Nitrous oxide fluxes in undisturbed riparian wetlands located in agricultural catchments: Emission, uptake and controlling factors

Soil Biology & Biochemistry 68 (2014) 291e299

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Nitrous oxide fluxes in undisturbed riparian wetlands located in agricultural catchments: Emission, uptake and controlling factors Joachim Audet a, *, Carl C. Hoffmann a, Peter M. Andersen a, Annette Baattrup-Pedersen a, Jan R. Johansen a, Søren E. Larsen a, Charlotte Kjaergaard b, Lars Elsgaard b a b

Aarhus University, Department of Bioscience, Vejlsøvej 25, 8600 Silkeborg, Denmark Aarhus University, Department of Agroecology, P.O. Box 50, Blichers Allé 20, 8830 Tjele, Denmark

a r t i c l e i n f o

a b s t r a c t

Article history: Received 24 June 2013 Received in revised form 16 August 2013 Accepted 7 October 2013 Available online 22 October 2013

Riparian wetlands can mitigate nutrient pollution to the aquatic environment when they serve as biogeochemically active buffer zones between arable land and water bodies. Nevertheless, as a result of the extensive nutrient transformation, wetlands hold a potential of atmospheric emission of greenhouse gases such as nitrous oxide (N2O). To quantify this potential, fluxes of N2O were measured over a year at 48 sub-plots located in four Danish riparian wetlands with contrasting characteristics of soil parameters and groundwater dynamics. The wetlands were hydrologically and physically relatively undisturbed, but they were all located in catchments dominated by agriculture. Individual fluxes of N2O measured using the static chamber technique ranged from
44 to 122 mg N2OeN m
2 h
1 (n ¼ 800) while cumulative fluxes ranged from
0.25 to 0.50 g N2OeN m
2 yr
1 (n ¼ 48), i.e., showing both uptake and emission of N2O. Modeling of the fluxes using linear mixed models revealed that ammonium in the groundwater was the only tested variable having a significant effect on N2O fluxes. Tentative maximum estimates showed that only about 2.2% of the total Danish N2O emissions could be related to freshwater wetlands (representing about 1.3% of the land area). Further, the low and frequently negative N2O fluxes (n ¼ 294) indicated that riparian wetlands, at least under some conditions, may actually reduce atmospheric N2O pollution, although the measured N2O uptake was weak. In conclusion, riparian ecosystems with only minor disturbances are not generally to be considered as hotspots of N2O emissions in the landscape. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Riparian wetlands Greenhouse gas Nitrous oxide Sink Source Uptake

1. Introduction Riparian wetlands are situated at the interface between terrestrial and aquatic ecosystems. In their natural state, such wetlands generally have a high biodiversity and serve as floodwater storage and filter for waterborne pollutants (de Groot et al., 2002). Wetlands can also sequester carbon (C) as photosynthetic plant uptake of carbon dioxide (CO2) often exceeds ecosystem respiration under water-saturated soil conditions (Reddy and DeLaune, 2008). The overall contribution of wetlands to climate change is still a matter of debate, though, as wetlands can also produce greenhouse gases (GHG), and they are the largest natural emitter of methane (CH4; IPCC, 2007). Hence, while some studies suggest that wetlands are net sources of GHG because of CH4 emissions (Bridgham et al.,

* Corresponding author. Tel.: þ45 871 585 62; fax: þ45 871 58 901. E-mail addresses: [email protected] (J. Audet), [email protected] (C.C. Hoffmann), [email protected] (P.M. Andersen), [email protected] (A. Baattrup-Pedersen), [email protected] (J.R. Johansen), [email protected] (S.E. Larsen), C.Kjaergaard@ agrsci.dk (C. Kjaergaard), [email protected] (L. Elsgaard). 0038-0717/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.soilbio.2013.10.011

2006), other reports argue that over a long time horizon (>100 yrs) wetlands can be considered as sinks for GHG (Mitsch et al., 2012; Whiting and Chanton, 2001). For example, in a modeling study (Mitsch et al., 2012) showed that over a time horizon of >300 yrs most wetlands are net C sinks because CH4 emissions are compensated by C sequestration in the soil. In addition to the exchange of CO2 and CH4, riparian soil may also contribute to fluxes of nitrous oxide (N2O). In water-saturated soils, it is assumed that the main N2O-producing process is deni
trification, which is the reduction of nitrate (NO
3 ) and nitrite (NO2 ) to the gaseous end products N2O or dinitrogen (N2) (Tiedje, 1982). Although the fraction of produced N2O might be small (Groffman et al., 1998), it may have important consequences for atmospheric pollution because N2O is a potent GHG with a global warming potential 298 times as strong as CO2 over a 100 yrs time horizon (IPCC, 2007). The capacity of wetland soils to transform aqueous N to gaseous N has been exploited within the context of wetland restoration where efficiency in mitigating aquatic N pollution has been documented (Hoffmann and Baattrup-Pedersen, 2007; Hoffmann et al., 2011). Yet, some studies have expressed concerns about

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Table 1 Soil characteristics (top soil, 0e30 cm) and dominant vegetation at the study sites. Wetland

Plot

Soil type (0e30 cm)

Soil pH

Bulk density (g cm
3)

TN (% DW)

N In top soil (g cm
2)

C/N ratio (mol mol
1)

Dominant vegetation (% of plant cover indicated in parentheses)

Karup

P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3

Fibric peat Hemist peat Hemist peat Hemist peat Hemist peat Sapric peat Sapric peat Fibric peat Hemist peat Fibric peat Fine sand Fine sand

6.6 6.7 6.8 6.3 6.3 7.0 6.3 6.5 5.8 5.5 4.7 4.8

0.12 0.29 0.53 0.10 0.30 0.14 0.36 0.04 0.23 0.17 1.25 1.10

1.20 0.80 0.39 2.40 0.79 1.30 0.46 2.30 1.70 1.50 0.16 0.28

0.043 0.070 0.062 0.072 0.071 0.055 0.050 0.028 0.117 0.077 0.060 0.092

20.4 20.4 18.8 21.4 20.7 21.5 15.7 22.8 16.5 18.7 15.3 15.8

Calliergonella cuspidata (45), Lotus pedunculatus (20), Festuca rubra (9) Menyanthes trifoliata (49), Carex nigra (22), C. cuspidata (15) Comarum palustre (36), Glyceria maxima (20), Cirsium palustre (16) M. trifoliata (32), C. cuspidata (26), F. rubra (12) Filipendula ulmaria (29), Equisetum fluviatile (25), L. pedunculatus (22) Lysimachia vulgaris (47), C. cuspidata (22), C. palustre (19) G. maxima (79), Epilobium hirsutum (11), Equisetum palustre (5) C. cuspidata (27), F. rubra (25), M. trifoliata (9) F. rubra (25), C. nigra (24), C. cuspidata (23) Lychnis flos-cuculi (16), Carex disticha (10), Agrostis stolonifera (9) Deschampsia flexuosa (36), Ranunculus repens (26), F. rubra (12) Holcus mollis (28), R. repens (21), D. flexuosa (20)

