Wildfire plays a pivotal role in controlling the dynamics of organic matter (OM) and inorganic solutes in both terrestrial and aquatic ecosystems. Fire can alter hydrologic flow paths in soil and increases susceptibility of soils to erosion (Spigel and Robichaud 2007, Florsheim et al. 2017). These changes increase the rate at which sediments, dissolved and particulate carbon (C), and nutrients are transported from post-fire landscapes and delivered to fluvial networks (Moody et al. 2013, Dahm et al. 2015, Mast et al. 2016, Abney et al. 2017, Esposito et al. 2017). For example, post-fire erosion mobilized 19.8 to 33.1 tons ha−1 of soil from a mountainous fire-impacted catchment in Italy (Esposito et al. 2017), and total dissolved solids and nitrate (NO3) were reported to increase 20 and 52%, respectively, in a Colorado Front Range river two years following fire (Mast et al. 2016). However, there are limited data available on how fire characteristics, including factors such as time since fire and fire severity (Keeley 2009), affect streamwater chemistry.

Fires can alter the cycling, concentration, and chemical composition of OM in soil (Santín et al. 2015, Araya et al. 2016, Santos et al. 2016, Araya et al. 2017) and aquatic ecosystems (Jaffé et al. 2013, Masiello and Louchouarn 2013). The thermal degradation of soil organic C and biomass produces a heterogeneous mixture of organic residues that are collectively referred to as pyrogenic (fire-derived) C (PyC). In post-fire landscapes, large quantities of PyC (as determined by an increase in degree of aromaticity) can be mobilized and transported to fluvial systems as particulate and dissolved C (particle size <0.7 μm; Güereña et al. 2015, Myers-Pigg et al. 2015, Wagner et al. 2015, Cotrufo et al. 2016, Abney et al. 2017, Abney and Berhe 2018). Global estimates indicate that at least 10% of the dissolved organic carbon (DOC) pool transported in rivers is in the form of PyC (Dittmar et al. 2012, Jaffé et al. 2013); however, the response of DOC to fire occurrence is highly variable with concentrations increasing (Ramchunder et al. 2013), decreasing (Betts and Jones 2009, Parham et al. 2013, Diemer et al. 2015), and showing no significant response (Mast and Clow 2008, Mast et al. 2016).

Spatial and temporal variability in the response of dissolved organic matter (DOM) indicates that the export of PyC to streams and rivers is likely driven by multiple factors including, for example, fuel accumulation, fire severity, hydrologic flowpaths, soil type, geomorphology of the landscape (i.e., slope steepness and length, curvature, and aspect), and time since fire (Parham et al. 2013, Larouche et al. 2015, Abney et al. 2017). In contrast, elevated solute concentrations in streams are often reported in post-fire landscapes (Chorover et al. 1994, Williams and Melack 1997; Smith et al. 2011, Parham et al. 2013). For example, nitrate anion (NO3) and cation (calcium, Ca2+; magnesium, Mg2+; and potassium, K+) concentrations often remain elevated for >2 yr following fire (Chorover et al. 1994, Mast and Clow 2008, Rhoades et al. 2011). However, less is known about how the concentrations of major solutes in streams respond to different levels of disturbances related to fire severity (i.e., low- versus high-severity fire), and site-level characteristics such as catchment area, vegetation cover, and stream geomorphology. This is especially critical in the western US. where the proportion of large patches affected by high-severity fire is increasing (Miller et al. 2009, Miller and Safford 2012, Reilly et al. 2017). As a result, the ability to produce a robust, predictive framework for the responses of streamwater chemistry to wildfire remains elusive.

