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Biogeosciences An interactive open-access journal of the European Geosciences Union
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BG | Volume 15, issue 13
Biogeosciences, 15, 3953–3965, 2018
https://doi.org/10.5194/bg-15-3953-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Biogeosciences, 15, 3953–3965, 2018
https://doi.org/10.5194/bg-15-3953-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 02 Jul 2018

Research article | 02 Jul 2018

Stable isotopes of nitrate reveal different nitrogen processing mechanisms in streams across a land use gradient during wet and dry periods

Stable isotopes of nitrate reveal different nitrogen processing mechanisms in streams across a land use gradient during wet and dry periods
Wei Wen Wong1, Jesse Pottage1, Fiona Y. Warry1, Paul Reich1,2, Keryn L. Roberts1, Michael R. Grace1, and Perran L. M. Cook1 Wei Wen Wong et al.
  • 1Water Studies Centre, School of Chemistry, Monash University, Clayton, 3800, Australia
  • 2Arthur Rylah Institute for Environmental Research, Department of Environment, Land Water and Planning, Heidelberg, 3084, Australia

Correspondence: Wei Wen Wong (weiwen.wong@monash.edu)

Abstract
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Understanding the relationship between land use and the dynamics of nitrate (NO3-) is the key to constrain sources of NO3- export in order to aid effective management of waterways. In this study, isotopic compositions of NO3- (δ15NNO3- and δ18ONO3-) were used to elucidate the effects of land use (agriculture in particular) and rainfall on the major sources and sinks of NO3- within the Western Port catchment, Victoria, Australia. This study is one of the very few studies carried out in temperate regions with highly stochastic rainfall patterns, enabling a more comprehensive understanding of the applications of NO3- isotopes in catchment ecosystems with different climatic conditions. Longitudinal samples were collected from five streams with different agriculture land use intensities on five occasions – three during dry periods and two during wet periods. At the catchment scale, we observed significant positive relationships between NO3- concentrations (p < 0.05), δ15NNO3- (p < 0.01) and percentage agriculture (particularly during the wet period), reflecting the dominance of anthropogenic nitrogen inputs within the catchment. Different rainfall conditions appeared to be major controls on the predominance of the sources and transformation processes of NO3- in our study sites. Artificial fertiliser was the dominant source of NO3- during the wet periods. In addition to artificial fertiliser, nitrified organic matter in sediment was also an apparent source of NO3- to the surface water during the dry periods. Denitrification was prevalent during the wet periods, while uptake of NO3- by plants or algae was only observed during the dry periods in two streams. The outcome of this study suggests that effective reduction of NO3- load to the streams can only be achieved by prioritising management strategies based on different rainfall conditions.

1 Introduction
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Anthropogenic sources of NO3- from catchments can pose substantial risk to the quality of freshwater ecosystems (Vitousek et al., 1997; Galloway et al., 2004). Over-enrichment of NO3- in freshwater systems is a major factor in development of algal blooms which often promote bottom water hypoxia and anoxia. Such anoxia intensifies nutrient recycling and can lead to disruption of ecosystem functioning and ultimately loss of biodiversity (Galloway et al., 2004; Carmago and Alonso, 2006). Freshwater streams are often sites for enhanced denitrification (Peterson et al., 2001; Barnes and Raymond, 2010). However, when NO3- loading from the catchment exceeds the removal and retention capacity of the streams, NO3- is transported to downstream receiving waters including estuaries and coastal embayments, which are often nitrogen-limited, further compounding the problem of eutrophication.

Understanding the sources, transport and sinks of NO3- is critical, particularly in planning and setting guidelines for better management of the waterways (Xue et al., 2009). Establishing the link between land use and the biogeochemistry of NO3- provides fundamental information to help develop NO3- reduction and watershed restoration strategies (Kaushal et al., 2011). To date, the most promising tool to investigate the sources and sinks of NO3- are the dual isotopic compositions of NO3- at natural abundance level (expressed as δ15NNO3- and δ18ONO3- in ‰). Preferential utilisation of lighter isotopes (14N and 16O) over heavier isotopes (15N and 18O) leads to distinctive isotopic signatures that differentiate the various NO3- sources/end members (e.g. inorganic and organic fertiliser, animal manure, atmospheric deposition) and the predictable kinetic fractionation effect when NO3- undergoes different biological processes (e.g. nitrogen fixation and denitrification). For instance, numerous previous culture-based experiments revealed that denitrification and phytoplankton assimilation fractionate N and O isotopes equally (1 : 1 pattern), leaving behind NO3- that is enriched in both 15N and 18O (Fry, 2006). Simultaneous measurement of δ15NNO3- and δ18ONO3- also provides complementary information on the cycling of NO3- in the environment. δ18ONO3- is a more effective proxy of internal cycling of NO3- (i.e. assimilation, mineralisation and nitrification) compared to δ15NNO3-. This is because during NO3- assimilation and mineralisation, N atoms are recycled between fixed N pools and the O atoms are removed and replaced by nitrification (Sigman et al., 2009; Buchwald et al., 2012).