Haderup

Simested

Villestrup

DW, dry weigh.

diverting N rich waters toward wetlands because of the risk of increased N2O emissions (Freeman et al., 1997; Groffman et al., 2000; Verhoeven et al., 2006; Bouwman et al., 2013; Hefting et al., 2013). This risk is especially present in catchments having high proportion of agricultural land use because their groundwaters are often contaminated by NO
3 derived from fertilizers (Smith et al., 1999; Moss, 2008). Existing studies from natural riparian wetlands have generally shown high spatial and temporal variability in N2O fluxes (Hefting et al., 2006; Jacinthe et al., 2012; Jørgensen et al., 2012); some riparian soils act as sources of N2O (e.g., Walker et al., 2002; Hefting et al., 2003) and others as N2O sinks (Blicher-Mathiesen and Hoffmann, 1999; Dhondt et al., 2004). Parameters such as NO
3 load, oxygen content and pH are known to influence N2O production (Reddy and DeLaune, 2008), but the dynamic interactions between the factors responsible for the production and emission of N2O in the field are still difficult to incorporate into predictive models (Groffman et al., 2000; Baggs, 2008; Morse et al., 2012; Butterbach-Bahl et al., 2013). To provide some insights into the N2O dynamics in natural riparian wetlands we measured N2O emissions over a year in four temperate riparian wetlands that were located in agricultural catchments but had relatively well preserved physical conditions (i.e., naturally meandering streams and absence of drainage in the wetland). We aimed at quantifying the seasonal and spatial dynamics of the fluxes of N2O and at identifying the controllers of these fluxes using a modeling approach. We hypothesized that N2O emission from such riparian wetlands could be substantial at least under certain environmental conditions because these ecosystems are located in agricultural catchment and hence may receive high loads of NO
3 . The study therefore targeted undisturbed wetlands located in contrasting areas and showing different characteristics in terms of, e.g., groundwater chemistry, groundwater level and soil properties, such as pH and mineral N content. 2. Materials and methods 2.1. Study sites The riparian wetlands were located along four naturally meandering streams, representing some of the least disturbed streams in Denmark (Baattrup-Pedersen et al., 2013). One site was located along River Karup (N 56.417, E 9.002 ), one along River Haderup (N 56.404 , E 9.009 ), one along River Simested (N 56.687, E 9.484 ) and one along River Villestrup (N 56.739 , E 9.958 ). Agriculture was the dominant land use representing 61% (Karup), 51% (Haderup), 82% (Simested) and 46% (Villestrup) of the river catchment area.

In each riparian wetland, three plots (P1, P2 and P3) having an area of ca. 25 m2 were selected based on differences in plant community types (Audet et al., 2013b) that we used as a way to capture environmental variability. All plots were located within 100 m from the stream channel. Although most of the plots may occasionally be flooded in periods with high discharges, no inundations by stream water occurred during the study period (June 2010eJuly 2011). However, some plots were inundated because of high groundwater level. Annual precipitation during the study period at the sites ranged between 688 and 831 mm and the mean temperature was 7.6  C. Each plot comprised four sub-plots (55  55 cm) that were established in order to cover spatial heterogeneities. The main characteristics of the plots regarding soil and vegetation characteristics are presented in Table 1, and a more detailed description of the plots and sub-plots is given in Audet et al. (2013b). The vegetation at Karup and at Haderup was not managed, whereas the study sites at Simested and Villestrup were grazed by cattle. Mineral fertilizer (200 kg N ha
1) was applied to the study site at Villestrup every year, including areas near the three study plots. At all study sites, the vegetation inside the plots was neither mowed nor grazed during the study period. 2.2. Soil characteristics and mineral N At each plot, undisturbed volumetric soil cores (5 cm diam., n ¼ 2) were collected at 0e30 cm depth with a liner sampler (04.15.SB, Eijkelkamp, NL) within a distance of ca. 5 m from the subplots. Soil pH was determined in the field directly in the wet soil cores using a field pH meter (HACH HQ11d) and a field electrode (Radiometer pH C2051-8). Soil bulk density was measured after drying one of the cores at 105  C. The second core was oven dried at 60  C and ground-milled before determination of soil C and N contents by dry combustion (elemental analysis) at AGROLAB GmbH, Germany, using international standards (ISO 10694, 1995; ISO 13878, 1998). The top soil (0e30 cm) content of total N was calculated as: N content (g g
1)  bulk density (g cm
3)  30 (cm). The mineral N content of the soil was determined on three occasions (March, May and June 2011) by randomly taking five individual cores (3.5 cm diam., 30 cm length) at every plot. The cores were pooled and stored in the dark at 2  C before further processing (within one week). The soil samples were thoroughly mixed and visible roots and stones removed. Duplicate samples of 10 g soil were extracted with 1 M KCl at a soil:KCl ratio of 1:4 (wt:wt) by shaking end-over-end for 60 min. The samples were then centrifuged (1000 rpm, 5 min) and the extracts filtered through Whatman GF/C glass fiber filters. The filtrates were collected and stored at 2  C prior to colorimetric analysis for NHþ 4 (DS/EN ISO 11905,

J. Audet et al. / Soil Biology & Biochemistry 68 (2014) 291e299

2004) and combined NO2eNO
3 analysis by the vanadium chloride reduction method (Braman and Hendrix, 1989) using an NOx analyzer model 42c (Thermo Environmental Instruments Inc., Waltham, USA).

