–3 nearby reference watersheds outside the burn perimeter (21 total; Figure 1B). Watersheds were selected based on perennial flow, distribution of burn severities within the watershed, accessibility, and, in the case of reference watersheds, proximity to and similar topography and vegetation as the burned watersheds. The majority of streams were first, second, or third order. In some cases, fourth or fifth order streams were sampled because lower order streams lacked adequate flow or were inaccessible. Burn severities were based on the Composite Burn Index (CBI), a standardized rating of the fire’s composite effects on understory vegetation and midstory and overstory trees.49 CBI burn severities included four categories: low, moderate, and high burn severity areas and “unchanged” (which can include unburned areas as well as areas that were burned so lightly that vegetation cover was largely unaffected). Burned watersheds spanned a wide range of burn extents (44–100% of watershed area burned) and burn severities (2–95% of watershed burned at high severity; Figure 1D; Table S1). Watershed areas ranged 1.19–235 km2 (median 11.0 km2). Watersheds spanned five level III ecoregions and encompassed a variety of forest types present in the northwestern US, with land cover dominated by evergreen forest (median 80.4% of watershed) followed by shrub/scrub (median 13.2%; Table S1).50 To broadly characterize forest types, we distinguished between fires in three geographic regions: the western Cascades, eastern Cascades, and “interior” (composed of sites in the Blue Mountains, Columbia Plateau, and Idaho Batholith ecoregions). Methods used for delineating catchments and determining watershed CBI, and land cover percentages, are described in the Supporting Information (SI; Geospatial Methods).

Figure 1.

Figure 1

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(A) Map of sampled wildfires from 2020 to 2021 in the northwestern U.S. (B) Example of sampled burned and reference watersheds associated with the Cougar Peak Fire, Oregon. (C) Example soil sampling locations relative to watershed burn severities and location of water, sediment, and biological samples in Bauers Creek and Cox Creek. (D) Summary of wildfire severity in each of the 57 sampled watersheds based on the Composite Burn Index.

Sample Collection and Analysis

Sample collection and analysis are detailed in SI. Briefly, water, sediment, periphyton, in-stream leaf litter, and aquatic invertebrates were collected in the stream channel at the downstream extent of each watershed, and soil samples (duff, organic soil, and mineral soil) were collected at upgradient locations (Figure 1C). All samples were collected using trace metal clean procedures51 during baseflow conditions. Baseflow conditions were targeted because they represent chronic exposure conditions, and they enabled relevant comparisons across watersheds (i.e., concentrations during stormflow conditions are dynamic and subject to hysteresis, complicating comparisons across watersheds). Water samples were collected directly into 2 L polyethylene terephthalate glycol bottles using the grab method at the center of flow. Sediment samples consisted of composites of the top ∼2.5 cm of sediment from three depositional areas along the sampled reach of each stream and were collected by using a clean stainless-steel or polyethylene hand scoop. Field duplicates of water and sediment samples are summarized in Table S2. Six water sample field blanks were also collected and are summarized in Figure S1. Periphyton was composited from submerged rocks by using a stainless-steel scraper. In-stream terrestrial leaf litter was collected from submerged leaf-dams and depositional areas, taking care to ensure that invertebrates were not included in the samples. Aquatic invertebrates representing five trophic guilds were targeted in each stream: shredders, grazers, collectors, filter-feeders (hereafter termed filterers), and predators. Invertebrates were primarily collected using kicknets or D-nets. Soil samples were collected from areas with different CBI burn severities throughout each watershed (Figure 1C). Three soil samples were collected from each represented CBI category when possible. Three soil layers were collected at each soil sampling location, when present: duff (undecomposed or partially decomposed leaf and needle litter on the soil surface), organic soil (O- and A- horizons; typically, <3 cm), and mineral soil (B-horizon, to a depth of up to 5 cm beneath the organic soil). Although we differentiate between duff and organic soils, these layers represent a gradation of litter decomposition that was qualitatively distinguished. An effort was made to minimize inclusion of organic soil in duff samples, but some inclusion may have occurred when organic soil particles were adhered to duff material. The separation of the organic and mineral layers was based on texture and color and therefore considered approximate. Soil samples were collected from an average of ten unique locations in each burned watershed, whereas three representative locations were targeted in each reference watershed (1234 total soil samples, including all layers). All samples were stored in the dark on ice while in the field. In the laboratory, sediment, periphyton, in-stream leaf litter, invertebrate, and soil samples were transferred to −20 °C until processing and analysis.

