Nitrogen-limited Cyanobacterial Harmful Algal Blooms in Deal Lake, New Jersey
Jason E. Adolf*1, Katie Saldutti2, Erin Conlon1, Eric Ernst3, Bill Heddendorf3, Sheri Shifren3, and Robert Schuster3
1Monmouth University, Biology Department, 400 Cedar Avenue, West Long Branch, NJ 07764. 2Rutgers, Department of Marine and Coastal Science, 71 Dudley Rd., New Brunswick, NJ 08901. 3NJ DEP, Bureau of Marine Water Monitoring, PO BOX 405, Stoney Hill Rd., Leeds Pt., NJ 08220. *Corresponding author.
Urban Naturalist, No. 57 (2022)
Abstract
Harmful algal blooms (HABs) caused by photosynthetic cyanobacteria (cyanoHABs) have shown expanded impacts in recent decades. Small lakes, reservoirs, and ponds common in highly populated regions are particularly susceptible to cyanoHABs because of high rates of nutrient delivery associated with urbanized watersheds. Deal Lake in Monmouth County, the largest coastal lake in New Jersey, has experienced recurrent HABs in recent years. Here, an analysis of cyanoHAB biomass, nutrient concentrations, and nutrient-addition bioassays (2017–2018) was conducted to address the relationship of cyanoHABs to environmental conditions. Stations within Deal Lake showed differences in median water quality parameters, possibly reflecting different watershed inputs. HAB biomass peaked in late summer in both years, with water temperatures between 77 and 86 °F (25 and 30 °C). Dissolved inorganic Nitrogen (N) peaked in late winter – early spring while organic N peaked in summer. Conversely, dissolved inorganic Phosphorus (DIP) was minimal in late-winter – spring, but elevated in summer during cyanoHABs when pH was also elevated. Nutrient addition bioassays indicated P-limitation in a March experiment, but N-limitation in summer when cyanoHABs were present. Deal Lake summertime cyanoHABs are N-limited, a condition that is reinforced by excess DIP likely coming from autochthonous sources during HAB events. Seasonally elevated water temperatures further reinforce the formation of cyanobacterial HABs in Deal Lake.
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Volume 9, 2022 Urban Naturalist No. 57
Nitrogen-limited
Cyanobacterial Harmful
Algal Blooms in Deal
Lake, New Jersey
Jason E. Adolf, Katie Saldutti, Erin Conlon,
Eric Ernst, Bill Heddendorf,
Sheri Shifren, and Robert Schuster
Urban Naturalist
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Cover Photograph: Summertime cyanobacteria discolor Deal Lake waters at the Jersey Shore.
Photograph © Jason Adolf.
1
1Monmouth University, Biology Department, 400 Cedar Avenue, West Long Branch, NJ 07764.
2Rutgers, Department of Marine and Coastal Science, 71 Dudley Rd., New Brunswick, NJ
08901. 3NJ DEP, Bureau of Marine Water Monitoring, PO BOX 405, Stoney Hill Rd., Leeds
Pt., NJ 08220. *Corresponding author: jadolf@monmouth.edu.
Associate Editor: Juan Carlos Villarreal Aguilar, Department of Biology, Laval University.
Nitrogen-limited Cyanobacterial Harmful
Algal Blooms in Deal Lake, New Jersey
Jason E. Adolf *1, Katie Saldutti2, Erin Conlon1, Eric Ernst3, Bill Heddendorf 3,
Sheri Shifren3, and Robert Schuster3
Abstract - Harmful algal blooms (HABs) caused by photosynthetic cyanobacteria (cyanoHABs) have
shown expanded impacts in recent decades. Small lakes, reservoirs, and ponds common in highly populated
regions are particularly susceptible to cyanoHABs because of high rates of nutrient delivery associated
with urbanized watersheds. Deal Lake in Monmouth County, the largest coastal lake in New Jersey,
has experienced recurrent HABs in recent years. Here, an analysis of cyanoHAB biomass, nutrient
concentrations, and nutrient-addition bioassays (2017–2018) was conducted to address the relationship
of cyanoHABs to environmental conditions. Stations within Deal Lake showed differences in median
water quality parameters, possibly reflecting different watershed inputs. HAB biomass peaked in late
summer in both years, with water temperatures between 77 and 86 °F (25 and 30 °C). Dissolved inorganic
Nitrogen (N) peaked in late winter – early spring while organic N peaked in summer. Conversely,
dissolved inorganic Phosphorus (DIP) was minimal in late-winter – spring, but elevated in summer
during cyanoHABs when pH was also elevated. Nutrient addition bioassays indicated P-limitation in a
March experiment, but N-limitation in summer when cyanoHABs were present. Deal Lake summertime
cyanoHABs are N-limited, a condition that is reinforced by excess DIP likely coming from autochthonous
sources during HAB events. Seasonally elevated water temperatures further reinforce the formation
of cyanobacterial HABs in Deal Lake.
Introduction
Harmful algal blooms (HABs) caused by cyanobacteria (cyanoHABs) in freshwater systems
are a growing phenomenon worldwide that impacts ecosystems, economies, and people
(O’Neil et al. 2012). Harmful impacts of cyanoHABs can include ecological disruption
through formation of dense surface accumulations that block sunlight from reaching benthic
communities; potential production of toxins that can affect humans, pets, and domestic animals;
as well as production of taste and odor compounds that impact municipal water supplies
(Paerl and Otten 2013, Watson et al. 2016). The proliferation and expanding impacts of cyanoHABs
around the world have been linked to nutrient over-enrichment, climate change and
changing use of aquatic environments, but the details behind the nutrient-climate-cyanoHAB
connection can differ from place-to-place, and over time within a given system (Chapra et
al. 2017, Griffith and Gobler 2020, Hallegraeff et al. 2021, Paerl 2018, Paerl and Huisman
2008, Paerl and Otten 2013, Paerl and Paul 2012). For instance, highly urbanized watersheds
have complex and sometimes novel patterns of nutrient cycling and delivery to small ponds,
retention basins, and lakes that are often found in these environments (reviewed in Carey et
al. 2013). The combination of heavy rainfall events and highly urbanized watersheds has been
shown to lead to severe water quality issues for lakes (Olds et al. 2018, Salerno et al. 2018,
Wei et al. 2020). CyanoHABs in urban waterbodies are of particular concern because of the
2022 Urban Naturalist 57:1–19
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potential for toxicity coupled to the high surrounding population densities (de la Cruz et al.
2017, Waajen et al. 2014, Lewitus et al. 2003).
Like all phytoplankton, cyanobacteria require both N and P as major nutrients for growth,
and are favored by particular sets of physical conditions (e.g., light, temperature, turbidity; Paerl
and Huisman 2008). However, determining the relative role of N vs. P in driving cyanoHABs is
complex due to factors including different species’ nutritional strategies (Paerl 2018, Paerl and
Otten 2013) as well as seasonal differences in nutrient availability (Chaffin et al. 2018a, Xu et
al. 2010). For example, cyanobacteria with the ability to fix atmospheric N2 may have an advantage
in N-limited water bodies due to their ability to access the pool of atmospheric N2 that is
unavailable to most other species of phytoplankton, but the existence of other factors (e.g, water
temperature) can sometimes result in dominance of non-N-fixers in N-limited lakes (reviewed in
Paerl and Otten 2016). Further, different forms of fixed N (e.g. nitrate, ammonium, or urea) have
been shown to be preferred by different species of phytoplankton leading to changes in natural
lake phytoplankton community structure (Trommer et al. 2020).
