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Foraminiferal assemblages as bioindicators of potentially toxic elements in Biscayne Bay, Florida

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Foraminiferal assemblages as bioindicators of potentially toxic elements in Biscayne Bay, Florida
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Carnahan, Elizabeth A
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Estuary
Heavy metals
Cu
Pb
Hg
Zn
Foram index
Benthic
Sediments
Dissertations, Academic -- Marine Science -- Masters -- USF   ( lcsh )
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bibliography   ( marcgt )
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ABSTRACT: Heavy-metal pollution is an issue of concern in estuaries such as Biscayne Bay that are heavily influenced by agricultural, urban, and harbor activities. The goals of this study were to provide a state of the bay assessment that can be used to interpret changes that have occurred over the past 60 years in Biscayne Bay, to provide a baseline to compare changes in the ecosystems during and after execution of the Comprehensive Everglades Restorations Plan (CERP), and to determine if benthic foraminiferal assemblages in Biscayne Bay reflect heavy-metal contamination in sediments. Surficial samples were collected at 147 sites throughout the bay. Analyses included geochemical assessment of the mud fraction for 32 chemical parameters, grain-size analysis, and assessment of foraminiferal assemblages at the genus level.Geochemical analyses revealed elevated concentrations of a suite of heavy metals in the sediments of the northern bay, between Miami and Key Biscayne, and the periphery of the southern bay from Black Creek Canal south to Turkey Point. Cluster analysis, multi-dimensional scaling, and multivariate-correlation analyses revealed three distinct foraminiferal assemblages. One assemblage, characteristic of the northern bay, was defined by stress-tolerant taxa including Ammonia, Cribroelphidium, Nonion, and Haynesina, which were present in low abundances. Distribution of this assemblage correlated with the most elevated concentrations of heavy metals. The assemblage that defined the southwestern margin of the bay was dominated by Ammonia and Quinqueloculina. This assemblage is characterized by the lowest diversities and highest abundances, and is likely influenced by both reduced salinity and elevated organic-carbon concentrations.
Thesis:
Thesis (M.S.M.S.)--University of South Florida, 2005.
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Includes bibliographical references.
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by Elizabeth A. Carnahan.
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Foraminiferal Assemblages As Bioindicator s Of Potentially Toxic Elements In Biscayne Bay, Florida by Elizabeth A. Carnahan 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. Barb Lidz, B.S. Gary Mitchum, Ph.D. Date of Approval: March 31, 2005 Keywords: estuary, heavy metals, Cu, Pb, Hg, Zn, FORAM index, benthic, sediments Copyright 2005, Elizabeth A. Carnahan

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ACKNOWLEDGEMENTS I am greatly indebted to my advisor, Dr Pamela Hallock Muller. Her continuing patience, support and guidance have been invaluable to me throughout my graduate career. I also acknowledge my committee members, Barb Lidz and Gary Mitchum, for their critical review s of my thesis. This research would not have been possible without samples collected by Christopher Reich and Eugene Shinn of th e U.S. Geological Survey. I acknowledge Rickard Curry and Biscayne National Park fo r the issuing of sampling permits. Special thanks to Ana Hoare, Kate Sheps, Heidi Gillum, Camille Daniels, and Nicole Caesar for their help with sample preparation. Thanks to the students of th e Reef Indicators Lab, family, and friends for their patience and moral support. Funding was provided by the University of South Florida/U.S. Geological Survey cooperative agreement 99HQAG0004. Water quality data were provided by the SERCFIU Water Quality Monitoring Networ k which is supported by SFWMD/SERC Cooperative Agreements #C-10244 and #C13178 as well as EPA Agreement #X99462194-0. I dedicate this thesis to my mother, Susan, who continues to learn, grow and develop and who has been a source of enc ouragement and inspiration to me throughout my life

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i TABLE OF CONTENTS LIST OF TABLES iii LIST OF FIGURES iv ABSTRACT vi 1. INTRODUCTION 1 Biscayne Bay, Florida 1 Heavy-Metal Contamination in Estuaries 3 Sources of Heavy Metals 5 The Biological Effects of Heavy Metals 6 The Human-Health Implications of Heavy-Metal Pollution 7 Heavy Metals in Biscayne Bay 8 Foraminifera as Bioindicators 11 Foraminiferal Studies in Biscayne Bay 11 Foraminifers as Bioindicators of Heavy-Metal Pollution 16 Estuaries: Each a Unique Setting 19 Objectives and Goals 20 2. METHODS 21 Sample Collection 21 Sample Processing 22 Geochemical Analysis 26 Grain Size Analysis 26 Analysis of Foraminiferal Assemblages 28 Data Analyses 29 Grain-Size Analysis 29 Geochemical Data Analysis 29 Multivariate Analyses of Foraminiferal Assemblages 31 FORAM Index Analyses 33 Environmental Data Analysis 35 Synthesis of Biotic and Environmental Data 35

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ii 3. RESULTS 36 Grain Size 36 Trace-Metal Distribution 39 Foraminiferal Assemblages 44 Sample Distribution 44 Key Genera 50 FORAM Index 56 Environmental Data 57 Multivariate Analyses 61 4. DISCUSSION 68 Limitations of Data 68 Heavy Metals: Comparisons with other Studies 72 Foraminiferal Distributions throughout Biscayne Bay 76 Foraminiferal Assemblages: Comp arisons with Previous Studies 82 Recommendations for Future Work 86 5. CONCLUSIONS 88 REFERENCES 90 APPENDICES 98 Appendix I List of genera id entified in Biscayne Bay 99 Appendix II Sample collection details 103 Appendix III Samples deleted from various analyses 106 Appendix IV Grain size re ported as weight percent 107 Appendix V-a Values for 32 chemical parameters measured in the 112 mud fraction Appendix V-b Values for 32 chemical parameters measured in the 131 sand fraction Appendix VI Raw counts of foraminife ral abundance in sediments from 132 Biscayne Bay Appendix VII Correlation matrix of measured elements and mud 201 Appendix VIII SIMPER output of diss imilarity between sample groups 203 Appendix IX Environmental data collected by the Southeast Research Center 213 Appendix X Cluster analysis of genera present in >5% of the samples 228

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iii LIST OF TABLES Table 1 Detection limits for 32 measured elements 27 Table 2 Functional groups and example genera defined by Hallock et al. (2003) 34 Table 3 Summary of median grain size in 139 sediment samples from Biscayne Bay 37 Table 4 Correlation matrix of metals of concern 39 Table 5 SIMPER groups, indicati ng within-sample group similarity 48 Table 6 Means and standard deviations of diversity, density, and grain-size data for SIMPER groups 50 Table 7 Correlation matrix of foraminiferal taxa and % mud 53 Table 8 Correlation matr ix of measured environmen tal variables versus key foraminiferal taxa and measures of density and diversity for samples collected in April 2002 59 Table 9 Correlation matrix of geochemi cal parameters and key foraminiferal taxa 62 Table 10 BIO-ENV results of measured environmental parameters as correlated to foraminiferal assemblage for samples collected in April 2002 65 Table 11 BIO-ENV results of measured geochemical parameters as correlated to overall foraminiferal assemblage for all three collections 66 Table 12 BIO-ENV results of measured geochemical parameters as correlated to FORAM Index components 66 Table 13 BIO-BIO results of foramini feral genera as correlated to overall assemblage 67 Table 14 Uses and sources of metals of concern 75 Table 15 Summary data for sa mples with FORAM indices >3.0 77

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iv LIST OF FIGURES Figure 1 Map of southeast coast of Florida, including Biscayne Bay, main waterways and urbanized areas 2 Figure 2 Classifications of the re lative degree of toxicity in four sediment tests 10 Figure 3 A petite Ponar grab 21 Figure 4(a) Chart of northern Bis cayne Bay indicating sample sites 23 Figure 4(b) Chart of central Bis cayne Bay indicating sample sites 24 Figure 4(c) Chart of southern Bis cayne Bay indicating sample sites 25 Figure 5 Schematic diagram of the BI O-ENV procedure: selection of the abiotic variable subset maximizing Spearman-rank correlation ( ) between biotic and abiotic similarity matrices (from Clark and Warwick, 2001) 36 Figure 6 Grain-size dist ribution in Biscayne Bay as (a) median phi and (b) % mud 38 Figure 7 Cluster analysis (R-mode) of geochemical data in sediment samples from Biscayne Bay 41 Figure 8 Metal distributions for m ud-sized sediments in Biscayne Bay 42 Figure 9 Plot of density ve rsus diversity of samples 44 Figure 10 MDS ordination of sample sites according to SIMPER groups 45 Figure 11 Chart of distribution of fora miniferal density in Biscayne Bay and surrounding canals with sample site s represented by SIMPER groups 47 Figure 12 Cluster analysis of key fo raminiferal taxa in Biscayne Bay 52 Figure 13 Distribution of FORAM Index values th roughout Biscayne Bay 56 Figure 14 Contours of environmenta l data obtained from Southeast Environmental Research Center 60

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v Figure 15 Comparison of concentrations of Cu, Pb, Zn, and Hg in the mud versus sand fractions of six samples 70 Figure 16 Bathymetry pr ofile of Biscayne Bay 74 Figure 17 MDS plot of sample sites represented by SIMPER groups showing urban, ocean, freshwater, and estuarine influences 78 Figure 18 Distribution of relative abundance of (a) Ammonia and (b) Miliolinella with sample sites represented by SIMPER groups 80 Figure 19 Distribution of the relative abundance of Ammonia, Cribroelphidium, Haynesina, Elphidium, and Nonion 81 Figure 20 Cluster analysis of forami niferal genera using data from Almasi (1978) 83

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vi FORAMINIFERAL ASSEMBLAGES AS BIOINDICATORS OF POTENTIALLY TOXIC ELEMENTS IN BISCAYNE BAY, FLORIDA Elizabeth Carnahan ABSTRACT Heavy-metal pollution is an issue of concern in estuaries such as Biscayne Bay that are heavily influenced by agricultural, ur ban, and harbor activities The goals of this study were to provide a “state of the bay” assessment that can be used to interpret changes that have occurred over the past 60 ye ars in Biscayne Bay, to provide a baseline to compare changes in the ecosystems during and after execution of the Comprehensive Everglades Restorations Pl an (CERP), and to determine if benthic foraminiferal assemblages in Biscayne Bay reflect hea vy-metal contamination in sediments. Surficial samples were collected at 147 sites throughout the bay. Analyses included geochemical assessment of the mud fraction for 32 chemical parameters, grainsize analysis, and assessment of foraminiferal assemblages at the genus level. Geochemical analyses revealed elevated concentrations of a suite of heavy metals in the sediments of the northern bay, between Miami and Key Biscayne, and the periphery of the southern bay from Black Creek Canal south to Turkey Point. Cluster analysis, multi-dimensional scali ng, and multivariate-correlation analyses revealed three distinct foraminiferal assembla ges. One assemblage, characteristic of the northern bay, was defined by st ress-tolerant taxa including Ammonia, Cribroelphidium, Nonion and Haynesina which were present in low a bundances. Distribution of this assemblage correlated with the most elevat ed concentrations of heavy metals. The assemblage that defined the southweste rn margin of the bay was dominated by Ammonia

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vii and Quinqueloculina This assemblage is characterized by the lowest diversities and highest abundances, and is likely influen ced by both reduced salinity and elevated organic-carbon concentrations. A diverse assemblage of smaller miliolids and rotaliids characterized the open-bay assemblage. This is the only assemblage with a significant component (~10%) of symbiont-bearing foramini fers. In the past 60 years, populations of symbiont-bearing taxa, particularly Archaias and Sorites which are indicators of normal, marine conditions, have decreased in Biscayne Bay, while populations of stresstolerant taxa have increased.

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1 1. INTRODUCTION Biscayne Bay, Florida As the number of people inhabiting the wo rld’s coastlines continues to rise, coastal ecosystems are increasingly threat ened by anthropogenic impacts. The population of Florida has grown exponentially from 2 million residents in 1940 to nearly 16 million residents in the year 2000. In the pa st decade, the largest increases occurred in counties located in southeast Florida. Th e Southeast Florida Metropolitan Statistical Area is the 13th most densely settled in the United States. Between 1990 and 2000, populations in Palm Beach, Broward, and Da de counties increased by 31%, 29%, and 16%, respectively (Office of Urban Pl anning and Development, 2004). Biscayne Bay (Fig. 1) is a shallow, s ubtropical marine estuary in southeast Florida, bordered on the west by Miami-Da de County and on the east by two barrier islands, five major carbonate keys, and a seri es of lesser keys (VanArman, 1984). As part of Biscayne National Park, Biscayne Bay is a resource of special interest. The bay is a site of much recreational and commercia l activity, including several marinas, a major cruise-ship port, and a U. S. Coast Guard port. Fresh water enters the estuary from the Mi ami, Little, and Oleta Rivers, as well as through the Biscayne Aquifer and many manm ade canals (VanArman, 1984). During the past century, the natural flow of fresh wate r into Biscayne Bay has been dramatically altered by the urbanization of southeast Flor ida and the drainage of Lake Okeechobee.

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2 Figure 1 Map of southeast coast of Florid a, including Biscayne Bay, main waterways and urbanized areas

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3 In the late 1940s, a massive flood-control project was initiated throughout central and south Florida (DeGrove, 1984). By drai ning 500,000 acres south of Lake Okeechobee and diverting freshwater flow for cattle farming, urban development, agricultural, industrial and municipal water supplies, the resultant levees and canals irreversibly damaged wetlands and associated ecosyste ms (Douglas, 1978). The altered hydrology has substantially affected salinity and nutrien t flux into Biscayne Bay. At the same time, urban and agricultural development have resu lted in air, land, and water pollution. Heavy-Metal Contamination in Estuaries The term “heavy metal” has been widely used and inadequately described in scientific literature over the past two decades (Duffus, 2002). The term is often defined as metals and metalloids that have been a ssociated with contamination or potential toxicity to an environment. However, there is no authoritative defini tion of this term in the relevant literature (Duffus, 2002). The International Union of Pure and Applied Chemistry recommends a new classification ba sed on the periodic table that reflects an understanding of the chemical basis of t oxicity (Duffus, 2002). However, no such classification has been accepted at this time. Therefore, within this document, the term “heavy metal” will be used to refer to specific, potentially toxic elements. While most heavy metals are biologically essential at very low concentrations, they are potentially toxic to estuarine and marine organism s above a threshold (Kennish, 1992). At higher concentrations, heavy metals act as enzyme inhibitors and can result in the demise of susceptible organisms. Some heavy metals, such as lead, have no known biological function, and may greatly affect biotic communities (Kennish, 1992).

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4 Heavy metals are some of the most common contaminants bound to estuarine sediments. While many metals are highly to xic in one form, they may be essential in another; the bioavailability of metals to marine organi sms depends on the physical and chemical forms of the metal (Riba et al., 2003) Metals adsorbed on particulate matter, carbonate complexes, and metal complexes wi th strong chelating agents (EDTA) show little or no bioavailability. Estuaries have gr adients in many variable s, including salinity, pH, dissolved oxygen, temperature, nutrients, and amount and composition of particles. According to Riba et al. (2003), in estuaries, salinity is the contro lling factor for the partitioning of contaminants between sediment s and overlying or interstitial waters. Fluctuations in pH, redox conditions, and salinity induce changes in heavy-metal speciation, and subsequent toxicity and bioavailability (Bourg, 1995). Long and Morgan (1990) evaluated the potential for biological effects of sediment-sorbed contaminants tested in the National Oceanic and Atmospheric Administration's (NOAA) Nati onal Status and Trends (NS& T) Program. Coastal and estuarine environments throughout the United States are annually sampled and chemically analyzed. The chemical data indicate relative degrees of contamination among the sampling sites, while providing neith er a measure of adverse biological effects nor an estimate of the potential for adverse effects. To complete the evaluation: (1) current literature was reviewed in which c oncentrations of chemicals associated with adverse biological effects are known; (2) appa rent ranges of chemical concentrations were determined in which effects are lik ely to occur, based upon a prevalence of evidence; and (3) the NS&T program’s sediment chemical data were evaluated relative to these consensus effects ranges. Data included in the review are sediment-quality values

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5 derived from many methods. The review evaluated data for 11 trace metals, 18 petroleum hydrocarbons, and 11 synthetic orga nic compound or classes. The 11 trace metals assessed include: Sb, As, Cd, Cr, Cu, Pb, Hg, Ni, Ag, Sn, and Zn (Long and Morgan, 1990). Long et al. (1995) assembled sediment-chemi stry and biological-effects data from numerous marine and estuarine reports to create guidelines for sediment chemistry and the associated potential for biological effect s. Effects-range limits (low and medium) were established for nine of the 11 prev iously noted trace elements. No strong relationships were observed between the incide nce of effects and the concentrations of mercury and nickel. The numerical guidelin es created by Long et al. (1995) are not intended to preclude the use of toxicity tests or other measur es of biological effects. They are useful as informal screening tool s in environmental assessments and should be accompanied by the information on the incidence of effects, which may prove useful in estimating the probability of observing sim ilar adverse effects within the defined concentrations ranges of pa rticular contaminants. Sources of Heavy Metals In natural systems, potentially toxic heavy metals can originate from rocks, ore minerals, and volcanoes. Weathering releases metals during soil formation and transports them to surface and/or aquifer waters. Na tural metal loading may be aggravated by anthropogenic sources (Siegel, 2002). Sc hropp and Windom (1988) noted the necessity to understand the geochemical processes that govern the behavior and fate of metals in estuaries and marine waters. Advective transport, mixing, and differential settling of sediment-sorbed metals are among the processes responsible for variations in trace-metal

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6 composition in different parts of an estuary (Kennish, 1992). Sources of heavy metals to estuaries are primarily (1) freshwater infl ux, (2) the atmosphere, and (3) anthropogenic activity. Excluding the anthropoge nic source, which frequently is locally significant, the primary source of these elements in estuaries is fluvial influx. Anthropogenic inputs are derived from a multitude of activities such as smelting operations, ash disposal, sewagesludge disposal, dredged-spoil dumping, and th e burning of fossil fuels. Municipal and industrial discharges in urbanized/industria lized regions can account for heavy, localized contamination in impacted systems (Kennis h, 1992). Other sources of heavy metals to coastal-marine environments include effluent s from power plants a nd desalination plants, and leaching of fertilizers and pesticides (Brown, 1987). The Biological Effects of Heavy Metals Potentially toxic metals follow natu ral pathways and cycles through the biosphere. Terrestrial, fluvial, estuarine, and oceanic life form s can suffer shortor longterm perturbations if these pathways or cy cles are interrupted by natural events or impacted by human activities. Mobilization of suspect metals, resulting in their bioavailability and hence access to a food web, can impact the integrity of a web. Conversely, immobilization of specific metals can have a negative impact if it causes a deficiency of an essential micronutrient within an ecosystem (Siegel, 2002). The chemical form of a potentially toxic metal determines its bioavailability to a food web. When a heavy metal enters a food web, organisms can react to its bioavailability in different ways. Some orga nisms may discriminate against the uptake of one or more potentially toxic metals. Others may incorporate the metal(s) in their soft or hard parts in proportion to the concentration(s) in the growth environments, excreting any

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7 excess. Still other organisms may be tolerant of heavy metals and will accumulate concentrations greatly in excess amounts in a growth environment without any damage (Siegel, 2002). Laboratory analyses must be performed to determine the concentrations of heavy metals in sediments. However, these resu lts alone do not offer an effective basis for estimating the potential for harmful effects to liv ing resources. Interpretive tools, such as those developed by Long et al. (1995), can relate sediment-che mistry to the potential for adverse biological effects. The free-metal ionic activity may be more important in producing metal toxicity than the total concentrati on of a metal (Kennish, 1992). Metal uptake by estuarine organisms occurs through diffusion as well as ingestion of food and particulate inorganic matter. The metals can be stored in the skel etal structure, concre tions, or intracellular matrices of an organism, and excreted in feces, eggs, and molting products. Organisms have additional defense mechanisms; metallo thioneins and other heavy metal-binding proteins bind metal contaminants within th e organism, thereby help ing to control heavymetal concentrations (Kennish, 1992). The Human-Health Implicatio ns of Heavy-Metal Pollution Even metals that are biologically essen tial have the potential to be harmful to humans and other living organisms at high levels of exposure (Hu, 2002). Humans can be exposed to metals through inhalation of dus t or gaseous particles, or ingestion through food and drink. Once a metal is incorporated, it is distributed to tissues and organs. Although excretion typically occurs through the kidneys and digestive tract, metals tend to persist in sites like the liver, bones, a nd kidneys for years or decades. Individual

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8 variability in vulnerability to metal toxicity remains a subject of investigation. Low-level metals exposure likely cont ributes to chronic disease and impaired functioning (Hu, 2002). Heavy Metals in Biscayne Bay As early as the 1970s, environmental scien tists noted chemical pollutants entering Biscayne Bay from the Miami River and othe r canals, altering the chemistry of the estuary (Waite, 1976). In recent years, the co ncentrations and distributions of potentially toxic chemicals in Biscayne Bay and adjoining canals have gained further attention. Whereas the geographic scope and objectives of studies have diffe red, the data have provided a relatively consiste nt picture of chemical cont amination in the surficial sediments of the bay (Long et al., 1999). The South Florida Water Management Dist rict (1994) recognized that water and sediment-quality degradation were problems in Biscayne Bay. They identified chronic problems with contamination by sewage in por tions of Biscayne Bay and identified trace metals and numerous other pollutants that had accumulated in the sediments of the central bay. A lack of bay-wide information on the toxicological condition of the bay sediments prompted several agencies to recogn ize a need for these data and a willingness to assist NOAA (Long et al., 1999). Long et al. (1999) collected 226 surface-sediment samples from nine major regions throughout the bay. The three southernmost zones include the entirety of the open bay (Fig. 2) Sediment chemistry was analyzed and laboratory toxicity tests were performed to indicate the potential for ecotoxicological effects in sediments.

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9 Long et al. (1999) tested sediment samp les for toxicity according to (1) amphipod ( Ampelisca abdita ) survival tests, (2) sea-urchin ( Arbacia punctulata ) fertility and (3) embryo-development tests, and (4) microbial bioluminescence ( Photobacterium phosphoreum ) (Microtox™) tests (Fig. 2). The range of toxicity tests revealed differences in severity, inciden ce, spatial patterns, and spatial extent of toxicity (Fig. 2). The most sensitive test, a bioassay of morphol ogical development of sea-urchin embryos, indicated pervasive toxicity th roughout the entire bay. The l east sensitive test, a bioassay performed with a benthic amphipod, indicated that acute toxicity was restricted to a very small portion of the bay. The toxicity test s of sediments from the northern bay, as well as from Coral Gables and Snapper Creek Ca nals, ranged from non-t oxic to moderately toxic by all four test parameters. Sediments from sites within and bordering Black Creek Canal and Turkey Point were moderately toxi c or highly toxic for at least one of four parameters, as were several sites in the southern, open bay. Several trace metals were found in concentr ations in excess of those expected in reference sediments. Chemicals of highest concern, copper, lead, and mercury, were elevated relative to numeric gu idelines, showed strongest concordance with a measure of toxicity and were most concentrated in sa mples in which toxicity was most severe. Whereas patterns of chemical contaminati on generally followed patterns in toxicity, several exceptions were noted (Long et al., 1999).

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10 Figure 2 Classifications of the rela tive degree of toxicity in four se diment tests: (1) amphipod survival tests, (2) sea-urchin fertility and (3) embr yo-development tests, and (4) microbial bioluminescence ( Photobacterium phosphoreum ) (Microtox™) (from Long et al., 1999)

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11 Foraminifera as Bioindicators The Foraminifera are a class of micr oscopic, shelled protists. Benthic foraminifers can be used as bioindicators of coastal pollution because: (1) they have short lifespans and specific niches, and th erefore respond quickly to environmental change; (2) they remain well preserved in the sedimentary record; (3) they are widely distributed yet generally regard ed as relatively immobile; (4) they are diverse; (5) they are small, abundant and easily sampled, and ther efore their use can be cost effective; and (6) their collection has minimal impact on e nvironmental resources (Yanko et al., 1994). Since benthic foraminifers vary temporally and spatially in relation to biotic and abiotic environmental variables, changes in conditions can lead to changes in species composition of the foraminiferal fauna (Culve r and Buzas, 1995). Observations by Buzas et al. (2002) have shown that biotic and abiotic factors re sponsible for variations in foraminiferal species abundance can operate on relatively small spatial scales. Their study proposed that long-term stability is achieved through considerable short-term variability in space and time. Therefore, caution must be taken when comparing live assemblages among stations. Rather, the accumulation of tests in the sediments (commonly referred to as total assemblage) more adequately reflects the foraminiferal community within an area (Scott and Medioli, 1980; Hallock et al., 2003). Foraminiferal Studies in Biscayne Bay Numerous studies have examined fora miniferal assemblages in Biscayne Bay over the past 65 years (Stubbs, 1940; Bu sh, 1949, 1958; Cole, 1974; Andersen, 1975; Goldstein, 1976; Almasi, 1978; Tisserand De lclos, 1979; Ishman et al., 1997; Hoare, 2002). Taxa, by genera, identified by thes e studies are summarized in Appendix I.

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12 Stubbs (1940) noted that local faunal lists of foraminifers from Florida's shallow coastal waters were lacking at that time. He described foraminiferal assemblages from seven bottom samples in the vicinity of Bisca yne Bay. Of the seven stations, five varied only slightly in depth, temperat ure, and bottom conditions. Ne vertheless, as Buzas et al. (2002) noted, inter-station variab ility can be remarkably high. Bottom characteristics of sample sites ranged from seagrass to har dbottom, and sediments ranged from fine to coarse quartz sand. Only nine of the 61 speci es listed (belonging to 23 genera) occurred at all five stations, only two species were found in all seven stations, and 22 of the species were recorded at only one station. No two stations showed the same assemblage of species or degree of abundance of indi viduals. Stubbs (1940) concluded that foraminifers are susceptible to very slight ecologic differences. Bush (1949) initially analyzed 10 sedi ment samples from Biscayne Bay for foraminiferal assemblages and sediment ch aracteristics. His continued work (Bush, 1958) expanded upon the pilot study, analyzing 63 samples originally collected. Results of his analyses were compared with ch emical and physical oceanographic factors obtained by others. Bush (1958) concluded th e bay contains a provincial foraminiferal fauna, a consequence of the environment of th e area. The southern portion of the bay is affected by a greater degree of environmenta l variability than the eastern margin. Bush (1958) found Quinqueloculina Triloculina Elphidium and Archaias to be the most common genera in the bay. Howeve r, although they were the most abundant, he did not find them to be characteristic of any one particular biotope. Cole (1974) studied the effect of thermal st ress on benthic foraminifera in a small, shallow lagoon located approximately 10 miles s outh of Miami at the southern end of the

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13 bay. The lagoon received hot marine water fr om cooling generators in the Cutler Power Plant. Cole (1974) found foraminiferal asse mblages within the la goon to be controlled by the precise zone sampled. The dominant group of foraminiferal species differed in each of the four environmental zones, but was cons istent for all samples within a particular zone. Species diversity and individual test sizes in th e live population correlated positively with distance from the effluent mouth, while the percentage of malformed individuals showed a ne gative correlation. Cole (1974) concluded that foraminiferal assemblages in cores from below 14 cm closely resembled normal-temperature assembla ges, while assemblages in the top of the cores reflected temperature influence. Under thermal stress, the dominant species comprised a greater percentage of the total population. Under normal conditions, population distributions were mo re even. Cole (1974) found Ammonia was the genus most resistant to temperature affects. Pr oportions of test deformities in, rather than presence of, Quinqueloculina and Triloculina were indicative of the stressed environment. Archaias and Sorites were relatively rare in the cores, and they were each only present in small numbers in one surface sample. Andersen (1975) investigated a portion of northern Biscayne Bay to determine the distribution of its benthic fora miniferal assemblages. He identified 75 genera in the 26 samples taken from 15 stations. Andersen conc luded that salinity wa s an important factor controlling assemblages within northern Biscayne Bay, and he recognized three faunal assemblages reflecting salinity variations. Ammonia beccarii and Elphidium gunteri galvestonense dominated the western bay margi n, characterized by brackish-water influence, whereas the Miliolidae were most numerous in the open bay and the

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14 Peneroplidae became increasingly numerous at the eastern bay margin stations, where conditions are more oceanic. Andersen also observed a relationship between the coarse fraction and foraminiferal data; as average se diment grain size incr eased, fewer tests and fewer species were found in the sample. He interpreted the presence of normally deeperwater species within the shallow bay waters as evidence of the active inshore transport of sediments at the bay's east ern margin (Andersen, 1975). Goldstein (1976) investigated the ecology a nd distribution of benthic foraminifera in a south Florida mangrove and salt-marsh hab itat in the vicinity of Turkey Point, an area characterized by wide fluctu ations in salinity, temperat ure, and water level. She found that each species had its own distinct distribution within the study area. She observed no faunal breaks in the distributi on of foraminiferal populations along her transect. Community characteristics also di splayed gradual changes along the transect, with diversity, equitability, and density of living individuals increasing seaward. Almasi (1978) investigated the taxon omy and distribution of recent benthic foraminifera in Barnes Sound, northeast Flor ida Bay (see Fig. 1), to determine factors that cause color variation in foraminiferal tests. Thirty stations along a series of transects were sampled for surface-sediment and water samples. Almasi (1978) found color variation, due to a series of r eactions that take place in a re ducing environment, in 45% of foraminiferal tests. The most a bundant genera in Barnes Sound were Archaias, Quinqueloculina, Elphidium and Triloculina Tisserand Delclos (1979) compared foraminiferal assemblages from Joe Kemp Key and Key Biscayne. Joe Kemp Key, located in Florida Bay, experiences terrestrial influence from the Everglades watershed. Key Biscayne, farther to the north and at the

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15 outer limits of Biscayne Bay, is influenced by urban Miami from the west and the open ocean to the east. Tisserand Delclos found clear faunal differences between the two islands. The Joe Kemp Key vicinity was dominated by members of the families Rotaliidae and Elphididae, whic h composed over 93% of the total assemblage. At Key Biscayne, these two families were rare a nd composed less than 6% of the total assemblage. The Key Biscayne assemblage was dominated by Archaias angulatus Peneroplis carinatus and Sorites marginalis, which together composed 45% of the population, and the family Miliolidae that acco unted for 28%. Overall, the Key Biscayne site showed higher diversity (Tisserand Delclos, 1979). During August 1996, Ishman et al. (1997) co llected surficial sediment-samples and water-column data from 23 sites within Bi scayne Bay. The researchers are part of a team that evaluated modern biotic distribu tions and determined natural versus humaninduced variability in the sout h Florida ecosystem prior to the Comprehensive Everglades Restoration Plan. Sixty-nine taxa of benthic foraminifers were identified in surfacesediment samples from Biscayne Bay. Hoare (2002) examined foraminiferal assemblages and heavy-metal concentrations on the western margin of Bis cayne Bay. Snapper Creek, believed to show nominal pollution, acted as a "r eference site" agains t areas believed to possess elevated concentrations of heavy metals. At the time of sampling, no environmental measurements were carried out. Measurements of temperature, salinity, and dissolved oxygen were later obtained from the Southeast Environmental Research Center, SERC, maintained by Florida International Universi ty (Hoare, 2002). Her pilot study indicated increasing water quality with increasing dist ance from shore, based on the foraminiferal

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16 assemblages. These sites are included in the results and discussion of my bay-wide assessment. The FORAM (Foraminifera in Reef A ssessment and Monitoring) Index of Hallock et al. (2003, p. 222) is "intended to provide resource managers with a measure, which is independent of coral populations, to determine whether water quality in the environment is sufficient to support reef growth or recovery.” This simple index is based on foraminiferal assemblage data from surficial sediments. I will utilize such data from Biscayne Bay to determine if the FORAM Index is a useful resource-assessment tool in a subtropical estuary and if modifications ar e necessary to adapt its use to estuarine environments. Foraminifers as Bioindicators of Heavy-Metal Pollution Pollution studies using benthic foraminifers as proxy indicators were initiated in the early 1960s, although pollu tion effects on foraminifers were recognized earlier (see reviews by Alve, 1995; Yanko et al., 1999; Schafer, 2000). Foraminifers are good indicators of pollution because they are of ten among the last organisms to disappear completely from an impacted site (Schafer 2000). Early research primarily targeted organic-waste discharges from sewage outfalls (Watkins, 1961) or from paper and pulp mills. Several studies addressed oil, thermal, and various other types of chemical pollution, and in recent years, studies of the effects of heavy-metal pollution on foraminifers have become more common (Alve, 1995). Studies examining foraminifers as bioi ndicators of heavy-metal pollution tend to fall into three categories: assemblage analyses, morphological analyses, and

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17 incorporations of heavy metals into forami niferal tests. Although much of the heavymetal research integrates these categories, I will address them separately. In recent years, several researchers have focused on morphological abnormalities of foraminifera in response to various pollution sources, particularly heavy-metal contamination (Watkins, 1961; Boltovskoy et al., 1991; Sharifi et al., 1991; Geslin et al., 1998; Yanko et al., 1998; Coccioni, 2000; Sami r, 2000; Samir and El-Din, 2001; Geslin et al., 2002; Elberling et al ., 2003). Although heavy-metal concentrations directly correlate with elevated percentages of deformed tests in many case studies, there is more to consider. No variable (temperature, sa linity, depth, carbonate solubility, dissolved oxygen, substrate, water motion, trace elem ents, etc.) acts independently on test morphologies (Boltovskoy et al., 1991). A st ressor such as salinity changes may cause abnormalities in one location but not in another (S harifi et al., 1991; Yanko et al., 1998). Background percentages of deformed te sts in unstressed conditions must be considered. Deformities are commonly found in up to 1% of total live populations, for a given species in given envi ronmental conditions, represen ting the range of natural variability (Yanko et al., 1998). However, it is very difficult to find ecosystems untouched, directly or indirec tly, by human impact. Geslin et al. (2002) found that, in Brazil, in the estuarine environments they st udied, it was difficult to distinguish natural from anthropogenic stress and, in fact, th eir study showed higher percentages of abnormal tests occurring in supposedly nonpolluted areas than in polluted areas. Nevertheless, a convincing amount of r ecent research supports the correlation between increased heavy-metal concentrations and aberrations in foraminiferal tests. Elberling et al. (2003) found that abnorma lities may represent a useful biomarker for

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18 evaluating trends in the biologi cal impact resulting from subm arine tailings disposal in Western Greenland. Samir (2000), working in Egypt, surmised that benthic foraminiferal abnormalities depend on the nature of the pol lutant. Heavy metals from industrial locations were associated with test defo rmations in Southhampton Water, England (Sharifi et al., 1991). However, in the pilo t study of the Biscayne Bay project, Hoare (2002) did not find a correlation between te st abnormalities and increased heavy-metal concentrations. Test abnormalities were observed at several sites. However, those occurrences were not at sites where tr ace-metal concentrations were highest. Consequently, test abnormalities were not cons idered in the bay-wide assessment. A vast amount of research has quantifie d and analyzed total benthic foraminiferal assemblages as bioindicators of heavy-me tal pollution (Naidu et al., 1985; Alve and Nagy, 1986; Banerji, 1992; Debenay et al., 2001; Gonzlez-Regalado et al., 2001; Cearreta et al., 2002; Armynot du Ch telet et al., 2004). Total densities and species richness tend to decrease in areas of elevat ed heavy-metal concentr ations (Naidu et al., 1985; Sharifi et al., 1991; Armynot du Ch telet et al., 2004). However, quite often, one or a few taxa of foraminifers will thrive in stressed environments (Schafer, 2000). For example, in soft-bottom fauna in Norwegian fjords, 22 out of 23 speci es tolerant of high concentrations of copper were present at st ations with very lo w diversity (Rygg, 1985). Debenay et al. (2001) and Armynot du Ch telet et al. (2004) both found Haynesina germanica, a tolerant pioneer species, to be an indicator of heavy-metal pollution. Sharifi et al. (1991) observed that H. germanica, Ammonia beccarii, and Elphidium excavatum not only dominated at all nine of their sample sites, but they also collectively constituted over 80% of living assemblage. Elphidium excavatum showed the highest tolerance to

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19 heavy-metal pollution, followed by H. germanica and A. beccarii. Banerji (1992) also found Elphidium to be least impacted by increased heavy-metal concentrations. Some researchers have noted that there are limitations to statistical analyses. In practice, it is often difficult to separate eff ects caused by heavy metals from those caused by organic material and conse quent hypoxia, since most pollu ted areas are subjected to some kind of organic enrichment (Alve, 1995). Debenay et al. (2001) found that correlation between heavy metals and the si lt and clay fraction of sediments makes it difficult to determine whether sediment ch aracteristics or pollution have the stronger influence on foraminiferal assemblages, excep t in areas heavily affected by pollution. Cearreta et al. (2002) found the occurrence of foraminifers in the two industrial zones along the Bilbao estuary in Northern Spain did no t correspond to defined levels of metals. Instead, oxygen limitation was believed to be the key factor explai ning the absence of foraminifers in sediment cores. In some cases, individual heavy metals or groups of heavy metals must be analyzed separately. Along the Bombay Coast in India, Banerji (1992) found a maximum diversity of foraminife rs coupled with highe r concentrations of Fe-Mn-Zn and lower concen trations of Co-Ni-Pb. Estuaries: Each a Unique Setting Estuaries tend to serve as recipients of domestic and indus trial effluents. Nevertheless, each estuary is unique. Di rect comparisons between an estuarine environment affected by many varying efflue nts and a normal-marine setting should be made with caution due to the dynamic physical chemical, biological, and biogeochemical properties of estuaries. However, comparisons within the same estuary between relatively unimpacted and anthropogenically impacted area s are often more reliable (Alve, 1995).

