Sediment Nitrous Oxide Fluxes Are Dominated by Uptake in a Temperate Estuary

Introduction

At the interface between the land and the sea, coastal marine ecosystems process large amounts of anthropogenic carbon (C) and nutrients (e.g., nitrogen (N) and phosphorus (P); Nixon, 1981; Boynton and Kemp, 1985; Gattuso et al., 1998; Hopkinson and Smith, 2005). Many of the processes that transform these elements occur in estuarine sediments making them biogeochemical “hot spots” (McClain et al., 2003; Groffman et al., 2009). In particular, sediments can be a substantial sink for reactive N through denitrification (Seitzinger, 1988; Christensen, 1994), and thus may play a key role in the flux of nitrous oxide (N₂O), a powerful greenhouse gas and ozone depleting substance (Ravishankara et al., 2009; Portmann et al., 2012; Myhre et al., 2013). Although coastal ecosystems are typically considered net sources of N₂O to the atmosphere (Bange et al., 1996; Seitzinger et al., 2000; Kroeze et al., 2005), the magnitude and environmental controls of these fluxes are not well-constrained (Murray et al., 2015). Additionally, there have been several reports of net uptake from a variety of coastal environments (e.g., Kieskamp et al., 1991; Kreuzwieser et al., 2003; LaMontagne et al., 2003; Rajkumar et al., 2008; Adams et al., 2012).

Whether coastal sediments are a source or sink of N₂O depends on a balance between both autotrophic and heterotrophic microbial processes that either produce and/or consume N₂O during the oxidation or reduction of N through the +1 oxidation state. In estuarine sediments, microbial nitrification, denitrification, and nitrifier-denitrification are likely to be the dominant processes producing N₂O (Figure 1). The role of other N cycling processes, including anaerobic ammonium oxidation (anammox), dissimilatory nitrate reduction to ammonium (DNRA), fungal denitrification, and chemodenitrification is unclear, but to date research suggests that their contribution to overall N₂O production is relatively small in marine environments (e.g., Shoun et al., 1992; Einsle et al., 1999; Cooper et al., 2003; Coby and Picardal, 2005; Kartal et al., 2007; Rakshit et al., 2008). In canonical nitrification and nitrifier-denitrification, N₂O can be released as a reductive by-product during the chemoautotrophic oxidation of ammonium/ammonia [NH_x(${\text{NH}}_4^{+}$/ ${\text{NH}}_3^{+}$)] through hydroxylamine (NH₂OH) to nitrite (${\text{NO}}_2^{-}$; Wrage et al., 2001; Frame and Casciotti, 2010; Santoro et al., 2011). N₂O can also be produced by both canonical denitrification and nitrifier-denitrification as an intermediate compound, during the reduction of oxidized N species to di-nitrogen gas (N2; Wrage et al., 2001; Fernandes et al., 2010). Alternatively, canonical denitrification, nitrifier-denitrification, DNRA, and N-fixation are capable of consuming N₂O (Firestone and Davidson, 1989; Sanford et al., 2012; Farías et al., 2013; Giblin et al., 2013; Figure 1).

FIGURE 1

Figure 1. Conceptual diagram depicting several of the known microbial processes that influence the flux of nitrous oxide at the sediment–water interface in shallow coastal marine ecosystems. The blue shading represents water above the sediments, light gray shading represents the oxic region of the sediment profile and the dark gray shading represents sub-oxic/anoxic sediments. Abbreviations for nitrogen species are as follows: di-nitrogen (N₂), ammonia/ammonium (NH_x), hydroxylamine (NH₂OH), nitrite (${\text{NO}}_2^{-}$), nitrate (${\text{NO}}_3^{-}$), nitric oxide (NO), nitrous oxide (N₂O). Red lines and font indicate an efflux of N₂O out of the sediments into the overlying water and blue lines indicate sediment N₂O uptake. Dashed arrow lines indicate the potential for a N₂O flux, but limited evidence from the current literature. Note that the vertical profile is idealized and certain processes may occur at the same depth when suitable micro-environmental conditions exist. Figure adapted from Baggs (2008).

The amount of N₂O produced or consumed depends on substrate availability and environmental conditions which regulate the relative rate of these processes (Zumft and Kroneck, 2007; Murray et al., 2015). Dissolved inorganic nitrogen (DIN) is one of the most significant factors controlling the flux of N₂O. High concentrations of ${\text{NH}}_4^{+}$ and nitrate (${\text{NO}}_3^{-}$) can increase the production of N₂O by enhancing nitrification and denitrification (Seitzinger and Nixon, 1985; Bange, 2006; Barnes and Upstill-Goddard, 2011; Moseman-Valtierra et al., 2011). Alternatively, low DIN coupled with low oxygen (O₂) concentrations can promote uptake of N₂O by denitrification and DNRA (Chapuis-Lardy et al., 2007; Figure 1). N₂O uptake can also occur under conditions of abundant DIN, when ${\text{NH}}_4^{+}$ dominates the inorganic N pool (Middelburg et al., 1995; Rajkumar et al., 2008; Adams et al., 2012). The quantity and quality of organic matter can greatly influence rates of net denitrification (Fulweiler et al., 2007, 2008; Eyre et al., 2013). And finally, the concentration of hydrogen sulfides can inhibit both nitrification (Joye and Hollibaugh, 1995) and NO and N₂O reduction by denitrifiers (Sørensen et al., 1980). However, the overall impact of organic matter and sulfide concentrations on sediment N₂O fluxes is unknown.

