University of Florida Thesis Or Dissertation

EFFECTS OF SIMULATED CYANOBACTERIA BLOOMS AND SEDIMENT RESUSPENSION ON SEVERAL SPONGE SPECIES FROM FLORIDA BAY

DANIELLE PULS

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2015

To Robert and Lisa Puls

ACKNOWLEDGMENTS

I thank Dr. Donald Behringer for his diligent guidance and support. I thank Dr. Edward

Phlips for his insight as a member of my graduate committee. I thank my lab mates, especially

Jason Spadaro and Nathan Berkebile, for their unending support and assistance. Finally, I thank my mother, father, brother, and sister for their love and patience.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 6

LIST OF FIGURES ...... 8

ABSTRACT ...... 9

CHAPTER

1 INTRODUCTION ...... 10

2 METHODS ...... 18

Viscosity Stress Trials ...... 18 Sponge Collection ...... 18 Experimental Setup ...... 18 Statistical Analysis ...... 20 Sediment Stress Trials ...... 20 Sponge Collection ...... 20 Experimental Setup ...... 21 Statistical Analysis ...... 22 Internal Canal Architecture Analysis ...... 22 Sponge Image Collection ...... 22 Image Analysis ...... 23 Statistical Analysis ...... 24

3 RESULTS ...... 26

Viscosity Stress Trials ...... 26 Sediment Stress Trials ...... 27 Internal Canal Architecture Analysis ...... 27 Mean Canal Area ...... 27 Percent of Porous Area ...... 29 Number of Canals per Unit Area ...... 29

4 DISCUSSION ...... 44

LIST OF REFERENCES ...... 53

BIOGRAPHICAL SKETCH ...... 57

LIST OF TABLES

Table page

3-1 Results of a one-way ANOVA testing for the effects of viscosity water treatment and time on pumping activity of Spheciospongia vesparium ...... 31

3-2 Results from a Pearson’s Chi Square test performed on each time interval that Spheciospongia vesparium was exposed to xanthan gum compared to those exposed to seawater only ...... 31

3-3 Results of a one-way ANOVA testing for the effects of viscosity water treatment and time on pumping activity of Spongia barbara ...... 31

3-4 Results from a Pearson’s Chi Square test performed on each time interval that Spongia barbara was exposed to xanthan gum added compared to those exposed to seawater only ...... 32

3-5 Results of a one-way ANOVA testing for the effects of viscosity water treatment and time on pumping activity of Hippospongia lachne...... 32

3-6 Results from a Pearson’s Chi Square test performed on each time interval that Hippospongia lachne was exposed to xanthan gum compared to those exposed to seawater only ...... 32

3-7 Results of two, one-way ANOVAs testing for the effects of sediment treatment and time on Spheciospongia vesparium ...... 33

3-8 Results from a Pearson’s Chi Square test performed on each time interval that Speciospongia vesparium was exposed to the sediment treatment compared to those exposed to seawater only ...... 33

3-9 Result of two, one-way ANOVAs testing for the effects of sediment treatment and time on Tectitethya crypta ...... 34

3-10 Results from a Pearson’s Chi Square test performed on each time interval that Tectitethya crypta was exposed to the sediment treatment compared to those exposed to seawater only ...... 34

3-11 Results of a one-way ANOVA testing for differences in mean canal area among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta for vertical sponge sections ...... 34

3-12 Results from a Tukey’s post-hoc analysis of differences in mean canal area for vertical sponge sections ...... 35

3-13 Results from a one-way ANOVA testing for differences in canal area among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta for the outermost slice from vertical sections ...... 35

3-14 Results from a Tukey’s post-hoc analysis of differences in canal area for the outermost slice from vertical sections...... 35

3-15 Results from a one-way ANOVA testing for differences in mean canal area among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta for horizontal sponge sections ...... 35

3-16 Results from a Tukey’s post-hoc analysis of differences in mean canal area for horizontal sponge sections ...... 35

3-17 Results from a one-way ANOVA testing the differences in the percent of porous area relative to total area of a vertical section among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 36

3-18 Results from a Tukey’s post-hoc analysis of differences in the percent of porous area relative to total area of a vertical section ...... 36

3-19 Results from a one-way ANOVA testing the differences in the percent of porous area relative to total area of a horizontal section among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 36

3-20 Results from a Tukey’s post-hoc analysis of differences in the percent of porous area relative to total area of a horizontal section ...... 36

3-21 Results from a one-way ANOVA testing the differences in the mean number of canals per cm2 area for vertical sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 36

3-22 Results from a Tukey’s post-hoc analysis of differences in the mean number of canals per cm2 area for vertical sections ...... 37

3-23 Results from a one-way ANOVA testing the differences in the mean number of canals per cm2 area for horizontal sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta...... 37

3-24 Results from a Tukey’s post-hoc analysis of differences in the mean number of canals per cm2 area for vertical sections ...... 37

LIST OF FIGURES

Figure page

2-1 Tank design to test sponges in the xanthan gum and sediment stress trials...... 25

3-1 Mean pumping activity over time of Spheciospongia vesparium exposed to xanthan gum versus S. vesparium exposed to seawater ...... 38

3-2 Mean pumping activity over time of Spongia barbara exposed to xanthan gum versus S. barbara exposed to seawater ...... 38

3-3 Mean pumping activity over time of Hippospongia lachne exposed to xanthan gum versus H. lachne exposed to seawater...... 39

3-4 Mean pumping activity over time of S. vesparium exposed to sediment versus S. vesparium exposed to seawater ...... 39

3-5 Mean pumping activity over time of Tectitethya crypta exposed to sediment versus T. crypta exposed to seawater only ...... 40

3-6 Mean canal area for vertical cross sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 40

3-7 Canal area for the outermost vertical cross section of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 41

3-8 Mean canal area for horizontal cross sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 41

3-9 Percent of porous space relative to total area for vertical sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 42

3-10 Percent of porous space relative to total area for horizontal sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta...... 42

3-11 Mean number of canals per cm2 area for vertical sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 43

3-12 Mean number of canals per cm2 area for horizontal sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta ...... 43

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

EFFECTS OF SIMULATED CYANOBACTERIA BLOOMS AND SEDIMENT RESUSPENSION ON SEVERAL SPONGE SPECIES FROM FLORIDA BAY

Danielle Puls

August 2015

Chair: Donald C. Behringer Major: Interdisciplinary Ecology

Florida Bay, USA, has been subjected to a series of blooms of the cyanobacteria

Synechococcus spp. from 1991-1995, 2007, and 2013 – each with a subsequent sponge die-off.

The blooms of the early 1990s killed over 40% of the loggerhead sponges and over 70% of other sponge species throughout western Florida Bay. In addition, winter storms and hurricanes increase the amount of particulate material in the water column for extended periods of time, which appears to cause stress to filter feeding sponges. My goals were to determine if increased water viscosity caused by blooms or turbidity caused by storm events adversely affected sponge filtration. I compared bloom-resistant sponge species: the loggerhead sponge Spheciospongia vesparium and the volcano sponge Tectitethya crypta with bloom-susceptible species: the yellow sponge Spongia barbara, the sheepswool sponge Hippospongia lachne, and the glove sponge

Spongia gaminea. In addition, I characterized the internal canal morphology for each species to determine if differences in response to increased viscosity corresponded with relative survival following the 2007 bloom event. This information is important to improve our understanding of the effects of cyanobacteria blooms on critical hard-bottom habitat and give predictive capabilities to managers regarding the potential effects of blooms as they develop and move throughout Florida Bay.

CHAPTER 1 INTRODUCTION

Stress is “a detrimental or disorganizing influence” (Odum, 1985). Although authors and disciplines differ on the definition of stress, it has been suggested that studying stress ecology would greatly improve our understanding of general ecosystem structure and function (Barrett and Rosenberg, 1978). The impacts of stress can be seen in classic ecological studies such as competition (Connell, 1961) and ecological succession (Sousa, 1979), where the creation of new habitable space and species composition were greatly influenced by physical stress. However, the structural composition of a community is also affected by physiological stresses on individual organisms, such as changes in temperature, nutrients, and salinity (Menge and

Sutherland, 1987). Changes in these physiological aspects can stress and alter the structure and functionality of food-web dynamics, community regulation, and recruitment (Menge and

Sutherland, 1987). Odum (1962) explained that structure and function are two foundational components in ecology, and understanding their interdependence is paramount to understanding natural phenomena. Stress is an integral factor that obscures the connection between these components, and its role has therefore become the focus of attention at multiple environmental scales.

