Catchment agriculture and local environment affecting the soil denitrification potential and nitrous oxide production of riparian zones in the Han River Basin, China

Agriculture, Ecosystems and Environment 216 (2016) 147–154

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Catchment agriculture and local environment affecting the soil denitrification potential and nitrous oxide production of riparian zones in the Han River Basin, China Wenzhi Liua , Ziqian Xionga,b , Hui Liuc , Quanfa Zhanga,b , Guihua Liua,* a b c

Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, PR China University of Chinese Academy of Sciences, Beijing 100049, PR China Institute of Hydroecology, Ministry of Water Resources and Chinese Academy of Sciences, Wuhan 430079, PR China

A R T I C L E I N F O

A B S T R A C T

Article history: Received 5 March 2015 Received in revised form 21 September 2015 Accepted 1 October 2015 Available online 19 October 2015

Riparian zones play an important role in reducing nitrogen (N) loading to rivers and streams primarily through soil denitrification which reduces nitrate (NO3–) to nitrous oxide (N2O) and dinitrogen (N2) gases. Although the relationships between local environments and soil denitrification are well understood, relatively little is known about the indirect effects of landscape factors (e.g., catchment agriculture) on the soil denitrification of riparian zones. In this study, we used the acetylene block technique to measure the denitrification potential and net N2O production of soils collected from 62 riparian sites in 15 subtropical rivers of varying catchment land uses. The results indicated that, among the local factors studied, the soil moisture, organic matter and NO3– concentrations were positively associated with both the denitrification potential and N2O production rate. Agricultural riparian zones had a denitrification potential (2.81
1.01 ng N g1 h1) significantly higher than forested riparian zones (0.66
0.24 ng N g1 h1). Additionally, the riparian denitrification potential increased with the percentage of agriculture in the catchments (R = 0.53, P < 0.05). Structural equation modeling revealed that the indirect effects of catchment agriculture on the riparian denitrification potential and N2O production rate were mediated primarily through soil NO3–. Our findings suggest that, compared to forested riparian zones, agricultural riparian zones have greater potential to remove N from polluted runoff. The conversion of original vegetation to agricultural lands in catchments may have a profound impact on the soil N cycles and NO3– removal capacity of riparian zones. ã 2015 Elsevier B.V. All rights reserved.

Keywords: Agricultural landscape Greenhouse gas Nitrogen cycles Potential denitrification Yangtze River Basin

1. Introduction Riparian zones, the interface between aquatic and terrestrial ecosystems, are thought to play an important role in the removal of excess nutrients, including nitrogen (N), from river and stream waters (Vought et al., 1994; Naiman and Decamps, 1997; Groffman and Crawford, 2003; Liu et al., 2014). Through a meta-analysis of published studies, Mayer et al. (2007) indicated that vegetated riparian zones around the world can intercept approximately 67.5% of N from surface and subsurface runoff. The main processes that contribute to the N retention in riparian zones are plant uptake, microbial immobilization, soil storage and denitrification (Saunder and Kalff, 2001; Burgin and Hamilton, 2007).

* Corresponding author at: Wuhan Botanical Garden, Chinese Academy of Sciences, Lumo Road No.1, Wuchang District, Wuhan, PR China. Fax: +86 27 87510251. E-mail address: [email protected] (G. Liu). http://dx.doi.org/10.1016/j.agee.2015.10.002 0167-8809/ ã 2015 Elsevier B.V. All rights reserved.

Soil denitrification is often the dominant process of N removal in riparian zones, which reduces nitrate (NO3–) to nitrous oxide (N2O) and dinitrogen (N2) gases (Seitzinger et al., 2006; Sirivedhin and Gray, 2006; Liu et al., 2011). Using in situ 15NO3– tracer mesocosm experiments, Kreiling et al. (2011) found that soil denitrification accounts for over 80% of the NO3– loss in the upper Mississippi River. N2 is the desired end product of soil denitrification, but incomplete denitrification may result in the production of N2O, a potent greenhouse gas that is approximately 300 times stronger than CO2 and is responsible for approximately 6% of global climate warming (Hefting et al., 2006; Palta et al., 2013). Local environmental factors, such as soil physical and chemical properties, have been associated with the soil denitrification in riparian zones (Hefting et al., 2006; Burgin et al., 2010). NO3– acts as a terminal electron acceptor and organic carbon acts as an electron donor for denitrifying microbes. Therefore, soil N and organic matter contents are generally recognized as the most important determinants of riparian soil denitrification (Hunt et al.,

