Phytoplankton Bloom Stimulation in Florida Bay
Samuel A. Chang, Taimur Z. Ahmad, & Rebecca F. Terrett
Princeton University
Tuesday 14th May, 2013
Abstract
Using the canonical Redfield Ratio of 16:1 N:P of phytoplankton biomass, we tested
under what mixing conditions phytoplankton blooms were stimulated in Florida Bay. While
Redfield’s ratio has been a highly regarded scientific finding in scholarly research, it has yet to
be fully applied to and analyzed in the Florida waters, most specifically the Bay area. To provide
new experimental data, Redfield’s ideal ratio of 16:1 N:P was applied to Florida Bay. With this
rationale, a hypothesized 3:1 site E to A ratio of water was calculated; this ratio would create the
most algal growth, coordinate A being the most southern point while E being the most northern
point (See Figure 1). The main purpose of this application was to ascertain whether or not certain
inflows and outflows form a pattern of nutrient relocation. Furthermore, nutrient levels were
important to develop a theory on the origins of specific nutrients that have been proven to incur
and induce high levels of algae. As hypothesized, nitrogen was expected to be limiting at E while
phosphorous was expected to be limiting at A. Nitrogen and Phosphorous, being the most
important macronutrients in water contamination, were measured along these transects. With this
assumption, nitrogen was hypothesized as a major source of contamination in site E and
phosphorus a major source of contamination in site A. Coordinates, salinity, and water samples
from each corresponding point (total of five) moving from a southwest to northeast transect were
taken. Various treatments were used to test for Nitrogen and Phosphorous levels, growth rates,
chlorophyll levels, and nutrient levels. Testing utilized various methods to obtain the results:
fluorometer and spectrophotometer. Supporting our hypothesis as well as Redfield’s ratio, the
highest chlorophyll levels were measured at the point with 3:1 site E to A. In addition, the data
indicates that P was in fact the limiting reagent at both points A and E. Finally, it was concluded
that P-rich inflow from the Gulf was minor when compared to the N and P-rich waters from the
Everglades; this inevitably meant that most of the algal bloom related issues in the Bay waters
are being caused by nutrient contamination from the Everglades. Furthermore, our data indicated
that phosphorus was in fact the limiting reagent at both points E and A. This may point towards
phosphorus as a major cause for nutrient contamination. Further research would have to show
any correlation between nutrient levels along the five points. This study provides a
comprehensive application of Redfield’s ratio to the Florida Bay ecosystem and may help future
researchers develop policies to help sustain the survival of Florida.
1
Introduction
Human activities have polluted the pristine waters of Florida ever since colonists settled
the land in 1521. Since then, inhabitants have attempted to tame its waters, draining the
Everglades by constructing various canals and lakes. For the purpose of agriculture and
residential vacation hot spots, much of the land’s natural form has now been stripped and
changed. With this in mind, it is no surprise that the biological consequences have been large.
Specifically, the health of the Florida Keys is of great concern for scientists. With the increase of
infrastructure and biological waste coming from both pollution through waste waters and
agricultural run offs, enriched nutrients have been steadily flowing within the Keys, causing an
increase in algal blooms. This inevitably leads to harm in coral reefs and tropical sea grass beds.
While these types of ecosystems can withstand some levels of nutrient enrichment
without serious ecological impact, the steady increase of microalgae growth have both decreased
the dissolved oxygen levels and increased the amount of photosynthesis in the waters. This has
caused degradation in wildlife biomes underneath the water’s surface. Phosphorus and nitrogen
levels are said to be major culprits of this degradation. Increased levels of phosphorous and
nitrogen have induced these drastic changes in the natural ecosystem and is now a prominent
issue in Florida. While scientists continue to study the impacts of water pollution in Florida,
research regarding the origins of such nutrients has led them to believe that the excess of
nitrogen originated from the Everglades outflow of fertilizer-enriched waters from agricultural
plants around Lake Okeechobee. Most interestingly, researchers have hypothesized that the
increased phosphorus levels come from inflows from the Gulf of Mexico (Gilbert, Heil, Madden,
Rudnick, Boyer & Seitzinger). This inevitably provides the necessary components for algal
blooms to flourish in this new man-altered ecosystem.
Thus, it is imperative that scientists continually study the waters surrounding Florida. Not
only do these records provide new insight on ecosystem degradation on the outskirts of South
Florida, it also provides an indication of water quality in the Everglades itself. Before these
nutrients can be assessed, however, a basic understanding of Nitrogen and Phosphorous ratios is
needed to form the rationale for the experiment. According to The Everglades Handbook:
Understanding the Ecosystem by Thomas E. Lodge, Lodge showed that nitrogen was the limiting
nutrient in the western side of Florida Bay and phosphorus was the limiting reagent in the central
to eastern borders of Florida Bay. Using such research as the basis for this experiment, it is thus
2
hypothesized that N concentrations would have greater ecological impact on the Bay farther
away from the Everglades and P concentrations would have greater influence on Florida Bay
closer to the Everglades.
In addition, specifically, the Redfield ratio is of great importance to the scientific
community when speaking of nutrient concentrations. Studied and confirmed in 1934, Alfred C.
Redfield analyzed thousands of biomass samples from various ocean regions in order to see if
there was a relationship between nutrient levels and organic matter. Surprisingly, Redfield found
a conserved ratio that scientists now use to determine which nutrients, if any, are limiting in an
aquatic ecosystem. This ratio shows that organic matter consisting of phytoplankton and algal
growth seem to reach its maximal accumulation at an N:P ratio of 16:1. This finding has been
applied to phytoplankton accumulation among coastal shores such as the Gulf of Mexico and the
Mississippi River (Lentz, 2010). Previous literature has also conducted similar experiments
testing the validity of the Redfield ratio, even in soil microbial biomass (Cleveland & Liptzin,
2007).
