Sediment nitrate reduction processes in response to environmental gradients along an urban river-estuary-sea continuum

Journal Pre-proof Sediment nitrate reduction processes in response to environmental gradients along an urban river-estuary-sea continuum

Hengchen Wei, Dengzhou Gao, Yong Liu, Xianbiao Lin PII:

S0048-9697(20)30695-1

DOI:

https://doi.org/10.1016/j.scitotenv.2020.137185

Reference:

STOTEN 137185

To appear in:

Science of the Total Environment

Received date:

18 November 2019

Revised date:

29 January 2020

Accepted date:

6 February 2020

Please cite this article as: H. Wei, D. Gao, Y. Liu, et al., Sediment nitrate reduction processes in response to environmental gradients along an urban river-estuary-sea continuum, Science of the Total Environment (2020), https://doi.org/10.1016/ j.scitotenv.2020.137185

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© 2020 Published by Elsevier.

Journal Pre-proof

Sediment nitrate reduction processes in response to environmental gradients along an urban river-estuary-sea continuum Hengchen Wei2‡, Dengzhou Gao3, Yong Liu5, Xianbiao Lin1,3,4‡* 1

Laboratory of Microbial Ecology and Matter Cycles, School of Marine Sciences, Sun

Yat-Sen University, Zhuhai 519082, China The University of Texas at Austin Marine Science Institute, 750 Channel View Drive,

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School of Geographic Sciences, Key Laboratory of Geographic Information Science of

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Port Aransas, Texas 78373, USA

Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai

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the Ministry of Education, East China Normal University, Shanghai, 200241, China

519000, China

Key Laboratory of South China Sea Fishery Resources Exploitation & Utilization,

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Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China

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*Corresponding Author:

E-mail address: [email protected]; Phone: +86-756-3668259 ‡

Xianbiao Lin and Hengchen Wei contributed equally to this work

Keywords: Denitrification; Anammox; DNRA; Sediment; Urban river-estuary-sea continuum; Nitrogen Cycling

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Abstract

Sediment denitrification (DEN), anaerobic ammonium oxidation (Anammox), and dissimilatory nitrate reduction to ammonium (DNRA) are three important nitrate (NO3–) reduction pathways in aquatic ecosystems. These processes modify nitrogen (N) loadings from land to the ocean, with important implications on the management of coastal

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eutrophication. While NO3– reduction has been studied intensively for various types of

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habitats, studies on its distributions along river-estuary-sea continua remain scarce. In

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this study, we examined these three pathways along a N-laden urban river-estuary-sea

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continuum comprised of three types of habitats (urban river, estuary, and adjacent sea) in

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the densely populated Shanghai-East China Sea area. The potential DEN, Anammox, and DNRA rates decreased seaward both in summer and winter in response to decreasing

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sediment organic matter (OM, 20 to 7 to 7 mg C g-1), ferrous oxide (9 to 2.7 to 2.8 mg Fe

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g-1), and bottom water dissolved inorganic nitrogen (543 to 112 to 21 μM). Among these pathways, DEN remained a major component (~69.6%) across habitats, while Anammox

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(47.9%) rivaled DEN (48.3%) in the urban river in winter. N retention index (NIRI), the ratio between retained and removed NO3–, ranged from 0–0.5 and increased downstream. Together, these results suggest that the decreasing gradients of OM and inorganic matter shape the distribution of NO3– reduction along the continuum, reflecting the diminishing impact of the river and human inputs from the urban river to the ocean. Our results highlight the importance of taking a continuum perspective in N cycling studies and emphasize the role of urban rivers as N removal hotspots, which should be a focus of research and management.

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Introduction

Nitrogen (N) is an essential element of all life forms, yet its presence on the planet is dominated by diatomic nitrogen gas (N2) in the atmosphere, a form only available to a number of bacterial, fungal, and archaea species (Galloway et al. 2004). N forms available to other organisms, known as reactive N, can be converted from N2 through

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processes such as natural biological N fixation, or lightning (Galloway et al. 2004). These

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natural processes are relatively slow and constant compared to anthropogenic N fixation,

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and as a result, natural ecosystems are often N limited. However, N cycles have been changed globally since the Industrial Revolution, as anthropogenic N fixation increased

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dramatically, mostly through the production of synthetic fertilizers for agriculture

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(Boesch 2002). The produced Nr will eventually be transported from land to ocean via

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river networks and atmospheric deposition, affecting ecosystems along the way (Seitzinger et al. 2002). Over the past decades, global Nr has increased by ~5 fold,

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contributing to widespread deterioration of coastal marine ecosystems, with

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consequences including increases in primary production, dissolved oxygen (DO) depletion, biodiversity decline, food web alteration, and harmful algal bloom expansion (Cloern 2001; Boesch 2002). Understanding the land-ocean interaction of N has become an important scientific and management issue. Coastal ecosystems at the interface between land and ocean, from river networks to estuaries and nearshore areas, are major sites for N transport and transformation from land to ocean. They function as filter units between environmental stressors and coastal ecosystems responses (in the sense of Cloern 2001, Bouwman et al. 2013, and Asmala et al. 2017). Understanding N cycles in coastal ecosystems under heavy human impact is

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Journal Pre-proof therefore important. The Yangtze River system and the East China Sea (ECS) in East Asia represent a typical example of a system heavily impacted by human activities. The Yangtze River, the world‟s fifth-largest river by discharge (Hu et al. 2012), has a 1.81 × 106 km2 watershed that houses 450 million people (Liu et al. 2008). It carries large amounts of inorganic N loadings to the sea (1.21–2.42 × 106 t N yr-1, Lin et al. 2016). The Yangtze River enters the ECS at Shanghai, a megacity that discharges ~5.9 × 105 t total N

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into its river networks annually (Gu et al. 2012). As a result, the Yangtze-ECS region is

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undergoing a series of ecological problems, including worsening eutrophication and

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hypoxia (Li et al. 2014; Wang et al. 2016) and a 7-fold increase in harmful algal blooms

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since 1993 (Qu and Kroeze 2010). This dramatic change is accompanied by a 12-fold increase in N concentrations in the estuary over the past few decades (Chai et al. 2006).

