EVALUATION OF FLORIDA BAY SEAGRASS

AFTER HURRICANE IRMA

by

AUBREY LYNN LORIA

MICHAEL STEINBERG, COMMITTEE CHAIR

JULIA CHERRY

NICHOLAS MAGLIOCCA

A THESIS

Submitted in partial fulfillment of the requirements

For the degree of Master of Science

in the Department of Geography

in the Graduate School of

The University of Alabama

TUSCALOOSA, ALABAMA

2019

Copyright Aubrey Lynn Loria 2019

ALL RIGHTS RESERVED

ii

ABSTRACT

When Hurricane Irma made US landfall on the Florida Keys on September 10, 2017, the

category 4 storm became the first major hurricane to hit the state since 2005. This study

investigated the impacts that Irma had on seagrasses in Florida Bay – an estuary at the southern

outlet of the Florida Everglades that is crucial to the environment and economy of South Florida

but that is threatened by anthropogenic impacts on water quality. A massive seagrass die-off in

2015 left the bay with hypersaline water and sulfide-saturated sediment that was held in place by

the bay’s network of carbonate mud banks. The promise of rainfall and storm surge from a major

hurricane offered a chance to refresh the bay and begin the process of recovering from the die-

off. By comparing seagrass density and community composition from after the 2015 die-off to

after Irma, I found that seagrass cover has become more uniform and that species richness has

increased throughout the study area. Seagrass density was lost in some shallow sections of the

study area, but pioneer species Halodule wrightii had begun colonizing the disturbed areas,

indicating that water quality had changed enough to support the less salt-tolerant species. The

positive changes in seagrass density, distribution, and diversity after Hurricane Irma indicate that

the storm may have flushed out the hypersaline water left after the 2015 die-off that had been

limiting seagrass recovery for two years.

iii

DEDICATION

Dedicated to the memory of my hero, teacher, and grandfather, Don, who meant to make

me an artist but accidentally made me a scientist. Don passed away two weeks after I completed

the field research for this thesis, but the love and pride he showed for his grandchildren has

continued to encourage me in the months since.

iv

LIST OF ABBREVIATIONS AND SYMBOLS

D Density using the Braun-Blanquet Cover-Abundance scale

PSU Practical Salinity Units

RKB Rabbit Key Basin

TKB Twin Key Basin

< Less than

= Equal to

≤ Less than or equal to

v

ACKNOWLEDGMENTS

This thesis simply could not have been done without all the help I received from my

incredible mentors, family, and support system. First, I thank Dr. Michael Steinberg (Committee

Chairman), for accepting my request to join his lab and encouraging me to revisit the work of his

former graduate student, Cynthia “Jo” McGinnis. Thank you to Jo for providing the groundwork

that makes this comparison so interesting and for making a trip to come speak with me at the

University of Alabama while I was putting together my thesis proposal.

Thank you to Everglades National Park (ENP), South Florida Natural Resources Center

(SFNRC), and the Florida Bay Interagency Science Center (FBISC) for providing logistical

support for this thesis. More specifically, thank you to Matt Patterson of the SFNRC for not only

coordinating this thesis with NPS and FBISC, but also for making sure I never had any question

go unanswered, I never went without any equipment that he could provide, and I never felt alone

when I was so far from home. Thank you to Dr. Jed Redwine for advice on several

methodologies. Thank you to Troy Mullins for helping me acquire GIS datasets.

Thank you to Eduarda and Mima for providing me with free room and board (respectively) for

nine weeks while I conducted my research in South Florida. It was wonderful getting to spend

that time with both of you.

Finally, thank you to my parents for my life, my sister for my ambition, and Stirton and

Lita for my courage. Thank you all for getting me here.

vi

CONTENTS ABSTRACT ................................................................................................................................ ii

DEDICATION ........................................................................................................................... iii

LIST OF ABBREVIATIONS AND SYMBOLS ...................................................................... iv

ACKNOWLEDGMENTS .......................................................................................................... v

LIST OF TABLES ................................................................................................................... viii

LIST OF FIGURES ................................................................................................................... ix

CHAPTER 1 INTRODUCTION ................................................................................................ 1

CHAPTER 2 BACKGROUND .................................................................................................. 5

2.1 Florida Bay Ecosystem ..................................................................................................... 5

2.2 Florida Bay Hydrology ..................................................................................................... 7

2.3 Plants Studied.................................................................................................................. 11

2.4 Hurricane Effects ............................................................................................................ 13

CHAPTER 3 MATERIALS AND METHODS ....................................................................... 17

3.1 Study Sites ...................................................................................................................... 17

3.2 Sampling Method ............................................................................................................ 19

3.3 Spatial Analysis .............................................................................................................. 22

CHAPTER 4 RESULTS ........................................................................................................... 24

vii

CHAPTER 5 DISCUSSION ..................................................................................................... 38

CHAPTER 6 CONCLUSION................................................................................................... 41

REFERENCES ......................................................................................................................... 42

APPENDIX ............................................................................................................................... 47

Accuracy Assessment ........................................................................................................... 47

viii

LIST OF TABLES

Table 1(a-b): Braun-Blanquet assessment of seagrass density (D) for all samples, separated by

species and basin. 1a contains pre-Irma data and 1b contains post-Irma. Adapted from

Fourqurean et al. (2001). ...............................................................................................................28

Table 2: Root Mean Square Error for each map by basin (when applicable) ................................47

ix

LIST OF FIGURES

1. Everglades National Park, Florida, USA. Park extent (green outline) and Florida Bay

extent (black dashed line) are shown .........................................................................................4

2. Annual mean volume transports (m3 s−1) for measured channels in Florida Bay (red

arrows and numbers), through the tidal passes between the Florida Keys (blue arrows

and numbers), and from mean river discharge (black arrows and numbers)