His research can be applied to the Florida Keys. Seeing as algal blooms have become
more and more prevalent within the Florida ecosystem, it seems rather intuitive that such
research should be applied and analyzed in this location.
With this basic understanding, this paper is set to apply the Redfield Ratio of N:P that
would induce the highest chlorophyll levels, forming our second hypothesis. Traveling from a
transect of points A to E, it is hypothesized that the point between these transects with 75% water
from site E and 25% from site A would be the point in which chlorophyll levels were highest
(see Figure 1). This hypothesis was based off of calculations derived from the 16:1 ideal ratio.
In other words, a 3:1 site E:A ratio of water mixture should give an approximately 16:1 N:P
ratio. The methods section details the way this determined.
Through mapping out and testing the area that would induce the most phytoplankton
growth, this experiment’s implications are far-reaching. By looking at which water inflows were
promoting the most growth, we were able to analyze which water inflows were most relevant for
causing algal bloom (i.e., the Bay or the Gulf), and what nutrients (N or P) were most important.
Not only does it provide previous knowledge to scientists regarding the nutrients present in the
keys, it also sheds new light on the origins of the excess nutrient inflows. Furthermore, the
Redfield ratio may show which nutrients are limiting and how future policy makers identify and
3
solve the issue. Providing an approximate location where these blooms are accumulated may also
allow for a more concentrated water treatment.
Methods
Gathering data for this experiment consisted of taking water and chlorophyll samples in
Florida Bay and in the mangrove swamps adjacent to the Bay on the dates of March 17th and
18th, 2013. Starting on the key of Islamorada, we took a motorboat northwards through the Bay,
sampling at five points. We later took samples in the mangrove swamp around Coot Bay pond
via canoe.
From Islamorada we stopped at five points getting progressively closer to the Everglades
(Figure 1). At points A, C, and E we took two liters of water using a water trap dropped over the
side of the boat. These two liters were for later inoculation or mixing. At every site (not just A,
C, and E) we also took an additional two liters for filtration on board the boat. One liter of water
was filtered through a 47 mm diameter glass fiber filter (with a pore size of about 0.7 microns)
using a hand-pump and the filter then folded and stored in tin foil for later chlorophyll analysis.
An additional 50 ml of water was filtered using a syringe and a 25 mm diameter glass fiber filter
of the same pore size and stored in a 50 ml centrifuge tube for later nutrient analysis. Both of
these types of samples were frozen shortly after being taken. Salinity readings and GPS
coordinates were also taken at every site. All water samples were taken at a depth of one meter.
The boat travelled 30 minutes between each point, which led to approximately five km (north to
south, not true distance) between each sampling site (plus or minus a kilometer or two). The
exception to this was the distance between site E and F (i.e. between the Bay itself and the
mangrove swamp), which was around 8 km.
Collection in the mangrove swamp was similar and occurred the day after the collection
in Florida Bay. We canoed into Coots Bay pond and took a sample directly in the actual swamp
by hand (the water was too shallow for a water trap). In the mangroves we only took one 50 ml
filtration sample (with the same filter size as above), salinity readings, and GPS coordinates. We
took these samples from two points: in the mangroves themselves and further out in the deeper
open water bay.
The same day as the Florida Bay collection we took an initial fluorescence reading using
a Turner fluorometer with an in situ chlorophyll filter and took that initial reading to be
representative phytoplankton level data for all our following mixtures and inoculations since no
4
growth was possible immediately after creating the mixtures and inoculations. The mixtures
were all made in 500 ml, clear, hard plastic Nalgene bottles.
The ratios were as follows: 400 ml of sample A to bottle one, 400 ml of sample B to
bottle two, 400 ml of sample C to bottle three, 400 ml of sample A to bottle four with 0.4 ml of
1.15 mM K2HPO4 solution added (i.e. adding P), 400 ml of sample C to bottle five with 0.4 ml of
20 mM NaNO3 solution added (i.e. adding N), 400 ml of sample A to bottle six with 0.4 ml of 20
mM N concentrate and 0.4 ml of 1.15 mM P concentrate (for Redfield’s 16:1 ideal ratio of N to
P), 400 ml of sample C to bottle seven with 0.4 ml of 20 mM N concentrate and 0.4 ml of 1.15
mM P concentrate (for the same reason as above), 40 ml of sample A with 270 ml of sample C
(6.75:1 C:A ratio) to bottle eight, 100 ml of sample A with 300 ml of sample C to bottle nine (3:1
C:A ratio), and finally 200 ml of both A and C sample to bottle ten (1:1 ratio of C:A). The
mixture for bottle nine was chosen to simulate Redfield’s ratio. Using the ratio N:P = 16:1 =
(N1*f + N2*(1-f))/(P1*f + P2*(1-f)) where N1 and P1 were N and P concentrations (in µM) at
the inflow from the Everglades to Florida Bay and N2 and P2 were N and P concentrations at the
inflow from the Gulf of Mexico (i.e., roughly the northern and southern ends of our vertical
transect), we solved for variable f, which gave the ratio of Everglades inflow water to Gulf
inflow water (in other words, N excess water to P excess water) that would most closely simulate
a N:P ratio of 16:1, therefore producing the most growth. The expected N and P data was taken
from a problem set. (Morel-Kraepiel, A., 2013, p. 1-2)
Each bottle was made to test a different aspect of conditions in the Bay. Bottles one, two,
and three were essentially controls (pure water). Bottles four and five were to test the limiting
reagent (N or P was added, growth or non-growth was observed). Bottles six and seven were to
test Redfield’s ratio and also to test which water source led to the most pronounced growth, and
for what reasons. Bottles eight, nine, and ten were designed to simulate different potential
mixings of the two inflows (i.e. a mixing simulating Redfield’s ratio, and equal mixture of
Everglades and Gulf water, and a test case of excess Everglades water).
