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Patch reefs in Biscayne National Park, FL

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Title:
Patch reefs in Biscayne National Park, FL sediments, foraminiferal distributions and a comparison of three biotic indicators of reef health
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Book
Language:
English
Creator:
Ramirez, Alexa
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla
Publication Date:

Subjects

Subjects / Keywords:
Bioindicator
SEDCON
FORAM
Carbonate
Coral
Dissertations, Academic -- Marine Science -- Masters -- USF   ( lcsh )
Genre:
non-fiction   ( marcgt )

Notes

Summary:
ABSTRACT: Coral cover remains highest on patch reefs at the northern end of the Florida reef tract. The reasons for this trend are not well understood, but may be related to the protection from extreme variations in water quality parameters provided by the near constant presence of islands at the north extent of the Florida Keys. Three indices have been developed based on Foraminifera and sediment constituents. Two of the indices, the FORAM Index and the SEDCON Index, were developed to indicate the suitability of a reef environment for continued reef accretion. The third index, the Photic Index, is an assessment of photic stress on reefs based on incidence of bleaching in a species of Foraminifera, Amphistegina gibbosa, which is known to experience loss of algal endosymbionts similar to bleaching in corals. Patch reefs were sampled in Biscayne National Park, FL to assess sediment characteristics and foraminiferal assemblages, as well as to examine trends in the three indices.Sediments associated with a majority (59%) of reefs were coarse sands; muddy sediments were restricted to a few inner patch reefs that were isolated from the influence of Caesar's Creek, which flushes water from inside Biscayne Bay onto the open shelf. Unidentifiable grains predominated in the sediment constituents, along with calcareous algae and molluskan debris. Shells from 82 genera of Foraminifera were identified in the sediments. Quinqueloculina was the most consistently common genus. Percent mud was the single most influential measured variable on the distribution of both sediment constituents and foraminiferal assemblages. Analysis of bleaching in the foraminifer Amphistegina gibbosa revealed that photo-oxidative stress was chronic at 94% of the sites.Patterns of FORAM and SEDCON Index values and their similarity to temperature, salinity, and percent mud distributions show that Caesar's Creek is affecting the benthic community in its immediate vicinity by providing flow that limits the accumulation of mud and potentially other anthropogenic stressors. Overall this study suggests that the reefs in this area are marginal for continued reef growth. A more detailed study of water quality through Caesar's Creek should be conducted to determine exactly how it is affecting the reefs in Biscayne National Park.
Thesis:
Thesis (M.S.)--University of South Florida, 2008.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
System Details:
System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Alexa Ramirez.
General Note:
Title from PDF of title page.
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Document formatted into pages; contains 137 pages.

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University of South Florida Library
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aleph - 002000956
oclc - 319167699
usfldc doi - E14-SFE0002518
usfldc handle - e14.2518
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SFS0026835:00001


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Patch Reefs in Biscayne National Park, FL: Sediments, Foraminiferal Distributions, and a Comparison of Three Biotic Indicators of Reef Health by Alexa Ramirez A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science College of Marine Science University of South Florida Major Professor: Pamela Hallock Muller, Ph.D. David Mann, Ph.D. Benjamin Flower, Ph.D. Date of Approval: May 19, 2008 Keywords: bioindicator, SEDCON, FORAM, carbonate, c oral Copyright 2008, Alexa Ramirez

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ACKNOWLEDGEMENTS I am very thankful for the help and support I have received from my major professor, Dr. Pamela Hallock Muller. Her dedicati on to helping me formulate and carry out this project makes her an outstanding advisor f or whom I am glad to have had the pleasure to work with. I would also like to thank the rest of my committee, David Mann and Ben Flower, for their advice and input during t he critical points of creation and revision of my thesis. Special thanks go to the staff at Biscayne National Park in Homestead, FL who made my sample collection a fast and painless proce ss (BNP permit number BISC-2007SCI-0023). Sample collection and processing was fu nded by NOAA through the Florida Hurricane Alliance and by the U.S. Environmental Pr otection Agency Gulf Ecology Division Grant No. X7-96465607-0. Acknowledgment of funding does not imply endorsement of results by any of the funding or per mitting agencies. Thank you to the Von Rosenstiels and the Sanibel-Ca ptiva Shell Club for their financial support to the College of Marine Science and myself, making it possible for me to concentrate on my degree and finish quickly. Thanks also to the members of the Reef Indicators L ab, especially Bryan McCloskey and Heidi Souder, for their foraminiferal identification expertise. Melanie Peters and James Locasio accompanied me on my sampl ing trip and helped make the trip run smoothly and on time. The end of my thesis woul d never have been reached without the support of my family and friends. Thank you to everyone who listened over the past two years.

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i TABLE OF CONTENTS LIST OF TABLES iii LIST OF FIGURES v ABSTRACT vii INTRODUCTION 1 Reef Decline in the Florida Keys 1 Patch Reefs in Biscayne National Park 4 Foraminifera 6 Biotic Indicators 7 PROJECT OBJECTIVES 13 METHODS 14 Field Area 14 Sampling Methods 16 Sample Processing 16 SEDCON and FORAM Indices 16 Live Symbiont-bearing Foraminifera (LSF) 18 Data Analysis 18 Statistical Analysis 18 Index Calculations 19 Pattern Analysis 23 RESULTS 25 Grain Size Analysis 25 Environmental Data 27 Foraminiferal Assemblages 29 FORAM Index 45 Sediment Constituent Analysis 48 SEDCON Index 55 Live Symbiont-bearing Foraminifera (LSF) 58 Photic Index 60 FORAM Index v SEDCON Index 62

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ii DISCUSSION 66 Limitations of Study 66 The Offshore Environment 67 Foraminiferal Assemblages 67 Sediment Constituent Assemblages 74 An Index Comparison 76 Live Symbiont-Bearing Foraminifera (LSF) 80 Patch Reef Health 83 Islands v Inlet: Sources of Stress or Security? 86 CONCLUSIONS 89 REFERENCES 91 APENDICES 97 Appendix I Results of grain-size analysis. 98 Appendix II-a List of foraminiferal genera found w ithin the patch reefs of Biscayne National Park 101 Appendix II-b Raw counts of foraminiferal genera i n patch reefs of Biscayne National Park. 102 Appendix III SIMPER results for dissimilarity betw een groups based on foraminiferal assemblages. 118 Appendix IV Moran’s I values and plots for both th e FORAM Index and the SEDCON Index. 124 Appendix V-a Raw counts of sediment constituents. 129 Appendix V-b Visual identification aid for major s ediment constituents 134 Appendix VI SIMPER results for dissimilarity betwe en groups based on LSF assemblages 135 Appendix VII Results of bleaching surveyed in live specimens of Amphistegina gibbosa and density of live symbiontbearing foraminifera 136 Appendix VIII Environmental data and comments from divers and boat captain 137

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iii LIST OF TABLES Table 1 Calculation of the FORAM Index 21 Table 2 Division of grains for sediment constituent analysis. 22 Table 3 Calculation of the SEDCON Index 22 Table 4 Visualization of the Photic Index 23 Table 5 List of common abbreviations used in summar izing results 24 Table 6 Size classifications of sediments and summa ry of median grain size. 25 Table 7 Pearson’s correlation matrix of environment al data 29 Table 8 Within-group similarity of the SIMPER defin ed groups for the foraminiferal assemblage 31 Table 9 Means for diversity, density, and environme ntal data for foraminiferal assemblage SIMPER groups. 35 Table 10 Correlation matrix of foraminiferal taxa 3 9 Table 11 Correlation matrix of foraminiferal taxa a nd environmental data 43 Table 12 Results of BIO-ENV test of correlation bet ween environmental variables and the foraminiferal assemblage. 45 Table 13 Correlation matrix for FORAM Index functio nal groups with environmental variables 48 Table 14 Within-group similarity of the two main SI MPER defined groups for the sediment constituents. 51 Table 15 Means for environmental data for sediment constituent SIMPER groups 51 Table 16 Dissimilarity between the two main groups defined by the SIMPER analysis of sediment constituents 52

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iv Table 17 Correlation matrix for sediment constituen ts 54 Table 18 Correlation matrix for sediment constituen ts and environmental variables 54 Table 19 Results of BIO-ENV test of correlation bet ween environmental variables and the sediment constituents 55 Table 20 Correlation matrix for SEDCON Index functi onal groups with environmental variables 56 Table 21 Within group similarity of SIMPER defined groups for the live symbiont-bearing foraminiferal assemblage 59 Table 22 Means for density, diversity, and environm ental data for LSF assemblage SIMPER groups 60 Table 23 Correlation matrix for foraminiferal taxa and sediment constituents 63 Table 24 One Way ANOVAs for a) SEDCON Index replica tes and b) FORAM Index replicates 66 Table 25 Summary table for percent contribution of foraminiferal taxa to each SIMPER group 69 Table 26 Comparison of three different methods of c alculating the FORAM Index 73 Table 27 Summary of data presented in this report a s rankings 88

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v LIST OF FIGURES Figure 1 Ozone anomaly at 45N 4 Figure 2 South Florida, Biscayne National Park 5 Figure 3 Sampling sites in Biscayne National Park 1 5 Figure 4 Percent mud in sediments from patch reefs of Biscayne National Park 26 Figure 5 Contours of a) salinity and b) temperature data collected during sampling 28 Figure 6 MDS plot of reefs represented by their SIM PER groups defined by similarity of foraminiferal assemblages 30 Figure 7 Sample sites with more than 50 forams repr esented by their foraminiferal assemblage SIMPER groups 35 Figure 8 Contours of FORAM Index values 47 Figure 9 Percentages of sediment constituents for s ites with highest and lowest percentages of unidentifiable grains 49 Figure 10 MDS plot of reefs represented by their SI MPER groups defined by similarity of sediment constituents 50 Figure 11 Contours of SEDCON Index values 57 Figure 12 MDS plot of reefs represented by their SI MPER groups defined by similarity of live symbiont-bearing foraminiferal assemblage 58 Figure 13 Sites represented by their Photic Index r elative value 61 Figure 14 FORAM Index values plotted against median grain size represented by Phi values. 72 Figure 15 FORAM Index values plotted against adjust ed SEDCON Index values 79

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vi Figure 16 Schematic of “Goldilocks” scenario reefs now face 81 Figure 17 Densities of Amphistegina gibbosa plotted against depth 83

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vii PATCH REEFS IN BISCAYNE NATIONAL PARK, FL: SEDIMENTS, FORAMINIFERAL DISTRIBUTIONS AND A COMPAR ISON OF THREE BIOTIC INDICATORS OF REEF HEALTH Alexa Ramirez ABSTRACT Coral cover remains highest on patch reefs at the n orthern end of the Florida reef tract. The reasons for this trend are not well und erstood, but may be related to the protection from extreme variations in water quality parameters provided by the near constant presence of islands at the north extent of the Florida Keys. Three indices have been developed based on Foramini fera and sediment constituents. Two of the indices, the FORAM Index and the SEDCON Index, were developed to indicate the suitability of a reef env ironment for continued reef accretion. The third index, the Photic Index, is an assessment of photic stress on reefs based on incidence of bleaching in a species of Foraminifera Amphistegina gibbosa which is known to experience loss of algal endosymbionts sim ilar to bleaching in corals. Patch reefs were sampled in Biscayne National Park, FL to assess sediment characteristics and foraminiferal assemblages, as w ell as to examine trends in the three indices. Sediments associated with a majority (59% ) of reefs were coarse sands; muddy sediments were restricted to a few inner patch reef s that were isolated from the influence of Caesar’s Creek, which flushes water from inside Biscayne Bay onto the open shelf. Unidentifiable grains predominated in the sediment constituents, along with calcareous

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viii algae and molluskan debris. Shells from 82 genera of Foraminifera were identified in the sediments. Quinqueloculina was the most consistently common genus. Percent m ud was the single most influential measured variable on th e distribution of both sediment constituents and foraminiferal assemblages. Analys is of bleaching in the foraminifer Amphistegina gibbosa revealed that photo-oxidative stress was chronic a t 94% of the sites. Patterns of FORAM and SEDCON Index values and their similarity to temperature, salinity, and percent mud distribution s show that Caesar’s Creek is affecting the benthic community in its immediate vicinity by providing flow that limits the accumulation of mud and potentially other anthropog enic stressors. Overall this study suggests that the reefs in this area are marginal f or continued reef growth. A more detailed study of water quality through Caesar’s Cr eek should be conducted to determine exactly how it is affecting the reefs in Biscayne N ational Park.

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1 INTRODUCTION Reef Decline in the Florida Keys Coral reefs worldwide are in a state of decline. R eefs are of immense economic importance to the human populations around them. T hey absorb wave energy, protecting islands and coastal areas from erosion and storm su rge; they are a key source of jobs in tourism and fisheries; and they potentially harbor cures for many diseases (Lidz 1997, Reaser et al. 2000). Corals are not only biologica lly important in nutrient-poor waters; they also provide the substrate upon which much of the community around them is based (Hallock et al. 2006). The Florida reef tract is n o exception to the aforementioned benefits. In 1996, stony coral cover on the Florida Keys’ ree fs was estimated at 11.9 percent. As of 2004, coral cover had declined to 6 .6%, with patch reefs having the highest at 16% (Beaver et al. 2005). The industrie s that depend on the reefs may be contributors to this decline, along with the genera l urbanization of Miami and the Keys (LaPointe and Clark 1992, Porter and Meier 1992, Li dz 1997). Many factors have contributed to the loss of coral cover, complicating the task of understanding and managing coral-reef ecosystems. One result of developed coastlines is often an increase in sedimentation to the offshore environment. While the reefs in Biscayne National Park are relatively removed from direct influences of coastal sedimentation, their proximity to heavily used boat channels (Hawk Channel and

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2 Caesar’s Creek) may leave them susceptible to sedim entation as a result of resuspension. Within Biscayne Bay, sedimentation rates have been measured to be 50-100mg cm-2 day-1 (Lirman et al. 2003). Lirman also measured higher rates of sedimentation in the vicinity of Caesar’s Creek, a very active boating channel. Frequently associated with sedimentation as a resul t of coastal runoff are excess nutrients from agricultural and suburban fertilizer s, as well as from human waste. This is especially important in areas similar to Biscayne N ational Park that are in close proximity to major urban areas (i.e., Miami). Carnahan et al (2008) found evidence of elevated levels of certain heavy metals in the mud fractions of sediments collected throughout Biscayne Bay. In southern Biscayne Bay she noted a n area of “remarkably high toxicity” that could not be explained through her study. Bec ause of the high potential for sediment resuspension as a result of currents, hurricanes, a nd boat traffic in Biscayne National Park, sediments cannot be considered a permanent si nk for contaminants. Resuspended sediments may also be an indirect source of polluti on and stress in impacted marine environments (Latimer et al. 1999, Lirman et al. 20 03). Turbid, nutrient-rich waters are not suitable habit at for mixotrophic organisms like corals (i.e., that host algal endosymbionts), which historically thrived in clear, oligotrophic environments. Elevated nutrient expos ure can have direct effects on a coral such as increased symbiont densities that result in slower growth rates as a result of competition for CO2 and/or carbonate between photosynthesis and calcif ication (Szmant 2002). Indirect effects include increased biomass of fleshy algae that may over grow and smother corals (Szmant 2002). In this way, nutrien t loading tends to favor growth of macroalgae over hermatypic corals (Hallock et al. 1 993). The end result is a community

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3 phase shift from stony coral-dominated reefs to com munites dominated by soft coral, sponges, and algae (Hallock et al. 1993; Dustan 199 9). In addition to local anthropogenic stressors, globa l stressors such as increased sea surface temperatures and ozone depletion have led t o higher frequencies and intensities of coral bleaching that are detrimental to coral reefs (Hoegh-Guldberg 1999). Bleaching is a natural response to stress in corals that can occur for several reasons including sedimentation, temperature extremes, and solar radi ation (Talge and Hallock 2003, Hallock et al. 2006). Beaver et al. (2005) recorde d an eight-year decline in stony coral cover in the Florida reef tract from 1996 to 2004. Of the eight years the only period of significant coral-cover decline occurred between 19 97 and 1999. This coincided with a world-wide bleaching event in 1998 as a result of w armer-than-normal sea surface temperatures (at least 1C higher than the summer m aximum) due to an El Nio Southern Oscillation perturbation (Hoegh-Guldberg 1999). Bleaching may also occur as a result of increased s olar radiation caused by ozone depletion. Since the 1970’s, measurements of strat ospheric ozone have shown a trend of decreasing ozone at mid to high latitudes (Randel e t al. 1999). The ozone anomaly from the long-term mean at 45 N latitude is currently a bout -6% per decade (Randel et al. 1999, Hallock et al. 2006). Addition of anthropoge nic chlorine is thought to be a main cause leading to the destruction of the ozone (Moli na and Rowland 1974). Large-scale volcanic eruptions (like that of Mt. Pinatubo in 19 91) can amplify the effects of increased atmospheric chlorine through the injection of SO2 into the stratosphere, which then reacts to create more reactive chlorine compounds (Fig. 1) (Roscoe 2001).

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4 Figure 1. Ozone anomaly at 45 N. Two major volcan ic events are noted to illustrate the effect on ozone depletion (modified from Roscoe 200 1). For every 1% decrease in ozone then, the levels of UV-B reaching the sea surface increases by 2% (Shick et al. 1996). This implies that the 10-15% decrease in stratospheric ozone that has occurred since the 196 0’s has resulted in a 20-30% increase in UV-B reaching the oceans at Florida Keys latitud es (Hallock et al. 2006). While the aforementioned stressors hardly begin to encompass the spectrum of factors resulting in the degradation of reefs, they do play an important role. This is especially true near the highly urbanized areas of Miami and Key Largo. Patch Reefs in Biscayne National Park Patch reefs range from isolated coral heads a few m eters wide to topographic features hundreds of meters in diameter. They are found between the mainland and bank or barrier reefs and are usually surrounded by halo s of bare sand (Shinn et al. 1989, Brock et al. 2004). Because sea level limits the v ertical growth of patch reefs, they typically occupy a range from 2 to 9m of water dept h (Marszalek et al. 1977). In theory,

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5 patch reefs should be most susceptible to anthropog enic effects due to their proximity (37 km) to shore (Ginsburg et al. 2001, Brock et al. 2004). The most concentrated area of patch reefs on the Fl orida reef tract is within the boundaries of Biscayne National Park (BNP) at the n orthern extent of the Florida reef tract (Fig. 2). The near continuous presence of El liot Key and Old Rhodes Key act as a buffer between the confined waters of Biscayne Bay and the open marine environment, thereby protecting the patch and bank reefs from na tural variations in temperature and salinity, as well as anthropogenic pollutants (Gins berg and Shinn 1993). Seaward of Elliot Key approximately 4000 patch reefs have been identified using aerial photography (Marszalek et al. 1977). Extreme water-quality var iations and the presence of tidally influenced mobile sands have limited reef growth no rth of Elliot Key (Ginsberg and Shinn 1993, Lidz 1997). The physical barrier provi ded by the Keys are a likely reason that patch reef coral cover in Biscayne National Pa rk is relatively high and that patch reefs account for some of the healthiest reefs left in South Florida (Beaver et al. 2005). Figure 2. South Florida; Biscayne National Park boundary shown in gray.

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6 Foraminifera The Foraminifera are a class of small shelled prot ists that exist in nearly all coastal and marine environments (SenGupta 1999). O ne informal group, known as larger benthic foraminifers, has evolved symbiotic relatio nships with algae analogous to those in corals (Lee and Anderson 1991, Hallock 1999). T he success of symbiont-bearing foraminifers is highly dependent on nutrient flux, especially nitrogen. The holobiont (host plus symbionts) functions optimally when the algal symbionts are deprived of nitrogen. When light is available, the symbionts p roduce large amounts of simple sugars during photosynthesis, which are translocated for u se by the host foraminifer. Therefore, food captured by the foraminifer can be used primar ily for growth and reproduction. However, in the presence of excess fixed nitrogen, the symbionts are able to grow and reproduce, potentially causing harm to the foramini feral host (Hallock 1999). More importantly, smaller foraminifers are able to out-c ompete the larger symbiont-bearing foraminifers for space and microalgae are able to o ver-grow the slower growing foraminifers (Cockey et al. 1996, Fujita and Halloc k 1999, Hallock 1999). Increasing human populations have also increased t he amount of nitrogen reaching coastal areas, resulting in either nutrifi cation or eutrophication. Human activities, including burning of fossil fuels and c hanges in land use world-wide, have caused an increase in atmospheric CO2 (Houghton et al. 2001), which increases ocean acidity and promotes dissolution of CaCO3 found in both coral skeletons and foraminiferal shells (Kleypas et al. 2006). Both s cenarios have produced changes in the benthic communities of tropical to subtropical wate rs where symbiont-bearing organisms have adapted to oligotrophic environments (Cockey e t al. 1996, Hallock 1999, Hallock et

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7 al. 2003). Along the Florida reef tract over the p ast 30 years, foraminiferal assemblages have shifted from dominance of symbiont-bearing tax a to smaller heterotrophic taxa (Cockey et al. 1996), which has occurred in conjunc tion with coral-cover decline (Porter and Meier 1992, Dustan 1999). In addition to the shift in assemblage composition other changes have been documented in the foraminiferal community. Beginni ng in June 1991, the foraminifer Amphistegina gibbosa experienced a population-wide bleaching event in t he Florida Keys. By 1992, population densities of A. gibbosa at depths to 20m decreased to less than 5% of densities from the previous year (Halloc k and Talge 1993). The onset of this bleaching event coincided with stratospheric ozone depletion following eruptions of Mt Pinatubo in the Philippines in May and June of 1991 (Hallock et al. 1995). Subsequent studies have shown foraminiferal bleaching to corre spond closely to the summer solstice, with populations beginning to recover by late summe r when temperatures peak (Hallock and Talge 1993; Williams and Hallock 2004, Hallock et al. 2006). Some coral bleaching was also present on the reefs where the bleached fo raminifers were observed (Hallock and Talge 1993). By 1992, bleaching in Amphistegina spp. was observed on reefs from Australia to Hawaii and Jamaica (Hallock et al. 200 6). These observations reveal the potential importance of symbiont-bearing foraminife ra to predict when photo-oxidative stress may impact the overall health of reef enviro nments (Hallock 2000a, Hallock et al. 2006). Biotic Indicators Water samples are often taken to assess the water q uality of the reef environment. However, the results can often be misleading as exc ess nutrients are quickly taken up by

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8 biological systems (Laws and Redalje 1979). While water samples may indicate normal nutrient concentrations, the effect of increased nu trient flux into an ecosystem typically results in a community change (e.g., Hallock 1988) known as a phase shift (Done 1992; McManus and Polsenberg 2004). By the time a water sample indicates a change in nutrients, the community has long been impacted (Ha llock and Schlager 1986, Hallock et al. 1993, Hallock et al. 2006). Symbiont-bearing benthic foraminifera require simil ar water-quality parameters as corals and are typically abundant on healthy cor al reefs. Because of their relatively short life cycles and sensitivity to environmental conditions, the foraminiferal community can respond more quickly than corals to changes in water quality (Hallock 2000b, Hallock et al. 2003). Foraminifers can be quickly and inexpensively collected to provide a statistically significant analysis of chronic ree f stress (Hallock et al. 2003). As a consequence, two indices have been developed t o relate the response of the calcifying benthic community to the status and suit ability of the environment for future reef growth. The FORAM Index (Hallock et al. 2003) and SEDCON Index (Daniels 2005) were developed separately and each approaches the foraminifer-coral relationship from a slightly different perspective. Based on observations of coral-reef communities, in cluding foraminiferal assemblages and sediment constituents, under a wide range of natural (e.g., Hallock 1987, 1988) and anthropogenic (e.g., Hallock et al. 1993, Cockey et al. 1996) nutrient fluxes, Hallock (1995, 2000b, Hallock et al. 2003) proposed that foraminiferal assemblages and reef sediment constituents could pr ovide low cost indicators of the potential for the environment to support mixotrophi c, calcifying organisms (i.e., corals

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9 and foraminifers dependant on algal symbiosis). Mo reover, sediment constituents might further provide a relative indicator of bioerosion rates. Bioerosional processes are major determinants of whether a reef is accreting or erod ing. A common scenario occurring along with and as a res ult of reef decline is the failure of reef communities to recover after a dist urbance (e.g., hurricanes, bleaching or disease outbreaks, and ship groundings), which resu lts in the decimation of large coral colonies decades to hundreds of years old. Because large coral colonies can persist in conditions where coral larvae cannot recruit and th erefore cannot replace previous colonies, the question arose: “How can scientists a nd resource managers predict if the environment can support continued coral dominance, including recovery following a catastrophic mortality event?” The FORAM (Foraminifera in Reef Assessment and Moni toring) Index (FI) focuses on assemblage changes within foraminiferal populations as reflected in reef sediments. The short lifespan and large numbers of foraminifers within an assemblage allows for a differentiation between chronic reef d ecline and acute mortality events (Cockey et al. 1996, Hallock et al. 2003). The bas ic underlying observation for this index is that sediments on healthy reefs have a larger pr oportion of shells of symbiont-bearing foraminifers compared to other smaller foraminifers and stress-tolerant foraminifers (Hallock 1988, Hallock et al. 2003). The presence of excess nutrients allows smaller heterotrophic foraminifers to bloom which causes th eir shells to dominate over the larger taxa (Cockey et al. 1996). In the calculation of t he FORAM Index, a value of 2 would result from the presence of 100% other smaller fora minifers, indicating heterotrophic processes dominate on the reef. To increase the FI value from 2, some symbiont-bearing

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10 species must be present. In an environment that su pports abundant calcifying mixotrophs, at least 25% of the foraminiferal assem blage are likely to be symbiontbearing taxa, resulting in an FI value greater than 4. The presence of stress-tolerant taxa in a sample results in a lowering of the FI value ( Hallock et al. 2003, Carnahan et al. submitted ). As such, a differentiation between coral declin e due to local nutrification or episodic events, like hurricanes or temperature ext remes, is possible using the FORAM Index. If chronic nutrification is present, as ind icated by the foraminiferal assemblage, coral reefs will likely be unable to recover from a nd continue to decline after a short term stress event (Hallock et al. 2003). The SEDCON (Sediment Constituent) Index also uses r eef sediment composition to assess the integrity of the reef system in the v icinity of the sample site (Daniels 2005). As previously noted, nutrification causes a phase s hift in benthic community composition (LaPointe and Clark 1992; Porter and Meier 1992, Do ne 1992, McManus and Polsenberg 2004). In a reef environment, evidence for this sh ift should be observable in the carbonate-sediment composition (Hallock 1988). For aminifers are an important contributor to reef sediments, especially larger, s ymbiont-bearing foraminifers (Cockey et al. 1996). Hallock (1988) noted that shells of lar ge foraminifers, along with physically eroded, identifiable coral fragments, are character istic in oligotrophic waters conducive to reef accretion. Meanwhile, the presence of smaller foraminiferal tests, unidentifiable carbonate grains, and calcareous algal fragments ar e indications of higher nutrient flux to the system (Hallock 1988, 2000b; Cockey et al. 1996 ). The potential for reef recovery following an acute event is dependent on water qual ity and rates of bioerosion (Hallock et al. 2006). Both of these should be reflected in th e composition of sediments.