Watershed inputs of P have often been implicated in cyanoHAB formation, particularly
as “legacy loading” to lake sediments that integrates years of past inputs (Sharpley et al.
2013, Randall et al. 2019). The tendency for HAB cyanobacteria, such as Microcystis spp.,
to have higher optimal growth temperatures (≥ 77 °F (25 °C)) than competitor chlorophytes
and diatoms is often cited to link their expansion to climate change (Paerl and Huisman
2008). However, climate-related changes in regional rainfall and hydrology affecting nutrient
transport to lake ecosystems are also important (Chapra et al. 2017). The complex
interactions between N, P, climate, growth and toxicity of cyanoHABs (Gobler et al. 2016),
underscores the need for comprehensive dual-nutrient management strategies that include
attention to N and P (Paerl 2018).
New Jersey is home to ~1700 lakes, some of which are located along the densely populated
New Jersey shore, and are referred to as coastal lakes. Historically, many of these coastal lakes
had a connection to the Atlantic Ocean, and some remain connected albeit through engineered
structures that run beneath streets and beaches in highly urbanized or developed watersheds.
Coastal lakes traditionally supported a wide range of uses, including spawning grounds for
anadromous fishes, swimming, fishing, and boating (Tiedemann et al. 2009). Presently, New
Jersey’s coastal lakes are beset with various water quality impairments (Tiedemann et al. 2009),
including but not limited to HABs, that preclude state certification for primary contact (e.g.
swimming). Deal Lake in Monmouth County, New Jersey (NJ) is the state’s largest coastal lake.
The watershed of Deal Lake is highly urban/suburban, and stormwater runoff has been identified
as a major source of sediment, nutrient and microbial pollution to the lake (Tiedemann et
al. 2009). Residents of the area value Deal Lake for its recreational boating and fishing opportunities,
and as a greenspace and wildlife refuge amidst the densely populated region in which
it exists. Understanding the relationship between nutrients and HABs in Deal Lake is necessary
for effective management and mitigation efforts that will ensure ongoing safe access to this
environment by people, pets and wildlife alike.
Summertime cyanoHABs have led to regulatory actions restricting the use of Deal Lake by
the public. The objective of this study was to analyze time series of water quality, nutrients, and
indicators of cyanobacterial biomass to identify relationships between these parameters, and to
gain insight into the relationship between watershed nutrient loading and HAB occurrence. Additionally,
nutrient addition bioassays were conducted in 2018 to determine whether N or P was
limiting cyanobacterial biomass.
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Materials and Methods
Field Site Description, Sampling, and Nutrient Analyses
Deal Lake is the largest coastal lake in the state of NJ, with a total surface area of 155
acres (0.63 km2), average depth of 1.8 m, a watershed area of 4400 acres (17.8 km2) that is
classified as “highly urbanized” (Souza 2011), and a trophic status classified as “eutrophic”
by previous investigations (Tiedemann et al. 2009). Seven NJ municipalities border Deal
Lake with a combined population of approximately 70,000. Deal Lake is characterized by an
eastward main basin adjacent to the Atlantic Ocean coastline that tapers to multiple tributary
“arms” to the west (Souza 2011; Fig. 1). The lake remains connected to the Atlantic Ocean
via a flume gate used to regulate lake level, as well as to allow migratory fish movements into
and out of the lake (Souza 2011). Deal Lake’s main basin has a volume of 0.9 × 106 m3, and
receives annual inputs of 8.1 × 106 m3 from tributaries and 1.9 × 106 m3 from stormwater annually
(Souza 2011). Fig. 1 shows the location of sampling stations on Deal Lake. Samples
were taken from the surface using a 1-liter bottle approximately bi-weekly to monthly, with
fewer samples in winter. Lakes were accessed from shoreline or bridges, and Secchi depth
was measured in situ along with conductivity, temperature, and dissolved oxygen (YSI Pro
2000 multiparameter probe).
Figure 1. Deal Lake and sampling locations. Deal Lake station number used in subsequent Figures is
the final digit in each station code. Wanamassa Pt. and Comstock St. are locations of nutrient addition
bioassays. “Primary” and “supplemental” stations are NJ DEP designations referring to requirements for
cell counting within two weeks, or at a later date, respectively.
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Chemical Analyses
1-L acid washed amber bottles were used to collect surface water samples for nutrient
analysis, pH, and chlorophyll a analysis in the Certified Chemistry Lab at the NJ Department of
Environmental Protection (DEP) Bureau of Marine Water Monitoring. Ammonia, Orthophosphate,
Nitrate + Nitrite, Total Phosphorus, and Total Nitrogen were analyzed on a SEAL AA3
segmented flow analyzer following EPA and USGS methodologies. An alkaline persulfate digestion
was performed on the samples to oxidize all the forms of phosphorus and nitrogen prior
to analysis for the Total Phosphorus and Total Nitrogen analysis. The pH was determined on a
Hach 440d multimeter with an IntelliCal PHC101 pH probe. The probe had a 3-point calibration
with pH buffers at 4, 7, and 10. The chlorophyll a was determined by filtering the sample
through a 1.85 in (47 mm) glass fiber filter, placing it in 10 mL of a solution of acetone, dimethyl
sulfoxide (DMSO), and water; 54%, 40%, and 6% respectively by volume, and then placing
it overnight in the freezer at 4 °F (-20 °C) for extraction. It was then analyzed on a Beckman
Coulter DU730 UV/Vis Spectrophotometer. Readings were taken before and after acidification
and entered into the following equation,
Chl a (μg L−1) = {[26.7 × (664b − 750b) – (665a – 750a)] × 0.01} / [(V2 × 2.54) ]} × 1000
where a = Post-acidification reading; b = Pre-acidification reading; V2 = volume of sample
in liters; L = light path length or width of cuvette (2.54 cm). Microcystin concentration was
measured by NJ DEP using ELISA assays (Abraxis p/n 520011) according to manufacturer’s
protocols including freeze-thaw cycles for cell lysis.
Hourly rainfall data were retrieved from http://njdep.rutgers.edu/rainfall/ for station
RABCH006, which is located at the eastern end of Deal Lake.
Nutrient Addition Bioassays
For each bioassay experiment, either 12 or 24 acid-washed 1-L cubitainers (4 or 8 treatments
in triplicates, respectively) were rinsed and filled with 800 mL Deal Lake water, and incubated
in the lake, in a submerged PVC enclosure covered with 1 layer of black fiberglass screening for
4–6 days. Nutrient stocks for nutrient amendments were purchased from the National Center for
Marine Algae and Microbiota at Bigelow Laboratory for Ocean Science (East Boothbay, ME,
USA). Nutrients were added in excess relative to typical Deal Lake concentrations, a strategy
commonly used in nutrient addition bioassays (Downing et al. 1999), and suited to the goal of
identifying the limiting nutrient. Treatments included addition of nitrogen (100 μM NO3, or
1,400 μg N L−1), ammonia (100 μM NH4, or 1,400 μg N L−1), and phosphorous (6.3 μM PO4,
or 195 μg P L−1) individually, and combined in Redfield ratio N:P requirements (16:1 molar).