Water samples were analyzed for filter-passing (<0.7 μm) volumetric THg and MeHg (f.THg and f.MeHg), dissolved organic carbon (DOC), particulate volumetric THg and MeHg (p.THg and p.MeHg), and suspended particulate material (SPM) by the U.S. Geological Survey (USGS) Mercury Research Laboratory (USGS-MRL; Madison, Wisconsin). Concentrations of f.THg, p.THg, and DOC were determined using standard methods.52−54 Concentrations of f.MeHg and p.MeHg were analyzed using standard preparation methods55,56 but were quantified by isotope dilution on an inductively coupled plasma mass spectrometer.57 SPM was calculated as the mass of particulates per volume of water filtered by subtracting the weight of the quartz fiber filter prior to sample collection from the freeze-dried weight after sample collection. Particulate gravimetric Hg concentrations (the concentration of Hg on particles, in nanograms per gram [ng/g]) were determined by dividing volumetric Hg concentrations (ng/L) by SPM. Mercury concentrations in sediments, soils, and biological material were determined at the USGS Contaminant Ecology Research Lab (Corvallis, Oregon). Sediments and soils were analyzed for THg following standard combustion protocols.54 Biological materials (periphyton, leaf litter, and invertebrates) were prepared for MeHg analysis by weak acid digestion (4 M nitric acid) and analyzed by aqueous phase ethylation, gas chromatography separation, and cold vapor atomic fluorescence spectroscopy.55,58 All quality control and assurance information for sample analysis can be found in the SI. All raw data pertaining to this work can be accessed online.59

Statistical Analysis

All statistical analyses were performed using JMP (v16.0.0) and R (v4.2.3) software.60,61 Unless otherwise noted, Hg concentrations were natural-log transformed to meet the assumptions of normality for modeling and then back-transformed for visualization using the delta method.62 Unless specified, all analyses employed linear mixed-effects models. Analyses used a paired watershed approach, with reference and burned watersheds paired at the fire level. Specifically, for each fire, we sampled burned watersheds within the fire perimeter and nearby unburned reference watersheds outside the fire perimeter, taking care to select reference watersheds with similar forest, hydrological, and physical characteristics as the burned areas. This approach, coupled with the use of fire as a random effect in our statistical analyses, effectively accounted for the shared variation in the local conditions of watersheds associated with each wildfire. Statistical significance was assessed using an α value of 0.05. However, because this binary cutoff can lead to the dismissal of relationships with real biological or geochemical significance,63−68 relationships with p-values > 0.05 (specifically those between 0.05 and 0.10) were considered potentially informative and are discussed, particularly when the plotted data show a clear relationship but with high variance due to the spatial and environmental variability across watersheds. Concentrations below the laboratory reporting limit (42% of f.MeHg and 59% of p.MeHg values) were used as reported (i.e., values that were measured and reported by the laboratory but which were below the laboratory’s long-term reporting limit) in statistical analyses.69

We employed a multistaged statistical approach to assess the effects of wildfires on various aspects of Hg cycling in forested catchments. First, we tested whether concentrations of aqueous THg and MeHg (filter-passing, particulate volumetric, and particulate gravimetric), sediment THg, DOC, and SPM differed between burned and associated unburned reference watersheds and whether these effects differed between two of the geographic regions we sampled (western Cascades and Interior; the eastern Cascades region only included two wildfires and thus was not included in this comparison). For each dependent variable, we used a model with burn status (i.e., burned versus reference) and region as fixed-effects, a burn status X region interaction, DOC as a covariate, a burn status X DOC interaction, and a fire event as a random effect. The inclusion of fire events as a random effect helped account for variation among localities that was not associated with wildfire effects, such that the results reflect the normalized differences between burned and the associated reference watersheds across all fires sampled. Initial models indicated that wildfire effects were largely consistent among regions (p > 0.05), so the region main-effect and the burn status X region interaction were subsequently removed from models.

Our second analysis examined the relationships between the above aqueous and sediment parameters and CBI burn severity within the burned watersheds. This was accomplished using models including the percent of the watershed with moderate—high burn severity as a covariate and fire event as a random effect. For this analysis, we also tested a more complex burn severity metric which integrated the extent and severity (including areas with unchanged or low burn severity) of fire across each watershed, but the two metrics were highly correlated (R-squared = 0.95) and yielded equivalent results. Therefore, only the former, simpler approach was used. Results are presented as partial residuals that have been adjusted using the median value of each parameter from burned watersheds and then back-transformed to simplify interpretation.