After creating these mixtures all of the bottles were inoculated using water from the
filtered (50 ml filtered) sample taken at point B. 2 ml of this sample were added to every bottle,
except bottle eight, where only 1.55 ml was added (this was to preserve proportionality – we ran
out of pure sample and had to downsize bottle eight, leading to the odd ratios of 6.75:1, etc.).
5
The fluorescence of this inoculation sample was also taken to ensure that enough phytoplankton
were present to ensure growth.
To store these samples we wanted to simulate natural growth conditions. In order to do
this the bottles were individually wrapped in black plastic mesh (only one layer) to shade them.
The shading was to simulate the effect of the water being originally at the depth of one meter.
After being tightly sealed the bottles were left in a pool except for when being sampled. They
floated in the warm (around 18-20 degrees C) pool all day and night and so got natural sunlight
patterns. Once a day the bottles were sampled for fluorescence (24 hour intervals). The
spectrophotometer was started 30 minutes prior to testing to warm it up. For each test 2 ml of
sample was taken from the respective bottle and used to rinse out a glass test tube. The rinse
water was discarded and a new 2 ml of sample was placed in the tube. This was the sample used
to read fluorescence. This process was repeated for all ten bottles every night.
After five days of growth every bottle had its remaining contents completely filtered out
using the 47 mm glass fiber filters. These filters were collected, stored in tin foil, and frozen for
later chlorophyll level analysis.
Back in the lab we proceeded to do analysis of chlorophyll, nitrogen, and phosphorous
levels. On March 25th we performed a persulfate digestion on our samples. Glass vials (one for
each sample and three blanks) were pre-combusted for a few hours at 500°C to remove organic
material, and the caps to those vials were soaked in methanol water for a few hours also to
remove any organic N and P. Both caps and vials were then rinsed with Hydro Pure water to
remove inorganic N. Once ready, all the vials were labeled with their respective sample site. 12
ml of sample was put into each vial (Hydro Pure water for the blanks). This was done with a
pipette, which was rinsed twice with Hydro Pure water between each transference. The order of
transference was done in our expected levels of lowest chlorophyll level to highest chlorophyll
level in an attempt to avoid contamination.
After transferring the samples a new pipette tip was attached. The tip was rinsed and
then three ml of the persulfate oxidizing solution was added to each vial. The vials were capped
immediately after the solution was added. All the samples were then autoclaved for 55 minutes
at 120 degrees Celsius and then stored at room temperature for further analysis.
After creating the persulfate digestions, we moved on to analyzing chlorophyll via the
filters we had collected previously. Each filter was put into a glass tube, and two further glass
6
tubes were used as blanks. Then, six ml of a solution of 90% acetone (or nine parts acetone to
one part water) was added to each non-blank tube. For the blanks, the 9:1 ratio was kept but with
a different proportion of 5.4 ml of acetone to 0.6 ml of water. After these preparations all the
tubes were capped, and parafilm was wrapped tightly around all the tops. The samples were then
refrigerated.
A few days later on March 26th we took fluorescence readings for the filter samples. The
process for this was identical to the way we had done the readings in Florida: two ml of sample
was added to a glass vial, the vial was rinsed with it, and the sample discarded. A further two ml
were then added and the reading taken in a warmed-up spectrophotometer.
Later in the week (April 1st) we took PO4 readings using a colorimetric assay. First we
gathered glass test tubes for all the persulfate solutions (which would give TP, or total
Phosphorous, levels), pure samples (which would give orthophosphate levels), standards, and
blanks. The solutions were prepared as follows: three ml of both the persulfate solutions and
pure samples were taken using a micropipette (the tip was changed each time) and transferred to
pre-labeled test tube. Two blanks were also prepared (pure water and water with persulfate).
Then, under the hood, 300 µL of mixed reagent (PO4(3-)) was added to each tube. Samples for
creating the standard curve were also made: like the regular solutions, three ml of each standard
(0.5, 1, 5, and 10 µM as well as a blank) were added to separate tubes, labeled, and then mixed
with 300 µL of mixed reagent. After creating these various solutions all the tubes were mixed in
a miniroto for a few seconds. They then sat on the lab table for 30 minutes. This whole time we
were very careful to not touch the bottom of the tubes in order to keep the spectrophotometer
readings as accurate as possible.
To take the readings, the spectrophotometer was set at a wavelength of 885 nanometers.
It was then zeroed with milliQ water. Then, starting with the reagent blank and going then to the
standards, pure samples, and finally persulfate solutions, we took absorbance readings for each
tube.
After taking these readings we created our standard curve and calculated the levels of TP
(organic P) and Orthophosphate (inorganic P) in our samples. To do this the five points of the
standard curve were first plotted using excel and the equation of the line (in the form of abs =
m*conc. + b) taken. The y variable was the absorbance as recorded by the spectrophotometer.
7
Solving for x (conc.) gave the TP concentration. Orthophosphate was just the absorbance
reading.
Next week, on April 8th, we did analysis for N levels. This too was using a colorimetric
assay. Just as with the week before all the requisite tubes were acquired and labeled (pure
samples to find Nitrate (inorganic N) levels, persulfate samples to find TDN, or total dissolved
Nitrogen levels, two blanks, and four standards). In each plastic centrifuge tube was 0.15 g of
Cadmium. Using a micropipette five ml of the respective samples or standards were added to
each tube, with the tip being changed each time. Then 330 µL of an Ammonium Chloride
solution were added to each tube. The tubes were capped and then put in a horizontal shaker for
60 minutes.
