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Globally significant yields of dissolved organic carbon from small watersheds of the Pacific coastal temperate rainforest

Authors:
  • Skeena Fisheries Commission
  • Hakai Institute and Simon Fraser University

Abstract and Figures

The perhumid region of the Pacific coastal temperate rainforest of North America (PCTR) is one of the wettest places on Earth and contains numerous small catchments that discharge freshwater and high concentrations of dissolved organic carbon (DOC) directly to the coastal ocean. However, empirical data on the flux and composition of DOC exported from these watersheds is scarce. We established monitoring stations at the outlets of seven catchments on Calvert and Hecate Islands, British Columbia, which represent the rain dominated outer-coast region of the PCTR. Over several years, we measured stream discharge, stream water DOC concentration, and stream water dissolved organic matter (DOM) composition. Discharge and DOC concentrations were used to calculate DOC fluxes and yields, and DOM composition was examined using absorbance and fluorescence spectroscopy, including parallel factor analysis (PARAFAC). The areal estimate of annual DOC yield in water year 2015 was 33.3 Mg C km−2 yr−1, with individual watersheds ranging from an average of 24.1–37.7 Mg C km−2 yr−1. This represents some of the highest DOC yields in the world exported to the ocean. We observed strong seasonality in the quantity and composition of exports, with the majority of DOC export occurring during the extended wet period of the year (September–April). Stream flow from catchments reacted quickly to rain inputs, resulting in rapid flushing of relatively fresh, highly terrestrial-like DOM. DOC concentration and measures of DOM composition were correlated with watershed attributes, including the extent of lakes and wetlands, and thickness of organic and mineral soils. Our discovery of high DOC yields from these small catchments on the outer-coast of the temperate rainforest is especially compelling as they represent the delivery of relatively fresh, highly terrestrial organic matter directly to the coastal ocean. This suggests that this coastal margin may play an important role in the global processing of carbon and in linking terrestrial carbon to marine ecosystems.
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Globally significant yields of dissolved organic carbon from small watersheds of the Pacific 1!
coastal temperate rainforest. 2!
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Allison A. Oliver1,2, Suzanne E. Tank1,2, Ian Giesbrecht2, Maartje C. Korver2, William C. 4!
Floyd3,4,2, Paul Sanborn5,2, Chuck Bulmer6, Ken P. Lertzman7,2 5!
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1University of Alberta, Department of Biological Sciences, CW 405, Biological Sciences Bldg., 7!
University of Alberta, Edmonton, Alberta, T6G 2E9, Canada 8!
2Hakai Institute, Tula Foundation, Box 309, Heriot Bay, British Columbia, V0P 1H0, Canada 9! 3Ministry of Forests, Lands and Natural Resource Operations, 2100 Labieux Rd, Nanaimo, BC, 10!
V9T 6E9, Canada 11!4Vancouver Island University, 900 Fifth Street, Nanaimo, BC, V9R 5S5, Canada 12!
5Ecosystem Science and Management Program, University of Northern British Columbia, 3333 13!
University Way, Prince George, BC, V2N 4Z9, Canada
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6BC Ministry of Forests Lands and Natural Resource Operations, 3401 Reservoir Rd, Vernon, 15!
BC, V1B 2C7, Canada 16!
7School of Resource and Environmental Management, Simon Fraser University, TASC 1- Room 17!
8405, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada 18!
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Corresponding author: aaoliver@ualberta.ca 21!
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Abstract 34!
The perhumid region of the Pacific coastal temperate rainforest of North America 35!
(PCTR) is one of the wettest places on Earth and contains numerous small catchments that 36!
discharge freshwater and high concentrations of dissolved organic carbon (DOC) directly to the 37!
coastal ocean. However, empirical data on the flux and composition of DOC exported from these 38!
watersheds is scarce. We established monitoring stations at the outlets of seven catchments on 39!
Calvert and Hecate Islands, British Columbia, which represent the rain dominated outer-coast 40!
region of the PCTR. Over several years, we measured stream discharge, stream water DOC 41!
concentration, and stream water dissolved organic matter (DOM) composition. Discharge and 42!
DOC concentrations were used to calculate DOC fluxes and yields, and DOM composition was 43!
examined using absorbance and fluorescence spectroscopy, including parallel factor analysis 44!
(PARAFAC). The areal estimate of annual DOC yield in water year 2015 was 33.3 Mg C km-2 45!
yr-1, with individual watersheds ranging from an average of 24.1-37.7 Mg C km-2 yr-1. This 46!
represents some of the highest DOC yields in the world exported to the ocean. We observed 47!
strong seasonality in the quantity and composition of exports, with the majority of DOC export 48!
occurring during the extended wet period of the year (September-April). Stream flow from 49!
catchments reacted quickly to rain inputs, resulting in rapid flushing of relatively fresh, highly 50!
terrestrial-like DOM. DOC concentration and measures of DOM composition were correlated 51!
with watershed attributes, including the extent of lakes and wetlands, and thickness of organic 52!
and mineral soils. Our discovery of high DOC yields from these small catchments on the outer-53!
coast of the temperate rainforest is especially compelling as they represent the delivery of 54!
relatively fresh, highly terrestrial organic matter directly to the coastal ocean. This suggests that 55!
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
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Author(s) 2017. CC-BY 3.0 License.
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this coastal margin may play an important role in the global processing of carbon and in linking 56!
terrestrial carbon to marine ecosystems. 57!
1. Introduction 58!
Freshwater aquatic ecosystems process and transport a significant amount of carbon 59!
(Cole et al., 2007; Aufdenkampe et al., 2011; Raymond et al., 2013). Export via running waters 60!
is an important mechanism in the removal of carbon from watersheds. Globally, riverine export 61!
is estimated to deliver around 0.9 Pg C yr-1 from land to the coastal ocean (Cole et al., 2007), 62!
with typically >50% quantified as dissolved organic carbon (DOC)(Meybeck, 1982; Ludwig et 63!
al., 1996; Alvarez-Cobelas et al., 2010; Mayorga et al., 2010). Rivers draining coastal watersheds 64!
serve as conduits of DOC from terrestrial and freshwater sources to marine environments 65!
(Mulholland and Watts, 1982; Kling et al., 2000; McClelland et al., 2014) and can have 66!
important implications for coastal carbon cycling, biogeochemical interactions, ecosystem 67!
productivity, and food webs (Hopkinson et al., 1998; Tallis, 2009; Tank et al., 2012; Regnier et 68!
al., 2013). In regions where empirical data are currently scarce, quantifying land-to-ocean DOC 69!
export is a clear priority for improving the accuracy of watershed and coastal carbon models. The 70!
transfer of water and organic matter from watersheds to the coastal ocean may represent an 71!
important pathway for carbon cycling and ecological subsidies between ecosystems. Therefore, 72!
better understanding of these linkages is needed for constraining predictions of ecosystem 73!
productivity and food webs in response to perturbations such as climate change. 74!
While quantifying DOC flux within and across systems is required for understanding the 75!
magnitude of carbon exchange, the composition of DOC (as dissolved organic matter, or DOM) 76!
is also important for determining the ecological significance of carbon exported from coastal 77!
watersheds. The aquatic DOM pool is a complex mixture that reflects both source material and 78!
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processing along the watershed terrestrial-aquatic continuum, and as a result can show 79!
significant spatial and temporal variation (Hudson et al., 2007; Fellman et al., 2009a; Graeber et 80!
al., 2012; Wallin et al., 2015). Both DOC concentration and DOM composition can serve as 81!
indicators of watershed characteristics (Koehler et al., 2009), hydrologic flow paths (Johnson et 82!
al., 2011; Helton et al., 2015), and watershed biogeochemical processes (Emili and Price, 2013). 83!
DOM composition can also influence its role in downstream processing and ecological function, 84!
such as susceptibility to biological (Judd et al., 2006) and physiochemical interactions 85!
(Yamashita and Jaffé, 2008). 86!
The Pacific coastal temperate rainforests of North America extend from the Gulf of 87!
Alaska, through British Columbia, to Northern California and span a wide range of precipitation 88!
and climate regimes. The wettest part of this region is described as the “perhumid” zone and is 89!
characterized by annual precipitation >1400mm, largely composed of rain and transient snow 90!
(Alaback, 1996)(Fig. 1). The perhumid Pacific coastal temperate rainforest (PCTR) extends 91!
from southeast Alaska through the outer coast of central British Columbia and contains forests 92!
and soils that have accumulated large amounts of carbon and store substantial quantities of 93!
organic matter relative to most other temperate forests (Gorham et al., 2012). Due to high 94!
precipitation and close proximity to the coast, this area represents a potential hotspot for the 95!
transport and metabolism of carbon across the land-to-ocean continuum, and quantifying these 96!
fluxes is pertinent for understanding global carbon cycling. Previous studies have shown that 97!
streams in this region can contain high concentrations of DOC (Fellman et al., 2010; D’Amore et 98!
al., 2015a) and high DOC yields (D’Amore et al., 2015b; D’Amore et al., 2016) but these studies 99!