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11 The FORAM and SEDCON indices are based upon constit uents in the sediments which accumulate over weeks to years and therefore these indices represent conditions on time frames of months to years. A third index, based on the abundance and condition of populations of Amphistegina spp ., has been proposed (Hallock 1995, Hallock et al. 2004), but not yet fully developed. Amphistegina spp are abundant and nearly ubiquitous members of the benthic biota on coral reefs and warm water carbona te shelves world-wide. The two most common species, A. gibbosa in the Western Atlantic and A. lessonii in the IndoPacific, are very similar in habitat and habitat re quirements (Hallock et al. 1986, 2004; Hallock 1999). In 1991, Amphistegina gibbosa were first observed to be experiencing bleaching in the Florida Keys (Hallock et al. 1995) However, foraminiferal bleaching precedes coral bleaching as they respond quickly to photo-oxidative stress that occurs during maximum solar radiation, rather than at maxi mum sea-surface temperatures (Hallock et al. 2006). Since 1991, A. gibbosa populations have been monitored for size, symbiont loss (bleaching), and shell condition (Hal lock et al. 1995, Williams et al. 1997, Hallock 2000a, Fisher 2007). Williams (2002) repor ted that during periods of acute photic stress there was a correlation with low popu lation densities and large specimen diameters, indicating suppressed reproduction. Con versely, when photic stress was absent or chronic, population densities increased a nd mean diameter decreased (Williams et al. 1997, Williams 2002). The proposed index, variously referred to as Amphistegina Photic Index or the Amphi Index, requires examination of Amphistegina specimens collected live and would utilize both log-normalized abundance of Amphistegina (e.g., Hallock 1995) and degree

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12 of bleaching (absent, chronic, or acute). Because r esponse to increased radiation occurs over periods of days to weeks, this index could pro vide an assessment of environmental conditions over shorter time periods of weeks to mo nths as opposed to the annual or inter-annual time scales of the FORAM and SEDCON in dices. The potential benefit of these three indices is the ease with which they can be applied and that they do not require touching or di srupting the actual reef. A simple collection of reef rubble or a small sediment sampl e is all that is necessary and can easily be incorporated into a preexisting monitoring progr am (Hallock et al. 2003). In many cases, sediments are routinely collected for grain size or chemical analysis. Sample processing for each index is kept as simple as poss ible in order to make them economically viable options for reef-monitoring pro grams throughout the world. A stereomicroscope and a technician trained in identi fication are the main necessities (Hallock et al. 2003, Daniels 2005).

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13 PROJECT OBJECTIVES The first goal of this project was to describe and characterize sediments and rubble samples at selected patch reefs in Biscayne National Park with respect to: grain size distribution total foraminiferal assemblages sediment constituents abundance of Amphistegina gibbosa and other live symbiont-bearing foraminifera and the presence and prevalence of bleaching in A. gibbosa The second goal of this project was to characterize spatial variability in the above parameters and compare them with selected measured environmental parameters. The final goal was to test the three indices (FORAM SEDCON, and Photic) on the BNP patch reefs to determine if they are compar able and useful in characterizing the patch reefs.

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14 METHODS Field Area Sampling for this project was conducted in Biscayne National Park seaward of Elliot Key. This area is affected by water emerging from Biscayne Bay in two areas: the main pass (also known as the Safety Valve), north of Ell iot Key, and Caesar’s Creek between Elliot Key and Old Rhode’s Key (Wang et al. 2003). USGS-LIDAR data and Landsat imagery were used to determine sampling sites (Fig. 3). A total of 32 reefs along ten roughly east-west transects were sampled, including 30 patch reefs and two bank-barrier reefs (Pacific and Lugano). Individual reefs were chosen to conform as much as possible to linear transects and were identified by the char acteristic sand halos. Several sites correspond to named reefs where past reef assessmen ts have been conducted (Nirvana, Bug Reefs [Ginsburg et al. 2001] and Dome, Star, El khorn [Jaap and Wheaton 1977, Dupont et al. in press ]) and/or buoyed reefs marked by Biscayne National Park. Elliot Key

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15 Figure 3. Sampling sites in Biscayne National Park

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16 Sampling Methods Sampling was conducted in early May 2007. At each reef, the following samples or environmental data were collected by SCUBA divers: three replicates of ~3 pieces of coral rubble in a p lastic Ziploc bag (for the Photic Index) three replicates of ~15cm3 of sediment in plastic vials (for the FORAM and SEDCON Indices) depth, dissolved oxygen, temperature, salinity, and pH Sediment samples were stored in a -40 C freezer until processed (Hallock et al. 2003, Daniels 2005). During collection, reef rubbl e samples were kept in a shaded area of the boat until they were able to be scrubbed wit h a soft toothbrush to remove sediment, algae, and attached fauna. The resulting mix of se diment and seawater was stored in 1liter, wide-mouth containers for transport to the l aboratory. In the laboratory, excess water was poured out of t he containers and the sediment was distributed into large Petri dishes and covered with fresh seawater, and then maintained in a culture chamber set on a 12-hour li ght/dark cycle at 25 C until assessed. Further sampling details can be found in Williams e t al. (1997) and Hallock et al. (2006). Sample Processing SEDCON and FORAM Indices Each sediment sample was washed with deionized wate r over a 63 m m sieve into 100 ml beakers to separate the mud from the sand-si zed fraction of the sample. Weights for the empty beakers were recorded prior to sievin g so the dry weight of each sample

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17 could be determined. All were placed in a 60 C drying oven until dry. After gently but thoroughly mixing the dried sample, a 1-gram sub-sa mple was taken for the FORAM Index analysis. Depending upon the grain size of th e sample, a small scoop (~0.1g) was weighed, sprinkled over a gridded tray, and observe d under a stereomicroscope (Hallock et al. 2003). A very fine artist’s brush (size 5/0), moistened wi th water, was used to pick foraminiferal specimens from the tray and place the m on a micropaleontological faunal slide coated in water-soluble glue. Additional por tions of the 1-gram sub-sample were picked until a sample size of approximately 150-200 specimens was reached or the entire 1-gram sample was analyzed. A sample of this size has been shown to be a statistically similar to a sample size of 300 while also conservi ng processing time (Dix 2001, Hallock et al. 2003). Each foraminifer was identified to t he genus level to minimize inconsistencies in species identification. Test de formities among the specimens were also noted. The remaining portion of the dried sediment was use d for grain-size analysis (Folk 1974) and the SEDCON Index (Daniels 2005). G rain-size analysis was conducted by sorting sediment samples through a set of sieves on a shaker table at medium strength for 10 minutes. Percent weights of each of the foll owing size fractions were determined: > 2mm (-1 ), 1-2 mm (0 ), 0.5-1 mm (1 ), 0.25-0.50 mm (2 ), 0.125-0.250mm (3 ), 63 m-0.125 mm (4 ), < 63 m (>4 ). For the sediment constituent analysis, the size fraction of 0.5-2mm was recombined for examination. Using this size fraction reduces errors of misidentification (Daniels 2005). A 1-gr am sub-sample was sprinkled onto a

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18 gridded tray; 300 calcareous grains were selected u sing a point-count method and transferred to a micropaleontological slide (as in the FORAM procedure) and identified. Live Symbiont-bearing Foraminifera (LSF) All Amphistegina gibbosa specimens were picked using forceps from the Petri dishes stored in the culture chambers. Live indivi duals were determined by color and pseudopodial activity and were then counted, measur ed (maximum diameter to the nearest 50m), and characterized. Symbiont color was noted as normal, partly bleached (less than 50% loss of symbiont color), or bleached (more than 50% loss of symbiont color). Other physical abnormalities, such as brea kage, were noted (Williams et al. 1997, Hallock et al. 2006). The rubble, from which the sediment slurry was scru bbed, was photographed over gridded paper with centimeter squares. The photogr aphs were analyzed to determine surface area using Coral Point Count with Excel Ext ensions. The surface areas were used to calculate densities of live foraminifers per 100 cm2. Data Analysis Statistical Analysis After the raw data were collected and recorded, the assemblage data were standardized and square-root transformed to create cluster analyses and MDS (multidimensional scaling) plots using the statistical pa ckage PRIMER v6 (Plymouth Routines In Multivariate Ecological Research, 2006). This de termined how the samples clustered (Q-mode analysis) as well as how the variables (for aminiferal genera) clustered (R-mode analysis). Square-root transformations were carrie d out on the assemblage data to down

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19 weigh the presence of highly abundant taxa/sediment constituents. Two-dimensional MDS plots were used in this analysis, which showed similarity between sites based on a Bray-Curtis similarity matrix. For an MDS plot, th e proximity between sites represented similarity and a stress level of 0.2 was considered to be a useful representation o f relationships (Clarke and Warwick 2001). The same process was carried out for R-mode analysis to define groupings of taxa. To enhance the interpretation of the MDS plots, the SIMPER (similarity percentages) routine was also performed in PRIMER. This analysis identified clustering of samples and also the taxa or sediment constituen ts that contributed to the similarity within a group and the dissimilarity between groups This analysis is especially useful when the stress level of an MDS plot is high becaus e it represents group structure based on the actual similarity matrix, not the MDS repres entation (Clarke and Gorley 2006). Another procedure included in PRIMER is known as BI O-ENV. This procedure was used to determine relationships between environ mental data (temperature, salinity, dissolved oxygen, and pH) and the assemblage data, and was used to detect which environmental parameters matched variation in assem blage data between sites. Pearson’s correlation matrices were also created us ing Statistica 8.0 (2007) statistical software to further aid the interpretat ion of the data. Index Calculations Foraminifers identified to genus for the FORAM Inde x (FI) were separated into three functional groups: larger symbiont-bearing fo raminifers, stress-tolerant taxa, and other smaller foraminifers. The percent abundance of each of these groups was used to calculate the FORAM Index (Hallock et al. 2003) (Ta ble 1). An FI value greater than 4

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20 indicates environments suitable for reef growth. A n FI value between 2 and 4 indicates marginal reef environments that may not be able to recover from a stress event. Below 2, the environmental condition is poor and unsuitable for reef growth (Hallock et al. 2003). Similarly, the 300 grains of sediment previously id entified were grouped into four functional groups for the SEDCON Index (SI) (Table 2). The percent abundances of the functional groups were used to calculate an index v alue (Daniels 2005) (Table 3). Several texts were used to aid in the identificatio n of sediment constituents (e.g., Bathurst 1976; Scoffin 1987). This index is a modified versi on of the FORAM Index to include the range of sediments in addition to foraminiferal tests. Like the FORAM Index, lower values indicate declining potential for reef accret ion. The third index, the Photic Index, is based on the density of Amphistegina and the percent experiencing bleaching in a sample (Table 4 ). Density of Amphistegina like the FI and the SI, should reflect the suitability of th e habitat for mixotrophic, calcifying organisms, though on a scale of weeks to months rat her than months to years. The incidence and intensity of bleaching relates only t o photic stress on time scales of days to weeks and therefore can’t be directly compared to t he sediment-based indices.

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21 Table 1. Calculation of the FORAM Index FI = (10*Ps)+(Po)+(2*Ph) Where, Ps= Ns/T Po= No/T Ph= Nh/T T = total number of specimens counted Ns= number of symbiont-bearing Foraminifera No=number of stress-tolerant Foraminifera* And, Nh= number of other small, heterotrophic Foraminifera “Opportunistic” as defined by Hallock et al. 2003 is changed to “stress-tolerant” in this paper (Yanko et al. 1999, Carnahan 2005, Carnahan e t al. submitted ).

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22 Table 2. Division of grains for sediment constituen t analysis modified from Daniels (2005); exemplary photos of major sediment constitu ents can be found in Appendix V-b SI functional group Sediment grain Community Role/ Feeding mode Interpretation Pc Scleractinian Coral Primary reef builder, mixotrophic Area suitable for calcification by algal symbiosis Pf Larger, symbiont-bearing foraminifers Sediment producer, mixotrophic Area suitable for calcification by algal symbiosis Coralline algae Framework builder, autotrophic Varies with other components Calcareous algae Sediment producers, autotrophic Nutrient signal, high CaCo3 saturation Molluscs Grazers/predators, heterotrophic Food resources plentiful, nutrient signal Echinoid Spines Bioeroders/grazers, heterotrophic Bioerosion, nutrient signal Worm Tubes Heterotrophic Abundant food resources Pah Other (smaller foraminifers, bryozoans, fecal pellets, etc) Sediment producers, heterotrophic Abundant food resources Pu Unidentifiable Bioerosion proxy Bioerosion proxy Table 3. Calculation of the SEDCON Index (Daniels 2 005) SI = (10*Pc)+(8*Pf)+(2*Pah)+(0.1*Pu) Where, Pc= Nc/T Pf= Nf/T Pah= Nah/T Pu=Nu/T T = toal number of grains counted (300) Nc= number of coral grains Nf=number of symbiont-bearing Foraminifera Nah=number of coralline algae, calcareo us algae, and heterotrophic skeletal grains And, Nu= number of unidentifiable grains

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23 Table 4. Matrix describing the proposed Photic Inde x. Pattern Analysis Spatial patterns between the two sediment-based in dices were compared based on their actual index values and also on the distribut ion of their SIMPER groupings. The Kriging method of interpolation was used in Surfer v8.05, surface mapping system (Golden Software 2004), to create contours of SEDCO N Index values and FORAM Index values. In addition, contours were created f or several of the measured waterquality parameters (salinity, temperature, % mud, e tc.). Maps were produced using ArcMap v9.2 (ESRI 2006). GeoDA 0.9.5-i, geostatistical analysis software (An selin et al. 2006), was used to determine if there was spatial autocorrelation and multivariate spatial correlation within

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24 and between each of the parameters and to what exte nt the correlations were significant. To do this, Moran’s I was calculated. This procedu re was similar to calculating a Pearson’s correlation except that a point’s value w as compared to a weighted average of its neighboring points’ values, such that there was spatial autocorrelation if a point was surrounded by points with similar values and furthe r from points with a large difference in value. This provided a spatial analysis of rela tionships between the calculated indices and the water-quality parameters to support the BIO -ENV procedure. Table 5. List of common abbreviations used in summa rizing the results. Abbreviation Definition BNP Biscayne National Park FI FORAM Index SI SEDCON Index PI Photic Index DO Dissolved Oxygen LSF Live Symbiont-bearing Foraminifera Density # of foraminiferal shells per gram of sediment Genera # of genera

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25 RESULTS Grain-Size Analysis Grain size was calculated as a weight-percent dist ribution as defined by the Wentworth scale (Table 6). Median grain size was c alculated for samples from each reef site and a median Phi size class was determined. A t the majority of reef sites (59%), sediments had a median Phi size of 1 (coarse sand). This size class, along with very coarse sand (accounting for 19% of sites), represen ted the range of sediment analyzed for the SEDCON Index. Of the samples from the remainin g sites, 16% had a median Phi of 2 (medium sand) and 6.3% had a median Phi of 3 (fin e sand) (Appendix I). Table 6. Size classifications of sediments and sum mary of median grain size. Size Description Size range Phi ( F ) size class # of sites with median grain size Gravel/Granule >2mm -1 0 Very coarse sand 1-2mm 0 6 Coarse sand 0.5-1mm 1 19 Medium sand 0.25-0.5mm 2 5 Fine sand 0.125-0.25mm 3 2 Very fine sand 63um-0.125mm 4 0 Silt/clay/mud <63um >4 0 Samples from five sites (16%) contained more than 10% mud, with the highest percentage of mud being 33% at Bug Reef. Contours of percent mud throughout the sampling area are illustrated in Figure 4.

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26 Figure 4. Percent mud in sediments from patch reefs of Biscayne National Park

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27 Environmental Data Temperature, salinity, dissolved oxygen (DO), and p H were measured at each site during sample collection. Temperature varied only slightly with less than a 2C range, while salinity varied less than 1‰. However, both temperature and salinity showed evidence of a spatial pattern (Fig. 5) with signifi cant (p<0.01) Moran’s I values (0.31 and 0.27 respectively). The two patterns also negative ly correlated with each other, which can be seen in the Pearson’s correlation matrix con structed for relationships between environmental parameters (Table 7). This is also s upported by a significant bivariate Moran’s I (-0.33). Since DO and pH had insignifica nt spatial autocorrelation, these parameters were excluded from further analysis beca use individually these parameters cannot effect spatial distribution of reefs if ther e is no pattern to their values. Salinity contours have an inshore-offshore trend, m eaning salinity decreased offshore. Off the mouth of Caesar’s Creek, a ‘bump ’ in the salinity contours indicated a tongue of lower salinity waters (Fig. 5a). The tem perature contours also showed an inshore-offshore trend, warming offshore. Further, the temperature contours also displayed a “bump’ similar to salinity in that warm er waters were in the same area that the lower salinity waters were located (Fig. 5b). Both temperature and salinity significantly correlated with percent mud and densi ty of forams, while salinity negatively correlated with depth.

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28 a) b) Figure 5. Contours of a) salinity and b) temperatur e data collected during sampling

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29 Table 7. Pearson’s correlation coefficients between environmental data (abbreviations as in Table 5) ( Bold indicates significance at p<0.05) FISI% MudDepthLSFPhiDensityGeneraTemperatureSalinit y FI1.00SI -0.53 1.00 % Mud -0.620.66 1.00 Depth0.06-0.25-0.291.00LSF0.16-0.19-0.24-0.181.00Phi -0.400.420.73 -0.15-0.071.00 Density -0.550.600.79 -0.17 -0.320.69 1.00 Genera -0.640.37 0.240.11-0.010.09 0.32 1.00 Temperature 0.33-0.61-0.42 0.14-0.09 -0.42-0.46 -0.121.00 Salinity -0.470.460.53-0.45 0.28 0.430.35 0.26 -0.48 1.00 Foraminiferal Assemblages Among the 32 reefs, a total of 82 genera of Foramin ifera were identified. The raw data for these analyses, including counts and d ensity, can be found in Appendix II. In Table 7, density (# of foraminiferal shells per gram of sediment) and genera (# of genera found at each site) were included as environ mental data as they gave a very general view of the foraminiferal assemblage. Note that the two variables had a significant positive correlation. The cluster and SIMPER analyses were run only on th ose foraminiferal assemblages where more than 50 specimens were prese nt in a gram of sample. Replicates were analyzed separately so that out of 64 possible samples, 44 remained after removing those samples that did not contain sufficient speci mens. The resulting analysis showed that sites clustered into five major groups (A, B, C, D, E). Each group had a within group similarity higher than 59% based on the SIMPER resu lts. Figure 6 is the MDS plot of the foraminiferal assem blage data symbolized by their SIMPER groups. Because the SIMPER groups gen erally match the clustering of the

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30 MDS plot (stress value = 0.18), this is a viable re presentation of similarity between sites. Table 8 is the SIMPER output showing the average wi thin group similarity, the percent that each genus contributes to the group’s similari ty, and which FORAM Index functional group each genus belongs to. SIMPER-gen erated dissimilarity tables between groups can be found in Appendix III. Environmental data were averaged among sites within a group and are reported in Table 9. Group A consists of six sites with a similarity of 68%. These sites dominate the area most immediately affected by Caesar’s Creek an d also the upper and lower most edges of the sampling area (Fig. 7). Other smaller foraminifers make up about 50% of the contribution while symbiont-bearing taxa accoun t for approximately 35%. Only one stress-tolerant genus is present in this group’s co ntributing taxa ( Elphidium ). Group A sites are characterized as having very little mud, low densities of foraminifers, and the lowest diversity, with the second highest average F I value. Group B was the biggest cluster with nine sites hav ing both replicates within it. This group represented the most intermediate of sit es with all environmental parameters being right in the middle of their ranges and all r eplicates having a similarity of 67%. It had a slightly higher contribution by stress-tolera nt taxa ( Elphidium, Bolivina and Ammonia ) as well as a higher contribution of other smaller foraminifers, and fewer symbiont-bearing Foraminifera. Because group B rep resented the most intermediate group, any site that had one replicate in group B a nd one replicate in another group was graphically displayed as the other group to represe nt the transition away from intermediate. These sites included 2.1, 2.2, 3.1, 9 .1, 9.2, and 9.3.