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20 The heterogeneity of nearshore marine setti ngs calls for a precautionary approach that recognizes our limited knowledge of the dynami c interplay between diagenetic effects and biological intera ctions, at both the species and co mmunity levels (Schafer, 2000). Objectives and Goals My research will utilize environmental data, geochemical data, grain-size analysis, and foraminiferal assemblages to characterize the present conditions in Biscayne Bay, Florida, building upon the pilot study of Hoare (2002). Specific questions being addressed include (1) are there areas in Biscayne Bay where sediments demonstrate elevated concentrations of heavy metals; (2) are there suites of heavy metals that cooccur; (3) do heavy-metal concentrations co rrelate with grain-size distribution; (4) are there identifiable foraminiferal assemblages within the bay and, if so, what are their distributions; (5) do oc currences of foraminiferal taxa or assemblages in sediments correlate with heavy-metal concentrations or other measured environmental parameters; (6) is the FORAM Index, which was developed as a bioindicator for reef environments, useful in resource assessment in a subtropi cal estuary; and if so, (7) does the FORAM Index require any modification to adapt its use to estuarine environments? The goal of this research project is to pr ovide a “state of the bay” asse ssment that can be used to interpret changes that have occurred over the past 60 years in Biscayne Bay, and to provide a baseline to compare changes in th e ecosystems during a nd after execution of the Comprehensive Everglades Restorat ions Plan (CERP) (Perry, 2004).

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21 2. METHODS Sample Collection US Geological Survey (USGS) personne l collected sediment samples from Biscayne Bay during three sampling trips in December 2000, July 2001, and April 2002 (Figs. 4a,b,c and Appendix II). In Decembe r 2000, divers collected samples by hand into plastic bags. A petite Ponar grab was used to collect sediment during the second and third collections (Fig. 3). Figure 3 A petite Ponar grab Depending on the bottom material (sandy vs muddy), the Ponar will sample to a depth of 1 to 4 cm into the sediment. Sedime nt samples were transfe rred into plastic bags and frozen until analysis was begun. A grab sample from Biscayne Bay usually represents accumulation of the past 5 years or less, based on accumulation rates of 1 cm per year (Ishman et al., 1997). However, in regions where sediments are very thin, the age of the surface sediments is

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22 undetermined (Wanless, 1976). In most of Biscayne Bay, the sediment cover is relatively thin, thickening near mangroves a nd along isolated mud banks (Chris Reich, USGS, personal communication). During the April 2002 collection, dissolved oxygen, salinity, and temperature were recorded in situ using a Hydrolab MiniSonde multi-probe instrument. Sampling depths were estimat ed from a bathymetric chart based on GPS coordinates. Sample Processing For processing, samples were thawed overnight. Each sample was mixed thoroughly and a subsample was wet sieved us ing deionized water over a 63-m mesh nylon sieve. Samples, separated into mud fraction (<63 m) and sand fraction (>63 m), were dried in an oven at less than 50 C. The mud fraction was weighed using an electronic balance and retained for geochemi cal analysis. The sand fraction was weighed and later used for grain-size analysis and a ssessment of the foraminiferal assemblage. Because several technicians processed the sa mples over three years, a few subsamples were lost, accounting for slight differences among sample totals among procedures (Appendix IV). Multivariate analyses will include only samples used in all individual analyses.

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23 Fi g ure 4 ( a ) Chart of northern Bisca y ne Ba y indicatin g sam p le sites

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24 Figure 4 (b) Chart of central Bis cayne Bay indicating sample sites

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25 Figure 4 (c) Chart of southern Bi scayne Bay indicating sample sites

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26 Geochemical Analysis Actlabs Group of Companies (http: //www.actlabs.com/home.htm, 2005) in Tucson, Arizona, analyzed the mud fractions (<63 m) of all samples for 32 elements using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). ICP-OES is a multi-element technique, capable of measuring elemental concentrations to very low detection limits (ppm to ppb). The sample mate rial is placed into solution using specific partial leaches, single acids, mixed acids, or fusion techniques using fluxes. The sample solution is then introduced into a radio frequency-excited plasma (~8000K). Atoms within the samples are excited to the point that they emit wavelength-specific photons or light that is characteristic of a particular element. The number of photons produced is directly related to the con centration of that element in the sample (Actlabs, 2004). Elements measured, their chemical symbols, and detection limits are presented in Table 1. In this document, elements will be referred to by their chemical symbol. Grain-Size Analysis The sand fractions (>63 m) were dry siev ed according to methods described by Folk (1980). The standard sieve set was secure d on top of a shaker. The subsample (3 to 20 grams) was gently disaggregated if necessa ry, and placed in the top, coarsest sieve. The shaker was then set to medium for a mini mum of five minutes. I visually determined if the sieving was complete. If not, the shaker was set for another five-minute interval until sieving was complete. The contents of each screen were poured onto tared weighing paper and weighed to the nearest milligram. The fractions were then recombined for the micropaleontological anal yses. In determining the percent mud of

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27 each sediment sample, calculations were ad justed to account for the fine fraction removed in the washing step. Table 1 Detection limits for 32 measur ed elements (*rarely detectable) Element PPM % Silver, Ag (ppm) 0.2 -*Cadmium, Cd (ppm) 0.5 -Copper, Cu (ppm) 1 -Manganese, Mn (ppm) 2 -Molybdenum, Mo (ppm) 2 -Nickel, Ni (ppm) 1 -Lead, Pb (ppm) 2 -Zinc, Zn (ppm) 1 -Aluminum, Al (%) -0.01 *Arsenic, As (ppm) 10 -Barium, Ba (ppm) 1 -*Beryllium, Be (ppm) 1 -Bismuth, Bi (ppm) 10 -Calcium, Ca (%) -0.01 Cobalt, Co (ppm) 1 -Chromium, Cr (ppm) 2 -Iron, Fe (%) -0.01 Potassium, K (%) -0.01 Magnesium, Mg (%) -0.01 Sodium, Na (%) -0.01 Phosphorus, P (%) -0.001 *Antimony, Sb (ppm) 10 -*Scandium, Sc (ppm) 1 -Tin, Sn (ppm) 10 -Strontium, Sr (ppm) 1 *Titanium, Ti (%) -0.001 Vanadium, V (ppm) 1 -*Tungsten, W (ppm) 10 -Yttrium, Y (ppm) 1 -Zirconium, Zr (ppm) 1 -Sulfur, S (%) +100 -Mercury, Hg (ppb) 5 ppb -

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28 Analysis of Foraminiferal Assemblages The sand fractions (>63 m) were analy zed microscopically for foraminiferal tests present as described by Ha llock et al. (2003). Each sa mple was poured into a clean petri dish and mixed thoroughly. A fine spatula was used to take a small scoop (approximately 0.1 grams) from the center of the mound, bottom up, to get an adequate representation of all grain sizes. The scoop was weighed to the nearest milligram. Each sample was then examined under a conventional stereomicroscope and the foraminifers were removed using a fine artist's brush moistened with water (tip size 3/0 to 5/0). Individual specimens were placed onto a cardboard micropaleontological faunal slide, which was coated thinly with watersoluble glue. This procedure was repeated until 150-200 specimens were obtained (Hallock et al., 2003). For generic classification, a sample number of this size provides a usef ul compromise between cost of analysis (investigator's time) and benef it (additional precis ion of larger samples) (Dix 2001). Foraminifers were identified to genu s using characteristics defined by Loeblich and Tappan (1987). Taxa identified in lo w abundances not previously described in Biscayne Bay included Bolivinella, Cornuspira, Floresina (Revets, 1990) and Lachlanella I identified Cribroelphidium, Laevipeneroplis, Haynesina, Affinetrina and Siphonaperta in significant numbers. Cribroelphidium, Laevipeneroplis and Haynesina bear close resemblance to other genera a nd the distinctions ar e not always made by researchers. Loeblich an d Tappan (1987) describe Elphidium with a carinate periphery and Cribroelphidium with a rounded, noncarinate periphe ry. However, the foraminifer commonly identified as Elphidium galvestonense (Poag, 1981) has a rounded,

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29 noncarinate periphery. In this study, I identified these two ge nera consistent with the description of Loeblich and Tappan (1987). Affinetrina (Loeblich and Tappan, 1987), characterized by a slit-like ap erture enclosing a long slende r tooth that is terminally inflated or bifid, is identified by many researchers as Triloculina planciana Likewise, I believe Siphonaperta (Loeblich and Tappan, 1987) is frequently identified as Quinqueloculina agglutinans or Quinqueloculina bicarinata (Poag, 1981). The total foraminiferal assemblage (incl uding both living and dead) was assessed. However individuals that were largely broken (less than 50% of the test remaining) or obviously geologically reworked were not in cluded in analyses. The composition of living assemblages solely reflects environmen tal conditions at that microhabitat at the time of sample collection (Buzas et al., 2002), whereas the total assemblages integrate information about the general conditions over a longer time period (Alve and Nagy, 1986). Data Analyses Grain-Size Analysis The raw weights for each grain-size cla ss were converted to weight percents for each sample. Median grain size for each sample was also calculated and is represented in phi (Appendix IV). Phi diameter is comput ed by taking the negative log of the diameter in millimeters. Geochemical-Data Analysis All 147 samples were analyzed for the 32 elements listed in Appendix V-a. Seven elements, Be, Sb, Ti, W, Cd, As, and Sc were detectable in fewer than 5% of the samples and were not considered in the statistical analyses.

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30 Eleven metals could be considered metals of concern based on work by Long and Morgan (1990); however, Sb, As, and Cd were so rarely detected that they were not considered in the statistical analyses. The remaining eight elements, Cr, Cu, Pb, Hg, Ni, Ag, Sn, and Zn, will be referred to as metals of concern in this paper. Contour maps were plotted for these metals of environmental c oncern using SURFER v.8 (Golden Software). For the remaining 25 elements, in samples in which a concentration was below detection limits, a concentration of half of the lowe st detectable concentration was used for analysis, consistent with recommenda tions of Parker and Arnold (1999). Using the statistical soft ware package, PRIMER-e v.5 (Plymouth Routines in Multivariate Ecological Research, 2000), simila rity matrices were constructed for sites (Q-mode) and for elements (R-mode) using l og (1+X) transformed data with Euclidean distance (0-inifinity) chosen as the similarity measure. Cl uster analyses and non-metric multi-dimensional scaling (MDS) plots were derived from the similarity matrices. Similarity measures based on Euclidean distan ce are sensitive to differences in sample magnitude (Parker and Arnold, 1999) though transforming the data reduces that sensitivity. MDS constructs a configuration of samples or variables, in this case 2dimensional, which attempts to satisfy all the conditions imposed by the rank similarity matrix. The stress coefficient, ranging fr om 0 to 1, measures th e success of the MDS plot. A stress coefficient <0.05 is excelle nt, <0.1 good, and <0.2 s till gives a potentially useful 2-dimensional picture. However, at the higher end of this range, multiple forms of analysis are recommended for crossc heck (Clarke and Warwick, 2001). Pearson’s correlation analyses of log (1+X) transformed data were conducted using Statistica v.5.5 (2000) to elucidate rela tionships between among metals. Analyses

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31 were based upon the assumption that all samp les were independent. These analyses produce Pearson's correlation coefficients (-1.01.0), which are relativ ely insensitive to differences in numerical size of the entitie s being clustered (Par ker and Arnold, 1999). A positive correlation is evidence of a general tendency that large values of X are associated with large values of Y and small values of X are associated with small values of Y. Conversely, a negative correlation is evidence of a general tendency that large values of X are associated with small values of Y and small values of X are associated with large values of Y. Multivariate Analysis of Foraminiferal Assemblages Foraminiferal data can be represented in either relative or absolute abundance. Relative abundance expresses each genus as a pe rcentage of total foraminifers present. Absolute abundance accounts for the number of foraminifers per unit mass, in grams, of bulk sediment sorted. I will report data as relative abundance unless otherwise noted. Shannon and Fisher diversity indices were calcul ated for each sample site. Fisher’s alpha index starts with the ratio of number of sa mples to number of sp ecies and generates from it a log series distribution that will predic t the number of species represented by one individual, two individuals, and so on. The Shannon diversity measure came from information theory and measures the order (or disorder) observed within a particular system (Hayek and Buzas, 1997). The first set of analyses determined groups of sample sites based on their similarity of foraminiferal assemblages. PRIMER-e v.5 was used to construct BrayCurtis similarity matrices on square-root transformed, X, data. This transformation down-weights the importance of the highly abunda nt species, so that similarities depend

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32 not only on their values, but also those of “mid-range” species. Based on this similarity matrix, Q-mode cluster analysis was performed and MDS plots constructed. The PRIMER SIMPER routine (simila rity percentages) examines the contributions of individual genera to the se paration of the groups, either for an observed clustering pattern or for the differences among set of samples (Clarke and Warwick, 2001). SIMPER analysis is carried out on s quare-root transformed data based on site groupings defined by the previous cluster anal ysis. SIMPER outputs several statistical parameters for each genus contributing to >90% similarity within each group or dissimilarity between groups. Outputs include average abundance, average similarity, a ratio of similarity to stan dard deviation, percent contri bution, and cumulative percent contribution of each genus. To determine which genera tend to co-o ccur (i.e., R-mode analyses), a BrayCurtis similarity matrix was constructed based on untransformed, row-standardized generic data for all taxa present in greater than 5% of the samples. Two species may have considerably different mean levels of abundance yet be perfectly similar in the sense that their counts are in strict ratio to each other across the samples. Row standardization entails dividing each original data entr y by its generic tota l and multiplying by 100 (Clarke and Warwick, 2001). Cluster analysis and MDS plots based on this similarity matrix were utilized to define foraminiferal assemblages. Pearson’ s correlation analyses of square-root transformed data were c onducted using Statisti ca (2000) to explain relationships between genera further.

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33 FORAM Index Analyses The FORAM Index (FI) entails enumeration of foraminiferal ta xa into functional groups defined by Hallock et al. (2003) (Tab le 2). Yanko et al. (1999) summarized a list of genera with known tolerance to pollution including Ammonia, Bolivina, Cribroelphidium and Haynesina Bernhard and Sen Gupta (1999) reported that Ammonia, Nonion, Bolivina and Brizalina have been present in low-oxygen foraminiferal assemblages. Other smaller, heterotrophic genera of the orders Rotaliida and Miliolida indicate the presence of intermediate f ood resources (Crevison, 2001). Archaias, Androsina, Laevipeneroplis, and Sorites harbor algal endosymbionts. Their presence indicates lower-nutrien t, adequate-light conditions. The FORAM Index (FI) utilizes foraminiferal assemblages from surface sediments of reef-associated environments to determine the suitability of benthic environments for communities dominated by al gal symbiotic organisms. An auxiliary goal of my study is to determine if the FI can be usefully applied to subtropical estuarine sediments and, if so, are modifications needed. The FI is calculated as follows (Hallock et al., 2003). FI = (10 x Ps) + (Po) + (2 x Ph) where Ps = Ns/T, Po = No/T, Ph = Nh/T and T = total number of specimens counted Ns = number of symbiont-bearing specimens No = number of opportunistic* specimens Nh = number of small, heterotrophic specimens *I shall refer to taxa considered opportunistic by Hallock et al. (2003) as “stress tolerant,” a usage more consistent with Yanko (1999).

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34 Table 2 Functional groups and example genera defined by Ha llock et al. (2003) Foraminifer Functional Group Genera Symbiont-bearing miliolids Borelis Laevipeneroplis Peneroplis Archaias Broeckina Cyclorbiculina Sorites Symbiont-bearing rotaliids Amphistegina Asterigerina Heterostegina Smaller miliolids Cornuspira Vertebralina Wiesnerella Hauerina Miliolinella Pyrgo Quinqueloculina Schlumbergerina Triloculina Spiroloculina Articulina Other, smaller perforate taxa Reussella Discogypsina Lobatula Discorbis Nonionoides Nonion Planorbulina Rosalina Opportunists Bolivina Cribroelphidium Elphidium Haynesina Ammonia Ammobaculites Trochammina Agglutinates Textularia Bigenerina

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35 Environmental-Data Analysis Environmental data (water temperature, dissolved oxygen, and salinity) collected in April 2002 were correlated with foramini feral assemblages using Pearson’s correlation analyses using Statistica (2000). The Southeast Environmental Research Center (SERC) Water Quality Monitoring Network collected data monthly over an 11 ye ar time period at site s throughout Biscayne Bay (http://serc.fiu.edu/wqmnetwork/, 2005). I computed the mean and standard error of water-quality parameters at each site for its entire sampling period. Contour plots were made for total organic carbon (T OC), salinity, and chlorophyll a (chl a ). These variables were chosen for their potential influen ce over the foraminiferal community. Total organic carbon is a potential indicator of food source for smaller, heterotrophic foraminifers (Crevison, 2001). Seve ral taxa, including agglutinates, Ammonia, and Elphidium (Sen Gupta, 1999) are euryhaline. La ws and Redalje (1979) found chlorophyll a to be the most sensitive indicator of se wage enrichment in a subtropical estuary. Synthesis of Biotic and Environmental Data PRIMER's BIO-ENV procedure was conducte d to examine the extent to which the physio-chemical data are related to the observed foraminiferal assemblages (Clark and Warwick, 2001). The approach was to first analyze the biotic data and then ask how well the information on environmental variables, in combination, matched the community structure (Fig. 5). This procedure was al so used to determine which subset of foraminiferal genera best described the total assemblage.

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36 Figure 5 Schematic diagram of the BIO-ENV pr ocedure: selection of the abiotic variable subset maximizing Spearman-rank correlation ( ) between biotic and abiotic similarity matrices (from Clark and Warwick, 2001) A Pearson’s correlation matrix of key ta xa, metals of concern, % mud, FI, and diversity coefficients was constructed using Statistica (2000) to refine relationships for use in interpretations.

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37 3. RESULTS Grain Size Weight-percent distribution of each gr ain size for each sample is shown in Appendix IV. Table 3 and Figure 6(a) summar ize the distribution of median sedimentgrain size throughout the bay. The median grai n size for the majority of sites was fine (37%) and medium (28%) sand, while 16% we re more than half mud. Percent mud distribution throughout the bay is contoured in Figure 6(b). Table 3 Summary of median grain size in 139 sediment samples from Biscayne Bay [see Figure 6(a)] Description of Grain Size Size range of sieve # of Sites with Median Grain Size Gravel or Granule X > 2 mm -1 2 Very Coarse Sand 1 mm < X 2 mm 0 4 Coarse Sand 0.5 mm < X 1 mm 1 15 Medium Sand 0.25 mm < X 0.5 mm 2 39 Fine Sand 0.125 mm < X 0.25 mm 3 52 Very Fine Sand 0.063 mm < X 0.125 mm 4 6 Silt and clay, i.e., mud X 0.063 mm >4 23

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38 (a) Median Phi (b) % Mud Figure 6 Grain-size distribution in Bisca yne Bay as (a) median phi and (b) % mud

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39 Trace-Metal Distribution Cluster analyses were carried out for 24 elements for all three sample sets individually (not shown) a nd combined (Fig. 7). Distri bution of Sr was sufficiently dissimilar as to mask other results and wa s subsequently removed from the cluster analyses. Several consistencies were noted on all four analyses. Ag was never closely linked with any other metal of concern; how ever, it closely linked with many essential nutrients. Ni, Cr, and Sn always clustered toge ther at a Euclidean distance <12, as did Cu and Hg. Zn ranged from being an outlier to closely linked to Hg and Cu. Overall, seven of the eight metals of concern occurred together in one distin ct cluster that also included Mn, Ba, Ca, Bi, and V. The second cluster in cluded Ag, elements characteristic of clay minerals (Al, Na, K), wetland soils (F e) and several rare-earth elements. A Pearson correlation matrix (Appendix VII) was constructed for 25 elements using Statistica (2000). Table 4 presents Pearson's correlation coefficients for the eight metals of concern. Strongest positive corr elations (>0.7) are shown by the heavy-metal pairs of Zn-Hg, Cu-Pb, Cu-Hg, Cu-Zn and Sn-A g. Most of the other heavy-metal pairs also show significant, positive correlations. Table 4 Correlation matrix of metals of concern (N=147, marked correlations are significant at p<0.05) Variable Ag CuNiPbZn Cr Sn Ag -Cu .49* -Ni .40* .57* -Pb .11 .72* .47* -Zn .60* .78* .67* .56* -Cr .39* .57* .61* .62* .55* -Sn .80* .48* .50* .03 .60* .34* -Hg .55* .71* .56* .66* .76* .66* .46*

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40 Ag, Cu, Pb, Zn, Cr, Hg, Sn, and Ni were contoured to show their distribution in mud-sized sediments throughout the bay (Fig. 8). All eight metals of concern show highest concentrations to th e northwest, between the mouths of the Miami River and Snapper Creek Canal (Fig. 1). Relatively high concentrations of these metals, with the exception of Sn and Hg, also occur just south of Turkey Point. Concentrations in the vicinity of the Black Point landfill are not as hi gh as in the northwest, but are elevated as relative to sites offshore. Silver and tin show elevated concentrations in the south-central portion of the bay.

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41 Zn Cu Hg Sn Pb Ni Cr V Bi Mn Ba Ca Na Mg Al K P Co S Ag Fe Zr Mo Y 302520151050 Euclidean Distance * * * * Figure 7 Cluster analysis (R-mode ) of geochemical data in sedime nt samples from Biscayne Bay (*metal of concern)

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42 -80.4-80.2 25.4 25.6 25.8 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 Ag (ppm) -80.4-80.2 25.4 25.6 25.8 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 Cu (ppm) -80.4-80.2 25.4 25.6 25.8 -5 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 Pb (ppm) -80.4-80.2 25.4 25.6 25.8 -20 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 Zn (ppm ) (a) Silver (d) Lead (c) Copper (b) Zinc Figure 8 Metal distributions for mu d-sized sediments in Biscayne Bay (Continued on the next page)

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43 (e) Chromium (h) Tin (g) Nickel (f) Mercury 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 Cr (ppm) 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 Hg (ppb) 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Ni (ppm) 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 Sn (ppm ) Figure 8 (Continued)

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44 Foraminiferal Assemblages Sixty-three genera of foraminifers were identified at 137 sites in Biscayne Bay. Raw counts, indices of diversity (number of genera, Fisher index, and Shannon index), FORAM Index, and density (forams per gram) for all samples included in analyses are presented in Appendix VI. Figure 9 shows no direct relationshi p between diversity (number of genera) and density (log of forami nifers per gram) of tests in the samples. Figure 9 Plot of density versus diversity of samples Sample Distribution A cluster analysis was performed on foraminiferal assemblage data for 137 sample sites throughout the bay. Samples grouped into three major groups (A, B, and C) at >53% similarity. Group B consisted of three subgroups that were >60% similar. Sample III-1 fused to groups B at 57% and will be considered an outlier (O). Figure 10 is a MDS plot of the sample simila rity matrix for all 137 sample sites. Each sample is represented according to its si te group derived from the cluster analysis. Because conclusions match with the cluster analys is and the sample size is large, this plot is considered a useful 2-dimens ional picture (stress value=0.16). 0 5 10 15 20 25 30 35 40012345Density (log forams per gram)Number of Genera

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45 C A B-3 B-2 B-1 O Stress: 0.16 Figure 10 MDS ordination of sample sites according to SIMPER groups SIMPER analysis was performed on groups A, B-1, B-2, B-3, and C. The cluster analysis, MDS plot (Fig. 10), and the SIMPER output (Table 5) consistently show that groups B-3 and C are most dissimilar (59%). Subgroups B-1, B-2, and B-3 exhibited <37% dissimilarity. SIMPER output of dissi milarity between groups is summarized in Appendix VIII. Figure 11 shows sample locations throughout the bay, indicating SIMPER groups. Group A consists of 20 samples predominan tly from the southwestern margin of Biscayne Bay (Figure 11). This group is ch aracterized by the highest abundance, lowest diversity, and coarsest sediments of any group (Table 6). Seven genera contribute to almost 92% of the within-sam ple variability (Table 5). Miliolids make up 60% of the assemblage, and stress-tolerant taxa, Ammonia Cribroelphidium and Haynesina, make up 32%. The B group of samples is characteri zed by higher diversity, dominance by smaller miliolids, and minimal contribution by stress-tolerant taxa.

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46 The 27 samples that make up subgroup B-1 co me from the north-central part of the bay (Fig. 11). Fifteen genera make up 92% of this relatively diverse assemblage; five smaller miliolid genera make up nearly half. Six stress-tolerant genera make up another quarter of the assemblage. Four other small ro taliid genera contribu te 18% to the group. Abundance of foraminiferal tests (mean X=1390 te sts/gm) is the lowest in this subgroup (Table 6). Twenty open-bay samples comprise subgroup B-2 (Fig. 11), with the highest diversity of any group or subgroup (Tables 5, 6) Again, smaller miliolid genera make up nearly half the assemblage, and other smalle r rotaliids compose 20% (Table 5). Stresstolerant taxa make up only 11% Four categories of symbi ont-bearing taxa are recorded and account for 10% of the assemblage. Even two agglutinate genera show up in this assemblage subgroup. Subgroup B-3 is the largest subgroup of samples, colle cted from 44 sites that dominate the southern, open bay (Fig. 11). Smaller miliolids dominate (63%), with other smaller rotaliids composing 16% of the a ssemblage and symbiont-bearing taxa 7% (Table 5). Only one stress-tolerant genus, Nonion was identified at 2.6%. Abundance was the highest and diversity lowest of the “B” subgroups (Table 6). Group C sites are mostly located in the northern portion of the bay (Fig. 11), closest to urban Miami influence. One sample, III-72, was collected nearest the Black Point Landfill. Group C is dominated by stre ss-tolerant taxa (61%) and the ubiquitous miliolids, Quinqueloculina and Triloculina (Table 5). Ammonia is the largest contributor (16.6 %). Other stress-tolerant genera include Cribroelphidium, Nonion, Haynesina,

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47 Brizalina, Elphidium and Bolivina Despite the predominance of finer sediments, the mean abundance of foraminiferal tests was relatively low (Table 6). 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000 21000 22000 23000 24000 25000 26000 A B-1 B-2 B-3 C Figure 11 Chart of distribution of foraminife ral density in Biscayne Bay with sample sites represented by SIMPER groups

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48 Table 5 SIMPER groups, indicatin g within-sample group similarity (*FORAM Index categories, SB=algal symbiont-bearing, SM=smaller miliolid, SR=smaller rotaliid, ST=stress-tolerant, AG= agglutinated, as per Hallock et al., 2003) Group A Average similarity: 71.36 Genus F.I.* Av.AbundAv.Sim Sim/SD Contrib% Cum.% Quinqueloculina SM 37.81 20.21 8.21 28.32 28.32 Ammonia ST 17.71 12.79 3.83 17.92 46.24 Triloculina SM 19.95 11.77 2.59 16.5 62.74 Affinetrina SM 6.08 6.99 2.38 9.80 72.54 Cribroelphidium ST 6.21 6.70 2.29 9.39 81.92 Miliolinella SM 3.78 4.23 1.74 5.93 87.86 Haynesina ST 1.92 2.8 1.31 3.93 91.79 Group B-1 Average similarity: 69.25 Genus F.I.* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina SM 34.00 14.14 7.42 20.42 20.42 Triloculina SM 10.76 7.00 2.87 10.12 30.53 Valvulineria SR 5.45 4.98 2.94 7.20 37.73 Affinetrina SM 4.76 4.42 3.14 6.38 44.11 Nonion ST 4.68 4.29 3.88 6.20 50.31 Cribroelphidium ST 4.60 3.99 2.94 5.76 56.07 Miliolinella SM 4.81 3.75 1.99 5.41 61.48 Articulina SM 3.70 3.66 2.62 5.29 66.77 Ammonia ST 4.37 3.62 2.18 5.22 71.99 Neoeponides SR 3.55 3.18 1.81 4.60 76.59 Rosalina SR 2.48 2.94 2.04 4.25 80.83 Haynesina ST 3.15 2.63 1.29 3.80 84.63 Discorbis SR 1.62 1.68 1.02 2.43 87.06 Elphidium ST 1.94 1.67 1.07 2.41 89.48 Brizalina ST 1.27 1.42 1.01 2.05 91.53 (Continued on the next page)

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49 Table 5 (Continued) Group B-2 Average similarity: 67.80 Species F.I.* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina SM 35.75 13.00 5.18 19.17 19.17 Miliolinella SM 7.43 5.76 4.32 8.49 27.66 Triloculina SM 7.99 4.87 2.08 7.18 34.84 Neoeponides SR 5.96 4.77 3.82 7.04 41.89 Articulina SM 4.38 4.30 4.18 6.34 48.22 Valvulineria SR 4.96 4.12 3.35 6.08 54.30 Affinetrina SM 2.94 2.91 2.18 4.30 58.60 Rosalina SR 2.07 2.64 2.32 3.89 62.48 Elphidium ST 2.18 2.33 1.67 3.43 65.91 Juv symb-miliolida SB 2.10 2.24 1.63 3.31 69.22 Nonion ST 2.19 2.05 1.29 3.03 72.25 Archaias SB 2.49 1.94 1.34 2.85 75.10 Discorbis SR 1.19 1.74 1.47 2.54 77.67 Brizalina ST 1.48 1.70 1.19 2.51 80.18 Siphonaperta AG 1.49 1.47 1.08 2.17 82.35 Laevipeneroplis SB 1.70 1.39 0.90 2.04 84.40 Androsina SB 1.86 1.36 0.96 2.00 86.40 Haynesina ST 1.45 1.18 0.76 1.74 88.13 Clavulina AG 0.76 1.08 1.07 1.60 89.73 Valvulina AG 1.30 1.07 0.87 1.58 91.31 Group B-3 Average similarity: 70.85 Species F.I.* Av.Abund Av.Sim Sim/SD Contrib% Cum.% Quinqueloculina SM 32.89 15.27 6.24 21.55 21.55 Miliolinella SM 20.73 11.57 5.21 16.34 37.89 Affinetrina SM 8.86 7.44 3.42 10.51 48.39 Triloculina SM 8.08 6.28 3.04 8.86 57.25 Valvulineria SR 4.36 3.67 1.61 5.18 62.43 Rosalina SR 2.80 3.62 2.52 5.11 67.55 Juv symb-miliolida SB 2.50 2.65 1.30 3.74 71.29 Archaias SB 2.57 2.62 1.44 3.70 74.99 Articulina SM 2.25 2.51 1.25 3.54 78.53 Neoeponides SR 1.77 2.28 1.36 3.21 81.75 Nonion ST 1.27 1.83 1.19 2.59 84.34 Siphonaperta AG 1.29 1.70 1.18 2.39 86.73 Discorbis SR 1.65 1.66 0.91 2.34 89.07 Valvulina AG 1.85 1.62 0.94 2.28 91.35 (Continued on the next page)