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Studies on the behavior of N within this area are therefore necessary to provide insights

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into the management of coastal eutrophication. Dissolved inorganic nitrogen (DIN), primarily NO3–, can be reduced to N2 or NH4+

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via three major pathways: denitrification (DEN), anaerobic ammonium oxidation

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(Anammox), and dissimilatory nitrate reduction to ammonium (DNRA). The former two processes reduce NO3– to N2 gas and represent a permanent N sink to a system, whereas DNRA transforms NO3– into NH4+, which does not remove N and potentially makes N more available to phytoplankton, thus potentially contributing further to eutrophication (Seitzinger 1988; Risgaard et al. 2004; Dalsgaard et al. 2005; Hietanen and Kuparinen 2008; Crowe et al. 2012). Traditionally, these N reduction pathways are determined by rate measurements often involving 15N addition methods (e.g., Nielsen 1992; Rysgaard et al. 1993; An and Gardner 2002; Thamdrup and Dalsgaard 2002; Song et al. 2013).

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Journal Pre-proof Advances in molecular methods have also made quantitative measurements of functional genes relevant to N cycling possible (Zehr and McReynolds 1989; Ward 1996; Zehr and Capone 1996). This approach provides another way to probe NO3– reduction and complements traditional rate measurements. While NO3– reduction pathways have been studied in various habitats of the broader Yangtze-ECS ecosystem before, the patterns were not compared among different habitats

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or examined along the entire urban river-estuary-sea continuum. Direct comparisons of N

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cycling for different types of habitats are scarce, partially due to inconsistency in

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methodology for N cycling measurements (Bierschenk et al. 2012; Bruesewitz et al.

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2017). Nonetheless, such comparisons are needed to view the continuum as a whole and to make comprehensive management decisions (Paerl 2009; Zhang 2015). Echoing this

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concept, we expanded previous work on NO3– reduction in the urban river networks in

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Shanghai, the Yangtze Estuary, and the adjacent ECS area. We compared NO3– reduction for these three types of habitats (namely, the urban river network, the estuary, and

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adjacent sea areas), and combined them to investigate the controlling environmental

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factors over the entire river-estuary-sea continuum. We hypothesized that nutrient and organic matter (OM) become depleted from upstream to downstream along the continuum, which decreases the potential rates of all three NO3– reduction pathways, with rates higher in summer than winter. We also hypothesized that the N retention (N cycled as NH4+ within the system instead of being removed as N2) becomes increasingly important along the continuum. To test these hypotheses, we (1) examined the spatial and seasonal distributions of NO3– reduction rates and their associated gene data along the urban river-estuary-sea

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Journal Pre-proof continuum, (2) determined key environmental variables affecting NO3– removal processes in this continuum, and (3) calculated and compared N retention index along the continuum and identified NO3– removal hotspots.

2 Materials and Methods

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2.1 Study Area and Sampling

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The greater Shanghai area is located onthe Yangtze River Delta (Figure 1), is a

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metropolis with a population of more than 23 million and a total land area of 6300 km2

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(Yu et al. 2013). The water area (569.6 km2) of its river network accounts for about 9%

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of its total land area (Lin et al. 2017a). With rapid urbanization, the urban river network received high loading of N and suffers from a series of ecological problems (Gu et al.

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2012; Yu et al. 2013). Downstream of the urban river network, the Yangtze Estuary

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covers an area of ~8500 km2. The mean annual temperature is 15 °C and the mean annual precipitation is 1004 mm (Cui et al. 2012). The increasing DIN is attributed to massive N

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loadings from agricultural activities and wastewater discharge within the Yangtze River basin and has caused severe eutrophication and frequent occurrences of harmful algal blooms during the past three decades (Chai et al. 2006; Dai et al. 2011; Li et al. 2014). Further offshore, the ECS is the largest marginal sea in northwestern Pacific and is influenced strongly by the Yangtze River (Gao et al. 2015). Annually, it receives a substantial amount of terrestrial material via the Yangtze River, including particulate OM (~1.20 × 107 t N yr-1, Liu et al 2007) and DIN (1.2–2.42 × 106 t N yr-1, Huang et al. 2006;

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Journal Pre-proof Kim et al. 2011; Chen et al. 2016). As a result, the ECS has suffered from eutrophication and hypoxia over the past several decades (Li et al. 2007; Song et al. 2013). A series of seasonal research efforts were made to quantify NO3– reduction rates and environmental conditions in the study region. The urban river network and the Yangtze Estuary habitats were surveyed from January 10–15, 2015 (winter) and from July 12–17, 2015 (summer), and the adjacent sea habitat from February 23–24, 2015 (winter) and

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from July 20–21, 2015 (summer). Rate data for DEN, Anammox, and DNRA in the urban

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river habitat and DEN and Anammox in the adjacent sea habitat were determined with

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slurry experiments and published in three previous papers (Cheng et al. 2016; Lin et al.

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2017a; b). In this study, we compiled some of those data with our new data (including DEN, Anammox, and DNRA rates in the estuary and DNRA in the adjacent sea, as well

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as their associated gene data for all three habitats) following the same methods as in the

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previous works, to form a balanced dataset. This dataset includes 11 stations in the urban river network of Shanghai, 10 stations in the Yangtze Estuary, and 9 stations in the near-

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shore region of ECS adjacent to the estuary (Figure 1). We compared NO3– reduction and

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environmental data among the habitats and explored the dataset for general patterns and relationships for the entire continuum. This data product is publicly available online (DOI: 10.17632/m2ky7vz8fk.2). At each station, triplicate surface (0–5 cm) sediment samples were collected with a box corer, subsampled with plexiglass tube (7 cm diameter), and sealed immediately with air-tight, acid-cleaned plastic bags, and stored at 4 °C. Bottom water samples were collected in polyethylene bottles and filtered through 0.22 μm filters (Millipore, Bedford, USA), and frozen (-20 °C) until analysis of DIN. Upon returning to the laboratory,

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Journal Pre-proof sediment in each core was immediately mixed thoroughly under a helium atmosphere. Part of the sediment was preserved at -80 °C for DNA extraction and subsequent molecular analysis, and the rest was stored at 4 °C for measurement of dissimilatory NO3– reduction rates and sediment physicochemical parameters.

2.2 Determination of Environmental Parameters

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We measured bottom water pH with a Mettler-Toledo pH Meter. Total organic

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carbon (TOC) and total N (TN) in sediments were analyzed on a thermal combustion

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furnace analyzer (Elementar analyzer vario MaxCNOHS, Germany), acidified with 1 M

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HCl (Hou et al. 2013). Exchangeable NH4+ and NO3– in sediments were extracted with 2 M KCl and subsequently measured with a nutrient autoanalyzer (SAN plus, Skalar

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Analytical B.V., Breda, The Netherlands), with detection limits of 0.5 μM for NH4+ and

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0.1 μM for NO3– (Hou et al. 2013). Total extractable iron (Fe) and ferrous oxides (Fe(II)) in sediments were extracted anaerobically with 10 mL mixtures of 0.5 M HCl and 0.5 M

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hydroxylamine hydrochloride (bubbled with N2 prior to the extraction) and measured

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following the ferrozine method. The concentrations of ferric oxides (Fe(III)) were calculated by subtracting Fe(II) from total extractable Fe (Lovley and Phillips 1987). Sediment grain sizes were measured with the laser diffraction technique (LS 13 320 Particle Sizing Analyzer, Beckman Coulter, USA). Sulfide (S2–) in sediments was determined using methylene blue spectrophotometry, as described in Deng et al. 2015. All sediment nutrient and OM parameters were normalized to the dry weight of the sediment.