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31 Figure 6. MDS plot of reefs represented by their SI MPER groups defined by similarity of foraminiferal assemblages. Table 8. Within-group similarity of the SIMPER-defi ned groups for the foraminiferal assemblage. (*FI group refers to FORAM Index functi onal group where SB-symbiontbearing, ST-stress-tolerant, and HT-heterotrophic) Group A n=9 Average simil arity: 68% Genus FI group* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina HT 4.08 9.64 8.49 14.2 14.2 Archaias SB 4.25 9.57 3.29 14.1 28.2 Discorbis HT 3.63 8.33 5.87 12.2 40.5 Laevipeneroplis SB 2.87 6.22 4.22 9.14 49.6 Triloculina HT 2.63 5.43 3.69 7.98 57.6 Siphonaperta HT 2.54 5.01 2.97 7.36 64.9 Rosalina HT 1.87 4.25 6.6 6.24 71.2 Elphidium ST 1.62 3.57 4.89 5.24 76.4 Amphistegina SB 1.68 3.33 3.44 4.89 81.3 Cyclorbiculina SB 1.49 3.12 3.32 4.58 85.9 Textularia HT 1.27 2.21 1.56 3.24 89.1 Asterigerina SB 0.85 1.41 1.13 2.07 91.2 A D E C B

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32 Table 8. (Continued) Group B n=24 Average simil arity: 67% Genus FI group* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina HT 5.36 10.8 9.94 16.1 16.1 Triloculina HT 3.09 6.02 5.81 8.95 25.0 Laevipeneroplis SB 2.99 5.72 6.33 8.51 33.5 Rosalina HT 2.51 4.71 5.63 7.01 40.6 Archaias SB 2.05 3.58 3.44 5.33 45.9 Siphonaperta HT 1.81 3.25 3.3 4.83 50.7 Discorbis HT 1.81 3.09 2.4 4.6 55.3 Elphidium ST 1.35 1.98 1.6 2.95 58.3 Amphistegina SB 1.22 1.96 1.94 2.92 61.2 Cycloforina HT 1.18 1.94 1.92 2.88 64.1 Triloculinella HT 1.1 1.78 1.65 2.65 66.7 Textularia HT 1.3 1.73 1.3 2.57 69.3 Miliolinella HT 1.04 1.51 1.32 2.25 71.5 Articulina HT 1.01 1.45 1.33 2.15 73.7 Peneroplis SB 0.95 1.4 1.37 2.09 75.8 Bolivina ST 1.05 1.3 1 1.93 77.7 Broekina SB 1.02 1.29 1.01 1.91 79.6 Haynesina ST 0.97 1.22 0.92 1.82 81.4 Spiroloculina HT 0.83 1.21 1.22 1.8 83.2 Ammonia ST 0.74 0.89 0.94 1.33 84.6 Hauerina HT 0.7 0.85 0.86 1.26 85.8 Adelosina HT 0.66 0.75 0.77 1.11 86.9 Cribroelphidium ST 0.69 0.73 0.68 1.09 88.0 Cyclorbiculina SB 0.66 0.69 0.75 1.03 89.0 Nonionoides ST 0.56 0.62 0.77 0.91 90.0 Asterigerina SB 0.65 0.6 0.6 0.89 90.8

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33 Table 8. (Continued) Group C n=4 Average simila rity: 74% Genus FI group* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina HT 6.59 15.3 16.0 20.8 20.8 Rosalina HT 3 6.63 20.8 9.02 29.8 Triloculina HT 2.42 5.16 7.13 7.02 36.8 Bolivina ST 2.23 4.75 7.49 6.45 43.3 Miliolinella HT 2 4.4 85.4 5.98 49.3 Laevipeneroplis SB 1.84 3.8 4.87 5.16 54.4 Elphidium ST 1.94 3.79 5.56 5.15 59.6 Cribroelphidium ST 1.38 2.86 5.55 3.89 63.5 Haynesina ST 1.35 2.68 3.42 3.65 67.1 Discorbis HT 1.32 2.4 2.88 3.26 70.4 Articulina HT 1.14 2.14 5 2.91 73.3 Sigmiolina HT 1.35 1.92 0.91 2.61 75.9 Bulimina ST 1.03 1.91 12.9 2.59 78.5 Cibicides HT 0.7 1.57 9.38 2.14 80.6 Eponides HT 0.75 1.57 9.38 2.14 82.8 Pseudohauerina HT 0.71 1.5 5.74 2.04 84.8 Cycloforina HT 0.92 1.44 0.91 1.96 86.8 Cornuspira HT 0.95 1.38 0.9 1.87 88.6 Nonionoides ST 0.94 1.29 0.88 1.75 90.4

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34 Table 8. (Continued) Group D n=4 Average simil arity: 64% Genus FI group* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina HT 5.24 10.0 9 15.5 15.5 Rosalina HT 2.91 5.44 5.57 8.42 23.9 Laevipeneroplis SB 2.75 4.93 7.17 7.63 31.6 Siphonaperta HT 2.24 4.11 17.9 6.36 37.9 Archaias SB 1.95 3.5 6.98 5.41 43.3 Discorbis HT 2.09 3.45 3.8 5.34 48.7 Sigmiolina HT 1.67 3.2 11.8 4.95 53.6 Triloculina HT 1.83 3.17 4.64 4.9 58.5 Ammonia ST 1.74 2.77 2.94 4.29 62.8 Cycloforina HT 1.17 2.02 4.48 3.12 65.9 Haynesina ST 1.29 1.96 5.7 3.04 69.0 Eponides HT 1.17 1.91 6.06 2.95 71.9 Elphidium ST 1.26 1.84 2.69 2.84 74.8 Peneroplis SB 1.06 1.83 6.11 2.83 77.6 Cornuspira HT 1.09 1.81 4.63 2.79 80.4 Textularia HT 1.16 1.24 0.91 1.91 82.3 Articulina HT 1.11 1.08 0.91 1.67 84.0 Miliolinella HT 1 0.97 0.84 1.51 85.5 Bulimina ST 0.85 0.96 0.89 1.49 87.0 Wiesnerella HT 0.82 0.9 0.87 1.39 88.3 Cibicides HT 0.62 0.8 0.91 1.24 89.6 Adelosina HT 0.67 0.8 0.91 1.23 90.8 Group E n=3 Average simil arity: 59% Genus FI group* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Archaias SB 4.52 8.08 7.44 13.7 13.7 Discorbis HT 3.37 7.51 15.0 12.7 26.4 Asterigerina SB 2.43 5.23 6.8 8.84 35.2 Laevipeneroplis SB 2.52 5.18 25.5 8.76 44.0 Cyclorbiculina SB 2.52 4.8 3.77 8.11 52.1 Amphistegina SB 2.32 4.41 5.77 7.45 59.5 Quinqueloculina HT 2.77 4.39 1.75 7.42 66.9 Neocornorbina HT 1.35 2.73 8.86 4.61 71.5 Siphonaperta HT 1.32 2.5 6.53 4.23 75.8 Heterostegina SB 1.27 2.47 7.34 4.18 80.0 Rosalina HT 2.27 2.26 0.58 3.83 83.8 Borelis SB 1.32 2.22 3.19 3.76 87.5 Triloculina HT 0.99 2.06 4.76 3.49 91.0

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35 Table 9. Means for diversity, density, and environm ental data for foraminiferal assemblage SIMPER groups. Group FI density (forams/g) # of genera pH Temperature DO Salinity % Mud Phi A 4.85 126 21.7 8.31 26.09 6.32 35.57 0.55 1.11 B 3.60 957 31.7 8.32 26.08 6.25 35.66 5.76 1.33 C 2.22 5518 29.8 8.22 25.83 6.42 35.82 26.4 2.75 D 3.13 1015 33.0 8.26 26.11 6.46 35.60 1.95 0.75 E 6.36 123 25.3 8.29 26.81 6.79 35.44 0.30 0.67 Figure 7. Sample sites with more than 50 foraminife rs represented by their foraminiferal assemblage SIMPER groups.

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36 Group C included the sites with the lowest FORAM In dex values and highest percent mud by far. The contribution of symbiont-b earing foraminifers in this group was only 5%, while almost 22% of the defining taxa were stress-tolerant, representing 5 different genera. Spatially, these sites were loca ted close to shore, and near the most interior portions of both Old Rhode’s Key and Ellio t Key and furthest from direct sources of water flow. The fourth group, Group D, appeared to be a transit ional group between Groups B and C. Each of the four sites that fell in this cl uster had a replicate also in B. The average FI was only slightly lower, and the average density and diversity of Foraminifera was only slightly higher (Table 9). Finally, Group E represents offshore sites in near optimal conditions with the highest average FI, lowest foraminiferal density, a nd lowest percent mud. More than half of the major contributing genera were symbiont-bear ing. Pearson’s correlation matrices were made to compare how the taxa represented in the SIMPER analyses correlated with each other (Tab le 10). All significant correlations between symbiont-bearing Foraminifera were positive as expected. The strongest taxa correlation was between Quinqueloculina and Bolivina at 0.78 (p<0.027), followed by Quinqueloculina and Rosalina at 0.74. The strongest negative correlation occur red between Quinqueloculina and Archaias (-0.47). While most significant correlations between smaller heterotrophic foraminifera and symb iont-bearing Foraminifera were negative, several genera had positive correlations, most notably Neocornorbina, which had significant positive correlations with Amphistegina Asterigerina and

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37 Cyclorbiculina R-mode analysis of the foraminiferal assemblage data did not reveal any significant clustering of taxa. Table 11 is a Pearson’s correlation matrix between foraminiferal genera and the environmental data. Density (shells/gram), number of genera, and percent mud almost always negatively correlated with symbiont-bearing foraminifera and positively correlated with the stress-tolerant and heterotroph ic foraminifera. Discorbis however, tended to have negative correlations with those env ironmental parameters, which also agrees with the positive correlations it has with t wo symbiont-bearing genera ( Amphistegina and Archaias ). While it seems circular to include FI as an env ironmental variable in this context since it is based on the g enera, what is shown from this is specifically which of the foraminifers correlated s trongest with the FI. For the symbiontbearing taxa, Archaias had the strongest relationship with the FI, while Quinqueloculina had the most influence of the smaller foraminifers. From Table 7, it is possible to see the negative co rrelation between salinity and temperature. As a result, those taxa that correlat ed positively with salinity (stress-tolerant and other smaller taxa) also correlated negatively with temperature and vice versa. Depth and density of live symbiont-bearing forams (LSF) d id not show strong correlations with other measured parameters. The BIO-ENV procedure in PRIMER was performed for a ll replicates with more than 50 foraminifers to determine which environment al parameters could best explain the foraminiferal assemblage. Because number of genera and density were parameters based on the assemblage themselves, they were removed fro m this analysis as were depth and LSF because their correlations with the assemblage were weak.

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38 Of the five contributing variables, percent mud was the single most influential variable on the distribution of the foraminiferal a ssemblage (0.49) (Table 12). However, the best combination of variables to explain the as semblage was temperature, salinity, and percent mud, which improved the correlation to 0.55.

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39 Table 10. Correlation matrix of foraminiferal taxa; bold type represents correlations significant at p<0.027. AmphiArchAsterBorBroekCyclorHeteroLaeviPene Amphistegina 1.00 Archaias 0.40 1.00 Asterigerina 0.180.221.00 Borelis 0.120.14 0.38 1.00 Broekina -0.05-0.110.12-0.081.00 Cyclorbiculina 0.29 0.650.39 0.24-0.131.00 Heterostegina 0.280.07 0.60 0.25-0.05 0.42 1.00 Laevipeneroplis 0.190.270.330.140.240.01-0.131.00 Peneroplis 0.18-0.090.15-0.030.24-0.060.090.281.00 Ammonia -0.15-0.24-0.12-0.090.03-0.27-0.100.010.07 Bolivina -0.40-0.44 -0.21-0.24-0.14-0.230.12-0.13-0.06 Bulimina -0.31-0.30-0.18-0.17-0.28-0.190.07-0.30-0.16 Cribroelphidium -0.25 -0.44 -0.13-0.17-0.20 -0.36 -0.09-0.15-0.17 Elphidium -0.31-0.13-0.21-0.210.12-0.16-0.24-0.08-0.03 Haynesina -0.31 -0.47 -0.26-0.16-0.10-0.27-0.13-0.02-0.07 Adelosina -0.36 -0.31-0.25-0.150.04-0.18-0.10-0.17-0.01 Articulina -0.17-0.30-0.18-0.220.14-0.33-0.15-0.010.05 Cibicides -0.09 -0.38 -0.26-0.280.25 -0.39 -0.250.020.16 Cornuspira -0.20 -0.37 -0.09-0.10-0.08-0.190.11-0.160.10 Cycloforina -0.12-0.32-0.19 -0.410.35 -0.30-0.170.04 0.41 Discorbis 0.470.71 0.180.25-0.180.320.210.00-0.09 Eponides -0.14-0.17-0.01-0.28-0.11-0.13-0.090.120.24 Hauerina 0.09-0.160.000.200.070.01-0.030.30 0.50 Miliolinella -0.32 -0.38-0.44 -0.19-0.25-0.33-0.12-0.24-0.24 Neocornorbina 0.44 0.29 0.40 0.33-0.13 0.38 0.310.30-0.09 Nonionoides -0.22-0.13-0.28-0.14-0.06-0.13-0.03-0.160.11 Pseudohauerina -0.08-0.230.060.270.14-0.31-0.090.110.28 Quinqueloculina -0.36-0.47-0.34 -0.32-0.06 -0.40 -0.180.020.11 Rosalina -0.21 -0.39 0.01-0.08-0.14-0.110.170.070.09 Sigmoilina -0.33-0.30-0.16-0.19-0.30-0.28-0.060.000.05 Siphonaperta 0.14 0.59 -0.03-0.100.01 0.42 -0.140.180.01 Spiroloculina 0.02-0.26-0.21-0.160.19-0.25-0.03-0.020.15 Textularia 0.14-0.020.090.300.24-0.03-0.150.21 0.38 Triloculina 0.15 -0.36-0.41 -0.290.28 -0.41-0.37 0.080.24 Triloculinella 0.06-0.230.10-0.100.15-0.310.040.010.22 Wiesnerella -0.22-0.28-0.040.17-0.21-0.23-0.090.13-0.11

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40 Table 10. (Continued) AmmBoliBuliCribroElphHaynAdelArtiCibi AmphisteginaArchaiasAsterigerinaBorelisBroekinaCyclorbiculinaHeterosteginaLaevipeneroplisPeneroplisAmmonia 1.00 Bolivina 0.181.00 Bulimina 0.390.62 1.00 Cribroelphidium 0.02 0.490.40 1.00 Elphidium -0.070.250.060.301.00 Haynesina 0.27 0.590.47 0.210.151.00 Adelosina 0.18 0.42 0.290.270.090.161.00 Articulina 0.31 0.34 0.19 0.38 0.230.080.301.00 Cibicides 0.31 0.340.36 0.100.220.330.19 0.37 1.00 Cornuspira 0.11 0.53 0.190.220.270.34 0.490.440.34 Cycloforina 0.120.180.090.20 0.35 0.260.14 0.42 0.29 Discorbis -0.09 -0.38 -0.10 -0.41 -0.10 -0.39 -0.29-0.21-0.18 Eponides 0.270.170.280.220.030.06-0.030.33 0.37 Hauerina 0.010.08-0.160.07-0.090.080.110.180.17 Miliolinella 0.17 0.640.640.47 0.34 0.440.340.420.39 Neocornorbina 0.01-0.25-0.21-0.21-0.18-0.27-0.17-0.03-0.31 Nonionoides -0.27 0.35 0.03 0.350.49 0.01 0.35 0.160.04 Pseudohauerina -0.070.09-0.020.270.12-0.090.080.190.17 Quinqueloculina 0.09 0.780.440.590.450.500.510.570.46 Rosalina 0.16 0.710.47 0.330.16 0.56 0.22 0.41 0.32 Sigmoilina 0.26 0.620.590.43 0.14 0.39 0.26 0.38 0.24 Siphonaperta 0.00 -0.40 -0.14 -0.37 -0.12-0.25-0.21-0.20-0.20 Spiroloculina 0.300.210.200.210.100.090.03 0.36 0.13 Textularia -0.16-0.31-0.22-0.21-0.10-0.14-0.30-0.130.05 Triloculina -0.160.14-0.060.280.150.110.300.30 0.44 Triloculinella 0.220.130.250.30-0.08-0.140.030.200.33 Wiesnerella 0.160.28 0.35 0.160.03 0.45 0.030.220.17

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41 Table 10. (Continued) CornuCyclofDiscEponHauerMilio Neocor NonPseud AmphisteginaArchaiasAsterigerinaBorelisBroekinaCyclorbiculinaHeterosteginaLaevipeneroplisPeneroplisAmmoniaBolivinaBuliminaCribroelphidiumElphidiumHaynesinaAdelosinaArticulinaCibicidesCornuspira 1.00 Cycloforina 0.141.00 Discorbis -0.21-0.191.00 Eponides 0.140.19-0.111.00 Hauerina 0.000.32-0.130.121.00 Miliolinella 0.44 0.21-0.160.17-0.021.00 Neocornorbina -0.20-0.130.25-0.260.18-0.171.00 Nonionoides 0.39 0.31-0.100.10-0.03 0.38 -0.171.00 Pseudohauerina 0.220.150.010.170.320.21-0.180.311.00 Quinqueloculina 0.640.46-0.40 0.310.21 0.73 -0.32 0.55 0.28 Rosalina 0.52 0.31-0.30 0.38 0.20 0.64 -0.040.250.08 Sigmoilina 0.47 0.14-0.24 0.50 -0.04 0.65 -0.290.270.29 Siphonaperta -0.36 -0.07 0.42 0.080.00-0.230.08-0.14-0.12 Spiroloculina -0.15 0.40 -0.160.060.090.290.030.170.00 Textularia -0.09-0.11-0.040.160.17-0.28-0.17-0.140.30 Triloculina 0.21 0.47 -0.330.040.320.12-0.260.290.21 Triloculinella -0.210.15-0.100.140.26-0.03-0.09-0.100.06 Wiesnerella 0.180.17-0.180.27-0.030.33-0.060.08-0.01

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42 Table 10. (Continued) QuinqRosaSigmoSiphonSpirolTextTrilocTrilocWies AmphisteginaArchaiasAsterigerinaBorelisBroekinaCyclorbiculinaHeterosteginaLaevipeneroplisPeneroplisAmmoniaBolivinaBuliminaCribroelphidiumElphidiumHaynesinaAdelosinaArticulinaCibicidesCornuspiraCycloforinaDiscorbisEponidesHauerinaMiliolinellaNeocornorbinaNonionoidesPseudohauerinaQuinqueloculina 1.00 Rosalina 0.74 1.00 Sigmoilina 0.680.70 1.00 Siphonaperta -0.37 -0.31-0.191.00 Spiroloculina 0.290.220.12-0.031.00 Textularia -0.15-0.13-0.150.140.001.00 Triloculina 0.42 0.04-0.07-0.240.210.171.00 Triloculinella 0.06-0.05-0.06-0.190.300.06 0.34 1.00 Wiesnerella 0.420.630.47 -0.190.18-0.01-0.07-0.171.00

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43 Table 11. Correlation matrix of foraminiferal taxa and environmental data; bold type represents correlations significant at p<0.027 FISIDepth% MudPhi Amphistegina 0.53 -0.28-0.26-0.34-0.30 Archaias 0.81-0.38 -0.02 -0.50 -0.27 Asterigerina 0.55-0.38 0.20 -0.43 -0.33 Borelis 0.38-0.43-0.11-0.30-0.08 Broekina 0.000.120.30-0.100.02 Cyclorbiculina 0.74 -0.330.08 -0.38-0.35 Heterostegina 0.58 -0.33-0.16-0.18-0.24 Laevipeneroplis 0.150.030.19-0.24-0.06 Peneroplis -0.100.050.07-0.05-0.07 Ammonia -0.340.220.010.110.10 Bolivina -0.570.57 -0.24 0.800.62 Bulimina -0.480.37 -0.32 0.56 0.33 Cribroelphidium -0.52 0.27-0.12 0.62 0.31 Elphidium -0.38 0.120.17 0.370.45 Haynesina -0.55 0.28-0.06 0.470.40 Adelosina -0.410.71 -0.17 0.47 0.19 Articulina -0.40 0.280.160.260.32 Cibicides -0.470.59 -0.25 0.470.56 Cornuspira -0.450.46 -0.10 0.44 0.32 Cycloforina -0.46 0.190.140.200.09 Discorbis 0.42 -0.33 -0.35-0.42 -0.13 Eponides -0.310.290.020.120.08 Hauerina -0.160.160.030.090.13 Miliolinella -0.590.46 -0.21 0.670.61 Neocornorbina 0.41 -0.250.04-0.26-0.21 Nonionoides -0.320.30-0.15 0.48 0.33 Pseudohauerina -0.210.060.070.250.33 Quinqueloculina -0.690.63 -0.11 0.710.56 Rosalina -0.510.40 -0.09 0.480.41 Sigmoilina -0.41 0.31-0.10 0.43 0.33 Siphonaperta 0.19-0.120.14 -0.40 -0.22 Spiroloculina -0.37 0.170.050.210.21 Textularia 0.03-0.26 0.45 -0.32-0.15 Triloculina -0.500.51 -0.10 0.41 0.20 Triloculinella -0.290.19-0.170.260.14 Wiesnerella -0.290.07-0.070.040.06

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44 Table 11. (Continued) TemperatureSalinityDensityGeneraLSF Density Amphistegina 0.18-0.10 -0.41 -0.280.27 Archaias 0.07-0.27 -0.43-0.61 0.23 Asterigerina 0.38 -0.34-0.290.02-0.03 Borelis 0.27-0.12-0.23-0.180.15 Broekina -0.060.08-0.110.270.09 Cyclorbiculina 0.35-0.41 -0.33 -0.43 0.04 Heterostegina 0.66 -0.32-0.16-0.20-0.10 Laevipeneroplis -0.43 0.13-0.070.180.14 Peneroplis -0.060.03-0.03 0.44 0.02 Ammonia -0.130.100.22 0.46 -0.15 Bolivina -0.360.410.85 0.34-0.33 Bulimina -0.110.33 0.69 0.27-0.29 Cribroelphidium -0.27 0.350.530.35 -0.15 Elphidium -0.200.110.340.08 -0.36 Haynesina -0.29 0.370.49 0.320.01 Adelosina -0.36 0.21 0.50 0.29-0.18 Articulina -0.21-0.03 0.450.49 -0.08 Cibicides -0.34 0.340.490.39 -0.16 Cornuspira -0.240.12 0.47 0.27-0.26 Cycloforina -0.140.060.18 0.53 0.06 Discorbis 0.16-0.03-0.33 -0.35 0.32 Eponides -0.220.200.26 0.53 -0.10 Hauerina -0.130.070.10 0.46 0.20 Miliolinella -0.31 0.360.79 0.19-0.10 Neocornorbina 0.21-0.22-0.28-0.120.13 Nonionoides -0.180.270.320.12-0.05 Pseudohauerina -0.130.200.330.24-0.02 Quinqueloculina -0.520.380.810.46 -0.22 Rosalina -0.280.27 0.660.48 -0.08 Sigmoilina -0.36 0.19 0.74 0.26-0.20 Siphonaperta -0.06-0.08 -0.35 -0.110.29 Spiroloculina -0.070.150.27 0.40 0.04 Textularia 0.09-0.12-0.240.22-0.01 Triloculina -0.38 0.330.22 0.40 0.03 Triloculinella -0.040.160.21 0.52 -0.04 Wiesnerella -0.050.110.280.23-0.09

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45 Table 12. Results of BIO-ENV test of correlation be tween environmental variables and the foraminiferal assemblage; bold type indicates the best variable or combination of variables to explain the assemblage # of Variables Correlation Determining Environmenta l Variables 1 0.49 % Mud 2 0.52 Temperature, % Mud 2 0.5 Salinity, % Mud 3 0.55 Temperature, Salinity, % Mud 3 0.48 Temperature, % Mud, phi 3 0.48 Salinity, % Mud, Dissolved Oxygen 3 0.48 Temperature, % Mud, Dissolved Oxygen 4 0.52 Temperature, Salinity, % Mud, phi 4 0.51 Temperature, Salinity, % Mud, Dissolved Oxyg en 5 0.49 Temperature, Salinity, % Mud, Dissolved Oxyg en, phi FORAM Index FORAM Index values were calculated for all replica tes containing more than 50 total Foraminifera. The following eight sites were removed from this analysis because they did not meet this criterion in either replicat e: 1.1, Shark, 3.2, 5.4, 8.1, Nirvana, Lugano, and 10.2. Values were calculated in accorda nce to the formula presented in Table 1, modified from Hallock et al. (2003). The reefs in the vicinity of the flow from Caesar’s Creek have the highest FI values (Fig. 8). High FI values correspond to SIMPER groups A and E, with Pacific Reef having the highest average FI value (7.0, SD=1.9). Lowest FI values correspond to SIMPER gro up C. The lowest FI value was at Bug Reef with an FI of 2.1 (SD=0.12). The Moran’s I value for spatial autocorrelation of FI values was not significant (0.254, p=0.054). This indicated that no significa nt spatial pattern existed in the FI values. However, there was significant bivariate s patial correlation between FI and

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46 temperature, salinity, and percent mud (0.314, 0.31 1, 0.355 respectively, p<0.05). Again the significant Moran’s I value is supported by a P earson’s correlation that was significant when FI was compared to salinity, tempe rature, and percent mud (Table 13). Also, Table 13 includes correlations between the fu nctional groups that make up the FI value and all of the environmental parameters. Alm ost all of the correlations were significant (again except LSF and depth) for each o f the components as well as the FI value itself.

