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\begin{document}

\title{Forest management impacts on greenhouse gas fluxes from riparian
soils along headwater streams}



\author[1]{Teresa Silverthorn}%
\author[1]{John Richardson}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\textbf{Silverthorn, T.K.} \textbf{* and Richardson, J.S.}~

Department of Forest and Conservation Sciences, The University of
British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada

* Corresponding author

Email:
\href{mailto:teresa.silverthorn@alumni.ubc.ca}{\nolinkurl{teresa.silverthorn@alumni.ubc.ca}};
\href{mailto:teresa.silverthorn@gmail.com}{\nolinkurl{teresa.silverthorn@gmail.com}}~

A version of the manuscript is published
at:~\url{https://doi.org/10.1007/s10021-021-00621-z}

\textbf{Manuscript highlights}

\begin{itemize}
\tightlist
\item
  Clear-cutting without a buffer decreased nitrous oxide emission and
  methane uptake
\item
  Riparian buffers appeared effective in mitigating forest harvest
  effects
\item
  Groundwater discharge areas had lower methane uptake, especially when
  harvested
\end{itemize}

\textbf{Abstract}

Increasing concentrations of atmospheric greenhouse gases (GHGs;
CO\textsubscript{2}, CH\textsubscript{4}, N\textsubscript{2}O) causes
climate change. Depending on the conditions, soils have the potential to
store carbon or to be a source of GHGs to the atmosphere. Riparian soils
in particular have high potential to store carbon, but also to be
sources of CH\textsubscript{4} and N\textsubscript{2}O. Headwater
streams make up a large proportion of stream length in a drainage
network, and their riparian zones have valuable ecosystem functions. In
parallel, the riparian zones of headwater streams are particularly
vulnerable to forest harvest. Studies of GHG fluxes from these unique
ecosystems remain limited. Our objective was to quantify the effects of
forestry practices and groundwater discharge (DIS) areas on GHG
emissions from riparian forest soils in coastal British Columbia. We
compared nine sites with three different forest management protocols: 1)
harvesting with a riparian buffer, 2) no buffer, and 3) reference sites
without harvesting. We measured gas fluxes, soil temperature, soil
moisture and depth to the groundwater table alongside headwater streams
monthly over one growing season. We found that CH\textsubscript{4}uptake
rates were 65\% lower at the no buffer sites, and N\textsubscript{2}O
emission rates were 52\% lower at the no buffer sites, when compared to
the reference sites. Additionally, CH\textsubscript{4} uptake was 54\%
lower at DIS areas than in non-DIS areas. The results of our research
help inform forest management by demonstrating that maintaining riparian
buffers can be effective in protecting the ecosystem functions
contributing to soil GHG fluxes.

\textbf{Keywords}

Carbon dioxide \textbar{} Headwater streams \textbar{} Methane
\textbar{} Nitrous oxide \textbar{} Forest harvest \textbar{} Riparian
buffer \textbar{} Riparian zone



\textbf{Introduction}

Greenhouse gases (GHGs) such as carbon dioxide (CO\textsubscript{2}),
methane (CH\textsubscript{4}), and nitrous oxide (N\textsubscript{2}O)
can absorb infrared radiation and trap heat in the atmosphere (IPCC
2007). This greenhouse effect is critical for maintaining livable
conditions for life on earth, but anthropogenic activities have caused
an unprecedented increase GHG concentrations in the atmosphere, leading
to global warming and climate change (IPCC 2007). Soils play an
important role in climate change, as they have the potential to store
carbon or to be a source of greenhouse gases to the atmosphere (Oertel
and others 2016).

Riparian zones are the three dimensional zones of direct interaction
between terrestrial and aquatic ecosystems (Gregory and others 1991).
Riparian ecosystems are a conservation priority due to their
disproportionately high value and diversity of ecological functions as
well as unique biodiversity combined with high vulnerability to
anthropogenic pressures (Ramey and Richardson 2017; Capon and Pettit
2018). Their unique properties, including shallow water tables, high
soil organic matter content, and high soil nitrogen concentrations,
create the potential for significant carbon sequestration (Gundersen and
others 2010), but also to produce significant amounts of anaerobically
produced CH\textsubscript{4} and N\textsubscript{2}O to the atmosphere
(Knoepp and Clinton 2009; Vidon and others 2018).

Forest harvest is a disturbance that can alter biogeochemical processes
in soils (Kreutzweiser and others 2008), resulting in a change in the
GHG emission rates (Lavoie and others 2013). However, soil ecosystem
responses to logging are highly variable and site specific due to
microsite level differences in variables such as soil properties,
moisture conditions, and biological interactions (Kreutzweiser and
others 2008). Therefore, the results from the many upland forest studies
are likely to differ from riparian zones.

The most common method of protecting streams and riparian areas from the
impacts of forest harvest is the use of riparian buffer zones,
consisting of a strip of trees adjacent to the stream that is either
left uncut or has limited harvesting (Richardson and others 2012). The
riparian zones of headwater streams are particularly vulnerable to
forest harvest, as buffer zones are often not required along these small
streams (Richardson and Danehy 2007). In British Columbia, 45\% of
surveyed small streams did not retain a riparian buffer after forest
harvest (Kuglerov\selectlanguage{ngerman}á and others 2020). Headwater streams are small,
ecologically significant, tributaries at the most upstream ends of a
stream network that make up to 80\% of stream length in a given drainage
network (Leopold and others 1964). Although riparian buffers are
effective in reducing the impacts of forest harvest by intercepting
sediments, maintaining bank stability, and providing shading among other
benefits (Richardson and others 2012), their usage remains contentious
in headwater systems, due to the large volume of timber that buffers
remove from commercial use (Richardson and Danehy 2007).

The major drivers of spatio-temporal variation in GHG flux rates include
soil temperature and soil moisture (Luo and Zhou 2006).
CO\textsubscript{2} emissions consist of the combined emissions from
root respiration (autotrophic respiration) and microbial decomposition
of organic matter (heterotrophic respiration), and as such,
CO\textsubscript{2} emissions are affected by substrate availability
(Luo and Zhou 2006). CH\textsubscript{4} is produced by methanogens in
anaerobic conditions, and consumed by methanotrophs in aerobic
conditions (Oertel and others 2016). Soil pH and substrate availability
impact microbial communities contributing to CH\textsubscript{4}exchange
(Serrano-Silva and others 2014). N\textsubscript{2}O is mainly produced
by denitrification under anaerobic conditions, in addition to
nitrification under aerobic conditions (Oertel and others 2016).
Important factors influencing these processes are nitrogen deposition
and fertilization, and soil pH (Dalal and Allen 2008).