have largely focused on southeast Alaska and relatively little is known about carbon exports 100!
from the perhumid PCTR of British Columbia, an area of approximately 97,824 km2 (calculated 101!
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from spatial data adapted from Wolf et al., 1995). In addition, due to the logistical challenges of 102!
conducting fieldwork in this remote region, previous studies have derived DOC flux from point 103!
measurements of DOC concentrations and modelled river discharge (e.g., Mayorga et al., 2010; 104!
Stackpoole et al., 2016). In this study, we conduct the first field-based estimates of DOC flux 105!
from relatively undeveloped perhumid Pacific coastal temperature rainforest watersheds of the 106!
British Columbia outer-coast. We examine temporal and spatial trends in flux, and describe 107!
compositional characteristics of DOM exported from these watersheds to the coastal ocean. 108!
Finally, we describe relationships between measures of DOC quantity, DOM character, and 109!
watershed attributes. 110!
2. Methods 111!
2.1 Study Sites 112!
Study sites are located on northern Calvert Island and adjacent Hecate Island on the 113!
central coast of British Columbia, Canada (Lat 51.650, Long -128.035; Fig. 1). Average annual 114!
precipitation and air temperature at sea level from 1981-2010 was 3356 mm yr-1 and 8.4 °C 115!
(average annual min= 0.9°C, average annual max= 17.9°C) (available online at 116!
http://www.climatewna.com/; Wang et al., 2012), with precipitation dominated by rain, and 117!
winter snowpack persisting only at higher elevations. Soils overlying the granodiorite bedrock 118!
(Roddick, 1996) are usually < 1 m thick, and have formed in sandy colluvium and patchy 119!
morainal deposits, with limited areas of coarse glacial outwash. Chemical weathering and 120!
organic matter accumulation in the cool, moist climate have produced soils dominated by 121!
Podzols and Folic Histosols, with Hemists up to 2 m thick in depressional sites (IUSS Working 122!
Group WRB, 2015). The landscape is comprised of a mosaic of ecosystem types, including 123!
exposed bedrock, extensive wetlands, bog forests and woodlands, with organic rich soils (Green, 124!
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2014; Thompson et al., 2016). Forest stands are generally short with open canopies reflecting the 125!
lower productivity of the outer-coast forests compared to the rest of the perhumid rainforest 126!
(Banner et al., 2005). Dominant trees are western red cedar, yellow cedar, shore pine and western 127!
hemlock with composition varying across topographic and edaphic gradients. Widespread 128!
understory plants include several bryophytes, salal, deer fern, and tufted clubrush. Wetland 129!
plants are locally abundant including diverse Sphagnum mosses and sedges. Although the 130!
watersheds have no history of mining or industrial logging, archaeological evidence suggests that 131!
humans have occupied this landscape for at least 13,000 years (McLaren et al., 2014). This 132!
occupation has had a local effect on forest productivity near habituation sites (Trant et al., 2016) 133!
and on fire regimes (Hoffman et al., 2016). We selected seven watersheds with streams draining 134!
directly into the ocean (Fig. 1). These numbered watersheds (626, 693, 703, 708, 819 844, and 135!
1015) range in size (3.2 to 12.8 km2) and topography (maximum elevation 160 m to 1012 m), are 136!
variably affected by lakes (0.3 – 9.1% lake coverage), and – as is characteristic of the outer coast 137!
– have a high degree of wetland coverage (24– 50%)(Table 1). 138!
2.2 Soils and watershed characteristics 139!
Watersheds and streams were delineated using a 3 m resolution digital elevation model 140!
(DEM) derived from airborne laser scanning (LiDAR) (Gonzalez Arriola et al., 2015). We then 141!
used GIS to summarize watershed characteristics for each watershed polygon and for all 142!
watersheds combined (Table 1). Topographic measures were estimated from the DEM (Gonzalez 143!
Arriola et al., 2015); lake and wetland cover from Province of British Columbia Terrestrial 144!
Ecosystem Mapping (TEM) (Green, 2014); soil material thickness from unpublished digital soil 145!
maps (Supplemental S1).We recorded thickness of organic soil material, thickness of mineral 146!
soil material, and total soil depth to bedrock at a total of 353 field sites. In addition to field-147!
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sampled sites, 40 sites with exposed bedrock (0 cm soil depth) were located using aerial 148!
photography. Soil thicknesses were combined with a suite of topographic, vegetation, and 149!
remote sensing (LiDAR and RapidEye satellite imagery) data for each sampling point and used 150!
to train a random forest model (randomForest package in R; Liaw and Wiener, 2002) that was 151!
used to predict soil depth values. Soil material thicknesses were then averaged for each 152!
watershed (Table 1). For additional details on field site selection and methods used for soil 153!
depth predictions, see Supplemental S1.1. 154!
2.3 Sample Collection and Analysis 155!
From May 2013 to July 2016, we collected stream water grab samples from each 156!
watershed stream outlet every 2-3 weeks (ntotal= 402), with less frequent sampling (~monthly) 157!
during winter (Fig. 1). All samples were filtered in the field (Millipore Millex-HP Hydrophilic 158!
PES 0.45µm) and kept in the dark, on ice until analysis. DOC samples were filtered into 60mL 159!
amber glass bottles and preserved with 7.5M H3PO4. Fe samples were filtered into 125mL 160!
HDPE bottles and preserved with 8M HNO3. DOC and Fe samples were analyzed at the BC 161!
Ministry of the Environment Technical Services Laboratory (Victoria, BC, Canada). DOC 162!
concentrations were determined on a TOC analyzer (Aurora 1030; OI-Analytical) using wet 163!
chemical oxidation with persulfate followed by infrared detection of CO2. Fe concentrations 164!
were determined on a dual-view ICP-OES spectrophotometer (Prodigy; Teledyne Leeman Labs) 165!
using a Seaspray pneumatic nebulizer. 166!
In May 2014, we began collecting stream samples for stable isotopic composition of δ13C 167!
in DOC (DOδ13C; n= 173) and optical characterization of DOM using absorbance spectroscopy 168!
(n= 259). Beginning in January 2016, we also analyzed samples using fluorescence 169!
spectroscopy (see section 2.6). Samples collected for DOδ13C were filtered into 40mL EPA glass 170!
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vials and preserved with H3PO4. DOδ13C samples were analyzed at GG Hatch Stable Isotope 171!
Laboratory (Ottawa, ON, Canada) using high temperature combustion (TIC-TOC Combustion 172!
Analyser Model 1030; OI Analytical) coupled to a continuous flow isotope ratio mass 173!
spectrometry (Finnigan Mat DeltaPlusXP; Thermo Fischer Scientific)(Lalonde et al. 2014). 174!
Samples analyzed for optical characterization using absorbance and fluorescence were filtered 175!
into 125mL amber HDPE bottles and analyzed at the Hakai Institute (Calvert Island, BC, 176!
Canada) within 24 hours of collection. 177!
2.4 Hydrology: Precipitation and Stream Discharge 178!
We measured precipitation using a TB4-L tipping bucket rain gauge with a 0.2mm 179!
resolution (Campbell Scientific Ltd.) located in watershed 708 (elevation= 16m a.s.l). The rain 180!
gauge was calibrated twice per year using a Field Calibration Device, model 653 (HYQUEST 181!
Solutions Ltd). 182!
We determined continuous stream discharge for each watershed by developing stage 183!
discharge rating curves at fixed hydrometric stations situated in close proximity to each stream 184!
outlet. Sites were located above tidewater influence and were selected based on favourable 185!
conditions (i.e., channel stability and stable hydraulic conditions) for the installation and 186!
operation of pressure transducers to measure stream stage. From August 2014 to May 2016 (21 187!
months), we measured stage every 5 minutes using an OTT PLS –L (OTT Hydromet, Colorado, 188!
USA) pressure transducer (0-4m range SDI-12) connected to a CR1000 (Campbell Scientific, 189!
Edmonton, Canada) data logger. Stream discharge was measured over various intervals using 190!
either the velocity area method (for flows < 0.5 m3s-1; ISO Standard 9196:1992, ISO Standard 191!
748:2007) or salt dilution (for flows > 0.5 m3s-1; Moore, 2005). Rating curves were developed 192!
using the relationship between stream stage height and stream discharge (Supplemental S2). 193!
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2.5 DOC flux 194!
From October 1, 2014 to April 30, 2016, we estimated DOC flux for each watershed 195!
using measured DOC concentrations (n= 224) and continuous discharge recorded at 15-minute 196!
intervals. The watersheds in this region respond rapidly to rain inputs and as a result DOC 197!
concentrations are highly variable. To address this variability, routine DOC concentration data 198!
(as described in section 2.2) were supplemented with additional grab samples (n= 21) collected 199!
around the peak of the hydrograph during several high flow events throughout the year. We 200!
performed watershed-specific estimates of DOC flux using the “rloadest” package (Lorenz et al., 201!
2015) in R (version 3.2.5, R Core Team, 2016), which replicates functions developed in the U.S. 202!
Geological Survey load-estimator program, LOADEST (Runkel et al., 2004). LOADEST is a 203!
multiple-regression adjusted maximum likelihood estimation model that calibrates a regression 204!
between measured constituent values and stream flow across seasons and time and then fits it to 205!
combinations of coefficients representing nine predetermined models of constituent flux. To 206!
account for potentially small sample size, the best model was selected using the second order 207!
Akaike Information Criterion (AICc). Input data were log-transformed to avoid bias and centered 208!
to reduce multicollinearity. For additional details on model selection, see Supplemental Table 209!
S3.1. 210!
2.6 Optical characterization of DOM 211!
Prior to May 2014, absorbance measures of water samples (n= 99) were conducted on a 212!