In addition to constraining NO3- budget and N cycling in various environmental settings, previous studies have also utilised the dual isotopic signatures of NO3- to study the effects of different land uses on the pool of NO3- in headwater streams (Barnes and Raymond, 2010; Sebilo et al., 2003), creeks (Danielescu and MacQuarrie, 2013) and large rivers (Voss et al., 2006; Battaglin et al., 2001). Barnes and Raymond (2010) for example found that both δ15NNO3- and δ18ONO3- varied significantly between urban, agricultural and forested areas in the Connecticut River watershed, USA. Several other investigators (Mueller et al., 2016; Mayer et al., 2002) showed positive relationships between δ15NNO3- and the percent of agricultural land in their study area, indicating the applicability of δ15NNO3- and δ18ONO3- to distinguish NO3- originating from different land uses. Danielescu and MacQuarrie (2013) and Chang et al. (2002) on the other hand found no correlations between NO3- isotopes and land use intensities in the Trout River catchment and the Mississippi River basin, respectively. These studies attributed the lack of correlation to catchment size (Danielescu and MacQuarrie, 2013) and the homogeneity of land use (Chang et al., 2002).

Despite the extensive application of NO3- isotopes to study the transport of terrestrial NO3- to the tributaries in the catchment, the majority of these studies were carried out in the United States and western Europe where climatic conditions, for example temperature and rainfall patterns, are different compared to that in the Southern Hemisphere. The Southern Hemisphere tends to have more sporadic and variable rainfall patterns compared to the Northern Hemisphere, and Australia is an example of this. The variable rainfall patterns can modulate different efficiencies of denitrification in soils and thus different fractionation effects to the residual NO3- pool (Chien et al., 1977; Billy et al., 2010). However, the lack of NO3- isotope studies in the Southern Hemisphere (Ohte, 2013) impedes a more thorough understanding of NO3- dynamics within catchment ecosystems.

Most previous studies investigating the relationship between land use and NO3- export using δ15NNO3- and δ18ONO3- have either focused on the seasonal or spatial variations in one stream, or used multiple streams with one site per stream (i.e. Mayer et al., 2002; Yevenes et al., 2016). Far fewer studies have incorporated longitudinal sampling of multiple streams over multiple seasons. Nitrate concentrations and concomitant isotopic signatures can change substantially, not only spatially but temporally. Changes in hydrological and physicochemical (notably temperature) conditions of a river can affect the relative contribution of different sources of NO3- and the seasonal predominance of a specific source (Kaushal et al., 2011; Panno et al., 2008). In some studies (e.g. Riha et al., 2014; Kaushal et al., 2011), denitrification and assimilation by plants and algae have been reported to be more prominent during the dry seasons compared to the wet seasons, but in other studies (e.g. Murdiyarso et al., 2010; Enanga et al., 2016) denitrification appeared to be more prevalent during the wet seasons as precipitation induces saturation of soils, resulting in oxygen depletion and thereby low redox potentials that favour denitrification. As such, if spatial and temporal variations of δ15NNO3- and δ18ONO3- are not considered thoroughly in a sampling regime, it can lead to misinterpretation of the origin and fate of NO3-. Proper consideration of the temporal variability of NO3- isotope signatures and transformation are particularly pertinent in catchments with highly stochastic rainfall patterns, such as Australia.

In this study, we examine both spatial and temporal variations of NO3- concentrations and isotopic compositions within and between five streams in five catchments spanning an agricultural land use gradient, enabling us to evaluate (1) the effects of agriculture land use on the sources and transformation processes of NO3- and (2) the effects of rainfall on the predominance of the sources and fate of NO3- in the catchments.

2 Materials and methods
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2.1 Study area

This study was undertaken using five major streams (Bass River, Lang Lang River, Bunyip River, Watsons Creek and Toomuc Creek) draining into Western Port (Fig. 1) which lies approximately 75 km south-east of Melbourne, Australia. Western Port is a nitrogen-limited coastal embayment recognised as a Ramsar site for migratory birds. The catchments in Western Port contain three marine national parks, highlighting its environmental and ecological significance. The catchments cover an area of 3721 km2 with land uses ranging from semi-pristine/state forest to high-density residential and intense agricultural activities. The area experiences a temperate climate with average annual rainfall ranging from 750 mm along the coast to 1200 mm in the northern highlands. Mean monthly rainfall was about 20 and 53 mm in 2014 and 2015, respectively (Australian Bureau of Meteorology 2014 – http://www.bom.gov.au/, last access: 30 Apri 2016).

https://www.biogeosciences.net/15/3953/2018/bg-15-3953-2018-f01

Figure 1Map of Western Port Bay (WPB) in southern Victoria, Australia, and major rivers discharging into WPB. Closed circles represent sampling sites where surface water samples were obtained. Values in parentheses represent the % agriculture area in the catchment.

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The catchment overlies a multi-layered combined aquifer system. The main aquifer consists of Quaternary alluvial and dune deposit (average thickness of < 7 m) as well as Baxter, Sherwood and Yallock formations (average thickness between 20 and 175 m). These aquifers are generally unconfined with radial groundwater flow direction from the basin edge towards Western Port Bay. The hydrogeology of Western Port can be found in Carillo-Rivera (1975).