293

Groundwater chemistry and groundwater level (GWL) were monitored at all 12 plots by installing piezometers with an inner diameter of 40 mm and a screen length of 50 cm (PEH tubes; Rotek A/S, Sdr Felding, Denmark). Installation of piezometers and collection of water samples were done as previously described (Audet et al., 2013b). Water samples were collected at each field visit (ca. every third week) and were directly filtered (0.45 mm nylon membrane SNY 4525, Frisenette, Denmark) into an 11-ml polypropylene tube (Sarstedt, Nümbrecht, Germany). Additionally, on five occasions between February and August 2011, samples of the groundwater entering the four wetlands were taken using piezometers (>100 cm depth) placed at the boundary between the terrestrial upland and the wetland. Nitrate was analyzed on a Dionex ICS-1500 IC system (Dionex corp.; Sunnyvale, USA) after filtration at 0.22 mm (nylon membrane SNY 2225; Frisenette) following method (DS/EN ISO 10304, 1996). The concentration of ammonium (NHþ 4 ) was analyzed colorimetrically (DS/EN ISO 11905, 2004).

(55  55 cm) was inserted into the soil to a depth of 10 cm to support the removable chambers. The chambers were made of opaque PVC (60  60  40 cm) and equipped with a fan, vent tube, closed-cell rubber profile, temperature sensor, digital thermometer and rubber septum largely following the design of Drösler (2005). The total height of the chamber with collar was about 40e45 cm above ground. To prevent soil disturbance during sampling wooden boardwalks were installed in front of the collars. At some occasionally flooded plots, the boardwalks rested on wooden poles (2 m length) inserted into the soil. The fluxes of N2O were monitored by placing the static chamber on the flanges of the frames and taking chamber gas samples after a deployment time of 0, 15, 30, 45 and 60 min. At each sampling event, a 20-ml gas sample was withdrawn in a nylon syringe mounted with a hypodermic needle and injected into a 12-ml pre-evacuated vial (Exetainer, Labco, High Wycombe, UK). The samples were stored at room temperature in the dark (typically 3e5 days) before gas analysis of N2O using a dual-inlet Agilent 7890 GC system interfaced with a CTC CombiPal autosampler (Agilent, Nærum, Denmark) configured and calibrated with standard gases as described in detail by Petersen et al. (2012). Soil temperatures at 10 cm depth (T-10 cm) were recorded manually at every sub-plot during flux measurements using a high precision thermometer (GMH3710, Omega Newport, Deckenpfronn, Germany).

2.4. Gas monitoring and temperature

2.5. Calculation of N2O fluxes

The monitoring of N2O fluxes started in June 2010 and ended in July 2011. The monitoring was carried out at ca. three week intervals in all 48 sub-plots, yielding a total of 800 flux measurements during the study period. Nitrous oxide fluxes between soil and atmosphere were measured using a two-part static chamber technique (Petersen et al., 2012). At each sub-plot, a PVC collar

Nitrous oxide fluxes were calculated by fitting linear regressions using the HMR procedure which is available as an add-on package (Pedersen, 2011) in the R software (version 2.15.1) (R Development Core Team, 2012). All fluxes were included in the modeling although the slope (b) of most linear concentration time-series was not significantly different from zero (n ¼ 734) when tested for b ¼ 0

2.3. Groundwater chemistry and water parameters

20

(a) Karup

(b) Haderup

0

Groundwater table (cm above ground)

−20 −40 P1 P2 P3

−60 −80 20

(c) Simested

(d) Villestrup

0 −20 −40 −60 −80 J

J A S O N D J F M A M J 2010 2011 Time (month and year)

J

J

J A S O N D J F M A M J 2010 2011

J

Time (month and year)

Fig. 1. Dynamics of groundwater level in the 12 studied wetland plots at four wetlands. Discontinuous lines indicate interruption of the monitoring due to freezing of the water.

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Table 2 Mean concentration in nitrate and ammonium in the groundwater entering the wetland (mean  standard deviation, n ¼ 5 except Karup n ¼ 4). Wetland

Nitrate (mg N L
1)

Karup Haderup Simested Villestrup

8.40 0.06 5.33 5.50

   

5.64 0.02 0.64 2.31

Ammonium (mg N L
1) 0.003 0.012 0.005 0.144

   

0.00 0.01 0.00 0.30

at a ¼ 0.05. Yet, with the current data coverage in the concentration time-series (n ¼ 5), and for a linear flux with, e.g., r2 ¼ 0.85, the statistical power (1
b) of the test for b ¼ 0 was only 63%, as calculated by the Fisher z transformation procedure, indicating a low probability of rejecting b ¼ 0 when this was false (Zar, 2010).

P1 1.5

Therefore, we chose to include all fluxes in the analysis except for a few aberrant fluxes (2% of the dataset) that were detected by visual inspection of the concentration time-series and judged as no flux datasets (i.e. they were set to zero). A non-linear increase in gas concentration over time can be observed when using non-steady state chambers (Davidson et al., 2002), but this was not the case in the present dataset containing mostly low fluxes. Linear interpolation between sampling dates was used to estimate the cumulative gas fluxes for N2O.

2.6. Statistics The statistical analysis was performed using the R software (version 2.15.1) (R Development Core Team, 2012). Empirical

P2

P3

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

(i)

(j)

(k)

(l)

J J A S O N D J F M A M J J 2010 2011

J J A S O N D J F M A M J J 2010 2011

J J A S O N D J F M A M J J 2010 2011

Time (month and year)

Time (month and year)

Time (month and year)

NO3−N NH4−N

Karup

1.0

0.5

Haderup

1.0

0.5

0 1.5

1.0

Simested

Groundwater ammonium and nitrate concentration (mg N L-1)

0 1.5

0.5

0 1.5

Villestrup

1.0

0.5

0

Fig. 2. Concentration of groundwater ammonium and nitrate in the 12 studied wetland plots at four wetlands. Discontinuous lines indicate interruption of the monitoring due to freezing of the water.

