Introduction
Anthropogenic nutrient enrichment is impacting aquatic ecosystems globally
(Smith, 2003). In many aquatic environments anthropogenic N loading from
wastewater treatment plants, urea-based fertilizers, animal waste, and
aquaculture is shifting the form of N available to phytoplankton from the
oxidized form of nitrate (NO3-), to the reduced form of ammonium
(NH4+; Glibert et al., 2016). The form of N accessed by
phytoplankton is of concern because it has been linked to changes in
phytoplankton abundance and species composition, and may provide advantages
to less desirable species of phytoplankton, including cyanobacteria that
produce harmful toxins (Sharp et al., 2010; Dugdale et al., 2007; Glibert et
al., 2011; Paerl et al., 2014). Given widespread alteration to the form and
concentration of N in aquatic ecosystems, understanding the availability and
uptake of different N sources at the base of the food web is critical to
establishment of effective nutrient management programs (Paerl et al., 2016).
Natural abundance stable isotope analysis is a powerful tool for tracing
nutrient sources because the isotopic composition of primary producers
reflects the isotopic composition of their source nutrients. Natural
abundance approaches have the advantage of integrating over space and time
and allowing measurement in situ, thus avoiding artifacts introduced in
lab-based studies (Finlay and Kendall, 2007). Natural abundance techniques
can also complement experimental studies that use 15N-labeled
substrates, which typically require short-term measurements in isolated
volumes that may not accurately represent field conditions. It is possible to
capitalize on the distinctive isotopic signatures of anthropogenic N sources,
such as sewage, to trace the transport of N through an ecosystem (McClelland
and Valiela, 1998; Gartner et al., 2002; Schlacher et al., 2005; DeBruyn and
Rassmussen, 2010; Pennino et al., 2016). Additionally, stable isotope
approaches have been used to distinguish between forms of dissolved inorganic
nitrogen (DIN) fueling primary production, which may be particularly
important in settings where anthropogenic activities are altering the
dominant available N form (York et al., 2007; Sugimoto et al., 2014; Lehman
et al., 2014).
Using natural abundance stable isotope techniques to trace the transfer of
different N sources into the base of aquatic food webs requires obtaining a
reliable value for the δ15N of phytoplankton (δ15N-PHY).
However, few field measurements of phytoplankton δ15N have been
published due, in part, to the difficulty of isolating a pure phytoplankton
sample from bulk particulate organic matter (POM), which variously contains a
mixture of live and dead phytoplankton, macrophyte detritus, bacteria,
terrestrial soil and leaves, and/or sediment with varying isotopic
compositions. One approach to solving this challenge is to estimate
δ15N-PHY from δ15N-POM when the carbon-to-nitrogen atomic
ratio (C : N) or the carbon-to-chlorophyll a weight ratio
(C : Chl a) of POM indicate dominance by phytoplankton. Because
terrestrial plant matter, periphyton, and macrophytes have C : N
ratios > 10, POM with a C : N ratio near the Redfield ratio
(6.6 to 8.3) has been used to identify POM primarily composed of
phytoplankton (Redfield, 1958; Thorp et al., 1998; Kendall et al., 2001).
Similarly, a ratio of C : Chl a less than 200 has been used to identify
POM of algal origin, with C : Chl a values above 200 indicating the
presence of significant detrital material (Parsons et al., 1961; Cifuentes et
al., 1989; Liu et al., 2007; Miller et al., 2013).
To determine δ15N-PHY in settings where POM contains a mixture of
organic matter sources, additional approaches have been developed ranging
from physical separation of phytoplankton from bulk POM by density (Hamilton
et al., 2005), to isolation of specific compounds such as chlorophyll (Sachs,
et al., 1999) or amino acids (McClelland and Montoya, 2002) for
δ15N analysis. More recently, Fawcett et al. (2011) demonstrated
the use of flow cytometry to separate phytoplankton from bulk POM for
δ15N analysis. Cell sorting by flow cytometry is an encouraging new
approach for investigations of phytoplankton N source because it
theoretically allows for detailed separation of the bulk POM pool into its
constituent parts (detritus, heterotrophic bacteria, phytoplankton,
prokaryotes, etc.) prior to isotopic analysis. For example, Fawcett et
al. (2011) were able to distinguish differences in prokaryote and eukaryote
phytoplankton access to upwelled NO3- in the Sargasso Sea using this
approach.
Here we report results of a study that tested application of flow cytometry
to isolate phytoplankton from bulk POM prior to isotopic analysis in the
Sacramento River, California, in a portion of the San Francisco Bay
estuary (SFE), where NH4+ concentrations are elevated by wastewater treatment plant (WWTP)
discharges. The goals of this study were to (1) determine the extent to which
δ15N-POM reflects δ15N-PHY in the Sacramento River, and
(2) trace the in situ movement of WWTP-derived NH4+ into
phytoplankton using natural abundance stable isotope techniques. This study
was conducted during two river-scale nutrient manipulation experiments when
WWTP effluent discharges high in NH4+ were halted, revealing changes
in δ15N-POM and δ15N-PHY in the presence and absence of
effluent. To our knowledge, this is the first application of flow cytometry
coupled with natural abundance stable isotope analysis in a highly disturbed
freshwater system.
Map of the study reach on the lower 70 km of the Sacramento River,
California, showing the location where effluent from the Sacramento Regional
Wastewater Treatment Plant (WWTP) enters the river and the locations of
samples collected during the October and June experiments.
The Sacramento–San Joaquin River delta forms the landward portion of the San
Francisco Bay estuary (SFE), and freshwater flow into the delta comes
primarily from the Sacramento River (Fig. 1). A long-term decline in primary
productivity has been documented in the SFE (Jassby et al., 2002) with
resulting declines in zooplankton and pelagic fishes (Sommer et al., 2007). A
myriad of factors including changes in flow regime, loss of habitat,
introductions of exotic bivalve species, and inputs of contaminants and
nutrients are believed to contribute to observed reductions in primary
productivity (Jassby and Cloern, 2000; Kimmerer, 2002; Muller-Solger et al.,
2002; Jassby, 2008). Nutrient concentrations have been increasing in the SFE
over time due to agricultural and urban runoff, and increased WWTP
discharges, but discharge from Sacramento Regional WWTP is the main source of
NH4+ in the upper SFE (Jassby, 2008).