Five longitudinal surveys were carried out between April 2014 and May 2015, two during wet periods (14 April 2014; 15 May 2015 – the total rainfall for 5 days before sampling was between 45 and 65 mm) and three during dry periods (8 April 2014; 22 May 2014; 21 March 2015 – the total rainfall for 5 to 10 days before sampling was < 5 mm). A total of 21 sampling sites indicated in Fig. 1 were selected across a gradient of catchment land use intensity. The five streams were selected based on the extent and distribution of land use types between and within each stream sub-catchment (see Fig. S1 in the Supplement), thus enabling comparisons within and between the streams.

In this study, catchment-intensive agriculture was used as a predictor of land use intensity in the catchment. These data were obtained from the National Environmental Stream Attributes database v1.1 (Stein et al., 2014), Bureau of Rural Sciences' 2005/06 Land Use of Australia V4 maps (http://www.agriculture.gov.au/abares/aclump, last access: 30 April 2016) and Victorian Resources Online (VRO). In the context of this study, the catchment-intensive agriculture variable is termed “percentage agriculture”. This term represents the percentage of the catchment subject to intensive animal production, intensive plant production (horticulture and irrigated cropping) and grazing of modified pastures. This variable also reflects the integrated diffuse sources of nutrients derived from intense agriculture including animal manure and inorganic fertilisers. The percentage agriculture for the sampling sites ranged between 2 and 96 % with the Bass River (94±2 %) > Lang Lang (79±5 %) > Watsons (76±4 %) > Toomuc (71±16 %) > Bunyip (upper Bunyip: 12±9 %; lower Bunyip: 54±10 %; Fig. 2). For the purpose of this study, Bunyip is divided into two sectors (upper and lower Bunyip) based on the proximity of the sampling sites (Fig. 1) and the percentage of land use. All the sampling sites in the upper Bunyip are situated in areas with > 30 % forestation (see Fig. S1). In general, the percentage agriculture decreases with increased distance from Western Port Bay (WPB) for all the streams except Bass River. There is an increase of about 2 % in percentage agriculture for Bass River with increased distance from WPB. Watsons Creek has the largest percentage of market gardens ( 91 %).

2.2 Sample collection and preservation

Water quality parameters (pH, electrical conductivity, turbidity, dissolved oxygen (DO) concentration and water temperature) were measured using a calibrated Horiba U-10 multimeter. Stream samples were collected for the analyses of dissolved inorganic nutrients (DIN) (ammonium, NH4+; NO3- and nitrite, NO2-), dissolved organic carbon (DOC) and NO3- isotopes (δ15NNO3- and δ18ONO3-). These samples were filtered on site using 0.2 µm Pall Supor® membrane disc filters. Filtered DOC samples were acidified to pH < 2 with concentrated hydrochloric acid. Samples for δ18OH2O were collected directly from the streams without filtering. Sediment samples were collected from the bottom of the rivers and were kept in zip-lock bags. All samples were stored and transported on ice until they were refrigerated (nutrient samples were frozen) in the laboratory. In addition to stream water and sediment, we also collected four samples of artificial/inorganic fertiliser (from the fertiliser distributor in the area) and five of cow manure (from local farmers).

2.3 DIN and DOC concentration measurements

All chemical analyses were performed within 1–2 weeks of sample collection except for isotope analyses (within 2 months). The concentrations of NO3-, NO2-, and NH4+ were determined spectrophotometrically using a Lachat QuikChem 8000 Flow Injection Analyzer (FIA) following standard procedures (APHA 2005). DOC concentrations were determined using a Shimadzu TOC-5000 Total Organic Carbon analyser. Analysis of standard reference materials indicated the accuracy of the spectrophotometric analyses and the TOC analyser was always within 2 % relative error.

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Figure 2The percent agriculture upstream for each of the sampling sites.

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2.4 Isotopic analyses

The samples for δ15NNO3- and δ18ONO3- were analysed using the chemical azide method based on the procedure outlined in McIlvin et al. (2005). In brief, NOx (NO3-+NO2-) was quantitatively converted to NO2- using cadmium reduction and then to N2O using sodium azide. The initial NO2- concentrations were insignificant, typically < 1 % relative to NO3-. Hence, the influence of δ15NNO2- was negligible and the measured δ15NN2O represents the signature of δ15NNO3-. The resultant N2O was then analysed on a Hydra 20–22 continuous flow isotope ratio mass spectrometer (CF-IRMS; Sercon Ltd., UK) interfaced to a cryoprep system (Sercon Ltd., UK). Nitrogen and oxygen isotope ratios are reported in per mil (‰) relative to atmospheric air (AIR) and Vienna Standard Mean Ocean Water (VSMOW), respectively. The external reproducibility of the isotopic analyses lies within ±0.5 ‰ for δ15N and ±0.3 ‰ for δ18O. The international reference materials used were USGS32, USGS 34, USGS 35 and IAEA-NO3-. Lab-internal standards (KNO3- and NaNO2-) with pre-determined isotopic values were also processed the same way as the samples to check on the efficiency of the analytical method. The δ18OH2O values were measured via equilibration with He–CO2 at 32 C for 24 to 48 h in a Finnigan MAT Gas Bench and then analysed using CF-IRMS. The δ18OH2O values were referenced to internal laboratory standards, which were calibrated using VSMOW and Standard Light Antarctic Precipitation. Measurement of two sets of triplicate samples in every run showed a precision of 0.2 ‰ for δ18OH2O. Sediment samples for the analysis of δ15N of total nitrogen were dried at 60 C before being analysed on the 20–22 CF-IRMS coupled to an elemental analyser (Sercon Ltd., UK). The precision of the elemental analysis and δ15N was 0.5 µg and ±0.2 ‰ (n=5), respectively.