Confirmation of initial nutrient concentrations following amendments was made by analyzing
a subset of samples on a 9500 Photometer (YSI) according to manufacturer’s instructions for
each analyte. Starting conditions for phytoplankton biomass and water temperature are shown
in Table 1. During the bioassays, samples were taken daily to monitor growth, and ensure no
catastrophic crashes occurred before the final sample was taken. A Turner Designs handheld
Cyanofluor was used in this experiment to detect and measure phycocyanin fluorescence (PC),
a pigment-based proxy for cyanobacterial biomass. Qualitative analysis was performed by microscopy
of pooled replicates from each treatment preserved in Lugol’s iodine (5% final by
vol.) solution. Boxplots were produced comparing in vivo fluorescence (IVF) measurements
at Tf relative to the control. ANOVA analysis for statistical significance (p < 0.05) was used to
analyze results.
Phycocyanin fluorescence (PC) has been shown to provide useful indices for tracking
changes in cyanobacterial biomass (Hodges et al. 2018, Pasztaleniec et al. 2020, Chaffin et al.
2018b), but still requires ground-truthing to cell measurements. Phycocyanin fluorescence was
measured with the Turner Designs CyanoFluor. It was ground-truthed to four cell count sample
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1A Ocean Ave 8/27/2018 245,000 0.16
101A N. Wanamassa Dr 8/27/2018 243,000 0.12
102A Sunset Ave 8/27/2018 205,000 0.1
103A Westra St 8/27/2018 51,000 0.01
104A Corlies Ave 8/27/2018 38,000 0
105A Main St 8/27/2018 727,000 0.15
1A Ocean Ave 8/16/2018 3,200 0.26
101A N. Wanamassa Dr 8/16/2018 15,000 0.13
102A Sunset Ave 8/16/2018 2,000 0.12
A Wickapecko Dr. 8/16/2018 n.p. 0.05
B Ridge Ave 8/16/2018 n.p. 0.01
103A Westra St 8/16/2018 11,800 0.1
104A Corlies Ave 8/16/2018 21,200 0.06
105A Main St 8/16/2018 12,400 0.19
1A Ocean Ave 8/2/2018 >20,000 1.88
101A N. Wanamassa Dr 8/2/2018 >20,000 0.92
102A Sunset Ave 8/2/2018 >20,000 0.82
A Wickapecko Dr. 8/2/2018 n.p. 0
B Ridge Ave 8/2/2018 n.p. 0
103A Westra St 8/2/2018 12,500 0.27
104A Corlies Ave 8/2/2018 n.p. 0.36
105A Main St 8/2/2018 >20,000 1.47
1A Ocean Ave 7/23/2018 >20,000 0.7
Psuedanabaena, Merismopedia
Aphanacaphasca,
Psuedanabaena, Merismopedia
Aphanacaphasca
Gleocapsa
Gleocapsa, Aphanacaphasca
Aphanocapsa, Psuedanabaena,
Merismopedia
Psuedanabaena, Merismopedia,
Raphidiopsis
Psuedanabaena, Raphidiopsis
Merismopedia
----
----
Merismopedia, Aphanocapsa
Psuedanabaena, Merismopedia,
Raphidiopsis, Aphanocapsa
Psuedanabaena, Merismopedia,
Raphidiopsis, Planktothrix
Oscillatoria, Psuedanabaena,
Merismopedia, Raphidiopsis
Psuedanabaena, Merismopedia
Raphidiopsis
Psuedanabaena, Merismopedia
----
----
Merismopedia
----
Merismopedia, Aphanocapsa
Raphidiopsis
Table 1. Cell and toxin sampling (2018) during Deal Lake bloom. n.p. = not present.
Site Location Date
Cell count
(cells/ml)
Microcystins
(μg/l) Dominant these taxa
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sets obtained from the summer of 2018, which included water samples taken from: 1) a Secchi
Dip event occurring in different coastal lakes on July 19th, 2) a bioassay done in Deal Lake on
July 3rd, 3) two bioassays completed in Deal Lake on July 3, and 4) Deal Lake samples taken
throughout the summer. These datasets contained in-vivo-fluorescence readings from a handheld
Cyanofluor (Turner Designs), and had corresponding samples preserved in 5% final (by volume)
Acid Lugol’s iodine solution. One milliliter of these samples was taken after the bottle was inverted
and placed in a gridded Sedgewick Rafter Counting Chamber. These chambers were left
alone to settle for ten minutes, and then examined on a Nikon Diaphot 300 Inverted microscope.
Each sample had five grids counted for three different types of cyanobacteria genera that were
dominant: Microcystis, Merismopedia, and Pseudanabaena. Microcystis and Merismopedia
were counted as “natural units”. They presented as clumps or sheets of cells, respectively, and
Pseudanabaena was counted as trichomes. Scatterplots were made comparing total cyanobacterial
cell counts to PC readings. The relationship between total cyanobacterial cells (per mL) and
phycocyanin fluorescence (RFU), based on this analysis, was:
Total cyanobacterial cells per mL = 0.0024*PC + 17.198 (r2 = 0.38, p < 0.001)
For confirmation of bioassay results based on fluorescence, cell counts were performed on
pooled replicates of treatments from the starting timepoint (T0) to the end of the experiments.
Cluster Analyses of Stations
To address whether the nine stations sampled on Deal Lake (Fig. 1) differ from each other
based on water quality measurements, a cluster analyses was performed using the “cluster”
package in R, and visualized using package “factoextra” with fviz_cluster and ggparcoord
functions. Cluster analysis is an exploratory statistical methodology that looks to group cases
(e.g., stations) into groups within which stations are more similar than stations are among
different groups based on some set of properties (e.g., median water quality parameters over
a specified time period). Partitioning around means (PAM) clustering was used as this is a
version of the general K-means clustering method that is less sensitive to outliers (i.e. more
robust). Data from springs and summers of 2017 and 2018, when the water temperature was
>57 °F (14 °C), was used because station #1 was not sampled outside this sample range, and
otherwise would have been excluded from the analysis. All water quality parameters were summarized
as median values by station, and used as input to calculate distance measures (function
fviz_dist), determine optimal number of clusters (function fviz_nbclust), and to perform PAM
clustering (function pam).
Results
Rainfall
The Deal Lake rain gauge recorded 46 in (1168 mm) of rain in 2017, and 61 in (1550
mm) in 2018. The timing of rain differed between years, with January–March showing similar
accumulations, March–July higher accumulations in 2017, and September–December higher
accumulations in 2018 (Fig. 2 and inset). Generally, 2017 was wetter earlier (March–July), and
2018 was wetter later (August–December) in the year (Fig. 2 inset).
