Giant Barrel Sponge) Population on the Southeast Florida Reef Tract Alanna D

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7-25-2019 Spatial and temporal trends in the Xestospongia muta (giant barrel sponge) population on the Southeast Florida Reef Tract Alanna D. Waldman student, [email protected]

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NSUWorks Citation Alanna D. Waldman. 2019. Spatial and temporal trends in the Xestospongia muta (giant barrel sponge) population on the Southeast Florida Reef Tract. Master's thesis. Nova Southeastern University. Retrieved from NSUWorks, . (514) https://nsuworks.nova.edu/occ_stuetd/514.

This Thesis is brought to you by the HCNSO Student Work at NSUWorks. It has been accepted for inclusion in HCNSO Student Theses and Dissertations by an authorized administrator of NSUWorks. For more information, please contact [email protected]. Thesis of Alanna D. Waldman

Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Science M.S. Marine Biology

Nova Southeastern University Halmos College of Natural Sciences and Oceanography

July 2019

Approved: Thesis Committee

Major Professor: David Gilliam, Ph.D.

Committee Member: Jose Lopez, Ph.D.

Committee Member: Charles Messing, Ph.D.

This thesis is available at NSUWorks: https://nsuworks.nova.edu/occ_stuetd/514 HALMOS COLLEGE OF NATURAL SCIENCES AND OCEANOGRAPHY

Spatial and temporal trends in the Xestospongia muta (giant barrel sponge) population on the Southeast Florida Reef Tract

Alanna Denbrook Waldman

Submitted to the Faculty of Halmos College of Natural Sciences and Oceanography in partial fulfillment of the requirements for the degree of Master of Science with a specialty in:

Marine Biology

Nova Southeastern University

August 2019

Table of Contents List of Figures ...... ii

List of Tables ...... ii

List of Equations ...... ii

List of Appendices ...... iii

1. Abstract ...... iv

2. Introduction ...... 1

3. Methodology ...... 6

3.1 Southeast Florida Coral Reef Evaluation and Monitoring Project (SECREMP) ...... 6

3.2 Broward County Biological Monitoring Project (BC BIO) ...... 10

3.3 Data Analysis ...... 10

4. Results ...... 13

4.1 Spatial and temporal trend analysis ...... 13

4.2 Impact of Hurricane Irma ...... 16

5. Discussion ...... 20

5.1 Long-term trends ...... 20

5.2 Divers of increasing density ...... 22

5.3 Hurricane Irma ...... 24

6. Conclusion ...... 25

7. Tables ...... 28

8. Literature Cited ...... 30

9. Appendices ...... 39

List of Figures Figure 1: Healthy and diseased Xestospongia muta ...... 5

Figure 2: Damaged Xestospongia muta ...... 5

Figure 3: Map of the Southeast Florida Reef Tract and study sites ...... 7

Figure 4: Map of the Southeast Florida Reef Tract and study sites ...... 8

Figure 5: Map of the Southeast Florida Reef Tract and study sites ...... 9

Figure 6: Xestospongia muta demographic measurements ...... 9

Figure 7: BC BIO photoquadrat ...... 10

Figure 8: Boxplot of regional density ...... 14

Figure 9: Boxplot of nearshore reef density ...... 14

Figure 10: Boxplot of middle reef density ...... 15

Figure 11: Boxplot of outer reef density ...... 15

Figure 12: SECREMP regional density and volume ...... 18

Figure 13: SECREMP nearshore reef density and volume ...... 18

Figure 14: SECREMP middle reef density and volume ...... 19

Figure 15: SECREMP outer reef density and volume ...... 19

Figure 16: SECREMP Regional density of size classes ...... 20

List of Tables Table 1: SECREMP list of permanent sites ...... 28

Table 2: BC BIO list of permanent sites ...... 29

List of Equations Equation 1: Volume calculation for frustum of a cone ...... 12

List of Appendices Appendix A: Linear regression of 2017 vent and base diameter measurments ...... 39

Appendix B: Linear regression of 2018 vent and base diameter measurments ...... 40

Appendix C: Size classes by volume parameters ...... 41

Appendix D: Regional SEFRT density of size classes 2013-2018 ...... 41

Appendix E: Nearshore reef density of size classes 2013-2018 ...... 41

Appendix F: Middle reef density of size classes 2013-2018 ...... 42

Appendix G: Outer reef density of size classes 2013-2018 ...... 42

Appendix H: SECREMP site densities 2003-2018 ...... 43

Appendix I: BC BIO site densities 2003-2018 ...... 44

Appendix J: SECREMP site volumes 2013-2018 ...... 45

iii

1. Abstract Xestospongia muta, the giant barrel sponge, is a key component of coral reef benthic communities in Southeast Florida and the Caribbean. Xestospongia muta increases habitat complexity and stability, and filters large volumes of water, enhancing water quality and facilitating nutrient cycling. Therefore, it is important to investigate trends in the X. muta population on Southeast Florida reefs in response to anthropogenic stressors, changing environmental conditions and acute disturbances and how these events affect its ecological role in the benthic community. This study identified trends in X. muta population density, volume, and size class distribution over time and across reef habitats on the Southeast Florida Reef Tract (SEFRT). Density and volume changes were also investigated following acute physical disturbance caused by Hurricane Irma in September of 2017. Images and demographic data collected at 41 permanent sites from two long-term monitoring projects, The Southeast Florida Coral Reef Evaluation and Monitoring Project (SECREMP) and the Broward County Biological Monitoring Project (BC BIO), were used to evaluate the X. muta population trends. Analyses of the data from 2003 to 2018 show that X. muta densities and volume increased over time regionally on the SEFRT and increased on the nearshore, middle, and outer reefs of the SEFRT. Xestospongia muta was found to be more abundant on the SEFRT compared to other locations including the Bahamas, the Florida Keys, Colombia, Belize and Saba. Highest mean density on the SEFRT was 0.35 individuals m-2 ±0.04 SEM, which was higher than the mean densities between 0.21 and 0.29 individuals m-2 at the Caribbean sites previously mentioned. Xestospongia muta individuals were categorized into size classes by volume to investigate density distribution of size classes on the SEFRT. Greater abundances in the smallest of five size classes (≤143.13 cm3) drove the increasing density trends. Despite the increasing trends from 2003 to 2018 with a peak in density and volume in 2017, Hurricane Irma caused a region-wide decline in population density and volume as well as a loss of individuals within the largest size class by volume (>17383.97 cm3). These results indicate that the X. muta population is exhibiting increasing long-term trends on the SEFRT, but also demonstrate that acute physical disturbances have a significant impact on the demographics of the population. Because of this sponge’s multiple roles in the reef communities, these trends have implications for structural complexity, nutrient cycling, water filtration, as well as carbon sequestration on the SEFRT. Keywords: Southeast Florida Coral Reef Conservation Area, sponge, density, volume, hurricane, disturbance, long-term trends, monitoring, demography, benthic habitat, size class

2. Introduction

Coral reefs occupy less than one percent of the seafloor, yet they are one of the most biologically diverse natural resources on Earth. Millions of people depend upon coral reefs for their livelihood, as they provide coastline protection, food sources, and opportunities for both ecotourism and recreation (Moberg and Folke 1999). In the United States, the Florida Reef Tract occupies roughly 30,800 km2, and extends 595 km from Martin County (27° 07.9’ N, 80° 08.042’W) south and west through the Dry Tortugas (24° 37.4’ N, 82° 55.3’ W) (Gilliam and Walker 2013). It is the third largest barrier reef ecosystem in the world (Finkl and Andrews 2008; Jaap and Hallock 1990) and provides Florida with both ecosystem services and economic benefits. These services include dissipating wave energy from tropical storms and hurricanes, protecting the populated coastline by reducing flood risk, recycling nutrients from land-based and offshore sources, and providing habitat for ecologically and economically important marine organisms (Jaap 2000; Principe et al. 2012; Ferrario et al. 2014; Storlazzi et al. 2019). Storlazzi et al. (2019) found that the value of coral reefs in the United States in reducing flood risk was $1.8 billion, and that the reefs protect 18,000 people from flooding annually. Economic benefits from recreational and professional diving and fishing services include $4.8 billion in tourism- related sales and $2.2 billion in annual income to the state of Florida from 71,000 marine associated jobs (Johns et al. 2001; Johns et al. 2004; Principe et al. 2012).