J. Audet et al. / Soil Biology & Biochemistry 68 (2014) 291e299 Table 3 Soil mineral N concentration in the 12 studied wetland plots (0e30 cm depth). Wetland

Plot

March 2011

May 2011

NHþ 4

NHþ 4

NO
3
1

mg N kg DW Karup

Haderup

Simested

Villestrup

P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3

NA 0.6 0.0 1.9 5.9 2.7 4.2 6.2 5.5 29.0 0.7 11.8

soil

NA 0.4 0.3 1.7 0.1 0.9 2.4 4.4 0.8 1.3 0.2 1.3

mg N kg DW NA 8.7 0.4 3.0 7.3 5.8 7.3 9.3 4.7 11.4 2.3 1.9

July 2011 NO
3


1

soil

NA 0.6 0.1 0.0 0.0 0.0 1.2 3.2 0.2 0.2 0.2 1.2

NHþ 4 mg N kg DW NA 14.4 7.2 7.0 7.7 1.7 3.2 5.2 6.7 2.9 2.7 5.0

NO
3
1

soil

NA 0.3 0.0 0.0 0.0 0.0 1.2 3.2 1.7 2.3 0.5 0.0

DW, dry weight. NA, not analyzed.

relationships between selected environmental parameters and fluxes of N2O were analyzed with linear mixed effect modeling (Zuur et al., 2009) using the R package “nlme” and the function “lme” (Pinheiro et al., 2012). To control variance heterogeneity and to ensure Gaussian dis
þ tribution, groundwater concentrations of NHþ 4 and NO3 (GW-NH4
and GW-NO3 ) were ln transformed prior to analysis. Sub-plots were included in the model as random factors. Based on Spearman correlation scores and using the function “corvif” from the R package “AED” (Zuur, 2009) to detect collinearity, the following independent variables were included in the model as
fixed effects: GW-NHþ 4 , GW-NO3 , soil pH, top soil N content and the interaction GWL  T-10 cm. As mineral N in the soil was determined only three times over the sampling period, this parameter could not be included in the model. Model selection was performed using the command “anova” in R to compare models with an analysis of deviance and removing terms of least significance one at a time in a backward stepwise fashion. The model was checked for normality and homogeneity of the variance by visual inspection of plots of residuals against fitted values. Model fit was evaluated as pseudoR2 calculated using function lmmR2 (Maj, 2011). Unless otherwise indicated, central tendencies are reported as mean  standard error (SE). 3. Results The contrasting soil and vegetation characteristics of the 12 plots are shown in Table 1. Most of the plots were located on peat soils except Villestrup P2 and P3 which were located on mineral soils (Table 1). Total nitrogen content in the soils differed markedly varying between 0.16 and 2.40% dry weight (DW) with the lowest values at Villestrup in P2 and P3 located on mineral soils. Soil pH was also low in these plots (pH < 5), whereas all other plots were located on soils having circumneutral pH (Table 1). Mean groundwater level ranged between
57 and 2.5 cm at Villestrup P2 (Fig. 1(d)) and Karup P2 (Fig. 1(a)), respectively. Some of the plots had relatively constant GWL over the study period (e.g., Karup P1 and Haderup P1), while others had more fluctuating GWL (e.g., Karup P3 and Villestrup P1). The groundwater entering the wetþ
1 lands was generally rich in NO
3 (>5 mg N L ) and low in NH4 (<0.15 mg N L
1) except at Haderup, that was low in NO
3 (<0.1 mg N L
1) (Table 2). The yearly mean concentration of inorþ ganic N (NO
3 þ NH4 ) in the groundwater in the upper soil was relatively low (below 0.4 mg N L
1) at all sites except at Villestrup

295

P2 and P3 (Fig. 2(k) and (l)), where slightly higher values occurred (up to 0.7 mg N L
1), probably because these plots were fertilized and because the N reduction in these mineral soils is likely to be þ low. In general, groundwater NHþ 4 (GW-NH4 ) was higher when the GWL was low (i.e. in summer) whereas groundwater NO
3 (GW
NO
3 ) seemed more variable over the study period (Fig. 2). Soil NO3 was always below 5 mg N kg
1 soil DW, while soil NHþ was more 4 variable among plots and over time, with values ranging between 0 and 29 mg N kg
1 soil DW (Table 3). The fluxes of N2O measured in all sub-plots are presented in Fig. 3. The individual fluxes were generally close to zero in all subplots except in the plots located on mineral soils at Villestrup P2 and P3 (Fig. 3(k) and (l)) where episodic emission events were observed. Overall, the individual N2O fluxes ranged from
44e to 122 mg N2OeN m
2 h
1. Yearly N2O emission across the sub-plots ranged between
0.25 and 0.5 g N2OeN m
2 y
1 (Table 4). Even within a single plot, the spatial variation in yearly N2O fluxes among sub-plots was sometime large, like at Villestrup P2 where emission was measured in sub-plot 1 (0.36 g N2OeN m
2 y
1) whereas uptake of N2O occurred in sub-plot 3 (
0.03 g N2OeN m
2 y
1; Table 4). The two plots with the highest N2O emissions, Villestrup P2 and P3 (0.10  0.08 and 0.29  0.08 g N2OeN m
2 y
1, respectively (n ¼ 4)), also had the lowest water table (annual mean
57 and
39 cm), the lowest soil pH and the highest groundwater concentration of NHþ 4 (annual mean 0.3 and 0.6 mg N L
1). However, the concentration of groundwater NO
3 was comparable with the other plots (annual mean 0.3 and 0.2 mg N L
1 at Villestrup P2 and P3, respectively.). The mixed modeling revealed that GW-NHþ 4 was the only significant explanatory variable for the fluxes of N2O, whereas no effect of the GWL, soil pH or GW-NO
3 could be demonstrated (Table 5). Overall, the explanatory power of the model was low (R2 ¼ 0.034). 4. Discussion The emission rates of N2O reported in the present study were in general low or even slightly negative. Thus, about 37% of the N2O fluxes were negative (i.e. 294 individual fluxes), indicating consumption of N2O by the soil. The ability of soils to act as N2O sink is a documented process (Chapuis-Lardy et al., 2007; Syakila et al., 2010) and is based on the consumption of N2O during nitrification or during denitrification, especially under NO
3 limitation (Chapuis-Lardy et al., 2007; Schlesinger, 2013; Wrage et al., 2004; Wu et al., 2013). Yet, few studies have evidenced consumption of N2O in riparian soils (Blicher-Mathiesen and Hoffmann, 1999; Dhondt et al., 2004). The wetlands investigated in the present study were located in catchments that are dominated by agricultural land use and some of them received NO
3 contaminated groundwater. Previous research have shown that, in riparian areas receiving high NO
3 loads, there is a risk of elevated N2O emissions (Hefting et al., 2003) as high NO
3 loads may hinder final reduction of the N2O produced during denitrification (Blackmer and Bremner, 1978; Lind et al., 2013). However, the emission of N2O at our plots was generally low and GW-NO
3 concentration in the upper soil did not have a significant effect on N2O fluxes according to the mixed model.
Although some of the sites received high NO
3 load, GW-NO3 at the
plots was generally low, indicating a removal of NO3 in the wetlands. Such efficient removal of NO
3 probably stimulated N2O uptake as the consumption of atmospheric N2O during denitrification is often linked to soils with low N availability (Chapuis-Lardy et al., 2007; Schlesinger, 2013; Wu et al., 2013). Hence our study show that, besides the capacity for wetland soils to remove NO
3 (e.g. Hill, 1996; Hoffmann et al., 2012; Lind et al., 2013), some wetlands are capable of consuming the greenhouse gas N2O and thereby