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2004). Recently, some studies have reported that local vegetation characteristics are also significantly related to riparian soil denitrification (e.g., Hopfensperger et al., 2009; Liu et al., 2011). Vegetation may impact riparian soil denitrification primarily by influencing the oxygen concentration of the substrate within the rhizosphere and by modifying the carbon input from plant residues and roots to soils (Sutton-Grier et al., 2013). Both oxygen concentration and carbon quantity in soils are generally considered the key regulators of denitrification process in riparian zones (Hill and Cardaci 2004; Burgin et al., 2010).

There is only a limited understanding of the importance of landscape factors (e.g., catchment land use) in determining riparian denitrification (Groffman and Crawford, 2003; Arango and Tank, 2008; Hopfensperger et al., 2014). It has been shown that riparian zones are fragile ecosystems and are particularly susceptible to impacts from the catchment and adjacent agriculture (Tockner and Stanford, 2002). Agricultural activities, such as irrigation, drainage, grazing, soil ploughing and extensive usage of N fertilizers in catchments, can alter both the riparian soil properties and vegetation characteristics (Nagasaka and Nakamura, 1999; Moffatt et al., 2004; Jha et al., 2010), which in turn may

Fig. 1. Locations of the 62 studied riparian sites in the Han River Basin of China.

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regulate the riparian denitrification potential and N2O production (Waters et al., 2014). However, no study to date has examined the indirect effect of catchment agriculture on soil denitrification and N2O production of riparian zones. In this study, we measured the denitrification potential and associated N2O production of soils collected from 62 riparian sites in 15Chinese rivers of varying catchment land uses. We hypothesized that the riparian denitrification potential and N2O production rate would be higher in agricultural catchments than in forested catchments due to the greater input of N. The aims of this study were (1) to compare the riparian denitrification potential and N2O production rate between agricultural and forested catchments; (2) to determine the relationships between local factors (i.e., soil properties and vegetation characteristics) and denitrification potential and N2O production rate; and (3) to examine the indirect effects of catchment agriculture on the riparian denitrification potential and N2O production rate.

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riparian site were combined and homogenized to form a composite soil sample. The soil samples were stored at approximately 5  C in a refrigerator until they were partitioned for the measurement of the soil denitrification potential and N2O production. In the field, longitude, latitude and elevation were recorded using a global positioning system (GPS; Model eTrex Summit, USA) for each site. The vegetation cover was visually evaluated in each plot by a 1 1 m grid frame that was divided into 100 cells (0.1  0.1 m; Noe and Zedler 2001). Species richness was defined as the number of plant species per plot (Liu et al., 2013). The Flora of China (http://www.efloras.org/) was used as the authority for identifying the plant species. 2.3. Measurements of denitrification potential and net N2O production

The Han River, originating from the Ningqiang county of Shaanxi province in China, is the longest tributary of the Yangtze River, with a length of 1577 km and a drainage area of 159,000 km2 (Fig. 1; Liu et al., 2013). The Han River Basin is located between 30 80 and 34110 north latitude and between 106 120 and 114140 east longitude. The annual average precipitation in the basin is approximately 804 mm, and 80% of the total rainfall is concentrated in the rainy season from May to October (Liu et al., 2011). The annual average temperature is 12–16  C, with the absolute highest and lowest temperature of 43  C and 13  C, respectively. The soil in the Han River Basin is clayey in texture and composed of yellow brown soil and cinnamon soil, and the bedrock is mainly composed of limestone, dolomites, schist and granite (Li et al., 2008). Terrestrial vegetation in the basin mainly includes coniferous forest (e.g., Pinus massoniana and Cunninghamia lanceolata), deciduous forest, mixed coniferous and broad-leaved forest, shrub and herb (Liu et al., 2009). The upper and lower reaches of the Han River are geographically divided by the Danjiangkou Reservoir, covering areas of 95,200 km2 and 63,800 km2, respectively (Fig. 1). Because the upper Han River Basin is mainly located in the mountainous region, the riparian zones are generally restricted to a narrow band adjacent to the river channel approximately 2–10 m wide (Liu et al., 2013). Riparian zone widths may vary with stream order, stream size and adjacent land use. There are many rivers or streams in the lower Han River Basin, where the land use and topography are complex and where most of the riparian zones have a width over 10 m. Most of the rivers in the lower Han River Basin are currently experiencing increasing N pollution and facing an eutrophication risk, due to the extensive agricultural activities in the catchments.