(Lee et al. 2016) .......................................................................................................................10

3. Thalassia testudinum (top), Halodule wrightii (middle), and Syringodium filiforme

(bottom). Illustrations are by Phillips and Menez (1988) and photographs are by Ken

Dunton (University of Texas). .................................................................................................11

4. Hurricane Irma's track in relation to Florida Bay and South Florida .......................................13

5. A wrack line composed entirely of dried seagrass, mostly Thalassia testudinum, left by

Hurricane Irma. This photo was taken over 300 meters from Flamingo Beach, FL. ..............15

6. Florida Bay salinity (PSU) one month before Hurricane Irma, one month after, and five

months after (SFWMD 2018). .................................................................................................16

7. Twin Key and Rabbit Key Basins and their position within Florida Bay. ..............................18

8. Bathymetry of Rabbit Key and Twin Key Basins. Contour interval: 0.25 m. Digital

Elevation Model provided by National Centers for Environmental Information (NCEI).

Vertical error estimated by NCEI to be no more than 15 cm ..................................................19

9. Location of sampling sites in RKB and TKB. .........................................................................20

10. Total seagrass cover defined by broad cover categories. Bare sediment is 0% cover;

Sparse cover is <10%; Moderate cover is 10-50%; dense cover is >50%. ..............................27

11. Halodule wrightii distribution before (top) and after (bottom) Hurricane Irma ......................30

12. Syringodium filiforme distribution before (a) and after (b) Hurricane Irma ............................31

13. Proportion (%) of sites in each basin that had significant positive or negative change in

density ......................................................................................................................................32

14. Direction and intensity of change in total seagrass cover after Hurricane Irma. .....................33

x

15. Thalassia testudinum cover before Hurricane Irma (top) and after Hurricane Irma

(bottom)....................................................................................................................................34

16. Halodule wrightii density before (top) and after (bottom) Hurricane Irma. ............................35

17. Syringodium filiforme density before (top) and after (bottom) Hurricane Irma. .....................36

18. Total Seagrass Cover by Braun-Blanquet value for before (top) and after (bottom)

Hurricane Irma .........................................................................................................................37

19. Aerial photography of the study area from one month after Hurricane Irma. Study basins

are outlined in yellow. The yellow star on the eastern edge of TKB marks the location of

sediment blow-outs. .................................................................................................................39

1

CHAPTER 1

INTRODUCTION

Florida Bay is a saltwater portion of Everglades National Park positioned between the

southern river outlets, the Gulf of Mexico, and the Florida Keys (Figure 1). It supports a

tremendous variety of fauna, many of which are critical to the South Florida economy and

ecosystem. Not only is Florida Bay home to threatened and endangered species, including four

protected species of sea turtles and the endangered American crocodile (Crocodylus acutus) and

manatee (Trichechus manatus laterostris) (Florida Museum of Natural History), but it is also a

popular fishing destination that contributes over $800 million annually in economic activity and

nearly 9,000 jobs to South Florida (Fedler 2009). The sport fish behind this spending, as well as

the previously mentioned protected species, all depend, at least in part, on the seagrass

communities of Florida Bay for survival (Tilmant 1989; Fourqurean and Robblee 1999).

Hurricane Irma made US landfall through the Lower Florida Keys, with the eye of the

hurricane passing within 60 kilometers of the western extent of Florida Bay. Throughout the

southeastern US, the storm decimated crops and demolished coastal developments, leaving an

estimated $50 billion worth of damage in its wake (Cangialosi et al. 2018). The damage to land

structures and vegetation was obvious but what interested South Florida ecologists was more

difficult to observe; what effects did Hurricane Irma have on seagrass beds in Florida Bay?

The anthropogenically modified hydrology and polluted waters of Florida Bay are

severely limiting to the wetland and benthic communities within it. The past 100 years of coastal

development and hydrologic alteration to the Everglades have caused the “chronic state of low

2

flow” in the northern and eastern sections of the bay that contribute to elevated salinity in the

estuarine basins (Brandt et al. 2016), while increased evaporation from rising sea surface

temperatures leads to a deficit of freshwater in the other subregions (Short and Neckles 1998;

Nuttle et al. 2000; Kelble et al. 2007). Prolonged periods of elevated salinity have been observed

to cause monocultures of Thalassia testudinum, which provide less suitable habitat for bay fish

species and are susceptible to widespread mortality (Thayer and Chester 1989; Bennet et al.

2005). The combination of high sea surface temperatures, hypoxia, and hypersalinity are

believed to be responsible for die-offs of T. testudinum like the one in 2015 (Borum et al. 2005;

Koch et al. 2007; Hall et al. 2016; National Park Service 2016).

In the months before Hurricane Irma struck in 2017, the basins that had been impacted by

the 2015 die-off still had water of higher salinity than average ocean water (South Florida Water

Management District 2018) and it was unclear whether the seagrass was recovering (Matt

Patterson, personal communication to the author, November 2017). Hurricanes are known to

reduce salinity in Florida Bay and are also expected to play a role in removal of sediment build-

up, increasing flow between basins (Zieman et al. 1989; Rudnick et al. 2005; Kelble et al. 2007).

It was predicted that total seagrass cover would increase after Irma and that community

composition would become more diverse as the influx in freshwater reduced bay salinity and

increased circulation, making conditions more suitable for the two target seagrass species

(Halodule wrightii and Syringodium filiforme) that are less salt-tolerant than T. testudinum.

Braun-Blanquet field survey methods were used to evaluate coverage and composition of

seagrass communities in two Florida Bay basins nearly a year after Hurricane Irma, at which

point colonization of scoured sediments could be seen. The basins used in this study had been

3

previously assessed using these same field-survey methods to map the extent of the 2015 die-off,

the data from which was compared to the post-Irma survey to detect changes in seagrass status.

