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Article

Seasonal- and Event-Scale Stream DOC Dynamics in Northern Hardwood-Dominated Headwater Catchments of Contrasting Forest Harvest History

by
Annie Gray
1,
Micheal Stone
1,*,
Kara L. Webster
2,
Jason A. Leach
2,
James M. Buttle
3 and
Monica B. Emelko
4
1
Department of Geography and Environmental Management, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada
2
Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, ON P6A 2E5, Canada
3
School of the Environment, Trent University, 1600 West Bank Drive, Peterborough, ON K9L 0G2, Canada
4
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
*
Author to whom correspondence should be addressed.
Water 2024, 16(19), 2724; https://doi.org/10.3390/w16192724
Submission received: 27 July 2024 / Revised: 15 September 2024 / Accepted: 18 September 2024 / Published: 25 September 2024
(This article belongs to the Section Water and Climate Change)
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Abstract

:
Forests are critical source regions of high-quality drinking water but forest disturbances such as harvesting can alter stream dissolved organic carbon (DOC) concentrations and influence source water treatability. Most stream DOC-centric forest harvesting impact studies report on effects <10 years post-harvest; less is known about the legacy effects of forest harvesting on stream DOC. Here, inter- and intra-catchment variability in stream DOC concentration and export were evaluated in two northern hardwood-dominated headwater catchments (unharvested reference and 24 years post-clearcut). The relationship between stream DOC and the concentration, spatial distribution, and hydrologic connectivity of hillslope solute pool DOC was investigated. Stream DOC concentrations in the legacy clearcut catchment exceeded those in the reference catchment for all flow conditions. Inter-catchment differences in DOC export were inconsistent. Hillslope solute pool DOC concentrations decreased with soil depth but were not significantly different between catchments. Concentration–discharge regression analysis indicated that DOC was primarily transport-limited (flushing) in both catchments. Aqueous potassium silica molar ratio data indicate the influence of groundwater on stream chemistry and streamflow was similar in both catchments. Results suggest that while clearcut harvesting can have detectable decadal-scale effects on stream DOC concentrations in northern hardwood-dominated headwater catchments, the effects are limited and likely do not pose a reasonable threat to downstream drinking water treatment operations.

1. Introduction

Approximately 30% of the Earth’s terrestrial surface is covered by forests [1], which provide numerous ecosystem services including the provision of high-quality drinking water supplies [2,3,4]. In the conterminous United States, about 60 million people rely on forested lands for more than half of their drinking water supply, despite forests only accounting for 38% of the total land area [5]. In Canada, drinking water for approximately two-thirds of the population is sourced from surface waters, much of which originates in forested areas [6]. The quality of source water delivered downstream to drinking water treatment plants has strong links to the disturbance history of the contributing landscapes [7,8] and is thus vulnerable to the impacts of natural and anthropogenic landscape disturbances such as wildfires [9] and forest harvesting practices [10]. Disturbance-induced increases in metrics of source water treatability, such as turbidity and dissolved organic carbon (DOC), can challenge downstream drinking water treatment operations, potentially resulting in reduced efficiency, higher costs, and greater health risks [7]. For example, greater source water DOC concentrations can exert increased coagulant and disinfection demands, react with disinfectants to create disinfection by-products, and increase the potential for consumer-side taste and odor problems [7].
Dissolved organic carbon is a ubiquitous and ecologically important water quality parameter, in addition to its significance as a metric of source water treatability. In aquatic ecosystems, DOC is a vector for metal [11] and persistent organic pollutant transport [12] and a regulator of light penetration in aquatic systems [13]. The amount and timing of DOC transferred from forested hillslopes to receiving streams are governed by complex interplays between catchment properties such as soil type and vegetation, soil biogeochemical processes that regulate soil solute concentrations, and soil moisture conditions that influence the mobilization and transport of hillslope solute pool DOC to receiving waters [14,15,16,17]. Due to ecological and hydrological linkages between forests and streams, particularly for headwater streams where hydrology strongly influences stream solute concentrations and export [18], snowmelt and precipitation events are key drivers of DOC export [19,20]. Under high-flow conditions in forested headwater catchments, rising water tables can intersect with organic-rich, upper riparian, and hillslope soil horizons of relatively high DOC concentrations, hydrologically connecting hillslope DOC pools and promoting the lateral transport of DOC pools into receiving streams [21]. Thus, stream DOC variability in forested headwater catchments is intrinsically linked to the concentrations, spatial distribution, and hydrologic connectivity of the hillslope DOC solute pools [22,23].
Forest harvesting is a major stand-replacing agent of disturbance in Canada’s boreal forests, represents an economically important industry [24], and has been proposed as a strategy to combat predicted, climate-exacerbated increases in the frequency and severity of wildfires [25,26,27]. However, the economic and wildfire mitigation benefits of forest harvesting must be weighed against the potential negative impacts of harvesting on source water treatability metrics such as DOC. To do so requires a robust understanding of the mechanisms, magnitude, and duration of forest harvesting impacts on stream DOC variability.
Following harvesting, forest soils typically experience reductions in rates of interception and evapotranspiration due to the removal of canopy cover and vegetation [28], which can increase soil moisture content and raise water tables [29]. Forest harvesting may also impact soil C biogeochemical cycling through increases in organic inputs (logging residues) and hypothesized increases in soil C decomposition, potentially resulting in higher DOC concentrations in hillslope solute pools [10,30]. Additionally, the use of heavy machinery during harvesting operations can cause soil compaction, decrease soil porosity, and reduce soil hydraulic conductivity [31]. The combined influences of canopy removal and soil compaction can preferentially route water via organic-rich surface and shallow subsurface flow paths [10,32,33], thereby enhancing the direct runoff component of streamflow and facilitating the hillslope-stream transport of DOC [10].
The response of stream DOC concentrations to forest harvesting practices has been widely studied but the results are often contradictory. For example, stream DOC concentrations may increase post-harvest [34,35,36,37], whereas a decrease [38] or no response has been reported elsewhere [39,40]. While providing important context regarding the influence of forest harvesting on the variability of stream DOC concentrations under a range of climatic conditions and catchment settings, most studies to date have occurred <10 years post-harvest. Few longer-term studies have been conducted [40,41,42]; accordingly, the legacy (decadal-scale) impact of forest harvesting on the variability of stream DOC concentrations and export is not well-understood, representing a temporal gap in the literature surrounding harvesting impacts on stream DOC. Additionally, few harvesting impact studies have directly related stream DOC dynamics under varying flow conditions to the concentrations, spatial distribution, and hydrologic connectivity of DOC in hillslope solute pools [21,43], representing a spatial gap in the literature regarding harvesting impacts on stream DOC.
To address temporal and spatial gaps in the literature surrounding forest harvesting impacts on stream DOC variability, recognizing in particular that inherent, inter-catchment differences in the concentrations, spatial distribution, and hydrologic connectivity of hillslope solute pool DOC in undisturbed headwater catchments help to account for inter-catchment differences in stream DOC concentration and export, this study examines and contrasts variability in stream and hillslope solute pool DOC in a reference (unharvested) catchment and a legacy (24 years post-harvest) clearcut catchment in the Canadian Shield. We hypothesize that (1) stream DOC concentrations in the legacy clearcut catchment will exceed those of the unharvested reference catchment, (2) while hillslope solute pool DOC concentrations will decrease with soil depth in both catchments, hillslope solute pool DOC will be higher in the legacy clearcut catchment relative to the unharvested reference catchment, and (3) that the near-surface flow response will be more immediate in the legacy clearcut catchment. The specific objectives of this study are (1) to evaluate inter- and intra-catchment variability in stream DOC concentrations, stream DOC export, and hillslope solute pool DOC concentrations during a range of flow conditions, (2) to investigate the spatial distribution and contribution to stream DOC of hillslope solute pool DOC, and (3) to evaluate and contrast changing hydrologic connectivity during a range of flow conditions.