The acetylene (C2H2) block technique was used to measure the denitrification potential of riparian soils (Smith and Tiedje 1979). Although the C2H2 blockage technique has a number of limitations (Qin et al., 2012), it is still amenable to large-scale comparisons of the soil denitrification potential (Groffman et al., 2006). The denitrification potential was determined in the presence of added carbon and NO3– and therefore provided an upper-bound estimate of in situ denitrification. C2H2 can inhibit the reduction of N2O to N2, causing the former to be the major end product of denitrification. When C2H2 is not added, the N2O gas is free to transform to N2, allowing the determination of the net N2O production rate (Xu et al., 2008). For the denitrification potential assays, 50 g of fresh soils from each riparian site were weighed into a 250-mL serum bottle with 30 mL of incubation solution (final concentrations: 0.1 g/L KNO3, 0.18 g/L glucose and 1 g/L chloramphenicol). All of the serum bottles were then sealed and purged with N2 gas for 2 min to induce anaerobic conditions. Approximately 10% of the bottle headspace was replaced with C2H2 to block the conversion of N2O to N2 during denitrification. We determined the net N2O production rate using a similar procedure, but without the addition of C2H2. The bottles were then incubated in the dark for 4 h at 15  C (the approximate in situ air temperature). The 4 h incubation time was determined after a trial, during which 5 random soil samples were incubated for 1, 2, 4, and 6 h to confirm that the N2O accumulation was linear. At the beginning and end of the incubation, 10 mL of the headspace gas samples were collected from each bottle (after shaking vigorously) using a syringe. The N2O concentrations were measured using a gas chromatograph (Agilent 7890, Santa Clara, CA, USA) equipped with an electron capture detector. The denitrification potential and net N2O production rate were calculated as the difference between the initial and final headspace N2O concentrations (corrected for N2O dissolved in water, Bunsen coefficient = 0.789) divided by the incubation time (4 h), and were expressed on the basis of soil dry matter (ng N g1 h1).

2.2. Field sampling and vegetation measurement

2.4. Measurements of soil physical and chemical properties

During the 7th and 13th of April 2012, we randomly selected 15 first-order and second-order rivers adjacent to the Danjiangkou reservoir in the Han River Basin (Fig. 1). We chose 3–9 riparian sites based on the river length and catchment area. The sites were evenly distributed along each river, and each site was separated by a minimum distance of 8 km. In each riparian site, a 15-m transect parallel to the water's edge was randomly established. Three plots (1 1 m) were surveyed along each transect at 5-m intervals. One soil core (3-cm diameter  7-cm depth) was collected using a hand corer in the center of a plot. The soil core was passed through a 1cm sieve to remove large gravel, and then, all of the cores from a

In the laboratory, the soil pH was measured in a soil to water ratio of 1: 5 (v/v) by a pH meter. The soil moisture was analyzed gravimetrically after drying the soil at 105  C for 24 h. The soil bulk density was measured by weighing soils of a known volume after drying for 24 h at 105  C. The soil organic matter content of airdried samples was determined from the loss during ignition for 4 h at 450  C. The soil NO3-N concentration was analyzed by extracting 20 g of fresh soil with 50 mL of 2 M KCl and using a Spectrumlab 752S spectrophotometer. The colorimetric reagents for NO3-N analysis were prepared as described by Henriksen and SelmerOlsen (1970).