The purpose of this project is to record the changes in seagrass beds in Florida Bay after

Hurricane Irma. Submersed aquatic vegetation is considered a keystone species in Florida Bay

and, as such, is monitored by multiple agencies throughout South Florida (Brandt et al. 2016).

Visualization of the cover and community composition of seagrass beds in Florida Bay after

Hurricane Irma provide insight into the environmental conditions of the ecosystem and can be

used to track changes as conditions in the bay change, either as a result of restoration or of

climate change. Visualization of areas where there is no seagrass cover may also help guide

restoration projects in the future.

4

Figure 1: Everglades National Park, Florida, USA. Park extent (green outline) and Florida

Bay extent (black dashed line) are shown.

5

CHAPTER 2

BACKGROUND

2.1 Florida Bay Ecosystem

Resting at the southern outlet of the Everglades, Florida Bay is a subtropical body of

water that is known for its diverse plants and wildlife. The bay comprises nearly one third of

Everglades National Park and the Marjory Stoneman Douglas Wilderness, giving it the highest

level of protection assigned to US federal lands (National Park Service 2009). Florida Bay is a

popular destination for ecotourists while also serving as a place for both work and recreation for

locals. Sport fish such as tarpon (Megalops atlanticus), bonefish (Albula vupes), red drum

(Sciaenops ocellata), and spotted seatrout (Cynoscion nebulosus) live within the bay, making the

site popular for recreational fishing (Tabb and Manning 1961; Tilmant 1989; Powell 2003). In

addition, a rich community of piscivorous birds (e.g., wading birds, magnificent frigatebirds, and

osprey) and several protected vertebrate species, like American crocodiles (Crocodylus acutus)

and green sea turtles (Chelonia mydas), hunt within the bay or graze upon its seagrass beds

(Fourqurean and Robblee 1999). When seagrass beds significantly decrease in density, the bay

fauna decrease in abundance and diversity in response (Fourqurean and Robblee 1999).

Florida Bay is important to people from all walks of life, so the widespread impacts from

seagrass die-offs are an economic concern as much as an ecologic concern. Changes in climate

and Florida Bay hydrology throughout the 20th and 21st century have caused accelerated

evaporation and low circulation between basins, resulting in periods of hypersalinity, often at the

end of the dry season (November to April) (Fourqurean and Robblee 1999; Koch et al. 2007; Lee

6

et al. 2016), the results of which have twice led to disastrous, widespread seagrass die-offs (Hall

et al. 2016). In basins with the lowest amounts of freshwater input, salinity has sometimes

reached 70 PSU, which is twice the average concentration of ocean water (Kelble et al. 2007).

While seagrasses are adapted to tolerate saline conditions, the mechanisms that control their

osmotic balance reduce photosynthetic efficiency (Touchette 2007) and increase their oxygen

demand for respiration (Koch et al. 2007).

The combination of elevated water temperature, decreased oxygen production from

photosynthesis, increased oxygen demand in plant tissues, and low circulation in the water

column creates hypoxic conditions, which encourages hydrogen sulfide production by anaerobic

microbes (Borum et al. 2005; Koch et al. 2007). Recent experiments have also found that, at

night, oxygen-deprived root tissue in Thalassia testudinum – the dominant seagrass species in

Florida Bay and the only species to survive long-term exposure to salinity over 40 practical

salinity units (PSU) – is especially susceptible to hydrogen sulfide toxicity via intrusion from

porewater when exposed to hypersaline conditions (Johnson et al. 2018). The decay of plant

tissues in anoxic conditions causes further hydrogen sulfide production, which results in a

positive feedback loop of decomposing seagrass leading to the mortality of the surrounding

seagrass (Carlson et al. 1994)

Hydrogen sulfide creates a “rotten egg” smell and yellow “fog” in the water (Hall et al.

2016; National Park Service 2016). The smell, along with floating masses of dead seagrass and

fish hurt the tourism industry and the decline in sport fish populations hurt the recreational

fishing industry. As stated by the Everglades Marine Team, “when Florida Bay is unhealthy, the

impacts are felt across South Florida” (National Park Service 2016).

7

The literature suggests that precipitation from extreme storms can reduce hypersaline

conditions and remove sediment and detritus buildup in Florida Bay, relieving some of the

chemical stress on seagrass (Davis et al. 2004; Rudnick et al. 2005; Steward et al. 2006). This

would improve seagrass productivity, allow the less salt-tolerant seagrass species to populate the

seagrass communities, and provide higher-quality habitat for marine life (Thayer and Chester

1989; Bennett et al. 2005; Touchette 2007). However, these weather events also cause physical

stress on plants from wave activity and scouring and may reduce light availability to submerged

vegetation with sediment suspension and algal blooms from the released sediment nutrients

(Fonesca et al. 1998; Fourqurean et al. 1999; Davis et al. 2004; Rudnick et al. 2005; Steward et

al. 2006; Carlson et al. 2010; Cole et al. 2018).

2.2 Florida Bay Hydrology

Starting in 1881, the Florida Everglades underwent over 100 years of hydrologic

alterations in order to reclaim wetlands to accommodate the growing population of South Florida

(Light and Dineen 1994). The most intensive alterations, the Central & South Florida Project,

were completed in the 1950s-1970s; the project installed a network of canals, levees, pumps, and

water conservation areas with the goal of preventing floods and augmenting the local water

supply (Light and Dineen 1994; Ogden et al. 2005). Because of the hydrologic diversion, 6.4

billion kilograms of water bypass the Everglades, leaving the system with only 30% of its

original flow (USFWS 1999). The reduced flow is often credited for the high salinity and

increased salinity variability in northern sections of Florida Bay and influencing community

composition (Bennett et al. 2005; Rudnick et al. 2005).

