xml version 1.0 encoding UTF-8 standalone no
record xmlns http:www.loc.govMARC21slim xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.loc.govstandardsmarcxmlschemaMARC21slim.xsd
leader nam 2200385Ka 4500
controlfield tag 001 002069310
007 cr mnu|||uuuuu
008 100421s2009 flu s 000 0 eng d
datafield ind1 8 ind2 024
subfield code a E14-SFE0003191
Williams, Ryann A.
Comparing reef bioindicators on benthic environments off southeast Florida
h [electronic resource] /
by Ryann A. Williams.
[Tampa, Fla] :
b University of South Florida,
Title from PDF of title page.
Document formatted into pages; contains 60 pages.
Thesis (M.S.)--University of South Florida, 2009.
Includes bibliographical references.
Text (Electronic thesis) in PDF format.
ABSTRACT: A goal of the U.S. Environmental Protection Agency is to develop protocols applicable to coral reefs to distinguish between the effects of local water quality and those associated with regional to global environmental change. One test case is the current-dominated southeast coast of Florida where the Delray Outfall delivers 30 million gallons per day (114,000 cubic meters per day) of secondary-treated sewage into the ocean. Five study sites were established at depths between 15 and 18 m, and at distances between 1 and 18 km distance from the outfall, where the Stony Coral Rapid Bioassessment Protocol (RBP) was conducted to determine coral cover and selected other parameters. During sampling, 29 surface sediment samples were collected that I analyzed with respect to sediment texture, foraminiferal assemblages, and sediment constituents. Most samples were characterized by fine sands with <2% mud.A total of 77 genera of foraminifers were identified, averaging 28 genera per sample. Abundances of foraminiferal shells varied among samples by more than an order of magnitude (83 to 1010 shells per g sediment). The Foraminifera in Reef Assessment and Monitoring (FORAM) Index was calculated from the foraminiferal data, yielding values of 3 or more for all sites, with 26 of the 29 test sites yielding values >4, indicating that water quality should support coral growth. Sediment constituent analyses revealed that the sediments were overwhelmingly dominated by unidentifiable fragments (60%), with molluscan debris second (20%), and calcareous algae third (4.5%); larger foraminiferal shells and coral fragments together made up less than 5.5%. The resulting sediment constituent (SEDCON) Index was consistently <2, indicating that erosional processes dominate over sediment production along the sampled shelf area.Results provided by the FORAM and SEDCON indices are consistent with results for stony coral based on the RBP. Stony coral cover was low at all sites, <2%, indicating that coral occurs in the area but neither dominates the benthos nor builds reefs. No relationship was observed between any parameter and distance from the Delray Outfall. However, both the RBP and FORAM Index indicated poorest conditions at the Horseshoe site, suggesting unidentified stressors in that vicinity.
Mode of access: World Wide Web.
System requirements: World Wide Web browser and PDF reader.
Advisor: Pamela Hallock Muller, Ph.D.
Stony coral rapid bioassessment protocol
x Marine Science
t USF Electronic Theses and Dissertations.
Comparing Reef Bioindicators on Benthic Environments off Southeast Florida by Ryann A. Williams 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. Benjamin Flower, Ph.D. Elizabeth Moses, Ph.D. Date of Approval: November 16, 2009 Keywords: f oraminifera, foram index, sedcon index, stony coral rapid bioassessment protocol, SECREMP Copyright 2009, Ryann A. Williams
DEDICATION I dedicate this thesis to my family, especially my mother, for her continuous support and effortless love throughout my graduate school career.
ACKNOWLEDGEMENTS I thank Dr. Pamela Hallock Muller, my major professo r, for her guidance and continuous support through my thesis research I would also like to thank the EPA Global Dr. William Fisher for the sediment samples and use of the R eef B ioasse ssme nt P rotocol data Thank you to the Bridge to the Doctorate Program for recruiting me. The financial support was greatly appreciated. I would specifically like to thank Dr. Ashanti Pyrtle and Mr. Bernard Batson for their hard work with recruiting and forwarding the program at the Coll ege of Marine Science. Many thanks go to my friends and family, especially my mother, for their support when times were trying. Thank you, Foram Team for your assistance in the lab.
i TABLE OF CONTENTS L IST OF TABLES ii ii LIST OF FIGURES i ii iii ABSTRACT i v INTRODUCTION 1 Introduction 1 State of Coral Reef 1 1 Introduction to Bioindicators 2 Characteristics of the Class Foraminifera 4 FORAM Index 6 SEDCON Index 8 Southeast Florida Bioindicators Project 9 PROJECT OBJECTIVES 14 8 METHODS 15 Sediment Texture and Constituents 15 Foraminiferal Assemblages 18 Data Analysis 19 RESULTS 21 Sediment Texture and Constituents 21 Foraminiferal Assemblages 23 Compariso ns 30 DISCUSSION 35 Rapid Bioassessment Protocol Data 35 Comparisons of Sediment Samples with RBP Results 38 CONCLUSIONS 40 REFERENCES CITED 42 APPENDICES 4 6 13 Appendix I P erce nt mud and the corrected sedim ent mass examined for a n alysis of t he foraminiferal assemblage 4 7 Appendix II Sediment textures : weight percent by phi sizes 4 8 Appendix III Raw for data of sediment constituents and SEDCON Index 49 Appendix IV Raw data for all F oraminifera counted 5 5
ii L IST OF TABLES Table 1 Functional Groups of Foraminifera used in coral reef assessments 4 Table 2 FI equation 6 Table 3 Examples of what the range of SEDCON Index can values represent 9 Table 4 Site information: distance repr esents distance f r om Delray Outfall off southeast Florida 12 Table 5 Rapid Bioassessment Protocol (RBP) coral condition indicators 13 Table 6 Sediment constituents categories 17 Table 7 SEDCON Index equation 18 Table 8 Summary of data from all sites : % mud, median phi, abundance (# shells/g sediment), number of genera, percentage s of symbiont bearing (SB), stress tolerant (ST), and other small foraminifers (OS) as well as FORAM Index (FI) and SEDCON Index (SI) 29 Table 9 Parameters calculate d for the RBP 36 Table 10 Results of Stony Coral Rapid Bioassessment Protocol: colony density (Col Dens), average % live tissue (Avg %LT), % live cover (%LC), total surface area (TSA), live surface area (LSA), average coral surface area (Avg CSA), an d vitality index (VI) 36 Table 11 Summary of RBP observations 38
iii LIST OF FIGURES Figure 1 Sites sampled for this study indicating locations along the southeast shelf of Florida 11 Figure 2 Schematic diagram of the Bray Curtis and MDS plot output of data 20 7 Figure 3 Average percent occurrence of sediment constituents in samples 22 Figure 4 Bray Curtis MDS plot for sediment constituents 22 # Figure 5 Cluster analysis of forminiferal data showing similarity am ong sites 24 Figure 6 Percentage of genera in the samples from southeast Florida coast 26 Figure 7 Cluster diagram of genera that occurred in at least three samples 27 Figure 8 Bray Curtis MDS plot of the genera that made up at least 1% of t he specimen from the combined data (Fig. 6) 28 Figure 9 Comparison of FI with median phi 30 Figure 10 Comparison o f the FI to the number of genera identified 31 Figure 11 Comparison of FI with shell abundance (#/g) in the sediment samples 32 Figure 12 Comparis on o f the number of genera in a sample with shell abundance in samples 32 Figure 13 Comparison of FI with site distance from the Delray Outfall 33 Figure 14 Comparison o f FI with SEDCON Index 34 Figure 15 Comparison of median phi with the SEDCON Index 3 4
