Measuring Impacts of Associated Microbial Communities on Caribbean Reef Sponges: Searching for Symbiosis

Measuring impacts of associated microbial communities on Caribbean reef sponges: Searching for symbiosis

Jeremy Brian Weisz

A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Marine Sciences

Chapel Hill 2006

Approved by Advisor: Niels Lindquist Reader: Christopher Martens Reader: Hans Paerl Reader: Rachel Noble Reader: Ute Hentschel

ii ABSTRACT

JEREMY BRIAN WEISZ: Measuring impacts of associated microbial communities on

Caribbean reef sponges: Searching for symbiosis

(Under the direction of Niels Lindquist)

Sponges (phylum Porifera) evolved in Precambrian times, and research suggests that many sponge species began associations with large, diverse microbial communities early in their evolutionary history. This long history of close interactions suggests that the relationships are beneficial to both partners, but there is little conclusive evidence to support this hypothesis. By comparing sponge species with large, diverse microbial communities, termed high microbial abundance (HMA) sponges, to sponge species nearly devoid of associated bacteria, termed low microbial abundance (LMA) sponges, my research sought to test the hypotheses of positive microbial influences on sponges and that a symbiosis exists between the partners.

HMA sponges were found to have significantly higher tissue densities, significantly lower in situ pumping rates, and significantly different in situ fluxes of various nitrogen species, suggesting that bacteria influenced the morphology, physiology, and nitrogen budget of their host sponges. Measurements of stable carbon and nitrogen isotope ratios of bulk sponge tissue for a variety of sponges from the Florida Keys, North Carolina, and Papua New

iii Guinea revealed that although carbon metabolism is most influenced by habitat, nitrogen metabolism varies with species, with most HMA sponges showing low nitrogen isotopic ratios generally indicating microbial metabolic processes. Transmission electron microscopy and denaturing gradient gel electrophoresis of two HMA sponges and an LMA sponge allowed me to characterize a portion of the microbial communities of the HMA sponges and to confirm the lack of extensive and diverse microbial communities among LMA sponges.

Because anaerobic microbes were found in the HMA sponges, I used submersible oxygen microsensors and tetrazolium salts to detect in situ zones of hypoxia within sponge tissue,

and found hypoxia in HMA sponges but not in LMA sponges. Finally, I measured the stable

carbon and nitrogen isotope ratios of spongin fibers, which makes up the sponge skeleton,

and sponge larvae or embryos, and found evidence of a transfer of nitrogen between the

sponges and their associated bacteria. My research supports the hypothesis that HMA

sponge evolution and ecology is impacted by their associated microbial community and that

this community directly benefits the host sponge, resulting in a symbiotic relationship.

iv To my parents, Maxine and David, who took me snorkeling for the first time and always encouraged me and supported me.

To my wife, Cassidy, who believed in me, even when I did not believe in myself.

To my son, Benjamin, just because.

v ACKNOWLEDGEMENTS

I am deeply indebted to my advisor, Dr. Niels Lindquist. He has given all of himself

to my training and has taught me not only to be a good scientist, but also to be a good

professor. I want to thank Dr. Chris Martens, the co-PI on this project, for his support, advice, and expertise. My other committee members, Drs. Hans Paerl, Rachel Noble, and

Ute Hentschel, have provided invaluable advice and assistance on all aspects of this work.

Melissa Southwell, Susanne Schmidt, and Dr. Jim Hench have all been excellent collaborators, providing help with data collection and data analysis, and sharing their data to

further my research. I would like to thank Channing Jones, my labmate, roommate, fellow

aquanaut, and friend. He acted as a sounding board for my ideas and my complaints, and

provided countless hours of assistance with the data collection and logistics of my research.

Thank you to my other labmates Lisa Weiss and Regan Converse. Thank you to Meredith

Kintzing, a wonderful technician, fellow aquanaut, neighbor, and friend who was always

there to lend a hand, even with the most menial of research tasks. Thanks to Johanna Kertesz

and Alice Dennis for other lab and field assistance. Many thanks go to Laura Lapham and

Howard Mendlovitz, who provided inordinate amounts of technical assistance with the mass

spectrometer, as well as other help in my many trips to Chapel Hill. Thanks to Sean Powers

and Melanie Bishop for their help with statistics.

This work could not have been completed without the help of the many support staff,

both at IMS and at NURC in Key Largo, FL. The IMS staff does an amazing job of keeping

everything running smoothly, and will always go out of their way to help out with whatever

vi odd projects and requests we come up with. The NURC staff, including the Aquarius staff, is committed to the success of our research and their knowledge of marine systems, both in general and specifically in the Key Largo area, is truly amazing.

The IMS community has provided a social support system that was an invaluable resource throughout my graduate school career. I specifically want to thank Julie Dyble,

Jason and Janelle Fleming, Kar Howe, Galen Johnson, Ben Peierls, Erik Sotka, Tim Steppe, and Eileen Vandenburgh.

Finally, I need to thank my parents Maxine and David, for their unending support and encouragement. I need to thank my wife Cassidy, who was been an assistant, an adviser, and an editor of my work, and has provided immeasurable mental and emotional support.

This work was financially supported by a Merit Assistantship and a Dissertation

Completion Fellowship from the Graduate School of UNC-CH, a Graduate Research

Fellowship from the National Science Foundation (NSF), and grants from the University

Research Council of UNC-CH, Biological Oceanography and Chemical Oceanography at

NSF, and NOAA/NURP at UNC-Wilmington. Additional financial support came from the

University of Wuerzburg, and equipment loans courtesy of Dauphin Island Sea Lab, Stanford

University, and Nortek Inc.

vii TABLE OF CONTENTS

Page LIST OF TABLES ...... xi

LIST OF FIGURES ...... xii

Chapter

I. Physiological and Morphological Differences in Caribbean reef sponges ...... 1

Introduction ...... 1

Methods ...... 6

Results ...... 11

Discussion ...... 12

References ...... 17

II. Differences in sponge metabolism ...... 45

Introduction ...... 45

Methods ...... 49

Sponge Collection ...... 49

Stable Isotope Measurements ...... 50

Analysis of Data ...... 51

Results ...... 54

Florida Samples ...... 54

North Carolina Sponges ...... 55

Papua New Guinea Sponges ...... 56

viii Regional Comparison ...... 56

Discussion ...... 56

References ...... 63

III. Linking molecular and microscopic diversity of sponge associated microbial communities to metabolic differences in host sponges ...... 94

Introduction ...... 94

Methods ...... 96

Sample Collection ...... 96

Transmission Electron Microscopy...... 98

Denaturing Gradient Gel Electrophoresis (DGGE) ...... 98

Results and Discussion ...... 100

References ...... 108

IV. Other impacts of associated bacteria on their host sponges...... 124

Introduction ...... 124

Methods ...... 130

Tetrazolium Salts ...... 130

Sumbersible Oxygen Meter ...... 130

Stable Isotope Analysis of Spongin...... 132

Larval Collection ...... 134

Results ...... 136

Tetrazolium Salts ...... 136

Submersible Oxygen Meter ...... 136

Stable isotopic comparison of spongin versus whole sponge tissue ...... 136

ix Stable isotopic comparison of larvae versus whole sponge tissue ...... 137

Discussion ...... 137

Final Conclusions ...... 142

References ...... 144

x LIST OF TABLES

Page Table 1.1 Sponge species used in the study and presence/absence of microorganisms ...... 21

Table 1.2 Previously published flow data ...... 22

Table 1.3 ANOVA Table of Species versus Density (g dry mass/ml) ...... 24

Table 1.4 ANOVA Table of Species versus Dye-determined Flow rates ...... 25

Table 1.5 ANOVA Table for the regression of Sponge Density vs Dye-determined Flow ...... 26

Table 2.1 Sponge species collected in Florida ...... 68

Table 2.2 ANOVA of δ15N vs. species for FL data ...... 70

Table 2.3 ANOVA of δ13C vs. species for FL data ...... 71

Table 2.4 ANOVA of δ15N vs. species for NC data ...... 72

Table 2.5 ANOVA of δ13C vs. species for NC data ...... 73

Table 2.6 ANOVA of δ15N vs. species for PNG data ...... 74

Table 2.7 ANOVA of δ13C vs. species for PNG data ...... 75

Table 3.1 Results of sequence analysis of selected DGGE bands ...... 114

Table 4.1 Characteristics of sponge species used in this work ...... 150

xi LIST OF FIGURES

Page Figure 1.1 Map of study sites ...... 27

Figure 1.2 Volume vs. dry mass for eight sponge species ...... 29

Figure 1.3 Photograph of dye measurement technique ...... 31

Figure 1.4 Photographs of ADV setup ...... 33

Figure 1.5 Density, in g dry mass ml-1, of 11 sponge species ...... 35

Figure 1.6 Pumping rate, in l s-1 kg dry mass-1, of 8 sponge species ...... 37

Figure 1.7 Flow speed of four individuals of Spheciospongia vesparium ...... 39

Figure 1.8 Average pumping rate (1000 L day-1 kg dry mass-1) of four individuals of S. vesparium ...... 41

Figure 1.9 Density, in g dry mass l-1, versus pumping rate, in l s-1 kg dry mass-1, for eight sponge species ...... 43

Figure 2.1 Maps of Sponge Collection Sites ...... 76

Figure 2.2 Cluster analysis for stable N isotope ratios of Florida sponges ...... 78

Figure 2.3 δ15N versus δ13C for Florida sponges ...... 80

Figure 2.4 Stable C isotope ratios of Florida sponges versus distance to the 20 m isobath ...... 82

Figure 2.5 Stable N isotope ratios of Florida sponges versus distance to the 20 m isobath ...... 84

Figure 2.6 δ15N versus δ13C for North Carolina sponges ...... 86

Figure 2.7 δ15N versus δ13C for Papua New Guinea sponges ...... 88

Figure 2.8 Cluster analysis of stable C and N isotope data of all sponge samples ...... 90

Figure 2.9 Proposed food web models ...... 92

Figure 3.1 Plots of d15N vs. d13C for three sponge species and suspended particulate organic matter (SPOM; Southwell et al. unpublished) ...... 118

xii Figure 3.2 TEM micrographs of three sponge species ...... 120

Figure 3.3 DGGE gel of 16S rRNA gene fragments ...... 122

Figure 4.1 Number of sponge species showing TTC deposition ...... 152

Figure 4.2 TTC deposition in sponges ...... 154

Figure 4.3 Oxygen saturation in sponges ...... 156

Figure 4.4 Plot of δ13C and δ15N values for spongin and bulk sponge tissue ...... 158

Figure 4.5 Cluster analysis for paired spongin and bulk tissue stable isotope ratios .....160

Figure 4.6 Plot of δ13C and δ15N values for reproductive products (larvae/embryos) and bulk sponge tissue ...... 162

Figure 4.7 Cluster analysis for paired reproductive products and bulk tissue stable isotope ratios ...... 164

xiii

Chapter I

Physiological and morphological differences in Caribbean reef sponges

Introduction

Sponges (Phylum Porifera) are the oldest extant animal phylum with fossils dating back at least 580 million years (Li et al. 1998). Today, there are at least 7,000 described sponge species (Hooper & Van Soest 2002), most of which are found on tropical reefs but also at higher latitudes and even in freshwater lakes and streams (Bergquist 1978).

Functionally, sponges share many features with unicellular protozoa particularly with respect to nutrition, cellular organization, gas exchange, reproduction, and response to environmental stimuli (Bergquist 1978). Sponges have no organs or tissues, and instead consist of a three- dimensional matrix, termed the mesohyl, with amoeboid cells that move freely through the sponge. Nevertheless, sponges are true metazoans, forming the base of the animal kingdom.

Sponges actively pump water through a unique and highly vascularized canal system using flagellated cells called choanocytes. These choanocytes propel their flagella in a spiral motion, producing water currents that move large quantities of water through their bodies

(Reiswig 1974). The flagellum of these choanocytes is surrounded by a collar of cilia, which the cells use to efficiently filter particulate organic matter (POM) from the seawater

(Bergquist 1978). Sponges can reduce bacterial loads by three orders of magnitude (Wehrl

2001), and some also remove dissolved organic matter (DOM) from the seawater (Yahel et al. 2003). The sponge must balance the energy requirement of pumping (Riisgard et al. 1993) with the need to pump sufficient water to obtain adequate nutrient and gas exchange.

The sponge also needs to eject the filtered water from the osculum with a sufficiently high velocity to prevent re-inhaling filtered water (Riisgard et al. 1993). Thus, the pumping rate is a crucial aspect of the basic biology and ecology of the sponge.

Many studies of suspension-feeding bivalves have shown that local resource depletion can occur when the filter-feeding removes nearly all of the POM in the benthic boundary layer (Buss & Jackson 1981, Peterson & Black 1987, Peterson & Black 1991,

Fegley et al. 1992). Given that in coral reef habitats sponges can rival scleractinian and alcyonarian corals in abundance and diversity (Targett & Schmahl 1984, Suchanek et al.

1985), the filtering activity of these sponges can significantly alter concentrations of POM

(Reiswig 1971b, Reiswig 1974, Reiswig 1981, Riisgard et al. 1993, Pile et al. 1996, Turon et al. 1997, Pile et al. 1997, Ribes et al. 1999, Lynch & Phlips 2000), and may impact concentrations of a variety of dissolved nutrient elements, oxygen and other chemicals in water moving over coral reefs. Knowing the pumping rate of a sponge is crucial for measuring particle filtering rates and chemical fluxes through the sponge, and therefore is also crucial to the understanding of nutrient cycles on the coral reef.

Given the importance of understanding sponge pumping rates, it is surprising how few attempts have been made to measure them as directly and as accurately as possible. The majority of prior studies that measured pumping rates of sponges were performed in the laboratory using sponges in non-flow through enclosures (Parker 1914, Jorgensen 1949,

1955, Vogel 1974, Gerrodette & Flechsig 1979, Riisgard et al. 1993, Thomassen & Riisgard

1995, Turon et al. 1997, Ribes et al. 1999, Kowalke 2000, Lynch & Phlips 2000). However, it has long been established that sponges act differently in the laboratory as compared to their

2 natural environment (Parker 1910, Jorgensen 1955, Harrison & Cowden 1976).

Additionally, many of these studies measured a clearance or filtration rate, rather than the

actual water velocities (Riisgard et al. 1993, Thomassen & Riisgard 1995, Turon et al. 1997,

Ribes et al. 1999, Kowalke 2000, Lynch & Phlips 2000). Only a handful of studies have

reported excurrent water velocities of sponges under natural conditions. Using an improved

design of a heated thermistor (LaBarbera & Vogel 1976), Vogel (1977) measured excurrent

water velocities in eight sponge species in Bermuda and found excurrent velocities ranging

from 7.5 to 22 cm/sec. Reiswig (1971a,b; 1974; 1981) made use of a similar heated

thermistor to study excurrent velocities of several sponge species and calculate partial energy budgets. This work has been cited many times and is generally recognized as the best in situ estimates of pumping rates for any sponge species. More recently, Savarese et al. (1997)

used a dye technique to calculate excurrent velocities of Baikalospongia bacillifera, a freshwater sponge. Finally, a similar dye technique described as the “InEx” technique

(Yahel et al. 2003, 2005) was used to measure excurrent velocities and filtration rates of the

Indo-Pacific sponge Theonella swinhoei. Although there is a growing body of data on the pumping rates of sponges, these data are still focused on a few species; thus, more work is needed to examine the range of pumping rates that may be found across many sponge species, especially under natural, or in situ, conditions.

The term bacteriosponge was coined by Reiswig (1974) to describe sponge species that have massive and morphologically diverse populations of microbes within their mesohyl.

These populations are also genetically diverse, and many of the microbes appear to be unique to sponges (Hentschel et al. 2002, 2006, Fieseler et al. 2004). Hentschel and co-workers

(2006) have more recently termed these sponges “high microbial abundance (HMA)

3 sponges”, and sponges lacking dense microbial communities they called “low microbial abundance (LMA) sponges.” Throughout the remainder of this dissertation, I will use

“bacteriosponge” and “HMA sponge” interchangeably to refer to sponges with massive populations of associated microorganisms, and I will use “LMA sponge” to refer to sponges without massive populations of associated microorganisms. Through electron microscopy studies of 11 sponge species, Vacelet and Donadey (1977) proposed that species containing

massive microbial communities (HMA sponges) also have dense tissue. Vacelet and

Donadey (1977) further noted that species that have sparse microbial communities (LMA

sponges) had well-irrigated tissue with densities lower than those of sponges hosting massive

microbial communities. As suggested by Vogel (1978), the denser tissue of some sponge

species results in smaller water canals throughout the sponge, and these small canals should

have increased resistance to the movement of water. One result of this density difference is

that sponge species should expend more energy to pump a unit volume of water at the same

rate as less dense sponges. Consequently, there should be large variations in pumping speeds

between sponge species. However, this hypothesis has never been empirically tested. Thus,

a goal of this work is to compare the pumping rates of high and low density sponges.