2. Materials and methods 2.1. Site description

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We obtained a land use map of the Han River Basin from the National Geomatics Center of China (http://www.globallandcover. com/). The map with a spatial resolution of 30 m was mainly derived from Landsat TM images in 2010. We delineated the catchment boundaries of the 15 studied rivers using a 1-km resolution digital elevation model. The land use data of each river’s catchment was extracted by using the overlay function on the catchment boundaries and the land use map in ArcGIS version 10.0 (ESRI, Redlands, California, USA). The original land use classes were grouped into four main categories: (1) vegetation, including forest, shrubland and grassland; (2) cropland, including paddy field, dry farmland and fruit garden; (3) built-up land, including urban areas, rural settlements and others (e.g., industrial areas, roads, and airports); and (4) water body, including lakes, rivers, streams, reservoirs, ponds and wetlands. Finally, the 15 catchments were roughly classified into agricultural (N = 6) and forested (N = 9) catchments. Agricultural catchments were those with >50% of cropland land uses in their watersheds (Table S1). 2.6. Statistical analyses For each studied river, we first calculated the mean values for denitrification potential, N2O production, soil properties and vegetation characteristics (Table S1). Before the statistical analysis, the data were tested with the Shapiro–Wilk test for normality and were square root transformed when appropriate. We used the ttest to examine the differences in the riparian denitrification potential, N2O production, soil properties and vegetation characteristics between agricultural and forested rivers. The relationships among the denitrification potential, N2O production, soil properties, vegetation characteristics and catchment agriculture were explored using the Pearson correlation test. The above statistical analyses were performed using PASW Statistics 18.0 software (IBM SPSS Inc., Chicago, USA). Structural equation modeling (SEM) was used to further examine the indirect effects of catchment agriculture on the riparian denitrification potential and N2O production. We first developed a conceptual model linking catchment agriculture indirectly to the riparian denitrification potential and N2O production (Fig. 2) based on the existing literature (e.g., Hopfensperger et al., 2014; Inwood et al., 2007) and ecological principles. We used the results from our Pearson correlation analysis to select the promising explanatory variables to include in

the SEM models. The indirect effects, i.e., effects mediated by other variables, were calculated simply by multiplying the standardized path coefficients involved. The chi-square (x2) test, comparative fit index (CFI) and standardized root mean-square residual (SRMR) were used to evaluate the overall fit of the SEM models. An insignificant x2 statistic (P > 0.05), a CFI value > 0.9 and SRMR value < 0.08 indicated that the SEM models fit the data well. The path coefficients, R-squared, direct and indirect effects, and model fit parameters were calculated in Mplus version 6.11 (Muthén and Muthén, Los Angeles, California, USA) using a robust maximum likelihood (MLR) estimator. 3. Results 3.1. Riparian denitrification potential and N2O production The riparian denitrification potential of the rivers ranged from 0.03 to 6.60 ng N g1 h1 and averaged 1.52 ng N g1 h1. The net N2O production rate varied between 0.02 and 0.49 ng N g1 h1, with a mean value of 0.19 ng N g1 h1. Agricultural riparian zones had a potential denitrification rate (2.81
1.01 ng N g1 h1) significantly higher than forested riparian sites (0.66
0.24 ng N g1 h1,P = 0.02, Fig. 3). However, the net N2O production rate was not significantly different between the agricultural riparian and forested riparian sites (P = 0.19, Fig. 3).

4

*

3.5

(ng N g-1 h-1)

2.5. Calculation of catchment land use

Agricultural rivers

3

Forested rivers

2.5 2 1.5 1

*

0.5 0

Denitrification potential

N2O production rate

Fig. 3. Denitrification potential and N2O production rate (mean
SE) of riparian zones in agricultural and forested catchments. An asterisk indicates a significant difference at P < 0.05.

Soil bulk density

Plant cover Catchment agriculture

Riparian denitrificaon Soil moisture

and N2O producon

Soil organic maer

Soil NO3– Fig. 2. Conceptual model identifying the expected indirect pathways for catchment agriculture to affect riparian denitrification potential and N2O production rate.