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P1 50

Sub-plot 1 Sub-plot 2

Sub-plot 3 Sub-plot 4

P2

P3

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

(i)

(j)

(k)

(l)

J J A S O N D J F M A M J J 2010 2011

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J J A S O N D J F M A M J J 2010 2011

Time (month and year)

Time (month and year)

Time (month and year)

Karup

25 0 −25 −50 50

Haderup

0 −25 −50 50 25

Simested

Nitrous oxide flux (µg N2O-N m-2 h-1)

25

0 −25 −50 150

Villestrup

100 50 0 −50

Fig. 3. Fluxes of nitrous oxide in the 48 sub-plots at the four studied wetlands. The black dots and line represent the mean of fluxes at sub-plot level (n ¼ 4). Note the different scale of the Y-axis at Villestrup.

mitigate not only water eutrophication but also atmospheric N2O pollution. The only sub-plots emitting more than 0.2 g N2OeN m
2 y
1 were located at Villestrup P2 and P3 to which fertilizers were applied. Yet, even at Villestrup P2 and P3 the N2O fluxes were comparatively low and in the lower range of the emissions (
0.02 to 3.12 g N2OeN m
2 y
1) reported in various studies of riparian soils (Table 6). Villestrup P2 and P3 had a low GWL facilitating oxygen diffusion into the top soil; consequently, the emission of N2O might not only be due to denitrification but may also be related to nitrification, as suggested by the positive significant effect of GW-NHþ 4 on the N2O fluxes identified by the mixed effect model. Additionally, these two plots also had the lowest soil pH (<5), and low pH may potentially influence both denitrification and nitrification processes and especially inhibits

the activity of the N2O reductases responsible for the conversion of N2O to N2 during denitrification (Baggs and Philippot, 2011; Knowles, 1982; Simek and Cooper, 2002; van den Heuvel et al., 2011). Nevertheless, it is difficult to conclude on the main processes responsible for N2O production in the present study as N2O might not only be produced in the wetland itself, but also elsewhere in the catchment and transported by the groundwater to the wetland. Apart from Villestrup P2 and P3 the study sites generally had relatively high GWL and low N2O emissions, which is comparable with the data compiled by Couwenberg et al. (2011) showing that for peat soils N2O emission usually occurs when GWL is deeper than 15 cm. Yet, the present modeling of the fluxes did not demonstrate any significant effect of the GWL or soil pH. The overall explanatory power of the model was low which substantiates the

J. Audet et al. / Soil Biology & Biochemistry 68 (2014) 291e299 Table 4 Cumulative fluxes of nitrous oxide in the 48 sub-plots at the four wetland study sites (sub-plots designated as S1 to S4 at each plot). Mean flux at plot level is indicated in bold (mean  standard error, n ¼ 4). Wetland

Plot

N2O g N2OeN m
2 y
1

Karup

Haderup

Simested

Villestrup

P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3

S1

S2

S3

S4

Mean

SE


0.01 0.17
0.01
0.07 0.06 0.02
0.04 0.03
0.03 0.12 0.36 0.22

0.03 0.00
0.02 0.00
0.01 0.00 0.02 0.06
0.01 0.05 0.04 0.35


0.03
0.09 0.01 0.10 0.02 0.10
0.05 0.13 0.04 0.07
0.03 0.08

0.04
0.25 0.00 0.06 0.10 0.00
0.02 0.03 0.07
0.06 0.04 0.50

0.01 L0.04 L0.01 0.02 0.04 0.03 L0.02 0.06 0.02 0.04 0.10 0.29

±0.01 ±0.08 ±0.00 ±0.03 ±0.02 ±0.02 ±0.01 ±0.02 ±0.02 ±0.03 ±0.08 ±0.08

Table 5 Relationships between soil and environmental parameters and individual fluxes of N2O (in mg N2OeN m
2 h
1) explored with a linear mixed model. Environmental variables

Estimate

Std error

Df

t-Value

P-value

(Intercept) GWL  T-10 cm T-10 cm ( C) GWL (cm)
1 GW-NO
3 (ln mg L )
1 GW-NHþ 4 (ln mg N L ) Soil pH

8.60

1.57

547

5.49

2.11

0.49

547

4.27

*** ns ns ns ns *** ns

ns, Not significant; ***p < 0.001.

difficulty in establishing reliable estimators of N2O fluxes (Baggs, 2008; Morse et al., 2012; Butterbach-Bahl et al., 2013), and this was especially the case in our dataset presenting mostly low fluxes. More frequent sampling of soil mineral N could possibly have improved the modeling, especially by sampling the active denitrification zone in the soil; however, only top soil samples were collected in the present study. The physical conditions of the riparian wetlands presented in this study were relatively well preserved (i.e. naturally meandering streams and natural hydrological connections between the stream and the riparian zone), potentially providing optimum conditions for complete denitrification (i.e. high GWL and available C) and subsequently low N2O emissions. However, whether these results apply to other wetland types, especially those that are more disturbed, needs to be confirmed. Particularly riparian soils with low pH (<5) appear to be critical for N2O emissions (van den Heuvel et al., 2011).