While these developments allowed massive population growth and urbanization in South

Florida, by the early 1980s public concern for the ecosystem inspired changes in water

8

management, starting with Florida Governor Graham’s launch of the “Save Our Everglades”

program in 1983 (Light and Dineen 1994). In 2000, the Comprehensive Everglades Restoration

Plan (CERP) set the guidelines for an interagency effort to restore the Everglades ecosystem

functions by imitating historic hydrology patterns (USACE and SFWMD 1999).

One of the many challenges of Everglades restoration is determining what the historic

hydrology patterns were; the quality and quantity of water in the freshwater Everglades and

Florida Bay were not well documented before the flow was diverted, so restoration efforts

depend upon statistical models and paleoecologic proxy data to estimate historic conditions

(Rudnick et al. 2005). The simulated historic conditions calculated by Rudnick et al. (2005) were

found to deliver 2.5-4 times as much freshwater to estuaries and wetlands as modern flow,

resulting in salinities in modern Florida Bay that are 5.3-20.1 PSU higher than before the

anthropogenic changes were made.

The complex network of mudbanks in Florida Bay restricts flow between basins, creating

a patchwork of variable water quality throughout the bay. Because of current hydrologic

conditions, only the northeastern section of the bay functions as a true estuary, where freshwater

from the Everglades mixes with saline water from the Gulf of Mexico; the rest of the bay

functions more like a tropical coastal lagoon, where most of the water flows in to the bay from

the Gulf of Mexico and precipitation is the primary source of freshwater (Rapozo 2001; Melo

and Lee 2012). Flow over shallow banks and through channels is primarily wind-driven and only

provide weak exchange between basins (Lee et al. 2006, 2008, 2016). As shown in Figure 2 (Lee

et al. 2016), basins in the western bay have greater exchange than interior and northeastern

basins, giving western basins a residence time of about 1 month compared to the 6-12-month

residence time in other sections (Lee et al. 2006, 2008, 2016). This restricted horizontal flow

9

makes it unclear how restoration of freshwater inflow from the Everglades may affect the bay;

approximately 75% of all freshwater runoff from the Everglades flows into the northeast section

of the bay, where the low outflow stores it for an average residence time of one year (Lee et al.

2008). Nuttle et al. (2000) argue that, while increasing runoff from the Everglades would have

little effect on salinity in the central and west regions of Florida Bay – where seagrass die-offs

have occurred in the past – and would increase the variability of salinity in the southern section,

the effect of freshwater runoff in the bay could be greater if inflow is increased during periods

when evaporation exceeds precipitation. Similarly, Lee et al. (2006, 2016) suggest that

increasing flow to McCormick Creek during the dry season would reduce salinity in the north-

central subregion of the bay, possibly preventing hypersaline events.

10

Figure 2: Annual mean volume transports (m3 s−1) for measured channels in Florida Bay (red

arrows and numbers), through the tidal passes between the Florida Keys (blue arrows and

numbers), and from mean river discharge (black arrows and numbers) (Lee et al. 2016).

11

2.3 Plants Studied

The seagrass species most commonly

found in the Florida Bay are Thalassia

testudinum, Halodule wrightii and Syringodium

filiforme and they are the only species evaluated

in this research. Thalassia testudinum has wide,

long, green leaves which grow off an extensive

underground rhizome. Syringodium filiforme

produces cylindrical leaves that are similar in

length, if not longer and are a lighter shade of

green than that of T. testudinum. Halodule

wrightii produces the shortest leaves of the three,

which are flat and dark green to almost black in

color (Figure 3).

Thalassia testudinum is the most abundant

seagrass in Florida Bay and is considered the

dominant species in these communities (Fourqurean

et al. 2001). The size and low nutrient requirements

of this species allow it to out-compete the other

species in most conditions. It is also the most salt-

tolerant species investigated; studies have found

that the optimal salinity range of Thalassia

testudinum is likely between 20 and 40 PSU

Figure 3: Thalassia testudinum (top),

Halodule wrightii (middle), and

Syringodium filiforme (bottom).

Illustrations are by Phillips and Menez

(1988) and photographs are by Ken Dunton

(University of Texas).

12

(Touchette 2007) and that in periods of prolonged salinity over 40 PSU, a monoculture of

Thalassia testudinum is observed (Bennett et al. 2005). Thalassia testudinum can be out

competed by S. filiforme in environments with low light availability or high phosphorous, which

is a limiting nutrient in Florida Bay and increases in concentration from east to west in this

system (Fourqurean et al. 1992). Halodule wrightii is the least sensitive to fluctuations in salinity

of the three species and is competitively excluded by the others in all environments expect

waters with high nutrient concentrations that experience widely fluctuating salinity or in the

wake of disturbance (Robblee et al. 1991).

While T. testudinum is dominant in succession, this species grows slowly (the median age

of single shoots of T. testudinum in Florida Bay is greater than 5 years) and typically reproduces

clonally, making it slow to repopulate areas defoliated by extreme weather (Robblee et al. 1991;

Peterson and Fourqurean 2001; Fourqurean et al. 2003). Halodule wrightii is considered a

pioneer species, which becomes established quickly in bare sediment if water quality is suitable

(Peterson and Fourqurean 2001). Considering the rates and requirements for growth of the three

species, it was expected that H. wrightii and S. filiforme, which could not tolerate the hypersaline

conditions present during the pre-Irma study, will exhibit new distributions after Irma. Halodule

wrightii was expected to be especially abundant in areas that were disturbed by the storm energy

where the dominant successional species – Thalassia testudinum – would not have had time to

reestablish after Hurricane Irma.

13

2.4 Hurricane Effects

Hurricane Irma made U.S. landfall at Cudjoe Key as a category 4 hurricane on September

10, 2017. Florida Bay and Everglades National Park were located to the east of Irma’s path,

where the strongest winds of the storm were directed (Figure 4). While traveling past the western

Figure 4: Hurricane Irma's track in relation to Florida Bay and South Florida.