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3.2. Riparian local factors and catchment land use The organic matter content of riparian soils ranged from a minimum value of 10.63 g kg1 to a maximum value of 37.28 g kg1, while the NO3– concentration varied from 0.66 to 2.56 mg kg1 (Table S1). The effects of land use on the soil bulk density and NO3– concentration were significant (Table 1). The riparian plant cover and species richness were significantly higher in agricultural riparian zones compared to forested riparian zones (Table 1). The soil properties were significantly related to the vegetation characteristics (Table 2). The plant cover was positively associated with soil organic matter (R = 0.59, P = 0.02) and NO3– concentration (R = 0.60, P = 0.02) but negatively related to the soil bulk density (R = 0.58, P = 0.03). The plant species richness was only significantly related to the soil NO3– concentration (R = 0.58, P = 0.02). Catchment agriculture had significant relationships with both soil properties and vegetation characteristics (Table 2). 3.3. Determinants of riparian denitrification potential and N2O production The denitrification potential and N2O production rate were both positively associated with soil moisture, organic matter and NO3– concentrations (Table 2). Plant cover was positively related to the denitrification potential (R = 0.56, P = 0.03), but not significantly related to the N2O production rate (Table 2). In the denitrification potential model (x2 = 7.509, P = 0.276; CFI = 0.984; SRMR = 0.041; Fig. 4A), the total indirect effect of catchment agriculture on denitrification potential (0.435) was significant (Table 3). Approximately 53.429%, 27.124% and 19.448% of this indirect effect was mediated via soil NO3–, organic matter and moisture, respectively (Table 4). In the N2O production rate model (x2 = 9.051, P = 0.171; CFI = 0.966; SRMR = 0.062; Fig. 4B), most of the indirect effect (74.483%) of catchment agriculture on the N2O production rate was mediated through soil NO3– (Table 4). 4. Discussion 4.1. Effects of local factors on the riparian denitrification potential and N2O production The effects of soil properties on riparian denitrification were frequently described in previous studies (e.g., Groffman and Crawford 2003; Hefting et al., 2006; Burgin et al., 2010). Our results indicated that soil variables, including moisture, NO3–, and organic matter contents, were the main factors affecting the denitrification potential and N2O production rate of riparian zones in the Han River Basin, China. One key to understanding the spatial pattern of riparian denitrification is the role of soil moisture (Saggar et al.,

151

2013). Consistent with earlier work (e.g., Groffman and Crawford 2003), we found significant positive correlations between soil moisture and the denitrification potential and N2O production rate. Moisture is an indicator of the aeration status of riparian soils. The higher soil moisture in riparian zones can inhibit oxygen diffusion into the soil, therefore, creating an anaerobic or anoxic environment favorable for denitrifying bacteria (Garcı’a-Ruiz et al., 1998). Seitzinger et al. (2006) also indicated that oxygen availability and the denitrification rate of soils changed rapidly depending on the soil moisture. Soil moisture influenced the denitrification potential in riparian zones can imply that wet riparian areas should be a high priority to be protected since they can provide greater N removal. Several studies reported that soil NO3– concentration generally explained the greatest amount of variance in the soil denitrification potential of riparian zones (e.g., Hunt et al., 2004; Bruland et al., 2006). Our study also found that the soil NO3– concentration had the greatest direct effects on the denitrification potential and N2O production rate. Because soil denitrification is an anaerobic process that converts NO3– into N2O and N2, a high concentration of NO3– in riparian soils may directly accelerate the denitrification rates. In the present study, both the denitrification potential and N2O production rate increased significantly with the increasing soil NO3– concentration in riparian zones. These results indicated that riparian denitrification in the Han River Basin was limited by the availability of NO3–, which was consistent with the relatively low concentrations of soil NO3– measured in this study (1.49
0.13 mg kg1). In a riparian zone with a high soil NO3– concentration (6.14 mg kg1) in Kentucky, USA, the soil denitrification potential was mostly determined by soil organic matter and only slightly by soil NO3– concentration (Hopfensperger et al., 2014). Our study, together with others, emphasized the importance of soil NO3– concentration in modeling riparian denitrification at low NO3– concentrations and the need to identify alternative variables (e.g., organic carbon content) at higher NO3– concentrations (Groffman and Crawford 2003; Inwood et al., 2005). Organic carbon acts as an electron supplier in the soil denitrification process (Liu et al., 2011). Through organic matter decomposition, the supply of soil carbon becomes available for denitrifying bacteria and fungi; hence, a positive relationship is often observed between soil organic matter and the denitrification potential (e.g., Groffman and Crawford 2003; Scaroni et al., 2010). The results from our study were consistent with previous work (e.g., Groffman and Crawford 2003; Hill et al., 2014) and indicated that the riparian denitrification potential of the Han River Basin was also limited by the availability of soil organic carbon. In addition, some studies have reported that not only organic matter quantity but also organic matter quality can affect the soil denitrification of riparian zones (Hill and Cardaci 2004; Dodla et al., 2008; Stelzer et al., 2014).