iv COMPARING REEF BIOINDICATORS ON BENTHIC ENVIRONMENTS OFF SOUTHEAST FLORIDA Ryann A. Williams ABSTRACT A goal of the U.S. Environmental Protection Agency is to develop protocols applicable to coral re efs to distinguish between the effects of local water quality and those associated with regional to global environmental change. One test case is the current dominated southeast coast of Florida where the Delray Outfall delivers 30 million gallons/day (114 ,000 cubic meters/day) of secondary treated sewage into the ocean. Five study sites were established at depths between 15 and 18 m, and at distances between 1 and 18 km distance from the outfall, where the Stony Coral Rapid Bioassessment Protocol (RBP) was conducted to determine coral cover and selected other parameters. During sampling, 29 surface sediment samples were collected that I analyzed with respect to sediment texture, foraminiferal assemblages, and sediment constituents. Most samples were char acterized by fine sands with <2% mud. A total of 77 genera of foraminifers were identified, averaging 28 genera per sample. Abundances of foraminiferal shells varied among samples by more than an order of magnitude (83 to 1010 shells/g sediment). The Fora minifera in Reef Assessment and Monitoring (FORAM) Index was calculated from the foraminiferal data, yielding values of 3 or more
v for all sites, with 26 of the 29 test sites yielding values >4, indicating that water quality should support coral growth. Se diment constituent analyses revealed that the sediments were overwhelmingly dominated by unidentifiable fragments (60%), with molluscan debris second (20%), and calcareous algae third (4.5%); larger foraminiferal shells and coral fragments together made up <5.5%. The resulting sediment constituent (SEDCON) Index was consistently <2, indicating that erosional processes dominate over sediment production along the sampled shelf area. Results provided by the FORAM and SEDCON indices are consistent with results for stony coral based on the RBP. Stony coral cover was low at all sites, <2%, indicating that coral occurs in the area but neither dominates the benthos nor builds reefs. No relationship was observed between any parameter and distance from the Delray Ou tfall. However, both the RBP and FORAM Index indicated poorest conditions at the Horseshoe site, suggesting unidentified stressors in that vicinity.
1 INTRODUCTION State of Coral Reefs The activities of humans are having dire effects on coral reef ec osystems worldwide (Hallock, 2005; Hoegh Guldberg et al., 2007; many others). Biologically available nitrogen has doubled annually due to human activities and is washed in aquatic ecosystems directly through rainfall and indirectly by river runoff ( Vitouse k et al., 1997). With the ocean surface taking up 30% of the atmospheric carbon dioxide associated with fossil fuel burning, deforestation, and other human activities, climates are changing while carbonate saturation in the oceans is decreasing, likely aff ecting rates calcification of reef building corals and other organisms that produce CaCO 3 shells or skeletons (Kleypas and Langdon, 200 6). Due to the depletion of the stratospheric ozone layer, ultraviolet radiation (UV b ) has increased such that the intens ity reaching the sea surface at Florida latitudes between April and August is comparable to that only seen around the summer solstice in the 1960s (Galloway et al., 1996 ). The input of additional terrestrial sediments associated with land use, the outbrea k of diseases, polluted groundwater and nutrient rich runoff, damaging fishing practices, overfishing, heating of tropical water, and disturbance of important echinoderm species has all contributed to coral decline (Sammarco et al., 2007). With these threa ts increasing globally every year, the very future of coral reefs is in question (Jackson, 2008)
2 Introduction to Bioindicators a measure, an index of measures, or a model that charac terizes an ecosystem or one of its critical components measureable and connected to a disturbance at one of the levels of organization in that ecosystem (Sammarco et al., 2007). Cora l reefs have been studied for decades, but few measurements have related the condition of a coral reef to the potential of the benthic community to construct reefs (Sammarco et al., 2007). For example, high percent cover by mature colonies does not necess arily mean that juvenile corals are able to recruit (Hallock et al., 2004). Thus, after a hurricane or ship grounding, the loss of mature colonies does not predict whether juveniles will recruit and the reef will recover. Jameson ( 2001) reviewed parameter s that have been proposed and di scussed their potential for use as bioindicators of reef condition. A bioindicator for coral reefs, as for all ecosystems, has to be quantifiable and linked to a level of organization in the ecosystem (Sammarco et al., 2007 ). An ideal bioindicator could be used by regulatory agencies, like the U.S. Environmental Protection Agency (EPA), to create limits that could hold violators accountable (Sammarco et al., 2007). Violaters can be held responsible with the aid of the Feder al Water Pollution to restore and maintain the chemical, physical, and biological integrity of the nation's waters by preventing point and nonpoint pollution sources, providing assis tance to publicly owned treatment works for the improvement of wastewater treatment, and maintaining the integrity of wetlands One goal of the EPA s Stoney Coral Rapid
3 Bioassessment Protocol (RBP) is to provide biocriteria to allow states to establish thresholds for aquatic resources for certain bodies of water and subsequently monitor the environment is not being able to sustain itself similar to surrou nding waters, action should be taken Numerous researchers have proposed that foraminifers can be useful as bioindicators (e.g., Alve, 1995; Yanko et al., 1999; Schafer et al., 2000 ). Hallock et al. (2003) proposed characterizing low latitude, shallow w ater benthic foraminiferal taxa into functional groups that reflect benthic community structure, including symbiont bearing, stress tolerant, and other small heterotrophic taxa (modified by Carnahan et al., 2009) (Table 1). Larger benthic foraminifers tha t host algal symbionts have similar environmental requirements as reef building corals, and they respond to similar stresses (Hallock et al., 2003). Their shorter life cycle, as compared to that of reef building corals, can indicate if changes in water qua lity might impact coral recruitment, thereby limiting the potential for coral communities to recover from a short term mortality event. Hallock and others (2003) proposed that foraminifers, especially the larger foraminifers that are prevalent on healthy coral reefs, provide a relatively inexpensive and statistically favorable (in terms of sample size) bioindicator for coral reefs.