Here we examine sediment N₂O fluxes in a shallow (2 m mean depth), temperate estuary (Waquoit Bay, Massachusetts, USA). Our goals were two-fold. First, we wanted to determine if the estuarine sediments in this system were a source or sink of N₂O. Second, we wanted to investigate the environmental characteristics (e.g., temperature, salinity, oxygen and nutrient concentrations and fluxes) influencing sediment N₂O fluxes. Determining the controls on the benthic flux of N₂O is an essential step in establishing the potential for estuarine sediments to mitigate emission of this powerful greenhouse gas. Furthermore, a better understanding of the role various environmental parameters play in N₂O budgets enables us to make better-constrained models that will improve management decisions on local, regional, and global scales. In Waquoit Bay, we hypothesized that the sediments would be dominated by N₂O uptake because ${\text{NO}}_2^{-}$ and ${\text{NO}}_3^{-}$ concentrations are low, while sediment organic matter is relatively high, and O₂ is consumed quickly in the upper millimeters of the sediment. We also hypothesized that both O₂ and nutrient dynamics would have a substantial impact on the magnitude of N₂O fluxes by influencing the relative balance of nitrogen cycling processes.

Methods

Sediment Coring and Field Measurements

We collected sediment cores and water samples from Waquoit Bay (41° 34′ N, 70° 32′ W) on six occasions at four sampling stations [Childs River Estuary (CRE), Metoxit Point (MP), South Basin (SB), and Sage Lot Pond (SLP); Figure 2] over 2 years (2012 and 2013; Table 1). We selected these sampling stations as they represent the environmental conditions of the Waquoit Bay estuarine system including variability in salinity and temperature profiles, external N loading rates, DIN (${\text{NO}}_2^{-}$, ${\text{NO}}_3^{-}$, ${\text{NH}}_4^{+}$), and dissolved inorganic P (DIP: ${\text{PO}}_4^{3-}$) concentrations, chlorophyll a concentrations, and sediment characteristics (as described by Foster and Fulweiler, 2014). Concentrations of DIN, DIP, and N₂O did not differ significantly between the surface and bottom waters, except on two occasions at the CRE station. On these sampling dates, CRE surface water NO_x (${\text{NO}}_2^{-}$ + ${\text{NO}}_3^{-}$) was significantly higher than the bottom water (p = 0.0003). In general, the water column at all stations is well-mixed, however at CRE freshwater inflow from river and groundwater can at times cause vertical stratification.

FIGURE 2

Figure 2. Sampling locations in Waquoit Bay, Massachusetts, USA. In 2012–2013 during summer and fall months we collected sediment cores and water samples from four stations: CRE (Childs River Estuary), MP (Metoxit Point), SB (South Basin), and SLP (Sage Lot Pond). Map adapted from Foster and Fulweiler (2014).

TABLE 1

Table 1. Environmental conditions at four stations sampled in Waquoit Bay, Massachusetts, USA.

We collected triplicate sediment cores using clear polyvinyl chloride (PVC) core tubes (10 cm diameter and 30 cm height) and a pole corer. The sediment height in the collected cores ranged from 9 to 17 cm. In the field cores were capped and kept in a cooler in order to maintain approximate field temperature until they were brought to an environmental chamber at Boston University. On core collection days, we measured in situ surface and bottom water O₂ concentrations, salinity, and temperature (Hach HQd using LDO101 and CDC401 probes) at each station. Bottom water was collected using a Niskin Water Sampler (General Oceanics, Miami, Florida, USA) and surface water was collected by hand. Duplicate water samples for DIN and DIP were immediately filtered into 30 mL acid washed and deionized water leached polyethylene bottles using a 60 mL acid washed polypropylene syringe and glass fiber filters (Whatman GF/F, 0.70 μm pore size). The vials were stored in a freezer (at approximately −15°C) until analysis. We also collected triplicate water samples for dissolved N₂O gas analysis using 12 mL Labco Limited Exetainer^® vials with gastight septa. Sample vials were filled from the bottom with ~3 times the overflow volume and preserved with 25 μL of saturated zinc chloride solution. These samples were then placed in a cooler on ice and transferred to a refrigerator (4–6°C) at the lab until analysis.