Forests and trees are critical in regulating water, energy, and carbon
cycles (Ellison and others 2017; Ilstedt and others 2016). Thus,
deforestation can alter local scale warming, rainfall, water
availability, and the emission of GHGs (Ellison and others 2017).
Studies have evaluated the effects of clear-cutting on GHG fluxes from
forest soils (Kähkönen and others 2002). Clear-cutting has been found to
increase soil temperatures (Hashimoto and Suzuki 2004) and increase the
elevation of the groundwater table (Bliss and Comerford 2002; Hotta and
others 2010). These changes can be attributed to the drastic reduction
in leaf area after harvesting, which reduces catchment-wide
transpiration rates (Bliss and Comerford 2002) and allows for an
increase in incoming sunlight, warming up the soil (Hashimoto and Suzuki
2004). Clear-cutting can increase CH\textsubscript{4} emissions due to
greater soil moisture and temperature (Wu and others 2011) and increase
N\textsubscript{2}O emissions due to greater soil moisture and increased
nitrogen availability as a result of increased rates of nitrogen
mineralization and/or reduced competition from roots (Kellman and
Kavanaugh 2008; Takakai and others 2008). Clear-cutting has inconsistent
effects on CO\textsubscript{2} emission rates, with some studies
reporting a decline (Striegl and Wickland 1998), an increase
(Paul-Limoges and others 2015), or no change (Kähkönen and others 2002)
in emissions following harvest. Nevertheless, to our knowledge, no one
has yet examined the effects of forest harvest in riparian forests
alongside streams on the rates of GHG fluxes.

In this study, we evaluated how forest management practices can alter
biogeochemical processes that subsequently affect GHG fluxes from
riparian soils along headwater streams. The objectives were: (1) to
quantify the effects of forest harvest practices on soil GHG flux rates;
(2) to determine if soil temperature, soil moisture, and/or groundwater
level were dominant driver(s) of gas fluxes; and (3) to determine the
effects of microtopographical variation on GHG flux rates.

\textbf{Methods}

\textbf{Site description}

The study sites were located in the 5,157 ha Malcolm Knapp Research
Forest (MKRF), at the foothills of the Coast Mountains, about 40 km east
of Vancouver, British Columbia (49° 16' N, 122° 34' W) (Figure 1). The
biogeoclimatic zone is Coastal Western Hemlock (Klinka and others 2005),
and the dominant tree species are Western Hemlock (\emph{Tsuga
heterophylla} ), Douglas-fir (\emph{Pseudotsuga menziesii} ), and
Western Red Cedar (\emph{Thuja plicata} ) (Klinka and others 2005). The
forest is mostly comprised of approximately 90-year old second growth,
naturally regenerated following widespread fire in 1925, and again in
1931 (Klinka and others 2005).

The climate is maritime, with slight continental influence due to the
mountains and inland location (Klinka and others 2005). The primary
climate (Köppen) classification is \emph{Cfb} , temperate oceanic
climate (Kottek and others 2006). The climate is characterized by mild
temperatures, with wet, mild winters, and cool, relatively dry summers
(Klinka and others 2005). Mean annual precipitation and air temperature
at the Environment Canada climate station located at the Research Forest
(Haney UBC RF Admin, station number 1103332) are 2131 mm and 9.7°C,
respectively (data for 1962 to 2006). The annual range in mean monthly
minimum and maximum temperature was 5.3°C to 13.8°C over the same
period.

Glacial till and colluvium are the predominant parent materials in MKRF
(Klinka 1976). In the southern portion, where our sites were located,
surficial deposits include glacio-fluvial and glacio-marine deposits
from Pleistocene era glaciation, overlaying compacted till or bedrock
(Klinka and others 2005; Klinka 1976). The soils formed on these
materials are shallow and can be expected to be coarse, acidic, and low
in basic cations (Klinka and others 2005). The soils at all sites were
designated a Humo-Ferric Podzol, except one site (E10B) had soil of the
Organic Order (likely a Hydric Mesisol). Previously reported properties
of mineral soil in undisturbed forest stands in Malcolm Knapp Research
Forest included 39 Mg ha\textsuperscript{-1} total carbon content, 2.5
kg ha\textsuperscript{-1} nitrate content, and 11.5 kg
ha\textsuperscript{-1} available phosphorous content (Turk and others
2008).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1. Location of study sites alongside headwater streams at Malcolm
Knapp Research Forest (MKRF), British Columbia, Canada.

\textbf{Study design and criteria}

This study compared three different forest management practices in and
near the riparian zone of headwater streams. A total of nine (n = 9)
headwater streams were chosen as field sites; three sites were not
recently logged (\textasciitilde{} 90 year-old stands), representing
relatively undisturbed reference conditions (``reference''); three sites
had a riparian buffer (reserve) zone of trees left standing along each
side of the stream (``buffer''); and three sites were clear-cut to the
stream margin without a riparian buffer zone (``no buffer'').

Field site selection criteria were chosen \emph{a priori} to identify
comparable streams and riparian zones (Table 1). Using geographic
information system data provided by MKRF, we identified clear-cut
cut-blocks that were harvested no more than five years earlier, in
Arcmap 10.6.1 (ESRI, Redlands, CA, USA). The selected buffer and no
buffer sites were logged three to five years earlier. At the buffer
sites, the average width of the buffer zone was 13.0 \selectlanguage{ngerman}± 2.8 m, and ranged
from 11.0 to 16.2 m. The study sites met Richardson and Danehy's (2007)
criteria for a headwater stream of a mean width \textless{}3 m and
catchment area \textless{}100 ha. The riparian zones at the study
reaches had a gentle slope gradient below 30°, with an average bank
slope of 13.2° ± 8.4 (Table 1). This ensured comparability of
groundwater table dynamics between sites, since stream water levels have
more control on riparian water table levels when the stream bank slope
has a lower gradient (Burt and others 2002).