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50 Table 5 (Continued) Group C Average similarity: 63.09 Genus F.I.* Av.AbundAv.Sim Sim/SD Contrib% Cum.% Ammonia ST 19.99 10.46 2.82 16.58 16.58 Quinqueloculina SM 20.57 9.72 2.44 15.40 31.98 Cribroelphidium ST 12.68 8.20 3.25 13.00 44.99 Nonion ST 11.60 7.26 2.10 11.51 56.49 Haynesina ST 7.17 4.91 1.58 7.78 64.27 Triloculina SM 5.70 3.90 1.37 6.18 70.46 Brizalina ST 3.64 3.68 1.81 5.84 76.30 Elphidium ST 2.21 2.55 1.36 4.04 80.34 Valvulineria SR 3.11 2.21 0.90 3.50 83.84 Discorbis SR 1.52 1.68 0.95 2.67 86.51 Bolivina ST 1.12 1.46 0.95 2.32 88.83 Rosalina SR 1.61 1.39 0.77 2.20 91.03 Table 6 Means and standard deviations of diversity, density, and grain-size data for SIMPER groups (*5 was substituted for median phi >4 to calculate mean) Group Forams/gm # Genera Fisher Shannon FORAM Index % Mud *Median mean (st. dev.) mean (st. dev.) mean (st. dev.) mean (st. dev.) mean (st. dev.) mean (st. dev.) mean (st. dev.) A 11585 (7411) 12.2 (2.9) 2.96 (0.95) 0.73 (0.09) 1.86 (0.25) 20 (14) 1.80 (1.54) B-1 1390 (1143) 22.5 (3.9) 7.28 (1.71) 1.03 (0.10) 2.04 (0.27) 20 (21) 3.07 (1.00) B-2 2722 (3355) 26.0 (4.2) 8.49 (1.41) 1.05 (0.11) 2.74 (0.73) 30 (19) 2.55 (1.64) B-3 3561 (3411) 18.4 (3.5) 5.16 (1.28) 0.91 (0.12) 2.64 (0.41) 19 (21) 2.50 (1.17) C 1721 (1704) 18.7 (5.4) 5.75 (2.09) 0.96 (0.14) 1.58 (0.23) 32 (27) 3.56 (1.08) Key Genera A preliminary cluster analys is was conducted using all ge nera present in greater than 5% of the samples (Appendix X). Appr oximately one-third of the genera had no greater than a 45% similarity to any other genera. After r eevaluation of the data set,

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51 foraminiferal taxa that never accounted for mo re than 5% of the total abundance of any sample were removed. The following anal yses include the remaining 23 key genera. Cluster analysis of 23 key genera for all sa mple sites formed three distinct clusters (Fig. 12). Groups 2-T and 3-T fuse at 38% si milarity before joining with Group 1-T at 27% similarity. One genus, Sorites, remained an outlier, with less than 10% similarity to any other foraminifer. Group 1-T is composed of Ammonia, Cribroelphidium, Nonion, Haynesina, Bolivina and Brizalina which are characteristic stress-tolerant taxa. Group 2-T included Elphidium, Discorbis, Quinqueloculina, Triloculina, Rosalina, Affinetrina, Milioline lla, Articulina, Neoeponides and Valvulineria All of the taxa are smaller, heterotrophic genera of the orders Rotaliida and Miliolida, though Elphidium is usually considered to be stress-tolerant. Group 3-T consisted of Archaias, Siphonaperta, Androsina, Valvulina, Laevipeneroplis, and the juvenile symbiont-bearing miliolids. Archaias, Androsina, Laevipeneroplis and the juveniles all har bor algal endosymbionts. Valvulina is a true agglutinated foraminifer, and Siphonaperta is an agglutinated miliolid. The Pearson correlation matrix (Table 7) between all key foraminiferal taxa shows significant positive and negative correla tions between taxa. Genera from clusters 2-T and 3-T tend to positively correlate to one an other and negatively correlate with members of group 1-T. Ammonia and Cribroelphidium show the strongest correlation at 0.77, while Ammonia and Miliolinella display the strongest, ne gative correlation (-0.70). There are no strong correla tions with percent mud.

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52 Sorites Laevipeneroplis Valvulina Androsina Juvenile Symb-Miliolida Siphonaperta Archaias Elphidium Discorbis Quinqueloculina Triloculina Rosalina Affinetrina Miliolinella Articulina Neoeponides Valvulineria Bolivina Brizalina Haynesina Nonion Ammonia Cribroelphidium 020406080100 Percent Similarity 1-T 2-T 3-T Figure 12 Cluster analysis of key fo raminiferal taxa in Biscayne Bay

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53 Table 7 Correlation matrix of foramini feral taxa and % mud (N=137, highlighted correlations significant at p<0.05) A ffin A rtic Miliol Quin Siph Trilo J Sym A ndr A ffinetrina 1.00 A rticulina 0.01 1.00 Miliolinella 0.65 0.13 1.00 Quinqueloculina 0.32 0.16 0.21 1.00 Siphonaperta 0.19 0.24 0.42 0.03 1.00 Triloculina 0.18 -0.04-0.14-0.04-0.031.00 Juv symb-mil 0.14 0.23 0.48 0.05 0.45 -0.161.00 A ndrosina 0.27 0.09 0.34 0.08 0.33 0.14 0.43 1.00 A rchaias 0.31 0.19 0.51 -0.01 0.66 0.03 0.54 0.60 Laevipeneroplis 0.10 0.24 0.24 0.01 0.34 -0.04 0.37 0.46 Sorites -0.09 0.16 0.02 -0.020.00 0.01 0.05 0.11 A mmonia -0.46 -0.46-0.70-0.38-0.45 0.02 -0.49 -0.38 Cribroelphidium -0.51 -0.31-0.61-0.49-0.34 -0.04 -0.38 -0.37 Elphidium -0.34 0.13 -0.25 -0.17-0.03-0.150.13 -0.16 Haynesina -0.53 -0.23-0.53-0.31-0.34 -0.04 -0.28 -0.41 Nonion -0.52 -0.08 -0.41-0.36-0.22-0.37-0.07 -0.40 Discorbis -0.08 0.05 0.10 -0.110.02 -0.110.15 -0.15 Neoeponides 0.14 0.40 0.20 0.22 0.38 -0.040.18 0.04 Rosalina 0.17 0.20 0.33 0.11 0.19 -0.28 0.26 0.08 Valvulineria 0.01 0.38 0.17 0.04 0.14 -0.130.12 -0.20 Bolivina -0.43 0.02 -0.50-0.17-0.27-0.20-0.35 -0.39 Brizalina -0.55 0.07 -0.51 -0.17 -0.26-0.25-0.29 -0.35 Valvulina 0.29 0.11 0.38 -0.06 0.38 0.13 0.21 0.53 % mud -0.27 0.05 -0.14-0.06-0.12 -0.19 -0.10 -0.31 A ffin A rtic Miliol Quin Siph Trilo J sym A ndr (Continued on the next page)

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54 Table 7 (Continued) A rch Laev Sorit A mm Crib Elph Hayn Non A ffinetrina A rticulina Miliolinella Quinqueloculina Siphonaperta Triloculina Juv symb-mil A ndrosina A rchaias 1.00 Laevipeneroplis 0.56 1.00 Sorites 0.16 0.34 1.00 A mmonia -0.58 -0.37 -0.141.00 Cribroelphidium -0.49 -0.27-0.190.77 1.00 Elphidium -0.11 0.22 0.26 0.08 0.18 1.00 Haynesina -0.37 -0.26 -0.02 0.44 0.51 0.12 1.00 Nonion -0.27 -0.16-0.06 0.37 0.40 0.35 0.37 1.00 Discorbis -0.03 -0.01-0.13-0.10-0.09 0.19 0.06 0.18 Neoeponides 0.27 0.29 0.16 -0.54-0.35 0.16 -0.20 -0.16 Rosalina 0.25 0.18 0.02 -0.47-0.33 0.07 -0.13 0.04 Valvulineria -0.02 0.00 0.05 -0.42-0.27 0.15 -0.01 0.11 Bolivina -0.34 -0.160.00 0.26 0.33 0.17 0.45 0.40 Brizalina -0.35 -0.10 0.17 0.20 0.37 0.30 0.54 0.48 Valvulina 0.45 0.23 0.04 -0.38-0.33 -0.14 -0.29 -0.36 % mud -0.22 -0.130.10 0.08 0.05 0.12 0.19 0.23 A rch Laev Sorit A mm Crib Elph Hayn Non (Continued on the next page)

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55 Table 7 (Continued) Disc Neo Ros Valv1 Boliv Briz Valv2 A ffinetrina A rticulina Miliolinella Quinqueloculina Siphonaperta Triloculina Juv symb-mil A ndrosina A rchaias Laevipeneroplis Sorites A mmonia Cribroelphidium Elphidium Haynesina Nonion Discorbis 1.00 Neoeponides 0.09 1.00 Rosalina 0.17 0.28 1.00 Valvulineria 0.29 0.53 0.32 1.00 Bolivina 0.12 0.01 0.05 0.09 1.00 Brizalina 0.01 -0.040.06 0.09 0.66 1.00 Valvulina -0.07 0.21 0.03 0.15 -0.25-0.25 1.00 % mud -0.12 0.07 -0.060.14 -0.010.17 -0.19 Disc Neo Ros Valv1 Boliv Briz Valv2

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56 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 A B-1 B-2 B-3 CFORAM Index FORAM Index values were computed fo r all sample sites and are reported in Appendix VI. Several modificat ions were made to functi onal groups defined by Hallock et al. (2003). In the FORAM Index calc ulation, stress-tolera nt genera included Ammonia, Cribroelphidium, Haynesina, Elphidium, Nonion, Nonionella, and Nonionoides All other taxa that do not harbor algal symbiont s were placed into the category of other, heterotrophic taxa. The northern and southwestern bay show the lowest FORAM Index values (Fig. 13). Values in open bay range from low-mid range to the highest, with only one sample 4. Figure 13 Distribution of FORAM Index valu es throughout Biscayne Bay (with sample sites represented according to SIMPER groups)

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57 Environmental Data During the third sample collection, in April 2002, seawater temperature, dissolved-oxygen levels, and salinity we re measured (Appendix II). Temperature variability was low, with less than a 3C range thr oughout the bay. Salinity and dissolved-oxygen concentration ha d greater site-to-site variab ility. A Pearson correlation matrix was constructed for measured environmental parameters versus key foraminiferal taxa and indices of density and diversity using Statistica (2000) Table 8 presents resulting Pearson's correlation coefficients. Perhaps most notably, Ammonia and Cribroelphidium negatively correlated with both salinity and dissolved oxygen. Stresstolerant Haynesina and Nonion also negatively correlated with dissolved-oxygen concentrations. Articulina Miliolinella and Quinqueloculina positively correlated to dissolved oxygen. Articulina Miliolinella, Neoeponides and several others positively correlated with salinity. Temp erature shows a weak, negative correlation with diversity, while salinity shows a stronger, positive co rrelation with divers ity. None of the environmental parameters show a si gnificant relationship to density. SERC data-collection sites (http://serc.fiu.edu/wqmnetwo rk/, 2005) are illustrated in Figure 14 (a); several SE RC collection sites occur farthe r north and south in the bay than our area of study and therefore were not considered; however, the data are represented in Appendix IX. Contour plot s [Fig. 14 (b,c,d)] were made for mean chlorophyll a (chl a ), total organic carbon (TOC), and sa linity. Site groups derived from SIMPER analysis (Table 5) are represen ted on the charts (Fig. 14). Chlorophyll a is highest in the northern portion of the bay, between Miami and Key Biscayne. The open bay shows the lowest concentration of chl a Salinity is lowest along the coast near Black

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58 Creek Canal. Nearshore areas to the north and south of Blackpoint exhibit salinities closer to normal marine condi tions. The picture of total organic carbon in the bay is nearly a perfect inverse image of salinity, showing a maximum off of Black Creek Canal and decreasing in the north, south, and offshore directions.

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59 Table 8 Correlation matrix of measur ed environmental variables versus key foraminiferal taxa and measures of density and diversity for samples collected in April 2002 (N=66, highlighted correlation s are significant at p<0.05) TemperatureDissolvedSalinity Oxygen A ffinetrina 0.12 0.21 0.04 A rticulina 0.02 0.30 0.39 Miliolinella 0.16 0.28 0.24 Quinqueloculina 0.14 0.41 0.12 Siphonaperta -0.22 -0.01 0.17 Triloculina 0.05 0.24 -0.08 Juv symb-mil -0.29 -0.07 0.45 A ndrosina 0.17 0.19 0.24 A rchaias -0.11 0.03 0.34 Laevipeneroplis -0.09 0.14 0.32 Sorites 0.13 0.19 0.12 A mmonia -0.07 -0.37 -0.52 Cribroelphidium -0.22 -0.36 -0.26 Elphidium -0.38 -0.07 0.29 Haynesina -0.23 -0.35 -0.02 Nonion -0.28 -0.38 0.12 Discorbis -0.04 0.09 0.19 Neoeponides -0.14 0.30 0.40 Rosalina 0.08 0.12 0.30 Valvulineria -0.17 0.19 0.43 Bolivina -0.07 -0.05 0.13 Brizalina -0.10 0.11 0.25 Valvulina 0.01 0.23 0.10 forams/gram 0.00 0.19 -0.17 # genera -0.34 0.11 0.59 Fisher index -0.35 0.08 0.59 Shannon index -0.44 0.07 0.68

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60 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 122 123 124 125 126 127 128 129 130 131 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9chl a A B-1 B-2 B-3 C 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 27 27.5 28 28.5 29 29.5 30 30.5 31 31.5 32 32.5 33 33.5 34 34.5 35 35.5 36 36.5Salinity A B-1 B-2 B-3 C 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5 5.2 A B-1 B-2 B-3 C TOC(a) SERC collection sites (b) chl a (c) TOC (d) Salinity Figure 14 Contours of environmental data obtained from Southeast Environmental Research Center. (a) SERC collection sites, (b) chl a, (c) TOC, and (d) salinity (with sample sites represented according to SIMPER groups)

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61 Multivariate Analyses A Pearson correlation matrix was construc ted for geochemical parameters versus key foraminiferal taxa and indices of density and diversity using Stat istica (2000). Table 9 presents resulting Pearson' s correlation coefficients. Median grain size showed stronger correla tions to foraminiferal genera than did percent mud. Affinetrina, Siphonaperta, Triloculina, Androsina, Archaias and Valvulina each showed a negative correlation to median phi. On the contrary, Ammonia, Cribroelphidium, Haynesina, Nonion, Bolivina and Brizalina correlated positively with median phi. Bolivina, Brizalina Ammonia, Cribroelphidium and Haynesina each show positive (>0.27) correlations with all eight metals of concern. Conversely, juvenile symbiont-bearing miliolids and Miliolinella maintain negative (<-0.35) correlations with the metals of concern. Two other symbiont-bearing foraminifers, Androsina and Archaias also show negative correla tions with all eight metals of concern; however, the relationships are somewhat w eaker (<-0.18). Of all meta ls of concern, Hg has the strongest correlations, both positive (0.66) a nd negative (-0.65), with key foraminiferal taxa. All metals of concern are negatively correlated to the FORAM Index, with the strongest correlation (-0.56) for mercury. Ex cept for Zn, the metals show virtually no correlation to measures of diversity.

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62 Table 9 Correlation matrix of geochemical parameters and key foraminiferal taxa (N=137, highlighted correlati ons are significant at p<0.05) (*metals of concern) (Continued on next page) Ag* Cu* Ni* Pb* Zn* Cr* Hg* Sn* Mn Mo Affinetrina -0.19 -0.30 -0.08 -0.30 -0.19 -0.19 -0.36 -0.21 0.27 -0.05 Articulina -0.28 -0.16 -0.20 -0.13 -0.34 -0.25 -0.27 -0.18 -0.31 -0.26 Miliolinella -0.37 -0.43 -0.36 -0.41 -0.51 -0.38 -0.65 -0.43 0.01 -0.14 Quinqueloculina -0.12 -0.23 -0.04 -0.20 -0.16 -0.12 -0.24 -0.15 0.08 -0.11 Siphonaperta -0.25 -0.22 -0.28 -0.15 -0.40 -0.21 -0.41 -0.27 -0.08 -0.16 Triloculina 0.06 -0.04 0.10 -0.10 0.18 -0.06 0.04 0.16 0.19 0.00 Juv Symb-Mil -0.38 -0.39 -0.47 -0.35 -0.57 -0.44 -0.56 -0.39 -0.46 -0.23 Androsina -0.25 -0.18 -0.28 -0.23 -0.24 -0.25 -0.34 -0.25 -0.11 -0.17 Archaias -0.37 -0.27 -0.32 -0.23 -0.43 -0.33 -0.51 -0.31 -0.24 -0.26 Laevipeneroplis -0.26 -0.19 -0.19 -0.15 -0.34 -0.35 -0.37 -0.22 -0.42 -0.20 Sorites -0.23 -0.09 -0.18 0.03 -0.16 -0.15 -0.14 -0.23 -0.24 -0.20 Ammonia 0.37 0.39 0.30 0.37 0.49 0.39 0.64 0.32 0.21 0.18 Cribroelphidium 0.41 0.42 0.28 0.36 0.42 0.39 0.66 0.37 0.13 0.25 Elphidium -0.02 0.02 -0.10 0.02 -0.12 -0.12 0.03 0.00 -0.42 -0.01 Haynesina 0.31 0.33 0.30 0.33 0.32 0.44 0.47 0.27 -0.01 0.21 Nonion 0.13 0.18 0.04 0.25 0.09 0.22 0.23 0.11 -0.29 0.14 Discorbis 0.14 0.04 -0.04 -0.02 -0.01 -0.04 -0.12 0.13 -0.10 0.13 Neoeponides -0.35 -0.22 -0.14 -0.03 -0.36 -0.25 -0.34 -0.34 -0.15 -0.30 Rosalina -0.11 -0.14 -0.13 -0.14 -0.27 -0.11 -0.27 -0.06 -0.03 -0.04 Valvulineria -0.32 -0.24 -0.13 -0.08 -0.32 -0.22 -0.30 -0.26 -0.18 -0.20 Bolivina 0.45 0.43 0.40 0.34 0.38 0.45 0.47 0.54 -0.02 0.37 Brizalina 0.35 0.42 0.26 0.35 0.32 0.35 0.41 0.38 -0.18 0.27 Valvulina -0.25 -0.16 -0.23 -0.15 -0.21 -0.23 -0.32 -0.28 0.06 -0.04 forams/gram 0.03 -0.15 0.03 -0.17 0.09 -0.09 0.00 0.06 0.26 0.06 # genera -0.16 -0.17 -0.11 -0.09 -0.35 -0.13 -0.25 -0.11 -0.43 -0.12 Fisher index -0.18 -0.14 -0.17 -0.06 -0.35 -0.15 -0.23 -0.13 -0.49 -0.17 Shannon index -0.10 -0.04 -0.14 0.05 -0.26 -0.08 -0.12 -0.08 -0.42 -0.08 FORAM index -0.36 -0.31 -0.33 -0.30 -0.42 -0.40 -0.56 -0.31 -0.28 -0.24

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63 Table 9 (continued) Bi Ca Co Fe K Mg Al Ba Na Sr P Affinetrina 0.00 0.06 0.08 -0.22 0.17 0.47 -0.06 -0.02 0.15 -0.07 -0.21 Articulina 0.08 0.04 -0.12 -0.31 -0.03 0.08 -0.31 0.00 0.04 0.14 -0.16 Miliolinella 0.23 0.20 0.07 -0.48 -0.03 0.41 -0.31 -0.13 -0.07 0.11 -0.45 Quinqueloculina 0.00 0.02 0.15 -0.20 0.14 0.31 -0.07 0.11 0.10 -0.04 -0.22 Siphonaperta 0.23 0.21 0.04 -0.26 -0.02 0.22 -0.22 -0.03 -0.02 0.24 -0.33 Triloculina -0.13 -0.04 0.02 -0.01 0.22 0.14 0.01 0.06 0.20 -0.09 -0.08 Juv Symb-Mil 0.24 0.07 -0.12 -0.54 -0.10 0.06 -0.47 -0.24 -0.09 0.15 -0.45 Androsina 0.19 0.11 -0.10 -0.31 0.01 0.14 -0.25 -0.05 0.01 0.09 -0.29 Archaias 0.29 0.16 -0.03 -0.42 0.06 0.23 -0.38 -0.07 0.07 0.22 -0.38 Laevipeneroplis 0.23 0.07 -0.11 -0.40 -0.10 -0.03 -0.38 -0.08 -0.10 0.19 -0.26 Sorites 0.22 0.06 -0.08 -0.20 -0.13 -0.10 -0.26 -0.01 -0.09 0.13 -0.14 Ammonia -0.29 -0.19 0.00 0.52 -0.04 -0.46 0.45 0.02 -0.07 -0.22 0.38 Cribroelphidium -0.33 -0.14 -0.09 0.49 -0.11 -0.50 0.38 -0.04 -0.12 -0.12 0.39 Elphidium 0.04 -0.15 -0.16 -0.07 -0.19 -0.34 -0.17 -0.25 -0.19 0.07 0.04 Haynesina 0.00 0.03 0.03 0.39 -0.06 -0.29 0.28 0.13 -0.04 0.10 0.27 Nonion -0.13 -0.16 -0.18 0.24 -0.17 -0.34 0.12 -0.12 -0.12 0.01 0.25 Discorbis 0.07 -0.01 0.14 0.02 -0.09 0.03 -0.03 -0.01 -0.05 0.02 0.05 Neoeponides 0.33 0.14 0.09 -0.37 0.02 0.15 -0.34 0.12 0.08 0.20 -0.22 Rosalina 0.15 0.09 -0.01 -0.16 -0.01 0.29 -0.16 -0.02 -0.01 0.15 -0.11 Valvulineria 0.21 0.02 0.03 -0.30 0.05 0.19 -0.32 0.04 0.11 0.07 -0.14 Bolivina -0.12 0.02 0.05 0.44 0.08 -0.03 0.33 0.24 0.18 0.16 0.56 Brizalina -0.06 -0.06 -0.04 0.34 -0.08 -0.19 0.17 0.09 0.01 0.11 0.46 Valvulina 0.17 0.09 -0.01 -0.24 0.10 0.23 -0.18 -0.09 0.12 0.03 -0.26 forams/gram -0.09 -0.02 0.18 -0.07 -0.04 -0.02 0.08 -0.07 -0.17 -0.15 -0.08 # genera 0.25 0.12 -0.07 -0.27 -0.14 0.02 -0.29 -0.02 -0.07 0.35 -0.14 Fisher index 0.25 0.07 -0.13 -0.28 -0.15 -0.07 -0.32 -0.05 -0.07 0.33 -0.13 Shannon index 0.20 0.03 -0.13 -0.17 -0.11 -0.08 -0.22 -0.09 -0.04 0.28 -0.10 FORAM index 0.28 0.14 -0.08 -0.48 0.05 0.27 -0.41 -0.07 0.06 0.19 -0.41

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64 Table 9 (continued) V Y Zr S f/g # gen Fish Shan % mud FI Med Affinetrina 0.07 0.06 0.14 -0.14 0.25 -0.09 -0.18 -0.16 -0.27 0.36 -0.46 Articulina -0.32 -0.37 -0.08 -0.23 -0.35 0.42 0.45 0.42 0.05 0.32 0.01 Miliolinella -0.22 -0.15 0.15 -0.48 0.09 0.10 0.01 0.00 -0.14 0.52 -0.47 Quinqueloculina -0.03 -0.06 0.09 -0.07 0.20 0.14 0.04 -0.20 -0.06 0.17 -0.11 Siphonaperta -0.12 -0.23 0.00 -0.31 -0.23 0.26 0.26 0.31 -0.12 0.58 -0.31 Triloculina 0.07 0.02 -0.06 0.12 0.22 -0.23 -0.21 -0.04 -0.19 0.08 -0.30 Juv Symb-Mil -0.41 -0.39 -0.01 -0.56 -0.17 0.31 0.32 0.30 -0.10 0.64 -0.07 Androsina -0.23 -0.21 0.05 -0.29 -0.05 0.01 0.04 0.10 -0.31 0.77 -0.44 Archaias -0.27 -0.35 0.01 -0.41 -0.26 0.23 0.27 0.31 -0.22 0.85 -0.41 Laevipeneroplis -0.45 -0.42 -0.05 -0.39 -0.26 0.39 0.43 0.41 -0.13 0.67 -0.23 Sorites -0.28 -0.27 0.03 -0.23 -0.14 0.35 0.42 0.27 0.10 0.24 -0.06 Ammonia 0.32 0.36 0.03 0.45 0.18 -0.42 -0.37 -0.30 0.08 -0.68 0.30 Cribroelphidium 0.22 0.27 -0.09 0.35 0.03 -0.23 -0.16 -0.06 0.05 -0.62 0.32 Elphidium -0.29 -0.24 -0.19 -0.22 -0.31 0.50 0.54 0.51 0.12 -0.06 0.19 Haynesina 0.23 0.30 -0.01 0.31 -0.08 0.07 0.11 0.20 0.19 -0.50 0.42 Nonion 0.07 0.08 -0.10 0.12 -0.27 0.20 0.25 0.29 0.23 -0.40 0.43 Discorbis -0.08 -0.04 -0.12 -0.08 -0.09 0.18 0.14 0.28 -0.12 -0.04 0.02 Neoeponides -0.23 -0.32 0.10 -0.29 -0.25 0.51 0.50 0.46 0.07 0.29 -0.14 Rosalina -0.10 -0.16 -0.13 -0.23 -0.18 0.36 0.32 0.32 -0.06 0.23 -0.05 Valvulineria -0.13 -0.23 0.08 -0.20 -0.20 0.40 0.39 0.46 0.14 0.01 0.06 Bolivina 0.21 0.19 -0.40 0.42 -0.25 0.26 0.27 0.26 -0.01 -0.38 0.35 Brizalina 0.05 0.06 -0.32 0.31 -0.27 0.34 0.36 0.35 0.17 -0.35 0.35 Valvulina -0.04 -0.10 0.10 -0.18 -0.11 0.05 0.03 0.21 -0.19 0.49 -0.52 forams/gram 0.01 0.13 0.09 -0.06 1.00 -0.34 -0.43 -0.46 0.01 -0.20 -0.04 # genera -0.35 -0.31 -0.17 -0.34 -0.34 1.00 0.95 0.77 0.11 0.28 0.15 Fisher index -0.37 -0.35 -0.16 -0.35 -0.43 0.95 1.00 0.83 0.09 0.31 0.12 Shannon index -0.26 -0.26 -0.18 -0.28 -0.46 0.77 0.83 1.00 -0.04 0.33 -0.05 FORAM index -0.35 -0.40 -0.02 -0.43 -0.20 0.28 0.31 0.33 -0.26 1.00 -0.42

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65 PRIMER's BIO-ENV procedure was conducte d on data from samples collected in April 2002 to examine the extent to which the measured environmental data were related to the observed foraminiferal assemblages. Initially, the procedure was run to determine the single environmental va riable (percent mud, temperat ure, dissolved oxygen, or salinity) that best described the distribution of the foraminiferal assemblages (Table 10). Then, multiple variables were analyzed to determine if an improved correlation existed. Salinity was the single environmental variab le with the highest correlation to the foraminiferal assemblages (0.34). The analysis of both percent mud and salinity slightly improved that correlation (0.40). Table 10 BIO-ENV results of measured e nvironmental parameters as correlated to foraminiferal assemblage for samples collected in April 2002 # Variables Correlation Determining Variables 1 0.338 Salinity 1 0.268 % Mud 1 0.239 Dissolved Oxygen 1 0.180 Temperature 2 0.401 Salinity, % Mud 2 0.343 Salinity, Temperature 3 0.397 Salinity, % Mud, Temperature 3 0.394 Salinity, % Mud, Dissolved Oxygen 4 0.395 % Mud, Temperature, Dissolved Oxygen, Salinity The BIO-ENV procedure was also used to compare foraminiferal assemblages and geochemical data for all three collections (Table 11). Hg is single geochemical parameter that best describes foraminiferal distributions throughout Biscayne Bay (0.38). The inclusion of multiple geochemical variables only slightly improved the correlation of Hg alone (i.e., Variables-H g, Mg, Sr, P, Correlation-0.45).

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66 Table 11 BIO-ENV results of measured geoche mical parameters as correlated to overall foraminiferal assemblage for all three collections # Variables Correlation Determining Variables 1 0.380 Hg 1 0.326 P 1 0.312 Fe 1 0.289 Zn 1 0.259 S 2 0.415 Hg, P 2 0.398 Hg, Sr 2 0.391 Hg, Fe 2 0.389 Hg, Sn 2 0.388 Hg, S 3 0.427 Hg, P, Sr 3 0.427 Hg, Mg, P 3 0.423 Hg, Sn, Hg 4 0.446 Hg, Mg, Sr, P 4 0.446 Hg, Mg, Sn, S 4 0.442 Hg, Fe, Mg, Sn 4 0.442 Hg, Mg, Sn, Sr A Bray-Curtis similarity matrix base d on the weighted components of the FORAM index was constructed. The BIO-E NV procedure was run to determine what geochemical variables best described the wei ghted assemblage (Table 12). Mercury had the strongest correlation (0.32) to the distribution of the we ighted components of the FORAM index in Biscayne Bay (Table 12). Table 12 BIO-ENV results of measured ge ochemical parameters as correlated to FORAM Index components # Variables Correlation Determining Variables 1 0.324 Hg 2 0.356 Hg, S 3 0.390 Hg, S, Mg 4 0.389 Hg, S, Mg, P The BIO-ENV procedure was run to isolat e the foraminiferal genera that best describe the total foraminiferal assemblage thus creating a BIO-BIO procedure (Table 13). Miliolinella was the genus whose presence and abundance best reflected the total

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67 foraminiferal assemblage (0.57). In contrast, Ammonia had one of the lowest correlations of any single biotic variab le (0.15). Nevertheless, Ammonia and Miliolinella were the two genera with the strongest correlation (0.72) to the total foraminiferal assemblage in Biscayne Bay. Table 13 BIO-BIO results of foraminiferal ge nera as correlated to overall assemblage # Variables Correlation Determining Variables 1 0.572 Miliolinella 1 0.153 Ammonia (19 genera ranked higher for 1 variable analysis) 2 0.716 Miliolinella, Ammonia 2 0.701 Quinqueloculina, Ammonia 3 0.782 Miliolinella, Ammonia, Quinqueloculina 3 0.771 Miliolinella, Ammonia, Valvulineria 4 0.821 Miliolinella, Ammonia, Affinetrina, Valvulineria 4 0.820 Miliolinella, Ammonia, Quinqueloculina, Nonion 5 0.853 Miliolinella, Ammonia, Affin etrina, Nonion, Valvulineria 5 0.847 Miliolinella, Ammonia, Quinqueloculina, Nonion, Valvulineria 6 0.870 Miliolinella, Ammonia, Quinque loculina, Affinetrina, Nonion, Valvulineria 7 0.884 Miliolinella, Ammonia, Qui nqueloculina, Archaias, Nonion, Valvulineria, Affinetrina The BIO-BIO procedure was also used to determine how well the FORAM index components match the entire foraminiferal as semblage. The combination of all three weighted components had a 0.686 Spearman-rank correlation to the entire foraminiferal distribution, while the distribu tion of stress-tolerant specie s alone had a correlation of 0.617.