Varian Cary-50 (Varian, Inc.) spectrophotometer at the BC Ministry of the Environment 213!
Technical Services Laboratory (Victoria, BC, Canada) and used to determine specific UV 214!
absorption at 254 nm (SUVA254). After May 2014, we determined optical characterization of 215!
DOM by absorbance and fluorescence spectroscopy at the Hakai Institute field station (Calvert 216!
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Island, BC, Canada) using an Aqualog fluorometer (Horiba Scientific, Edison, New Jersey, 217!
USA). Samples were run in 1 cm quartz cells and strongly absorbing samples were diluted prior 218!
to analysis to avoid excessive inner filter effects (Lakowicz, 1999). We used absorbance scans 219!
to determine SUVA254 as well as the spectral slope ratio (SR). SUVA254 has been shown to 220!
positively correlate with increasing molecular aromaticity associated with the fulvic acid fraction 221!
of DOM (Weishaar et al., 2003), and is calculated by dividing the Decadic absorption coefficient 222!
at 254 nm by DOC concentration (mg C L-1). To account for potential Fe interference with 223!
absorbance values, we corrected SUVA254 values by Fe concentration according the method 224!
described in Poulin et al., (2014). SR has been shown to negatively correlate with molecular 225!
weight (Helms et al., 2008), and is calculated as the ratio of the spectral slope from 275 nm to 226!
295 nm (S275-295) to the spectral slope from 350 nm to 400 nm (S350-400). 227!
We measured excitation and emission spectra (as excitation emission matrices, EEMs) on 228!
samples every three weeks from January to July 2016 (n= 63) and used the Horiba Aqualog to 229!
apply the appropriate instrument corrections for excitation and emission, inner filter effects, and 230!
Raman signal calibration. We calculated the Fluorescence Index and Freshness Index for each 231!
EEM. The Fluorescence Index is often used to indicate DOM source, where higher values are 232!
more indicative of microbial-derived sources of DOM and lower values indicate more terrestrial-233!
derived sources (McKnight et al., 2001), and is calculated as the ratio of emission intensity at 234!
450 nm to 500 nm, at an excitation of 370 nm. The Freshness Index is used to indicate the 235!
contribution of authochthonous or recently microbial-produced DOM, with higher values 236!
suggesting greater autochthony (i.e., microbial inputs), and is calculated as the ratio of emission 237!
intensity at 380 nm to the maximum emission intensity between 420 nm and 435 nm, at 238!
excitation 310 nm (Wilson and Xenopoulos, 2009). 239!
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To further characterize features of DOM composition, we performed PARAFAC analysis 240!
using EEMs data within the drEEM toolbox for Matlab (Mathworks, MA, USA) (Murphy et al., 241!
2013). PARAFAC is a statistical technique used to decompose the complex mixture of the 242!
fluorescing DOM pool into quantifiable, individual components (Stedmon et al., 2003). We 243!
detected a total of six unique components, and validated the model using core consistency and 244!
split-half analysis (Murphy et al., 2013; Stedmon and Bro, 2008). Components with similar 245!
spectra from previous studies were identified using the online fluorescence repository, 246!
OpenFluor (Murphy et al., 2014), and additional components with similar peaks were identified 247!
through literature review. Since the actual chemical structure of fluorophores is unknown, we 248!
used the concentration of each fluorophore as maximum fluorescence of excitation and emission 249!
in Raman Units (Fmax) to derive the percent contribution of each fluorophore component to total 250!
fluorescence. 251!
2.7 Data analysis and statistics 252!
We evaluated relationships between stream water DOC and watershed characteristics by 253!
relating DOC concentration and measures of DOM character to catchment attributes using 254!
redundancy analysis (RDA; type 2 scaling) in the package rdaTest (Legendre and Durand, 2014) 255!
in R (version 3.2.2, R Core Team, 2015). To maximize the amount of information available, we 256!
performed RDA analysis on samples collected from January to July 2016, and therefore included 257!
all parameters of optical characterization (i.e., all PARAFAC components and spectral indices). 258!
We assessed the collinearity of DOM compositional variables using a variance inflation factor 259!
(VIF) criteria of > 10, which resulted in the removal of PARAFAC components C2, C3, and C5 260!
prior to RDA analysis. Catchment attributes for each watershed included average slope, percent 261!
area of lakes, percent area of wetlands, average depth of mineral soil, and average depth of 262!
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organic soil. Relationships between variables were linear, so no transformations were necessary 263!
and variables were standardized prior to analysis. To account for repeat monthly measures per 264!
watershed and potential temporal correlation associated with monthly sampling, we included 265!
sample month as a covariable (“partial-RDA”). To test whether the RDA axes significantly 266!
explained variation in the dataset, we compared permutations of residuals using ANOVA (9,999 267!
iterations; test.axes function of rdaTest). 268!
3. Results 269!
3.1 Hydrology 270!
Annual precipitation for both water years (WY2015= 2661 mm; WY2016= 2587 mm), 271!
was lower than the predicted historical mean annual precipitation estimated at the location of our 272!
rain gauge (Fig. 1), which was approximately 2890 mm yr-1 for the years 1981-2010 (Wang et 273!
al., 2012; available at http://www.climatewna.com/). It is worth noting that annual precipitation 274!
at our rain gauge location (elevation = 16 m) is substantially lower than the average amount 275!
received at higher elevations, which for years 1981-2010 was approximately 5027 mm yr-1 at an 276!
elevation of 1000m within our study area. Annually, this area receives a very high amount of 277!
annual rainfall relative to most regions of the world (http://data.worldbank.org) but also 278!
experiences strong seasonal variation, with an extended wet period from fall through spring, and 279!
a much shorter, typically drier period during summer. In WY2015 and WY2016, 86-88% of the 280!
annual precipitation on Calvert Island occurred during the 8-months of wetter and cooler weather 281!
between September and April (~75% of the year), designated the “wet period” (WY2015 wet= 282!
2388 mm, average air temp= 7.97°C; WY2016 wet= 2235 mm; average air temp= 7.38°C). The 283!
remaining annual precipitation occurred during the drier and warmer summer months of May284!
August, designated the “dry period” (WY2015 dry= 314 mm, average air temp= 13.4°C; 285!
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WY2016 dry= 352 mm, average air temp= 13.1°C). Overall, although WY2015 was slightly 286!
wetter than WY2016, the two years were comparable in relative precipitation during the wet 287!
versus dry periods. 288!
Stream discharge (Q) responded rapidly to rain events and, as a result, closely tracked 289!
patterns in total precipitation, and exhibited clear seasonal patterns (Fig. 2). Similar to 290!
precipitation data, higher Q occurred during the wet versus the dry period. Total Q for all 291!
watersheds combined was 22% greater (range for individual watersheds= 4% to 27% greater in 292!
WY2015 versus WY2016) for the wet period of WY2015 (total Q= 223.02 * 106; range= 5.13 * 293!
106 – 111.51 * 106 m3) compared to the total Q for all watersheds in the wet period of WY2016 294!
(total Q= 182.89 * 106; range= 4.17 * 106 – 91.45 * 106 m3). 295!
3.2 Temporal and spatial patterns in DOC concentration and DOC flux 296!
Stream waters were high in DOC concentration relative to the global average 297!
concentrations in freshwater discharged directly to the ocean (average DOC for Calvert and 298!
Hecate Islands = 10.4 mg L-1, std= 3.8; average global DOC= ~ 6 mg L-1)(Meybeck, 1982; 299!
Harrison et al., 2005) (Table 1; Fig. 3). Q-weighted average DOC concentrations were higher 300!
than the average measured DOC concentrations (11.1 mg L-1, Table 2), and also resulted in 301!
slightly different ranking of the watersheds for highest to lowest DOC concentration. Within 302!
watersheds, flow-weighted DOC concentrations ranged from a low of 8.4 mg L-1 (watershed 303!
693) to a high of 19.3 mg L-1 (watershed 819). Variability tended to be higher in watersheds 304!
where DOC concentration was also high (watersheds 626, 819, and 844) and lower in watersheds 305!
with greater lake area (watersheds 1015 and 708)(Table 2; box plots, Figure 3). Low DOC 306!
concentration and variability in DOC concentrations were also observed for watershed 703, 307!
which lacks a high lake area but had the highest water yield as a result of having both the largest 308!
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total watershed area and the highest maximum elevation (resulting in greater precipitation 309!
delivered to the catchment). On an annual basis, DOC concentrations decreased through the wet 310!
period, and then increased through the dry period. 311!
Annual and monthly watershed DOC yields are presented in Table 1. For the total period 312!
of available Q (October 1, 2014 - April 30, 2016; 19 months), areal (all watersheds) DOC yield 313!
was 52.3 Mg C km-2 (95% CI= 45.7 to 68.2 Mg C km-2). For the complete water year of 2015, 314!
areal annual DOC yield was 33.3 Mg C km-2 yr-1 (95% CI= 28.9 to 38.1 Mg C km-2 yr-1). Total 315!
monthly rainfall was strongly correlated with monthly DOC yield (Fig. 4), and average monthly 316!
yield for the wet period (3.35 Mg C km-2 mo-1; 95% CI= 2.94 to 4.40 Mg C km-2 mo-1) was much 317!
greater than average monthly yield during the dry period (0.50 Mg C km-2 mo-1; 95% CI= 0.41 to 318!
0.62 Mg C km-2 mo-1). 319!
On a per-watershed basis, DOC load generally increased with total watershed area, but 320!
this pattern was not maintained for DOC yield (Fig. 5). During WY2015, per-watershed yields 321!
ranged from 24.1 to 43.6 Mg C km-2 (Table 1). Overall, 94% of the export in WY2015 occurred 322!