297

The absence of high N2O emissions in our study might also be related to the use of static chambers allowing only small-sized areas to be monitored; our results and several studies have shown great spatial variability in N2O emissions (Ball et al., 1997; Hefting et al., 2006; Audet et al., 2013a; van den Heuvel et al., 2009), and possible hotspots may have been missed despite the effort to cover spatial variation as identified by plant community types. Further, temporal variability of N2O emission can be high even on a daily scale (Jørgensen et al., 2012), and although 800 flux measurements were conducted in our study, this sampling frequency may have missed hot moments of N2O emission (Butterbach-Bahl et al., 2013; Groffman et al., 2009; McClain et al., 2003). To establish a tentative estimate of the contribution of N2O emissions from Danish riparian wetland soils, we multiplied the highest emission rate found in our study (0.50 g N2OeN m
2 y
1) by the area of freshwater wetlands in Denmark (569 km2; Stjernholm and Kjeldgaard, 2005). This amounts to a yearly emission of about 0.45 Gg N2O as compared with the 20 Gg N2O emitted in Denmark in 2010 (Nielsen et al., 2013). Hence, riparian wetland N2O emissions represent only about 2.2% of the total Danish N2O emissions (as worst-case scenario), while according to Nielsen et al. (2013) agriculture accounts for 84% of the N2O emissions. Conversely, if the area of Danish wetland acted as sink for N2O and taking the highest uptake rate from our study (
0.25 g N2OeN m
2 y
1) the maximum consumption by Danish wetlands would reduce the Danish emission by 1.1%. Although, Danish wetlands represent only 1.3% of the total land area, such low contribution to the total N2O emission probably holds for many countries of the temperate zone. Hence, whereas some studies have debated the role of wetlands as potential large N2O emitters (Freeman et al., 1997; Groffman et al., 2000; Verhoeven et al., 2006; Bouwman et al., 2013), our results show that riparian wetlands are not general hotspots for N2O in the landscape. If this conclusion can be extended to restored wetlands reaching an equilibrium state, it appears that the beneficial effect of wetlands on the aquatic environment is not achieved at the expense of N2O emissions, at least in wetlands with soil pH > 5 (Hefting et al., 2013; van den Heuvel et al., 2011). In conclusion, low and negative N2O emission rates were measured in relatively preserved natural wetlands, with contrasting characteristics in hydrology, soil and vegetation, although these wetlands were located in catchments dominated by agricultural activities. The consistent occurrence of negative fluxes indicates that, besides the beneficial function of wetlands in mitigating aquatic pollution, these ecosystems may at least temporarily mitigate atmospheric N2O pollution, albeit the present N2O consumption was low. However, the parameters controlling the fluxes were difficult to disentangle and only an effect of NHþ 4 was identified. Overall, this study suggests that N2O emission from relatively well

Table 6 Nitrous oxide fluxes in riparian soils reported from various countries. References

Country

Wetland type

Annual N2O flux (g N2OeN m
2 y
1)

Method

Dhondt et al. (2004) Ambus and Christensen (1995) Audet et al. (2013a) This study Soosaar et al. (2011) Hefting et al. (2003) Kim et al. (2009) Walker et al. (2002) Weller et al. (1994)

Belgium Denmark Denmark Denmark Estonia The Netherlands USA USA USA

Three riparian sites mixed vegetation, forest and grass Riparian grassland Riparian wetland first year after restoration Four riparian sites Two riparian sites alder forest Two riparian buffers forest and grass Three riparian forest buffers Two riparian grasslands Riparian forest


0.02 to 0.21 0.066 0.03e3.12
0.25 to 0.50 0.04e0.07 0.2e2.0 0.29 2.42e2.45 0.035

SC SC SC SC SC SC SC OC SC, OC

SC, static chambers; OC, open chambers.

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preserved riparian ecosystems is low even when receiving NO
3 contaminated groundwater. Acknowledgments The authors wish to acknowledge the support of the landowners of our study sites: Paul T. Jensen, Niels Barslund, Ellen M. Jensen and Gert Risgård. The authors are grateful for the assistance by the staff at Aarhus University: Erling Pedersen, Uffe Mensberg, Henrik Stenholt, Stig T. Rasmussen, Kitte Gerlich, Marlene V. Skjærbæk, Dorte Nedergaard, Tinna Christensen and Anne M. Poulsen. This work is part of the MONITECH project funded by the Danish Council for Strategic Research, grant no. 2104-08-0050. References Ambus, P., Christensen, S., 1995. Spatial and seasonal nitrous-oxide and methane fluxes in Danish forest-ecosystems, grassland-ecosystems, and agroecosystems. J. Environ. Qual. 24, 993e1001. Audet, J., Elsgaard, L., Kjaergaard, C., Larsen, S.E., Hoffmann, C.C., 2013a. Greenhouse gas emissions from a Danish riparian wetland before and after restoration. Ecol. Eng. 57, 170e182. Audet, J., Johansen, J.R., Andersen, P.M., Baattrup-Pedersen, A., Brask-Jensen, K.M., Elsgaard, L., Kjaergaard, C., Larsen, S.E., Hoffmann, C.C., 2013b. Methane emissions in Danish riparian wetlands: ecosystem comparison and pursuit of vegetation indexes as predictive tools. Ecol. Indicat. 34, 548e559. Baggs, E.M., 2008. A review of stable isotope techniques for N2O source partitioning in soils: recent progress, remaining challenges and future considerations. Rapid Commun. Mass Spectrom. 22, 1664e1672. Baggs, E.M., Philippot, L., 2011. Nitrous oxide production in the terrestrial environment. In: Moir, J.W.B. (Ed.), Nitrogen Cycling in Bacteria e Molecular Analysis. Caister Academic Press, Norfolk, pp. 211e232. Ball, B.C., Horgan, G.W., Clayton, H., Parker, J.P., 1997. Spatial variability of nitrous oxide fluxes and controlling soil and topographic properties. J. Environ. Qual. 26, 1399e1409. Blackmer, A.M., Bremner, J.M., 1978. Inhibitory effect of nitrate on reduction of N2O to N2 by soil microorganisms. Soil Biol. Biochem. 10, 187e191. Blicher-Mathiesen, G., Hoffmann, C.C., 1999. Denitrification as a sink for dissolved nitrous oxide in a freshwater riparian fen. J. Environ. Qual. 28, 257e262. Bouwman, A.F., Beusen, A.H.W., Griffioen, J., Van Groenigen, J.W., Hefting, M.M., Oenema, O., Van Puijenbroek, P.J.T.M., Seitzinger, S., Slomp, C.P., Stehfest, E., 2013. Global trends and uncertainties in terrestrial denitrification and N2O emissions. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 368, 20130112. Braman, R.S., Hendrix, S.A., 1989. Nanogram nitrite and nitrate determination in environmental and biological materials by vanadium (III) reduction with chemiluminescence detection. Anal. Chem. 61, 2715e2718. Bridgham, S., Megonigal, J., Keller, J., Bliss, N., Trettin, C., 2006. The carbon balance of North American wetlands. Wetlands 26, 889e916. Butterbach-Bahl, K., Baggs, E.M., Dannenmann, M., Kiese, R., ZechmeisterBoltenstern, S., 2013. Nitrous oxide emissions from soils: how well do we understand the processes and their controls? Philos. Trans. R. Soc. Lond. B: Biol. Sci. 368. Baattrup-Pedersen, A., Jensen, K.M.B., Thodsen, H., Andersen, H.E., Andersen, P.M., Larsen, S.E., Riis, T., Andersen, D.K., Audet, J., Kronvang, B., 2013. Effects of stream flooding on the distribution and diversity of groundwater-dependent vegetation in riparian areas. Freshw. Biol. 58, 817e827. Chapuis-Lardy, L., Wrage, N., Metay, A., Chotte, J.-L., Bernoux, M., 2007. Soils, a sink for N2O? A review. Glob. Change Biol. 13, 1e17. Couwenberg, J., Thiele, A., Tanneberger, F., Augustin, J., Bärisch, S., Dubovik, D., Liashchynskaya, N., Michaelis, D., Minke, M., Skuratovich, A., Joosten, H., 2011. Assessing greenhouse gas emissions from peatlands using vegetation as a proxy. Hydrobiologia 674, 67e89. Davidson, E.A., Savage, K., Verchot, L.V., Navarro, R., 2002. Minimizing artifacts and biases in chamber-based measurements of soil respiration. Agric. For. Meteorol. 113, 21e37. de Groot, R.S., Wilson, M.A., Boumans, R.M.J., 2002. A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol. Econ. 41, 393e408. Dhondt, K., Boeckx, P., Hofman, G., Van Cleemput, O., 2004. Temporal and spatial patterns of denitrification enzyme activity and nitrous oxide fluxes in three adjacent vegetated riparian buffer zones. Biol. Fertil. Soils 40, 243e251. Drösler, M., 2005. Trace Gas Exchange and Climatic Relevance of Bog Ecosystems, Southern Germany. Deparment of Ecology, Technical University of Munich, Munich, p. 182. DS/EN ISO 10304, 1996. Water Quality e Determination of Dissolved Fluoride, Chloride, Nitrite, Orthophosphate, Bromide, Nitrate and Sulfate Ions Using Liquid Chromatography of Ions e Part 1: Method for Water with Low Contaminant. DS/EN ISO 11905, 2004. Water Quality e Determination of Nitrogen e Part 1: Method Using Oxidative Digestion with Peroxydisulfate.