2. Methods and Materials

2.1. Study Site

This study was conducted at the Turkey Lakes Watershed (TLW; 47°03′ N, 84°25′ W) approximately 60 km north of Sault Ste Marie, Ontario, Canada (Figure 1). Brief summaries of the physiographic, biological, and hydro-climatological characteristics of the TLW are provided below and reported in more detail elsewhere [36,44,45]. The TLW drains an area of approximately 10.5 km2 on the Canadian Shield with a total relief of ~300 m [45]. Regional geology is characterized by a Precambrian bedrock composed of silicate greenstone with occasional granitic outcrops [46]. Bedrock is overlain by a compacted sandy loam basal till and a silt-loam ablation till [47]. Soils are predominantly orthic humo-ferric podzols characterized by a ~5 cm thick LFH horizon composed of well-defined L and F layers [47] and spatially dispersed, highly humified organic soils present in depressions, wetlands, and riparian areas [48].
The forest is hardwood-dominated and characteristic of the Eastern Temperate Mixed Forest [49], with mature, shade-tolerant sugar maple, yellow birch, and conifers comprising 90%, 9%, and 1% of the forest coverage, respectively [50]. Mean annual air temperature and precipitation at the TLW from 1998–2021 were 4.9 °C and 1187 mm, respectively [36]. Snow cover contributes approximately 35% of the annual precipitation [32] and generally develops in October and melts during the March–May freshet period [51]. In 1997, a Forest Harvesting Impacts Study was initiated within multiple catchments at the TLW to evaluate the effects of a gradient of forest harvesting intensities (clear-felling, shelterwood, selection cut, and unharvested control) on a variety of forest ecohydrological variables, including forest recovery, soil productivity, and the quantity and quality of surface waters using a Before-After Control-Impact (BACI) paired-catchment approach [32,36,52].

2.2. Experimental Design

This study was conducted in two headwater catchments—C32 and C31 (Figure 1). Catchment C32 is undisturbed and serves as a reference while catchment C31 was harvested in the fall of 1977 using a diameter-limited “clearcut”. The clearcut procedure involved the felling and removal of trees with a diameter at breast height (DBH) > 20 cm and the felling of trees with 10 cm ≥ DBH ≤ 20 cm [53]. Clearcutting is not a common silvicultural practice in the region [54] but may be used under certain conditions [36]. At the TLW, clearcutting was used to maximize harvesting impacts on hydrologic and biogeochemical processes in C31 [55]. Harvesting in C31 reduced the basal area by 78% and stocking by 76% [53]. As of 2014, total stocking in C31 has exceeded pre-harvest levels [53], which may be related to natural regeneration via the establishment of pioneer species such as yellow birch and cherry in harvested areas [32]. The basal area in C31 remains below pre-harvest levels [53]. Catchments C32 and C31 have similar areas, reliefs, slopes, aspects, and wetland coverage (Table 1). Notably, in each catchment, there are local topographic depressions that are intermittently saturated depending on the time of year, rainfall patterns, and soil moisture conditions, previously described in the literature as small, cryptic-treed mineral wetlands (i.e., forested swamps) characterized by mineral soils and a shallow organic surface layer of approximately 10 to 20 cm [56,57]. These mineral wetland features comprise 1% and 3% of the respective areas of the study watersheds (Table 1).

2.3. Field Methods

2.3.1. Hydrometeorological Monitoring

The streamflow was estimated from 10 min water level measurements made at the outlets of C32 and C31 using 90° V-notch weirs with stilling basins and Steven’s Smart PT SDI-12™ pressure and temperature transducers. Stage data were converted to instantaneous discharge. Ten-minute precipitation data were recorded approximately 0.4 km southwest of the study basins at a Natural Resources Canada monitoring station (“Meadow Station”, Figure 1) using an OTT Pluvio weighing rain gauge (OTT HydroMet, Kempten, Germany).

2.3.2. Stream Sampling

Stream samples were collected between 25 March 2021 and 30 October 2021 at the weirs. This study encompassed a range of hydrological conditions including a freshet sampling period, a post-freshet (hereafter “intermediate”) sampling period, and the fall wet-up (hereafter the fall sampling period). Freshet sampling began on 25 March 2021 and ended on 9 May 2021 based on observations of stream discharge and snowpack on-site. The intermediate sampling period from 10 May 2021 to 8 October 2021 included baseflow conditions and four precipitation events sampled at sub-daily frequencies (hereafter precipitation events A to D). The fall sampling period took place between 9 October 2021 and 30 October 2021.
During the freshet and fall sampling periods, daily composite stream samples were collected using automated ISCO 6700 samplers (ISCO, Lincoln, NE, USA), such that 250 mL sub-samples were collected every six hours. ISCO samples were collected in acid-washed, triple-rinsed 1 L polypropylene sample bottles. During the precipitation events, samples were collected at pre-set intervals, ranging from every thirty minutes to every two hours, for the duration of each event. Sample collection intervals were constant within each event and were based on the intensity, timing, and duration of the precipitation events as predicted by local weather forecasts. Grab samples were collected approximately weekly during baseflow conditions in the intermediate sampling period using acid-washed, triple-rinsed, triple-sample-rinsed 500 mL HDPE field bottles.

2.3.3. Groundwater Sampling

Basal till groundwater and ablation till groundwater were sampled from drive-point piezometers (Solinst Canada Ltd., Georgetown, ON, Canada) with inside diameters (i.d.) of 2 or 4 cm, positioned along hillslope transects established perpendicular to the stream in each catchment [33] (Figure 1). Three piezometer nests were situated on both sides of the stream along a topslope–midslope–toeslope continuum. At each nest, one piezometer was screened in the basal till and one in the ablation till. In C32, basal and ablation till piezometer installation depths were (mean ± SD) 0.93 ± 0.09 m and 0.40 ± 0.03 m, respectively. The corresponding piezometer installation depths in C31 were 1.09 ± 0.19 m and 0.45 ± 0.05 m. Although most piezometers had 10 cm screens, some were outfitted with 25 cm screens [33].
In addition to the basal and ablation till groundwater piezometer transects, groundwater was also collected from a piezometer transect deployed in the wetlands of both catchments (Figure 1). Wetland piezometers (4 cm i.d.) were installed in C32 and C31 at depths of 0.37 ± 0.03 m and 0.39 ± 0.03 m, respectively.
Groundwater sampling occurred approximately weekly during the freshet and fall sampling periods and approximately monthly under baseflow conditions during the intermediate sampling period. Groundwater samples were also collected during each of the four sampled precipitation events. A peristaltic pump was used to purge each piezometer 24 h prior to sampling to allow the piezometer sufficient recharge time and to ensure that samples were representative of the conditions of the respective sampling times [33]. Purging continued until either (a) the piezometer was dry or (b) 5 min had elapsed, whichever came first. Samples were collected in acid-washed, triple-rinsed, triple-sample-rinsed 500 mL HDPE field bottles.

2.3.4. Mineral Soil Water and LFH Percolate Sampling

To evaluate the spatial and temporal variability of soil water chemistry in the shallow subsurface hillslope profile, soil pits were dug by hand adjacent to the hillslope piezometer nests in each catchment to depths (mean ± SD) of 0.64 ± 0.10 m and 0.65 ± 0.10 m in C32 and C31, respectively [57] (Figure 1). Each soil pit was instrumented with two zero-tension lysimeters. Lysimeters were installed laterally into the upslope cut-face 6 months prior to the start of sample collection to allow the surrounding soil to settle [58]. The first lysimeter was placed directly below the leaf litter layer in each pit to capture water percolating through the organic-rich forest floor (hereafter “LFH percolate”). The second lysimeter was situated in the mineral soil horizon approximately 20 cm below the contact with the LFH layer to capture water traveling laterally through the mineral soil horizon (hereafter “mineral soil water”). To maximize contact between the screen mesh and overlying soil matrix (LFH or mineral soil), glass wool topped with a mixture of local soil (taken from the excavated area to make room for the respective lysimeters) and saturated with DI water was placed on top of the screen mesh. Each lysimeter drained into 1 L acid-washed, triple-rinsed HDPE sample bottles housed in protective plastic totes within each soil pit. Sample bottles were monitored weekly during the freshet and fall sampling periods and collected when a minimum of 500 mL had accumulated.