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47 Figure 8. Contours of FORAM Index values. Sites wit h more than 50 forams/gram of sediment are represented by their SIMPER group.

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48 Table 13. Correlation matrix for FORAM Index functi onal groups with environmental variables; Ps – percent symbiont-bearing foraminife rs, Po – percent stress-tolerant foraminifers, Ph – percent other small foraminifers ( Bold indicates significance at p<0.05) FIFIPsFIPoFIPhFI1.00FIPs1.00 1.00 FIPo-0.73-0.71 1.00 FIPh-0.95-0.960.49 1.00 % Mud -0.62-0.610.620.51 Depth0.060.07-0.05-0.06LSF0.160.15 -0.38 -0.04 Phi -0.40-0.390.450.31 Density -0.55-0.540.570.45 Genera -0.64-0.640.410.63 Temperature 0.330.33 -0.22 -0.33 Salinity -0.47-0.470.400.42 Sediment-Constituent Analysis The average amount of unidentifiable grains across samples was 52% (SD=18%) ranging from 14% at Dome Reef to 79% at reef 5.1. Where the percent of unidentifiable grains was low, the dominant constituents were calca reous algae and mollusk fragments (Fig. 9). Identifiable coral fragments never contr ibuted more than 3.7% to any one sample. Assemblage composition for each replicate at each site can be found in Appendix V. The results of the SIMPER analysis on the sedimentconstituent assemblage is shown in the MDS plot in Figure 10. Two main group s were identified. The constituents defining group A were dominated by calcareous algae mollusks, and unidentifiable grains (Table 14). This group represented sites wit h higher SEDCON Index (SI) values,

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49 Figure 9. Percentages of sediment constituents for sites with highest and lowest percentages of unidentifiable grains

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50 lower temperatures, and an average percent mud of 1 7% (Table 15). Group B was dominated by the same three sediment constituents; however, unidentifiable grains played a more important role, contributing 23% to t he group’s similarity. This group was characterized by lower SI values, higher temperatur es, and lower percent mud (1.1%). Nirvana Reef is an outlier; this site had the lowes t percent mud and SI value. While the within-group similarity was high for both of the la rger groups, 91% for group A and 88% for group B, the dissimilarity between the two grou ps was only 16% (Table 16). Figure 10. MDS plot of reefs represented by their S IMPER groups defined by similarity of sediment constituents A B

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51 Table 14. Within-group similarity of the two main S IMPER-defined groups for the sediment constituents Group A n-6 Average s imilarity: 90.6% Species SI group Av.Abund Av.Sim Sim/SD Contrib% Cum.% Calcareous Algae Pah 2.46 15.8 48.8 17.4 17.4 Molluscs Pah 2.19 13.8 13.0 15.2 32.6 Unidentifiable Pu 2.17 13.6 15.5 15.0 47.7 Other Pah 1.42 8.83 19.2 9.74 57.4 Symbiotic Forams Pf 1.36 7.88 11.9 8.7 66.1 Worm Tubes Pah 1.2 7.34 10.6 8.1 74.2 Gorgonian Sclerites Pah 1.08 6.15 5.13 6.78 81.0 Group B n-25 Average si milarity: 88.3% Species SI group Av.Abund Av.Sim Sim/SD Contrib% Cum.% Unidentifiable Pu 2.76 20.2 13.1 22.9 22.9 Molluscs Pah 2.13 15.2 15.2 17.2 40.1 Calcareous Algae Pah 1.76 11.9 6.83 13.4 53.5 Worm Tubes Pah 1.08 7.46 9.88 8.45 62.0 Coral Pc 1.08 7.4 7.47 8.38 70.4 Symbiotic Forams Pf 1.11 6.99 2.83 7.93 78.3 Other Pah 0.99 6.03 4.41 6.83 85.1 Table 15. Means for environmental data for sediment constituent SIMPER groups Group SI pH Temperature DO Salinity % Mud Phi A 1.89 8.26 25.95 6.29 35.75 17.3 2.00 B 1.13 8.29 26.20 6.38 35.58 1.10 0.88 Nirvana 0.85 8.25 26.09 6.43 35.60 0.06 1.00

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52 Table 16. Dissimilarity between the two main groups defined by the SIMPER analysis of sediment constituents Groups B & A Average dissimilarity = 16.2 Group B Group A Constituent SI group Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Cum.% Fecal Pellets Pah 0.24 0.97 2.83 1.71 17.5 17.5 Calcareous Algae Pah 1.76 2.46 2.48 2.18 15.4 32.9 Unidentifiable Pu 2.76 2.17 2.11 2.93 13.0 45.9 Other Pah 0.99 1.42 1.62 1.63 10.1 56.0 Echinoid Spines Pah 0.72 0.85 1.4 1.2 8.68 64.6 Coralline Algae Pah 0.7 0.59 1.29 1.18 7.96 72.6 Symbiotic Forams Pf 1.11 1.36 1.24 0.96 7.66 80.3

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53 Correlation matrices were created to determine if a ny of the constituents varied with respect to each other (Table 17). The stronge st relationship was between calcareous algae and unidentifiable grains at -0.84. The stro ngest positive correlation was between calcareous algae and the other category which inclu ded smaller foraminifers and bryozoans. Interestingly, there was a significant n egative correlation between identifiable coral fragments and symbiont-bearing foraminifers ( -0.28), though percentages of both tended to be small. Constituents were also correlated to environmental data in Table 18. Again, those constituents that correlated positively with salini ty, tended to correlate negatively, as expected, to temperature. Unidentifiable grains ha d a strong negative correlation (-0.72) with percent mud. The other category and the calca reous algae, which positively correlated to each other, also both positively corr elated to the SI values. When the BIO-ENV routine was used to compare waterquality parameters to the sediment constituent assemblage, percent mud again came out as the single most influential environmental parameter with a 0.48 cor relation to the assemblage (Table 19). No other variable or combination of variables was a ble to produce a stronger correlation than percent mud.

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54 Table 17. Correlation matrix for sediment constitue nts ; bold type indicates significance at p<0.05 CoralSFCor. AlgaeMolluscsCal. AlgaeESWTGSFPOtherUni d Coral1.00Symbiotic Forams -0.28 1.00 Coralline Algae 0.26 -0.191.00 Molluscs0.07 0.31-0.32 1.00 Calcareous Algae -0.33 0.14-0.200.001.00 Echinoid Spines-0.060.11-0.18 0.37 0.081.00 Worm Tubes0.02-0.07-0.060.00 0.28 0.161.00 Gorgonian Sclerites-0.080.05-0.150.10 0.31 0.22 0.33 1.00 Fecal Pellets-0.24-0.02-0.190.10 0.54 0.15 0.160.38 1.00 Other -0.26 0.23-0.030.22 0.62 0.21 0.270.270.41 1.00 Unidentifiable0.23 -0.390.28-0.49-0.84-0.30-0.31-0.39-0.53-0.73 1.00 Table 18. Correlation matrix for sediment constitue nts and environmental variables; bold type indicate s significance at p<0.05 FISI% MudPhiDepthLSFSalinityTemperature Coral-0.09-0.09 -0.28-0.44 -0.03-0.05-0.010.09 Symbiotic Forams-0.20 0.680.390.26 0.11 -0.29 0.03 -0.29 Coralline Algae0.13 -0.32 -0.23 -0.33 -0.02-0.17 -0.310.54 Molluscs -0.400.570.310.270.28 -0.040.22 -0.45 Calcareous Algae -0.470.670.630.46 -0.250.07 0.68-0.39 Echinoid Spines -0.260.280.340.340.29 -0.070.19 -0.31 Worm Tubes -0.39 0.230.170.230.25-0.080.100.02 Gorgonian Sclerites -0.360.33 0.21 0.33 0.08-0.01 0.28 -0.25 Fecal Pellets -0.360.380.570.57 -0.18-0.09 0.30 -0.19 Other -0.500.690.490.49 0.25-0.13 0.30-0.30 Unidentifiable 0.64-0.92-0.72-0.56 0.000.05 -0.630.53

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55 Table 19. Results of BIO-ENV test of correlation be tween environmental variables and the sediment constituents. Bold indicates the best variable of combination of variables to explain the assemblage. # of Variables Correlation Determining Environmental Variables 1 0.482 % Mud 2 0.435 Salinity, % Mud 2 0.402 % Mud, phi 2 0.402 Temperature, %Mud 3 0.428 Salinity, % Mud, phi 3 0.393 Temperature, Salinity, %Mud 3 0.366 Temperature, %Mud, phi 4 0.386 Temperature, Salinity, %Mud, phi SEDCON Index Because a standard number of sediment grains were p icked for each sample (300), all replicates at all sites could be used to calcul ate SEDCON Index values (SI values). Values were calculated based on the equation derive d in Daniels (2005) and shown in Table 3. The range of mean values among the reefs was from 0.64 (SD=0.03) at Shark Reef to 2.48 (SD=0.42) at Reef 9.3. The mean SI va lue was 1.26. Figure 11 shows the contour lines of SI values for the study area with each site represented by its SIMPER group. The lowest SI val ues are found in the vicinity of Caesar’s Creek, while the reefs furthest from direc t sources of water flow have the highest SI values. The sites with high values are associated with SIMPER group A, while Group B is a catch all for almost everything e lse. Moran’s I value for spatial autocorrelation was sig nificant for the SI values at 0.21 (p<0.05). This indicates there is significant clustering and a pattern exists. The SI significantly co-varied with temperature, salinity, and depth (Moran’s I= 0.27, 0.22, 0.19 respectively; p<0.05) (Appendix IV). The significa nt Moran’s I value is supported by a

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56 Pearson’s correlation that is significant when SI i s compared to salinity, temperature (Table 18). Table 20. Correlation matrix for SEDCON Index funct ional groups with environmental variables; Pc – percent coral grains, Pf – percent symbiont-bearing foraminifers, Pah – percent autotrophic/heterotrophic grains, Pu – perc ent unidentifiable grains ( Bold indicates significance at p<0.05) SISIPcSIPfSIPahSIPu SI1.00SIPc -0.11 1.00 SIPf 0.67 -0.291.00 SIPah 0.79 -0.210.131.00 SIPu -0.89 0.21 -0.31-0.98 1.00 % Mud 0.66 -0.30 0.320.69-0.72 Depth-0.250.16-0.03 -0.360.35 LSF-0.19-0.09 -0.35 0.080.00 Phi 0.42-0.38 0.16 0.54-0.53 Density 0.60 -0.27 0.380.56-0.61 Genera 0.37 0.250.06 0.36-0.37 Temperature -0.61 0.13-0.30 -0.590.63 Salinity 0.46 -0.10-0.02 0.66-0.63

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57 Figure 11. Contours of SEDCON Index values; sites r epresented by their sedimentconstituent assemblage SIMPER group

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58 Live Symbiont-bearing Foraminifera (LSF) Data for Amphistegina gibbosa populations and density of other LSF collected from the reef rubble can be found in Appendix VI. These data did not correlate with most other counts and measures noted previously, wi th the exception of the assemblage data for symbiont-bearing Foraminifera in the sedim ent constituent analysis (-0.29, Table 16) and therefore also with the percent of Foramini fera at each site (-0.35, Table 18). Cluster and MDS analyses of the LSF assemblage data are shown in Figure 12. SIMPER analysis of these clusters revealed three di stinct groups, each with ~80% similarity. There were three outlier reefs, 1.1, 5 .4, 9.3, which strongly differ from each other as well as from the SIMPER clusters. Figure 12. MDS plot of reefs represented by their S IMPER groups defined by similarity of live symbiont-bearing foraminiferal assemblage A C B A

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59 Groups A and C are defined by a large contribution to the within group similarity by Amphistegina gibbosa They differ with the second contributing species which is Archaias angulatus for group A and Laevipeneroplis proteus for group C (Table 21). Group B had the highest contribution by L. proteus, followed A. gibbosa Dissimilarities between the groups and the outlier reefs can be fou nd in Appendix VI. Table 21. Within group similarity of SIMPER defined groups for the live, symbiontbearing foraminiferal assemblage Group A n=7Average similarity: 83%SpeciesAv.AbundAv.SimSim/SDContrib% Cum.% A. gibbosa 5.2717.337.3620.920.9 A. angulatus 4.3413.495.7316.337.1 L. proteus 3.7712.047.214.551.7 C. compressus 3.7511.427.813.865.4 A. carinata 2.737.883.459.574.9 Androsina 2.426.573.027.9282.8 S. marginalis 1.43.962.524.7787.6 P. pertusus 1.223.343.484.0391.6 Group B n=13Average similarity: 78.6%SpeciesAv.AbundAv.SimSim/SDContrib% Cum.% L. proteus 7.3329.710.3937.837.8 A. gibbosa 3.7213.514.3917.255.0 A. angulatus 3.4312.034.4615.370.3 L. bradyi 2.37.682.579.7880.1 P. pertusus 1.465.053.516.4386.5 C. compressus 1.543.581.154.5591.1 Group C n=9Average similarity: 82.1%SpeciesAv.AbundAv.SimSim/SDContrib% Cum.% A. gibbosa 6.7325.926.8231.631.6 L. proteus 5.3720.636.4625.156.7 C. compressus 2.758.051.839.8166.5 L. bradyi 2.127.434.749.0575.6 A. angulatus 27.365.468.9784.6 P. pertusus 1.454.674.185.6990.2

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60 Environmentally, Group A had the highest mean FI v alue as well as the highest diversity of symbiont-bearing foraminifera and lowe st percent mud (Table 22). Group C had the lowest FI of the major groups as well the l owest diversity and highest percent mud. Table 22. Means for density, diversity, and environ mental data for LSF assemblage SIMPER groups Density GroupFISI(LSF/100cm2)# GenerapHTemperatureDOSalinity% MudPhi A6.071.7611310.78.2426.416.5435.470.2%0.71 B4.091.2690.99.38.3226.086.3035.653.0%1.23C3.181.361048.88.2926.066.2735.667.4%1.11 1.1N/A1.641466.08.2026.216.6635.430.4%1.005.4N/A1.2051.26.08.3626.326.2835.760.7%1.009.32.511.625.738.1025.776.7035.6923.4%2.00 Photic Index Calculations of the Photic Index, based on abundanc e and bleaching of live Amphistegina gibbosa were carried out by multiplying the number of the density rank by the number of the bleaching rank shown in Table 4 s uch that each box corresponded to a unique number. Again, these numbers were not defin itively quantitative and a higher number did not necessarily indicate a better enviro nment. Most sites (75%) had a Photic Index value of 8 indi cating that environmental conditions supported Amphistegina but only at intermediate abundances, and that bleaching stress was chronic. Another six sites ha d a value of 4, indicating poor environmental conditions and chronic photic stress. The remaining two sites (1.1 and 9.3) had a value of 5, representing unfavorable env ironmental conditions overall. Figure 13 shows a spatial representation of these values.

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61 Figure 13. Sites represented by their Photic Index relative value

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62 FORAM Index v SEDCON Index Table 23 is a Pearson’s correlation matrix of foram iniferal taxa to sediment constituents. The most notable trends here were th e positive correlations between the symbiont-bearing Foraminifera and the coralline alg ae and unidentifiable grains. Also noteworthy were the negative correlations between t he symbiont-bearing Foraminifera and calcareous algae, fecal pellets, and the “other” category. The results of these correlations were an overall n egative correlation between the FORAM Index and the SEDCON Index (-0.53) as seen in Table 7. Spatially, the patterns between the two indices co-varied significantly wit h a Moran’s I value of -0.399 (p=0.01). Again the Moran’s I showed a negative re lationship in the variation of the patterns. The contour maps for each index (Figures 8 and 11) also showed reversed patterns.

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63 Table 23. Correlation matrix for foraminiferal taxa and sediment constituents; bold type represents a significant correlation at p<0.027 Coral Symbiotic Forams Coralline AlgaeMolluscs Amphistegina 0.08-0.280.19-0.27 Archaias -0.12-0.01-0.01-0.12 Asterigerina 0.11-0.02 0.50 -0.04 Borelis -0.11-0.15 0.45-0.43 Broekina -0.150.13-0.020.01 Cyclorbiculina -0.050.08 0.35 -0.22 Heterostegina -0.08-0.03 0.49-0.39 Laevipeneroplis 0.08-0.01-0.200.16 Peneroplis 0.050.030.150.07 Ammonia 0.110.04-0.130.15 Bolivina -0.220.33-0.250.24 Bulimina -0.050.24-0.110.14 Cribroelphidium -0.10-0.02-0.150.28 Elphidium -0.040.08-0.230.29 Haynesina -0.130.08-0.260.14 Adelosina -0.29 0.65 -0.230.27 Articulina -0.060.09-0.100.21 Cibicides 0.030.24-0.150.19 Cornuspira -0.110.190.140.23 Cycloforina 0.060.02-0.240.26 Discorbis 0.03-0.190.03-0.06 Eponides 0.47 -0.020.040.31 Hauerina -0.050.130.07-0.02 Miliolinella -0.080.10-0.190.30 Neocornorbina 0.04-0.070.32-0.18 Nonionoides -0.170.12-0.050.08 Pseudohauerina -0.06-0.100.180.04 Quinqueloculina -0.130.27-0.27 0.43 Rosalina 0.030.100.01 0.37 Sigmoilina -0.020.05-0.060.33 Siphonaperta 0.15-0.06-0.060.13 Spiroloculina 0.06-0.03-0.100.11 Textularia 0.22-0.22 0.38 -0.12 Triloculina -0.050.13-0.300.00 Triloculinella 0.100.12-0.080.00 Wiesnerella 0.15-0.02-0.040.07

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64 Table 23. (Continued) Calcareous AlgaeEchinoid SpinesWorm TubesGorgonian ScleritesAmphistegina -0.02-0.18-0.04-0.06 Archaias -0.35 -0.07-0.14-0.32 Asterigerina -0.52 -0.01-0.20-0.10 Borelis -0.15-0.19-0.10-0.02 Broekina 0.060.20-0.13-0.04 Cyclorbiculina -0.38 0.03-0.11-0.32 Heterostegina -0.25-0.110.11-0.17 Laevipeneroplis -0.06-0.06-0.190.26 Peneroplis -0.030.110.120.26 Ammonia 0.120.060.170.20 Bolivina 0.40 0.25-0.070.07 Bulimina 0.250.01-0.07-0.11 Cribroelphidium 0.300.19-0.08-0.12 Elphidium -0.05 0.44 -0.180.03 Haynesina 0.240.06-0.070.28 Adelosina 0.38 0.18-0.09-0.02 Articulina 0.180.26-0.070.00 Cibicides 0.46 0.04-0.070.22 Cornuspira 0.330.28-0.100.06 Cycloforina 0.060.320.110.04 Discorbis -0.19-0.15-0.10-0.24 Eponides 0.090.040.140.16 Hauerina 0.13-0.020.030.16 Miliolinella 0.40 0.17-0.09-0.02 Neocornorbina -0.19-0.14-0.11-0.04 Nonionoides 0.34 0.250.020.01 Pseudohauerina 0.170.180.17-0.04 Quinqueloculina 0.440.34 -0.100.11 Rosalina 0.230.25-0.230.21 Sigmoilina 0.190.100.010.08 Siphonaperta -0.18-0.08-0.07-0.04 Spiroloculina 0.120.140.110.15 Textularia -0.04-0.060.000.03 Triloculina 0.58 0.160.020.15 Triloculinella 0.130.03-0.030.07 Wiesnerella 0.02-0.08-0.090.22

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65 Table 23. (Continued) Fecal PelletsOtherUnidentifiable Amphistegina -0.08-0.030.19 Archaias -0.34-0.370.44 Asterigerina -0.36 -0.28 0.50 Borelis -0.22-0.22 0.37 Broekina -0.26 0.52 -0.12 Cyclorbiculina -0.36-0.340.46 Heterostegina -0.14-0.22 0.39 Laevipeneroplis -0.110.09-0.02 Peneroplis -0.090.27-0.07 Ammonia 0.180.15-0.22 Bolivina 0.51 0.24 -0.54 Bulimina 0.43 0.07-0.33 Cribroelphidium 0.35 0.03 -0.36 Elphidium 0.170.04-0.11 Haynesina 0.43 0.12-0.31 Adelosina 0.030.18 -0.54 Articulina 0.330.26-0.31 Cibicides 0.490.54-0.60 Cornuspira 0.38 0.29 -0.47 Cycloforina 0.100.18-0.21 Discorbis -0.20-0.300.29 Eponides 0.090.09-0.26 Hauerina 0.010.16-0.16 Miliolinella 0.59 0.21 -0.53 Neocornorbina -0.10-0.270.28 Nonionoides 0.120.07 -0.35 Pseudohauerina -0.020.26-0.19 Quinqueloculina 0.52 0.33 -0.66 Rosalina 0.50 0.15 -0.42 Sigmoilina 0.38 0.10 -0.35 Siphonaperta -0.31-0.110.15 Spiroloculina 0.230.33-0.22 Textularia -0.22 0.40 0.06 Triloculina 0.25 0.55-0.59 Triloculinella 0.060.18-0.16 Wiesnerella 0.34 -0.14-0.06

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66 DISCUSSION Limitations of Study Three rubble and sediment replicates were collected for this study. However, due to the time required to process each index, only tw o sediment replicates were analyzed. A one way ANOVA calculated for the SEDCON and FORAM index values showed no significant difference between the two replicates s o two sediment replicates was deemed sufficient (Table 24). Table 24. One Way ANOVAs for a) SEDCON Index replic ates and b) FORAM Index replicates a) One Way ANOVA Source of VariationSSdfMSFP-valueF crit Between Sites10.52316310.3394579.475913.88E-091.810 379 Within Sites0.18716410.1871641.0106130.3186643.9958 87 b) One Way ANOVA Source of VariationSSdfMSFP-valueF crit Between Sites50.57827192.6620147.2608352.41E-052.13 7009 Within Sites0.12898710.1289870.0848280.7724434.0981 72 The samples were collected in early May of 2007 pri or to heavy rains associated with South Florida summers. Since the environmenta l data collected with the YSI only represented a snapshot in time, the true effects of environment on the reefs can only be hypothesized. Long-term monitoring of environmenta l data is needed to make more definitive conclusions. The Southeast Research Cen ter (SERC), which conducts long term monitoring of water quality along the Florida reef tract, has only two monitoring

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67 stations within the study area, although four other s are in the general vicinity. While this added insight into the environmental conditions of the area, the resolution of their sampling did not provide enough detail for comparis on. As mentioned in Daniels (2005), an issue that is in volved with most indices that require identification training is an improved fami liarity as samples are processed. To minimize the effect of having more unidentifiables (for the SEDCON Index) or improperly identified foraminifera (for the FORAM I ndex) in early samples, care was taken to have an experienced technician provide a t horough training. At the conclusion of identifications, early samples were revisited fo r a final count. Books and picture taxonomic aides were also used to assure proper ide ntifications and minimize error. The Offshore Environment Figures 4 and 5, which illustrate percent mud, sali nity, and temperature distributions, provide an overview of the environme nt offshore of the Keys in Biscayne National Park, which provide shelter from direct in fluence (good or bad) of Biscayne Bay. All three variables showed a similar pattern, an anomalous bump near the outflow of Caesar’s Creek. Because temperature and salinit y are frequently used as tracers of water masses, I deduced that the contours reflect a plume of water emerging from Biscayne Bay. The force of the tidal flow in this area appears to also influence grain-size distribution. Foraminiferal Assemblages The foraminiferal assemblage data allowed for the c reation of a Q-mode cluster analysis and then SIMPER grouping of sites. Five g roups were distinguished through this procedure (Fig. 7). Groups A and E represente d sites with FI values greater than