2.5 Data analysis

The relationships between percentage agriculture and surface water NO3- concentrations were assessed using linear regression. Percentage agriculture was the predictor variable. NO3- concentration and δ15NNO3- were response variables. Relationships between δ15NNO3- and NO3- concentration as well as δ18ONO3- and δ15NNO3- were assessed using Pearson's correlation. The NO3- isotopes' response variables were assessed at two spatial scales – individual stream and catchment scale. The catchment scale integrates data from all five studied streams. Any graphical patterns or relationships derived from using these scales represent processes that occur somewhere in the catchment either in the streams or prior to entering the streams with data from the individual stream likely to represent more localised processes to that particular stream.

3 Results
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The streams were oxic throughout the course of our study period with % DO saturation between 60 and 110 % (see Fig. S2 in the Supplement). There was no apparent spatial and temporal variation in DO; however, % DO saturation was slightly lower during the dry periods (average of 73 ± 20 %) compared to the wet periods (average of 82 ± 12 %). Temperature was also relatively consistent, with an average of 13 ± 2 C. Ammonium concentration was generally low (< 4 µM) except during the wet periods in Bunyip ( 7 µM), Lang Lang ( 21 µM) and Bass ( 29 µM). DOC concentrations were typically 0.8±0.4 mM. Nitrite concentrations were also low in all the streams, ranging between 0.1 and 0.4 µmol L−1.

The spatial and temporal variations of NO3- concentration, δ15N and δ18O across the sites are shown in Fig. 3. NO3- concentrations ranged between 7 and 790 µM with averages of 21±15, 50±130, 64±43, 71±43 and 190±280µM for Toomuc, Bunyip, Bass, Lang Lang and Watsons, respectively. The lowest NO3- concentration was observed in the lower Bunyip (4 µM), while the highest NO3- concentration was observed in Watsons Creek (790 µM) at the most downstream site. Nitrate concentrations were generally higher during the wet periods compared to the dry periods in all streams (Fig. 3). During the wet periods, NO3- concentrations typically followed an increasing trend heading downstream except for the Bass River which exhibited the opposite NO3- trend with lower concentrations at downstream sites. During the dry periods, only the Bunyip and Bass rivers showed apparent longitudinal patterns in NO3- concentrations, with decreasing concentrations moving downstream in both. Sites with high-percentage agriculture generally also exhibited high NO3- concentrations (Fig. 4), particularly during the wet periods.

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Figure 3Spatial and temporal variations of nitrate concentrations and isotope values. Closed circles represent data obtained during the wet periods. Open circles represent data obtained during the dry periods.

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Overall, δ15N of the riverine NO3- spanned a wide range (+4 to +33 ‰). Approximately 62 % of the obtained δ15NNO3- values fell below +10 ‰. More enriched δ15NNO3- values (> +10 ‰) were typically observed during the dry periods and were coincident with a high-percentage agriculture (Fig. 4). Among all sites, δ15NNO3- values in the Bunyip and Bass were relatively depleted (+4 to +12 ‰ for Bunyip and +10 to 12 ‰ for Bass), with the lower range found at upper Bunyip (+4 to +8 ‰). There was no discernible pattern spatially or temporally in δ18ONO3-, except that higher values were found in Lang Lang and Bass during the wet periods, with +4 to +6 and +5 to +9 ‰, respectively, compared to the dry periods (< +4 ‰). For other sampling sites, δ18ONO3- ranged between +2 and +13 ‰. The isotope compositions of sediment, water, artificial fertiliser and cow manure/organic fertiliser are presented in Table 1. The δ15N-TN of three potential sources – artificial fertiliser, organic fertiliser and soil organic matter – ranged from −0.5 to +0.7, +6 to +13 and +4 to +5 ‰, respectively.

Table 1The isotopic compositions of potential sources of NO3- in the catchment.

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Figure 4Relationship between (a) NO3- concentration, (b) δ15NNO3- and the percentage of agricultural land use. In (b) the solid line represents the relationship between the variables during dry periods; the dotted line represents wet periods.

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4 Discussion
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4.1 Potential sources of NO3-