2.3.5. Throughfall Sampling

A throughfall collector was installed adjacent to one soil pit in each basin to characterize precipitation solute concentrations. In C32, it was deployed next to the “top” pit in the upper west transect, and in C31, the throughfall collector was located adjacent to the “top” pit of the lower east transect (Figure 1). Throughfall collectors consisted of a plastic funnel, protected from the accumulation of leaf litter by a mesh, attached to a steel post driven securely into the ground [57]. Proximity to the respective soil pits allowed the throughfall collectors to empty into 1 L acid-washed, triple-rinsed HDPE bottles in protective plastic pit liners. Collection of the throughfall sample bottles was coincident with that of the lysimeter sample bottles.

2.4. Laboratory Analysis

Samples were transported on ice from the field and generally frozen within one week, but some samples were refrigerated (<4 months) prior to freezing due to COVID-19-related shutdowns and limited lab access. It is recognized that hold times and freeze-thaw may impact DOC concentrations [59,60]. After thawing, all samples were analyzed at the Water Chemistry Laboratory at the Great Lakes Forestry Centre in Sault Ste Marie, ON, using standardized methods and quality control practices [44]. For DOC, all samples were filtered using pre-soaked and pre-rinsed 0.45 µm mixed cellulose ester filters (GN-6 Metricel, VWR).

2.5. Data Analysis

Data processing, statistical analysis, and graphic visualization were conducted using R version 4.0.2 [61]. Differences were considered statistically significant at p ≤ 0.05.

2.5.1. Analytical Methods Related to Objective 1: Evaluate Inter- and Intra-Catchment Variability in Stream DOC Concentrations, Stream DOC Export, and Hillslope Solute Pool DOC Concentrations during a Range of Flow Conditions

Descriptive statistics and boxplots were used to evaluate inter- and intra-catchment variability in stream DOC concentrations, stream DOC export, and hillslope DOC concentrations. The non-parametric Mann–Whitney U test was used to evaluate inter-catchment differences in stream DOC concentrations, stream DOC export, and hillslope solute pool DOC concentrations as normality assumptions were not met and sample sizes were often <30. To reduce bias in the inter-catchment comparisons of stream DOC concentration, only samples collected from both catchments on the same day under freshet, baseflow, and fall conditions or on the same date and time during precipitation events were used for inter-catchment Mann–Whitney U tests. Similarly, inter-catchment Mann–Whitney U tests for DOC export included only DOC export values from each catchment with a temporal partner in the other catchment. Intra-catchment differences in stream and hillslope solute pool DOC concentrations and stream DOC export were evaluated using the non-parametric Kruskall–Wallis test.
For the freshet and fall sampling periods, stream DOC export (mg s−1 ha−1) was evaluated for each catchment by multiplying the average daily water yield (L s−1 ha−1) by the daily composite stream DOC concentration (mg L−1). For samples collected under baseflow conditions, instantaneous water yield (L s−1 ha−1) was multiplied by stream DOC concentration for each sampling time. For samples collected during precipitation events A to D, the frequency of discharge measurements differed from the frequency of stream chemistry sampling. Accordingly, stream DOC concentrations (mg L−1) were interpolated using linear regression and were multiplied by instantaneous water yield (L s−1 ha−1) to determine DOC export (mg s−1 ha−1). More specifically, linear regression between streamflow and sampled DOC followed by interpolation of DOC concentrations was conducted for each interval between consecutive streamflow local maxima or minima, determined from visual examination of the respective hydrographs. In cases where a local maximum or a local minimum occurred between two samples and a linear regression could not be determined for at least one adjacent limb, the regression interval was extended to include the next local maximum or minimum and linear extrapolation was used.

2.5.2. Analytical Methods Related to Objective 2: Investigate the Spatial Distribution and Contribution to Stream DOC of Hillslope Solute Pool DOC

Concentration–discharge (C–Q) regression relationships are widely used to investigate solute hillslope-stream transport dynamics and to characterize stream solute export regimes (e.g., transport-limited vs. source-limited) under varying seasonal and hydrologic conditions. Variations in concentration–discharge relationships have been linked to catchment characteristics such as the spatial distribution of hillslope solute pools, slope, size, vegetation, land use history, and the relative location and size of wetlands [62,63,64,65]. Recent studies [62,64,65] have applied the conceptual framework for C–Q analysis provided by [66], which combines two metrics: the slope of the ln(C)–ln(Q) regression line [67] and the ratio of the coefficient of variations [68]. In the present study, DOC–Q relationships were evaluated for multiple flow conditions using the analytical framework presented in [66] and recently applied for undisturbed headwater catchments at the Turkey Lakes Watershed [65]. Briefly, the slope of the regression line between the ln-transformed stream DOC concentration and the ln-transformed stream discharge at the respective catchment outlets (hereafter ln (DOC)–ln(Q)) was calculated for each catchment and flow condition (the freshet sampling period, baseflow, precipitation events A–D, and the fall sampling period). The ratio of the coefficients of variation (CV) of DOC concentration and discharge was also calculated (hereafter CVDOC/CVQ). Slopes and CV ratios were then interpreted with respect to four general categories of C–Q behavior [62,69] (Table 2). Notably, the use of these categories is intended only to complement and facilitate the interpretation of the concept of a continuum of solute behavior, rather than as a strict set of operational definitions [65,70]. Following [65], slope values of ln (DOC)–ln(Q) > 0.1 were considered indicative of flushing behavior and slope values of <−0.1 were considered indicative of dilution behavior. Although other slope thresholds, e.g., |0.2|, have been used [70], |0.1| was selected due to its best alignment with [65]. Where the ln (DOC)–ln(Q) regression relationship was not statistically significant (Spearman, p > 0.05), a CVC/CVQ value of 0.5 was considered as the threshold between chemostatic (<0.5) and chemostochastic (>0.5) behavior [65], predicated on the work of [68], which suggests that values < 0.5 (chemostatic behavior) may be indicative of a conservative tracer.

2.5.3. Analytical Methods Related to Objective 3: Evaluate and Contrast Changing Hydrologic Connectivity during a Range of Flow Conditions

To evaluate catchment flow path changes with potential implications for stream DOC variability, the aqueous molar ratio of potassium (K+) and silica (SiO2) (hereafter K:SiO2) was evaluated for each stream and hillslope solute pool sample for which both K+ and SiO2 concentrations were above their respective detection limits. K:SiO2 has been previously used at the TLW to examine the impact of forest harvesting practices on flow path dynamics during the spring freshet [33] and across a long-term sampling program [32]. Here, we present detailed stream and hillslope solute pool K:SiO2, K+ concentrations and SiO2 concentrations for a range of flow conditions (freshet, baseflow, precipitation events, and fall) and seasonal conditions (freshet, intermediate, and fall). Inter- and intra-catchment variability in stream and hillslope K:SiO2, K+ concentrations, and SiO2 concentrations are presented in boxplots, evaluated using descriptive statistics, and contrasted via Mann–Whitney U tests (inter-catchment) or Kruskal–Wallis tests (intra-catchment). Following the approach of Section 2.5.1, stream samples from either catchment without a temporal partner in the other catchment (same day under freshet, baseflow, and fall conditions, or same date and time during precipitation events) were excluded from inter-catchment Mann–Whitney U tests to reduce bias in the inter-catchment comparisons of stream K:SiO2 ratios, K+ concentrations, and SiO2 concentrations.