4 Table 1. Functional groups of Foraminifera used in coral reef assessments (Hallock et al., 2003, modified according to C arnahan et al., 2009). (*Opportunistic is considered stress tolerant in this project) Characteristics of the Class Foraminifera The Foraminifera are a class of amoeboid protists in the Phylum Granuloreticulosea, which are characterized by granular reti culopodia (a specific kind of pseudopodia) (Sen Gupta, 1999). The Foraminifera are characterized by an organic, agglutinated or calcareous test (i.e., shell), which may be a single chamber or multiple chambers. Though unicellular, the cytoplasm has two d istinct components with relatively different functions. The endoplasm, which is contained within the shell, contains the nucleus (or many nuclei) and functions to accumulate the organic matter required for
5 reproduction. The microtubule rich ectoplasm is found in the outermost portion of the shell where it produces reticulopodia, enabling foraminifers to feed, move, and grow new chambers (Hallock, 1999). Benthic foraminifers have been recorded in the geologic record back to the Cambrian Period (e.g., Sen G upta, 1999). These protists can be epibenthic, epiphytic, infaunal, or planktic. The estimate of 16 orders and 10,000 species ranks them among the most diverse protists in the ocean. Foraminifers are identified by shell characteristics, including mineralog y, chamber arrangement, and ornamentation. These protists range in size from less than 0.05 mm to >5 cm in diameter. Only a small percentage, 40 to 50 species, are planktonic (Sen Gupta, 1999). Approximately 10% of the 150 families of Foraminifera includ e members that host algal endosymbionts ( Lee and Anderson, 1991). Most, but not all benthic symbiont bearing foraminifers tend to grow to larger sizes than benthic fo There are both advantages and disadvantages to symbioses with algae (e.g. Hallock, 2000; Wooldridge, 2009). The major advantage is that the algae photosynthesize and provide the host with sugars or lipids when the host lives i n shallow, clear waters where there is plenty of sunlight. But there are several disadvantages as well. If food is plentiful, faster growing smaller foraminifers can dominate the assemblage. If dissolved nutrients (DIN, DIP) are plentiful, the symbionts will use the products of photosynthesis to grow and reproduce, instead of providing photosynthate to the host. Algal symbiosis packs many active cells into a very small space. As a consequence, the host symbiont unit, known as a holobiont, may be particu larly sensitive
6 to oxygen depletion at night when both the host and the algae are using oxygen for respiration. During the day, if the algae are exposed to too much sunlight, they may produce toxic levels of oxygen radicals within the host, causing photo oxidative stress. Thus, environments containing excess organic carbon, excess nitrogen or excess sunlight can cause physiological stress to the host (Hallock, 1999; Hallock and others, 2006a,b; Wooldridge, 2009). FO RAM Index The Foraminifera in Reef Asse ssment and Monitoring (FORAM) Index utilizes benthic foraminiferal assemblages from surface sediments (Table 1) (Carnahan et al., 2009). Table 2. FI equation. FI = (10 x P s ) + (P o ) + (2 x P h ) Where, P s = N s /T, P o = N o /T, P h = N h /T And, T = total number of specimens counted N s = number of specimens of symbiont bearing taxa N o = number of specimens of stress tolerant taxa N h = number of specimens of other small, heterotrophic taxa This index is based upon three ecological groupings of foramini fers: a) the larger foraminifers that host algal symbionts, b) smaller foraminifers which bloom when food
7 resources are fairly abundant but organic matter does not exceed availability of oxygen, and c) stress tolerant foraminifers that prevail in euryhalin e environments, where oxygen becomes limiting or where chemical pollutants are prevalent (Hallock et al., 2003, modified by Carnahan et al., 2009). Foraminiferal assemblages can indicate whether water quality can support healthy coral reefs and allow them to recover after a mortality event. For example, because foraminifers have shorter life spans than corals, the slow decline of water quality, which adult corals can survive, but that limits coral recruitment, can be detected using foraminifers (Ha llock et al., 2004 ). The FORAM Index (FI) is based upon observations that larger foraminifers are prevalent on healthy coral reefs, but smaller taxa overwhelm the larger ones when nutrification occurs (Hallock et al., 2003). With an indicator of suitable water qua lity, resource managers can predict if the coral reef can recover after a mass bleaching, ship grounding, or disease event. The FI would be able to detect, over time, decline in local water quality as compared to regional to global changes that are affecti ng benthic communities, including coral reefs (Hallock et al., 2003, 2006). Carnahan and others (2009) explained that the FI has a reference point of 2 (Table 2), representing 100% smaller taxa. To have an FI>2, there must be some symbiont bearing taxa, a nd for FI>4, symbiont bearing taxa must make up at least 25% of the assemblage. The latter can occur either under limited supply of organic matter or physical conditions that limit the abundance of the shells of smaller foraminifers in the sediments. On the other hand, if stress tolerant taxa are present and symbiont bearing taxa are sparse or absent, the FI <2. Stress tolerant foraminifers predominate under
8 hyposaline environments, where excess organic matter results in high biological oxygen demand, or where other chemical stresses would preclude reef growth. SEDCON Index The SEDCON index, which utilizes sediment constituents, was proposed to indicate combined effects of water quality, benthic community structure, and bioerosion (Table 3) (Daniels, 200 5). The basic premise is similar to that for the FI, i.e., sediment constituents will be dominated by remains of the dominant producers. So on a healthy accreting coral reef, sediments should be dominated by recognizable fragments of stony coral and the shells of larger benthic foraminifers, resulting in a SEDCON value greater than four (Table 3) (Daniels, 2005). On a nutrified reef, remains of calcareous green algae and grazing gastropods should dominate, generally with shells of smaller foraminifers an d some unrecognizable fragments originating from bioerosion of the reef substrate. As nutrification increases, the proportion of bioeroded material should theoretically increase (Hallock, 1988).