Once the shaking was finished, the tubes were centrifuged for about a minute to pellet the
Cadmium. Then, using a micropipette and being careful not to take up the Cadmium 3.3 ml of
each solution was transferred to separate labeled glass test tubes. 167 µL of color reagent were
then added to each tube, and all the tubes were vortexed briefly. The tubes then rested for ten
minutes.
To take the N level readings, the spectrophotometer had its wavelength set to 543
nanometers. The spectrophotometer was zeroed on the reagent blank (the pure water blank).
After taking readings for the pure samples and standards, the spectrophotometer was re-zeroed
using the persulfate blank, and then all the persulfate samples were processed.
Just as with the P readings, by plotting the standard curve, taking the equation of the line,
setting y equal to the absorbance readings, and solving for x, we were able to calculate TDN
levels in our samples. Nitrate was just the absorbance reading.
A further calculation we did that day was for growth rate in our various mixed, pure, and
nutrient spiked samples of Florida Bay water. To do this we first took the natural logarithm of
each of our fluorescence readings, which had previously been plotted on excel. After this, we
plotted these natural logarithms onto excel graphs. We then deleted any points on the graphs that
were not in the growth phase (i.e., a point which would take away from the actual growth rate).
With just these points remaining we added trend lines to the graphs and had the equations
displayed. The growth rate was then the m variable in the equation for a line.
The final part of the experiment was to analyze data on metals collected in the
Everglades. Using our water samples from the Bay and the mangroves, the levels of Mo, V, and
8
Fe were in those samples was found in counts per second using an ICPMS. Then using a
calibration curve (in the same way as for finding N and P levels), this data was converted into
ppb (parts per billion). Furthermore, rate of N2 fixation was measured using the mangroves
samples. An acetylene reduction assay was performed on the samples from sites F and G and
ethylene levels were measured using a FID gas chromatograph.
Results
Figure 1. Locations of the 7 sampling sites in Florida Bay. This map was created by inputting
the GPS coordinate data (recorded by the boat at each site) into the ArcMap program of ArcGIS.
9
Table 1. Experiment set-up.
Bottle Number
1
2
3
4
5
6
7
8
9
10
Incubations
400 ml A
400 ml C
400 ml E
400 ml A + 0.4ml of 1.15mM P
400 ml E + 0.4ml of 20mM N
400 ml A + 0.4ml each of 1.15mM P and
20µM N (16:1 ratio)
400 ml E + 0.4ml each of 1.15mM P and
20µM N (16:1 ratio)
270 ml E + 40 ml A
300 ml E + 100 ml A
200 ml E + 200 ml A
Chlorophyll Data:
Table 2. Fluorescence Readings.
Bottle
Number
17-Mar
18-Mar
19-Mar
20-Mar
21-Mar
1
12.19
10.23
15.31
20.23
19.06
2
12.19
10.18
14.76
16.28
14.85
3
12.19
16.89
27.84
19.7
12.81
4
12.19
10.53
18.96
33.06
25.36
5
12.19
15.67
26.52
24.14
15.49
6
12.19
12.01
18.5
26.44
42.57
7
12.19
15.33
58.13
423.25
797.65
8
12.19
13.35
17.59
12.86
18.44
9
12.19
14.88
20.4
20.37
30.79
10
12.19
11.51
11.84
9.1
11.76
Time (hr)
t=0
t = 23.25
t = 47.75
t = 72.75
t = 93.75
10
Figure 2. Fluorescence Levels for Bottles 1-3 over Time. All three bottles display the typical
phases of growth: lag, exponential, and stationary phases, yet bottle 3 experiences a greater fall
off in fluorescent readings over time than the other two.
11
Figure 3. Fluorescence Levels for Bottles 4-7 over Time. The fluorescence readings for bottles
4-6 can be viewed more closely in the inset. Bottles 4 and 5 exhibit the three phases of growth,
but bottle 6 and 7 both lack a stationary phase, still in exponential phase.
12
Figure 4. Fluorescence Levels for Bottles 8-10 over Time. Both bottle 8 and 9 show some
growth, whereas bottle 10 shows little to none growth. None of the three bottles exhibit all of the
classic growth phases in the time frame of the experiment, as they all lack the stationary phase,
and there are no clear exponential phases of growth.
Table 3. Growth Rates for Incubation bottles 1-10.
Bottle
Growth Rate (day-1)
1
0.331
2
0.228
3
0.415
4
0.554
5
0.391
6
0.420
7
1.411
8
0.185
9
0.259
10
0.000
Figure 5. Growth Rates determined from the fluorescent readings of Incubation bottles 1-3.
In order to achieve a line that would fairly represent the exponential phase from the growth in
each of the incubation bottles, certain data points were excluded. The natural log of the
fluorescent readings at both t = 0 and t = 93.75 were omitted for both bottle 1 and 2; at t = 72.75
and t = 93.75 for bottle 3.
13
Figure 6. Growth Rates determined from the fluorescent readings of Incubation bottles 4-7.
In order to achieve a line that would fairly represent the exponential phase from the growth in
each of the incubation bottles, certain data points were excluded. The natural log of the
fluorescent readings at both t = 0 and t = 93.75 were omitted for bottle 4; at t = 72.75 and t =
93.75 for bottle 5; at only t = 0 for both bottle 6 and 7.
Figure 7. Growth Rates determined from the fluorescent readings of Incubation bottles 810. In order to achieve a line that would fairly represent the exponential phase from the growth in
each of the incubation bottles, certain data points were excluded. The natural log of the
14
fluorescent readings at both t = 72.75 and t = 93.75 were omitted for both bottle 8 and 9; at t =
72.75 for bottle 10.