14

edge of Florida Bay, the storm’s maximum recorded wind speed was 115 knots and minimum

pressure was 931 mb. Maximum inundation in the Lower Keys was nearly 2.5 m above the

normal tide line. Throughout the Keys, rainfall totals of 10-15 inches (25-38 cm) were reported

(Cangialosi et al. 2018).

In the United States, Irma caused 10 direct human deaths and 82 indirect human deaths.

The Middle and Lower Keys sustained the most damage, where an estimated 25% of all homes

were destroyed, while 90% of all homes were damaged. Irma cost an estimated $50 billion in

damages to structures and agriculture in the U.S. alone (Cangialosi et al. 2018).

Hurricanes and other extreme weather events are known to cause damage to natural and

man-made structures alike, but the short- and long-term effects of tropical cyclones (TCs) on

submerged aquatic vegetation can depend on the bathymetry, as well as the size, windspeed, and

traveling speed of the storm and water quality in the weeks after the storm passes (Craighead and

Gilbert 1962; Davis 2004; Carlson et al. 2010). It is uncommon for storm surge and shear

strength to damage fully submerged seagrasses, especially in a protected bay, but the sediments

disturbed by the storm can limit seagrass photosynthesis for several days and the resultant

deposition can bury leaves, either of which can cause seagrass mortality or reduced productivity

(Carlson et al. 2010). Because nutrients (especially phosphorous) accumulate in the carbonate

bay sediments, suspension of sediment also makes these nutrients available to algae, causing

blooms (Rudnick et al. 2005).

15

In Florida Bay, some basins

are shallow enough that storm surge

and winds can scour seagrass beds,

removing sediment, seagrass root

networks, and detritus from the bay

floor (Davis et al. 2004). Wrack lines

– lines made of buoyant material that

clings to structures and is often used

to determine the peak water level of a

flood – that could be seen across

South Florida after Irma made it clear that seagrass had indeed been removed from the bay floor

by the storm (Figure 5).

While hurricanes cause devastation to structures and natural features, TCs are important

for regulating water quality and circulation in Florida Bay, with extreme weather events

providing a hydrologic pulse to the region (Davis et al. 2004; Rudnick et al. 2005; Steward et al.

2006). Buildup of carbonate sediment banks reduce flow between basins, contributing to the

hypersaline and hypoxic conditions during periods of high evaporation and low inflow to the

bay; storm surge is thought be able to remove enough sediment to restore flow while also

transporting excess, sediment-bound nutrients out of the bay (Rudnick et al. 2005). Freshwater in

Florida Bay is almost entirely acquired as rainfall, meaning that TC precipitation can also relieve

salt stress in confined basins (Nuttle et al. 2000). In 2018, the South Florida Water Management

District (SFWMD) reported salinities of 30-45 practical salinity units (PSU) throughout most of

the bay the month before Hurricane Irma, whereas one month after Irma most of the bay was

Figure 5: A wrack line composed entirely of dried seagrass,

mostly Thalassia testudinum, left by Hurricane Irma. This photo

was taken over 300 meters from Flamingo Beach, FL.

16

recorded at 0-20 PSU (Figure 3). Five months after Irma, most of the bay still had salinity

concentrations below 30 PSU (SFWMD 2018), which is below the average salinity of ocean

water (35 PSU) and conducive to growth for all three of the target seagrass species (Fourqurean

et al. 2002; Touchette 2007).

Figure 6: Florida Bay salinity (PSU) one month before Hurricane Irma, one month after, and

five months after (SFWMD 2018).

17

CHAPTER 3

MATERIALS AND METHODS

3.1 Study Sites

This study used two adjacent hydrogeologic basins – Rabbit Key Basin (RKB) and Twin

Key Basin (TKB) – that were impacted by the seagrass die-off in 2015 (McGinnis 2017). The

basins are located in the western subregion of Florida Bay (Figure 7), where precipitation is the

primary source of freshwater and most inflow comes from the Gulf of Mexico (Nuttle et al.

2000; Lee et al. 2016). Despite their close proximity, the basins differ substantially in water

quality and community compositions (Fourqurean et al. 2003), so all analysis of seagrass data in

this investigation will consider the basins individually.

Twin Key Basin was the first basin surveyed. The 65 km2 basin was turbid and affected

by abundant microalgae but the visibility was not impacted enough to prevent sampling. TKB

experiences hypersalinity more frequently than its western neighbor, RKB, due to its main

source of inflow coming from the bay’s most hypersaline basins (Lee et al. 2006, 2016). RKB is

smaller and shallower than TKB (47 km2) (Figure 8), but its position in the bay provides RKB

with direct water exchange with the Gulf of Mexico and the associated regulation of salinity (Lee

et al. 2016). RKB also had better visibility than TKB, most likely due to lower water column

nutrient concentrations limiting microalgal populations (Fourqurean et al. 1992). The southern

18

edge of TKB had the greatest depth in the study area (nearly 3 meters below mean sea level) but,

overall, the majority of the study area is 1-2 meters deep (Figure 8).

Figure 7: Twin Key and Rabbit Key Basins and their position within Florida Bay.

19

3.2 Sampling Method

In the pre-Irma, post die-off study, 35 study sites were randomly generated for each study

basin (McGinnis 2017). Of those 35 sites, 30 sites in TKB and 20 sites in RKB were surveyed

pre-Irma. For this Post-Irma study, researchers navigated to the same locations surveyed in the

pre-Irma study using a vessel-mounted GPS with waypoints uploaded using the DNRGPS

application by the Minnesota Department of Natural Resources. Of the sites that had Pre-Irma

data, all but two sites were surveyed – two sites in RKB were in water too shallow for the

research vessel that was larger than the one used for the Pre-Irma survey – resulting in a total of

48 study sites (Figure 9).

