Edaphic Conditions Regulate Denitrification Directly and Indirectly by

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Edaphic conditions regulate denitrification directly and indirectly by altering denitrifier abundance in wetlands along the Han River, China Ziqian Xiong, Laodong Guo, Quanfa Zhang, Guihua Liu, and Wenzhi Liu Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 25 Apr 2017 Downloaded from http://pubs.acs.org on April 25, 2017

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Environmental Science & Technology

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Edaphic conditions regulate denitrification directly and indirectly by

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altering denitrifier abundance in wetlands along the Han River, China

3 4

Ziqian Xiong a, b, Laodong Guo c, Quanfa Zhang a, Guihua Liu a*, Wenzhi Liu a, c*

5 6

a

7

Chinese Academy of Sciences, Wuhan 430074, P.R. China

8

b

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P.R. China

10 11

c

Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden,

College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049,

School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee,

53204, USA

12 13

*Corresponding author

14

Phone: +86 27 87510987

15

Fax: +86 27 87510251

16

Email: [email protected] (Guihua Liu);

17

[email protected] (Wenzhi Liu)

18 19

Type: Research Articles.

20

Author contributions: QZ, GL, and WL designed the study; ZX, GL, and WL performed

21

the research; ZX, LG, and WL analysed the data; ZX, LG, QZ, GL, and WL wrote the

22

manuscript.

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ACS Paragon Plus Environment


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Abstract

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Riparian wetlands play a critical role in retaining nitrogen (N) from upland runoff

27

and improving river water quality, mainly through biological processes such as soil

28

denitrification. However, the relative contribution of abiotic and biotic factors to

29

riparian denitrification capacity remains elusive. Here we report the spatio-temporal

30

dynamics of potential and unamended soil denitrification rates in 20 wetlands along

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the Han River, an important water source in central China. We also quantified the

32

abundance of soil denitrifying microorganisms using nirK and nirS genes. Results

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showed that soil denitrification rates were significantly different between riparian

34

and reservoir shoreline wetlands, but not between mountain and lowland wetlands.

35

In addition, soil denitrification rates showed strong seasonality, with higher values in

36

August (summer) and April (spring) but lower values in January (winter). The

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potential and unamended denitrification rates were positively correlated with

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edaphic conditions (moisture and carbon concentration), denitrifier abundance, and

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plant species richness. Path analysis further revealed that edaphic conditions could

40

regulate denitrification rates both directly and indirectly through their effects on

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denitrifier abundance. Our findings highlight that not only environmental factors, but

42

also biotic factors including denitrifying microorganisms and standing vegetation,

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play an important role in regulating denitrification rate and N removal capacity in

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riparian wetlands.

45 46

Keywords: Denitrifying communities, Microbial abundance, Potential denitrification,

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Riparian zone, Wetland vegetation

48 2


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TOC/Abstract Art

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49

Introduction

50

It is estimated that anthropogenic activities in the world contribute

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approximately 2.1×1011 kg of reactive nitrogen (N) to terrestrial ecosystems every

52

year.1 Nitrogen mainly comes from industrial and agricultural sources such as

53

wastewater discharge, chemical fertilizers, animal wastes, atmospheric deposition

54

and crop fixation.2‒4 Nitrogen inputs to the terrestrial environments now greatly

55

exceed biological demand, and this excess N can easily leach into rivers, streams, and

56

other aquatic ecosystems.5 Elevated N concentrations in river and stream water

57

commonly result in a number of environmental issues such as deterioration of water

58

quality, eutrophication, toxic algal blooms, and loss of biodiversity.6

59

Riparian wetlands, the transition zone between terrestrial and aquatic systems,

60

play an important role in removing N from runoff and improving river water quality.7,8

61

It has been reported that average N removal efficiency for global riparian zone is

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approximately 67.5%.9 Nitrogen can be removed or retained by riparian wetlands

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mainly through soil denitrification, anammox, plant uptake, soil storage, and