Whether at the organismal scale or above, implications of stress are being studied on marine and coastal systems because of the strong association between observed stress conditions and the changing global climate (Harley et al., 2006). Rapid changes in temperature have been a primary focus of research because of the negative physiological responses observed in many marine organisms (Rousch et al., 2003; Webster et al., 2008). At the individual scale, temperature elevation experiments on diatoms, important organisms in marine food webs, were used to look at changes in lipid content that could in turn affect other organisms that depend on

them for growth and reproduction (Rousch et al., 2003). Exposure to quick spikes in temperature

(2 h) showed changes in fatty acid composition, while longer durations did not have the same effect. At larger scales, stress on coral reefs has drawn attention from scientists and managers alike because of their ecological importance and rate of decline (Pandolfi et al., 2003; Hoegh-

Guldberg et al., 2007) The impact of bleaching due to elevated temperatures and the threat of ocean acidification to the calcium carbonate structure of the corals is a major concern for reef community health (Hoegh-Guldberg et al., 2007). Stress can impact multiple trophic levels linked within a system (Peterson et al., 2006), which forces us to consider what impacts physical and physiological stresses have on the connections between these levels.

Sponges are particularly important in connecting trophic levels on Caribbean reefs, contributing to reef species diversity and abundance, facilitating symbioses with associated microorganisms, and driving benthic-pelagic coupling (Diaz and Rutzler, 2001). For example,

Goeij et al. (2013) studied the paradox of thriving coral reef communities in oligotrophic systems, discovering that sponges serve as a dissolved organic matter (DOM) loop to recycle nutrients for reef fauna. Psammobiontic sponges, some of which can reverse the flow of water through their canals, also link the benthos and water column by creating water circulation through the sediment that generates a nutrient flow for bacteria in the sand patches between reef formations (Rutzler, 1997). Although these cases demonstrate the impacts that sponges have on reef and adjacent habitat ecology, the ecological role of sponges remains understudied (Becerro,

2008; Diaz and Rutzler, 2001). Sponges also thrive in habitats other than reefs and their role in these systems is of similar importance (Peterson et al., 2006).

Sponge mass mortality events. The cause of sponge mortality is often not straightforward. Mass mortalities have been recorded worldwide (Galstoff et al., 1939; Smith,

1939; Butler et al., 1995; Cervino et al., 2006; Gaino et al., 1992; Cebrian et al., 2011) and the speculated causes of these die-offs are diverse. Sponges are legally harvested in the

Mediterranean and Caribbean regions and because of their commercial importance, one of the first recorded instances of sponge mortality occurred in the Bahamas (Galstoff et al., 1939).

Several commercial species were affected by what was described as “fungus-like filaments” infecting the mesohyl of impacted sponges. The die-offs eventually reached Key West, Florida, and later that year a mortality event affected Belize (formerly British Honduras). During the latter event, several commercially harvested species were impacted but other organisms

(including noncommercial sponge species) remained unaffected (Smith, 1939). Analysis of infected sponges revealed the same fungus-like filaments, thus it was suggested that water currents carried the pathogen from the Bahamas to Key West to Belize (Smith, 1939). However, the oceanographic current patterns we are now aware of make this direction of transport unlikely

(Cowen et al., 2006). If a pathogen is suspected as the cause of a sponge mortality event it is important to identify, but the symbiotic bacteria sponges harbor often make distinguishing symbiont from pathogen extremely challenging (Cebrian et al., 2011; Gaino et al., 1992).

Cebrian et al. (2011) studied and described the mass mortality event of Ircinia fasciculata that occurred in the Mediterranean in 2008 and 2009. This case differed from other die-offs seen in the Caribbean in 1939 because the cause was determined as temperature stress. I. fasciculata has a close association with its symbiotic cyanobacteria, making it more susceptible to temperature spikes when photosynthesis is hindered. I. fasciculata mortality was 80-100% in some areas while a sympatric species, the heterotrophic bacteria-hosting sponge Sarcotragus spinosulum, suffered insignificant mortality (Cebrian et al., 2011). During a previous epizootic off the coast of Italy, commercially important species of the genera Spongia and Hippospongia

suffered high mortality, but it was again difficult to distinguish the causal agent because bacteria penetrating the sponge fibers may have been pathogenic or symbiotic (Gaino et al., 1992).

However, when tissue samples from healthy and infected Spongia officinalis were compared an unidentified bacterium was found only in the unhealthy sponges.

From 1996 to 2000, Ianthella basta sponges were negatively affected by tissue lesions in

Papua New Guinea (Cervino et al., 2006). Investigation revealed that five bacteria isolates were associated with the lesions and only sponges within 20 km of shore were infected, leading to the hypothesis that pesticides from near-shore deforestation and palm oil plantations may have been the cause. Multiple comparative studies between different pesticides and the bacteria isolates are cited to support this theory but none were conclusive. This highlights that anthropogenic inputs can have indirect environmental effects but that identifying the source of the impact is not often clear. Kinne (1980) compiled an extensive review on marine diseases, including many that affect sponges, and noted the main causes of disease and mortality in sponges are from bacteria.

Florida Bay, USA, has been subjected to a series of algae blooms of the cyanobacterium

Synechococcus spp. from 1991-1995, 2007, and 2013 each with a subsequent sponge die-off

(Butler et al., 1995; Lynch and Phlips, 2000, Butler et al., 2015). The blooms during the 1990s killed over 40% of the loggerhead sponges Spheciospongia vesparium and over 70% of other sponge species throughout western Florida Bay (Butler et al., 1995), and much of the decimated sponge community had not recovered by the time of the next bloom in 2007 (Peterson et al.,

2006). Florida Bay is a unique estuary system located below the Everglades. This shelf lagoon is

1600 km2 in area with an average depth of 3 m and the shallow calcium carbonate basins that make up the Bay are a mosaic of hard bottom and seagrass bed habitats (Robblee et al., 1991;

Butler et al., 1995). The basins are surrounded by mud banks that restrict water circulation

(Robblee et al., 1991; Fourqurean & Robblee, 1999) and weaken tidal influence (Robblee et al.,

1991). The seagrass beds are mainly comprised of Thalassia testudinum, while the hard bottom habitats are dominated by a variety of sponge species, octocorals, and small hard corals. The sponges are not only important because they are a main component of the bay system and provide an essential ecosystem function by filtering the water, but also because they provide habitat structure for a multitude of juvenile fish and crustacean populations (Butler et al., 1995).

The loss of the sponge communities in the bay has been hypothesized to have caused system- wide trophic dysfunction, including phytoplankton blooms with greater frequency and magnitude

(Peterson et al., 2006).

Investigations into the cause of these algae blooms required a broad-scale view of

Florida’s intricate watershed that links rivers and lakes found in the center of the state to the Bay and reef tract that define the south portion of the peninsula. Water sheet flow from the

Everglades empties into the northern portion of the Bay, resulting in an influx of freshwater to the area. Uncharacteristic hypersaline conditions in the area were therefore partially implicated as the cause of mass die-offs of seagrass beds noted in 1987 (Robblee et al., 1991), events that were implicated as the initial spark for Synechococcus blooms because of the large amounts of phosphorus released into the water column (Phlips, pers. comm.). T. testudinum die-offs were patchy between 1984 and 1994, with the largest density declines occurring in central and western

Florida Bay (Hall et al., 1999). These reports were consistent with algae bloom patterns observed in the Bay, which may have further contributed to seagrass mortality by increasing light attenuation (Phlips et al., 1995). Although the connection between mass sponge mortalities and

Synechococcus blooms are undeniable, no direct causal relationship has been established (Lynch

and Phlips, 2000). Laboratory experiments have been unsuccessful in understanding this relationship, possibly because of short-term nature of the experiments (Lynch & Phlips, 2000).

Synechococcus produces sticky mucilage as a product of its sheath, which is composed of a carbohydrate polymer that encapsulates the algal cell (Phlips et al., 1989). At high bloom densities, this mucilage becomes concentrated as the algae begin to senesce. It has been suggested that this mucilage is capable of inhibiting sponge function, ultimately leading to sponge mortality. Sponges of the class demospongiae have intricate canal and chamber systems that could potentially become restricted by the mucilage and prevent sufficient oxygenation of the sponge cells. Food particle uptake by choanocytes and subsequent archaeocyte digestive functions could also be reduced to a critical point that results in sponge mortality (Butler et al.,

1995). However, short duration experiments showed that sponges could efficiently filter young

Synechococcus algae blooms that do not produce mucilage (Lynch and Phlips, 2000).