Incubation Set Up and Sampling

Sediment cores were placed in a water bath in an environmental chamber set to the ambient field temperature. The sediment cores were kept in the dark, uncapped, and bubbled gently with ambient air overnight (>12 h) to keep the overlaying water oxygenated without disturbing the surface of the sediment (Fulweiler et al., 2008; Heiss et al., 2012; Fields et al., 2014).

To determine benthic flux rates we conducted two separate static core incubations (Banta et al., 1995). Both incubations were conducted in the dark. During the first incubation we collected samples to determine the DIN/DIP fluxes, and in the second incubation we collected samples to determine the flux of dissolved N₂O gas. We separated these incubations in order to minimize the sample volume taken from the cores at each time point thus decreasing potential dilution impacts. The two incubations were separated by at least 12 h and cores were again bubbled gently with ambient air (Fulweiler et al., 2007; Heiss et al., 2012; Vieillard and Fulweiler, 2012). Before each of the core incubations we carefully siphoned off the water overlaying the sediment and replaced it with filtered (0.2 μm), station-specific bottom water (Giblin et al., 1995; Hopkinson and Smith, 2005; Fulweiler et al., 2008). After each core tube was filled it was then sealed with no air headspace (water volume above cores ranged from 1.1 to 1.8 L) with an acrylic gas-tight lid equipped with inflow and outflow ports (Dornblaser et al., 1989). Magnetic stir bars fixed to the core tops provided gentle mixing of the overlying water (~40 revolutions min⁻¹) with minimal re-suspension of sediments (Dornblaser et al., 1989; Giblin et al., 1995; Hopkinson et al., 2001; Renaud et al., 2008). The incubation temperatures ranged from 6 to 30°C (Table 1). Incubation time was determined by balancing the following criteria: achieving a 62.5 μM (2 mg O₂ L⁻¹) drop in dissolved O₂ (Giblin et al., 1995), five sampling time points at intervals of at least 60 min, and dissolved O₂ concentrations kept above the hypoxic threshold (>62.5 μM; Heiss et al., 2012). Incubation times ranged between 5 and 17 h.

At each time point 60 mL of water was collected from the cores and filtered for DIN and DIP analysis as described above in the field sampling description. Dissolved O₂ concentrations were measured at three time points (initial, middle, and final) using an optical dissolved oxygen sensor (Hach LDO101). At the start of the second incubation we replaced the overlying water with filtered station water and the cores were again sealed with the gas tight lids and the incubation proceeded. We collected duplicate water samples for N₂O at five time points allowing for overflow for each sample vial (Labco Limited Exetainer^®).

Sampling Analysis and Flux Calculations

Dissolved inorganic nitrogen concentrations were determined by high-resolution digital colorimetry on a Seal Auto Analyzer 3 with segmented flow injection using standard techniques (Solorzano, 1969; Johnson and Petty, 1983; Grasshoff et al., 1999). Our laboratory minimum detection limits (MDLs) for the period of this study are 0.082, 0.035, 0.006, and 0.012 μM for ${\text{NH}}_4^{+}$, NO_x(${\text{NO}}_2^{-}$ + ${\text{NO}}_3^{-}$), ${\text{NO}}_2^{-}$, ${\text{PO}}_4^{3-}$ channels, respectively. Concentration values for ${\text{NO}}_2^{-}$ and ${\text{NO}}_3^{-}$ were consistently low and in many cases below the detection limit of the analysis method. As a result NO_x was often less than the measured concentration of ${\text{NO}}_2^{-}$ yielding a negative (i.e., “non-detect”) value for ${\text{NO}}_3^{-}$.

Concentrations of dissolved N₂O gas were measured directly using a headspace equilibration technique similar to published methods (Kling et al., 1991). In brief, we created a headspace in each vial by adding 5 mL of ultra-high purity helium while simultaneously removing 5 mL of water sample. We carried out this procedure used Hamilton^® gastight glass syringes equipped with stopcocks and Luer Lock connection dispensing needles, entering the Labco Exetainer^® vials through the septa. Once the headspace was created, samples were shaken vigorously and left on their sides to equilibrate for a minimum of 1 h. After equilibration, we sampled the headspace and injected it into a Shimadzu 2014 Gas Chromatograph (GC) using a electron capture detector (ECD) with a ⁶³Nickel (Ni) source. The columns contained HayeSep^®and Shimalite^®. Di-nitrogen (UPC grade) was used as the carrier gas and the make-up gas was a P5 mixture (5% methane, argon balance). Detector/column temperatures and gas flows followed specifications from the manufacturer (Shimadzu). Concentrations of headspace N₂O were determined through a linear regression of peak area and standard concentrations custom made by Airgas^® (Radnor Township, Pennsylvania, USA). The amount of N₂O in the headspace was calculated using the Ideal Gas Law and aqueous concentrations of the dissolved gas were calculated according to Henry's Law using a Bunsen coefficient determined by the equation and constants of Weiss and Price (Weiss and Price, 1980).