Unfortunately, multiple environmental and anthropogenic stressors threaten the ability of reef habitats to provide ecological and economic services globally, and the Florida Reef Tract is no exception (Goldberg and Wilkinson 2004; Hoegh-Guldberg et al. 2007; Halpern et al. 2008; Hoegh-Guldberg and Bruno 2010). Temperature fluctuations associated with climate change destabilize reef health, increasing bleaching and disease events, which can lead to mortality of reef species (Baker et al. 2008). The increased frequency and severity of storms and hurricanes throughout the greater Caribbean (Wilkinson 2004) may increase run off and sedimentation, reduce light availability, trigger upwelling of cold, nutrient-rich water, and elevate physical stress on benthic assemblages (Collier et al. 2008). The increasingly urbanized Florida coastline with its rapidly growing human population has increased pollution, boat use, and fishing pressure on the nearby (0.5-2 km) Florida Reef Tract, exacerbating the already detrimental impacts of global climate change on reef assemblages (Collier et al. 2008). Extensive coastal development

has increased coastal run off as well as activities such as beach nourishment and port expansion to support the growing economy. These activities threaten the health and persistence of coral reefs by altering natural coastlines, increasing sedimentation, and decreasing water quality (Marszalek 1981; Lirman and Miller 2003; Chiappone et al. 2005; Lapointe et al 2005a; Lapointe et al 2005b; Trnka and Krauss 2006; Collier et al. 2008). Increased coastal development has also led to increased boat traffic and fishing pressures, ship groundings, anchor drag, and derelict fishing gear, which damage and remove important marine organisms from benthic habitats (Jaap 1984; Lirman and Miller 2003; Chiappone et al. 2005; Collier et al. 2008).

The Southeast Florida Reef Tract (SEFRT), the northernmost component of the Florida Reef tract which is part of the Southeast Florida Coral Reef Conservation Area, is a 170-km- long, high-latitude reef system that parallels the southeastern Florida coast from Martin County south to Miami-Dade County. The SEFRT exists at the northern limit of coral growth, exposing it to a greater range of conditions, both anthropogenic and environmental. It is characterized by a nearshore ridge complex, and three separate linear limestone reefs (Jaap and Hallock 1990; Hoegh-Guldberg et al. 2007; Halpern et al. 2008; Finkl and Andrews 2008; Collier et al. 2008; Hoegh-Guldberg and Bruno 2010; Gilliam 2011; Gilliam and Walker 2013; Macintyre and Milliman 1970; Lighty 1977; Macintyre 1988; Lirman and Miller 2003; Banks et al. 2007; Walker et al. 2008). The nearshore ridge complex lies closest to shore, inshore of the inner reef, over a depth range of 3-7 m. The inner reef lies 0.5-1 km from shore with the same depth range as the nearshore ridge. The middle reef is 1-1.5 km from shore with a reef crest in 6-8 m, and the outer reef lies 1.5-2 km from shore with a reef crest in 15-21 m (Lighty et al. 1978; Moyer et al. 2003; Dodge et al. 2007; Walker et al. 2008).

The SEFRT supports assemblages of octocorals, zoanthids, macroalgae, sponges, and scleractinian corals (Moyer et al. 2003). However, Jones (2018) and Gilliam (2011, 2012) have observed stony coral cover declines at certain sites in response to thermal stressors and have documented sponges, macroalgae, and octocorals as the primary benthic assemblage components along the SEFRT. Trends of increasing abundance and cover of sponges on the SEFRT reflect similar trends on coral reefs throughout the Caribbean (Norström et al. 2009; Colvard and Edmunds 2011), which have been partially attributed to the significant declines in reef-building scleractinian coral cover and an associated increase in space available for sponges (Suchanek et

al 1985; Hughes 1994; Hughes 1996; Schutte et al. 2010). However, because coral cover throughout the Caribbean is higher than the coral cover on the SEFRT, the loss of scleractinian corals is likely not a measurable change that is driving the increase in sponge cover on the SEFRT (Schutte et al. 2010; Jones 2018). Regardless of the drivers, substantial increases in sponge cover on Caribbean reefs could potentially decrease space for scleractinian coral recruitment as they occupy physical space and their mesohyl, the supportive structure comprised of spicules and spongin that make up the body of the sponge, may have chemicals that deter coral settlement (Norström et al. 2009; Bell et al. 2014). Sponges also release nutrients, which increases colonization by macroalgae (de Goeij et al 2013; Pawlik et al. 2016). Although sponges may reduce the ability of scleractinian coral settlement and increase colonization by opportunistic species, they do provide benefits to the reef. Sponges are considered to be one of the oldest organisms and they increase habitat complexity and provide food for invertebrates and reef fishes (Buettner 1996; Diaz and Rützler 2001; Henkel and Pawlik 2005; Dunn et al. 2015; Feuda et al. 2017). Their structure supports a soundscape that attracts reef organisms (Butler et al. 2016). Stabilization of rubble by sponges creates structurally sound habitat for coral recruitment, which assists in reef restoration and facilitates the building of reef framework (Wulff and Buss 1979; Wulff 1984; Biggs 2013). Sponges enhance water quality by removing bacteria, sediments, microalgae, and other small organisms from the water column via filter feeding (Reiswig 1971; pile 1997; Principe et al. 2012). This decreases turbidity, which increases water clarity and light availability for photosynthetic organisms (Peterson et al. 2006; McMurray et al. 2010). The combination of high volume filtration, including consumption of dissolved organic material, accompanied by their diverse assemblages of microbial endosymbionts give sponges essential roles in cycling of nutrients, carbon and nitrogen (Southwell et al. 2008; Olson and Gao 2013; Fiore et al. 2013a; Fiore et al. 2013b; Pawlik 2016).

Xestospongia muta (Schmidt 1870), the giant barrel sponge (Figure 1A) occurs on tropical and subtropical western Atlantic reefs from Bermuda, throughout the Gulf of Mexico and southward throughout the Caribbean at depths between 2 and 150 m (Buettner 1996). It can reach several meters in height and diameter, live for thousands of years, and provide biomass and ecosystem functions not offered by other sponge species (Diaz and Rützler 2001; Southwell et al. 2008; McMurray et al. 2008; McMurray 2017). Its compact spicular architecture of the mesohyl, rigid structure (Jones et al. 2005), and barrel-like shape provide habitat for reef organisms and

rigid protection against physical disturbance which improves reef resilience. Its shape and biomass allow it to filter a greater volume of water than any other benthic invertebrate (Vogel et al. 1977). This efficient filtration, coupled with proteobacterial and cyanobacterial endosymbionts in the mesohyl, gives it an essential role in cycling nutrients on reefs. The microbial community within the sponge and the continuous filtration of seawater recycles nitrogen and carbon, providing nutrients for the oligotrophic reef system and the higher trophic levels (Rützler 1991, Diaz and Rützler 2001; Richelle-Maurer et al. 2003; Southwell et al. 2008; Bell 2008; de Goeij et al. 2013; Fiore et al. 2013a; Fiore et al. 2013b; McMurray 2014; Morrow et al. 2016; McMurray 2017). Unlike stony corals who depend on a symbiotic relationship with zooxanthellae for photosynthesis, X. muta can survive without its cyanobacterial symbionts because the relationship between the sponge host and the symbiont is commensal. Therefore, if the mesohyl is bleached, it does not lose its ecosystem functions and can continue to filter water effectively and efficiently (Thacker 2005; McMurray et al. 2008). This species is considered an allogenic ecosystem engineer based on its modification of the abiotic properties of the surrounding seawater, which enhances water quality and facilitates nutrient cycling on the SEFRT, making it a species of interest to study (McMurray 2017).