Spheciospongia vesparium is a key species affected by the blooms because these sponges house many species of invertebrates in their canals, at their bases, and pump water at an estimated rate of 0.114 ± 0.019 s-1 l-1 (Wall et al., 2012). Structurally, the species is barrel- shaped, and individuals can reach sizes of up to 1 m in diameter, dominating the hard bottom communities in Florida Bay in terms of biomass. They have average internal canal sizes of 0.5 to1.0 cm, even if the individual is holistically small (Westinga and Hoetjes, 1981). They are known to be negatively affected by Synechococcus blooms, with nearly 100% mortality in regions of Florida Bay most heavily affected by the Synechococcus blooms in 2007 (Butler and

Behringer, unpublished data). Although S. vesparium was negatively impacted throughout the bloom-impacted area, other sponge species, especially those commercially harvested, suffered even higher mortality.

Cyanobacteria blooms are clearly harmful to sponge communities in Florida Bay, but are not the only factors contributing to mortality. Large storm events such as hurricanes, have significantly decreased populations, and have had varying levels of impact depending on the sponge species (Stevely et al., 2011; Cropper and DiResta, 1999). Long-term surveys of sponge populations in the Bay over a 15-year period (1991-2006) documented the change in species abundance in response to Synechococcus blooms and Hurricane Wilma, which hit as a Category

3 storm in 2005 (Stevely et al., 2011). Susceptibility to sponge mortality was correlated with structural differences and exposure to wave energy, but mortality was seen at every site. Certain sponge species in Biscayne Bay, FL, suffered 50-100% mortality post Hurricane Andrew in areas affected by scouring or covered by re-suspended sediments (Cropper and DiResta, 1999).

Sponges tend to grow in areas with low sediment deposition (Cropper and DiResta, 1999), which leads us to suggest that looking at impacts of particle resuspension on sponge functionality could help us understand how sponges respond and cope with storm-related stress.

Therefore, I conducted experiments from 2013-2015 to examine the effects of simulated sediment resuspension and cyanobacteria blooms on sponge species from Florida Bay. I used five species to test the effects of two particular stress factors, increased water viscosity and sediment load, on sponge function. I also characterized the internal canal architecture of three sponge species to determine how this architecture corresponds with their survival following

Synechococcus blooms.

Objective 1: To determine if increased water viscosity, comparable to the mucilage produced by senescing Synechococcus, restricts sponge canals, chambers and/or choanocytes, causing reduced pumping and increased sponge mortality. If so, variation to susceptibility may potentially be seen

as well. I hypothesized that increased water viscosity would reduce pumping in all sponge species.

Objective 2: To determine if increased water column particulate load decreased sponge pumping. I hypothesized that this factor would reduce pumping among all sponge species.

Objective 3: To determine if the size of the internal canal architecture of a sponge species corresponds with its susceptibility to mortality from Synechococcus spp. blooms. I hypothesized that the most susceptible sponge species would have the smallest canal architecture.

CHAPTER 2 METHODS

Viscosity Stress Trials

Sponge Collection

During July 2013 and October 2014, Scheciospongia vesparium sponges were cut and secured to patio pavers to heal and regrow in near their original location in the hard-bottom of

Florida Bay. This was done by cutting whole individuals from the sea floor and slicing them into multiple, smaller pieces approximately 20 cm x 10 cm. The pieces were tightly secured to small pavers using plastic zip-ties, while submerged in seawater-filled bins onboard the research vessel. These sponge cuttings were placed back into the water and to heal for up to one year.

During June, July and October of 2014, Hippospongia lachne and Spongia barbara were removed from the sea floor and secured in a similar fashion as that of S. vesparium. These individuals were not cut into smaller pieces but remained whole because of their suspected susceptibility to stress. These sponges were set on the bottom and allowed to heal for up to a month. At the end of July 2014, pavers with live sponges were moved from their cutting sites and placed in Long Key Bight, FL, for ease of accessibility during experiments. This new site was on the ocean side of the Florida Keys, surrounded by banks to allow for influxes of cooler, off-shore water and to avoid boating traffic that may stress the sponges.

Experimental Setup

Experimental 37.8-liter tanks (n=6) were set up inside of Goshen Marine Laboratory, located on Long Key, FL. Offshore water was collected as needed during the height of incoming tide on the ocean side of the Florida Keys and filtered through a 0.35 micron filter to remove most plankton and particulates before being placed in the tanks. Tank water temperatures (24.4 ±

0.4º C) were allowed to acclimate indoors overnight to ensure cool and less stressful conditions

for sponges. All tanks were aerated and salinity was maintained at the ambient salinity of (41 ± 1 psi) to keep conditions consistent across tanks. Sponges were collected in the early morning from

Long Key Bight, placed in water-filled buckets, and transported immediately back to the laboratory. One sponge was placed in each tank and specimens were allowed to acclimate to their new environment for 2 h.

Batches of xanthan gum were made each morning by heating filtered sea water and thoroughly mixing in powdered gum to create a hyper-concentrated suspension. Equal volumes of this suspension were distributed to each treatment tank until viscosity readings (1.43 ± .29 cp) were comparable to that of the mucilage produced by Synechococcus sp. at bloom density

(Phlips et al., 1989). Control tanks received equal volumes of additional filtered sea water to standardize inoculation procedure and maintain similar volumes of water in each tank. Viscosity readings were taken using a Thermo Scientific brand Gilmont Falling-Ball (size no. 1) viscometer. Experimental tank water was carefully pipetted into the glass tubing, a steel ball

(8.02 g/mL) was inserted and allowed to fall while time, in seconds, was recorded. This time measurement was inputted to the given equation, µ = K*(휌t –휌)*t, where µ is the viscosity in centipoise (cp); K is the viscometer constant; 휌t is the density of the ball; 휌 is the density of the liquid; and t is the time of descent (in minutes). Density of the liquid was determined by first weighing a dry cuvette, pipetting in a known volume of tank water, and then reweighing the cuvette. This process was repeated for each experimental and control tank at the start of the experiment.

Before the start of every trial, each sponge was tested by injecting it with 0.05-0.10 mm of fluorescein dye at the sponge base to determine that the individual was actively pumping and filtering water. The base of a sponge is typically where the ostia are located, the pores through

which an individual intakes water and food particles. If an individual was not pumping at the beginning of the experiment it was not used.

Immediately after adding xanthan gum or sea water (control) each sponge was again tested to determine if it was pumping (considered time=0). Fluorescein dye quickly colors the tank water and cannot be used more than once on a sponge; therefore, red and blue food coloring dyes were subsequently used throughout each trial. Each sponge was tested every hour for pumping and a yes/no result was recorded. Because of their complex internal canal system, sponges sometimes needed to be tested at multiple base points to ensure that pumping was accurately recorded. Throughout trials, sponges would close their oscula, or ex-current canals, so testing multiple points was essential. Trials lasted for eight to ten hours, depending on the health state of the individuals. At the end of each trial, the sponges were removed from the tanks and the water displacement volumes were recorded for each individual. The experimental setup was immediately broken down and all components were cleaned to reduce the risk of residual xanthan gum being present for subsequent trials.

Statistical Analysis

A one-way ANOVA was used to test for the effects of viscosity treatment and time on the proportion of actively pumping sponges from t = 0 to 600 min. Since yes/no recordings translate into binary data, ones (yes) and zeroes (no) were averaged at each hourly time step for each species of sponges, for both treatment and control groups. A Pearson chi square test was then used to compare treatment and control groups at these time steps.

Sediment Stress Trials

Sponge Collection

Spheciospongia vesparium sponges from the same array created for the xanthan gum trials were also used for sediment trials. During the summer 2014, Tectitethya crypta sponges

were removed from the seafloor on the ocean side of Lower Matecumbe Key, Florida.

Individuals were kept whole due to their small size and were zip-tied to pavers in the same fashion described previously, and placed in arrays on location to heal for a month. S. vesparium and T. crypta were then transferred to a single location in Long Key Bight, Florida, for ease of accessibility during experiments.

Experimental Setup

Experimental tanks (n=8) were set up inside of Goshen Marine Laboratory and offshore water was collected and filtered as described above before being placed in the tanks. Water temperatures (27.6 ± 0.7º C) were allowed to acclimate indoors overnight to ensure cool and less stressful conditions for individual sponges. All tanks were aerated and salinity readings were taken to keep conditions consistent across tanks. Each experimental tank was equipped with two aerators that were positioned around the interior perimeter of the glass to create enough lift to keep sediment particles suspended in the water column. Sponges were collected in the early morning from Long Key Bight, placed in water-filled buckets, and transported immediately back to the laboratory. One sponge was placed in each tank and specimens were allowed to acclimate to their new environment for two hours.