The objective of this study was to examine the potential influences of fire severity and time since last fire on streamwater chemistry by examining solute concentrations and DOM composition. We hypothesized that nutrient, cation, and anion concentrations would be positively correlated with high-severity fire (>1 yr following wildfire), whereas DOC concentration would be negatively correlated with high-severity fires. We also expected to see an increase in aromaticity and a decrease in molecular weight (MW) of DOM corresponding with high-severity fire, as an increase in fire severity would lead to higher proportions of PyC (Knicker 2007) and low molecular weight DOM (Norwood et al. 2013, Santos et al. 2016) transported from soils to streams. Additionally, we hypothesized that streamwater solute concentrations would decrease with an increase in time since fire due to ecosystem recovery; whereas aromaticity would increase with time since fire as soil PyC would become progressively more oxidized and hydrophilic, therefore highly mobile, over time (Knicker 2007, Abiven et al. 2011, Näthe et al. 2017). To test these hypotheses, we measured nutrient, cation and anion, and DOC concentrations, MW of DOM, as well as the distribution of major chemical functional groups in streamwater DOM across sites that differed in time since fire (from 1 to 13 yr since last burn) and experienced either low- or high-severity wildfires in the Sierra Nevada of California, USA.

Materials and methods


Streams selected for this study were located in Yosemite National Park, in the Sierra Nevada, California, USA, and were tributaries of the Tuolumne and Merced rivers. This study consisted of six low-severity and six high-severity burned sites or reaches (each within its own catchment or sub-catchment), with burn severity assessed at the reach scale (Jackson and Sullivan 2015), as shown in Table 1 and Fig. 1. The dominant upland vegetation types were: California Red Fir Belt in Tamarack, Frog, Cascade, Crane, Chilnualna, and Coyote creeks; Mixed Conifer in Grouse, Middle Tuolumne, and South Tuolumne creeks; Subalpine Conifer in Meadow, Camp, Buena Vista, and Mono creeks (Keeler-Wolf et al. 2012). Chaparral was also commonly interspersed within coniferous vegetation zones (Keeler-Wolf et al. 2012). Ponderosa pine (Pinus ponderosa Douglas ex C. Lawson), Jeffrey pine (Pinus jeffreyi Balf.), sugar pine (Pinus lambertiana Douglas), red fir (Abies magnifica A. Murray bis), lodgepole pine (Pinus contorta Douglas ex Loudon var. murrayana [Balf.] Englem.), incense-cedar (Libocedrus decurrens [Torr.] Florin), chinquapin (Castanopsis sempervirens [Kellogg] Dudley), and buck brush (Ceanothus L. spp.) were among the dominant upland species observed in the riparian zone (Sawyer et al. 2009, Keeler-Wolf et al. 2012). Riparian species included quaking aspen (Populus tremuloides Michx.), mountain azalea (Rhododendron occidentale Torr. & A. Gray), red-osier dogwood (Cornus sericea L. ssp. occidentalis [Torr. & A. Gray] Fosberg), and willow (Salix L. spp.) (Sawyer et al. 2009).

Table 1 Fire and site-level characteristics for study reaches in Yosemite National Park, California, USA (modified from Jackson and Sullivan 2015). Channel-reach morphology was classified following Montgomery and Buffington (1997). Stream order was determined based on Strahler (1957). Aspect was used as a coarse proxy for heat load (McCune and Keon 2002). Streamwater was sampled from the sites between 1 and 13 years after the last fire
Fig. 1
figure 1

Sampling locations in sites affected by low-severity (green) and high-severity (orange) fire in Yosemite National Park in the Sierra Nevada, California, USA. Streamwater was sampled from the sites between 1 and 13 years after the last fire

Elevation of the study sections varied between 1574 and 2154 m a.s.l., with time since fire ranging from 1 to 13 yr (see Table 1 for other site-level characteristics); all fires were naturally occurring wildfires (not prescribed). Our main goal was to examine the effect of fire severity (low versus high), but we also sampled an unburned reference stream (Chilnualna Creek), which served as a counterpoint to our burned streams, and helped us to identify changes in streamwater chemistry attributable to fire. Middle Tuolumne and South Tuolumne study reaches were within the perimeter of the Rim Fire, a high-severity fire that started in August 2013, burning an area of approximately 1041 km2 (Lydersen et al. 2014). The Rim Fire was considered the largest wildfire in recorded Sierra Nevada history to date.

Fire severity at each study reach was determined based on the condition of the conifer canopy within approximately 50 m of the stream (i.e., those trees that could influence light penetration into the stream). Low-severity reaches were characterized as having an intact conifer canopy, despite the riparian understory having burned. High-severity reaches were characterized as having its conifer canopy removed by wildfire over at least 75% of the reach (Jackson and Sullivan 2009, Malison and Baxter 2010).