Much work has been done on the microbial communities associated with many

sponge species. It has been estimated that these microbial communities can make up 40% of

the biomass of an individual sponge (Wilkinson 1987). Because of this abundance and

diversity, the associated microbial community can have impacts on all aspects of the sponge

biology. While many of these impacts will be discussed in later sections of this dissertation,

this chapter will discuss potential effects of microbial communities on the nitrogen budget of

the sponge. Previous research, as well as concurrent work done by Melissa Southwell

4 (Southwell et al. 2005, 2006), has shown that sponge microbes actively transform nitrogen compounds. Prior research on five sponge species, involving incubating sponges in aquaria, has shown that bacteriosponges expel nitrate (Corredor et al. 1988, Diaz & Ward 1997), indicating that nitrification, the oxidation of ammonium to nitrite and then nitrite to nitrate, is occurring in these species. The source of nitrogen to fuel this nitrification is unclear, because the rates of nitrate build-up in the water of the aquaria were much greater than expected given the low ambient ammonium concentration (Corredor et al. 1988, Diaz & Ward 1997).

Both Corredor and colleagues (1988) and Diaz and Ward (1997) hypothesized that sponge cells may be providing ammonium, produced as a byproduct of oxidation of PON and DON, to nitrifying bacteria, or that nitrogen fixing bacteria are excreting ammonium that is taken up by the nitrifying bacteria. As both of these studies involved sponges in chambers, their validity can be questioned. My pumping rate studies have been coupled with DIN concentrations in sponge excurrent water to provide in situ DIN flux measurements from sponges (Southwell et al. 2005, 2006). Differences in the speciation and magnitude of the

DIN fluxes between HMA sponges and LMA sponges may provide further clues to sponge- microbe nutrient exchange and indicate differences in the nitrogen cycle of the two groups of sponges.

Two basic methods have been used to measure sponge pumping rates in situ: dye tracking and flow meters. Dye-based methods allow for rapid quantification of excurrent velocities, and can provide an instantaneous measurement on many individuals with a minimal investment of time or supplies. Current meters can provide longer time scale measurements, but they require a much larger investment of time and supplies to each individual sponge, and thus they are limited to fewer species and/or fewer individuals. In

5 this study, we (1) measured sponge tissue densities to examine correlations between tissue density and pumping rates, (2) used both dye-video and Acoustic Doppler Velocimeter

(ADV) methodologies to measure sponge excurrent speeds in situ, (3) combined these data with sponge dimensions and masses to calculate sponge pumping rates, and (4) combined sponge pumping rates with levels of DIN in ambient and sponge excurrent water collected by

Melissa Southwell to estimate DIN/DON fluxes mediated by sponges. We hypothesize that

HMA sponges will have higher tissue densities and lower pumping rates than LMA sponges.

We also hypothesized that HMA sponges will excrete nitrate, while LMA sponges will not.

Methods

This study was conducted over the course of several trips to the National Undersea

Research Center (NURC) in Key Largo, Florida. Measurements were made at two locations:

Conch Reef (24º 57.230’ N, 80º 27.223’W) and a set of small patch reefs that will be referred to as Diadema Reef (24º 59.198’ N, 80º 26.096’ W) (Fig. 1.1). Eight sponge species were used in this work: Agelas conifera, Aplysina archeri, Callyspongia plicifera, Callyspongia vaginalis, Ircinia strobilina, Niphates digitalis, Spheciospongia vesparium, and Xestospongia muta. These species were selected because they all have a single osculum, which allows the flow of the entire sponge to be measured at once. Data from the literature and microbial cell counts of sponge tissue performed in the Hentschel lab allowed each sponge species to be classified as either a HMA sponge or a LMA sponge (Table 1.1).

Healthy-looking individuals were chosen and their dimensions were measured in order to estimate tissue volumes for later use in density measurements. For at least three individuals of each species, the whole sponge was collected for density measurements after

6 all flow measurements and water collections were complete. Density measurements were also made on Aplysina cauliformis, Ircinia felix and Niphates erecta, which had also previously been identified as either HMA sponges or LMA sponges (Table 1.1). These three species are less suitable for flow measurements due to their numerous small oscula, but were included in the density analysis because these data are important for other research topics in

this dissertation. All individuals were kept on ice until they were returned to the NURC base

where their volumes were measured by displacement of seawater in a graduated cylinder.

Some individuals, especially of larger species (e.g. Xestospongia muta) were cut into sections

before volume was determined. Volume by displacement was determined for each section

and then total volume was calculated as the sum of all sections. Wet mass of the sponges

was measured after the sponges were removed from water and allowed to drain for

approximately 10 seconds. Next, sponges were placed in a drying oven at ~60ºC for at least

48 hours and then weighed again to determine their dry mass. Density was calculated for

these individual as dry mass divided by volume. Note that sponge mass is frequently

reported as ash-free dry mass (AFDM, e.g. Kowalke 2000), which excludes spicule mass

from any calculations, including density. The AFDM density was not used in this study

because the aim of this study was to determine relative differences among species in the

amount of sponge volume devoted to water canals. Thus, spicules, which can make up a

significant portion of the sponge mass (Bergquist 1978), were included in these density

calculations. A simple linear regression, with volume as the independent variable and dry

mass as the dependent variable, was calculated for each species mentioned above (Fig. 1.2).

As the r2 values for each regression were greater than 0.95, it was concluded that volume measurements accurately predicted the dry mass of an individual sponge. For individual

7 sponges that were not collected, linear measurements of all dimensions of the sponge were

collected in situ and volume was calculated from these measurements.

Density data were first analyzed with a simple t-test to determine if there was a

statistically significant difference in the densities of the HMA sponges versus the LMA

sponges. Following this analysis, density data were tested for normality using the

Kolmogorov-Smirnov test. The density data were then analyzed with a one-way ANOVA

with species as the independent factor and density as the dependent factor, followed by

Fisher’s PLSD post-hoc test to detect species level differences.

Excurrent water velocities were measured by measuring dye movement in the

excurrent stream. This provides an instantaneous snapshot of the excurrent velocity and

allows us to estimate the flow across the whole osculum. For measurements via dye

movement, a ruler attached to a flexible arm and small cement block was positioned directly

behind and parallel to the excurrent stream (Fig. 1.3). One diver positioned a video camera

to record the movement of the dye, while the other held a small syringe filled with

fluoroscein dye dissolved in seawater. Small puffs of dye were released in the excurrent

stream while the camera recorded its movement in front of the ruler. To ensure that the

sponge caused all upward movement of the dye, dye puffs were also released next to the

excurrent stream and their movement was recorded by the video camera.

Videotapes of dye data were watched frame by frame and dye speed was calculated as

the distance traveled by the sharp trailing edge of the puffs over as many frames as possible

divided by the time it was observed. The interval between frames was 1/30th of a second.

The movement of five to ten puffs across the entire oscular opening was averaged together to obtain a velocity (in cm/s) for each observation. This average value was multiplied by the

8 area of the osculum to obtain the volume of water moving through the sponge per second.

Dye data was tested for normality using the Kolmogorov-Smirnov test and then analyzed

with a nested one-way ANOVA with species as the independent factor, sponge individual as

the blocking variable, and flow, in L of water per second per kg dry mass of sponge, as the

dependent factor. This was followed by Fisher’s PLSD post hoc test to detect interspecific

differences in the flow.

The pumping rate of the sponge S. vesparium was also measured with Acoustic

Doppler Velocimeters (ADVs). ADVs measure water velocities in a small sampling volume

(0.25-1.0 cm3) by measuring the Doppler shift in sound waves emitted from a transmitter on the ADV and reflected off particles in the water back to three independent receivers on the

ADV. S. vesparium was chosen for further measurements with the ADV because it typically has a wide single cluster of oscula with an upward orientation, which makes it easy to position the ADV sampling volume within the excurrent stream. Additionally, several individuals of this species were found in seagrass beds surrounding the Diadema patch reefs.

This site was chosen because (1) its backreef position minimized wave-generated turbulence,

(2) its shallow depth (<10 m) gave sufficient bottom time for divers to manipulate the ADVs, and (3) the flat topography of the seagrass bed allowed for a relatively uniform horizontal movement of the ambient flow without the turbulence caused by the structure of the reef.

The minimal vertical movement of the ambient flow should greatly reduce any confounding impacts on measuring vertical velocities generated by the sponge. We used five ADVs: four

Nortek Vector Velocimeters and one Sontek Argonaut ADV. The Nortek instruments sampled at 32 Hz and the Sontek sampled at 1/3 Hz, with sampling volumes of 1.0 cm3 and

0.25 cm3, respectively. All of the Nortek instruments were held in place using custom built

9 PVC frames designed to hold the ADVs in place but with the ability to easily position the

ADV head at a range of heights and angles (Fig. 1.4a). The Sontek ADV was held in place

using three adjustable aluminum arms mounted in concrete bases (Fig. 1.4b). One of the

Nortek ADVs was used to measure ambient flow and was placed over seagrass ~1 m distant

from an individual of S. vesparium. Each of the remaining ADVs was placed over a separate

individual of S. vesparium. Each ADV was in place from 17 November until 22 November

2004, and was only occasionally removed to download data and replace batteries. The

position of the sampling volume of the ADVs was estimated using a ruler and dye to visualize the plume. They were positioned to measure the flow approximately 2 cm above

the sponge in the center of the excurrent plume. The Nortek ADV used to measure ambient

flow was positioned so that its height above the seafloor was approximately equal to that of

the other instruments. To compare the results of dye measurements to ADV measurements,

dye measurements were made, as described above, once a day on each test sponge during the

course of the ADV experiments. These measurements were made while the ADVs were in

place so that a nearly direct comparison of flow rates could be made.

ADV data were averaged at one-minute intervals to reduce the data to a manageable

number of points. Directly comparing the dye and ADV measurements collected at the same

time interval was not done because the process of taking the dye measurements involves

placing hands, syringes and rulers near or into the sampling volume of the ADV. Thus, ADV

data from the five minutes preceding the dye measurement was compared to the dye

measured flow rates. A five-minute moving average of the ADV data showed that any

significant changes in velocity occurred on time scales larger than five minutes, thus this dye

versus ADV comparison was reasonable. For each individual sponge, the five-minute

10 average excurrent velocity for the ADV data was paired with the matching average dye excurrent velocity and the pairs were analyzed with a paired t-test. To examine the correlation between density and flow, a simple linear regression was performed with the average density of each species as the independent, or X, variable, and the average flow calculated from the dye data as the dependent, or Y, variable.

Pumping rate data were also examined from published studies of other investigators to detect any patterns between HMA sponges and LMA sponges. An analysis of all published flow values that could be converted to a unit of liters of water per second per liter of sponge (Table 1.2) was conducted. Assuming that HMA sponge/LMA sponge patterns are consistent with a genus, each species in Table 1.2 was determined to be either a HMA sponge or a LMA sponge. Two simple t-tests were conducted, one with and one without the data from this study, comparing all of the pumping rates from the HMA sponges to all of the pumping rates from the LMA sponges.

Results

A t-test revealed a significant difference between the density of the HMA sponge group versus the density of the LMA sponge group (t-value = 5.833; p<0.0001). The

ANOVA indicated significant interspecific differences (F-value = 19.890; p<0.0001; Table

1.3), however, the post hoc test showed no clear distinction between the LMA sponge group and the HMA sponge group (Fig. 1.5), as both species in the genus Ircinia grouped with the

LMA sponges.

The pumping rate data from the dye method showed significant interspecific differences (F value = 24.31; p<0.0001; Table 1.4), and the post-hoc test showed that the

11 species have a significant break between the HMA sponge species versus the LMA sponge species (Fig. 1.6). C. plicifera had a significantly greater pumping rate than did all of the

other species, while its congener C. vaginalis did not differ from N. digitalis.

The ADV data from the four individuals of S. vesparium did not reveal any clear

periodic tendencies, but did show occasional drops to slow or no flow (Fig. 1.7). A

comparison between the dye data and the ADV data for S. vesparium resulted in no

significant differences for three of the four individuals (F value = 24.331; p<0.0001; Fig 1.8).

For the fourth individual, the ADV gave a significantly lower velocity than the dye. The

linear regression of density versus pumping rate was significant (F value = 8.007 p = 0.030;

Table 1.5) and the variation in density explained 57% of the variation in the flow (r2 = 0.572;

Fig. 1.9).

Analysis of prior published pumping rate data showed that pumping rates of the

HMA sponges were significantly lower than those of the LMA sponges both with data from this study (t-value = 4.323, p = 0.002) and without data from this study (t-value = 2.289, p =

0.0337).

Discussion

The analysis of the density data supports the hypothesis for the existence of a group of dense sponges and a group of less dense, or well-irrigated, sponges. The ANOVA of species versus density shows that interspecific differences generally back this significant split, with the exception of the sponges in the genus Ircinia. Both I. felix and I. strobilina have intermediate densities, and group with the LMA sponges. From a visual examination of these species, it appears that they are fairly dense, but similar density data from Chanas and

12 Pawlik (1995) support this intermediate density. These anomalies to my model are worthy of

further study, but is beyond the scope of the current work. With the Ircinia spp. exception in

mind, the density data correlate well with the presence or absence of abundant microbial associates, meaning that the HMA sponges are high-density sponges.

Comparing the ADV data to dye data for four individuals of S. vesparium, it appears

that there is general agreement between the two methodologies. While 5-min averaged ADV

velocity measure immediately prior to the dye sampling was lower than the dye velocity for

the majority of the measurements, the ADV and dye flow speeds for three of the four individuals were not significantly different. The ADV data for the fourth individual yielded

a significantly slower flow than the dye measurements. Further, the ADV data showed that

this sponge had consistently lower flow speeds than the other individuals, while the dye data

show that it was in the same range as the other individuals. The excurrent opening in this

species often consists of a cluster of small oscula, as opposed to a single large, deep osculum,

and our dye work revealed eddies within their excurrent flow. While care was taken to avoid

placing the sampling volume of the ADVs into an eddy, it was certainly possible that the

sampling volume of this ADV was positioned within an eddy, or that the flow characteristics

just above the clustered oscula changed as pumping rates varied, and thereby measured a

lower flow speed.

Overall, the ADV data suggest that this species generally maintains a near constant

flow at a maximum velocity, which is interspersed with periods of reduced pumping rates or

even periods of cessation in pumping. This result is consistent with in situ flow speed and

pumping rate data on Tethya crypta and Verongia gigantea (Reiswig 1971b, 1974) that show

occasional periods of reduced pumping and cessations in pumping, but differs from

13 Reiswig’s data on Mycale sp. from the same studies (Reiswig 1971b, 1974), which does not show these periods of reduced or ceased pumping. From his studies, Reiswig (1971b) suggested that the average daily pumping rate of any sponge can be estimated as anywhere from 55% to 100% of the maximum, depending on species, while other researchers suggest that the average daily pumping rate of any species should be conservatively estimated as a constant 50% of the maximum velocity as measured by dye movement (A.J. Pile, pers. comm.). Our data show that for this species, the best estimate would be a constant 70% of the dye velocity. However, we cannot conclude from our data which estimate is more appropriate for the “average sponge” or if there even is an average sponge. In any case, the general agreement between dye data and ADV data support the validity of both methodologies.

The dye data for eight sponge species supports the hypothesis that HMA sponges have slower pumping rates than do the LMA sponges, and the analysis of prior published pumping rate data confirms that this pattern is not unique to this study. The density data suggest that there is a morphological explanation for this difference, because the smaller water canals (Vogel 1978) would tend to reduce the maximum attainable flow speed at a given energy input due to exponentially increasing frictional forces as tube diameter decreases and length increases. Smaller and longer tubes in the aquiferous system also increase the surface area over which exchanges of dissolved materials can occur between cells within the sponges and the water moving through the canals.

The presence of the diverse microbial community in these sponges may also explain the slower pumping rates. As shown by Yahel et al. (2003), HMA sponges take up dissolved organic nutrients. This additional nutrient source is probably not available to the non-

14 bacteriosponges, suggesting that the bacteriosponges can more efficiently utilize a high

proportion of the total amount of organic matter in the water they pump, and thus may not

need to pump as much water to meet their energy and nutrition requirements. DIN data from

these sponges (Southwell et al. 2006) also showed that 12 of the 13 bacteriosponges

examined host active nitrifying bacteria that produce nitrite and nitrate, while the non- bacteriosponge excretes only ammonium. These data clearly show the results of microbially- mediated N conversions that appear to be common among the bacteriosponges, whereas the form of excreted N from non-bacteriosponges indicate a strictly heterotrophic, non-microbial metabolism.

This research has shown that there are significant differences between HMA sponge

and LMA sponge morphology and physiology. While we do not yet have evidence that the

presence of bacteria is either caused by, or the result of, these morphological or physiological

differences between sponge species, these correlations provide an important foundation for

further research on this topic. Additionally, this research has shown that sponge pumping

rate data are vital to any efforts to estimate the potential impact of sponges on nutrient cycles

of coral reefs, seagrass, and other benthic communities. Future work focused on the impacts

of sponge on the nutrient cycles of coral reef habitats should include more nutrient analyses

on ambient and excurrent water samples, which will allow for assessments of sponge impacts

on carbon, oxygen, and phosphorus cycles. Additionally, by comparing dye data to ADV

data in other species we should be able to establish the percentage of time that each sponge

species spends pumping. The differences in tissue density, pumping rates, and N cycling

between HMA sponges and LMA sponges suggest that associated bacteria do impact the

morphology, physiology, and nutrient budgets of their host sponges. These impacts provide

15 evidence supporting a symbiotic relationship between sponges and associated

microorganisms. Additionally, the methods developed for this work were shown to be effective at determining sponge pumping rates in situ, and thus can be used to provide crucial data on the metabolism and fluxes of nutrients through sponges, and crucial data on the impacts of these sponges with the nutrient cycles of the reef.