Flux rates across the sediment–water interface were determined by calculating the linear regression slope of the nutrient or gas concentration over the incubation time (Banta et al., 1995; Giblin et al., 1997; Hopkinson et al., 1999; Heiss et al., 2012) when the coefficient of determination (R²) was ≥0.65 (Prairie, 1996). Positive fluxes represent a net efflux (i.e., production) of the analyte out of the sediments into the water column, and negative fluxes represent a net influx (i.e., uptake) of the analyte into the sediments from the water column (Fulweiler et al., 2008; Heiss et al., 2012). On some occasions the R² ≤ 0.65. When there was no change in the analyte concentration the flux was determined to be net zero, representing either a balance between production and consumption processes in the sediments and/or rates that are below our detection limit. We designated fluxes as “non-detect” when there was a change in the analyte concentrations but the change was not linear (R² < 0.65).

Dissolved inorganic nitrogen fluxes from 2012 were published previously (Foster and Fulweiler, 2014). We compiled these 2012 data with DIN flux data from 2013 in this study to use as supporting data to compare to the 2012–2013 N₂O and DIP flux data.

Data Analysis

All statistical tests were conducted using the JMP software package (version 11.0.0, copyright 2013, SAS Institute Inc., Cary, North Carolina, USA). To determine if flux rates were significantly different from each other we ran analysis of variance (ANOVA) tests with sampling date and station as the main effects (Heiss et al., 2012; Vieillard and Fulweiler, 2012; Brin et al., 2014). We then conducted an all pairs Tukey-Kramer post-hoc tests (Tukey, 1949) to further examine where differences existed in our datasets. Variance in N₂O fluxes across stations and sampling dates were homogenous according to the O'Brien's unequal variance test (p = 0.4366 and 0.0723, station and date, respectively). We determined outliers in dataset distributions as points that exceed 1.5 times the interquartile range beyond the first or third quartiles using Grubb's test for outliers (Grubbs, 1950). We determined outliers in our linear regression models as data points with a Cook's D influence value >1.0 (Cook, 1977). To determine the parameters that best described the variability observed in the N₂O flux rates we applied single variable linear regression models and then developed multiple linear regression (MLR) models. We constructed the MLR models stepwise using minimum Akaike's Information Criterion (AICc; Akaike, 1973) as the stopping rule in the forward direction. To evaluate the appropriateness of using linear models, we plotted the model predictions against the model residuals and verified that the data were randomly distributed across y = 0. For all statistical analyses we interpreted a p ≤ 0.05 as statistically significant.

Results

Nitrous Oxide Fluxes across the Sediment Water Interface

N₂O fluxes ranged from −99 to 78 nmol N₂O m⁻² h⁻¹. However, on one sampling date (6-Aug-2012), we measured uncharacteristically high N₂O fluxes (−1346 to 681 nmol N₂O m⁻² h⁻¹) well outside the range of the other data. All 6 cores with non-zero fluxes from this date were outliers (p < 0.0001). We attribute these high fluxes to the initial N₂O concentrations measured in each of the cores at the start of the incubation. On this date, initial N₂O concentrations were 1–2 orders of magnitude greater than the initial concentrations measured for the other incubations (p < 0.0001; Table 1), and were strongly correlated with N₂O uptake rates (R² = 0.77, p = 0.068, n = 6 cores). In order to more accurately investigate the environmental controls on N₂O fluxes, we did not include the 6-August-2012 N₂O fluxes in our analyses.

On average, Waquoit Bay sediments consumed N₂O (−23 ± 5.2 nmol N₂O m⁻² h⁻¹, mean ± SE, significantly less than zero, p < 0.0001, n = 39 cores). N₂O fluxes did not differ across stations (p = 0.2410; Figure 3). Sediment N₂O uptake (i.e., negative flux) was observed in a majority of the cores with significant N₂O fluxes (28 negative, 2 positive, and 9 zero; Figures 4A,C,E,G, 5A,C).

FIGURE 3

Figure 3. Sediment nitrous oxide (N₂O) fluxes across the sediment–water interface from cores collected across the four Waquoit Bay sampling stations. Stars indicate outliers in the station distribution of N₂O flux rates. Positive fluxes indicate that sediments are a net source of N₂O and negative fluxes indicate sediments are a net N₂O sink. Net zero fluxes indicate a balance between source and sink processes. Abbreviations for sampling stations: Childs River Estuary (CRE), Metoxit Point (MP), South Basin (SB), and Sage Lot Pond (SLP). Stations are listed from a relatively high external N load (CRE) to a relatively low N load (SLP). Overall sediments consumed N₂O (−23 ± 5.2 nmol m⁻² h⁻¹, mean ± SE, significantly less than zero p < 0.0001, n = 39) and did not differ between stations (p = 0.2412, α = 0.05).