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68 four, where the environmental conditions were, in t heory, favorable for mixotrophic, calcifying organisms. These sites were characteriz ed by very low percent mud, low foraminiferal densities, and low foraminiferal dive rsity. The map in Figure 7 shows that these SIMPER groups were most likely being influenc ed by the net outflow of water from Caesar’s Creek (Wang et al. 2003). The same s cenario is likely to be occurring at the south end of the study area, with water exchang e through the inlet south of Old Rhode’s Key. Only one genus of stress-tolerant for aminifer was present in Group A ( Elphidium ) and none in Group E. Carnahan et al. ( submitted ) also found in their study of foraminiferal assemblages from within Biscayne B ay, that while Elphidium is a stresstolerant genus, it tended to group with the “other smaller” foraminifers in statistical analyses. Conversely, Group C reefs occur closest to shore an d towards the interior of the islands where they are sheltered from constant inte nse water exchange. This resulted in reefs characterized by high percent mud and low per centages of symbiont-bearing Foraminifera contributing to the assemblage. This group also had the highest contribution of stress-tolerant taxa (Table 25). Carnahan et al. ( submitted ) conducted a study of foraminiferal assemblages wi thin Biscayne Bay. They recognized three distinct foram iniferal assemblages within the Bay, freshwater influenced, urban pollution influenced, and oceanic influenced. When compared to the data from this thesis, the oceanicinfluenced assemblage (B-2) most closely resembled Group C. Percent mud for Group B -2 (from Carnahan 2005) and Group C (from this data) were 30% and 26.4% respect ively and the mean FORAM Index values were 2.74 and 2.22. In combination the two datasets may represent the full

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69 spectrum of foraminiferal assemblages from highly i mpacted, near-shore environments, to open bay environments, to coral reef/open shelf assemblages. The SIMPER data combined with the contour lines cre ated for the FI value showed a similar pattern to what has been observed in previous variables, the influence of Caesar’s Creek outflow (Fig. 8). The Moran’s I val ue for the FI was insignificant (0.25, p=0.054), indicating no significant clustering of F I values. However, the significant relationship between FI and salinity, temperature, and mud did imply that a pattern exists. The lack of significance in the FI pattern could be attributed to the fact that eight sites had to be removed from analysis due to low numbers of specimens. Table 25. Summary table for percent contribution of foraminiferal taxa to each SIMPER group. Hallock et al. (2003) determined that the FI was re latively unaffected by grain size in the samples they analyzed, especially in th e most common median grain sizes for reef samples (Phi of 1 and 2). The majority of Bis cayne reefs also fell within this range. The range of FI values for 1 and 2 phi between the two studies were very similar (~2.5 to Group Stress-tolerant Smaller Miliolids Smaller Rotalids Agglutinated Symbiont-bearing Miliolids Symbiont-bearing Rotalids (parentheses indicate # of genera/group) 5.24 22.1 18.5 10.6 27.8 6.96 A (1) (2) (2) (2) (3) (2) 9.12 39.1 12.5 7.4 18.9 3.81 B (5) (9) (3) (2) (5) (2) 21.7 45.2 18.3 0 5.16 0 C (5) (8) (5) (0) (1) (0) 11.7 37.1 18.0 8.27 15.9 0 D (4) (9) (4) (2) (3) (0) 0 10.9 21.1 4.23 34.3 20.5 E (0) (2) (3) (1) (4) (3)

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70 6). This study even had a site approaching an FI v alue of 7. However, when the whole range of phi values was considered, there seemed to be some dependence on grain size that is not observed in the 2003 study (Fig. 14). This could be a result of the detail in which this study area was sampled allowing for more minute changes to be observed over a distance of one to two kilometers as opposed to t ens of kilometers. It could also be due to the variation in flow patterns affecting the ree fs in Biscayne National Park. One aspect of the FORAM Index that has been adjuste d since its inception is the definition of “opportunistic” taxa. In Hallock et al. (2003), only two genera ( Ammonia and Elphidium ) were specifically listed as opportunistic. Howev er, four families under which several genera may be opportunistic were also listed, including Bolivinidae and Buliminidae. For index calculations in this projec t Ammonia Ammobaculites, Bolivina, Bulimina, Cribroelphidium and Elphidium were all considered opportunistic or stresstolerant. Moreover, in Carnahan (2005), genera inc luded in the stress-tolerant category did not include Bolivina or Bulimina but did include Nonion Nonionoides and Nonoinella To compare the difference, a second index value was conducted excluding Bolivina and Bulimina and including Nonion Nonionoides and Nonoinella Both values are reported in Table 26. Another affect on the FI value was the presence of a particular genus of symbiont-bearing foraminifera that is not common in the western Atlantic, Monalysidium This genus was originally left out of the FORAM Index calculation for that reason, but a third calculation of FI values w as done including all of the genera of previously mentioned stress-tolerant taxa (as sugge sted by Carnahan et al. ( submitted ) as well as including Monalysidium as a symbiont-bearing foraminifer. This value is also listed in Table 26.

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71 The differences among all three calculations are mi nimal. The only site with a difference above 0.09 was replicate one of Reef 5.4 at 0.33 for the first calculation and 0.38 for the second calculation. The relatively la rge deviation is a result of the extremely low numbers of Foraminifera in this sample (27 fora minifers total). As a result, this sample is one of the eight that was removed from ot her analyses. Thus, whether the less common genera are considered as “other smaller” tax a or not has minimal influence on the FI where a sufficient sample size is present.

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72 a) b) Figure 14. FORAM Index values plotted against media n grain size represented by Phi values. a) is Figure 3 from (Hallock et al. 2003) w ith range of Phi sizes from this study noted, b) is grain-size data from this study.

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73 Table 26. Comparison of three different methods of calculating the FORAM Index. SiteRepFI Value FI value (Carnahan 2005) Difference FI Value (all stress tolerant genera and Monalysidium as symbiont-bearing) Difference 1.1R15.335.330.005.330.001.1R25.255.250.005.250.001.2R18.678.670.008.670.001.2R24.114.12-0.014.110.00SharkR17.717.710.007.710.00SharkR29.119.110.009.110.002.1R13.233.25-0.023.230.002.1R23.173.25-0.083.24-0.072.2R13.253.26-0.013.240.012.2R22.652.73-0.082.69-0.043.1R13.653.650.003.650.003.1R23.183.170.013.160.013.2R17.337.330.007.330.003.2R26.006.000.006.000.00BugR12.022.07-0.052.010.02BugR22.192.27-0.092.180.01ElkhornR16.446.440.006.440.00ElkhornR25.085.13-0.055.080.014.1R13.343.36-0.023.340.014.1R23.583.59-0.013.58-0.014.2R13.443.430.023.430.024.2R22.502.57-0.072.500.00PacificR18.368.360.008.360.00PacificR25.635.620.015.620.015.1R15.225.170.055.170.055.1R25.605.62-0.025.600.005.2R14.554.550.004.530.025.2R25.095.090.005.080.025.3R13.803.790.023.790.025.3R26.526.520.006.520.005.4R14.864.530.334.480.385.4R24.334.330.004.330.006.1R13.383.39-0.013.380.006.1R24.154.140.014.140.016.2R13.954.03-0.084.01-0.076.2R23.903.890.013.890.016.3R13.973.97-0.013.970.006.3R25.065.040.015.040.017.1R13.463.47-0.013.450.017.1R23.943.920.023.910.02StarR13.583.62-0.043.570.01StarR24.003.990.013.990.017.2R14.354.36-0.014.350.017.2R24.814.82-0.014.810.008.1R16.706.700.006.700.008.1R24.244.240.004.240.00NirvanaR14.674.670.004.670.00NirvanaR210.0010.000.0010.000.008.2R13.503.480.023.470.038.2R23.213.26-0.063.25-0.049.1R13.513.61-0.093.57-0.059.1R24.914.93-0.014.910.009.2R12.362.40-0.052.350.019.2R23.033.06-0.033.010.029.3R12.322.34-0.022.300.029.3R22.702.77-0.072.71-0.01LuganoR19.479.470.009.470.00LuganoR27.337.330.007.330.0010.1R12.002.000.002.000.0010.1R28.008.000.008.000.0010.2R15.805.800.005.800.0010.2R26.056.050.006.050.00DomeR13.053.07-0.013.040.01DomeR23.613.550.053.550.05

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74 Sediment-Constituent Assemblages The underlying premise of the SEDCON Index was base d on models first published by Hallock (1988). On subtropical Pacif ic atolls, which tend to be in very low-nutrient oceanic waters, symbiont-bearing foram inifers (i.e., mixotrophs) tend to be the dominant sediment constituent, followed by iden tifiable bits of coral (mixotrophs) and coralline algal (autotrophs) fragments, and wit h much smaller proportions of debris from calcareous algae (autotrophs), gastropods, ech inoids and smaller foraminifers (heterotrophs) (e.g., Hallock 1988). In areas with continental or upwelling influence that provides additional nutrient flux, the benthic comm unity becomes less dominated by mixotrophs, as calcareous, filamentous and fleshy a lgae become more prevalent, along with the gastropods and echinoids that feed upon th e algae. The skeletal debris of the autotrophic and heterotrophic carbonate producers s hould become more prevalent in the sediments. There will be more carbonate mud product ion, both through the breakdown of calcareous algal skeletons to aragonite needles, an d also because the gastropods and echinoids are bioeroding the carbonate substrate. As nutrient flux further increases, plankton densities increase, providing more food fo r filter-feeding sponges and bivalves, some of whom are very active bioeroders. In low en ergy environments, bioerosional debris includes large volumes of carbonate muds. H allock (1988) and Lidz and Hallock (2000) postulated that the proportion of unidentifi able fragments should increase in higher energy environments, where muds are swept aw ay. Thus, the formula Daniels (2005) proposed for the S EDCON index is based on the premise that if 100% of the sediments were iden tifiable coral fragments (not realistic), the SEDCON value would be 10. More realistic is th e possibility that 95% of the

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75 sediments could be shells of symbiont-bearing foram inifers, which would give a minimum SI value of 7.6, and up to 8.1 if the other 5% was coral fragments. If the sediments were 100% identifiable coralline and calc areous algae and molluscan and echinoid fragments, the SI value would be 2. Sedim ent composed 100% of unidentifiable carbonate grains would have a SI value of 0.1. Thu s, there must be mixotrophic contributors for the SI to be greater than 2, and t here must be unidentifiable debris for the SI to be less than 2. In the sediments collected from all of my sites, un identifiable grains typically were the most common constituent, so most of the SI values I calculated were <2. Where unidentifiable grains played a smaller role, calcar eous algae and mollusks played larger roles. Two sample groups were identified using the SIMPER procedure on the sediment constituent assemblage. Group A samples tended to have high mud fractions (17%) compared to Group B (1.1%). However, it is Group A that had the higher average SI value (Table 15), probably because the low energy e nvironment and abundant mud protected identifiable grains from further breakdow n. The overall range of SI values was very small, from 0.64 to 2.48. Thus, if the assump tions upon which the SI is based are valid, these SEDCON Index values indicate a benthic environment that is dominated by autotrophic and heterotrophic carbonate producers r ather than mixotrophs. There appears to be a problem in the underlying ass umptions of the SEDCON Index as it applies to the reefs in Biscayne Nation al Park, and possibly to other areas with extremes in hydrodynamic setting. The unidentifiab le category had significant negative correlations with all of the other constituents tha t represented nutrient signals and abundant food resources (Table 17). In an environm ent where bioerosion is a dominant

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76 process there should also be other indicators of in creased food sources that would stimulate the bioeroders and so one would expect th is relationship to be positive. Also, the positive correlation mentioned earlier between the calcareous algae, the “other” category, and the SI indicate another problem. Thi s correlation implies that where autotrophy and heterotrophy were high, the SI was h igher than elsewhere. This should not be the case since these constituents represent nutrification, which is detrimental to reef accretion. However, none of the reefs in BNP can be deemed “he althy” due to the narrow range of SI values, which may also pose a problem i n determining solutions to adjust the SEDCON Index. However, Daniels (2005), which is th e document defining the SEDCON Index, had a similar range of SI values from 0.92 to 2.58 across patch reefs and offshore reef sites in the Florida Keys. To more a dequately test this index, a gradient from healthy reef to degraded reef must be examined An Index Comparison Looking at Figures 8 and 12, the similarity between the two indices is obvious in their pattern, but inverse in their values. The tw o indices had a -0.53 Pearson’s correlation coefficient and a -0.40 Moran’s I. One index appears to be missing or misreading an important component that is causing t his inverse relationship. The problem appears to be in the SEDCON Index, with in grain size and the role of unidentifiable grains. Group A from the SEDCON SIMPER groups had three of the same reefs from Group C in the FORAM SIMPER groupin g. Both of these groups had the highest percent mud, but while the FORAM group has the lowest FI values, the SEDCON group had the highest SI values. Table 23, the correlation matrix between

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77 foraminiferal taxa and sediment constituents, showe d that unidentifiable grains positively correlate with those foraminifers that support alga l symbionts while negatively correlated with heterotrophic Foraminifera. This implies that areas with high percentages of unidentifiable grains are also suitable for algal s ymbiosis in foraminifera thereby indicating that conditions would also be favorable for algal symbiosis in corals. This may also be supported by the presence of a positive relationship between unidentifiables, symbiont-bearing and coralline algae, which is thou ght to provide a favorable substrate for juvenile corals to settle (Morse and Morse 1984 Raimondi and Morse 2000). The SEDCON Index provides a fast and easy assessmen t of the reef environment making it a simple and useful tool to add to a moni toring plan. But the point must be emphasized that it is a highly simplified, new anal ysis and some adjustments may need to be made in order for it to provide useful results. The SEDCON Index identifies the autotrophic/heterotrophic functional group as a com bined indicator of nutrient levels and food resources. At the same time, it separately ide ntifies percentages of unidentifiable grains as indicative of bioerosion, another proxy o f food resources. The problem identified by this research lies in thi s definition. The muddiest reefs were considered by the SEDCON Index to be the healt hiest because they had the least amount of unidentifiable grains. However, muddy se diments are likely an indication of calmer waters, and in calmer waters sediments are l ess likely to be affected by physical erosion thereby allowing more grains to be identifi able. Conversely, lack of mud in a sediment sample may be an indication of a higher en ergy environment. In this case, grains in the analyzed size fraction would be more likely to mobilize and experience physical erosion, thereby making them unidentifiabl e.

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78 Because there is an outflow of water from Biscayne Bay through Caesar’s Creek and because this creek is tidally dominated, the re efs in transect 5 must experience near constant water exchange. Since these reefs corresp ond to SIMPER groups A and E in the FORAM analysis, I deduced that these groups represe nt reefs in higher energy environments. Likewise, those reefs most dissimila r to groups A and E likely represent reefs in the lowest energy environment, i.e., group C. Following this logic, since Group C from the FORAM analysis overlaps with Group B from the SEDCON analysis, the reefs in Grou p B must also represent low energy environments. This is supported by the pres ence of mud accumulated in the sediment sample. In a simple attempt to validate this hypothesis, th e coefficients for the Pah and the Pu functional groups in the SEDCON Index equation wer e reversed. This increased the weighting of unidentifiables to now represent relat ive wave or current energy and down weighs the influence of indicators of increased nut rients. The results of this simple change as compared to the FORAM Index values can be seen in Figure 15. Thus, the two indices had a correlation coefficient of 0.59. When the SEDCON Index was originally created by Dan iels (2005), the results showed that the equation she developed correlated w ith percent coral cover for her sampled reefs in the Florida Keys. Also, the SI va lues she calculated had no correlation with percent mud. This is a likely cause for the d eficiencies in the index. The reefs off the Florida Keys, especially off of the middle and lower Keys, are subject to strong currents emerging from Florida Bay (Lidz 2005). Wi thout a large continuous landmass to divert the flow, muddy sediments cannot build up Thus, the SEDCON Index may

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79 provide an accurate depiction of a reef system on a n open shelf, but where landmasses prevent adequate circulation though a shallow reef environment, the influence of muddy sediments alters the interpretation of the index va lues. Figure 15. FORAM Index values plotted against modif ied SEDCON Index values Unfortunately, monitoring of coral cover in Biscayn e National Park is sparse and sporadic such that no data were available to compar e to the indices. While this would have been an interesting analysis, these indices ar e meant to describe the ability of a marine environment to support reef growth, not to d escribe the physical status of present reefs, so this lack of data is not an important iss ue. It is not the goal of this thesis to definitively c orrect the SEDCON Index. Merely, these findings suggest that the correlation between the two indices is strong enough to indicate that the SEDCON index could be viable with some alterations and should not be

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80 completely disregarded, but rather adjusted. In th e event that the SEDCON Index can be adjusted, the point should be made that the SEDCON Index had the smaller learning curve and also took less time to analyze in compari son to the FORAM Index. Actual microscope time required to process one sample from start to finish was consistently about one hour for the SEDCON Index. The processing time for the FORAM Index, depending on the grain size distribution of the sam ple, ranged in processing time from 45 minutes to three hours. For both indices, processi ng time decreased as experience was gained. Live Symbiont-bearing Foraminifera (LSF) The larger species diversity, along with the presen ce of Asterigerina carinata a species thought to be very tolerant of high energy environments (e.g., Crevison et al. 2006), as one of the contributing species to Group A’s similarity, indicates that this group is subject to sufficient amounts of water circulati on. This may minimize the effect that anthropogenic pollutants entering the reef system m ay have on these reefs, resulting in a relatively high mean FI value. Five of the seven r eefs in this group fall on the eastern most side of the sampling area and so are more expo sed to open ocean circulation patterns. Reef 1.1 was the only reef that exceeded Group A’s abundance of A. carinata This reef is also located in the vicinity of a tida lly influenced creek and would therefore also be exposed to higher energy flow. Amphistegina gibbosa the foraminifer on which the Photic Index is base d, were the most important contributor to Groups A and C, d espite the fact that Group C includes some of the muddiest reefs. This species accounts for the major difference between Groups B and C. A. gibbosa abundance never exceeded 61 individuals/100cm2, a density

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81 which Hallock (1995) considered as indicating subop timal conditions for Amphistegina Still, the relatively high abundance of live A. gibbosa specimens in the muddy Group C, as well as its relatively high overall density of L SF, can probably best be explained as a result of the “Goldilocks” nature of both symbiontbearing foraminifers and corals. While both corals and foraminifers historically thr ive on offshore reefs exposed to higher energy environments, and removal from local stresso rs near shore, the global increase of UV radiation also makes the clearest offshore reefs most vulnerable to photo-oxidative stress. I propose that this leaves the intermediat e reefs as the most suitable habitat remaining for continued reef growth (Fig. 16). Figure 16. Schematic of “Goldilocks” scenario reefs now face. Because the Photic Index is intended to detect glob al stressors and most of the reefs had the same impact level, this index was les s useful in defining a spatial pattern. However, the uniformity of the values did indicate that the study area may be suffering from chronic photic stress as well as some level of other stressors. While the other indices were useful in suggesting local incidences of stress, this index shows that the reefs are also subject to the global stress of incr eased UV radiation. Two reefs (1.1 and 9.3) had a value of five, meaning very few A. gibbosa and little or no bleaching. The low densities may indicate environmental conditions tha t are generally unfavorable for

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82 symbiotic organisms. However, Reef 1.1 had a numbe r of LSF that exceeded the overall mean, yet it did not have enough symbiont-bearing f orams in the sediment assemblage to include in other analyses. Reef 9.3, however, migh t have been expected to have a PI value of 5 given its place among SIMPER group C in the foraminiferal assemblage data. This index seemed to provide some additional qualit ative results for assessing the health of Biscayne patch reefs. However, while Amphistegina gibbosa can be found in depths less than five meters to depths of 100 meter s, they tend to be more abundant from 15 to 40 meters depth (Hallock 1999). The range of depths sampled in Biscayne National Park was less than two meters at Elkhorn reef to te n meters at reef 7.1. Because no reef fell within this zone of preference, the reefs are all comparable to each other. Figure 17 shows no relationship between the density of A. gibbosa and depth. Highly variable photic conditions are probably why A. gibbosa are generally less abundant at shallower depths. Where water transparency is more consisten t, Amphistegina abundances tend to be higher, even at depths of 1-2 meters. In regard s to the Photic Index, however, there may have been some complications in terms of the de nsity ranking since one would not expect to see large densities of A. gibbosa in such shallow waters to begin with. Despite this, the PI does indicate that photic stress was c hronic throughout the sampled area in May 2005.

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83 Figure 17. Densities of Amphistegina gibbosa (per 100cm2) plotted against depth showing no depth dependence for the sampled reefs Patch Reef Health An overall assessment of patch reef health in this area of Biscayne National Park would need to include coral cover data. However, b ased on the indices applied for this project (Table 27), I can conclude that for most of the reefs in the sampled area, reef accretion is negligible and the probability of reco very after an acute event, such as a hurricane, boat grounding, or bleaching, is low. T hese conclusions are in agreement with Fisher et al. (2007) and Dupont et al. ( in press ), which both include analyses of reef conditions in BNP. Dupont at al. ( in press ) conducted a comparative analysis of a coral cover data set from 1977 in Biscayne National Park with data sets collected in the 1990’s. Their results showed that there has been significant loss of cora l cover in that time period and that continued loss is probable. However, they also sho wed that over that time period species richness was relatively stable and concluded that r ecovery of the reef system may be possible if environmental conditions are restored.