3. Results

3.1. Precipitation and Streamflow

Annual (January to December) precipitation for 2021 at the Turkey Lakes Watershed was 1183.9 mm, while annual stream discharge was 424.2 mm and 320.3 mm in C32 and C31, respectively (Figure 2 and Table 3). C32 had continuous streamflow throughout the study period whereas C31 had intermittent flow with 48 zero-flow days. Precipitation and streamflow data are given in Table 3 by flow condition and catchment.

3.2. Results Related to Objective 1: Evaluate Inter- and Intra-Catchment Variability in Stream DOC Concentrations, Stream DOC Export, and Hillslope Solute Pool DOC Concentrations during a Range of Flow Conditions

3.2.1. Stream DOC Concentrations

Stream DOC concentration ranged from 0.93 mg L−1 to 5.13 mg L−1 and 1.41 mg L−1 to 6.32 mg L−1 in the unharvested reference catchment C32 (n = 179) and the legacy clearcut catchment C31 (n = 158), respectively, over the approximately 7-month period. DOC concentrations for C32 and C31 were (mean ± SD) 2.42 ± 0.69 mg L−1 and 3.56 ± 1.02 mg L−1, respectively. Additional descriptive statistics are provided by flow condition in Table 4. Inter- and intra-catchment variability in stream DOC concentrations are presented in Figure 3a and Figure 3b, respectively.
Stream DOC concentrations were higher in C31 than in C32 under all flow conditions, with statistically significant inter-catchment differences in stream DOC concentration (Mann–Whitney U test, p ≤ 0.05, Figure 3a). The absolute values of the mean inter-catchment (C32–C31) difference in stream DOC concentration exceeded the detection limit for DOC concentration in this study (0.400 mg L−1) and were 0.52 mg L−1, 0.84 mg L−1, 2.01 mg L−1, 1.66 mg L−1, 0.89 mg L−1, 1.48 mg L−1, and 1.09 mg L−1 for the freshet sampling period, baseflow, event A, event B, event C, event D, and the fall sampling period, respectively. The overall mean inter-catchment absolute value of differences was 1.21 mg L−1.
Intra-catchment stream DOC concentrations differed significantly (Kruskal–Wallis test, p ≤ 0.05) between the sampled flow conditions. DOC concentrations during high-flow conditions (freshet, precipitation events A–D, and fall) were elevated relative to baseflow conditions (Figure 3b). Notably, the range of DOC concentrations during precipitation events A–D was comparable to those of the freshet and fall sampling periods. For both catchments, the minimum observed DOC concentrations occurred during the freshet sampling period. The maximum observed DOC concentrations occurred in the freshet and fall periods, respectively, for C32 and C31 (Figure 3b).

3.2.2. Stream DOC Export

Stream DOC export in C32 ranged from 2.09 × 10−2 mg s−1 ha−1 to 6.79 mg s−1 ha−1 (n = 757). In the legacy clearcut catchment C31, stream DOC export from 1.61 × 10−7 mg s−1 ha−1 to 9.25 mg s−1 ha−1 was observed (n = 648). Average DOC export (± SD) from C32 was 0.36 ± 0.42 mg s−1 ha−1, whereas average DOC export (±SD) from C31 was 0.69 ± 0.84 mg s−1 ha−1. Inter- and intra-catchment variability in stream DOC export is visualized, respectively, by Figure 3c,d.
Inter-catchment comparisons of stream DOC export revealed significant differences (Mann–Whitney U test, p ≤ 0.05) under baseflow conditions and during precipitation events A–C. Under baseflow conditions, stream DOC export from C32 exceeded that of C31, whereas, during precipitation events A–C, DOC export from C31 exceeded export from C32 (Figure 3c). In contrast, DOC export did not differ significantly between the catchments for the freshet sampling period, event D, or the fall sampling period (Figure 3c).
Intra-catchment stream DOC export was lowest under baseflow conditions and peaked during the freshet sampling period in both C32 and C31 (Figure 3d). Of the four sampled precipitation events, the highest DOC export for both catchments occurred during event A.

3.2.3. Hillslope Solute Pool DOC Concentrations

Descriptive statistics for hillslope solute pool DOC concentrations are provided in Supplementary Table S1. No significant inter-catchment difference in DOC concentration was observed for any hillslope solute pool (Figure S1).
Intra-catchment hillslope solute pool DOC concentrations generally followed a vertical gradient, decreasing with depth from the upper soil horizon DOC pools (LFH percolate and mineral soil water) to the basal and ablation till groundwater DOC pools (Figure 4). Vertical stratification was most apparent during the intermediate and fall sampling periods, corresponding with the highest observed DOC concentrations in the LFH percolate and mineral soil water solute pools (Figure 4). Dissolved organic carbon concentrations in the LFH percolate and mineral soil water solute pools of each catchment significantly exceeded their respective stream DOC concentrations in all sampling periods (Mann–Whitney U test, p ≤ 0.05, Figure 4). In contrast, basal and ablation till groundwater DOC concentrations in C32 were not significantly different from the stream samples collected across all sampling periods (Figure 4). Notably, only one sample was collected from both the basal till groundwater and ablation till groundwater solute pools in C32 during the intermediate sampling period (Table S1), as the water table was below the depth of most piezometers at sampling times. Accordingly, adequate characterization of DOC concentrations in either ablation till groundwater or basal till groundwater in C32 during the intermediate sampling period and robust comparisons to stream DOC concentrations were not possible. In C31, basal till groundwater did not differ significantly from stream DOC concentrations under freshet, intermediate baseflow, and fall conditions (Figure 4) but was significantly lower than stream event samples (Mann–Whitney U test, p ≤ 0.05, Figure 4). Ablation till groundwater DOC concentrations in C31 were significantly lower than stream DOC concentrations (Mann–Whitney U test, p ≤ 0.05, Figure 4) during the freshet and fall sampling periods. During the intermediate sampling period, ablation till groundwater DOC in C31 significantly exceeded baseflow stream DOC concentrations but was significantly lower than stream DOC concentrations during precipitation events.

3.3. Results Related to Objective 2: Investigate the Spatial Distribution and Contribution to Stream DOC of Hillslope Solute Pool DOC

Regression relationships between streamflow and stream DOC concentrations were examined at the seasonal and event levels to investigate the spatial distribution and contribution to stream DOC of hillslope solute pool DOC in C32 and C31. Log-transformed DOC concentration–discharge (ln (DOC)–ln(Q)) regression relationships are presented in Figure 5a for each sampled flow condition. All observed ln (DOC)–ln(Q) relationships were statistically significant (p ≤ 0.05) except for baseflow in both catchments.
Freshet, baseflow, and fall Spearman rank-order correlation coefficients were, respectively, 0.80, 0.33, and 0.87 in C32 and 0.57, 0.20, and 0.66 in C31. During precipitation events A–D, the Spearman rank-order correlation coefficient ranged from 0.70 to 0.90 for C32 and from 0.55 to 1 for C31 (Figure 5a). The slopes of the ln (DOC)–ln(Q) regression relationships in C32 were higher than those in C31 for all conditions except for precipitation Event B (Figure 5a). The slopes for all catchments and conditions were <0.5. The CVDOC/CVQ ratios for the study catchments are plotted in Figure 5b. Ratios in C32 tended to exceed those in C31. (Figure 5b). Inter-catchment differences were most apparent for Event A and the fall sampling period, whereas CVDOC/CVQ ratios were most similar for baseflow and Event B (Figure 5b).