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Journal Pre-proof 2.3 Sediment Incubation Experiments Potential DEN and Anammox rates were determined using N isotope-tracing techniques in an anaerobic glovebox filled with helium. For concise purposes, these potential rates are simply referred to as rates in this paper. Briefly, slurries of a 1:7 sediment/ water ratio were stirred for 30 min and purged with helium, then transferred into 12-mL vials pre-purged with helium (Labco Exetainers). Subsequently, vial samples

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were pre-incubated at field temperature in dark for 24 h (and 48 h for urban river

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samples), to remove any residual NO3–, NO2– and oxygen. After the pre-incubation, we

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followed the previously reported method (Thamdrup and Dalsgaard 2002) and applied three different 15N labeling treatments as follows: (1) 15NH4+ (99.12 atom%), (2) 15NH4+

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+ 14NO3–, and (3) 15NO3– (99.21 atom%). The final concentration of 15N in each vial was

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~100 μM. Reactions were quenched by adding 200 μL 50% ZnCl2 solution to each vial at

the difference of

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3-hour intervals during the total 12-hour incubation. The

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N-atom% was calculated as

N atom% in the stock solution (99.21 atom%

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NO3–) and in the

N2 produced during the incubations were measured by membrane inlet mass

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residual ambient NO3– and NO2–, ranging from 86% to 99%. Concentrations of 29N2 and

spectrometry (MIMS, Kana et al. 1994; An and Gardner 2002). In addition, the concentrations of produced

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NH4+ were determined with a combination of the NH4+

oxidation technique and MIMS analysis to estimate the potential DNRA rates (Yin et al. 2014). These methods are consistent with the previous studies for this area (Cheng et al. 2016; Lin et al. 2017a; b) and are detailed in Hou et al. 2013 and Yin et al. 2014. DEN and Anammox rates are traditionally derived from 28N, 29N, and 30N concentrations using equations in Thamdrup and Dalsgaard 2002. However, the co-existence of DNRA could

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Journal Pre-proof intervene with the result of DEN and Anammox rates calculated this way, as it assumes that

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N2 could only be produced by DEN. This assumption is violated when coupled

DNRA-Anammox is significant, which also produces

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N2 (Song et al. 2013, 2016; Salk

et al. 2017). This problem affects both slurry and whole-core incubations, and a few methods have been developed to account for the effect of DNRA on DEN and Anammox rates (Song et al. 2016; Salk et al. 2017). In this study, we used the equations in Song et

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al. 2016 for slurry experiments to calculate the adjusted DEN and Anammox rates.

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DNRA rates were calculated using equations from Porubsky et al. 2008. All rates were

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normalized to the sediment dry weights and reported in μmol N kg-1 h-1.

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2.4 Extraction of DNA and quantification of N-cycling related genes

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DNA was extracted from 0.25 g homogenized fresh sediment samples using a

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PowersoilTM DNA Isolation Kits (MOBIO, USA) following the manufacturer‟s instructions. Real-time q-PCR analysis of the extracted DNA was performed to measure

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the gene abundance of the NO3– reducing bacteria (i.e., nirS, anammox bacterial 16S

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rRNA, and nrfA genes) with an ABI 7500 Detection System (Applied Biosystems, Canada) using the SYBR green method. The details of the primers and q-PCR conditions for these genes are shown in Table S1 (supplementary material). The standard curves for the nirS, anammox bacterial 16S rRNA, and nrfA genes were created using a 10-fold dilution series (102–109 copies) of the standard plasmids DNA (Zheng et al. 2016). The amplification efficiencies were 77.5–96.6%. These gene abundances were calculated by the constructed standard curve and then converted into copies per gram of dry soil.

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Journal Pre-proof 2.5 Statistical Analyses In this study, the contribution of DEN to total NO3– reduction was expressed as DEN%, defined as 100 × [DEN/(DEN+Anammox+DNRA)], and similarly for Anammox and DNRA. One-way analysis of variance (ANOVA), followed by Tukey‟s HSD test, was conducted to compare the spatial and seasonal differences in NO3– reduction functional gene abundance, rates, and environmental parameters. These statistical

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analyses were performed with SPSS 19.0. All assumptions were met for the ANOVA

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analysis. We also used multivariate analyses to explore the variations of NO3– reduction

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and environmental data and the relationships between these two sets of parameters for the entire continuum. Specifically, we performed principal component analysis (PCA) to

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describe the variations of the entire dataset, including NO3– reduction and environmental

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data. We also performed canonical correspondence analysis (CCA) with forward variable

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selection based on R2 on environmental variables to describe the relationships between the NO3– reduction variable matrix and the environmental data matrix in a multivariate

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manner. The significance of the fit was tested with a permutation test. The theories and

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mathematical implementation of these two methods can be found in Legendre and Legendre 2012. We conducted the PCA and CCA analyses using the stats and vegan packages in R.

3 Results 3.1 The physiochemical characteristics of the river-sea continuum Sharp gradients of physical conditions (i.e., salinity and DO) and physiochemical properties (i.e., DIN, TN, TOC, Fe, and S2–) were observed along the urban river-estuary-

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Journal Pre-proof sea continuum. Overall spatial patterns were consistent between summer and winter (Figure 2). Average salinity increased from 0.3 ppt in the urban river to 3.2 ppt in the estuary and 29.1 ppt in the adjacent sea in summer, and from 0.6 to 5.2 to 30.4 in winter (Figure 2 a & b). Along with the salinity rise, DO increased from the urban river to the sea, from < 30% saturation in the urban river to 60% and 100% in the estuary and the sea in both seasons, with concentrations significantly higher in winter than summer (Table 1;

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Figure 2 a & b). In contrast to salinity and DO, physiochemical parameters generally

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decreased seaward. The locations of dramatic drops varied for the different parameters,

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and concentration levels differed between winter and summer. Specifically, NO3– decreased from the urban river network to the Yangtze Estuary and the adjacent sea, with

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concentrations higher in winter than summer (Table 1; Figure 2 c & d). NH4+ also

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dramatically declined from the urban river network to the estuary and the adjacent sea,

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with concentrations also higher in winter than summer (Table 1; Figure 2 c & d). Sulfide, Fe(II), TN, and TOC generally followed similar patterns as NH4+, with dramatic

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decreases occurring between the urban river and the Yangtze Estuary (Table 1; Figure 2 e

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– h). The seasonal differences for these parameters were less drastic compared to their spatial differences and were less consistent along the continuum. An exception is S2–, which was considerably lower in winter than summer in the urban river network and the opposite in the Yangtze Estuary and the adjacent sea (Table 1; Figure 2 e & f).