during the wet period, with a clear decrease in area-normalized export between WY2015 and 323!
WY2016 (Fig. 5). 324!
3.3 Temporal and spatial patterns in DOM composition 325!
Iron-corrected SUVA254 values were relatively high compared to the range typically 326!
found in surface waters (average SUVA254 for Calvert and Hecate Islands= 4.42 L mg-1 m-1, std= 327!
0.46; range of SUVA254 in surface waters = 1.0 to 5.0 L mg-1 m-1)(Spencer et al., 2012) 328!
suggesting DOM exported from these watersheds is comprised of highly aromatic carbon 329!
compounds. Values of SUVA254 were relatively consistent across watersheds, however there was 330!
a strong seasonal trend that countered seasonal trends in DOC concentration; SUVA254 values 331!
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generally increased over the wet period and decreased over the dry period (Fig. 3). In contrast to 332!
SUVA254, SR showed clear variation between watersheds, indicating systematic differences in the 333!
average molecular weight of the DOM pool between watersheds. Overall values of SR were low 334!
(average SR = 0.78, std= 0.04; range= 0.71 to 0.89) compared to the range typically observed in 335!
surface waters. This suggests that DOM was of high molecular weight, i.e., comprised of larger 336!
molecules that have not been chemically or biologically degraded through processes such as 337!
microbial utilization or photodegradation, and therefore are potentially more biologically 338!
available (Amon and Benner, 1996). Similar to SUVA254, SR also appeared to fluctuate 339!
seasonally, with values decreasing (increasing in molecular weight) during the wet season and 340!
showing higher, more variable values during the dry season. 341!
The stable isotopic composition of dissolved organic carbon (DOδ13C) was relatively 342!
similar across watersheds (average DOδ13C= -26.53‰, std= 0.36; range= -27.67‰ to -24.89‰) 343!
and exhibited some seasonal variation; values became slightly less depleted throughout the wet 344!
period relative to the dry period. Values for DOδ13C suggested that terrestrial carbon sources 345!
originating from C3 plants and soils were the dominant input to catchment stream water DOM 346!
(Finlay and Kendall, 2007). 347!
3.4 Characterization of DOM- PARAFAC 348!
PARAFAC analysis indicated that terrestrial-derived organic carbon dominated spectral 349!
signatures across watersheds and across time. Six fluorescence components were identified 350!
through PARAFAC (“C1” through “C6”)(Table 2). Additional details on PARAFAC results are 351!
provided in Supplemental Table S4.1, Fig. S4.2, and Fig. S4.3. Of the six components, four were 352!
found to have close spectral matches in the OpenFluor database (C1, C3, C5, C6; minimum 353!
similarity score > 0.95), while the other two (C2 and C4) were found to have similar peaks 354!
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represented in the literature. The first four components (C1 through C4) are described as 355!
terrestrial-derived and comprised the majority of total fluorescence across all watersheds (Fig. 6). 356!
C1 was by far the most dominant component in terms of percent contribution to total 357!
fluorescence, suggesting a high and consistent supply of humic-like terrestrial material that is 358!
relatively fresh (less-processed). Of the terrestrial-like components, C1, C2, and C4 exhibited 359!
similar patterns to each other in their contribution to total fluorescence (Fig. 6) (Supplemental 360!
Fig. S4.4), whereas component C3 appeared inversely related to the other terrestrial-like 361!
components and exhibited the lowest spatial variability in percent contribution to total 362!
fluorescence. Components C5 and C6 had spectral patterns indicative of autochthonous or 363!
microbial-like origins, with C6 being the only component representing a distinct protein or 364!
tryptophan-like contribution. Concentrations of C5 and C6 were correlated to one another (Fmax
365!
C5 vs. Fmax C6, r2= 0.22, p < 0.001), but neither appeared to covary with terrestrial components. 366!
Relative to other components, C5 and C6 demonstrated the greatest variation between 367!
watersheds (Supplemental Fig. S4.4). In general, the rank order of the components’ percent 368!
contribution to total fluorescence and variability between watersheds was maintained over time, 369!
although on average percent composition of C2 and C4 was higher, and C3 was lower for 370!
watersheds 819 and 844 relative to the other watersheds (Supplemental Fig. S4.4). The relative 371!
importance of various components appeared consistent across the wet and dry periods, although 372!
slightly more variation was observed during the dry period. 373!
3.5 Relationships between watershed characteristics and DOC exports 374!
Results of the partial-RDA (type 2 scaling) were significant in explaining variability in 375!
DOM concentration and composition (semi-partial R2= 0.33, F= 7.90, p< 0.0001)(Fig. 7). Axes 1 376!
through 3 were statistically significant at p< 0.001, and the relative contribution of each axis to 377!
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the total explained variance was 47%, 30%, and 22%, respectively. Additional details on the 378!
RDA test are provided in Supplemental Figs. S5.1-S5.2 and Tables S5.3 – S5.5. Axis 1 described 379!
a gradient of watershed inundation from lakes versus wetlands, with lake area and mean mineral 380!
soil material thickness showing a strong positive contribution, and wetlands showing a strong 381!
negative contribution to this axis. The Freshness Index, Fluorescence Index, SR and fluorescence 382!
component C6 were all positively correlated with this axis, while component C4 showed a clear 383!
negative correlation. Axis 2 described a subtler gradient of soil composition from greater mean 384!
organic soil material thickness to greater mean mineral soil material thickness. DOC 385!
concentration, DOδ13C, SUVA, and fluorescence component C1 all showed a strong, positive 386!
correlation with Axis 2. Axis 3 described a gradient of watershed steepness, from lower gradient 387!
slopes with more wetland area and thicker organic soil material to steeper slopes with less 388!
developed organic horizons. Average slope contributed negatively to Axis 3 (see Supplemental 389!
Table S5.5), followed by positive contributions from both percent wetland area and thickness of 390!
organic soil material. DOδ13C showed the most positive correlation with Axis 3, whereas 391!
fluorescence components C1 and C4 showed the most negative. 392!
4. Discussion 393!
4.1 DOC flux: High DOC yields from small catchments to the coastal ocean 394!
Freshwater DOC yields from Calvert and Hecate Island watersheds are some of the 395!
highest recorded globally, and in the upper range for this region when compared to previous 396!
regional predictions from global models (Mayorga et al., 2010) and DOC exports quantified for 397!
southeastern Alaska (D’Amore et al., 2015a; D’Amore et al., 2016; Stackpoole et al., 2016). On 398!
a global scale, DOC yields from Calvert and Hecate Island watersheds were higher than 399!
estimates from many tropical rivers including the Congo River (Spencer et al., 2016), 400!
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Amazonian blackwater rivers (Moreira-Turcq et al., 2003; Waterloo et al., 2006) and southeast 401!
Asian rivers draining virgin tropical peatlands (Baum et al., 2007), even though these types of 402!
tropical rivers are often regarded as having disproportionately high carbon export compared to 403!
temperate and Arctic rivers (Aitkenhead and McDowell, 2000; Borges et al., 2015). 404!
While comparable DOC yields have been estimated from other high-latitude catchments 405!
that receive high amounts of precipitation and contain organic soils (e.g. Naiman, 1982; Ågren et 406!
al., 2007), these are typically small catchments containing low (first or second) order headwater 407!
streams draining to higher order stream reaches. While headwater streams have been shown to 408!
export up to 90% of the total annual carbon in stream flow (Leach et al., 2016), DOC exported 409!
from headwaters and low order streams may potentially undergo significant processing before 410!
reaching the ocean. In that regard, our discovery of high DOC yields from Calvert and Hecate 411!
Island watersheds is especially compelling because these catchments drain directly to the ocean, 412!
therefore providing a large and concentrated supply of relatively fresh terrestrial DOC directly to 413!
a low DOC marine environment. Over much of the complex, incised outer coast of the perhumid 414!
Pacific coastal temperate rainforest, small, rainfall-dominated catchments are the most direct 415!
source of freshwater runoff to the coastal ocean (Eaton and Moore, 2010; Hill et al., 2015; 416!
Royer, 1982). Our findings suggest that the small catchment of this region enable geographically 417!
distributed inputs of high DOC flux directly to the coastal ocean, and that this region could 418!
represent a significant biogeochemical hotspot for coastal carbon cycling. 419!
Flashy stream hydrographs indicate that hydrologic residence times for Calvert and 420!
Hecate Island watersheds are typically short, presumably as a result of small catchment size, high 421!
drainage density, and relatively shallow soils with high hydraulic conductivity (Gibson et al., 422!
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2000; Fitzgerald et al., 2003). Precipitation is a well-established driver of stream DOC export 423!
(Alvarez-Cobelas et al., 2012) particularly in systems containing organic soils and wetlands 424!
(Olefeldt et al., 2013; Wallin et al., 2015; Leach et al., 2016). In general, frequent high 425!
precipitation events and short residence times are expected to result in pulsed exports of stream 426!
DOC that is rapidly shunted downstream, thus reducing time for in-stream processing (Raymond 427!
et al., 2016). Rapid runoff is presumably accompanied by rapid increases in water tables and 428!
lateral movement of water through shallow soil layers rich in organic matter (Fellman et al., 429!