Sample collection and solute analysis

We collected streamwater samples every two weeks from June through October 2014 (reference, n = 8; low-severity, n = 48; high-severity, n = 46). All sampling occurred between 10 and 14 months after the Rim Fire started. Samples were collected at baseflow, during daylight hours, and from the middle of the channel (i.e., laterally) and stream reach (i.e., longitudinally). Samples were filtered through Whatman GF/F filters (GE Healthcare Bio-Sciences, Pittsburgh, Pennsylvania, USA) and into acid-washed 125 ml HDPE bottles, and were immediately placed on ice, and frozen upon return to the laboratory. Samples were sent overnight to the University of New Hampshire’s Water Quality Analysis lab.

We analyzed DOC and total dissolved nitrogen (TDN) using high temperature catalytic oxidation on a Shimadzu TOC-VSCH with TNM-1 nitrogen unit (Shimadzu, Marlboro, Massachusetts, USA). Cations and anions were measured using ion chromatography with a Dionex ICS-1000 (ICS 1000; Dionex, Sunnyvale, California, USA), and ammonium cations (NH4+) with a SmartChem 200 discrete automated colorimetric analyzer (Westco, Brookfield, Connecticut, USA) using the alkaline phenate standard method (EPA method 350.1; US EPA 1993). Dissolved organic nitrogen (DON) was calculated as the difference between TDN and dissolved inorganic nitrogen (NO3 + NH4+). Values below instrument specific minimum detection limit (MDL) were replaced with half the MDL.

Specific ultraviolet-visible (UV) absorbance

Specific UV absorbance at 254 nm (SUVA254) was used as a proxy for aromaticity in DOC (Weishaar et al. 2003) on samples collected from August through October (reference, n = 4; low-severity, n = 29; high-severity, n = 28). We measured absorbance between 200 and 400 nm using a UV-VIS spectrophotometer (Evolution 300; Thermo Scientific, Waltham, Massachusetts, USA). Samples were analyzed inside a quartz cell with 1.0 cm path length, and we calculated SUVA254 (mg C L−1 m−1) by dividing the specific absorbance coefficient at 254 nm by the path length (m) and DOC concentration (mg C L−1), as described by Weishaar et al. (2003). We used ultrapure water as the blank. As high-molecular-weight molecules are expected to absorb light more strongly at longer wavelengths than at shorter wavelengths, we also used the ratio of absorption coefficients at 250 nm to 365 nm (E2:E3) to infer molecular size of organic compounds in DOM (Helms et al. 2008). The ratio E2:E3 is inversely correlated with the molecular size of DOM compounds.

Solution-state 1H-NMR spectroscopy

The composition of streamwater DOM was only determined on filtered samples collected from August through October (reference, n = 4; low-severity, n = 29; high-severity, n = 28) using liquid-state 1-D 1H-NMR spectroscopy (described below), which provides information on the molecular composition of compounds that are bound to hydrogen in solutes. To remove hydrogen in water molecules, before analyses, streamwater sub-samples were completely freeze-dried (Labconco Freezone 2.5; Kansas City, Missouri, USA). The solid residues were then transferred to a 5 mm NMR tube and redissolved in deuterium oxide. 1H-NMR spectra were acquired on a two-channel Agilent Propulse 500 MHz spectrometer (Agilent Technologies Inc., Santa Clara, California, USA), using presaturation and PURGE (Presaturation Utilizing Relaxation Gradients and Echoes) water suppression techniques with 1024 scans, 2.6 s acquisition time, and 20 s relaxation delay (d1). Spectra were processed using MNova (Mestrelab Research, Santiago de Compostela, Spain). For each 1H-NMR spectrum, we integrated the total signal within each of the five regions (Hertkorn et al. 2013, Santos et al. 2016), as shown in Fig. 2: aliphatic (δH ~ 0.0 to 1.9 ppm), functionalized aliphatic (δH ~ 1.9 to 3.1 ppm), oxygenated (δH ~ 3.1 to 4.3 ppm), unsaturated (δH ~ 5.3 to 7.0 ppm), and aromatic functional groups (δH ~ 7.0 to 10 ppm). We expressed the total signal within each region as percentage of the total NMR signal across all five regions. We also used the aromatic:oxygenated (Arom:Oxy) ratios to evaluate whether burning increased the proportion of aromatics compared to polysaccharides in streamwater.