Figure 8: Bathymetry of Rabbit Key and Twin Key Basins. Contour interval: 0.25 m. Digital

Elevation Model provided by National Centers for Environmental Information (NCEI).

Vertical error estimated by NCEI to be no more than 15 cm.

20

For each study site, once the vessel reached the waypoint, a team member dropped a soft-

weighted buoy to mark the spot. A pair of snorkelers then attached two 30-meter transect tapes to

the buoy and swam in different, random directions. Each diver haphazardly dropped a 0.25 m²

PVC quadrat at 5-meter intervals (5, 10, 15, 20, and 25 meters from the buoy) and analyzed the

seagrass cover within the quadrat where it landed.

Density was assessed using the Braun-Blanquet cover-abundance method, which ranks

shoot density on an ordinal scale; a 5 on the scale represents 75-100% cover, 4 represents 50-

75%, 3 represents 25-50%, 2 represents 10-25%, and 1 represents less than 10%. If seagrass is

found in the transect but there is too little for it to provide cover, a ranking of 0.5 is used to

Figure 9: Location of sampling sites in RKB and TKB.

21

indicate that that there were several shoots of seagrass or 0.1 indicates that there was one shoot

of seagrass. Each new snorkeler was trained by an experienced team member to ensure that

Braun-Blanquet values assigned by different researchers corresponded to the same approximate

density throughout the study. Snorkelers recorded the Braun-Blanquet value describing cover-

abundance of the three target-species at each of the 10 transects upon their return to the vessel.

The Braun-Blanquet method is used in this study for two reasons: the pre-Irma survey

utilized this method and changing the metric would make the validity of comparisons between

datasets questionable (Fonesca et al. 1998), and because it is a rapid, easily used method which is

invaluable when the funding, resources, and weather limits the number of days that can be spent

collecting data. If a more time-intensive metric, such as shoot density, had been found for each

site, a much smaller number of sites would have been used in this study and, as a result,

interpolation would have been less robust. This survey method is also preferred by National

Parks officials over more destructive methods, such as measuring biomass or collecting dredge

samples, both of which kill the seagrass sampled (Matt Patterson, personal communication to

author, November 2017). In comparison, Braun-Blanquet surveying is minimally destructive,

with the anchor of the boat inflicting the only obvious damage to seagrass. Other less direct

methods of quantifying seagrass distribution involve remote sensing, which was not appropriate

for this research because the type of benthic vegetation visible in remotely sensed imagery is

nearly impossible to determine for Florida Bay. Not only is the water often too turbid to see the

bottom, but several macroalgae species can be seen throughout the study area, some of which

drift freely along the sea floor, making it possible for images taken hours apart to have different

distributions of submersed aquatic vegetation (Matt Patterson, personal communication to

author, November 2017). The community structure of seagrass also limits the utility of remote

22

sensing in this environment, as seagrass can grow in multiple stories and all three species can be

present at a site in a nearly-even distribution (Fourqurean et al. 2002); spectral signatures could

be used to identify species in areas with more homogenous composition but, for heterogenous

communities like those in the western Florida Bay, it would not have been useful. In the context

of this research, the only practical survey method was Braun-Blanquet.

3.3 Spatial Analysis

Change analysis for each species was performed in IBM® SPSS®. While the Braun-

Blanquet cover-abundance method is useful for rapidly approximating density in the field, the

ordinal nature of the data requires use of non-parametric tests for determining significant change.

The Kruskal-Wallis test was chosen to determine which sites had significant (P=0.05) difference

in species density and total density – the sum of the three species densities in each sample –

between the two study periods. The test was performed for all four density variables for each of

the 48 sites (192 Kruskal-Wallis calculations total). Tests used the 20 sample values describing

each density variable – ten samples from the pre-Irma survey and ten samples from the post-Irma

survey – a total of 3,840 data points. The recorded Kruskal-Wallis test statistics indicated

whether a variable had the same mean rank across the two study periods; test statistics of P<0.05

meant that the data distribution between the two time periods were significantly different.

Sites that had significant change in total density were plotted in ArcMap. Maps indicating

zones of significant change in density were created using only these sites; the difference in

medians from before and after Hurricane Irma was used to indicate if the change was positive or

negative and inverse Distance Weighting (IDW) was used to create a raster for these points.

Density of seagrass and density of individual species was mapped by plotting the median

Braun-Blanquet score for the density variable at the coordinates assigned to each site. A raster

23

surface was created for each species by basin using Inverse Distance Weighting (IDW)

interpolation with a cell size of 45 meters. This cell size was selected because it produced cells of

the same area as a circle with a radius of 25 meters – the furthest sampling distance from the

buoy at each site. Other IDW settings were kept at default, with a distance power of 2 and a 12-

point search parameter. The rasters were processed to the extent of each basin using appropriate

polygons. After extraction by a mask of the same basin polygons, the raster data was classified

by Braun-Blanquet value. Maps are shown with an overlay outlining locations of shallow banks,

where intertidal communities are likely to differ from benthic seagrass meadows and where

sampling was sometimes impossible in the 25-foot NPS research vessel. The shallow banks

polygon layer is provided by the Florida Fish and Wildlife Conservation Commission-Fish and

Wildlife Research Institute.