Sediment was collected from the bayside of Long Key. Only the top layer was removed from the seafloor, as this thin veneer contains the particles that would readily become re- suspended in the water column during a storm event. Approximately 8 oz of sediment were introduced into the treatment tanks to extremely reduce the visibility in each tank. Visibility was measured by placing a ruler along the outside edge of the tank and moving a brightly-colored object along the inside edge until the object was no longer visible. Control tanks were mixed with additional filtered sea water to maintain volume. Before the start of each experiment, each

sponge was tested for pumping as above and if it was not pumping it was not used in the experiment.

Immediately after inoculation by either play sand or sea water, each sponge was again tested to determine if it was pumping (t=0). Red and blue food coloring dyes were used throughout each trial to accurately confirm whether or not an individual was pumping. Each sponge was tested every 15 min for 2 h and a yes/no answer was recorded for visible pumping.

During the first hour, aeration remained on to simulate sediment resuspension during a storm event, but was turned off after the 60-min measurement was recorded. The lack of aeration during the second hour allowed the sand to settle, progressively allowing sediments to settle to the bottom and simulating immediate, post-storm conditions. At the end of the trial, the sponges were removed from the tanks and the water displacement volumes were recorded. The experimental setup was immediately broken down and all components were cleaned to reduce the risk of residual play sand being present for subsequent trials.

Statistical Analysis

Ones and zeroes were averaged at each 15-min time step, for each species of sponges, for both treatment and control groups. Since the data collected is the same type as mentioned above, the same statistical analysis was performed.

Internal Canal Architecture Analysis

Sponge Image Collection

Between March and October 2014, the sponges of the species S. vesparium (n=18), H. lachne (n=13), S. barbara (n=20), T. crypta (n=19), and Spongia graminea (n=16) were removed from the seafloor bayside of Marathon and both bay and ocean-side of Long Key, Florida. These individuals were transported back to Long Key and sliced vertically into 1 cm wide sections, starting from the exterior of the sponge and progressing toward the middle of the specimen. This

methodology was adapted and modified from Duffy (1992), where they sliced sponges into thin cross sections, covered each section with a clear acetate sheet, and outlined each canal with a marker. For this analysis, each slice was laid down flat and individually photographed so that the internal canal structure was completely exposed. Three to six slices were taken per individual to account for the range in canal sizes from the outer edge to the interior of the sponge and both horizontal and vertical sections were made to analyze variations in internal structure. Vertical sections include the small incurrent openings located near the base of the sponge that then branch into larger, filter-feeding canals. Horizontal sections, contrarily, do not contain these incurrent openings other than on the edge of the section and are instead characterized by the ex-current canals that form from the top of the sponge down toward its base. Therefore, images from each species were analyzed separately as either vertical or horizontal images. Each photograph that was taken was subsequently uploaded and processed using an open-source image analysis program called ImageJ.

Image Analysis

ImageJ can be tailored to recognize precise scales; therefore, every image taken had a ruler visible next to the sponge slice that could then be used to create a pixel to millimeter scale.

By drawing a line from the top of one end of the ruler to the top of the other end, a linear distance was obtained in terms of number of pixels and converted into millimeters. Thus each image was scaled which allowed me to measure the area of each section by manually outlining the sponge image and then applying the pixel/mm ratio to create a catalogue of total area and the areas of the internal canals. I scrolled through each image and drew the outline of every canal that was completely perpendicular to the sponge slice. Standardizing the selection of canals to measure in this way was important due to the internal canal intricacies found in the order demospongiae.

I analyzed mean canal area, the percent of porous area, and the average number of canals for both vertical and horizontal sections for each species. Mean canal area was a basic average of each canal area measured for every section. There were natural variations within and among species so to account for this, the mean canal area was divided into the total area measured for each section to produce the percentage of porous area, relative to the total area of the sponge.

These first two analyses did not account for the ranges in canal area seen among the five sponge species used. Two sponge species could theoretically have the same percent of porous area but could have widely differing canal numbers and sizes. Therefore, to further characterize internal morphology, the number of canals from each section were summed and then divided by the total area to give the number of canals per unit area.

Lastly, these analyses were performed separately on the outermost slice of the vertical sections to determine if this would be a better comparison between species because of the large variability in morphology between and among species, and the first slice could act as a better standard measure. The outmost surface might also be a better comparison since it is apt to be the first area affected by high viscosity or suspended sediment. A similar comparison with the outermost horizontal slice was not possible do to presence of oscula and the more variable nature of the upper surface of most sponges.

Statistical Analysis

In order to avoid pseudoreplication, canal area measurements from all slices from each sponge were averaged to a singular mean value. The mean values were then log-transformed to meet the assumption of a normal distribution and analyzed using a one-way ANOVA that tested for a significant difference in canal area means among the five sponge species. A Tukey’s HSD test was then used to determine which treatments differed. Separate analyses were performed on

the mean values from vertical sections, horizontal sections, and the outermost slice only from vertical sections.

The percent of porous area, relative to the total area, averaged for each individual sponge was log-transformed to meet the same assumption of normality and analyzed using a one-way

ANOVA. This analysis tested for a significant difference in porous area among species, and a subsequent Tukey’s post-hoc test determined which treatments differed.

The ratio of the number of canals per unit area for each individual sponge was likewise log-transformed and analyzed using a one-way ANOVA. This analysis tested for a significant difference in the number of canals per cm2 area among the five species test and a Tukey’s post- hoc test revealed which treatments differed.

Figure 2-1. Tank design to test sponges in the xanthan gum and sediment stress trials. Aeration placement is pictured to show how air bubbles do not interfere with sponge filtration.

CHAPTER 3 RESULTS

Viscosity Stress Trials

Spheciospongia vesparium ranged from 110 - 500 mL in volume with a mean of 301 ±

102 mL standard deviation (s.d.). A one-way ANOVA using factors of treatment, time, and the interaction between treatments was significant for both factors and the interaction (Table 3-1).

Because treatment was a significant factor (df = 1, F = 262.75, P < 0.001), a Pearson’s Chi

Square test was then performed to determine the time intervals at which xanthan gum significantly reduced pumping. There were significant differences between treatment and control sponges at every time interval after 60 min (Table 3-2).

Spongia barbara ranged from 100 - 350 mL in volume with a mean of 206 ± 67 mL s.d.

A one-way ANOVA using factors of treatment, time, and the interaction between treatment and time was significant for both factors and the interaction (Table 3-3). Because treatment was a significant factor (df = 1, F = 199.49, P < 0.001), a Pearson’s Chi Square test was then performed to show the time intervals at which xanthan gum significantly reduced pumping. There were significant differences between treatment and control sponges at every time interval after 120 min (Table 3-4).

Hippospongia lachne ranged from 100 – 625 mL in volume with a mean of 274 ± 140 mL s.d. A one-way ANOVA using factors of treatment, time, and the interaction between treatment and time revealed a significant difference for both treatment and time, but not the interaction (Table 3-5). Because treatment was a significant factor (df = 1, F = 273.73, P <

0.001), a Pearson’s Chi Square test was then performed to show the time intervals at which xanthan gum significantly reduced pumping. There were significant differences between treatment and control sponges at every time interval (Table 3-6).

Sediment Stress Trials

Spheciospongia vesparium ranged from 45 - 400 mL in volume with a mean of 181 ±

115 mL s.d. Two, one-way ANOVAs were performed using factors of treatment, time, and the interaction between treatment and time. The first analysis tested time = 0-60 min, when aeration was on, and the second analysis tested time = 60-120 min, when aeration was off. Both analyses revealed that time was a significant factor, as was the interaction of treatment and time (Table 3-

7). Because the interaction was significant (df = 1, F = 9.259, P = 0.0032; df = 1, F = 5.198, P =

0.025; for aeration on and aeration off, respectively), a Pearson’s Chi Square test was performed to show the time intervals at which sediment significantly reduced pumping. There was a significant difference between treatment and control sponges at only the 60 min stage (Table 3-

8).

Tectitethya crypta ranged from 25 – 340 mL in volume with a mean of 122 ± 91 mL s.d.