\par\null

Table 1. Characteristics of riparian study sites alongside headwater
streams under differing forestry management conditions in Malcolm Knapp
Research Forest, British Columbia, Canada. Values represent mean ±
\emph{SD} of three sites for each treatment. See Table A1 in Appendix A
for the values for each site.\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
Reference & No buffer & Buffer\tabularnewline
Stream bankfull width (m) & 2.3 \selectlanguage{ngerman}± 1.7 & 1.4 \selectlanguage{ngerman}± 0.7\tabularnewline
Catchment area (ha) & 27.3 \selectlanguage{ngerman}± 19.0 & 6.63 \selectlanguage{ngerman}± 6.3\tabularnewline
Elevation (m) & 305.5 \selectlanguage{ngerman}± 36.5 & 329 \selectlanguage{ngerman}± 37.4\tabularnewline
Reach length (m) & 64.0 \selectlanguage{ngerman}± 9.2 & 46.3 \selectlanguage{ngerman}± 11.2\tabularnewline
Bank slope (°) & 37.7 \selectlanguage{ngerman}± 22.8 & 18.8 \selectlanguage{ngerman}± 6.6\tabularnewline
Stream slope (°) & 8.7 \selectlanguage{ngerman}± 5.2 & 7.9 \selectlanguage{ngerman}± 3.7\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{ngerman}

\par\null

\textbf{Greenhouse gas and soil sampling}

The net terrestrial biosphere-atmospheric exchange of
CO\textsubscript{2}, CH\textsubscript{4}, and N\textsubscript{2}O was
measured using closed, static chambers (Figure A1 in Supplemental
Materials). Gas samples were collected on approximately a monthly basis
from June to September, 2019. At each site, six chambers were placed
along the study reach, on level ground, about 1 to 2 m from the stream
bank-full margin, in order to capture an area within the zone of
influence of the stream (Gregory and others 1991). Chambers (diameter of
30.5 cm, height of 23 cm) made of grey PVC pipe were permanently
inserted about 10 cm below the soil surface at least 10 days (on average
23 days) prior to the first gas sampling to reduce the effects of soil
and root disturbances.

At each site, the chambers were stratified according to local
groundwater discharge conditions, in groundwater discharge (DIS) and
non-groundwater discharge (ND) microsites, in order to account for some
of the high spatial variability associated with GHG fluxes from soils
(Vidon and others 2015). These DIS areas, or discrete riparian inflow
points, occur when upland-originating groundwater converges and
discharges in a depression in the topography of the riparian zone
(Kuglerová and others 2014). The DIS areas were identified in Arcmap
10.6.1 using a 1 m digital elevation model (DEM) and flow accumulation
modelling using a channelization threshold of 1 ha. This modelling
process assumes that topography and gravity control water movement, and
that the groundwater flow path follows the ground surface (Kuglerová and
others 2014). The DIS areas were then confirmed with field observations
of topography, wetness, and hydrophilic vegetation.

During gas sampling, a PVC lid was placed on top of the chamber and
headspace air samples were taken at 0, 15, 30, and 45 minutes after
closure. Headspace air samples of 20 mL were taken from a rubber septa
sampling port in the middle of the lid using a 23 gauge needle and a 50
mL syringe after pumping 20 mL of the headspace gas twice to facilitate
mixing. The gas sample was then injected into a pre-evacuated 12 mL
exetainer (LabCo Ltd., Lampeter, Wales) until over-pressurized. After
gas sampling, air temperature of the headspace was recorded and two
ambient air samples were taken for reference.

Sampling was performed between 9:15 and 16:30 h to capture peak fluxes
and reduce the effects of diurnal variation (Parkin and Venterea 2010).
Given the difficulty of sampling 54 chambers in one day, three sites
were sampled per day over three days, in randomized order within
treatment, each month. Gas samples were analysed on a 7890A gas
chromatograph (Agilent Technologies Inc., CA, USA) equipped with a flame
ionization detector and an electron capture detector (Agilent
Technologies Inc., CA, USA).

On each gas sampling date, volumetric soil moisture (± 3\%) was recorded
at each chamber using a GS3 ProCheck portable probe (Decagon Devices,
Inc., Washington, USA) by using the mean of three readings, each no more
than 0.5 m from each chamber, at a depth of 5.5 cm from the LFH layer.
The depth to the water table was also measured on each sampling date by
blowing into a thin tube attached to a meter stick lowered into a well
until the bubbling noise of the groundwater was heard, and corresponding
depth on the meter stick was noted. The well was made of perforated PVC
pipe wrapped in landscape fabric installed at least 40 cm deep into the
soil. Based on the groundwater table level data from the wells installed
at each chamber, eight DIS areas were re-classified after the fact in
cases where the well was dry for at least 80\% of the sampling
occasions. Over the entire sampling period, continuous soil temperature
readings (± 0.5°C) were taken at 1 hr intervals using iButton®
dataloggers (DS1992L- Thermochron and DS1923- Hygrochron, Maxim
Integrated Products, USA) buried about 10 cm below the soil surface. At
each site, one ibutton was buried adjacent to a chamber in a DIS and ND
area, respectively, and an additional ibutton was buried at the most
upstream chamber, 0.5 m and 1.5 from stream bank-full width,
respectively. Air temperature (± 0.04°C) was measured at each site using
two HOBO U23 Pro v2 data loggers (Onset Computer Corporation, MA, USA)
located 0.5 m and 1.5 m from the stream bank-full width at each study
reach.