64

microbial immobilization.10 Soil denitrification is thought to be the most critical

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process for N removal, because it can permanently remove the N through reducing

66

nitrate (NO3–) to N gaseous products including nitrous oxide (N2O) and dinitrogen

67

(N2).11 For instance, Kreiling et al. (2011) reported that the denitrification process

68

could account for nearly 82% of the NO3– removal in the upper Mississippi River.12

69

Edaphic characteristics, such as soil moisture, N and carbon (C) availability, can

70

directly and indirectly affect the denitrification rate in riparian wetlands.13,14 For

71

example, Hefting et al. (2006) showed that soil pH, moisture and organic matter were

72

the main determinants of denitrification activity in a forested riparian buffer.15 Hunt 4


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et al. (2004) reported that soil NO3– and C levels could account for the majority of

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variance in soil denitrification rates in a forested riparian wetland.13 Several studies

75

have demonstrated that large-scale riparian features such as geomorphological

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factors (e.g., slope and altitude) and land use are also significantly correlated with N

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removal capacity.16,17 Geomorphic character can regulate soil conditions and

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vegetation characteristics in riparian zones, which may in turn impact the soil

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denitrification rates.17

80

With the development of molecular technologies, a number of studies have

81

focused on the relationships between soil denitrification rates and denitrifier

82

abundance, but their results are somewhat inconsistent.18‒20 Deslippe et al. (2014)

83

found that the abundance of nirS–type denitrifier was positively correlated to

84

denitrification potential in riparian soils.21 Graham et al. (2014), on the other hand,

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did not observe a significant increase in explanatory power when functional gene

86

abundances were added to statistical models to predict soil denitrification rates.22

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Moreover, vegetation has long been recognized as an important biotic factor in

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determining wetland denitrification process.23 A meta–analysis revealed that wetland

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macrophytes increased soil denitrification rates by 55% on average, mainly by

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providing organic matter and introducing oxygen that enhanced generation of NO3–

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from nitrification.24

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In this study, we examined seasonal variation in potential and unamended soil

93

denitrification rates in 20 wetlands along the Han River, a water source area of the

94

South-to-North Water Transfer Project in China. We used nirK and nirS genes as

95

markers to quantify the denitrifier abundance in wetland soils. We hypothesized that

96

edaphic conditions such as available C and N could affect denitrification rates both 5



97

directly and indirectly through their effects on denitrifier abundance. Therefore, our

98

study had several purposes, including (1) investigating the spatio-temporal patterns

99

of soil potential and unamended denitrification rates in wetlands along the Han River,

100

China; (2) quantifying the relative contributions of abiotic and biotic factors to

101

wetland denitrification rates; and (3) elucidating the direct and indirect pathways of

102

the effect of edaphic conditions on wetland denitrification rates.

103 104

Materials and methods

105

Study areas

106

The Han River is the largest tributary of the Yangtze River and drains an area of

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approximately 159,000 km2 (Fig. 1). It originates from Ningqiang County of Shaanxi

108

Province and flows southeast, emptying into the Yangtze River in Wuhan City. The

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Han River basin has a north subtropical monsoon climate, where the annual average

110

temperature is 12–16 °C and annual mean precipitation is approximately 804 mm.17

111

Since 1968, eight large reservoirs have been built on the Han River to provide

112

benefits including flood control, freshwater supply, and electric power generation.

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Among the eight reservoirs, the largest one is the Danjiangkou Reservoir, which has a

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total area of 745 km2 and a mean water depth of approximately 23 m.14 The majority

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of these reservoirs have large areas of shoreline wetlands in the transition zone

116

between low and high water levels. In contrast to riparian wetlands, reservoir

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shoreline wetlands experience large water-level fluctuations (3–15 m annually), and

118

are mainly formed at the former farmlands and forests.14

119

The Han River can be divided into two geomorphically distinct reaches by the

120

Danjiangkou Reservoir.25 The upper reach, from the source to the Danjiangkou 6


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Reservoir with a length of 925 km, has typical mountain landscapes (Fig. 1).