Two, one-way ANOVAs used factors of treatment, time, and the interaction between treatment and time. Again, analyses looked at aeration on and aeration off, respectively. Results showed that treatment and time were significant factors while aeration was on (Table 3-9). Because treatment was a significant factor (df = 1, F = 9.397, P = 0.0031) a Pearson’s Chi Square test was performed to show the time interval at which sediment significantly reduced pumping. Results revealed a difference at the 30 min time interval (Table 3-10).

Internal Canal Architecture Analysis

Mean Canal Area

Mean canal area data were log-transformed to correct for non-normal distribution for analyses on both vertical and horizontal sections. A one-way ANOVA performed on mean vertical sections from the five sponge species showed a significant difference in canal area (df =

4, F = 12.45, P < 0.001; Table 3-11). A Tukey’s post-hoc test revealed significant differences

among some but not all sponge species (Table 3-12 and Figure 3-6). S. vesparium, H. lachne, and S. barbara, having the largest canals, did not significantly vary from one another. S. graminea differed from S. vesparium and H. lachne (P = 0.0081 and P = 0.037, respectively) but not from S. barbara or T. crypta. T. crypta, having the smallest canal area, varied from S. vesparium, H. lachne, and S. barbara (P < 0.001, P < 0.001, and P = 0.0015, respectively).

A one-way ANOVA was subsequently performed on the outmost sections of each vertical slice (df = 4, F = 9.591, P < 0.001). A Tukey’s post-hoc test revealed the same groupings among sponge species seen for mean vertical canal area (Table 3-14 and Figure 3-7). S. vesparium, H. lachne, and S. barbara again did not significantly vary from one another. S. graminea differed from S. vesparium and H. lachne (P = 0.044 and P = 0.049, respectively) but not from S. barbara or T. crypta. T. crypta varied from S. vesparium, H. lachne, and S. barbara

(P < 0.001, P < 0.001, and P = 0.0035, respectively). Although I hypothesized that the first slice might be a better ‘standard’ section to compare, analyses revealed the same grouping patterns for both the averaged vertical canal sizes and the outermost vertical section.

A one-way ANOVA performed for horizontal sections on mean canal area showed a significant difference among species (df= 4, F = 20.76, P < 0.001; Table 3-15). A Tukey’s post- hoc test (Table 3-16 and Figure 3-8) revealed that S. vesparium, H. lachne, and S. barbara again did not significantly differ from each other. S. graminea significantly varied from S. vesparium,

H. lachne, S. barbara, and T. crypta (P = 0.0018, P = 0.0023, P < 0.001, and P = 0.033, respectively). T. crypta had the smallest horizontal mean canal area, significantly varying not only from S. graminea, but from S. vesparium, H. lachne, and S. barbara as well (P < 0.001, P <

0.001, and P < 0.001, respectively).

Percent of Porous Area

Percent of porous area, relative to total area, data were log-transformed to correct for non-normal distribution for analyses on both vertical and horizontal sections. A one-way

ANOVA performed on vertical sections from the five sponge species showed a significant difference in porous area (df = 4, F = 18.61, P < 0.001). A Tukey’s post-hoc test revealed significant differences among some but not all sponge species (Table 3-18 and Figure 3-9). S. vesparium, H. lachne, and S. barbara, having the highest percentages of porous are, did not significantly vary from one another. S. graminea differed from S. vesparium and T. crypta (P =

0.0203 and P < 0.001, respectively). T. crypta, having the lowest percentage of porous area, significantly differed from S. vesparium, H. lachne, and S. barbara as well (P < 0.001, P <

0.001, and P < 0.001, respectively).

Results from a one-way ANOVA performed on horizontal sections showed a significant difference among sponge species (df = 4, F = 11.85, P < 0.001). A Tukey’s post-hoc analysis revealed that every species except for T. crypta did not differ in the percentage of porous area

(Table 3-20 and Figure 3-10). T. crypta had a significantly lower percentage, relative to from S. vesparium, H. lachne, S. barbara, and S. graminea (P < 0.001, P < 0.001, P < 0.001, and P =

0.0070, respectively).

Number of Canals per Unit Area

The ratio of the number of canals per unit area for each sponge section was log- transformed to correct for non-normal distribution of data. Results from a one-way ANOVA on vertical sections showed a significant difference among species (df = 4, F = 4.15, P = 0.0071). A subsequent Tukey’s post-hoc test revealed differences among a few species (Table 3-22 and

Figure 3-11). S. graminea had the relatively highest number of canals per cm2 sponge area,

significantly varying from H. lachne and T. crypta (P = 0.01 and P = 0.031, respectively), which had the fewest.

Results from a one-way ANOVA performed on horizontal sections showed that there was not a significant difference in number of canals per cm2 area among sponge species (df = 4, F =

1.518, P = 0.216). A Tukey’s post-hoc test revealed similar trends seen in the vertical sections, with S. graminea averaging more canals per unit area relative to the other sepcies (Table 3-24 and Figure 3-12).

Table 3-1. Results of a one-way ANOVA testing for the effects of viscosity water treatment and time on the proportion of Spheciospongia vesparium actively pumping at 60 min intervals from t = 0 to 600 min. Water treatments included seawater with xanthan gum added to increase viscosity or seawater only control. An asterisk indicates a significant affect. Factor df Mean square F value P value Treatment 1 21.954 262.75 * < 0.001 Time 1 3.234 38.71 * < 0.001 Treatment x time 1 1.552 18.58 * < 0.001 Error 156 0.084

Table 3-2. Results from a Pearson’s Chi Square test performed on each time interval that Spheciospongia vesparium was exposed to seawater with xanthan gum added (n=10), compared to those exposed to seawater only (n=5). An asterisk indicates a significant decrease in pumping for the xanthan gum treatment. Time (minutes) df Chi2 value Adj. P value 60 1 1.8375 0.18 120 1 11.25 * 0.0010 180 1 11.25 * 0.0010 240 1 11.25 * 0.0010 300 1 8.5714 * 0.0045 360 1 10.9091 * 0.0025 420 1 15 * < 0.001 480 1 11.25 * 0.0010 540 1 15 * 0.0010 600 1 10 * 0.0050

Table 3-3. Results of a one-way ANOVA testing for the effects of viscosity water treatment and time on the proportion of Spongia barbara actively pumping at 60 min intervals from t = 0 to 600 min. Water treatments included seawater with xanthan gum added to increase viscosity or seawater only control. An asterisk indicates a significant affect. Factor df Mean square F value P value Treatment 1 27.565 199.49 * < 0.001 Time 1 5.867 42.46 * < 0.001 Treatment x time 1 3.302 23.90 * < 0.001 Error 345 0.138

Table 3-4. Results from a Pearson’s Chi Square test performed on each time interval that Spongia barbara was exposed to seawater with xanthan gum added (n=19), compared to those exposed to seawater only (n=13). An asterisk indicates a significant decrease in pumping for the xanthan gum treatment. Time (minutes) df Chi2 value Adj. P value 60 1 1.7573 0.36 120 1 4.5219 0.051 180 1 5.6556 * 0.021 240 1 11.4687 * 0.0020 300 1 9.8446 * 0.0030 360 1 17.5654 * 0.001 420 1 20.9776 * < 0.001 480 1 14.0722 * < 0.001 540 1 18.1483 * < 0.001 600 1 22.8571 * < 0.001

Table 3-5. Results of a one-way ANOVA testing for the effects of viscosity water treatment and time on the proportion of Hippospongia lachne actively pumping at 60 min intervals from t = 0 to 600 min. Water treatments included seawater with xanthan gum added to increase viscosity or seawater only control. An asterisk indicates a significant affect. Factor df Mean square F value P value Treatment 1 34.76 273.730 * < 0.001 Time 1 2.05 16.146 * < 0.001 Treatment x time 1 0.49 3.861 0.050 Error 296 0.13

Table 3-6. Results from a Pearson’s Chi Square test performed on each time interval that Hippospongia lachne was exposed to seawater with xanthan gum added (n=16), compared to those exposed to seawater only (n=12). An asterisk indicates a significant decrease in pumping for xanthan gum treatments. Time (minutes) df Chi2 value Adj. P value 60 1 13.5882 * < 0.001 120 1 7.4786 * 0.014 180 1 14.5833 * 0.0010 240 1 11.4991 * 0.0045 300 1 17.082 * < 0.001 360 1 14.1167 * < 0.001 420 1 14.0486 * 0.0015 480 1 14.1167 * < 0.001 540 1 13.4697 * 0.0010 600 1 20.3077 * < 0.001