Phosphorus Data:
Figure 8. TP and Orthophosphate Concentrations Traveling North to South in Florida
Bay. The TP and orthophosphate concentrations from the seven sampling sites were calculated
by coupling the standard curve equation, y = 0.0224x (not shown), and the absorbance data. Sites
G and F were not of direct interest as they were not in the bay (see Figure 1) so the
concentrations in µM were plotted against distance in km between the sites starting at site E
which was at distance = 0 km, traveling south in Florida Bay. Except for the data at site B, which
is likely to be experimental error, the orthophosphate concentrations are consistently lower than
the TP concentrations, which is what was to be expected.
15
Nitrogen Data:
Figure 9. TDN and Nitrate Concentrations Traveling North to South in Florida Bay. The
TDN and nitrate concentrations from the seven sampling sites were calculated by coupling the
standard curve equation, y = 0.0391x + 0.002 (not shown), and the absorbance data. Sites G and
F were not of direct interest as they were not in the bay (see Figure 1) so the concentrations in
µM were plotted against distance in km between the sites starting at site E which was at distance
= 0 km, traveling south in Florida Bay. Except for a couple of points (at site D and F), the nitrate
concentrations are lower than the TDN concentrations, which is what was to be expected.
Figure 10. N vs. P for sites E-A.
16
Metal Data:
Calibration Curve Equations:
Fe: y = 13012x
Mo: y = 4290.8x
V: y = 8765.5x
Figure 11. Concentration of Metals Fe, Mo, and V traveling North to South in Florida Bay.
The concentrations of three metals (iron, molybdenum, and vanadium) from the seven sampling
sites were calculated by coupling the standard curve equations (equations shown above; curves
not shown) and the intensity data collected from the ICP-MS. Sites G and F were not of direct
interest as they were not in the bay (see Figure 1) so the concentrations in ppb were plotted
against distance in km between the sites starting at site E which was at distance = 0 km, traveling
south in Florida Bay. While the curves for Fe and Mo are true to size, that of vanadium’s has
been multiplied by 10 in order to magnify its activity. Both the concentration in ppb of the metals
Mo and V behave in the same fashion throughout the course of the bay. Fe, on the other hand,
follows a trend that is the inverse of that of Mo (and V).
17
Figure 12. Mo vs. V for sites E-A.
Figure 13. N vs. Fe for sites E-A.
18
Figure 14. N vs. Mo for sites E-A.
Table 4. Summary of Data Collected, Organized by Site Location.
Chlorophyll
Data from
Salinity Filter (rfu)
Nitrate
Concentrations (µM)
TDN
Orthophosphate
TP
Site
GPS coordinates
N
W
G
25°11.253'
80°54.213' 18-Mar
15
0.358
0.128
0.08929
0.0893
F
25°11.155'
80°54.068' 18-Mar
15
0.818
1.36
0
0.179
E
25°06.865'
80°28.018' 17-Mar
35
1049.37
0.102
1.08
0.04464
0.223
D
25°03.805'
80°31.310' 17-Mar
32
710.93
0.537
0.486
0
0.179
C
25°01.068'
80°32.898' 17-Mar
35
1321.2
0.716
1.54
0
0.446
B
24°58.488'
80°37.465' 17-Mar
40
524.27
0.486
1.02
0.2679
0.045
A
24°56.137'
80°42.454' 17-Mar
40
1074.98
-0.0512
0.409
0
0.223
Date
19
Growth
Rate
(day-1)
0.415
0.228
0.331
Figure 15. P vs. Chlorophyll for sites E-A.
Figure 16. N vs. Chlorophyll for sites E-A.
20
Discussion
Composed solely of seawater taken directly from Florida Bay, incubation bottles 1-3
served as controls for this experiment. The results from bottles 4-10 can be compared to the
results obtained from the controls to see what exactly the effects of the various incubations were.
Despite this, as both figure 2 and table 3 demonstrate, the water taken from site E experienced
the greatest fluorescent readings (a peak of 27.84 rfu) and growth rate (0.415 day-1) out of the
three controls. This means that the most northern water out of these three sites (site A, C, and E)
experienced the greatest algae growth, and has an environment more conducive to growth.
Incubation bottles 4 and 5 were set up for the sole purpose of identifying the limiting
nutrient at site A and E. Based off of previous scientific studies conducted about the Everglades,
multiple assumptions were in mind before beginning this lab experiment. One of these
assumptions was that the algal growth in the water at site E (exiting the Everglades) was limited
by phosphorus, whereas the algae growing at site A (southern point of Florida Bay) was limited
by nitrogen. Of course the experiment could not automatically assume these facts, and thus the
limiting nutrient was tested at each site by adding 0.4ml of 1.15µM phosphate to 400ml of water
collected at site A (bottle 4), and by adding 0.4ml of 20µM nitrogen to 400ml of water collected
at site E (bottle 5). If the growth rates between these two bottles are compared to their respective
control bottles (bottle 1 compared to bottle 4, and bottle 3 to bottle 5), the resulting values are
quite interesting. The growth rate increases from 0.331 day-1 to 0.554 day-1 from bottle 1 to 4,
implying that adding phosphate improved algal growth at site A, yet this does not match the
expectations for nitrogen was believed to be the limiting nutrient. At site E the growth rate
diminishes very slightly from 0.415 day-1 to 0.391 day-1 from bottle 3 to 5. This suggests that
adding nitrogen had no beneficial effect, so nitrogen cannot be the limiting nutrient and instead
phosphorus is. This result was what had been assumed from the start. Therefore the data appears
to support the claim that phosphorus is the limiting nutrient at both site A and site E.