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68 4. DISCUSSION Limitations of Data Samples analyzed in this study were co llected in December 2000, July 2001, and April 2002. The first collection targeted si tes in northern Biscayne Bay, including suspected areas of pollution in the upper part of the bay, alon g a transect off Black Point in southern Biscayne Bay, and several open-bay sites (Hoare, 2002). The second collection included mostly openbay sites with minimal terrestrial influence. The third collection included 68 sites baywide. Possible temporal va riations in heavy metals and/or foraminiferal assemblages cannot be di fferentiated from differences resulting from targeted sampling (i.e., suspected area s of pollution vs. open-bay sites). Environmental data (temperature, salin ity, and dissolved-oxygen concentrations) were collected only during the third collection. This restri cted the number of samples that could be examined using direct corre lation analyses. Although environmental data are available from the Southeast Research Ce nter (2005), sample site s are not identical. Use of SERC data are therefore limite d to comparison of contoured results. In the original design of this study, whic h preceded my participation, the decision was made to conduct geochemical analys es on mud fractions, as opposed to bulk samples, because, according to Siegel (2002), me tals tend to concentr ate in the clay-size sediment fraction more than in other size fr actions by adsorption onto charged surfaces of minerals and associated amorphous solids. To determine if the metals were indeed primarily concentrated in the mud fractions the sand fractions of six samples, two

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69 randomly chosen from areas subjectively labele d low, moderately, and highly toxic, were sent for geochemical analyses (Appendix Vb). Each sample contained varying amounts of 32 elements, in no direct relationshi p to concentrations carried in their mud fractions (Fig. 15). Due to the natural por osity of carbonate grains, significant amounts of mud can be trapped within the sand fraction of carbonate samples. Thus, heavy-metal concentrations for this study ca nnot be directly comp ared with results from studies that measured metals in bulk samples. Schropp and Windom (1988) normalized meta l concentrations to aluminum. They described this interpretive tool for Floridian estuaries to determine anthropogenic versus natural areas of increased heavy-me tal concentrations. Aluminum was chosen because it is the most abundant, naturally occu rring metal, it is hi ghly refractory, and its concentration is generally not influenced by anthropogenic sources. However, their work was based upon bulk-sediment samples. Thus geochemical data from the Biscayne Bay study cannot be appropriately analyzed and interpreted by normalizing metal concentrations to aluminum, since the ratio of metals to aluminum varies between mud and sand fractions (Appe ndix V-a,b and Fig.11).

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70 Copper0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% S-13S-29SS-25SS-31III-6III-14 Samples mud sand Lead0% 20% 40% 60% 80% 100% S-13S-29SS-25SS-31III-6III-14 Samples mud sand Zinc0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% S-13S-29SS-25SS-31III-6III-14 Samples mud sand Mercury0% 20% 40% 60% 80% 100% S-13S-29SS-25SS-31III-6III-14 Samples mud sand Fi g ure 15 Com p arison of concentrations of Cu Pb Zn and H g in the mud versus sand fractions of six sam p les

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71 Other anthropogenic contaminants shown to enter south Florida’s estuaries, including polynuclear aroma tic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), pesticides, herbicides, insecticides, and fungicides (Corcoran et al., 1984; Long and Morgan, 1990; Strom et al., 1992; Miles and Pf euffer, 1997; Scott et al., 2002), were not measured. Data for total organic carbon a nd nitrogen were available from the SERC dataset (2005). Similar to previous studies mentioned, sediment-quality assessment guidelines (SQAGs) developed for Florida coastal waters by MacDonald (1994) also were based on bulk-sediment samples and are t hus not directly comparable to my results. Preliminary SQAGs were derived and evaluated for 34 prio rity substances, including metals, PCBs, PAHs, pesticides, chlorinated organic substanc es (i.e., dioxins), a nd phthalate esters. They were not intended to be used as sediment -quality criteria but we re intended to assist sediment-quality assessment applications, such as identifying prior ity areas for non-pointsource management actions, designing wetla nd-restoration projects, and monitoring trends in environmental contamination. Long et al. (1995) established effects-ra nge limits (low and medium) for nine trace elements, total PCBs, two pesticides 13 PAHs, and three classes of PAHs, as informal screening tools in environmental asse ssment, to be utilized alongside toxicity tests or other measures of biological eff ects on benthic organisms. The analytical approaches reviewed and included in thei r (1995) report were ba sed on bulk-sediment geochemical analysis. Thus, the geochemical parameters reported here for Biscayne Bay cannot be directly compared to ER-L and ER-M concentrations.

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72 Heavy Metals: Comparisons with other Studies Long et al. (1999) measured sedimentological features and concentrations of trace metals, pesticides, other chlorinated com pounds and PAHs in 226 bulk sediment samples in Biscayne Bay. Sediment samples were te sted for toxicity according to (1) amphipod survival test, (2) sea-urchin fertility and (3 ) embryo-development tests, and (4) microbial bioluminescence tests (Fig 2). Lead contamination was highest in the lo wer Miami River, exceeding 400 ppm in some samples. Lead concentrations in Coral Gables Canal, Snapper Creek Canal, Military Canal, Black Creek Canal, and North Canal, were roughly one order of magnitude lower. Lead levels in the open ba sin south of Rickenbacker Causeway rarely exceeded 5 ppm. The chemical and toxicity data (Fig. 2), together, indicated that sediments from the open basin in the northern and central bay were the least impacted. Stations on the western margin of the central bay, on average, ranked highest in toxicity but among the lowest in chemical contamination. In the northwest margin of the bay, the opposite pattern was apparent; high chemical contamination, but lower toxicity. A section of southern Biscayne Bay showed re markably high toxicity that could not be explained with the chemical data, indicating that the results of toxicity tests were probably not driven by the chemi cals that were measured. Similar to results of Long et al. (1999), th e areas of highest concentrations (up to 77 ppm of Pb in mud fraction) of heavy meta ls in mud fractions in my study were found in the northwest bay, off Miami and in Black Creek Canal. Unlike results of Long et al. (1999), I detected elevated concentrations of several metals in mud fractions of sediment from the southwestern bay, off Turkey Point. The open bay offshore of Black Creek

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73 Canal showed intermediate metal concentrations, indicating potential dispersal of contaminants from Black Creek Canal. Possibl e reasons for this disparity in the open bay include subsurface movement of contaminants seagrass trapping of fine particles with bound metals, or grain-size characteristics of the area. Salinity data indicated the greatest freshwater influence and/or the least flushing offshore from Black Creek Canal. Total organic-carbon concentrations we re also highest in sediments from this locale, which is near the Black Point Landfill. Caccia et al. (2003) reported on the dist ribution and co-occurrence of selected trace metals, not including As, Ag, Sn, a nd Hg, in Florida Bay, the large estuary surrounded by the Everglades to the north a nd the Florida Keys to the south. Surface sediments were collected at 40 stations across Florida Bay in June, November and February 2000-2001. Nickel, Zn, Cu, Cr, and Pb showed similar distributions. Biscayne Bay also showed a similarity in the occurrence of these metals in addition to Sn and Hg (Fig. 7). Caccia et al. (2003) found most metals to have direct corr elations with organic carbon. Seagrasses can trap su spended particulate matter a nd fine sediments with high trace-metal and organic-carbon concentrations, causing thei r accumulation in seagrass beds (Caccia et al., 2003). This could explai n the anomalously high concentrations of Ag and Sn in south-central Bisca yne Bay, an area reported as a s eagrass community (Fig. 16). In my study, I could not determine whether heavy metals correlate with grain size, because geochemical measurements were not conducted on bulk samples.

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74 Although I found several areas with elevated concentrations of the entire suite of heavy metals no two metals of concern retained a strong, positive correlation coefficient throughout all three sample sets. Absolute metals concentrations in coastal sediments are influenced by sediment mineralogy, grain size, organic content, and anthropogenic enrichment (Schropp and Windom, 1988). The variety of natural and anthropogenic sources (Table 14) of the di fferent metals ensures differences in distribution throughout the bay. Figure 16 Bathymetry Profile of Biscayne Bay (USGS)

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75 Table 14 Uses and sources of metals of c oncern (adapted from Siegel, 2002, p. 40, with additions from Novot ny, 1995, and Eisler, 1996) As Cd Cr Cu HgNi Pb Sn Zn Ag Alloys x x x x x x x Batteries and Electro/Chem Cells x x x x x Biocides (Agriculture, Antifouling) x x x x Ceramics and Glass x x x Chemicals, Pharmaceuticals, Dental x x x x x x x x Coatings (Anti-Corrosives) x x x x x Photography x Electrical Equipment and Apparatus x x Fertilizers x x x x x x x x Fossil Fuel Combustion, Electricity x x x x x Mining, Smelting, Metallur gy x x x x x x x x x Nuclear Reactor (Mod, Absorber) x Paints and Pigments x x x x x x x Petroleum Refining x x x x x x Pipes, Sheets, Machinery x x Plastics x x x Pulp and Paper x x x x x Rubber x Semi-conductors, Super-conduc tors x x Tanning and Textiles x x x Wood Preservation Treatment x x x x Metal corrosion, urban runoff x x x Roofs, runoff from x x x x x x

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76 Foraminiferal Distributions throughout Biscayne Bay To determine if identifiable assemblages of foraminifers were characteristic of regions of Biscayne Bay, I used Q-mode clus ter analysis, then anal yzed resulting groups using the SIMPER procedure (e.g., Clarke and Warrick, 2001). These analyses distinguished three groups of s ites, which I labeled A, B, and C (Table 5). Within the B group, three subgroups were fu rther distinguished. Sites characterized by the Group A assemblage had mean foraminiferal abundances that were more than three times higher th an any other group (Table 6, Fig. 11), while taxonomic diversity at these sites was relatively low. This group primarily occurred at sites between Black Creek Canal and Turkey Point, where salinity was lowest and TOC was highest (Fig. 14). Thus, salinity likely reduced diversity, while abundant food was available to s upport high densities of species that tolerated the salinity stress. Together Ammonia and Quinqueloculina made up 46% of the assemblage, resulting in a mean FORAM Index of 1.86 (Table 6), reflecting those stresses. Group B sites were dominated by smaller miliolid foraminifers (Table 6). The sites characterized by subgroup B1 were distributed throughout the north-central part of the bay (Fig. 11). Subgroup B-1 exhibited th e lowest average de nsity (Fig. 11), less contribution from symbiont-bearing foramini fers than subgroups B-2 and B-3, and the greatest similarity to group C. Subgroup B-2 assemblages occurred at sites farthest from anthropogenic influence, showed the greatest diversity, and had the highest contribution from symbiont-bearing miliolids. Subgroup B-3 a ssemblages, with intermediate values of diversity and density, dominated sites in th e southern, open bay. Characteristics of

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77 Subgroup B-3 share similarities with those of assemblages in Group A. Mean FORAM Indices were 2.04, 2.74, and 2.64 for B-1, B-2, and B3 respectively (Table 6). Sites with FORAM Indices >3 all occurred in subgroups B-2 and B-3, had a medi an grain size of 2 phi, contained less than 20% m ud (Table 15), and some samp les likely were collected from hardbottom communities (Figs. 11 and 16). Table 15 Summary data for sa mples with FORAM indices >3.0 SS17 SS22 SS43 SS44 III6 III14 III16 III17 III22 III26 III36 SIMPER Group B-3 B-3 B-3 B-3 B-3 B-2 B-2 B-2 B-3 B-2 B-3 Forams/Gram 1281 1539 308 1652 300 495 634 579 1487 289 814 Number of Genera 21 15 14 22 16 28 22 26 20 24 18 Fisher index 6.85 4.11 3.98 6.62 4.81 10.57 7.22 8.86 6.41 8.37 5.37 Shannon Index 1.04 0.99 0.79 1.03 1.01 1.18 1.12 1.13 1.09 1.17 0.99 % Mud 10.33 3.04 0.71 7.62 7.60 19.59 16.31 14.09 11.18 7.81 5.42 Median Grain Size 2.00 1.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 FORAM Index 3.38 3.05 3.83 3.77 3.46 3.99 3.38 3.12 3.65 5.06 3.25 Group C sites, which occurred mostly in th e northern portion of the bay closest to urban Miami influence, were dominated by Ammonia and other stress-tolerant taxa. This dominance is reflected in the mean FORA M Index, 1.58, the lowest of any group. This group exhibited the lowest density, despite it s occurrence primarily in fine sands and mud. Although Long et al. (1999) found sediment s from this area of the bay to exhibit relatively low toxicity, the st ressors apparently are chronic, as indicated by the low densities of foraminifers, dominance by stre ss-tolerant taxa, and the low abundances of ubiquitous miliolids. This enigma tic combination may indicate that in-situ production of tests by stress-tolerant taxa is suppresse d by unfavorable conditions, and that mixing processes (e.g., waves, currents, boat traffic) transport small numbers of diverse smaller

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78 taxa into the area, thereby anomalously el evating diversity, while possibly somewhat diluting toxicity. Three factors appear to st rongly influence distributions of foraminifers throughout Biscayne Bay. Freshwater had the stronge st influence on group A along the southwest margin. Freshwater influence is represen ted by decreased salin ity and increased TOC (Fig. 14). The influences of urban polluti on marked group C in the northern sector. Finally, oceanic influence characterized subgrou p B-2, found in the east,-central sector. Subgroup B-3, found in the southern sector of the bay, was the least impacted by any one influence and was a relatively characteri stic subtropical estuarine foraminiferal assemblage. When these interpretations were placed on the MDS plot (Fig. 17), subgroup B-1 was evident not only as inte rmediate between urban and oceanic influences, but also as an intermediate between impacted (group C) and relatively unimpacted (subgroup B-3) subtropical estuarine foraminifers. C A B-3 B-2 B-1 O Stress: 0.16Oceanic Freshwater Urban Estuarine: Relatively-Unimpacted Figure 17 MDS plot of sample sites re presented by SIMPER groups showing urban, ocean, freshwater, and estuarine influences

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79 Alve (1995) described fora miniferal stress response to organic pollution. As pollution increases, populations of tolerant sp ecies increase at the expense of more sensitive taxa, so opportunistic species bloom and dominate (e.g., characteristic of my Group A sites). However, in a study of a fjord in western Norway, Alve (1991) found that increased heavy-metal pollution corres ponded with an impoverished foraminiferal abundance (more analogous to my Group C sites). Contour plots were constructe d of the distributions of Ammonia and Miliolinella to elucidate the distribution of these two key taxa in Bis cayne Bay (Fig. 18). Whereas Ammonia was nearly absent th roughout the open bay [Fig. 18(a)], the genus was predominant in the northern portion of the bay, between the mainland and Key Biscayne, and nearshore in the southern bay close to canal sites. Miliolinella was rare in the northern bay, increased in abundance in the central bay, and reached maximum abundance in the southern bay, offshore. In my study, individu als identified as Miliolinella included a high proportion of juveniles. The presence of abundant Miliolinella can indicate abundant food sources and reproductive blooms, while lower abundances can possibly refl ect introduction by physical processes. This group alone best de scribed the entire foraminiferal assemblage (0.572), and in combination with Ammonia that correlation is increased (0.716) (Table 18).

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80 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 -0.5 4.5 9.5 14.5 19.5 24.5 29.5 34.5 39.5 44.5 49.5 54.5 A B-1 B-2 B-3 C(a) Ammonia (b) Miliolinella 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 A B-1 B-2 B-3 C Figure 18 Distribution of relative abundance of (a) Ammonia and (b) Miliolinella with sample sites represented by SIMPER groups (white areas indicated insufficient information to contour)

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81 Figure 19 illustrates the relative abunda nce of stress-tolerant taxa including Ammonia, Cribroelphidium, Elphidium, Haynesina, and Nonion The distribution is consistent with that of Ammonia alone [Fig. 18(a)]. Howeve r, the areas of dominance expand. The stress-tolerant assemblage in the northern bay extends farther south than the Ammonia alone. Likewise, the assemblage along the southern margin of the bay extends farther seaward. Figure 19 Distribution of the relative abundance of Ammonia, Cribroelphidium, Haynesina, Elphidium, and Nonion (with sample sites represented by SIMPER groups) 25.4 25.6 25.8 -80.4-80.3-80.2-80.1 -0.5 9.5 19.5 29.5 39.5 49.5 59.5 69.5 79.5 89.5 99.5 A B-1 B-2 B-3 C

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82 Foraminiferal Assemblages: Comp arisons with Previous Studies Bush (1958) identified Ammonia (which he called Streblus ) in his 1948 collection as the twelfth most common foraminifer in the bay, characteristic of areas directly affected by dilution by fresh water and weak currents. Ammonia was present in nearly all, and predominant (>10%) in 5 out of 16, of Bush’s (1958) northern bay sites and at its maximum, 52.5%, south of Black Creek Canal. Bush described a nearshore biotope affected by surface-water runoff from nearby la nd and drainage canals characterized by the presence of Ammonia He identified Ammonia in the northern bay as well as in several open-bay sites. A ndersen (1975) reported that Ammonia dominated the western margin of the bay. Ishman et al. (1997) identified three dis tinct assemblages in Biscayne Bay: an Ammonia-Elphidium assemblage, an Archaias -miliolid assemblage, and a bolivinid assemblage. The Ammonia-Elphidium assemblage was predominant in restricted environments (salinities <35) in northern Biscayne Bay, Barnes Sound, and in adjacent freshwater-discharge points. The Archaias -miliolid assemblage was predominant at sites situated in unrestricted, open-marine central and southern Biscayne Bay. The bolivinid assemblage occurred in the northernmost Bi scayne Bay, associated with diatomaceous muds that are rich in organic matter, indi cating high productivity (I shman et al., 1997). Samples were not collected from the north ernmost sector of the bay for my study. Bolivinids tend to be tolerant of hypoxia and can dominate where organic carbon is abundant (Ishman et al., 1997) Almasi (1978) reported on th e ecology and color variation of benthic foraminifers in Barnes Sound, northeast Florida Bay. Th at historical study cannot recreate the

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83 foraminiferal distribution throughout Biscayne Bay due to its limited coverage. However, I performed a cluster analyses (F ig. 20) of foraminiferal genera based on a Bray-Curtis similarity matrix of Almasi’s ro w-standardized generic data. Foraminifers described as Elphidium galvestonense were included as Cribroelphidium for consistency with my taxonomy. In Almasi’s (1978) study, several taxa were present in low abundances (always <5%) in many of the samples. Ammonia, Cribroelphidium, Quinqueloculina, Triloculina, Valvulina, and Archaias dominated the samples and formed two clusters (Fig. 20). Group 1-A is composed of Ammonia and Cribroelphidium linking at 71% similarity, with Miliolinella fusing with the two at 55% similarity. In group 2-A Quinqueloculina and Triloculina fuse first at 71% similarity, followed by Valvulina (67%) and Archaias (59%). The major difference of th is cluster with my results from Biscayne Bay (Fig. 13) is the linkage of Miliolinella with the stress-tolerant genera. However, Miliolinella links to group 1-A just befo re groups 1-A and 2-A fuse. 1-A 2-A Figure 20 Cluster analysis of foraminifera l genera using data from Almasi (1978)

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84 I utilized R-mode cluster analyses (Parker and Arnold, 1999) to determine which foraminiferal genera tended to occur together, running the analysis on data from each collection separately, and data from all samp les combined. These analyses also enable comparison with functional groups defined by Hallock et al. (2003) for use in the FORAM Index. The assemblages of key fo raminiferal taxa in my study show a reasonably consistent picture among collecti on dates. However, several taxa did fluctuate in their associations. In the overall analysis, Elphidium clustered with the smaller, heterotrophic taxa. However, in separate analysis of the first samples collected, Elphidium clustered with the stress-tolerant genera. Th is is not surprising, since Elphidium has been shown to withstand low-oxygen levels (Bernhard and Sen Gupta, 1999), marine pollution (Yanko et al., 1999), and other stress. Elphidium as well as Haynesina, Nonion, Nonionella, Bulimina Fursenkoina and Reophax have been shown to sequester chloroplasts (Bernhard and Bowser, 1999). It is unknown whether th e host benefits from photosynthetic activity of the se questered chloroplasts or from an as yet unidentified biochemical pathway associated with the chloroplasts (Bernhard and Bowser, 1999). Regardless, this relationship apparently gives Elphidium and other taxa an ecological advantage in low-oxygen and other stressed environments. Sorites was present in only 12% of the total samples and never accounted for more than 5% of the population in any sample. Sorites an endosymbiont-bearing miliolid, was absent from all samples collect ed in December 2000 and was an outlier in samples from the other collections. Fujita and Hallock (1999) reported that Sorites

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85 appears to favor primary phytal substrates, particularity Thalassia blades, over epiphytized substrates, and predicted that Sorites populations would decline when nutrient pollution stimulated epiphytic grow th on seagrass. Bush (1958) observed Sorites to be representative of the northeast porti on of Biscayne Bay, an area influenced by the open ocean, and present in up to 10 % abundance. In my study, Sorites never accounted for more than 2% of any sample in northeas t Biscayne Bay. This disparity indicates a change in habitat for Sorites in the past 50 years in northeastern Biscayne Bay. Members of taxonomic group 3-T (Fig. 13) include two agglutinated taxa, three groups of closely related and physically si milar symbiont-bearing taxa, and juvenile symbiont-bearing foraminifers not identifiabl e to genus. Fluctuations among collections may represent a recent bloom (Buzas et al., 2002 ) or lack of comparable results for the more rare taxa. Archaias the most abundant symbiont-beari ng foraminifer that I identified, accounted for 16% of one sample and never more than 11% of the assemblage at any other site. In contrast, Bu sh (1958), reporting on sample s collected in 1948, showed Archaias to be abundant throughout ce ntral and southern (avera ge >18%) Biscayne Bay. Bush (1958) and I saw Archaias to be rare in the northern ba y. Present distributions of both Archaias and Sorites indicate substantial decline in water and sediment quality in the central and southern bay over the past half century. Archaias tolerates eurytopic conditions (Fujita and Hallock, 1999), excep t with respect to hypoxia (Hallock and Peebles, 1993). Symbiont-bearing miliolids sh ow a positive correlation to salinity that cannot be distinguished from a possible nega tive correlation with TOC, whose contoured data are a mirror image of salinity.

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86 Some agglutinated foraminifers, such as Reophax (Scott et al., 2005) and Trochammina (Zalensky, 1959) are pollution indicators. However, the most common agglutinates identified in this study, Valvulina and Siphonaperta, cluster with symbiontbearing foraminifers that are in dicative of more pristine en vironments (Hallock et al., 2003). These two genera secrete calcite cements (Loeblich and Tappan, 1987) and therefore likely require near-normal marine salinities. When FORAM Indices were recalculated to include this cluster, calcium became one of the elements accounting for the foraminiferal distribution (correlation=0.346, variables=Ag, Ca, Mg, S, Hg). Further research is required to distinguish among ta xonomic groups of agglutinates as to which are stress-tolerant and which are not. Bolivina and Brizalina were strongly correlated with each other and less strongly with other stress-tolerant taxa. Th ese genera and other buliminids (i.e., Fursenkoina Alve, 2003) have been shown to tolerate high TOC and low-oxygen conditions (Bernhard and Sen Gupta, 1999). Includi ng these genera in the stress -tolerant taxa improved the correlation between the FORAM Indices and potential stresso rs (correlation=0.371, variables = Ag, Fe, Mg, S, Hg ). I recomme nd that foraminifers belonging to the order Buliminida be grouped with othe r stress-tolerant taxa in cal culating the FORAM Index. Recommendations for Future Work The Sediment Quality Triad developed in the mid 1980s by Long and Chapman is a conceptual framework for co llecting synoptic measurements of sediment chemistry, toxicity, and benthos, and the use of these measures collectively to assess relative sediment quality (Chapman et al., 1997). My study included the sediment chemistry and the benthos. Salinity (0.338) and Hg (0.380) correlated with the foraminiferal

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87 assemblages, however did not account for all of the biological vari ability. Sampling and analyses of TOC, PAHs, PCBs and biocides could elucidat e the contributions of food sources and toxins on forami niferal distributions. My study did not investigate the speciati on and therefore bioavailability of the elements assessed. Further field and laborat ory research could clarify the correlation between foraminifers and chemical species, a nd consequent toxicity of heavy metals of concern. Future laboratory t oxicity studies of concentra tion thresholds, reproductive inhibition, and presence of heavy metals in foraminiferal tests may also help to clarify the relationship between heavy metals and foraminifers. Arsenic and cadmium, while metals of con cern, have not been discussed in this analysis because of their low levels of occu rrence. Long et al. (1995) reported biological effects of concentrations as low as 8.2 ppm for As and 1.2 for Cd. However, the detection limits of ICP-OES techniques used in this study are 10 ppm for As and 0.5 for Cd (Table 1). Therefore, my data on th e distributions of arsenic and cadmium in Biscayne Bay are inconclusive. More sensitive techniques on bulk samples are recommended.

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88 5. CONCLUSIONS • Heavy metals of concern, Cr, Ni, Pb, S n, Hg, Cu, and Zn, co-occurred in Biscayne Bay. Ag clustered with elements characteris tic of clay minerals (Al, Na, K), wetland soils (Fe), and several rare-earth elements. • Muds from northern Biscayne Bay, off Mi ami, showed highest concentrations of metals of concern, followed by muds from the southern bay near Turkey Point. Elevated concentrations of metals were al so documented in muds from in the southcentral bay, off Black Creek Canal. • Three groups characterize foraminiferal di stributions in Biscayne Bay. Smaller, heterotrophic taxa are dominated by Miliolinella, Quinqueloculina, Affinetrina and Triloculina Ammonia planispiral rotaliids, and buliminids exhibit stress-tolerance. The agglutinated genera, Valvulina and Siphonaperta, co-occur with symbiontbearing miliolids. • Northern Biscayne Bay is characterized by stress-tolerant taxa present in relatively high diversity and low abundance. Highest abundances and lowest diversities are found in assemblages dominated by Ammonia and Quinqueloculina that occur along the periphery of the southern bay between Black Creek Canal and Turkey Point. Open-bay sites show intermediate abundances and the highest dive rsities of smaller miliolids and rotaliids; symbiont-bearing taxa account for approximately 10% of this assemblage.

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89 • Symbiont-bearing taxa, as well as several smaller, heterotrophic genera, correlate positively with salinity and negatively with heavy metals. Several smaller heterotrophs correlate positively with dissolved-oxygen concentration. • Stress-tolerant rotaliids and buliminids co rrelate positively to metals of concern. While the rotaliids correlate negatively to salinity, Brizalina shows a positive relationship. • Measured parameters do not account for all of the biological va riability, and further research is recommended to identify other potential controlling factors. • The FORAM Indices provided an effec tive weight-of-evidence approach for comparing conditions throughout Biscayne Bay, as evidenced by average FORAM Indices of SIMPER groups. • Over the past 60 years, the decline in prevalence of foraminifers with algal symbionts, and the increased prevalence of stress-tolerant genera reflects declining water and sediment quality.

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90 REFERENCES Actlabs Group of Companies. 2005. http://www.actlabs.com/home.htm. Almasi, M.N. 1978. Ecology and Color Variat ion of Benthic Foraminifera in Barnes Sound, Northeast Florida Bay. Thesis: University of Miami, Coral Gables, FL. Alve, E. 1991. Benthic Foraminifera in se diment cores reflecting heavy metal pollution in Srfjord, western Norway. Journal of Foraminiferal Research 21(1), 1-19. Alve, E. 1995. Benthic foraminiferal responses to estuarine pollution: A review. Journal of Foraminiferal Research 25, 190-203. Alve, E. 2003. A common opportunistic foramini feral species as an indicator of rapidly changing conditions in a range of environmen ts. Estuarine, Coastal and Shelf Science 57(3), 501-514. Alve, E., Nagy, J. 1986. Estuarine foraminife ral distribution in Sa ndebukta, a branch of the Oslo fjord. Journal of Foraminiferal Research 16, 261-283. Andersen, B.L. 1975. A population study of the benthonic foraminiferida in northern Biscayne Bay, Florida. Tulane Studies in Geology and Paleontology 11(4), 253-301. Armynot du Ch telet, E., Debenay, J.-P., Soulard, R. 2004. Foraminiferal proxies for pollution monitoring in moderated polluted ha rbors. Environmental Pollution 127, 2740. Banerji, R.K. 1992. Heavy metals and bent hic foraminiferal distribution along Bombay Coast, India: Benthos ’90. Studies in Bent hic Foraminifera. Tokai University Press, Sendai, pp. 151-157. Bernhard, J.M., Bowser, S.S. 1999. Bent hic foraminifera of dysoxic sediments: Chloroplast sequestration and functiona l morphology. Earth-Science Reviews 46, 149165. Bernhard, J.M., Sen Gupta, B.K. 1999. Forami nifera of oxygen-depleted environments. In: Sen Gupta, B.K. (ed.), Modern Foraminife ra. Kluwer Academic Publishers, Boston, pp. 201-216.

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91 Boltovskoy, E., Scott, D.B., Medioli, F.S. 1991. Morphological variations of benthic foraminiferal tests in response to changes in ecological parameters: A review. Journal of Paleontology 65, 175-185. Bourg A.C.M. 1995. Speciation of heavy me tals in soils and gr oundwater implications for their natural and provoked mobility. In: Salomons, W., Frstner, U., Mader, P. (eds.), Heavy Metals: Problems and Solutions. Springer, New York, pp. 19-31. Brown, B.E. 1987. Heavy metal pollution on co ral reefs. In: Salvat, B. (ed.), Human Impacts on Coral Reefs: Facts and Recommendations. Antenne Museum E.P.H.E., French Polynesia, pp. 119-134. Bush, J. 1949. A Preliminary Report on the Foraminifera of Biscayne Bay, Florida and Their Ecological Relations. Thesis : Indiana Universi ty, Bloomington, IN. Bush, J. 1958. The Foraminifera and Sedi ments of Biscayne Bay, Florida and Their Ecology. Dissertation: University of Washington, Seattle, WA. Buzas, M.A., Hayek, L.C., Reed, S.A., Jett, J. A. 2002. Foraminiferal densities over five years in the Indian River La goon, Florida: A model of pulsa ting patches. Journal of Foraminiferal Research 32, 68-93. Caccia, V.G., Millero, F.J., Palanques, A. 2003. The distribution of trace metals in Florida Bay sediments. Mari ne Pollution Bulletin 46, 1420-1433. Cearreta, A., Irabien, M.J., Le orri, E., Yusta, I., Quintan illa, A., Zabaleta, A. 2002. Environmental transformation of the Bilbao estuary, N. Spain: microfaunal and geochemical proxies in the sedimentary recor d. Marine Pollution Bulletin 44 (6), 487503. Chapman, P.M., Anderson, B., Carr, S., Engl es, V., Green, R., Hameed, J., Harmon, M., Haverland, P., Hyland, J., Ingersoll, C., Long, E ., Rogers Jr, J., Salaza r, M., Sibley, P.K., Smith, P.J., Sqartz, R.C., Thompson, B., Windom, H. 1997. General guidelines for using the sediment quality triad. Ma rine Pollution Bulletin 34(6), 368-372. Clark, K.R., Warwick, R.M. 2001. Changes in Marine Communities: An Approach to Statistical Analysis and Interpreta tions. PRIMER-E Ltd, Plymouth, UK. Cole, S.A. 1974. The Effect of Thermal St ress Conditions on Benthic Foraminifera in Biscayne Bay, Florida. Thesis: Un iversity of Illinois, Urbana, IL. Coccioni, R. 2000. Benthic foraminifera as bioindicators of heavy metal pollution: A case study from the Goro Lagoon (Italy). In : Martin, R. (ed.), Environmental Micropaleontology. Kluwer Academic/P lenum Publishers, New York, pp. 71-103.

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92 Corcoran, E.F., Brown, M.S., Freay, A.D. 1984. The Study of Trace Metals, Chlorinated Pesticides, Polychlorinated Biphenyls and Phthal ic Acid Esters in Sediments of Biscayne Bay. Rosenstiel School of Marine and Atmo spheric Science, Univ ersity of Miami, Miami, FL. Crevison, H. 2001. Sediment Cores from the Fl orida Reef Tract: is Resolution Sufficient for Environmental Applications? Thesis: Un iversity of South Florida, Tampa, FL. Culver, S.J., Buzas, M.A. 1995. The effects of anthropogenic habitat disturbance, habitat destruction, and global warming on shallow ma rine benthic foraminifera. Journal of Foraminiferal Research 25 (3), 204-211. Debenay, J.P., Tsakiridis, E., Southard, R., Grossel, H. 2001. Factors determining the distribution of foraminiferal assemblages in Po rt Joinville Harbor (I le d’Yeu, France): The influence of pollution. Journa l of Marine Micropaleontology 43, 75-118. DeGrove, J.M. 1984. History of water manage ment in South Florida. In: Gleason, P. (ed.), Environments of South Florida Pres ent and Past II, Miam i Geological Society, Coral Gables, FL pp. 22-27. Dix, T.L. 2001. The distribution and ecology of benthic foraminifera of Tampa Bay, Florida. PhD Dissertation: Univers ity of South Florida. Tampa, FL. Douglas, M.S. 1978. The Everglades: River of Grass: Banyan Books Inc., Miami, FL. Duffus, J.H. 2002. “Heavy Metals”--A mean ingless term? IUPAC, Pure and Applied Chemistry 74, 793-807. Eisler, R. 1996. Silver hazards to fish, wild life and invertebrates: A synoptic review. Biological Report 32 and Contaminant Hazard Reviews Report 32. Washington, D.C., U.S. Department of the Interior National Biological Service. Elberling, B., Knudsen, K.L., Kristens en, P.H., Asmund, G. 2003. Applying foraminiferal stratigraphy as a biomarke r for heavy metal contamination and mining impact in a fiord in West Greenland. Marine Environmental Research 55, 235-256. Folk, R.L. 1980. Petrology of Sedimentar y Rocks. Hemphill, Austin, TX. Fujita, K., and Hallock, P. 1999. A compar ison of phytal substrate preferences of Archaias angulatus and Sorites orbiculus in mixed macroalgal-seagrass beds in Florida Bay. Journal of Foraminife ral Research, 29 (2), 143–151. Geslin, E., Debenay, J.-P., Duleba, W., Bone tti, C. 2002. Morphological abnormalities of foraminiferal tests in Brazilian enviro nments: comparison between polluted and nonpolluted areas. Marine Micropaleontology 45, 151-168.