122

Therefore, riparian wetlands in the upper Han River basin are commonly restricted to

123

a narrow band (2‒10 m in width) adjacent to the river channel.25 Land cover in this

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mountain sub-basin is dominated by natural vegetation, especially deciduous and

125

coniferous forests (Table S1). In the lower Han River basin, the mean elevation is

126

about 283 m with a relatively flat topography (Table S1). Agriculture is the dominant

127

landscape in this lowland sub-basin.17

128

In 2002, the Chinese government launched the South-to-North Water Transfer

129

Project to divert freshwater to the northern cities (e.g., Beijing and Tianjin) from the

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Yangtze River basin.26 The upper Han River is the water source area for the middle

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rout of this inter-basin water transfer project. Therefore, the water quality and

132

wetland functions of the Han River have been of great concern during recent

133

years.17,27,28 Due to increased nutrients input from industrial wastewater, agricultural

134

fertilizers, and domestic sewage, the Han River has suffered from serious N

135

pollution.27 The concentration of total N (mainly NO3–) in river waters varied between

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0.07 and 16.73 mg/L, with a mean value of 2.34 mg/L.29 Excess N has resulted in

137

water quality degradation and other attendant ecological issues, including

138

eutrophication and harmful algal blooms.30

139 140

Field sampling

141

In January (representing winter), April (spring), August (summer), and

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November (autumn) of 2015, field sampling was conducted at 15 riparian wetlands

143

and 5 reservoir shoreline wetlands along the Han River, China (Fig. 1). These

144

wetlands were selected randomly and their coordinates were recorded using a 7



145

hand-held global positioning system (Unistrong Co., Ltd, Beijing, China). At each

146

sampling wetland, one sampling transect was randomly established perpendicular to

147

river flow and extended from the water's edge to the upland edge of the wetlands

148

(i.e., the highest water-level areas).

149

The transect length varied from less than 5 m to approximately 35 m. One to

150

three plots (1× 1 m) were set up along each transect in 10-m intervals depending on

151

the transect length. Because of the fluctuating water levels of the Han River, a total of

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35, 39, 46 and 37 plots were established along the 20 transects in January, April,

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August and November, respectively.

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At each plot, five soil cores (10 cm deep) were collected randomly using a hand

155

corer and then well mixed immediately to form a composite sample. Approximately

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300 g of soil from each plot was put into a plastic bag and stored at about 5 °C in a

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refrigerator (FYL-YS-30L, Fuyilian Co., Beijing, China). In addition, about 10 g of soil

158

was collected at each plot in a centrifuge tube and immediately frozen in liquid N2. At

159

each sampling transect, a 500–ml surface water sample (approximately 0.2 m below

160

surface) was collected from a river location adjacent to this transect.

161 162

Measurements of soil denitrification rates

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We used the acetylene (C2H2) inhibition method to determine the potential and

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unamended denitrification rates of wetland soils.31 The C2H2 inhibition technique has

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a long history of successful use,7,16,23 although it has several drawbacks such as

166

inhibition of nitrification process.32 Potential denitrification rate was an upper-bound

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estimate of in situ denitrification with C and NO3– amendments, while unamended

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denitrification (background or basal denitrification) rate provided a conservative 8


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estimate and measured without nutrient addition.33

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Potential denitrification rate was measured according to Xiong et al. (2015).17

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Specifically, approximately 25 g of fresh soils from each plot were weighed into a

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250-mL brown glass bottle with 20 mL of incubation solution (final concentrations:

173

0.18 g/L glucose, 0.1 g/L KNO3, and 1 g/L chloramphenicol). Unamended

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denitrification rate was determined using a similar procedure, but with the addition

175

of 20 mL of unfiltered river water instead of incubation solution. All bottles were

176

sealed with a rubber stopper and purged with 99.999% N2 for 2 min to create anoxic

177

environments. To inhibit the reduction of N2O to N2 during denitrification process, 25

178

mL of C2H2 was then added to each bottle using a syringe. These bottles were

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incubated in the dark at room temperatures (4.5, 15.1, 25.8 and 11.4 ℃ in January,

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April, August and November, respectively) for 2 h, as recommended by Opdyke et al.