Xestospongia muta responds to global climate change, extreme environmental conditions, and anthropogenic factors by bleaching and becoming diseased (Figure 1B) (Angermeier et al. 2011; McMurray et al. 2011; Cuvelier et al. 2014). Fluctuating temperatures along with ocean acidification cause a loss of cyanobacterial symbionts, destabilizing the sponge microbiome and increasing its susceptibility to disease, such as sponge orange band disease (SOB) (Mulheron 2014; Morrow et al. 2016; Lesser et al. 2016). On the SEFRT in April of 2012 there were reports of a SOB disease event which affected individual X. muta within the SEFRT population (Mulheron 2014). Climate change has also increased the frequency and intensity of storms and hurricanes, many of which have hit South Florida. The most recent to affect South Florida was Hurricane Irma in September 2017, a category 4 hurricane with winds reaching 100 km h-1 over the SEFRT (Cangialosi et al. 2018). These energetic events increase wave action and rubble movement, causing the detachment and shearing of sponges and subsequent loss of biomass and function (Wilkinson 2004; McMurray and Pawlik 2009) (Figure 2 A, B). This species is further threatened by destructive fishing and boating practices, as individuals can be damaged by fishing line, anchor drag and ship groundings (Figure 2C). Individuals can recover from such events if

damage does not remove the base of the sponge (Woodley et al. 1981; Wulff 1995; Jaap 2000; Chiaponne et al. 2002; Wulff 2006; Collier et al. 2008; McMurray and Pawlik 2009; Gilliam et al. 2008).

A B

Figure 1. A) Healthy Xestospongia muta; B) Bleached sponge mesohyl with Sponge Orange Band disease.

A B C

Figure 2. A, B) Damaged X. muta sheared by Hurricane Irma; C) derelict rope bisecting X. muta. The goal of this study was to use images and demographic data collected at a total of 41 permanent sites from two long-term monitoring projects (discussed below) to identify possible density trends in X. muta populations regionally on the SEFRT and on the nearshore, middle, and outer reef tracts of the SEFRT from 2003 to 2018. Of the 41 sites, a subset of 20 was used to evaluate both density and volume trends, including size class density distributions, regionally and across all three reef habitats, from 2013 to 2018. These data were then used to identify any differences pre- and post-Hurricane Irma to evaluate its impact on the X. muta population. Although many hurricanes have affected Southeast Florida during this period, I chose to focus on one to understand the impact of an acute physical disturbance on the X. muta population of the SEFRT, hypothesizing that hurricanes significantly affect X. muta population densities, volume,

and size class distribution. Although McMurray et al. (2008, 2009, 2010, 2011, 2014, 2015, 2017) have described X. muta populations in the Florida Keys, no published data exist on X. muta population densities, volume, or size classes on the SEFRT. Furthermore, few studies address the impact of acute physical disturbances, specifically from hurricanes, on X. muta populations (Blair et al. 1994; Gilliam et al. 2008). Understanding X. muta population trends is useful in assessing the current state of the population on the SEFRT and the functional characteristics the population provides for the marine ecosystem. It also provides baseline data for future investigations of this important species on the SEFRT.

3. Methodology

3.1 Southeast Coral Reef Evaluation and Monitoring Project (SECREMP) The Southeast Coral Reef Evaluation and Monitoring Project (SECREMP) is a long-term monitoring project that examines temporal changes and the status of the benthic communities on the SEFRT. From 2003 to 2009, ten permanent sites were surveyed annually. In 2010, two more sites were added and, by 2013, the project surveyed 22 permanent sites annually between May and September through the 2018 sampling (Table 1, Figures 3-5). Only 20 sites were used for this study. Four, 22 x 1-m belt transects (88 m2 total area per site) were surveyed per site, each with a north to south orientation. Within each belt transect, images were taken along the east side of the transect tape and X. muta demographic data were collected within 0.5 m off each side of the transect tape. Demographic measurements of X. muta included height, maximum base diameter, and maximum barrel diameter (Figure 6B and 6C). Data collection also included measurement of the maximum diameter of the apical opening, correctly termed the vent (Figure 6A), which was outside the statement of work for SECREMP.

Transect images were then analyzed to assess X. muta densities by sites from 2003 to 2011, and demographic data were used to calculate density from 2012 to 2018. Together, these data were used to identify density trends regionally on the SEFRT and for the nearshore, middle, and outer reef habitats. Density from 2013 to 2018 was calculated using only the in situ demographic data for the regional, nearshore, middle, and outer reefs. Due to small sample sizes and similarities in both depth and habitat, the nearshore ridge complex and inner reef sites were grouped and analyzed as the nearshore reef for this study. Height, and vent and base diameters (Figure 6) were used to calculate volume of each individual sponge from 2013 to 2018 to assess

regional volume and volume across all three reef habitats. Volume of each sponge recorded from 2013 to 2018 was also used to group individuals into five size classes based on volume to assess regional density in terms of size class distributions (McMurray et al. 2010).

Figure 3. Site locations in Palm Beach and Broward Counties. Index map shows the location on the Florida Peninsula. See text for study abbreviations.

Figure 4. Site locations in Broward County. See text for study abbreviations.

Figure 5. Site locations in Miami-Dade County. See text for study abbreviations.

A B C

Figure 6. SECREMP X. muta measurements: A) maximum vent diameter, B) maximum base diameter, and C) height. 9

3.2 Broward County Biological Monitoring Project (BC BIO) The Broward County Biological Monitoring Project (BC BIO) was created to assess the impacts of beach re-nourishment on the SEFRT benthic community. Twenty-one permanent sites were surveyed annually between September and January from 2003 to 2018 (aside from 2012, when one site was not sampled) (Table 2, Figures 3-5). Each site consisted of one 20 x 1.5-m transect oriented north to south (30 m2 total area per site). Along each transect, 40 photographs were taken of a quadrat (100 cm x 75 cm) (Figure 7), and X. muta demographic data (height, and diameter measurements) were taken within each of the 40 quadrats. Images were analyzed to assess densities of X. muta by site in 2003 and 2004, and the in situ demographic data were used to calculate density from 2005 to 2018. These data were then used together (and in conjunction with the SECREMP data) to identify density trends regionally and for each of the reef habitats. Due to small sample sizes and similarities in both depth and habitat, the nearshore ridge complex and inner reef sites were grouped together and analyzed as the nearshore reef. It is important to note that, for both long-term monitoring projects, data from 2009 were omitted, because only 10 of the total 41 sites were surveyed that year.

Figure 7. X. muta in a 0.75 m2 photoquadrat at one of the BC BIO sites.

3.3 Data Analysis All analyses were conducted in the statistical program R studio (R Core Team 2017). Density was first assessed regionally across all 41 studied sites along the SEFRT (2003-2018). Density trends over time were identified using images and in situ data from both monitoring projects. Density was then assessed by reef habitat (nearshore, middle, and outer reef) across

sampling years to determine which, if any, of the reef habitats was driving density changes. To ensure that image data were not significantly different from in situ data, 10% of sites with both in situ and image data (of sites surveyed from 2003 to 2018, see Tables 1 and 2), were randomly selected. Densities were calculated from both in situ data and site images. A paired t-test was run to see if the densities calculated from the in situ data and images were significantly different. Regional X. muta density trends from 2003 to 2018 were analyzed using a parametric linear regression. Density trends on the middle and outer reef tracts from 2003 to 2018 were also analyzed using a parametric linear regression. The nearshore densities from 2003 to 2018 were analyzed using a polynomial regression because the nearshore density data did not meet the parameters of a parametric linear analysis. For the analyses in the results, density was calculated by taking total number of individual sponges at all the sites combined over the total area of the sites combined. Linear mixed-effects models were run to identify significant differences between sample years for regional, nearshore, middle and outer reefs and to identify if the SOB disease event recorded in April of 2012 caused significant decreases in density.