There are three major potential sources of NO3- in the catchments – artificial fertiliser, cow manure/organic fertiliser and soil organic matter (SOM) – see Table 1 for the δ15N-TN values. The average δ15N-TN value of soils is used to directly represent the soil organic portion as most of the nitrogen in soils is generally bound in organic forms. Nitrogen isotope of the NO3- produced from the potential end members usually retains the signature of the δ15N-TN as a result of tight coupling between mineralisation (production of ammonium from organic matter) and nitrification (oxidation of ammonium to NO3-). The δ18O of NO3- generated by nitrification of these sources (δ18ONO3-final) is, however, decoupled from δ15NNO3-. As shown in Eq. (1), which is adapted from Buchwald et al. (2012), δ18ONO3-final relies on the oxygen isotope of water (δ18OH2O), oxygen isotope of dissolved oxygen (δ18OO2), kinetic isotope fractionation associated with incorporation of oxygen during ammonia oxidation (18εk-O2), kinetic isotope fractionation associated with incorporation of oxygen from water during ammonia oxidation (18εk-H2O,1) and nitrite oxidation (18εk-H2O,2), equilibrium isotope effect associated with oxygen isotope exchange between nitrite and water (18εeq) as well as the fraction of nitrite oxygen atoms exchanged with H2O during ammonia oxidation (xAO) (Casciotti et al., 2010; Buchwald et al., 2012). To date, 18εk-O2 and 18εk-H2O cannot be separated. Previous culture studies have reported the overall 18εk-O2+18εk-H2O,1 to range between 17.9 and 37.6 ‰ (Casciotti et al., 2010), while 18εk-H2O,2 ranged from 12.8 to 18.2 ‰ (Buchwald and Casciotti, 2010). These values together with a 18εeq value of 14 ‰, average δ18OH2O of −5.3 ‰ and δ18OO2 of 23.5 ‰ were used to calculate the maximum and minimum estimates of the δ18O of newly produced NO3- from nitrification. The minimum estimate of δ18ONO3-final was calculated using the lower range of 18εk-O2+18εk-H2O,1 (17.9 ‰) and 18εk-H2O,2 (12.8 ‰), while the maximum estimate was calculated using the upper range of 18εk-O2+18εk-H2O,1 (37.6 ‰) and 18εk-H2O,2 (18.2 ‰). Based on the assumptions that ammonia was fully oxidised to NO3- (as no accumulation of NO2- was observed during our study period) and there was complete exchange of oxygen isotope between nitrite and H2O during ammonia oxidation (xAO=1), which likely characterises most freshwater systems (Casciotti et al., 2007; Snider et al., 2010; Buchwald and Casciotti, 2013); we calculated the δ18O of produced NO3- from nitrification to be between −2.03 and −0.23 ‰.

δ18ONO3-final=23+13xAOδ18OH2O+13δ18OO2-18εk,O2-18εk,H2O,1(1)1-xAO-18εk,H2O,2+2318εeqxAO

The δ15N-TN of cow manure (+6 to +13 ‰) was most variable compared to other end members. This variation reflects the extent of volatilisation, a highly fractionating process. Volatilisation can cause a fractionation effect of up to 25 ‰ in the residual NH4+ (Hübner, 1986). As such, the lower value of +6 ‰ indicates a relatively fresh manure sample and is assumed to represent the initial δ15N of the cow manure before undergoing any extensive fractionation.

Atmospheric deposition did not appear to be an important source of NO3- in this study based on the relatively depleted δ18ONO3- values (ranged from +2 to +8 ‰ during the wet periods, and from +1.5 to +13 ‰ during the dry periods) of the riverine samples. The δ18ONO3- of atmospheric deposition were reported to range from +60 to +95 ‰ in the literature (Kendall, 2007; Elliott et al., 2007; Pardo et al., 2004). Similarly, groundwater was not considered as an important source of NO3- to the streams based on the low NO3- concentrations ( 0.7 to 7.0 µM) reported in previous studies (Water Information System Online; http://data.water.vic.gov.au/monitoring.htm, last access: 29 April 2016).

4.2 General characteristics of NO3- in the streams

Agricultural land use (i.e. market gardens and cattle rearing) appeared to influence NO3- concentrations in our study sites. As shown in Fig. 4a, during the wet periods, high NO3- concentrations (> 40 µM) were particularly observed at sites with more than 70 % agricultural land use. During the dry periods, although NO3- concentrations were generally lower than 36 µM, the outliers were observed at sites with more than 70 % agricultural land use. Similarly, enriched δ15NNO3- in the streams were mainly found at sites with high-percentage agricultural land use (between 75 and 85 %) for both dry and wet periods, suggesting that enriched δ15NNO3- in the stream originated from agricultural activities. In fact, the most enriched δ15NNO3- values (> 30 ‰) were observed at the most downstream site of Watsons Creek which has the largest percentage of market gardens (although the total agricultural area is not the highest amongst all the studied sites). We also observed a significant positive relationship between δ15NNO3- and percentage agriculture during the wet periods (r2=0.39, p < 0.01; Fig. 4b). This further supports the contention that agricultural activities were the main control of the δ15NNO3- in the streams. Other researchers (e.g. Mayer et al., 2002; Voss et al., 2006) have also documented similar trends of enriched δ15NNO3- with increasing percentage agriculture. For example, Harrington et al. (1998), Mayer et al. (2002) and Voss et al. (2006) observed highly significant positive relationships between percentage agriculture land area and δ15NNO3- with r2∼0.7. However, these studies showed comparatively narrower and more depleted ranges of δ15NNO3-, with 2.0 to 7.3, 4 to 8 and −0.1 to 8.3 ‰, respectively, suggesting more subtle changes in δ15NNO3- over a large span of agriculture land areas in these studies compared to our study (see Table 2).

Given that none of the predicted sources of NO3- in the Western Port catchment exhibited an initial δ15NNO3- of more than +6 ‰ (see Table 1), the isotopically enriched NO3- as well as the variability of NO3- concentrations observed in this study were consequences of a series of transformation processes. Hence, we propose the following factors to explain the heavy isotopes and the different NO3- concentrations across different periods observed in our study.