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(2006) and Bruesewitz et al. (2012).33,34 At the start and end of incubation, 5 mL of

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headspace gas samples were collected from each bottle using a syringe after shaking

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vigorously.

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The N2O concentrations were determined using a gas chromatograph fitted with

185

an electron capture detector (Agilent 7890, Santa Clara, USA). Potential and

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unamended soil denitrification rates were calculated as the difference between the

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start and end N2O concentrations (corrected for N2O dissolved in water using Bunsen

188

coefficient) divided by incubation time (2 h) and soil dry weight, and data were

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reported in ng N g‒1 h‒1.

190 191 192

Measurements of vegetation, edaphic conditions and water quality In the field, vegetation cover at each plot was visually estimated using a 1×1 m 9



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grid frame that was subdivided into 100 cells (10×10 cm).28 Species richness was the

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number of vascular plant species present in a plot. In the laboratory, soil pH was

195

determined in a soil to water ratio of 1: 5 (v/v) by a pH meter, while soil moisture was

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measured gravimetrically after drying 30 g of fresh soil at 105°C for 24 h. In order to

197

determine the percentage of fine substrates (i.e., sand, silt and clay), approximately

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50 g of air-dried soil were sieved through a 10–mesh sieve.17 The soil density was

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analyzed by weighing 50 cm3 of homogenized fresh soils after drying overnight at

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105°C. The concentration of soil NO3–‒N was measured by extracting 10 g of fresh

201

soils with 100 mL of KCl for 1 h and using an automatic analyzer (EasyChem plus,

202

Systea, Italy). The soil total carbon (STC) was determined by an elemental analyzer

203

(Vario TOC cube, Elementar, Germany) using air-dried and sieved (100-mesh) samples.

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Water NH4+‒N and NO3–‒N concentrations were determined by an automatic

205

analyzer (EasyChem plus, Systea, Italy).

206 207

Determination of denitrifier abundances

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Genomic DNA was extracted from replicate sediment subsamples using the

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PowerSoil DNA Isolation Kit (MoBio Laboratories, Inc., Carlsbad, USA) following the

210

manufacturer’s instructions. DNA quality was detected in 1% TAE‒agarose gel stained

211

with Goldview and imaged under UV light. The abundance (i.e., copy number) of nirS

212

and nirK genes was determined in triplicate using a Roche LightCycler480 real-time

213

PCR System (Roche Diagnostics, Mannheim, Germany) with the fluorescent dye SYBR

214

green

215

nirSCd3aF/nirSR3cd were applied for nirK and nirS genes, respectively. The 20 μL

216

quantitative PCR mixture contained 10 μL of SybrGreen qPCR Master Mix (2×), 1 μL of

quantitative

PCR

method.

Primer

sets

of

10


nirK876/nirK1040

and

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primers (10 μM) and 2 μL of DNA template. Standard curves were constructed with

218

10-fold serial dilutions of a known amount of plasmid DNA containing fragments of

219

nirK and nirS genes. The primer sequence and thermal cycling procedures were listed

220

in Table S2.

221 222

Statistical analyses

223

All data were assessed for normality by using the Shapiro–Wilk test before

224

further statistical analyses. Non-normally distributed data were natural log (ln) or

225

square root (sqrt) transformed to improve their normality. T-test and One-way

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ANOVA with Tukey post-hoc tests were conducted to examine differences in

227

denitrification rates, denitrifier abundances, vegetation characteristics and edaphic

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conditions among seasons and between wetland types. The relationships between

229

denitrification rates and biotic and abiotic factors were evaluated using the Pearson

230

correlation coefficient. Stepwise multiple regression analyses were used to identify

231

which factors best explained the variations in denitrification rates. The above

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statistical analyses were performed using PASW 19.0 statistics software (IBM SPSS

233

Inc., Chicago, USA).