The Sacramento Regional WWTP currently employs secondary treatment that does
not include a nitrification step, and thus the majority of N in the final
effluent is in the form of NH4+, with little to no N in the form of
NO3- or nitrite (NO2-). The concentration of NH4+ in
treated effluent ranges from 1700 to 2400 µM, while NO3-
concentrations are typically below the WWTP's reported detection limit
of < 0.7 µM (O'Donnell, 2014). Upstream of the WWTP, the
concentration of NH4+ is commonly < 0.4 µM, while
concentrations of NH4+ > 5 µM are commonly
measured downstream of the effluent input (Kratzer et al. 2001; Foe et al.,
2010). NH4+ discharge from WWTPs is of particular concern in the SFE
because several studies have indicated that elevated concentrations of
NH4+ may be causing changes in phytoplankton species abundance and
productivity (Dugdale et al., 2007, 2012; Glibert et al., 2011; Parker et
al., 2012b).
Methods
Field sampling
This study focused on the 70 km channelized reach of the Sacramento River
extending from the city of Sacramento downstream to Isleton (Fig. 1), where
the river enters the more hydrodynamically complicated network of open water,
channels, and sloughs called the Cache Slough Complex. The only significant
inflow within the study reach is just below the Freeport Bridge where treated
effluent from the Sacramento Regional WWTP enters the river. River flows are
monitored at two USGS stations located at Freeport Bridge and Walnut Grove
(http://waterdata.usgs.gov/usa/nwis).
Field sampling was conducted as part of a larger experiment designed to
examine changes in phytoplankton abundance and community composition in the
presence and absence of wastewater in the Sacramento River. For details of
the field methods employed see Kraus et al. (2017a). Briefly, field sampling
was conducted using a Lagrangian sampling approach during 24 to 29 October 2013,
and 30 May to 4 June 2014 (hereafter referred to as the “October”
and “June” experiments). During both October and June, sampling was
coordinated with ∼ 20 h WWTP effluent discharge holds, creating a
∼ 15 km stretch of effluent-free river to allow comparison of two
parcels of river water; one containing effluent high in NH4+ (+EFF)
and one without effluent (-EFF). During both experiments, +EFF and -EFF
parcels were tracked using small drifters and a high-speed mapping boat
equipped with a custom-designed flow-through instrument package that
continuously displayed surface–water measurements of specific conductance (a
conservative tracer), to assure that samples were collected from within the
designed parcel of water. On both dates +EFF and -EFF parcels were
tracked and sampled over ∼ 80 h (3.5 days) as they traveled
∼ 70 km downstream (Fig. 1). Water samples were collected from both
parcels each day at approximately 2 to 3 h intervals between 08:00 and
17:00 PST. Discrete water samples were collected from 1 m depth using a 3k
Shurflo pump with clear 1/2 in. tubing using USGS protocols (USGS,
2006). Samples were pumped into 8 L Teflon Jerri cans and then transferred
into a 20 L churn (USGS, 2006) for subsampling. Subsamples were collected for
nutrients, chlorophyll a (Chl a), plankton identification and enumeration,
flow cytometry, and stable isotope analysis.
Dissolved nutrients and chlorophyll a concentrations
Nutrient and Chl a concentration analyses were performed at the San
Francisco State University Romburg Tiburon Center as described in Parker et
al. (2012a). Water samples for nutrient analysis were immediately filtered
through Whatman GF/F filters using a 50 mL syringe into either 20 mL HDPE
scintillation vials or 50 mL centrifuge tubes, placed on dry ice, and then
stored at -20 ∘C until analysis. Concentrations of NO2-
and NO3- plus NO2- were analyzed independently on a Bran and
Luebbe AutoAnalyzer II. Samples for NH4+ determination were collected
separately into 50 mL centrifuge tubes after similar filtration. These
samples were also immediately frozen for later analysis by colorimetry using
a Hewlett Packard diode array spectrophotometer with a 10 cm path cell
length.
Chl a samples were concentrated onto 25 mm, 0.70 µm, Whatman
GF/F filters using a low vacuum (< 250 mm Hg). Filters were stored
dry at 4 ∘C for up to 1 week. Prior to analysis, Chl a was
extracted from the filters in 90 % acetone for 24 h at 4 ∘C.
Analysis was performed fluorometrically with a Turner Designs model 10AU
using 10 % hydrochloric acid to correct for and measure phaeophytin. The
fluorometer was calibrated with commercially available Chl a (Turner
Designs chlorophyll a standard).
Stable isotope analysis of POM, NO3-, and NH4+
Stable isotope analysis of POM, NO3-, and NH4+ were performed
at the US Geological Survey's Menlo Park Stable Isotope Laboratory. Nitrogen
has two stable isotopes, 14N and 15N, and the relative abundance of
14N and 15N is expressed as δ15N
(‰) = [(Rsample/Rstandard)-1] × 1000,
where Rsample is the ratio of 15N to 14N in a sample,
and Rstandard is the ratio of the isotopes in AIR, the recognized
reference material for δ15N values. Replicate samples for isotopic
analysis of POM were filtered through pre-combusted GF/F filters, and the
filters were frozen at -4 ∘C until analysis. Filters were
freeze-dried, ground, and vapor-acidified to remove any carbonate prior to
analysis for δ15N and C : N atomic ratio using a
Carlo Erba NA 1500 elemental analyzer connected to a Micromass Optima mass
spectrometer. Analytical precision for duplicate analyses of the same POM
sample was < 0.5 ‰ for δ15N. Samples for
NO3- isotopes (δ15N-NO3-) were filtered through
0.45 µm nucleopore filters, and the filtrate was kept frozen until
analysis using a minor modification of the Sigman et al. (2001) and Casciotti
et al. (2002) microbial denitrifier method using a modified Gilson
autosampler connected to an IsoPrime mass spectrometer. Analytical precision
for sample replicates was 0.3 ‰ for δ15N-NO3-.