9 Table 3. Examples of what the range of SEDCON Ind ex values can represent. SEDCON INDEX Sediment Constituent Example 10 100% coral fragments 9 50% coral fragments, 50% LBF 8 100% symbiont bearing foraminiferal shells 6 50% coral fragments and 50% algal or non symbiotic skeletal grains 4 25% coral f ragments and 75% algal or non symbiotic skeletal grains 2 100% algal or non symbiotic skeletal grains 1.05 50% algal or non symbiont skeletal grains and 50% unidentifiable fragments 0.1 100% unidentifiable fragments Southeast Florida Bioindicators Pro ject Fisher) are developing protocols applicable to coral reefs to distinguish between the effects of local water quality and those of regional to global environmental change. One t est case consists of 5 stations off the southeast of Florida at depths of ~15 17 m (Fig. 1), in the general vicinity of the Delray Outfall, which delivers 30 million gallon/day (~114,000 cubic meters) through a 0.76m port of secondarily treated sewage into the ocean in the Atlantic at a depth of 29m (Hazen and Sawyer, 1994). The discharge is approximately 609m away from shore. A collaborating team (Region IV, Georgia Institute of Technology) observed that Lyngbya, an opportunistic cyanobacterium, was preval ent on soft coral near the outfall and declined in abundance with increasing distance from the outfall (Fisher, unpublished 2007a).
10 Five study sites were established between 1 and 18 km distance from the outfall (Fig. 1, Table 4), where the Stony Coral Rap id Bioassessment Protocol (RBP) was conducted to determine coral cover and selected other parameters (Table 5). To make the observations, a radial belt transect method was used. In an area suitable for coral growth, a 10 m line was extended from a tripod. A 2 m wide swath was then surveyed along an 180 o arc, maintaining a distance of 10 m from the tripod, resulting in an assessment area of 56.6 m 2 The EPA field team also videotaped benthic communities along transects at Southeast Flo rida Coral Reef Evalu ation and Monitoring Project (SECREMP) locations. Video transect stations at each site are 2x22 m and are 10 m apart. Sediment samples collected from the Delray sites and one SECREMP reference site were made available for my study.
11 Figure 1. Sites sam pled for this study, indicating locations along the southeast shelf of Florida (Fisher, unpublished 2007 b) (image of Florida found at http://www.doh.state.fl.us/disease_ctrl /refugee/Overview/mission.html .)
12 Table 4. Site information: distance represents distance from Delray Outfall off southeast Florida. + indicates distance down current, indicates up current Site Depth (m ) Distance (km) Latitude Longitude Horseshoe Ree f 1 7 .4 + 18.3 26 37.561 80 01.410 Gulf Stream N 15.2 + 6.6 26 31.240 80 01.935 Gulf Stream S 15.8 + 2.9 26 29.272 80 02.350 Delray Ledge 16.2 + 1.0 26 28.238 80 02.566 Seagate Reef 16.5 1.0 26 26.587 80 02.848 SECREMP 7.6 NA 26 08.872 80 05.758
13 Table 5. Rapid Bioassessment Protocol (RBP) coral condition indicators.
14 PROJECT OBJECTIVES The primary goal of my project was to apply the FORAM and SEDCON indices at sites off southeast Florida in conjunction wi th RBP bioindicator data collected by Region 4 personnel of the U.S. EPA Global Change Research Team. In doing so, I collected and analyzed foraminiferal assemblage and sediment constituent data. My results are then compared to the results from the EPA con ducted RBP.
15 METHODS The 29 surface sediment samples assessed for this study were collected by the EPA Global Change Research Team on September 24 October 3, 2007 (Fisher, unpublished 2007b). Samples were kept frozen until processed. The samples were sent to me identified only by numbers so I had no knowledge of which samples represented replicates. Sediment Texture and Constituents Each sediment sample was washed over a 0.063 mm sieve to remove and collect most of the mud fraction. The suspended mud f raction was placed in a beaker and allowed to settle overnight, then as much water as possible was extracted from the beaker using a pipette without disturbing the settled mud. The remaining mud sample was placed into a smaller beaker and allowed to settle overnight, after which additional water was removed. Then the sample was dried in an oven at 60 o C and then weighed. The sand sized sediments (>0.063 mm) were washed into a small beaker and water was extracted using a pipette. The sample was then dried an d weighed. The dry sand sized fraction was divided using a sample splitter. One half of the sand sized fraction was sub sampled to assess the foraminiferal assemblages. The other half was used for grain size analysis and assessment of the sediment constitu ents. To determine grain size distribution, the subsample was weighed, then placed in a tower of sieves (0.063 2mm) and shaken for 10 minutes. Each fraction was weighed and
16 recorded, including any sediment that passed through the 0.063 mm sieve. The weigh t percent of each size fraction was then calculated and the median phi size was determined. For sediment constituent analysis, the medium and coarse sand fractions captured on the 0.5 mm and 1.0 mm sieves were thoroughly mixed. Approximately 1 g of sedime nt was sprinkled over a gridded tray and 300 pieces that fell on the grid lines were picked to a micropaleontological slide for further identification (Daniels, 2005). The 300 pieces are identified into the categories shown in Table 6. The SEDCON Index was calculated using the formula developed by Daniels (2005) (Table 7).
17 Table 6. Sediment constituent categories (Daniels, 2005). SI functional group Sediment grain Community Role/ Feeding mode Interpretation c Scleractinian coral Primary reef builder, mixotrophic Area suitable for calcification by algal symbiosis f Larger, symbiont bearing foraminifers Sediment producer, mixotrophic Area suitable for calcification by algal symbiosis ah Coralline algae Framework builder, autotrophic Varies wi th other components Calcareous algae Sediment producers, autotrophic Nutrient signal, high CaCo 3 saturation Mollusks Grazers/predators, heterotrophic Food resources plentiful, nutrient signal Echinoid spines Bioeroders/grazers, heterotrophic Bioerosi on, nutrient signal Worm tubes Heterotrophic Abundant food resources Other (smaller foraminifers, bryozoans, fecal pellets, etc) Sediment producers, heterotrophic Abundant food resources u Unidentifiable Bioerosion proxy Bioerosion proxy
18 Tabl e 7. SEDCON Index equation (Daniels, 2005; Ramirez, 2008). SI= (10*P c )+(8*P f )+(2*P ah )+(0.1*P u ) Where, P c =N c /T P f =N f/ T P ah =N ah /T P u =N u /T And, T = total number of grains counted (300) N c =number of coral fragments N f =number of symbiont bearing forami nifera/shells N ah =number of coralline algae, calcareous algae, and heterotrophic skeletal grains N u =number of unidentifiable grains Foraminiferal Assemblages The unsieved half of the sediment sample was thoroughly mixed, then a subsample was weig hed, sprinkled over a gridded tray, and examined under a stereomicroscope (Hallock et al., 2003). All foraminiferal specimens were picked onto a micropaleontological faunal slide coated with water soluble glue (Ramirez 2008). If 150 200 foraminifers were n ot obtained in the first portion, the procedure was repeated with subsequent weighed subsamples until 150 200 specimens were isolated or until 1 g of sediment was examined (Hallock et al., 2003). The foraminifers were then sorted and identified to genus an d the genera were sorted into functional groups (Table 1). From the foraminiferal assemblages the FI was calculated using the formula described in Table 2.