Fig. 2
figure 2

Liquid-state 1H-NMR spectra of dissolved organic matter (DOM) representative of the reference stream, low-severity fire, and high-severity fire sites in Yosemite National Park, California, USA, with the following major functional groups assigned for DOM components (shades of gray): aromatic, unsaturated, oxygenated, functionalized aliphatic, and aliphatic structures. The water region is not included in the integration: δH ~ 4.3 to 5.3 ppm. Sites were sampled between 1 and 13 years after the last fire

Statistical analysis

We examined the effects of fire severity and time since fire using linear (LMM) and generalized linear (GLMM) mixed-effects models using the package lme4 in R (Bates et al. 2015). Response variables DOC, DON, TDN, sodium cation (Na+), Ca2+, sulfate anions (SO42−), Mg2+, phosphate anion (PO43−), K+, chloride anion (Cl), NO3, and NH4+; as well as aromatic, unsaturated, oxygenated, functionalized aliphatic, and aliphatic functional groups; Arom:Oxy ratio; SUVA254; and E2:E3 were analyzed separately as a function of fire severity (low versus high), time since fire, and the interaction term fire severity × time since fire. To evaluate the distribution of the data, we used the Individual Distribution Identification tool in Minitab 18 Statistical Software (Minitab, Inc., State College, Pennsylvania, USA). DON, TDN, Na+, and Ca2+ fitted to a normal distribution. We used Johnson transformation to fit SO42−, Mg2+, aromatics, unsaturated, and aliphatics, Arom:Oxy, SUVA254, and E2:E3 to a normal distribution. We used the gaussian distribution for DOC and gamma distribution for PO43−, K+, Cl, NO3, and NH4+; thus we used GLMM models to analyze these response variables. In GLMMs, we included fire severity and time since fire as fixed effects, and reach (to account for variability in site-level characteristics shown in Table 1) and collection date as random effects. For LMMs, we used the MuMIn package ( to describe the amount of the variance (R2) explained by the fixed effects alone (marginal, Rm2) and the fixed and random effects combined (conditional, Rc2) (Nakagawa and Schielzeth 2013). Owing to the relatively small sample size, we were unable to include site characteristics (e.g., geomorphology, aspect, etc.) into the models as fixed effects. However, we visually evaluated patterns of aspect and bed morphology across low- and high-severity reaches via box plots (Additional files 1, 2, 3, and 4). Because the stream reach was our main experimental unit of replication, having only one reference reach precluded its inclusion in linear models as an unburned “treatment.” However, because we had multiple sampling locations and periods per reach for both reference as well as low- and high-severity fire reaches, we visually evaluated the relationships between reference and treatment responses (Table 2; Figs. 3 and 4; Additional files 1, 2, 3, and 4). We determined significance at α = 0.05 for all analyses. All statistical analyses were conducted using Minitab 18 and R version 3.4.0 (R Development Core Team;

Table 2 Solute concentrations and DOM molecular composition of the reference (Chilnualna) streamwater in Yosemite National Park, California, USA. Streamwater was sampled from the reference site >100 years after the last fire. Values shown are means ± (standard error)
Fig. 3
figure 3

Changes in average solute concentrations of (a) Ca2+, (b) Na+, (c) Cl, (d) K+, (e) Mg2+, (f) DOC, (g) TDN, (h) NO3, (i) DON, (j) SO42−, (l) PO43−, and (m) NH4+ over time since fire (years) in streams flowing through riparian zones that burned with low-severity (open circle) and high-severity (closed circle) fire in Yosemite National Park, California, USA. Sites were sampled between 1 and 13 years after the last fire. Dotted line represents the mean value for the reference stream (±1 standard error is provided in Table 2). DOC = dissolved organic carbon; DON = dissolved organic nitrogen; TDN = total dissolved nitrogen. Error bars represent ±1 standard error