The validity of statistical relationships between points from ordinal data is a topic of

debate in statistics (Allen and Seaman 2007). The ranges of percent cover that each Braun-

Blanquet class represents are not all equal and the distribution of the data is not normal, leading

to my assertion that it is not appropriate to derive statistical relationships from this data as if it

were interval data. For these reasons, Kriging – an interpolation method that uses the variance of

the data to create maps that are weighted by the statistical significance of data over distance –

was not used, despite its reputation as a more robust interpolation method. Because of the ordinal

nature of the Braun-Blanquet values, spatial interpolation should only be used to determine the

boundaries between the classes; the area between boundaries cannot be interpolated to non-

integer numbers (Feoli and Orloci 2012). While IDW interpolation may oversimplify the

geospatial patterns present, it produces a visualization of general trends in the study area that

may be useful for natural resource management.

24

CHAPTER 4

RESULTS

After Hurricane Irma, overall density of seagrass in the study area became more

contiguous, with fewer patches of bare sediment (no seagrass) and sparse cover (<10% seagrass

cover) observed (Figure 10). Distribution of the three seagrass species increased in both basins in

all but one variable; S. filiforme in Twin Key Basin (Table 1). The pioneer species Halodule

wrightii experienced the greatest change in distribution, as it was found in 25% more samples in

RKB and 6.3% more samples in TKB after Irma. Thalassia testudinum grew in the greatest

densities, providing dense cover (>50% seagrass cover) at 40.6% of samples in RKB and 18.3%

of samples in TKB.

Twin Key Basin was overwhelmingly dominated by T. testudinum (Table 1). Only 0.3%

of samples in this basin reported more than 10% cover from any other species, which in this case

was Halodule wrightii. While density of H. wrightii was low in TKB, its distribution after Irma

spanned most of the basin (Figure 11). Syringodium filiforme, however, was almost completely

absent in TKB, where only one pre-Irma sample at one site reported its presence. With a Braun-

Blanquet value of 0.1, the single shoot of S. filiforme found in TKB was not enough to change

the site’s median S. filiforme density, so no map of S. filiforme density in TKB was produced.

T. testudinum was also the most abundant seagrass species in RKB, but H. wrightii and S.

filiforme appeared concurrently in greater densities in this basin than in TKB (Table 1). Both H.

wrightii and S. filiforme were distributed across the basin, with few patches where they were

absent (Figures 11, 12).

25

Kruskal-Wallis tests determined significant change in density of seagrasses in both

basins. The difference between post-Irma and pre-Irma median densities for each site provided

information on the direction of change at these significant sites (Figures 13, 14). While positive

and negative changes were seen throughout the study area, Halodule wrightii was the only

species to not experience significant negative change after Hurricane Irma. Syringodium filiforme

experienced equal proportions of positive and negative change while T. testudinum and total

seagrass density in both basins had at least 10% more sites experience positive change than

negative change.

Thalassia testudinum density became more uniform throughout the study area, as areas of

sparse cover and areas of dense cover both approached more moderate densities (Figure 15).

Density of H. wrightii increased in both basins, though it provided no more than 10% cover in

most of the study area (Figure 16). Basin-wide density of S. filiforme did not change noticeably,

though the patterns of density shifted after Hurricane Irma (Figure 17). Changes in individual

species’ density influenced the total seagrass cover, which became more uniform after Irma

(Figures 10, 18).

The accuracy of each density interpolation, calculated by Root Mean Squared Error

(RMSE), is presented in the Appendix. Error was measured using the difference between

interpolated values and a set of observations not used to create the interpolated maps;

approximately 10% of the sites from each basin were reserved for use in the RMSE. The most

accurate interpolation was the post-Irma map of total cover in RKB (0.035 RMSE) and the least

accurate interpolation was the pre-Irma map of total cover in TKB (1.517 RMSE). Because of

the “patchy” nature of seagrass beds in the study area, this amount of error is expected; the

interpolation maps represent the median density of each species, but bare patches and unusually

26

dense patches should be anticipated (Pramova et al. 2013). More reliable maps, made by

classifying total cover into the broader categories of “Bare,” representing no cover, “Sparse,”

representing less than 10% cover, “Moderate,” representing 10-50% cover, and “Dense,”

representing more than 50% cover, are shown for before and after Irma (Figure 10).

27

Figure 10: Total seagrass cover defined by broad cover categories. Bare sediment is 0% cover;

Sparse cover is <10%; Moderate cover is 10-50%; dense cover is >50%.

28

Table 3(a-b): Braun-Blanquet assessment of seagrass density (D) for all samples, separated by species and basin. 1a contains pre-

Irma data and 1b contains post-Irma. Adapted from Fourqurean et al. (2001).

29

30

Figure 11: Halodule wrightii distribution before

(top) and after (bottom) Hurricane Irma.

31

Figure 12(a-b): Syringodium filiforme distribution before (a) and after (b)

Hurricane Irma.

32

Figure 13: Proportion (%) of sites in each basin that had significant positive or negative

change in density.

33

Figure 14: Direction and intensity of change in total seagrass cover after Hurricane

Irma.

34

Figure 15: Thalassia testudinum cover before Hurricane Irma

(top) and after Hurricane Irma (bottom).

35

Figure 16: Halodule wrightii density before (top) and after (bottom) Hurricane Irma.

36

Figure 17: Syringodium filiforme density before (top) and after (bottom)

Hurricane Irma.

37

Figure 18: Total Seagrass Cover by Braun-Blanquet value for before

(top) and after (bottom) Hurricane Irma.

38

CHAPTER 5

DISCUSSION

Hurricane Irma produced strong western winds over Florida Bay, which directed

powerful waves towards the northwest within both basins that may have caused the decrease in

seagrass density visible in the west and northwest sections of both basins (Figure 13). In TKB,

T. testudinum cover increased after Hurricane Irma in the north-northeast portion of the basin.

This region was severely impacted by the seagrass die-off in 2015, so positive change in cover

indicates that conditions became more hospitable for T. testudinum in this part of the bay (Matt

Patterson, personal communication to author, November 2018). The northern section of TKB

receives flow from Whipray Basin and other north-central basins of that experience some of the

most extreme, chronic hypersalinity in Florida Bay (Lee et al. 2006, 2016), so regulation of

salinity and improved flow due to the influx of freshwater from Hurricane Irma may have had

greater impact in this area than in other parts of the study area.