16 References

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Reiswig HM (1981). Partial carbon and energy budgets of the bacteriosponge Verongia fistularis (Porifera: Demospongiae) in Barbados. P.S.Z.N. I: Marine Ecology 2: 273- 293.

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Vogel S (1974). Current-induced flow through the sponge, Halichondria. Biological Bulletin 147: 443–456.

Vogel S (1977). Current-Induced Flow through Living Sponges in Nature. Proceedings of the National Academy of Sciences of the United States of America 74: 2069-2071.

Vogel S (1978). Evidence for One-Way Valves in Water-Flow System of Sponges. Journal of Experimental Biology 76: 137-148.

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Yahel G, Sharp JH, Marie D, Hase C, Genin A (2003). In situ feeding and element removal in the symbiont-bearing sponge Theonella swinhoei: Bulk DOC is the major source for carbon. Limnology and Oceanography 48: 141-149.

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20 Table 1.1: Sponge species used in the study and presence/absence of microorganisms

Species HMA Sponge? Reference

Agelas conifera Yes Richelle-Maurer et al. 2003

Aplysina archeri Yes Fieseler et al. 2004

Callyspongia plicifera No Hentschel et al. 2006

Callyspongia vaginalis No Hentschel et al. 2006

Ircinia strobilina Yes Vincente 1990

Niphates digitalis No Chapter 3

Spheciospongia vesparium Yes Vincente 1990

Xestospongia muta Yes Hentschel et al. 2006

21 Table 1.2: Previously published flow data

Bacteria Flow Species in Citation Method (L/s/L) sponge? Verongia lacunosa Y 0.005- Gerrodette & Flechsig Tracer in tank 0.034 1979

S. vesparium Y 0.069 Lynch & Phlips 2000 Tracer in tank

Halichondria N 0.080 Lynch & Phlips 2000 Tracer in tank metanadocia

Biemna sp. N/A* 0.221 Lynch & Phlips 2000 Tracer in tank

Halichondria panacea N 0.045 Riisgard et al. 1993 Tracer in tank

Haliclona urceolus Y 0.042 Riisgard et al. 1993 Tracer in tank

Halichondria N 0.240 Vogel 1974 Tracer in tank bowerbank

Thenea muricata N/A 0.050 Witte et al. 1997 Tracer in tank

Verongia fistularis Y 0.049- Reiswig 1971b Heated 0.276 Thermistor

Verongia gigantea Y 0.050- Reiswig 1974 Heated 0.100 Thermistor

Tethya crypta Y 0.180 Reiswig 1974 Heated Thermistor

Mycale sp. N 0.210- Reiswig 1974 Heated 0.270 Thermistor

Haliclona permollis Y 0.049- Reiswig 1975a Heated 0.116 Thermistor

Haliclona permollis Y 0.131 Reiswig 1975b Heated Thermistor

* No designation of HMA sponge or LMA sponge could be determined, and thus these species were not included in any analysis.

22 Table 1.2 Continued

Bacteria Flow Species in Citation Method (L/s/L) sponge? Dysidea avara Y 0.017 Ribes et al. 1999 Dye in field

Baikalospongia Y 0.040-0.60 Savarese et al. 1997 Dye in field bacillifera

Theonella swinhoei Y 0.043 Yahel et al. 2003 Dye in field

C. plicifera N 0.578 This study Dye in field

C. vaginalis N 0.374 This study Dye in field

N. digitalis N 0.365 This study Dye in field

A. conifera Y 0.073 This study Dye in field

A. archeri Y 0.102 This study Dye in field

I. strobilina Y 0.093 This study Dye in field

S. vesparium Y 0.176 This study Dye in field

X. muta Y 0.078 This study Dye in field

23 Table 1.3: ANOVA Table of Species versus Density (g dry mass/ml)

Source Degrees of Sum of Mean Square F-value P-value Freedom Squares Species 13 0.055 0.004 15.452 <0.0001

Residual 39 0.011 0.0002736

24 Table 1.4: ANOVA Table of Species versus Dye-determined Flow rates

Source Degrees of Sum of Mean F-value P-value Freedom Squares Square Species 7 274.479 39.211 24.331 <0.0001

Residual 89 143.429 1.612

25 Table 1.5: ANOVA Table for the regression of Sponge Density vs Dye-determined Flow

Source Degrees of Sum of Mean F-value P-value Freedom Squares Square Regression 1 18.923 18.923 8.007 0.0300

Residual 6 14.180 2.363

Figure 1.1: Map of study sites. The right panel is an enlargement of the area in the left panel. The two study sites, Conch Reef and Diadema Reef, are indicated by the letters, CR and DR, respectively.

27 28

Figure 1.2: Volume vs. dry mass for eight sponge species. Note that both axes are plotted as a log scale.

29 30

Figure 1.3: Photograph of dye measurement technique. The long needled syringe is used to release dye into the excurrent stream.

Figure 1.4: Photographs of ADV setup. (A) The Norteks in their adjustable frames. (B)The ADV in the foreground is the Sontek with the aluminum arms and concrete bases.

33 34

Figure 1.5: Density, in g dry mass ml-1, of 11 sponge species. Filled bars are HMA sponges and open bars are LMA sponges (see Table 1.1). Horizontal bars signify species that are not significantly different. Values are mean ±SE.

Figure 1.6: Pumping rate, in l s-1 kg dry mass-1, of 8 sponge species. Filled bars are HMA sponges and open bars are LMA sponges (see Table 1.1). Letters signify species that are not significantly different. Values are mean ±SE.

Figure 1.7: Flow speed of four individuals of Spheciospongia vesparium. Lines represent speeds, in cm s-1, as measured by Acoustic Doppler Velocimeter. Open circles are flow speeds measured by the dye methodology. Data are plotted at date and time in 2004.

Figure 1.8: Average pumping rate (1000 L day-1 kg dry mass-1) of four individuals of S. vesparium. Filled bars are ADV measurements and open bars are dye measurements. The asterisk denotes comparisons that are significantly different (p<0.05). Values are mean ±SE.

30 Dye 25 ADV * p<0.05 20

15 * 10 1000L/day/L sponge 5

0 Individual of S. vesparium

Figure 1.9: Density, in g dry mass l-1, versus pumping rate, in l s-1 kg dry mass-1, for eight sponge species. Filled symbols are HMA sponges and open symbols are LMA sponges (see Table 1.1). The slope of the linear regression was significantly different than zero (p=0.030) and r2=0.572. Values are mean ±SE.

Chapter II

Differences in Sponge Metabolism

The work presented in this chapter that occurred in Florida is part of a larger research project involving Niels Lindquist, Christopher Martens, and Melissa Southwell. The goal of the larger project is to use stable isotopes to examine the role of sponges in C and N cycling across environmental gradients from nearshore to the outer reef tract near Key Largo, FL.

Portions of the work in this chapter are to be included in a manuscript on this topic by C.S.

Martens, N. Lindquist, J.B. Weisz, and M.W. Southwell.

Introduction

Sponges are abundant in a wide range of habitats from tropical to polar environments

(Reiswig 1973, Dayton et al. 1974, Rutzler 1978, Wenner et al. 1983, Suchanek et al. 1985,

McClintock 1987, Schmahl 1990). Sponge have an exceptional capacity to pump (Parker

1914, Jorgensen 1949, 1955, Vogel 1974, Gerrodette & Flechsig 1979, Riisgard et al. 1993,

Thomassen & Riisgard 1995, Turon et al. 1997, Ribes et al. 1999, Kowalke 2000, Lynch &

Phlips 2000, Chapter 1) and filter (Reiswig 1971a, b, Reiswig 1974, Reiswig 1981, Riisgard et al. 1993, Pile et al. 1996, Turon et al. 1997, Pile et al. 1997, Ribes et al. 1999, Lynch &

Phlips 2000) seawater, which allows them to significantly alter the concentrations of dissolved and particulate organic matter (DOM and POM) and nutrient elements in surrounding waters (Reiswig 1971a, b, Reiswig 1974, Reiswig 1981, Corredor et al. 1988, Riisgard et al. 1993, Pile et al. 1996, Diaz and Ward 1997, Turon et al. 1997, Pile et al. 1997,

Ribes et al. 1999, Lynch & Phlips 2000, Yahel et al. 2003, Chapter 1). However, the

question of specifically what sponges consume, and therefore what impacts sponges have on

reef nutrient cycles, has long puzzled marine scientists. Some of the earliest work on the

subject was done by collecting samples of incurrent (i.e. ambient) and excurrent water and

examining the samples under a light microscope to determine the identity and quantity of the

various microorganisms retained by a sponge (Reiswig 1971a). Reiswig was unable to

characterize the bulk of the particulate mass in the water samples because they were too

small to be resolved by a light microscope. Pile (1997) used flow cytometry to classify the

remaining particles and determined that sponges primarily feed on nanoplankton and

picoplankton. Other flow cytometry studies of sponges have confirmed this analysis (Pile et

al. 1997, Turon et al. 1997), thus using modern analytical tools to solve Reiswig’s mystery.

Although these flow cytometry studies have provided insight in the sponge diet, the

question is complicated by the fact that some sponge species contain endobiotic autotrophic and heterotrophic microorganisms (Hentschel et al. 2003, 2006 and references therein) that are capable of a diverse range of microbially-mediated processes that can affect the biogeochemical cycles of carbon, nitrogen and other elements critical to reef ecology. A

more complete understanding of sponge impacts on coral reef biogeochemistry is important

given that coastal eutrophication, climate warming and overfishing create conditions

detrimental to corals while favoring increases (Zea 1994, Rutzler 2004) or, in some instances

decreases (Butler et al. 1995), in sponge abundance.

In the clear water of the Great Barrier Reef (GBR), photosymbionts play a substantial

role in the nutritional ecology of sponges (Wilkinson 1983), while Caribbean reefs have few

46 phototrophic sponges but support a greater abundance and mass of sponges than Indo-Pacific

reefs (Wilkinson 1987, Wilkinson and Cheshire 1990). Many Caribbean species are

bacteriosponges (sensu Reiswig 1974) that internally host massive and diverse communities

of heterotrophic and autotrophic bacteria. Reiswig (1981) provided evidence that Aplysina

fistularis, a bacteriosponge, could not meet its C and energy needs solely from filtered POM

and therefore proposed that its microbial community took up substantial amounts of DOM

from filtered water. Yahel et al. (2003) showed that dissolved organic carbon (DOC), not

POM, provided the majority of C taken up by the Red Sea bacteriosponge, Theonella

swinhoei. Sponge associated microbes can also utilize and alter inorganic nutrient elements

released by the sponge host. For example, the nitrifying bacteria hosted by Chondrilla

nucula (Diaz et al. 2004) can oxidize virtually all of the ammonium generated by the organic

matter catabolism of the host sponge (Diaz and Ward 1997). The nitrate released from C.

nucula was estimated to fuel 50-120% of total reef primary productivity on a Puerto Rican

reef where C. nucula cover was ~12% (Corredor et al. 1988). Reiswig (1981) also

emphasized the role of sponges in reef ecology through their capture and remineralization of

nutrient elements from dissolved and particulate organic matter.

Ratios of the stable isotopes of C (13C/12C) and N (15N/14N) have been used extensively in biogeochemical and ecological studies to identify sources of C and N inputs to organisms and communities, and to identify particular metabolic pathways contributing to element cycling within them (reviewed by Fogel and Cifuentes 1993). For example, Fry and

Parker (1979) used stable isotopes of C and N to study the diet of a variety of fishes and invertebrates in seagrass meadows. By comparing the stable isotope ratios of the fish and invertebrates to the stable isotope ratios of various potential food sources, including seagrass

47 and other benthic vegetation, Fry and Parker (1979) determined that the seagrasses and other benthic vegetation were an important component of the diet of the animals in question.

Using these isotope tracers with sponge tissue will allow us to better determine what food sources are actually being consumed by a sponge, and potentially allow us to detect inputs of nutrients from microbial associates of sponges.

Here we present the results of an extensive survey of sponge stable C and N isotopic ratios across a range of natural habitats near Key Largo, FL (Fig. 1), as well as smaller surveys off the coast of North Carolina (NC) and the reefs of Papua New Guinea (PNG). The

Florida Keys provide a diversity of habitats, from large offshore reefs to shallow patch reefs

surrounded by seagrass to mangrove forests. Measurements among these diverse habitats are particularly useful for testing hypotheses regarding the relative importance of organic matter

sources and sponge-hosted microbial processes in controlling sponge tissue isotopic

composition and sponge contributions to nutrient cycling in benthic habitats and overlying

waters. As it was previously hypothesized that benthic filter-feeding invertebrates consume

organic matter originating in surrounding benthic vegetation (Fry and Parker 1979, Alber and

Valiela 1995), we also surveyed stable C and N isotopic ratios of the seagrass Thalassia

testudinum, the dominant benthic vegetation around Key Largo, FL (Fourqurean and Zieman

1991). We then compared the Florida sponges to NC and PNG sponges to examine regional

and interocean differences in sponge nutrition using these isotope tracers. We hypothesized that HMA sponges should have different C and N stable isotope ratios as compared to LMA sponges due to nutritional input from associated microorganisms. Additionally, we hypothesized that both groups of sponges should have different isotope ratios in nearshore versus offshore sites, due to inputs of terrestrial nutrient inputs.

Methods

Sponge Collection

Near Key Largo, Florida, sponge samples were collected at five sites in Florida Bay

and 12 ocean-side sites, although the collections focused on three sites in Florida Bay and

eight ocean-side sites (Fig. 2.1a). Our collections focused on ten species: Amphimedon compressa, Aplysina cauliformis, Callyspongia vaginalis, Ircinia campana, Ircinia felix,

Ircinia strobilina, Niphates digitalis, Niphates erecta, Spheciospongia vesparium, and

Xestospongia muta, but in total, 24 species were sampled from at least one site (Table 2.1).

These species were chosen based on observations of their abundance, both at a given site and across the area. At each collection site, 3-6 individuals of each species were sampled. We cut a 2 to 3 cm3 piece from each sponge that included both surface and underlying tissues so

as to reduce data variability by homogenizing surface and sub-surface tissues that may have

different microbial communities and thus stable isotope compositions. Tissue samples were

placed in Ziploc bags during the dive, and then frozen upon our return to the UNCW/NURC

base. Blades of the seagrass Thalassia testudinum were also collected ~100 m landward of

Pickles Reef (Fig.2.1a: PR), an outer reef tract site, and at three patch reefs (Fig. 2.1a: 3SR,

TAV, TRI) closer to Key Largo and processed as described above for the sponge samples.

In Papua New Guinea, sponges were collected during two research cruises on the

M/V Golden Dawn in 2000 and 2001. Sponges were collected from four sites along the

northern coast of New Britain Island in 2000 and three sites off of the city of Madang in 2001

(Fig 2.1b). All PNG sponge collections were made using the protocol described above.

49 In North Carolina, sponges were collected from a variety of habitats in the area of

Morehead City and Beaufort (Fig 2.1c). In near-shore environments, sponges were collected from the Morehead City floating docks, the Mitchell Village groin, the Beaufort Bridge floating docks, Radio Island Jetty, Cape Lookout Jetty, and the wrecks of the Indra and the

liberty ship Theodore Parker (NC artificial reefs AR-330 and AR-315, respectively).

Sponges were also collected at three sites offshore. NC sponge species were collected

following the protocol described above.

Stable Isotope Measurements

In preparation for stable isotope analyses, all frozen tissue samples were lyophilized and ground using an agate mortar and pestle. Samples were weighed into tared combusted silver boats (5x9 mm; Costech Analytical; Valencia, CA) on a Cahn C-30 Microbalance and then exposed to HCl vapor in closed containers to remove carbonate. Samples were then placed in a 70oC oven for 1 hr to remove residual acid. Sample C and N compositions and

isotopic values were determined on a Carlo Erba NA 1500 elemental analyzer equipped with

autosampler interfaced via a Finnigan ConFlo II to a Finnigan MAT 252 isotope ratio mass

N 3 spectrometer. The stable isotopic ratio was calculated as: δ X = [(Rsample - Rstd)/Rstd] x 10 in units of parts per thousand (‰). The coefficient NX is the heavy stable isotope of the element

(13C or 15N). R is the ratio 13C/12C or 15N/14N of both sample and standard. The standard for C isotopic measurements is Pee Dee Belemnite (0.0‰) and for nitrogen is atmospheric N2

(0.0‰) Instrument specified standard deviations for δ13C and δ15N analyses are 0.2 and

0.3‰, respectively. Pure acetanilide standard is used as a quality assurance standard to ensure complete combustion.

Analysis of Data

Data from the different geographic regions (FL, NC, and PNG) were first analyzed

separately, and then grouped and analyzed. Florida data were more extensively analyzed

because there were a sufficient number of data points to complete additional data analyses.