3.2 Spatial and temporal variations of NO3– reduction pathways In general, DEN, Anammox, and DNRA rates decreased from the urban river network to the adjacent sea along the continuum, particularly between the urban river

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Journal Pre-proof network and the estuary, where the differences were most dramatic. These spatial patterns were mostly consistent between summer and winter, but rates differed substantially. DEN was the dominant NO3– reduction pathway in both seasons across the continuum, while Anammox was also important at the urban river network in winter. In summer, average DEN rates decreased from the urban river (28.6 μmol kg-1 h-1) to the estuary (5.9 μmol kg-1 h-1) and the adjacent sea (5.4 μmol kg-1 h-1) (Figure 3 a;

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Table 1). Anammox followed a similar spatial pattern as DEN (Figure 3 c; Table 1). The

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average rates were one order of magnitude higher in the urban river (6.5 μmol kg-1 h-1),

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than in the estuary (1.2 μmol kg-1 h-1) and the adjacent sea (1.7 μmol kg-1 h-1). Average DNRA rates also decreased from the urban river (2.0 μmol kg-1 h-1) to the estuary (1.0

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μmol kg-1 h-1) and the adjacent sea (1.3 μmol kg-1 h-1) (Figure 3 e; Table 1). Among the

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three processes, DEN was dominating, with its proportion of the total NO3– reduction

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(%DEN) ranging from 70% in the urban river to 78% in the estuary, and 71% in the adjacent sea. %Anammox ranged from 22% to 11% to 17% from the urban river to the

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& k; Table 1).

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estuary to the adjacent sea, and %DNRA ranged from 7% to 11% to 12% (Figure 3 g, i,

In winter, spatial patterns of the three NO3– reduction processes mirrored those in summer. Average DEN rates were high in the urban river (12.5 μmol kg-1 h-1) and low in the estuary and the adjacent sea (both ~3 μmol kg-1 h-1) (Figure 3 b; Table 1). Average Anammox rates ranged from 11.4 to 0.6 and 0.8 μmol kg-1 h-1 from the urban river to the estuary and the adjacent sea (Figure 3 d; Table 1). Average DNRA rates were 1, 0,41, and 0.42 μmol kg-1 h-1 in the urban river, estuary, and adjacent sea habitats (Figure 3 f; Table 1). DEN was still the dominating process, with %DEN ranging from 48% in the urban

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Journal Pre-proof river to 68% in the estuary and the adjacent sea (Figure 3 h; Table 1). Anammox in the urban river rivaled DEN, accounting for 48% of the total NO3– reduction (Figure 3 j; Table 1). In the estuary and the adjacent sea, the average percentages of Anammox were 17% and 20%, respectively. DNRA remained a minor component, whose average percentages were 4%, 14%, and 12% in the urban river, the estuary, and the adjacent sea (Figure 3 l; Table 1).

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The distributions of the functional genes (i.e., nirS, Anammox 16s RNA, and nrfA)

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generally matched those of their corresponding N reduction pathways (DEN, Anammox,

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and DNRA, respectively) described above (Figure 4 a – f). Between seasons, the

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distribution within each zone changed (Figure 4), but the differences were less substantial compared to the changes in rates (Figure 3; Table 1). Patchy hotspots for Anammox 16s

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RNA:nirS occurred in the urban river and the adjacent sea during winter, and for

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nrfA:nirS in the sea during winter. The gene abundance correlated well with corresponding rates (Spearman coefficients of 0.76, 0.70, and 0.44 for DEN, Anammox,

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and DNRA, respectively), indicating agreement between these two sets of measurements.

3.3 Multivariate analyses on NO3– reduction and environmental parameters When all data are included, the PCA result shows that the PC1 was mainly driven by spatial differences between the urban river and the other two habitats (Figure 5 a). Along PC1, urban river samples are distributed towards the negative side, whereas samples from the estuary and the adjacent sea are towards the positive side and well mixed. DEN, Anammox, DNRA, %Anammox, and all physiochemical parameters except sediment NO3– have negative loadings on PC1, whereas %DNRA, depth, %DEN, and

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Journal Pre-proof sediment NO3– have positive loadings. Along PC2, urban river samples are separated by different seasons, with summer samples distributed more towards the negative side of PC2 and winter sample more towards the positive side. The estuary and adjacent samples, however, are still mixed. Bottom water NO3– and NH4+, as well as %Anammox, have high positive loadings on PC2, whereas sediment S2-, DEN, and %DEN have high negative loadings (Figure 5 a). To further characterize the variations in the estuary and

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adjacent sea data, we repeated the PCA analysis, excluding the urban river data. The PCA

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result shows that PC1 was mainly driven by seasonal differences, where summer data

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were on the positive side and winter on the negative side of PC1. DEN rates had the

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largest positive loading on PC1, and bottom water NH4+ had the largest negative loading. TOC, TN, Fe(II), Anammox and DNRA also contribute to the seasonal separation, as

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they all have positive loadings on PC1. PC2 is mainly driven by the spatial differences,

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where the adjacent sea samples are distributed towards the negative direction of PC2 and the estuary samples towards the positive side (Figure 5b). Bottom water NO3– has the

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largest positive loadings on PC2, whereas depth has the largest negative loadings.

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Anammox and DNRA also have negative loadings, but DEN has virtually no loading on PC2 (Figure 5b).

The result of the CCA analyses on summer and winter data shows that sediment Fe(II), TN or TOC, and bottom water NH4+ best explain the variations in DEN, Anammox, DNRA rates and their percent contributions (Figure 6 a & b). In summer, urban river sites featured by high Anammox and %Anammox rank high on the gradient of sediment Fe(II), whereas urban river sites featured by high DEN rank high on the gradients of TN and bottom water NH4+. On the other side, the estuary and the adjacent

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Journal Pre-proof sea sites are exemplified by high %DEN and %DNRA and rank low on those gradients. The DNRA rates, however, do not differ much among habitats (Figure 6 a). In winter, the urban river sites featured by high Anammox, DEN, DNRA, and %Anammox rank high on both the Fe(II) and TOC gradients, whereas the estuary and sea sites with high %DEN and %DNRA rank low on these gradients (Figure 6 b). Overall, high rates of DEN and Anammox and high %Anammox characterized the urban river sites, which lay on the

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higher end of TOC, TN, bottom water NH4+, and Fe(II) gradients, whereas high %DEN

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and %DNRA characterize the estuary and the adjacent sea, which lay on the lower end of

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these gradients.