\textbf{Statistical analysis}

Gas flux rates were calculated by linear regression of gas
concentrations over time. Each time series was evaluated for goodness of
fit by visual inspection (Collier and others 2014). Additional quality
control measures included visual inspection for abnormally high and low
values outside the range of reported riparian emissions, as well as
Cook's Distance statistical test (Zuur and others 2007). In sum, these
quality control measures resulted in the removal of 11\% of flux rate
data points for CO\textsubscript{2}, 26\% for CH\textsubscript{4}, and
34\% for N\textsubscript{2}O. Using the ideal gas law, the flux rate was
converted to \selectlanguage{greek}µ\selectlanguage{english}mol, and then the molecular mass was used to translate
this value into \selectlanguage{greek}µ\selectlanguage{english}g or mg. These equations are described by Collier and
others (2014). For statistical analysis, we used the software
\emph{R}3.6.1 (R Core Team 2020). We used linear mixed effects (LME)
models to evaluate the forest management effects on GHG fluxes using the
``glmmTMB'' package (Brooks and others 2017). The models included the
AR(1) autoregressive covariance structure to account for temporal
autocorrelation and repeated measures (Kravchenko and Robertson 2015).
The model residuals were tested for normality and homogeneity of
variance. When the model residuals violated the assumption of normality,
they were transformed and tested again. In the case of models with
N\textsubscript{2}O flux rate as the response variable, the flux data
were log-transformed. We used a \emph{post hoc} Tukey's HSD test to
compare pairwise differences in treatment levels. For all statistical
analyses, significance was accepted at p \textless{} 0.05.

\textbf{Results}

\textbf{Environmental variables}

Mean soil temperature (June to September) was, on average, the lowest at
the reference sites (13.6 \selectlanguage{ngerman}± 1.5 °C; mean ± \emph{SD} ), intermediate at
the buffer sites (14.4 ± 1.3 °C), and highest at the no buffer sites
(14.9 ± 1.3 °C) (Figure 2). Maximum and mean daily air temperature
followed the same trend, with a mean temperature of 14.5 ± 2.0 °C, 14.8
±2.2 °C, and 15.3 ± 2.6 °C, at the reference, buffer, and no buffer
sites, respectively. Mean soil temperature was similar at the
groundwater discharge (DIS) areas (14.1 ± 1.6 °C) compared to the ND
areas (14.5 ± 1.5 °C).

Mean soil moisture (measured as volumetric soil water content) was
highest at no buffer sites (Figure 3A). The mean soil moisture from June
to September was 43.3 ± 14.4\%, 45.5 ±16.7\%, 50.4 ± 14.3\% at the
reference, buffer, and no buffer sites, respectively. In terms of local
groundwater conditions, mean soil moisture was significantly higher in
the DIS areas at 55.4 ± 11.4\% compared to 41.6 ± 15.1\% in the ND
areas, across all treatments.

Mean depth to the groundwater table was the lowest at the no buffer
sites, and was significantly lower than the buffer and reference sites
(Figure 3B). The mean depth to the groundwater table (June to September)
was 28.7 ± 9.6 cm, 26.2 ± 12.7 cm, and 15.9 ± 8.9 cm at the reference,
buffer, and no buffer sites, respectively. In terms of local groundwater
conditions, mean depth to the groundwater table was significantly lower
at the DIS areas (20.0 ± 12.6 cm) compared to the ND areas (27.4 ± 10.1
cm), across all treatments. There was no statistically significant
difference in daily average soil temperature and soil moisture between
treatments.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 2. Mean daily soil temperature \textasciitilde{}10 cm below the
soil surface in the riparian zone of headwater streams in the Pacific
coastal rainforest of British Columbia across reference (R, n = 3),
buffer (B, n = 3), and no buffer (NB, n = 3) treatments from June to
October 2019.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 3. Mean volumetric water content (A) and depth to the groundwater
table (B) in the riparian zone of headwater streams in the Pacific
coastal rainforest of British Columbia across reference (R, n = 3),
buffer (B, n = 3), and no buffer (NB, n = 3) treatments, as well as in
groundwater discharge (DIS) areas and in non-groundwater discharge (ND)
areas from June to October 2019. Boxplots display the median, 25th and
75th percentiles, whiskers (1.5 times the IQR), and individual outliers
(dots), for this and subsequent boxplots.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 4. Riparian forest soil carbon dioxide (A), methane (B), and
nitrous oxide (C) flux rates from reference (R; n = 3), buffer (B; n =
3), and no buffer (NB; n = 3) treatments alongside headwater streams in
the Pacific coastal temperate rainforest of British Columbia across five
sampling periods from June to October, 2019. Arrows indicate outliers
along with their values.

\textbf{Carbon dioxide}

Mean soil CO\textsubscript{2} efflux (mg CO\textsubscript{2}-C
m\textsuperscript{-2} h\textsuperscript{-1}) for the reference, buffer,
and no buffer sites for the entire sampling period (June to September)
was 65.7 \selectlanguage{ngerman}± 29.9, 76.0 ± 39.1, 71.5 ± 40.9, respectively (Figure 4A).
Based on the linear mixed effects (LME) model,
CO\textsubscript{2}emissions were not significantly different between
treatments (Table 2). However, over the sampling period,
CO\textsubscript{2} emissions were, on average, 16\% higher at the
buffer sites and 9\% higher at the no buffer sites compared to the
reference sites, respectively. Mean soil CO\textsubscript{2} emissions
peaked in the middle of the growing season, with 85.9 ± 38.5 mg
CO\textsubscript{2} m\textsuperscript{-2}h\textsuperscript{-1} in July
and 83.6 ± 42.0 mg CO\textsubscript{2}m\textsuperscript{-2}
h\textsuperscript{-1} in August. Mean soil CO\textsubscript{2} emissions
were the lowest in the spring followed by the autumn, with 53.1 ± 24.78
mg CO\textsubscript{2}m\textsuperscript{-2} h\textsuperscript{-1} in
June and 56.9 ± 33.9 mg CO\textsubscript{2} m\textsuperscript{-2}
h\textsuperscript{-1} in September. CO\textsubscript{2} fluxes were not
significantly different between local groundwater conditions. On
average, over the study period CO\textsubscript{2} efflux was 64.9 ±
37.6 at DIS sites and 74.9 ± 36.3 mg CO\textsubscript{2}
m\textsuperscript{-2} h\textsuperscript{-1} at ND areas. Soil
temperature, soil moisture, and depth to the groundwater table were
significant predictors of CO\textsubscript{2} fluxes according to the
LME models, with a marginal r\textsuperscript{2} of 0.16, 0.11, and
0.06, respectively. For every degree increase in soil temperature, the
mean CO\textsubscript{2} flux rate increased by 8.13 mg. For every
percent increase in soil moisture, the mean CO\textsubscript{2} flux
rate decreased by 0.58 mg. For every cm increase in depth to the
groundwater table, the mean CO\textsubscript{2}flux rate increased by
0.48 mg.

