Gulf of Mexico Offshore OpeatFons

Monitoring Experiment, Final Report

Phase I: Sublethal Responses to

Contaminant Exposure

96°W I:: f:7

-:

.MAI-686(2)

a

-J

Kilometers 0 25 50

Miles 0 10 25 50

U.S. Department of the Interior Minerals Management Service Gulf of Mexico OCS Region

Galveston

- *- GA-288 (5)

50 m -

MAI-622 (3)

lOOm----------------- HI-A389 (4)

- MU-A85 (1 5OQm------------ -, ----------__1-

p -

---2 c-' ---------------------,- _./-- IOOO fl---- --------- -- - 27°N

OCS Study

MMS 95-0045
Gulf of Mexico Offshore Operations

Monitoring Experiment, Final Report

Phase I: Sublethal Responses to

Contaminant Exposure

Editor

Mahion C. Kennicutt II

Prepared under MMS Contract

14-35-0001-30582

by

Texas A&M University

Texas A&M Research Foundation

College Station, Texas

Pubhshed by

U.S. Department of the Interior Minerals Management Service Gulf of Mexico OCS Region

OCS Study

MMS 95-0045

New Orleans

September 1995
DISCLAIMER

This report was prepared under contract between the Minerals Management Service (MMS) and Texas A&M University. This report has been technically reviewed by the MMS and approved for publication. Approval does not signify that the contents necessarily reflect the views and policies of the Service, nor does mention of trade names of commercial products constitute endorsement or recommendation for use. It is, however, exempt from review and compliance with MMS editorial

standards.

REPORT AVAILABILITY

Extra copies of the report may be obtained from the Public Information Unit

(Mail Stop 5034) at the following address:

U.S. Department of the Jntenor Minerals Management Service

Gulf of Mexico OCS Region Public Information Unit (MS 5034)

1201 Elmwood Park Boulevard

New Orleans, Louisiana 70 123-2394

Telephone Number: (504) 736-2519

1 -800-200-GULF

CITATION

Suggested Citation:

Kennicutt, M.C., II, ed. 1995. Gulf of Mexico Offshore Operations Monitoring Experiment, Phase I: Sublethal Responses to Contaminant Exposure. Final Report. OCS Study MMS 95-0045. U.S. Department of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New Orleans, Louisiana. 709 pp.