3.4. Results Related to Objective 3: Evaluate and Contrast Changing Hydrologic Connectivity during a Range of Flow Conditions

3.4.1. Stream K:SiO2 Ratios

Stream K:SiO2 ratios in C31 exceeded and differed significantly (Mann–Whitney U test, p ≤ 0.05) from those in C32 across all sampled flow conditions except the fall sampling period (Figure 6a). Similarly, stream K+ concentrations were higher in C31 and significantly different (Mann–Whitney U test, p ≤ 0.05) from those in C32 under all flow conditions except the fall sampling period (Figure 6a). Stream SiO2 concentrations did not differ significantly between the catchments during the freshet sampling period, under baseflow conditions, during precipitation event D, or during the fall sampling period (Mann–Whitney U test, p > 0.05, Figure 6a). In contrast, during precipitation events A–C, stream SiO2 concentrations in C31 exceeded and differed significantly from C32 (Mann–Whitney U test, p ≤ 0.05, Figure 6a).
The lowest stream K:SiO2 ratios occurred during the freshet sampling period in both C31 and C32 (Figure 6b). In C32, the maximum observed stream K:SiO2 ratios occurred during the fall sampling period, whereas the maximum observed stream K:SiO2 value in C31 occurred during the freshet sampling period. Stream K:SiO2 ratios during baseflow conditions were generally lower than all other flow conditions in both catchments (Figure 6b). The maximum observed stream K+ concentrations occurred during the fall sampling period in both catchments. A notable contrast between the intra-catchment trends for stream K+ is shown in Figure 6b. In C32, stream K+ concentrations during the freshet sampling period generally exceeded those observed under baseflow conditions, whereas the opposite was observed in C31. Stream SiO2 concentrations were markedly lower during the freshet sampling period, relative to other flow conditions, for both C32 and C31. In C32, a general increase in stream SiO2 concentrations was observed across precipitation events A–D (Figure 6b). A similar trend was not observed in C31 as events B and D showed slightly elevated stream SiO2 concentrations, similar to baseflow SiO2 concentrations, relative to events A, C, and the fall sampling period (Figure 6b).

3.4.2. Hillslope Solute Pool K:SiO2 Molar Ratios

No significant inter-catchment differences in the K:SiO2 ratio were observed for any hillslope solute pool during any sampling period with the following exceptions (Mann–Whitney U test, p ≤ 0.05): basal till groundwater during the freshet sampling period (higher K:SiO2 in C31), wetland groundwater during the intermediate and fall sampling periods (higher K:SiO2 in C32), and LFH percolate during the fall sampling period (higher K:SiO2 in C31) (Figure S2).
Intra-catchment K:SiO2 ratios decreased with depth in the soil profile, meaning that relatively higher ratios were observed in the throughfall, LFH percolate, and mineral soil water solute pools and relatively lower ratios were observed in the basal and ablation till groundwater solute pools. As the K:SiO2 ratios of the throughfall, LFH percolate, and mineral soil water solute pools of both catchments were consistently and significantly higher (Mann–Whitney U test, p ≤ 0.05) than the K:SiO2 ratios of the corresponding stream samples, the throughfall, LFH percolate, and mineral soil water solute pools are excluded from Figure 7 and are included in Figure S3. Results for the remaining solute pools are discussed below.
During the freshet sampling period, stream K:SiO2 ratios in C32 were significantly (Mann–Whitney U test, p ≤ 0.05) lower than the K:SiO2 ratios observed in the ablation till groundwater solute pool. During the freshet sampling period, stream K:SiO2 ratios in C31 were significantly lower than the basal till groundwater solute pool (Mann–Whitney U test, p ≤ 0.05, Figure 7).
During the intermediate sampling period, K:SiO2 ratios for the basal till groundwater and wetland groundwater solute pools were significantly greater than the stream K:SiO2 ratios under both baseflow and event conditions in C32 (Mann–Whitney U test, p ≤ 0.05, Figure 7), whereas ablation till groundwater K:SiO2 ratios were significantly lower (Mann–Whitney U test, p ≤ 0.05, Figure 7). In C31, K:SiO2 ratios for the basal till groundwater and wetland groundwater solute pools in C31 were significantly lower (Mann–Whitney U test, p ≤ 0.05) than stream K:SiO2 ratios collected during Events A–D (Figure 7).
During the fall sampling period, stream K:SiO2 ratios in C32 were significantly less (Mann–Whitney U test, p ≤ 0.05) than the wetland groundwater and significantly higher (Mann–Whitney U test, p ≤ 0.05) than the basal and ablation till groundwater K:SiO2 ratios (Figure 7). In C31, stream K:SiO2 ratios did not differ significantly from the basal till groundwater and wetland groundwater solute pools (Figure 7).
Across all sampling periods, K:SiO2 ratios from the basal till groundwater, ablation till groundwater, and wetland groundwater solute pools of both catchments were most similar to the corresponding stream K:SiO2 ratios, with considerable overlap in the ranges of the groundwater solute pool K:SiO2 ratios. Inter- and intra-catchment variability in K+ and SiO2 concentrations are presented, respectively, in Figures S4 and S5.

4. Discussion

4.1. Legacy Clearcutting Implications for Stream DOC Variability

Forest harvesting-induced elevations of stream DOC concentrations have been previously reported at the TLW [36] and elsewhere [34,35,71]. The overall mean inter-catchment difference in stream DOC concentration observed in this study, 1.21 mg L−1, supports hypothesis 1, that stream DOC concentrations in the legacy clearcut catchment would exceed those in the unharvested reference catchment, aligning with previously reported increases in stream DOC attributed to forest harvesting: 1 mg L−1 [72], 3.0 mg L−1 [35], and 1.02 mg L−1 [36], with the latter value based on previous work in C32 and C31 using a Before-After Control-Impact design. Accordingly, the data of this study suggest that harvest-induced elevations in stream DOC concentrations may persist at decadal scales. Notably, the magnitude of the impact was relatively modest (~1 mg L−1 DOC) compared to intra-catchment variability at seasonal and event scales (Figure 3a,b).
Whereas stream DOC concentrations were consistently higher in C31 than in C32, a similar pattern was not observed for stream DOC export. No significant inter-catchment difference in stream DOC export (Mann–Whitney U test, p > 0.05, Figure 3c) was observed for the freshet sampling period, for the fall sampling period, or for precipitation event D. DOC export from C31 exceeded C32 for precipitation events A–C. Under baseflow conditions, DOC export was higher in C32 (Figure 3c). The inconsistent inter-catchment differences in stream DOC export may be explained by inter-catchment differences in streamflow. Throughout the study period, there was streamflow in C32; however, in C31, 48 no-flow days were observed. Streamflow in C32 generally exceeded that in C31 under low-flow conditions, consistent with observations of relatively higher DOC exports in C32, whereas peak flows in C31, such as event-scale hydrograph responses, often exceeded C32, consistent with the relatively higher event-scale DOC exports observed in C31 (Figure 3c).
Due to the limited legacy impact of clearcut harvesting on stream DOC concentrations in C31 observed in this study and the lack of concurrent increases in stream DOC export, the data of this study suggest that clearcut harvesting in this biogeographical setting likely does not pose a reasonable threat, in terms of stream DOC concentrations, to downstream drinking water treatment operations at decadal scales in northern hardwood-dominated headwater catchments.

4.2. Legacy Clearcutting Implications for Hillslope Solute Pool DOC Concentrations

Post-harvest elevations in stream DOC concentration are typically attributed to one or more of the following [10,35]: harvest-induced increases in hillslope solute pool DOC concentrations and/or flow path shifts, including elevated groundwater levels in favor of faster, near-surface flow paths which can intersect organic-rich upper soil horizons.
Vertical stratification of hillslope solute pool DOC concentrations was observed in both catchments (Figure 4), consistent with hypothesis 2. Decreases in hillslope solute pool DOC concentrations with depth are well-documented for forested watersheds [16,73] and are commonly attributed to complex mechanisms of organic matter retention, transformation, and degradation, including DOC adsorption to and/or co-precipitation with mineral soils [74,75,76].
Despite the similar intra-catchment distributions of hillslope solute pool DOC, no significant inter-catchment difference in DOC concentration was observed for any hillslope solute pool, in contrast to hypothesis 2. This suggests that any impact(s) of clearcut harvesting on hillslope solute pool DOC concentrations have not persisted until 24 years post-clearcut, despite the previously observed post-harvest changes in tree species composition in C31 [32]. Accordingly, the data do not provide sufficient evidence to support post-harvest impacts on hillslope solute pool DOC concentrations as an explanation for the relatively higher stream DOC concentrations observed in C31. However, this statement must be viewed with caution due to the lack of pre-harvest hillslope solute pool DOC concentration data for comparison. For instance, it is possible that, during the pre-harvest period, one or more of the hillslope solute pools in C31 were lower than in C32. Additionally, the literature shows mixed results regarding the impact of forest harvesting on hillslope solute pool DOC concentrations < 10 years post-harvest, including both increases [77] and decreases [38]. These observations may be due to inter-study differences in factors such as soil conditions and the timing and type of forest harvest used, among other site-specific conditions [10]. A greater emphasis on hillslope solute pool DOC concentrations in future harvesting-centric BACI studies is warranted.