A subset of data was used to assess the density, volume, and size class densities from 2013 to 2018 and also to assess the damage of an acute physical disturbance event on the X. muta population. Because the monitoring years for pre- and post-Hurricane Irma were not the same for the two projects, data from only one, SECREMP, was used for clarity, as it captured the pre- and post-hurricane monitoring events with consistent demographic data collection. The years 2013 to 2018 were used, because demographic data used for volume and size class calculations were collected for all 20 SECREMP sites during that period.

Density changes associated with Hurricane Irma were analyzed using linear mixed- effects models. Variations in density pre- (2017) and post-hurricane (2018) were assessed regionally and by reef tract. Density trends from 2013 to 2018 were investigated using generalized additive models for the regional, nearshore, middle, and outer reefs to identify density trends within the SECREMP dataset in the years preceding Hurricane Irma to evaluate the population before and after an acute physical disturbance event.

Although density identifies the number of individuals in the population, sponge volume is useful to evaluate and extrapolate the services the X. muta population contributes to the ecosystem (e.g., in terms of water volume filtered and nutrients recycled) (Rützler 1991; Diaz

and Rützler 2001; Richelle-Maurer et al. 2003; Taylor et al. 2007; Southwell et al. 2008; de Goeij et al. 2013; Fiore et al. 2013a; Fiore et al. 2013b; McMurray 2014; Morrow et al. 2016; McMurray 2017). Individuals with higher volume will provide more ecosystem services for the marine community, while the opposite is true for the lower volume sponges. Investigating the volume also provides insight into the volume changes on the SEFRT regionally and across the three reef habitats. Volume was calculated using the formula derived for the geometric model of a frustum of a cone following McMurray et al. (2008; Equation 1).

Equation 1. Vsponge=1/12*pi*h(vd^2+(vd)(bd)+bd^2)

where h = height, vd = vent diameter, and bd = base diameter (all measurements in cm). Individual sponge volume was calculated using measurements from SECREMP data in 2017 and 2018. Vent diameter data were not collected before 2017. To evaluate the volume trends in the years preceding the acute physical disturbance and to provide a more descriptive data set, the relationship between base diameter and vent diameter was analyzed using linear regressions to derive an equation with which to calculate vent diameter of individuals from previous monitoring events (Appendices A and B). The vent diameter was calculated for each individual sponge from 2013 to 2016 using both the 2017 and 2018 regression equations. The volume of each sponge was calculated using both vent diameters and the average of these two volumes was used for analyses. Volume was analyzed using linear mixed-effects models on the regional, nearshore, middle, and outer reef data and generalized additive models were used to assess volume trends from 2013 to 2018.

Individual sponges from 2013 to 2018 were grouped into five size classes (I-V) by volume (Appendix C). Size classes were chosen based on statistical analyses done on population distribution of X. muta by McMurray et al. (2010) to encompass the range of sizes found within a X. muta population. The size class by volume parameters set by McMurray et al. (2010) were used to identify population volume distribution across sampling years along the SEFRT. Size class changes between sampling years were used to identify densities of individuals in each size class regionally driving both X. muta volume and density changes on the SEFRT (see Appendix E, F, and G for the density of Individuals in each size classes on the nearshore, middle, and outer reefs).

4. Results 4.1 Spatial and temporal trend analysis No significant differences were recorded between the site densities calculated from both images and in situ so the data were used in conjunction for all density analyses (paired t-test, p>0.05). Regional X. muta density exhibited a significant increasing trend from 2003 to 2018 (parametric linear regression, p< 0.0001, R2=0.84) (Figure 8; see Appendices H and I for site densities). The lowest density was 0.16 individuals m-2 in 2003 (n=161 sponges), and the highest was 0.37 individuals m-2 in 2017 (n=886). Density significantly decreased from 2017 to 2018 with 0.32 individuals m-2 (n=771) (linear mixed-effects model, p< 0.01). Density on the nearshore reef decreased from 2003 to 2007 but then increased to 2018 (parametric polynomial regression, p <0.0001, R2=0.88) (Figure 9). The lowest nearshore density was 0.04 individuals m-2 in 2003 (n=14) and the highest 0.09 individuals m-2 in 2017(n=81). Densities increased significantly on both the middle and the outer reefs from 2003 to 2018 (parametric linear regression, p <0.0001, R2=0.89; parametric linear regression, p <0.0001, R2=0.84) (Figures 10 and 11). The lowest density on the middle reef was 0.19 individuals m-2 in 2003 (n=59) and the highest 0.48 individuals m-2 in 2017 (n=287). The lowest on the outer reef was 0.27 individuals m-2 in 2003 (n= 88) and the highest 0.59 individuals m-2 in 2017 (n=518). The outer reef exhibited the highest densities across all years compared to the nearshore and middle reefs. There was no significant decrease in density from 2011 to 2012 for the regional, nearshore, middle, or outer reefs in response to the SOB disease event (linear mixed-effects model, p>0.05).

Figure 8. Regional X. muta density along the SEFRT (number of sites used: 2003-2009, n=31; 2010, n=33; 2011, n=35; 2012, n=34; 2013-2018, n=41). Middle bars of boxplots=median values, box length=interquartile range (IQR), and whiskers extend from upper and lower IQR to maximum and minimum values. Asterisk denotes significant difference between 2017 and 2018.

Figure 9. Nearshore reef X. muta density along the SEFRT (number of sites used: 2003-2010, n=11; 2011, n=12; 2012, n=11; 2013 to 2018, n=15). Graphics as in Figure 8. Dots indicate outliers.

Figure 10. Middle reef X. muta density along the SEFRT (number of sites used: 2003-2012, n=10; 2013-2018, n=12). Graphics as in Figure 9.

Figure 11. Outer reef X. muta density along the SEFRT (number of sites used: 2003-2009, n=10; 2010, n=12, 2011 and 2012, n=13 2013 to 2018, n=14). Graphics as in Figure 9.

Within the SECREMP dataset from 2013 to 2018, densities increased regionally and across all reef tracts from 2013 to 2017 (generalized additive model; regional: p<0.0001; nearshore: p >0.05; middle: p <0.0001; outer: p <0.0001; Figures 12, 13, 14, and 15). Although nearshore densities did not increase significantly, the data displayed an increasing trend over time. The lowest densities, both regionally and for each habitat for the SECREMP dataset, were recorded in 2013 and the highest in 2017 as follows: regional had 0.26 individuals m-2 (n=461) and 0.39 individuals m-2 (n=684); nearshore reef had 0.05 individuals m-2 (n=34) and 0.10 individuals m-2 (n=73); middle reef had 0.35 individuals m-2 (n=123) and 0.56 individuals m-2 (n=19); outer reef had 0.43 individuals m-2 (n=304) and 0.59 individuals m-2 (n=415).

Volume trends increased regionally and across all reef habitats from 2013 to 2017 (generalized additive model; regional: p<0.0001; nearshore: p<0.0001; middle: p<0.0001; outer: p <0.0001; Figures 12, 13, 14, and 15, see Appendix J for volume by site). As with SECREMP densities above, smallest total volumes regionally and in each habitat were recorded in 2013 and largest in 2017 as follows: regional had 8.9x106 cm3 and 1.4x107 cm3; nearshore reef had 3.3x105 cm3 and 6.2x105 cm3; middle reef had 1.2x106 cm3 and 2.6x106 cm3; outer reef had 7.5x106 cm3 and 1.1x107 cm3. Across all sampling years, 2013 to 2018, the outer reef had the highest volume compared to both the nearshore and middle reefs.

The regional density on the SEFRT of the sponges in the smallest size class (I) increased from 0.04 individuals m-2 in 2013 to 0.12 individuals m-2 in 2017. (Figure 16). Size classes II, III, IV, and V fluctuated over time, with regional densities ranging from 0.04 to 0.10 individuals m-2. Highest regional density by size class were as follows: II had 0.07 individuals m-2 in 2014; III had 0.07 individuals m-2 in 2017; IV had 0.05 individuals m-2 in 2014; V had 0.10 individuals m-2 in 2017. In 2013, the largest size class (V) had the highest regional density of any size class, whereas in 2018, the smallest size class (I) had the highest regional density of any size class.