4 Discussion

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NO3– reduction at the sediment-water interface in coastal aquatic environments is an

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important N removal/retention mechanism at the land-ocean interface (Herbert 1999). While these pathways have been studied intensively in various riverine, estuarine, and

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marine ecosystems, they have not been compared across different types of habitats along

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a hydrologically connected continuum. We address this gap by examining NO3– reduction along an urban river-estuary-sea continuum in the Shanghai-ECS area. DEN, Anammox, and DNRA decreased seaward in response to decreasing OM (i.e., TOC and TN) and inorganic matter (i.e., NO3–, NH4+, S2–, and Fe(II)) from the urban river to the sea. N loading from human activities is removed and modified by this continuum before reaching the continental shelf, with the urban river playing a particularly important role. Our results highlight the importance of cross-ecosystem comparisons and comprehensive management strategies accounting for different types of habitats along a continuum.

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4.1 Environmental factors affecting NO3– reduction along the urban river-estuarysea continuum 4.1.1 Temperature effects In this study, NO3– reduction rates were significantly higher in summer than in

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winter. This result is consistent for both DEN and DNRA across all three habitats (p<0.05; Table 1). In contrast, Anammox rates in the urban river network were higher in

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winter than in summer (p<0.05; Table 1). Temperature can be an important controlling

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factor for seasonal differences in N cycling. It is often positively related to NO3–

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reduction rates, as metabolisms often increase with temperature (Bremner and Shaw 1958;

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Bachand and Horne 1999). High temperatures have been shown to favor DNRA over DEN in temperate salt marshes and estuarine sediments (King and Nedwell 1985; Ogilvie

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et al. 1997a; b). This observation is consistent with our finding that %DNRA was higher

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in summer than winter in the urban river, where DNRA rates were highest. However, the seasonal differences of %DNRA were marginal in the estuary and adjacent sea,

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supporting a previous conclusion that temperature does not play a major role in regulating %DNRA in those two habitats (Deng et al. 2015). Anammox has a lower optimal temperature (12 °C) than DEN (24 °C) and DNRA (>17 °C) (Kelly-Gerreyn et al. 2001; Jetten et al. 2001) and has been shown to better adapt to cold environments than DEN (Canion et al. 2014). This difference could explain the faster rates in winter than summer (11.4 compared to 6.4 μmol kg-1 h-1) in the river network. This seasonal pattern did not hold for the estuary and the adjacent sea, where both rates were much lower (0.6 – 1.6 μmol kg-1 h-1) than in the urban river. One explanation is the coupling of Anammox

17

Journal Pre-proof with DEN and DNRA in the estuary and adjacent sea (Figure S1), as partial DEN and DNRA can produce NO2– and NH4+, respectively, to fuel Anammox. In low N environments, Anammox is often limited by NO2– availability, and anammox bacteria adapted to such environments can have other metabolisms to reduce NO3– to N2 via NO2– (DEN) or via NH4+ and NO2– (DNRA and Anammox) (Kartal et al. 2007). This mechanism may be particularly important in warm summer months when DEN and

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DNRA rates were presumably high. Consistent with this idea, our Anammox rates in

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summer were significantly higher than in winter in the estuary and the adjacent sea (P <

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0.05, Table 1), where N levels were low compared to the urban river (Table 1). However,

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our incubation experiments were not sufficient to discern the specific metabolism pathways of Anammox bacteria. More research is needed to understand the metabolism

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of Anammox bacteria in the coastal ECS area.

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4.1.2. Organic matter and nutrient effects The Yangtze Estuary and the adjacent ECS receive most OM from land via the

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Yangtze River (Yang et al. 2015; Lin et al. 2017b). The effects of this riverine source diminish from the river mouth to offshore (Figure 2 & 5; Table 1). Nutrient concentrations are also high at the river mouth, which leads to higher in-situ production, another major input to the OM pool. The increasingly deep water column seaward also reduces OM deposition on sediments, as particles are subject to water column degradation and remineralization before reaching the seafloor (Babbin and Ward 2013). In addition, DO levels also increased seaward, which may promote remineralization, a sink for OM, as remineralization occurs faster in oxic than anoxic environments

18

Journal Pre-proof (Laufkötter et al. 2017). Collectively, these geophysical conditions create environmental gradients from the urban river to the sea, characterized by decreasing OM and nutrient availability, which increasingly favor OM consumption over production and preservation. These environmental gradients along the continuum set the stage for the variations of N biogeochemistry along the continuum. Specifically, the gradients of sediment OM (i.e., TN and TOC) contents and the associated variations in inorganic nutrients (bottom

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water NO3– and NH4+) and sediment Fe (II) are apparent driving factors for the observed

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patterns in NO3– reduction rates. The distributions of DEN, Anammox, and DNRA rates

-p

were consistent with OM distributions in space and time (Figures 2, 3, & 5). DEN and

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Anammox were tightly associated with sediment TOC and TN (Figure 6). Our data corroborate the idea that both TN and TOC reflect OM contents in sediments, which fuel

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dissimilatory NO3– reduction in a wide range of ecosystems around the world (Seitzinger

na

et al. 2006; Burgin and Hamilton 2007, and the references therein). OM serves as electron donors and provides energy for DEN (Tiedje et al. 1983). It may also fuel

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Anammox via coupling with DEN, which produces NO2–, a substrate of Anammox

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(Thamdrup and Dalsgaard 2002; Engström et al. 2005; Nicholls and Trimmer 2009). OM may also supply inorganic N for both DEN and Anammox via remineralization, and this mechanism is presumably more important in warm summer. A previous study on sediment remineralization rates for the ECS area demonstrates that organic N is transformed into inorganic N faster in summer (Lin et al. 2016). Along with sediment OM, bottom water NH4+ also contributed to the spatial patterns of DEN, DNRA, and Anammox (Figure 6). Spatially, its distributions matched the seaward decreasing patterns of the three NO3– reduction rates (Figure 2 & 3); seasonally,

19

Journal Pre-proof it was significantly higher in winter than summer for all habitats (Table 1), likely a result of slower uptake activities in the colder winter. Bottom water NH4+ can affect Anammox, as it serves as the electron donor in this process (Burgin and Hamilton 2007). NH4+ concentration was also correlated to DEN and DNRA (Figure 6), even though it is not a required substrate in both processes. Its positive correlation with DNRA could be partly explained by that it is an end product of the process. However, its link to DEN is

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probably due to its correlation with bottom water NO3– and sediment TOC and TN

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(Spearman coefficients ranges from 0.53 to 0.71). NO3– and OM are electron acceptors

-p

and donors in both respiratory DEN and DNRA (Burgin and Hamilton 2007). The interrelationships among these parameters also suggest that they all followed the same

re

gradient of diminishing human influence from the river to the ocean. In fact, the largest

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source of variations in the dataset is the spatial difference between urban river and the

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other two habitats, as the urban river had higher values in all organic and inorganic matter variables except for sediment NO3– (Figure 5). As a result, the urban river had the highest

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NO3– reduction rates (Figure 3; Table 1).