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84 An interesting analogy to the Dupont et al. ( in press ) observations may be the discrepancy I observed between abundances of live s ymbiont-bearing foraminifers (LSF), which were quite variable (8-569/100cm2 of reef rubble), and the relatively few ( 10%) shells of symbiont-bearing foraminifers encountered during the SEDCON Index analysis. Results from the SEDCON Index revealed that the maj ority of the constituents were unidentifiable. The original assumption for the SED CON Index was that the unidentifiable fraction results primarily from bioe roded material, although certainly a significant component also can be physically abrade d fragments. The decadal-scale, precipitous decline in coral cover reported by Dupo nt et al. ( in press ) and present low coral cover (Miller et al. 2000, Moulding and Patte rson 2002) is consistent with the presence of relatively few recognizable coral fragm ents and shells of symbiont-bearing foraminifers. On the other hand, the presence and variable abundances of LSF are consistent with the Dupont et al. ( in press ) observation that coral species richness has not declined. That is, environmental conditions, inclu ding water quality, for the studied patch and bank reefs of Biscayne National Park gene rally support the survival of calcifying symbioses, including a diversity of cora l and LSF species, but not their dominance and production of significant proportions of the carbonate sediments. So the question then emerges, are the causes of the decadal-scale decline in coral cover on BNP patch reefs local, regional, or global ? Certainly the decline in Acropora spp. that once dominated, e.g., Elkhorn Reef, is li kely associated with the regional whiteband epidemic (Gladfelter 1982, Santavy et al. 2005 ). Similarly, the evidence for chronic photo-oxidative stress, as indicated by chronic lev els of bleaching in live Amphistegina

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85 gibbosa likely provides further evidence for at least par t of the decline being associated with global-change factors. However, local decline in water quality must also b e considered. Fisher et al. (2007) documented that coral-lesion recovery at Ali na’s Reef in BNP was poor, but that the presence of large coral heads with substantial live tissue indicated that the stress was relatively recent. Alina’s Reef lies in the plume from Caesar’s Creek. Moreover, Downs et al. (2006) documented evidence for xenobiotic st ress in reef fish at Alina’s Reef. Additionally, the dredging associated with the main tenance of Hawk Channel could be a major source of mud and re-suspended nutrients and/ or toxins. Finally, assessing the indices themselves, they dem onstrated both applications and limitations. First of all, each of the indices ind icates something different. The SEDCON Index reflects a) the community structure relative to calcifying symbioses (stony coral and symbiont-bearing foraminifers) versus sediment production by calcifying autotrophs and heterotrophs, and b) the accretion potential as reflected by proportions of coral and calcareous algal production versus bioeroded materi al. The FORAM Index also indicates the relative suitability of the environment for cal cifying symbioses. Unfortunately both indices are influenced by sediment texture, especia lly sediments with significant proportions of mud. Therefore, comparing sediments of relatively similar textures is advisable. The inverse correlation between the SED CON and FORAM indices in my samples indicates that, at low SEDCON values, produ ction by calcareous algae can overwhelm production by symbiont-bearing foraminife rs, even when live symbiontbearing foraminifers can be found in some abundance in the environment. Thus, the

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86 indices should be evaluated independently and over a general area, and are not sufficiently sensitive enough to reflect subtle dif ferences among similar patch reefs. Similarly, the three potential indices provided by assessing LSF indicate again somewhat different aspects of the environment. Esp ecially in very shallow environments, Amphistegina gibbosa densities can be quite variable, so their widespre ad presence at intermediate densities on BNP patch and bank reefs indicated that environmental conditions were generally favorable, at least during the time of sampling. Similarly, those densities combined with evidence f or chronic bleaching indicated that water quality, including water transparency, was su fficient for photo-oxidative stress to be occurring, but that the stress was not acute. F isher (2007), reporting on a variety of diagnostic parameters on upper Florida Keys patch r eefs, found that chronic bleaching in A. gibbosa tended to be most prevalent at the reefs that cons istently had the highest densities of A. gibbosa and the best rates of recovery of coral lesions. Finally, the overall densities of LSF revealed generally intermediate ab undances with substantial variability among reefs. These trends again show that conditio ns are suitable for their persistence but not dominance as sediment producers. And all o f these trends support the assumption, presented in Figure 16, that Florida’s coral reefs and reef-associated biota today are being squeezed between the impacts of inc reasing terrestrial influence as humans alter coastal habitats, and increasing photo -oxidative stresses associated with stratospheric ozone depletion and global climate ch ange. Islands v Inlet: Sources of Stress or Security? The two islands that separate Biscayne Bay from the open shelf (Elliot Key and Old Rhode’s Key) may be influencing the patch reefs in the sampled area in both positive

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87 and negative ways. First, the Keys prevent Biscayn e Bay waters from directly influencing the reef environment. However, in doin g so, they are also limiting the area of water flow and forcing higher velocity exchange thr ough Caesar’s Creek. As velocity decreases with distance from the creek there is lik ely to be flocculation of muds, and potentially pollutants, out of the water column and on to the reefs more distant from Caesar’s Creek. On the other hand, reefs in proxim ity to the undeveloped islands may be more sheltered from the effects of harmful UV radia tion by higher concentrations of colored dissolved organic matter (CDOM) produced by the mangroves on the islands. Conversely, Caesar’s Creek may be the main source o f pollution from within Biscayne Bay onto the reefs, which may result in a larger nutrient flux on those reefs in its immediate proximity, however, the constant wate r motion may prevent any more serious pollutants and heavy metals from settling o n the reef. Additionally, turbidity caused by the water motion may also add some protec tion from the increased levels of UV radiation. Because my analysis did not include water transpare ncy analyses or sediment toxicology studies, it would be hard to say for sur e which, the islands or the inlet, is a greater cause/source of stress and to what degree. However, these would be interesting aspects to research in the future. Also, because t he reefs in this area seem to be affected by chronic photic stress, the beneficial effects of the islands and the inlet, relative to water transparency, may be very important to the pe rsistence of the reefs in Biscayne National Park.

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88 Table 27. Summary of data presented in this report as rankings. indicates insufficient specimens (< 50 per sample) to calculate the index or index ranking. AmphisteginaAmphistegina Rank DefinitionFISIbleachingdensityLSF density 1 poor<2<2>40%<10<10 2 marginal2-42-45-40%10-10010-100 3 good>4>4<5%>100>100 SiteFI RankSI RankBleach RankAmphi RankLSF Rank 1.13.00*1.003.00*1.003.001.23.001.002.00*2.003.00 Shark3.00*1.002.00*2.002.00 2.12.001.002.00*2.002.002.22.001.002.00*1.002.003.12.001.002.00*2.002.003.23.00*1.002.00*2.003.00 Bug2.001.002.00*2.002.00 Elkhorn3.001.002.00*2.002.00 4.12.001.002.002.003.004.22.001.002.00*2.002.00 Pacific3.001.002.00*2.002.00 5.13.001.002.00*2.002.005.23.001.002.00*1.002.005.33.001.002.00*2.002.005.43.00*1.002.00*2.002.006.12.001.002.00*1.002.006.22.001.002.00*2.003.006.33.001.002.00*2.003.007.12.001.002.00*1.003.00 Star2.001.002.00*2.002.00 7.23.001.002.00*2.003.008.13.00*1.002.00*2.002.00 Nirvana3.00*1.002.002.003.00 8.22.001.002.002.003.009.13.001.002.00*1.002.009.22.002.002.00*2.002.009.32.002.003.00*1.001.00 Lugano3.00*1.002.00*2.003.00 10.13.00*1.002.002.002.0010.23.001.002.00*2.003.00 Dome2.001.002.00*2.003.00

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89 CONCLUSIONS 1. The pattern of salinity, temperature, and percent m ud indicate waters emerging from Biscayne Bay through Caesar’s Creek into the s tudy area. 2. The influence of the water emerging from the bay is reflected in the FORAM and SEDCON Indices. 3. Analyses of both the FORAM Index and the SEDCON Ind ex produced SIMPER groups that seemed to reflect physical processes th at are affecting the reefs (i.e., high and low energy environments). The FORAM Index created more distinct groupings that reflected transitional conditions. 4. The SEDCON Index was faster and easier to apply, wh ile the FORAM Index produced more inter-reef detail. Moreover, the BNP samples revealed previously undocumented dependence of both indices on sediment texture. 5. Each of the potential biotic indicators, i.e., the SEDCON Index, the FORAM Index, and each of three parameters associated with living symbiont-bearing foraminifers, reveals slightly different aspects of environmental conditions, providing a potential diagnostic suite that appears more robust for the area than any single parameter. 6. Based on the suite of biotic indicators, environmen tal conditions throughout most of the high density patch reefs in Biscayne Nationa l Park appear to be marginal

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90 for reef growth. The average FI value across all r eefs was 4.12; the average SI value was 1.26. Amphistegina gibbosa densities averaged 24 specimens per 100 cm2, while total LSF densities averaged 102 specimens per 100 cm2. 7. Global and regional stressors, such as white-band d isease, increased shortwavelength solar radiation associated with stratosp heric ozone depletion, and increasing sea-surface temperatures, are likely com pounding the effects of declining local water quality. Reef recovery from an acute event in this area is likely to be poor. 8. Long-term monitoring of environmental variables and coral cover should be conducted to determine if the net effect of the wat er emerging from Biscayne Bay is positive or negative. This includes but is not limited to monitoring for heavy metals and pesticides that are known to accumulate within the Bay.

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91 REFERENCES Anselin L, Syabri I, Kho Y (2006) GeoDa: An Introdu ction to Spatial Data Analysis. Geographical Analysis 38:5-22 Bathurst RGC (1976) Carbonate Sediments and Their D iagenesis. Elsevier Scientific Publishing Company, New York Beaver CR, Jaap WC, Porter JW, Wheaton J, Callahan M, Kidney J, Kupfner S, Torres C, Wade S, Johnston D (2005) Coral Reef Evaluation and Monitoring Project, 2004 CREMP Executive Summary. Fish and Wildlife Research Institute, St Petersburg 12 Brock J, Wright CW, Clayton T, Nayegandhi A (2004) LIDAR optical rugosity of coral reefs in Biscayne National Park, Florida. Coral Ree fs 23:48-59 Carnahan EA (2005) Foraminiferal assemblages as bio indicators of potentially toxic elements in Biscayne Bay, Florida. Thesis, Universi ty of South Florida. Tampa, FL Carnahan EA, Hoare AM, Hallock P, Lidz BH, Reich CD (2008) Distribution of Heavy Metals and Foraminiferal Assemblages in Sediments o f Biscayne Bay, Florida, USA. Journal of Coastal Research 24:159–169 Carnahan EA, Hoare AM, Hallock P, Lidz BH, Reich CD ( submitted ) Foraminiferal assemblages in Biscayne Bay, Florida, USA: Response s to urban and agricultural pollution in a subtropical estuary Clarke KR, Gorley, RN (2006) PRIMER v6: User Manual /Tutorial. Primer-E, Plymouth Clarke KR, Warwick, RM (2001) Change in marine comm unities: an approach to statistical analysis and interpretation. PRIMER-E, Plymouth Cockey E, Hallock P, Lidz BH (1996) Decadal-scale c hanges in benthic foraminiferal assemblages off Key Largo, Florida. Coral Reefs 15: 237-248 Crevison HL, Hallock P, McRae G (2006) Sediment cor es from the Florida reef tract: is resolution sufficient for environmental application s? Journal of Environmental Micropaleontology, Microbiology, and Meiobenthology 3:61-82.

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92 Daniels CA (2005) Coral reef assessment an index ut ilizing sediment constituents. Thesis (unpublished), University of South Florida. Tampa, FL Dix TL (2001) The distribution and ecology of benth ic foraminifera of Tampa Bay, Florida. PhD Dissertation (unpublished), University of South Florida. Tampa, FL Done TJ (1992) Phase shifts in coral reef communiti es and their ecological significance. Hydrobiologia 247:121-132 Downs C, Fauth J, Wetzel D, Hallock P, Halas J, Cur ry R, Woodley C (2006) Investigating Coral Reef Degradation at Alina's Ree f in the Florida Keys: Cellular Physiology of White Grunt (Haemulon plumieri ) as a Biological Indicator. Environmental Forensics 7:15-32 Dupont JM, Jaap WC, Hallock P ( in press ) A retrospective analysis and comparative study of stony coral assemblages in Biscayne Nation al Park, FL (1977-2000) Dustan P (1999) Coral reefs under stress: sources of mortality in the Florida Keys. Natural Resources Forum 23: 147-155 Fisher E (2007) Assessing the health of coral reef ecosystems in the Florida Keys at community, individual and cellular scales. PhD Diss ertation. University of South Florida, Tampa, Fla. Fisher EM, Fauth JE, Hallock P, Woodley CM (2007) L esion regeneration rates in reefbuilding corals Montastraea spp. as indicators of c olony condition. Marine Ecology Progress Series 339:61-71 Folk RL (1974) Petrology of sedimentary rocks. Hemp hill's, Austin, Tex. Fujita K, Hallock P (1999) A comparison of phytal s ubstrate preferences of Archaias angulatus and Sorites orbiculus in mixed macroalgal-seagrass beds in Florida Bay. Journal of Foraminiferal Research 29:143-151 Ginsburg RN, Shinn EA (1993) Preferential Distribut ion of the Reefs in the Florida Reef Tract: the Past is the Key to the Present. Global A spects of Coral Reefs, Health Hazards and History: H21-H26 Ginsburg RN, Gischler E, Kiene WE (2001) Partial mo rtality of massive reef-building corals: an index of patch reef condition, Florida R eef Tract. Bulletin of Marine Science 69:1149-1173 Gladfelter WB (1982) White-band disease in Acropora palmata : implications for the structure and growth of shallow reefs. Bulletin of Marine Science 32: 639-643

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93 Hallock P (1987) Fluctuations in the trophic resour ce continuum: a factor in global diversity cycles? Paleoceanography 2:457-471 Hallock P (1988) The role of nutrient availability in bioerosion: Consequences to carbonate buildups. Palaeogeography, Palaeoclimatol ogy, Palaeoecology 63:275-291 Hallock P (1995) Amphistegina (Foraminiferida) Dens ities as a Practical, Reliable, LowCost Indicator of Coral Reef Vitality A Coral Reef Symposium on Practical, Low Cost Monitoring Methods for Assessing the Biota and Habi tat Conditions of Coral Reefs. Office of Ocean and Coastal Resource Management, Na tional Oceanic and Atmospheric Association, Silver Spring, MD 37-44 Hallock P (1999) Symbiont-bearing Foraminifera. In: Sen Gupta BK (ed) Modern foraminifera. Kluwer Academic Publishers, Dordrecht ; Boston Hallock P (2000a) Symbiont-Bearing Foraminifera: Ha rbingers of Global Change? Micropaleontology 46:95-104 Hallock P (2000b) Larger Foraminifera as Indicators of Coral Reef Vitality. In: Martin R (ed) Environmental Micropaleontology: The Applicati on of Microfossils to Environmental Geology. Kluwer Academic/Plenum Publi shers, New York, Dordrecht, pp121-150 Hallock P, Schlager W (1986) Nutrient Excess and th e Demise of Coral Reefs and Carbonate Platforms. PALAIOS 1:389-398 Hallock P, and Talge HK (1993) Symbiont loss (bleac hing) in benthic foraminifera; implications for biomineralization and sediment pro duction. Geological Society of America (Abstracts) 25: 139 Hallock P, Forward LB, Hansen HJ (1986) Influence o f environment on the test shape of Amphistegina. Journal of Foraminiferal Research 16: 224-231 Hallock P, Barnes K, Fisher EM (2004) From satellit es to molecules: A multiscale approach to environmental monitoring and risk asses sment of coral reefs. Journal of Environmental Micropaleontology, Microbiology, and Meiobenthology 1:11-39 Hallock P, Lidz BH, Cockey-Burkhard EM, Donnelly KB (2003) Foraminifera as Bioindicators in Coral Reef Assessment and Monitori ng: The FORAM Index. Environmental Monitoring and Assessment 81: 221-238 Hallock P, Muller-Karger FE, and Halas JC (1993) Co ral reef decline. National Geographic Research and Exploration 9: 358-378

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94 Hallock P, Talge HK, Cockey EM, Muller RG (1995) A new disease in reef-dwelling Foraminifera; implications for coastal sedimentatio n. Journal of Foraminiferal Research 25:280-286 Hallock P, Williams DE, Fisher EM, Toler SK (2006) Bleaching in Foraminifera with Algal Symbionts: Implications for Reef Monitoring a nd Assessment. Anurio do Instituto de Geocincias 29: 108-128 Hoegh-Guldberg O (1999) Climate Change, coral bleac hing, and the future of the world’s coral reefs. Marine and Freshwater Resources 50: 83 9-866 Houghton JT, Ding Y, Griggs DJ, Noguer M, van der L inden PJ, Dai X, Maskell K, Johnson CA eds. (2001) Climate Change 2001: The Sci entific Basis: Contributions of Working Group I to the Third Assessment Report of t he Intergovernmental Panel on Climate Change Jaap WC, Wheaton J (1977) Report to National Park S ervice: Biscayne National Monument reef studies Kleypas JA, Feely RA, Fabry VJ, Langdon C., Sabine CL, Robbins LL (2006) Impacts of Ocean Acidification on Coral Reefs and Other Marine Calcifiers: A Guide for Future Research, report of a workshop held 18–20 April 200 5, St. Petersburg, FL, sponsored by NSF, NOAA, and the U.S. Geological Survey, 88 pp Latimer JS, Davis WR, Keith DJ (1999) Mobilization of PAHs and PCBs from In-Place Contaminated Marine Sediments During Simulated Resu spension Events. Estuarine, Coastal and Shelf Science 49:577-595 Lapointe BE, Clark MW (1992) Nutrient Inputs from t he Watershed and Coastal Eutrophication in the Florida Keys. Estuaries 15:46 5-476 Laws EA, Redalje DG (1979) Effect of sewage enrichm ent on the phytoplankton population of a subtropical estuary. Pacific Scienc e 33:129-144 Lee JJ, Anderson OR (1991) Symbiosis in Foraminifer a. In: Lee JJ, Anderson OR (eds) Biology of Foraminifera. Academic Press Limited, Sa n Diego, CA, pp157-220 Lidz BH (1997) Fragile Coral Reefs of the Florida K eys: Preserving the Largest Reef Ecosystem in the Continental U.S. US Geological Sur vey Open-File Report 97-453 Lidz B (2005) Mapping Benthic Ecosystems and Enviro nments in the Florida Keys Open-File Report. U.S. Geological Survey, St. Peter sburg, FL Lidz BH, Hallock P (2000) Sedimentary petrology of a declining reef ecosystem, Florida Reef Tract (U.S.A.). Journal of Coastal Research 16 :675-697

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95 Lirman D, Orlando B, Maci S, Manzello D, Kaufman L Biber P, Jones T (2003) Coral communities of Biscayne Bay, Florida and adjacent o ffshore areas: diversity, abundance, distribution, and environmental correlates. Aquatic Conservation: Marine and Freshwater Ecosystems 13:121-135 Marszalek DS, Babashoff G, Noel MR, Worley DR (1977 ) Reef Distribution in South Florida. Proceedings, Third International Coral Ree f Symposium, RSMAS, University of Miami. 2: 223-229 McManus JW, Polsenberg JF (2004) Coral-algal phase shifts on coral reefs: Ecological and environmental aspects. Progress In Oceanography 60:263-279 Miller MW, Weil E, Szmant AM (2000) Coral recruitme nt and juvenile mortality as structuring factors for reef benthic communities in Biscayne National Park, USA. Coral Reefs 19:115-123 Molina MJ, Rowland FS (1974) Stratospheric sink for chlorofluoromethanes: chlorine atomc-atalysed destruction of ozone. Nature 249:810 -812 Morse ANC, Morse DE (1984) Recruitment and metamorp hosis of Haliotis larvae induced by molecules uniquely available at the surf aces of crustose red algae. Journal of Experimental Marine Biology and Ecology 75: 191-215 Moulding A, Patterson M (2002) Biscayne National Pa rk coral reef inventory and monitoring project. Final Report. National Park Ser vice, Homestead Porter, JW, Meier OW (1992) Quantification of loss and change in Floridian reef coral populations. American Zoologist 32: 625 640 Raimondi PT, Morse ANC (2000) The Consequences of C omplex Larval Behavior in a Coral. Ecology 81:3193-3211 Randel WJ, Stolarski RS, Cunnold DM, Logan JA, Newc hurch MJ, Zawodny JM (1999) Trends in the Vertical Distribution of Ozone. Scien ce 285:1689-1692 Reaser JK, Pomerance R, Thomas PO (2000) Coral Blea ching and Global Climate Change: Scientific Findings and Policy Recommendati ons. Conservation Biology 14(5): 1500-1511 Roscoe HK (2001) The Risk of Large Volcanic Eruptio ns and the Impact of this Risk on Future Ozone Depletion. Natural Hazards 23:231-246

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96 Santavy DL, Summers JK, Engle VD, Harwell LC (2005) The condition of coral reefs in South Florida (2000) using coral disease and bleach ing as indicators. Environmental Monitoring and Assessment 100: 129-152 Scoffin TP (1987) An Introduction to Carbonate Sedi ments and Rocks. Chapman and Hall, New York Sen Gupta BK (1999) Modern foraminifera. Kluwer Aca demic Publishers, Dordrecht ; Boston Shick JM, Lesser MP, Jokiel PL (1996) Effects of ul traviolet radiation on corals and other coral reef organisms. Global Change Biology 2 :527-545 Shinn EA, Lidz BH, Kindinger JL, Hudson JH, Halley RB (1989) Reefs of Florida and the Dry Tortugas: A Guide to the Modern Carbonate E nvironment of the Florida Keys and the Dry Tortugas. American Geophysical Union, I nternational Geological Congress Field Trip Guidebook T176 Szmant AM (2002) Nutrient Enrichment on Coral Reefs : Is It a Major Cause of Coral Reef Decline? Estuaries 25:743-766 Talge HK, Hallock P (2003) Ultrastructural Response s in Field-Bleached and Experimentally Stressed Amphistegina gibbosa (Class Foraminifera). The Journal of Eukaryotic Microbiology 50:324-333 Wang JD, Luo J, Ault JS (2003) Flows, Salinity, and Some Implications for Larval Transport in South Biscayne Bay, Florida. Bulletin of Marine Science 72(3): 695–723 Williams DE (2002) Population Ecology of BleachingStressed Amphistegina gibbosa in the Florida Keys (1991-1999): Influence of Solar Ra diation on Reef Dwelling Foraminifera. PhD Dissertation (unpublished), Unive rsity of South Florida. Tampa, FL Williams DE, Hallock P (2004) Bleaching in Amphistegina gibbosa d’Orbigny (Class Foraminifera): observations from laboratory experim ents using visible and ultraviolet light. Marine Biology 145: 641-649 Williams DE, Hallock P, Talge HK, Harney JN, McRae G (1997) Responses of Amphistegina gibbosa Populations in the Florida Keys (USA) to a Multi-Y ear Stress Event (1991-1996). Journal of Foraminiferal Researc h 27(4): 264-269 Yanko V, Arnold AJ, Parker WC (1999) Symbiont-beari ng Foraminifera. In: Sen Gupta BK (ed) Modern foraminifera. Kluwer Academic Publis hers, Dordrecht; Boston

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97 APPENDICES

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98 Appendix I. Results of grain-size analysis, percent weight of s ize fraction. Bold indicates median size fraction. Shading represents size fract ion analyzed for the SEDCON Index. PHI SIZES -101234>4 SiteReplicate > 2mm>1mm>0.5mm>0.25mm >0.125mm >0.063mm <0.063mm 1.1R121.41% 44.54% 31.13%2.12%0.26%0.18%0.37% 1.1R210.50%23.50% 50.72% 13.28%1.20%0.32%0.48% 1.2R13.69% 59.40% 33.05%3.10%0.46%0.16%0.14% 1.2R210.72%35.79% 31.74% 18.49%2.49%0.32%0.45% SharkR10.03%5.64% 85.36% 8.77%0.17%0.01%0.01% SharkR20.67%13.73% 74.10% 11.11%0.36%0.02%0.03% 2.1R146.20% 37.74% 11.47%2.64%0.95%0.42%0.58% 2.1R236.88% 39.35% 19.34%2.88%0.68%0.32%0.55% 2.2R116.53%27.57% 33.08% 14.11%4.48%2.50%1.73% 2.2R210.98%20.55% 29.12% 17.88%10.05%5.92%5.49% 3.1R19.23%26.95% 28.28% 15.96%13.12%5.52%0.95% 3.1R27.66%20.05% 34.34% 21.61%10.85%4.10%1.39% 3.2R141.20% 51.13% 7.37%0.23%0.04%0.02%0.02% 3.2R27.39%42.19% 45.61% 4.67%0.12%0.00%0.02% BugR19.42%9.56%13.98%11.94% 13.47% 16.81%24.81% BugR27.52%4.82%8.94%11.42%12.74% 14.33% 40.23% ElkhornR127.86% 48.55% 20.64%2.11%0.54%0.15%0.14% ElkhornR29.70%22.49% 42.67% 18.51%4.56%0.96%1.12% 4.1R110.36%16.74% 27.66% 22.27%15.71%3.63%3.62% 4.1R29.04%14.66%25.06% 23.22% 17.28%4.87%5.88% 4.2R110.10%8.09%17.34% 27.71% 22.71%6.48%7.58% 4.2R26.84%12.22%21.57% 19.77% 17.25%6.54%15.80% PacificR11.21%10.06% 70.43% 17.05%1.08%0.06%0.12% PacificR26.53%36.98% 47.37% 7.39%1.38%0.20%0.15% 5.1R14.66%19.83% 58.52% 14.89%1.73%0.18%0.18% 5.1R218.05% 51.45% 22.01%5.54%2.23%0.39%0.33% 5.2R18.30%19.85% 49.15% 19.64%2.16%0.29%0.62% 5.2R23.42%12.08% 50.02% 29.07%3.32%0.48%1.62% 5.3R14.55%25.04% 54.91% 12.67%2.18%0.30%0.34% 5.3R214.13%28.11% 45.05% 9.61%1.69%0.34%1.06% 5.4R115.00% 36.28% 40.97%5.35%1.35%0.34%0.71% 5.4R210.44%36.74% 40.40% 8.53%2.73%0.51%0.66%