\par\null

Table 2. Pairwise difference between Treatment levels (reference, R;
buffer, B; and no buffer, NB) using Tukey's HSD \emph{post hoc} test for
the linear mixed effects models explaining the dynamics of carbon
dioxide, methane, and nitrous oxide fluxes, respectively. All models
included the autocorrelation term ``AR1(Week + 0 \textbar{}
Site/Chamber)''. Bolded comparison indicates a significant effect at
\emph{p} \textless{} 0.05.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Model} & \textbf{Comparison} & \textbf{Est.} & SE &
p\tabularnewline
CO\textsubscript{2} \textasciitilde{} Treatment & R - B & -8.65 & 11.2 &
0.72\tabularnewline
R - NB & -1.86 & 11.4 & 0.99 &\tabularnewline
B - NB & 6.79 & 11.4 & 0.82 &\tabularnewline
CH\textsubscript{4} \textasciitilde{} Treatment & R - B & -6.65 & 6.82 &
0.59\tabularnewline
\textbf{R - NB} & \textbf{-22.35} & \textbf{6.96} & \textbf{\textless{}
0.01} &\tabularnewline
B - NB & -15.71 & 6.97 & 0.07 &\tabularnewline
N\textsubscript{2}O \textasciitilde{} Treatment & R - B & 0.33 & 0.14 &
0.06\tabularnewline
\textbf{R - NB} & \textbf{0.39} & \textbf{0.14} & \textbf{0.02}
&\tabularnewline
B - NB & 0.06 & 0.14 & 0.90 &\tabularnewline
\bottomrule
\end{longtable}

\par\null

\textbf{Methane}

Mean soil CH\textsubscript{4} fluxes (\selectlanguage{greek}µ\selectlanguage{english}g CH\textsubscript{4}-C
m\textsuperscript{-2} h\textsuperscript{-1}) for the reference, buffer,
and no buffer sites for the entire sampling period (June to September)
were -26.3 \selectlanguage{ngerman}± 17.7, -19.7 ± 21.6, and -9.1 ± 22.2, respectively (Figure
4B). Therefore, on average, all of the treatments were a net
CH\textsubscript{4} sink over the study period. Based on the LME model,
CH\textsubscript{4} uptake was significantly different between
treatments (R - NB: p \textless{} 0.01, Table 2);
CH\textsubscript{4}uptake was on average 1.26 times lower at the buffer
sites than the reference sites, and 3.71 times lower at the no buffer
sites than the reference sites. CH\textsubscript{4} fluxes were
significantly (p \textless{} 0.001) different between local groundwater
conditions, with CH\textsubscript{4} uptake being significantly lower in
the DIS areas (Figure 5). CH\textsubscript{4} gas flux was -11.2 ± 22.5
\selectlanguage{greek}µ\selectlanguage{english}g CH\textsubscript{4} m\textsuperscript{-2} h\textsuperscript{-1} at
the DIS areas while -24.4 \selectlanguage{ngerman}± 19.2 \selectlanguage{greek}µ\selectlanguage{english}g
CH\textsubscript{4}m\textsuperscript{-2} h\textsuperscript{-1} at the ND
sites, on average, for the entire study period. Soil moisture and depth
to groundwater were significant predictors of CH\textsubscript{4} fluxes
according to the LME models, with a marginal r\textsuperscript{2} of
0.37 and 0.46, respectively. For every percent increase in soil
moisture, mean CH\textsubscript{4} flux rate increased by 0.50 \selectlanguage{greek}µ\selectlanguage{english}g. For
every cm increase in depth to the groundwater table, mean
CH\textsubscript{4}flux rate decreased by 0.67 \selectlanguage{greek}µ\selectlanguage{english}g.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Figure 5. Riparian forest soil methane flux rates from reference (R; n =
3), buffer (B; n = 3), and no buffer (NB; n = 3) treatments, and from
groundwater discharge (DIS) and non-groundwater discharge (ND) areas
along headwater streams in the Pacific coastal temperate rainforest of
British Columbia in 2019 (June - September). Boxplots that do not share
the same uppercase letter show significant differences based on LME
models (\emph{p} \textless{} 0.05).

\textbf{Nitrous oxide}

Mean soil N\textsubscript{2}O fluxes (\selectlanguage{greek}µ\selectlanguage{english}g N\textsubscript{2}O-N
m\textsuperscript{-2} h\textsuperscript{-1}) for the reference, buffer,
and no buffer sites for the entire sampling period (June to September)
were 3.6 \selectlanguage{ngerman}± 2.6, 2.1 ± 2.4, and 1.7 ± 1.6, respectively (Figure 4C).
According to the LME model, there was a treatment effect on
N\textsubscript{2}O fluxes, with significantly (R - NB: p = 0.02, Table
2) higher fluxes at the no buffer sites compared to the reference sites.
Over the sampling period, N\textsubscript{2}O fluxes were, on average
1.70 times lower at the buffer sites and 2.05 times lower at the no
buffer sites, compared to the reference sites, respectively.
Additionally, mean soil N\textsubscript{2}O fluxes were the highest in
the spring, and gradually declined throughout the summer to the fall,
with the highest monthly mean measured in June (4.1 ± 2.9 \selectlanguage{greek}µ\selectlanguage{english}g
N\textsubscript{2}O m\textsuperscript{-2} h\textsuperscript{-1}) and
lowest monthly mean in September (1.6 \selectlanguage{ngerman}± 2.2 \selectlanguage{greek}µ\selectlanguage{english}g N\textsubscript{2}O
m\textsuperscript{-2} h\textsuperscript{-1}). N\textsubscript{2}O fluxes
were not significantly different between local groundwater conditions.
On average, over the study period N\textsubscript{2}O efflux was 2.5 \selectlanguage{ngerman}±
2.2 at the DIS areas and 2.4 ±2.5 \selectlanguage{greek}µ\selectlanguage{english}g N\textsubscript{2}O
m\textsuperscript{-2} h\textsuperscript{-1}at the ND areas. None of the
environmental variables (i.e. soil moisture, soil temperature, and depth
to the groundwater table) were significant predictors of
N\textsubscript{2}O fluxes.