2009; D’Amore et al., 2015b) We observed distinct seasonality of DOC delivery to the coastal 430!
ocean, which may be important for determining downstream effects on ecological processes. 431!
4.2. DOM character: Sources, variability, and implications for coastal marine foodwebs 432!
On Calvert and Hecate Islands, short catchment residence times reduce opportunities for 433!
in-stream production and processing, and, in conjunction with water flowing through abundant 434!
sources of DOM from organic-rich soils, wetlands, and forests, result in high quantities of 435!
terrestrial DOM export from watersheds to the ocean. This is consistent with findings from 436!
previous studies on DOM exports from streams draining small headwater catchments 437!
(Yamashita et al., 2011), and undisturbed catchments comprised of mixed forest and wetlands 438!
(e.g. Wickland et al., 2007; Fellman et al., 2009a; Spencer et al., 2010). Seasonal variability in 439!
DOM composition may be attributed to differences in DOM source due to seasonal changes in 440!
biological activity or as a result of shifting flow paths that affect hydrologic interactions with 441!
different DOM source materials (Fellman et al., 2009b). Rising water tables can establish strong 442!
hydraulic gradients that initiate and sustain prolonged increases in metrics like SUVA254, until 443!
the progressive drawdown of upland water tables constrain flow paths (Lambert et al., 2013). 444!
For example, during the wet and cooler period DOM increased in aromaticity and molecular 445!
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weight, indicating an increase in contributions of more plant and soil-derived material as 446!
saturated conditions promote the mobilization of a wide range of DOM source materials 447!
(McKnight et al., 2001; Kalbitz et al., 2002). However, this trend was reversed during the dry 448!
and warmer period, suggesting a shift in the source of DOM and/or increased contributions from 449!
microbial products and plant exudates, and perhaps deeper flow paths that contribute to mineral 450!
binding and export of older, more processed terrestrial material (McKnight et al., 2001; van Hees 451!
et al., 2005). Similarly, proportions of fluorescence components were more consistent across 452!
watersheds during the wet period compared to the dry period, further suggesting that water table 453!
draw down and unsaturated soils lead to more diverse flow paths and interaction with different 454!
sources of DOM. The interaction of sources and flow paths during wet versus dry periods may 455!
have important consequences for the downstream fate of this material. 456!
Biological utilization of DOM is influenced by its composition (e.g. Judd et al., 2006; 457!
Fasching et al., 2014), therefore differences in the nature of DOM exports will likely alter the 458!
downstream fate and ecological role of freshwater-exported DOM. The majority of the 459!
fluorescent DOM pool was comprised of C1, which is described as humic-like, less-processed 460!
terrestrial soil and plant material (see Table 2), and thus may represent a relatively fresh, 461!
seasonally-consistent contribution of terrestrial material from streams to the coastal ecosystem. 462!
This may have ecological significance as a potential subsidy for downstream microbial 463!
production. In lakes, for example, pulsed contributions of less-processed humic material 464!
exported from rivers have been shown to stimulate bacterial production (Bergström and Jansson, 465!
2000). In comparison to the more humic fractions, the tryptophan-like component, C6, represents 466!
a portion of the DOM pool comprised of a higher proportion of proteins that are preferred and 467!
readily utilized by microbial communities (Stedmon and Markager, 2005). Although C6 468!
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represents a minor, more variable proportion of total fluorescence in comparison to the more 469!
humic compounds such as C1, even a small proteinaceous fraction of the overall DOM pool can 470!
play a major role in overall bioavailability and bacterial utilization of DOM (Berggren et al., 471!
2010; Guillamette and Giorgio, 2011). While previous studies have suggested that bacteria 472!
prefer autochthonous carbon sources, they also readily utilize allochthonous terrestrial DOC 473!
subsidies (Bergström and Jansson, 2000; Kritzberg et al., 2004; McCallister and Giorgio, 2008), 474!
enabling humic and fulvic material to potentially fuel a low but continuous level of bacterial 475!
productivity after more labile sources have been consumed (Guillamette and Giorgio, 2011). 476!
Given that the small watersheds of this region export very high amounts of terrestrial DOC, there 477!
is clear potential for this stream-exported DOM to provide pulsed contributions of terrestrial 478!
subsidies to coastal foodwebs. 479!
4.3 Relationships between watershed attributes and exported DOM 480!
While previous studies have implicated wetlands as a major driver of DOM composition, 481!
the analysis of relationships between Calvert and Hecate Island landscape attributes and variation 482!
in DOM character suggests that controls on DOM composition are more nuanced than being 483!
driven solely by the influence of wetlands. Ågren et al. (2008) found that when wetland area 484!
comprised >10% of total catchment area, wetland DOM was the most significant driver of 485!
stream DOM composition during periods of high hydrologic connectivity. Wetlands comprise an 486!
average of 37% of the total area of the watersheds used in this study, so, based on Agren et al. 487!
(2008) they should be a primary driver of DOC concentration and DOM composition. In our 488!
study, although we observed characteristics of DOM commonly found in wetland exports, 489!
wetlands do not appear to be the single leading driver of variability. Other factors, such as the 490!
depth of organic and mineral soil materials, alternative DOC-source pools, and watershed 491!
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residence time appear to be important drivers of DOC concentration and DOM composition. In 492!
these watersheds, soils with pronounced accumulations of organic matter are not restricted to 493!
wetland ecosystems. While Hemists occur in the latter, which comprise 27.8% of the watersheds, 494!
Folic Histosols occur on hillslopes over an additional 25.7% of the study area (Supplemental 495!
S1.2). This suggests the importance of widely distributed, alternative soil DOM source-pools, 496!
such as Folic Histosols and associated Podzols with thick forest floors on hillslopes, available to 497!
contribute high amounts of terrestrial carbon for export. 498!
Although lakes make up a relatively small proportion of the total landscape area, their 499!
influence on DOM export appears to be important. The proportion of lake area can be a good 500!
predictor of organic carbon loss from a catchment since lakes often increase hydrologic 501!
residence times and thus increase opportunities for biogeochemical processing (Algesten et al., 502!
2004; Tranvik et al., 2009). In our study, watersheds with a larger percentage of lake area 503!
exhibited lower DOC yields, and lake area was correlated with parameters that represent greater 504!
autochthonous DOM production or microbial processing such as higher Freshness Index, SR, 505!
Fluorescence Index, and higher proportions of component C6. In contrast, watersheds with a 506!
high percentage of wetlands contributed a different composition of DOM than watersheds with a 507!
high percentage of lakes, therefore the proportion of different landscape types, such as wetlands 508!
or lakes, appears to be an important factor influencing aspects of DOM export. In addition, 509!
watersheds with the slowest response to rain events had lakes close to their catchment outlet 510!
(e.g., watershed 1015, data not shown) that appear to dampen the response to rain events and 511!
increased residence time low in the watershed. Therefore, the relative location of wetlands and 512!
lakes within the catchment and their proximity to the watershed outlet also likely plays an 513!
important role in the overall composition of DOM exports. 514!
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Soil composition also plays a role in the quantity and character of DOM exported from 515!
Calvert and Hecate Island watersheds. Organic and mineral soil materials provide different 516!
environments for the production, retention, and degradation of DOM. It is generally known that 517!
where peat has accumulated enough to form organic soils (Hemists), DOM is the most mobile 518!
fraction of organic matter and accumulates under conditions of soil saturation and limited 519!
drainage, resulting in the enrichment of poorly biodegradable, more stable humic acids 520!
(Stevenson, 1994; Marschner and Kalbitz, 2003). However, on hillslopes where Folic Histosols 521!
have formed under more freely drained conditions, high rates of respiration in organic soils can 522!
result in further enrichment of aromatic and more complex molecules, and this material may be 523!
rapidly mobilized and exported to streams (Glatzel et al., 2003). Preferential retention of certain 524!
DOM fractions by sorption to mineral horizons can increase stability of the DOM pool by 525!
reducing biodegradation, and is postulated as the main process by which DOM is retained in 526!
forest soils (Kalbitz et al., 2005; Kaiser et al., 1997). In our study, the presence of thicker organic 527!
soil material was positively correlated to higher DOC concentrations, as well as higher 528!
proportions of C1, representing less processed, humic-like compounds. Steeper slopes were also 529!
correlated with C1 (RDA Axis 3), suggesting that steeper slopes and adequate drainage may 530!
result in the rapid mobilization of this material from organic soil horizons. 531!
Changing environmental conditions, such as shifting precipitation and temperature 532!
regimes, may affect future DOC fluxes. Long term patterns in DOC flux have been observed in 533!
many places (e.g., Worrall et al., 2004; Borken et al., 2011; Lepistö et al., 2014) and continued 534!