Water Quality Parameters by Stations and Cluster Analyses
Examination of water quality parameters by station (Fig. 3) suggested differences that were
subsequently supported by PAM cluster analyses (Fig. 4). Water temperature (Fig. 3A) was the
only WQ quality parameter not showing a significant difference among sites. Stations 4A and
4B tended to stand out as different from the other sites for most parameters. Sites 4A and 4B, in
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the southwest arm of Deal Lake (Fig. 1), had lower median Chl a (Fig. 3F) specific conductivity
(Fig. 3B), pH (Fig. 3C), D.O. (Fig. 3E) TP (Fig. 3H), PO4 (Fig. 3L) as well as organic N and P
(Fig. 3M, N) than other stations. These same stations (4A and 4B) also had higher median DIN
(Fig. 3I, J, K), DIN:DIP (Fig. 3O), and TN:TP (Fig. 3P) relative to other sites. Likewise, PAM
cluster analysis put stations 4A and 4B into a separate group (cluster 2) from the rest of the stations
(Fig. 4A) based on elevated median DIN, TN, TN:TP, and DIN:DIP (Fig. 4B), consistent
with an abundance of unincorporated DIN at these sites.
Water Quality Time Series
As a result of the cluster analysis, stations 4A and 4B were excluded from the time series
analysis presented here. Water temperature minima occurred between December and Feb (Fig.
5A), with the lowest recorded average temperature of 36.5 °F (2.5 °C) occurring Dec 13, 2017,
followed by averages of 39.7 °F and 43.9 °F (4.3 °C and 6.6 °C), recorded March 27, 2017 and
March 14, 2018, respectively. Water temperature maxima occurred between July and September
(Fig. 5A), with the highest recorded average temperature of 87.4 °F (29.3 °C) recorded August 9,
2018, followed by 84.4 °F and 83.3 °F (29.1 °C and 28.5 °C) on July 13 and 18, 2017, respectively.
Lake pH was elevated in summer, and lower in winter. Average lake pH minima were ~6.5–
7.5 in the December through March, and then elevated at 8.0–10.0 between June and September
(Fig. 5B).
Lake average dissolved inorganic nitrogen (DIN) was elevated between February and
May, with station averages in the 600–1045 μg L−1 range (Fig. 5C). The eight highest DIN
values (>1000 μg L−1) were associated mostly (5 of 8 observations) with station 4, located
in the southwestern arm of the lake, but also stations 2, 6, and 7. Elevated values tended to
occur in March (5 of 8 observations), but three of the station 4 elevated DIN values were
recorded in May, June, or August. The DIN was composed of 59±18.1% NH3 during these
elevated times. Lower values of DIN occurred between July and October, with lake average
Figure 2. Hourly rainfall, 2017 – 2018. Retrieved from http://njdep.rutgers.edu/rainfall/ station RABCH006,
located near station 2 on the site map. Inset graph shows annual rainfall accumulation curves for each year.
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Figure 3. Box and whisker plots comparing water quality parameters by station. Horizontal line at the
center of each box is the median, while the bottom and top of the box are the 1st and 3rd quartiles,
respectively. Whiskers extend to 1.5 × the interquartile range. Heavy black points in line with the whiskers
are outliers. Jitter (red) shows individual sample values.
Figure 4. Cluster analysis of stations based on median water quality parameters. A. Clustering of stations
determined by PAM algorithm, showing stations 4A and 4B separate from the others. B. Plot showing
standardized values of parameters by group.
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values between 3.4 and 28.5 μg L−1, with the exception of some values recorded at station 4
as mentioned above. During these times DIN was 75±14.2% NH3. Lake average organic N
varied from ~500 μg L−1 in the winter and spring to ~1500–2200 μg L−1 in the summer and
early autumn (Fig. 5D).
Figure 5. Physical/chemical parameter time series measured in Deal Lake. Different symbols represent
individual station values for each sampling date. The line connects station averages (not shown) for each
sampling date.
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Lake average DIP tended to be below 25 μg L−1 in winter and spring, and 50–100 μg L−1 in
summer, with anomalously high values recorded at station 5 located in the northwest arm of the
lake in August 2017 (Fig. 5E). A similar pattern was seen for organic P, with winter minima and
summer maxima (Fig. 5F).
Lake average DIN:DIP (mol) (Fig 5G) peaked above 100 in late winter and spring, and
was low in summer, dropping to <1 on nine occasions recorded in July, August and September.
Lake average organic N:P (Fig. 5H) tended to peak at ~50 between July and November, and was
lowest at ~25 in March–April.
Regressions of Chl a on Nutrients
Cyanobacterial-dominated phytoplankton blooms were observed in both years, tending to
occur between July and October, with a larger bloom detected in 2017 compared to 2018 (Fig.
6A). A subset of samples (n = 55) measured for both Chl a and phycocyanin show a strong
correlation (R = 0.64, p < 0.05) between these two parameters, consistent with cyanobacteria
being the dominant phytoplankton during high biomass periods. The highest Chl a values were
associated with lower DIN values (Fig. 6B). Organic N increased linearly with Chl a (Fig.
6C), explaining 76% (p < 0.001) of the variability. DIP increased linearly with Chl a (Fig. 6D)
explaining 58% of the variability (p < 0.001). Organic P increased linearly with Chl a, but was
weakly related (Fig. 6E). The ratio of organic N:P was not significantly related to Chl a (Fig. 6F).
Deal Lake Microcystin Measurements
Measurements of Deal Lake microcystin concentrations made by NJ DEP and Monmouth
County Department of Health (MCDH) during the 2018 bloom show relatively low levels consistently
below guidance levels of 3 μg L−1 despite cell numbers that approach 104–106 μL−1
(Table 1). Toxin levels measured early in the bloom tended to be higher than those measured
later in the bloom despite elevated cell numbers reported later in the bloom.
Nutrient Addition Nioassays
Nutrient addition bioassays were performed on Deal Lake water on three different dates
in 2018. The earliest bioassay performed on Deal Lake in 2018 was March 24–28, with To Chl
a levels of 9 μg L−1 (Table 2). In this bioassay P was determined to be the limiting nutrient of
a chlorophyte and diatom dominated phytoplankton community based on increased Chl and
PC over the control and N treatments (Fig.
7A., 7B.). The May 31 bioassay was performed
at a time when To Chl a biomass
was 68 μg L−1 (Table 2). Chl and PC values
did not significantly differ from the control
(p = 0.112) (Figs. 7C., 7D.). Microscopic
analyses of these samples showed
predominant flagellates and diatoms with
some cyanobacteria present. July 3 bioassays
at Comstock St. and Wanamassa Pt.
had To Chl a levels of 67 and 147 μg L−1,
respectively (Table 2). These bioassays
show a strong and significant response to
nutrient addition in both PC and Chl values,
especially treatments containing NH4
(Fig. 7E–H). Qualitative analysis of pre-
Table 2. Starting phytoplankton biomass (Chl a) and
water temperature conditions for in-lake nutrient
bioassays. The Mar 23 bioassay was performed
at station 4A. May 31 and Jul 12 bioassays were
performed at Wanamassa Pt. For Jul 3, ‘cs’ refers to
Comstock St. and ‘wp’ refers to Wanamassa Pt. as
locations of the bioassays.
Mar 23 9 7–8
May 31 68 19–20
Jul 3_cs 67 25–29
Jul 3_wp 147 25–29
Jul 12 85 27–28
Bioassay
Start Chl a
(μg L−1)
Water temp.