Fig. 4
figure 4

Changes in average dissolved organic matter composition of (a) SUVA254, (b) E2:E3, and (c) Arom:Oxy over time since fire (years) in streams flowing through riparian zones that burned with low-severity (open circle) and high-severity (closed circle) fire in Yosemite National Park, California, USA. Sites were sampled between 1 and 13 years after the last fire. Dotted line represents the mean value for the reference stream (±1 standard error is provided in Table 2). Error bars represent ±1 standard error


Differences in streamwater solute concentrations between burned streams and the reference stream

Visual assessment of stream solute concentrations in the reference stream (Table 2, Fig. 3) showed that streams flowing through riparian zones that burned with high severity exhibited elevated Ca2+, Na+, K+, and PO43− concentrations (Fig. 3a, b, d, and l). A similar trend was observed for these solutes in streams of low-severity fire. Overall, DOC (Fig. 3f), TDN (Fig. 3g), DON (Fig. 3i), and NH4+ (Fig. 3m) concentrations associated with fire severity levels were lower than those associated with the reference stream. We observed similar trends when visually evaluating these relationships based on aspect (orientation of the slope) and stream channel morphology (see also Additional files 1 and 3). For example, Ca2+, Na+, K+, and PO43− concentrations were lower in west aspect (reference stream) than in other slope classes (burned streams; Additional file 1a, b, d, and l). We also observed higher concentrations of Ca2+ and K+ in pool-riffle burned streams relative to pool-riffle reference stream (Additional file 3a and d), while NH4+ exhibited lower concentrations in pool-riffle burned streams relative to pool-riffle reference stream (Additional file 3m).

Effects of fire severity and time since fire on streamwater solute concentrations

LMMs and GLMMs (Table 3 and Fig. 3) indicated that fire severity was related to decreased DOC (P = 0.0006) and DON (P = 0.026) concentrations. Time since fire was associated with decreased DON (P < 0.0001) and TDN (P = 0.032) concentrations and increased Cl concentrations (P = 0.036) (Table 3). Interactions between fire severity and time since fire were significant for DOC (P = 0.004) and DON (P = 0.036) concentrations (Table 3; Fig. 3f and i; Additional file 5a and b). For high-severity fire, DOC and DON concentrations decreased with time since fire, whereas in low-severity fire, DOC concentrations increased and DON concentrations slightly decreased with time since fire. For many models, site was also an important factor when considering solute responses to fire, as suggested by the amount of variation explained (Rc2) when random effects (reach and collection date) were included (Table 3). Random effects (Additional file 6) indicated that variability in site-level characteristics such as channel morphology and aspect played a role in solute responses (Additional files 1, 2, 3, 4, and 7). For example, Rc2 values were approximately twice as large as Rm2 values for DON and TDN (Table 3). Visual assessments of solute concentrations showed that the north aspect exhibited the highest concentrations of Ca2+, K+, and Mg2+ (Additional file 1a, d, and e). For both Ca2+, Na+, K+, PO43−, the lowest concentrations were in the west aspect (Additional file 1a, b, d, and l), which corresponds to the aspect of the reference reach. The north-northwest aspect exhibited the highest concentrations of Cl and SO42+ (Additional file 1c and j).

Table 3 Results from linear (LMM) and generalized linear (GLMM) mixed-effects models with fixed effects (fire severity, time since fire, fire severity × time since fire) and random effects (reach and collection date, not shown) for streamwater chemistry in burned watersheds of Yosemite National Park, California, USA. Streamwater was sampled from the sites between 1 and 13 years after the fire. Marginal (Rm2) and conditional (Rc2) coefficients of determination are shown for variation explained by fixed effects alone, and by both fixed and conditional effects, respectively. N/A means that R2 and denominator degrees of freedom (ddf) values are not available for GLMMs, and thus for DOC, NO3, NH4+, K+, Cl, and PO43−. Bolded P values indicate a significant effect (P < 0.05). F. aliphatics = functionalized aliphatics

Differences in streamwater DOM composition between burned streams and the reference stream

Visual evaluation of DOM composition showed that SUVA254 (a measure of aromaticity in DOM) and E2:E3 (measure of DOM average molecular size) were lower for burned streams than for the reference stream (Table 2; Fig. 4a and b). In general, Arom:Oxy rations (Fig. 4c) were lower for high-severity burned streams than for the reference stream, with the exception of one high-severity burned stream. The strongest resonance in 1H-NMR spectra across all streams was in the aliphatic region, contributing over 60% of the proton signals from streamwater DOM (Table 2; Figs. 2, 5a and b).