19 After evaluating the foraminiferal assemblages and calculating the FORAM and SEDCON indices those data were sent to the EPA Global Change Research Team for comparison with their data set. I then received the sample locations and depths from the EPA team, along with a summary of their coral assessment data (RBP) and the distances of the sites f rom the Delray Outfall. The null hypotheses are that sites do not differ significantly with respect to sample median phi size, percent mud, SEDCON index, foraminiferal shell abundances (#/gram of sediment), number of genera, and FI. The alternative hypothe ses are that the samples will differ in one or more of the parameters. Data Analysis Data analysis procedures primarily used non parametric techniques conducted using the PRIMER software (Clarke and Gorley, 2006). Bray Curtis Cluster Analyses and Multi Di mensional Scaling (Q mode) were used to identify clusters of similar samples (Fig. 2) based on sediment constituents, foraminiferal assemblages, or both. The same techniques in r mode attempted to identify foraminiferal taxa that tended to occur together. The raw data were transformed by finding the fourth roots to minimize the effect of larger sample sizes from dominating the analysis. Scatter plots and regression analysis were used to compare the indices, median phi, total genera, percent mud, and densit y. The ANOSIM analysis was used as an analysis of similarities, between the foraminifer abundance and distance, median phi and foraminifer abundance, SEDCON Index and foraminifer abundance, and distance and the FORAM Index.
20 Figure 2.Schematic diagram o f the Bray Curtis and MDS plot output of data. (Clarke and Warwick, 2001).
21 R esults Sediment Texture and Constituents Grain size analysis of the 29 samples revealed that most contained less than 2% mud (Appendix I). The median phi ranged from 1 (coarse) to 3 (fine), with the finer sands predominating (Appendix II). The dominant medium and coarse sand sized sediment constituents in all samples were unidentifiable grains, with percentages ranging from 50% to 69%. Molluscan shell fragments were t he most common identifiable constituent, ranging from 11% to 30%. Coral fragments and shells of symbiont bearing foraminifers together never made up more than 13% of this size fraction (Fig. 3, Appendix III). Multidimensional scaling (MDS) plots of sample sites based on Bray Curtis similarity analysis for the sediment constituents did not show any grouping by sample sites (Fig. 4 ) The MDS plot had a 2 D stress of 0.18, indicating a useful representation of the data set. As a result of the predominance of unidentifiable grains, all of the SEDCON indices were similar and very low, ranging from 0.92 to 1.50 (Table 8). The lowest average SEDCON value was from the Horseshoe Reef, 1.13, while the highest average SEDCON value was from Gulf Stream South, 1.28.
22 Figure 3. Average percent occurrence of sediment constituents in samples. Figure 4. Bray Curtis MDS plots for sediment constituents.
23 Foraminiferal Assemblages In the 29 samples examined, a total of 77 genera were identified (Appendix IV). The domi nant genus was Amphistegina representing 24% of foraminiferal shells identified, followed by Quinqueloculina 8.4%, Laevipeneroplis 8.2%, Ammonia 7.9% and Haynesia 6.4%. Symbiont bearing foraminifers dominated in 21 of the 29 samples and 4 were dominat ed by the other small foraminifera. The Horseshoe Reef foraminiferal assemblage was dominated by stress tolerant taxa. The number of genera per sample ranged from 17 to 38. All of the samples yielded more than 50 shells per gram of sediment, so all samples were included in subsequent analyses. Seventeen out of the 29 samples did not have 150 foraminifers per one gram, but five of those reached at least 140 foraminifers. Shell abundance was quite variable, ranging from 84 to more than 1010 foraminiferal shel ls per gram. Bray Curtis similarity analysis for foraminiferal assemblages revealed that all samples examined were more than 50% similar (Fig. 5) and that 27 of the 29 samples analyzed were more than 60% similar. The three SECREMP samples, which were the most similar set of samples, were only 70 75% similar. The MDS plot produced by this analysis did not produce a meaningful representation, as the stress value exceeded 0.20 (see criteria of Clarke and Warwick, 2001).
24 Figure 5. Cluster analysis of for aminiferal data showing similarity among sites.
25 Bray Curits similarity analysis was also used for the generic level data. Only 56 genera that occurred in at least 3 samples were included in the analyses (Fig. 7). The resulting cluster diagram revealed th at 35 genera were very loosely related to the overall assemblage, while a core group of 21 genera tended to occur with >50% similarity. Those taxa tended to be the most common ones (Fig. 6), so an MDS plot was constructed that included only the 21 genera t hat made up at least 1% of the assemblage. That group included the symbiont bearing, Amphistegina, Borelis, Cyclorbiculina, Laevipenoroplis, and Asterigerina along with two ubiquitous smaller miliolids, Quinqueloculina and Triloculina and the common aggl utinate, Textularia which occurred together 80% of the time. The two stress tolerant genera, Ammonia and Haynesia, occurred together with more than 85% similarity. All samples yielded a FI of at least 3, and 26 of 29 yielded FI values greater than 4. The three samples with FIs <4 were from fine sandy sediments (median phi=3).
26 Figure 6. Percentages of genera in the samples from the southeast Florida coast.
27 Figure 7. Cluster diagram of genera that occurred in at least three samples. The core grou p of 21 genera are in the black box.
28 Figure 8. Bray Curtis MDS plot of the genera that made up at least 1% of the specimens from the combined data (Fig. 6). The green ellipse indicates most of the symbiont bearing foraminifers, red indicates the high e nergy tolerant Discorbis, and brown indicates the stress tolerant genera.