Samples for δ15N analysis of NH4+
(δ15N-NH4+) were prepared using a slightly modified version
of the method of Holmes et al. (1998) and analyzed on a Carlo Erba NA 1500
elemental analyzer connected to a Micromass Optima mass spectrometer (Kendall
et al., 2001). Analysis of δ15N-NH4+ was only possible on
samples with NH4+ concentrations greater than 15 µM.
Precision for this method based on replicate analyses of samples in this
study was < 0.4 ‰.
Flow cytometry and δ15N analysis of sorted
phytoplankton
At a subset of stations, samples were collected (n=27) for flow
cytometric separation of phytoplankton from bulk POM for N-isotopic analysis
using the method described in detail in Fawcett et al. (2011). For each
sample, 1 L of river water was pre-concentrated onto four 47 mm
0.2 µm polycarbonate filters using a gentle vacuum (less than
< 250 mm Hg). Filters were transferred to 15 mL
Falcon tubes containing 10 mL of river water and 500 µL of
10 % paraformaldehyde (PFA) for a final concentration of 0.5 % PFA.
During preliminary investigations of Sacramento River water samples, we
observed substantial loss of intact phytoplankton cells when freezing and
thawing the pre-concentrated samples, and a degradation of Chl a
fluorescence after > 9 days of storage. Because both of these
processes reduce the number of detectable phytoplankton cells in a sample
over time and potentially impact δ15N values of the sorted
populations, all of the samples included in this study were sorted from
unfrozen samples (stored in the dark at 4 ∘C) within 1 week of
collection.
Phytoplankton were sorted with an Influx Cell Sorter in logarithmic mode (BD
Biosciences, San Jose, CA, USA). Prior to sorting, sample concentrates were
pre-filtered using 50 µm mesh size filters to prevent clogging of
the 70 µm diameter flow cytometer nozzle with large particles.
Phytoplankton were detected and sorted into a gate using forward scatter
(proxy for cell size) and chlorophyll fluorescence at 692 nm. Chlorophyll
autofluorescence was excited using a 200 mW, 488 nm sapphire
laser (Coherent, Santa Clara, CA, USA). To ensure a sufficient mass of
nitrogen, approximately 10 million cells were sorted directly into 5 mL
polystyrene Falcon tubes orientated at a low angle to the sort stream.
Regular analysis of sort purity (calculated by analyzing a sorted sample to
determine the proportion of events that fall within the target gate as a
percentage of total event rate) was approximately 95 %. Because the river
water contained abundant detritus and sediment, long sort times were required
to achieve high sample purity. Unfortunately, the need to sort unfrozen
samples within 1 week of collection precluded sorting sufficient cells for N
isotopic analysis of individual populations such as diatoms or cyanobacteria.
Instead, all phytoplankton cells were sorted into a single sample from each
location.
Sorted cells were transferred to 20 mL glass vials and dried down under
vacuum using a centrifugal evaporator. Dried phytoplankton samples were
redissolved in 20 µL ultra-high-purity deionized water and
transferred into tin capsules. Capsules were dried overnight at
60 ∘C and then crushed into small cubes. δ15N analysis of
sorted phytoplankton was conducted using elements of a coupled Carlo Erba
CHNS-O EA1108 elemental analyzer and Thermo Finnigan GasBench II system with
automated cryo-trapping system that is connected to an isotope ratio mass
spectrometer (Thermo Fisher Scientific) at the UC Santa Cruz Stable Isotope
Laboratory facility. The elemental analyzer and GasBench were configured to
run small samples using the methods described in Polissar et al. (2009). In
this configuration, samples as small as 35 nmol N could be analyzed with a
precision of 0.5 ‰. Phytoplankton samples analyzed for this study
(δ15N-PHY) ranged in size between 50 and 100 nmol N. Analysis of
duplicate samples (sorted and analyzed independently) indicated a precision
of 0.8 ‰ for the entire method.
Quantification of phytoplankton N source
A two-end-member stable isotope mixing model approach was used to quantify
changes in the N source used by phytoplankton encountering elevated
NH4+ concentrations downstream of the WWTP. Assuming that
NO3- and NH4+ were the only available N sources, the
percentage of N uptake from NH4+ (%NH4) was calculated
according to Eq. (1), where δ15NNO3,
δ15NNH4, and δ15NPHY are the N isotopic
ratios for NO3-, NH4+, and phytoplankton, and
εNO3 and εNH4 are the
enrichment factors for NO3- and NH4+, respectively (York et
al., 2007).
%NH4=[(δ15NNO3-εNO3)-δ15NPHY][(δ15NNO3-εNO3)-(δ15NNH4-εNH4)]×100
The enrichment factor (ε) is an expression of the magnitude of
fractionation between the substrate (e.g., NH4+ or NO3-) and
product (e.g., phytoplankton). Phytoplankton are able to process 14N
faster than 15N (due to a difference in energy required to break bonds)
and this results in lower δ15N values in phytoplankton cells
compared to their nutrient source as long as the nutrient source is not
completely exhausted. In an open system when N substrates are not used to
exhaustion, ε can be approximated as the instantaneous
difference between δ15Nsubstrate and
δ15Nproduct.
Summary of conditions in the two water parcels sampled in October
2013; one parcel did not receive effluent (-EFF) and one parcel did receive
effluent (+EFF) as it passed the wastewater treatment plant (WWTP). A
travel time of zero represents the time each parcel passed the location where
effluent from the WWTP enters the river.