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Together, these results suggest that the gradients of DIN reflected the gradient of decreasing anthropogenic N input from upstream to downstream, and along this gradient, sediment microbial communities showed decreasing NO3– reduction potential. N input was removed by sediments along the continuum mainly through DEN, and to a less degree, through Anammox, whose role was more important in winter. The variations of NO3– reduction along DIN gradients are studied for the Colne Estuary, United Kingdom (Dong et al. 2009), where DEN, Anammox, and DNRA rates also decreased downstream in response to decreasing water column NO3– availability, consistent with our

20

Journal Pre-proof observation. They also found the highest %Anammox (~30%) occurred in their most organic-rich sites, matching our observations for the urban river network. Sediment Fe(II) also appeared to play a role in NO3– reduction (Figure 6). In the Shanghai-ECS region, similar positive correlations between DEN and Fe(II) were reported for the Yangtze Estuary (Deng et al. 2015), but not for the river networks in Shanghai (Cheng et al. 2016) or the adjacent ECS (Lin et al. 2017b). Fe(II) functions as

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an electron donor to NO3– or NO2– in N reduction processes (Straub et al. 1996; Behrendt

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et al. 2013; Roberts et al. 2014). Specifically, Fe(II) can be coupled to DEN through the

re

-p

following stoichiometry:

In addition to Fe, organic substrates are often required to facilitate this process

lP

(Kappler et al. 2005; Muehe et al. 2009; Chakraborty and Picardal 2013). Our urban river

na

has high OM and Fe(II), making it suitable for this process. Fe(II) is also reported, in a

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2011):

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smaller number of publications, to reduce NO3– to NH4+ (Weber et al. 2006; Coby et al.

Fe(II) can be a controlling factor in the partitioning of DEN and DNRA, as Fe(II) addition has been shown to stimulate DNRA but not DEN in some incubation experiments (Robertson et al. 2016; Robertson and Thamdrup 2017), or high DNRA rates have been measured at sites with high Fe(II) concentrations (Roberts et al. 2012, 2014). In this study, however, the associations of Fe(II) with DNRA and %DNRA were generally weaker than with DEN (Figure 6), and DNRA was not a major pathway in our system (Table 1), suggesting that the coupling with DNRA was less important than DEN.

21

Journal Pre-proof Similar to Fe(II), S2– could also serve as an electron donor to NO3– in DEN and DNRA processes (Sørensen et al. 1979; Reyes-Avila et al. 2004; Wang et al. 2009). Interestingly, Fe(II) was related positively with Anammox, especially in winter (Figure 6). Although Anammox bacteria have been shown to reduce NO3– to N2 via anaerobic oxidation of Fe2+ in cultures (Oshiki et al. 2013), such process had not been reported for natural coastal environments. Fe(II) could also link to Anammox through its correlation with

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Fe(III) (Spearman coefficient 0.52, p<0.05); in fact, Fe(III) showed a higher correlation

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with Anammox in winter than Fe(II) (Spearman coefficient of 0.75 compared to 0.69).

-p

Anammox could be coupled to Fe(III) reduction, where Fe(III) receives electrons from NH4+ oxidation. This process has been documented for soil (Yang et al. 2012; Huang et

re

al. 2016), wetland sediments (Li et al. 2015), and more recently, for marine sediments

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(Rios-Del Toro et al. 2018). It may explain the Fe(III)-Anammox correlations found in

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the urban river network in this area previously (Cheng et al. 2016).

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4.2 Environmental implications

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When all three pathways are considered, the partitioning of the fate of N between permanent loss as N2 and internal cycling as NH4+ can be characterized by a N retention index (NIRI), defined as the ratio between DNRA rate and the sum of DEN and Anammox rates (Plummer et al. 2015). NIRI increased with TOC and S2– in the Niantic River Estuary (NRE), USA (Plummer et al. 2015). In our system, NIRI was lowest in the urban river zone and increased seawards in both seasons and generally decreased with sediment TOC, Fe(II), S2–, and bottom water NO3– in a nonlinear way (Figure 7). These results suggest that more NO3– is retained within the system as NH4+ as organic matter

22

Journal Pre-proof and nutrients become more limiting from the river to the sea. The reasons for the contrast between our system and the NRE are twofold. First, DNRA is favored over DEN in organic-rich but NO3–-poor environments (Kelso et al. 1997; Silver et al. 2001), but such conditions did not occur in this study. Second, instead of having high OM but low NO3–, high concentrations of both concurred in the urban river habitat and followed the same pattern downstream. Moreover, NO3– was ample across our continuum and was 1–2

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orders of magnitude higher than that in the NRE (never exceeded 3 μM), but the TOC

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level was generally lower than the NRE (up to 25 compared to up to 100 mg C g-1).

-p

Second, DNRA could be linked to S2– oxidation, in which case, would promote DNRA

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over DEN, as free S2– inhibits the last two steps of DEN (Burgin and Hamilton 2007). However, DEN would not be inhibited if metal-bound sulfide, like FeS, is abundant, as

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often occurs in river sediments (Brunet and Garcia-Gil 1996; Holmer and Storkholm

na

2001). In agreement with this possibility, we did not find negative relationships between S2– and DEN or positive relationships between S2– and DNRA (Figure 5). Collectively,

ur

evidence shows that the downstream diminishing riverine and human impacts in our

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system play a predominant role, where NO3– reduction and the substrates generally follow the same spatial pattern, and the presence of FeS might also be important. As a result, high-OM-low-NO3– conditions and inhibitory effects of S2– are generally absent in our continuum, and the NIRI was regulated differently compared with the NRE. Along the continuum, the urban river sediments supported 4 times faster NO3– reduction rates than the downstream estuary and adjacent sea, with a higher proportion of NO3– removed as N2 (Figure 8). Downstream, however, a higher proportion of NO3– is retained as NH4+, which is more available to phytoplankton and could potentially fuel

23

Journal Pre-proof harmful algal blooms. Although the urban river has the fastest NO3– reduction rates, the estuary and the adjacent sea are 40 and 60 times the size of the urban river, respectively. Therefore, those two habitats will still be the major sites of NO3– reduction in the continuum, despite the lower rates. Nevertheless, fast cycling in the urban river sediments can have large impacts on the local environment of Shanghai, which is of major economic and ecological importance. The urban river network is, therefore, a NO3–

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reduction hotspot and should be a focus of future research and management.