\par\null

Table 2. Pairwise difference between Treatment levels (reference, R;
buffer, B; and no buffer, NB) using Tukey's HSD \emph{post hoc} test for
the linear mixed effects models explaining the dynamics of carbon
dioxide, methane, and nitrous oxide fluxes, respectively. All models
included the autocorrelation term ``AR1(Week + 0 \textbar{}
Site/Chamber)''. Bolded comparison indicates a significant effect at
\emph{p} \textless{} 0.05.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Model} & \textbf{Comparison} & \textbf{Est.} & SE &
p\tabularnewline
CO\textsubscript{2} \textasciitilde{} Treatment & R - B & -8.65 & 11.2 &
0.72\tabularnewline
R - NB & -1.86 & 11.4 & 0.99 &\tabularnewline
B - NB & 6.79 & 11.4 & 0.82 &\tabularnewline
CH\textsubscript{4} \textasciitilde{} Treatment & R - B & -6.65 & 6.82 &
0.59\tabularnewline
\textbf{R - NB} & \textbf{-22.35} & \textbf{6.96} & \textbf{\textless{}
0.01} &\tabularnewline
B - NB & -15.71 & 6.97 & 0.07 &\tabularnewline
N\textsubscript{2}O \textasciitilde{} Treatment & R - B & 0.33 & 0.14 &
0.06\tabularnewline
\textbf{R - NB} & \textbf{0.39} & \textbf{0.14} & \textbf{0.02}
&\tabularnewline
B - NB & 0.06 & 0.14 & 0.90 &\tabularnewline
\bottomrule
\end{longtable}

\par\null

\textbf{Discussion}

For the sampling period, the riparian forest soils examined in this
study were a net sink of CH\textsubscript{4,} and a net source of
CO\textsubscript{2} and N\textsubscript{2}O. The reference sites had
significantly higher N\textsubscript{2}O emissions and significantly
higher CH\textsubscript{4} uptake than the sites with no buffer.
CH\textsubscript{4} uptake was significantly higher in the ND areas
compared to the DIS areas, reflecting the difference in soil moisture
and resulting aerobic conditions required for methanotrophy and
anaerobic conditions required for methanogenesis (Oertel and others
2016). Soil temperature, soil moisture, and depth to the groundwater
table were significant predictors of CO\textsubscript{2} emissions. Soil
moisture and depth to the groundwater table were significant predictors
of CH\textsubscript{4} fluxes.

\textbf{Effects of forest harvest}

Although riparian zones are widespread across the global landscape, we
found very few studies examining GHG fluxes from the riparian zones of
small streams (Goodrick and others 2016; Soosaar and others 2011), and
even fewer for headwater streams (Chang and others 2014; De Carlo and
others 2019a). Due to the distinct environmental conditions of riparian
zones (Vidon and others, 2018), the effects of forest harvest on GHG
fluxes are likely to differ here from upland soils. Riparian zones of
headwater streams in particular are unique due to their steep
geomorphology, high groundwater influence, and susceptibility to low
flows (Richardson and Danehy 2007). Therefore, this study fills the
knowledge gap of the effects of forest harvest on GHG fluxes from
riparian zones of headwater streams.

Clear-cutting has inconsistent effects on CO\textsubscript{2} emission
rates (Striegl and Wickland 1998; Ullah and others 2009), with studies
reporting a decline (Striegl and Wickland 1998), an increase (Lavoie and
others 2013; Paul-Limoges and others 2015), or no change (K\selectlanguage{ngerman}ähkönen and
others 2002) in CO\textsubscript{2} emissions following harvest. In this
study, there was no significant difference in
CO\textsubscript{2}emission rates between treatments, although
CO\textsubscript{2}emissions were highest at the buffer sites. This lack
of a significant treatment difference may have been because of the
distinct conditions in riparian forests compared to upland forests.
Riparian zone soils have high moisture levels due to shallow water
tables and a strong groundwater influence (Goodrick and others 2016).
Therefore, the rise in temperature following forest harvest that can
explain the rise in CO\textsubscript{2} following harvest in upland
forests (Lavoie and others 2013), may be buffered by the generally
moister and cooler soils of riparian forests (Clinton and others 2010),
resulting in a less distinct rise in CO\textsubscript{2} emissions
following harvest in riparian forests compared to upland forests.
Moreover, the mild mean annual temperature and narrow range in annual
temperature in our study region may have meant limited temperature
differences, resulting in a small effect size of the treatments.

Soil temperature, soil moisture, and depth to the groundwater table were
significant predictors of CO\textsubscript{2} fluxes. This is consistent
with the large body of literature on the drivers of soil respiration
(Luo and Zhou 2006). Soil respiration usually increases exponentially
with temperature, reaches a maximum, and then declines (Luo and Zhou
2006). Temperature controls many aspects of soil respiration from the
activity of cellular enzymes, to root growth and microbial activity (Luo
and Zhou 2006). Soil moisture is another well-established driver of soil
CO\textsubscript{2} emissions, with the common conceptual relationship
where soil respiration is low under dry conditions, reaches a maximum at
intermediate soil levels, and decreases at high soil moisture content
where anaerobic conditions depress aerobic microbial activity (Luo and
Zhou 2006). The interactive effects of these two variables on soil
respiration is a key knowledge gap (Meyer and others 2018). Our research
provides valuable information to help understand the effects of these
factors on soil respiration in the unique riparian environment.