Parcel
Travel
Chl a
[NO3-]
[NH4+]
δ15N-NO3-
δ15N-NH4+
POM C : N
C : Chl a
δ15 N-POM
δ15 N-PHY
time (h)
(µg L-1)
(µM)
(µM)
(‰)
(‰)
(atomic)
(wt : wt)
(‰)
(‰)
-EFF
-18.9
8.0
2.8
0.6
6.9
24.2
6.3
-EFF
-14.2
5.4
2.7
0.7
6.4
27.9
4.9
-EFF
-12.0
7.1
2.8
0.8
8.8
6.8
22.5
6.0
6.5
-EFF
5.0
4.0
3.2
1.4
9.1
6.8
33.7
6.4
6.2
-EFF
8.2
3.3
3.3
1.2
6.2
36.6
3.0
-EFF
10.3
2.9
3.1
0.8
7.2
56.8
5.3
-EFF
12.9
4.9
3.4
1.9
8.6
7.4
35.3
4.8
6.6
-EFF
29.5
3.5
4.4
4.3
8.1
20.5
4.6
-EFF
32.5
3.5
3.5
1.2
7.4
40.4
5.6
-EFF
34.5
3.0
5.4
7.8
6.6
26.4
2.3
-EFF
36.9
5.4
7.7
7.0
7.7
36.6
2.3
-EFF
53.6
4.3
6.4
2.1
7.6
7.7
21.3
4.6
4.4
-EFF
56.0
4.0
8.7
2.4
7.6
32.5
3.5
-EFF
59.0
6.4
11.1
18.2
7.1
30.3
-0.5
-EFF
61.0
6.1
15.3
24.4
7.7
19.3
0.3
-EFF
77.1
1.8
14.0
5.2
7.9
23.2
-2.5
-EFF
80.2
1.6
9.4
4.9
7.8
72.3
2.9
-EFF
82.5
2.1
9.8
3.0
7.9
28.9
2.2
-EFF
85.5
3.3
9.0
6.1
7.1
7.9
38.6
2.2
2.8
+EFF
-18.7
4.7
3.6
0.4
6.8
20.0
7.8
+EFF
-14.5
7.6
3.6
0.5
7.3
19.7
6.8
+EFF
-12.5
6.3
3.5
0.5
9.3
7.1
21.0
7.4
7.8
+EFF
3.3
4.3
4.0
98.5
6.7
7.9
7.2
57.4
3.2
5.3
+EFF
6.3
2.8
4.4
101.3
6.9
71.2
1.3
+EFF
9.1
7.3
4.7
92.0
6.5
8.3
6.8
27.9
1.2
1.8
+EFF
11.7
4.2
4.9
94.5
6.4
37.5
1.2
+EFF
29.2
2.1
6.7
63.3
5.4
8.8
6.8
65.7
1.2
+EFF
32.0
3.1
7.0
77.0
7.2
53.5
-1.0
+EFF
34.0
2.0
7.5
76.5
4.2
8.3
7.1
70.0
-0.2
-2.0
+EFF
52.3
2.1
13.0
86.3
7.5
48.7
1.7
+EFF
55.9
4.3
13.8
82.7
8.3
26.2
-0.4
+EFF
59.0
2.3
15.6
85.1
2.6
9.4
8.5
49.5
-1.0
-3.5
+EFF
76.7
2.5
28.8
71.2
1.7
9.9
8.0
38.1
0.5
-6.4
+EFF
78.9
1.6
9.4
77.2
9.8
53.4
-0.5
+EFF
82.6
1.1
20.0
78.0
1.8
9.7
8.2
87.4
-0.1
Results
During the October and June experiments, tidally averaged flow in the
Sacramento River was ∼ 200 m3 s-1. Due to tidal influence,
river velocities at the top of the reach ranged from -0.06 to
+0.40 m s-1, while farther downstream river velocities ranged from
-0.11 to +0.46 m s-1, for an average velocity of about
0.18 m s-1. Slack flow and flow reversals occurred around midday
during the October sampling, and in the early morning and late afternoon
during the June sampling. Water temperatures in October were
∼ 16.5 ∘C, whereas the river was warmer in June
(∼ 22 ∘C). Chl a concentration at the top of the study reach
was 8 µg L-1 in October and 20 µg L-1 in
June. During both sampling periods large declines in Chl a concentration
were observed in all parcels as they traveled downstream starting
∼ 16 km above the WWTP, such that by the time the parcels reached the
most downstream sampling points Chl a concentrations were about
2 µg L-1 (Table 1; Kraus et al., 2017a).
Downstream trends in NO3- and NH4+
concentrations
Nitrate concentrations increased downstream during the October and June
campaigns in both +EFF and -EFF parcels; however, the downstream gains in
NO3- were more modest in -EFF parcels (Fig. 2). During both the
October and June sampling campaigns, NH4+ concentrations were low
(< 1.0 µM) upstream of the WWTP. Immediately downstream of
the WWTP NH4+ concentrations increased in the +EFF parcel to
∼ 100 µM in October and ∼ 60 µM in June. The
maximum NH4+ concentration in October was higher than in June due to
a greater percentage of effluent in the river (4.0 % in October compared
to 2.7 % in June; Kraus et al., 2017a). During the 3 days of downriver
travel following effluent addition, riverine NH4+ concentrations
decreased modestly in the +EFF parcels. In contrast, NH4+
concentration remained less than 20 µM downstream of the WWTP in
the -EFF parcels, and a slight increase in concentration was observed
during downstream transit. In June, phytoplankton growth rates may have been
N limited at the most upstream locations, as the concentration of DIN was
close to the half-saturation constant of 7 µM frequently used to
model phytoplankton growth (Travis et al., 2015).
Concentration of NO3- (a) and NH4+ (b) in samples
collected during the October and June Lagrangian experiments from parcels
that either received effluent (+EFF) or did not receive effluent (-EFF) as
they traveled past the WWTP. Samples are plotted by travel time, where zero
represents the time the parcel passed the location where effluent high in
NH4+ enters the river.