4.3. Legacy Clearcutting Implications for Flowpath Behaviour—Insight from DOC Concentration–Discharge Regression Analysis and K:SiO2

Dissolved organic carbon concentration–discharge regression analysis suggested that DOC export behavior in both C32 and C31 is primarily transport-limited (flushing), a pattern commonly observed in forested catchments in the TLW [78] and elsewhere [79,80]. Specifically, flushing and chemostatic DOC–Q behavior has been previously reported in C32 [65]. Additionally, the slopes of the ln(DOC)–ln(Q) regression relationships were consistently <0.5 in both basins, in alignment with observations of weak DOC–Q relationships from other small boreal forested catchments [62,81]. In general, shifting flow paths and rising water tables during high-flow conditions in forested catchments can saturate organic-rich riparian zones and upper soil horizons, thus promoting lateral hillslope-stream DOC transport [21].
For any given flow condition, C31 had lower CVDOC/CVQ ratios compared to C32, suggesting a relatively homogenous/uniform distribution of solute sources in C31 whereby shifts in hydrologic connectivity (flow path changes) do not influence DOC concentrations [62]. If harvest-induced flow path changes were still impacting stream DOC in C31 (hypothesis 3), it could be expected that the contribution of the fast, near-surface flow paths associated with clearcut harvesting in C31 [33] would be reflected in the C-Q framework and result in relatively higher CVDOC/CVQ ratios for C31, in contrast to the results of this study. It is possible that the small, cryptic-treed mineral wetlands located near the catchment outlet in C32 influenced the relatively higher CVDOC/CVQ ratios observed in C32, potentially masking legacy harvesting impacts on inter-catchment differences in CVDOC/CVQ—wetland position and extent have been related to CVDOC/CVQ in undisturbed headwater catchments of the TLW [65].
Variability in stream K:SiO2 was used as an indicator of changing hydrologic connectivity (flow paths) in the study catchments at seasonal and event scales, such that higher stream K:SiO2 ratios, similar to those of near-surface solute pools such as forest floor percolate and mineral soil water, are indicative of faster surface flow paths and lower stream K:SiO2 ratios, similar to those of basal and ablation till groundwater solute pools, denoting slower, deeper flow paths [33]. In this study, stream K:SiO2 values in each catchment were similar to those of their respective basal and ablation till groundwater solute pools, as well as the respective wetland groundwater solute pools, which is consistent with previous, freshet-centric work on flow paths at the TLW. This highlights the importance of shallow soil water pathways, routed above the ablation till/basal till contact [47] by means of a perched water table over the basal till [47,78]. The agreement of this study with previous work at the TLW provides support for the continued use of K:SiO2 as a proxy for changing flow paths at the TLW. Nonetheless, the future use of K:SiO2 as a flow path proxy in C32, as well as its insight in this study, may be constrained by the confounding influence of wetlands on SiO2 [51].
Previous work on K:SiO2 at the TLW has also provided evidence for harvest-induced flow path shifts in favor of faster, near-surface flow paths [32,33]. Should clearcut harvesting still be impacting flow paths in C31 (hypothesis 3), we might expect to see distinctly higher stream K:SiO2 values relative to the basal and ablation till groundwater K:SiO2 in C31—similar to the observations of [33] in C31 4 years post-harvest. The K:SiO2 results of this study contrast our hypothesis and [33], aligning instead with the recent end-member mixing analysis completed in C31 and C32 [57]. The authors of ref. [57] characterized stream chemistry in C32 and C31 as primarily driven by basal and ablation till groundwater, with wetland groundwater contributions in both catchments, especially C32, and suggested that, approximately 24 years post-harvest, flow path recovery in C31 has largely occurred. Thus, the K:SiO2 results of the present study do not support legacy harvesting impacts on flow paths in C31 as an explanation for the elevated stream DOC concentrations.

4.4. Study Limitations and Uncertainties

The results of this study do not support the persistence of mechanisms typically attributed to immediate and short-term post-harvest increases in stream DOC concentrations, despite the evidence of a persistent inter-catchment difference. Thus, inherent experimental limitations and other possible factors must be further considered. In particular, the relatively higher stream DOC concentrations in C31 under baseflow conditions are of note, consistent with the pattern observed in [34] for harvested boreal catchments in Sweden. The authors of [34] recognized that, although harvesting impacts on stream DOC concentrations under high flow conditions may be explained by factors commonly associated with forest harvesting, such as higher water tables and flow path changes, the presence of persistently elevated DOC concentrations under groundwater-driven baseflow conditions may require further investigation. A possible explanation was discussed in [34]—the release of DOC from harvesting residues which may, over time, move into deeper groundwater pools that typically contribute to baseflow in forested catchments. Similarly, ref. [42] suggested that decadal-scale, harvest-induced differences in vegetation (e.g., leaf litter quality) and rates of organic matter accumulation and decomposition could result in long-term effects on stream DOC. Harvest-induced differences in vegetation, for instance, the establishment of pioneer species such as yellow birch and cherry, have been observed in C31 [32]. The suggestion of a missing “endmember” in [57] may provide some additional insight as to why stream DOC concentrations in C31 exceeded C32 under baseflow conditions in this study. It is possible that there is a groundwater solute pool contributing to baseflow in C31 [57] with a DOC concentration influenced by the release and downward vertical transport of DOC from harvesting residues over time [34] and/or by post-harvest vegetation changes in C31 [32]. This hypothesis is supported by observations of the water table being below the depth of most basal and ablation till piezometers in C31 during the intermediate sampling period. It is also possible that there are locations of preferential flow in either catchment, not captured by the hillslope transects, which are influencing stream DOC variability [82]. In particular, this study is limited by the lack of explicit characterization of the riparian zone, including potential discrete riparian inflow points [83], as riparian zones are “near-stream” solute pools associated with rapid DOC inputs during high-flow conditions [21,84].
It is possible that, over time, the relevance of individual post-harvest mechanisms shifts from commonly cited, short-term impacts (flow path changes, elevated water tables, etc.) to other, less well-understood processes such as long-term decay of harvest residues. Further research is needed to better understand the factors influencing stream DOC in post-harvest headwater catchments at decadal timescales, especially with respect to groundwater-driven baseflow conditions, and would benefit from the explicit characterization of riparian zones, the inclusion of inter-annual datasets, and the use of study sites that include common, harvest-associated infrastructure such as roads and culverts.