111
TABLE OF CONTENTS

PAGE

List of Figures xiii

List of Tables Xxxi

Acknowledgments xliii

Executive Summaiy 1

1.0 Introduction 1-1

1.1 StudySiteSelection 1-5

1.2 History of Operations at the Study Sites 1-12

V

1.2.1 Matagorda Island Area Block 686 (MAI-686)

1.2.2 Mustang Island Area Block A85 (MU-A85)

1.2.3 High Island A389 (HI-A389)-East Flower

1 - 12

1 - 12

GardenBank 1-15

2.0 Study Design and Statistical Model 2-1

2.1 Statistical Model Development - Univariate Analysis 2-2

2.1.1 TotalDesignAnalyses 2-4

2.1.2 ByPlatformAnalyses 2-5

2.1.3 ByCruiseAnalyses 2-6

2.1.4 By Cruise*Platform Analyses 2-7

2.1.5 Decomposition of Models for Trawl Data 2-8

2.2. Multivariate Analyses 2-9

2.3 The Sampling Design 2-10

2.4 Variables and Transformations Used in the Study Design 2-11

2.5 PowerAnalysis 2-18

3.0 FieldMethods 3-1

3.1 Navigation. 3-1

3.2 Hydrocasts and CTII) Profiler 3-1

3.3 Boxcoring and Trawling 3-3

3.4 Sedimentology 3-7

3.5 Sediment Samples for Contaminant Chemistry 3-7

3.6 Biological Tissue Sampling for Chemistry and

Toxicology 3-8

3.6.1 Megafauna - Invertebrates 3-8

3.6.1.1 Taxonomic Identification and Sorting 3-8

3.6.1.2 Chemistry and Toxicology 3-8
4.0

3.6.2 Megafauna - Demersal Fish 3-11

3.7 Meiofauna 3-14

3.8 Macroinfauna Community Studies 3-15

3.9 Megafauna - Invertebrate Reproductive Studies 3-16

3.9.1 Immunological Probe Development and

Incubation 3-19

3.10 Pore Water for Toxicity Testing 3-21

LaboratoryMethods 4-1

4.1 Physicochemical Measurements 4-1

4.1.1 Nutrients 4-1

4.1.2 Salinity 4-1

4.1.3 Dissolved Oxygen 4-2

4.1.4 Quality Assurance 4-2

4.2 Sedimentology 4-3

4.2.1 Grain Size 4-3

4.2.2 Mineralogy 4-5

4.2.3 Total Organic Carbon and Total Carbon 4-6

4.2.4 Redox 4-7

4.3 Conthniinant Analyses 4-7

4.3.1 Hydrocarbons 4-7

4.3.1.1 Clean Procedures 4-9

4.3.1.2 Sediment Extraction 4-9

4.3.1.3 Sediment Extract Purification 4-9

4.3.1.4 Tissue Extraction 4-10

4.3.1.5 TissueExtractPurification 4-1.0

4.3.1.6 Quantitative Determination of Aliphatic Hydrocarbons and the Unresolved Complex Mixture (UCM) - Sediment

Only 4-11

4.3.1.7 Quantitative Determination of

Polynuclear Aromatic Hydrocarbons

(PAH) - Sediments, Pore Waters, and

Tissues 4-12

4.3.1.8 QUality Control 4-16

4.3.2 Trace Metals 4-16
4.3.2.1 Sample Preparation 4-16

4.3.2.2 Sample Digestion and Anaiysis 4-17

4.3.2.3 Quality Control/Assurance Procedures 4-18

4_4 Meiofauna 4-20

44. 1 Nematode Feeding Types 4-20

4.4.2 Nematode Biomass 4-22

4.4.3 Harpacticoid Life History and Reproduction

Study 4-22

4.44 Harpacticoid Toxicity Testing 4-23

4.4.5 Diversity Analysis 4-24

4.4.6 Fish Predation on Meiofauna 4-26

4.4.7 Nematode Production Modeling 4-26.

4.5 Meiofauna Genetic Variability 4-28

4.6 Macminfauna 4-34

4.7 Megafauna - Invertebrates 4-35

4.7J Reproductive ElforL 4-35

4.7.2 luixnunological Probe 4-42

4.8 Megafauna - Demersal Fish 4.-4 5

4.8.1 Necropsies 4-46

4.8.2 Histopatbology and Splenic Macrophage

Aggregate Analysis Methods 4-46

4.8.3 Analysis of Fish Food 4-47

4.9 Detoxification 4-47

4.9.1 Crustaceans 4-47

4.9.2 Annelids 4-48

4.9.3 Molluscs 4-48

4.9.4 Fish 4-48

4.9.5 Ethoxyresorufin 0-deethylase (EROD) Assay for

Fish 4-48

4.9.6 Aryl Hydrocarbon Hydroxylase (AHH) Assay for

Fish and Invertebrates 4-49

4.9.7 Rat Hepatoma H-411E Assay 4-49

4.9.8 mRNAMethod 4-50

4.9.8.1 Isolation of RNA 4-50

4.9.8.2 Northern Blot 4-51

49.9 PAH Metabolites in Bile 4-52

4.9.10 Dosing Experiments 4-52

4.9.11 Ah Receptor Binding 4-52

.vTt:L
5.0

vi"