4.2 Impact of Hurricane Irma

Regional density decreased significantly during the sampling year following Hurricane Irma, from 0.40 individuals m-2 in 2017 to 0.31 individuals m-2 in 2018, a loss of 132 individuals (linear mixed-effects model, p <0.0001; Figure 12). For context, each consecutive year from 2013 to 2017 gained individuals and 2018 was the only year individuals were lost from the population. The three reef habitats demonstrated the same trend, with densities decreasing from

2017 to 2018 (linear mixed-effects model; nearshore: p >0.05; middle: p <0.01; outer: p <0.001; Figures 13, 14, and 15) as follows: nearshore reef decreased from 0.10 individuals m-2 to 0.07 individuals m-2, a loss of 21 individuals; middle reef decreased from 0.56 individuals m-2 to 0.47 individuals m-2, a loss of 32 individuals; and the outer reef decreased from 0.59 individuals m-2 to 0.48 individuals m-2, a loss of 79 individuals.

Regional X. muta volume peaked in 2017 and then decreased significantly between 2017 and 2018 with a loss of 4.2x106 cm3 (linear mixed-effects model, p <0.001, Figure 12). Xestospongia muta suffered a loss of 3.7x105 cm3 volume on the nearshore reef from 2017 to 2018, although the decline was not significant (Figure 13). By contrast, volume on both the middle and outer reef decreased significantly post-Irma sampling (linear mixed-effects model, p <0.05; Figures 14 and 15), the middle reef losing 8.7x105 cm3 and the outer reef losing 3.3x106 cm3 of volume.

All five size classes decreased in density pre- (2017) to post-hurricane (2018) monitoring. Although size class I had the highest regional density in 2018 (0.11 individuals m-2) compared to the four larger size classes, it was still a decrease from 2017 (0.12 individuals/m2). The other size class densities decreased from 2017 to 2018 as follows: II-0.06 to 0.05 individuals m-2; III- 0.07 to 0.04 individuals m-2; IV- 0.05 to 0.04 individuals m-2; and V-0.10 to 0.07 individuals m-2. Thus, density of size class I declined the least from 2017 to 2018, whereas size classes III and V decreased the most following Hurricane Irma.

Figure 12. Left: SECREMP regional density and Right: regional volume, n=20 sites. The middle bars of the boxplots represent the median values, the box length represents the interquartile range (IQR), the whiskers extend from the upper and lower IQR to the maximum and minimum values, and the dots indicate outliers. Asterisks represent a significant difference between years 2017 and 2018.

Figure 13. Left: SECREMP nearshore reef density and Right: nearshore reef volume, n=8 sites. Graphics as in Figure 12.

Figure 14. Left: SECREMP middle reef density and Right: middle reef volume, n=4 sites. Graphics as in Figure 12.

Figure 15. Left: SECREMP outer reef density and Right: outer reef volume, n=8 sites. Graphics as in Figure 12.

Figure 16. Densities (individual m-2) within each of the five size classes across sampling years on the SEFRT. Size class I includes the smallest individuals by volume and size class V are the largest individuals by volume. Colors correspond to years. See text for volumes of each size class.

5. Discussion 5.1 Long-term trends

Long-term monitoring of the X. muta population on the SEFRT showed a significant increasing trend in density both regionally and on each of the three reef habitats. Although X. muta populations have been studied in the Florida Keys (McMurray 2008, 2010, 2016, 2018; McMurray et al. 2015; Pawlik et al. 2016) and throughout the Caribbean in the Bahamas, Colombia, Belize and Saba (de Bakker et al. 2016; Maldonado et al. 2016), the long-term spatial and temporal trends and status of X. muta populations along the SEFRT have not been well documented. Densities of X. muta throughout sites in the Caribbean range between 0.01 and 0.72 individuals m-2 (McMurray et al. 2015; de Bakker et al. 2016; Maldonado et al. 2016). Within this dataset there were both middle and outer reef sites that approached densities close to 1 individual m-2 with the outer reefs consistently having the highest densities; values that have not previously been reported in the literature. Mean densities in the Caribbean are between 0.21 and 0.29 individuals m-2, while the mean density on the SEFRT is 0.35 individuals m-2 ±0.04 SEM, indicating that X. muta is most abundant on the SEFRT compared to other locations in its range for which densities have been recorded (McMurray et al. 2015; de Bakker et al. 2016;

Maldonado et al. 2016). McMurray et al. (2015) found that over 12 years of sampling in the Florida Keys, the X. muta population increased by 122%, indicating that the trends reported here for the SEFRT are also occurring in the Florida Keys. Over a 16-year sampling period, the regional X. muta population density on the SEFRT increased by 100%, from a density of 0.16 individuals m-2 in 2003 to 0.32 individuals m-2 in 2018. In 2017, before Hurricane Irma, the regional density on the SEFRT was higher than in any previous sampling year with a density of 0.37 individuals m-2 correlating to a 130% increase from 2003.

Densities on both middle and outer reefs increased significantly from 2003 to 2018, and both supported consistently greater densities of X. muta than the nearshore habitat. These two habitats thus drove the region-wide increasing trend. Densities on the nearshore reef decreased during sampling from 2003 to 2007, but the trend increased from 2008 to 2018, variability that might be attributable to levels of irradiance or the wider range of water temperatures characteristic of this shallower habitat. Unlike stony corals, X. muta do not need light to survive and can rely on heterotrophic feeding when conditions are not favorable for photosynthesis, therefore higher levels of irradiance in the nearshore habitat could prevent X. muta larvae from settling in the nearshore habitats (McGrath et al. 2018). It has been found that sponge larvae exhibit negative phototaxis, moving away from high light intensity into depths with lower light intensity to settle (Maldonado 2006). Research on the impact of irradiance and UV light on cyanobacteria found that cyanobacteria actively moved away from high levels of both irradiance and UV light, therefore it is likely that the cyanobacterial symbionts in X. muta mesohyl prefer areas of intermediate light levels (Kruschel and Castenholz 1998). Water temperatures in the shallow, nearshore environment are seasonally variable with higher temperatures in the summer (Jones 2018). A review by Bell et al. (2017) found that temperature is the most important abiotic factor that controls the physiological performance and development of sponges. Therefore, X. muta may preferentially settle in deeper habitats in their larval stages to avoid high levels of irradiance and to settle in a habitat with a more stable temperature, which explains the higher densities of X. muta on the deeper middle and outer reef habitats. Despite the varying environmental conditions and anthropogenic stressors affecting the SEFRT, the X. muta population has continued to exhibit increasing density trends from 2003 to 2018 regionally and on the middle and outer reefs, and from 2008 to 2018 on the nearshore reef, indicating that the

population is resistant to, adapting to, or benefitting from these changing conditions and the rate of new settlement is greater than mortality events within the population (Bell et al. 2017).

5.2 Drivers of increasing density

Bell et al. (2014, 2017) found that two Xestospongia species were most abundant, although smaller, at a site subject to high human impact and activities as well as near sewage outfalls and areas of high turbidity. The SEFRT is offshore a highly urbanized coast with multiple densely populated cities. It is therefore likely that increased runoff from development along the coastline, disposal of sewage from outfalls, port activity, and agricultural fertilizers have increased local nutrient concentrations and turbidity (Lapointe et al. 2005a, 2005b). These added nutrients could be contributing to the growth and survival of the heterotrophic sponges as they recycle the excess nutrients or, perhaps, the population is unaffected by the changing ocean conditions (Zea 1994; Ward-Paige et al. 2005; Gochfeld 2007; Norström et al 2009; Bell et al. 2014; Bell et al. 2017). During the initial investigation of the X. muta population density data at the site level, there was no significant correlation between site densities and distance of sites from outfalls or ports. Correlation does not always indicate causation, and the annual, long-term monitoring is not designed to address direct impact from these features. While it is likely that water quality and nutrient concentration associated with these man-made features do have an impact on the X. muta population, the monitoring was not designed to capture these impacts. Additionally, distance of the monitoring sites from these features may not be an accurate proxy of impact given the multiple eddies and currents that carry water in multiple directions along the southeast Florida coastline (Lee 1975; Sponaugle et al. 2005). Water quality tests and mesohyl samples at each site would be more applicable and value added for future research to identify if there is a correlation between nutrient concentrations in the water column and in the sponges, driving increasing population densities.