monitoring of this system will allow us to better understand the underlying drivers of export. For 535!
example, changes in soil temperature and moisture could influence the stability of the organic 536!
matter pool, as processes such as organic matter production and sorption have strong 537!
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relationships with temperature and oxidation state. Therefore, additional research is needed to 538!
assess soil properties relevant to DOM mobility (e.g., texture, sesquioxide content), landscape 539!
attributes, and flow paths for predicting DOM export in this region and the consequences of 540!
shifting conditions such as those associated with altered land use or climate change. 541!
5. Conclusions 542!
Previous work has demonstrated freshwater discharge is substantial along the coastal 543!
margin of the Pacific temperate rainforest, and plays an important role in processes such as ocean 544!
circulation (Royer, 1982; Eaton and Moore, 2010). Our finding that small catchments in this 545!
region export some of the highest yields of terrestrial DOC in the world to coastal waters 546!
suggests that freshwater inputs may also influence ocean biogeochemistry and food web 547!
processes through terrestrial organic matter subsidies. Our findings also suggest that this region 548!
may be currently underrepresented in terms of its role in global carbon cycling. Currently, there 549!
is no region-wide carbon flux model for the Pacific coastal temperate rainforest or the greater 550!
Gulf of Alaska, which would quantify the importance of this region within the global carbon 551!
budget. Our estimates represent the hypermaritime outer-coast zone, where subdued terrain, high 552!
rainfall, ocean moderated temperatures and poor bedrock have generated a distinctive ‘bog-553!
forest’ landscape mosaic within the greater temperate rainforest (Banner et al. 2005). To quantify 554!
regional scale fluxes of rainforest carbon to the coastal ocean, further research will be needed to 555!
estimate DOC yields across the west-to-east, and north to south, gradients of topography, 556!
climate, hydrology, soils and vegetation. Further study on the controls of DOC export from these 557!
watersheds, such as the role of landscape type (e.g., different wetland and forest types within the 558!
ecosystem mosaic), watershed attributes (e.g., stream connectivity, slope, etc.), and detailed 559!
characterization of soils, are warranted. Coupled with current studies investigating the fate of 560!
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25!
terrestrial material in ocean food webs, this work will improve our understanding of coastal 561!
carbon patterns, and increase capacity for predictions regarding the ecological impacts of climate 562!
change. 563!
564!
Author Contributions 565!
The authors declare that they have no conflict of interest. 566!
A.A. Oliver prepared the manuscript with contributions from all authors, designed analysis 567!
protocols, analyzed samples, performed the modeling and analysis for dissolved organic carbon 568!
fluxes, parallel factor analysis of dissolved organic matter composition, and all remaining 569!
statistical analyses. S.E. Tank assisted with designing the study and overseeing laboratory 570!
analyses, crafting the scope of the paper, and determining the analytical approach. 571!
I. Giesbrecht led the initial DOC sampling design, helped coordinate the research team, oversaw 572!
routine sampling and data management, and led the watershed characterization. 573!
M.C. Korver developed the rating curves, and conducted the statistical analysis of discharge 574!
measurement uncertainties and rating curve uncertainties. W.C. Floyd lead the hydrology 575!
component of this project, selected site locations, installed and designed the hydrometric 576!
stations, and developed the rating curves and final discharge calculations. C. Bulmer and P. 577!
Sanborn collected and analyzed soil field data and prepared the digital soils map of the 578!
watersheds. K.P. Lertzman conceived of and co-led the overall study of which this paper is a 579!
component, helped assemble and guide the team of researchers who carried out this work, 580!
provided input to each stage of the study. 581!
582!
Acknowledgements 583!
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26!
This work was funded by the Tula Foundation and the Hakai Institute. The authors would like to 584!
thank many individuals for their support, including Skye McEwan, Bryn Fedje, Lawren McNab, 585!
Nelson Roberts, Adam Turner, Emma Myers, David Norwell, and Chris Coxson for sample 586!
collection and data management, Clive Dawson and North Road Analytical for sample 587!
processing and data management, Keith Holmes for creating our maps, Matt Foster for database 588!
development and support, Shawn Hateley for sensor network maintenance, Jason Jackson and 589!
the entire staff at Hakai Energy Solutions for installing and maintaining the sensors and 590!
telemetry network. Thanks to Santiago Gonzalez Arriola for generating the watershed summaries 591!
and associated data products, and Ray Brunsting for overseeing the design and implementation 592!
of the sensor network and the data management system at Hakai. Additional thanks to Lori 593!
Johnson and Amelia Galuska for soil mapping field assistance, and Francois Guillamette for 594!
PARAFAC consultation. Thanks to Dave D’Amore for inspiring the Hakai project to investigate 595!
aquatic fluxes at the coastal margin and for technical guidance. Lastly, thanks to Eric Peterson 596!
and Christina Munck who provided significant guidance throughout the process of designing and 597!
implementing this study. 598!
599!
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the impact of low molecular weight compounds on carbon dynamics and respiration in forest 970!
soils: a review, Soil Biol. Biochem., 37, 1–13, doi:10.1016/j.soilbio.2004.06.010, 2005. 971!
972!
Wallin, M., Weyhenmeyer, G., Bastviken, D., Chmiel, H., Peter, S., Sobek, S. and Klemedtsson, 973!
L.: Temporal control on concentration, character, and export of dissolved organic carbon in two 974!
hemiboreal headwater streams draining contrasting catchments, J. Geophys. Res. Biogeosci. 120, 975!
832–846, doi:10.1002/2014jg002814, 2015. 976!
977!
Wang, T., Hamann, A., Spittlehouse, D.L., and Murdock, T.Q.,: ClimateWNA- High resolution 978!
spatial climate data for Western North America, J. Appl. Meterol. Climatol., 51, 16-29, 979!
doi:dx.doi.org/10.1175/JAMC-D-11-043.1, 2012.!980!
981!
Waterloo, M., Oliveira, S., Drucker, D., Nobre, A., Cuartas, L., Hodnett, M., Langedijk, I., Jans, 982!
W., Tomasella, J., Araújo, A., Pimentel, T. and Estrada, J.: Export of organic carbon in run-off 983!
from an Amazonian rainforest blackwater catchment, Hydrol. Process., 20, 2581–2597, 984!
doi:10.1002/hyp.6217, 2006. 985!
986!
Weishaar, J.L., Aiken, G.R., Bergamaschi, B.A., Fram, M.S., Fujii, R. and Mopper, K.: 987!
Evaluation of specific ultraviolet absorbance as an indicator of the chemical composition and 988!
reactivity of dissolved organic carbon, Environ. Sci. Technol., 37, 4702–8, 989!
doi:10.1021/es030360x, 2003. 990!
991!
Wickland, K., Neff, J., and Aiken, G.: Dissolved Organic Carbon in Alaskan Boreal Forest: 992!
Sources, Chemical Characteristics, and Biodegradability, Ecosystems, 10, 1323-1340, 2007. 993!
994!
Wilson, H.F. and Xenopoulos, M.A.: Effects of agricultural land use on the composition of 995!
fluvial dissolved organic matter, Nat. Geosci., 2, 37–41, doi:10.1038/ngeo391,!2009.!996!
997!
Wolf, E.C., Mitchell, A.P., and Schoonmaker, P.K.: The Rain Forests of Home: An Atlas of 998!
People and Place, Ecotrust, Pacific GIS, Inforain, and Conservation International, Portland, 999!
Oregon, 24 pp., available at: http://www.inforain.org/pdfs/ctrf_atlas_orig.pdf, 1995. 1000!
1001!
Worrall, F., Burt, T., and Adamson, J.: Can climate change explain increases in DOC flux from 1002!
upland peat catchements?, Sci. Total. Environ., 326, 95–112, 1003!
doi:10.1016/j.scitotenv.2003.11.022, 2004. !1004!
1005!
Yamashita, Y. and Jaffé, R.: Characterizing the Interactions between Trace Metals and Dissolved 1006!
Organic Matter Using ExcitationEmission Matrix and Parallel Factor Analysis, Environ. Sci. 1007!
Technol., 42, 7374–7379, doi:10.1021/es801357h, 2008. 1008!
1009!
Yamashita, Y., Kloeppel, B., Knoepp, J., Zausen, G. and Jaffé, R.: Effects of Watershed History 1010!
on Dissolved Organic Matter Characteristics in Headwater Streams, Ecosystems, 14, 1110–1122, 1011!
doi:10.1007/s10021-011-9469-z, 2011. 1012!
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
c
Author(s) 2017. CC-BY 3.0 License.
!
36!
Figure 1. The location of Calvert Island, British Columbia, within the perhumid region of the 1013!
Pacific coastal temperate rainforest (right) and the study area on Calvert and Hecate Islands, 1014!
including the seven study watersheds, corresponding stream outlet sampling stations, and 1015!
location of the rain gauge (left). Characteristics of individual watersheds are described in Table 1016!
1. 1017!
1018!
1019! 1020!
1021!
1022!
1023!
1024!
1025!
1026!
1027!
1028!
1029!
1030!
1031!
1032!
1033!
1034!
1035!
1036!
1037!
1038!
1039!
1040!
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
c
Author(s) 2017. CC-BY 3.0 License.
!
37!
Figure 2. Hydrological patterns reflect the high amounts of precipitation and rapid runoff 1041!
response typical of watersheds located in the study area (a) the hydrograph and precipitation 1042!
record from Watershed 708 illustrates seasonal patterns in runoff and rainfall for the study period 1043!
of October 1, 2015-April 30, 2016. Grey shading indicates the wet period (September 1-April 1044!
30) and the unshaded region indicates the dry period (May 1-August 30) (b) Correlation of daily 1045!
(24 hour) areal runoff (discharge of all watersheds combined) to 48 hour total rainfall recorded at 1046!
watershed 708. For the period of study, comparisons of daily runoff to 48-hr rainfall 1047!
(runoff:rainfall mean= 0.92, std ±0.27) indicated that the response in discharge from catchments 1048!
is relatively rapid following precipitation. 1049!
1050! 1051!