234

To further explore the direct and indirect effects of edaphic conditions on

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denitrification rates, a path analysis (structural equation modeling without latent

236

variables) consisted of three steps were conducted. Firstly, based on previous

237

research,18 we developed a conceptual model linking abiotic and biotic factors to soil

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denitrification rates (Figure S1). Secondly, promising explanatory factors were

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selected to include in path analysis according to results of the above Pearson

240

correlation analysis. To simplify our path model, we used a compound variable 11



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(nirK+nirS abundance) instead of nirK abundance and nirS abundance. Finally, path

242

coefficients, R2, and model fit parameters were calculated using AMOS 20.0 software

243

(Amos Development Corporation, Chicago, USA). Maximum likelihood estimation

244

method was used and missing data were handled using the option of “Estimate

245

means and intercepts”. The indirect effects (effects mediated by other factors) refer

246

to the mathematical product of all possible paths.28 A comparative fit index (CFI)

247

value > 0.90 indicated that the final path models provide an acceptable fit.

248 249

Results

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Wetland denitrification rates

251

Potential denitrification rates showed great variation, ranging from 0.06 to 511

252

ng N g‒1 h‒1 and averaging 51.79 ng N g‒1 h‒1. Unamended denitrification rates varied

253

between 0.03 and 105 ng N g‒1 h‒1, with a mean value of 10.56 ng N g‒1 h‒1.

254

Denitrification rates in lowland wetlands were slightly but not significantly higher

255

than those in mountain wetlands (Fig. 2). However, reservoir shoreline wetlands

256

supported greater denitrification rates than riparian wetlands (Fig. 2). Sampling

257

seasons had a strong influence on both potential and unamended denitrification

258

rates (Fig. 3). The highest denitrification rates occurred in August and April, while the

259

lowest denitrification rates were observed in January.

260 261

Wetland biotic and abiotic factors

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The abundance of nirK gene in wetland soils ranged from 0.31×105 to 84.50×105

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gene copies g−1 soil, while the abundance of the nirS gene varied between 0.11×105

264

and 69.20×105 gene copies g−1 soil. The mean abundance of nirK gene (5.22×105 gene 12


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copies g−1 soil) was approximately twice that of nirS gene (2.69×105 gene copies g−1

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soil). There was no significant difference in nirS and nirS gene abundances among

267

seasons (p>0.05; data not shown) and between wetland types (Table S3).

268

Soil moisture was generally higher in lowland wetlands than in mountain

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wetlands (Table S4). In addition, relative to the riparian wetlands, reservoir shoreline

270

wetlands had significantly higher soil pH and STC (Table S3). There existed a

271

significant difference in all edaphic conditions except fine substrate between

272

sampling seasons (Table S4). The Soil NO3–‒N and STC concentrations in August were

273

significantly higher than those in January and April. Soil moisture was positively

274

related to nirK gene abundance, plant species richness and plant cover, while soil

275

NO3–‒N concentration was negatively correlated with nirS gene abundance and plant

276

species richness (Table 1).

277 278

Determinants of wetland denitrification rates

279

Soil denitrification rates were strongly associated with several abiotic and biotic

280

factors, when all type wetlands were considered (Table 2). Both potential and

281

unamended denitrification rates showed significant positive relationships with

282

denitrifier abundance, plant richness, soil moisture and STC. Stepwise regression

283

analyses demonstrated that nirK abundance was the most important predictor of

284

potential and unamended denitrification rates, explaining 32.5% and 18.6% of their

285

variations, respectively.