4.10 Pore Water Toxicity Testing 4-53

4.10.1 SeaUrchinTests 4-54

4.10.2 Tests with Meiobenthic Species 4-55

Descriptive Results 5-1

5.1 Physicochemical Characteristics of the Study Sites 5-1

5.2 Sedimentology 5-15

5.2.1 Grain Size 5-22

5.2.2 Mineralogy 5-32

5.2.3 Carbon Content 5-35

5.2.4 Redox Conditions (Eh) 5-45

5.3 Contaminants 5-45

5.3.1 Hydrocarbons in Sediments 5-52

5.3.2 Trace Metals in Sediments 5-68

5.3.3 Hydrocarbons in Fish Livers, Fish Stomach Contents, and Invertebrate Soft Tissues 5-86

534 Trace Metals in Fish Livers, Fish Stomach

Contents, and Invertebrate Soft Tissues 5-96

5.3.5 Sediment Interstitial (Pore) Water 5-96

5.4 Meiofauna 5-106

54.1 Vertical Distribution and Power 5-106

5.4.2 Community Abundance and Diversity 5-108

5.4.3 Community Structure 5-118

5.4.4 NematodeTrophicDynamics 5-126

5.4.4.1 Modeling of Nematode Trophic Dynamics 5-134

5.4.5 Predation on Meiofauna 5-141

5.4.6 Life History and Reproduction 5-144

5.4.6.1 Reproduction 5-144

5.4.6.2 Life History Characteristics 5-144

5.4.7 Genetic Variability 5-147

5.5 Macminfauna. 5-147

5.5.1 Seasonal Trends 5-153

5.5.2 Diversity 5-153

5.5.3 Abundance 5-158
6.0

ix

5.5.4 Comparison of Abundances of Numerically

Dominant Taxa 5-162

5.6 Megafauna - Invertebrates 5-173

5.6.1 CatchPerUnitEffort 5-178

5.6.2 Individual Size and Size Frequency Distributions 5-178

5.6.3 Histopathology 5-188

5.6.4 ReproductiveEffort.. 5-194

5.6.5 Male-to-Female Ratios and Percent Gravid

Females 5-196

5.6.6 Stage of Reproductive Development 5-202

5.6.6.1 Visuallnspection 5-202

5.6.6.2 HistologicalAnalysis 5-202

5.6.6.3 Immunological Probe 5-212

5.7 Megafauna-DemersalFish 5-212

5.7.1 Fish Food Analysis 5-213

5.7.2 Histopathology 5-223

5.8 Detoxification 5-224

5.8.1 AHH Activity in Invertebrates 5-229

5.8.2 EROD and AHH Activity in Fish 5-229

5.8.3 Bffiaiy PAH Metabolites in Fish 5-250

5.8.4 Rat Hepatoma H-411E J3ioassays 5-250

5.8.5 CYP1A mRNA 5-250

5.9 Sediment Porewater Toxicity Testing 5-259.

5.9.1 SeaUrchinTests 5-259

5.9.2 Tests with Meiobenthic Species 5-264

Discussion 6-1

6.1 Physicochemiczil Parameters 6-1

6.1.1 Water Temperature 6-12

6.1.2 Salinity 6-13

6.1.3 Nutrients 6-16

6.1.4 DissolvedOxygen 6-19

6.1.5 Suspended Particulate Matter 6-28

6.2 Sedimentology and Contaminant Chemistry 6-30

6.2.1 Principal Component Analysis of Sediment

and Contaminant Variables 6-33
6.2.2 Hypothesis Testing 6-35

6.2.3 Spatial and Temporal Variations in Sediment

Contaxmnants 6-47

6.2.4 Comparative Evaluation of Contaminant Levels at

the Platform Sites 6-51

6.2.4.1 Hydrocarbons 6-51

6.2.4.2 Metals 6-52

6.2.4.2.1 Comparisons with Previous Platform Monitoring Studies 6-54

6.2.4.2.2 Comparisons with Other Sedimentary Settings 6-61

6.2.4.2.3 The Potential for Biological Effects Associated with the

Observed Sediment Metal

Levels 6-66

6.3 Biological Accumulation of Contaminants in Megafauna 6-66

6.3.1 HypothesisTesting 6-69

6.3.2 Historical Comparisons of Trace Metals in Tissues 6-70

6.4 Meiofauna 6-80

6.4.1 Meiofauna.l Communities 6-82

6.4.1.1 Meiofaunal Abundance and Diversity 6-82

6.4.1.2 Meiofaunal Community Structure 6-85

6.4.1.3 Nematode Trophic Dynamics 6-100

6.4.1.4 Predation Pressure on Meiofauna 6-106

6.4.2 ReproductionandLifeHistory 6-107

6.4.2.1 Reproduction 6-108

6.4.2.2 life History Characteristics 6-109

6.4.2.3 Body Size 6-124

6.4.3 Harpacticoid Genetic Diversity 6-124

6.4.4 Relationship to Environmental Variables 6-131

6.4.4.1 Meiofauna Community Structure 6-134

6.4.4.2 Harpacticoid Life History 6-136

6.4.4.3 Harpacticoid Genetic Variability 6-140

6.5 Macminfauna. 6-141

6.5.1 Analysis of the Overall Study Design 6-145

6.5.2 Analysis by Platform Site 6-148

x
6.5.3 Macroinfauna Community Structure 6-154

6.5.4 Relationship to Environmental Parameters 6-167

6.6 Megafauna - Invertebrates 6-169

6.6.1 Catch Per Unit Effort (CPUE) 6-171

6.6.2 Size-Frequency Distributions 6-173

6.6.3 Histopathology 6-176

6.6.4 ReproductiveEffoit 6-180