Fig. 5
figure 5

Liquid-state 1H-NMR-based dissolved organic matter composition in streams flowing through riparian zones of Yosemite National Park, California, USA, that burned with (a) low-severity fire (South Tuolumne Creek, Grouse Creek, Coyote Creek, Cascade Creek, Camp Creek, Mono Creek) and (b) high-severity fire: (Middle Tuolumne Creek, Tamarack Creek, Crane Creek, Frog Creek, Meadow Creek, and Buena Vista Creek). Sites were sampled between 1 and 13 years after the last fire. Values for the reference stream are included in each panel (a and b). Shades of gray represent the distribution of functional groups: aromatic, unsaturated, oxygenated, functionalized aliphatic, and aliphatic structures

Effects of fire severity and time since fire on SUVA254, E2:E3 ratio, and DOM functional groups

Time since fire alone was related to decreased SUVA254 (P = 0.039), whereas fire severity was associated with increased E2:E3 (P = 0.031; Table 3). The interaction fire severity × time since fire was significant for SUVA254 (P = 0.042) and E2:E3 ratios (P = 0.020; Table 3; Fig. 4a and b; Additional file 5). For low-severity fires, SUVA254 increased and E2:E3 ratios decreased with time since fire, whereas for high-severity fires, SUVA254 decreased and E2:E3 ratios slightly increased with time since fire. Neither fire severity nor time since fire was a significant predictor of the relative distribution of DOM functional groups (Table 3). Visual assessment of DOM composition showed that the east aspect had higher proportion of both unsaturated and aromatics structures and Arom:Oxy ratios relative to the south aspect (Additional file 2d, e, and f). In burned streams, SUVA254 was higher in the east than in the north-northwest aspect (Additional file 2g). There were no apparent differences in DOM composition between pool-riffle and step-pool stream channel morphology (Additional file 4).


The influence of fire

The observed low concentrations of DOC, DON, TDN, and NH4+ in burned streams compared with the reference stream are consistent with other studies that examined these responses within a decade after wildfire disturbance (Betts and Jones 2009). We offer two explanations for these trends. First, our results likely reflect the removal of C and nitrogen (N) from surface soils by fire and runoff, which resulted in lower export of groundwater C and N from burned sites relative to unburned sites. Second, it is also possible that the lower C concentrations relative to reference streams resulted from the removal of aboveground vegetation by fire, decreasing evapotranspiration, and increasing baseflow. In contrast to our results for DOC, DON, TDN, and NH4+, the concentrations of other solutes (Ca2+, Na+, K+, and PO43−) increased relative to the reference stream, similar to results reported for other regions (Chorover et al. 1994, Williams and Melack 1997, Stephens et al. 2004, Bêche et al. 2005, Engle et al. 2008). Greater concentrations of these solutes relative to the reference stream are attributed to the dissolution of these ions from post-burn ashes (inorganic residues) in deep soil or deposited into stream sediments (Ranalli 2004). However, we acknowledge that using a single reference stream may limit the interpretation of our results drawn from this comparison by constraining local, site-level variability. For instance, our reference site represented pool-riffle bed morphology and west-facing slope, and thus limited our understanding of how variability in bed morphology (e.g., step-pool) and aspect may interact with fire to influence solutes. Nonetheless, using the unburned stream as a counterpoint to our burned streams provided complementary information and additional context that was helpful in interpreting our results.