The results of our study were in line with other studies, which have
also found that clear-cutting increased CH\textsubscript{4} efflux from
the soil (Kähkönen and others 2002; Wu and others 2011). This rise can
be attributed to higher average summer soil temperatures, greater soil
moisture, and higher dissolved organic carbon concentrations in
clear-cuts (Ullah and others 2009; Wu and others 2011). Forest harvest
can result in soil compaction, reduced transpiration, and a rise in the
groundwater table, all of which promote waterlogging and anaerobic
conditions (Christiansen and others 2017; Gundersen and others 2010). In
our study, soil moisture and depth to the groundwater table were
significant predictors of CH\textsubscript{4} fluxes, while temperature
was not. In agreement with our results, CH\textsubscript{4} uptake was
three times lower following clear-cutting in a temperate spruce forest
in southern Germany (Wu and others 2011). In another study,
clear-cutting turned a spruce forest soil in Finland from a sink to a
source of CH\textsubscript{4}, with a 40\% decrease in
CH\textsubscript{4} consumption rates (Kähkönen and others 2002). The
lower CH\textsubscript{4} uptake following forest harvest may be
explained by the harmful impacts of soil disturbance on methanotrophic
bacteria, resulting in the inhibition of CH\textsubscript{4}-oxidation
(Le Mer and Roger 2001; Wu and others 2011). Alternatively, the
anaerobic conditions created by higher soil moisture concentrations
following forest harvest can promote the production of
CH\textsubscript{4} (Wu and others 2011). A clear-cut wetland in Québec,
Canada produced 131 times more CH\textsubscript{4} than the undisturbed
wetland soil, likely due to higher soil temperature and soil moisture in
the clear-cut (Ullah and others 2009). In our study, the no buffer sites
still were a net sink, albeit a weak sink, of CH\textsubscript{4} over
the growing season. This is likely because unlike many wetlands, most
riparian soils do not have consistently anoxic soils, which promote
methanogenesis (Dalal and Allen 2008). Given that there was no
significant difference in CH\textsubscript{4} flux rates between the
buffer and reference sites, it appears that riparian buffers may be
effective in preserving soil ecosystem conditions contributing to
CH\textsubscript{4} fluxes. Consequently, riparian buffer zones may be
an effective strategy for forest managers interested in maintaining
CH\textsubscript{4} balance in riparian zone soils.

The lower N\textsubscript{2}O emissions in the no buffer sites compared
to undisturbed riparian zones was a surprising result because many other
studies have reported an increase in N\textsubscript{2}O emissions
following forest harvest. Typically, forest harvest can increase soil
moisture and mobilize soil nitrogen, promoting N\textsubscript{2}O
emissions from logged forest sites (Kreutzweiser and others 2008).
Higher N\textsubscript{2}O emissions were seen following forest harvest
in the taiga region of eastern Siberia, Russia (Takakai and others
2008). Additionally, N\textsubscript{2}O emissions were 2.7 times higher
in clear-cut than in mature black spruce forest soil in Québec, Canada
(Ullah and others 2009). However, these studies were not conducted in
riparian forests, which have unique conditions such as shallow water
tables, high soil organic matter quality and quantity, and high soil
nitrogen availability, unlike most upland forests (Knoepp and Clinton
2009; Vidon and others 2018). Given that forests are typically sources
of N\textsubscript{2}O (Dalal and Allen 2008), the lower
N\textsubscript{2}O fluxes in the no buffer compared to the reference
sites is a departure from undisturbed ecosystem function. The
unexpectedly low N\textsubscript{2}O fluxes at the no buffer sites could
be explained by the mechanical soil disturbance in the riparian zone
caused by forest harvest. The disruption of the structure and function
of microbial communities responsible for nitrification and
denitrification could contribute to the comparatively low
N\textsubscript{2}O fluxes at the no buffer sites (Tan and others 2005).
Meanwhile, N\textsubscript{2}O fluxes at the buffer sites were not
significantly different from the reference sites, thus, riparian buffers
may be effective in preserving soil ecosystem conditions contributing to
N\textsubscript{2}O fluxes. A decline in soil
CO\textsubscript{2}emissions was attributed to the disruption of the
soil surface and death of tree roots following the clear-cutting of a
jack pine stand in Saskatchewan (Striegl and Wickland 1998). Moreover,
soil compaction as a result of forest harvest has been found to reduce
net nitrification rates in the forest floor and mineral soil as well as
reduce the soil microbial biomass nitrogen (Tan and others 2005).

None of our measured environmental variables (i.e. soil temperature,
soil moisture, and depth to the groundwater table) were significant
drivers of N\textsubscript{2}O fluxes. Thus, perhaps some environmental
variables not measured in this study could explain some of the
unexplained treatment differences. For instance, soil nitrogen
concentrations are an important driver of N\textsubscript{2}O fluxes
(Christiansen and others 2012). A large proportion of nitrogen in upland
soils is transferred to riparian ecosystems, where it can be retained
via biological assimilation or removed via denitrification (Pinay and
others 2018). Denitrification rates were positively correlated with soil
nitrate content in a riparian forest along the Louge River in south-west
France (Pinay and others 1993). Moreover, streamwater nitrate
concentrations have been found to increase in the short term following
forest harvest in western North America due to enhanced soil
nitrification rates (Feller 2005). This increased flow of nitrate from
the soil into streams in the short term, subsequently returns to
pre-harvest levels due to uptake by rapidly growing biomass (Feller
2005). This phenomenon could explain the lower N\textsubscript{2}O
emissions we observed at the sites with rapidly re-growing vegetation,
harvested over three years earlier, compared to the reference sites.

In addition to the effects of external nutrient inputs, the potential
for nitrogen retention and removal can vary between climatic regions,
based on differences in soil moisture conditions and nitrogen supply. In
temperate regions with high humidity, such as our study region, high
soil moisture promotes nitrification and denitrification (Christiansen
and others 2012). In contrast, Mediterranean and arid regions have lower
denitrification rates due to low water availability and short residence
time of water and solutes (Pinay and others 2018).