5. Conclusions

This study combined a pre-established Before-After Control-Impact–based paired catchment design with high-frequency stream sampling and intensive hillslope solute pool sampling to offer new insights into seasonal- and event-scale DOC dynamics in forested headwater catchments of contrasting harvest history (clearcut vs. unharvested reference). Twenty-four years post-harvest, stream DOC concentrations in the clearcut catchment exceeded (mean increase 1.21 mg L−1) and differed significantly (p ≤ 0.05) from the unharvested reference catchment across all sampled flow conditions (freshet, precipitation events, baseflow, and fall). In contrast, a consistent, concurrent increase in stream DOC export was not observed, attributed to inter-catchment differences in streamflow whereby streamflow in C31 was generally less than that from C32. Although the results of this study support a detectable and persistent legacy impact of clearcut harvesting on stream-dissolved organic carbon at the Turkey Lakes Watershed, the magnitude of the impact was limited and likely does not represent a reasonable threat to downstream drinking water treatment operations at decadal scales. As the study catchments were similar in terms of the concentrations, spatial distribution, and hydrologic connectivity of DOC (evaluated via hillslope solute pool sampling, concentration–discharge regression analysis, and the potassium silica molar ratio), this study was unable to determine the mechanism(s) responsible for the persistent post-harvest increase in stream DOC concentrations. This study highlights the need for further research into these mechanisms, potentially including the long-term decay of forest harvesting residues or shifts in species composition during regeneration. In particular, the inclusion of hillslope solute pool sampling, event-scale stream sampling, and flow path analysis in future BACI and paired catchment-based forest harvesting impact studies is warranted.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16192724/s1, Table S1: Descriptive Statistics for Hillslope Solute Pool DOC Concentrations; Figure S1: Inter-catchment variability in hillslope solute pool DOC concentrations (mg L−1) by sampling period; Figure S2: Inter-catchment variability in hillslope solute pool K:SiO2 ratios by sampling period; Figure S3: Intra-catchment variability in stream and hillslope solute pool K:SiO2 ratios by sampling period; Figure S4: Inter- and intra-catchment variability in stream and hillslope solute pool K+ concentrations by catchment and sampling period; Figure S5: Inter- and intra-catchment variability in stream and hillslope solute pool SiO2 concentrations by catchment and sampling period.

Author Contributions

Conceptualization, A.G., M.S., K.L.W., J.A.L., J.M.B. and M.B.E.; methodology, A.G., M.S., K.L.W., J.A.L. and J.M.B.; formal analysis, A.G. and M.S.; investigation, A.G., M.S., K.L.W., J.A.L. and J.M.B.; resources, M.S., K.L.W., J.A.L. and J.M.B.; data curation, A.G., M.S. and J.A.L.; writing—original draft preparation, A.G. and M.S.; writing—review and editing, A.G., M.S., K.L.W., J.A.L., J.M.B. and M.B.E.; visualization, A.G.; supervision, M.S., K.L.W. and M.B.E.; project administration, A.G., M.S. and K.L.W.; funding acquisition, M.S., K.L.W. and M.B.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Canadian Forest Service’s Sustainable Forest Management program and the forWater NSERC Network for Forested Drinking Water Source Protection Technologies (NETGP-494312-16), a pan-Canadian interdisciplinary strategic network.

Data Availability Statement

Data supporting the reported results are with the authors and can be made available upon request.

Acknowledgments

This research was conducted on the traditional territory of the Batchewana First Nation. The authors acknowledge with gratitude the field, lab, and technical contributions of the following individuals: Will Fines, Cory Chessum, Shelby Robertson, Kristi Broad, Jaime Broad, Laura Hawdon, Danielle Hudson, Stephanie Nelson, Linda Vogel, and Olivia Fines. The operation and maintenance of the Turkey Lakes Watershed is conducted by Natural Resources Canada, Environment and Climate Change Canada, and Fisheries and Oceans Canada in cooperation with the Ontario Ministry of Natural Resources and Forestry.

Conflicts of Interest

The authors declare no conflicts of interest.