Freeman, C., Lock, M.A., Hughes, S., Reynolds, B., Hudson, J.A., 1997. Nitrous oxide emissions and the use of wetlands for water quality amelioration. Environ. Sci. Technol. 31, 2438e2440. Groffman, P., Butterbach-Bahl, K., Fulweiler, R., Gold, A., Morse, J., Stander, E., Tague, C., Tonitto, C., Vidon, P., 2009. Challenges to incorporating spatially and temporally explicit phenomena (hotspots and hot moments) in denitrification models. Biogeochemistry 93, 49e77. Groffman, P.M., Gold, A.J., Addy, K., 2000. Nitrous oxide production in riparian zones and its importance to national emission inventories. Chemosphere e Glob. Change Sci. 2, 291e299. Groffman, P.M., Gold, A.J., Jacinthe, P.A., 1998. Nitrous oxide production in riparian zones and groundwater. Nutr. Cycl. Agroecosyst. 52, 179e186. Hefting, M.M., Bobbink, R., de Caluwe, H., 2003. Nitrous oxide emission and denitrification in chronically nitrate-loaded riparian buffer zones. J. Environ. Qual. 32, 1194e1203. Hefting, M.M., Bobbink, R., Janssens, M.P., 2006. Spatial variation in denitrification and N2O emission in relation to nitrate removal efficiency in a N-stressed riparian buffer zone. Ecosystems 9, 550e563. Hefting, M.M., van den Heuvel, R.N., Verhoeven, J.T.A., 2013. Wetlands in agricultural landscapes for nitrogen attenuation and biodiversity enhancement: opportunities and limitations. Ecol. Eng. 56, 5e13. Hill, A.R., 1996. Nitrate removal in stream riparian zones. J. Environ. Qual. 25, 743e755. Hoffmann, C.C., Baattrup-Pedersen, A., 2007. Re-establishing freshwater wetlands in Denmark. Ecol. Eng. 30, 157e166. Hoffmann, C.C., Heiberg, L., Audet, J., Schønfeldt, B., Fuglsang, A., Kronvang, B., Ovesen, N.B., Kjaergaard, C., Hansen, H.C.B., Jensen, H.S., 2012. Low phosphorus release but high nitrogen removal in two restored riparian wetlands inundated with agricultural drainage water. Ecol. Eng. 46, 75e87. Hoffmann, C.C., Kronvang, B., Audet, J., 2011. Evaluation of nutrient retention in four restored Danish riparian wetlands. Hydrobiologia 674, 5e24. IPCC, 2007. Climate Change 2007: the Physical Science Basis. Contribution of Working Group I to the Fourth Assessment. Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 996 pp. ISO 10694, 1995. Soil Quality e Determination of Organic and Total Carbon after Dry Combustion (Elementary Analysis). ISO 13878, 1998. Soil Quality e Determination of Total Nitrogen Content by Dry Combustion (“Elemental Analysis”). Jacinthe, P.A., Bills, J.S., Tedesco, L.P., Barr, R.C., 2012. Nitrous oxide emission from riparian buffers in relation to vegetation and flood frequency. J. Environ. Qual. 41, 95e105. Jørgensen, C.J., Struwe, S., Elberling, B., 2012. Temporal trends in N2O flux dynamics in a Danish wetland e effects of plant-mediated gas transport of N2O and O2 following changes in water level and soil mineral-N availability. Glob. Change Biol. 18, 210e222. Kim, D.G., Isenhart, T.M., Parkin, T.B., Schultz, R.C., Loynachan, T.E., Raich, J.W., 2009. Nitrous oxide emissions from riparian forest buffers, warm-season and coolseason grass filters, and crop fields. Biogeosci. Discuss. 6, 607e650. Knowles, R., 1982. Denitrification. Microbiol. Rev. 46, 43e70. Lind, L.P.D., Audet, J., Tonderski, K., Hoffmann, C.C., 2013. Nitrate removal capacity and nitrous oxide production in soil profiles of nitrogen loaded riparian wetlands inferred by laboratory microcosms. Soil Biol. Biochem. 60, 156e164. Maj, A., 2011. lmmfit: Goodness-of-Fit-Measures for Linear Mixed Models with OneLevel-Grouping. http://CRAN.R-project.org/package¼lmmfit. McClain, M.E., Boyer, E.W., Dent, C.L., Gergel, S.E., Grimm, N.B., Groffman, P.M., Hart, S.C., Harvey, J.W., Johnston, C.A., Mayorga, E., McDowell, W.H., Pinay, G., 2003. Biogeochemical hot spots and hot moments at the interface of terrestrial and aquatic ecosystems. Ecosystems 6, 301e312. Mitsch, W.J., Bernal, B., Nahlik, A.M., Mander, Ü., Zhang, L., Anderson, C.J., Jørgensen, S.E., Brix, H., 2012. Wetlands, carbon, and climate change. Landsc. Ecol., 1e15. http://dx.doi.org/10.1007/s10980-012-9758-8. Morse, J.L., Ardon, M., Bernhardt, E.S., 2012. Using environmental variables and soil processes to forecast denitrification potential and nitrous oxide fluxes in coastal plain wetlands across different land uses. J. Geophys. Res.-Biogeosci. 117, G02023. Moss, B., 2008. Water pollution by agriculture. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 363, 659e666. Nielsen, O.K., Plejdrup, M.S., Winther, M., Hjelgaard, K., Nielsen, M., Hoffmann, L., Fauser, P., Mikkelsen, M.H., Albrektsen, R., Gyldenkærne, S., Thomsen, M., 2013. Projection of Greenhouse Gases 2011e2035. Aarhus University, DCE eDanish Centre for Environment and Energy, 179 pp. Pedersen, A.R., 2011. HMR: flux estimation with static chamber data. http://CRAN.Rproject.org/package¼HMR. Petersen, S.O., Hoffmann, C.C., Schäfer, C.M., Blicher-Mathiesen, G., Elsgaard, L., Kristensen, K., Larsen, S.E., Torp, S.B., Greve, M.H., 2012. Annual emissions of CH4 and N2O, and ecosystem respiration, from eight organic soils in Western Denmark managed by agriculture. Biogeosciences 9, 403e422. Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., R Development Core Team, 2012. nlme: Linear and Nonlinear Mixed Effects Models. http://CRAN.R-project.org/ package¼nlme. R Development Core Team, 2012. R: a Language and Environment for Statistical Computing. http://www.R-project.org/. Reddy, K.R., DeLaune, R.D., 2008. Biogeochemistry of Wetlands: Science and Applications. CRC Press, Boca Raton, Florida, p. 774. Schlesinger, W.H., 2013. An estimate of the global sink for nitrous oxide in soils. Glob. Change Biol.. http://dx.doi.org/10.1111/gcb.12239.