(°C)
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served samples indicated three dominant cyanobacteria types Microcystis, Pseudanabaena
and Dolichospermum, with relatively fewer flagellate and diatom species present compared
to the May 31 bioassay. The July 12 bioassay had a T0 Chl a value of 85 μg L−1 (Table 2), and
showed nitrogen limitation again (Fig. 7I, J). The PC growth in this experiment responded
strongly and significantly to all nitrogen containing treatments (p < 0.001), while total biomass
of Chl did not respond significantly to any single treatment. Microscopic examination
of pooled replicate samples from the June 28 bioassays at both sites showed dominant Micro-
Figure 6. A. Chl a time series in Deal Lake. Different symbols represent individual station values for each
sampling date. The line connects station averages (not shown) for each sampling date. B. – F. Scatterplots
and regressions of Chl a on nutrient parameters. Results of simple linear regression analyses are shown on
each graph where relevant.
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cystis, Pseudanabaena, and Mersimopedia that showed increases in abundance similar to that
seen in fluorescence measurements. Cell counts in the July 12 pooled replicate samples (Fig.
8C) did not reflect fluorescence measurements as much in terms of total cell counts, but did
show a response of Microcystis to treatments containing ammonium.
Discussion
Deal Lake, the largest of New Jersey’s coastal lakes, was loaded with DIN during the
winters observed here, followed by transformation of DIN to organic N (in the form of phytoplankton
including HAB biomass) over the summer growing season. Meanwhile, DIP remained
low in winter, but increased in the summer in the presence of high cyanoHAB biomass. Consequentially,
the nutrient limiting phytoplankton biomass shifted from P in winter and spring to N
in summer when HABs predominated. Further, water temperatures above 77 °F (25 °C) typified
Deal Lake in summer, and likely contributed to the observed cyanoHABs. These patterns have
important implications for lake management and rehabilitation.
Spatial Variability Within Deal Lake
The groupings of stations revealed by examinations of water quality parameters (Fig. 3) and
cluster analyses (Fig. 4), based on elevated levels of DIN at stations 4A and 4B, are consistent
with a significant source of DIN being present in the southwest arm of Deal Lake. While determining
the source of this DIN was beyond the scope of this study, at least two possible sources of
this nitrogen are considered: a golf course, and a historical landfill (presently the site of a mall)
located adjacent to the arm of the lake containing these stations. A review of nutrient export from
Figure 7. Boxplots comparing treatments to the control at the bioassay endpoint. A. Mar 2018 Chl, B. Mar
2018 PC, C. May 2018 Chl, D. May 2018 PC, E. Jun 2018 Chl (location), F. Jun 2018 PC (location), G. Jun
2018 Chl (location), H. Jun 2018 PC (location), I. Jul 2018 Chl, J. Jul 2018 PC. Treatment codes are N=
nitrate; P = phosphate; Am = Ammonia. In each graph, treatments with different letters were significantly
different (p < 0.05) by ANOVA post-hoc test (Tukey). Treatments on the x-axis are coded C (control), N
(nitrate), P (phosphate), NP (nitrate + phosphate), AmN (ammonia + nitrate), AmP (ammonia + phosphate),
AmNP (ammonia + nitrate+phosphate). “n.s.” indicates non-significant ANOVA
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Figure 8 Comparisons of dominant taxa counts (MC = Microcystis, MP = Merismopedia, PA =
Pseudanabaena) from pooled replicates for nutrient-addition bioassays from A. Counts are in “natural
units” (NU). A. June 2018 (Comstock St)., B. June 2018 (Wanamassa Point), and C. Jul 2018 (Wanamassa
Point). Treatments on the x-axis are coded C (control), N (nitrate), P (phosphate), NP (nitrate + phosphate),
AmN (ammonia + nitrate), AmP (ammonia + phosphate), AmNP (ammonia + nitrate + phosphate).
golf courses found “reasonably low” export from such systems, but emphasized the potential for
wide ranging variability depending on site specific soil, rainfall, and best management practices
(Bock and Easton 2020). Landfill leachate can also be highly variable depending on the age and
regional climatology of the facility, but DIN is identified as a common leachate (particularly as
reduced ammonia) along with alkaline pH and elevated conductivity (Luo et al. 2020). Stations
4A and 4B do show elevated ammonia, consistent with landfill leachate, but also elevated nitrate,
relatively acidic pH, and low specific conductivity compared to other sites. While stations 4A
and 4B appear to be associated with a source of DIN to Deal Lake, further study is needed to
identify the source of such nutrients.
Seasonal Cycle of Nutrients in Deal Lake
Deal Lake was loaded with DIN over the winters when water temperature and cyanoHAB
biomass in the lake was generally low. The watershed of Deal Lake is highly urbanized (78.1%)
with a high proportion of impervious surfaces (32.2%), making the lake susceptible to stormwater
runoff (NJAES 2019). Urban stormwater runoff is a known source of N and P to lakes
and coastal waters in many locations (Taylor et al. 2005, Silva et al. 2019). It is a very likely
source of winter DIN loading, although specific characterization of the chemical composition
of Deal Lake stormwater runoff has not been done. It is interesting to note that in 2017, when
heavier Deal Lake blooms were observed, heavier rainfall occurred before (March–July) the
HAB-season compared to 2018 when rainfall was greater after (Sept–Dec) the HAB season
(Fig. 2). Due to anthropogenic climate change, NJ has seen an 8% increase in precipitation over
the past decade, including an increase in extreme precipitation events (>2 in. (51 mm) in a day),
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and similar changes in NJ precipitation are expected to occur through the second half of the 21st
century (Runkel et al. 2017). Together, these observations suggest that stormwater runoff will
continue to be a major issue contributing to cyanoHABs in Deal Lake. Characterization and
management of urban stormwater runoff, as well as tracking the timing of rainfall, should be a
priority in the context of cyanoHAB mitigation for Deal Lake.
The conclusion that Deal Lake shifts from winter P-limitation to summer N-limitation is
supported by nutrient addition bioassays performed in 2018 as well as by nutrient time series
throughout the study. Similar patterns of seasonal shifting from P- to N-limitation upon the onset
of cyanoHABs have been made by Xu et al. (2010) and Paerl et al. (2015) in Lake Taihou, China,
as well as Chaffin et al. (2018a). Nutrient addition bioassay results suggest a temporal shift
over the course of spring to summer in the nature of limiting nutrients, from P- to N-limitation.
First, the mixed flagellate-diatom assemblage assayed 5/31/2018 showed no response in the Chl
signal. The conclusion that these assemblages were not nutrient limited is in agreement with the
fact that these assays were performed at the time of year when lake DIN:DIP is starting to reach
its minimum (Fig. 5G). Early (6/28/2018) and late (7/12/2018) summer bioassays showed clear
N-limitation, but no synergistic effect of N and P additions as has been described elsewhere
(reviewed in Paerl et al. 2016). At the time these assays were performed, Deal Lake DIN:DIP
had been low for about one to two months (Fig. 5), due to the combined effect of DIN depletion
and DIP accumulation. The continuing rainfall during this period (Jul–Oct) likely delivers high
DIN loads through stormwater runoff, creating episodic opportunities for growth and perhaps,
toxin production.