The interaction between fire severity and time since fire

Our results indicated that declines in DOC and DON concentrations, aromaticity (expressed as decreased SUVA254), and mean molecular weight DOM (expressed as increased E2:E3 ratios) with time since fire were associated with high-severity fires. The thermal degradation of OM typically decreases C stocks in the forest floor and soil C concentrations (Nave et al. 2011), therefore limiting the supply of soil DOM. As such, an increase in fire severity can lead to decreased C and N concentrations and stocks in surface soils (Homann et al. 2011), decreasing the amount of C and N that is vertically transported to lower soil depths and ultimately exported to streams. In studies conducted two to three years following a fire in the Sierra Nevada, high-severity fires were reported to decrease total C stocks in organic horizons relative to unburned treatments (Maestrini et al. 2017, Adkins et al. 2019). During high-severity fires, increases in soil heating can also decrease mineral soil C concentrations (Almendros et al. 2003, Araya et al. 2017) and lead to low molecular weight DOM (Norwood et al. 2013, Santos et al. 2016) transported from soils to streams. Our results suggest that an increase in fire severity decreased C and N concentrations and molecular size of DOM over time under baseflow conditions, likely due to the thermal degradation of topsoil OM. Increases in hydrophobicity in post-fire soils (DeBano 2000, Doerr et al. 2000, González-Pérez et al. 2004) inhibits water infiltration during the wet season, increasing post-precipitation runoff and the transport of OM from soils to streams. In this investigation, however, runoff was not the process feeding DOM into the study streams, as our sampling occurred during the dry (summer and fall) seasons. As such, our results reflect processes occurring at baseflow. Under such conditions, terrigenous DOM is primarily transported to streams via subsurface flow (Johnson and Reynolds Jr. 1977, Inamdar et al. 2011, Lee et al. 2018).

Our results for aromaticity suggest that the export of aromatic compounds, possibly from PyC, from soils to streams under baseflow conditions responds differently to different fire severities over time. Soil heating and the thermal degradation of OM by fire increase the amount of particulate and soluble PyC in surface soils (Miesel et al. 2015, Santos et al. 2016), a portion of which can move to lower soil depths via leaching (Hockaday et al. 2006, 2007; Santos et al. 2017) and has been documented in major rivers around the globe (Jaffé et al. 2013). We attribute the decrease in post-fire PyC export from soils to streams in high-severity fire to the greater losses of PyC remaining in soil during the first years after fire. The first storms after fire typically lead to greater post-precipitation erosion and runoff (Spigel and Robichaud 2007, Scott et al. 2009), thus greater removal of OM (including PyC) and its concomitant transport from soils to streams. In contrast to our results for high-severity fire, aromaticity in low-severity burned streams, where conifer canopy remains intact, increased with time. Increases in aromaticity are typically associated with increases in photochemical reactions between DOC and ultraviolet light (i.e., photodegradation) and often correlate with decreases in DOM bioavailability (Balcarczyk et al. 2009, Cory et al. 2014). An increase in aromatic compounds in DOC could decrease aquatic productivity; it has been shown that bacterial production rates are not stimulated by aromatic, slow cycling compounds. Rather, rates of bacterial production are often stimulated by more labile forms of DOC (Berggren et al. 2010). Decreased aromaticity with time since fire in high-severity fires would likely decrease rates of DOC photo-mineralization to carbon dioxide (CO2) and increase aquatic productivity, heterotrophy, and other associated metabolic processes. Understanding the coupled response and cycling of carbon and nitrogen (N) in this landscape, however, remains unclear.

The influence of time since fire

Time since fire was associated with decreased total and organic N concentrations and proportions of aromatic compounds in DOC pool, but increased Cl concentrations. These results suggest that, under baseflow conditions, these variables respond to fire for multiple years and are likely related to post-burn vegetation recovery and concurrent increases in the biological uptake of N, a limiting nutrient in soil, and Cl mobilization. Thus, it is possible that the supply of soil N that is vertically transported to lower soil depths and ultimately exported to streams over time decreased with vegetation recovery. Our results for N contrast to the elevated TDN concentrations reported 14 years after fire in Colorado (Rhoades et al. 2018), suggesting that other site-level processes (e.g., land cover type) might play a role in how N cycles in fire-affected watersheds. The underlying mechanisms leading to increased Cl concentrations over time is unclear, but it is possibly related to changes in chemical weathering rates. Nonetheless, the magnitude of N and Cl responses are likely not high enough to significantly impact freshwater ecosystems.