Increasing sponge densities throughout the Caribbean might be attributable to increased substrate availability associated with the significant decrease in stony coral cover (Jones 2018, Ward-Paige et al. 2005; Norström et al. 2009; McMurray et al. 2010). While this may be true in the Caribbean where coral cover is higher (Schutte et al. 2010), stony coral cover is less than 3% on the SEFRT. Its decline has therefore not likely contributed to the increasing X. muta populations, because of the vast hard bottom available for sponge settlement (Jones 2018).

However, an unprecedented and ongoing disease event along the SEFRT that began in 2014 has significantly decreased live stony coral cover (Walton et al. 2018). During this period, the results of the current study show an increase in X. muta abundance. Therefore, the compounding anthropogenic and environmental stressors causing alteration of the habitat (e.g., increased sea surface temperatures, pollution, nutrient enrichment, port activity, beach nourishing activities, dredging) that likely caused the stony coral disease outbreak (although the actual cause remains unknown) did not affect the X. muta population. Conversely, activities such as beach nourishment and dredging cause sedimentation and McGrath et al. (2017) found that Xestospongia species have a higher tolerance to sediment exposure because of their ability to filter water continuously. Therefore, Xestospongia can survive in areas with sedimentation from development and can cope with both chronic and acute disturbances better than other reef taxa (McGrath 2017). It is also interesting to note that, although conditions such as predation, overgrowth, and disease were not addressed in this study, fewer than 10 incidences were noted of SOB disease even after reports of a disease event affecting the X. muta population in April of 2012 (Cowart et al. 2006; Mulheron 2014). This contrasts with Webster’s review (2007) of an increase in sponge diseases globally, including incidences of disease within the X. muta populations. Although the 2012 monitoring for both monitoring projects occurred after the presence of disease in April of 2012, it is likely that the monitoring did not capture the full extent of the disease on the X. muta population of the SEFRT. The SOB disease bleaches and disintegrates the mesohyl of the sponge, causing the sponge to break apart and dissipate, which can progress as quickly as weeks or even days (Cowart et al. 2006; Angermeier et al. 2011). Therefore, by the time the sites were monitored the diseased sponges may have disintegrated completely and were not captured in the monitoring. Upon evaluation there was no significant decrease in density from 2011 to 2012 for regional, nearshore, or outer reef, and either the disease event was not as widespread as initially recorded, or the monitoring did not capture the full extent of the disease on the SEFRT. These results suggest that the X. muta population on the SEFRT, in contrast to other sponge populations and reef taxa throughout the Caribbean, can withstand at least some changes in water quality, turbidity, and fluctuating temperatures associated with increasing anthropogenic and environmental stressors, and disease events.

5.3 Hurricane Irma

Density and volume of X. muta decreased significantly following Hurricane Irma. The high wind energy generated by hurricanes over the sea surface causes intense wave action and subsurface water movement. The subsequent movement of rubble and derelict marine debris, and the dislodgement of rocks and corals, damages, dislodges, fragments, and breaks benthic organisms (Scoffin 1993; Harmelin-Vivien 1994). Wulff (1995) documented the reduction in density and biomass of erect sponges in Panamá following Hurricane Joan, specifically those species with skeletons of siliceous spicules, like X. muta. Similarly, after Hurricane Andrew passed over Florida in 1992, Blair et al. (1994) observed the damage and detachment of X. muta on the southern portion of the SEFRT. Although Hurricane Irma was the only disturbance investigated during this study, it was severe enough to interfere with the regional long-term trends exhibiting a significant decrease in density between 2017 and 2018. The results demonstrate the significant effect of an acute physical disturbance, specifically the significant region-wide decrease in both the density and volume of the X. muta population on the SEFRT. The damage was not localized to one portion of the reef tract or one area of the region. Therefore, we can deduce that the decreases were not driven by a local disturbance, such as a ship grounding, damage from derelict marine debris, or anchor drag. Xestospongia muta populations in all three reef habitats throughout the study area decreased in density, numbers of individuals, and volume resulting in losses of functional services to the reef communities provided by this species. Xestospongia muta is an erect sponge with compact spicular architecture and rigid structure that make it susceptible to mechanical damage from hurricanes (Wulff 1995, 2006). Fortunately, those individuals that were damaged from physical disturbance have the ability to recover (Gilliam et al. 2008). Xestospongia muta mesohyl is homogenous and not highly differentiated, allowing the sponge to regrow (Korotkova 1963; Ayling 1981; Wulff 2006). Sheared X. muta with bases still attached to the substrate have been observed to regenerate faster than the growth rate of healthy individuals that have not been sheared or damaged (McMurray et al. 2008). Data collection in 2019 will provide insight into the recovery potential of the damaged individuals in terms of growth shown by volume changes and in density from the recruitment of new individuals.

The density data for the different size classes indicates an increase in the smallest size class (I), which are the sponges with the smallest volumes, over time. Less than a year after the hurricane, size class I had the highest density compared to the four larger size classes. An increase in smaller individuals in a population is indicative of an acute disturbance affecting the population (Bell et al. 2017). Although size class I sponges increased in density, region-wide density decreases post-hurricane were driven mostly by losses of sponges in size classes II to V. The loss of the larger sponges by volume represents a loss of ecosystem services provided to the reef habitat. However, the increase in the smaller sponges in this study, coupled with a study finding higher abundances of smaller sponges after Hurricane Joan (Wulff 1995), suggest that sponge populations thrive according to the intermediate disturbance hypothesis: the idea that intermediate levels of frequency and size of disturbances in an ecosystem allow for certain species in a community to proliferate (Grime 1973; Connell 1978). It is also likely that X. muta is an early colonizer during successional events such as those created by disturbance from hurricanes (Hirata 1987; Masi et. al 2015). Although hurricanes may cause sponge damage, they also may promote asexual reproduction, increasing population density via reattachment. During hurricanes pieces of sponges break off and have the ability to reattach to the substrate and grow as long as the piece of sponge is stationary for enough time to grow onto the substrate and reattach (Bush 2012). Despite the losses of X. muta after hurricane Irma, recruitment and regeneration as well as reattachment following such an acute physical disturbance could allow the population to recover. The increasing density of the small size classes as well the ability of this species to regrow, will increase habitat structure and complexity for invertebrates and fishes over time. As stony coral cover continues to decrease and structural complexity from the degrading scleractinian skeletons is lost, habitat provided by X. muta that is recolonizing, reattaching, and regenerating may become crucial for some reef organisms.

6. Conclusion While X. muta does not replace the ecosystem services of scleractinian corals, the increasing trends in both density and volume offer functional benefits to reef habitats. Certain sponge species, like Cliona delitrix, which is also a common sponge species found throughout the Caribbean, also have been exhibiting increasing distribution on the SEFRT, probably in