Our third analysis examined the linkages between aqueous THg concentrations in streams and THg concentrations in the three soil horizons sampled throughout each watershed. We also contrasted these relationships between burned and unburned reference watersheds. This analysis used models with burn status as a fixed-effect, the area-weighted geometric mean THg concentration in each soil horizon as a covariate, a burn status X soil THg interaction, and a fire event as a random effect. For the area-weighted geometric mean THg in soils, we calculated the geometric mean THg concentration in each horizon and burn severity combination within each watershed and then used the areal extent of each burn severity class to calculate the area-weighted mean soil THg concentrations for each horizon across the watershed. Results are presented as partial residuals that have been adjusted using the median value of each parameter from burned watersheds and then back-transformed to simplify interpretation.

Our fourth analysis assessed differences in MeHg concentrations of basal resources (in-stream terrestrial leaf litter and periphyton) and five invertebrate guilds between burned or unburned reference watersheds using linear mixed-effects models. The basal resources model included burn status and resource type as fixed-effects, a burn status X resource type interaction, DOC, a burn status X DOC interaction, and a random effect of the fire event. The invertebrate model followed a similar structure with burn status and guild as fixed-effects, a burn status X guild interaction, DOC, a burn status X DOC interaction, and fire event and invertebrate taxa (to account for differences in the taxa comprising each guild among streams) as random effects. For each resource type and invertebrate guild, the significance of differences between burned and reference watersheds were determined using pairwise contrasts to avoid inflation of familywise error rates.

Our fifth analysis examined the relationships between watershed CBI burn severity and invertebrate MeHg concentrations. This utilized guild-specific linear mixed-effect models with the same structure outlined in our second-tier analysis.

Finally, we assessed whether burn status affected the relationships between Hg concentrations in water (THg and MeHg) and invertebrate guilds (MeHg).70 These guild-specific models included burn status as a fixed-effect, the watershed least-squares mean MeHg concentration of the guild as a covariate, a burn status X invertebrate MeHg concentration interaction, and the fire event as a random effect.

Results

Abiotic Concentrations

The effect of wildfires on concentrations of stream DOC and filter-passing Hg species varied. Across all study watersheds, DOC concentrations were 19% lower in burned watersheds compared to associated reference watersheds (p = 0.10, Figure 2A). Although DOC concentrations tended to decline with increasing watershed burn severity, this relationship was weak and not significant (p = 0.61; Figure 2B). DOC concentrations were significantly correlated with most abiotic stream Hg parameters measured (p < 0.001–0.034; Table S3), with the exception of THg concentrations on suspended particles (gravimetric p.THg) and in sediment (p = 0.82 and p = 0.53, respectively; Table S3). The relationships between DOC and stream Hg concentrations were generally the same in burned and reference watersheds (burn status X DOC interaction p = 0.12–0.95; Table S3), except that the slope between DOC and filter-passing THg concentrations was higher in reference watersheds than in burned watersheds (p = 0.022; Table S3). Given the apparent role of DOC in mediating wildfire effects on stream Hg concentrations, subsequent comparisons of Hg concentrations between burned and reference watersheds account for differences in DOC concentrations among watersheds.

Figure 2.

Figure 2

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Least-squares mean (±SE) dissolved organic carbon (DOC; A), filter-passing total mercury (THg; C), and filter-passing methylmercury (MeHg; E) concentrations in streamwater collected from 21 reference and 36 burned watersheds in the northwestern U.S.; and the relationships between each constituent and the percent of the watershed classified as either moderate or high burn severity using the Composite Burn Index in the 36 burned watersheds (B, D, F). Points in B, D, and F are adjusted partial residuals standardized to the least-squares mean concentrations in burned catchments. The horizontal green lines and shaded bands in parts B, D, and F represent the least-squares mean ± SE concentrations in the 21 reference watersheds. Least-squares means account for variation among individual fires and, in panels C and E, differences in DOC concentrations between burned and reference watersheds. p-values 0.05–0. 099 are shown in bold black [mg, milligrams; ng, nanograms; L, liter].