Downstream trends in δ15N of NO3- and
NH4+
Table 1 presents δ15N values of NO3- and NH4+ for
all samples collected during the October and June campaigns with
concentrations sufficient for analysis. During the October field campaign,
δ15N-NO3- started at 8.5 ‰ upstream of the WWTP
and decreased downstream in both the +EFF and -EFF parcels. The magnitude
of the decrease was greatest in the parcel containing wastewater effluent;
over 83 h of travel downstream of the WWTP δ15N-NO3-
decreased by 7.5 ‰ in the +EFF parcel, whereas
δ15N-NO3- only decreased by 1.6 ‰ in the -EFF
parcel. In June, upstream values for δ15N-NO3- were lower
than in October (3–5 ‰), and remained relatively stable as both the
+EFF and -EFF parcels traveled downstream (Fig. 5).
Due to low concentrations of NH4+ upstream of the WWTP, it was only
possible to measure δ15N-NH4+ in the +EFF parcels
downstream of the WWTP. In the +EFF parcels δ15N-NH4+
increased from 7.9 to 9.7 ‰ in October and from 8.0 ‰ to
10.7 ‰ in June with downstream travel. We also observed that
δ15N-NH4+ increased while NO3- concentration
increased and δ15N-NO3- values decreased during transit in
parcels containing effluent, which suggests nitrification was occurring. This
observation is consistent with high rates of nitrification reported in the
Sacramento River (Hager and Schemel, 1992; Parker et al., 2012a; O'Donnell
2014; Damashek et al., 2016; Kraus et al., 2017b).
Downstream trends in particulate organic matter and
phytoplankton
δ15N-POM values decreased over the study reach in all parcels,
though downstream trends were not monotonic: in particular, we observed
periods during the night when δ15N-POM
increased > 2 ‰ (Fig. 3). The addition of effluent
caused a larger decrease in δ15N-POM values during transit compared
to the -EFF parcels in October and June. C : N atomic ratios in all POM
samples were near the Redfield ratio, ranging from 6.8 to 8.9, suggesting the
POM was primarily phytoplankton (Tables 1 and 2). C : Chl a
(weight : weight) ratios of POM ranged from 10 to 170 for all samples, with a
median value of 35, which is also consistent with phytoplankton-dominated POM
during October and June (Table 1).
Comparison of Chl a, δ15N-POM, and δ15N-PHY in
parcels sampled in October (a, c) and June (b, d) for
parcels that did receive effluent from the WWTP (+EFF) and parcels that did
not receive effluent (-EFF). Samples are plotted by travel time, where zero
indicates the time the parcel passed the location where effluent high in
NH4+ enters the river. Shaded areas indicate nighttime.
Comparison of δ15N-POM and δ15N-PHY for October
and June experiments for parcels that received effluent (+EFF) and parcels
that did not receive effluent (-EFF). The grey circle indicates the six
+EFF samples collected > 20 h downstream of the WWTP.
Summary of conditions in the two parcels sampled in June 2014; one
parcel did not receive effluent (-EFF) and one parcel did receive effluent
(+EFF) as it passed the wastewater treatment plant (WWTP). A travel time of
zero represents the time each parcel passed the location where effluent from
the WWTP enters the river.
Parcel
Travel
Chl a
[NO3-]
[NH4+]
δ15N-NO3-
δ15N-NH4+
POM C : N
C : Chl a
δ15 N-POM
δ15 N-PHY
time (h)
(µg L-1)
(µM)
(µM)
(‰)
(‰)
(atomic)
(wt : wt)
(‰)
(‰)
-EFF
-26.1
20.7
0.4
0.6
3.8
7.0
10.3
5.7
2.1
-EFF
-23.4
10.5
0.4
0.3
7.1
35.4
6.2
-EFF
-20.6
8.8
0.8
0.8
3.5
7.6
41.5
5.1
4.7
-EFF
-2.4
6.6
1.5
1.7
6.8
19.5
6.1
4.6
-EFF
0.7
1.8
1.4
7.1
5.7
-EFF
3.3
4.7
3.3
1.6
4.3
8.4
33.9
3.9
5.5
-EFF
21.9
3.8
2.3
2.0
4.9
7.4
26.3
4.1
6.0
-EFF
24.8
2.1
1.9
4.3
7.9
4.0
-EFF
27.9
4.3
1.5
1.8
5.1
8.0
68.7
4.0
-EFF
45.8
2.6
3.2
11.0
3.6
7.2
36.8
0.4
3.5
-EFF
49.4
3.0
3.7
4.4
8.9
0.3
3.3
+EFF
-25.1
15.9
1.1
1.0
3.9
7.2
10.5
6.5
7.4
+EFF
-22.7
13.2
0.6
1.0
7.1
14.0
7.6
+EFF
-19.7
11.6
0.5
0.6
7.3
32.8
7.2
6.4
+EFF
-1.5
4.9
1.3
1.4
7.3
34.5
3.9
5.1
+EFF
2.3
7.6
2.3
55.1
8.0
7.3
59.8
1.1
+EFF
4.3
5.3
2.6
58.8
3.4
8.3
7.5
100.1
1.3
+EFF
23.5
4.3
5.3
53.0
3.2
9.0
7.4
34.1
1.5
-4.0
+EFF
26.2
6.3
44.1
8.8
7.9
161.8
1.0
+EFF
28.2
2.9
7.4
48.6
3.6
8.7
8.1
115.8
0.4
-4.8
+EFF
51.0
10.8
43.4
3.1
10.7
8.8
174.6
1.4
-3.7
Similar to δ15N-POM, δ15N-PHY values decreased with
downstream travel in all parcels, but the magnitude of decrease was much
greater in the +EFF parcels despite the fact that effluent contained
NH4+ with a higher δ15N value than NO3- present
upstream of the WWTP (Fig. 3). For many samples, the difference between
δ15N-POM and δ15N-PHY was less than 1 ‰
(Fig. 4). However, δ15N-POM values diverged from δ15N-PHY
after more than 20 h of travel past the WWTP in the +EFF parcels. The largest
difference between δ15N-POM and δ15N-PHY was
∼ 7 ‰ in the October +EFF parcel at the most downstream site
(Figs. 3, 4).