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99 Appendix I. (Continued) Results of grain-size analysis, percent weight of s ize fraction. Bold indicates median size fraction. PHI SIZES -101234>4 SiteReplicate > 2mm>1mm>0.5mm>0.25mm >0.125mm >0.063mm <0.063mm 6.1R17.61%10.51%21.34% 27.49% 27.26%4.45%1.35% 6.1R25.99%14.36% 29.65% 24.71%19.52%3.74%2.02% 6.2R117.35%24.02% 47.91% 9.41%0.89%0.13%0.28% 6.2R22.18%11.32% 52.32% 30.15%3.50%0.48%0.06% 6.3R10.58%2.83%35.65% 43.66% 15.83%1.16%0.29% 6.3R21.58%2.98%30.50% 40.90% 21.10%1.93%1.02% 7.1R19.44%17.65% 33.51% 20.31%9.40%5.35%4.34% 7.1R27.16%20.50% 37.39% 20.94%7.92%3.55%2.52% StarR112.24%16.04% 29.54% 24.42%13.86%1.73%2.16% StarR25.87%6.61%14.92% 35.07% 31.99%2.77%2.77% 7.2R17.78%12.97% 37.10% 31.62%7.96%1.09%1.47% 7.2R212.83%12.77% 40.36% 25.21%5.83%1.04%1.96% 8.1R15.80%39.69% 48.21% 5.49%0.49%0.09%0.24% 8.1R213.42% 60.55% 25.37%0.51%0.01%0.00%0.15% NirvanaR18.95% 45.75% 40.29%4.65%0.26%0.04%0.06% NirvanaR23.07%32.97% 60.63% 3.12%0.14%0.02%0.06% 8.2R116.15%23.90% 29.29% 18.05%8.91%2.06%1.64% 8.2R27.31%10.27%17.27% 17.27% 15.77%8.39%23.71% 9.1R18.42%15.23% 37.48% 23.41%11.17%2.97%1.32% 9.1R29.10%8.77%26.75% 29.70% 17.20%4.86%3.62% 9.2R12.50%4.44%10.12%17.84% 24.71% 23.04%17.34% 9.2R24.70%6.84%16.24%17.18% 19.25% 18.47%17.33% 9.3R16.61%11.48%21.75% 15.59% 13.72%12.07%18.78% 9.3R24.83%8.51%19.84% 14.77% 12.81%11.31%27.92% LuganoR10.44%36.20% 58.31% 4.72%0.10%0.02%0.21% LuganoR215.20% 38.22% 41.28%4.84%0.30%0.06%0.10% 10.1R17.09% 74.84% 17.54%0.31%0.02%0.01%0.19% 10.1R23.26%39.95% 53.10% 3.25%0.31%0.04%0.09% 10.2R14.65%18.02% 51.43% 22.00%3.70%0.14%0.05% 10.2R21.00%13.29% 58.12% 23.05%4.17%0.23%0.14% DomeR16.58%17.43% 31.21% 25.58%14.24%1.75%3.21% DomeR211.93%15.32% 23.92% 19.95%15.44%4.05%9.39%

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100 Appendix I. (Continued) Average grain-size for each site. Values for perce nt mud used in correlations and plotting were taken from this t able. PHI SIZES -1 0 1 2 3 4 >4 Reef Site> 2mm>1mm>0.5mm>0.25mm>0.125mm>0.063mm<0.0 63mm 1.115.95%34.02% 40.92% 7.70%0.73%0.25%0.43% 1.27.21% 47.60% 32.40%10.80%1.47%0.24%0.29% Shark 0.35%9.68% 79.73% 9.94%0.26%0.02%0.02% 2.141.54% 38.55% 15.40%2.76%0.81%0.37%0.56% 2.213.75%24.06% 31.10% 16.00%7.27%4.21%3.61% 3.18.44%23.50% 31.31% 18.79%11.98%4.81%1.17% 3.224.30% 46.66% 26.49%2.45%0.08%0.01%0.02% Bugs 8.47%7.19%11.46%11.68% 13.11% 15.57%32.52% Elkhorn 18.78% 35.52% 31.65%10.31%2.55%0.56%0.63% 4.19.70%15.70% 26.36% 22.74%16.50%4.25%4.75% 4.28.47%10.16%19.45% 23.74% 19.98%6.51%11.69% Pacific 3.87%23.52% 58.90% 12.22%1.23%0.13%0.13% 5.111.36%35.64% 40.26% 10.21%1.98%0.29%0.26% 5.25.86%15.97% 49.58% 24.35%2.74%0.38%1.12% 5.39.34%26.58% 49.98% 11.14%1.94%0.32%0.70% 5.412.72%36.51% 40.69% 6.94%2.04%0.42%0.68% 6.16.80%12.43%25.50% 26.10% 23.39%4.09%1.69% 6.29.77%17.67% 50.11% 19.78%2.19%0.31%0.17% 6.31.08%2.90%33.07% 42.28% 18.46%1.55%0.65% 7.18.30%19.08% 35.45% 20.62%8.66%4.45%3.43% Star 9.06%11.32%22.23% 29.74% 22.93%2.25%2.46% 7.210.31%12.87% 38.73% 28.41%6.89%1.07%1.72% 8.19.61% 50.12% 36.79%3.00%0.25%0.05%0.19% Nirvana 6.01%39.36% 50.46% 3.88%0.20%0.03%0.06% 8.211.73%17.08% 23.28% 17.66%12.34%5.23%12.68% 9.18.76%12.00% 32.11% 26.56%14.18%3.91%2.47% 9.23.60%5.64%13.18%17.51% 21.98% 20.75%17.33% 9.35.72%9.99%20.80% 15.18% 13.27%11.69%23.35% Lugano 7.82%37.21% 49.80% 4.78%0.20%0.04%0.15% 10.15.18% 57.40% 35.32%1.78%0.17%0.03%0.14% 10.22.82%15.66% 54.78% 22.53%3.94%0.19%0.10% Dome 9.25%16.37% 27.56% 22.77%14.84%2.90%6.30%

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101 Appendix II-a. List of foraminiferal genera found within the patch reefs of Biscayne National Park by this study. Symbiont-bearing Cycloforina Siphonaperta Amphistegina Cymbaloporetta Siphonina Androsina Disconorbis Siphoninoides Archaias Discorbinella Spiroloculina Asterigerina Discorbis Textularia Borelis Fischerinella Treromphalus Broekina Eponides Triloculina Cyclorbiculina Floresina Triloculinella Gypsina Fursenkoina Wiesnerella Heterostegina Glabratella Laevipeneroplis Glabratellina Monalysidium Globigerinoides Peneroplis Globocassidulina Sorites Globorotalia Stress-tolerant Globulina Ammonia Guttulina Ammobaculites Haplophragmoides Bolivina Hauerina Bulimina Lachlanella Cribroelphidium Lobatula Elphidium Miliolinella Haynesina Montfortella Nonion Neocornorbina Nonionella Neoeponides Nonionoides Patellina Heterotrophic Planorbulina Adelosina Polymorphina Affinetrina Poroepodines Anomalinoides Pseudohauerina Articulina Pyrgo Astrononion Quinqueloculina Bigenerina Rectobolivina Brizalina Reophax Cancris Reussella Carpenteria Rosalina Cibicides Sigmavirgulina Clavulina Sigmoilina Cornuspira Sigmoilinita

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102 Appendix II-b. Raw counts of foraminiferal genera from the two se diment replicates of 32 reefs in Biscayne National Park. 1.1R11.1R21.2R11.2R2SharkR1SharkR22.1R12.1R2Amphistegina5112Androsina1Archaias720223524Asterigerina331114BorelisBroekinaCyclorbiculina144 1GypsinaHeterosteginaLaevipeneroplis261411811Monalysidium1Peneroplis1 11SoritesAmmonia11 3AmmobaculitesBolivina2Bulimina112Cribroelphidium24Elphidium311Haynesina31NonionNonionellaNonionoidesAdelosina11Affinetrina1AnomalinoidesArticulina12AstrononionBigenerina1 1Brizalina1CancrisCarpenteriaCibicides1 1Clavulina11Cornuspira1 1Cycloforina2221CymbaloporettaDisconorbisDiscorbinella1Discorbis2321933FischerinellaEponides1 4Floresina

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103 Appendix II-b. (Continued) 1.1R11.1R21.2R11.2R2SharkR1SharkR22.1R12.1R2FursenkoinaGlabratella1Glabratellina2Globigerinoides1Globocassidulina1Globorotalia1GlobulinaGuttulinaHaplophragmoidesHauerinaLachlanella111Lobatula1Miliolinella34MontfortellaNeocornorbina1 1NeoeponidesPatellinaPlanorbulina3 4PolymorphinaPoroepodines1PseudohauerinaPyrgo1 1Quinqueloculina732115435Rectobolivina1Reophax1ReussellaRosalina151715SigmavirgulinaSigmiolina5Sigmiolinita3Siphonaperta21046Siphonina1Siphoninoides1Spiroloculina12Textularia143137Treromphalus1Triloculina2316137Triloculinella225Wiesnerella12Total Forams 12443013479136146 Density (forams/g) 12443013479444209 Number of genera716527552839Foram Index 5.335.258.674.117.719.113.233.24 SIMPER Group ADB

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104 Appendix II-b. (Continued) 2.2R12.2R23.1R13.1R23.2R13.2R2BugR1BugR2Amphistegina128AndrosinaArchaias9410821Asterigerina3Borelis111Broekina21231Cyclorbiculina1Gypsina1HeterosteginaLaevipeneroplis1071710138MonalysidiumPeneroplis1211Sorites1111Ammonia817 3AmmobaculitesBolivina34 1113Bulimina3115Cribroelphidium24 55Elphidium114135135Haynesina171255Nonion2 1NonionellaNonionoides31 4Adelosina121 1Affinetrina1AnomalinoidesArticulina5712AstrononionBigenerina1Brizalina11 1CancrisCarpenteriaCibicides11211Clavulina1Cornuspira11323Cycloforina23433Cymbaloporetta1Disconorbis3215Discorbinella1 2Discorbis4128941FischerinellaEponides1211Floresina11

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105 Appendix II-b. (Continued) 2.2R12.2R23.1R13.1R23.2R13.2R2BugR1BugR2Fursenkoina1Glabratella1Glabratellina2Globigerinoides1Globocassidulina11Globorotalia1Globulina1GuttulinaHaplophragmoidesHauerina1LachlanellaLobatula2Miliolinella2325611MontfortellaNeocornorbina112NeoeponidesPatellina1Planorbulina11PolymorphinaPoroepodinesPseudohauerina111Pyrgo1 31Quinqueloculina48505129138374Rectobolivina15ReophaxReussellaRosalina714671518SigmavirgulinaSigmiolina43 8Sigmiolinita21Siphonaperta5641111Siphonina1SiphoninoidesSpiroloculina132 12Textularia32 1Treromphalus1Triloculina113183159Triloculinella24 15Wiesnerella23Total Forams 139160172137320185194 Density (forams/g) 460160057168532018147760 Number of genera31313233282630Foram Index 3.242.693.653.167.336.002.012.18 SIMPER Group BDBDCC

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106 Appendix II-b. (Continued) ElkhornR1ElkhornR24.1R14.1R24.2R14.2R2PacificR1Paci ficR2Amphistegina73107173Androsina7Archaias117411523213Asterigerina27 48Borelis1 114Broekina1611Cyclorbiculina151 86GypsinaHeterostegina2 21Laevipeneroplis110151415739MonalysidiumPeneroplis42321Sorites2Ammonia145AmmobaculitesBolivina6517Bulimina2 3Cribroelphidium321Elphidium16161Haynesina543Nonion111NonionellaNonionoides11Adelosina2Affinetrina11211AnomalinoidesArticulina361311AstrononionBigenerinaBrizalina1CancrisCarpenteriaCibicides1121ClavulinaCornuspira11322Cycloforina27513Cymbaloporetta111 1Disconorbis3Discorbinella1Discorbis22171169711FischerinellaEponides11Floresina1

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107 Appendix II-b. (Continued) ElkhornR1ElkhornR24.1R14.1R24.2R14.2R2PacificR1Paci ficR2FursenkoinaGlabratella2Glabratellina1Globigerinoides1Globocassidulina1GloborotaliaGlobulinaGuttulinaHaplophragmoides1Hauerina122111Lachlanella111Lobatula1Miliolinella3451MontfortellaNeocornorbina2111113NeoeponidesPatellinaPlanorbulina1PolymorphinaPoroepodinesPseudohauerina1 1Pyrgo221Quinqueloculina2152544941112Rectobolivina1Reophax1Reussella1Rosalina21613815813SigmavirgulinaSigmiolinaSigmiolinitaSiphonaperta5353711Siphonina1113SiphoninoidesSpiroloculina1142Textularia3311Treromphalus11Triloculina12023221711Triloculinella426141Wiesnerella1111Total Forams 915517319115515073101 Density (forams/g) 9194577478767150073101 Number of genera633323424331727Foram Index 6.445.083.343.583.432.508.365.62 SIMPER Group EBBBBEE

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108 Appendix II-b. (Continued) 5.1R15.1R25.2R15.2R25.3R15.3R25.4R15.4R2Amphistegina32112552AndrosinaArchaias13422282814Asterigerina1113Borelis2222Broekina111Cyclorbiculina14361122Gypsina1Heterostegina1Laevipeneroplis43614444MonalysidiumPeneroplis1 11Sorites11Ammonia1AmmobaculitesBolivina1222BuliminaCribroelphidium1Elphidium23621Haynesina1 2Nonion1Nonionella11Nonionoides12Adelosina11AffinetrinaAnomalinoidesArticulina1121AstrononionBigenerina1BrizalinaCancrisCarpenteriaCibicidesClavulina1CornuspiraCycloforina111CymbaloporettaDisconorbis1DiscorbinellaDiscorbis958891FischerinellaEponidesFloresina

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109 Appendix II-b. (Continued) 5.1R15.1R25.2R15.2R25.3R15.3R25.4R15.4R2Fursenkoina11Glabratella1Glabratellina1GlobigerinoidesGlobocassidulinaGloborotalia1GlobulinaGuttulinaHaplophragmoidesHauerinaLachlanella1 1Lobatula1Miliolinella1 21MontfortellaNeocornorbina111Neoeponides1PatellinaPlanorbulina3PolymorphinaPoroepodinesPseudohauerina1Pyrgo1 1Quinqueloculina842126118RectobolivinaReophax1ReussellaRosalina2532317Sigmavirgulina1Sigmiolina1SigmiolinitaSiphonaperta114201313Siphonina1SiphoninoidesSpiroloculina11Textularia135221Treromphalus11Triloculina796753Triloculinella21121Wiesnerella113Total Forams 60429813256444027 Density (forams/g) 60429813256444027 Number of genera1819212222202011Foram Index 5.175.604.535.083.796.524.484.33 SIMPER Group AAAA

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110 Appendix II-b. (Continued) 6.1R16.1R26.2R16.2R26.3R16.3R27.1R17.1R2Amphistegina32223322Androsina1Archaias687121635515Asterigerina2431233Borelis1322Broekina3512116Cyclorbiculina1141134Gypsina1HeterosteginaLaevipeneroplis132122126161110Monalysidium1Peneroplis151133Sorites1 121Ammonia1121 2AmmobaculitesBolivina12 31Bulimina11Cribroelphidium2 11Elphidium86134247Haynesina637NonionNonionella3Nonionoides11211Adelosina1112Affinetrina1AnomalinoidesArticulina41325Astrononion1Bigenerina11112BrizalinaCancrisCarpenteriaCibicides121Clavulina12 21Cornuspira21Cycloforina24112145Cymbaloporetta1113Disconorbis1Discorbinella2Discorbis14769212833FischerinellaEponides3211Floresina1

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111 Appendix II-b. (Continued) 6.1R16.1R26.2R16.2R26.3R16.3R27.1R17.1R2Fursenkoina21Glabratella1 1GlabratellinaGlobigerinoides1Globocassidulina1 1Globorotalia11GlobulinaGuttulinaHaplophragmoidesHauerina21312Lachlanella2 1Lobatula12Miliolinella11265221MontfortellaNeocornorbina1311NeoeponidesPatellinaPlanorbulina24112PolymorphinaPoroepodinesPseudohauerina21 11Pyrgo221 2Quinqueloculina4138283319285345RectobolivinaReophaxReussellaRosalina681915661316SigmavirgulinaSigmiolina1SigmiolinitaSiphonaperta1067917859Siphonina13Siphoninoides1Spiroloculina2112113Textularia1010123142Treromphalus1Triloculina1613104481213Triloculinella331232Wiesnerella41Total Forams 171168153137118159160176 Density (forams/g) 16765601801371181771584587 Number of genera3733322922263533Foram Index 3.384.144.013.893.975.043.453.91 SIMPER Group BBBBAABB

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112 Appendix II-b. (Continued) StarR1StarR27.2R17.2R28.1R18.1R2NirvanaR1NirvanaR2Amphistegina5652Androsina12Archaias5923103211Asterigerina2141Borelis131312Broekina354Cyclorbiculina3161 1Gypsina1Heterostegina1 1Laevipeneroplis1114182812MonalysidiumPeneroplis542Sorites11Ammonia1121AmmobaculitesBolivina822Bulimina1Cribroelphidium23Elphidium1251Haynesina443NonionNonionellaNonionoides111Adelosina21Affinetrina1AnomalinoidesArticulina21111AstrononionBigenerinaBrizalinaCancrisCarpenteriaCibicides111Clavulina1Cornuspira321Cycloforina1321Cymbaloporetta11DisconorbisDiscorbinellaDiscorbis2911551FischerinellaEponides31Floresina12

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113 Appendix II-b. (Continued) StarR1StarR27.2R17.2R28.1R18.1R2NirvanaR1NirvanaR2Fursenkoina1GlabratellaGlabratellinaGlobigerinoidesGlobocassidulinaGloborotalia1Globulina1GuttulinaHaplophragmoidesHauerina2231Lachlanella13LobatulaMiliolinella4122MontfortellaNeocornorbina11NeoeponidesPatellinaPlanorbulina2PolymorphinaPoroepodinesPseudohauerina22Pyrgo111Quinqueloculina4943443311RectobolivinaReophaxReussella1Rosalina1761371SigmavirgulinaSigmiolina321SigmiolinitaSiphonaperta47117Siphonina3SiphoninoidesSpiroloculina22Textularia12551Treromphalus1Triloculina102117144Triloculinella31311Wiesnerella1Total Forams 157183195150102532 Density (forams/g) 781458195250102532 Number of genera3533303171532Foram Index 3.573.994.354.816.704.244.6710.00 SIMPER Group BBBB

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114 Appendix II-b. (Continued) 8.2R18.2R29.1R19.1R29.2R19.2R29.3R19.3R2Amphistegina3311Androsina1 1Archaias449123125Asterigerina341Borelis11Broekina1623Cyclorbiculina1112Gypsina1HeterosteginaLaevipeneroplis131223241617108Monalysidium11 1Peneroplis42421221Sorites11 1Ammonia2221611AmmobaculitesBolivina138215999Bulimina323Cribroelphidium24442Elphidium11576122Haynesina12216424Nonion1 14NonionellaNonionoides4 3151Adelosina13121275Affinetrina1AnomalinoidesArticulina11229344AstrononionBigenerinaBrizalina11CancrisCarpenteriaCibicides12212Clavulina11Cornuspira314261Cycloforina43225143Cymbaloporetta1 11DisconorbisDiscorbinella1Discorbis31525410FischerinellaEponides21213111Floresina8

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115 Appendix II-b. (Continued) 8.2R18.2R29.1R19.1R29.2R19.2R29.3R19.3R2Fursenkoina1132Glabratella1Glabratellina1 1Globigerinoides2GlobocassidulinaGloborotalia1GlobulinaGuttulinaHaplophragmoidesHauerina1321212Lachlanella11Lobatula11Miliolinella121133104MontfortellaNeocornorbina1111NeoeponidesPatellinaPlanorbulina11121PolymorphinaPoroepodinesPseudohauerina1112PyrgoQuinqueloculina415467371546712975RectobolivinaReophaxReussellaRosalina61320541172014Sigmavirgulina1Sigmiolina361117SigmiolinitaSiphonaperta96912116Siphonina1 1SiphoninoidesSpiroloculina312321Textularia42312Treromphalus1Triloculina1916101214112024Triloculinella2222515Wiesnerella1511Total Forams 141151196134346187279200 Density (forams/g) 5641007156813406920374055804000 Number of genera3233312833383034Foram Index 3.473.253.574.912.353.012.302.71 SIMPER Group BBDBCBCB

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116 Appendix II-b. (Continued) LuganoR1LuganoR210.1R110.1R210.2R110.2R2DomeR1DomeR 2Amphistegina3431233AndrosinaArchaias1041413545Asterigerina231Borelis111Broekina126Cyclorbiculina54Gypsina111HeterosteginaLaevipeneroplis2125813MonalysidiumPeneroplis11Sorites112Ammonia1111Ammobaculites1Bolivina4BuliminaCribroelphidium12Elphidium231Haynesina2Nonion1NonionellaNonionoides12Adelosina31Affinetrina1AnomalinoidesArticulina6AstrononionBigenerina1BrizalinaCancris1Carpenteria1Cibicides11Clavulina211Cornuspira4Cycloforina1 3Cymbaloporetta2Disconorbis1DiscorbinellaDiscorbis11202169Fischerinella1Eponides1111Floresina

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117 Appendix II-b. (Continued) LuganoR1LuganoR210.1R110.1R210.2R110.2R2DomeR1DomeR 2Fursenkoina2GlabratellaGlabratellina1GlobigerinoidesGlobocassidulina11Globorotalia122GlobulinaGuttulina11HaplophragmoidesHauerinaLachlanellaLobatula1Miliolinella4MontfortellaNeocornorbina1 4NeoeponidesPatellinaPlanorbulina21Polymorphina1PoroepodinesPseudohauerina1Pyrgo2Quinqueloculina1 28155434Rectobolivina1ReophaxReussellaRosalina14659SigmavirgulinaSigmiolinaSigmiolinita1Siphonaperta1141016Siphonina14Siphoninoides2Spiroloculina1Textularia4131TreromphalusTriloculina3102122Triloculinella22WiesnerellaTotal Forams 151224157159151146 Density (forams/g) 151224157199755365 Number of genera462422213633Foram Index 9.477.332.008.005.806.053.043.55 SIMPER Group AABB

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118 Appendix III. SIMPER results for dissimilarity between groups ba sed on foraminiferal assemblages. Groups A & BAverage dissimilarity = 40.22 Group A Group B GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Archaias 4.252.052.652.36.66.6 Discorbis 3.631.812.122.195.2811.87 Quinqueloculina 4.085.361.51.843.7315.6 Siphonaperta 2.541.811.171.342.9218.52 Bolivina 0.31.051.111.342.7621.28 Cyclorbiculina 1.490.661.071.512.6623.93 Haynesina 0.290.971.051.342.6126.54 Articulina 0.271.011.051.552.629.14 Miliolinella 0.661.041.011.442.531.64 Groups A & CAverage dissimilarity = 53.51 Group A Group C GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Archaias 4.250.624.473.368.358.35 Quinqueloculina 4.086.593.084.545.7514.1 Discorbis 3.631.322.823.355.2719.37 Siphonaperta 2.540.522.492.084.6524.02 Bolivina 0.32.232.362.994.4228.43 Amphistegina 1.6802.052.873.8432.27 Cyclorbiculina 1.4901.823.443.4135.68 Miliolinella 0.6621.691.773.1538.83 Sigmiolina 0.141.351.551.612.8941.72 Cribroelphidium 0.241.381.432.412.6744.39 Rosalina 1.8731.392.612.5946.99 Haynesina 0.291.351.392.132.5949.58 Textularia 1.270.181.381.732.5952.16 Laevipeneroplis 2.871.841.351.522.5354.69 Articulina 0.271.141.172.082.1956.88 Cornuspira 0.10.951.121.582.158.97 Bulimina 0.21.031.051.841.9660.93 Asterigerina 0.8501.041.711.9462.87