To first address the assumption of independence of samples in the Florida dataset necessary

for all other statistical tests, we performed a cluster analysis (Everitt 1977) on the entire δ15N and then the entire δ13C data set using SAS (Statistical Analysis Systems, Inc., Cary, NC).

An average δ15N or δ13C value for each site/species combination was used for each analysis.

The results of the cluster analyses for both the δ13C and δ15N data resulted in three important clusters. Clusters cannot be properly tested for significance, but generally there is a major break in the r2 values which indicates how many clusters are important (McGarigal et al.

2000). These clusters for the C data showed no patterns in site or species. Although the N data showed no site pattern, the cluster analysis did reveal a break between species (see

Results). This indicates that there was independence between samples and suggested a possible statistically significant difference in the δ15N values of all of the species.

All further statistical analyses were carried out using Statview for Windows

(Statistical Analysis Systems, Inc., Cary, NC). To examine interspecific differences in the N isotope data and determine which species fell into which δ15N group, we performed a one- way ANOVA with species as the independent factor and δ15N values as the dependent factor, followed by Fisher’s protected least significant difference (PLSD) post-hoc test. Based on the results of these tests, each species was assigned to either the high or low δ15N group. We

51 also performed a one-way ANOVA on the δ13C data followed by Fisher’s PLSD post-hoc test to examine interspecific differences in the C isotope data.

For sponges from the eight major collection sites (Conch-Deep, Conch-Mid, Conch-

Shallow, Duane, Pickles, Tavernier Rocks, Three Sisters, and Triangles; Fig 2.1a), simple linear regressions were performed on the C and N data sets split into the high and low δ15N groups. The δ15N values and the δ13C values were independently regressed against distance between the collection site and the 20 m isobath of the outer reef tract. This distance to the

20 m isobath (DTI) measure enabled us to assign a unique numerical value that linked together sites of similar environments. The 20 m isobath was chosen because it approximates the break between deeper reefs habitats influenced primarily by oceanic physics and biology from regions behind the outer reefs dominated by seagrass meadows and shallow patch reefs. The regressions showed that the slope for the high and low δ15N groups significantly differed from zero, indicating that δ15N and δ13C ratios were changing between inshore and offshore sites.

To test for differences in the δ13C and δ15N values of offshore (Conch-Deep, Conch-

Mid, Duane, and Pickles) versus inshore (Tavernier Rocks, Three Sisters, and Triangles) sponges, both between and within δ15N groups, it was first necessary to balance the data set.

This analysis was limited to the 12 most common species for which there were at least five replicate individuals at one of the seven major collection sites. Note that sponges collected at the Conch-Shallow site were removed from this analysis as the site as characteristics of both offshore and inshore habitats (JBW pers. obs.). At each site, five individuals of each species were randomly selected, resulting in a balanced data set. This process was repeated four more times so that five randomly generated data sets were produced. For each data set,

52 simple unpaired t-tests were run comparing inshore versus offshore values for all of the data,

and then separately for the high and the low δ15N sponge groups. If at least three of the five

data sets had p-values less than 0.05 for any comparison, then the comparison was considered

to be statistically significant.

Isotope data for NC sponges were analyzed for interspecific differences in both δ15N and δ13C values using a one-way ANOVA as described for the FL data. The NC data were also analyzed with a simple t-test to detect differences between offshore and inshore samples.

Isotope data for Papua New Guinea were analyzed for interspecific differences as described for FL and NC sponge data. The sample for Ianthella basta and the sample for Theonella swinhoei were excluded from the PNG analysis because there was only one replicate of each species.

To examine large-scale geographic patterns, data from all three regions were put into a cluster analysis. As with the earlier cluster analysis, average values for each site/species comparison were put into the analysis. For the FL data, only the ten focal species (see species listed above under “sponge collections”) were used. For the NC dataset an average value for each species across all sites was used in the analysis, as very few species in this dataset were collected at different sites and no species were collected at both inshore and offshore sites. Additionally, this cluster analysis was performed on the δ13C and δ15N values simultaneously. Using both measurements in the analysis allows each site to be better characterized.

Results

Florida Samples

The cluster analysis showed no groupings of samples based any site or species (Fig

2.2), thus indicating that there was independence among the samples, and that the assumption

of the ANOVA was met. The ANOVA for species versus δ15N value was significant (F =

45.725, p<0.0001; Table 2.2). Plotting the δ15N values versus the δ13C values showed no interspecific pattern in the δ13C data, but showed this significant break in the δ15N values (Fig

2.3), thus indicating that further analyses could be carried out on the split dataset. Seagrass at all four collection sites had high δ13C [-7.98 ± 0.32‰ (mean ± 1SE), n = 10] and low δ15N

[1.90 ± 0.28‰ (mean ± 1SE), n = 10] values, which were within the previously reported range of values for T. testudinum in the Florida Keys (Anderson & Fourqurean 2003).

The ANOVA for interspecific differences in δ13C values was significant (F = 20.125, p<0.0001; Table 2.3). Regressing the δ13C values versus DTI showed that sponges in both the high and low δ15N groups differed significantly between the inshore sites and the offshore sites (Fig 2.4), indicating a major shift in sponge C sources across these habitats.

The regression analysis of the δ13C survey data showed that the collection site significantly

correlated with the δ13C values of all sponge species, explaining 56.8% of the variability in their δ13C values. In the shallow patch reefs, the δ13C value of the HMA sponges was significantly lower than the LMA sponges (Fig 2.4, average t-value = 3.733, average p =

0.0011), but in the offshore reefs, this situation was reversed (Fig 2.4, average t-value = -

3.774, average p = 0.0031).

54 Regressing δ15N values for high and low δ15N sponges for each collection site against

DTI (Fig. 2.5) revealed a significant, progressive enrichment of 15N in tissue of low δ15N sponges moving from the nearshore patch reefs to the outer reef tract sites. In contrast, high

δ15N sponges showed a slight but statistically significant depletion of 15N along the same gradient.

North Carolina Sponges

The NC sponges collected offshore differed significantly from the inshore collections, with the offshore sponges having significantly higher δ13C values and significantly lower

δ15N values. The ANOVA for δ15N was significant (F = 22.917, p<0.0001, Table 2.4) and the post hoc test showed that all of the inshore sponge samples fell into the high δ15N group, while the offshore samples fell into both groups, (Fig 2.6). Interestingly, for those sponge species found both in Fl and on offshore NC reefs, their δ15N values were always similar, either both having low δ15N or both having high δ15N values. The ANOVA for δ13C was significant (F = 17.242, p<0.0001, Table 2.5) and the post hoc test showed that all the offshore sponges, except N. erecta, had significantly heavier values than the inshore species.

There were some differences among the inshore samples, with those species collected at the two wreck sites (The Indra and The Theodore Parker) being intermediate between the offshore samples and the samples from docks, groins, and jetties in the coastal sounds near

Morehead City.

55 Papua New Guinea Sponges

The ANOVA for δ15N values was significant (F = 16.802, p < 0.0001, Table 2.6), and the post-hoc test showed that two species (Hyrtios sp. and X. carbonara) differed from each other and all other species, with their values placing them in the low δ15N group, while the remaining species were not significantly different from each other, constituting the high

δ15N group. The ANOVA for δ13C values was significant (F = 15.303, p < 0.0001, Table

2.7), and the post-hoc test showed that Haliclona sp. was significantly lighter than all of the other species, while Hyrtios erecta was significantly heavier than all of the other species.

Regional Comparison

The cluster analysis for all data resulted in seven apparently significant clusters (Fig

2.8). There was no clustering based on region. Clustering was primarily driven by a few unique locations (FL bay samples and inshore NC samples) and the low vs. high δ15N split.

There were no distinctions between PNG samples, FL samples from ocean-side of Key

Largo, and offshore NC sponges, except for low vs. high δ15N.

Discussion

Analysis of the δ13C data for Florida showed that location explained a majority of the variability in the carbon data for Florida sponges and that there was a significant difference between nearshore and offshore sites. While an obvious difference between many of these sites is the depth, regressions of sponge δ13C values versus depth had much lower r2 values

(combining the high and low δ15N groups, r2 = 0.400 for δ13C versus depth, r2 = 0.573 for

δ13C versus DTI), and thus the inshore-offshore difference in carbon isotope data is likely

56 driven primarily by other factors. Another large difference between the nearshore and

offshore site is the presence of abundant seagrass meadows, dominated by T. testudinum, surrounding nearshore patch reef sites, and the absence of seagrass at the offshore sites.

Because T. testudinum has relatively heavy (i.e. more positive) δ13C values, its presence could easily drive this difference, provided that seagrass derived C was being consumed by the sponges at these inshore sites. Additionally, stable isotope studies of seagrass bed communities have shown that many organisms consumed seagrass-derived carbon, including filter-feeding bivalves like Aequipectin irradians and Anadara antiquate (Fry and Parker

1979, Fry et al. 1983). Given this trophic transfer pattern, seagrass carbon may be accessible to sponges by direct filtration of detritus or by consumption of bacterial decomposers of seagrass. Additionally, seagrass is known to exude large amounts of DOM (Ziegler and

Benner 1999), which could be taken up by resident sponge bacteria (Yahel et al. 2003) or consumed by bacterioplankton and subsequently filtered by the sponge (Ziegler and Benner

1999). Using 15N labeled seagrasses, Alber and Valiela (1995) studied filter feeding by the bay scallop, Argopecten irradians, and found that the scallops obtained N from aggregates of organic matter exuded by the seagrasses. Because they collected these aggregates on 0.7 µm pore size filters, these aggregates are within a size range accessible to sponges (Hooper et al.

2002). Alber and Valiela proposed a model of a detrital food web to explain how nutrients from primary producers are consumed by filter-feeding organisms. Based on this model, we propose two food web models that explain the sources of nutrients to sponges in both nearshore (Fig 2.9a) and offshore (Fig 2.9b) environments. In nearshore habitats, seagrasses leach nutrients into the water, either as excess photosynthate (Ziegler and Benner 1999) or during decay. These nutrients are aggregated by plankton and adsorptive processes and

57 become a food source for sponges. Additionally, decaying seagrasses become part of the

organic detritus, which, due to the shallow water, is resuspended frequently by even moderate wave action. In offshore habitats, the input of heavy seagrass-derived C is absent, and the major external source of particulate nutrition for sponges is derived from plankton directly as POM or aggregated DOM. Organic detritus in offshore habitats likely does not

contain seagrass, and this detritus is resuspended less frequently, as greater wave intensity is

needed to disturb benthic habitats in these deeper waters.

The fact that all of the sponge species studied were enriched in 13C near seagrass beds suggests that both HMA sponges and LMA sponges consume seagrass C. However, LMA sponges have a significantly greater difference in their δ13C values between nearshore and offshore sites (Fig 2.4). This suggests that the LMA sponges have a significantly different source of C between nearshore and offshore sites, while the HMA sponges appear to be buffered by some other C source, presumably mediated by their associated microbial community.

Based on literature sources and the results of our studies, all of the FL sponge species in this study have been classified as either HMA sponges or LMA sponges (Table 2.1). All of the 11 low δ15N species represented in Fig. 3 are HMA sponges. Among the 15 high δ15N sponges, five are known to be HMA sponges (Table 2.1). The strong association between low δ15N tissue values and the presence of abundant microbes in sponges suggest that internal microbial activity can exert significant control on the N isotopic composition of the

HMA sponges. This disparity therefore appears to be related to internal processing of N suggesting that sponges in high and low δ15N groups differ significantly in their N cycling pathways. While there is also some difference in the internal processing of N in high δ15N

58 HMA sponges versus high δ15N LMA sponges, as evidenced by the nitrification detected in

high δ15N HMA sponges but not in high δ15N LMA sponges (Chapter 1), we as yet have no

data to suggest that any of these differences influence the N cycle of the sponge itself.

However, for the low δ15N HMA sponges, their microbial communities probably give them access to N sources that are unavailable to the LMA sponges, and possibly the high δ15N

HMA sponges, which are limited to eukaryotic, and therefore exclusively, heterotrophic metabolic processes. There are many possible microbially-mediated mechanisms that either alone or in combination could explain the diverse N stable isotopic values of the bactersiosponges. These include N2 fixation, fractionation during bacterial NH4 uptake, and

DON uptake by associated bacteria. Although, there is little data to support or refute any of these hypotheses, all three rely on microbial uptake of N species that are unavailable to sponge cells. Therefore, our isotope survey provides direct evidence of nutrients obtained by bacteria, despite the lack of evidence for the mechanism.

Like the reefs of the FL Keys, offshore reefs of NC had both high and low δ15N sponges, and the sponge species common to both locales (e.g., Niphates erecta, Ircinia strobilina, Agelas conifera) had similar δ15N values, suggesting that sponge species retain a particular mode of nutrition independent of location or environment. This result parallels recent findings that many HMA sponges share microbes unique to sponges and that these specific associations are maintained across vast geographic ranges (Hentschel et al. 2002).

Interestingly, there was no overlap in species between nearshore NC and any FL sponges, and all the nearshore NC sponges all had relatively high δ15N values. As low δ15N sponges are all HMA sponges, with apparently characteristically high tissue densities (Chapter 1), and the majority of high δ15N sponges are LMA sponges (~66%), it is possible that HMA

59 sponges would either be unable to survive, or at least be outcompeted in the more POM-rich and nutrient-rich temperate waters found in nearshore habitats in NC. HMA sponges may not be able to effectively filter-feed because the heavy particulate load could overwhelm their small canal system. In oligotrophic, POM-replete waters, such as those found over many coral reefs, the HMA sponges are nutritionally successful probably because of the apparent nutritional inputs via their microbial associates as DOM uptake (Yahel et al. 2003), photoautotrophy (Wilkinson 1983) and possibly chemoautotrophy, such as nitrification

(Corredor et al. 1988, Diaz and Ward 1997). These input of C and nutrients via associated microbes give the HMA sponges the energy to compete with other benthic organisms and to allocate resources to effectively defend against abundant potential predators present in the reef environment However, in temperate climates, especially nearshore habitats influenced by large inputs of nutrients in runoff and where POM is much more abundant, these HMA sponges are not able to compete, and thus are competitively excluded by fast growing benthic invertebrates and seaweeds. A study by Walters and Pawlik (2005) examined wound healing rates in several Caribbean sponge species and determined that species that are chemically defended have slower wound healing rates. As three of the four chemically undefended species are LMA sponges, and all three of the chemically defended species are HMA sponges, we can conclude that HMA sponges generally have slower wound healing rates, and presumably slower overall growth rates, as compared to LMA sponges. This supports the hypothesis that HMA sponges may be out-competed in eutrophic habitats such as nearshore

NC.

The NC C isotope data is also consistent with the FL data in that there appears to be a gradient in δ13C values moving offshore, though unlike the FL data, the gradient goes from

60 light values inshore to heavier values offshore. This spatial pattern in the NC sponges is

expected, because the nearshore NC sponges are likely influenced by terrestrial nutrient

inputs while the offshore NC sponges are less affected by terrestrial nutrient inputs. The

stable C isotope ratios of terrestrial organic matter are generally lighter than those of marine

organic matter, because fractionation can occur in terrestrial environments where C is not

limited, but fractionation is limited in marine environments where C can be limited (Hoefs

2004). As previously discussed, this pattern is reversed in FL because the nearshore habitats

are more influenced by the seagrass, which has a stable C isotope ratio heavier than both

oceanic and terrestrial organic matter. Although there was not sufficient data to confirm this

NC inshore-offshore gradient in stable C isotope ratios, it appears that in NC, like FL, N

isotope ratios show interspecific variability, while C isotope ratios show geographic

variability.

Although the PNG data analysis only revealed two species with low δ15N values,

several of the other species are known to be HMA sponges. Studies by Wilkinson (1983)

suggested that on outer, oceanic reefs like the GBR, which likely has similar sponge

communities to PNG, about 90% of sponges received significant nutritional inputs from

associated phototrophic microorganisms.

Our investigations of broad regional and inter-ocean trends failed to reveal distinct

patterns except for reinforcing a consistent species based dichotomy between high and low

δ15N sponges. The largest difference between clusters separated several sponges from

Florida Bay from the remaining samples. These Florida Bay sponge samples have notably heavier δ13C values, which are likely related to receiving nutrient inputs from a much different source than the sponges from the patch reefs and reef tract. The next largest

61 difference between clusters divided samples from inshore NC, which is heavily impacted by

terrestrial organic matter, from the remaining samples. These patterns suggest that there is a

significant difference in sponge nutrition between reef habitats and other nearshore

environments. Thus, on a global scale, the differences in sponge nutrition are characterized

by different carbon sources, which are primarily a function of the differences in the dominant

POM and DOM sources. However, on local scales, the differences in sponge nutrition

appear to be driven by factors that cause the split in δ15N ratios.

Our stable isotope survey has revealed that sponges have a variety of complex interactions with the biogeochemical cycles of the reef. While most of these interactions are poorly understood, our data has shown that they vary between habitat types and between sponge species. As evidenced by the nitrogen flux calculations (Southwell et al. 2006), sponges can have major impacts on nutrient cycles of the reef. Therefore, while it remains crucial that we understand these sponges in order to understand the complex biogeochemistry of the changing reef environment, it is apparent that significant research in these areas will be required. The stable isotope analyses have been shown to be a useful tool for surveying the nutrient flows into and out of the sponge.