Discussion
Comparison of δ15N of POM and phytoplankton
C : N and C : Chl a ratios suggest that POM in the Sacramento River
collected in October and June was primarily phytoplankton. Previous studies
in the SFE have also reported POM C : N ratios near the Redfield ratio
(Canuel et al., 1995; Cloern et al., 2002), and in a survey of POM across the
SFE, Wienke and Cloern (1987) reported a median C : Chl a ratio of 50
over a range of phytoplankton community composition and productivity. The
median C : Chl a ratio of 35 observed in this study is also in
agreement with previous studies which have used a C : Chl a ratio of 35
as a conservative estimate of the phytoplankton C : Chl a ratio in the SFE
(Cloern et al., 1995; Canuel et al., 1995; Sobczak et al., 2005). Consistent
with the interpretation that POM contained primarily phytoplankton, we found
general agreement between δ15N-POM and δ15N-PHY,
particularly in samples that did not contain effluent. However, we also
observed a divergence between in δ15N-PHY and δ15N-POM
values within 24 h following the addition of effluent containing high
concentrations of NH4+. The slower response to a change in N sources
observed in bulk POM compared to intact phytoplankton isolated by flow
cytometry suggests that the bulk POM pool contained a significant fraction of
dead or inactive phytoplankton not actively taking up nitrogen.
During the October and June experiments, phytoplankton samples were collected
for quantitative enumeration and qualitative evaluation (for details see
Kraus et al., 2017a). Patterns in the phytoplankton assemblages were examined
and potential differences between the +EFF and -EFF parcels were tested
for significance using analysis of similarity (ANOSIM). The results of this
analysis showed no statistical difference between the assemblages present in
+EFF and –EFF parcels in either October or June (Kraus et al., 2017a).
During both experiments it was observed that diatoms accounted for
∼ 90 % of the algal biovolume, and that upstream of the WWTP
colonies appeared more vibrant compared to downstream samples which contained
abundant decrepit cells and partially empty frustules (Kraus et al., 2017a).
A downstream decline in cell health, which mirrored decreasing Chl a
concentration, was observed in both +EFF and -EFF parcels. The
observation of declining cell health in phytoplankton may help explain how
bulk POM could contain primarily phytoplankton cells and yet also display a
different downstream trend in δ15N values when compared to sorted
phytoplankton. Because phytoplankton cells were sorted from bulk POM based on
a ratio of cell size and Chl a fluorescence associated with healthy and
intact cells, an increasing abundance of decrepit cells would not influence
δ15N-PHY, but it could dilute the contribution of live
phytoplankton to the δ15N value of bulk POM.
δ15N-NO3, δ15N-NH4, and
δ15N-PHY in parcels that received effluent from the WWTP (+EFF)
in October (a) and June (b). Samples are plotted by travel time, where zero
indicates the time the parcel passed the location where effluent high in
NH4+ enters the river. The concentration of NH4+ was too low
to allow for isotopic analysis upstream of the WWTP.
It is also possible that the presence of effluent caused an increase in
heterotrophy by bacteria and zooplankton in the +EFF parcels, resulting in
δ15N-POM values greater than δ15N-PHY downstream of the
WWTP. Heterotrophic bacterial abundance was not measured during this study,
but dissolved oxygen concentration was monitored in the both parcels, and in
both October and June experiments dissolved oxygen concentrations were lower
in the parcels containing effluent (Kraus et al., 2017a). During the June
experiment, zooplankton biomass was measured in the -EFF and +EFF
parcels, and a decrease in zooplankton biomass was observed in the +EFF
parcel downstream of the WWTP (Kraus et al., 2017a). Thus, while we cannot
rule out the possibility that zooplankton growth elevated δ15N-POM
downstream of the WWTP in October, it is unlikely that zooplankton caused the
divergence between δ15N-POM and δ15N-PHY in the +EFF
parcel in June. Temporal variability in δ15N-POM also provides some
indirect evidence of bacterial reworking of bulk POM during downstream
transport. On multiple occasions in this study we observed that
δ15N-POM increased overnight in both +EFF and -EFF parcels.
Isotopic fractionation during remineralization by bacteria has been shown to
produce NH4+ ∼ 3 ‰ lower than its organic matter
source (Hoch et al., 1994), thus increasing the δ15N value of the
remaining organic matter. If N remineralization exceeded uptake under low
light conditions, it could explain observed increases in δ15N-POM
at night. Remineralization of labile POM during downstream transport would
also dilute the isotopic signal of NH4+ uptake by phytoplankton,
resulting in δ15N-POM values greater than δ15N-PHY
downstream of the WWTP in the +EFF parcels. This interpretation would also
be consistent with the results of a previous investigation into spatial and
temporal variability of δ15N of POM in the freshwater portion of
the SFE by Cloern et al. (2002). In that study, the authors reported little
overlap between δ15N-POM values and the δ15N values of
potential organic matter sources to POM, suggesting that bacterial processing
had overprinted the isotopic composition of a significant fraction of the
organic matter sources present in bulk POM.
Quantification of phytoplankton N source
To trace the movement of WWTP-derived NH4+ into phytoplankton
downstream of the WWTP, we employed a two-end-member mixing model approach.
The data used for mixing model calculations of phytoplankton N source using
Eq. (1) are shown in Fig. 5. Use of this approach requires knowledge of
enrichment factors for NO3- (εNO3) and
NH4+ (εNH4). Enrichment factors for
phytoplankton N use have been measured in numerous laboratory and field
investigations (Cifuentes et al., 1989; Waser et al., 1998; Altabet et al.,
1999; Needoba et al., 2003; Karsh et al., 2014). While a range of values have
been reported for fractionation during assimilation, in general,
εNO3 tends to be lower (2–7 ‰) than
εNH4 (0–25 ‰). However, enrichment factors
are known to be impacted by light, growth rate, and N concentration, and both
N-limited conditions and high growth rates have been shown to result in lower
enrichment factors (Finlay and Kendall, 2007).