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93 Geslin, E., Debenay, J.-P., Lesourd, M. 1998. Abnormal wall textures and test deformation in Ammonia (hyaline foraminifer). Journa l of Foraminiferal Research 28, 148-156. Goldstein, S.T. 1976. The Distribution and Ecol ogy of Benthic Foraminifera in a South Florida Mangrove Environment. Thesis: University of Florida, Gainesville, FL. Gonzalez-Regalado, M.L., Ruiz, F., Baceta, J.I., Gonzalez-Regalado, E., Munoz, J.M. 2001. Total benthic foraminifera assemblages in the southwestern Spanish estuaries. Geobios 34(1), 39-51. Hallock, P., and Peebles, M.W. 1993. Fo raminifera with chlorophyte endosymbionts: Habitat of six species in the Florida Keys. Marine Micropaleontology 20, 277–292. Hallock, P., Lidz, B., Cockey-Burhard, E.M ., Donnelly, K.B. 2003. Foraminifera as bioindicators in coral reef assessmen t and monitoring: The FORAM Index. Environmental Monitoring and Assessment, 81, 221-238. Hayek, L.C., Buzas, M.A. 1997. Surveying Na tural Populations. Columbia Univeristy Press, New York. Hoare, A. 2002. Analysis of Biscayne Bay Sediments: Do Benthic Foraminifera Reflect Trace Metal Contamination? Thesis: Univ ersity of South Florida, Tampa, FL. Hu, H. 2002. Human health and heavy metals exposure. In: McCally, M. (ed.), Life Support: The Environment and Human Health MIT Press, Cambridge, MA, pp. 65-82. Ishman, S.E., Graham, S., D'Ambrosio, J. 1997. Modern benthic foraminifera distributions in Biscayne Bay: Analogs for historical reconstructions. U.S. Geological Survey Open File Report, 97-34. Kennish, M.J. 1992. Ecology of Estuaries: Anth ropogenic Effects. CRC Press Inc, Boca Raton, FL. Laws, E.A., Redalje, D.G. 1979. Effect of sewage enrichment on the phytoplankton population of a subtropical estu ary. Pacific Science 33, 129-144. Loeblich, A.R., Tappan, H. 1987. Foraminifera l Genera and Their Classification. Van Nostrand-Reinhold, New York. Long, E.R., Morgan, L.G. 1990. The potential for biological effects of sediment-sorbed contaminants tested in the National St atus and Trends Pr ogram. NOAA Technical Memorandum NOS OMA 52. National Oceanic and Atmospheric Administration, Seattle, WA.

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94 Long, E.R., MacDonald, D.D., Smith, S.L., Ca lder, F.D. 1995. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. Environmental Management 19(1), 81-97. Long, E.R., Sloane, G.M., Scott, G.I., Thomps on, B., Carr, R.S., Biedenbach, J., Presley, B.J., Scott, K.J., Mueller, C., Brecken-Fols, G., Albrecht, B., Anderson, J.W., Chandler, G.W. 1999. Magnitude and Ex tent of Chemical Contamination and Toxicity in Sediments of Biscayne Bay and Vicinit y. NOAA Technical Memorandum NOS NCCOS CCMA. MacDonald, D.D. 1994. Approach to the A ssessment of Sediment Quality in Florida Coastal Waters: Volume 1 Development and Evaluation of Sediment Quality Assessment Guidelines. Florida Department of Environmental Protection, Tallahassee, FL. Miles, C.J., Pfeuffer, R.J. 1997. Pesticides in canals in south Florida. Archives of Environmental Contamination and Toxicology 32, 337-345. Naidu, T.Y., Rao, D.C., Rao, M.S. 1985. Fora minifera as pollution indicators in the Visakhapatnam harbour complex, east coast of India. Bulletin of Geological, Mining, and Metallurgical Society of India 52, 88-96. Novotny, V. 1995. Diffuse sources of polluti on by toxic metals and impact on receiving waters. In: Salomons, W., F rstner, U., Mader, P. (eds.) Heavy Metals: Problems and Solutions. Springer, New York, pp. 33-52. Office of Urban Planning and Redevelopm ent. 2004. Broward-by-the-Numbers. Planning Services Division, Ft. Lauderdale, FL. Parker, W.C., Arnold, A.J. 1999. Quantitative methods of data analysis in foraminiferal ecology. In: Sen Gupta, B.K. (ed.), Modern Fo raminifera. Kluwer Academic Publishers, Boston, pp. 71-89. Perry, W. 2004. Elements of south Florid a’s Comprehensive Ever glades Restoration Plan. Ecotoxicology 13 (3), 185-193. Poag, C.W. 1981. Ecologic Atlas of Benthi c Foraminifera of the Gulf of Mexico. Marine Science International, Woods Hole, MA. Revets, S.A. 1990. The genus Floresina gen. nov. The Journal of Foraminiferal Research 20 (2), 157-161. Riba, I., Garcia-Luque, E., Blasco, J., DelVa lls, T.A. 2003. Bioavailability of heavy metals bound to estuarine sediments as a func tion of pH and salinity values. Chemical Speciation and Bioavailability 15(4), 101-114.

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95 Rygg, B. 1985. Distribution of species along pollution-induced diversity gradients in benthic communities in Norwegian Fjords. Marine Pollution Bulletin 16(12), 469-474. Samir, A.M. 2000. The response of benthic foraminifera and ostracods to various pollution sources: A study from two lagoons in Egypt. Journal of Foraminiferal Research 30, 83-98. Samir, A.M., El-Din, A.B. 2001. Benthic foraminiferal assemblages and morphological abnormalities as pollution proxies in two E gyptian bays. Marine Micropaleontology 41, 193-227. Schafer, C.T. 2000. Monitoring nearshor e marine environments using benthic foraminifera: Some protocols and pitfa lls. Micropaleontology 46(1), 161-169. Scott, D.B., Medioli, F.S. 1980. Living vs. total foraminiferal popula tions: their relative usefulness in paleoecology. Journal of Paleontology 54, 814-831. Scott, D.B., Tobin, R., Williamson, M., Medi oli, F.S., Latimer, J.S., Boothman, W.A., Asioli, A., Haury, V. 2005. Pollution monito ring in two North American estuaries: Historical reconstructions usi ng benthic Foraminifera. Journal of Foraminiferal Research 35(1), 65-82. Scott, G.I., Fulton, M.H., Wirth, E.F., Ch andler, G.T., Key, P.B., Daugomah, J.W., Bearden, D., Chung, K.W., Strozier, E.D., DeLorenzo, M., Siversten, S., Dias, A., Sanders, M., Macauley, J.M., Goodman, L.R., LaCroix, M.W., Thayer, G.W., Kucklick, J. 2002. Toxicological studi es in tropical ecosystems: An ecotoxicological risk assessment of pesticide runoff in south Fl orida estuarine ecosystems. Journal of Agricultural and Food Chemistry 40, 4400-4408. Schropp, S.J., Windom, H.L. 1988. A Gu ide to the Interp retation of Metal Concentrations in Estuarine Sediments. Florida Department of Environmental Regulation, Coastal Zone Manageme nt Section, Tallahassee, FL. Sen Gupta, B.K. 1999. Foraminifera in marg inal marine environments. In: Sen Gupta, B.K. (ed.), Modern Foraminifera. Kluw er Academic Publishers, Boston, pp. 141-159. Sharifi, A.R., Crouda, I.W., Austin, R.L. 1991. Benthic foraminifera as pollution indicators in Southampton Water, Southern England, UK. Journal of Micropaleontology 10, 109-113. Siegel, F.R. 2002. Environmental Geochemistry of Potentially Toxic Metals. Springer, New York.

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96 South Florida Water Management District 1994. An Update of the Surface Water Improvement and Management Plan for Bis cayne Bay. SFWMD, West Palm Beach, FL. The Southeast Environmental Res earch Center (SERC). 2005. (http://serc.fiu.edu/wqmnetwork/). Strom, R.N., Braman, R.S., Jaap, W.C., Dola n, P., Boomer Donnelly, K., Martin, D.F. 1992. Florida Scientist 55(1), 1-13. Stubbs, S.A. 1940. Studies of foraminifera from seven stations in the vicinity of Biscayne Bay. Proceedings of the Florida Academy of Sciences for 1939, 4, 225-230. Tisserand Delclos, L. 1979. Foraminiferes de de ux localities de la baie de Floride et des environs: Joe Kemp Key et Key Biscayne. Notes du Laboratoire de Paleontologie de l'Universite de Geneve 4(2), 19-25 (French). United States Geological Survey (USGS). 2005. http://sofia.usgs.gov/publications /fs/145-96/. VanArman, J. 1984. South Florida's estuaries. In: Gleason, P. (ed.), Environments of South Florida Present and Pa st II, Miami Geological Soci ety, Coral Gables, FL pp. 79-96. Viarengo, A. 1989. Heavy metals in marine i nvertebrates: mechanis ms of regulation and toxicity at the cellular le vel. CRC Critical Review s Aquatic Sciences 1, 295-317. Waite, T.D. 1976. Man’s impact on the chemistry of Biscayne Bay. In: Thorhaug, A., Volker, A. (eds.), Biscayne Bay: Past, Pres ent and Future, Special Report University of Miami Sea Grant 5, 279-286. Wanless, H.R. 1976. Geological setting and rece nt sediments of the Biscayne Bay region. In: Thorhaug, A., Volker, A. (eds.), Bisca yne Bay: Past, Present and Future, Special Report University of Miami Sea Grant 5, 1-32. Watkins, J.G., 1961. Foraminiferal ecology around the Orange County, California ocean sewer outfall. Micropaleontology 7, 199–206. Yanko, V., Kronfeld, J., and Flexer, A. 1994. Response of benthic foraminifera to various pollution sources: Implications for polluti on monitoring. Journal of Foraminiferal Research 24, 1-17. Yanko, V., Ahmad, M., Kaminski, M. 1998. Morphological deformities of benthic foraminiferal tests in response to pollution by heavy metals: Implications for pollution monitoring. Journal of Foraminiferal Research 28, 177-200.

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97 Yanko, V., Arnold, A.J., Parker, W.C. 1999. Effects of marine pollution on benthic Foraminifera. In: Sen Gupta, B.K. (ed.), Modern Foraminifera. Kluwer Academic Publishers, Boston, pp. 217-235. Zalensky, E.R. 1959. Foraminiferal ecol ogy of Santa Monica Bay, California. Micropaleontology 5(1), 101-126.

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98 APPENDICES

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Appendix IList of genera identified in Biscayne Bay (including this study)* Foraminiferal taxa were omitted because taxonomy was outdated or incorrectFinal List Deletions*AdelosinaCymbaloporettaNodobaculariellaStetsoniaAnomalina AffinetrinaDiscammina Nodosariidae TextulariaAschemonella AllogromiaDiscorbisNonionTrifarinaCibicidella AmmobaculitesElphidiellaNonionellaTriloculinaCribrononion AmmodiscusElphidiumNonionoidesTrochamminaCribrostomoides AmmoniaEponidesNubeculariaUvigerinaCyclogyra AmmotiumFissurinaNummoloculinaValvulinaCymbalopora AmphisteginaFloresinaPatellinaValvulineriaDendritina AndrosinaFursenkoinaPeneroplisVertebralinaDiscorinopsis AnomalinoidesGlabratellaPlanorbulinaWiesnerellaEdentostomina ArchaiasGlabratellinaPolymorphinaFlorilus ArticulinaGlobigerinaPseudoclavulinaGallowayus AsterigerinaGlobigerinellaPseudonodosariaGaudryina AstrononionGlobigerinoidesPulleniatinaLoxostomum BigenerinaGlobocassidulinaPyrgoNeoalveolina BolivinaGloborotaliaQuinqueloculinaPraesorites BolivinellaGlobulinaRectobolivinaPseudobolivina BolivinellinaGuttulinaReophaxPseudopatellinoides BolivinitaHanzawaiaReussellaRecurvoides BorelisHaplophragmoidesRobertinoidesRhizammina BrizalinaHauerinaRosalinaRotalia BroeckinaHaynesinaRotaliamminaStreblus BuliminaHeterosteginaSagrinaTretomphalus BuliminellaHomotremaSigmavirgulinaTrillina BuliminoidesHopkinsinellaSigmoilinaVirgulina CalcitubaJadamminaSiphogenerina CancrisLachlanellaSiphonaperta CarpenteriaLaevipeneroplisSiphonina CassidulinaLagenaSorites CibicidesLamarckinaSpirillina ClavulinaLiebusellaSpirolina CornuspiraMassilinaSpiroloculina CornuspiramiaMiliamminaStainforthia CornuspiroidesMiliolinella CribroelphidiumMonalysidium CycloforniaNeoconorbina CyclorbiculinaNeoeponides 99

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Appendix I continued Stubbs (1940)Bush (1949)Bush (1958)Cole (1974)AmphisteginaAmphisteginaAmphisteginaSigmoilinaAmmonia ArchaiasAnomalinaArchaiasSiphoninaAmmotium BorelisArchaiasArticulinaSoritesArchaias CibicidesArticulinaAsterigerinaSpirillinaArticulina ClavulinaAsterigerinaBigenerinaSpiroloculinaBolivina DiscorbisBigenerinaBolivinaStreblusCarterina ElphidiumBorelisCancrisTextulariaCribroelphidium HauerinaClavulinaCassidulinaTretomphalusCyclogyra MassilinaCornuspiraCibicidesTriloculinaDiscorbis MonalysidiumCymbaloporaClavulinaValvulinaElphidium PeneroplisDendritinaCornuspiraVertebralinaMiliolinella PlanorbulinaDiscorbisCornuspiramiaVirgulinaNonion PyrgoElphidiumCornuspiroidesWiesnerellaNubecularia QuinqueloculinaFlintinaCymbaloporettaPlanorbulina RotaliaGlobigerinaDiscorbisQuinqueloculina SiphoninaGlobigerinoidesElphidiumRosalina SoritesGloborotaliaGallowayusSorites SpirolinaGuttulinaGlobigerinellaSpiroloculina SpiroloculinaMassilinaGlobigerinoidesTextularia TextulariaMiliolinellaGloborotaliaTriloculina TriloculinaNonionGlobulinaTrochammina ValvulinaNonionellaHeterosteginaValvulina VertebralinaParrinaHomotremaValvulineria PeneroplisLoxostomum PulleniatinaMassilina PyrgoNeoalveolina QuinqueloculinaNonionella RotaliaNummoloculina SoritesPeneroplis SpirolinaPlanorbulina SpiroloculinaPraesorites TextulariaPyrgo TrillinaQuinqueloculina TriloculinaRectobolivina ValvulinaRhizammina VertebralinaRotalia VirgulinaSchlumbergerina100

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Appendix I continued Tisserand Andersen (1975)Goldstein (1976)Almasi (1978)Delclos (1979)AmmobaculitesMassilinaAllogromiaAmmoniaAmmonia AmmoniaMiliamminaAmmobaculitesArchaiasArchaias AmmotiumMiliolinellaAmmodiscusArticulinaArticulina AmphisteginaMonalysidiumAmmoniaClavulinaAsterigerina ArchaiasNeoconorbinaArchaiasCribroelphidiumCymbaloporetta ArticulinaNodobaculariellaArticulinaDiscorbisDiscorbis AsterigerinaNonionAschemonellaElphidiumElphidium AstrononionNonionellaAstrononionMassilinaEponides BigenerinaNubeculariaBigenerinaMiliolinellaHeterostegina BolivinaPeneroplisCalcitubaNonionNonion BolivinitaPlanorbulinaCarpenteriaPyrgoPeneroplis BorelisPseudobolivinaClavulinaQuinqueloculinaQuinqueloculina BroeckinaPseudonodosariaCribroelphidiumRosalinaSorites BuliminaPyrgoDiscorbisSoritesTextularia BuliminellaQuinqueloculinaDiscorinopsisSpiroloculinaTriloculina BuliminoidesRectobolivinaElphidiumTriloculina CassidulinaReophaxHaplophragmoidesValvulina CibicidesReussellaJadammina ClavulinaRosalinaMassilina CribroelphidiumRotaliaMiliammina CyclogyraRotaliamminaMiliolinella CyclorbiculinaSagrinaPlanorbulina CymbaloporettaSigmavirgulinaPyrgo DiscorbisSiphogenerinaQuinqueloculina EdentostominaSiphoninaReophax ElphidiumSpirillinaRosalina FissurinaSpirolinaSigmoilina FlorilusSpiroloculinaSorites FursenkoinaStetsoniaSpiroloculina GuttulinaTextulariaTextularia HanzawaiaTretomphalusTriloculina HaplophragmoidesTrifarinaTrochammina HauerinaTriloculina HeterosteginaTrochammina LagenaUvigerina LamarckinaValvulina LoxostomumWiesnerella101

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Appendix I continued Ishman (1997)Hoare (2002)AmmobaculitesStainforthiaAdelosinaPolymorphina AmmoniaTextulariaAmmobaculitesPseudopatellinoides AmphisteginaTriloculinaAmmoniaPyrgo ArchaiasTrochamminaAndrosinaQuinqueloculina ArticulinaUvigerinaAnomalinoidesReophax AsterigerinaValvulinaArchaiasRobertinoides AstrononionValvulineriaArticulinaRosalina BolivinaWiesnerellaAsterigerinaSagrina BuliminaBigenerinaSiphonaperta BuliminellaBolivinaSpirillina CassidulinaBolivinellinaSpirolina CibicidesBrizalinaSpiroloculina ClavulinaBuliminaTextularia CribrostomoidesBuliminellaTriloculina CyclogyraCibicidesUvigerina DiscorbisClavulinaValvulina ElphidiumCribroelphidium FlorilusCymbaloporetta FursenkoinaDiscammina GaudryinaDiscorbis GlobocassidulinaElphidiella MiliolinellaElphidium NodobaculariellaEponides Nodosariidae Glabratella NonionellaGlabratellina NubeculariaLaevipeneroplis PatellinaLiebusella PeneroplisMiliolinella Planktonic Monalysidium PseudoclavulinaNeoconorbina PyrgoNeoeponides QuinqueloculinaNodobaculariella RectobolivinaNonion RecurvoidesNonionoides RosalinaPatellina SoritesPeneroplis SpiroloculinaPlanorbulina102

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Appendix II Sample collection details (ND= no data) SampleLatitudeLongitudeDateSampleLatitudeLongitudeDateS-125.724-80.23212/24/2000SS-725.509-80.2747/12/2001S-225.720-80.23012/24/2000SS-825.483-80.2827/11/2001S-325.725-80.23012/24/2000SS-925.445-80.3187/12/2001S-425.725-80.22912/24/2000SS-1025.395-80.2157/11/2001S-525.724-80.23112/24/2000SS-1125.455-80.2167/12/2001S-625.715-80.22912/24/2000SS-1225.450-80.2087/12/2001S-725.680-80.26212/24/2000SS-1325.464-80.2937/12/2001S-825.660-80.26212/24/2000SS-1425.450-80.3117/12/2001S-925.667-80.24912/24/2000SS-1525.479-80.1947/12/2001S-1025.667-80.25612/24/2000SS-1625.495-80.2397/12/2001S-1125.679-80.26012/24/2000SS-1725.484-80.2667/11/2001S-1225.598-80.23712/24/2000SS-1825.454-80.3357/12/2001S-1325.667-80.26312/24/2000SS-1925.389-80.1927/11/2001S-1425.667-80.25412/24/2000SS-2025.446-80.3297/12/2001S-1525.667-80.26012/24/2000SS-2125.473-80.3407/12/2001S-1625.700-80.17212/24/2000SS-2225.489-80.3237/12/2001S-1725.700-80.17212/24/2000SS-2325.491-80.3397/12/2001S-1825.531-80.33012/24/2000SS-2425.476-80.3297/12/2001S-1925.528-80.32512/24/2000SS-2525.490-80.3397/12/2001S-2025.524-80.23112/24/2000SS-2625.475-80.3357/12/2001S-2125.526-80.33012/26/2000SS-2725.460-80.2217/12/2001S-2225.530-80.32812/26/2000SS-2825.474-80.3397/12/2001S-2325.522-80.30712/26/2000SS-2925.473-80.2907/11/2001S-2425.521-80.30212/26/2000SS-3025.473-80.3177/12/2001S-2525.723-80.23112/26/2000SS-3125.501-80.2637/12/2001S-2625.719-80.23612/26/2000SS-3225.456-80.3047/12/2001S-2725.718-80.23412/26/2000SS-3325.455-80.3317/12/2001S-2825.720-80.23812/26/2000SS-3425.460-80.2987/12/2001S-2925.726-80.23212/26/2000SS-3525.456-80.3247/12/2001S-3025.721-80.23812/26/2000SS-3625.488-80.3397/12/2001S-3125.729-80.23212/26/2000SS-3725.490-80.3337/12/2001S-3225.722-80.24212/26/2000SS-3825.455-80.3347/12/2001S-3325.717-80.23212/26/2000SS-3925.490-80.3367/12/2001SS-125.456-80.3197/12/2001SS-4025.484-80.2567/12/2001SS-225.468-80.2887/11/2001SS-4125.477-80.1927/12/2001SS-325.481-80.2927/11/2001SS-4225.484-80.2127/12/2001SS-425.441-80.3237/12/2001SS-4325.428-80.2127/12/2001SS-525.490-80.3297/12/2001SS-4425.410-80.2467/12/2001SS-625.439-80.3207/12/2001 103

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Appendix II continued Tem p D.O.D.O.S p ConSalinit y (ND= no data) (*C)(%)(mg/L) (S/cm)(ppt) SampleLat LongDateIII-125.421-80.3264/15/200228.25154.58.78NDND III2 25.420-80.3224/15/200227.00106.78.564311027.8 III-325.418-80.3164/15/200226.88107.46.815706738.0 III4 25.410-80.3014/15/200226.99109.16.945626637.5 III5 25.404-80.2894/15/200226.84128.98.235623637.4 III6 25.400-80.2824/15/200227.04116.97.415569137.0 III7 25.394-80.2704/15/200226.51104.66.685622737.4 III8 25.388-80.2584/15/200226.60110.37.065588337.3 III9 25.386-80.2514/15/2002NDNDNDNDND III-1 0 25.396-80.2374/15/200227.41117.57.615246134.6 III-1125.502-80.1914/15/200227.17121.67.605504336.6 III-1 2 25.512-80.1904/15/200226.68124.37.925546436.9 III-1325.525-80.1764/15/200226.31103.36.545544136.8 III-1 4 25.527-80.1954/15/200226.71129.38.375536436.8 III-1 5 25.530-80.1994/15/2002NDNDNDNDND III-1 6 25.533-80.2034/15/200226.35118.97.685547936.9 III-1 7 25.538-80.2144/15/200226.78128.38.195575437.1 III-1 8 25.532-80.2284/15/2002NDNDNDNDND III-1 9 25.539-80.3124/15/200226.2182.25.623763723.9 III-2 0 25.538-80.3104/15/200226.0687.76.173653823.1 III-2125.400-80.2914/15/200226.0590.56.174663330.4 III-2 2 25.539-80.2754/16/200225.7699.16.455304735.1 III-2325.534-80.2594/16/200225.87112.57.125512436.6 III-2 4 25.538-80.2454/16/200225.9595.46.225603237.3 III-2 5 25.538-80.2344/16/200225.99158.16.865579137.1 III-2 6 25.538-80.2174/16/200225.8192.66.045569137.0 III-2 7 25.541-80.1934/16/200226.25100.56.625554936.9 III-2 8 25.543-80.1784/16/200226.23104.76.775540436.9 III-2 9 25.558-80.1954/16/200226.21126.86.815569837.1 III-3 0 25.580-80.1724/16/200226.59103.36.685543436.9 III-3125.584-80.1904/16/200225.91152.17.535559437.0 III-3 2 25.585-80.1944/16/200226.2097.66.305597737.2 III-3325.587-80.2104/16/200225.7397.86.355583237.1 III-3 4 25.591-80.2294/16/200225.91100.76.615615937.4 III-3 5 25.593-80.2474/16/200226.1496.96.225651637.6 III-3 6 25.597-80.2704/16/200226.3897.06.175515836.7 III-3 7 25.602-80.2964/16/200226.79108.27.074911832.2 III-3 8 25.603-80.3054/16/200227.49104.36.864597729.9 III-3 9 25.604-80.3074/16/200227.95140.79.264461728.8 III-4 0 25.629-80.2784/16/200227.78143.09.264909232.2 III-4125.630-80.2694/16/200226.60116.17.625103233.6 104

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Appendix II continued Tem p D.O.D.O.S p ConSalinit y (ND= no data) (*C)(%)(mg/L) (S/cm)(ppt) SampleLat LongDateIII-4 2 25.630-80.2534/16/200226.35106.96.945571437.0 III-4325.632-80.2394/16/200226.21107.56.925683737.9 III-4 4 25.633-80.2264/16/200226.16107.26.955678837.9 III-4 5 25.628-80.2104/16/200226.00107.66.955628537.5 III-4 6 25.642-80.1924/16/200226.11102.66.655551336.9 III-4 7 25.641-80.1804/16/200226.34105.46.815524536.7 III-4 8 25.641-80.1504/16/200226.40100.26.425507436.6 III-4 9 25.640-80.1464/16/2002NDNDNDNDND III-5 0 25.664-80.1724/16/200227.00113.57.295460736.3 III-5125.663-80.1854/16/200226.14108.36.875478336.3 III-5 2 25.661-80.2014/16/200226.12106.16.855558437.0 III-5325.658-80.2214/16/200226.30109.77.055668137.7 III-5 4 25.654-80.2454/17/200226.39124.18.085449836.1 III-5 5 25.655-80.2574/17/200226.94112.27.215147533.9 III-5 6 25.657-80.2674/17/200226.7087.75.874850931.8 III-5 7 25.715-80.1704/17/200225.8687.65.825412136.0 III-5 8 25.717-80.1654/17/200225.9692.66.065405736.0 III-5 9 25.725-80.1574/17/200225.6972.45.085457236.2 III-6 0 25.734-80.1714/17/200226.1294.26.125299135.1 III-6125.735-80.1824/17/200225.9691.26.005277835.0 III-6 2 25.736-80.1964/17/200225.9192.56.235176534.1 III-6325.744-80.2104/17/200226.2288.95.895050633.2 III-6 4 25.734-80.2114/17/200226.2988.15.825027633.0 III-6 5 25.708-80.1894/17/200225.9297.56.495439936.1 III-6 6 25.725-80.2044/17/200225.8596.96.415201534.3 III-6 7 25.716-80.1964/17/200225.9095.56.215414635.9 III-6 8 25.700-80.1864/17/200225.9792.56.065434836.0 III-6 9 25.520-80.2544/17/200225.92119.67.155629937.5 III-7 0 25.528-80.2714/17/200226.1194.76.135578437.1 III-7125.520-80.2814/17/200226.2792.76.055332835.3 III-7 2 25.537-80.3334/17/200227.4153.03.732940818.2 III-7325.525-80.3134/17/200226.83111.07.753714723.5 Tem p D.O.D.O.S p ConSalinit y (*C)(%)(mg/L)(S/cm ) (ppt) Max 28.25158.19.265706738.0 Min 25.7382.25.623653823.1 Mean 26.56112.97.145295035.0 St Dev 0.6318.70.9252793.9 105

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106 Appendix III Samples deleted from various analyses (F=Foraminiferal Assemblage Analyses, G-S=Grain-Size Analyses, E=Environmental Analsyses, M=Analyses of Metals) Sample Analyses Excluded From Why? S-8 F Micropaleontological slid e lost, I was not able to reidentify sample with consistent taxonomy S-13 F Total number of foraminifers too small to analyze SS-11 F, G-S No grainsize data recorded SS-12 F, G-S No grainsize data recorded SS-23 F, G-S Subsample lost SS-33 F, G-S Incomplete grain-size data recorded SS-36 F, G-S Incomplete grain-size data recorded SS-37 F, G-S Incomplete grain-size data recorded III-1 E Salinity was not reported for this site III-9 F,G-S, E, M Original sample lost III-15 E No environmental data were reported for this site III-18 F, G-S, E, M Original sample lost III-48 F, G-S Foraminifers were all reworked III-49 F, G-S, M Sample contained no mud to analyze geochemically, foraminifers were all reworked III-63 F, G-S Subsample lost

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Appendix IVGrain size reported as weight percentSAMPLEMedian>2 mm>1 mm>0.5 mm> 0.25 mm > 0.125 m m >0.063 m m <0.063 mm -101234>4 S-1 30.211.102.1426.6555.976.807.12 S-2 30.000.212.0535.8453.973.694.24 S-3 30.060.400.8623.2258.377.509.59 S-4 30.250.253.4343.1245.112.785.07 S-5 30.030.390.8120.6855.598.6513.85 S-6 30.320.033.8843.5746.462.753.00 S-7 33.691.582.6719.5354.416.1411.98 S-8 31.670.999.1630.0749.064.904.16 S-9 25.111.7011.3232.8841.083.174.73 S-10 20.971.0311.4537.1438.903.886.63 S-11 323.783.983.7411.4626.946.0524.05 S-12 31.742.463.7333.6750.201.656.56 S-13 37.283.132.5228.0654.941.532.53 S-14 >42.841.164.5713.9617.971.1758.32 S-15 27.814.739.0132.5642.182.041.69 S-16 >40.010.540.418.7713.1313.0664.08 S-17 317.243.055.7817.5526.715.8023.87 S-18 310.205.466.698.8023.6411.2433.98 S-19 219.8213.6712.4310.5113.744.1625.68 S-20 13.5919.4730.8618.1416.942.978.03 S-21 211.5817.6118.7714.2218.145.4014.29 S-22 214.3515.4812.6711.8318.888.1318.65 S-23 28.4314.8725.9416.2514.873.8715.78 S-24 114.4313.8024.1416.1514.973.7012.81 S-25 31.311.735.1536.2347.814.113.65 S-26 30.000.503.3740.6950.414.780.25 S-27 30.000.475.0138.7547.654.963.15 S-28 31.681.616.2834.1229.9421.834.53 S-29 131.1916.4512.4115.9110.112.3011.63 S-30 31.340.992.7526.1733.7330.924.10 107

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Appendix IV continuedSAMPLEMedian>2 mm>1 mm>0.5 mm> 0.25 mm > 0.125 m m >0.063 m m <0.063 mm -101234>4 S-31 43.572.122.1010.3028.4714.8938.55 S-32 31.292.223.2918.3859.3912.283.14 S-33 30.080.423.8744.2146.944.010.47 SS-1 14.0412.2035.2424.9018.354.111.14 SS-2 41.341.843.779.9324.0717.3241.73 SS-3 11.5519.3032.5518.3718.116.114.02 SS-4 >46.381.281.682.414.895.9777.39 SS-5 127.1621.1311.9010.8310.609.319.06 SS-6 132.988.2011.7614.0810.617.0415.33 SS-7 28.508.7722.7517.7618.207.4616.56 SS-8 30.394.7810.2812.7937.1022.1412.52 SS-9 31.573.578.7316.3625.999.7034.08 SS-10 221.1210.2110.9513.2715.7011.6817.07 SS-13 >43.890.971.634.0813.5612.6363.25 SS-14 313.673.125.079.3319.466.8942.46 SS-15 33.883.957.5617.9139.7610.6216.32 SS-16 29.814.308.4632.7434.313.297.09 SS-17 24.456.1416.8123.8731.426.9910.33 SS-18 043.797.086.146.704.694.7426.86 SS-19 36.166.428.9815.0121.5021.2320.70 SS-20 041.359.6511.2911.118.015.0113.57 SS-21 039.1515.058.8311.638.175.9511.23 SS-22 122.2423.3026.4415.800.518.673.04 SS-24 320.668.9110.279.6510.277.7832.46 SS-25 >416.858.936.505.696.115.3550.57 SS-26 128.7520.8816.3013.928.974.766.41 SS-27 20.331.2711.6143.2735.123.484.91 SS-28 227.419.958.9512.6015.609.9515.56 SS-29 112.0523.2832.7216.3910.403.441.72 SS-30 117.5317.2431.4013.529.875.115.33 SS-31 39.8110.879.7311.7014.999.2833.61 108

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Appendix IV continuedSAMPLEMedian>2 mm>1 mm>0.5 mm> 0.25 mm > 0.125 m m >0.063 m m <0.063 mm -101234>4 SS-32 >43.260.820.942.558.397.4976.55 SS-34 >43.251.061.785.2512.4210.5965.65 SS-35 123.6021.3223.2512.499.856.453.05 SS-38 -167.131.984.023.742.861.4918.78 SS-39 218.0010.3611.6417.6422.1813.097.09 SS-40 38.184.737.9613.8932.159.5623.53 SS-41 37.008.3313.1213.7935.3914.168.20 SS-42 36.722.917.3424.8429.436.2622.49 SS-43 22.326.8819.3643.3625.901.460.71 SS-44 27.307.7015.1629.6729.183.367.62 III-1 >417.303.793.797.135.772.8859.33 III-2 27.508.5112.9821.5529.778.6511.05 III-3 38.358.168.3514.2339.687.4313.79 III-4 21.2311.3519.4423.8537.732.104.29 III-5 213.849.489.0630.0831.151.245.16 III-6 21.075.2012.2439.8633.170.857.60 III-7 20.000.6111.6252.6131.320.063.77 III-8 219.3313.5416.2822.4616.205.796.42 III-10 312.5912.9311.1410.0310.375.5337.41 III-11 133.019.807.679.286.642.7730.83 III-12 37.784.786.8117.6525.456.2131.32 III-13 >42.892.392.955.4916.456.4863.35 III-14 215.045.538.4630.3517.373.6519.59 III-15 -153.2014.726.034.141.330.8419.74 III-16 215.379.5013.2925.0416.234.2516.31 III-17 211.867.667.1331.5625.951.7514.09 III-19 313.816.545.909.9037.067.8118.98 III-20 125.2414.3816.1810.179.522.0322.47 III-21 110.6818.6021.2411.2824.605.168.43 III-22 23.0411.5325.8819.8124.853.7111.18 III-23 227.309.418.827.247.248.3231.66 109