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67 Table 2.1: Sponge species collected in Florida

Species Avg. Avg. N HMA/ Reference δ13C* δ15N* groupa LMAb

Agelas clathrodes -17.44 4.98 High HMA Hentschel et al. unpub

Agelas conifera -18.22 4.46 High HMA Richelle-Maurer et al. 2003

Agelas schmidti -17.51 4.40 High HMA Hentschel et al. unpub

Amphimedon compressa -17.15 4.79 High LMA Hentschel et al. unpub

Aplysina cauliformis -17.90 1.95 Low HMA Chapter 3

Aplysina fulva -18.27 2.25 Low HMA Vincente 1990

Callyspongia plicifera -18.24 4.01 High LMA Hentschel et al. 2006

Callyspongia vaginalis -16.68 3.67 High LMA Hentschel et al. 2006

Calyx podatypa -17.78 1.75 Low HMA Hentschel et al. unpub

Chondrilla nucula (bay)† -14.52 5.23 High HMA Rutzler 1990

Chondrilla nucula (reef)† -18.87 1.53 Low HMA Rutzler 1990

Ectyoplasia ferox -19.19 2.29 Low HMA Hentschel et al. unpub

Iotrochota birotulata -18.39 3.82 High LMA Hentschel et al. unpub

Ircinia campana -15.80 -0.05 Low HMA Vincente 1990

Ircinia felix -16.09 1.15 Low HMA Chapter 3

Ircinia strobilina -15.90 1.59 Low HMA Vincente 1990

Ircinia variablis -12.31 -0.02 Low HMA Sara 1971

Mycale laxissima -13.61 4.63 High LMA Rutzler 1990

Niphates digitalis -16.57 4.20 High LMA Chapter 3

Niphates erecta -16.28 4.26 High LMA Chapter 3

68 Table 2.1 Continued

Species Avg. Avg. N HMA/ Reference δ13C* δ15N* groupa LMAb

Smenospongia aurea -16.56 2.25 Low HMA Fieseler et al. 2004

Spheciospongia vesparium -13.60 4.44 High HMA Vincente 1990

Spongia officinalis -12.11 -1.64 Low HMA Wilkinson et al. 1984

Tedania ignis -17.48 6.33 High LMA Hentschel et al. unpub

Ulosa ruetzleri -19.48 5.77 High LMA Hentschel et al. unpub

Xestospongia muta -19.41 4.59 High HMA Hentschel et al. 2006

* Average δ13C and δ15N values for the species at all collection sites. a N group indicates whether the species fell into the group of high δ15N or low δ15N sponges. b HMA indicates HMA sponges and LMA indicates LMA sponges † Chondrilla nucula is found at site in Florida Bay and along the reef tract. It is listed twice because the Florida Bay samples fall into the high δ15N group, while the reef tract samples fall into the low δ15N group.

69 Table 2.2: ANOVA of δ15N vs. species for FL data

Degrees of Sum of Source Mean Square F-value P-value Freedom Squares Species 24 988.080 41.170 45.725 <0.0001 Residual 299 269.212 .900

70 Table 2.3: ANOVA of δ13C vs. species for FL data

Degrees of Sum of Source Mean Square F-value P-value Freedom Squares Species 24 1053.204 43.883 20.125 <0.0001 Residual 299 651.975 2.181

71 Table 2.4: ANOVA of δ15N vs. species for NC data

Degrees of Sum of Source Mean Square F-value P-value Freedom Squares Species 10 138.032 13.803 22.917 <0.0001 Residual 35 21.080 0.602

72 Table 2.5: ANOVA of δ13C vs. species for NC data

Degrees of Sum of Source Mean Square F-value P-value Freedom Squares Species 10 77.104 7.710 17.242 <0.0001 Residual 35 15.651 0.447

73 Table 2.6: ANOVA of δ15N vs. species for PNG data

Degrees of Sum of Source Mean Square F-value P-value Freedom Squares Species 6 41.781 6.963 16.802 <0.0001 Residual 55 22.794 0.414

74 Table 2.7: ANOVA of δ13C vs. species for PNG data

Degrees of Sum of Source Mean Square F-value P-value Freedom Squares Species 6 29.868 4.978 15.303 <0.0001 Residual 55 17.567 0.325

Figure 2.1: Maps of Sponge Collection Sites. (A) Collections sites in the Key Largo, FL area. The larger area map is found in Figure 1.1. (B) Collection sites in North Carolina. Inshore sites are shown and offshore sites, which are outside the map area, are indicated by arrows. The Secret Site is located at 34º 07.513’ N / 76º 33.580’ W, and Ten Fathom Ledge is located at 34º 23.330’ N / 76º 35.650 W.

Figure 2.2: Cluster analysis for stable N isotope ratios of Florida sponges. Thick lines on the right side of the dendrogram indicate the significant clusters.

Figure 2.3: δ15N versus δ13C for Florida sponges. Points are the average value for each species (n=3 – 45) at all collection sites in the Key Largo, Florida area. Error bars indicate one standard error. Triangles represent those species that fall into the high δ15N group and circles represent those species that fall into the low δ15N group. Open symbols are HMA sponge species, while closed symbols are the LMA sponges.

80 7 6 5 4 N

3 15 δ 2 1 0 High δ15N Low δ15N -1 -2 -21 -19 -17 -15 -13 -11 δ 13C

Figure 2.4 Stable C isotope ratios of Florida sponges versus distance to the 20 m isobath. Triangles represent the average value for all low δ15N species at each site, and circles represent the average value for all high δ15N species at each site. Error bars indicate one standard error. Site codes are as follows: TAV is Tavernier Rocks, TRI is Triangles, SIS is Three Sisters Reef, CNS is the shallow site on Conch Reef, PIC is Pickles Reef, CNM is the intermediate depth site on Conch Reef, CND is the deep site on Conch Reef, and DUA is the wreck of the Duane. Values near the lines are the results of the linear regression for each group.

82 83

Figure 2.5 Stable N isotope ratios of Florida sponges versus distance to the 20 m isobath. Graph follows Figure 2.4. The linear regression lines are present.

Figure 2.6 δ15N versus δ13C for North Carolina sponges. Points are the average value for each species (n=2 – 7) at all collection sites. Error bars indicate one standard error. Triangles represent those species collected at inshore sites and circles represent those species collected at offshore sites.

5 N

4 15 δ

2 Inshore Offshore 1

0 -23.0 -22.0 -21.0 -20.0 -19.0 -18.0 δ13C

Figure 2.7 δ15N versus δ13C for Papua New Guinea sponges. Points are the average value for each species (n=3 – 45) at all collection sites. Error bars indicate one standard error.

4 N

3 15 δ

0 -20.0 -19.5 -19.0 -18.5 -18.0 -17.5 -17.0 δ13C

Figure 2.8 Cluster analysis of stable C and N isotope data of all sponge samples. Only the structure of important clusters is shown. Samples that make up each group are listed by species name and collection sites.

Group 1

Group 2 N. erecta Conch Shallow N. erecta Pickles X. muta Three Sisters

Group 3 Group 5 Group 4 A. compressa Tavernier Rocks A. compressa Three Sisters Group 5 A. compressa Triangles C. nucula Grouper Creek C. nucula Jewfish Creek Group 6 C. nucula Porjoe Key Group 7 C. vaginalis Tavernier Rocks 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 Average distance between clusters C. vaginalis Three Sisters Group1 N. erecta Duane C. vaginalis Triangles Adocia NC inshore Oceanapia sp. New Britain M. laxissima Three Sisters Aplysilla NC inshore Petrosia sp. New Britain N. digitalis Three Sisters Microciocia NC inshore T. swinhoei New Britain N. erecta Tavernier Rocks N. erecta NC offshore X. muta Conch Deep N. erecta Three Sisters Petrosia sp Madang X. muta Conch Shallow N. erecta Triangles Sun Sponge NC inshore X. muta Duane S. vesparium Jewfish Creek Unk. blue sponge NC inshore X. muta Pickles S. vesparium Tavernier Rocks Unk. gray sponge NC inshore X. testudinaria Madang Unk. orange sponge NC X. testudinaria New Britain inshore X. testudinaria New Britain Group 6 Unk. purple sponge NC A. cauliformis Tavernier inshore Rocks X. muta Conch Mid Group3 A. cauliformis Triangles A. cauliformis Conch Deep I. campana Rodriguez Group 2 A. cauliformis Conch Mid I. campana Three Sisters A. cauliformis Conch Deep A. cauliformis Conch Shallow I. felix Conch Shallow A. compressa Conch Mid A. cauliformis Duane I. felix Duane A. compressa Duane A. cauliformis Pickles I. felix Rodriguez A. compressa Pickles A. cauliformis Three Sisters I. felix Tavernier Rocks A. conifera NC offshore A. fulva Duane I. felix Tavernier Rocks C. vaginalis Conch Deep Hyrtios erecta Madang I. felix Three Sisters C. vaginalis Conch Mid Hyrtios sp. New Britain I. strobilina Conch Mid C. vaginalis Duane I. felix Conch Deep I. strobilina Conch Shallow C. vaginalis Pickles I. felix Conch Mid I. strobilina Habitat Callyspongia sp. 2 New Britain I. felix NC offshore I. strobilina Three Sisters 11 I. felix Pickles I. strobilina Triangles Haliclona sp. New Britain I. strobilina Duane I. variablis Jewfish Creek Hyrtios erecta Madang I. strobilina NC offshore Hyrtios erecta Madang X. carbonara New Britain Group 7 I. basta New Britain C. nucula Cowpen I. birotulata Duane Group 4 I. variablis Cowpen I. birotulata Habitat A. compressa Conch Shallow S. vesparium Cowpen N. digitalis Conch Deep C. vaginalis Conch Shallow S. vesparium Porjoe Key N. digitalis Duane N. digitalis Conch Shallow N. erecta Conch Mid N. digitalis Pickles

Figure 2.9 Proposed food web models. Models explain the sources of nutrients to sponges in (A) nearshore and (B) offshore environments. In both cases sponge are shown to be consuming POM, however bacteriosponges can also consume DOM

Chapter III

Linking molecular and microscopic diversity of sponge associated microbial

communities to metabolic differences in host sponges

Introduction

Sponges have likely hosted associated microorganisms since the first appearance of the phylum over 500 million years ago (Wilkinson 1984). Modern day sponges can host a variety of microbes, including cyanobacteria (Vincente 1990, Arillo et al. 1993,

Magnino et al. 1999), diverse heterotrophic bacteria (Wilkinson 1978a, b, c; Santavy et al. 1990, Magnino et al. 1999), unicellular algae (Sara and Liaci 1964; Rützler 1990;

Wilkinson 1992), fungi (Holler et al. 2000, Webb and Maas 2002), and zoochlorellae

(Gilbert and Allen 1973). In some species, microorganisms can account for up to 60% of the sponge biomass (Wilkinson 1978a, b, c), exceeding seawater concentrations by two to three orders of magnitude (Friedrich et al. 2001). Because sponge-microbe associations are widely distributed across sponge taxa and, in some cases, are unique to sponges

(Hentschel et al. 2002, 2006), many of these associations are thought to be truly symbiotic rather than transient associations resulting from sponge filter feeding activity

(Preston et al. 1996, Fuerst et al. 1999, Haygood et al. 1999). Physiological and ecological roles that have been ascribed to sponge microbial symbionts include nutritional enhancements, (Wilkinson 1992, Arillo et al. 1993, Vacelet et al. 1995),

stabilization of the sponge skeleton (Wilkinson et al. 1981), and secondary metabolite production (Unson et al. 1994, Bewley et al. 1996, Schmidt et al. 2000). Although both cultivation-based and molecular studies have shown that microbial communities can vary considerably among sponge species (Wilkinson 1978a, b, c; Wilkinson et al. 1981;

Santavy et al. 1990; Webster and Hill 2001), recent molecular data presented by

Hentschel and co-workers (2002, 2006) suggest that many diverse sponge species, even from different oceans, share a common set of unique associated microbes.

Reiswig (1974) coined the term “bacteriosponge” to describe sponge species with a significant biomass of microorganisms. Vacelet and Donadey (1977) performed studies on 11 taxonomically diverse demosponge species using transmission electron microscopy and identified two different types of associations between microbes and the host sponge.

Sponges with dense tissue contain numerically large and morphologically diverse microbial communities (i.e. bacteriosponges), while those with well-irrigated tissues contain few bacteria and typically only a single morphotype. However, this interesting dichotomy in microbial associations among sponges has received little additional attention, possibly because most modern studies of sponge-associated bacteria have focused on those sponge species producing pharmacologically active secondary metabolites (Haygood et al. 1999, Moore 1999). Many of these sponges (e.g. Theonella swinhoei) host high densities of associated microbes (Piel 2004).

A broad survey of stable carbon and nitrogen isotope ratios of sponges in the Key

Largo, Florida (FL) area (see Chapter 2) revealed three distinct groups of sponges: one group (n=11 species), composed of HMA sponges, had low δ15N values (-1.64 to 2.29), a second group (n=10 species), composed of LMA sponges, had high δ15N values (3.67

to 6.33), and the third group (n=6 species), composed of HMA sponges with high δ15N values (4.40 to 5.23). These δ15N values represent the ratio of 15N to 14N in the bulk sponge tissue and can provide information on sources of the nitrogen. The distinct, significant break of ~1.5 ppm between the low and high groups was surprising and suggestive of a fundamental difference in N metabolism. As this work was conducted prior to recognizing the difference between the high δ15N HMA sponges and high δ15N

LMA sponges, only species from the first two groups were used in this work.

The values of the high δ15N group are indicative of N acquired from an allochthonous dietary source. Because prokaryotic microbes are responsible for most biologically mediated transformations of N (Zehr and Ward 2002), the low δ15N sponges likely arise from N transformations performed by associated microbes that results in an enrichment of 14N in their tissue. In this study, we used microscopy and molecular tools

to investigate how the relative presence or absence of microorganisms relates to the δ15N value of the two low δ15N sponges and one high δ15N sponge.

Methods

Sample Collection

Based upon the results of the stable isotope survey of Florida Keys sponges (see

Chapter 2), three representative species were chosen for this study: the rope sponge

Aplysina cauliformis, the ball sponge Ircinia felix, and the rope sponge Niphates erecta

(Fig. 3.1). A. cauliformis has a relatively low or “light” δ13C value (-17.73‰) and a moderately light δ15N value (2.14‰). I. felix has a higher δ13C value (-16.30‰) and a lower δ15N value (1.47‰). N. erecta has heavier δ13C (-16.05‰) and δ15N (4.41‰)

values. Sponge samples were collected using SCUBA from two sites near Key Largo,

Florida: Conch Reef is part of the outer reef tract with an oceanic nutrient profile and subject to periodic upwelling of deep Florida Current water (Leichter et al. 2003).

Sponges were collected from a depth of approximately 20-25 m. Three Sisters Reef is a small inshore patch reef surrounded by a dense seagrass meadow and having an average depth of 5 m. A single-edge razor blade was used to cut a small section (approximately 2-

3 cm³) of tissue of each sponge, which included both the surface pinacoderm and inner mesophyl. Three individuals of each species were collected at each site. Tissue samples were placed individually in plastic bags and stored in their bags on ice until further processing, which always occurred within 3 to 4 hours. Samples for molecular genetic work were cut from each sample, briefly rinsed with sterile seawater, placed in 2 mL

Nalgene cryopreservation tubes, and frozen in liquid nitrogen. Samples for transmission electron microscopy (TEM) were preserved with 2.5% glutaraldehyde in sterile seawater, and stored at 4ºC.

To differentiate between sponge-associated bacteria and seawater bacteria passing through the sponges at the time of collection, ambient water samples were also collected and analyzed. Water samples were collected in collapsible containers by SCUBA from

0.5-1 m above the reefs, pre-filtered through a 39 µm Nitex mesh to remove larger particles (Reiswig 1975, Turon et al. 1997) and then vacuum-filtered onto 0.22 µm nylon membrane filters. To ensure that sufficient biomass was collected, filtration continued until the flow rate through the filter dropped below approximately 1 drop per minute.

Filters were then folded in half, wrapped in aluminum foil and stored in liquid nitrogen until further processed.

Transmission electron microscopy

Sponge tissue that had been preserved for TEM were cut into smaller pieces several mm3 in size using a EtOH-sterilized scalpel, rinsed for 10 min in 1x PBS three

times and fixed overnight in 2% osmium tetraoxide (v/v). After two additional rinses

with 1x PBS, the pieces were dehydrated in an ethanol series (30%, 50%, 70%, 100%)

and incubated 3x30 min in 1x propylene oxide. Following overnight incubation in 1:1

(v/v) propylene oxide/Epon 812 (Serva) the samples were embedded in Epon 812 at

60ºC. The embedded samples were subsequently sectioned with an ultramicrotome (OM

U3, Reichert, Austria) and examined on an EM 10 electron microscope (Zeiss,

Germany).