  1. During the wet period when surface runoff was conspicuous and residence time of the water column was low, in-stream NO3- was comprised mainly of externally derived NO3- (i.e. fertilisers, manure and soil organic matter) and there was limited in-stream processing of these NO3-. The high NO3- concentrations and the heavy δ15N–NO3- values reflect the occurrence of mineralisation, nitrification and subsequent preferential denitrification of the isotopically lighter NO3- source/s in either the waterlogged soil or in the soil zone underneath the market gardens before transport to the streams through surface runoff.

  2. During the dry periods when surface runoff was negligible and residence time of the water column was high, there was minimal introduction of external NO3- into the streams and in-stream processing of NO3- was more apparent than during the wet periods. In addition to mineralisation and nitrification, volatilisation and assimilation by plant and algae were highly likely to occur in the stream, further reducing the NO3- concentration and further fractionating the isotopic signature of NO3-.

These processes are conceptualised in Fig. 5 and are corroborated in the following discussion using two graphical methods: the Keeling plot and the isotope biplot. In an agricultural watershed, the co-existence of multiple sources and transformation processes can potentially complicate the use of NO3- isotopes as tracers of its origin. Keeling plots (δ15NNO3- vs. 1/[NO3-]) are generally very useful to distinguish between mixing and fractionation (i.e. assimilation and bacterial denitrification) processes (Kendall et al., 1998). The latter typically results in progressively increasing δ15NNO3- values as NO3- concentrations decrease and yields a curved Keeling plot. Meanwhile, mixing of NO3- from two or more sources can result in a concomitant increase in both δ15NNO3- and NO3- concentrations and results in a straight line on the Keeling plot (Kendall et al., 1998). A biplot (δ18ONO3- vs. δ15NNO3-) on the other hand is a proven diagnostic method to elucidate the presence of two isotope fractionating processes: assimilation and denitrification.

https://www.biogeosciences.net/15/3953/2018/bg-15-3953-2018-f05

Figure 5Conceptual diagram illustrating the sources and processes of NO3- during the wet and dry periods in the Western Port catchment. The values of the enrichment factor (ε) were obtained from the literature (Kendall et al., 2007) to indicate the relative contribution of the transformation processes to the isotopic compositions of the residual NO3-.

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4.3 Key controlling processes of nitrate during the wet periods

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Figure 6Relationship between δ15NNO3- and 1/[NO3-] for individual streams during the wet and dry periods.

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In-stream processing of NO3- was not evident during the wet periods based on the lack of relationships between δ18ONO3- and [NO3-] as well as between δ18ONO3- and δ15NNO3- for the individual streams (shown in Supplement Fig. S3). If denitrification was dominant, both δ15NNO3- and δ18ONO3- values are expected to increase in a 1 : 1 pattern at low NO3- concentration – a trend which has been proven by numerous culture-based experiments to indicate the occurrence of denitrification (Granger and Wankel, 2016). In addition, high DO in the water column ruled out the possibility of pelagic denitrification.

Careful examination of the Keeling plots for individual streams (Fig. 6) revealed that during the wet periods, NO3- concentrations were significantly and linearly correlated with 1/[NO3-] in all the streams. These relationships strongly suggest mixing between two sources (with distinctive isotopic signatures) as the dominant process regulating the isotopic composition of the residual NO3- in the streams during the wet periods. The different trends in the Keeling plots (Fig. 6) for individual streams indicate that the isotopic signature of the dominant NO3- source varied temporally and spatially across the catchments. Negative trends on the Keeling plots for Bunyip, Lang Lang and Toomuc (Fig. 6) clearly show that the dominant NO3- source was isotopically enriched (above +10 ‰ for Bunyip and Toomuc and +14 ‰ for Lang Lang), while the positive trends on the Keeling plots for Bass and Watsons show that the dominant NO3- source was more isotopically depleted (less than +8 ‰ for Bass and less than +9 ‰ for Watsons). Nevertheless, the isotopic signatures of the dominant source indicated by the y-intercepts of the Keeling plots were a lot more enriched than the initial δ15NNO3- of all three pre-identified NO3- end members. Interestingly, these δ15NNO3- values increased with percentage agriculture, except for Bass (Fig. 7). The fact that there was a clear fractionation pattern ( 2 : 1) when integrating the isotope values of all the streams (catchment scale) suggests that denitrification was still prevalent during the wet periods (Fig. 8a), but this process was more likely to occur prior to NO3- entering the streams via surface runoff. We explain these observations on the basis that increased rainfall created a “hot moment” in the soil whereby organic matter mineralisation and nitrification were stimulated, followed by denitrification within the waterlogged soil. Waterlogging can result in root anoxia and increased denitrification, leading to significant isotopic enrichment of the residual NO3- (Chien et al., 1977; Billy et al., 2010), which was then washed into the streams. The extent of this process (mineralisation–nitrification–denitrification) was greatest at Bass and Watsons, sites with the highest agricultural activity (Fig. 8a). Based on Fig. 8a, the isotope enrichments of the riverine NO3- followed the denitrification trend of the artificial fertiliser and the NO3- isotopes were distributed in between the denitrification ranges of both artificial fertiliser and SOM, suggesting the important contributions of these two sources during the wet periods.

https://www.biogeosciences.net/15/3953/2018/bg-15-3953-2018-f07

Figure 7Relationship between δ15NNO3- of the dominant initial source (indicated by the y-intercept of the Keeling plots; Fig. 6) and percentage agriculture during wet periods. Data for the Bass-dry period were also presented because only the Keeling plot for the Bass-dry period indicates mixing between different sources. The shaded area represents the δ15NNO3- of the potential end members.