Other changes in cover may be explained by the bathymetry of these basins. RKB is

confined from the southwest by Ninemile Bank, which is believed to have shielded much of the

basin from the most intense wave action. Conversely, the eastern inlets to TKB are less protected

by banks and are shallow, leaving this region exposed to scouring waves. As seen in Figure 17,

this region did not have uniform dense cover before Irma, meaning that existing sediment could

have been removed or suspended by wave action. As a result, sediment experienced a “blow-out”

at this location, possibly taking the seagrass with it; aerial photography from one month after

Irma shows plumes of suspended sediment going from the banks and narrow channels into TKB

39

(Figure 18). If physical removal by wave energy did not cause the decline in T. testudinum

density on the eastern edge of TKB, then the reduced light penetration from suspended sediment

and algal blooms is another possible cause (Short and Neckles 1999; Rudnick et al. 2005). This

area is also noteworthy because, while T. testudinum density significantly decreased, H. wrightii

has increased in density there after Irma (Figure 15). The transition from T. testudinum to H.

wrightii aligns with the literature, which identifies H. wrightii as a successful pioneer species

after disturbance (Peterson and Fourqurean 2001). This also indicates that water quality has

changed to be more suitable to H. wrightii since the pre-Irma survey; H. wrightii has been found

to decline in water with salinity over 30 PSU and to be absent over 40 PSU (Bennett et al. 2005;

Touchette 2007).

Figure 19: Aerial photography of the study area from one month after Hurricane Irma. Study

basins are outlined in yellow. The yellow star on the eastern edge of TKB marks the location of

sediment blow-outs.

40

The distribution of H. wrightii and S. filiforme also changed, with H. wrightii (Figure 8)

becoming denser throughout the center and southeastern portion of the basin and S. filiforme

(Figure 9) becoming denser in the northern portion of the basin. These changes in density could

have been caused by improved nutrient or light availability, which is evidenced by the inverse

relationship between T. testudinum and S. filiforme in this basin; S. filiforme has been found to

out-compete T. testudinum in waters with low light or high phosphorous concentrations, which is

the limiting nutrient for primary production in the western section of the bay (Fourqurean et al.

1992).

The change in median total density of both basins (Figure 10), makes it clear that after

Hurricane Irma, both basins showed less area that had bare sediment or sparse cover (less than

10% cover, or 0-1 in Braun-Blanquet values, as mapped). The post-Irma map also shows more

uniform coverage, indicating that cover is more contiguous after Irma. More contiguous, dense

cover can stabilize sediments more efficiently, preventing the resuspension of sediment and

nutrients, which lead to algae blooms (Rudnick et al. 2005; Hansen and Reidenbach 2017).

The data shows that there are sections of the bay that experienced a significant loss of

seagrass but there are other areas that not only experienced a significant increase in seagrass

density, but also demonstrated higher species richness when water quality became more

hospitable to H. wrightii and S. filiforme, which forms more suitable habitat for fish and other

bay fauna (Bennett et al. 2005). This research contributes new data to the literature on Florida

Bay ecology by providing evidence that tropical cyclones may help accelerate recovery after

seagrass die-off events. Factors that may have influenced seagrass recovery include 1) dilution of

hypersaline water by precipitation and storm surge and 2) removal of built-up sediments from

banks and channels, allowing more water exchange between basins.

41

CHAPTER 6

CONCLUSION

The precipitation-dependency and low flow between basins in Florida Bay makes the

region prone to water deficit, leading to variable salinity. In cases of prolonged hypersalinity,

interaction between environmental stressors can cause wide-spread seagrass die-offs (Borum et

al. 2005; Koch et al. 2007; Johnson et al. 2018). After an extensive die-off event in 2015,

hypersaline water that was high in hydrogen sulfide concentration and low in dissolved oxygen

due to the decomposing seagrass remained trapped in the confined basins of the bay. When

Hurricane Irma passed Florida Bay in 2017, scientists from multiple agencies in South Florida

were interested to see the positive and negative effects that the event might have on the

hydrologically challenged system.

While the storm caused decline in seagrass density in some parts of the study area,

seagrass cover in the majority of the study area became more uniform and more diverse. This

research shows that, throughout the study basins, the overall seagrass density increased and there

was less area with bare sediment. I also found that the non-dominant species Halodule wrightii

and Syringodium filiforme began growing in greater densities in some areas where they had

already been established and had colonized some patches of sediment that had been left bare

after Hurricane Irma. There are still portions of both basins that show a significant reduction in

seagrass density after Irma but the positive influence the storm had on seagrass communities

after a die-off event is an ecological silver lining to this devastating storm.

42

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47

APPENDIX

Accuracy Assessment

The accuracy of each interpolated map was performed using 10% of the data points, which were

reserved during interpolation. Root Mean Squared Error of each site is reported in Table 3. Error

was calculated as the difference between observed values and the nearest boundary of the range

used to define the predicted values.

Table 4: Root Mean Square Error for each map by basin (when applicable).

RABBIT KEY BASIN TWIN KEY BASIN

T. TESTUDINUM pre-Irma 1.051855741 1.041633333

T. TESTUDINUM post-Irma 0.637965908 0.777281588

H. WRIGHTII pre-Irma 0.360555128 N/A

H. WRIGHTII post-Irma 1.457909634 0.057735027

S. FILIFORME pre-Irma 0.070710678 N/A

S. FILIFORME post-Irma 0.320156212 N/A

TOTAL COVER pre-Irma 0.285745516 1.517124473

TOTAL COVER post-Irma 0.035355339 0.777281588