Concentrations of f.THg were similar in burned and reference watersheds when accounting for differences in DOC (p = 0.23; Figure 2C), and we observed no relationship between the percentage of the watershed with moderate to high burn severity and f.THg concentrations (Figure 2D). In contrast, concentrations of f.MeHg were slightly higher in burned watersheds (51%, p = 0.060; Figure 2E).

Wildfire effects on suspended particulates and particle-associated Hg fractions were more pronounced than the effects on filter-passing fractions. Burned watersheds had higher concentrations of SPM (99% greater, p = 0.067; Figure 3A), volumetric p.THg (89%, p < 0.001; Figure 3C), and volumetric p.MeHg (178%, p < 0.0001; Figure 3E) compared to reference watersheds. Furthermore, watersheds experiencing more severe wildfires had higher concentrations of SPM (p = 0.007; Figure 3B), volumetric p.THg (p = 0.028; Figure 3D), and volumetric p.MeHg (p = 0.020; Figure 3F). The concentrations of p.THg on suspended particles (gravimetric concentrations) were similar in burned and reference watersheds (p = 0.76; Figure 3G), but decreased with increasing percentage of moderate–high burn severity (p = 0.026; Figure 3H). In contrast, burned watersheds had 40% greater gravimetric p.MeHg concentrations (i.e., enrichment of MeHg on particles; p = 0.027; Figure 3I). The percentage of p.THg as p.MeHg (%p.MeHg) was also 38% greater in burned watersheds (p = 0.47). Gravimetric p.MeHg concentrations did not increase with an increasing percentage of moderate-high burn severity in the watershed (Figure 3J). In streambed sediment, THg concentrations were nearly the same in burned and reference watersheds (p = 0.82). As noted in the Methods, wildfire effects were largely consistent among regions (p > 0.05).

Figure 3.

Figure 3

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Least-squares mean (±SE) suspended particulate material (SPM; A) and particulate total and methylmercury (THg and MeHg, in ng/L and ng/g; C, E, G, I) concentrations in streamwater collected from 21 reference and 36 burned watersheds in the northwestern U.S.; and the relationships between each constituent and the percent of the watershed classified as either moderate or high burn severity using the Composite Burn Index in the 36 burned watersheds (B, D, F, H, J). Points are adjusted partial residuals standardized to the least-squares mean concentrations in burned catchments. The horizontal green lines and shaded bands in parts B–J represent the least-squares mean ± SE concentrations in the 21 reference watersheds. Least-squares means account for variation among individual fires and, in panels C, E, G, and I, differences in DOC concentrations between burned and reference watersheds. p-values <0.05 are shown in bold red; p-values 0.05–0. 099 are shown in bold black [mg, milligrams; ng, nanograms; g, grams; L, liter].

Relationships between Watershed Soil and Stream THg

Evaluation of the relationships between concentrations of in-stream THg and watershed soil THg showed that in reference watersheds, stream f.THg was positively related to soil THg concentrations in all three soil horizons (green regression lines in Figure 4A–C, p ≤ 0.017; Table S4). However, interaction effects suggested these relationships differed between reference and burned watersheds (Figure 4A–C; interaction terms = 0.004–0.088), with no relationship observed in burned watersheds (Figure 4A–C; regression p ≥ 0.25, Table S4). Burned and reference watersheds also differed in their relationships between stream volumetric p.THg and soil THg (p of interaction terms 0.016–0.065; Figure 4D–F;), but the individual relationships were weak (p = 0.042–0.47; Table S4). In contrast, we found consistent positive relationships between soil THg and stream gravimetric p.THg (p < 0.001–0.021), and between soil THg and stream sediment THg (p < 0.001–0.22), all of which were unaffected by burn status (p of interaction terms ≥0.19; Figure 4G–L; Table S4).

Figure 4.

Figure 4

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Relationships between area-weighted geometric mean THg concentrations in watershed soil layers (duff, organic soils, and mineral soils) and THg concentrations in streamwater and sediment in 21 reference (green points and lines) and 36 burned (purple points and lines) watersheds in the northwestern U.S. Area-weighted means account for differences in soil THg concentrations among Composite Burn Index burn severity classes and the area of each watershed comprised of each burn severity class. Regression lines shown only for p-values < 0.05. p-values <0.05 are shown in bold red; p-values 0.05–0. 099 are shown in bold black [Covar., covariance; Interact., Interaction between burned and reference treatments; g, grams; ng, nanograms; L, liter].