The influence of site-level characteristics

Site-level characteristics, when included as a random effect in the LMMs and GLMMs, emerged as playing a role in the responses of solutes to fire. Results suggest that the responses observed in this study are an integrative signal, capturing processes at the site-to-subcatchment scale. For example, we observed elevated Ca2+, K+, and Mg2+ in burned (but not reference) stream reaches with pool-riffle versus step-pool bed morphology (Additional file 3a, d, and e). The mechanisms behind the relationship between specific site-characteristics and streamwater chemistry are unclear, but likely associated with the role of bedrock lithology in affecting both chemical weathering rates and the geomorphic structure of the stream channel. Lower values of Ca2+ and K+ at our pool-riffle and west aspect reference reach may suggest an interaction between bed morphology, aspect, and fire. The effect of site-level characteristics is consistent with previous observations that streamwater chemistry as well as DOC quantity can be impacted by landscape and catchment characteristics (Johnson et al. 1997, Clow and Sueker 2000, Ahearn et al. 2005, Li et al. 2013, Larouche et al. 2015, Lintern et al. 2018). For example, findings from a study conducted in Rocky Mountain National Park, Colorado, USA, revealed that topography and geology explained 80% of the variation in the concentration of many solutes in streamwater (Clow and Sueker 2000). Topography (i.e., slope and elevation), for instance, controls fire severity, hydrological flow within catchments, and the transport of sediments and solutes to streams (Certini 2005, Lintern et al. 2018). We observed that north-northwest aspect was associated with particularly high concentrations of Cl and SO42− (Additional file 1c and j). Thus, local catchment characteristics must be considered in predictive models when assessing the long-term effects of wildfires on streamwater DOM and other solutes. This approach would improve predictions of streamwater chemistry’s vulnerability to projected increases in wildfire frequency and severity, and the areal size in the Sierra Nevada (Miller et al. 2009, Miller and Safford 2012, Kitzberger et al. 2017). Further research is needed to better understand the importance of landscape characteristics in controlling the transport of terrigenous DOM and other solutes to fluvial networks.

Aliphatic: the dominant structure in streamwater DOM

Aliphatic structures (i.e., lipids, fatty acids, and amino acids) dominated streamwater DOM composition across the fire-impacted catchments, consistent with previous studies that analyzed the composition of DOM from freshwater systems (Repeta et al. 2002, Bianchi et al. 2004, Lam et al. 2007). Our results showed no differences in the proportion of aliphatic structures between burned and unburned streams. Additionally, neither fire severity nor time since fire were significant predictors of proportion of aliphatic structures in streamwater DOM. Taken together, these results suggest that fire does not affect processes that control the mobilization and transport of these DOM compounds from deep soils to streams. The predominance of aliphatic structures in streamwater DOM is commonly assumed to be of autochthonous origin (i.e., algae in streamwater; Degens et al. 1991); however, aliphatic compounds are also reported to dominate in deep soils, presumably derived from microbial residues (Rumpel and Kögel-Knabner 2011). Owing to the fact that these streams were predominately first- and second-order streams with full canopies, it is most likely that the major aliphatic structures detected in streamwater are of allochthonous origin, providing further evidence that the measured DOM was exported from deep soils (Lee et al. 2018).


In the western US, the amount of area burned is increasing, with fire projected to increase in frequency and severity (Miller et al. 2009, Miller and Safford 2012, Kitzberger et al. 2017). In our study, fire severity, time since fire, as well as their interaction, and variability in site-level characteristics emerged as the strongest influences on streamwater chemistry. These results suggest that multiple-year responses of streamwater chemistry to wildfires in the Sierra Nevada will depend on fire severity. Post-fire changes in streamwater chemistry could have long-term implications for aquatic organisms and the balance of energy and nutrient availability and stoichiometry (e.g., C:N) during the dry season and when internal production may be low. Changes in energy and nutrient limitation could affect metabolic processes of aquatic ecosystems (Wymore et al. 2016). Understanding how wildfire severity and time since fire will interact to affect larger ecosystems and landscape-scale processes will be key to understanding how catchments will respond to future disturbances.