J. Audet et al. / Soil Biology & Biochemistry 68 (2014) 291e299 Simek, M., Cooper, J.E., 2002. The influence of soil pH on denitrification: progress towards the understanding of this interaction over the last 50 years. Eur. J. Soil Sci. 53, 345e354. Smith, V.H., Tilman, G.D., Nekola, J.C., 1999. Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environ. Pollut. 100, 179e196. Soosaar, K., Mander, Ü., Maddison, M., Kanal, A., Kull, A., Lõhmus, K., Truu, J., Augustin, J., 2011. Dynamics of gaseous nitrogen and carbon fluxes in riparian alder forests. Ecol. Eng. 37, 40e53. Stjernholm, M., Kjeldgaard, A., 2005. I&CLC2000 CORINE Land Cover Update in Denmark. Final report to European Commission DG Regio and EEA. National Environmental Research Institute, Silkeborg, Denmark, 43 pp. Syakila, A., Kroeze, C., Slomp, C.P., 2010. Neglecting sinks for N2O at the earth’s surface: does it matter? J. Integr. Environ. Sci. 7, 79e87. Tiedje, J.M., 1982. Denitrification. In: Page, A.L. (Ed.), Methods of Soil Analysis. Part 2, second ed. American Society of Agronomy, Madison, Wisconsin, USA, pp. 1011e1024. van den Heuvel, R.N., Bakker, S.E., Jetten, M.S., Hefting, M.M., 2011. Decreased N2O reduction by low soil pH causes high N2O emissions in a riparian ecosystem. Geobiology 9, 294e300. van den Heuvel, R.N., Hefting, M.M., Tan, N.C.G., Jetten, M.S.M., Verhoeven, J.T.A., 2009. N2O emission hotspots at different spatial scales and governing factors for small scale hotspots. Sci. Total Environ. 407, 2325e2332.

299

Verhoeven, J.T.A., Arheimer, B., Yin, C.Q., Hefting, M.M., 2006. Regional and global concerns over wetlands and water quality. Trends Ecol. Evol. 21, 96e103. Walker, J.T., Geron, C.D., Vose, J.M., Swank, W.T., 2002. Nitrogen trace gas emissions from a riparian ecosystem in southern Appalachia. Chemosphere 49, 1389e 1398. Weller, D.E., Correll, D.L., Jordan, T.E., 1994. Denitrification in riparian forests receiving agricultural discharges. In: Mitsch, W.J. (Ed.), Global Wetlands: Old World and New. Elsevier Science, pp. 117e131. Whiting, G.J., Chanton, J.P., 2001. Greenhouse carbon balance of wetlands: methane emission versus carbon sequestration. Tellus B 53, 521e528. Wrage, N., Velthof, G.L., Laanbroek, H.J., Oenema, O., 2004. Nitrous oxide production in grassland soils: assessing the contribution of nitrifier denitrification. Soil Biol. Biochem. 36, 229e236. Wu, D., Dong, W., Oenema, O., Wang, Y., Trebs, I., Hu, C., 2013. N2O consumption by low-nitrogen soil and its regulation by water and oxygen. Soil Biol. Biochem. 60, 165e172. Zar, J.H., 2010. Biostatistical Analysis, fifth ed. Prentice-Hall, Englewood Cliffs, New Jersey, USA. 944 pp. Zuur, A.F., 2009. AED: Data Files Used in Mixed Effects Models and Extensions in Ecology with R. http://www.highstat.com/book2.htm. Zuur, A.F., Ieno, E.N., Walker, N., Saveliev, A.A., Smith, G.M., 2009. Mixed Effects Models and Extensions in Ecology with R. Springer, New York, 574 pp.