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In fact, the deviation of the δ15NNO3- : δ18ONO3- from the 1 : 1 trend to 2 : 1 corroborates the co-existence of other processes in our system (i.e. nitrification and/or anammox) in addition to denitrification. Based on the multi-process model developed by Granger and Wankel (2016), the negative deflation of the denitrification trend (1 : 1) is strongly driven by concurrent NO3- production catalysed by nitrification and/or anammox (Granger and Wankel, 2016) when the rate of NO3- reduction to NO2- (via denitrification) is higher than the rate of NO2- oxidation to NO3- (via nitrification and/or anammox). A higher reduction rate of NO3- to NO2- tends to create a NO2- pool with enriched δ15N due to isotopic fractionation (0 to 20 ‰) during the reduction of NO2- to N2 (the last step of denitrification). The subsequent oxidation of the δ15N-enriched NO2- leads to the production of NO3- which is isotopically more enriched than denitrified NO3- owing to inverse kinetic fractionation effects (−35 to 0 ‰), driving the negative deviation of δ18ONO3- : δ15NNO3- from the 1 : 1 trend (Granger and Wankel, 2016). During the wet periods, simultaneous occurrence of these three processes (nitrification, annamox and denitrification) was plausible due to the redox dynamics in the waterlogged soil zone. Downward percolation of oxygenated rain water could induce nitrification while denitrification and anammox could be promoted in the anoxic interstitial spaces of the waterlogged soil zone.

4.4 Key controlling processes of nitrate during the dry periods

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Figure 8Biplot of δ15NNO3- vs. δ18ONO3- for (a) wet and (b) dry periods. The blue shaded area represents possible isotopic compositions of denitrified NO3- originated from SOM (δ15N: +4.5 ‰). The grey shaded area represents the possible isotopic composition of denitrified NO3- originated from inorganic fertiliser (δ15NNO3-: +0.1 ‰). The δ18ONO3- used were −2.3 and ±0.23 ‰ representing the minimum and maximum estimates of δ18O of nitrified NO3-, respectively. The shaded areas were plotted based on the theoretical 1 : 1 and 2 : 1 denitrification relationships between δ15NNO3- and δ18ONO3- (Kendall et al., 2007).

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Figure 9Biplot of δ15NNO3- vs. δ18ONO3- for Bunyip and Toomuc (group B data in Fig. 8b). Shaded areas represent theoretical assimilation trends for cow manure, SOM and inorganic fertiliser. The maximum and minimum starting values for δ18ONO3- were estimated from Eq. (1). The starting δ15NNO3- is the δ15N-TN value of respective end member. Solid and dotted lines represent the assimilation trends for Bunyip (both lower and upper Bunyip) and Toomuc, respectively. Assimilation rather than denitrification was considered a more plausible process controlling the distribution pattern for the group B dataset as the water column was oxic throughout the study period.

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Unlike the wet periods, only NO3- in the Bass River showed an apparent relationship with δ15NNO3- (Fig. 6) during the dry periods. There was no obvious relationships between δ15NNO3- and 1/[NO3-] for all other systems during the dry periods limiting the interpretation available from the Keeling plots. This also suggests that mixing between two end members alone is inadequate to explain the variability of δ15NNO3- during the dry periods. In general, during the dry periods, none of the samples show a noticeable pattern of denitrification on a biplot of δ18O vs. δ15N (Fig. 8b). The isotopic composition of the riverine NO3- appeared to be clustered into three groups (A, B and C in Fig. 8b).

NO3- in group A showed consistent δ18O but variable δ15N. This is demonstrated by the Lang Lang and Bass, coincident with the highest percentage of agriculture. The consistent δ18O (δ18O of  2.5 ‰) shows the importance of nitrification (δ18O of −2.03 to −0.23 ‰) and at the same time ruled out the occurrence of denitrification and assimilation. In the absence of the removal processes, the heavy and variable δ15NNO3- values (+6 to +20 ‰) imply that animal manure was an apparent source of NO3- during the dry periods for Lang Lang and Bass. This is because volatilisation of 14N ammonia from the animal manure over time can lead to enrichment of 15N in the residual NH4+ to > +20 ‰ (Bateman and Kelly, 2007) which can subsequently be nitrified to produce isotopically enriched NO3- without affecting its δ18ONO3-. Tight coupling between mineralisation and nitrification results in NO3- retaining the isotopic signature of the residual NH4+ (Deutsch et al., 2009) in the manure. Hence, it is not surprising that δ15NNO3- > +13 ‰ in the group A dataset is indicative of nitrified “aged” animal manure. Because of the huge variability in the fractionation effect of ammonia volatilisation, it is difficult to affix an average δ15N value to represent the isotopic signature of this end member. As such, apportioning the relative contribution of nitrified manure versus other sources (nitrified organic matter in the sediment and inorganic fertiliser) is not possible.