29 Table 8 Summary of data from all sites: % mud, median phi, abundance (# shells/g sediment), number of genera, percentage s of symbiont bearing (SB), stress tolerant (ST), and othe r small foraminifers (OS) as well as FORAM Index (FI) and SEDCON Index (SI).
30 Comparisons Comparing the FI to median phi (Fig. 9) shows that all FIs less than 4 were found in fine sands (phi 3). Otherwise no trend is evident between sediment texture and the FI. Figure 9. Comparison of FI with median phi There was no significant relationship with FI and the number of genera. In samples with an FI of 6 or more, between 19 and 34 genera were found (Fig. 10). Interestingly, number of genera per sam ple was not related to shell abundance (Fig.11; Appendix IV). In the sample with the highest shell abundance, 1010/g, 27 genera were identified. In the sample with the fewest shells, 84/g, 24 genera were found.
31 Figure 10: Comparison of the FI to the number of genera identified. Comparing FI with the abundances of foraminiferal shells per gram of sediment revealed a significant (R 2 =0.52, p <0.01) negative correlation (Fig. 11). The number of genera is not significantly correlated (R 2 =0.07) with she ll abundance (Fig. 12).
32 Figure 11. Comparison of FI with shell abundance (#/g) in the sediment samples (p<0.01). Figure 12. Comparison of the number of genera with shell abundance in samples. Data from my analyses ar e summarized by sites in Table 8 Seagate had the highest median FI (7.2) and highest median percentage of SBF (65%), followed by Delray Ledge (median FI= 6.8, medium SBF= 61%). Those sites had relatively coarse sediments with the predominant median phi of 1. Gulfstream North and South S ites were
33 relatively similar with median FI ~6 and median % SBF ~50% The predominant median phi for those sites was 3. The highest shell abundance (1010/g) was recorded at the Gulfstream South site. The three samples from the SECREMP site were the most homogenous of the replicates, median SBF= 54%, FI= 6.2, and median phi= 1. The lowest overall percentage of symbiont bearing foraminifers came from the Horseshoe Reef (median 31%), which also has the lowest FI values (median 4.0) and by far the highest per centages of the stress tolerant taxa (median 43%). The ANOSIM analyses between median phi and the foraminifer abundance, distance from the outfall and foraminifer abundance, and distance from the outfall and the FI value (Fig. 13) revealed that Horseshoe Reef was the most significantly different compared to other sites, with r values equaling, 3%, 1%, and 1.5%, respectively. Figure 13. Comparison of FI with site distance from the Delray Outfall. The negative distances reflect an upcurrent site.
34 Figure 14. Comparison of FI with SEDCON Index. The SEDCON indices were quite homogenous, varying less than 0.8 units over all 29 samples. Thus, comparisons of the SEDCON Index with other parameters (Fig. 14 and 15) yielded few insights. SEDCON Index valu es show no change with sediment texture, falling almost evenly into the three median phi groups, indicating that overall sediment texture did not influence composition of the medium and coarse fractions (Fig. 15; Table 8). Figure 15. Comparison of media n phi with the SEDCON Index.
35 DISCUSSION Analyses of the sediment samples from the Delray Outfall vicinity revealed that the foraminiferal assemblages have a relatively high proportion of symbiont bearing taxa, while the sediment constituents indicat e predominance of erosion rather than reef accretion. Thus, my data indicate that the water quality at the sites is suitable at least for symbiont bearing foraminifers and that other processes must be promoting erosion over carbonate accretion. Compariso n of my data with the data collected by the EPA using the RBP methods may help illuminate what is limiting coral production. Rapid Bioassessment Protocol Data Fisher (2007) and personal communication (2009) described the results of Stony Coral Rapid Bioa ssessment Protocol (RBP) at the five Delray Outfall sites (Table 5). The goal for the RBP is use as a means to regulate human induced stressors under the Clean Water Act (CWA). The RBP provided data on abundance, composition, size, presence of bleaching or disease in the corals, as well as, presence of boring sponges ( Cliona ), sea fans ( Gorgonia ), and sea urchins ( Diadema ) (Table 9). Coral species richness was determined for each station to compare with regional values.
36 Table 9. Parameters calculated f or the RBP. (Fisher, personal communication 2009) Colony density = # of colonies/ 56.5m 2 Average % live tissue Sum of Colony Surface Area =total surface area (TSA) Average Colony Surface Area (AVCSA) = TSA/ # of colonies in transect area Live Surface Area (LSA) = colony surf ace area x decimal percent live tissue (eg. 87.5%= 0.875) Vitality Index = (LSA/TSA) *100 3D Total Coral Cover (3DTC) =TSA normalized by transect area (m 2 ) 3D Live Coral Cover (3DLC) = LSA normalized by transect area (m 2 ) Table 10. Results of Stony Coral Rapid Bioassessment Protocol: colony density (C ol Dens), average % live tissue (Avg %LT), % live cover (%LC), total surface area (TSA), live surface area (LSA), average coral surface area (Avg CSA), and vitality index (VI) (Fisher, personal communication, 2009). The RBP assessment found 12 coral spec ies and 153 colonies. The dominate coral was Montastraea cavernosa (60%) followed by Porites astreoides Meandrina meandrites, and Dichocoenia stokesii. The relative abundance of M. cavernosa varied from 46% at Horseshoe Reef to 66% at Seagate Reef. The R BP data are summarized in Table 10.
37 There are no apparent trends in any parameter with distance from the Delray Outfall. Horseshoe Reef, which was the furthest downstream and Seagate Reef, which was the only upstream site, were least likely to be affected by the secondary treated sewage treatment water. Seagate Reef had the highest colony density, but the smallest colonies overall. Horseshoe Reef had the lowest colony density and lowest coral cover, but the highest average percent live tissue on individua l corals counted. The sites, which likely received the most nutrients from the treated sewage, were the Delray Ledge and Gulf Stream; these sites had higher total and live surface areas and higher percent live cover (both 2 and 3 dimensional estimates) tha n the other sites (Table 11). Fisher (personal communication, 2009) recommended repeat sampling with higher number of samples to better define variability among stations and detect potential differences in responses. Live coral cover data collected by SECR EMP from Palm Beach County stations in 2003 2005 (FWC RI, 2005) were similar to those collected by Fisher using RBP (Fisher, personal communication, 2009). At three SECREMP sites, cora l cover ranged from 0.90 1.26% and M. cavernosa was dominate. Fisher (pe rsonal communication, provide similar estimates for live coral cover.