Denaturing Gradient Gel Electrophoresis (DGGE)

A small (20-30 mg) piece of tissue was cut from each frozen sponge sample. The

sponge tissue was then ground with a mortar and pestle while submerged in liquid

nitrogen. Genomic DNA was extracted with the Fast DNA SPIN Kit for soil (Q-Biogene)

according to the manufacturer’s instructions. DNA was extracted from water filters by

vortexing half of each filter in 600 µl sterile MilliQ water. The filter was then removed

and the remaining water was subjected to two rounds of thermal lysis by placing the

tubes in liquid nitrogen and then quickly transferring them into a 100ºC heating block

and then repeating this cycle. The water was then incubated at 37ºC for 1 h with 0.1

volumes of proteinase K (20 ug/µl) and 0.1 volumes of a lysis buffer (Hentschel,

unpublished). This was followed by two more rounds of thermal lysis. The water was

stored at 4ºC for up to 24 hours until used in PCR reactions. Immediately prior to use, the samples were heated to 95ºC for three minutes to denature any residual proteinase K.

The 16S rRNA gene sequence was PCR amplified using universal primers 341F spanning Escherichia coli positions 341-357 and 907R spanning Escherichia coli positions 907-926. A 40-bp GC-clamp was attached to the 3’ end of the forward primer.

PCR was performed using a Mastercycler Gradient (Eppendorf, Hamburg, Germany) as follows: one initial denaturation step for 2 min at 95ºC; 30 cycles of 1 min at 95ºC, 1 min at 54ºC and 1.5 min at 72ºC; and one final elongation step for 10 min at 72ºC. The PCR mix consisted of 5 µl 10x reaction buffer, 1 µl of each primer (100 pmol final concentration), 1 µl of deoxyribonuleoside triphosphates (10 µmol), 2.5U MasterTaq

DNA polymerase (Eppendorf), 1 µl DNA template (10 µl from water filters), and sterile water up to 50 µl. Three independent PCR reactions were performed for each species.

DGGE was performed using a Bio-Rad DCode Universal Mutation Detection

System (Bio-Rad, München, Germany) on an 8% (w/v) polyacrylamide gel in 1x TAE and using a 40-80% denaturing gradient; 100% denaturant corresponds to 7 M urea and

40% formamide (v/v). Electrophoresis was performed for 6 h at 150 V and 60ºC. The gels were stained for 30 min with ethidium bromide (0.5 µg/ml) and then visualized and photographed with a GelDoc System (GelDoc 2000, Bio-Rad).

DNA bands that were clearly separated were excised from DGGE gels and stored in 20 µl of sterilized distilled water overnight at 4 °C. Subsequently, 4 µl of eluted PCR product was amplified as above with the exception that the primer 341F did not contain a

GC-clamp. Some PCR products could be sequenced directly, but in most cases, the PCR amplification products were purified (Geneclean kit, Bio101, Vista, CA, USA), ligated

into the pGEM-Teasy vector and transformed in CaCl-competent E.coli DH5alpha

(Promega Corp., Madison, WI, USA). Plasmid DNA was isolated and sequenced on an

ABI 377Xl automated sequencer (Applied Biosystems) using the M13 universal and M13 reverse sequencing primers. The obtained sequences were aligned using the ABI Prism

Autoassembler v. 2.1 software (Perkin Elmer, Foster City, CA, USA) and BLASTed

(Altschul et al. 1997) to find highly homologous sequences.

Results and Discussion

Transmission electron micrographs of the mesohyl of both A. cauliformis and I. felix (Fig. 3.2A, B) showed an abundance of intercellular bacteria and a variety of bacterial morphotypes. In contrast, micrographs of N. erecta (Fig. 3.2C), as well as the congener N. digitalis (data not shown), showed a diffuse scattering of morphologically uniform intercellular bacteria and a few intracellular bacteria that appeared partially digested. These observations support Vacelet and Donadey’s (1977) hypothesis that there are two fundamentally different types of sponges defined by the type of associated microbial community they host. As discussed above, the HMA sponges have a massive and complex microbial community while the LMA sponges have a sparse and simple microbial community.

DGGE profiles (Fig. 3.3) showed distinct banding patterns for A. cauliformis, I. felix, N. erecta, and the ambient water samples. There was little to no variation between individuals, but the DGGE profiles do not allow us to examine any between site variations. The presence of multiple DGGE bands for A. cauliformis and I. felix support

TEM results showing a high density of morphologically diverse microorganisms.

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Differences in the number and positions of DGGE bands between these two sponge species and water column samples suggest that sequences from the sponges represent sponge-specific microbial strains. Many of the sequences of the bands from these two species showed high homology with previously reported sequences from other sponge- associated microorganisms (Table 3.1, Webster et al. 2001, Hentschel et al. 2002, Thoms et al. 2003, Thacker 2005). In contrast, the negligible banding produced by DGGE from the sponge N. erecta was consistent with TEM images showing a minimal presence of morphologically uniform bacteria within this species. The sequence for the lone DGGE band from this species shows high affinity to a known seawater bacterium (Rhodobacter sp., Althoff et al. 1998).

Studies by Taylor et al. (2004) and Webster et al. (2004) of Australian and

Antarctic sponges, respectively, showed results for other sponge species that were similar to the results in this study. In both the Taylor et al. (2004) and Webster et al. (2004) studies, DGGE of 16S fragments revealed at least one sponge species with few (<5) bands and at least one species with many bands. Sequences from the bands in the apparent LMA sponges species had high homology to sequences from seawater bacteria but not to sponge-specific microbes, while sequences from the bands in the apparent

HMA sponge species had high homology to sponge-specific microbes. This suggests that the HMA sponge/LMA sponge dichotomy is a fundamental aspect of sponge communities world-wide.

The first studies on sponge-associated microorganisms used light microscopy to investigate sponge tissues (Feldmann 1933 and references therein). Later studies used electron microscopy to more clearly identify the associated bacteria (Sara 1971, Vacelet

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and Donadey 1977, Bewley et al. 1996, Magnino et al. 1999). While many recent studies have used a variety of molecular techniques to characterize these communities of microorganisms, few studies link molecular methods to electron microscopy methods

(but see Althoff et al. 1998, Friedrich et al. 1999, Thoms et al. 2003). By using both methods to study these microbial communities, we were able to conclusively show that the species revealed to be HMA sponges by TEM have molecular profiles consistent with the sponge-specific microbiota while the species revealed to be LMA sponges by TEM have molecular profiles similar to seawater bacteria. These results are consistent with the few prior studies that linked molecular methods to electron microscopy methods (Althoff et al. 1998, Friedrich et al. 1999, Thoms et al. 2003). By further combining these data with stable nitrogen and carbon isotope data, we are able to show that there are likely significant metabolic differences between the HMA sponge and LMA sponges. This is supported by studies of the respiration and energetics of three sponge species (Reiswig

1974). Reiswig found that two LMA sponges (Mycale sp. and Tethya crypta) had a significantly different metabolism than a HMA sponge (Verongia gigantea). The LMA sponges used less oxygen and meet their respiratory demands solely by consuming POM.

In contrast, the HMA sponge used much more oxygen, and the sponge, as a community of microorganisms, commensal invertebrates, and sponge cells, needed to consume DOM to meet its respiratory demands. These data are the only thorough measurements of sponge respiration, and support the hypothesis of an important difference in the metabolism of HMA sponges versus LMA sponges.

Vacelet and Donadey (1977) hypothesized that the dense tissue of the bacteriosponges necessitates more complete usage of organic matter in the pumped

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water, which may be accomplished through mutualistic interactions with microorganisms. They also hypothesized that the well-irrigated tissue of LMA sponges, like N. erecta examined in this study, were likely not in a mutualistic relationship with their sparse, monotypic bacterial associate. The link between our isotope data and our

TEM and DGGE data supports this hypothesis. As filter-feeding animals, sponges are thought to obtain their nutrition by consuming suspended particulate organic matter

(SPOM) (Reiswig 1971a, b). Therefore, the stable N isotope ratio of their tissue is predicted to be enriched by ~3‰ over their SPOM food source (Peterson and Fry 1987).

The data from our stable isotope survey (see Chapter 2, Fig 3.1), when combined with

SPOM data (Southwell et al. unpublished), show that N. erecta, the LMA sponge, has a

δ15N value that is on average 2.32‰ higher then the SPOM δ15N value, while the δ15N values for the other two species do not significantly differ from the SPOM δ15N value.

The isotope values of N. erecta therefore suggest that it is consuming SPOM, while the isotope values of A. cauliformis and I. felix suggest substantial inputs of autochtonous nitrogenous organic matter. While it is possible that the HMA sponges are selectively feeding on a portion of the SPOM that has a lower δ15N value, there is little evidence for this. Pile (1999) did find differences among three sponge species in their retention efficiencies of four types of plankton. These differences were attributed to differences in the morphology of the sponge species that resulted in the species feeding at different height above the benthos. The availability of these four types of plankton changed at various heights above the benthos and thus influenced what was available to the sponges.

However, the HMA sponges include species with a variety of morphologies, including species that feed very close to the benthos, such as I. felix, and species that feed ~20 cm

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above the bottom, such as A. cauliformis. As this difference includes the range in which

Pile (1999) measured variation in retention efficiencies, it is unlikely that selective

SPOM feeding explains the variation in stable N isotopes, and thus it is likely that the isotope values of A. cauliformis and I. felix indicate that they are also receiving a

nitrogenous nutrient input from another source. Because all eukaryotic metabolic

processes result in 15N enrichment in tissues (i.e. higher δ15N values), δ15N values near

0‰ only come from prokaryotic nitrogen metabolism (e.g., N2 fixation, ammonium uptake). Thus, the additional N input to the HMA sponges is probably from an associated microbe that either retains the low δ15N signal within its own tissues or potentially provides nitrogenous nutrient inputs to sponge cells (this issue is the topic of

Chapter 4). If present, this microbial input of nitrogen to the HMA sponges would occur in a mutualistic interaction as described by Vacelet and Donadey (1977).

The presence of a large, diverse microbial community within the mesohyl of the

HMA sponges provides the sponge with immediate access to a wide range of metabolic transformations of carbon, nitrogen, and other elements, as well as production of bioactive natural products. Because of this interaction, there are a number of opportunities for the sponges to benefit from metabolic diversity of their associated microbes. For example, phototrophic sponges (sensu Wilkinson 1983) utilize dissolved

CO2 in addition to the energy and nutrients that they use from filtered particulate organic matter. Further, if nitrogen fixation is occurring in some sponges (Wilkinson et al. 1999), these species can utilize dissolved N2 gas to supplement the nitrogen they receive from particulate and dissolved organic nitrogen. This process can drive the δ15N values of the sponge toward the low values seen in the HMA sponges (Chapter 2). By examining the

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phlyogenetic data, it is possible to make some conjectures as to the functions of the various microbes residing in the HMA sponges. For example, the cyanobacteria (shallow band 4 – A. cauliformis) likely carry out photosynthesis. This fixation of carbon is consistent with the light δ13C value of A. cauliformis (Fig. 3.1), because the fractionation

of carbon isotopes associated with photosynthesis by cyanobacteria generally results in

values near -25‰ (Valley and Cole 2001), while carbon inputs from POM in the vicinity

of the sampled sponges was generally near -15‰ (Fig. 3.1). Deep band 4 (I. felix) has

high homology to members of the Phylum Chloroflexi, the green non-sulfur bacteria.

Anoxygenic photosynthesis exhibited by Chloroflexi generally produces a δ13C value of -

14‰ (van der Meer et al. 2000). Bacteria in Phylum Nitrospira (deep band 1) oxidize nitrite to nitrate, which is the second step in the nitrification process. Nitrification has been documented in sponges (Corredor et al. 1988, Diaz and Ward, 1997), and uptake of ammonium, including uptake associated with nitrification has been proposed as an explanation for the low δ15N values in sponges (see Chapter 2). In addition, because so many of the microbes in these sponges are unidentified (Table 3.1; Hentschel et al. 2002), even to the level of phyla (Fieseler et al. 2004), the range of metabolic process occurring in these HMA sponges is unknown. Recent work has suggested that processes including methane oxidation (Vacelet et al. 1996), sulfate reduction (Hoffmann 2003, Hoffmann et al. 2005) and dehalorespiration (Ahn et al. 2003) may be occurring in some sponges.

While the roughly equal abundances of HMA sponges and LMA sponges on the reefs of the Florida Keys suggests that there is no advantage to having massive microbial communities, the ratio of HMA sponges to LMA sponges is not consistent throughout the world. Wilkinson (1987) and Wilkinson and Cheshire (1990) compared sponge

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communities between the Caribbean and the Indo-Pacific and concluded that Indo-Pacific reefs have much greater abundances of phototrophic sponges. Wilkinson (1987) suggested that Caribbean sponges have much more POM to consume and thus are less dependent on photosynthetic input. Thresher (1982) studied egg volume and clutch size of demersal spawning coral-reef fishes and noted differences among western Atlantic and western Pacific species. Because of the previously noted correlation between water column productivity and egg volume (Cushing 1967, Bagenal 1971) and the increased productivity in the western Atlantic as compared to the western Pacific (Sheldon et al.

1972), Thresher (1982) hypothesized that the differences he noted for the coral-reef fish egg volume result from the higher primary production in the western Atlantic Ocean as compared to the western Pacific Ocean. The ratio of HMA sponges to LMA sponges in a given region may therefore be dependent upon overall productivity of the region, with

HMA sponges abundances inversely correlated to productivity. Given that sponge species may have originally evolved with large associated communities (Wilkinson

1984), it is possible that HMA sponge secondarily lost these associations when they radiated into habitats with greater availability of POM and the patterns we see are the result of associated bacteria impacting the ecology and evolution of their hosts sponges throughout their long evolutionary history, and thus impacting the species distributions of

HMA sponges versus LMA sponges.

We have shown that variations in the δ15N and δ13C value of bulk sponge tissue are correlated with variations in the composition of the associated microbial commuities of sponges. As hypothesized by Vacelet and Donadey (1977), it appears that the LMA sponges are making use of the abundant POM, while the HMA sponges receive inputs

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from their diverse microbial communities. Therefore, by combining measurements of the stable N and C isotope ratio of a sponge with molecular and microscopic characterization of the microbial community, we can begin to understand not only the identity of the associated microbial community of the sponge, but also what role those microbes might play in the nitrogen and carbon metabolism of the host sponge and begin to understand the nature of the associations.

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Figure 3.1: Plots of δ15N vs. δ13C for three sponge species and suspended particulate organic matter (SPOM; Southwell et al. unpublished). Each point is the average for all samples from Three Sisters Reef, indicated by circles, and Conch Reef, indicated by triangles. N = 3-6 samples for each datum point. Bars = ±1SE

118

5 Niphates erecta Niphates erecta 4

SPOM

N Aplysina cauliformis 3

15 Conch Reef δ Three Sisters Reef Ircinia felix 2 Aplysina cauliformis

SPOM 1 Ircinia felix

0 -21-20-19-18-17-16-15-14-13 δ13C

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Figure 3.2: TEM micrographs of three sponge species. Shown are the tissues of (A) Ircinia felix, (B) Aplysina cauliformis, and (C) Niphates erecta. b = bacteria, c = cyanobacteria, s = sponge cell, n= sponge cell nucleus. The scale bar represents 1 µm.

120

s s

b b c

n s ABC

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Figure 3.3: DGGE gel of 16S rRNA gene fragments. Fragments are amplified from Ircinia felix, Aplysina cauliformis, Niphates digitalis and seawater from the shallow site (‘Three sisters reef’) (A) and the deep site (‘Conch reef’) (B). Three replicate PCR reactions were run for each sample. Numbers indicate DGGE bands from which sequence information could be obtained (See Table 3.1).

122

f 11 e 12

e 10 2 3 4 5 7 8 9 R 6 1 15

s 13 14 r 16 17 18

Aplysina Niphates Ircinia felix Water column cauliformis erecta

f 16 e 8 9 10 14 15 e 3

R 1 4 6 19 h 2 5 7 17 18 c 11 12 13

C 20 21 22

123

Chapter IV

Other impacts of associated bacteria on their host sponges

Introduction

The study of sponge-associated bacteria began in the mid to late 19th century with the observation of single-celled “algae” parasitizing sponges (Carter 1878 cited in Feldmann

1933). Little was known about the interactions beyond microscopic evidence of their existence. The first observations suggesting a less antagonistic interaction were made by

Weber Van Bosse (1910 cited in Feldmann 1933). Since these early investigations, many researches have suggested that these associations are symbiotic in nature, but there is little evidence to support these hypotheses (Hentschel et al. 2003, 2006 and references therein).

The confusion over the nature of the interaction between sponges and bacteria stems from the complexity of the microbial community and the resulting difficulty in detecting a specific benefit for either partner, and also from uncertainty over the definition of the term symbiosis.

The word symbiosis was originally coined by Anton de Bary in 1878 to describe the interaction between fungi and algae in lichens (Sapp 1994). His definition was “the living together of unlike named organisms” (Sapp 1994). Today, however, the term symbiosis has essentially become synonymous with mutualism (Sapp 2004). In this work, we will use the terms symbiosis and mutualism interchangeably and define them as the living together of unlike organisms with mutual benefit to both organisms. This is to be distinguished from commensalism, which is an interaction in which one species benefits while the other has no net harm or benefit (Morin 1999). Therefore in order to define the sponge-microbe interaction as a true symbiosis, we must find evidence of a specific benefit for both partners.