Biological Concentrations

As was observed with most abiotic stream Hg parameters, DOC concentrations were significantly correlated with MeHg in most biological matrices (p ≤ 0.004), with the exceptions of MeHg in periphyton (p = 0.10), filterers (p = 0.11), and in-stream leaf litter (p = 0.37; Table S3). The relationships between DOC and biological MeHg concentrations were generally the same in burned and reference watersheds (burn status X DOC interaction p = 0.10–0.86; Table S3), except among grazers and collectors (burn status X DOC interaction p = 0.010–0.013). Therefore, as was done with abiotic Hg parameters, comparisons of biological MeHg concentrations between burned and reference watersheds account for differences in DOC concentrations among watersheds.

Both watershed-derived (i.e., allochthonous) and in-stream produced (i.e., autochthonous) basal resources (in-stream terrestrial leaf litter and periphyton, respectively) had similar MeHg concentrations in burned and reference watersheds (Figure 5A,B). There was also little difference in MeHg concentrations of shredders or predators in burned versus reference watersheds when accounting for differences in DOC among watersheds (p ≥ 0.50; Figure 5C). However, MeHg concentrations were elevated in grazers (33%, p = 0.096), collectors (251%, p = 0.001), and filterers (48%; p = 0.0097) in burned watersheds compared to reference watersheds (Figure 5C). Relationships between MeHg concentrations and burn severity were also assessed but were not significant (p > 0.05) for any of the basal resources or invertebrate guilds (Table S5).

Figure 5.

Figure 5

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Least-squares mean (±SE) MeHg concentrations in (A) in-stream terrestrial leaf litter, (B) periphyton, and (C) aquatic invertebrate guilds collected from 21 reference and 36 burned watersheds in the northwestern U.S. Least-squares means account for variation among individual fires and differences in DOC concentrations among watersheds. p-values are for pairwise contrasts between reference and burned treatments for each group. p-values < 0.05 are shown in bold red; p-values 0.05–0. 099 are shown in bold black.

Lastly, our assessment of whether burn status affected the relationships between Hg concentrations in water and invertebrates showed that with few exceptions (Figure S2C,O), the slopes of these relationships were not affected by watershed burn status (i.e., p of interaction terms > 0.05). Aqueous MeHg concentrations (filter-passing, particulate volumetric, and particulate gravimetric) strongly correlated with invertebrate MeHg concentrations across all guilds (Figure S2; Table S6; p of covariate term ≤ 0.005), except particulate gravimetric MeHg and MeHg in collectors, which were weakly correlated (p ≥ 0.14; Figure S2I). Among the aqueous THg fractions, we observed significant relationships between filter-passing THg and invertebrate MeHg (Figure S3; p of covariate term ≤ 0.01), which were unaffected by watershed burn status. However, relationships between particulate THg fractions (volumetric and gravimetric) and invertebrate MeHg fractions were generally poor and unaffected by watershed burn status (Figure S3; Table S7). Similarly, relationships between sediment THg and invertebrate MeHg were poor and unaffected by the watershed burn status (Figure S3; Table S7).

Discussion

Wildfire Effects on Mercury Transport

Concentrations of f.THg one year post fire were similar (p = 0.23) in burned and reference watersheds when accounting for DOC, which was lower in burned watersheds than reference watersheds (p = 0.10). These results partially corroborate those from Jensen et al.35 who found no differences in either DOC or f.THg concentrations between a burned and reference watershed in the southeastern U.S. However, when DOC was not accounted for, f.THg concentrations in the current study were slightly lower in burned watersheds than in reference watersheds (25%; p = 0.059), suggesting that the effects of fire on f.THg were linked to changes in carbon flux from the watershed. Soil organic carbon quality and concentration strongly influence the mobilization of f.THg from forested catchments71−74 and are affected by fires in complex ways.75 For example, pyromorphic humus or black carbon—recalcitrant types of organic matter formed during fires—can sequester f.THg through complexation, thereby reducing f.THg mobilization.22,29,40,76 Similarly, the effect of fires on stream DOC is complex and often dependent on local catchment and climatic conditions, with studies reporting increased, decreased, or unchanged DOC concentrations following wildfires, particularly among smaller headwater streams.33,77−80 This variability in the observed effects of wildfire on DOC likely also reflects differences in the timing of sampling among studies and the strong temporal patterns in DOC mobilization following the wildfire. High temporal resolution studies have shown that DOC concentrations in wildfire-affected streams typically increase in the short term (i.e., months post fire), but often decline over the medium term, with the time needed to see these changes influenced by fire severity, watershed characteristics, and precipitation events.80−82 Because DOC plays a critical role in regulating Hg transport from watersheds to headwater streams,71−74 the temporal variability in DOC responses to wildfire are likely to have implications for Hg cycling that are not fully represented by short-term studies.