FIGURE 4

Figure 4. Relationship between initial geochemical parameter concentrations and sediment nitrous oxide (N₂O) fluxes across the sediment–water interface. The first column of plots (A,C,E,G) compares parameters to “N₂O Flux” which includes positive, zero, and negative rate values, while the second column (plots B,D,F,H) compares parameters to “N₂O Uptake” which is a subset including negative rates only. Please note that only two cores had positive flux values (and seven cores were net zero), so it was not possible to have a subset for “Production.” Geochemical parameters include N₂O (% saturation; A,B), dissolved inorganic nitrogen (DIN; C,D), phosphorus (DIP; E,F), and temperature (G,H). Lines through points show results from the single variable linear regression models. p-values were determined with significance level α = 0.05. For all cores, the initial total DIN concentrations were predominantly ${\text{NH}}_4^{+}$ with very little to no contribution of oxidized nitrogen compounds. In all cores ${\text{NH}}_4^{+}$ accounted for >75% of the total DIN and in all but one core it accounted for >91%.

FIGURE 5

Figure 5. Influence of sediment oxygen (O₂) (A) and phosphate (${\text{PO}}_4^{3-}$) (C) fluxes on the nitrous oxide (N₂O) flux across the sediment–water interface. The relationships considering sediment uptake rates are shown in the adjacent column of plots for O₂ (B) and ${\text{PO}}_4^{3-}$ (D). “Flux” includes all positive, zero, and negative rates, while “uptake” includes negative rates only. Lines through points show results from the single variable linear regression models. p-values were determined with significance level α = 0.05.

Influence of Environmental Conditions and Sediment Dynamics

N₂O Flux

To investigate the relative influence of environmental conditions and sediment dynamics on N₂O fluxes, we compared N₂O fluxes (i.e., net positive, zero, and negative values) to initial water column concentrations of geochemical parameters and sediment nutrient and O₂ fluxes measured concurrently. Geochemical conditions included, salinity, temperature, DIN, DIP, N:P, O₂ (% saturation), N₂O (% saturation), and sediment fluxes included ${\text{NH}}_4^{+}$, ${\text{NO}}_2^{-}$, ${\text{NO}}_3^{-}$, DIP, and O₂. Across the various geochemical parameters we found that the initial concentrations of N₂O (% saturation), DIN, DIP as well as temperature all significantly influenced N₂O fluxes (p < 0.0001, p = 0.0019, 0.0017, 0.0192, for N₂O, DIN, DIP, and temperature, respectively; Table 2). All these parameters were inversely correlated to N₂O fluxes, where higher initial concentrations and temperatures led to more negative N₂O fluxes (Figures 4A,C,E,G). Based on the MLR using all of these initial parameters, N₂O (% saturation) and DIP created the best fit model (MLR: R² = 0.60, p < 0.0001; Table 2). We also found sediment N₂O fluxes were positively related to O₂ and DIP fluxes, although the relative statistical significance was not as strong (p = 0.0696 and 0.0762, O₂ and DIP, respectively; Figures 5A,C and Table 3).

TABLE 2

Table 2. Results from linear regression models comparing initial concentrations and measurements of environmental parameters on nitrous oxide (N₂O) fluxes across the sediment–water interface.

TABLE 3

Table 3. Linear regression model results comparing oxygen and nutrient flux rates on nitrous oxide (N₂O) fluxes across the sediment–water interface.

N₂O Uptake

Overall, sediments in Waquoit Bay consumed N₂O with 72% of the cores showing net N₂O uptake (i.e., negative fluxes; Figure 4). To better understand what environmental conditions influenced N₂O uptake rates we examined how the negative fluxes alone varied with other measured parameters (Table 2). Similar to the N₂O flux results, we found that sediment N₂O uptake was inversely correlated to the initial N₂O (% saturation), DIN, DIP, and temperature [p < 0.0001 for N₂O (% saturation), DIN, DIP, p = 0.0010 for temperature] where higher nutrient concentrations and temperatures resulted in greater N₂O uptake (i.e., greater negative fluxes; Figures 4B,D,F,H). Oxygen(% saturation) was also significantly correlated to N₂O uptake (p = 0.0194), although the relationship was positive with lower O₂ (% saturation) concentrations corresponding to higher N₂O uptake rates (i.e., greater negative fluxes). The influence of DIP on N₂O uptake rates was stronger than DIN based on the slope of the linear regression model (m = −53.1 vs. −4.93 nmol N₂O m⁻² h⁻¹ per μM DIP vs. DIN, respectively; Figures 4D,F). The ratio of initial concentrations of DIN to DIP (n = 25) appeared to influence N₂O uptake rates, although the correlation was not statistically significant for a linear model [N₂O uptake = (1.32 * N:P) − 60.2, R² = 0.14, p = 0.061, n = 25, removing two outliers from the N:P dataset] or an exponential model [N₂O uptake = −(e^{3.98− (0.035 * N:P)}), R² = 0.15, p = 0.061, n = 25]. Nonetheless the highest rates of N₂O uptake (>50 nmol m⁻² h⁻¹) were observed only when the initial N:P ratios were below 16:1 (Figure 6).