In the context of other studies, the soils in our study area have a
moderate nutrient content and the GHG flux rates in this study were
comparable to those reported in other temperate riparian zones. The
soils in undisturbed stands at Malcolm Knapp Research Forest have
previously been categorized as medium-nutrient (Collins and others
2001), with reported mineral soil nitrate content of 2.5 kg
ha\textsuperscript{-1} and a C:N ratio of 23 (Turk and others 2008).
Mean gas flux rates at the reference sites (June to September) were 65.7
± 29.9 mg CO\textsubscript{2}
m\textsuperscript{-2}h\textsuperscript{-1}, -26.3 ± 17.7 \selectlanguage{greek}µ\selectlanguage{english}g
CH\textsubscript{4}-C m\textsuperscript{-2} h\textsuperscript{-1}, and
3.6 \selectlanguage{ngerman}± 2.6 \selectlanguage{greek}µ\selectlanguage{english}g N\textsubscript{2}O-N m\textsuperscript{-2}
h\textsuperscript{-1}. Since we measured gas fluxes from June to
September, our average flux rates should be slightly higher than annual
flux rates reported from temperate studies that include winter months
when microbial activity is lower, and hence flux rates are lower. The
average annual CO\textsubscript{2} flux rate in flood-prone riparian
forest in an agricultural landscape along the White River in Indiana,
USA measured 48.8 mg CO\textsubscript{2}m\textsuperscript{-2}
h\textsuperscript{-1} and was significantly related to the C:N ratio
(16.4) of soil organic matter (Jacinthe and others 2015). At a temperate
riparian forest in an agriculturally dominated landscape in Ontario,
Canada, the mean annual CO\textsubscript{2} emissions were 18 mg
CO\textsubscript{2}m\textsuperscript{-2} h\textsuperscript{-1}, with a
soil organic carbon content of 84.1 g C kg\textsuperscript{-1} and a
total nitrogen content of 12.5 g N kg\textsuperscript{-1} (De Carlo and
others 2019a). At the same location, mean annual N\textsubscript{2}O
emissions were 5.93 \selectlanguage{greek}µ\selectlanguage{english}g m\textsuperscript{-2} h\textsuperscript{-1}, and
were significantly correlated with soil total nitrogen (12.5 g N
kg\textsuperscript{-1}) (De Carlo and others 2019b). A riparian forest
in New Jersey had a C:N ratio of 21 and a N\textsubscript{2}O emission
rate of 0.9 \selectlanguage{greek}µ\selectlanguage{english}g N m\textsuperscript{-2} h\textsuperscript{-1} (Ullah and
Zinati 2006). Nevertheless, there is a lack of studies about GHG
emissions from riparian zones of headwaters streams, moreover most of
the literature is in agriculture-dominated landscapes and not in
forested riparian areas impacted by forest harvest practices.

\textbf{Effects of local groundwater conditions}

Landscape features that dictate soil characteristics, such as local
microtopography, can be important for predicting riparian GHG emissions
as they may affect the spatial distribution of soil moisture, nutrients,
and organic matter, thus consequently affecting the intensity of GHG
emissions (Jacinthe and Vidon 2017; Soosaar and others 2011). Local
groundwater discharge conditions may create particularly important
microsite variation in the riparian zones of streams. Soil conditions in
DIS areas have been found to have higher base cations, soil moisture, pH
levels, and nitrogen concentrations when compared to surrounding soils
(Giesler and others 1998). These soil conditions may influence the
processes controlling soil GHG fluxes. However, it is unknown how forest
harvest in the riparian zone might influence conditions in DIS areas,
and how GHG fluxes may subsequently be influenced. We hypothesized that
due to the higher soil moisture at DIS areas, the emission of
anaerobically produced CH\textsubscript{4} and N\textsubscript{2}O would
be higher than at ND areas. There were no significant differences
between the DIS and ND areas for CO\textsubscript{2} and
N\textsubscript{2}O emissions, although ND areas generally had higher
CO\textsubscript{2} emissions on average and DIS areas generally had
higher N\textsubscript{2}O emissions. However, CH\textsubscript{4}uptake
was significantly lower in the DIS sites compared to the ND sites. This
means that DIS sites were more likely to be CH\textsubscript{4} sources,
while ND sites were more likely to be CH\textsubscript{4} sinks. Similar
results were found in riparian zones in central Indiana, where a
topographic depression in the riparian forest accounted for 78\% of
annual CH\textsubscript{4} emissions, despite only covering
\textless{}8\% of the total land area (Jacinthe and others 2015).
Additionally, GHG fluxes from flowing stream waters have been found to
peak downstream of DIS areas, due to their lateral gas inputs from
riparian soils (Lupon and others 2019). Given that CH\textsubscript{4}
fluxes were highest in DIS areas at no buffer sites, the results of our
study provide additional support for the use of hydrologically adapted
buffers, which provide more protection for wet areas, such as DIS areas,
in the riparian zone (Tiwari and others 2016). The variable buffer width
adapted to site-specific hydrological conditions can protect
biogeochemical and ecological functions as well as provide economic
savings when compared to fixed-width buffers (Tiwari and others 2016).

\textbf{Conclusions}

In conclusion, our work shows that forest harvest and local groundwater
conditions influence GHG emissions from riparian forest soils alongside
headwater streams. Our results demonstrate that riparian buffers may be
effective in protecting soil ecosystem functions contributing to
CH\textsubscript{4} and N\textsubscript{2}O fluxes. Nevertheless, our
findings should not diminish the importance of maintaining intact
riparian forests for other benefits, such as the unique biodiversity
riparian areas sustain. Given our finding that local groundwater
conditions play an important role in driving CH\textsubscript{4} fluxes,
forest managers may choose to consider hydrologically adapted buffers to
reduce CH\textsubscript{4} emissions. This new information about the
effects of forest harvest in the riparian zone on GHG flux rates should
be considered in local policy discussions regarding how forest harvest
in the riparian zone can contribute to climate change, and what can be
done to mitigate or diminish the impacts. Considering that many small
streams are left unprotected in British Columbia (Kuglerov\selectlanguage{ngerman}á and others
2020) and elsewhere, perhaps the leverage of climate change mitigation
may influence policy changes leading to increased retention of riparian
buffer zones in the region. In sum, this research may be useful to
forest managers interested in managing riparian buffer zones for GHG
balance and climate change mitigation.

\textbf{Acknowledgements}

We thank the European Commission and the Natural Sciences and
Engineering Research Council (Canada) for funding, in the frame of the
collaborative international Consortium SOSTPRO financed under the 2016
Joint Call of the WaterWorks 2015 ERA-NET Cofund. This ERA-NET is an
integral part of the 2016 Joint Activities developed by the Water and
FACCE JPIs. We are grateful to NSERC and UBC for additional support
through scholarships and other funds. We appreciate the hard work
contributed by volunteers, field assistants, and other members of the
Stream and Riparian Research Lab, namely, Olivia Hester who helped
extensively with the field work. Thank you to David Levy-Booth and Chun
Chung Yeung for their advice on GHG monitoring, as well as countless
others for their inputs and counsel.

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