Table 3-7. Results of two, one-way ANOVAs testing for the effects of sediment treatment and time on Spheciospongia vesparium. The first analysis tested for effects with on-going aeration and particle re-suspension. Sediment treatments included the addition of sandy sediment to seawater or seawater only control. An asterisk indicates a significant affect. Variable Factor df Mean square F value P value Aeration on Treatment 1 0.494 3.215 0.077 Time 1 3.676 23.914 * < 0.001 Treatment x time 1 1.424 9.259 * 0.0032 Error 81 0.154

Aeration off Treatment 1 0.4765 2.505 0.12 Time 1 1.9059 10.021 * 0.0022 Treatment x time 1 0.9886 5.198 * 0.025 Error 1 0.1902

Table 3-8. Results from a Pearson’s Chi Square test performed on each time interval that Speciospongia vesparium was exposed to the sediment treatment (n=9), compared to those exposed to seawater only (n=8). An asterisk indicates a significant decrease in pumping. Time (minutes) df Chi2 Value Adj. P value 0 1 1.1953 0.47 15 1 0.0079 1.000 30 1 0.0182 1.000 45 1 1.4462 0.35 60 1 7.1373 * 0.022 75 1 0.5542 0.64 90 1 0.0182 1.000 105 1 0.0079 1.000 120 1 0.0182 1.000

Table 3-9. Result of two, one-way ANOVAs testing for the effects of sediment treatment and time on Tectitethya crypta. The first analysis tested for effects with on-going aeration and particle re-suspension. Sediment treatments included the addition of sandy sediment to seawater or seawater only control. An asterisk indicates a significant affect. Variable Factor df Mean square F value P value Aeration on Treatment 1 1.9286 9.397 * 0 .0031 Time 1 1.5000 7.309 * 0.0086 Treatment x time 1 0.0000 0.000 1.0000 Error 71 0.2052

Aeration off Treatment 1 0.3810 1.901 0.17 Time 1 0.0267 0.133 0.72 Treatment x time 1 0.0305 0.152 0.70 Error 71 0.2004

Table 3-10. Results from a Pearson’s Chi Square test performed on each time interval that Tectitethya crypta was exposed to the sediment treatment (n=8), compared to those exposed to seawater only (n=7). An asterisk indicates a significant decrease in pumping. Time (minutes) df Chi2 value Adj. P value 0 1 0.7143 0.60 15 1 1.7267 0.32 30 1 5.4018 * 0.040 45 1 0.6027 0.56 60 1 1.7593 0.29 75 1 0.6027 0.57 90 1 0.0446 1.000 105 1 0.1339 1.000 120 1 2.6374 0.19

Table 3-11. Results of a one-way ANOVA testing for differences in mean canal area among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta for vertical sponge sections. An asterisk indicates a significant affect. Factor df Mean square F value P value Species 4 1.9955 12.45 * < 0.001 Error 36 0.1603

Table 3-12. Results from a Tukey’s post-hoc analysis (T) of differences in mean canal area for vertical sponge sections. Mean canal area, area range, and number of individuals used (n) are given. Species Mean canal area (mm2) Range (mm2) T n S. vesparium 12.84 1.51 - 31.51 A 8 H. lachne 7.14 4.14 - 10.69 A 6 S. barbara 4.79 0.65 - 10.01 AB 8 S. graminea 2.24 0.48 - 6.03 BC 9 T. crypta 0.88 0.18 - 4.34 C 10

Table 3-13. Results from a one-way ANOVA testing for differences in canal area among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta for the outermost slice from vertical sections. An asterisk indicates a significant affect. Factor df Mean square F value P value Species 4 2.766 9.591 * < 0.001 Error 33 0.2884

Table 3-14. Results from a Tukey’s post-hoc analysis (T) of differences in canal area for the outermost slice from vertical sections. Mean canal area, area range, and number of individuals used (n) are given. Species Mean canal area (mm2) Range (mm2) T n S. vesparium 10.93 1.19 - 15.51 A 6 H. lachne 7.72 1.98 - 12.60 A 6 S. barbara 4.09 2.09 - 6.70 AB 6 S. graminea 2.94 0.16 - 15.95 BC 9 T. crypta 1.15 0.07 - 9.62 C 11

Table 3-15. Results from a one-way ANOVA testing for differences in mean canal area among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta for horizontal sponge sections. An asterisk indicates a significant affect. Factor df Mean square F value P value Species 4 1.4833 20.76 * < 0.001 Error 39 0.0714

Table 3-16. Results from a Tukey’s post-hoc analysis (T) of differences in mean canal area for horizontal sponge sections. Mean canal area, area range, and number of individuals used (n) are given. Species Mean canal area (mm2) Range (mm2) T n S. vesparium 3.24 1.03 - 6.63 A 10 H. lachne 3.32 1.77 - 4.62 A 7 S. barbara 5.00 0.57 - 8.25 A 12 S. graminea 0.99 0.49 - 1.47 B 7 T. crypta 0.46 0.13 - 1.06 C 8

Table 3-17. Results from a one-way ANOVA testing the differences in the percent of porous area relative to total area of a vertical section among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. An asterisk indicates a significant affect. Factor df Mean Square F value P value Species 4 2.6106 18.61 * < 0.001 Error 36 0.1403

Table 3-18. Results from a Tukey’s post-hoc analysis (T) of differences in the percent of porous area relative to total area of a vertical section. Percent of porous area and number of individuals used (n) are given. Species Porosity (%) T n S. vesparium 3.42 A 8 H. lachne 1.68 AB 6 S. barbara 0.91 AB 8 S. graminea 0.70 B 9 T. crypta 0.14 C 11

Table 3-19. Results from a one-way ANOVA testing the differences in the percent of porous area relative to total area of a horizontal section among S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. An asterisk indicates a significant affect. Factor df Mean square F value P value Species 4 1.5313 11.85 * < 0.001 Error 39 0.1293

Table 3-20. Results from a Tukey’s post-hoc analysis (T) of differences in the percent of porous area relative to total area of a horizontal section. Percent of porous area and number of individuals used (n) are given. Species Porosity (%) T n S. vesparium 0.85 A 10 H. lachne 0.82 A 7 S. barbara 1.38 A 12 S. graminea 0.52 A 7 T. crypta 0.11 B 8

Table 3-21. Results from a one-way ANOVA testing the differences in the mean number of canals per cm2 area for vertical sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. An asterisk indicates a significant affect. Factor df Mean square F value P value Species 4 0.13799 4.15 * 0.0071 Error 37 0.03325

Table 3-22. Results from a Tukey’s post-hoc analysis (T) of differences in the mean number of canals per cm2 area for vertical sections. Number of canals and individuals (n) are given. Species Nbr of canals/ cm2 T n S. vesparium 0.31 AB 8 H. lachne 0.18 B 6 S. barbara 0.24 AB 8 S. graminea 0.41 A 9 T. crypta 0.23 B 11

Table 3-23. Results from a one-way ANOVA testing the differences in the mean number of canals per cm2 area for horizontal sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Factor df Mean square F value P value Species 4 0.11606 1.518 0.216 Error 39 0.07644

Table 3-24. Results from a Tukey’s post-hoc analysis (T) of differences in the mean number of canals per cm2 area for vertical sections. Number of canals and individuals (n) are given. Species Nbr of canals/ cm2 T n S. vesparium 0.29 A 10 H. lachne 0.24 A 7 S. barbara 0.30 A 12 S. graminea 0.52 A 7 T. crypta 0.20 A 8

* * * * * * * * * 1

0.8

0.6 Trt Ave (n=10) 0.4 Cntrl Ave (n=5)

Pumping Pumping (percentage) 0.2

0 0 60 120 180 240 300 360 420 480 540 600 Time (mins)

Figure 3-1. Mean pumping activity over time of Spheciospongia vesparium exposed to xanthan gum (treatment) versus S. vesparium exposed to seawater only (control). Asterisks indicate a significant decrease in pumping in treatment sponges, relative to control sponges.

1 * * * * * * * *

0.8

0.6 Trt Ave (n=19) 0.4 Cntl Ave (n=13)

Pumping Pumping (percentage) 0.2

0 0 60 120 180 240 300 360 420 480 540 600 Time (mins)

Figure 3-2. Mean pumping activity over time of Spongia barbara exposed to xanthan gum (treatment) versus S. barbara exposed to seawater only (control). Asterisks indicate a significant decrease in pumping in treatment sponges, relative to control sponges.

