Edaphic Conditions Regulate Denitrification Directly and Indirectly

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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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Edaphic conditions regulate denitrification directly and indirectly by

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altering denitrifier abundance in wetlands along the Han River, China

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

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a

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

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b

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P.R. China

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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

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*Corresponding author

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Phone: +86 27 87510987

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Fax: +86 27 87510251

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Email: [email protected] (Guihua Liu);

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[email protected] (Wenzhi Liu)

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Type: Research Articles.

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

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

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manuscript.

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Abstract

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

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

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

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

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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

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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

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

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

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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

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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

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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.

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Keywords: Denitrifying communities, Microbial abundance, Potential denitrification,

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Riparian zone, Wetland vegetation

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Introduction

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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

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

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wastewater discharge, chemical fertilizers, animal wastes, atmospheric deposition

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

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

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

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

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

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

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

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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

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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

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

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

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

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

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

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

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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

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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

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

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focused on the relationships between soil denitrification rates and denitrifier

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

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

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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

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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

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

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

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

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

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

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

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

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

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

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the effect of edaphic conditions on wetland denitrification rates.

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Materials and methods

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Study areas

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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

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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

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

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

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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

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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

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are mainly formed at the former farmlands and forests.14

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

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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).

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

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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

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

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

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landscape in this lowland sub-basin.17

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

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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

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

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

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

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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

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water quality degradation and other attendant ecological issues, including

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eutrophication and harmful algal blooms.30

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Field sampling

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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

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

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

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

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sampling wetland, one sampling transect was randomly established perpendicular to

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

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

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

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

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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

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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

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

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

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

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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

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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:

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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

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

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

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

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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

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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

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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.

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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

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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

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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

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

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

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(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

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analyzer (EasyChem plus, Systea, Italy).

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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

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

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

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

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

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green

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

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

quantitative

PCR

method.

Primer

sets

of

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

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

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

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in Table S2.

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Statistical analyses

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

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

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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

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denitrification rates, denitrifier abundances, vegetation characteristics and edaphic

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conditions among seasons and between wetland types. The relationships between

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

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correlation coefficient. Stepwise multiple regression analyses were used to identify

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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

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Inc., Chicago, USA).

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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

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

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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

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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

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

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

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

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

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

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

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Results

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Wetland denitrification rates

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

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

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

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Denitrification rates in lowland wetlands were slightly but not significantly higher

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

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

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seasons had a strong influence on both potential and unamended denitrification

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

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lowest denitrification rates were observed in January.

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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

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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

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

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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

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

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significant difference in all edaphic conditions except fine substrate between

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

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

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

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

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species richness (Table 1).

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Determinants of wetland denitrification rates

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Soil denitrification rates were strongly associated with several abiotic and biotic

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

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unamended denitrification rates showed significant positive relationships with

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

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analyses demonstrated that nirK abundance was the most important predictor of

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

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variations, respectively.

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The CFI values for potential and unamended denitrification models were 0.949

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

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

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

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conditions, especially moisture, could affect potential denitrification rates both

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

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

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

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

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

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Discussion

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Spatial and temporal dynamics of wetland denitrification rates

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

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

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

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

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

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

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

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

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

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

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

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

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

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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

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denitrification rates in soils increased considerably with incubation temperatures.36

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

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

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incubation experiments, the addition of chloramphenicol might significantly reduce

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the potential and unamended soil denitrification rates.

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

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

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

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

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

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

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

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

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wetlands.

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Furthermore, reservoir shoreline wetlands along the Han River supported

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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

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

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

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

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

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

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

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

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

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

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

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

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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

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

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

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

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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

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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

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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

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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

References

442

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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