Many possible symbiotic functions have been proposed for the bacteria associated with sponges. These include the bacteria as a source of nutrition by ways of intracellular

digestion and/or by translocation of metabolites (Wilkinson and Garrone 1980; Borowitzka et

al. 1988), access to novel, bacteria-specific traits like autotrophy, nitrogen fixation and

nitrification (Wilkinson and Fay 1979, Wilkinson 1983, Corredor et al. 1988, Diaz and Ward

1997), processing of metabolic waste (Beer and Ilan 1998), stabilization of the sponge

skeleton (Wilkinson et al. 1981), and involvement in chemical defense against predators and

biofouling (Bakus et al. 1986, Unson et al. 1994, Bewley et al. 1996). Despite all of this

research, only one study have been able to conclusively prove that a symbiotic, i.e.

mutualistic, relationship exists. That study demonstrated a transfer of photosynthate from

phototrophic symbionts to the host sponge (Wilkinson 1983).

The first three chapters of this dissertation provided evidence of morphological,

physiological, and metabolic differences between the HMA sponge and the LMA sponges,

but have not shown that a true symbiosis exists between some sponges and their microbial

associates. The work in this chapter will examine three additional characteristics of several

sponge species, internal oxygen concentration, stable isotope ratios of sponge larvae, and

stable isotope ratios of sponge skeletal fibers, to establish differences between the HMA

sponge species and the LMA sponge species, and the mechanisms producing these

differences, with the ultimate goal of testing the hypothesis that there is a true symbiotic

interaction between sponges and their associated bacteria.

125 The first characteristic examined was oxygen concentrations within sponge tissues.

Although a sponge only has a few cell types, many sponge species are known to host massive and diverse communities of microorganisms (reviewed by Hentschel et al. 2006). These bacteria are potentially capable of a wide-range of metabolic processes (Chapter 3), including anaerobic processes such as sulfate reduction and reductive dehalogentation, and possibly nitrogen fixation and denitrification. Imhoff and Truper (1976) isolated and cultured anoxygenic phototrophic bacteria from sponges, and more recently, microorganisms known to prefer anaerobic conditions, such as Archaea (Preston et al. 1996; Margot et al. 2002;

Webster et al. 2001), sulfate-reducing bacteria (Schumann-Kindel et al. 1997; Manz et al.

2000, Hoffmann et al. 2005), and dehalorespiring bacteria (Ahn et al. 2003) have been detected in sponge tissue. Gatti et al. (2002) used oxygen microoptodes to measure oxygen concentrations within the tissue of the Mediterranean bacteriosponge Suberites domuncula.

They detected oxygen concentrations within the sponge that were around 50% of the ambient, i.e. saturated, seawater. Studies by Hoffmann et al. (2005) have shown that a temperate bacteriosponge, Geodia barretti, has anoxic zones. They measured sulfate reduction and found sulfate-reducing bacteria within these anoxic zones. Because anoxia in sponge tissues is directly tied to the presence of microorganisms, we hypothesize that the

LMA sponges should not have these anoxic zones. Further, because we have shown that

LMA sponges have lower tissue densities and faster flow rates (Chapter 1), we would expect tissues of the LMA sponges to be more oxygenated than the tissues of the HMA sponges.

As seen in prior studies (Gatti et al. 2002, Hoffman et al. 2005) using microelectrode or microoptode probes to measure internal oxygen concentrations, none of which were conducted in situ, provides the most accurate measurements of oxygen gradients in sponge

126 tissues. Unfortunately, their use is time consuming, as multiple replicate measurements need to be made on each individual, with each measurement taking at least thirty seconds to make.

Although this would not be a significant amount of time if one were sitting in a laboratory, sponges do not typically exhibit normal behavior in aquaria (Parker 1910, Jorgensen 1955,

Harrison and Cowden 1976) and thus accurate measurements can only be made in situ (i.e. on the reef). Therefore, to analyze a large number of sponge species in situ, we used a chemical treatment designed to detect reducing environments. Treatment of organisms or environmental samples with tetrazolium salts allows for rapid, though qualitative, measurements to be made on multiple samples over a tractable period of time for SCUBA diving. Tetrazolium salts are colorless heterocyclic organic compounds that form insoluble, intensely colored crystals, called formazan crystals, when reduced, which is an irreversible process (Jambor 1954). The tetrazolium salt 2,3,5-triphenyl-2-tetrazolium chloride (TTC) was synthesized in 1894 by von Pechman and Runge (cited in Pearse 1961), and has been used in a variety of histological investigations of electron transfer pathways within plant and animal tissues (Pearse 1961). TTC and other tetrazolium salts have also been used to detect the presence of bacteria in otherwise clean environments, such as meat packing plants (e.g.

Emswiler et al. 1976) and to identify the location of micro-environmental condition conducive to electron transfer reactions, such as nitrogen fixation, in algae and bacteria (e.g.

Paerl and Bland 1982, Piehler et al. 1999). TTC is reduced by mitochondrial dehydrogenases or related prokaryotic enzymes (Rich et al. 2001). TTC is not directly indicative of an anoxic environment, but recent work has shown that although TTC can be partially reduced in the presence of oxygen, formazan deposition from TTC reduction (which requires a transfer of two electrons) cannot outcompete oxygen and thus only occurs in the absence of oxygen as

127 an electron acceptor. Therefore, this treatment, especially when supported by in situ oxygen measurements, can be used as an efficient alternative to visualize low oxygen environments within sponges.

The second set of characteristics I examined were the stable C and N isotopic values of sponge larvae and embryos. These analyses were conducted to test the hypothesis that nutritive matter of microbial origin becomes incorporated into sponge reproductive products and that this nutrient transfer, and thus evidence of symbiosis, would be readily apparent by comparing stable C and N isotopic values of whole sponge tissues versus that of sponge larvae and embryos. Demosponges (Class Demospongiae) show a broad range of reproductive strategies, including clonal reproduction (Corriero et al. 1998), and various forms of sexuality, including hermaphroditism and gonochorism (Fromont 1994), viviparity

(Meroz and Ilan 1995), and oviparity (Mariani et al. 2000).

I propose that if sponge-associated microbes are at all involved in the production of sponge reproductive products, either via a nutrient transfer to sponge cells or through bacterial inclusion in eggs or larvae as a vehicle for vertical transmission of the symbionts, the stable N isotopic ratios of the reproductive products should match those of the bulk adult tissue. Although this methodology will not allow me to detect evidence of a symbiosis in the high δ15N HMA sponges, because I would expect the reproductive products of both high

δ15N HMA sponges and LMA sponges to fall in the high δ15N range, by measuring these larval stable isotope ratios of low δ15N species, I can provide additional support for a symbiotic interaction between the host sponge and the associated microorganisms. I will also measure values of high δ15N HMA sponges and LMA sponges as a methodological control.

128 The third and final set of characteristics examined were the stable C and N isotope values of the sponge skeleton. The skeleton of a sponge consists of a fibrous protein, similar to collagen, called spongin. These spongin fibers are secreted by specialized cells in the sponge mesohyl called spongocytes (Simpson 1984). These spongocytes form precursors for spongin synthesis in their endoplasmic reticulum, secrete these precursors, and then assemble the final structures extracellulary (Vacelet 1971). There are no indications that microorganisms are at all associated with the production of these fibers, therefore the stable isotope values of these fibers reflect sponge biomass without including any microbial biomass. Therefore, this work will test the hypothesis that stable isotope values of spongin will not differ from those of bulk sponge tissue, indicating a nutrient transfer from microbes to sponge host. As with the larvae methodology, I will only be able to detect evidence of a symbiotic interaction in the low δ15N HMA sponges, but I will still measure the high δ15N

HMA sponges and LMA sponges as a methodological control. Because these spongin fibers are highly refractory (Simpson 1984), it is easy to isolate them from the remainder of the sponge. Simple treatments with dilute bleach will remove the non-refractory organic matter and leave the spongin behind (Chanas and Pawlik 1995).

In this study, we (1) used TTC and oxygen meters to test the hypothesis that HMA sponges have internal low oxygen regions, (2) used stable C and N isotope ratios to test the hypothesis that associated bacteria transfer nitrogen to the larvae of the host sponge, and (3) used stable C and N isotope ratios to test the hypothesis that associated bacteria transfer nitrogen to the spongin skeleton of the host sponge.

129 Methods

As discussed in prior chapters, through a variety of methods, we have classified 26 sponge species as either low or high δ15N species and as either HMA sponges or LMA sponges (Table 1). These classifications are used throughout the rest of this work.

Tetrazolium Salts

TTC incubations were performed on three individuals of all 26 species listed in Table

1. TTC was mixed to a concentration of 2.5 mg/ml in seawater. It was placed in syringes covered with black electrical tape to prevent exposure to light, which can cause incidental reduction and formazan crystal production. A healthy looking sponge was chosen and a small amount of fluoroscein dye was released into the excurrent stream to confirm that the sponge was actively pumping. Once it was determined that the sponge was pumping, a small amount of TTC solution (approx. 0.5-1 ml) was released next to the sponge. Although the solution is essentially clear, because of the small difference in density, it was possible to watch the solution enter and leave the sponge, propelled by the pumping mechanism of the sponge. After approximately 30 seconds, a section of sponge surrounding the injection site was cut off and placed into a Ziploc bag. Sponges were brought back to the boat, and immediately cut open and photographed to document the presence or absence of TTC deposition.

Submersible Oxygen Meter

To confirm that any reducing environments detected through TTC deposition were zones of hypoxia or anoxia we use a Clark-type microelectrode probe and submersible

130 oxygen meter (Unisense, Denmark) to measure oxygen levels within the tissues of undisturbed sponges in the field. Measurements were made on three healthy looking individuals of Ircinia campana, Aplysina cauliformis, and Niphates erecta on September 27,

2003 at Three Sisters Reef, and on three individuals of A. cauliformis, Ircinia felix, and

Niphates erecta on March 15, 2004 at Triangles Reef. As with the TTC study, individual sponges were first checked using fluoroscein dye to determine that the sponge was actively pumping. Then the 5 cm needle probe was inserted approx. 2 cm into the tissue. The probe was allowed to settle for at least 30 seconds and then the meter reading was recorded. Five reading were made on each individual, and three individuals per species were measured.

Saturation values were determined between measurements of each individual sponge by holding the probe in the water column. In all cases, depths were sufficiently shallow (<7 m) and wave action was great enough to mix the water column, likely ensuring full oxygen saturation in water near the sponges. We were unable to devise an appropriate device to

measure the zero saturation point of the probe in situ, but measurements on the zero point

were made at the beginning and end of each day by placing the probe in a syringe filled with

pure helium. There was little variation in these readings (<1% of the total range), so these

values were deemed to be sufficiently accurate. The theoretical saturation concentration of

oxygen was determined using the temperature and salinity measurements and was

determined to be 211.3 µmol/l for both days. For each individual, an equation was

determined based on the line connecting the saturation value of each individual and the

theoretical saturation value with a zero value and the zero point for each day. These

equations were used to convert each meter reading to an actual oxygen concentration value.

131 A nested one-way ANOVA was performed on the oxygen concentration values to detect interspecific differences. The analysis consisted of species as the independent variable and the multiple oxygen concentration measurements on each individual were nested within a single “oxygen” dependent variable.

Stable Isotope Analysis of Spongin

These analyses were performed on two separate occasions using two different, though similar, methodologies. The first set of samples was collected on two trips to NURC, in June and October of 2000. Two individuals each of Aplysina cauliformis, Callyspongia vaginalis,

Ircinia felix, and Niphates erecta from Three Sisters Reef (25º 01.610’ N / 80º 23.671’ W)

and Tavernier Rocks (25º 00.433’ N / 80º 30.917’ W) were collected, along with two

individuals each of I. felix from Conch Reef (24º 57.34’ N / 80º 27.26’ W), Mycale laxissima

from Three Sisters Reef, N. erecta from the wreck of the Duane (24º 59.388’ N / 80º 22.888’

W), and Spheciospongia vesparium from Cowpen Cut (25º 00.216’ N / 80º 33.55’ W) and

Tavernier Rocks. Tissue samples were placed in scintillation vials, frozen, and returned to

IMS. Samples were freeze-dried on a Speed Vac and then ground in a mortar and pestle. A small portion of each individual’s whole-tissue sample was set aside for later comparison with other fractions. Each sample was then weighed, and placed into a filter tower. The tissue was mixed with HPLC grade dichloromethane (DCM) and left for five minutes. The

DCM was filtered off, and then HPLC grade water was mixed with the tissue. This was also left for five minutes, and then filtered off. Following the protocol of Chanas and Pawlik

(1995) to reduce sponge tissue to spongin, a 0.5% solution of sodium hypochlorite (10% bleach) was mixed with the remaining tissue. This was left until the bubbling had stopped,

132 generally about 5 minutes, indicating that no further digestion of labile tissue was taking place. The bleach was filtered off and then the bleaching step was repeated. After the second bleaching step, the remaining tissue was rinsed twice with distilled water to remove traces of bleach, removed from the filter tower, and placed back into a scintillation vial. The tissue samples were then dried on the speed-vac for 48 hours.

Carbon and nitrogen stable isotope ratios were then determined on the bleached tissue samples and the whole tissue samples that were previously set aside as follows. Samples were weighed into tared combusted silver boats (5x9 mm; Costech Analytical; Valencia, CA) on a Cahn C-30 Microbalance and then exposed to HCl vapor in closed containers to remove carbonate. Samples were then placed in a 70oC oven for 1 hr to remove residual acid.

Sample C and N compositions and isotopic values were determined on a Carlo Erba NA

1500 elemental analyzer equipped with autosampler interfaced via a Finnigan ConFlo II to a Finnigan MAT 252 isotope ratio mass spectrometer. The stable isotopic ratio was

N 3 calculated as: δ X = [(Rsample - Rstd)/Rstd] x 10 in units of parts per thousand (‰). The coefficient NX is the heavy stable isotope of the element (13C or 15N). R is the ratio 13C/12C or

15N/14N of both sample and standard. The standard for C isotopic measurements is Pee Dee

Belemnite (0.0‰) and for nitrogen is atmospheric N (0.0‰). Instrument specified standard

deviations for δ13C and δ15N analyses are 0.2 and 0.3‰, respectively. Pure acetanilide

standard is used as a quality assurance standard to ensure complete combustion.

For the second set of analyses, tissue samples of eight species were collected from

one of two sites in the Key Largo area in February 2005. Three individuals were collected of

each species. Tissue from Ircinia campana, Xestospongia muta, Smenospongia aurea, A.

cauliformis, N. erecta, Niphates digitalis, and Agelas schmidti was collected at Diadema Reef

133 (24º 59.198’ N / 80º 26.096’ W). Tissue from Agelas conifera was collected at Conch Reef.

All tissue samples were placed in scintillation vials, frozen and brought back to IMS.

Samples were dried on a speed vac for 48 hours, and then ground in a mortar and pestle.

Approximately one third of the ground tissue was set aside in a 1.5 ml microcentrifuge tube

for whole tissue stable isotope analysis. A solution of 0.5% sodium hypochlorite (10%

bleach) was poured into the vials until the tissue was submerged. This was left until the

bubbling had stopped, generally about 5 minutes, indicating that no further digestion of labile

tissue was taking place. The samples were centrifuged for 2 minutes and the supernatant

containing bleach and digested tissue was poured off. More bleach was added to the vials,

repeating the process until the supernatant was clear, generally three washes with bleach,

indicating that all of the labile tissue was gone. The remaining spongin fibers were rinsed

twice with distilled water and then dried again on the Speed-Vac. Stable isotope ratios of the

spongin samples and matching bulk tissue samples were then measured as described above.

For each species, data on spongin versus bulk tissue values were directly compared

for both δ13C and δ15N using simple paired t-tests. A cluster analysis was performed on all of the data using SAS (SAS Institute, city, NC) to detect the patterns of associations within the data set. The analysis was performed on the average δ13C and the average δ15N value for both bulk tissue and for spongin, i.e. four values for each species pooled across collection sites.

Larval Collection

Larvae or embryos where collected from six sponge species in the Key Largo area: A. conifera, I. felix, I. strobilina, M. laxissima, S. aurea, and X. muta. In all cases, after the

134 collection, larvae or embryos and adult tissue samples were put on ice, brought back to the lab, placed in labeled scintillation vials, and stored at -20ºC. Embryos of Xestospongia muta were collected from Elbow Reef (25º 08.18’N / 80º 15.64’ W) shortly after the spawning event in September 2002. The embryos and the mucilaginous sheath in which they were embedded were collected by sucking them off the adult individuals using a turkey baster.

The embryo-containing sheaths were gently squirted into numbered Ziploc bags and a piece of the adult tissue was placed into another Ziploc bag with a matching number, allowing us to keep the embryos paired with their parent. Embryos of Agelas schmidti were collected from North North Dry Rocks (25º 08.25’N / 80º 17.35’W) shortly after their spawning event

in June 2002. These embryos were collected in the same fashion as those of X. muta

described above.