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4.3 Considerations on NO3– reduction measurements

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This study emphasizes the importance of a continuum view in contrast to a segmented view in the transport and transformation of N loading from land to ocean and

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highlights the value of direct comparisons of N cycling measurements among different

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ecosystems. While N cycling has been studied intensively for lakes, estuaries, and marine systems, direct comparisons of N cycling rates have always been challenging, in part

15

N tracer-slurry incubation is a feasible and uniform way to measure

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demonstrated that

ur

because of absent or inconsistent N process measurements (Bruesewitz et al. 2017). We

potential N transformation rates, which facilitates direct cross-ecosystem comparisons. Slurry incubations are simple and more convenient relative to intact-core methods. This consideration is important for shallow sandy riverbeds, where intact cores are difficult to obtain. Slurry incubations are also more feasible when sample and replication numbers are large, as desirable for cross-system comparisons. However, this method has some major limitations: First, adding site water will dilute the porewater in the sediment, and the subsequent mixing of the slurry destroys any vertical gradients in chemicals in

24

Journal Pre-proof sediment samples and alters the processes. Second, in some cases, the loss of gas due to sampling and the resulting exchange with the headspace will disrupt the equilibrium between these two phases (Hansen et al. 2000). And lastly, the pre-incubation and the addition of substrates in the method result in a departure from the in-situ status of the microorganism communities and the measured numbers only reflect the “potential” for N cycling pathways. In a recent comparison between slurry incubation and intact-core

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experiment, Trimmer et al. (2006) found Anammox rates might be underestimated. This

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represents a major drawback compared to intact-core methods, as the “potential” rates

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generally cannot be extrapolated to obtain areal fluxes for a system.

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The potential NO3– reduction rates measured in this study fall within the range of values reported for a number of river and coastal marine systems around the world (Table

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S2). Compared with other measurements also using slurry experiments, our potential

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rates for the estuarine habitat agree well with a previous study on the Yangtze Estuary (Deng et al. 2015). Our DEN rates were slightly lower and Anammox rates higher than

ur

those in the Pearl River Estuary, another major riverine estuary heavily polluted with N

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in China (Wang et al. 2012). Our urban river had lower DEN but higher Anammox rates compared to Koisegawa River, Japan, which is also under heavy human impacts (Zhou et al. 2014). Our results of the potential NO3– reduction rates were also complemented by functional gene abundance data, which showed good agreement with the potential rates (Figures 3 & 4; Table S3). The functional gene data provide a new perspective to characterize the distributions of N cycling in the environment and confirmed the metabolism pathways that we quantified via isotope addition experiments. However, its

25

Journal Pre-proof link to actual reaction rates is affected by a number of factors, including regulatory factors, nutrient availability, and even time of the day (Capone et al. 2008). For example, the magnitude of gene expression can changed dramatically over a daily course (Chen et al. 1997). This will further add complexity to the relationship between gene expression and reactions rates. For future research on this area, we recommend using intact-core incubations to

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quantify N cycling rates more accurately and increasing the number of sampling sites to

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better characterize the continuum. We also recommend advanced molecular tools such as

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environment sequencing and compound-specific isotope analysis, which can characterize

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the changes in the communities responsible for N cycling along a continuum and quantify the metabolisms of microorganisms alongside bulk N cycling rates. This will provide a

5 Conclusions

na

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more comprehensive picture of N cycling along a river-sea continuum.

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Denitrification, Anammox, and DNRA are the major NO3– reduction pathways, with

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the former two removing N out of a system permanently as N2 or N2O whereas DNRA retains N in the system. The distributions of these processes have been studied extensively in riverine, estuarine, and marine ecosystems, but few studies have examined them along a continuum that incorporates all three types of ecosystems. Here, we compared NO3– reduction data for such a continuum and found all three pathways decreased from the river network to the adjacent sea, following decreasing gradients of OM and associated inorganic matter. Multivariate analyses show that OM content and nutrients, such as DIN and Fe(II) impact the spatial and seasonal patterns of NO3–

26

Journal Pre-proof reduction. Within the continuum, the estuary and the adjacent sea probably remove more N in absolute terms due to their vast areas, but the river network supported faster N cycling rates, which can greatly impact its local ecosystem. Our study demonstrates the importance of the continuum as a NO3– sink and highlights the role of the urban river network as a NO3– reduction hotspot. Future management and research efforts should focus on these considerations to optimize understanding and solution of problems caused

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by excessive N pollution in river-estuary systems.

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Acknowledgment

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This work was jointly supported by the National Natural Science Foundation of

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China (Nos. 41522604, 41271114 and 41071135), the China Postdoctoral Science Foundation (No. 2019M653151), and the Fundamental Research Funds for the Central

na

Universities (No.19lgpy93 and No.181gzd07). We thank Lv Cheng, Fengyu Deng, Rong

Jo

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Wang, and Juan Gao for helping with sample analysis.

27

Journal Pre-proof

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Figure 1. Sampling locations within the urban river network (Shanghai city), the Yangtze Estuary, and the adjacent sea of the East China Sea area, China.

Figure 2. Spatiotemporal variations of physical and chemical parameters in the bottom water and sediments along the urban river-estuary-sea continuum. Panels a – d show

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Figure 3. Spatiotemporal variations of NO3– reduction rates (a – f) and fractional

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contribution of each reduction pathway to the total NO3– reduction (g – l) in the

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Figure 4. Spatiotemporal variations of nirS, Anammox 16s RNA, and nrfA gene abundance (a – f) and the ratios of Anammox 16s RNA:nirS and nrfA:nirS (g – j) in the

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sediments of the urban river-estuary-sea continuum.