      

       

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



  

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
 

Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
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Author(s) 2017. CC-BY 3.0 License.
!
38!
Figure 3. Seasonal (timelines, by date) and spatial (boxplots, by watershed) patterns in DOC 1052!
concentration and DOM composition for stream water collected at the outlets of the seven study 1053!
watersheds on Calvert and Hecate Islands. Daily precipitation and annual temperature are shown 1054!
in the top left panel. Grey shading indicates the wet period (September 1-April 30) and the 1055!
unshaded region indicates the dry period of each water year. 1056!
1057!
1058!


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
     

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
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

      




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
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  
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Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
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!
39!
Figure 4. Monthly areal DOC yields and precipitation for water year 2015 (WY2015) and the 1059!
wet period (October 1-April 30) of water year 2016 (WY2016). Error bars represent standard 1060!
error. Total rain and DOC yield were significantly correlated (r2 = 0.77) and months of higher 1061!
rain produced higher DOC yields. In WY2015, the majority of DOC export (~94% of annual 1062!
load) occurred during the wet period (~88% of annual precipitation). 1063!
1064! 1065!
1066!
1067!
1068!
1069!
1070!
1071!
1072!
1073!
1074!
1075!
1076!
1077!
1078!
1079!
1080!
1081!
           


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

    
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
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Author(s) 2017. CC-BY 3.0 License.
!
40!
Figure 5: DOC loads and yields for the seven study watersheds and the total area of study (all 1082!
watersheds combined, or “areal”) on Calvert and Hecate Islands for the complete water year 1083!
2015 (WY2015; Oct 1 - Sep 30), and October 1- April 30 of the wet period for water year 2015 1084!
(WY2015 wet) and water year 2016 (WY2016 wet). Because DOC yields were only available 1085!
for September in WY2015, this month was excluded from the wet period totals in order to make 1086!
similar comparisons between years. Error bars represent standard error. Total DOC load tended 1087!
to increase by increasing watershed area, and the total amount of DOC exported during the wet 1088!
period was higher in WY2015 compared to WY2016. DOC yield was also higher for the wet 1089!
period of WY2015 compared to WY2016, but differences between watersheds were independent 1090!
of total watershed area, indicated different drivers of DOC export on a per-area basis. 1091!
1092!

       


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
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
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




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


Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
c
Author(s) 2017. CC-BY 3.0 License.
!
41!
Figure 6: Percent contribution of the six components identified in parallel factor analysis 1093!
(PARAFAC) for samples collected every three weeks from January-July, 2016 from the seven 1094!
study watersheds on Calvert and Hecate Islands study watersheds. Points represent means ± 1095!
standard deviation for all watersheds combined. The grey shading indicates the wet period and 1096!
the unshaded region indicates the dry period. 1097!
1098!
1099!
1100!
1101!
1102!
1103!
1104!
1105!
1106!
1107!
1108!
1109!
1110!
1111!
1112!
1113!
1114!
1115!
1116!
1117!
1118!
1119!
       