Larvae of I. felix and I. campana were collected at Three Sisters Reef following the

methods of Lindquist et al. (1997). Sponges were covered with fine-mesh netting made of

10-15 cm of pantyhose connected to a buoyant capture device made of a 200 mL Nalgene®

bottle with an upside-down funnel in the mouth to prevent larvae from leaving the bottle.

The netting caused no harm to the sponge, but prevented larvae from escaping into the water

column. Larvae of M. laxissima were collected at Three Sisters Reef. Individuals of this species were covered with fine-mesh netting made of an intact knee-high pantyhose. Larvae trapped in the netting after a release were collected by slowly removing the netting from the sponge and capturing the larvae out of the water column using the reverse end of a glass

Pasteur pipet. Larvae of S. aurea were collected at Three Sisters Reef by capturing the larvae

out of the water column using the reverse end of a glass Pasteur pipet as the sponge released

them. All larvae and adult tissue samples were brought back to IMS, freeze dried on a

135 Speed–Vac, ground with a mortar and pestle, and analyzed for carbon and nitrogen stable isotope ratios as described above.

Isotope data for larval and matching adult samples were statistically analyzed following the same procedures used for spongin and matching bulk samples.

Results

Tetrazolium Salts

TTC deposition did not occur in any of the LMA sponges, but did occur in all of the

HMA sponge species except Xestospongia muta (Fig 4.1, Table 4.1). In the HMA sponges, deposition occurred throughout the endoderm, but did not occur in the ectoderm layer. In species with large excurrent channels, like Ircinia felix, deposition did not occur in the lining of the channels (Fig 4.2).

Submersible Oxygen Meter

Oxygen microsensor data show highest average tissue concentrations in N. erecta and lowest values in A. cauliformis (Fig 4.3). The values for C. vaginalis, I. campana and I. felix are intermediate. Statistical analyses showed that the internal oxygen concentrations in A. cauliformis were significantly lower than in all other species, and the oxygen concentration values in N. erecta were significantly higher than those in I. felix.

Stable isotopic comparison of spongin versus whole sponge tissue

The results of the t-tests on data for each species were mixed, with some species showing significant differences in either d13C values, d15N values, or both (Fig 4.4). The

136 cluster analysis resulted in four apparent clusters (Fig 4.5), which showed a strong association between species, but no grouping of spongin or whole tissue values.

Stable isotopic comparison of larvae versus whole sponge tissue

The results of the stable isotope analysis of larvae were very similar to the results seen with spongin. The t-tests on data for each species were mixed, with some species showing significant differences in either d13C values, d15N values, or both (Fig 4.6). The cluster analysis resulted in three apparent clusters (Fig 4.7), which showed a strong association between species, but no grouping of larval or whole tissue values.

Discussion

TTC deposition only indicates reducing environments, and not specifically hypoxic or anoxic environments. However, data from the oxygen microsensor and other researchers

(Gatti et al. 2002, Hoffman et al. 2005) provide supporting evidence that, within sponges,

TTC deposition is occurring in low oxygen environments. Although the oxygen meter data resulted in intermediate saturation values for C. vaginalis, I. campana, and I. felix, all three species have intermediate density values (Chapter 1) which go along with their intermediate oxygen saturation values. A linear regression of density and oxygen saturation values shows that there is a high correlation between the two (r2=0.785). There is also large variability in the measurements, which is a major cause of the lack of significant differences between species.

Despite the inconsistencies with the oxygen microsensor data, it does appear that the

TTC is showing low oxygen zones, supporting the hypothesis of hypoxic/anoxic zones in

137 HMA sponges and not in LMA sponges. The ability of sponge cells to tolerate these hypoxic/anoxic conditions suggests that some sponges have evolved to tolerate low oxygen, reducing conditions, potentially indicating a tightly co-evolved system allowing for the presence of large, metabolically active populations of microorganisms within some sponge species. The ability to tolerate hypoxic or anoxic conditions is not unique to sponges. For example, hydrothermal vent mussels (Bathymodiolus thermophilus) are periodically bathed in anoxic waters, allowing their chemolithotrophic symbionts access to hydrogen sulfide

(Johnson et al. 1994). Hoffman et al. (2005) suggested that G. barreti occasionally slows or ceases its pumping to maintain the anoxia within its tissues. Although this is not strong evidence for symbiosis, it does suggest that there is a specific benefit for anaerobic members of the associated microbial community. By providing an anoxic habitat with a constant supply of nutrients, the sponge represents an ideal habitat for these anaerobes, indicating that at a minimum, there is a commensal interaction between the sponge and their associated microbial community.

The comparison of stable C and N isotopic ratios of adult sponges and their reproductive products showed large inter-specific differences, especially in δ13C values, which did not follow any consistent pattern. Larvae of viviparous sponges are all lecithotrophic (Maldonado 1997) and larvae of these brooding species (e.g., M. laxissima, S. aurea) tend to be rich in lipids (Bergquist 1978). These lipids represent a rich source of energy, which the larvae and juvenile stages need until an active filter-feeding stage is reached. Because lipids tend to have very light δ13C values (Hoefs 1997), the larvae are significantly different than the bulk adult tissues, which have proportionally lower lipid levels (Bergquist 1978). The data for I. campana showed no significant difference in δ15N

138 ratio and the data for I. felix showed that the larvae had a significantly heavier δ15N ratio, but still within the range of low δ15N group. Both of these cases suggest a nitrogen transfer from symbiont to host. The data for S. aurea showed that the larvae had a significantly heavier

δ15N ratio, with the larvae falling well into the high δ15N group, suggesting that no nitrogen transfer is occurring. As high δ15N HMA sponges, no easy conclusions can be drawn from the data of X. muta and A. schmidti. Additionally, these two species are oviparous, spawning embryos in a mucilaginous sheath. The stable isotope ratio includes this mucous material, which is probably a polysaccharide and will influence the stable isotope data. Despite these variable patterns, the cluster analysis still groups larvae/embryos and adult tissues together for two of the three low δ15N species, suggesting that, for these species, the associated bacteria play some role in the production of the reproductive products.

Given that vertical transmission of symbionts (i.e. the direct transfer of symbionts from parent to offspring) has been implicated as a factor driving evolution away from parasitism and toward mutualism (Yamamura 1993, Herre et al. 1999), we would expect sponges to show this pattern. Bacteria have been observed, via transmission electron microscopy (TEM), in the eggs or larvae of species in the genus Tethya (Gaino et al. 1987;

Gaino and Sarà 1994), Geodia (Sciscioli et al. 1994), Chondrosia (Lévi and Lévi 1976),

Erylus (Sciscioli et al. 1989), Aplysina (Vacelet 1975; Gallissian and Vacelet 1976), Stelletta

(Sciscioli et al. 1991), Hippospongia and Spongia (Kaye 1991). Additionally, the association of cyanobacteria with eggs of Chondrilla nucula, Petrosia ficiformis and Pellina semitubulosa was suggested in two studies using fluorescence microscopy (Scalera Liaci et al. 1971, 1973). The presence of cyanobacteria within eggs was demonstrated using TEM in

Chondrilla australiensis (Usher et al. 2001) and other studies (Maldonado et al. 2005, Usher

139 and Ereskovsky 2005, Usher et al. 2005) have confirmed vertical transmission in sponges in the genus Chondrilla. Oren and colleagues (2005) detected cyanobacteria in the larvae of

Diacarnus erythraenus using molecular techniques, and Ereskovsky and colleagues (2005) detected associated bacteria in all stages of reproduction in the sponge Haliscara dujardini.

These studies strongly support a hypothesis of vertical transmission in HMA sponges.

As we do not know the relative biomass of bacterial cell to sponge cells within an

embryo or larvae, we can not be sure if any low δ15N values are the result of a nutrient transfer from microbes to host or if we are merely measuring the stable N isotope ratio of the microbial biomass. Therefore, the isotope data of the reproductive products do not allow us to distinguish between vertical transmission of associated microbes and a direct nutrient transfer to the host. However, either situation provides some evidence for a benefit for the host sponges.

The t-tests comparing each species’ whole tissue and spongin stable C and N isotopic compositions did not show any consistent differences between spongin and bulk tissue stable isotope ratios. However, this is primarily to the low power of the statistical tests driven the low number of replicates. Despite the lack of power, the cluster analysis revealed a strong grouping based on species as well as the δ15N group. Species groupings from the cluster analysis indicate that the spongin isotope ratios of each species are similar to the bulk sponge isotope ratios of that species. Although the metabolic causes for the split between low δ15N

HMA sponges, high δ15N HMA sponges, and high δ15N LMA sponges are not clear, the low

δ15N values must be driven by microbial metabolic pathways (Hoefs 1997). However,

because the HMA sponges have a significant community of associated bacteria, up to 40% of

the sponge biomass (Vacelet and Donadey 1977), the bulk tissue isotope ratio could just

140 represent the mixture of sponge and microbial biomass. In contrast, the spongin isotope ratios are for a product solely derived from sponge cells, thus, the similarities between bulk and spongin stable isotope ratios for the low δ15N species, indicate that sponge cells in these species contain N with the low 14N/15N ratios. As these ratios can only be formed by microbial metabolic pathways, the sponge must be receiving an N input from an associated microbe.

The data presented in this chapter provide strong evidence for a commensal interaction involving nutrient exchange between sponges and their associated microorganisms. Additionally, because so many members of the microbial community are unique to sponges (Chapter 3, Hentschel et al. 2002, 2003, 2006), including an entire phylum

(Fieseler et al. 2004), the host sponges are providing a unique habitat for these microbes. As discussed above for the anaerobic bacteria, this habitat represents a benefit for the microbial community. Although we have not shown which specific bacteria are providing benefits to the sponge and which specific bacteria are receiving benefits from the sponge, we have shown that the associated microbial community as a whole both gives and receives benefits.

This evidence supports a hypothesis of symbiosis between the host sponge and the entire associated microbial community. Prior research has shown symbiotic interactions involved in transfer of photosynthate (Wilkinson 1983). Other studies have shown nutrient transfer from sponges to macroalgal partners (Trautman et al. 2000, Davy et al. 2002), but have not yet demonstrated a benefit to the sponge. This work therefore represents the first significant evidence that sponge-associated microbes provide nitrogen to their sponge hosts. When combined with the habitat benefits for the microbial community, this evidence indicates that the interaction is a mutualistic relationship.

141

Final Conclusions

The work in this dissertation sought to measure impacts of associated microbial communities on host sponges. Though it is unclear whether many of the measured characteristics are caused by the microorganisms, or that the microorganisms colonized sponges as a result of these characteristics, it is clear that there are significant differences between the HMA sponges and the LMA sponges. These characteristics, including density, pumping rate, stable nitrogen isotope ratios of bulk tissue, spongin, and larvae, and tissue

oxygen concentrations, all have significant impacts on the physiology and ecology of the

sponge species involved in the interaction.

Wilkinson (1984) suggested that the symbiosis between sponges and microbes began

prior to taxonomic diversification, a finding supported by the uniform microbial communities

in diverse sponges from different oceans (Hentschel et al. 2002). In later work, Wilkinson

(1987) suggested that the presence of symbiotic microorganisms helped the sponge evolve

during their early evolutionary period when the atmosphere was transitioning from a

reducing to an oxidizing environment. Wilkinson (1983) also suggested that more recently,

photosynthetic symbionts drove some specific sponge species to alter their morphologies to a

characteristic flattened shape. The data presented in these four chapters suggests that

microbial communities have played a role in the evolution of all HMA sponges by impacting

their ecology and allowing them to radiate into a greater variety of niches. Because

symbiosis has played a major role in the evolution of multicellular organisms (Margulis

1970), understanding the nature of symbiotic animal-microbe interactions is crucial to

understanding processes that drove the evolution of animals. As sponges represent the base

142 of the animal kingdom, understanding their symbiotic relationships may provide clues to the evolution of higher animals (Wilkinson 1987). This work represents a significant step toward understanding sponge-microbe interactions.

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149 Table 4.1: Characteristics of sponge species used in this work

Species N-group* Bact?** Reference TTC?†

Agelas clathrodes High HMA Hentschel et al. unpub Yes

Agelas conifera High HMA Richelle-Maurer et al. 2003 Yes

Agelas schmidti High HMA Hentschel et al. unpub Yes

Amphimedon compressa High LMA Hentschel et al. unpub No

Aplysina cauliformis Low HMA Chapter 3 Yes

Aplysina fulva Low HMA Vincente 1990 Yes

Callyspongia plicifera High LMA Hentschel et al. 2006 No

Callyspongia vaginalis High LMA Hentschel et al. 2006 No

Calyx podatypa Low HMA Hentschel et al. unpub Yes

Chondrilla nucula Low HMA Rützler 1990 Yes

Ectyoplasia ferox Low HMA Hentschel et al. unpub Yes

Ircinia campana Low HMA Vincente 1990 Yes

Ircinia felix Low HMA Chapter 3 Yes

Ircinia strobilina Low HMA Vincente 1990 Yes

Ircinia variablis Low HMA Sara 1971 Yes

Mycale laxissima High LMA Rützler 1990 No

Niphates digitalis High LMA Chapter 3 No

Niphates erecta High LMA Chapter 3 No

Ptilocaulis sp. High LMA Hentschel et al. unpub No

Table 4.1 Continued

150 Species N-group* Bact?** Reference TTC?†

Spheciospongia vesparium High HMA Vincente 1990 Yes

Spongia officinalis Low HMA Wilkinson et al. 1984 Yes

Ulosa ruetzleri High LMA Hentschel et al. unpub No

Xestospongia muta High HMA Hentschel et al. 2006 No

* N group indicates whether the species fell into the group of high δ15N or low δ15N sponges. ** HMA indicates an HMA sponge, and LMA indicates an LMA sponge.

151

Figure 4.1: Number of sponge species showing TTC deposition. Filled bars are those in which TTC deposition occurs, and open bars are those in which deposition does not occur.

152

153

Figure 4.2: TTC deposition in sponges. (A) The HMA sponge Ircinia campana showing treated and untreated tissue. The red coloration is from formazan deposition. (B) The LMA sponge Niphates erecta showing treated tissue without any deposition. (C) The HMA sponge Ircinia felix showing treated tissue. Note the red areas showing formazan deposition and the clear areas without deposition around the major water canals.

154 Untreated

Treated A

155

Figure 4.3: Oxygen saturation in sponges. Bars indicate average ±SE for oxygen concentration within the tissue of individuals of five sponge species. Different letters indicate species that are statistically significantly different. N=3-5.

156 157

Figure 4.4: Plot of δ13C and δ15N values for spongin and bulk sponge tissue. Triangles represent the average values for bulk tissue and circles represent the average values for spongin. Points for the same species are connected with an arrow originating with the bulk value and pointing toward the spongin value. Points are identified with species codes: Aca is Aplysina cauliformis, Acon is Agelas conifera, As is Agelas schmidti, Cv is Callyspongia vaginalis, Ic is Ircinia campana, If is Ircinia felix, Ml is Mycale laxissima, Nd is Niphates digitalis, Ne is Niphates erecta, Sa is Smenospongia aurea, Sv is Spheciospongia vesparium, and Xm is Xestospongia muta. Symbols after the species code represents the significance values of the paired t-tests comparing bulk and spongin values; - is not significant (p>0.05) and * is significant (p<0.05). The statistical code for δ13C is followed by the statistical code for δ15N.

158

Nd-- 5 Sv-- Ml-* Xm*- Ne** 4 As-- Cv*- Acon-- 3 δ15N Sa-- 2 Aca** Bulk 1 If** Spongin Ic-- 0

-1 -22 -20 -18 -16 -14 -12 -10 δ13C

159

Figure 4.5: Cluster analysis for paired spongin and bulk tissue stable isotope ratios. Groups indicated by thick vertical lines on the right side of the dendrogram indicate the important clusters.

160

161

Figure 4.6: Plot of δ13C and δ15N values for reproductive products (larvae/embryos) and bulk sponge tissue. Triangles represent the average values for bulk tissue and open circles represent the average values for reproductive products. Points for the same species are connected with an arrow originating with the bulk value and pointing toward the larvae/embryo value. Points are identified with species codes: As is Agelas schmidti, Ic is Ircinia campana, If is Ircinia felix, Ml is Mycale laxissima, Sa is Smenospongia aurea, and Xm is Xestospongia muta. Symbols after the species code represents the significance values of the paired t-tests comparing bulk and larvae/embryo values; - is not significant (p>0.05) and * is significant (p<0.05). Statistical code for δ13C is followed by statistical code for δ15N.

162

5 Ml ** As *- Xm ** 4

3 δ15N Sa ** 2 If -* 1

Adult 0 Ic -- Larve/Embryo -1 -21 -20 -19 -18 -17 -16 -15 -14 -13 δ13C

163

Figure 4.7: Cluster analysis for paired reproductive products and bulk tissue stable isotope ratios. Groups indicated by thick vertical lines on the right side of the dendrogram indicate the important clusters.

164

Group M.laxissima adult 1

I.felix larvae

S. aurea adult

Group I.felix adult 2

I.campana larvae

I.campana adult

X.muta adult

M.laxissima larvae

X. muta embryo Group 3 S. aurea larvae

A. schmidti embryo

A. schmidti adult

1.25 1.00 0.75 0.50 0.25 0.00 Average distance between clusters

165