While both N and P can potentially enter the lake water column through allochthonous
and/or autochthonous (e.g. Søndergaard et al. 2013) sources, the pattern of DIP accumulation
observed in the low-rainfall summer period in Deal Lake strongly suggests an autochthonous
source. The apparent accumulation of autochthonous DIP drives Deal Lake toward N-limitation
when cyanoHABs are present. Deal Lake is shallow (5.9 ft (1.8 m) average depth), a characteristic
that favors sediment-driven nutrient cycling due to the high sediment surface to volume in
shallow systems (Pace and Prairie 2005). Lake sediments can be a sink for P under aerobic and
oxidizing conditions, but establishment of anaerobic or reducing conditions due to organic matter
loading of the sediment surface (Moore et al. 1998), as well as elevated pH (Christophoridis
and Fytianos 2006) that favors release of P to the water column. Additionally, sedimentation of
cyanobacterial biomass can change lake nutrient fluxes. Chen et al. (2014) experimentally demonstrated
increased P mobilization, related to elevated rates of iron and sulfur reduction, from
Lake Taihou (China) sediments after amendment with cyanobacterial bloom biomass. Further,
benthic feeding common carp (Cyprius carpio, Linnaeus 1758) are abundant in Deal Lake (Tiedemann
et al. 2009), and a study in shallow Kohlman Lake (MN) showed a 55–92% increase
in P available for release in areas where carp were active (Huser et al. 2016), suggesting another
potential source of elevated P release from Deal Lake sediments. The correlation between elevated
pH and HAB biomass occurring in Deal Lake likely generates conditions at the sediment
surface that favors the release of sediment-bound P after lakes are loaded with DIN over the
winter–spring, helping sustain cyanoHABs.
Average Deal Lake water temperatures measured in this study reached 84.2 °F (29 °C) in
July of 2017, and 82–84 °F (28–29 °C) in July–August of 2018. That was warmer than the average
Deal Lake temperatures of 66.6–68.9 °F (19.3–20.5 °C)) reported for that time of year in a
1978 comprehensive study carried out by NJ DEP (Wagner 1978). These elevated temperatures
can be expected to favor cyanobacterial dominance over competitor chlorophytes and diatoms
(Paerl and Huisman 2008), particularly in the presence of excessive nutrient loading. There
are two likely causes of Deal Lake warming. First, infilling of the lake by sediment runoff has
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reduced lake depth, and therefore volume, according to long-time residents, such that solar
insolation would heat the remaining water volume to a higher temperature than previously attained.
Second, climate change impacts in NJ include a 38 °F (3 °C) increase in annual average
temperatures and an increase in the number of days with temperatures above 95 °F (35 °C) over
the last century (Runkel et al. 2017). In combination, these two factors have likely resulted in a
warmer Deal Lake than existed 42 years ago (Wagner 1978), and are contributing to the ongoing
cyanoHAB issues experienced there.
Species Composition and Potential Toxicity
The species composition of summer 2018 Deal Lake HABs can be interpreted as an indicator
of N-overloading (Paerl 2018) because the two main species present, Microcystis and Pseudanabaena,
are not N-fixers (Paerl and Otten 2013). This conclusion can appear contradictory,
however, considering the low levels of DIN, low DIN:DIP, and bioassay results during bloom
periods reported here, all of which point to N-limitation. Views on the factors favoring non-
N-fixing cyanobacteria, particularly Microcystis, have evolved to include the acknowledgment
that other environmental factors can support the dominance of non-N-fixing forms in N-limited
environments (Paerl and Otten 2016). Species composition data available for the May–July
bioassays conducted in 2018 show a succession from flagellate and diatom dominance in May
to predominance of Microcystis, Pseudanabaena, and less so, Dolichospermum (which can
fix N) in cyanoHAB water of Deal Lake later in the summer. This apparently non-intuitive
dominance of non-N-fixers in N-limited temperate lakes has been observed elsewhere and attributed
to factors other than N-availability as the driving force of cyanobacterial community
composition. It includes the affinity of species like Microcystis for growth at high temperatures
typical of late-season temperate lakes, as well as Microcystis’ versatility in N-form utilization
including inorganic and organic forms, and the competitive disadvantage of N-fixation stemming
from its energetic costs, micronutrient requirements, and oxygen sensitivity (reviewed in
Paerl and Otten 2016). Later season water temperatures between 75 and 86 °F (25 and 30 °C)
observed in this study are consistent with water temperature being a predominant factor in late
season Microcystis abundance in Deal Lake.
The low toxicity of the 2018 Deal Lake cyanobacteria bloom is likely related to the nutrient
conditions, particularly low DIN, present in the lake during summer blooms. The nutrients
feeding a bloom not only affect growth, but can also affect the toxicity of cells making up the
cyanoHAB population because toxins such as microcystin are N-rich molecules (Gobler et al.
2016). Although speculative due to a paucity of toxin data collected during these years (Table
1), declining microcystin concentrations between 7/2/2018 and 8/27/2018 occurs over the time
period of N-limitation as shown through nutrient time series (Fig. 5C) and nutrient addition
bioassays (Fig. 7). There are two important corollaries of this tentative conclusion that deserve
further attention. First, blooms occurring earlier in the season when N is more prevalent may
be more toxic per unit biomass than late-season N-limited blooms, although low cell numbers
might limit overall lake toxicity. Second, rainfall or other events occurring mid- to late-summer
that introduce large DIN loads, establishing high-density cyanoHABs, may result in ephemeral
increases of toxicity that could easily be missed by routine monitoring. For coastal lakes like
Deal Lake that drain to the ocean at swimming beaches, the potential for exposure of bathers
to high cell density and/or toxic outflows also needs to be considered.
Conclusion and Management Implications
Deal Lake provides a small-scale model system for examining the relationship between
nutrient loading, climate, and the growth of freshwater cyanoHABs in highly urbanized enUrban
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vironments. Based on this preliminary analysis of monitoring data and nutrient addition bioassays,
Deal Lake fits the profile of a lake experiencing cyanoHABs due to a combination of
anthropogenic eutrophication and elevated water temperatures. Management actions should
target watershed improvements aimed at decreasing seasonal nutrient loading through tributary
and stormwater inputs, but should also cautiously consider dredging to remove sediment
P, as Deal Lake is small enough to make this feasible, but results from other lakes are variable
(e.g. Hamilton et al. 2016, Paerl 2018). New Jersey’s 2013 fertilizer law banning P and
requiring at least 20% slow-release N (NJDEP 2013) will not address legacy P already in lake
sediments. The dynamics described here in fact suggest that the magnitude of HABs in Deal
Lake will increase with DIN loading rather than P because excess autochthonous P is available
in summer. The question of whether early season blooms or summer blooms experiencing
anomalously high DIN-loading through storms achieve higher toxicity needs to be addressed
in a management context.
Although Deal Lake is small relative to other lakes experiencing HABs nationally, it exists
within a densely populated and highly developed watershed. New Jersey is in fact the most
densely populated state in the US, and towns and cities along the New Jersey shore experience
dramatic seasonal population increases. A Monmouth County study determined the average
summer daytime population increased 73% over the average year-round population (Monmouth
County Planning Board 2008), so the population increase coincides with the timing of Deal
Lake cyanoHABs. These factors, combined, make the potential impacts of HABs in New Jersey
coastal lakes on human populations greater than would be suggested by their size.
Acknowledgements
The authors wish to thank Monmouth University students Marissa DeTorre, Cidia Dominique, and
Justine Violante for work done in the Spring 2018 Ecosystem Analysis class; NJ DEP Bureau of Freshwater
and Biological Monitoring for sample collections; the Deal Lake Commission and Deal Lake Watershed
Alliance for assistance with sampling and logistics; and the Monmouth University School of Science Summer
Research Program and Urban Coast Institute for student support.