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Appendix IV continuedSAMPLEMedian>2 mm>1 mm>0.5 mm> 0.25 mm > 0.125 m m >0.063 m m <0.063 mm -101234>4 III-24 >417.6412.397.884.763.532.3051.52 III-25 424.249.784.673.975.332.6249.39 III-26 220.216.6814.6429.0718.573.027.81 III-27 >419.496.594.534.123.232.5459.51 III-28 >412.982.062.502.564.123.7572.03 III-29 218.379.569.5112.9710.705.5133.39 III-30 >424.364.393.463.803.974.2255.80 III-31 >411.448.718.659.126.814.2950.99 III-32 313.7011.669.5511.7311.077.9134.39 III-33 23.763.907.9436.4034.422.7410.84 III-34 27.633.7711.6732.4131.782.839.92 III-35 31.672.043.2815.2261.943.0312.81 III-36 23.755.0718.0025.7939.592.365.42 III-37 26.4010.1719.3520.0626.603.3414.08 III-38 30.410.461.3221.8070.113.702.21 III-39 222.436.147.5416.1522.832.4722.43 III-40 >418.331.961.642.954.421.4769.23 III-41 321.035.678.7014.3717.171.6631.39 III-42 310.392.236.2919.1050.092.739.16 III-43 30.982.335.3226.1553.542.589.09 III-44 21.902.766.8644.8634.991.297.35 III-45 >45.712.134.0614.0517.605.1151.35 III-46 >46.954.285.517.1913.3810.2352.47 III-47 31.272.896.7015.8934.3113.0425.90 III-48 314.151.592.2116.1861.012.212.64 III-49 30.132.2910.5042.9743.410.700.00 III-50 416.8810.067.456.198.1612.3838.89 III-51 43.433.534.277.1016.1519.7245.80 III-52 329.246.935.497.9710.086.6033.69 III-53 34.353.435.5534.4034.293.1014.87 III-54 32.921.595.1119.0647.564.9218.83 110

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Appendix IV continuedSAMPLEMedian>2 mm>1 mm>0.5 mm> 0.25 mm > 0.125 m m >0.063 m m <0.063 mm -101234>4 III-55 21.869.6525.2227.7826.733.495.29 III-56 45.382.224.1812.9821.866.4046.97 III-57 34.152.083.9210.3970.407.731.33 III-58 34.151.142.438.6638.777.3737.48 III-59 >41.080.310.310.460.892.7994.16 III-60 219.266.487.9922.8224.017.8011.64 III-61 34.382.853.5614.2325.9412.5636.48 III-62 20.580.584.9563.0523.721.445.68 III-64 30.470.133.1939.9351.272.682.34 III-65 33.031.243.5340.5040.873.337.50 III-66 >42.322.323.7811.5115.159.5555.37 III-67 >41.241.191.682.858.9613.1270.96 III-68 >42.971.241.813.1918.6515.6856.46 III-69 045.399.226.165.104.793.2726.07 III-70 25.0910.1720.7215.1915.965.7227.15 III-71 34.247.9620.3217.1425.428.3216.61 III-72 >43.201.852.783.633.541.5283.47 III-73 >49.682.822.223.835.2418.5557.66 111

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Appendix V-a Concentrations of 32 elements measured in the mud fraction ND denotes concentrations below detection limit s SAMPLES-1S-2S-3S-4S-5S-6S-7S-8Ag (ppm)1.451.190.871.231.351.131.060.76Cd (ppm)NDNDNDNDNDNDNDNDCu (ppm)231.96116.95136.74228.50179.6442.23185.3520.00Mn (ppm)43.4236.2825.3031.6936.8931.2215.1619.69Mo (ppm)4.663.543.087.534.064.797.722.77Ni (ppm)9.2514.618.4710.2412.8968.959.7015.83Pb (ppm)43.9834.6136.3144.8240.7521.8435.054.26Zn (ppm)160.02157.01113.33171.91136.1699.29190.4040.55Al (%)0.500.680.440.540.510.360.340.12Al (ppm)4982.446784.974445.775384.835063.423575.653394.101231.25As (ppm)NDNDNDNDNDNDNDNDBa (ppm)21.6029.1215.6525.8421.2654.9316.6118.37Be (ppm)NDNDNDNDNDNDNDNDBi (ppm)NDNDNDNDNDNDNDNDCa (%)28.9324.8418.1921.9728.1424.0125.9519.08Co (ppm)NDNDNDNDND1.66NDNDCr (ppm)28.3932.8122.9832.9229.0919.2920.686.77Fe (%)1.431.320.941.341.230.570.740.27K (%)0.040.050.030.080.030.220.060.23Mg (%)0.660.950.520.730.601.540.601.58Na (%)0.470.910.571.890.436.371.457.17P (%)0.040.040.030.050.030.040.050.01Sb (ppm)NDNDNDNDNDNDNDNDSc (ppm)ND1.08NDNDNDNDNDNDSn (ppm)39.4131.8129.1134.7244.1642.8837.0930.96Sr (ppm)3086.383224.452105.102579.703209.642110.163150.642505.43Ti (%)NDNDNDNDNDNDNDNDV (ppm)18.1124.0413.8318.0316.2212.8811.277.20W (ppm)NDNDNDNDNDNDNDNDY (ppm)4.395.743.404.284.593.023.091.40Zr (ppm)NDNDNDNDNDNDNDNDS (%)1.521.581.141.651.431.301.371.08Hg (ppb)385.67274.36389.35390.08465.1491.01166.0039.54 112

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Appendix V-a continued ND denotes concentrations below detection limit s SAMPLES-9S-10S-11S-12S-13S-14S-15S-16Ag (ppm)0.640.971.091.321.411.080.751.64Cd (ppm)NDNDNDND1.03NDNDNDCu (ppm)85.9327.01191.694.13250.0628.7542.0920.01Mn (ppm)19.1135.5416.5712.1994.2539.6941.1517.45Mo (ppm)19.982.975.05ND10.342.764.614.59Ni (ppm)13.3212.7132.604.7949.3214.749.325.13Pb (ppm)27.9114.5033.49ND14.1516.5612.856.51Zn (ppm)130.0446.82181.274.27287.8657.26160.2436.87Al (%)0.260.170.250.040.150.190.190.11Al (ppm)2649.901681.882481.83423.131536.211938.311899.761079.61As (ppm)13.55NDNDND39.37NDNDNDBa (ppm)23.9422.0714.9616.1471.2623.7625.8716.22Be (ppm)NDNDNDNDNDNDNDNDBi (ppm)NDNDNDNDNDNDNDNDCa (%)12.7121.6923.3629.8119.8324.7921.4734.39Co (ppm)NDNDNDND2.23NDNDNDCr (ppm)14.649.6418.855.1011.4811.739.9813.71Fe (%)0.860.460.800.070.410.530.600.40K (%)0.170.220.100.121.580.060.100.01Mg (%)1.211.540.781.523.691.251.230.95Na (%)4.574.842.653.9525.391.372.980.25P (%)0.110.200.150.020.100.070.040.02Sb (ppm)NDNDNDNDNDNDNDNDSc (ppm)NDNDNDNDNDNDNDNDSn (ppm)21.3127.7937.1338.7462.9334.8933.5744.78Sr (ppm)1225.682347.562901.515655.441328.882685.712045.166499.43Ti (%)NDNDNDNDNDNDNDNDV (ppm)24.667.278.153.457.719.2510.047.33W (ppm)NDNDNDNDNDNDNDNDY (ppm)2.101.623.141.11ND1.991.452.58Zr (ppm)NDNDNDNDNDNDNDNDS (%)2.340.981.510.533.350.760.920.58Hg (ppb)82.2464.24180.9419.0078.3969.8650.4277.00 113

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SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s S-17S-18S-19S-20S-21S-22S-23S-24 1.541.250.870.540.540.590.800.67 NDNDNDNDNDNDNDND 15.7221.2820.3916.2417.0122.4617.3616.29 17.4545.2631.3138.8123.7223.4638.5640.65 7.072.622.55ND2.542.503.712.23 6.176.4912.498.014.757.995.439.52 6.035.733.914.248.425.983.505.08 77.5850.0046.9929.6237.1840.0441.3924.03 0.150.260.130.080.080.080.130.05 1548.912647.891268.69829.97782.09774.231256.34539.33 NDNDNDNDNDNDNDND 16.3418.9217.7113.4015.2317.3320.8315.96 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 32.9430.3822.4915.3821.9021.5525.4318.79 ND1.03ND2.23NDNDNDND 14.319.195.373.837.275.117.863.57 0.350.410.330.200.210.210.350.14 0.040.050.140.610.030.090.030.29 0.940.801.121.390.920.900.971.67 0.830.813.397.060.650.270.616.95 0.050.040.040.020.030.020.030.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 38.7042.1429.9023.6741.1239.0249.5223.31 6457.383264.532239.001858.881607.522576.862350.822280.45 NDNDNDNDNDNDNDND 8.984.276.476.817.936.837.976.60 NDNDNDNDNDNDNDND 3.133.241.62ND2.342.512.26ND NDNDNDNDNDNDNDND 0.570.750.960.440.560.530.610.50 77.0091.4369.1254.1741.0047.0019.9788.98 114

PAGE 124

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s S-25S-26S-27S-28S-29S-30S-31S-32 0.910.780.690.801.930.982.070.90 NDNDNDNDNDNDNDND 216.43111.9287.21365.99410.85194.06368.08151.76 31.6623.1731.1431.9447.0027.9347.9633.73 4.655.352.887.423.914.664.263.12 11.3311.9526.7713.3912.2812.3111.4510.73 41.8521.1529.9837.2177.3046.7570.7418.12 287.07247.77115.01482.99250.27237.46264.20141.77 0.410.330.560.390.710.390.630.13 4058.713306.695550.493928.877096.263895.896314.901321.75 NDNDNDNDNDNDNDND 19.8628.8723.5730.3029.2723.3126.0022.03 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 22.5018.0116.5216.5632.3920.2833.1122.28 NDNDND1.41NDNDNDND 25.1418.0926.3321.4840.5725.8133.8214.16 1.140.670.960.801.541.031.650.77 0.060.160.160.170.040.080.060.07 0.761.071.231.150.630.620.710.50 1.484.003.684.500.401.750.991.56 0.040.040.040.120.070.050.060.08 NDNDNDNDNDNDNDND NDNDNDND1.03NDNDND 28.4330.0822.5031.5349.4036.4843.9135.31 2804.771116.472129.722180.093915.372475.173858.111980.12 NDNDNDNDNDNDNDND 16.8112.0027.6010.7816.7313.4116.665.13 NDNDNDNDNDNDNDND 4.032.914.643.254.753.474.641.88 NDNDNDNDNDNDNDND 1.381.141.301.510.871.451.020.98 289.58164.13136.84457.34953.91348.23990.79606.94 115

PAGE 125

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s S-33SS-1SS-2SS-3SS-4SS-5SS-6SS-7 0.580.35NDND0.65NDNDND NDNDNDNDNDNDNDND 37.989.2124.5914.7031.2015.5915.7336.71 33.2750.7343.2825.7247.9836.3633.6530.23 2.882.91NDND5.91NDNDND 15.191.8214.077.167.716.5711.428.37 9.026.2920.9615.499.5215.8716.1816.12 58.423.6420.0529.8029.7929.6726.511.70 0.120.100.220.130.260.150.240.16 1231.15988.442215.501297.012580.371458.942433.951632.92 NDNDNDNDNDNDNDND 16.0311.6625.1622.8416.5822.9425.3726.99 NDNDNDNDNDNDNDND NDND13.2710.09NDND10.3212.46 14.6630.6439.0728.5731.2729.2029.8538.73 NDNDNDNDNDNDNDND 9.295.4911.478.0713.747.3111.519.49 0.320.330.340.260.630.190.310.21 0.290.090.030.200.030.110.030.02 1.411.501.321.401.081.120.631.19 7.501.700.395.800.172.910.420.25 0.020.010.010.010.010.010.010.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 23.41NDNDND12.28NDND12.33 1707.272532.083882.512900.412972.822440.572314.034227.80 NDNDNDNDNDNDNDND 7.3912.816.2514.8613.956.206.544.98 NDNDNDNDNDNDNDND 1.762.423.081.904.082.062.942.17 ND1.233.913.383.694.515.913.83 0.850.360.431.000.580.720.650.37 79.0727.3475.6230.7253.1891.1456.9032.32 116

PAGE 126

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s SS-8SS-9SS-10SS-11SS-12SS-13SS-14SS-15 0.491.160.390.39ND0.430.390.43 NDNDNDNDNDNDNDND 3.1811.214.743.076.568.276.854.86 26.9651.448.657.386.7247.6943.168.40 3.504.962.843.44ND3.273.902.85 1.765.272.912.202.133.792.381.25 3.536.59ND2.3412.836.015.093.31 ND6.87NDND2.12NDNDND 0.110.200.020.050.040.150.130.03 1065.851978.62172.48495.35351.271480.181286.13266.35 NDNDNDNDNDNDNDND 11.3511.5510.9111.1629.1011.9510.9616.13 NDNDNDNDNDNDNDND NDNDNDND14.66NDNDND 34.2232.7834.7731.2140.0630.5531.4236.02 NDNDNDNDNDNDNDND 6.199.403.605.047.177.086.344.77 0.150.330.030.070.050.250.220.04 0.030.020.010.020.020.050.020.01 1.471.430.960.951.051.291.411.34 0.540.170.220.360.610.180.240.25 0.000.010.010.000.010.010.010.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDND10.3212.04NDNDND10.88 3756.632836.394927.134485.225114.673259.922872.614617.90 NDNDNDNDNDNDNDND 10.348.70ND2.142.624.636.701.71 NDNDNDNDNDNDNDND 2.153.841.041.611.322.552.821.21 1.582.21NDND2.491.411.72ND 0.260.430.160.200.340.280.320.23 9.2933.327.838.6619.0616.6020.6910.11 117

PAGE 127

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s SS-16SS-17SS-18SS-19SS-20SS-21SS-22SS-23 0.410.440.430.470.44NDND0.76 NDNDNDNDNDNDNDND 78.5412.2423.3614.139.5919.2715.2563.83 28.2921.9641.1614.8441.1041.5537.9833.64 3.942.9918.123.254.01NDND6.61 ND2.6511.494.602.829.035.257.18 2.133.6013.67ND6.4117.8110.256.53 NDND19.16NDND20.2824.0020.27 0.070.070.500.010.170.380.130.39 703.26657.294950.55149.861724.283830.321342.593922.68 NDNDNDNDNDNDNDND 13.5910.8415.5213.0014.2323.9421.2212.62 NDNDNDNDNDNDNDND NDNDNDNDNDND10.41ND 35.4532.5426.4235.4534.5330.6427.7619.35 NDNDNDNDNDNDNDND 5.395.1715.744.688.3713.847.2814.06 0.370.150.480.040.250.400.230.57 0.070.020.040.020.020.030.130.10 1.141.190.520.941.530.341.150.54 0.480.200.250.300.200.183.720.44 0.010.000.020.010.010.020.010.03 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 11.0912.3615.7911.05NDNDND13.95 4957.294022.931715.555449.913453.482085.282190.661751.56 NDNDNDNDNDNDNDND 3.713.9618.601.106.469.055.518.10 NDNDNDNDNDNDNDND 1.561.835.051.193.153.932.253.67 ND1.193.91ND1.886.493.252.83 0.250.190.950.170.360.710.660.76 9.246.9871.2720.1716.18103.40149.6561.52 118

PAGE 128

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s SS-24SS-25SS-26SS-27SS-28SS-29SS-30SS-31 0.382.08ND0.33NDND0.300.37 NDNDNDNDNDNDNDND 19.1035.5815.563.2316.9712.637.2925.85 38.0538.6038.067.3441.2031.3537.1032.35 7.26NDND2.95NDND2.953.72 5.458.135.681.387.565.712.251.92 5.6925.5315.95ND15.8216.563.383.27 29.3450.8025.71ND21.079.37NDND 0.160.220.210.050.400.140.070.08 1627.432222.742103.04530.724026.621404.29664.25798.50 NDNDNDNDNDNDNDND 15.0519.9818.7811.5521.0221.839.1611.91 NDNDNDNDNDNDNDND NDNDNDNDND11.08NDND 23.8926.4224.8526.1025.7030.5422.2930.27 NDNDNDND1.01ND1.35ND 7.2012.159.384.4115.898.994.005.44 0.220.340.220.070.420.230.200.16 0.270.050.030.070.030.110.180.03 1.490.610.621.060.381.241.311.13 5.461.200.371.780.232.673.530.24 0.030.040.020.010.020.010.010.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDND11.21NDNDND11.28 2189.151964.861917.573526.231998.043172.931983.234035.18 NDNDNDNDNDNDNDND 8.897.196.822.7210.9813.9121.343.57 NDNDNDNDNDNDNDND 1.872.872.611.274.702.191.601.63 1.735.444.13ND6.913.62NDND 0.531.050.550.240.610.560.290.21 47.24185.6399.538.3495.9819.5221.138.86 119

PAGE 129

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s SS-32SS-33SS-34SS-35SS-36SS-37SS-38SS-39 0.48ND0.530.360.93ND0.231.91 NDNDNDNDNDNDNDND 8.8324.0614.9010.7852.8416.2223.6524.13 36.0842.4833.1638.0237.5935.8924.2930.68 3.09ND9.322.875.20ND6.38ND 3.088.186.344.9419.105.964.665.31 5.3011.757.134.198.7612.945.6514.35 ND37.2418.10ND28.6824.769.9123.08 0.150.270.270.080.310.130.140.26 1493.702664.222704.45815.003064.211293.731413.572640.93 NDNDNDNDNDNDNDND 13.2024.1810.829.7711.9419.398.2923.67 NDNDNDNDNDNDNDND NDNDNDNDND10.68ND12.03 32.1421.7623.3426.0516.7921.9110.1826.85 ND1.21NDND1.12ND1.64ND 7.6111.329.294.4912.136.235.8010.85 0.260.260.270.190.590.160.280.33 0.020.110.030.020.060.150.030.07 1.360.930.691.120.450.950.380.60 0.193.020.290.280.423.670.201.61 0.010.010.030.000.030.010.010.02 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDND11.1412.9711.87ND11.61ND 3121.561687.731908.612072.291619.301973.33756.252787.53 NDNDNDNDNDNDNDND 5.989.008.465.168.983.436.866.52 NDNDNDNDNDNDNDND 2.953.143.611.982.881.811.753.30 1.646.502.321.313.102.771.674.87 0.300.850.480.220.740.640.370.70 26.04110.7950.6030.1468.2686.2136.60210.18 120

PAGE 130

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s SS-40SS-41SS-42SS-43SS-44III-1III-2III-3 ND0.560.25ND0.87NDNDND NDNDNDNDNDNDNDND 10.2715.3111.2127.1828.4028.09300.6639.87 12.949.505.972.5316.5128.0683.2152.21 ND3.743.05ND3.26NDNDND 6.064.006.6111.294.499.1121.2411.23 12.864.223.4312.283.8911.3755.4216.87 ND1.2915.6029.243.4022.29279.9216.93 0.090.020.040.030.070.160.390.30 872.11225.09374.91322.44710.591591.433900.792997.64 NDNDNDNDNDNDNDND 20.4711.3410.2026.5514.0722.53184.2331.74 NDNDNDNDNDNDNDND 13.46NDND10.29NDND115.3818.30 31.6030.2619.1316.8530.9620.7167.2137.65 NDNDNDNDNDND4.131.14 6.866.443.394.257.7310.1127.7815.92 0.120.150.080.050.390.290.690.44 0.020.030.080.380.020.100.150.05 0.861.281.001.351.081.192.041.35 0.350.582.758.730.222.653.300.97 0.000.010.000.010.010.020.010.01 NDNDNDNDNDND22.20ND NDNDNDNDNDNDNDND ND13.1812.47ND15.17NDNDND 3932.173752.032338.331617.414170.151327.724389.262758.30 NDNDNDNDNDNDNDND 4.973.122.324.924.1612.7938.4714.59 NDNDNDNDNDND30.55ND 1.711.14ND1.171.712.909.445.83 2.30NDND1.921.664.8323.006.43 0.300.230.311.010.211.191.370.71 18.5913.4811.4431.539.0937.819.1319.72 121

PAGE 131

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-4III-5III-6III-7III-8III-10III-11III-12 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 53.1220.1014.0941.0819.4538.6522.6011.76 34.5622.0718.8114.959.3311.248.845.10 NDNDNDNDNDNDNDND 5.405.785.005.285.284.343.982.68 14.9012.4112.4619.6010.3715.2814.6310.11 ND6.87ND28.48ND5.076.30ND 0.180.160.180.140.100.040.030.07 1825.911646.281790.851351.17966.73363.02305.37721.30 NDNDNDNDNDNDNDND 18.2620.0521.5423.1819.9023.5118.6321.39 NDNDNDNDNDNDNDND ND10.1811.0612.9812.2613.7010.14ND 28.1026.6427.3321.4830.8627.7126.7929.50 NDNDNDNDNDNDNDND 10.2610.5210.5111.438.115.416.2511.45 0.310.180.190.160.130.110.060.08 0.070.150.070.110.030.020.060.04 1.131.131.060.750.760.570.850.94 1.242.921.842.930.630.261.651.01 0.010.010.010.010.010.010.020.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 2262.992408.992589.152462.244137.733901.153366.823665.57 NDNDNDNDNDNDNDND 12.428.088.316.052.852.092.693.54 NDNDNDNDNDNDNDND 2.992.842.942.891.671.19ND1.29 3.302.463.032.372.541.841.961.92 0.460.610.480.560.390.240.470.46 19.0322.8427.9030.3722.8530.1323.6418.54 122

PAGE 132

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-13III-14III-15III-16III-17III-19III-20III-21 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 68.6952.5016.9015.9917.5423.7119.7213.56 9.8519.349.893.598.2651.4466.0446.14 NDNDNDNDNDNDNDND 5.473.924.423.736.716.464.784.55 27.3232.3814.0611.0611.3216.5113.9911.98 23.7287.51NDNDND20.5011.04ND 0.020.020.030.020.040.260.100.12 249.81182.70327.30231.03438.852646.72974.941190.75 NDNDNDNDNDNDNDND 17.7112.3922.9223.0424.8120.4720.3421.81 NDNDNDNDNDNDNDND 13.8212.4913.9214.6312.94NDND11.60 27.4015.0533.9440.1136.9121.2423.8530.50 NDNDNDNDNDNDNDND 10.063.626.614.796.2111.475.867.26 0.280.190.030.060.050.500.350.26 0.010.020.070.010.040.060.100.05 0.480.441.030.690.890.731.051.16 0.310.481.800.271.041.342.091.20 0.010.010.010.010.010.020.020.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 3929.532032.104466.566223.865182.411718.061840.562731.21 NDNDNDNDNDNDNDND 3.951.243.401.602.819.738.8813.03 NDNDNDNDNDNDNDND NDND1.12ND1.123.421.691.86 2.551.802.022.411.766.293.973.98 0.300.160.400.290.371.260.930.64 202.3420.7720.2821.0723.0049.8536.4020.13 123

PAGE 133

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-22III-23III-24III-25III-26III-27III-28III-29 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 13.3419.5412.929.8510.1713.4015.2310.26 25.5212.9010.677.384.339.594.858.25 NDNDNDNDNDNDNDND 3.412.434.372.993.674.563.203.49 18.8113.1410.8010.108.4713.2412.8912.96 NDNDNDNDNDNDNDND 0.110.060.050.060.030.030.020.03 1064.60604.15511.50577.30252.35343.22194.42264.31 NDNDNDNDNDNDNDND 21.2323.3017.1016.3618.8225.5733.9722.60 NDNDNDNDNDNDNDND 11.5913.22ND12.0011.9311.7010.7112.10 34.9935.7130.6832.6234.3134.3534.1436.33 NDNDNDNDNDNDNDND 8.326.366.576.494.817.218.605.63 0.170.070.090.070.030.060.080.04 0.040.020.040.040.120.04ND0.06 1.130.990.700.760.951.020.970.93 1.000.710.941.162.600.920.231.21 0.010.010.010.010.010.020.010.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 3776.424383.634470.334909.054930.644428.004275.285145.92 NDNDNDNDNDNDNDND 10.583.684.133.192.583.852.413.99 NDNDNDNDNDNDNDND 1.861.371.401.19ND1.291.131.15 2.812.242.011.661.292.263.051.91 0.420.380.320.360.400.410.440.34 15.2123.5538.9219.2712.5416.1830.6115.60 124

PAGE 134

SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-30III-31III-32III-33III-34III-35III-36III-37 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 12.138.8010.4113.2913.2211.1617.2030.89 6.0011.399.938.1711.2412.8820.8126.25 NDNDNDNDNDNDNDND 19.553.264.994.454.493.963.525.57 9.3111.3511.1613.8912.2011.8310.1710.95 NDNDNDNDNDNDND1.63 0.030.030.040.040.050.070.100.07 275.69340.47402.23362.92468.72656.851015.16718.66 NDNDNDNDNDNDNDND 22.7521.4022.2022.3223.2417.3016.5621.96 NDNDNDNDNDNDNDND 11.6513.1112.5810.7012.0810.50NDND 33.1135.9335.1935.7734.5929.7628.7422.65 NDNDNDNDNDNDNDND 6.396.216.616.727.196.837.116.22 0.070.050.050.060.080.100.190.20 0.080.080.050.030.040.040.050.15 1.050.990.870.790.910.870.951.11 2.251.841.150.820.760.931.171.97 0.010.010.010.010.010.010.000.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 4381.915115.944950.345171.284579.023673.632996.961734.22 NDNDNDNDNDNDNDND 2.052.542.932.794.163.819.814.65 NDNDNDNDNDNDNDND 1.281.271.351.281.421.501.801.13 1.851.872.011.981.931.962.793.29 0.400.380.330.290.320.330.390.55 19.7319.9024.9819.4424.1824.9837.0529.25 125

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SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-38III-39III-40III-41III-42III-43III-44III-45 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 26.9933.0030.8019.8910.699.8825.7111.92 25.7726.1930.1657.6427.5215.4918.017.98 NDNDNDNDNDNDNDND 6.195.114.735.925.703.675.614.68 16.7711.1813.1014.9115.1311.3517.139.88 9.6415.9338.889.39NDNDNDND 0.160.120.090.140.120.090.080.06 1615.881182.16882.431430.341223.55940.16826.60613.85 NDNDNDNDNDNDNDND 26.2925.3130.6230.0321.3024.1123.7423.75 NDNDNDNDNDNDNDND NDNDNDNDND10.8910.36ND 21.7020.4021.1727.9531.9933.2428.5734.80 NDNDNDNDNDNDNDND 8.016.326.819.939.318.748.886.98 0.270.260.380.430.190.150.170.13 0.090.090.140.080.040.090.090.03 1.040.951.381.251.010.940.860.73 2.111.504.431.160.981.962.300.61 0.010.020.030.020.010.010.010.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 1444.011388.411338.372108.723356.624242.573849.805085.15 NDNDNDNDNDNDNDND 7.217.3210.9010.958.538.735.966.09 NDNDNDNDNDNDNDND 1.591.261.151.762.172.151.811.72 4.304.044.325.423.412.962.682.48 0.850.891.430.980.450.450.500.36 29.0354.9747.6640.8627.3026.2523.7521.52 126

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SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-46III-47III-48III-50III-51III-52III-53III-54 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 14.3513.6117.0613.1813.119.138.0914.43 7.058.577.9110.198.997.9614.2823.92 NDNDNDNDNDNDNDND 6.485.9710.584.414.723.544.555.31 7.4110.8717.0413.6611.8213.5510.2512.05 NDND8.82NDNDNDNDND 0.030.020.030.060.060.050.150.15 304.75248.59322.95637.61590.53547.341513.451497.55 NDNDNDNDNDNDNDND 20.1620.7023.2423.4023.8621.2622.4419.83 NDNDNDNDNDNDNDND 11.77ND10.3711.7710.8210.3010.72ND 31.4831.7521.2332.8334.9035.7135.1629.26 NDNDNDNDNDNDNDND 6.455.9413.008.397.926.6010.779.98 0.140.170.070.140.150.160.210.34 NDND0.290.020.030.010.040.02 0.440.541.200.760.760.630.840.80 0.200.208.330.430.590.390.840.20 0.010.010.010.020.010.010.010.01 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 5189.755223.062996.464434.944862.485327.904802.733193.36 NDNDNDNDNDNDNDND 4.063.193.704.834.254.298.809.50 NDNDNDNDNDNDNDND 1.201.251.392.242.111.832.602.25 3.003.632.332.892.832.853.535.69 0.290.280.860.300.320.310.420.49 45.4442.4731.3339.1933.3727.0429.8932.70 127

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SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-55III-56III-57III-58III-59III-60III-61III-62 ND0.71NDND0.210.81NDND NDNDNDNDNDNDNDND 27.4443.5716.5218.4521.28289.8117.5924.21 48.0827.077.229.449.74ND11.1017.55 NDNDNDNDNDNDNDND 6.204.744.374.415.252.745.126.56 26.1145.708.6113.9414.4435.5812.9222.84 18.3165.085.795.8131.4962.67ND16.38 0.130.230.060.080.04ND0.070.26 1329.662323.01553.06826.30444.31ND717.452583.66 NDNDNDNDNDNDNDND 22.5224.8014.2817.6111.192.8118.6222.59 NDNDNDNDNDNDNDND 10.09NDNDND12.13ND12.07ND 24.8024.3817.8923.7115.500.6335.2725.01 NDNDNDNDNDNDNDND 9.3414.876.9110.1514.31ND9.6818.54 0.461.150.150.200.190.030.420.55 0.110.050.150.070.010.010.010.11 1.150.370.630.700.380.020.770.85 2.081.163.131.780.390.100.222.84 0.010.030.010.020.02ND0.010.02 NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND NDNDNDNDNDNDNDND 1937.541487.522303.123151.811883.1758.564086.202851.65 NDNDNDNDNDNDNDND 23.1412.004.085.435.94ND5.0813.76 NDNDNDNDNDNDNDND 1.662.441.612.482.82ND2.303.71 4.5710.532.232.354.601.353.955.14 0.710.860.490.480.750.040.370.91 49.43185.5338.4558.19107.1653.3380.28128.64 128

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SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-63III-64III-65III-66III-67III-68III-69III-70 0.760.42NDNDNDND0.41ND NDNDNDNDNDNDNDND 105.8369.2123.6818.9515.3321.3087.9512.50 23.2832.2216.2815.226.721.682.1916.15 NDNDNDNDNDNDNDND 9.8914.335.514.624.25ND1.703.22 42.5341.6814.0918.6314.2911.5321.3710.14 108.46102.425.193.3110.7611.8437.55ND 0.560.870.180.090.020.02ND0.08 5590.088675.301772.70888.02218.85161.59ND807.75 NDNDNDNDNDNDNDND 25.1556.3617.7412.875.793.522.5716.59 NDNDNDNDNDNDNDND ND12.77ND10.22NDNDND11.51 21.6325.1325.5423.2610.513.571.1027.93 NDNDNDNDNDNDNDND 61.2148.6514.039.354.891.71ND6.48 1.261.590.350.240.080.040.030.12 0.040.080.100.02NDND0.020.02 0.440.890.760.520.220.140.030.90 0.791.512.530.520.100.190.170.55 0.030.040.010.010.000.00ND0.00 NDNDNDNDNDNDNDND 1.011.52NDNDNDNDNDND NDNDNDNDNDNDNDND 2229.712512.492972.132865.101292.46460.34169.623061.60 NDNDNDNDNDNDNDND 14.7250.9110.885.472.641.10ND5.31 NDNDNDNDNDNDNDND 6.319.302.962.05NDNDND1.30 12.4717.483.862.841.831.091.222.66 1.091.640.640.350.150.070.030.30 487.1985.0070.3060.3850.2743.5335.6624.84 129

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SAMPLE Ag (ppm) Cd (ppm) Cu (ppm) Mn (ppm) Mo (ppm) Ni (ppm) Pb (ppm) Zn (ppm) Al (%) Al (ppm) As (ppm) Ba (ppm) Be (ppm) Bi (ppm) Ca (%) Co (ppm) Cr (ppm) Fe (%) K (%) Mg (%) Na (%) P (%) Sb (ppm) Sc (ppm) Sn (ppm) Sr (ppm) Ti (%) V (ppm) W (ppm) Y (ppm) Zr (ppm) S (%) Hg (ppb) Appendix V-a continued ND denotes concentrations below detection limit s III-71III-72III-73 NDNDND NDNDND 10.92139.8917.36 28.2537.8161.19 NDNDND 3.5310.646.40 18.1145.6119.42 ND97.957.93 0.130.410.23 1265.654146.152272.72 NDNDND 26.6627.1627.22 NDNDND 11.1811.5011.74 37.4735.2333.67 NDNDND 7.7121.8410.14 0.190.890.50 0.160.020.03 1.370.170.93 3.100.160.55 0.010.040.02 NDNDND NDNDND NDNDND 4114.722882.662858.07 NDNDND 9.5620.9212.52 NDNDND 2.093.732.83 3.529.126.21 0.560.790.93 18.90143.8637.09 130