Table 1 The mean values and standard errors (SE) of the local and landscape factors of riparian zones in agricultural and forested catchments. Units Local factors Soil pH Soil moisture Soil bulk density Soil organic matter Soil NO3– Plant cover Plant species richness Landscape factors Catchment agriculture

Agricultural riparian (n = 6)
0.08
1.88
0.04*
2.92
0.19*
6.37*
0.40*

% g cm3 g kg1 mg kg1 %

8.45 9.59 1.06 23.12 1.91 21.92 1.93

%

56.44
3.20*

Forested riparian (n = 9)

All riparian (n = 15)

8.36
0.10 6.36
0.83 1.21
0.04* 16.90
1.64 1.22
0.11* 0.48
0.27* 0.14
0.07*

8.39 7.65 1.15 19.39 1.49 9.06 0.86

15.09
1.93*

31.63
5.66

Mean
SE followed by an asterisk indicates a significant difference (P < 0.05) between the agricultural and forested rivers.










0.07 0.96 0.03 1.68 0.13 3.70 0.28

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Table 2 Pearson correlation coefficients among the denitrification variables, local and landscape factors of riparian zones (n = 15). Soil pH Denitrification variables Denitrification 0.17 N2O production rate 0.14 Local factors Soil pH Soil moisture Soil bulk density Soil organic matter Soil NO3– Plant cover Plant species richness

1.00

Soil organic matter

Soil bulk density

0.68b 0.67b

0.58a 0.44

0.67b 0.55b

0.74b 0.72b

0.56a 0.22

0.20 1.00

0.13 0.81b 1.00

0.13 0.58a 0.44 1.00

0.13 0.66b 0.51 0.74b 1.00

-0.01 0.40 0.58a 0.59a 0.60a 1.00

Landscape factors Catchment agriculture a b

Soil NO3–

Soil moisture

Plant cover

Plant species richness 0.50 0.23

0.09 0.27 0.47 0.44 0.58a 0.95b 1.00

Catchment agriculture 0.53a 0.25

0.02 0.28 0.49 0.5a 0.63a 0.87b 0.86b

1.00

Significant at the 0.05 level. Significant at the 0.01 level.

(A)

Soil bulk density

-0.881**

-0.485* Plant cover 0.929** Catchment agriculture

-0.147

-0.210 R2=0.629

0.276

0.302* 0.229

Soil moisture

Denitrificaon potenal

0.507 0.333*

0.367**

0.387

-0.036

Soil organic maer 0.401* 0.334*

Soil NO3–

(B)

Soil bulk density

-0.881**

-0.485* Plant cover 0.929** Catchment agriculture

-0.147

-0.210 R2=0.585

0.276

0.347* -0.028

Soil moisture 0.507

-0.036 0.333*

0.387

N2O producon

(Allen et al., 2002). Higher plant cover may also reduce soil water evaporation in riparian zones and result in relatively high moisture in soils (Liu et al., 2011). It should be noted that plant uptake is one of the main pathways to remove inorganic N from the riparian soils (Burgin and Hamilton 2007). Therefore, the harvesting of aboveground plant biomass in winter may be a feasible manner by which nutrients can be subsequently removed from riparian zones in the Han River Basin of China. It should be noted that soil denitrification of riparian zones may also be significantly affected by overlying water quality (e.g., dissolved oxygen and NO3– concentration) during flooding season. Li et al. (2008) reported that water quality in the Han River basin exhibited a seasonal variation with higher N concentration and lower dissolved oxygen in the rainy season as compared to the dry season. Therefore, it is expected that riparian denitrification in the wet seasons will be significantly higher than that in the dry seasons. In addition, both soil properties and vegetation characteristics (e.g., plant cover) in riparian zones may also be significantly affected by season (Clément et al., 2002). Further studies are needed to investigate the temporal variations of soil denitrification to assess the N removal capacity of the riparian zones in the Han River basin.

rate

0.512* *

4.2. Effects of catchment agriculture on riparian denitrification potential and N2O production

Soil organic maer 0.401* Soil NO3–

0.334*

Fig. 4. Structural equation models depicting the indirect effects of catchment agriculture on the riparian denitrification potential (A) and N2O production rate (B). Notes: black lines indicate positive or negative effects; numbers adjacent to the lines are standardized path coefficients; *indicates p < 0.05; **indicates p < 0.01; the R2 values above the denitrification variable boxes represent the total variance explained by the models.