We observed positive relationships between watershed soil THg and stream f.THg in reference watersheds, but these relationships did not hold in burned watersheds (Figure 4A–C), suggesting that wildfires may decouple the linkages often observed between the chemical characteristics of a watershed and its outlet stream.44,83,84 This decoupling may be associated with altered watershed or in-channel hydrology,14,30 changes in organic matter cycling,76 reduced soil Hg concentrations,25−28 and (or) other processes, and would require further investigation to decipher.

Wildfires also altered the transport of particles and particle-associated Hg and MeHg in the current study, despite few changes in the relationships between watershed soil THg concentrations and stream p.THg or p.MeHg concentrations. Concentrations of stream SPM and volumetric p.THg and p.MeHg were 89–178% greater in burned compared to reference watersheds (Figure 3A,C,E), likely associated with increased erosion from vegetation loss, hydrophobic soil development, reduced infiltration, and rill development.14,15,33,85,86 Although our results suggested that the relationships between watershed soil THg and stream volumetric p.THg may have differed between burned and reference watersheds, these relationships were very weak regardless of burn status (Figure 4D–F). These weak relationships, coupled with higher SPM concentrations in burned watersheds (Figure 3A) and the fact that both burned and reference watersheds had similar positive relationships among watershed soil THg, gravimetric p.THg, and sediment THg (Figure 4G–L), further support the conclusion that differences in particulate THg cycling in the wildfire-affected streams resulted from altered particle transport and delivery rather than enrichment of THg on particles.

The observed increased supply of particulate Hg from burned watersheds may result in increased methylation in downstream environments, especially if it is accompanied by increases in nutrients and organic carbon. Nutrients and organic carbon can stimulate microbial activity and facilitate Hg methylation,87 and their concentrations in streams commonly increase following wildfires.16,33,88 For example, in a reservoir downstream from a wildfire in New Mexico (U.S.), Caldwell et al.36 observed large increases in bed-sediment concentrations of THg (6-fold) and total organic carbon (4.4-fold), but a disproportionately larger increase in sediment MeHg (30-fold). Prescribed burns have been shown to reduce wildfire burn severity,89 and here we show that lower burn severity resulted in lower concentrations of volumetric p.THg and p.MeHg (Figure 3). Minimizing post-fire particulate mobilization may therefore be effective in reducing effects on downstream environments. Although post-wildfire management of particle erosion and transport is challenging, pre-wildfire prescribed burns may help limit post-wildfire particulate Hg mobilization and downstream effects on Hg methylation.

Evidence for Increased Hg Methylation in Burned Watersheds

In addition to potentially increasing Hg methylation in downstream environments, the following lines of evidence suggest that wildfires may have promoted MeHg production in the studied headwater streams or adjacent terrestrial environments.

  • 1.

    After accounting for differences in DOC, f.THg concentrations were similar in burned and reference watersheds, but f.MeHg concentrations were 51% higher (p = 0.060) in burned watersheds compared to reference watersheds (Figure 2C,E), resulting in MeHg comprising a larger proportion (52% higher) of the Hg in filter-passing water from burned sites compared to reference sites. Furthermore, we observed a weak positive relationship between concentrations of f.MeHg and burn severity (not statistically significant due to high variability, p = 0.21) but not between f.THg and burn severity (p = 0.86; Figure 2F,D).

  • 2.

    The ratio of f.MeHg to DOC was approximately 30% higher in burned watersheds relative to unburned reference watersheds. This suggests the observed increase in f.MeHg is due to changes in MeHg pools (terrestrial or aquatic) rather than simply changes in the mobilization of MeHg associated with differences in carbon transport.90,91

  • 3.

    The elevated gravimetric concentration (i.e., ng/g) of p.MeHg (p = 0.027), but not p.THg (p = 0.76; Figure 3G,I), in burned watersheds indicates MeHg enrichment on the suspended particles from burned watersheds (40% greater than reference watersheds).

