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Harmful Algal Bloom Intensity and Estuarine Nutrient Loading

BSEN 5220: Geospatial Technologies in Biosystems John Llorens | Paisley Guo

December 2, 2015

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Abstract: Analysis was conducted on publically available geospatial data to determine the strength of any correlation, should one exist, between harmful algal bloom cell count intensity and the nitrogen and phosphorous yields predicted by the SPARROW watershed model. Additionally, analysis was conducted on this data to examine any potential relationships between water temperature or salinity and bloom event intensity. The results of the analysis attempting to find a correlation between salinity or temperature and cell count were inconclusive. The results of the analysis attempting to find a correlation between total nitrogen or phosphorous loads delivered by the estuary and the average cell count of all samples within the estuary yielded low R2 values of 0.15 and 0.01, suggesting that the analysis was inconclusive. This is likely due to the fact that total load does not account for the area of the estuary. The results of the analysis attempting to find a correlation between total nitrogen or phosphorous yields and bloom event intensity suggested a correlation between nitrogen and phosphorous yields and the average bloom event cell count, with R2 values of 0.83 and 0.75, respectively.

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TABLE OF CONTENTS

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Introduction………………………….……………………..………………………2-3 !

Objectives……………….…..………………………………….……………………...3 !

Methods……..…………………….………………….………….…………………..3-5 !

Results……………………….………………..………………….………………….5-6 !

Conclusions……………….…………………………………………………………6-7 !

References……………………..………………………………………………………8 !

Appendix……………………………………………………………………………9-17 !

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Introduction:

Harmful algal blooms are a growing threat to U.S. coastal waters, capable of causing both

ecological and economic damage and endangering human health. Harmful algal blooms, often

referred to as “red tides,” are caused by a sudden and dramatic increase in the concentration of

biotoxin producing or oxygen depleting species of phytoplankton within estuarine, marine, or

fresh water. In large concentrations, these phytoplankton may cause enough oxygen depletion or

produce high enough concentrations of biotoxins to cause very high levels of wildlife mortality

in the affected area. As phytoplankton may contain photosynthetic pigments ranging from green

to red, harmful algal blooms may appear red or brown in color. This pigmentation is illustrated

in Figure 1.

Harmful algal blooms in the Gulf of Mexico are caused by high concentrations of the

phytoplankton Karenia Brevis. This species produces a biotoxin that paralyzes the central

nervous system of marine life to an extent where respiration is difficult, leading to high levels of

wildlife mortality (Texas Parks and Wildlife). The high levels of biotoxin and wildlife mortality

facilitates the growth of harmful diseases within surviving wildlife, rendering it unfit for human

consumption and causing other effects on associated ecosystems. Birds in the area may die after

consuming contaminated fish. Commercial fisheries may be closed to prevent harvesting of

contaminated seafood. Even air quality in the surrounding area may suffer, leading to unpleasant

symptoms in humans.

Harmful algal blooms are generally considered to be a naturally occurring phenomenon

(Texas Parks and Wildlife). As the growth of marine phytoplankton is limited by nitrogen and

phosphorous content within the water, it is reasonable to assume that areas which may contain

elevated levels of these nutrients may have an impact on the potential for harmful algal bloom

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events. These areas may include coastal upwelling zones or estuaries that transport large

amounts of agricultural runoff (Lam and Ho, 1989).

As water flows from the mainland into the Gulf of Mexico, it generally follows a path

which can be modeled. Areas that collectively discharge into a specific body of water are known

as watersheds. In-stream water nutrient loading is often modeled using statistical methods which

account for water quality upstream and watershed properties. One such model is known as

SPARROW (SPAtially-Referenced Regression On Watershed attributes) and it integrates

monitoring data with landscape information (Preston et al, 2009). This model can be used to

produce geospatial data pertaining to estuaries that deliver to the Gulf of Mexico. This model is

shown in Figure 2.

Objectives:

The objective of this analysis is to determine if any correlation can be made between

harmful algal bloom cell count densities within west coast Florida estuaries and the predicted

yearly yields and loads of nitrogen and phosphorous within each estuary as modeled by

SPARROW. Additionally, water temperature and salinity within the Gulf of Mexico were also

analyzed in relation to harmful algal bloom cell counts to determine a statistical correlation, if

any, exists.

Methods:

Geospatial data containing the locations, dates, cell counts of harmful phytoplankton, and

other varying information regarding samples of water taken is publically available from the

Florida Fish and Wildlife Conservation Commission and Florida Fish and Wildlife Research

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Institute. This data was acquired in the form of a GIS shape file, which illustrates the locations

where each individual sample was taken. In order to produce a sufficient sample size that falls

within the bounds of the SPARROW model GIS data for estuaries delivering to the Gulf of

Mexico, several collections of data spanning a wide range of dates was selected for analysis.

The sample data ranges from 08/18/1953 to 07/30/2015. This data was separated into several

shape files spanning approximately 10 years of data collection each.

As the selected data pertaining to harmful algal blooms is predominately collected within

the Gulf of Mexico and around the Florida coast, the geospatial estuary data generated by the

SPARROW model along the Gulf of Mexico coast was selected. This data is available from the

NOAA National Centers for Environmental Information. The data is also provided as a GIS

shape file.

ArcMap was utilized to view and analyze the selected data. Once the SPARROW model

geospatial data was imported into ArcMap, the individual polygons along the Gulf of Mexico

coast were first filtered to eliminate all polygons lying outside of Florida’s state boundary.

Additionally, polygons that had not yet been modeled for nitrogen and phosphorous yields and

loads were also excluded. Finally, neighboring polygons within the same estuary were merged if

and only if the total nitrogen and phosphorous yields and loads were identical, so as to increase

the potential for additional sample sites to lie within the new larger polygon to provide a more

reliable cell count average.