We found that the riparian denitrification potential was positively related to plant cover in the Han River Basin. Other studies also reported that denitrification potential was typically higher in soils with vegetation than those without (e.g., Christensen and Sørensen 1986; Griffiths et al., 1993). Vegetation can indirectly influence the soil denitrification process both in physical and biochemical approaches (Liu et al., 2011). Riparian plants not only supply organic carbon to the denitrifying bacteria but also transport oxygen to the root area to enable nitrifying microbes to oxidize NH4+ to NO3–, which may then be denitrified

In the upper Han River basin of China, the land use was dominated by forest and shrub (81% of the total basin area). Agricultural land accounted for approximately 14% of the total land area (Li et al., 2009, 2012). Agriculture is recognized as the most important source of nonpoint-source pollution affecting the water quality and soil properties in the Han River Basin (Liu et al., 2011). The intensive use of N fertilizers in paddy fields, dry farmlands and fruit gardens in China has led to an increased N concentration in surface waters and soils (Zhu et al., 2006). Approximately 92% of the annual N input to the Yangtze River comes from agriculture runoff (Zhu et al., 2006). Moreover, between the agricultural and forested catchments, there exist very different topography, flow pathways and drainage networks that may strongly affect the transformation and output of NO3– (Burt and Pinay 2005; Lohse et al., 2009; Pärna et al., 2012). For instance, more N was found to be transported into rivers in catchment areas covered with permeable agricultural soils because of lower retention contents and greater transport capacity (Jiang et al., 2014). Our study showed that both soil NO3– and organic matter concentrations in riparian zones increased with catchment agriculture. Agricultural

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Table 3 Standardized direct, indirect and total effects of local and landscape factors on the riparian denitrification potential and N2O production rate according to the SEM models. Indirect effects refer to the mathematical product of all of the possible paths from one variable to another via intermediate variables. Total effects refer to the sum of the direct and indirect paths. The path diagrams are shown in Fig. 4. Denitrification potential

N2O production rate

Direct effects

Indirect effects

Total effects

Direct effects

Indirect effects

Total effects

Local factors Soil moisture Soil Bulk density Soil organic matter Soil NO3– Plant cover

0.302a 0 0.229 0.367b 0

0.300a 0.530b 0.132 0.038 0.183

0.602b 0.530b 0.361 0.329b 0.183

0.347a 0 0.028 0.512a 0

0.254b 0.530b 0.198 0.018 0.086

0.602 0.530b 0.170 0.494a 0.086

Landscape factors Catchment agriculture

0

0.435b

0.435b

0.407b

0.407b

a b

0

Significant at the 0.05 level. Significant at the 0.01 level.

Table 4 Indirect effects of catchment agriculture on the riparian denitrification potential and N2O production rate mediated by local factors. Denitrification potential Indirect effects Local factors Soil moisture Soil organic matter Soil NO3–

0.085 0.118 0.232

Total indirect effects

0.435

N2O production rate Contribution (%) 19.448 27.124 53.429

Indirect effects 0.097 0.014 0.324

100

0.407

Contribution (%) 22.299 3.218 74.483 100

Note: percentage of contribution was calculated using the sum of absolute values for contributing effects.

landscapes may also increase carbon inputs to rivers and streams as a result of increased soil erosion and organic matter transport or increased plant productivity that increases the rates of organic matter deposition to soils (Bruesewitz et al., 2011). Moreover, some studies have indicated that agricultural activities in catchments can alter the denitrifier community composition, diversity and abundance (e.g., Baxter et al., 2012), which in turn may influence the soil denitrification process of riparian zones. Inwood et al. (2007) proposed that catchment land use may influence stream sediment denitrification through effects on water NO3– concentrations or sediment characteristics. Our study found that the soil denitrification potential of riparian zones differed significantly between agricultural and forested catchments in the Han River Basin. By using a SEM model, our study further revealed that the significantly indirect effects of catchment agriculture on riparian denitrification potential and N2O production were mainly mediated through soil NO3–. To develop the economy and increase income, many low-elevation shrublands and grasslands in the Han River Basin have been removed and replaced with dry farmlands and fruit gardens. The results from our study suggested that the conversion of original vegetation to agricultural lands in the catchments may have profoundly impacted the soil N cycles and NO3– removal capacity of riparian zones. 5. Conclusions In summary, the results of this research showed that both landscape and local factors had significant correlations with the soil denitrification potential and net N2O production of riparian zones in the Han River Basin, China. The indirect effects of catchment agriculture on the riparian denitrification potential and N2O production were mediated through soil NO3–, organic matter and moisture. Given that riparian zones serve as a sink of NO3–, the

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