 
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
c
Author(s) 2017. CC-BY 3.0 License.
!
42!
Figure 7: Results from the partial-Redundancy analysis (RDA; type 2 scaling) of DOC 1120!
concentration and DOM composition versus watershed characteristics. Angles between vectors 1121!
represent correlation, i.e., smaller angles indicate higher correlation. Symbols represent different 1122!
watersheds, and numbers on symbols represent the sample month in 2016: 1= January, 2= 1123!
February, 3= March, 4= early April, 5= late April, and 6= May. 1124!
1125!
1126!
RDA1
RDA2
Watershed
626
693
703
708
819
844
1015
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
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Author(s) 2017. CC-BY 3.0 License.
!
43!
Table 1: Watershed characteristics, discharge, DOC concentrations, and DOC yields for the seven study watersheds on Calvert and 1127!
Hecate Islands. Additional details on the methods used to determine watershed characteristics can be found in Supplementary 1128!
Material. 1129!
1130!
Water-
shed
Area
(km2)
Avg.
Slope
(%)
Lakes
(%
Area)
Wetlands
(% Area)
Avg. Depth
Organic
Soils
(cm)
Avg. Depth
Mineral
Soils
(cm)
Total
Q
Yield *
(mm)
DOC*a
(mg L-1)
Q-
weighted
Avg. DOC*
(mg L-1)
DOC Annual
Yield b
WY2015*
(Mg C km-2)
DOC Monthly
Yield b
Wet Season**
(Mg C km-2)
DOC Monthly
Yield b
Dry Season***
(Mg C km-2)
626 3.2 21.7 4.7 48.0 39.4 ±24.3 30.8 ±8.3 3673 11. 0 ± 3.5 15.3 37.7
(31.9 – 44.2)
3.59
(3.05 – 4.18)
0.62
(0.49 – 0.77)
1015 3.3 34.2 9.1 23.8 39.5 ±17.2 33.7 ±8.6 3052 11 .2 ±1. 6 12.9 24.7
(23.6 – 25.8)
2.56
(2.45 – 2.78)
0.27
(0.25 – 0.28)
819 4.8 30.1 0.3 50.2 37.9 ±19.1 29.8 ±5.7 3066 14.0 ±3.5 19.3 35.7
(31.7 – 40.2)
3.80
(3.37 – 5.10)
0.57
(0.48 – 0.67)
844 5.7 32.5 0.3 35.2 35.4 ±18.0 29.1 ±6.4 4129 13.1 ±3.6 15.9 43.6
(34.2 – 54.9)
4.24
(3.36 – 5.30)
0.54
(0.36 – 0.77)
708 7.8 28.5 7.5 46.3 36.2 ±19.7 29.9 ±6.0 3805
9.5 ±2.4 10.9 24.1
(22.2 – 26.0)
2.67
(2.46 – 4.07)
0.38
(0.34 – 0.43)
693 9.3 30.2 4.4 42.8 35.4 ±16.1 30.2 ±6.4 5866 7.7 ±2.5 8.4 29.7
(25.9 – 34.0)
3.19
(2.79 – 4.94)
0.41
(0.32 – 0.52)
703 12.8 40.3 1.9 24.3 37.3 ±16.5 35.8 ±13.4 6058 6.3 ±2.6 9.0 37.0
(32.5 – 42.0)
3.48
(3.07 – 4.02)
0.64
(0.52 – 0.77)
All 46.9 32.7 3.7 37.1 37.4 ±17.7 32.2 ±9.2 4730 10.4 ±3.8 11. 1 33.3
(28.9 – 38.1)
3.35
(2.94 – 4.40)
0.50
(0.41 – 0.62)
* Calculated for water year 2015 (WY2015; Oct 1, 2014-Sep 30, 2015)
** Wet period average monthly yield calculated from October-April and September, WY2015 and October-April, WY2016
*** Dry period average monthly yield calculated from May-August, WY2015
a Mean ± standard deviation
b Total ± 95% confidence interval
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
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!
44!
Table 2: Spectral composition for the six fluorescence components identified using PARAFAC, including excitation (Ex.) and 1131!
emission (Em.) peak values, percent composition across all samples, and likely structure and characteristics of the fluorescent 1132!
component based on previous studies. 1133!
1134!
Component Ex. (nm) Em. (nm) % Compositiona Potential structure/
Characteristics
Previous studies with
comparable results
C1 315 436 34.1 ±2.2
(31.1-39.3)
Humic-like, less
processed terrestrial, low
molecular weight,
enriched fulvic acid
Coble, 2007; Garcia et al.
2015; Graeber et al.
2012; Walker et al. 2014;
Yamashita et al. 2011.
C2 270/ 380 484 20.2 ±1.9
(16.1-25.6)
Not commonly reported,
similarities to humic-like,
more processed terrestrial,
high molecular weight
Boehme & Coble, 2000;
Coble et al. 1998; La
Pierre et al. 2014;
Stedmon et al. 2003;
C3 270 478 17.8 ±1.8
(12.8-20.8)
Humic-like, highly
processed terrestrial;
refractory, oxidized
quinone-like
Stedmon & Markager,
2005; Yamashita et al.
2010
C4 305/ 435 522 14.8 ±2.6
(9.4-22.3)
Not commonly reported,
similarities to fulvic-like,
contributed from soils
Lochmuller & Saavedra,
1986; Stedmon et al.,
2003
C5 325 442 9.8 ±3.5
(0.0-15.9)
Aquatic humic-like
terrestrial; autochthonous,
microbial produced; may
be photoproduced
Boehme & Coble, 2000;
Coble et al. 1998;
Stedmon et al., 2003
C6 285 338 3.4 ±2.5
(0.0-9.3)
Amino acid-like/
Tryptophan-like.
Freshly added from land,
autochthonous. Rapidly
photodegradable
Murphy et al. 2008;
Shutova et al. 2003;
Stedmon et al. 2007;
Yamashita et al. 2003
a Mean ± stdev (min-max) from all samples
Biogeosciences Discuss., doi:10.5194/bg-2017-5, 2017
Manuscript under review for journal Biogeosciences
Published: 19 January 2017
c
Author(s) 2017. CC-BY 3.0 License.
... Dissolved organic carbon (DOC) is one of the main forms of fluvial carbon loss from terrestrial ecosystems and export from northern wetlands typically ranges from 10 to 30 g m -2 year -1 (Worrall et al. 2003(Worrall et al. , 2009Billett et al. 2010). However, in the PCTR, abundant precipitation and frequent soil flushing results in wetland DOC fluxes as large as 50 g C m -2 year -1 (D'Amore et al. 2015a), placing these values in the upper range of DOC export from forested and wetlands streams (Aitkenhead and McDowell 2000;Å gren et al. 2007;Moore et al. 2011;Oliver et al. 2017). As a result, fluvial carbon fluxes in this region may account for a substantial ([40%) component of total ecosystem carbon export. ...
... Moreover, lateral export of DOC may be particularly important to wetland carbon budgets in humid ecoregions like the tropics and the PCTR where abundant precipitation leads to saturated soils and frequent hydrologic flushing of carbon-dense soils. Previous research from PCTR and tropical peatlands has shown that areaweighted DOC export from these ecosystems is among the highest in the world (Moore et al. 2011(Moore et al. , 2013D'Amore et al. 2015a;Oliver et al. 2017). Our findings and those of others (Nilsson et al. 2008;Billett et al. 2010;Moore et al. 2013) reinforce the importance of lateral DOC export as a carbon loss pathway that should be included in terrestrial ecosystem carbon budgets. ...
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The perhumid coastal temperate rainforest (PCTR) of southeast Alaska has some of the densest soil organic carbon (SOC) stocks in the world (>300 Mg C ha−1) but the fate of this SOC with continued warming remains largely unknown. We quantified dissolved organic carbon (DOC) and carbon dioxide (CO2) yields from four different wetland types (rich fen, poor fen, forested wetland and cedar wetland) using controlled laboratory incubations of surface (10 cm) and subsurface (25 cm) soils incubated at 8 and 15 °C for 37 weeks. Furthermore, we used fluorescence characterization of DOC and laboratory bioassays to assess how climate-induced soil warming may impact the quality and bioavailability of DOC delivered to fluvial systems. Soil temperature was the strongest control on SOC turnover, with wetland type and soil depth less important in controlling CO2 flux and extractable DOC. The high temperature incubation increased average CO2 yield by ~40 and ~25% for DOC suggesting PCTR soils contain a sizeable pool of readily biodegradable SOC that can be mineralized to DOC and CO2 with future climate warming. Fluxes of CO2 were positively correlated to both extractable DOC and percent bioavailable DOC during the last few months of the incubation suggesting mineralization of SOC to DOC is a strong control of soil respiration rates. Whether the net result is increased export of either carbon form will depend on the balance between the land to water transport of DOC and the ability of soil microbial communities to mineralize DOC to CO2.
... Similarly, hypermaritime forests have been studied in Southeast Alaska (Alaback 1982, Buma et al. 2016, Bisbing and Amore 2018, Buma and Thompson 2019, but it is unclear if knowledge from Alaska's hemlock spruce-dominated forest stands are transferable to the cedarhemlock stands of coastal BC. Information on old-growth forest structure in hypermaritime temperate rainforests on the coastal margin of BC is scarce despite their importance for wildlife (Adams et al. 2017, Obrist et al. 2020, Service et al. 2020), soil carbon storage (McNicol et al. 2019), and exports of dissolved organic carbon (Oliver et al. 2017), which provide energy subsidies to marine environments (St. Pierre et al. 2020). ...
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Dendrochronological analyses were conducted across a gradient of productivity and soil drainage quality characterizing four vegetation types in a low‐productivity hypermaritime (perhumid) temperate rainforest on the Central Coast of British Columbia, Canada. We examined the structure, composition, and stand dynamics of trees growing in 400 m2 plots located in blanket bog, bog woodland, bog forest, and zonal forest vegetation types. We sampled over 2500 trees and 1500 seedlings and saplings and our dendrochronological reconstruction of six tree species revealed establishment ages extending to 660 A.D. (1350 yr). All forest plots contained numerous old trees (>250 yr) and the zonal forest and bog forest vegetation types contained significantly taller trees and also had the greatest amount of suppressed, shade‐tolerant tree species. The bog woodland vegetation type contained more seedlings and saplings than the other three vegetation types combined. The bog forest vegetation type had the highest density of dead standing trees (~530 per hectare). Blanket bogs contained an open structure with very few old trees (>250 yr). Significant differences in the ages of trees existed between forested vegetation types and the more open blanket bog vegetation type. Several trees exceeded 1000 yr in age and were situated in lower‐productivity bog forest and bog woodland sites. We found no evidence of widespread tree cohort establishment, indicating that small‐scale disturbances such as individual tree mortality and gap‐forming dynamics are likely the most frequent disturbance in the study area.
... The impact of precipitation on DOC fluxes is considerable as well. In similar sized ocean-draining watersheds on the central coast of British Columbia, where annual rainfall is double and forest soils are thicker organic layers and have higher soil C contents than that observed in the SLW [49], DOC fluxes (0.377 Mg C ha −1 year −1 ) are almost 10 times those estimated in this study [50]. The annualized DOC flux parameters selected for the three catchment types only represent a small fraction of the slow above and belowground DOM pools; however, accumulation over many years could impact the C sequestration expectations, and therefore the watershed-scale C budget [10]. ...
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