The purpose of incubation bottles 6 and 7 was to explicitly test Redfield’s ratio. Bottle 7
(which was 400ml E plus the 16:1 ratio of N:P) experienced not only greater growth than bottle
6, but had the greatest growth rate overall with a growth rate of 1.411 day-1. (The second greatest
growth rate overall was observed in bottle 4 (0.554 day-1) and then bottle 3 (0.415 day-1)). As the
values in the last column of table 2 explicitly show (in addition to the data shown in table 3 and
Figures 2-4), no other incubation could compare to the chlorophyll growth monitored in bottle 7
21
which was still soaring at a fluorescent reading of 797.65 rfu at t = 93.75 (when the experiment
was stopped). The highest fluorescence reading observed in bottle 6 was 42.57 rfu. Therefore if
the same volume of water from two different sites had the same 16:1 N:P treatment, and yet
differed so vastly in chlorophyll production, it is a reasonable assessment that water at site E has
the nutrient composition which is favorable for algal growth. With Redfield’s ratio in mind, to
determine whether or not the ratio is accurate, the results from bottles 6 and 7 need to be
compared to the controls. The large change in growth rates between 400ml E versus 400ml E +
16:1 N:P (bottle 3 vs. bottle 7), which is from 0.415 day-1 to 1.411 day-1, supports Redfield’s
ratio as significantly more algae growth was observed. This being said, the information gathered
from the incubation of bottle 6 neither greatly supports nor refutes Redfield’s ratio, as the growth
rate increased by less than 25% (the control experienced a growth rate of 0.331 day-1 compared
to 0.420 day-1 from bottle 6). Although this was not the kind of increase in algae production seen
with bottle 7, it is nevertheless an increase so overall this experiment confirms Redfield’s ratio.
Finally, the last three incubation bottles (8-10) were engineered to test Redfield’s ratio as
it applied in real life to Florida Bay, or in other words, to test the hypothesis. These three bottles
all involved mixing ratios of water from sites A and E to simulate an area in the bay that exists
but could not be logically reached or located to be tested for confirmation. The greatest growth
was expected to be observed in bottle 9 (3:1 ratio of E:A) as it reflected the area in the bay which
would naturally have a 16:1 ratio of N:P based off of previously stated assumptions about
nutrient concentrations associated with geography. This was observed (see Figure 4). Bottle 9
had a growth rate of 0.259 day-1, which was greater than the growth rates noted from the 6.75:1
and 1:1 ratios in bottles 8 and 10 respectively. Considering it is both theoretically and physically
impossible to test the fluorescent readings and growth rates of every single type of ratio
imaginable, especially given the time and travel restraints imposed on this experiment, the results
achieved do verify the hypothesis in the simplest sense: the application of Redfield’s ratio
induced more growth than any other ratio. Yet greater growth was still observed in 2 of the 3
controls (at the two sites alone without mixing) than seen in bottle 9, which was supposed to be
the ideal mixture. In this sense, while the hypothesis has not been technically disproved, it has
not been proved.
In addition to chlorophyll measurements, nutrient concentrations were also gauged. In the
place of using incubation bottles, the nutrient data was calculated from samples collected
22
immediately in the field. And instead of just 3 sites used for the first half of this lab (A, C, and
E), the second part concerning nutrients involved 7 sites referred to as A-G (see Figure 1). This
being said, only sites E-A were really focused upon when looking at trends, as sites G and F do
not give a good representation of Florida Bay in comparison to sites E-A. A few more
assumptions were made about nutrients before starting the lab, which shaped predictions about
the results. It is well known that nitrogen is found in excess in the Everglades, and because of
this, nitrogen concentrations were expected to be highest at the most northern sites and decrease
along a geographical transect moving from north to south through Florida Bay. Accordingly, a
similar relationship between the concentration of phosphorus in Florida Bay and the
geographical coordinates was expected, but in the opposite manner to nitrogen. With the
assumption that phosphorus was the limiting nutrient at site E, it was predicted that the total
phosphorus (TP) concentrations would rise along the transect when traveling south in Florida
Bay. Neither of these predictions was accurate. As figure 9 shows, there was not a linear pattern
associated with geographical location. The highest total dissolved nitrogen (TDN) concentrations
were found at site C with 1.535 µM, closely followed by site F with 1.355 µM. And the lowest
TDN concentrations are found at sites G, A, and D respectively. As the graph shows, the
concentration decisively dips at site D, which completely rejects the possibility that there is a
linear relationship between transect location and nitrogen concentration. However, site D has a
greater nitrate concentration than TDN, which cannot logically be true. And if the TDN
concentration at site D was deemed to be experimental error, then the trend for nitrate nearly
perfectly mimics that of TDN. Nitrate concentration is lowest at the outer edges, most north and
south points (E and A), and rises and drops in between, reaching a peak at site C at 0.716µM.
For phosphorus, there appears to be no pattern that suggests a geographical relationship.
The greatest TP concentration was observed at site C with a concentration of 0.4464 µM, which
is in fact exactly twice the concentration noted at site A (0.2232 µM), which clearly indicates no
increase of TP along a transect moving south in the bay. The TP concentration is the same (0.223
µM) at sites A and E, and both rises (site C) and drops (site D and B) in between: there is no
obvious trend. Orthophosphate concentration remains low for all the sites except for site B,
where it is greater than the TP concentration. Because this cannot be the case (TP must always be
greater), this data is most likely due to experimental error, so it is difficult to know what the real
orthophosphate concentration is at site B. Either way there is no linear relationship between the
23
concentration and location along the transect, with three of the sites lacking orthophosphate
altogether. Figure 10 is another representation of the inaccuracy of the assumptions. If nitrogen
decreased along the transect while phosphorus increased, the graph of nitrogen plotted against
phosphorus should show this inverse relationship. Yet figure 10 demonstrates no relationship
between the concentrations of the two nutrients.