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Appendix V-b Concentrations of 32 elements measured in the sand fraction ND denotes concentrations below detection limit s SAMPLES-13S-29SS-25SS-31III-6III-14 Ag (ppm) NDND0.89NDNDND Cd (ppm) ND1.631.82NDNDND Cu (ppm) ND50.3724.71ND10.072.15 Mn (ppm) 3.5618.5523.701.898.181.85 Mo (ppm) NDNDNDNDNDND Ni (ppm) ND5.2112.821.54NDND Pb (ppm) 11.9962.6965.4649.8427.7924.80 Zn (ppm) 4.78142.6963.4211.279.994.64 Al (%) ND0.890.13ND0.03ND As (ppm) NDNDNDNDNDND Ba (ppm) 11.8817.3020.8524.1010.738.31 Be (ppm) NDNDNDNDNDND Bi (ppm) NDNDNDNDNDND Ca (%) 8.7232.0030.5632.2819.0517.75 Co (ppm) NDNDNDND1.06ND Cr (ppm) ND9.388.33ND3.08ND Fe (%) 0.030.590.250.010.050.02 K (%) ND0.010.01NDNDND Mg (%) 0.020.270.500.210.320.23 Na (%) 0.110.250.250.190.150.14 P (%) 0.010.020.050.00ND0.00 Sb (ppm) NDNDNDNDNDND Sc (ppm) NDNDNDNDNDND Sn (ppm) NDNDNDNDNDND Sr (ppm) 561.313806.942225.856466.011085.051324.84 Ti (%) NDNDNDNDNDND V (ppm) ND3.967.34NDNDND W (ppm) NDNDNDNDNDND Y (ppm) ND1.102.03ND1.34ND Zr (ppm) ND1.201.82NDNDND S (%) 0.030.420.840.100.120.08 Hg (ppb) 5.40213.59175.237.877.08ND 131

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Appendix VI Raw counts of foraminiferal abundance in sediments from Bisca y ne Ba y SampleS-1S-2S-3S-4S-5S-6 Other Miliolida Affinetrina 251210 Articulina 55236 Cornuspira 12 Hauerina Lachlanella M iliolinella 145 Nodobaculariella Pyrgo Quinqueloculina 3258703251165 Siphonaperta 11124 Spiroloculina 125 Triloculina 250542670 Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias 1 B orelis Cyclorbiculina Laevipeneroplis 5 M onalysidium 62125 Peneroplis 33114 Sorites Spirolina 1 S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia 452536244421 Cribroelphidium 26614162318 Elphidium 635315 Haynesina 102359 Nonion 11927283010 Nonionella Nonionoides 1131 132

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Appendix VI continued SampleS-1S-2S-3S-4S-5S-6 Other Rotaliida Cibicides Cymbaloporetta 1 Discorbis 23448 Eponides Glabratella 1242 Glabratellina Neoconorbina Neoeponides 19 Planorbulina 1 R osalina 3115211 Valvulineria 11016 Robertinida R obertinoides 1 Spirillinida Patellina Spirillina 1 La g enida Polymorphina Buliminida B olivina 341117 B rizalina 878552 B ulimina B uliminella 11121 Floresina 23 Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina 5 R eophax 112 Planktonic Foraminifera2 Total # of Forams Picked 190136199139220417 133

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Appendix VI continued SampleS-1S-2S-3S-4S-5S-6 Total # of Forams Picked 190136199139220417 SIMPER Group CCCCCB-1Mass Assessed, g rams 0.300.100.151.020.100.30 Total Mass Assessed 0.320.100.171.070.120.31 Forams/Gram 5881302119913018951348 Number of Genera 201922172030 Fisher Alpha Index 5.646.016.305.085.357.39 Shannon Diversit y Index 1.020.880.950.980.981.02 % Mud 7.124.249.595.0713.853.00 Median Grain Size 333333 FORAM Index 1.861.791.721.531.642.16 134

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Appendix VI continued SampleS-7S-9S-10S-11S-12S-13 Other Miliolida Affinetrina 12214 Articulina 44 Cornuspira Hauerina 1 Lachlanella M iliolinella 12112 Nodobaculariella Pyrgo 1 Quinqueloculina 17107265124 Siphonaperta Spiroloculina 212 Triloculina 880832 Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida 1 Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium 1 Peneroplis 2 Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia 192553611 Cribroelphidium 21112332 Elphidium 21532 Haynesina 2021431 Nonion 133115277 Nonionella Nonionoides 1 135

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Appendix VI continued SampleS-7S-9S-10S-11S-12S-13 Other Rotaliida Cibicides 1 Cymbaloporetta Discorbis 2365 Eponides Glabratella 122 Glabratellina Neoconorbina Neoeponides 2 Planorbulina 1 R osalina 431111 Valvulineria 9121266 Robertinida R obertinoides Spirillinida Patellina 11 Spirillina 1 La g enida Polymorphina Buliminida B olivina 332223 B rizalina 9105113 B ulimina B uliminella 11 Floresina 11 Fursenkoina Hopkinsinella R eussella 1 Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina 6 Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked 13113916613916438 136

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Appendix VI continued SampleS-7S-9S-10S-11S-12S-13 Total # of Forams Picked 13113916613916438 SIMPER Group CCB-1CB-1N/AMass Assessed, g rams 0.230.160.050.140.050.98 Total Mass Assessed 0.260.170.050.180.051.00 Forams/Gram 4998283100754306538 Number of Genera 14122217247 Fisher Alpha Index 3.973.156.785.087.702.52 Shannon Diversit y Index 1.010.950.950.901.030.53 % Mud 11.984.736.6324.056.562.53 Median Grain Size 322333 FORAM Index 1.491.361.931.261.951.95 137

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides S-14S-15S-16S-17S-18S-19 19511 32111 311 2 816633294538 1 352 221772034116 1 1 21 2 1 15212193724 327131414 4111 4232944 42246 3 138

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked S-14S-15S-16S-17S-18S-19 114 93331 22 1 514 551 8845 31 1 1334 111101 1 15 3 2 1 1 1 2 11 188151143162139209 139

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index S-14S-15S-16S-17S-18S-19 188151143162139209B-1B-1CCAA0.030.050.010.140.010.01 0.070.050.030.180.020.01 261129705137914917815535 18231828108 4.877.565.459.682.471.65 0.910.951.021.140.680.59 58.321.6964.0823.8733.9825.68 >42>4332 1.952.031.591.661.651.80 140

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides S-20S-21S-22S-23S-24S-25 1813310113 33273 13127 1 974936546339 2 21 5410861313132 411 63 212 1 1 1 2631244111 151062211 315 732314 435 1 1 141

PAGE 151

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked S-20S-21S-22S-23S-24S-25 1535 14 29 363 31610 1 2 3 2 2 249230134129162146 142

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index S-20S-21S-22S-23S-24S-25 249230134129162146AAAAB-1C0.020.010.010.010.030.32 0.020.010.010.010.030.33 114501971610900108664708440 15117142021 3.512.411.573.995.976.72 0.830.690.590.800.931.02 8.0314.2918.6515.7812.813.65 122213 1.862.141.782.182.091.90 143

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides S-26S-27S-28S-29S-30S-31 920137 399161 81044 1 646767403936 2 2113 29211961312 23 3 2 379141326 476293024 113 678141511 454433 13 144

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked S-26S-27S-28S-29S-30S-31 1 2 1643 1232 1 1 62915 343105 479155 1 11 4 310433 427777 1211 111 2 11 1131 1 159188189147169139 145

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index S-26S-27S-28S-29S-30S-31 159188189147169139B-1B-1B-1CB-1C0.930.220.160.020.100.04 0.930.230.170.020.100.07 1718281128649516212135 222620212116 6.918.175.656.686.324.67 0.961.061.031.021.100.95 0.253.154.5311.634.1038.55 333134 1.992.201.861.581.631.50 146

PAGE 156

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides S-32S-33SS-1SS-2SS-3SS-4 1921231620 1 11 126461956 349433758114 6321 2 1539191324 2 131 45102 11 3 1 12 4952 51713 232 531719 54 147

PAGE 157

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked S-32S-33SS-1SS-2SS-3SS-4 1 32 1 55425 265933 9114323 13 242 1 12 1 841 1 2 119133175162141284 148

PAGE 158

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index S-32S-33SS-1SS-2SS-3SS-4 119133175162141284CB-1B-3B-3B-3B-30.360.260.070.010.090.01 0.370.260.070.020.090.04 3205052437858115388028 112014161620 2.966.533.584.404.644.90 0.591.020.920.900.870.86 3.140.471.1541.734.0277.39 33141>4 1.102.072.212.302.892.05 149

PAGE 159

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides SS-5SS-6SS-7SS-8SS-9SS-10 204919193710 63910 1 318841727322 123 911003741103122 35 32481743614 1837 5614 1842 713 1 122 2 112 2922 961175 1225 1212 13104 2 150

PAGE 160

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked SS-5SS-6SS-7SS-8SS-9SS-10 2 423122 1 1 84711 4358139 4621156 16 3 122 14341 231420176170342270 151

PAGE 161

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index SS-5SS-6SS-7SS-8SS-9SS-10 231420176170342270AB-3B-3B-3B-3B-20.010.020.050.030.030.14 0.010.020.060.030.050.17 26258177802937495768321599 151420171827 3.592.795.814.704.057.44 0.810.871.020.780.951.01 9.0615.3316.5612.5234.0817.07 112332 2.071.983.442.812.102.43 152

PAGE 162

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides SS-13SS-14SS-15SS-16SS-17SS-18 2913257107 63234 1 1 60227041256 1 1315835464250 13454 220181196 137261 2112 117610 1116 1 11 41131 612220 3213 228 616122 1 153

PAGE 163

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked SS-13SS-14SS-15SS-16SS-17SS-18 1 1 216312 2521 139224 310122 3 3 11 15651 275168187155140137 154

PAGE 164

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index SS-13SS-14SS-15SS-16SS-17SS-18 275168187155140137B-3B-3B-3B-3B-3A0.010.040.050.230.100.01 0.030.070.060.240.110.02 91882248332963412819109 242016202112 6.305.924.196.116.853.17 0.790.980.850.961.040.81 63.2542.4616.327.0910.3326.86 >433220 2.072.272.602.993.381.59 155

PAGE 165

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides SS-19SS-20SS-21SS-22SS-24SS-25 215316125 6152 1 1315820236 1 535981285040 34 1 101438234411 7227 4211811 211 1 3 2 21692463 55305212 42 25818 15811 156

PAGE 166

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked SS-19SS-20SS-21SS-22SS-24SS-25 2 1 3252 1 632 91121 31812 1 121 122124 1 148147251154210150 157

PAGE 167

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index SS-19SS-20SS-21SS-22SS-24SS-25 148147251154210150B-2AAB-3B-3A0.060.010.010.100.050.03 0.070.010.010.100.070.07 20961494717825153929552181 281412152010 10.223.802.634.115.442.41 1.110.840.770.991.010.72 20.7013.5711.233.0432.4650.58 30013>4 2.951.861.643.052.681.44 158

PAGE 168

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides SS-26SS-27SS-28SS-29SS-30SS-31 181131352323 531329 11 948221333046 121 59331641237345 1223 12 46815161112 411047 144221 31225 1 211 1122 1814811 511641 111311 222 441114 159

PAGE 169

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked SS-26SS-27SS-28SS-29SS-30SS-31 1 1 3732 16104 211653 319117 21 223 1196 176138309423190186 160

PAGE 170

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index SS-26SS-27SS-28SS-29SS-30SS-31 176138309423190186AB-3AB-3B-3B-30.030.170.010.110.070.02 0.030.180.010.110.070.03 531378123721367927255613 102315271824 2.307.833.306.424.887.34 0.780.970.680.930.911.03 6.414.9115.561.725.3333.61 122113 2.502.821.822.442.412.60 161

PAGE 171

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides SS-32SS-34SS-35SS-38SS-39SS-40 25242630920 692 1221 51526524379 11 10065992247055 116 11 157443815 24111 1241 16 11 211 8931 31326222 213 123 36222 162

PAGE 172

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked SS-32SS-34SS-35SS-38SS-39SS-40 1114 23321 51811 121138 11 125 212178252448154225 163

PAGE 173

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index SS-32SS-34SS-35SS-38SS-39SS-40 212178252448154225B-3B-3B-3AAB-30.020.010.030.020.010.05 0.070.040.030.020.010.07 29244704788121405130073186 152017131121 3.685.774.122.502.715.67 0.700.810.810.670.720.90 76.5565.653.0518.787.0923.53 >4>41-123 2.082.132.131.771.902.68 164

PAGE 174

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides SS-41SS-42SS-43SS-44III-1III-2 56510101225 1281724 32 422091318863 1 5823965663680 331 2 238653616 10125121 31115 35661 63 2222 2 21 6 264 126 51113 165

PAGE 175

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked SS-41SS-42SS-43SS-44III-1III-2 320411 1 2116 415164 1122012 211 3 1 2434 141684130177143232 166

PAGE 176

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index SS-41SS-42SS-43SS-44III-1III-2 141684130177143232B-3B-3B-3B-3OB-30.030.070.420.100.020.02 0.030.090.420.110.050.03 46238033308165226438973 142214221015 3.864.343.986.622.453.58 0.760.840.791.030.800.82 8.2022.490.717.6259.3311.05 3322>42 2.972.193.833.771.992.04 167

PAGE 177

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-3III-4III-5III-6III-7III-8 1129910517 19947 376623161728 1 1 427548347044 1542 31832202526 1106661 1114772 2851052 11 1 114 3 1233 42125 168

PAGE 178

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-3III-4III-5III-6III-7III-8 1 83112 425227 3106615 1285315 1 2 2 164211 134264163129143177 169

PAGE 179

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-3III-4III-5III-6III-7III-8 134264163129143177B-3B-3B-3B-3B-3B-30.030.220.230.402.920.06 0.030.230.240.433.030.07 42781170687300472588 181617161322 5.603.754.784.813.476.59 0.890.940.961.010.731.05 13.794.295.167.603.776.42 322222 2.192.862.763.462.992.16 170

PAGE 180

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-10III-11III-12III-13III-14III-15 257258 8125778 21 15142071214 1512 6634474339116 313 114 291414181123 15511 144461 32572 11 3332105 11 33221 952171 111 5111 1211726 73101 12211 21 171

PAGE 181

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-10III-11III-12III-13III-14III-15 21111 13 2311 12 12 17621612 1312 433424 96625 1 1 3 13 425444 54 1 11 1 312 712 1 202143147152139236 172

PAGE 182

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-10III-11III-12III-13III-14III-15 202143147152139236B-2B-2B-2B-1B-2B-20.100.090.040.100.230.06 0.150.120.060.280.280.07 1303116424625464953382 282626282829 8.799.309.1410.0810.578.69 1.071.201.111.171.180.93 37.4230.8431.3263.3519.5919.74 313>42-1 2.572.992.792.893.992.33 173

PAGE 183

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-16III-17III-19III-20III-21III-22 53109127 681332 813151918 221 344150856634 414211 3 2828385689 836 5824 76315 1 453 211 21 614511 42183 6511 13111 211 174

PAGE 184

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-16III-17III-19III-20III-21III-22 3 21 941148 3157 252164 1 211 11 15111 37845 144157189228150139 175

PAGE 185

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-16III-17III-19III-20III-21III-22 144157189228150139B-2B-2AAB-3B-30.190.230.030.060.100.08 0.230.270.040.070.110.09 6345795280310113211487 222611142320 7.228.862.553.297.586.41 1.121.130.720.750.941.09 16.3114.0918.9822.478.4311.18 223112 3.383.121.551.762.433.65 176

PAGE 186

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-23III-24III-25III-26III-27III-28 15121229 51114758 113 1 11 171612485 3 351 10560322367200 123811 12132 1017416212 22838 131 422221 12 5 1 132 3 2253 2613 82333 61103312 1 12 177

PAGE 187

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-23III-24III-25III-26III-27III-28 1211 1 4223 1 11 107175811 12 7638 1451421020 1 1 113 321510 11 136 221111 235 1 216151151139137349 178

PAGE 188

Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-23III-24III-25III-26III-27III-28 216151151139137349B-2B-3B-2B-2B-2B-20.010.030.050.440.030.02 0.010.060.090.480.070.08 147622711169828919134436 221827242436 6.135.339.548.378.3410.01 0.890.931.191.170.950.89 31.6651.5249.397.8159.5172.04 2>442>4>4 1.992.232.105.062.252.28 179

PAGE 189

Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-29III-30III-31III-32III-33III-34 936117 11145876 1 13171219920 1 1221 8013040595751 511141 121 557165 264235 113 2241 41253 23 11 23 117 66621 6721 48682 312 1 180

PAGE 190

Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-29III-30III-31III-32III-33III-34 1214 13 332412 11 85201597 441125 3252111525 3 1 131 231 351 2 2 1 41 121 1 152283136165142162 181

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-29III-30III-31III-32III-33III-34 152283136165142162B-2B-2B-2B-1B-2B-30.050.020.040.050.490.14 0.070.050.070.080.550.16 21545438185221652581013 203425221822 6.1610.068.996.825.466.87 0.841.031.041.030.951.00 33.3955.8050.9934.3910.849.92 2>4>4322 2.202.282.402.082.612.71 182

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-35III-36III-37III-38III-39III-40 21216172 745526 1 3018251571 1 55505110013873 1211 9672516 5621 543 471 37 1 1315 131262 1 22227 1 183

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-35III-36III-37III-38III-39III-40 331 4312 68515 14418327 2 1 173148122140208149 184

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-35III-36III-37III-38III-39III-40 173148122140208149B-3B-3B-3B-3AB-10.280.170.040.500.020.06 0.320.180.050.510.030.19 53781423822757015777 19181312813 5.445.373.683.141.653.43 0.980.990.770.500.500.74 12.815.4214.082.2122.4369.23 32232>4 2.813.252.172.211.811.91 185

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-41III-42III-43III-44III-45III-46 8133924 4210693 11 12 516181655 1 5112 664345373345 3111 12 19121313315 11145 11 132 213 1 362718 5111211267 21311 154111 576132412 1 186

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-41III-42III-43III-44III-45III-46 11131 13 2114 11 1 1987474 26332 189149119 1 1 112 1213 1 213 1 2 2221 1 163146158141152176 187

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-41III-42III-43III-44III-45III-46 163146158141152176B-1B-1B-1B-1CB-10.160.180.120.520.130.09 0.230.190.130.560.270.18 7127581177250565984 152623252628 4.039.177.368.808.949.31 0.881.091.101.111.121.20 31.399.169.097.3551.3552.47 3332>4>4 1.922.131.872.121.802.16 188

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-47III-50III-51III-52III-53III-54 23227 3321513 4 1511416 11 2 314742184785 11 199441410 13211 1 1 1 211 12 111 1 1 551733128 527141314 1118452 101035106 5172220145 13112 189

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-47III-50III-51III-52III-53III-54 5661 1 241352 2 936128 683522 9171481411 21 1 1 12111 22532 2 1 1113 2 2 1 1 1 132155158131174201 190

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-47III-50III-51III-52III-53III-54 132155158131174201B-1B-1CCB-1B-10.100.030.020.060.200.10 0.140.050.040.100.230.13 9502870407813577441584 232527242723 8.028.419.258.588.926.66 1.131.111.141.081.130.99 25.9038.8945.8033.6914.8818.83 344333 1.961.961.891.601.951.87 191

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-55III-56III-57III-58III-59III-60 425512 34415 53119 1 471733279734 41 111 121716136 3 132 2 462 1 1 1 31 11 353645 2242797 41365 2024343 521715162 22 192

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-55III-56III-57III-58III-59III-60 1113 11 284 6 1 16121 2482 10124135 6 1 11 2 111122 11 2 1 1 1 1 1 2 13214698106228100 193

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-55III-56III-57III-58III-59III-60 13214698106228100B-2CB-1B-1CB-10.160.130.540.130.010.09 0.170.240.550.200.190.10 77761917951812111004 241025212719 8.552.4310.777.857.916.95 1.050.861.071.100.961.06 5.2946.971.3337.4894.1611.64 2433>42 2.581.322.831.881.692.02 194

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-61III-62III-64III-65III-66III-67 7113 1214 11 131221 122 273362451935 21 41619689 2342 1 1 13 3 423010382226 98151520 331862 13348106 118671815 112 195

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-61III-62III-64III-65III-66III-67 111 131 2241 111 212 122 36275 1 1362 3 1 1 1 1 12 129133125149131132 196

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-61III-62III-64III-65III-66III-67 129133125149131132CB-1ACCC0.040.490.660.650.010.02 0.070.520.670.700.030.06 195125818621344972396 191916182117 6.156.074.875.367.045.19 0.941.020.770.931.110.95 36.485.682.347.5055.3770.96 3233>4>4 1.711.722.091.641.691.60 197

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Appendix VI continued Sample Other Miliolida Affinetrina Articulina Cornuspira Hauerina Lachlanella M iliolinella Nodobaculariella Pyrgo Quinqueloculina Siphonaperta Spiroloculina Triloculina Wiesnerella S y mb-Miliolida Juvenile Symb-Miliolida Androsina Archaias B orelis Cyclorbiculina Laevipeneroplis M onalysidium Peneroplis Sorites Spirolina S y mb-Rotaliida Amphistegina Asterigerina Opportunistic Rotaliida Ammonia Cribroelphidium Elphidium Haynesina Nonion Nonionella Nonionoides III-68III-69III-70III-71III-72III-73 1710812 21943 224327111 25 1434552680 1321 2 31691645 241371 21 514 1 1 25 1 3417523 4211297 65312 3283 29932241 3 198

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Appendix VI continued Sample Other Rotaliida Cibicides Cymbaloporetta Discorbis Eponides Glabratella Glabratellina Neoconorbina Neoeponides Planorbulina R osalina Valvulineria Robertinida R obertinoides Spirillinida Patellina Spirillina La g enida Polymorphina Buliminida B olivina B rizalina B ulimina B uliminella Floresina Fursenkoina Hopkinsinella R eussella Sagrina Sigmavirgulina Uvigerina Textulariida (A gg lutinated) Clavulina Valvulina Lituolida (A gg lutinated) Discammina R eophax Planktonic Foraminifera Total # of Forams Picked III-68III-69III-70III-71III-72III-73 1 34532 21 18232 2171213 51118132 1 1 1111 82 1 1 111174194136139200 199

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Appendix VI continued Sample Total # of Forams Picked SIMPER Group Mass Assessed, g rams Total Mass Assessed Forams/Gram Number of Genera Fisher Alpha Index Shannon Diversit y Index % Mud Median Grain Size FORAM Index III-68III-69III-70III-71III-72III-73 111174194136139200CB-2B-3B-3CA0.020.020.030.040.080.02 0.030.020.040.040.490.04 32227146455931502844704 15252120718 4.688.005.976.471.554.79 0.891.151.011.060.540.83 56.4626.0727.1516.6183.4757.66 >4023>4>4 1.532.552.732.661.021.90 200

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Appendix VII Correlation matrix of measured elements and mud(N=137, highlighted correlations are significant at p<0.05)AgCuMnMoNiPbZnAlBaBiCaCo CrAg1.00 Cu0.47 1.00 Mn0.300.21 1.00 Mo0.640.320.31 1.00 Ni0.360.540.390.26 1.00 Pb0.12 0.74 0.15-0.07 0.52 1.00 Zn0.600.770.380.420.660.57 1.00 Al0.500.650.580.410.630.610.67 1.00 Ba-0.06 0.230.37 -0.15 0.550.430.200.42 1.00 Bi-0.46 -0.05-0.16 -0.49 0.03 0.24-0.22 -0.14 0.48 1.00 Ca-0.13 -0.310.32 -0.070.06-0.15 -0.36 0.06 0.600.35 1.00 Co 0.020.17 0.20 0.05 0.25 0.06 0.18 0.12 0.310.31 0.041.00 Cr0.390.570.520.310.650.620.540.860.62 0.03 0.35 0.091.00Fe0.590.760.560.460.600.630.740.900.37-0.21 0.020.08 0.84K0.080.09 0.20 0.07 0.36 -0.02 0.30 0.06 0.20 -0.08-0.15 0.36 0.00Mg0.02 -0.280.41 0.160.12 -0.36 -0.16-0.05 0.36 0.06 0.470.23 0.03Na0.050.110.140.01 0.40 0.08 0.31 0.07 0.33 0.00-0.08 0.24 0.10Pb0.550.520.250.480.550.360.590.450.21-0.27 -0.090.05 0.47Sn0.800.480.270.680.48 0.06 0.610.44 0.03 -0.45 -0.090.09 0.39Sr-0.08 -0.33 0.05-0.07-0.03 -0.22-0.42 -0.07 0.440.330.91 -0.04 0.25V0.260.410.720.300.540.480.510.770.51 -0.05 0.200.210.77Y0.350.410.630.320.500.430.450.840.46 0.01 0.28 0.16 0.83Zr-0.55 -0.130.15 -0.58 0.00 0.29 -0.160.07 0.400.490.22 0.080.13S0.410.620.500.340.730.580.740.750.56 -0.120.020.13 0.76Hg0.560.710.310.290.570.660.760.680.17-0.28-0.21 -0.06 0.65% Mud-0.11-0.15-0.15-0.11-0.14-0.03-0.13 -0.20 -0.140.080.05-0.10-0.08AgCuMnMoNiPbZnAlBaBiCaCo Cr 201

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Ag Cu Mn Mo Ni Pb Zn Al Ba Bi Ca Co Cr Fe K Mg Na Pb Sn Sr V Y Zr S Hg % Mud Appendix VII continuedFeKMgNaP SnSrVYZrSHgMud 1.00 0.071.00 -0.07 0.48 1.00 0.09 0.880.50 1.00 0.570.24 0.04 0.30 1.00 0.560.19 0.090.15 0.60 1.00 -0.08 -0.170.36 -0.11-0.07-0.011.00 0.750.270.260.310.340.26 -0.011.00 0.72 -0.070.09-0.04 0.280.25 0.09 0.78 1.00 -0.05-0.16-0.12-0.11 -0.33-0.71 0.00 0.230.26 1.00 0.790.36 0.14 0.480.620.46 -0.12 0.750.61 0.041.00 0.76 0.10 -0.36 0.12 0.560.50-0.230.460.46 -0.13 0.65 1.00 -0.14 -0.36-0.25-0.40 -0.09 -0.23 0.07 -0.20 -0.10 0.20-0.20 -0.021.00FeKMgNaP SnSrVYZrSHgMud 202

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Appendix VIII SIMPER output of dissimilarit y amon g sample g roups Groups C & B-1 Average dissimilarity = 43.44 Group CGroup B-1 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Ammonia 19.994.373.521.638.18.1 Quinqueloculina 20.57342.451.075.6513.75 Cribroelphidium 12.684.62.211.275.0818.83 M iliolinella 0.524.812.191.675.0523.87 Affinetrina 0.714.762.131.774.9128.78 Nonion 11.64.682.11.544.8233.61 Triloculina 5.710.762.091.34.838.41 Neoeponides 0.513.552.041.664.743.11 Haynesina 7.173.151.921.324.4247.53 Valvulineria 3.115.451.651.263.851.33 Articulina 1.173.71.581.293.6354.96 B rizalina 3.641.271.471.473.3858.34 R osalina 1.612.481.261.412.961.24 Elphidium 2.211.941.211.332.7964.03 Discorbis 1.521.621.091.232.5266.55 B olivina 1.120.861.011.312.3268.87 Juv Symb-Mil0.620.810.941.152.1671.03 Cibicides 0.470.770.881.072.0373.06 Spiroloculina 0.20.760.871.19275.05 Nonionoides 0.660.360.821.161.8976.95 Glabratella 0.550.280.7111.6378.58 Pyrgo 0.190.460.650.861.4980.07 Peneroplis 0.230.420.630.941.4681.53 B uliminella 0.430.260.620.851.4482.97 Archaias 00.670.610.671.484.36 Siphonaperta 0.160.360.560.891.2885.65 Cymbaloporetta 0.120.430.540.761.2586.9 Laevipeneroplis 0.030.420.530.771.2288.12 M onalysidium 0.330.190.510.741.1889.29 Floresina 0.120.270.480.791.190.39 203

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Appendix VIII continued Groups C & A Average dissimilarity = 47.39 Group CGroup A SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Nonion 11.60.944.231.968.938.93 Triloculina 5.719.953.921.288.2617.19 Quinqueloculina 20.5737.813.361.137.0824.27 Affinetrina 0.716.082.992.136.330.57 B rizalina 3.640.022.742.225.7836.35 Haynesina 7.171.922.481.435.2241.58 Cribroelphidium 12.686.212.271.164.7946.36 M iliolinella 0.523.782.211.534.6651.02 Ammonia 19.9917.712.171.24.5955.61 Valvulineria 3.110.661.951.44.1259.73 Elphidium 2.210.41.691.573.5763.3 R osalina 1.610.581.441.253.0566.35 Discorbis 1.520.521.41.362.9669.31 B olivina 1.1201.391.422.9472.24 Articulina 1.170.691.181.252.574.74 Androsina 0.031.091.110.892.3577.09 Nonionoides 0.6600.951.12.0179.1 Juv Symb-Mil0.620.260.870.971.8380.93 Neoeponides 0.510.290.780.861.6582.57 Glabratella 0.550.060.740.841.5684.13 B uliminella 0.4300.580.681.2385.36 Valvulina 0.240.330.580.611.2386.59 Cibicides 0.4700.560.631.1887.77 Siphonaperta 0.160.190.490.721.0388.8 M onalysidium 0.3300.450.580.9589.75 Peneroplis 0.230.120.440.580.9390.68 204

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Appendix VIII continued Groups B-1 & A Average dissimilarity = 41.68 Group B-1Group A SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Ammonia 4.3717.713.491.838.378.37 Valvulineria 5.450.662.692.216.4514.82 Triloculina 10.7619.952.541.236.0920.92 Nonion 4.680.942.211.665.3126.22 Neoeponides 3.550.292.211.655.331.52 Articulina 3.70.691.951.414.6936.21 R osalina 2.480.581.751.714.240.4 M iliolinella 4.813.781.631.363.944.3 Cribroelphidium 4.66.211.511.353.6247.92 Haynesina 3.151.921.441.343.4651.39 Elphidium 1.940.41.421.313.4154.8 Quinqueloculina 3437.811.41.293.3558.15 B rizalina 1.270.021.381.433.3161.46 Discorbis 1.620.521.361.423.2764.73 Affinetrina 4.766.081.261.323.0367.76 Androsina 0.151.091.060.932.5570.31 Spiroloculina 0.760.0311.222.472.7 B olivina 0.8600.990.992.3775.07 Juv Sym Mil0.810.260.931.132.2477.31 Cibicides 0.7700.890.952.1579.45 Archaias 0.670.080.710.731.7181.16 Pyrgo 0.460.10.680.821.6382.79 Peneroplis 0.420.120.660.831.5984.38 Siphonaperta 0.360.190.630.861.585.89 Valvulina 0.230.330.590.731.4287.31 Laevipeneroplis 0.420.020.580.781.488.71 Cymbaloporetta 0.4300.510.631.2389.94 Glabratella 0.280.060.490.761.1991.13 205

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Appendix VIII continued Groups C & B-3 Average dissimilarity = 59.46 Group CGroup B-3 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% M iliolinella 0.5220.735.873.489.889.88 Ammonia 19.990.325.872.399.8819.75 Cribroelphidium 12.680.923.941.926.6226.37 Affinetrina 0.718.863.452.665.8132.18 Nonion 11.61.273.41.895.7237.9 Haynesina 7.170.682.841.644.7842.68 Quinqueloculina 20.5732.892.591.024.3547.04 B rizalina 3.640.132.342.063.9450.98 Archaias 02.571.991.693.3554.33 Triloculina 5.78.081.921.213.2357.55 Valvulineria 3.114.361.81.323.0360.58 Juv Symb-Mil0.622.51.661.462.7863.36 Androsina 0.032.071.561.142.6365.99 Neoeponides 0.511.771.51.62.5368.52 Valvulina 0.241.851.481.212.4971.01 Elphidium 2.210.521.441.512.4273.44 R osalina 1.612.81.41.462.3675.8 Articulina 1.172.251.351.372.2778.07 B olivina 1.1201.251.422.1180.18 Discorbis 1.521.651.231.22.0782.25 Siphonaperta 0.161.291.221.42.0584.29 Nonionoides 0.660.040.851.111.4385.73 Laevipeneroplis 0.030.70.690.711.1686.89 Peneroplis 0.230.40.691.031.1588.04 Glabratella 0.550.060.660.821.1289.16 Cibicides 0.470.040.530.670.990.06 206

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Appendix VIII continued Gropus B-1 & B-3 Average dissimilarity = 40.00 Group B-1Group B-3 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% M iliolinella 4.8120.733.431.878.588.58 Ammonia 4.370.322.191.655.4814.05 Cribroelphidium 4.60.921.791.494.4818.54 Haynesina 3.150.681.651.584.1322.67 Archaias 0.672.571.61.473.9926.66 Nonion 4.681.271.571.363.9230.58 Triloculina 10.768.081.531.333.8234.4 Androsina 0.152.071.451.153.6338.03 Affinetrina 4.768.861.431.53.5741.6 Juv Symb-Mil0.812.51.421.433.5545.15 Valvulineria 5.454.361.391.313.4648.61 Valvulina 0.231.851.321.193.351.9 Neoeponides 3.551.771.291.253.2355.14 Elphidium 1.940.521.241.293.0958.23 Articulina 3.72.251.221.083.0561.28 Quinqueloculina 3432.891.191.272.9764.25 B rizalina 1.270.131.191.382.9667.21 Discorbis 1.621.651.161.252.8970.1 Siphonaperta 0.361.291.081.342.772.8 Spiroloculina 0.760.050.91.22.2675.06 R osalina 2.482.80.91.282.2477.3 B olivina 0.8600.90.992.2479.54 Laevipeneroplis 0.420.70.820.972.0581.59 Cibicides 0.770.040.810.962.0283.61 Peneroplis 0.420.40.71.111.7685.37 Pyrgo 0.460.260.670.951.6787.04 Cymbaloporetta 0.430.060.510.721.2888.33 Floresina 0.270.130.490.811.2389.56 Nonionoides 0.360.040.460.681.1490.7 207