286

The CFI values for potential and unamended denitrification models were 0.949

287

and 0.933, respectively, indicating that the path models were acceptable (Fig. 4). For

288

the model of potential denitrification rate (Fig. 4a), denitrifier abundance was the 13



289

most important factor in explaining the denitrification rate (Table 3). Edaphic

290

conditions, especially moisture, could affect potential denitrification rates both

291

directly and indirectly by altering denitrifier abundance (Table 3). A similar result was

292

obtained from the unamended denitrification model (Fig. 4b). The final models,

293

which included a subset of direct and indirect effects of abiotic and biotic factors,

294

accounted for 61.5% of the variation in potential denitrification rates and 55.4% of

295

the variation in unamended denitrification rates (Fig. 4).

296 297

Discussion

298

Spatial and temporal dynamics of wetland denitrification rates

299

We compared soil denitrification rates in wetlands along the Han River with

300

those in other riparian zones measured by the same C2H2 inhibition method (Table

301

S5). The mean potential denitrification rate in wetlands along the Han Rive was 51.8

302

ng N g‒1 h‒1. This value was considerably higher than values observed in some

303

previous studies, including 25.3 ng N g‒1 h‒1 in a riparian wetland in Maryland, USA

304

and 1.52 ng N g‒1 h‒1 in riparian zones adjacent to the Danjiangkou Reservoir,

305

China.25,35 However, the majority of previous studies reported a potential

306

denitrification rate between 100 and 3000 ng N g‒1 h‒1 (Table S5). This difference

307

could be mainly due to three reasons. First, there was a great difference in

308

concentrations of added N and C in determining potential denitrification rates among

309

studies. For instance, the added N content in our study was approximately 11.09 μg

310

NO3–‒N g-1 soil, which was considerably lower than that in Dhondt et al. (2004) (50

311

μg NO3–‒N g-1 soil) and in McCarty et al. (2007) (600 μg NO3–‒N g-1 soil).35,36 Second,

312

the sampling seasons and incubation temperatures had a significant effect on soil 14


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potential denitrification rates.37 Dhondt et al. (2004) found that potential

314

denitrification rates in soils increased considerably with incubation temperatures.36

315

Third, many previous studies used the chloramphenicol to inhibit the microbial

316

growth and block the de novo synthesis of denitrification enzymes.8,13,31,35 In our

317

incubation experiments, the addition of chloramphenicol might significantly reduce

318

the potential and unamended soil denitrification rates.

319

Scaled to an areal basis using the density of surface soils (top 10 cm), the mean

320

unamended denitrification rate in wetlands along the Han Rive was 0.79 mg N m‒2

321

h‒1 or 6920 kg N km‒2 y‒1. Piña-Ochoa and Álvarez-Cobelas (2006) reported that the

322

mean denitrification rate of global rivers was approximately 29540 kg N km‒2 y‒1.38 In

323

addition, Seitzinger et al. (2006) indicated that there were considerable spatial

324

variations in global river denitrification, with a predicted average denitrification rate

325

of 12963 kg N km‒2 y‒1.39 This may suggest that the wetlands along the Han River

326

have relatively low denitrification and N removal rates compared with global river

327

wetlands.

328

Furthermore, reservoir shoreline wetlands along the Han River supported

329

greater denitrification rates than riparian wetlands (Fig. 2). This result can be mainly

330

ascribed to the fact that, in comparison with riparian wetlands, reservoir shoreline

331

wetlands have higher soil C concentrations which are positively correlated to the

332

potential and unamended denitrification rates (Table S3 and Table 2). We also found

333

that sampling season had a strong influence on both potential and unamended

334

denitrification rates in wetlands along the Han River (Fig. 3). The highest

335

denitrification rates were observed in August and April, while the lowest

336

denitrification rates occurred in January. It has been reported that denitrification 15



337

rates are positively correlated with temperature, with higher values in summer than

338

in winter.40 In the Han River basin, the mean air temperature in August (summer) and

339

April (spring) is 24.8 and 15.2 °C, respectively, while mean temperature in January

340

(winter) is only 2.5 °C.41 Thus, temperature is one of the important determinants of

341

soil denitrification rates in wetlands along the Han River. It should be noted that C

342

and N can also be temporarily adsorbed on soil particles or retained in pore waters.17

343

These effects may somewhat moderate the difference in soil denitrification rates

344

among seasons.