Although some of these relationships were not statistically significant at α = 0.05, they are likely environmentally significant, and their combined weight of evidence is compelling. The most parsimonious explanation for these multiple lines of evidence is increased MeHg production in burned watersheds compared to reference watersheds. The potential for wildfires to increase Hg methylation in headwater streams or watershed soils has not been previously documented and has implications for our understanding of wildfire impacts to Hg cycling; however, the mechanism and specific location of enhanced methylation (i.e., soils, stream sediments, or streamwater) is unclear without direct measurements of microbial MeHg production. These findings are supported by a recent laboratory study which reported that wildfire ash stimulated MeHg production in sediments by leaching labile organic matter and mobilizing inorganic Hg.29 Considering that wildfires are expected to increase in frequency and severity with climate change,92−94 these results may have important future implications for MeHg bioaccumulation in headwater streams as well as downstream environments. A study of 38 Canadian lakes with recently burned, clear-cut, or undisturbed catchments reported that fish Hg concentrations were highest in two of the burned catchments.95 Additionally, they found the burned lakes had more variability in fish Hg concentrations than the cut and undisturbed lakes, highlighting both the potential for wildfires to increase downstream Hg bioaccumulation and the potential importance of individual habitat use or foraging behavior in influencing wildfire effects on Hg bioaccumulation. This variability may also help explain why other studies of wildfire effects on downstream MeHg bioaccumulation have reported increased bioaccumulation in some species and locations but not others.37,41−43,96,97

Wildfire Effects on Hg in Biota

Wildfire effects on biological MeHg concentrations were mixed but largely cascaded from effects observed in abiotic matrices. Both watershed-derived and in-stream produced basal resources (in-stream terrestrial leaf litter and periphyton, respectively) had statistically similar MeHg concentrations in burned and reference watersheds. However, whereas stream leaf-litter MeHg concentrations were essentially invariable relative to burn status (Figure 5A), the least-squares mean periphyton concentration for burned watersheds was 22% higher than the mean from the associated reference watersheds (Figure 5B). A similar pattern was observed between the respective primary consumers of these basal resources, with grazer invertebrates having a 33% higher mean MeHg concentration from burned watersheds than from reference watersheds (p = 0.096) while shredder concentrations were unaffected by watershed burn status (p = 0.743; Figure 5C). The lack of a wildfire effect on MeHg concentrations in stream leaf litter and associated shredders is unsurprising considering wildfire primarily influences litter quantity with little change in quality or composition,47,98,99 and MeHg concentrations in terrestrial leaf litter are typically low.89,90 In contrast, periphyton are known to accumulate aqueous MeHg, trap settling particles and particle-bound Hg from the water column,91,92 and be locations of Hg methylation.100−102 These processes all contribute to the higher observed MeHg concentrations in periphyton compared to leaf litter.103 Further, increased light availability and nutrient concentrations following wildfire are known to alter periphyton distribution, composition, and productivity, facilitating an increased importance of periphyton in fire-affected stream food webs.47,104,105 For these reasons, wildfire and other watershed disturbances appear to have a more pronounced effect on periphyton and reliant consumer MeHg concentrations than is observed for taxa reliant on terrestrial litter inputs.97,106−108

Filterers and collectors had greater MeHg concentrations in burned watersheds compared to reference watersheds (48 and 251% higher, respectively; p ≤ 0.0097; Figure 5C). Both of these guilds primarily forage on particulate detritus, so their elevated MeHg concentrations likely reflect the higher concentrations of volumetric and gravimetric p.MeHg in burned watersheds (Figure 2). However, MeHg concentrations in filterers and collectors did not increase with increasing moderate to high burn severity (p = 0.69 and 0.48, respectively; not plotted), indicating that even low severity burns may be enough to affect MeHg concentrations in filterers and collectors.