Literature Cited
Bock, E.M., and Z.M. Easton. 2020. Export of nitrogen and phosphorus from golf courses: A review.
Journal of Environmental Management 255:109817. https://doi.org/10.1016/j.jenvman.2019.109817
Carey, R.O., G.J. Hochmuth, C.J. Martinez, T.H. Boyer, M.D. Dukes, G.S. Toor, and J.L. Cisar. 2013.
Evaluating nutrient impacts in urban watersheds: Challenges and research opportunities. Environmental
Pollution 173:138–149. https://doi.org/10.1016/j.envpol.2012.10.004
Chaffin, J.D., T.W. Davis, D.J. Smith, M.M. Baer, and G.J. Dick. 2018a. Interactions between nitrogen
form, loading rate, and light intensity on Microcystis and Planktothrix growth and microcystin
production. Harmful Algae 73:84–97. https://doi.org/10.1016/j.hal.2018.02.001
Chaffin, J.D., D.D. Kane, K. Stanislawczyk, and E.M. Parker. 2018b. Accuracy of data buoys for measurement
of cyanobacteria, chlorophyll, and turbidity in a large lake (Lake Erie, North America): Implications
for estimation of cyanobacterial bloom parameters from water quality sonde measurements. Environmental
Science and Pollution Research 25:25175–25189. https://doi.org/10.1007/s11356-018-2612-z
Chapra, S.C., B. Boehlert, C. Fant, V.J. Bierman, J. Henderson, D. Mills, D.M.L. Mas, L. Rennels, L.
Jantarasami, J. Martinich, K.M. Strzepek, K.M., and H.W. Paerl. 2017. Climate change impacts on
harmful algal blooms in U.S. freshwaters: A screening-level assessment [Research article]. Environmental
Science and Technology 51:8933–8943. https://doi.org/10.1021/acs.est.7b01498
Chen, M., T.R. Ye, L.R. Krumholz, and H.L. Jiang. 2014. Temperature and cyanobacterial bloom biomass
influence phosphorous cycling in eutrophic lake sediments. PLoS ONE 9:e93130. https://doi.
org/10.1371/journal.pone.0093130
Urban Naturalist
J.E. Adolf, K. Saldutti, E. Conlon, E. Ernst, B. Heddendorf, S. Shifren, and R. Schuster
2022 No. 57
17
Christophoridis, C., and K. Fytianos. 2006. Conditions affecting the release of phosphorus from
surface lake sediments. Journal of Environmental Quality 35:1181–1192. https://doi.org/10.2134/
jeq2005.0213
de la Cruz, A., Logsdon, R., Lye, D., Guglielmi, S., Rice, A., Kannan, M.S. Harmful Algae Bloom
occurrence in urban ponds: relationship of toxin levels with cell density and species composition.
Journal of Earth and Environmental Science 25:704-726.
Downing, J.A., C.W. Osenberg, and O. Sarnelle. 1999. Meta-analysis of marine nutrient-enrichment
experiments: Variation in the magnitude of nutrient limitation. Ecology 80:1157–1167.
Griffith, A.W., and C.J. Gobler. 2020. Harmful algal blooms: A climate change co-stressor in marine
and freshwater ecosystems. Harmful Algae 91:101590. https://doi.org/10.1016/j.hal.2019.03.008.
Gobler, C.J., J.A.M. Burkholder, T.W. Davis, M.J. Harke, T. Johengen, C.A. Stow, and D.B. Van de
Waal, D. B. 2016. The dual role of nitrogen supply in controlling the growth and toxicity of cyanobacterial
blooms. Harmful Algae 54:87–97. https://doi.org/10.1016/j.hal.2016.01.010
Hallegraeff, G.M., D.M. Anderson, C. Belin, M.Y.D. Bottein, E. Bresnan, M. Chinain, H. Enevoldsen,
M. Iwataki, B. Karlson, C.H. McKenzie, I. Sunesen, G.C. Pitcher, P. Provoost, A. Richardson,
L. Schweibold, P.A. Tester, V.L. Trainer, A.T. Yñiguez, and A. Zingone. 2021. Perceived global
increase in algal blooms is attributable to intensified monitoring and emerging bloom impacts.
Communications Earth and Environment 2. https://doi.org/10.1038/s43247-021-00178-8
Hamilton, D.P., N. Salmaso, and H.W. Paerl. 2016. Mitigating harmful cyanobacterial blooms:
Strategies for control of nitrogen and phosphorus loads. Aquatic Ecology 50:351–366. https://doi.
org/10.1007/s10452-016-9594-z
Hodges, C.M., Wood, S.A., Puddick, J., McBride, C.G., Hamilton, D.P. 2018. Sensor manufacturer,
temperature, and cyanobacteria morphology affect phycocyanin fluorescence measurements. Environmental
Science and Pollution Research 25:1079-1088.
Huser, B.J., P.G. Bajer, C.J. Chizinski, and P.W. Sorensen. 2016. Effects of common carp (Cyprinus
Carpio) on sediment mixing depth and mobile phosphorus mass in the active sediment layer of a
shallow lake. Hydrobiologia 763:23–33. https://doi.org/10.1007/s10750-015-2356-4
Lewitus, A.J., L.B. Schmidt, L.J. Mason, J.W. Kempton, S.B. Wilde, J.L. Wolny, and A.H. Ringwood.
2003. Harmful algal blooms in South Carolina residential and golf course ponds. Population and
Environment, 24:387–413. https://doi.org/10.1023/A:1023642908116
Luo, H., Y. Zeng, Y. Cheng, D. He, and X. Pan. 2020. Recent advances in municipal landfill leachate:
A review focusing on its characteristics, treatment, and toxicity assessment. Science of the Total
Environment 703:135468. https://doi.org/10.1016/j.scitotenv.2019.135468
Monmouth County Planning Board. 2008. Monmouth County Summer Coastal Population Study.
43 pp. Monmouth County Hall of Records, Freehold, NJ. https://www.co.monmouth.nj.us/documents/
24/Coastal%20Pop%20Study%20Report.pdf
Moore, P.A., K.R. Reddy, and M.M. Fisher. 1998. Phosphorus flux between sediment and overlying
water in Lake Okeechobee, Florida: Spatial and temporal variations. Journal of Environmental
Quality 27:1428–1439. https://doi.org/10.2134/jeq1998.00472425002700060020x
NJAES. 2019. Impervious cover reduction plan for Deal Lake watershed, Monmouth County, New
Jersey. Rutgers Cooperative Extension Water Resources Program, New Brunswick, NJ. http://water.
rutgers.edu/Projects/NJ_Sea_Grant/RAP/Draft_RAP_DealLakeWatershed_04082019.pdf
NJDEP. 2013. Christie administration fully implements landmark fertilizer law to reduce pollution and
keep waterways clean. https://www.nj.gov/dep/newsrel/2013/13_0038.htm
Olds, H.T., S.R. Corsi, D.K. Dila, K.M. Halmo, M.J. Bootsma, and S.L. McLellan. 2018. High levels
of sewage contamination released from urban areas after storm events: A quantitative survey with
sewage specific bacterial indicators. PLoS Medicine 15:1–23. https://doi.org/10.1371/journal.
pmed.1002614
O’Neil, J.M., T.W. Davis, M.A. Burford, and C.J. Gobler. 2012. The rise of harmful cyanobacteria
blooms: The potential roles of eutrophication and climate change. Harmful Algae 14:313–334.
https://doi.org/10.1016/j.hal.2011.10.027
Urban Naturalist
J.E. Adolf, K. Saldutti, E. Conlon, E. Ernst, B. Heddendorf, S. Shifren, and R. Schuster
2022 No. 57
18
Pace, M.L., and Y.T. Prairie. 2005. Respiration in lakes. Pp. 103–121 In P.A. Del Giorgio and P.J. le B.