345 346

Direct and indirect effects of edaphic conditions on wetland denitrification rates

347

Edaphic conditions, including moisture, NO3– concentration and C availability,

348

can directly affect the instantaneous rate of soil denitrification.17,18 Consistent with

349

earlier studies,42,43 there existed positive correlations between soil moisture and

350

denitrification rates in wetlands along the Han River (Table 2). The oxygen availability

351

changed rapidly depending on soil moisture and the consequent rate of oxygen

352

diffusion through soils.43 High soil moisture can inhibit oxygen diffusion and thereby

353

create anaerobic or anoxic environments favorable for denitrification. Our study also

354

revealed that soil NO3– content had a positive relationship with the wetland

355

denitrification rate (Table 2). Such a relationship was frequently observed in previous

356

studies,17,44 because NO3– was the terminal electron receptor of the denitrification

357

process. Many studies have examined the influences of C or organic matter contents

358

on soil denitrification rates.7,44 In this study, we observed positive correlations

359

between STC and potential and unamended denitrification rates (Table 2), consistent

360

with many previous studies.17,44 The positive relationships between soil NO3– or C 16


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concentrations and denitrification rates suggest that the denitrification process in

362

wetlands along the Han River is probably both C‒ and N‒ limited.

363

Knowledge of how edaphic conditions interactively control denitrifying microbial

364

communities and their ecological functions is relevant to better understanding N

365

removal capacity of wetlands.18 Several studies have assumed that edaphic

366

conditions can affect soil denitrification rates indirectly by altering microbial

367

communities.16,45 However, evidence for this assumption remains limited.18,46 Here, it

368

is evident that the indirect effect of soil moisture, NO3– and STC concentrations on

369

the wetland denitrification rates was mediated through denitrifier abundance (Fig. 4).

370

Soil moisture was positively correlated to nirK gene abundances, while soil NO3– and

371

STC concentrations were negatively correlated with nirS gene abundances (Table 1),

372

implying habitat selection on nirK and nirS denitrifiers and supporting the

373

speculations on niche differentiation.47 In riparian wetlands, soil moisture was

374

negatively correlated with oxygen availability, which could be a critical factor in

375

determining the structure of denitrifying communities.17 Previous studies have

376

reported that nirS–type denitrifiers are found in constantly anoxic conditions and

377

nirK–type denitrifiers are found in environments with fluctuating oxygen levels.16

378

Organic carbon, the primary electron donor for respiratory denitrifying bacteria, has

379

been shown to play an important role in regulating the abundance of denitrifying

380

communities.47 In general, the abundance of nirS gene increased with increasing

381

NO3– concentration in soils, because NO3– served as a terminal electron acceptor.18

382

These inconsistent results demonstrated that the abundance of nirS gene may

383

respond differently to the NO3– loads in different environments. Future work is

384

needed to examine the mechanisms by which soil NO3– and STC regulate the niche 17



385

differentiation between nirK- and nirS-type denitrifiers.

386 387

Denitrifier abundance and its direct effect on wetland denitrification rates

388

In the present study, the mean abundances of nirK and nirS genes were 5.22 and

389

2.69×105 gene copies g−1 soil, respectively. In some previous studies conducted in a

390

wide range of wetland habitats, nirS gene in soils generally had a greater abundance

391

compared to bacterial nirK gene.48‒50 However, consistent with our results, Dandie et

392

al. (2011) also reported a dominant role of nirK–type denitrifiers in soil denitrifying

393

communities in a riparian zone.51 Therefore, our findings suggest that nirK‒type

394

denitrifiers are important in wetlands along the Han River. Recent studies have

395

indicated that the abundance of nirK and nirS genes differs seasonally.20 However, we

396

found that there was no significant difference in nirK and nirS gene abundances

397

among seasons (p>0.05; data not shown) and between wetland types (Table S4). Our

398

results support earlier observation by Uksa et al. (2014) who also indicated that the

399

abundance of nirS-type denitrifier did not change significantly over time.52 This

400

suggested that denitrifier abundance do not necessarily covary with the

401

denitrification rates at a temporal scale.