Based on Redfield’s ratio and the fact that the algae bacteria require nitrogen and
phosphorus to grow, there should be an inverse relationship between the collected data on
chlorophyll (fluorescence readings) and concentrations of the nutrients at these sites; the greater
the chlorophyll growth, the fewer nutrients should be present because they have been used up for
this growth. While there appears to be no such correlation between the chlorophyll data in the
sixth column of table 4 (under the heading: “Chlorophyll data from filter”) and the TDN/nitrate
graph (Figure 16 shows no trend), the values from table 4 do match up with phosphorus
concentrations. However little of a pattern it seems to follow, the trend of the TP concentrations
is absolutely mimicked by the fluorescence readings for sites A-E. Starting at site E at 1049.37
rfu, the fluorescence drops slightly to 710.93 rfu, spikes up to 1321.2 rfu, down to 524.27 rfu,
and returns to 1074.98 at site A. Figure 15 directly reflects this positive correlation. These results
strongly propose a tight link between TP concentrations and algae growth: phosphorus seems to
have a greater effect on algae than nitrogen does. However, because the inorganic phosphorus
concentrations were so low, it can be concluded that most of the TP concentrations were indeed
bio-available organic phosphorus. This conclusion is rather puzzling. The large amount of
organic phosphorus may originate from algae sources themselves and account for the biomass
detected. This may provide an explanation for why there was more organic phosphorus in TP
than inorganic phosphorus.
Despite this agreement between data, unfortunately the information extracted from these
two graphs (Figures 8 and 9) contradicts the conclusions about Florida Bay drawn from the
incubation bottles’ fluorescence and growth rate data. The previous conclusion made about
limiting nutrients, which was made by comparing incubation bottles 4 and 5 to bottles 1 and 3
respectively, seems to be incorrect when these nutrient graphs are interpreted. Because the
concentration of nitrate at site A is a negative value, which means 0 µM in other words, and the
TP concentration is 0.22 µM, this heavily suggests that nitrogen must be the limiting nutrient.
Yet the increase in growth rates when phosphate was added to A implied phosphorus limited
24
growth originally. What is more is that the significant difference in the results from bottles 6 and
7 insinuated – based on the belief that phosphorus is limiting at both site A and E - that there
must be a much greater concentration of TP at site E than at site A for this to occur. But figure 8
reveals that the concentration is in fact identical at both sites. The conflicting data may in part be
due to the fact that the incubation bottles were inoculated with chlorophyll from another different
site entirely in order to have high enough fluorescence levels to be read. This step of the
experiment could have easily modified the growth rate data obtained from the incubation bottles,
explaining why it does not agree with the data acquired on site.
On top of the nutrients, the presence of metals was recorded as a final portion of this
experiment. From previous lab work and experiments, it has been noted that diazotrophs fix
nitrogen at different rates depending on the types of metals in their environment. Molybdenum is
preferential to vanadium, which is preferential to iron. Nitrogen is fixed from the atmosphere as
an alternative source to nitrate in the waters to support growth. Therefore molybdenum
concentrations would be expected to be the highest wherever growth rates are high and nitrate
concentrations are low. The same association would be expected for vanadium as well, but
because vanadium is less preferred/effective than molybdenum, its concentration should be low
throughout the bay. As figure 11 displays, these expectations were reasonably accurate. The
concentrations of Mo and V follow an almost identical trend throughout the bay (Figure 12
confirms this as, besides one data point, the concentrations of the two metals are correlated).
Molybdenum is highest at site E with a concentration of 0.266 ppb, then second highest at site A
with 0.232 ppb. Nitrate is indeed the lowest at site E and A (Figure 9), and for site E (where Mo
concentration peaks) the growth rates that are applicable are those of bottles 3 and 7, which are
two of the highest rates (table 3). Interestingly, the concentration of Fe from E-A is near to an
inverse of the trend of Mo/V. Not only this, but the Fe trend appears to be a mirror image of the
nitrate trend (Figure 9). Figure 13 confirms a positive correlation between nitrate and Fe
concentrations (with the exception of one site’s data). The relationship between Mo and nitrate
concentrations is shown in figure 14. The two appear to be inversely related: the lower the
concentration of nitrate, the higher the concentration of Mo. If Mo is indeed the preferred metal
environment for nitrogen fixation, this graph supports the concept that nitrogen fixation occurs at
low nitrate levels.
25
Salinity levels for sites E to A were also graphed in comparison to nitrogen and
phosphorus levels. Because the salinity readings had little variance, the data was omitted from
this report. Furthermore, there was no correlation at all between salinity concentrations and
nitrogen and phosphorus levels. However, it can be inferred that Everglades inflow may still play
a large role at both points A and E mainly because phosphorus was limiting at both locations.
Conclusion
We expected to see the highest growth rate in a mixture of 3:1 E:A water (as opposed to a
1:1 or 6.75:1 ratio) because that mixture best simulates Redfield’s ratio (based on our
assumptions about P and N inflow from the Gulf and Everglades). The water flowing in to the
Bay from the Everglades is carrying both N and P but our data from bottles four and five shows
that P is the limiting reagent at both points A and E. Bottles six and seven both had the exact
same Redfield’s ratio treatment, but only bottle seven – which was E water, whereas bottle six
was A water – had significant growth. What this should show is that the water flowing from the
Everglades is carrying the excess P needed to cause algal bloom in Florida Bay. By the time the
water has reached point A the level of P should be significantly reduced to the point that large
growth is diminished. This would show that water flowing in from the Gulf of Mexico cannot be
causing major P contamination.
However, in a contradiction to the above, our nutrient data showed no clear P or N trend
through Florida Bay. Basically both TP and orthophosphate levels were the same at the two
endpoints and spiked in between. The same trend held for nitrate and TDN levels, although for
N at least there was not a spike but a gradual rise and fall over sites D through B. In other words,
our nutrient transect graphs contradict the fact that P is the limiting reagent at both sites E and A.