38 Table 11. Summary of RBP observations. Site Name Observations Horseshoe Reef Lowest colony density Low est coral cover Seagate Reef Highest density Smallest colonies Highest abundance of Montastraea cavernosa Gulf Stream (N and S) Highest total and live coral cover Largest colonies of M. cavernosa Lowest vitality index (live surface area to total surface area) Delray Ledge Infested by a boring sponge, Cliona Comparisons of Sediment Samples with RBP Results The EPA data for coral cover and average sizes are consistent with the data resulting from the FORAM and SEDCON Indices. The foraminiferal assembla ges are dominated by Amphistegina a symbiont bearing g all cases and >4 in 26 of 29 samples. According to Hallock and others (2003), in areas SEDCON Indices for all sites indicate that erosion is the dominant process, which is consistent with the generally small coral size and low percent coral cover. Interestingly, at Horseshoe Reef, which was 18.3 km from the Delray Outfall and the deepest of all the sites, 17.4 m, FI values were the lowest, as were both coral colony density and live coral cover. The stress tolerant foraminiferal genera were dominant in most samples at this site. Thus, the various bioindicators suggest that other factors are likely affecting water quality at the Horseshoe Reef site.
39 Temperature may be limiting coral growth and accretion more than it is limiting the occurrence of symbiont bearing foraminifers. This study represents the northern most application of these bioindicators and previous studies have show n that th e symbiont bearing foraminifers have wider temperature ranges, thriving as low 15 o C (Culver and Buzas, 1981; Langer and Hottinger, 2000), than reef accretion (e.g., Grigg, 1982). According to Ver on (2000), coral reef development occurs where temp eratures lower than 18 o C and higher than about 32 o C not occur for extended periods of time. Many zooxanthellate coral taxa, like symbiont bearing foraminifera, can occur over wider temperature ranges. The southeast coastline of Florida has a narrow con tinental shelf that is exposed to the northward flowing Florida Current (Beal et. al., 2008). The narrow shelf is also exposed to high wave energy, at least during winter storms and summer tropical storm activity (Hartog et al., 2008). Strong mixing of sed iments likely accounts for general similarity among sediment constituents and foraminiferal assemblages. The SEDCON values were extremely consistent and ranged from 0.92 to1.50 (Fig. 14). Ramirez (2008) found similar SEDCON values on the most exposed reef s in Biscayne National Park. While the FI was not as consistent as the SEDCON Index, the similarity of foraminiferal assemblages among samples always exceeded 50%, but never exceeded 80% (Fig. 5). Moreover the assemblages in the three SECREMP samples, whi ch were the most similar set of replicates, again, were only 70 75% similar to each other and fell within the overall group of samples. Likewise, a core group of 21 genera occurred in most of the samples (Fig. 8). Again, Ramirez (2008) reported similar for aminiferal assemblages and FI values on the most exposed reefs in Biscayne National Park.
40 CONCLUSIONS 1. The Delray Outfall did not appear to influence foraminiferal assemblages at the sampled sites. 2. The water quality at the southeast Florida study sites is sufficiently high that both zooxanthellate corals and algal symbiont bearing larger foraminifers are common in the benthic communities, but are not major constituents in the sediments. 3. Unidentifiable carbonate fragments are the overwhelmingly dominant med ium to coarse sand size sediment constituents, while coral fragments and shells of larger foraminifers accounted for an average of less than 6% of the sediment constituents, indicating that erosion exceeds carbonate accretion in the study area. 4. The forami nifers found in the sediments represent a relatively well mixed assemblage of the most common taxa along the southeast Florida shelf: Amphistegina was the single most abundant genus seen, followed by Quinqueloculina and Laevipeneroplis. 5. Shells of Ammonia and Haynesia, both characteristically stress tolerant genera, were surprisingly abundant, making up approximately 15% of the total assemblage. Their abundance may reflect the prevalence of Lyngbya blooms observed in the study area.
41 6. Along the relatively nar row, high wave and current energy coastline of southeast Florida, regional processes are at least as important as local factors in limiting coral growth and reef accretion.
42 REFERENCES CITED Alve E. 1995. Benthic foraminiferal responses to estuarine po llution: a review. Journal of Foraminiferal Research. 25: 190 203. Beal LM, Hummon JM, Williams E, Brown OB, Baringer W, Kearns EJ. 2008. Five years of Florida Current structure and transport from the Royal Caribbean Cruise Ship Explorer of the Seas Journ al of Geophysical Research. 113: 1 11. Carnahan EA, Hoare AM, Hallock P, Lidz BH, Reich CD. 2009. Foraminiferal assemblages in Biscayne Bay, Florida, USA: Responses to urban and agricultural influences in a subtropical estuary. Marine Science Bulletin 10.1 016: 1 13. Clarke KR, Gorley RN. 2001. Primer v5 Roborough, Plymouth, UK: Plymouth Marine Laboratory. www.primer e.com Clarke KR, Warwick RM. 2001. Changes in Marine Communities: An Approach to Statistical Analysis a nd Interpretation. PRIMER E Ltd, Plymouth, UK. Clean Water Act 1987. Clean Water Act of 1987, 2 nd Edition. Alexandria (VA): The Water Pollution Control Federation, 318 pp. Culver SJ, Buzas MA. 1981. Distribution of Recent Benthic Foraminifera in the Gulf o f Mexico. Smithsonian Contributions to Marine Science, Washington, DC. 898 pp. Daniels CA. 2005. Coral Reef Assessment: An Index Utilizing Sediment Constituents. MS Thesis (unpublished), University of South Florida. Tampa, FL. Fisher WS. 2007a Coral Condit ion in Southeast Florida. Addendum, Quality Assurance Project Plan. (unpublished document). Fisher WS. 2007b. Coral Condition in Southeast Florida. Quality Assurance Project Plan. (unpublished document) Fisher WS. 2007 Stony Coral Rapid Bioass essment Protocol. Washington (DC): U. S. Environmental Protection Agency, Office of Water Report EPA Publication. 60 pp. Fisher WS. 2009. Stony Coral Condition of Southeast Florida Near Coastal Reefs. Personal communication, Oct. 8, 2009. Florida F ish and Wildlife Conservation Commission, Fish and Wildlife Research Institute, and National Coral Reef Institute. 2005. Southeast Florida Coral Reef Evaluation and Monitoring Project 2004 Year 2 Final Report. Available at: http://www.nova.edu/ncri/researc h/SECREMP_yr2final.pdf