402

As soil denitrification is a microbial–mediated process, the denitrifier abundance

403

may directly regulate the denitrification rate.19,53 So far, only a few studies have

404

investigated the relationships between denitrifier abundance and soil denitrification

405

rates in riparian zones, and their results are not consistent.21,51 Dandie et al. (2011)

406

demonstrated that there was no significant correlation between soil denitrification

407

rates and denitrifier abundances in riparian zones.51 However, Deslippe et al. (2014)

408

reported that the abundance of nirS–type denitrifier was positively related to 18


Page 18 of 36

Page 19 of 36


409

denitrification potential in riparian soils.21 These seemingly contradictory results are

410

not surprising, because soil denitrification rates reflect the readily activated enzymes

411

but the gene pools only partly contribute to the enzyme activities at a given time.54

412

In addition, the presence of nirK and nirS genes in soils does not necessarily mean

413

that such genes will be expressed or that the protein products of denitrifying genes

414

will function equivalently.53 In the present study, soil denitrification rates increased

415

with increasing abundance of nirK and nirS genes (Table 2), suggesting that the

416

denitrifier gene abundance could be an important limiting factor of soil

417

denitrification and N removal rate in wetlands in the Han River basin.

418

In summary, our study indicated that soil denitrification rates were significantly

419

different between riparian and reservoir shoreline wetlands along the Han River. As

420

we hypothesized, edaphic conditions could significantly affect wetland denitrification

421

rates both directly and indirectly. Directly, soil moisture, NO3–‒N and C availability

422

were positively correlated with soil denitrification rates. Indirectly, edaphic

423

conditions could regulate denitrification rate through their effects on denitrifier

424

abundance. Our findings provide evidence that not only environmental factors, but

425

also biotic factors including denitrifying communities and vegetation, play a critical

426

role in regulating soil denitrification rates. Therefore, future ecological restoration

427

such as revegetation and soil C amendment may effectively enhance the N removal

428

capacity of wetlands along the Han River in the Yangtze River basin.

429 430

Acknowledgments

431

We thank Hui Liu, Xiaoliang Jiang, Zhiyong Zhang and Wenyang Li for their

432

assistance with field sampling, sample processing and laboratory analyses, and four 19



433

anonymous reviewers for their constructive comments which improved the

434

manuscript. This research was funded in part by the National Natural Science

435

Foundation of China (Grant No. 31270583 and 31570463) and the Key Research

436

Program of the Chinese Academy of Sciences (Grant No. ZDRW-ZS-2016-7).

437

438

Notes

439

The authors declare no competing financial interest

440

441

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442

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27



Page 28 of 36

Table 1 Pearson correlation coefficients between biotic factors (denitrifier abundance and vegetation characteristics) and abiotic factors (edaphic conditions and water quality). nirK abundance 5

‒1

nirS abundance 5

Plant richness

‒1

Plant cover

(10 copies g )

(10 copies g )

-0.45**

-0.25

-0.29**

-0.21*

0.33*

0.18

0.19*

0.24**

-0.12

-0.18

-0.05

0.04

-0.22

-0.20

-0.16

-0.16

Soil NO3 ‒N (mg kg )

0.14

-0.29*

-0.29**

-0.12

STC (mg g‒1)

0.01

-0.29*

-0.14

0.08

-0.20

0.23

0.29**

0.13

0.04

-0.24

-0.05

-0.05

Soil pH Moisture (%) Fine substrate (%) ‒3

Density (g cm ) –

‒1

NH4+‒N (mg L‒1) –

‒1

NO3 ‒N (mg L )

(%)

STC, soil total carbon; * p

Edaphic Conditions Regulate Denitrification Directly and Indirectly by

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