* * * * * * * * 1 * * *

0.8

0.6 Trt ave (n=16) 0.4 Cntl ave (n=12)

Pumping Pumping (percentage) 0.2

0 0 60 120 180 240 300 360 420 480 540 600 Time (mins)

Figure 3-3. Mean pumping activity over time of Hippospongia lachne exposed to xanthan gum (treatment) versus H. lachne exposed to seawater only (control). Asterisks indicate a significant decrease in pumping in treatment sponges, relative to control sponges.

0.8 *

0.6

Trt Ave (n=9) 0.4 Cntrl Ave (n=8)

Pumping Pumping (Percentage) 0.2

0 0 15 30 45 60 75 90 105 120 Time (mins)

Figure 3-4. Mean pumping activity over time of Spheciospongia vesparium exposed to sediment (treatment) versus S. vesparium exposed to seawater only (control). The dashed line represents when aeration was turned off. Asterisks indicate a significant decrease in pumping in treatment sponges, relative to control sponges.

0.8 *

0.6

Trt Ave (n=8) 0.4

Cntl Ave (n=7) Pumping Pumping (Percentage) 0.2

0 0 15 30 45 60 75 90 105 120 Time (mins)

Figure 3-5. Mean pumping activity over time of Tectitethya crypta exposed to sediment (treatment) versus T. crypta exposed to seawater only (control). The dashed line represents when aeration was turned off. Asterisks indicate a significant decrease in pumping in treatment sponges, relative to control sponges.

16 A

) n=8 2 12 A n=6 8 AB n=8 BC 4 n=9 C

n=10 MeanCanalArea (mm 0 S. vesparium H. lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-6. Mean canal area with standard errors bars for vertical cross sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) represented above each bar.

16 n=6

) 2 12 A n=6

8 AB BC n=6 n=9 C 4

MeanCanalArea (mm n=11

0 S. vesparium H. lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-7. Canal area with standard errors bars for the outermost vertical cross section of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) are represented above each bar.

) 2 12

A 8 n=12 A A n=10 n=7 4 B C n=7

MeanCanalArea (mm n=8

0 S. vesparium H. lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-8. Mean canal area with standard errors bars for horizontal cross sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) are represented above each bar.

A 5.0 n=8

4.0

3.0 AB n=6 2.0 AB n=8 B Porous (%)Area n=9 1.0 C n=11 0.0 S. vesparium H. lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-9. Percent of porous space relative to total area with standard errors bars for vertical sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) are represented above each bar.

5.0

4.0

3.0 A 2.0 n=12 A A Porous (%)Area n=10 n=7 A 1.0 n=7 B n=8 0.0 S. vesparium H. lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-10. Percent of porous space relative to total area with standard errors bars for horizontal sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) are represented above each bar.

0.8

2 A 0.6 n=9 AB n=8 AB 0.4 B B n=8 n=6 n=11

0.2 Number Number canals/of cm

0 S. vesparium H. Lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-11. Mean number of canals per cm2 area with standard error bars for vertical sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) are represented above each bar.

0.8 A

n=7

2 0.6

A A n=10 0.4 A n=12 n=7 A n=8

0.2 Number Number canals/of cm

0 S. vesparium H. Lachne S. barbara S. graminea T. crypta Sponge Species

Figure 3-12. Mean number of canals per cm2 area with standard error bars for horizontal sections of S. vesparium, H. lachne, S. barbara, S. graminea, and T. crypta. Tukey’s post-hoc analysis showing significant differences among species and the number of individuals used (n) are represented above each bar.

CHAPTER 4 DISCUSSION

This study aimed to better understand the connection between Synechococcus blooms and subsequent sponge mortality events that occur periodically in Florida Bay. Previous studies have shown declines in sponge biomass, diversity, and function following blooms (Butler et al., 1995;

Wall et al., 2012), but laboratory trials have been unable to determine the specific cause for mortality (Lynch and Phlips, 2000). When exposed to seawater under simulated bloom viscosity, all three species tested (S. vesparium, S. Barbara, and H. lachne) stopped pumping and remained inactive for the duration of the trials. Simulations of storm conditions via sediment resuspension further helped determine how sponges react to stress by showing declines in pumping for both species tested (S. vesparium and T. crypta). Subsequent settling of sediment particles correlated with increased pumping for S. vesparium but not T. crypta. Image analyses of internal morphology quantified differences in canal area for sponge species that ranged in susceptibility to stress conditions. In general, S. vesparium individuals had the largest amount of canal area, followed by H. lachne, S. barbara, S. graminea, and T. crypta, respectively.

It would have been ideal to have used mucilaginous, old-stage Synechococcus cultures as the main treatment considering Lynch and Phlips (2000) showed that sponges could efficiently filter young, non-mucilaginous cells. Therefore, I originally cultured bloom-density levels of old- stage Synechococcus, early-stage Synechococcus, and Nannochlropsis (control food algae) at large quantities for weeklong trials. However, contamination or other unidentified environmental conditions led to repeated culture crashes forcing me to reformulate my methodology and approach to the main objective. This led to the use of a comparable polysaccharide, xanthan gum, to manipulate the viscous properties of the seawater. Xanthan gum has a comparable

viscosity vs. shear rate curve to the carbohydrate produced by Synechococcus (Phlips et al.,

1989), making it the most suitable choice over other thickeners.

Despite the need to use an alternative treatment, my results support decreased pumping rates recorded for S. vesparium in simulated bloom conditions versus areas not experiencing a bloom. The complete cessation of pumping suggests that prolonged exposure to increased viscosity seawater, as occurs during extended bloom conditions, could ultimately lead to sponge death. Results showed that the duration of exposure to the increased viscosity played a lesser, but still significant role in the decreased pumping activity. The subsequent onset of cell starvation, anoxia in the mesohyl causing stress on symbiotic microbial communities (Fiore et al., 2010), and death of infaunal organisms (pers. obs.) are potential factors that could either contribute to or directly cause sponge mortality.

Although filtration stopped for the duration of the trial, death of individual sponges could not be validated. This is in part because the study was a laboratory experiment with a relatively short duration compared to natural blooms and because initial signs of mortality are poorly defined in literature (Gaino et al., 1992). Sponge die-offs are typically recorded post- event and subsequent studies tend to focus on causation (Galstoff et al., 1939; Smith, 1939;

Butler et al., 1995; Cervino et al., 2006; Gaino et al., 1992; Cebrian et al., 2011). Observations have been made of H. lachne mesohyl retreating inward shortly after a storm event (Storr, 1976), but this reaction was not witnessed during the current study. Health of sponge mesohyl could not be evaluated during the study timeframe and physical decay was not notably visible for any species at the termination of the trials.

Determining the timeframe during which stress begins to cause sponge mortality could play an important role in the resilience of hard-bottom sponge communities to bloom events. At

the conclusion of the final set of trials, individuals of the bloom-susceptible species H. lachne

(n=3) and S. barbara (n=2) were removed from treatment tanks and placed in clean tanks containing only ambient seawater. After 13 h, both S. barbara and one H. lachne sponge had recommenced pumping after having shut down for the duration of their exposure to viscosity treatment. This suggests the experiments were not long enough to cause death but provokes questions about the effect of bloom duration on sponge survival. Literature on the long-term pumping patterns of S. vesparium is scant, but it has been assumed to pump continuously (Wall et al., 2012). However, in my experiments, both treatment and control group S. vesparium had to be injected with dye at multiple incurrent locations to determine if pumping was occurring. This suggests that not all canals are continuously facilitating water flow. This should be tested more explicitly in the field since the observations here may have been a response to mesocosm conditions. Validating relative pumping patterns between stressed and unstressed individuals for this important hard-bottom species could increase the accuracy of Bay-wide filtration estimates

(Peterson et al., 2006) and be a potential indicator of environmental stress.

My second objective was to determine the effect of sediment resuspension in the water column, as occurs during wind or storm events, on sponge pumping activity. Mass sponge mortality has been noted after storm events (Cropper and DiResta, 1999; Stevely et al., 2011) and could be an additive concern for dwindling sponge populations impacted by periodic algae blooms in Florida Bay. When S. vesparium and T. crypta individuals were exposed to sediment resuspension that mimicked storm or wind events neither species demonstrated a consistent significant reaction to sediment exposure. S. vesparium individuals significantly decreased pumping acitivity at 60 min and T. crypta individuals stopped pumping at 30 min. Trends in the data showed that particle resuspension caused declines in the proportion of individuals pumping

over the first hour for S. vesparium and then a nearly full return of pumping activity by the end of the second hour. T. crypta displayed similar trends to S. vesparium in pumping decreases over the first half hour but these trends were then masked by low numbers of pumping individuals in both the treatment and control groups during the remainder of the trial.