Results from this study are based on medium-term watershed Hg conditions post wildfires and during summer and autumn baseflow conditions and are not intended to comprehensively assess all effects of wildfire on Hg cycling in these watersheds. In particular, Hg concentrations were likely different during runoff events, especially during “first flush” events in the weeks and months following the fires.23,37,85,109 While we recognize the importance of these first flush events for Hg mobilization, the focus of the current study was on baseflow conditions and medium-term effects, which we identified as an existing knowledge gap relevant to biological exposure in the years following the fire. Cumulative post-fire rainfall (52–290 cm)110 may have affected the observed stream Hg concentrations, but parsing this effect would also require Hg deposition rates across the study area (e.g., from the National Atmospheric Deposition Program’s Mercury Deposition Network), which were not available for the period of study. Similarly, the effects of wildfires on Hg cycling and bioaccumulation in these watersheds at greater time scales (5–10+ years) are not clear. Wildfire effects on streams and watersheds may persist for years or even decades,39,48,107 and change over time as riparian and upland vegetation and soils recover.111,112 Lastly, our analysis considered the burn severities of each watershed but did not evaluate the proximity of the burn to the surface or subsurface flow paths. Distance-weighting burn areas relative to the stream corridor113 may provide future studies with additional insights.

In this study, we demonstrated that wildfires can impact Hg mobility and cycling in headwater streams and directly influence some biological Hg concentrations post burn. Volumetric p.THg and p.MeHg concentrations were greater in burned watersheds, likely due to increased erosion. Filter-passing MeHg concentrations were higher in burned watersheds, and suspended particles in burned watersheds were enriched in MeHg but not THg, indicating the potential for wildfires to change the Hg methylation potential and availability in headwater streams, with potential implications for MeHg transport to downstream environments. Lastly, we demonstrate that wildfire effects on biota were largely reflective of effects on abiotic matrices, with greater particulate Hg concentrations in burned watersheds resulting in greater MeHg concentrations in filterers and collectors, the invertebrate guilds most reliant on particulate detritus. With few exceptions, the relationships between aqueous Hg (THg, MeHg) and invertebrate MeHg were not affected by burn status (Figures S2 and S3), indicating that although wildfires may alter the availability of Hg for uptake into stream food webs, wildfires do not appear to fundamentally alter the processes linking Hg availability and bioaccumulation. If this is indeed the case, such conservation of water-food web Hg relationships following wildfire would allow the leveraging of a vast body of work on the drivers of Hg cycling in unburned ecosystems to understand and predict potential wildfire effects over a range of watershed and fire conditions. However, it is notable that substantial variation in the relationships between abiotic and biotic Hg has been observed among regional assessments and individual unburned watersheds.114−116 Therefore, any application of these relationships to understand wildfire effects would benefit from additional studies characterizing such variation.

Acknowledgments

The authors gratefully acknowledge S.Ducar, E.Grey, T.Glidden, B.Eachus, T.Elliott, and D.Dubose for sample collection, and the staff at the USGS Mercury Research Lab and Contaminant Ecology Research Lab for sample analysis. Funding was provided by the USGS Northwest Pacific Islands Region and the USGS Environmental Health Toxics Substances Hydrology and Contaminant Biology Programs. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c00789.

  • Additional information on geospatial methods; sample collection and analysis methods; QAQC results; and relationships between aqueous and invertebrate mercury (PDF)

  • Sampling location information; relative percent differences in duplicate samples; statistical results of models testing the effects of burn status and dissolved organic carbon on total mercury and methylmercury concentrations; regression statistics between mercury in soil and mercury in stream water and sediment in reference and burned watersheds; regression statistics between watershed burn severity and methylmercury in basal resources and invertebrate guilds; regression statistics between methylmercury in stream water and invertebrate guilds; regression statistics between total mercury in stream water and methylmercury in invertebrate guilds (XLSX)

Author Contributions

Conceptualization: C.E.S., J.J.W., A.K.B.; Methodology: J.J.W., C.E.S., A.K.B.; Formal analysis: J.J.W., A.K.B.; Investigation: A.K.B., J.J.W., B.J., S.E.J.; Resources: C.E.S., S.E.J.; Writing original draft: A.K.B., J.J.W., S.E.J.; Reviewand editing: J.J.W., C.E.S., S.E.J., B.J.; Visualization: A.K.B., J.J.W., B.J.; Project administration: C.E.S., A.K.B.; Funding acquisition: C.E.S.

The authors declare no competing financial interest.

Notes

For consideration in ES&T Special Issue: Wildland Fires: Emissions, Chemistry, Contamination, Climate, and Human Health

Special Issue

Published as part of Environmental Science & Technologyvirtual special issue “Wildland Fires: Emissions, Chemistry, Contamination, Climate, and Human Health.”

Supplementary Material

es4c00789_si_001.pdf (766.6KB, pdf)
es4c00789_si_002.xlsx (44.5KB, xlsx)

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