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Figure 5. Bi-plots of principal component analysis (PCA) on NO3– reduction variables

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(rates and percent contributions) and environmental variables. Panel a shows PCA on all data; panel b shows PCA on data excluding the urban river network. Samples are coded in different colors and shapes to distinguish seasons and habitats. The %variations explained by each PC is listed in parentheses. ANA represents Anammox. Variables with # are bottom water variables; variables without # are sediment variables. Figure 6. Coordination tri-plots of the Canonical Correspondence Analysis on NO3– reduction variable and environmental variable matrices for summer (a) and winter (b). All environmental variables are significant (p<0.05 at a 0.05 confidence level) by

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Journal Pre-proof permutation tests. ANA represents Anammox. Variables with # are bottom water variables; variables without # are sediment variables.

Figure 7. Nitrogen retention index (NIRI) decreases nonlinearly with sediment total organic carbon (TOC), S2–, Fe(II), and bottom water NO3–. Triangles represent samples in the urban river, circles represent the estuary, and squares represent the adjacent sea.

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Figure 8. Sediment NO3– reduction rates (μmol kg-1h-1) and percent contributions of each

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Shanghai-East China Sea area. Values are averages of both summer and winter data.

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Table 1. Mean values (±SE) of rates (DEN, Anammox, and DNRA), gene abundance (nirS, Anammox 16S rRNA, and nrfA), and physicochemical parameters in sediments and bottom waters from the urban river, Yangtze Estuary, and adjacent sea habitats.

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Adjacent Sea Summer Winter

12.5±2.29aB 11.41±1.37aB 1.00±0.34aB 48.2±2.60bB 48.0±2.35aA 3.83±0.94bB 3.39±0.96aA

8.81±1.68bA 1.16±0.25bA 1.01±0.09bA 78.0±2.76cA 11.0±2.57cB 11.1±1.45bA 1.34±0.25bA

3.03±0.81bB 0.60±0.12bB 0.41±0.05cB 68.7±4.06aB 17.4±3.40bA 13.9±2.62aA 0.99±0.11bA

7.61±0.79bA 1.69±0.14bA 1.26±0.15bA 71.2±1.80bA 16.6±1.66bB 12.2±1.37bA 1.08±0.22bA

3.15±0.74bB 0.83±0.21bB 0.42±0.05bB 68.8±3.07aA 19.6±2.51bA 11.8±1.85cA 0.81±0.15bA

8.64±0.92aA

9.14±1.38aA

2.69±0.27cA

3.19±0.70bA

3.61±0.57bA

4.14±0.72bA

3.48±0.66aA 0.52±0.13aA 0.24±0.10aA 27.3±0.26aA 0.33±0.06aA 1.85±0.18aA 8.36±3.16aA 148±7.33aA 108±25.4aA 0.32±0.03aA 79.0±12.5aA 11.0±0.84aA 518±90.7aA 18.9±4.07aA 2.31±0.22aA

2.70±0.39aA 0.44±0.15aA 0.12±0.02aB 6.08±0.07bB 0.57±0.12aB 2.43±0.24aB 3.69±1.85aB 341±43.4aB 489±113aB 1.70±0.42aB 139±26.6aB 8.55±0.66aB 216 ±64.1aB 21.2±2.74aA 1.84±0.20aB

2.14±0.25bA 0.28±0.05bA 0.20±0.03 aA 25.5±0.61bA 3.18±2.65bA 5.01±0.26bA 0.62±0.10bA 99.0±11.1bA 1.39±0.22bA 7.92±1.63cA 2.76±0.63cA 3.16±0.42bA 105±30.5bA 7.41±0.80bA 0.60±0.12bA

1.98±0.20aA 0.33±0.07bA 0.22±0.03 bA 5.77±0.05cB 5.20±3.01bA 7.65±0.21bB 1.09±0.14bB 118±9.64bA 5.34±0.82bB 2.78±0.77aB 12.2±2.99bB 2.20±0.24bB 312±183aB 7.26±0.82bA 0.65±0.08bA

2.28±0.53bA 0.39±0.09bA 0.24±0.06 aA 22.4±0.19cA 29.1±0.69cA 4.55±0.26bA 0.12±0.01cA 3.22±0.30cB 1.76±0.25bA 1.89±0.46bA 5.30±0.46bA 2.94±0.33bA 131±20.0bA 7.99±0.44bA 0.84±0.08cA

2.13±0.21aA 0.64±0.16aA 0.37±0.10 cA 7.56±0.46aB 30.4±0.64cA 7.81±0.17bB 0.31±0.06cB 33.0±7.32cA 4.33±1.25bB 1.02±0.06bB 4.61±0.54cA 2.64±0.19bA 256±138aB 6.56±0.43bA 0.65±0.05bB

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28.6±7.06aA 6.45±1.02aA 2.01±0.77aA 70.4±5.60aA 22.2±3.77aB 7.40±2.93aA 4.36±1.88aA

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DEN (μmol kg-1 h-1) Anammox (μmol kg-1 h-1) DNRA (μmol kg-1 h-1） DEN% (%) Anammox% (%) DNRA% (%) nirS (×106 copies g-1) Anammox 16S rRNA (×105copies g-1) nrfA (×105 copies g-1) Aanmmox 16S/nirS nrfA/nirS # T (°C) # Salinity (ppt） # DO (mg L-1） # NO2– (μM) # NO3– (μM) # NH4+ (μM) -1 NO3– (μg N g ) + NH4 (μg N g-1) Fe(II) (mg Fe g-1) S2– (μg S g-1) TOC (mg C g-1) TN (mg N g-1)

Yangtze Estuary Summer Winter

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Urban River Summer Winter

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Significant spatial differences (p<0.05 at a 0.05 confidence level, Tukey‟s multiple

comparison test) among the three habitats for the same season are denoted by different lower-case letters. Within each habitat, significant seasonal differences between summer and winter (p<0.05 at a 0.05 confidence level, student t-test) are denoted by different upper-case letters. # indicates bottom water variables.

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Author Contributions Conceived and designed the experiments: Xianbiao Lin; Performed the experiments: Hengchen Wei, Dengzhou Gao, and Xianbiao Lin; Analyzed the data: Xianbiao Lin, Hengchen Wei, and Yong Liu; Contributed reagents/materials/analysis tools: Hengchen Wei, Dengzhou Gao, Yong Liu, and Xianbiao Lin; Wrote the paper: Hengchen Wei and

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Xianbiao Lin.

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Journal Pre-proof Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

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Journal Pre-proof Highlights Organic and inorganic matter gradients exist along a river-sea continuum

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Potential nitrate reduction rates decreased along the continuum

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Ratios of retained/removed nitrate increased along the continuum

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Potential nitrate reduction rates were linked to organic matter and nutrients

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We directly compared nitrate reduction measurements for a hydrologic continuum

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Figure 1

Figure 2

Figure 3

Figure 4

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Figure 8