The short duration of treatment exposure shows how quickly these sponge species reacted to turbid tank conditions. Although my experiments showed the initial responses of these species to sediment resuspension, storms vary in magnitude and so any long-term responses to sustained treatment conditions could not be determined. I observed pumping activity in the treatment group for both species, which suggests that these species have adaptations to handle sediment resuspension. However, understanding to what degree S. vesparium and T. crypta can handle these stressful conditions remains to be tested. Decreased oxygen levels, depleted nutrient intake and stress on microbial communities are potential consequences from prolonged cessation. My results indicate that S. vesparium have a relatively slower initial reaction to particle resuspension but may compensate for this in their ability to quickly regain pumping ability. T. crypta promptly shutdown filtration but subsequent patterns could not be discerned so increasing the number of replicates may give better insight to the drop seen in the control group. Additionally testing pumping patterns in species not adapted to handling frequent turbidity in the water column would provide an important relative comparison.

S. vesparium and T.crypta are psammobiontic sponges, which means that these species bury part of their structure below the sediment surface, growing interstitially with the surrounding sediment (Rutzler, 1997). S. vesparium is the closest relative to Spheciospongia cuspidifera, a species described as having an inverted water-flow morphology, which means that it uses its above-ground structure as the incurrent and pushes water through the portion that

develops in the substrata (Rutzler 1997). Although S. vesparium does not have this reversed morphology, its close taxonomic relationship and typical sediment covered exterior suggests that it might have adaptations to handle high sediment conditions of the seafloor. Indeed, there are documented instances of S. vesparium “backwashing”, or expelling sediment particles through the ostia as an apparent method of canal cleansing (Storr, 1976, pers. obs.). T. crypta does not use backwashing, but this species has the ability to close its oscula when conditions are adverse

(Reiswig, 1971). Reiswig (1971) documented filtration shutdown during storm events and noted that pumping patterns were relatively complex. T. crypta is also found either fully or partially covered in sediment, which can attest to their resistance to physical perturbations.

It is apparent that sponge species in Florida Bay respond differently to disturbances in the water column, so the final objective of this study was to relate this variability in pumping activity to a sponge species’ internal canal architecture. Vertical sections from sponges revealed a range of mean canal sizes steadily progressing from the largest in S. vesparium to the smallest in T. crypta. Horizontal sections carried similarities to vertical sections with the exception of S. barbara, which had the largest canals. The relatively large canals seen in S. vesparium could contribute to its ability to better withstand bloom events (Butler and Behringer, unpublished data) while the large horizontal canals seen in S. barbara characterize its oscula and match personal field observations of these species.

Mean canal area does not give a true indication of how porous a sponge is, but a comparison of the relative amount of porous space among species revealed similarities to mean canal area for both vertical and horizontal sections. Vertical and horizontal sections showed that

S. vesparium, H. lachne, and S. barbara had the largest percentages of porous area, followed by

S. graminea and finally T. crypta with significantly less porous space than the other species. The

gap between T. crypta and the other sponge species is logical upon visual inspection of their internal morphology because of the sheer lack of canals. Horizontal sections were less porous than vertical sections, which probably resulted from the absence of vertically oriented incurrent canals located at the bottom of a sponge.

Comparing the number of canals present among species was used to determine the connection between a sponge species’ mean canal area and percentage of porous space because it could help or hinder a sponge’s ability to cope with viscous or turbid conditions. Vertical sections showed that S. graminea had the largest number of canals per unit area, and interestingly there was no significant difference among any species for horizontal sections. Since these sections capture the internal structure of a sponge as filtration progresses upward through the ex-current canals, sections did not include ostia but capture the less abundant oscular canals that are oriented more vertically in the sponge. Vertical and horizontal sections both showed that

S. graminea had the most numerous canals, despite having relatively small mean canal area and porosity. This species fared poorly during personal field observations and was susceptible to mortality following cyanobacteria blooms (Butler and Behringer, unpublished data). Its numerous, small canals could easily clog and be a sign that this is a pioneering species (Horn,

1974), which grows quickly but lacks the ability or physical structure to resist stressful conditions brought on by cyanobacteria blooms and possibly sediment resuspension.

Standardizing the image processing was difficult due to the complexity of a sponge’s internal structure. Duffy (1992) used a method of covering the largest slices from a sponge with a plastic sheet and using a felt-tip pen to trace the perimeter and then measuring the shortest diameter distance for each canal that fell on an overlaid grid point. However, I found that by overlaying a grid on the images, I was missing many of the canals and underestimating the

amount of porous space. Defining the perimeter of the canal was usually unclear because they weave through the sponge, creating varying angles and patterns along the surface of an individual section. Unlike Duffy (1992), whose focus was on calculating the smallest space a shrimp could occupy, my goal was to precisely measure even the smallest porous spaces to characterize different aspects of the internal structure. Therefore, I traced the portion of the canal that was absolutely perpendicular to the surface for every canal in each slice to standardize my methodology.

There is very little literature on quantifying the internal canal structure of sponges.

Biomass (Wall et al., 2012), volume by water displacement (Westinga and Hoejtes, 1981; Lynch and Phlips, 2000), filtration rates (Reiswig, 1971; Peterson et al., 2006; Weisz et al., 2008) microbial community composition (Poppell et al., 2014), mean canal sizes (Westinga and

Hoejtes, 1981; Duffy, 1992) and general taxonomic classification are part of a running list of ways sponges have been previously characterized. Demosponges are known to have a complex internal structure but it may be variations in morphology that drives their survival in adverse conditions.

Although T. crypta and S. vesparium are both psammobiontic sponges, they have obvious external and internal morphological differences. The ostia of T. crypta are imbedded in the base of the sponge (Reiswig, 1971) in contrast to S. vesparium whose ostia are readily visibly along the lower exterior of the sponge (pers. obs.). The lack of canals could help in the ability of T. crypta to close its osculum and handle bloom or sediment re-suspension events. When vertical cross sections of S. vesparium were made, in many cases it appeared as though the internal ex- current canals had been closed. This was similar to the closing of oscula in live sponges observed during both the sediment and viscosity stress trials. Although only anecdotal, this ability could

allow S. vesparium survive adverse water column events, in addition to their relatively large canal size and percent of porous space.

Understanding the structure and function of ecologically important organisms such as sponges is critical in mitigating impacts that phytoplankton communities have on other systems and researchers point to filter feeders as a means of lessening the magnitude of these blooms

(Prins et al., 1997; Coen et al., 2007). For example, bivalves are noted for their top-down control of phytoplankton communities in estuarine systems, from San Francisco Bay, CA (Prins et al.,

1997) to Chesapeake Bay, VA (Coen et al., 2007). Restoration goals for the Eastern oyster

Crassostrea virginica include controlling phytoplankton blooms and hypoxia, promoting diversity, and reducing turbidity in Chesapeake Bay (Coen et al., 2007). Like the sponge community in Florida Bay, these oyster reefs are not only functionally important for water column clarity but also promote species diversity by providing structural habitat (Coen et al.,

2007). The intricate connectivity of communities, such as sponges and oyster beds, to overall ecosystem health highlights how important it is to evaluate both the physical and physiological factors that could stress and negatively impact marine and estuarine environments.

Conclusion. This study was aimed at better understanding the connection between reoccurring algal blooms and subsequent mass sponge mortalities in Florida Bay. In doing so, I gathered evidence to support that Synechococccus bloom properties and sediment re-suspension hinder sponge filtration, which could eventually lead to sponge mortality. Exposure to viscosity levels comparable to the mucilage produced by dense, senescing Synechococcus cells caused significant cessation in pumping for all sponge species tested. Turbid conditions, as caused by storm events, showed only brief cessation. Characterizing structural differences in internal canal architecture enhanced our understanding of the internal structure of less well-studied sponge

species and showed a potential connection between a species and vulnerability to clogging.

Gaining a better understanding of physiological and morphological adaptations for handling stress can help researchers and managers alike in directing efforts to restore the Bay ecosystem.

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BIOGRAPHICAL SKETCH

Danielle grew up along the coastline of Southwest Florida, where she was exposed to the surrounding islands and water systems. These natural systems’ influences on the local culture and development of the region inspired her to pursue a career in ecological sciences. Starting in

2008, she attended the University of Florida, where she met Dr. Don Behringer. As her adviser, he opened many doors to build a career in marine ecology, predominately through her opportunity to conduct research on sponge mortality in the Florida Keys. She currently resides in

Gainesville working under a project that assesses the impact of dredging on the marine habitat.