FIGURE 6

Figure 6. Nitrous oxide (N₂O) flux across the sediment–water interface compared to the ratio of nitrogen (N) to phosphorus (P). N:P ratios were determined from the initial dissolved inorganic N (DIN) and P (DIP) molar concentrations measured from water above the sediments at the start of the incubation. Orange shading highlights N₂O fluxes from cores with an initial N:P ratio below 16.

From these individual linear regression models we found that N₂O (% saturation), DIN, DIP, and temperature were all significantly correlated to N₂O uptake rates (all p < 0.0001) with DIP being the most influential parameter (based on AICc of best-fit; Table 2). Covariance among three of the predictive parameters DIN, DIP and N₂O (% saturation) caused multicollinearity in our MLR model (N₂O vs. DIP: R² = 0.74, p < 0.0001; DIP vs. DIN: R² = 0.75, p < 0.0001). The best-fit MLR model included temperature and a combined parameter of these three co-varying variables created by multiplication [DIN * DIP * N₂O (% saturation)]. This MLR model strongly predicted N₂O uptake rates (MLR: R² = 0.90, p < 0.0001; Table 2).

We also compared N₂O uptake rates to sediment flux dynamics and found that sediment uptake of O₂ and DIP were positively correlated to uptake of N₂O (p = 0.0002 and p < 0.0001, O₂ and DIP, respectively; Figures 5B,D, Table 3). In particular, DIP uptake had a strong predictive power on N₂O uptake (R² = 0.78). We found no significant relationships between N₂O uptake and any of the DIN fluxes (Table 3). It was difficult to clearly determine the influence of ${\text{NO}}_2^{-}$ and ${\text{NO}}_3^{-}$ uptake however, because of the low sample sizes from numerous non-detect concentration values. Based on the large variation in sample sizes between the flux parameters, we did not compare AICc scores from the single variable linear regression models, and did not construct an MLR. Best-fit evaluations were based on p-values.

Discussion

Influential Parameters on Sediment N₂O Uptake

Sediment N₂O fluxes in Waquoit Bay were dominated by uptake at all the sites and across all sampling dates. These findings are consistent with a previous study conducted in Waquoit Bay two decades ago (LaMontagne et al., 2003). In a recent global review of coastal N₂O flux ranges, Murray et al. (2015) found that 37% of the locations reported negative N₂O flux rates. In fact, substantial uptake rates have been measured in a range of latitudes and coastal systems including, salt marshes (Blackwater estuary, Essex, UK; Adams et al., 2012), mangroves (Brisbane and near Port Douglas, Queensland, Australia; Kreuzwieser et al., 2003), intertidal sediments (Rowley River, Massachusetts, USA; Vieillard and Fulweiler, 2014), and in estuarine open water bodies (Adyar River Estuary, India; Rajkumar et al., 2008).

We found that sediment N₂O uptake rates (i.e., negative fluxes) are significantly influenced by DIN, DIP, N₂O (% saturation), O₂ (% saturation), temperature, and the rate of sediment DIP and O₂ uptake. When we consider all N₂O fluxes together (i.e., positive, zero, and negative values), these factors are also the dominant predictive parameters, although the relationships are weaker. Based on the findings of previous studies and our current understanding of sediment N₂O flux dynamics, some of the relationships found were expected (e.g., temperature, N₂O, and O₂ % saturations, and O₂ uptake), while others were less so (e.g., DIN and DIP concentrations and DIP uptake).

Temperature is often a key factor regulating bacterial activity and we therefore expected it to play a role in regulating N₂O sediment fluxes (Nowicki, 1994; Barnes and Owens, 1999). In Waquoit Bay, higher temperatures were positively correlated to both sediment N₂O fluxes and uptake rates, although it explained only a small portion of the variability. Water column N₂O and O₂ (% saturation) also played an influential role on sediment N₂O uptake rates. Higher concentrations of N₂O where positively correlated to high rates of N₂O uptake, indicating that adding more reactant (i.e., N₂O) facilitates greater consumption rates. In contrast, low O₂ (% saturation) corresponded to high N₂O uptake rates. This is consistent with research from oxygen minimum zones (OMZs) that have found N₂O consumption by denitrification in the oxygen-depleted core of OMZs (Cohen and Gordon, 1978; Yoshida et al., 1984; Yoshinari et al., 1997; Farías et al., 2007; Yamagishi et al., 2007). Low O₂ conditions favor N₂O consuming processes (e.g., denitrification, DNRA, heterotrophic N-fixation; Figure 1), which use anaerobic metabolic pathways and consume organic carbon. Similarly, we found sediment O₂ uptake to be positively correlated to N₂O uptake, signifying the importance of organic matter substrate since the rate of sediment O₂ uptake can be a proxy for the amount of organic matter in the sediments (i.e., high organic matter content promotes high O₂ uptake rates).