Williams (Eds.). Respiration in Aquatic Ecosystems. New York: Oxford University Press.
Paerl, H.W. 2018. Mitigating toxic planktonic cyanobacterial blooms in aquatic ecosystems facing increasing
anthropogenic and climatic pressures. Toxins 10:1–16. https://doi.org/10.3390/toxins10020076
Paerl, H.W., and J. Huisman. 2008. Climate: Blooms like it hot. Science 320:57–58. https://doi.
org/10.1126/science.1155398
Paerl, H.W., and T.G. Otten. 2016. Dueling “CyanoHABs”: Unravelling the environmental drivers controlling
dominance and succession among diazotrophic and non-N2-fixing harmful cyanobacteria. Environmental
Microbiology 18:316–324. https://doi.org/10.1111/1462-2920.13035
Paerl, H.W., and Otten, T.G. 2013. Harmful cyanobacterial blooms: causes, consequences, and controls.
Microbial Ecology 65:995–1010. https://doi.org/10.1007/s00248-012-0159-y
Paerl, H.W., and Paul, V. J. 2012. Climate change: Links to global expansion of harmful cyanobacteria.
Water Research 46:1349–1363. https://doi.org/10.1016/j.watres.2011.08.002
Paerl, H.W., J.T. Scott, M.J. McCarthy, S.E. Newell, W.S. Gardner, K.E. Havens, D.K. Hofman, S.W.
Wilhelm, and W.A. Wurtsbaugh. 2016. It takes two to tango: When and where dual nutrient (N and P)
reductions are needed to protect lakes and downstream ecosystems. Environmental Science and Technology
50:10805–10813. https://doi.org/10.1021/acs.est.6b02575
Paerl, H.W., Xu, H., Hall, N. S., Rossignol, K. L., Joyner, A. R., Zhu, G., and Qin, B. 2015. Nutrient limitation
dynamics examined on a multi-annual scale in Lake Taihu, China: Implications for controlling
eutrophication and harmful algal blooms. Journal of Freshwater Ecology 30:5–24. https://doi.org/10.10
80/02705060.2014.994047
Pasztaleniec, A., Hutorowicz, A., Napiorkowska-Krzebietke, A. 2020. Rapid monitoring of cyanobacteria
in lakes – A case study in the Wel River catchment, Poland. Limnological Review 20:41-49
Randall, M.C., G.T. Carling, D.B. Dastrup, T. Miller, S.T. Nelson, K.A. Rey, N.C. Hansen, B.R. Bickmore,
and Z.T. Aanderud. 2019. Sediment potentially controls in-lake phosphorus cycling and harmful
cyanobacteria in shallow, eutrophic Utah Lake. PLoS ONE 14: 1–17. https://doi.org/10.1371/journal.
pone.0212238
Runkle, J., Kunkel, K., Champion, S., Frankson, R., Stewart, B., and Sweet, W. 2017. New Jersey State
Climate Summary. NOAA National Centers for Environmental Information, Silver Spring, MD. https://
statesummaries.ncics.org/chapter/nj/
Salerno, F., G. Viviano, and G. Tartari. 2018. Urbanization and climate change impacts on surface water
quality: Enhancing the resilience by reducing impervious surfaces. Water Research 144: 491–502.
https://doi.org/10.1016/j.watres.2018.07.058
Sharpley, A., H.P. Jarvie, A. Buda, L. May, B. Spears, and P. Kleinman. 2013. Phosphorus legacy: Overcoming
the effects of past management practices to mitigate future water quality impairment. Journal
of Environmental Quality 42:1308–1326. https://doi.org/10.2134/jeq2013.03.0098
Silva, T.F.G., B. Vinco-Leite, B.J. Lemaire, G. Petrucci, A. Giani, C, Figueredo, and N.D.O. Nascimento.
2019. Impact of urban stormwater runoff on cyanobacteria dynamics in a tropical urban lake. Water 11:
946 doi:10.3390/w11050946.
Søndergaard, M., R. Bjerring, and E. Jeppesen. 2013. Persistent internal phosphorus loading during summer
in shallow eutrophic lakes. Hydrobiologia 710:95–107. https://doi.org/10.1007/s10750-012-1091-3.
Souza, S. 2011. The Deal Lake Watershed Protection Plan. Prepared by Princeton Hydro, LLC. Ringoes,
NJ. 76 pp.
Taylor, G.D., T.D. Fletcher, T.H.F. Wong, P.F. Breen, and H.P. Duncan. 2005. Nitrogen composition in
urban runoff — Implications for stormwater management. Water Research 39: 1982–1989. https://doi.
org/10.1016/j.watres.2005.03.022
Tiedemann, J.A., M. Witty, and Souza, S. 2009. The Future of Coastal Lakes in Monmouth County. Monmouth
University Urban Coast Institute, West Long Branch, NJ, USA. 70 pp.
Trommer, G., M. Poxleitner, and H. Stibor. 2020. Responses of lake phytoplankton communities to changing
inorganic nitrogen supply forms. Aquatic Sciences 82. https://doi.org/10.1007/s00027-020-0696-2
Waajen, G.W.A.M., E.J. Faassen, and M. Lürling. 2014. Eutrophic urban ponds suffer from cyanobacterial
blooms: Dutch examples. Environmental Science and Pollution Research 21: 9983–9994. https://doi.
org/10.1007/s11356-014-2948-y
Urban Naturalist
J.E. Adolf, K. Saldutti, E. Conlon, E. Ernst, B. Heddendorf, S. Shifren, and R. Schuster
2022 No. 57
19
Wagner, K. 1978. Intensive lake study of Deal Lake, Asbury Park, NJ. Lakes Management Program, Division
of Water Resources, NJ Department of Environmental Protection, Trenton, NJ, USA.
Watson, S.B., P. Monis, P. Baker, and S. Giglio. 2016. Biochemistry and genetics of taste- and odor-producing
cyanobacteria. Harmful Algae 54:112–117.
Wei, Y., L. Yuanxi, L. Yu, X. Mingxiang, Z. Liping, and D. Qiuliang. 2020. Impacts of rainfall intensity
and urbanization on water environment of urban lakes. Ecohydrology and Hydrobiology 20:513–524.
https://doi.org/10.1016/j.ecohyd.2020.06.006
Xu, H., H.W. Paerl, B.Qin, G. Zhu, and G. Gao. 2010. Nitrogen and phosphorus inputs control phytoplankton
growth in eutrophic Lake Taihu, China. Limnology and Oceanography 55:420–432.