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119 Appendix III. (Continued) Groups A & DAverage dissimilarity = 45.72 Group A Group D GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Archaias 4.251.952.662.565.835.83 Discorbis 3.632.091.772.043.879.7 Sigmiolina 0.141.671.723.453.7713.47 Ammonia 0.271.741.652.23.6117.08 Cyclorbiculina 1.490.211.462.253.220.28 Amphistegina 1.680.491.381.623.0223.31 Quinqueloculina 4.085.241.341.652.9226.23 Haynesina 0.291.291.261.872.7528.97 Rosalina 1.872.911.192.052.6131.58 Articulina 0.271.111.141.32.4934.06 Cornuspira 0.11.091.132.542.4836.55 Eponides 0.191.171.112.172.4338.98 Triloculina 2.631.831.071.412.3441.32 Bolivina 0.30.91.041.052.2843.6 Miliolinella 0.6611.011.362.2145.82 Groups A & EAverage dissimilarity = 43.09 Group A Group E GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Rosalina 1.872.272.043.444.744.74 Archaias 4.254.521.991.574.619.34 Triloculina 2.630.991.982.174.5913.94 Asterigerina 0.852.431.952.644.5218.46 Quinqueloculina 4.082.771.821.14.2222.68 Elphidium 1.620.271.692.373.9326.61 Siphonaperta 2.541.321.61.433.730.31 Heterostegina 01.271.583.043.6833.99 Cyclorbiculina 1.492.521.371.343.1737.16 Neocornorbina 0.361.351.282.12.9740.13 Amphistegina 1.682.321.091.252.5242.65 Borelis 0.721.321.091.482.5245.17

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120 Appendix III. (Continued) Groups B & CAverage dissimilarity = 40.11 Group B Group C GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Archaias 2.050.621.621.924.034.03 Siphonaperta 1.810.521.462.163.647.67 Quinqueloculina 5.366.591.382.143.4411.12 Bolivina 1.052.231.381.613.4314.55 Amphistegina 1.2201.372.243.4117.96 Sigmiolina 0.261.351.361.633.421.36 Textularia 1.30.181.331.383.3224.68 Laevipeneroplis 2.991.841.321.713.2827.96 Miliolinella 1.0421.091.62.7230.68 Broekina 1.020.181.041.412.5933.27 Groups B & DAverage dissimilarity = 37.40 Group B Group D GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Sigmiolina 0.261.671.482.813.963.96 Triloculina 3.091.831.352.123.617.57 Ammonia 0.741.741.121.572.9910.56 Bolivina 1.050.91.011.42.7113.27

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121 Appendix III. (Continued) Groups B & EAverage dissimilarity = 49.41 Group B Group E GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Quinqueloculina 5.362.773.031.776.146.14 Archaias 2.054.522.941.355.9412.08 Triloculina 3.090.992.363.994.7816.86 Cyclorbiculina 0.662.522.161.894.3721.23 Asterigerina 0.652.432.012.424.0725.3 Discorbis 1.813.371.742.353.5328.83 Rosalina 2.512.271.71.423.4432.27 Heterostegina 0.031.271.422.872.8735.13 Amphistegina 1.222.321.341.412.737.84 Elphidium 1.350.271.31.422.6340.46 Bolivina 1.050.661.161.412.3542.81 Haynesina 0.9701.11.372.2245.04 Borelis 0.451.321.071.552.1747.21 Cycloforina 1.180.381.051.532.1249.34 Groups C & DAverage dissimilarity = 38.24 Group C Group D GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Siphonaperta 0.522.241.93.484.964.96 Archaias 0.621.951.472.453.848.8 Quinqueloculina 6.595.241.472.443.8412.64 Bolivina 2.230.91.461.453.8216.46 Ammonia 0.591.741.291.743.3819.84 Cribroelphidium 1.380.421.231.963.2223.06 Textularia 0.181.161.171.463.0626.12 Miliolinella 211.121.42.9229.04 Nonionoides 0.9401.041.562.7231.76 Laevipeneroplis 1.842.751.021.492.6734.43

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122 Appendix III. (Continued) Groups C & EAverage dissimilarity = 62.77 Group C Group E GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Archaias 0.624.524.81.937.657.65 Quinqueloculina 6.592.774.662.427.4315.08 Cyclorbiculina 02.523.072.844.8819.96 Asterigerina 02.432.96.774.6124.57 Amphistegina 02.322.822.814.4929.06 Discorbis 1.323.372.414.663.8332.9 Elphidium 1.940.272.032.313.2336.12 Miliolinella 20.3322.843.1939.31 Bolivina 2.230.661.961.593.1342.44 Triloculina 2.420.991.73.572.745.14 Rosalina 32.271.680.962.6747.81 Haynesina 1.3501.613.732.5750.38 Neocornorbina 01.351.595.092.5452.92 Sigmiolina 1.3501.591.612.5355.44 Heterostegina 01.271.5332.4457.89 Borelis 0.151.321.42.072.2260.11 Cribroelphidium 1.380.331.271.82.0262.13

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123 Appendix III. (Continued) Groups D & EAverage dissimilarity = 53.32 Group D Group E GeneraAv.AbundAv.AbundAv.DissDiss/SDContrib%Cum.%Archaias 1.954.522.971.45.565.56 Quinqueloculina 5.242.772.841.645.3310.9 Cyclorbiculina 0.212.522.622.444.9115.8 Amphistegina 0.492.322.071.943.8919.69 Asterigerina 0.732.431.882.043.5323.23 Sigmiolina 1.6701.847.853.4526.68 Ammonia 1.740.271.642.043.0729.75 Rosalina 2.912.271.530.972.8832.62 Haynesina 1.2901.422.422.6735.29 Heterostegina 01.271.423.052.6637.96 Discorbis 2.093.371.392.042.6240.57 Neocornorbina 0.211.351.252.382.3442.91 Borelis 0.21.321.241.832.3245.24 Elphidium 1.260.271.131.562.1147.35 Bolivina 0.90.661.0712.0149.36 Siphonaperta 2.241.321.021.771.9151.28 Eponides 1.170.271.011.731.8953.17 Peneroplis 1.060.5412.181.8755.04

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124 Appendix IV. Moran’s I values and plots for both the FORAM Inde x and the SEDCON Index. Scales are in standard deviations from the mean. a) Insignificant spatial autocorrelation of FORAM Index (FI) values. b) Significant bivariate spatial correlation of FI and Temperature.

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125 Appendix IV. (Continued) c) Significant bivariate spatial correlation of FI and Salinity. d) Significant bivariate spatial correlation of FI and Percent Mud.

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126 Appendix IV. (Continued) e) Significant spatial autocorrelation of SEDCON Index (SI) values. f) Significant bivariate spatial correlation of SI and Temperature

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127 Appendix IV. (Continued) g) Significant bivariate spatial correlation of SI and Salinity. h) Significant bivariate spatial correlation of SI and Depth.

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128 Appendix IV. (Continued) Moran’s I value and plot for spatial correlation be tween the SEDCON Index and the FORAM Index.

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129 Appendix V-a. Raw counts of sediment constituents from the two s ediment replicates of 32 reefs in Biscayne National Park. 1.1R11.1R21.2R11.2R2SharkR1SharkR22.1R1 Coral (Pc)854122411Symbiotic Forams (Pf)861011120Coralline Algae (Pah)0001130Molluscs (Pah)73957386523690Calcareous Algae (Pah)1714304012159Echinoid Spines (Pah)0321001Worm Tubes (Pah)13141410Gorgonian Sclerites (Pah)1210001Fecal Pellets (Pah)0100110Other (Pah)1278103Unidentifiable (Pu)191169172137229235175Pc 2.67%1.67%1.33%4.00%0.67%1.33%3.67% Pf 2.67%2.00%3.33%3.67%0.33%0.67%0.00% Pah 31.00%40.00%38.00%46.67%22.67%19.67%38.00% Pu 63.67%56.33%57.33%45.67%76.33%78.33%58.33% SEDCON Index 1.161.181.221.670.620.661.19 SIMPER group CCCCCCC 2.1R22.2R12.2R23.1R13.1R23.2R13.2R2 Coral (Pc)11532675Symbiotic Forams (Pf)18115575Coralline Algae (Pah)5010320Molluscs (Pah)97506866774284Calcareous Algae (Pah)17466413252234Echinoid Spines (Pah)1401111Worm Tubes (Pah)3791805Gorgonian Sclerites (Pah)1652210Fecal Pellets (Pah)0230011Other (Pah)23641014Unidentifiable (Pu)162169130206163216161Pc 3.67%1.67%1.00%0.67%2.00%2.33%1.67% Pf 0.33%2.67%3.67%1.67%1.67%2.33%1.67% Pah 42.00%39.33%52.00%29.00%42.00%23.33%43.00% Pu 54.00%56.33%43.33%68.67%54.33%72.00%53.67% SEDCON Index 1.291.221.480.851.230.961.21 SIMPER group CCCCCCC

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130 Appendix V-a. (Continued) BugR1BugR2ElkhornR1ElkhornR24.1R14.1R24.2R1 Coral (Pc)50114262Symbiotic Forams (Pf)67212223Coralline Algae (Pah)1075102Molluscs (Pah)91685549486854Calcareous Algae (Pah)941108115357105Echinoid Spines (Pah)6310221Worm Tubes (Pah)6503784Gorgonian Sclerites (Pah)02031212Fecal Pellets (Pah)68000314Other (Pah)5140111615Unidentifiable (Pu)808321621217314688Pc 1.67%0.00%3.67%1.33%0.67%2.00%0.67% Pf 2.00%2.33%0.67%4.00%0.67%0.67%1.00% Pah 69.67%70.00%23.67%24.00%41.00%48.67%69.00% Pu 26.67%27.67%72.00%70.67%57.67%48.67%29.33% SEDCON Index 1.751.610.971.001.001.281.56 SIMPER group BBCCCCB 4.2R2PacificR1PacificR25.1R15.1R25.2R15.2R2 Coral (Pc)2233111Symbiotic Forams (Pf)796107719Coralline Algae (Pah)03102202Molluscs (Pah)41194941236454Calcareous Algae (Pah)11414171563134Echinoid Spines (Pah)4311000Worm Tubes (Pah)121566265Gorgonian Sclerites (Pah)4106001Fecal Pellets (Pah)10001000Other (Pah)17010168Unidentifiable (Pu)89234207215258185176Pc 0.67%0.67%1.00%1.00%0.33%0.33%0.33% Pf 2.33%3.00%2.00%3.33%2.33%2.33%6.33% Pah 67.33%18.33%28.00%24.00%11.33%35.67%34.67% Pu 29.67%78.00%69.00%71.67%86.00%61.67%58.67% SEDCON Index 1.630.750.890.920.531.001.29 SIMPER group BCCCCCC

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131 Appendix V-a. (Continued) 5.3R15.3R25.4R15.4R26.1R16.1R26.2R1 Coral (Pc)3522887Symbiotic Forams (Pf)4422323Coralline Algae (Pah)0111221Molluscs (Pah)72386841678747Calcareous Algae (Pah)25497470282133Echinoid Spines (Pah)0012611Worm Tubes (Pah)84621164Gorgonian Sclerites (Pah)2062749Fecal Pellets (Pah)0030000Other (Pah)104113160Unidentifiable (Pu)185199133177155153195Pc 1.00%1.67%0.67%0.67%2.67%2.67%2.33% Pf 1.33%1.33%0.67%0.67%1.00%0.67%1.00% Pah 36.00%30.67%54.33%39.67%44.67%45.67%31.67% Pu 61.67%66.33%44.33%59.00%51.67%51.00%65.00% SEDCON Index 0.990.951.250.971.291.281.01 SIMPER group CCCCCCC 6.2R26.3R16.3R27.1R17.1R2StarR1StarR2 Coral (Pc)7302332Symbiotic Forams (Pf)97613738Coralline Algae (Pah)4002137Molluscs (Pah)6310661831057249Calcareous Algae (Pah)462740836399Echinoid Spines (Pah)00161301Worm Tubes (Pah)2454315Gorgonian Sclerites (Pah)2305420Fecal Pellets (Pah)0010000Other (Pah)203891630Unidentifiable (Pu)16515018316915213799Pc 2.33%1.00%0.00%0.67%1.00%1.00%0.67% Pf 3.00%2.33%2.00%4.33%2.33%1.00%2.67% Pah 39.67%46.67%37.00%38.67%46.00%52.33%63.67% Pu 55.00%50.00%61.00%56.33%50.67%45.67%33.00% SEDCON Index 1.321.270.961.241.261.271.59 SIMPER group CCCCCCC

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132 Appendix V-a. (Continued) 7.2R28.1R18.1R2NirvanaR1NirvanaR28.2R18.2R2 Coral (Pc)15105441Symbiotic Forams (Pf)50037213Coralline Algae (Pah)0331030Molluscs (Pah)54474337524996Calcareous Algae (Pah)692620232897107Echinoid Spines (Pah)0012200Worm Tubes (Pah)30300149Gorgonian Sclerites (Pah)53012113Fecal Pellets (Pah)0001004Other (Pah)41000712Unidentifiable (Pu)15921522022720511355Pc 0.33%1.67%3.33%1.67%1.33%1.33%0.33% Pf 1.67%0.00%0.00%1.00%2.33%0.67%4.33% Pah 45.00%26.67%23.33%21.67%28.00%60.33%77.00% Pu 53.00%71.67%73.33%75.67%68.33%37.67%18.33% SEDCON Index 1.120.770.870.760.951.431.94 SIMPER group CCCAABB 9.1R29.2R19.2R29.3R19.3R2LuganoR1LuganoR2 Coral (Pc)2241142Symbiotic Forams (Pf)401017275715Coralline Algae (Pah)0001011Molluscs (Pah)9510085100744647Calcareous Algae (Pah)171049194941932Echinoid Spines (Pah)1356110Worm Tubes (Pah)4485034Gorgonian Sclerites (Pah)35121200Fecal Pellets (Pah)01540000Other (Pah)15161451001Unidentifiable (Pu)12341606061225208Pc 0.67%0.67%1.33%0.33%0.33%1.33%0.67% Pf 13.33%3.33%5.67%9.00%19.00%0.33%1.67% Pah 45.00%82.33%73.00%70.67%60.33%23.33%28.33% Pu 41.00%13.67%20.00%20.00%20.33%75.00%69.33% SEDCON Index 2.071.992.072.192.780.700.84 SIMPER group CBBBBCC

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133 Appendix V-a. (Continued) 10.1R110.1R210.2R110.2R2DomeR1DomeR2 Coral (Pc)1420513Symbiotic Forams (Pf)218874Coralline Algae (Pah)420010Molluscs (Pah)365587824747Calcareous Algae (Pah)58425457160180Echinoid Spines (Pah)124213Worm Tubes (Pah)703259Gorgonian Sclerites (Pah)233243Fecal Pellets (Pah)000041Other (Pah)03331421Unidentifiable (Pu)1761901381395629Pc 4.67%0.67%0.00%1.67%0.33%1.00% Pf 0.67%0.33%2.67%2.67%2.33%1.33% Pah 36.00%35.67%51.33%49.33%78.67%88.00% Pu 58.67%63.33%46.00%46.33%18.67%9.67% SEDCON Index 1.300.871.291.411.811.98 SIMPER group CCCCBB

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134 Appendix V-b. Visual identification aid for major sediment consti tuents.

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135 Appendix VI. SIMPER results for dissimilarity between groups ba sed on LSF assemblages. Groups A & BAverage dissimilarity = 36.3% Group B Group A SpeciesAv.AbundAv.AbundAv.DissDiss/SDContrib% Cum.% L. proteus 7.333.776.884.3918.918.9 C. compressus 1.543.754.51.7712.431.3 Androsina 0.092.424.482.5612.443.7 A. carinata 1.272.733.541.739.7653.4 A. gibbosa 3.725.273.141.68.6362.1 A. angulatus 3.434.342.61.67.1569.2 L. bradyi 2.31.362.231.466.1475.4 B. orbitolitoides 1.150.112.051.525.6381.0 S. marginalis 0.431.42.011.85.5386.5 H. antillarium 0.030.831.552.084.2890.8 Groups A & CAverage dissimilarity = 31.3% Group A Group C SpeciesAv.AbundAv.AbundAv.DissDiss/SDContrib% Cum.% A. angulatus 4.3424.452.6714.214.2 Androsina 2.420.094.442.614.228.4 A. carinata 2.730.723.832.1112.240.7 L. proteus 3.775.373.172.1710.150.8 A. gibbosa 5.276.732.91.669.2660.1 C. compressus 3.752.752.741.188.7668.8 B. orbitolitoides 0.111.091.961.786.2775.1 S. marginalis 1.40.461.951.636.2481.3 L. bradyi 1.362.121.71.35.4586.8 B. pulchra 0.830.41.471.324.791.5 Reef 1.1 & Group AAverage dissimilarity = 49.4% Reef 1.1 Group A SpeciesAv.AbundAv.AbundAv.DissDiss/SDContrib% Cum.% A. gibbosa 05.2710.786.721.821.8 A. carinata 6.672.738.074.2516.338.2 C. compressus 03.757.663.7715.553.7 Androsina 02.424.912.669.9663.7 L. bradyi 3.521.364.412.988.9472.6 L. proteus 5.583.773.693.027.4780.1 S. marginalis 01.42.872.715.8185.9 A. angulatus 3.154.342.561.715.1891.1 Group A & Reef 5.4Average dissimilarity = 35.9% Group AReef 5.4 SpeciesAv.AbundAv.AbundAv.DissDiss/SDContrib% Cum.% A. angulatus 4.3408.685.3624.224.2 Androsina 2.4204.832.6613.537.6 C. compressus 3.756.014.532.4212.650.3 L. proteus 3.775.653.763.1310.560.7 L. bradyi 1.3602.731.887.5968.3 A. carinata 2.731.462.641.867.3575.7 P. pertusus 1.222.532.622.747.383.0 B. pulchra 0.8301.651.274.687.6 H. antillarium 0.8301.651.974.692.2

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136 Appendix VII. Results of bleaching surveyed in live specimens of Amphistegina gibbosa and density of live symbiont-bearing foraminifera ( per 100cm2). Amphistegina gibbosa Total Live Symbiont-bearing Forams Site %Adults %Bleached Density Density Raw Count 1.1 0.00 0.00 0.00 146.4 201 1.2 88.9 33.3 10.8 112.0 114 Shark 39.7 32.8 27.5 97.2 182 2.1 48.0 24.7 43.4 75.2 127 2.2 50.0 40.0 4.71 47.3 99 3.1 88.9 33.3 29.5 57.2 132 3.2 43.9 27.6 48.0 165.3 330 Bug 31.7 6.67 30.2 53.0 100 Elkhorn 47.5 10.0 17.3 44.5 101 4.1 42.9 17.5 53.8 129.2 156 4.2 49.4 18.8 33.1 67.4 173 Pacific 67.7 16.1 15.6 92.6 178 5.1 71.4 28.6 20.9 62.1 102 5.2 15.4 15.4 4.40 27.6 76 5.3 50.0 5.56 17.0 68.2 72 5.4 20.0 40.0 10.9 51.2 47 6.1 72.2 33.3 7.34 37.2 80 6.2 31.3 18.8 11.7 148.0 391 6.3 59.5 23.8 17.2 271.4 569 7.1 50.0 20.0 6.54 139.8 218 Star 57.7 28.9 27.6 75.0 143 7.2 39.3 16.7 30.3 177.3 492 8.1 43.1 19.6 30.2 86.6 150 Nirvana 47.8 28.4 60.7 217.5 489 8.2 63.4 26.8 51.2 175.2 228 9.1 40.0 26.7 8.14 50.4 109 9.2 31.8 22.7 17.4 90.5 123 9.3 100.0 0.00 0.71 5.70 8 Lugano 46.3 29.3 25.5 111.5 177 10.1 52.9 22.1 54.2 98.9 124 10.2 44.7 13.2 23.6 104.5 174 Dome 38.7 9.68 24.4 165.1 213

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137 Appendix VIII. Environmental data and comments from divers and bo at captain. SiteDepth (m)pH Temperature DOSalinityComments 1.16.108.226.216.6635.431.23.358.2926.266.7835.52Shark4.888.1726.616.3635.332.16.108.2726.126.6435.582.24.278.326.267.0635.783.18.848.1926.266.2335.41red grouper3.22.748.2726.046.3835.61abundant, high diversity c oral Bug Reefs 5.188.2625.946.4535.96 Elkhorn1.528.34277.8635.56lots of diadema, grunts w / parasites 4.16.108.3426.26.2935.6lots of broken coral heads, known fishing spot 4.23.968.3526.17635.65Pacific6.408.2726.726.2535.38good visability, lots of garbage on bottom, known fishing spot 5.13.668.2626.166.235.36good visability, near boat channel (marker 4), minimal thalasia 5.28.848.2626.46.135.37near boat channel (marker 3)5.34.578.3226.316.4535.65.43.358.3626.326.2835.766.18.238.3926.246.2135.636.28.238.4626.316.3635.66black band disease prevale nt on corals 6.33.668.4626.086.5835.747.110.068.2226.066.2235.52lots of relief, juvenile fishes Star6.408.3525.996.1335.647.24.578.4125.955.9335.778.13.058.2226.16.3435.59nicest reef (Jim), some sma ll cervicornis Nirvana2.448.2526.096.4335.6lots of new growth cora l, including cervicornis, nicest reef (Mel) 8.24.278.2826.016.3535.69red grouper9.18.848.2825.85.935.61mostly gorgonians and fire c oral 9.23.668.2425.686.0835.669.33.968.125.776.735.69Lugano5.498.1126.276.2735.45ship wreck (1913), sedi ment sample very orange 10.13.668.3225.74635.7810.23.968.2525.576.0435.71Dome4.578.326.116.1835.86high relief, large boulder corals, red grouper


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Patch reefs in Biscayne National Park, FL :
b sediments, foraminiferal distributions and a comparison of three biotic indicators of reef health
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by Alexa Ramirez.
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[Tampa, Fla] :
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2008.
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ABSTRACT: Coral cover remains highest on patch reefs at the northern end of the Florida reef tract. The reasons for this trend are not well understood, but may be related to the protection from extreme variations in water quality parameters provided by the near constant presence of islands at the north extent of the Florida Keys. Three indices have been developed based on Foraminifera and sediment constituents. Two of the indices, the FORAM Index and the SEDCON Index, were developed to indicate the suitability of a reef environment for continued reef accretion. The third index, the Photic Index, is an assessment of photic stress on reefs based on incidence of bleaching in a species of Foraminifera, Amphistegina gibbosa, which is known to experience loss of algal endosymbionts similar to bleaching in corals. Patch reefs were sampled in Biscayne National Park, FL to assess sediment characteristics and foraminiferal assemblages, as well as to examine trends in the three indices.Sediments associated with a majority (59%) of reefs were coarse sands; muddy sediments were restricted to a few inner patch reefs that were isolated from the influence of Caesar's Creek, which flushes water from inside Biscayne Bay onto the open shelf. Unidentifiable grains predominated in the sediment constituents, along with calcareous algae and molluskan debris. Shells from 82 genera of Foraminifera were identified in the sediments. Quinqueloculina was the most consistently common genus. Percent mud was the single most influential measured variable on the distribution of both sediment constituents and foraminiferal assemblages. Analysis of bleaching in the foraminifer Amphistegina gibbosa revealed that photo-oxidative stress was chronic at 94% of the sites.Patterns of FORAM and SEDCON Index values and their similarity to temperature, salinity, and percent mud distributions show that Caesar's Creek is affecting the benthic community in its immediate vicinity by providing flow that limits the accumulation of mud and potentially other anthropogenic stressors. Overall this study suggests that the reefs in this area are marginal for continued reef growth. A more detailed study of water quality through Caesar's Creek should be conducted to determine exactly how it is affecting the reefs in Biscayne National Park.
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Advisor: Pamela Hallock Muller, Ph.D.
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