Table 2Comparison of NO3- concentrations and isotopes across different systems reported in the literature.

* Values estimated from presented figures might not accurately represent the actual data.

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NO3- in group B has variable δ15N and δ18O values as shown by Bunyip and Toomuc. This could be attributed to isotopic fractionation during plant and/or algae uptake of NO3- as substantiated by the parallel increase in δ18ONO3- vs. δ15NNO3- (Fig. 9). Denitrification was ruled out due to high levels of dissolved oxygen in the water column. Close convergence of the linear relationships onto the theoretical assimilation trends of the nitrified artificial fertiliser and SOM (Fig. 9) reiterate the dominant contribution of these sources to the riverine NO3- during the dry periods. It is worth noting that the initial δ18O of nitrified NO3- was estimated assuming full O isotopic equilibration between NO2- and H2O. Partial O isotope disequilibrium which was possible could affect the initial δ18O signature of nitrified NO3-. If this happened, the minimum estimate of δ18O of nitrified NO3- could be more depleted and the overall linear relationship of δ18ONO3- : δ15NNO3- would shift, resulting in more obvious contribution of artificial fertiliser, SOM and possibly organic fertiliser (Fig. 9). This scenario emphasises the sensitivity of the initial δ18O of nitrified NO3- in determining the relative contribution of multiple sources in the catchment.

NO3- in group C comprised the most enriched δ15N and δ18O in the entire dataset (Fig. 8). These isotope values were observed in Watsons Creek which has the highest percentage of market gardens. These samples were collected when the creek was not flowing, hence the enriched δ15N and δ18O values could be indications of repeated cycles of internal processes (i.e. volatilisation, nitrification, denitrification and assimilation) in the same pool which enriched the N isotope but had slight effects on the O isotope of NO3-.

Although the isotope values during the dry periods appeared to be more likely controlled by artificial fertiliser and SOM, the contribution from organic fertiliser cannot be excluded. As mentioned in the preceding text, most of the fertiliser-derived NO3- was denitrified in the catchment during the wet periods creating an artefact of heavy NO3- isotopes in the streams. This NO3- could exhibit a similar enriched isotopic composition as the volatilised manure (particularly if there was disequilibrium of O isotope between NO2- and H2O). Overlapping of these isotopic values made it difficult to distinguish between all the three sources – a disadvantage of using NO3- isotopes in a system where multiple sources and transformation processes coexist.

5 Conclusions
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This study highlights the effect of rainfall conditions on the predominance of sources and transformation processes of NO3- on both individual stream and catchment scale. The significant positive relationships between percentage agriculture and NO3- concentrations (r2=0.29; p < 0.05) as well as δ15NNO3- (r2=0.39; p < 0.01) particularly during the wet period showed that enriched NO3- concentrations and δ15NNO3- values resulted from agricultural activities. The dual isotopic compositions of NO3- revealed that both mixing of diffuse sources and biogeochemical attenuation controlled the fate of NO3- in the streams of the Western Port catchments. During the wet periods, inorganic fertiliser appeared to be the primary source of NO3- to the streams while SOM, in addition to inorganic fertiliser was also a dominant source of NO3- during the dry periods. Denitrification in the catchment appeared to be the more active removal process during the wet periods in contrast to a greater importance of in-stream assimilation during the dry periods. However, these removal processes were insufficient to remove the agricultural-derived NO3- inferring that the streams were unreactive conduits of NO3- which might pose a potential NO3- enrichment threat to downstream ecosystems. To the best of our knowledge, this is the first study in Australia and also one of the very few targeted studies in the Southern Hemisphere investigating the origin and sink of NO3- on a catchment scale using both δ15N and δ18O of NO3-. The application of NO3- isotopes in a region with highly variable and unpredictable rainfall patterns such as the Western Port catchments, although challenging, is imperative particularly in setting guidelines for sustainable land use management actions.

Data availability
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Data availability. 

The data related to this article are available online at https://doi.org/10.4225/03/5b2c683663395.

Supplement
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Supplement. 

The supplement related to this article is available online at: https://doi.org/10.5194/bg-15-3953-2018-supplement.

Competing interests
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Competing interests. 

The authors declare that they have no conflict of interest.

Acknowledgements
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Acknowledgements. 

We thank the associate editor and the reviewers for their constructive comments. We also thank Douglas Russell, Dale Christensen and Tina Hines for their help in the lab and in the field. We thank Neil Cranston for his help in providing samples of cow manure. This work was supported by Melbourne Water Corporation and an Australian Research Council Grant (LP130100684) to PLMC.

Edited by: Manmohan Sarin
Reviewed by: three anonymous referees

References
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Over-enrichment of nitrate can pose substantial risk to the quality of freshwater ecosystems. Hence, understanding the dynamics of nitrate is the key to better management of waterways. This study evaluates the relationship between the effects of land use and rainfall on the major sources and processing of nitrate within and between five streams in five catchments spanning an agricultural land use gradient. We found that rainfall exerted significant control over the fate of nitrate.
Over-enrichment of nitrate can pose substantial risk to the quality of freshwater ecosystems....
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