response to disturbances. The conditions driving the X. muta density increases may also be driving increases in the C. delitrix population. Cliona delitrix is an excavating sponge that bores into healthy, bleached or diseased scleractinian corals, causing added partial or total coral mortality (Chaves-Fonnegra et al. 2016). Unlike C. delitrix, however, X. muta is not an excavating sponge, but instead settles on available substrate and does not actively settle on living coral; therefore the life stages of X. muta do not compromise coral growth or health unlike other sponge species. While X. muta may settle on substrate viable for coral recruits, available substrate is not likely a limiting factor because, as mentioned before, there is less than 3% coral cover on the SEFRT (Jones 2018) Although sponge species like C. delitrix can negatively impact reef taxa, X. muta may mitigate some negative effects of anthropogenic stressors impacting the reef habitat, including cycling excess nutrients in the water column, increasing water clarity and quality for photosynthesizing organisms, storing carbon within its mesohyl to reduce ocean acidification, and generating habitat complexity and reef protection against physical disturbance not offered by other sponge species (de Goeij et al. 2013; Pawlik et al. 2018; McMurray et al. 2018; Wooster et al. 2019; Rützler 1991, Diaz and Rützler 2001; Richelle-Maurer et al. 2003; Southwell et al. 2008; Fiore et al. 2013a; Fiore et al. 2013b; McMurray 2014; Morrow et al. 2016; McMurray 2017). Because X. muta exhibits observable damage from physical disturbances, the population can also provide warning of physical damage to other sensitive reef taxa (Gochfeld et al. 2007). Acute disturbances affect the population and significant losses were captured after Hurricane Irma. However, Irma was not severe enough to change the long-term increasing trends of the nearshore, middle or outer reef habitats. Multiple disturbance events can drive down densities, but throughout the study they were not severe or frequent enough to interfere with the long-term increasing trends indicating the population has the potential for recovery. X. muta can recover from disturbances such as hurricanes or bleaching events more effectively than many other reef taxa (Thacker 2005; McMurray et al. 2008). Therefore, it is important to continue to study resilient reef constituents like X. muta and its long- term spatial and temporal population trends so that we can understand the services it provides and how the population contributes to alternative stable states of reef habitats. Future sampling will provide insight into the continuing population trends in response to environmental and anthropogenic changes. However, it would be beneficial to incorporate water quality changes into data collection and analysis to examine nutrient concentrations and how they may be

affecting the X. muta population. As climate change continues to threaten and drastically alter the physical and chemical properties of the ocean and increases the intensity and frequency of storms and hurricanes, it is imperative to investigate benthic reef organisms and their responses to changing environmental conditions by identifying changes in the long-term trends. It is especially important to focus on the abundant ecosystem engineers such as X. muta that remain stable, maintain healthy populations, and contribute to the overall health of the reef system. As primary reef building species decline, studies of X. muta can provide baseline information for resource managers to better prepare for the future of the SEFRT.

7. Tables

Table 1. Twenty-two SECREMP sites with corresponding depths (m) and geographic coordinates. Asterisks denotes sites not used in study.

Year of Site Depth (m) Reef Habitat Latitude (N) Longitude (W) Establishment DC1 2003 8 Nearshore 25° 50.540’ 80° 06.249’

DC2 2003 14 Middle 25° 50.534’ 80° 05.698’

DC3 2003 17 Outer 25° 50.526’ 80° 05.286’

DC4 2011 12 Outer 25° 40.357’ 80° 05.301’

DC5 2011 7 Nearshore 25° 39.112’ 80° 05.676’

DC6 2013 6 Nearshore 25° 57.098’ 80° 06.545’

DC7 2013 18 Middle 25° 57.511’ 80° 05.627’

DC8 2013 8 Nearshore 25° 40.712’ 80° 07.117’

BCA 2003 8 Nearshore 26° 08.985’ 80° 05.810’

BC1 2003 8 Nearshore 26° 08.872’ 80° 05.758’

BC2 2003 12 Middle 26° 09.597’ 80° 04.950’

BC3 2003 17 Outer 26° 09.518’ 80° 04.641’

BC4 2013 9 Nearshore 26° 08.963’ 80° 05.364’

BC5 2013 12 Middle 26° 18.111’ 80° 04.090’

BC6 2013 18 Outer 26° 18.064’ 80° 03.654’

PB1 2003 8 Nearshore 26° 42.583’ 80° 01.714’

PB2 2003 17 Outer 26° 40.710’ 80° 01.095’

PB3 2003 17 Outer 26° 42.626’ 80° 00.949’

PB4 2010 17 Outer 26° 29.268’ 80° 02.345’

PB5 2010 17 Outer 26° 26.504’ 80° 02.846’

MC1* 2006 5 Nearshore 27° 07.900’ 80° 08.042’

MC2* 2006 5 Nearshore 27° 06.722’ 80° 07.525’

Table 2. Broward County Biological Monitoring Project sites surveyed with corresponding depths (m) and geographic coordinates. All sites were established in 1997. Asterisks denote sites not used in study.

Site Depth (m) Reef Habitat Latitude (N) Longitude (W)

BOCA1* 9 Middle 26° 20.8030' 80° 03.8830'

DB1* 5 Nearshore 26° 18.5869' 80° 04.3928'

DB2 11 Middle 26° 18.6280' 80° 04.0262'

DB3 17 Outer 26° 18.6828' 80° 03.5764'

FTL1 6 Nearshore 26° 09.5343' 80° 05.7475'

FTL2 15 Middle 26° 09.5971' 80° 04.9522'

FTL3 18 Outer 26° 09.5183' 80° 04.6406'

FTL4 6 Nearshore 26° 08.2080' 80° 05.8440'

FTL5 8 Nearshore 26° 08.872' 80° 05.758'

FTL6* 8 Nearshore 26° 08.985' 80° 05.810'

HB1* 6 Nearshore 26° 16.8357' 80° 04.5390'

HB2 11 Middle 26° 16.5350' 80° 04.2620'

HB3 15 Outer 26° 16.4255' 80° 03.8189'

HH2 6 Nearshore 26° 00.6946' 80° 06.7572'

JUL1 12 Middle 26° 00.3014' 80° 05.8134'

JUL2 16 Outer 26° 00.2593' 80° 05.3010'

JUL6 4 Nearshore 26° 04.9120' 80° 06.2226'

JUL7 10 Middle 26° 04.9635' 80° 05.7321'

JUL8 15 Outer 26° 04.9957' 80° 05.0990'

POMP1 6 Nearshore 26° 11.4356' 80° 05.2256'

POMP2 15 Middle 26° 11.3289' 80° 04.8039'

POMP3 16 Outer 26° 11.2141' 80° 04.3650'

POMP4 6 Nearshore 26° 12.7320' 80° 05.2010'

POMP5 9 Middle 26° 14.5660' 80° 04.7310'

POMP6 16 Middle 26° 14.5660' 80° 04.3980'

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9. Appendices Appendix A. Plot of base diameter (cm) in relation to vent diameter (cm) of the individual sponges measured during 2017 monitoring to identify the linear relationship between the two measurements. The Equation of the trend line was then used to calculate vent diameter of individuals from 2013 to 2016 using the measurements of the base diameter.

Appendix B. Plot of base diameter (cm) in relation to vent diameter (cm) of the individual sponges measured during 2018 monitoring to identify the linear relationship between the two measurements. The Equation of the trend line was used to calculate vent diameter of individuals from 2013 to 2016 using the measurements of the base diameter.

Appendix C. Size classes by volume (cm3) of individual sponges with size class I being the smallest individuals and size class V being the largest individuals. Size classes included I (≤143.13 cm3), II (>143.13 cm3 and ≤1077.13 cm3), III (>1077.13 cm3 and ≤5666.32 cm3), IV (>5666.32 and ≤17383.97 cm3), and V (>17383.97 cm3).

Size Class I II III IV V

>143.13 cm3 >1077.13 cm3 Volume ≤143.13 >5666.32 and >17383.97 and ≤1077.13 and ≤5666.32 range (cm3) cm3 ≤17383.97 cm3 cm3 cm3 cm3

Appendix D. Densities (m-2) of each size class on the SEFRT from 2013 to 2018

2013 2014 2015 2016 2017 2018

I 0.04 0.06 0.08 0.09 0.12 0.11

II 0.05 0.07 0.06 0.06 0.06 0.05

III 0.05 0.06 0.06 0.07 0.07 0.04

IV 0.04 0.05 0.05 0.05 0.05 0.04

V 0.07 0.07 0.07 0.08 0.10 0.07

Appendix E. Densities (m-2) of each size class on the nearshore reef from 2013 to 2018

2013 2014 2015 2016 2017 2018

I 0.01 0.02 0.01 0.02 0.03 0.03

II 0.01 0.01 0.02 0.02 0.02 0.02

III 0.01 0.01 0.01 0.02 0.02 0.01

IV 0.01 0.01 0.01 0.01 0.01 0.01

V 0.01 0.01 0.01 0.01 0.01 0.01

Appendix F. Densities (m-2) of each size class on the middle reef from 2013 to 2018

2013 2014 2015 2016 2017 2018

I 0.09 0.10 0.13 0.15 0.17 0.20

II 0.10 0.11 0.09 0.08 0.12 0.09

III 0.07 0.10 0.11 0.12 0.11 0.06

IV 0.05 0.05 0.05 0.05 0.08 0.05

V 0.05 0.06 0.06 0.08 0.08 0.06

Appendix G. Densities (m-2) of each size class on the outer reef from 2013 to 2018

2013 2014 2015 2016 2017 2018

I 0.06 0.08 0.11 0.13 0.17 0.14

II 0.08 0.10 0.09 0.08 0.07 0.05

III 0.08 0.09 0.10 0.09 0.10 0.07

IV 0.08 0.09 0.08 0.08 0.07 0.07

V 0.14 0.14 0.14 0.16 0.18 0.14

Appendix H. SECREMP site densities (m-2) by year. Sites listed from nearshore to outer reef habitats.