43 Galloway JN, Sch lesinger WH, Levy II H Michaels A Schnoor JL 1995. Nitrogen fixation: Anthropogenic enhancement environment response. Global Biogeochemical Cycles. 9(2): 235 252. Grigg RW. 1982. Darwin Point: A threshold for atoll formation. Coral Reefs. 1:29 34. Hallo ck P. 1988. The role of nutrient availability in bioerosion: consequences to carbonate buildups. Palaeogeography, Palaeoclimatology, Palaeoecology. 63:275 291. Hallock P. 1999. Chapter 8: Symbiont Bearing Foraminifera. Barun K. SenGupta (ed.). Modern Foram infera. p.123 139. Hallock P. 2000. Larger Foraminifera as Indicators of Coral Reef Vitality. In: Martin RE (ed) Environmental Micropaleontology. Kluwer Academic/Plenum Publishers, New York. 121 150. Hallock P. 2005. Global change and modern coral reefs: New opportunities to understand shallow water carbonate depositional processes. Sedimentary Geology. 175:19 33. Hallock P, Barnes K, Fisher EM. 2004. Coral reef risk assessment from satellites to molecules: A multi scale approach to environmental monitor ing and risk assessment of coral reefs. 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 Monitoring: The FORAM I ndex. Environmental Monitoring and Assessment. 81: 221 238. Hallock P, Williams DE, Fisher EM, Toler SK. 2006a. Bleaching in Foraminifera with Algal Symbionts: Implications for Reef Monitoring and Risk Assessment. Anuario de Instituto de Geociencias UFRJ. 29: 108 128. Hallock P, Williams DE, Toler SK, Fisher EM, Talge HK. 2006 b Bleaching in reef dwelling foraminifers: implications for reef decline. Proceedings, 10^th International Coral Reef Symposium, Okinawa, Japan, June 2004. p. 729 737. Hartog WM Benedet L, Walstra DR, van Koningsveld M, Stive MJF. 2008. Mechanisms that Influence the Performance of Beach Nourishment: A Case Study in Delray Beach, Florida. Journal of Coastal Research. 24: 1304 1319. Hazen and Sawyer. 1994. SEFLOE II Final Report: Broward County Office of Environmental Services North Regional Wastewater Treatment Plant; City of Hollywood Utilities Department Southern Region Wastewater Treatment Plant; Miami Dade Water and Sewer Department North District Wastewater Treatment Plant; Miami Date Water and Sewer Department Central District Wastewater Treatment Plant. Hollywood (FL): Hazen and Sawyer. National Oceanic and Atmospheric Administration.
44 Hoegh Guldberg O, Mumby PJ, Hooten AJ, Steneck RS, Greenfield P, Gomez E, Harvell CD, Sale PF, Edwards AJ, Caldeira K, Knowlton N, Eakin CM, Iglesias Prieto R, Muthiga N, Bradbury RH, Dubi A, Hatziolos ME. 2007. Coral Reef Under Rapid Climate Change and Ocean Acidification. Science Review. 318(5): 1737 1742. Jackson J. 2008. Ecological extinction and evolution in the brave new ocean. PNAS. 105: 11458 11465. Jackson LE, Kurtz J C and Fisher WS ( eds ) 2000. Evaluation Guidelines for Ecological Indicators. EPA/620/R 99/005. U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC. 107 p. Jameson SC, Erdmann MV Kar r JR, Potts KW. 2001. Ch arting a course toward diagnostic monitoring: A continuing review of coral reef attributes and a research strategy for creating coral r eef indexes of biotic integrity. Marine Pollut ion Bulletin. 69: 701 744. Kleypas JK, Langdon C. Coral Reefs and Changing Seawater Carbonate Chemistry. 2006. Coral Reefs and Climate Change: Science and Management. AGU. P. 73 110. Micropalentology. 46: 105 126. Lee JJ, Anderson OR. (eds). 1991. Symb iosis in Foraminifera. In: Biology of Foraminifera. Academic Press, London. pp 157 220. Ramirez A. 2008 Patch Reef Health in Biscayne National Park: A Comparison of Three Foraminiferal Indices MS Thesis (unpublished), University of South Florida. Tampa, FL Sammaro PW, Hallock P, Lang JC, LeGore RS. 2007. Roundtable Discussion Groups Summary Papers: Environmental Bio Indicators in Coral Reef Ecosystems: The Need to Align Research, Monitoring, and Environmental Regulation. Environmental Bioindicators. 2:35 4 6. S chafer CT 2000. Monitoring nearshore marine environments using benthic foraminifera: some protocols and pitfalls: Micropaleontology, 46:161 169. SenGupta B. (ed). 1999. Modern Foraminifera. Kluwer Academic Publisher, Dordrecht. pp. 3 6 Ver on JEN. 2000. Coral of the World. Australian Institute of Marine Science, Townsville. 463 pp.
45 Vitousek PM, Aber JD, Howarth RW, Likens GE, Matson PA, Schindler DW, Schlesinger WH, Tilman GD. 1997 Human alteration of the global nitrogen cycle: sources and conseque nces: Ecological Application 7 : 737 750. Wooldridge SA. 2009. A new conceptual model for the warm water breakdown of the coral algae endosymbiosis. Marine and Freshwater Research: 60: 483 496. Yanko V, Arnold AJ, Parker WC. 1999. Effects of marine pollutio n on benthic foraminifera, in Sen Gupta, B. K. (ed.), Modern Foraminifera: Kluwer Academic Publishers, Boston pp. 217 235.
46 A PPENDICES
47 Appendix I. P ercent mud and the correct ed sedim ent mass examined for analysis of the foraminiferal assemblage
48 Appendix I I. Sediment textures: weight p ercent by phi size
49 Appendix III. Raw data for the sediment constituents and SEDCON Index.
50 Appendix III. (Continued)
51 Appendix III. (Continued)
52 Appendix III. (Continued)
53 Appendix III. (Continued)
54 Appendix III. (Continued)
55 Appendix IV Raw data of all the foraminifera counted in the 29 samples.
56 Appendix IV. (Continued)
57 Appendix IV. (Continued)
58 Appendix IV. (Continued)
59 Appendix IV. (Co ntinued)
60 Appendix IV. (Continued)