At points E and A P is in fact in excess, with N at 0 µM at site A, according to our nutrient data,
despite the fact that our inoculation bottles support an opposite conclusion (growth rates
increased in A water when P was added, and did not change in E water when N was added,
showing that N was not limiting at E and that P was limiting at A).
The reasons for why this could be so are numerous. Disregarding experimental error,
seasonal differences in nutrient levels in the water (or even just differences with each tide) could
have influenced our data in ways we did not expect. It is possible that water inflow from the
Everglades and the Gulf change based on the time of year, or that the chemical make-up of that
inflow water changes seasonally. Furthermore, our assumptions about nutrient level inflows were
26
based on a single problem set. It is entirely possible that the data we took from this problem set
as our expected nutrient inflows was either rough or simply not seasonally accurate. A final
possibility is the nature of the transect. Though we moved a great distance south to north, we
also simultaneously moved quite far east, progressively further away from the Gulf inflow. This
could certainly have led to different nutrient levels than we expected.
However, if we consider only the inoculation bottle data we see stronger trends in support
of our hypothesis that Everglades run off is the source of nutrient pollution in Florida Bay. Either
way the inoculation data also shows that Gulf inflow is fairly insignificant, at least in the areas
that we tested. If the inflow from the Gulf was causing significant nutrient pollution then levels
of P would be far higher at our more southerly points, making them N-limited. Instead
chlorophyll levels track TP levels exactly throughout our samples from the Bay, while nitrate,
TDN, and orthophosphate levels had no clear correlation to chlorophyll samples taken directly
from the Bay. Since water from our northerly points (E, etc.) provoked much higher growth
clearly the nutrients allowing such growth must be coming from the Everglades. Furthermore, it
seems likely that the nutrient in question is P and not N as we originally suspected. Similarly, it
is significant to note that of our two Redfield’s ratio inoculation bottles, only the one made from
site E water had remarkable growth. This shows that the water closest to the Everglades inflow is
the most nutrient rich.
Overall our research produced conflicting results in regards to our hypothesis.
Chlorophyll levels taken directly from the Bay showed no clear trend and were nearly identical
at points A and E which suggests no significant difference in terms of chemical makeup between
these two sites. Our nutrient transect data for N and P supports this conclusion. This data would
seem to refute our hypothesis, namely it would appear the inflow from neither the Everglades nor
the Gulf was having any sort of significant impact on water composition along our transect.
However our inoculation data does in fact contain support for our hypothesis. E water,
both as a control and when modified to Redfield’s ratio, had a higher growth rates than A or C.
Bottles four and five showed that P was limiting at both sites A and E. And furthermore bottle
eight showed that our predicted ideal mixture of 3:1 E:A water did in fact produce the highest
growth rate of any of our pure water mixtures, supporting our expected levels of nutrient inflow
from the Everglades and the Gulf. The problem set we used as a basis for our inflow expectations
led us to believe that water entering from the Everglades was N-rich and P-limited, whereas
27
water entering from the Gulf was P-rich and N-limited. Our nutrient transect data does not
support or refute these points, but our inoculation data supports the first statement, namely that P
is limiting in terms of Everglades inflow. However, our data also suggests that Gulf inflow is Plimited and is in fact not much of a factor on growth in general. What this leads to is the
possibility that despite the Everglades inflow being N-rich, it is still the P contained by that water
that is causing algal blooms in the Bay, more or less independent of Gulf inflow.
The implications of our research are mainly in identifying the sources of nutrient
pollution in Florida Bay. Though nutrient pollution is only one possible explanation for algal
bloom, our work shows that inasmuch as nutrient pollution is an issue P is the main nutrient of
concern. Furthermore, P from the Everglades – and not from the Gulf – would appear to be the
main source of pollution, suggesting that current efforts to keep P levels in the Everglades at or
below 10 ppb are not succeeding. In the course of this experiment we were also able to confirm
Redfield’s ratio as being the optimal ratio of N to P for growth.
References
Cleveland, C., & Liptzin, D. (2007). C:n:p stoichiometry in soil: is there a ‘‘redfield ratio’’ for
the microbial biomass?. Biogeochemistry, doi: 10.1007/s10533-007-9132-0
Gilbert, P., Heil, C., Madden, D., Rudnick, J., Boyer, J., & Seitzinger, S. (n.d.). Florida bay:
Signs of ecosystem stress. Retrieved from
http://www.cop.noaa.gov/stressors/resourcelanduse/current/Glibert_Florida BayFinal.pdf
Lentz, J. (2010). Nutrient stoichiometry – redfield ratios. Retrieved from
http://www.sce.lsu.edu/cego/documents/reviews/oceanography/nutrient_stoichiometry.pdf
Lodge, Thomas E. (2010). The everglades handbook: Understanding the ecosystem
Morel-Kraepiel, A. (2013) “Homework 2 – Algal Bloom in Florida Bay.” Retrieved from:
https://blackboard.princeton.edu/webapps/portal/frameset.jsp?tab_group=courses&url=%
2Fwebapps%2Fblackboard%2Fexecute%2Fcontent%2Ffile%3Fcmd%3Dview%26conten
t_id%3D_1488401_1%26course_id%3D_149070_1%26framesetWrapped%3Dtrue.
Acknowledgements
We would like to thank our instructors Anne Morel-Kraepiel and Andrew Babbin for all the help
they gave us in our fieldwork and on the report itself. We would also like to thank Sven Kranz
for his help with our fieldwork.
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Honor Code
This paper represents our own work in accordance with University regulations.
/s/ Rebecca Terrett, Taimur Ahmad, Sam Chang
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