2003 2004 2005 2006 2007 2008 2010 2011 2012 2013 2014 2015 2016 2017 2018

BC1 0.14 0.17 0.11 0.11 0.09 0.06 0.03 0.09 0.07 0.06 0.11 0.09 0.11 0.16 0.15

BC4 no no no no no no no no no 0.15 0.26 0.26 0.27 0.31 0.24 data data data data data data data data data BCA 0 0 0 0 0 0 0 0 0 0 0 0 0 0.01 0

DC1 0.09 0.06 0.09 0.03 0 0.03 0.11 0 0.02 0.06 0.02 0.07 0.10 0.13 0.06

DC5 no no no no no no no 0.03 0.10 0.11 0.10 0.10 0.14 0.22 0.14 data data data data data data data DC6 no no no no no no no no no 0.01 0.01 0.01 0.01 0.01 0.01 data data data data data data data data data DC8 no no no no no no no no no 0 0 0 0 0 0 data data data data data data data data data PB1 0.06 0.09 0 0 0 0 0 0 0 0 0 0.01 0 0 0

BC2 0.28 0.20 0.26 0.09 0.11 0.11 0.17 0.37 0.25 0.35 0.50 0.50 0.51 0.57 0.57

BC5 no no no no no no no no no 0.46 0.49 0.46 0.59 0.66 0.57 data data data data data data data data data DC2 0.34 0.45 0.60 0.40 0.34 0.26 0.23 0.26 0.26 0.31 0.35 0.43 0.41 0.47 0.34

DC7 no no no no no no no no no 0.28 0.34 0.43 0.41 0.53 0.39 data data data data data data data data data BC3 0.43 0.43 0.37 0.37 0.57 0.45 0.57 0.80 0.48 0.34 0.63 0.63 0.55 0.63 0.49

BC6 no no no no no no no no no 0.38 0.38 0.33 0.36 0.41 0.40 data data data data data data data data data DC3 0.17 0.14 0.17 0.20 0.20 0.26 0.11 0.17 0.22 0.26 0.25 0.28 0.31 0.31 0.23

DC4 no no no no no no no 0.45 0.55 0.57 0.61 0.64 0.64 0.67 0.47 data data data data data data data PB2 0.09 0.11 0.14 0.06 0.09 0.09 0.06 0.03 0.10 0.11 0.14 0.17 0.24 0.34 0.30

PB3 0.37 0.37 0.45 0.20 0.43 0.40 0.17 0.45 0.33 0.55 0.55 0.60 0.66 0.61 0.58

PB4 no no no no no no 0.49 0.68 0.73 0.60 0.70 0.73 0.72 0.78 0.70 data data data data data data PB5 no no no no no no 0.91 0.97 0.68 0.65 0.74 0.88 0.85 0.97 0.66 data data data data data data

Appendix I. BC BIO site densities (m-2) by year. Sites listed from nearshore to outer reef habitats.

2003 2004 2005 2006 2007 2008 2010 2011 2012 2013 2014 2015 2016 2017 2018

FTL1 0 0 0.07 0.03 0 0 0 0 0 0 0 0 0 0 0

FTL4 0.10 0.10 0.07 0.13 0.03 0.17 0.07 0.07 0.03 0.13 0.10 0.17 0.13 0.10 0.17

FTL5 0 0 0 0.03 0.07 0.03 0.03 0.03 no 0.07 0.03 0.03 0.13 0.10 0.10 data HH2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

JUL6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

POMP1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

POMP4 0.03 0.03 0.03 0.03 0.07 0.03 0.03 0.03 0.03 0.03 0.07 0.07 0.07 0.07 0.07

DB2 0.17 0.13 0.17 0.20 0.10 0.17 0.23 0.23 0.20 0.23 0.33 0.23 0.27 0.27 0.30

FTL2 0.23 0.27 0.27 0.27 0.37 0.37 0.43 0.47 0.33 0.60 0.47 0.63 0.70 0.57 0.67

HB2 0.27 0.27 0.27 0.27 0.27 0.37 0.27 0.23 0.20 0.37 0.37 0.40 0.33 0.50 0.50

JUL1 0.10 0.10 0.23 0.20 0.30 0.27 0.50 0.33 0.43 0.33 0.23 0.27 0.33 0.40 0.57

JUL7 0.03 0.17 0.30 0.40 0.37 0.30 0.27 0.23 0.17 0.27 0.17 0.27 0.33 0.13 0.17

POMP2 0.10 0.10 0.17 0.40 0.33 0.40 0.43 0.33 0.40 0.40 0.30 0.40 0.47 0.33 0.37

POMP5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

POMP6 0.33 0.37 0.43 0.40 0.63 0.53 0.63 0.60 0.53 0.87 0.67 0.53 0.93 0.83 0.97

DB3 0.13 0.20 0.27 0.23 0.47 0.87 0.73 0.87 0.53 0.53 0.60 0.80 0.93 0.87 0.63

FTL3 0.17 0.20 0.23 0.20 0.27 0.33 0.40 0.37 0.30 0.43 0.27 0.43 0.37 0.47 0.43

HB3 0.40 0.53 0.70 0.70 0.77 0.60 0.70 0.57 0.60 0.80 0.50 0.43 0.43 0.50 0.47

JUL2 0.30 0.27 0.33 0.40 0.47 0.43 0.73 0.70 0.70 0.70 0.70 0.73 0.77 0.57 0.63

JUL8 0.17 0.17 0.37 0.27 0.33 0.40 0.27 0.30 0.27 0.37 0.33 0.30 0.43 0.37 0.43

POMP3 0.53 0.43 0.40 0.57 0.50 0.63 0.53 0.60 0.70 0.83 0.50 0.70 0.83 0.67 0.83

Appendix J. Total volume (cm3) at each site listed from nearshore to outer reef from 2013 to 2018

2013 2014 2015 2016 2017 2018

BC1 6954 20334 26562 26252 29429 21028

BC4 133643 106324 167884 200348 154005 44324

DC1 1182 458 1336 3611 4959 1983

DC5 184076 321973 351871 355275 416719 158960

DC6 5129 5187 8060 8060 11824 20664

BCA 0 0 0 0 0.92 0

PB1 0 0 0 0 0 0

DC8 0 0 0 0 0 0

BC2 155956 245054 247377 272759 406054 322877

BC5 314511 332275 442393 533920 579192 481686

DC2 432626 427849 402643 624882 933759 331462

DC7 269553 322087 449311 569557 706374 612345

BC3 384420 462351 519058 498789 633470 568018

BC6 724220 815131 862670 918247 900201 888616

DC3 419323 352167 275761 469733 603253 358959

DC4 1366852 1325453 1284976 1916692 2277575 1135682

PB2 84254 86813 96217 141807 149847 125071

PB3 1391746 1110477 1590411 1492545 2181153 2241328

PB4 2279531 2528588 3064645 3102944 3096097 1701304

PB5 836335 847903 933245 1116717 1238763 774919