In numerous studies, the concentration of N has been shown to be a good predictor of N₂O fluxes from a variety of ecosystems from both terrestrial (Eichner, 1990; Liu and Greaver, 2009; Acton and Baggs, 2011) and marine environments (Seitzinger and Nixon, 1985; Murray et al., 2015). The hypothesis that N loading to coastal systems increases the efflux of N₂O is based on a conceptual model where increasing N loads to coastal areas stimulates primary production and the biological N cycle which leads to greater emission of N₂O during processes such as nitrification and denitrification (Seitzinger et al., 1984, 2000; Firestone and Davidson, 1989). In contrast to this model we found higher sediment N₂O uptake rates under increasing DIN concentrations. This is likely driven by the fact that DIN was dominated by ${\text{NH}}_4^{+}$ while ${\text{NO}}_2^{-}$ and ${\text{NO}}_3^{-}$ concentrations were so low they were undetectable. In addition, we also observed higher sediment N₂O uptake rates under increasing DIP concentrations. Although, we recognize that these correlations do not necessarily signify causality, we hypothesize that microbial processes responsible for N₂O consumption may be stimulated by water column DIN and DIP and thus, sediment N₂O uptake could be limited by inorganic nutrient availability.

This hypothesis is also supported by the uptake of DIP in these sediments and the positive correlation between DIP uptake and N₂O uptake. Sediment DIP uptake is particularly intriguing since marine sediments are typically considered to be a source of DIP. High sulfate concentrations (Sugawara et al., 1957; Caraco et al., 1989), and low bottom water O₂ conditions (Mortimer, 1941, 1942) characteristic of shallow marine systems limit their ability to retain DIP through mineral precipitation and/or adsorption which enhances sediment release of DIP. The seasonal variability of the benthic DIP flux is characterized with a high efflux of DIP during the warmest months of the year (Nixon et al., 1980; Jensen et al., 1995). In contrast to these commonly observed trends, we found that DIP was consumed in the majority of Waquoit Bay sediment cores across all incubation temperatures. Although, DIP fluxes are often explained by abiotic adsorption/mineral formation in coastal marine sediments, uptake of DIP by microorganisms can also substantially limit regenerated DIP release (Gächter et al., 1988). In Waquoit Bay, sediment O₂ uptake had a positive linear relationship to DIP uptake (R² = 0.40, p < 0.0001, plot not shown). One interpretation of this result is that at least part of the DIP uptake may be explained by microbial aerobic metabolism. We might then expect that anaerobic metabolisms may also be influencing DIP uptake if we assume that the stoichiometric requirement for P would be high for any actively growing microorganism (Vadstein and Olsen, 1989; Vadstein, 2000; Arrigo, 2005) reflecting the increased allocation to growth “machinery” such as P-rich ribosomal RNA (Elser et al., 1996; Arrigo, 2005).

Literature from terrestrial studies have shown that P concentrations can play an important role on N₂O emissions by influencing microbial rates of nitrification and denitrification (Minami and Fukushi, 1983; Hall and Matson, 1999). In addition, Vieillard and Fulweiler (2014) found evidence of P limitation on the flux of N₂O from an experimental study conducted in a temperate tidal flat. In Waquoit Bay we found that initial DIP concentrations and DIP uptake were among the most influential factors on sediment N₂O uptake. Initial DIP concentrations had a stronger impact than DIN concentrations on N₂O uptake rates, and we observed the highest N₂O uptake rates when the initial N:P ratio was below 16:1 (Figure 6). Taken together, these results indicate that P may play an important role in the regulation of N₂O fluxes in these and perhaps other estuarine sediments.

An Ecosystem Service: Sediment Net N₂O Uptake

Low oxidized N concentrations (i.e., ${\text{NO}}_3^{-}$ and ${\text{NO}}_2^{-}$) are a key environmental characteristic of both terrestrial (Chapuis-Lardy et al., 2007) and aquatic (Murray et al., 2015) ecosystems exhibiting N₂O consumption. These conditions are likely to occur in many shallow, macrophyte-dominated ecosystems, like the one we studied here. Despite high nutrient loading, Waquoit Bay bottom waters have relatively low DIN concentrations due to efficient nutrient uptake by macroalgae (Peckol et al., 1994). In this study, the DIN pool measured in the cores was dominated by ${\text{NH}}_4^{+}$ and concentrations of ${\text{NO}}_3^{-}$ and ${\text{NO}}_2^{-}$ were consistently low or below the detection limit (Table 1) as were the sediment fluxes of both species. Under these conditions, the source of ${\text{NO}}_3^{-}$ for denitrifiers comes primarily from nitrification, in coupled nitrification-denitrification (Jenkins and Kemp, 1984). In Waquoit Bay the bottom waters are frequently under-saturated with respect to O₂ (D'Avanzo and Kremer, 1994) and it is likely that nitrification rates at the sediment–water interface are low, thus there is little available ${\text{NO}}_3^{-}$ for denitrification. Additionally, surface waters in Waquoit Bay were consistently at saturation or super-saturated with respect to N₂O, likely as a result of the septic contaminated groundwater inflow (LaMontagne et al., 2003) and water column nitrification (Barnes and Owens, 1999). Under conditions where N₂O is at or above saturation, and concentrations of ${\text{NO}}_3^{-}$ and O₂ are low, microorganisms with the N₂O reductase enzyme (which transforms N₂O to N₂) can use exogenous N₂O as the sole electron acceptor for respiration (Zumft and Kroneck, 2007), and the balance of the N₂O flux may tip toward net uptake vs. production (Figure 1).