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Appendix VIII continued Groups A & B-3 Average dissimilarity = 45.73 Group AGroup B-3 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Ammonia 17.710.326.133.0213.4213.42 M iliolinella 3.7820.734.532.059.9223.33 Triloculina 19.958.083.151.266.8830.21 Cribroelphidium 6.210.922.721.755.9536.17 Valvulineria 0.664.362.361.495.1741.33 Archaias 0.082.572.121.624.6445.98 R osalina 0.582.81.991.794.3650.34 Juv Symb-Mil0.262.51.921.594.2154.54 Quinqueloculina 37.8132.891.751.283.8358.37 Androsina 1.092.071.631.213.5561.92 Articulina 0.692.251.61.443.4965.41 Valvulina 0.331.851.571.23.4468.86 Neoeponides 0.291.771.571.553.4472.29 Haynesina 1.920.681.481.413.2375.53 Discorbis 0.521.651.451.263.1778.7 Affinetrina 6.088.861.451.113.1781.87 Siphonaperta 0.191.291.391.433.0384.91 Nonion 0.941.271.281.392.8187.71 Elphidium 0.40.520.871.151.9189.62 Laevipeneroplis 0.020.70.760.711.6791.29 208

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Appendix VIII continued Groups C & B-2 Average dissimilarity = 54.7 GroupCGroupB-2 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Ammonia 19.990.135.572.610.1810.18 Cribroelphidium 12.681.343.441.776.2916.47 M iliolinella 0.527.432.952.795.3921.85 Nonion 11.62.192.751.745.0326.89 Neoeponides 0.515.982.722.224.9731.85 Quinqueloculina 20.5735.752.631.124.8136.66 Haynesina 7.171.452.261.54.1340.79 Triloculina 5.77.991.821.273.3344.12 Articulina 1.174.381.711.663.1347.26 Archaias 02.491.711.463.1350.39 Valvulineria 3.114.961.591.322.953.29 Affinetrina 0.712.941.521.52.7856.07 Juv Symb-Mil0.622.11.391.512.5358.6 Androsina 0.031.861.381.262.5261.13 Laevipeneroplis 0.031.71.351.312.4663.59 B rizalina 3.641.481.311.412.3965.98 Siphonaperta 0.161.491.211.362.2268.2 Valvulina 0.241.31.131.192.0770.27 R osalina 1.612.071.131.432.0672.34 Elphidium 2.212.181.021.261.8674.2 B olivina 1.120.370.971.341.7675.96 Clavulina 00.760.951.481.7377.7 Discorbis 1.521.190.921.281.6879.37 Peneroplis 0.230.80.861.171.5780.94 Pyrgo 0.190.830.841.041.5482.48 Cibicides 0.470.580.811.261.4883.96 Spiroloculina 0.20.670.791.221.4585.41 Sorites 0.120.910.790.821.4586.86 Nonionoides 0.660.210.751.141.3788.23 Glabratella 0.550.050.610.841.1189.35 B uliminella 0.430.170.570.811.0490.39 209

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Appendix VIII continued Groups B-1 & B-2 Average dissimilarity = 36.98 Group B-1Group B-2 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Ammonia 4.370.132.21.855.945.94 Cribroelphidium 4.61.341.631.454.4110.34 Triloculina 10.767.991.461.193.9414.29 Archaias 0.672.491.41.313.7918.08 Haynesina 3.151.451.331.373.5921.67 M iliolinella 4.817.431.311.393.5425.21 Androsina 0.151.861.281.263.4728.68 Nonion 4.682.191.261.313.4132.09 Quinqueloculina 3435.751.251.483.3935.48 Neoeponides 3.555.981.251.33.3838.87 Juv Symb-Mil0.812.11.161.423.1542.02 Laevipeneroplis 0.421.71.141.283.0745.09 Siphonaperta 0.361.491.091.342.9448.03 Affinetrina 4.762.941.081.312.9350.96 Elphidium 1.942.181.071.332.953.85 Valvulina 0.231.31.021.22.7656.61 Valvulineria 5.454.960.981.362.6559.26 B rizalina 1.271.480.91.312.4461.71 Clavulina 00.760.91.492.4364.14 Articulina 3.74.380.871.122.3666.5 Discorbis 1.621.190.871.342.3568.85 Pyrgo 0.460.830.821.132.2271.06 B olivina 0.860.370.811.132.1873.25 Peneroplis 0.420.80.81.222.1675.41 Cibicides 0.770.580.771.222.0977.5 Spiroloculina 0.760.670.751.262.0479.53 R osalina 2.482.070.751.222.0381.57 Sorites 0.10.910.740.832.0183.57 Nonionoides 0.360.210.530.881.4385 Cymbaloporetta 0.430.10.50.791.3586.35 Fursenkoina 0.240.30.490.751.3287.66 Floresina 0.270.150.460.821.2588.91 B uliminella 0.260.170.420.711.1590.06 210

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Appendix VIII continued Groups A & B-2 Average dissimilarity = 51.29 Group A Group B-2 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% Ammonia 17.710.135.783.3311.2711.27 Neoeponides 0.295.983.012.435.8617.13 Triloculina 19.957.992.941.255.7222.86 Valvulineria 0.664.962.361.794.6127.47 Cribroelphidium 6.211.342.341.544.5732.04 Articulina 0.694.382.161.994.236.24 Archaias 0.082.491.811.43.5239.76 M iliolinella 3.787.431.761.463.4443.2 Quinqueloculina 37.8135.751.671.373.2546.45 Juv Symb-Mil0.262.11.591.643.149.55 Affinetrina 6.082.941.581.543.0952.64 R osalina 0.582.071.531.712.9955.63 Elphidium 0.42.181.521.562.9758.6 B rizalina 0.021.481.511.672.9561.55 Laevipeneroplis 0.021.71.491.332.964.45 Nonion 0.942.191.451.412.8367.28 Androsina 1.091.861.391.272.7169.99 Siphonaperta 0.191.491.371.382.6672.65 Haynesina 1.921.451.281.362.4975.14 Valvulina 0.331.31.21.22.3577.49 Discorbis 0.521.191.121.542.1979.68 Peneroplis 0.120.80.991.151.9381.61 Clavulina 0.120.760.951.351.8583.46 Pyrgo 0.10.830.921.011.7985.25 Spiroloculina 0.030.670.911.261.7887.03 Cibicides 00.580.861.271.6888.71 Sorites 00.910.830.771.6390.34 211

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Appendix VIII continued Groups B-3 & B-2 Average dissimlarity = 36.9 Group B-3Group B-2 SpeciesAv.Abun d Av.Abun d Av.DissDiss/SDContrib%Cum.% M iliolinella 20.737.432.431.76.586.58 Affinetrina 8.862.941.921.785.2211.8 Neoeponides 1.775.981.691.434.5816.38 Triloculina 8.087.991.521.294.1320.5 Quinqueloculina 32.8935.751.491.364.0224.53 Valvulineria 4.364.961.351.293.6528.18 Androsina 2.071.861.351.313.6531.83 Elphidium 0.522.181.31.483.5235.34 B rizalina 0.131.481.291.593.538.85 Archaias 2.572.491.271.253.4342.28 Laevipeneroplis 0.71.71.261.323.4345.71 Articulina 2.254.381.221.213.349.01 Valvulina 1.851.31.21.263.2552.26 Haynesina 0.681.451.111.293.0255.28 Juv Symb-Mil2.52.11.111.39358.29 Nonion 1.272.191.081.322.9261.2 Cribroelphidium 0.921.341.061.332.8764.07 Siphonaperta 1.291.4911.332.7166.78 Discorbis 1.651.190.981.252.6569.43 R osalina 2.82.070.841.352.2871.71 Pyrgo 0.260.830.831.092.2573.96 Spiroloculina 0.050.670.831.242.2576.21 Peneroplis 0.40.80.821.272.2378.44 Clavulina 0.310.760.811.32.1980.63 Sorites 0.060.910.780.812.182.73 Cibicides 0.040.580.771.262.0984.82 B olivina 00.370.510.81.3986.21 Ammonia 0.320.130.510.871.3787.58 Planorbulina 00.330.40.621.0988.67 Neoconorbina 0.010.240.390.721.0589.73 Fursenkoina 0.030.30.370.57190.73 212

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Appendix IX Environmental data collected b y Southeast Research CenterSITESTALATLONNOXNO3NO2NH4TN Convoy Point10125.48-80.32 N=133Average0.13900.13370.00520.02640.5155 St. Error0.01700.01660.00050.00220.0203 Black Point10225.55-80.29 N=133Average0.09340.08810.00530.02740.4856 St. Error0.01280.01240.00050.00310.0165 Near Black Ledge10325.57-80.29 N=133Average0.04590.04220.00370.01870.4040 St. Error0.00760.00720.00040.00170.0127 BNP Marker C10425.60-80.22 N=133Average0.00680.00550.00130.00890.2378 St. Error0.00080.00070.00010.00050.0089 Biscayne Channel10525.65-80.19 N=33Average0.01050.00860.00190.01200.2382 St. Error0.00190.00180.00020.00080.0136 White Marker10625.63-80.13 N=33Average0.00500.00370.00130.00840.1926 St. Error0.00110.00100.00010.00070.0126 Fowey Rocks10725.59-80.10 N=33Average0.00210.00120.00080.00640.1567 St. Error0.00020.00020.00010.00080.0101 Marker G-1B10825.57-80.19 N=133Average0.00340.00250.00090.00600.2063 St. Error0.00040.00040.00000.00030.0081 Midbay North10925.56-80.24 N=133Average0.00850.00710.00140.00840.2210 St. Error0.00160.00150.00010.00060.0077 Fender Point11025.51-80.29 N=133Average0.07680.07320.00360.01960.3695 St. Error0.01020.00990.00030.00130.0148 Featherbed Bank11125.52-80.24 N=133Average0.00800.00670.00130.00990.2285 St. Error0.00160.00150.00010.00080.0081 Sands Cut11225.49-80.19 N=133Average0.00490.00400.00100.00860.2049 St. Error0.00160.00150.00010.00060.0073 213

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Appendix IX continuedSITESTALATLONNOXNO3NO2NH4TN Elliott Key11325.441667-80.22333 N=133Average0.0120.0110.0010.0200.245 St. Error0.0020.0020.0000.0010.008 Caesar Creek11425.385-80.19167 N=33Average0.0030.0020.0010.0080.184 St. Error0.0010.0000.0000.0010.011 Adams Key11525.404167-80.24083 N=33Average0.0110.0090.0020.0130.221 St. Error0.0020.0010.0000.0010.011 Rubicon Keys11625.4-80.255 N=133Average0.0140.0130.0010.0110.243 St. Error0.0020.0020.0000.0010.008 Totten Key11725.385-80.265 N=33Average0.0170.0150.0020.0200.304 St. Error0.0030.0030.0000.0030.021 Broad Creek11825.348333-80.255 N=33Average0.0100.0080.0020.0110.265 St. Error0.0020.0020.0000.0010.024 Pumpkin Key11925.318333-80.30333 N=33Average0.0250.0210.0040.0350.425 St. Error0.0040.0030.0010.0050.035 Card Sound South12025.314167-80.34333 N=33Average0.0280.0230.0040.0360.450 St. Error0.0040.0030.0010.0050.033 Card Sound North12125.355-80.29167 N=133Average0.0140.0120.0020.0140.293 St. Error0.0020.0020.0000.0010.010 West Arsenicker12225.42017-80.31083 N=133Average0.0520.0490.0030.0200.354 St. Error0.0080.0080.0000.0010.013 Pelican Bank12325.445-80.28333 N=133Average0.0410.0390.0020.0180.314 St. Error0.0040.0040.0000.0010.012 South Midbay12425.4725-80.23333 N=133Average0.0100.0090.0010.0190.267 St. Error0.0010.0010.0000.0010.013 Turkey Point12525.47-80.28333 N=33Average0.0510.0470.0040.0220.337 St. Error0.0100.0100.0000.0020.021 BNP Marker B12625.67167-80.205 N=100Average0.0120.0100.0020.0120.265 St. Error0.0020.0020.0000.0010.015 Shoal Point12725.63-80.25 N=100Average0.0160.0140.0020.0130.291 St. Error0.0030.0030.0000.0010.013 Matheson Beach12825.68833-80.23333 N=100Average0.0170.0150.0020.0120.303 St. Error0.0020.0020.0000.0010.012 Marker G-7112925.73667-80.185 214

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Appendix IX continuedSITESTALATLONNOXNO3NO2NH4TN N=100Average0.0160.0130.0020.0190.268 St. Error0.0010.0010.0000.0020.011 South Dodge Island13025.76333-80.17167 N=100Average0.0210.0180.0030.0220.262 St. Error0.0020.0020.0000.0020.012 North Venetian Basin13125.8-80.16667 N=100Average0.0250.0220.0020.0170.269 St. Error0.0020.0020.0000.0010.010 North I-195 Basin13225.81667-80.16667 Average0.0170.0150.0020.0150.280 St. Error0.0020.0020.0000.0010.011 North Normandy Isle13325.86667-80.15 N=100Average0.0290.0250.0030.0250.293 St. Error0.0030.0020.0000.0020.013 Oleta River Park13425.905-80.13333 N=100Average0.0340.0290.0050.0240.270 St. Error0.0040.0030.0010.0030.014 South Card Sound13525.31667-80.31667 N=100Average0.0150.0130.0020.0150.307 St. Error0.0020.0020.0000.0010.012 215

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Appendix IX continuedSTALATLONDINTONTPSRPAPACHLA 10125.48-80.32 Average0.16540.35040.00660.00130.37100.38 St. Error0.01850.01310.00040.00010.02710.02 10225.55-80.29 Average0.12080.36480.00680.00150.41890.37 St. Error0.01520.01280.00040.00010.02900.03 10325.57-80.29 Average0.06460.33940.00630.00130.38200.38 St. Error0.00880.01100.00040.00010.02500.05 10425.60-80.22 Average0.01570.22210.00600.00100.11340.31 St. Error0.00110.00880.00040.00010.00630.02 10525.65-80.19 Average0.02240.21580.00540.00070.07870.51 St. Error0.00230.01300.00020.00010.00440.05 10625.63-80.13 Average0.01330.17930.00570.00050.07970.62 St. Error0.00160.01250.00030.00010.00840.06 10725.59-80.10 Average0.00850.14830.00450.00050.05160.46 St. Error0.00090.01030.00020.00010.00430.05 10825.57-80.19 Average0.00940.19690.00600.00080.09560.28 St. Error0.00050.00810.00040.00010.00510.02 10925.56-80.24 Average0.01690.20410.00530.00080.12350.28 St. Error0.00190.00740.00030.00010.00610.02 11025.51-80.29 Average0.09640.27300.00580.00100.19900.30 St. Error0.01100.01040.00030.00010.01180.02 11125.52-80.24 Average0.01790.21060.00560.00080.12800.26 St. Error0.00210.00770.00030.00010.00680.02 11225.49-80.19 Average0.01350.19130.00620.00080.10590.29 St. Error0.00180.00700.00030.00010.00530.02 11325.44-80.22 Average0.03270.21270.00580.00080.14800.29 St. Error0.00230.00790.00030.00010.00780.02 11425.39-80.19 Average0.01110.17330.00540.00060.08010.42 St. Error0.00120.01180.00040.00010.00580.05 216

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Appendix IX continuedSTALATLONDINTONTPSRPAPACHLA 11525.40-80.24 Average0.02430.19630.00460.00060.11110.36 St. Error0.00220.01120.00020.00010.01150.05 11625.40-80.26 Average0.02550.21720.00590.00080.12410.31 St. Error0.00300.00790.00030.00010.00660.02 11725.39-80.27 Average0.03690.26750.00510.00070.13620.41 St. Error0.00510.01940.00020.00010.00780.05 11825.35-80.26 Average0.02100.24360.00490.00060.10940.38 St. Error0.00280.02360.00020.00010.00820.05 11925.32-80.30 Average0.05940.36580.00610.00070.21570.69 St. Error0.00860.03060.00030.00010.03580.11 12025.31-80.34 Average0.06350.38630.00650.00090.19480.62 St. Error0.00810.02880.00050.00020.02200.10 12125.36-80.29 Average0.02820.26440.00600.00080.14390.36 St. Error0.00270.00960.00030.00010.00770.03 12225.42-80.31 Average0.07210.28190.00620.00100.30990.37 St. Error0.00910.01030.00030.00010.01620.03 12325.45-80.28 Average0.05930.25480.00560.00090.16360.32 St. Error0.00480.01070.00030.00010.00740.02 12425.47-80.23 Average0.02880.23810.00510.00080.15760.28 St. Error0.00220.01240.00020.00010.00800.02 12525.47-80.28 Average0.07280.26390.00440.00090.14980.39 St. Error0.01160.01870.00020.00020.00770.06 12625.67-80.21 Average0.02350.24130.00690.00100.13360.45 St. Error0.00300.01460.00040.00010.01120.04 12725.63-80.25 Average0.02970.26170.00650.00110.16250.35 St. Error0.00400.01250.00050.00010.00990.06 12825.69-80.23 Average0.02900.27400.00680.00110.14650.58 St. Error0.00280.01200.00040.00010.01310.07 12925.74-80.19 Average0.03450.23390.00740.00110.13710.81 St. Error0.00290.01050.00040.00010.01010.07 217

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Appendix IX continuedSTALATLONDINTONTPSRPAPACHLA 13025.76-80.17 Average0.04320.21910.00790.00120.11600.93 St. Error0.00390.01030.00040.00010.00860.08 13125.80-80.17 Average0.04190.22670.00880.00130.14371.21 St. Error0.00290.00940.00040.00020.01550.10 13225.82-80.17 Average0.03200.24850.00860.00120.15971.08 St. Error0.00290.01060.00040.00010.01380.12 13325.87-80.15 Average0.05320.24030.01130.00130.24231.82 St. Error0.00480.01270.00050.00010.02310.13 13425.91-80.13 Average0.05800.21240.01050.00140.18221.67 St. Error0.00680.01170.00050.00010.01820.11 13525.32-80.32 Average0.03000.27670.00670.00120.14420.38 St. Error0.00310.01160.00040.00010.00880.03 218

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Appendix IX continuedSTALATLON 10125.48-80.32 Average St. Error 10225.55-80.29 Average St. Error 10325.57-80.29 Average St. Error 10425.60-80.22 Average St. Error 10525.65-80.19 Average St. Error 10625.63-80.13 Average St. Error 10725.59-80.10 Average St. Error 10825.57-80.19 Average St. Error 10925.56-80.24 Average St. Error 11025.51-80.29 Average St. Error 11125.52-80.24 Average St. Error 11225.49-80.19 Average St. Error 11325.44-80.22 Average St. Error 11425.39-80.19 Average St. Error TOCSi(OH)4SAL_SSAL_BTEMP_STEMP_B 4.440.1927.9129.3826.2826.35 0.110.020.570.510.360.36 4.990.3826.9127.5626.0126.01 0.100.040.540.520.380.38 4.370.2029.2329.5526.0426.05 0.110.020.460.460.360.36 2.540.0334.9334.9825.6925.69 0.070.000.180.180.350.36 2.53N/A33.6733.9526.0926.14 0.16N/A0.440.380.590.59 2.30N/A34.8535.2626.5026.50 0.18N/A0.280.200.510.51 1.81N/A35.5935.7126.7226.68 0.16N/A0.160.130.430.43 2.330.0335.3135.3525.8025.80 0.060.000.130.130.360.36 2.570.0335.1535.2825.7825.77 0.070.000.190.180.360.36 3.610.0831.1031.6726.0726.08 0.090.010.460.420.350.35 2.660.0335.3835.5325.7425.73 0.070.000.200.170.360.36 2.410.0235.6535.6525.8325.83 0.060.000.130.120.360.36 2.740.0335.2735.3925.7225.71 0.070.000.230.200.350.35 2.08N/A35.3835.4726.5226.49 0.15N/A0.190.180.580.57 219

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Appendix IX continuedSTALATLON 11525.40-80.24 Average St. Error 11625.40-80.26 Average St. Error 11725.39-80.27 Average St. Error 11825.35-80.26 Average St. Error 11925.32-80.30 Average St. Error 12025.31-80.34 Average St. Error 12125.36-80.29 Average St. Error 12225.42-80.31 Average St. Error 12325.45-80.28 Average St. Error 12425.47-80.23 Average St. Error 12525.47-80.28 Average St. Error 12625.67-80.21 Average St. Error 12725.63-80.25 Average St. Error 12825.69-80.23 Average St. Error 12925.74-80.19 Average St. Error TOCSi(OH)4SAL_SSAL_BTEMP_STEMP_B 2.47N/A34.3934.4326.2026.19 0.14N/A0.360.350.590.59 2.830.0434.7135.0125.8425.85 0.070.010.230.200.350.36 3.32N/A32.6232.6726.1526.17 0.21N/A0.590.580.600.60 2.73N/A33.9533.9526.2226.25 0.16N/A0.420.420.590.60 4.35N/A30.7731.9226.4326.54 0.18N/A0.640.490.610.65 4.80N/A29.7130.3126.5326.49 0.24N/A0.760.700.590.61 3.590.0433.1833.7325.9325.95 0.090.000.300.250.350.35 4.200.1031.2031.6525.8725.89 0.110.010.450.440.350.36 3.400.0632.8833.3425.6925.73 0.100.010.350.310.350.35 2.940.0335.1135.3125.7425.72 0.100.000.220.200.350.35 3.31N/A30.9131.5025.7625.93 0.19N/A0.750.690.610.61 3.100.1133.6934.4425.8225.70 0.090.010.310.230.410.41 3.530.1132.3733.1525.9125.84 0.100.010.400.350.410.42 3.700.1231.4432.2925.9325.83 0.080.010.340.310.420.42 3.300.2132.5733.6925.9725.95 0.080.020.290.220.380.37 220

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Appendix IX continuedSTALATLON 13025.76-80.17 Average St. Error 13125.80-80.17 Average St. Error 13225.82-80.17 Average St. Error 13325.87-80.15 Average St. Error 13425.91-80.13 Average St. Error 13525.32-80.32 Average St. Error TOCSi(OH)4SAL_SSAL_BTEMP_STEMP_B 3.270.2433.0233.7326.1926.16 0.130.030.240.210.350.35 3.460.2431.6532.2426.0926.05 0.080.020.240.230.380.38 3.890.2030.6031.1125.8225.80 0.090.010.300.290.410.41 3.800.3630.3832.6726.0626.21 0.110.030.390.230.390.40 3.520.2431.8935.1226.4026.15 0.160.020.410.130.330.30 4.300.0632.0933.2225.8125.92 0.110.010.400.330.410.42 221

PAGE 231

Appendix IX continuedSTALATLON 10125.48-80.32 Average St. Error 10225.55-80.29 Average St. Error 10325.57-80.29 Average St. Error 10425.60-80.22 Average St. Error 10525.65-80.19 Average St. Error 10625.63-80.13 Average St. Error 10725.59-80.10 Average St. Error 10825.57-80.19 Average St. Error 10925.56-80.24 Average St. Error 11025.51-80.29 Average St. Error 11125.52-80.24 Average St. Error 11225.49-80.19 Average St. Error 11325.44-80.22 Average St. Error 11425.39-80.19 Average St. Error DO_SDO_BTURBpHTN:TPN:P 6.737.070.718.18214.98561.47 0.120.150.050.0212.69134.41 6.977.130.488.29187.171158.12 0.130.140.020.0212.04625.41 6.876.930.588.24177.59302.71 0.110.120.030.0210.6852.60 6.256.301.128.17116.4873.49 0.070.080.070.028.918.69 6.216.192.05N/A102.41155.42 0.100.100.21N/A7.0144.91 6.316.321.21N/A83.23119.82 0.110.100.16N/A7.6630.56 6.366.340.50N/A90.7057.81 0.090.100.11N/A11.079.76 6.246.250.808.1899.1751.16 0.090.090.050.028.236.00 6.306.300.848.17119.7682.49 0.080.080.050.038.809.81 6.586.670.648.16166.56381.52 0.090.100.040.029.9872.00 6.186.221.088.19104.95136.69 0.080.090.170.025.9043.73 6.116.130.868.1685.22N/A 0.090.100.060.034.76N/A 6.266.270.888.21113.12202.27 0.070.070.050.026.4225.31 6.346.383.87N/A91.6671.26 0.110.110.92N/A9.5813.30 222

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Appendix IX continuedSTALATLON 11525.40-80.24 Average St. Error 11625.40-80.26 Average St. Error 11725.39-80.27 Average St. Error 11825.35-80.26 Average St. Error 11925.32-80.30 Average St. Error 12025.31-80.34 Average St. Error 12125.36-80.29 Average St. Error 12225.42-80.31 Average St. Error 12325.45-80.28 Average St. Error 12425.47-80.23 Average St. Error 12525.47-80.28 Average St. Error 12625.67-80.21 Average St. Error 12725.63-80.25 Average St. Error 12825.69-80.23 Average St. Error 12925.74-80.19 Average St. Error DO_SDO_BTURBpHTN:TPN:P 6.136.151.71N/A116.93182.09 0.140.150.23N/A8.4833.06 6.076.071.048.15112.58115.15 0.080.090.090.026.9412.57 6.346.391.26N/A134.71225.09 0.120.120.14N/A7.0855.84 6.256.262.08N/A119.83195.45 0.150.150.39N/A7.5847.18 6.476.451.10N/A159.60249.69 0.110.130.10N/A10.2349.45 6.436.391.48N/A162.46281.73 0.110.150.17N/A10.0165.32 6.226.270.668.15131.89103.91 0.080.090.040.037.8915.60 6.466.500.638.22146.96214.41 0.090.090.040.028.1028.55 6.276.270.808.16147.89292.43 0.080.080.060.028.8650.62 6.286.310.788.20141.55241.88 0.070.070.040.0310.6068.95 6.326.242.27N/A188.96249.87 0.110.111.51N/A16.2735.25 6.306.291.278.17105.2981.03 0.090.090.090.0310.1712.11 6.336.410.388.16133.41150.71 0.120.130.030.0311.6130.33 6.296.460.528.15133.74114.16 0.120.140.040.0313.5417.72 6.046.081.308.1495.68155.58 0.070.080.080.037.6524.12 223

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Appendix IX continuedSTALATLON 13025.76-80.17 Average St. Error 13125.80-80.17 Average St. Error 13225.82-80.17 Average St. Error 13325.87-80.15 Average St. Error 13425.91-80.13 Average St. Error 13525.32-80.32 Average St. Error DO_SDO_BTURBpHTN:TPN:P 6.046.061.758.1383.28301.07 0.080.080.230.036.1568.57 5.915.921.428.1174.58220.64 0.100.100.080.035.0938.96 6.236.280.858.1777.47186.66 0.130.130.060.025.1950.41 6.336.001.718.0962.24138.43 0.080.110.150.024.9422.98 6.086.041.228.1161.97179.81 0.080.080.070.024.4035.47 6.416.390.408.19121.07118.07 0.090.110.040.037.9623.12 224

PAGE 234

Appendix IX continuedSTALATLON 10125.48-80.32 Average St. Error 10225.55-80.29 Average St. Error 10325.57-80.29 Average St. Error 10425.60-80.22 Average St. Error 10525.65-80.19 Average St. Error 10625.63-80.13 Average St. Error 10725.59-80.10 Average St. Error 10825.57-80.19 Average St. Error 10925.56-80.24 Average St. Error 11025.51-80.29 Average St. Error 11125.52-80.24 Average St. Error 11225.49-80.19 Average St. Error 11325.44-80.22 Average St. Error 11425.39-80.19 Average St. Error DIN:TP%SAT_T%SAT_BSi:DIN 56.1093.9899.6220.23 5.851.582.042.42 37.3496.0098.6216.54 4.271.691.801.67 23.7896.4697.4216.12 2.701.521.581.43 6.9690.6891.4812.51 0.550.780.911.28 9.6090.2490.1922.71 0.961.051.105.50 5.5392.8693.186.13 0.641.461.320.82 4.5694.3994.061.81 0.581.281.330.23 4.2591.0491.26 0.281.151.180.00 8.4391.6691.7216.40 0.960.970.991.33 40.5093.6595.3521.47 5.731.101.242.78 8.1490.1290.7516.64 1.011.061.191.83 5.6389.4789.719.24 0.781.261.41 14.1991.1491.331.61 1.090.820.910.13 5.3993.5794.141.82 0.721.431.550.03 225

PAGE 235

Appendix IX continuedSTALATLON 11525.40-80.24 Average St. Error 11625.40-80.26 Average St. Error 11725.39-80.27 Average St. Error 11825.35-80.26 Average St. Error 11925.32-80.30 Average St. Error 12025.31-80.34 Average St. Error 12125.36-80.29 Average St. Error 12225.42-80.31 Average St. Error 12325.45-80.28 Average St. Error 12425.47-80.23 Average St. Error 12525.47-80.28 Average St. Error 12625.67-80.21 Average St. Error 12725.63-80.25 Average St. Error 12825.69-80.23 Average St. Error 12925.74-80.19 Average St. Error DIN:TP%SAT_T%SAT_BSi:DIN 12.5089.4589.713.52 1.111.801.850.38 10.6288.2388.292.49 0.881.081.160.23 15.8291.5192.321.97 1.771.561.540.06 9.6591.0391.29 1.012.131.990.00 20.8892.4892.901.54 2.561.191.530.03 21.9491.4691.211.87 2.421.251.920.15 11.3289.6190.573.74 1.020.911.070.37 26.3091.8892.672.73 3.011.061.130.21 26.1590.0890.293.55 2.340.890.980.33 13.7291.6592.044.87 1.020.870.940.57 36.4189.7789.0615.80 4.840.961.161.76 8.4590.8791.1810.53 0.971.111.111.18 11.1390.4592.014.25 1.441.501.600.35 10.8989.3092.115.30 1.161.411.810.83 11.4586.9388.115.36 1.270.891.070.47 226

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Appendix IX continuedSTALATLON 13025.76-80.17 Average St. Error 13125.80-80.17 Average St. Error 13225.82-80.17 Average St. Error 13325.87-80.15 Average St. Error 13425.91-80.13 Average St. Error 13525.32-80.32 Average St. Error DIN:TP%SAT_T%SAT_BSi:DIN 12.3187.5687.884.66 1.061.001.090.63 11.3284.5884.9511.03 0.981.191.271.55 8.0888.1589.0417.50 0.711.531.583.03 10.6889.7286.4535.57 0.951.011.406.23 12.1187.7988.8886.09 1.391.111.0633.42 11.3591.7092.2541.08 1.391.041.398.99 227

PAGE 237

228 Discammina Reophax Cyclorbiculina Hauerina Planktonic Foraminifera Cornuspira Spirolina Patellina Spirillina Sorites Neoconorbina Planorbulina Quinqueloculina Triloculina Affinetrina Miliolinella Ammonia Cribroelphidium Haynesina Nonion Neoeponides Valvulineria Articulina Rosalina Elphidium Discorbis Peneroplis Laevipeneroplis Valvulina Androsina Juvenile Symb-Miliolida Siphonaperta Archaias Pyrgo Clavulina Floresina Nonionoides Cibicides Spiroloculina Bolivina Brizalina Glabratella Monalysidium Buliminella Cymbaloporetta Robertinoides Fursenkoina 100 80 60 40 20 0 Appendix X Cluster analysis of genera present in >5% of the samples


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Carnahan, Elizabeth A.
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Foraminiferal assemblages as bioindicators of potentially toxic elements in Biscayne Bay, Florida
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by Elizabeth A. Carnahan.
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[Tampa, Fla.] :
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2005.
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Thesis (M.S.M.S.)--University of South Florida, 2005.
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Text (Electronic thesis) in PDF format.
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ABSTRACT: Heavy-metal pollution is an issue of concern in estuaries such as Biscayne Bay that are heavily influenced by agricultural, urban, and harbor activities. The goals of this study were to provide a state of the bay assessment that can be used to interpret changes that have occurred over the past 60 years in Biscayne Bay, to provide a baseline to compare changes in the ecosystems during and after execution of the Comprehensive Everglades Restorations Plan (CERP), and to determine if benthic foraminiferal assemblages in Biscayne Bay reflect heavy-metal contamination in sediments. Surficial samples were collected at 147 sites throughout the bay. Analyses included geochemical assessment of the mud fraction for 32 chemical parameters, grain-size analysis, and assessment of foraminiferal assemblages at the genus level.Geochemical analyses revealed elevated concentrations of a suite of heavy metals in the sediments of the northern bay, between Miami and Key Biscayne, and the periphery of the southern bay from Black Creek Canal south to Turkey Point. Cluster analysis, multi-dimensional scaling, and multivariate-correlation analyses revealed three distinct foraminiferal assemblages. One assemblage, characteristic of the northern bay, was defined by stress-tolerant taxa including Ammonia, Cribroelphidium, Nonion, and Haynesina, which were present in low abundances. Distribution of this assemblage correlated with the most elevated concentrations of heavy metals. The assemblage that defined the southwestern margin of the bay was dominated by Ammonia and Quinqueloculina. This assemblage is characterized by the lowest diversities and highest abundances, and is likely influenced by both reduced salinity and elevated organic-carbon concentrations.
590
Adviser: Dr. Pamela Hallock Muller.
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Estuary.
Heavy metals.
Cu.
Pb.
Hg.
Zn.
Foram index.
Benthic.
Sediments.
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Dissertations, Academic
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