The geospatial data representing the test sites during harmful algal bloom events was then

analyzed. As the data was provided in multiple packages spanning ranges of dates, feature

points representing harmful algal bloom samples were first merged into a single shape file and

the attribute tables were associated. The data was then filtered to exclude feature points deemed

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irrelevant for the objective. All feature points with a cell count of zero were excluded, as it was

determined that these may either represent samples that were not tested for cell count or were

tested and returned a result of zero. Feature points with a zero value for the salinity or

temperature attribute were assumed to have no data in that field, and subsequently excluded

when exporting the data tables from ArcMap for analysis of that particular variable. The cell

count density for each feature point with an associated temperature measurement was analyzed,

and then the cell count density for each feature point with an associated salinity measurement

was analyzed.

To determine a potential association between the intensity of harmful algal bloom events

and SPARROW modeled estuary nutrient yields, only feature points lying within the estuaries

were considered. The diffusion of nitrogen and phosphorous in the Gulf of Mexico after leaving

the estuary is likely influenced by several factors that may include currents, atmospheric

conditions and pressure, or temperature. It was therefore not deemed feasible to associate these

feature points with specific polygons by proximity or any other factor given the timespan over

which the sample data was collected and the number of factors that could influence these

associations should they exist. Each polygon representing an estuary with a unique nitrogen and

phosphorous yield and total load was then exported in a table, along with the average cell density

of all feature points representing harmful algal bloom samples that lie within that particular

polygon. This resulting table was then graphed and analyzed to determine a correlation, if any.

Results:

The results of the analysis conclude that the SPARROW watershed model has potential

to illustrate estuaries that are at high risk for particularly intense harmful algal bloom events.

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While harmful algal bloom events may be a natural occurrence and inherently unpredictable, it

does appear that nitrogen and phosphorous yields in estuaries by the upstream may influence the

intensity of these blooms, at least within the estuary itself or in the general vicinity of the

estuary.

Figure 3 can be compared with Figures 5, 6, and 7 and from these comparisons it can be

seen that the number of samples taken, which may be indicative of the number of harmful algal

bloom events, may be related to the phosphorous loads and yields and nitrogen yields in each

estuary. Comparing figures 3 and 4 suggest no relationship.

Figures 12 and 13 illustrate the cell count plotted against temperature and salinity,

respectively. These figures suggest very little relationship between these variables.

Figures 8 and 9 demonstrates that plotting the average cell count for all samples within

the estuary against the estuary’s total nitrogen and phosphorous loads delivered yields an R2

value of 0.15 and 0.01, respectively.

Figures 10 and 11 demonstrate that plotting the average cell count for all samples within

the estuary against the estuary’s total nitrogen and phosphorous yields achieves an R2 value of

0.83 and 0.75, respectively.

Conclusions:

The number of samples, while potentially related to the number of individual harmful

bloom events, is not indicative of such a statistic. Multiple samples may appear for the same

event, or no samples for a particular even may be present. While interesting, visual comparison

of Figures 3 through 7 does not offer conclusive evidence of a correlation between frequency or

number of bloom events and estuary nutrient yields.

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The apparent lack of relationship between salinity or temperature and harmful algal

bloom cell count intensity suggests that the analysis is inconclusive

The linear relationship and corresponding high R2 values seen in Figures 10 and 11 this

suggests a correlation between the average cell count density of a harmful algal bloom event and

the nitrogen and phosphorous yields of an estuary as predicted by the SPARROW model.

The analysis of estuary total loads delivered in relation to average cell count intensity was

also inconclusive, yielding very low R2 values. This is likely due to the fact that total load

represents the total amount of the nutrient delivered by the estuary, and does not account for the

water volume and the resulting concentration of the aforementioned nutrient.

The results of these analyses may illustrate the potential for use of watershed models such

as the SPARROW model in unexpected applications, and potentially illustrates the importance of

watershed modeling due to the impact that agricultural runoff may have on ecosystems,

economies, and human health in distant areas.

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References:

United States Department of the Interior and United States Geological Survey. 2 November

2011. Retrieved 2 December 2015. http://water.usgs.gov/nawqa/sparrow/index.html

Preston, S.D., Alexander, R.B., Woodside, M.D., and Hamilton, P.A., 2009, SPARROW

MODELING—Enhancing Understanding of the Nation’s Water Quality: U.S. Geological

Survey Fact Sheet 2009–3019

Texas Parks and Wildlife. 15 September 2015. Retrieved 2 December 2015.

https://tpwd.texas.gov/

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R²!=!0.15173!

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Cell!Co

unt(Ce

lls/Litre)!

Total!Nitrogan!Load!Deliverd(Metric!Ton/Yr)!

Figure!8:!Cell!Count!vs!Total!Nitrogen!Load!Delivered!

R²!=!0.00707!

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Figure!9:!Cell!Count!vs!Total!Phosphorus!Load!Deliverd!

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R²!=!0.83229!

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Figure!10:!Cell!Count!vs!Total!Nitrogen!Yield!

R²!=!0.75137!

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Figure!11:!Cell!Count!vs!Total!Phosphorus!Yield!

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Figure!12:!Cell!Count!vs!Temperature!

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Figure!13:!Cell!Count!vs!Salinity!

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! Appendix:

Figure!1:!Harmful!Algal!Bloom!“Red!Tide”!

Source:!http://strangesounds.org!!!!!!!!!!!! ! ! !

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Figure!2:!SPARROW!Watershed!Model!

! Source:!http://water.usgs.gov! ! ! !

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