There have been relatively few field investigations of
εNO3 in fresh water settings. In single species
culture studies, values of εNO3
from < 1 ‰ to as high as 20 ‰ have been reported
(Granger et al., 2004). In other coastal and estuarine field investigations
εNO3 values between 2 and 7 ‰ have been
reported (York et al., 2007, and references therein) and in a recent study in
the Danube Delta a value of 2.7 ‰ was reported based on a Rayleigh
distillation model (Möbius and Dähnke, 2015). In this study, we
estimated εNO3 from the difference between
δ15N-NO3- and δ15N-PHY in river water upstream of
the WWTP where NH4+ concentrations are low and NO3- is the
dominant N source. The average offset between δ15N-NO3- and
δ15N-PHY in this portion of the river was 3 ‰ (n=6),
which fits within the range of previously reported values from culture and
field investigations of εNO3 where growth was not
nutrient limited. Field investigations of εNH4 are
even less common than NO3- investigations. Values ranging from 0 to
25 ‰ have been reported from both culture and field studies (Waser
et al., 1999). In this study, the minimum value of
εNH4 that resulted in solutions to Eq. (1) between 0
and 100 was 17 ‰ (using a εNO3 value of
3 ‰). An enrichment factor of 17 ‰ is relatively high
compared to other studies; however, previous investigations of
εNH4 focused on nutrient-limited conditions. Elevated
NH4+ concentrations in this study may help explain the large apparent
enrichment factor.
The percentage of the phytoplankton N pool that was derived from NH4+
(%NH4) versus NO3- calculated using values of
εNH4 ranging from 17 ‰ (the minimum value
required for valid solutions to the model) to 25 ‰ (highest reported
value) illustrates that model solutions become increasingly sensitive to
εNH4 as δ15N-PHY decreases downstream.
Nevertheless, despite the uncertainty in enrichment factors, a gradual
increase in the percentage of N derived from NH4+ is apparent
(Fig. 6). In the October +EFF parcel the
estimated portion of phytoplankton N derived from NH4+ increased to
50 % over 60 h of travel time and may have reached as high as 88 %
after 80 h. Similar patterns were observed between the October and June
samplings. However, mixing model calculations were only completed at three
locations in June because δ15N-PHY was greater than
δ15N-NO3- and δ15N-NH4+ at the top of the
study reach (discussed below).
Modeled percentage of phytoplankton N sourced form NH4+
(%NH4) versus travel time past the wastewater treatment plant in the
October parcel that received effluent (+EFF). Calculations were made using
an enrichment factor for NO3- of 3 ‰, and three different
enrichment factors for NH4+ (17, 20, and 25 ‰). Error
bars indicate propagated error from the ±0.8 ‰ uncertainty
in δ15N-PHY values. See text for details.
Mixing model calculations suggest that downstream of the WWTP, a significant
portion of the phytoplankton N pool was derived from NO3- despite the
presence of high concentrations of NH4+. However, N uptake
experiments conducted using 15N-tracer incubation techniques as part of
this effluent hold study indicate a near immediate switch from NO3-
uptake to NH4+ uptake when NH4+ concentrations were elevated
in this portion of the river (Travis, 2015; Kraus et al., 2017a). The
apparently gradual increase over time in the proportion of δ15N-PHY
derived from NH4+ suggests either that simultaneous uptake of
NO3- and NH4+ occurs in the river under conditions not
captured by the 15N-tracer incubations, or that the N turnover time of
phytoplankton is much longer than the ∼ 80 h travel time covered in
this study.
We can estimate potential N turnover time as the mean concentration of POM-N
(µM) divided by the mean rate of N uptake (µM d-1)
measured downstream of the WWTP during 24 h 15N-tracer experiments.
This estimate assumes that all POM-N comes from phytoplankton and it
represents a minimum turnover time because it is based on potential N uptake
rates measured under high light conditions, in bottles where phytoplankton
are isolated from the impacts of turbulence and mixing which may transport
cells into lower light environments. In the October +EFF parcel, the
concentration of particulate N (mean ± standard deviation) downstream
of the WWTP was 4.0 ± 1.0 µM, while the potential
NH4+ uptake rate was 1.4 ± 0.6 µM d-1
(mean ± standard deviation; Travis, 2015). This implies that it would
take ∼ 66 h to completely turnover phytoplankton N with newly
assimilated NH4+ if phytoplankton switched to 100 % NH4+
uptake. After 60 h of travel time in the presence of elevated NH4+
concentrations, mixing model calculations indicate that only ∼ 50 %
of the phytoplankton N was derived from NH4+, suggesting NH4+
uptake rates in the river are much lower than the potential growth rates
measured in 15N uptake experiments. Given that phytoplankton in the
river likely experienced light limitation, it is reasonable to infer that
lower in situ growth rates resulted in an N turnover time greater than 80 h.
Because δ15N-PHY reflects a time-integrated mixture of N uptake, an
N turnover time > 80 h would mute changes in δ15N-PHY
following an abrupt switch to NH4+ uptake.
While there is a general consensus that phytoplankton preferentially take up
NH4+ when NH4+ concentrations are elevated (for reviews see
Dortch, 1990; Glibert et al., 2016), simultaneous uptake of NO3- and
NH4+ has been documented in several field studies. For example, Berg
et al. (2001) report nearly equal percentages of NO3- and
NH4+ uptake with a small percentage of N uptake as urea for the
spring bloom diatom Thalassiosira baltica. Likewise, Twomey et
al. (2005) report near parity of uptake of N as NO3- and NH4+
for the phytoplankton community in the Neuse River estuary. Both field- and
laboratory-based studies make it clear that different cells respond
differently to the presence of multiple N sources (Dortch, 1990). Diatoms,
for example, can reach maximum growth rates when using both NO3- and
NH4+, whereas cyanobacteria appear to be NH4+ specialists
(Senn and Novick, 2014, and references therein). During this study, diatoms
were the most abundant type of algae, which would be consistent with
simultaneous use of NO3- and NH4+. However, 15N-tracer
uptake measurements made during 24 h bottle incubations in this section of
the Sacramento River have consistently found that 15N-NO3 uptake
rates are near zero when NH4+ concentrations are elevated (Parker et
al., 2012a; Kraus et al., 2017a) meaning that if simultaneous uptake of
NO3- and NH4+ occurred in the river it would appear to
require conditions (such as light limitation) not captured in these
incubations.