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Water 16 02724 g001
Figure 1. Study Site and Instrumentation.
Figure 1. Study Site and Instrumentation.
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Figure 2. Study period streamflow (mm) and precipitation (mm) at 10 min intervals. Dashed vertical lines delineate the end of the freshet sampling period (leftmost) and the start of the fall sampling period (rightmost). Gaps in the streamflow record for C31 are due to instrument malfunction.
Figure 2. Study period streamflow (mm) and precipitation (mm) at 10 min intervals. Dashed vertical lines delineate the end of the freshet sampling period (leftmost) and the start of the fall sampling period (rightmost). Gaps in the streamflow record for C31 are due to instrument malfunction.
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Figure 3. (a) Inter-catchment variability in stream DOC concentration by flow condition. (b) Intra-catchment variability in stream DOC concentration by flow condition. (c) Inter-catchment variability in stream DOC export by flow condition. (d) Intra-catchment variability in stream DOC export by flow condition. The 25th, 50th, and 75th percentiles are shown by solid horizontal lines. Means are shown by dotted horizontal lines. Whiskers indicate maximum and minimum values. Open circles represent individual data points. Asterisks represent the level of statistical significance for the Mann–Whitney U test for inter-catchment differences in DOC concentration (a) and export (c) and the Kruskal–Wallis test for intra-catchment differences in DOC concentration (b) and export (d). **: p ≤ 0.01, ***: p ≤ 0.001, ****: p ≤ 0.0001.
Figure 3. (a) Inter-catchment variability in stream DOC concentration by flow condition. (b) Intra-catchment variability in stream DOC concentration by flow condition. (c) Inter-catchment variability in stream DOC export by flow condition. (d) Intra-catchment variability in stream DOC export by flow condition. The 25th, 50th, and 75th percentiles are shown by solid horizontal lines. Means are shown by dotted horizontal lines. Whiskers indicate maximum and minimum values. Open circles represent individual data points. Asterisks represent the level of statistical significance for the Mann–Whitney U test for inter-catchment differences in DOC concentration (a) and export (c) and the Kruskal–Wallis test for intra-catchment differences in DOC concentration (b) and export (d). **: p ≤ 0.01, ***: p ≤ 0.001, ****: p ≤ 0.0001.
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Figure 4. Intra-catchment variability in hillslope solute pool DOC concentration by sampling period. The 25th, 50th, and 75th percentiles are shown by horizontal lines. Whiskers indicate range. For all asterisks, *: p ≤ 0.05, ***: p ≤ 0.001, ****: p ≤ 0.0001 (Mann–Whitney U test). Asterisks in the freshet and fall sampling periods denote statistically significant differences relative to stream samples (black = “greater than”, brown = “less than”). Asterisks in the intermediate sampling period denote statistically significant differences relative to baseflow stream samples (black = “greater than”, brown = “less than”). Circles in the intermediate sampling period denote statistically significant differences (Mann–Whitney U test) relative to event (A–D) stream samples (°: p ≤ 0.05, °°: p ≤ 0.01, °°°°: p ≤ 0.0001; black = “greater than”, brown = “less than”).
Figure 4. Intra-catchment variability in hillslope solute pool DOC concentration by sampling period. The 25th, 50th, and 75th percentiles are shown by horizontal lines. Whiskers indicate range. For all asterisks, *: p ≤ 0.05, ***: p ≤ 0.001, ****: p ≤ 0.0001 (Mann–Whitney U test). Asterisks in the freshet and fall sampling periods denote statistically significant differences relative to stream samples (black = “greater than”, brown = “less than”). Asterisks in the intermediate sampling period denote statistically significant differences relative to baseflow stream samples (black = “greater than”, brown = “less than”). Circles in the intermediate sampling period denote statistically significant differences (Mann–Whitney U test) relative to event (A–D) stream samples (°: p ≤ 0.05, °°: p ≤ 0.01, °°°°: p ≤ 0.0001; black = “greater than”, brown = “less than”).
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Figure 5. (a) ln (DOC)–ln(Q) regression relationships by flow condition. For daily composite samples collected during the freshet and fall sampling periods, Q refers to the mean discharge for the sample collection date (L s−1). For samples collected during baseflow and precipitation events A–D, Q refers to instantaneous discharge (L s−1). (b) Slope of ln (DOC)–ln(Q) relationships vs. the ratio of the coefficient of variation of DOC concentration to the coefficient of variation of discharge by catchment and flow condition. The solid grey lines represent theoretical bounds described by [66]. Dotted lines and text annotations illustrate the conceptual categories as described in Table 2.
Figure 5. (a) ln (DOC)–ln(Q) regression relationships by flow condition. For daily composite samples collected during the freshet and fall sampling periods, Q refers to the mean discharge for the sample collection date (L s−1). For samples collected during baseflow and precipitation events A–D, Q refers to instantaneous discharge (L s−1). (b) Slope of ln (DOC)–ln(Q) relationships vs. the ratio of the coefficient of variation of DOC concentration to the coefficient of variation of discharge by catchment and flow condition. The solid grey lines represent theoretical bounds described by [66]. Dotted lines and text annotations illustrate the conceptual categories as described in Table 2.
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Figure 6. (a) Inter-catchment variability in stream K:SiO2 molar ratios, K+ concentrations, and SiO2 concentrations under freshet, intermediate baseflow, intermediate precipitation event (A–D), and fall sampling period flow conditions. (b) Intra-catchment variability in stream K:SiO2 molar ratios, K+ concentrations, and SiO2 concentrations under freshet, intermediate baseflow, intermediate precipitation event (A–D), and fall sampling period flow conditions. The 25th, 50th, and 75th percentiles are shown by horizontal lines. Whiskers indicate maximum and minimum values. Open circles represent individual data points. Asterisks represent the level of statistical significance for (a) Mann–Whitney U test and (b) Kruskal–Wallis tests. *: p ≤ 0.05, ***: p ≤ 0.001, ****: p ≤ 0.0001.
Figure 6. (a) Inter-catchment variability in stream K:SiO2 molar ratios, K+ concentrations, and SiO2 concentrations under freshet, intermediate baseflow, intermediate precipitation event (A–D), and fall sampling period flow conditions. (b) Intra-catchment variability in stream K:SiO2 molar ratios, K+ concentrations, and SiO2 concentrations under freshet, intermediate baseflow, intermediate precipitation event (A–D), and fall sampling period flow conditions. The 25th, 50th, and 75th percentiles are shown by horizontal lines. Whiskers indicate maximum and minimum values. Open circles represent individual data points. Asterisks represent the level of statistical significance for (a) Mann–Whitney U test and (b) Kruskal–Wallis tests. *: p ≤ 0.05, ***: p ≤ 0.001, ****: p ≤ 0.0001.
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Figure 7. Intra-catchment variability in stream and hillslope solute pool K:SiO2 ratios by sampling period. The 25th, 50th, and 75th percentiles are shown by horizontal lines. Whiskers indicate range. The reader is encouraged to note the differences in the y-axis. For all asterisks, *: p ≤ 0.05, **: p ≤ 0.01, ***: p ≤ 0.001, ****: p ≤ 0.0001 (Mann–Whitney U test). Asterisks in the freshet and fall sampling periods denote statistically significant differences relative to stream samples (black = “greater than”, brown = “less than”); asterisks in the intermediate sampling period denote statistically significant differences relative to baseflow stream samples (black = “greater than”, brown = “less than”); circles in the intermediate sampling period denote statistically significant differences relative to event (A–D) stream samples (°: p ≤ 0.05, °°°°: p ≤ 0.0001; black = “greater than”, brown = “less than”).
Figure 7. Intra-catchment variability in stream and hillslope solute pool K:SiO2 ratios by sampling period. The 25th, 50th, and 75th percentiles are shown by horizontal lines. Whiskers indicate range. The reader is encouraged to note the differences in the y-axis. For all asterisks, *: p ≤ 0.05, **: p ≤ 0.01, ***: p ≤ 0.001, ****: p ≤ 0.0001 (Mann–Whitney U test). Asterisks in the freshet and fall sampling periods denote statistically significant differences relative to stream samples (black = “greater than”, brown = “less than”); asterisks in the intermediate sampling period denote statistically significant differences relative to baseflow stream samples (black = “greater than”, brown = “less than”); circles in the intermediate sampling period denote statistically significant differences relative to event (A–D) stream samples (°: p ≤ 0.05, °°°°: p ≤ 0.0001; black = “greater than”, brown = “less than”).
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Table 1. Physiographic characteristics of the study catchments 1.
Table 1. Physiographic characteristics of the study catchments 1.
Catchment CharacteristicC32C31
Harvest HistoryUnharvestedClearcut
Area (ha)6.744.62
Relief (m)10759
Weir Elevation (m.a.s.l.)352359
Average Slope (°)17.4914.61
AspectSWSW
Wetland Area (%)13
Note: 1 Adapted from [53].
Table 2. C–Q analytical framework (adapted from [62,65,69]).
Table 2. C–Q analytical framework (adapted from [62,65,69]).
ln (DOC)–ln(Q) SlopeCVDOC/CVQInterpretation
0 < slope < |0.1| or p > 0.05≥0.5Chemostochastic DOC behavior whereby DOC varies independently of Q
0 < slope < |0.1| or p > 0.05≤0.5Chemostatic DOC behavior, indicative of a relatively homogenous or uniform source whereby changes in hydrologic connectivity and flow paths do not impact DOC concentration
Slope > 0.1Not applicableFlushing DOC behavior indicative of a transport-limited export regime
Slope < −0.1Not applicableDilution DOC behavior indicative of a source-limited export regime
Table 3. Precipitation and streamflow by flow condition.
Table 3. Precipitation and streamflow by flow condition.
Flow ConditionDateTotal Precipitation (mm)Total Streamflow
C32 (mm)		Total Streamflow
C31 (mm)
Calendar Year1 January 2021 to 31 December 20211183.9424.2320.3
Freshet25 March 2021 to 9 May 2021116.2150.0132.9
Event A24 May 2021 to 25 May 202125.41.62.0
Event B21 June 2021 to 22 June 202118.90.60.5
Event C24 June 2021 to 26 June 202113.71.82.5
Event D15 July 2021 to 16 July 202117.20.70.4
Fall9 October 2021 to 30 October 202197.927.418.5
Table 4. Stream DOC concentrations (mg L−1) by catchment and flow condition.
Table 4. Stream DOC concentrations (mg L−1) by catchment and flow condition.
CatchmentFreshetBaseflowEvent AEvent BEvent CEvent DFallAll
nC3246202419272122179
C315013241427822158
minimumC320.931.381.961.671.671.311.630.93
C311.411.823.032.632.703.552.401.41
maximumC325.132.654.642.743.983.794.815.13
C314.814.486.055.865.926.266.326.32
meanC322.501.752.812.222.562.372.532.42
C313.042.614.813.823.444.483.623.56
medianC322.311.692.662.232.442.462.492.36
C313.062.465.033.653.184.103.503.38
SDC320.760.290.750.350.510.750.700.69
C310.660.670.840.960.801.020.811.02
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Gray, A.; Stone, M.; Webster, K.L.; Leach, J.A.; Buttle, J.M.; Emelko, M.B. Seasonal- and Event-Scale Stream DOC Dynamics in Northern Hardwood-Dominated Headwater Catchments of Contrasting Forest Harvest History. Water 2024, 16, 2724. https://doi.org/10.3390/w16192724

AMA Style

Gray A, Stone M, Webster KL, Leach JA, Buttle JM, Emelko MB. Seasonal- and Event-Scale Stream DOC Dynamics in Northern Hardwood-Dominated Headwater Catchments of Contrasting Forest Harvest History. Water. 2024; 16(19):2724. https://doi.org/10.3390/w16192724

Chicago/Turabian Style

Gray, Annie, Micheal Stone, Kara L. Webster, Jason A. Leach, James M. Buttle, and Monica B. Emelko. 2024. "Seasonal- and Event-Scale Stream DOC Dynamics in Northern Hardwood-Dominated Headwater Catchments of Contrasting Forest Harvest History" Water 16, no. 19: 2724. https://doi.org/10.3390/w16192724

APA Style

Gray, A., Stone, M., Webster, K. L., Leach, J. A., Buttle, J. M., & Emelko, M. B. (2024). Seasonal- and Event-Scale Stream DOC Dynamics in Northern Hardwood-Dominated Headwater Catchments of Contrasting Forest Harvest History. Water, 16(19), 2724. https://doi.org/10.3390/w16192724

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