We propose that Waquoit Bay, is similar to many other temperate estuaries where relatively long water residence times, low O₂ conditions, and high macroalgae production create an environment conducive to net N₂O sediment uptake. During these conditions sediments can consume N₂O and provide an important and perhaps underappreciated ecosystem service. Of course, here we have measured the uptake of N₂O by the sediments, not the water–atmosphere flux. A key next step is to determine if this sediment uptake rate is large enough to make the system a net sink of N₂O from the atmosphere. We propose that under certain conditions sediment N₂O uptake could substantially lower water column concentrations so that the percent saturation of N₂O dips below equilibrium with the atmosphere. Under this circumstance there would be a net flux from the atmosphere into the estuary. For example, in Waquoit Bay, summer conditions include warm water, high primary productivity, low ${\text{NO}}_3^{-}$ concentrations, and large diel swings in dissolved O₂ with the potential for persistent (on the order of days) low oxygen concentrations. In addition, winds in Waquoit Bay are predominantly onshore (south-westerly) during the summer, which reduces estuarine circulation and increases residence time (Geyer, 1997). These summertime conditions would stimulate microbial processes consuming N₂O and promote N₂O under-saturation.

Conclusions and Implications

Coastal ecosystems represent an important component of the global N₂O budget, however the estimates from these regions are not well-constrained. This is due, in part, to a limited understanding of the environmental factors influencing N₂O consumption. In this study we found that sediments from a shallow, temperate estuary acted as a net N₂O sink, despite heavy N loads from the surrounding watershed. Such sediment consumption of N₂O likely decreases the net ecosystem efflux to the atmosphere and export to the neighboring ocean. We found that initial water column DIP, DIN, N₂O, temperature and sediment DIP and O₂ uptake were all positively correlated to N₂O uptake from the estuarine sediments. Of all the geochemical conditions and processes measured we found that both the initial concentration and sediment uptake rate of DIP most significantly influence sediment N₂O uptake. This has several potential implications for estuarine biogeochemical cycles of C, P, and N. While N inputs can accelerate C fixation by primary producers, nutrients like P could influence rates of C turnover by heterotrophs. In addition, DIP consumption by benthic heterotrophic processes could have a secondary effect on pelagic primary producers that rely on the regeneration of nutrients from sediments for growth. Furthermore, if N₂O uptake is driven primarily by denitrifiers we hypothesize that DIP may limit overall denitrification, which would decrease the natural filtering process that transforms reactive N (e.g., ${\text{NO}}_3^{-}$) into its largely unreactive form (e.g., N₂). Of course, future field observations and experimental work will need to test this hypothesis, but if true, it would challenge our understanding of what controls N removal in estuarine sediments. Going forward, efforts to improve our understanding of the environmental factors driving N₂O fluxes in coastal ecosystems is of critical importance as it will promote better management decisions, generate more accurate greenhouse gas budgets, and enhance our ability to predict the response to future environmental change.

Author Contributions

Both authors (SF and RF) were involved in all aspects of the research presented, including the study design, field sampling, lab incubations/experiments, sample analytical analyses, data analysis and interpretation, and writing. SF took the lead on these research elements and wrote the first draft of the manuscript. RF contributed substantially by advising on all aspects of the research, providing funding support, assisting with field and lab work, and providing manuscript comments and edits. SF and RF are accountable for all aspects of the work presented.

Funding

Funding and support for this work was provided in part by the Woods Hole Sea Grant (awarded to RWF), the Alfred P. Sloan Foundation Fellowship (awarded to RWF), and the National Defense Science and Engineering Graduate student fellowship administered through the American Society for Engineering Education (awarded to SQF).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank the National Estuarine Research Reserve and specifically C. Weidman, for the site access, boat use, and field assistance during this project. The following Fulweiler Lab members and Boston University Marine Program students assisted us in the field and/or during the lab incubations: E. Heiss, S. Newell, S. Donovan, K. Czapla, M.K. Rogener, S. Buckley, K. Yoshimura, M. Yacano, G. Hillyer, R. Lauto, Z. Bengtsson, A. Banks, R. Schweiker, J. Luthringer, D. Forest, and S. Andrews. We would like to thank K. Czapla and A. Al-Haj for running the nutrient samples and H. Emery and E. Morgan for assisting us with the GC greenhouse gas methods development. H. Emery also helped with statistical analysis. And finally, we would like to thank T. Maguire for creating the Waquoit Bay sampling stations map.

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