Another possible explanation for the observed gradual increase in the
%NH4 making up the phytoplankton N pool in the +EFF parcels is that
δ15N-PHY represents a mixture of phytoplankton actively taking up
NH4+ (as observed in bottle incubations) and phytoplankton subsisting
on an internal supply of NO3- acquired upstream of the WWTP. Previous
investigations have shown that diatoms are capable of accumulating an
internal DIN pool under both N-sufficient and N-deficient conditions and that
DIN accumulation is impacted by prior conditioning of the cells (Dortch,
1982; Collos, 1982; Lomas and Glibert, 2000). During the June transect
δ15N-PHY was greater than δ15N-NO3 at the top of the
study reach and remained greater than both δ15N-NO3- and
δ15N-NH4+ for > 40 h of downstream transport.
Because δ15N-PHY should be equal to or lower than the
δ15N value of its source N, it appears that during the June
experiment phytoplankton N was acquired above the study reach. A similar
observation was made in the Childs River of Massachusetts, where
phytoplankton maintained a stable δ15N value over several days of
downstream transport while both δ15N-NO3- and
δ15N-NH4+ decreased, leading York et al. (2007) to infer that
phytoplankton growth was sustained by internal N stores. If a portion of the
phytoplankton community acquired N upstream of the study reach and then was
advected downstream without taking up additional N, this could account for the
20 % apparent contribution of NO3- to δ15N-PHY after
80 h of transport.
Conclusions
Monitoring the spatial influence and biological uptake of anthropogenic
nutrient loading in aquatic ecosystems is a pressing resource management
challenge. Natural abundance stable isotope approaches have the potential to
help regional monitoring programs with this challenge if applied in
well-characterized systems. In this study, we took advantage of a river-scale
nutrient manipulation experiment to test the use of flow cytometry to isolate
phytoplankton from bulk POM prior to isotopic analysis. Comparison of
δ15N-POM and δ15N-PHY revealed that POM and phytoplankton
share similar downstream trends in the Sacramento River, suggesting that POM
(which is relatively easy to collect and analyze) may be a useful proxy for
phytoplankton under certain conditions. However, where phytoplankton growth
rates are low, or N sources change abruptly, δ15N-POM may not
reflect localized changes in δ15N-PHY, which could lead to
inaccurate interpretation of the relative importance of different N sources
if not carefully considered.
Isolating phytoplankton allowed for the use of a mixing model approach to
trace the movement of WWTP NH4+ into the phytoplankton N pool. We
found that even in the presence of high concentrations of NH4+, where
15N uptake experiments suggest preferential uptake of NH4+ and
little to no NO3- uptake, a large portion of phytoplankton N
(10–60 %) was derived from NO3- following several days of
downstream transport (Fig. 6). Differences observed between the natural
abundance and 15N-labeled approaches highlight the strengths and
weaknesses of both methods. The strength of the natural abundance approach is
that it allows in situ observation, thus avoiding the potential artifacts
associated with altered conditions such as increased light availability and a
lack of turbulence and grazing that may impact phytoplankton populations in
bottle incubations. A significant drawback of the natural abundance approach
is that it integrates all N use up to the point of sampling, thus potentially
complicating interpretation of short-term (∼ 24 h) changes in N
sources. When the results of both approaches are considered together, it
appears that in situ growth rates were much lower in the river than observed
in bottle incubations, leading to a slow turnover of phytoplankton N and a
gradual change in δ15N-PHY.
Results of this study indicate that flow cytometry coupled with natural
abundance stable isotope techniques can provide valuable insight into how
different nutrient sources enter the food web. Obtaining pure phytoplankton
samples in the presence and absence of effluent allowed us to determine that
the presence of WWTP effluent containing NH4+ with a distinctly high
δ15N value resulted in a decrease in δ15N-PHY values due
to large enrichment factors in this nutrient replete setting. One implication
of this finding is that planned upgrades to the Sacramento River WWTP
(including nitrification and denitrification), which will reduce NH4+
inputs to the SFE by 2021, may actually result in an increase in
δ15N-PHY. This increase may subsequently be transferred up the food
chain. Results from this study provide an important baseline for future
stable isotope investigations of nutrient flow in the SFE following WWTP
upgrades.
While flow cytometry allowed for determination of δ15N-PHY separate
from bulk POM, we did encounter challenges in applying this approach in a
riverine setting which warrant further exploration and method development.
Unfortunately, due to abundant sediment as well as fragile phytoplankton
cells, we were not able to complete isotopic analysis of distinct
phytoplankton populations within bulk POM. The limitation was not sample
size, but rather the time required to sort sufficient material before the
sample degraded. Future investigations could avoid this issue by combining
sorted samples collected over several days or weeks. This approach would
reduce temporal resolution, but this reduction may actually be appropriate
given that low phytoplankton growth rates observed in this study complicated
interpretation of changes in δ15N-PHY over shorter timescales.
Additional research is needed to establish sampling strategies that allow for
sorting of different populations of phytoplankton (such as diatoms) or
bacteria from bulk POM. For example, isotopic data collected in this study,
particularly downstream trends in δ15N-NH4+ and
δ15N-NO3- as well as the daily temporal variations in
δ15N-POM, suggest that additional N cycling processes such as
nitrification and remineralization influence N source availability for
phytoplankton. If future studies focused on sorting unique populations of
bacteria and phytoplankton, it would be possible to isotopically trace the
pathways by which N becomes available to phytoplankton. This could greatly
improve our understanding of natural and anthropogenic cycling of N in
aquatic systems.