6.6.5 Male-to-Female Ratios and Percent Gravid Females 6-181

6.6.6 Stage of Reproductive Development 6-182

6.6.7 Histopathology and Stage of Reproductive

Development 6-188

6.7 Megafauna-DemersalFish 6-190

6.8 Detoxification 6-193

6.8.1 AHH Activity in Invertebrates 6.8.2 EROD and AHH Activity in Fish

6.8.3 Biliary PAH Metabolites in Fish 6.8.4 Rat Hepatoma H4IIE Bioassays 6.8.5 CYPIAmRNALeveIs

6.8.6 Dosing Experiments

6.9 Pore Water Toxicity 6-209

7.0 Summary, Conclusions, and Recommendations 7-1

7.1 Summary of Major Programmatic Results 7-1

7.1.1 Summary of the Abiotic Setting 7-1

7.1.2 Summary of Meiofaunal Studies 7-2

7.1.3 Summary of Macroinfaunal Studies 7-4

7.1.4 Summary of Megafauna Studies 7-5

7.1.5 Summary of Detoxification Studies 7-6

7.1.6 Summary of Porewater Toxicity Studies 7-9

7.2 Assessment of Benthic-Based Indicators of Biological

Response 7-11

7.2.1 Confounding of Environmental Variables 7-11

7.2.2 Sediment Quality Triad Approach to Integration

of Results 7-22

7.2.3 Utility of Higher Taxonomic Levels 7-31

7.3 Megafaunal, Epibenthic Organisms as Indicators of

Biological Response 7-47

7.4 Testing the Generality of the Observed Patterns 7-48

7.5 Heterogeneity of Variance as an Impact Response 7-51

6-195

6-197

6-200

6-202

6-203

6-204

xi
76 Genetic Variabffity as a Measure of Impact 7-54

7.7 Recommendations for Future Studies 7-54

8.0 Literature Cited 8-1

xii
LIST OF FIGURES

Figure Page

1 Location of the original five study sites sampled on Cruise 1 4

1.1 Program organizational chart 1-2

1.2 Location of the original five study sites sampled on Cruise 1 1-6

1.3 Frequency distribution of total unresolved complex mixture

(UCM, ppm), total alkanes (C10-C34, ppb) and total

polycyclic aromatics (PAH, ppb) concentrations in

sediments for Cruise 1 1-9

1.4 Distribution of barium concentrations (ppm) in sediments

from Cruise 1 by radii and distance from the platform 1-10

1.5 Monthly production of condensate, gas, and water at MAJ686 1-14

1.6 Monthly production of condensate, gas, and water at MUA85 1-17

1.7 Monthly production of condensate, gas, and water at HIA389 1-18

2.1 Summary of boxcorer and trawl locations at MAT-686 for Cruises 1 (January 1993), 2 (June 1993), 3 (January 1994), and 4 (June 1994) 2-12

2.2 Summary of boxcorer and trawl locations at MU-A85 for Cruises 1 (January 1993), 2 (June 1993), 3 (January 1994), and 4 (June 1994) 2-14

2.3 Summary of boxcorer and trawl locations at HI-A389 for Cruises 1 (January 1993), 2 (June 1993), 3 (January 1994), and 4 (June 1994) 2-16

3.1 Activities at each quantitative boxcoring station including

sampling protocols for water column and boxcore samples 3-2

3.2 Boxcore ifiustrating 'Tvegematic" partitioning 3-5

3.3 Sample processing protocol for trawl collections 3-6

3.4 Sample processing protocol for megafaunal invertebrates

from trawls 3-9
3.5 Sample processing protocol for megafaunal invertebrate and demersal fish tissues for contaminant chemistry and

toxicology 3-10

3.6 Sample processing protocol for fish taken from trawis 3-12

3.7 Megafaunal invertebrate life history sampling protocol 3-20

4.1 Summary of hydrocarbon analytical protocols 4-8

4.2 The model for predicting platform effects on depositfeeding nematode standing stock 4-27

5.1 Summary of the temperatures (°C) and saJinities for surface, mid-, and bottom waters at MAI-686 for Cruises 1 and 4 5-8

5.2 Summary of dissolved oxygen concentrations (mL/L) for surface, mid-, and bottom waters at MAI-686 for all cruises 5-10

5.3 Relationship between oxygen and nutrient concentrations at MAI-686 for all cruises 5-11

5.4 Summary of the temperatures (°C) and salinities for surface, mid-, and bottom waters at MU-A85 for Cruises 1 and 2 5-12

5.5 Salinity values for surface, mid-, and bottom waters at MUA85forCruise3 5-13

5.6 Summary of dissolved oxygen concentrations (mL/L) for surface, mid-, and bottom waters at MU-A85 for all cruises 5-14

5.7 Summary of nitrate (p.M) concentrations for surface, mid-, and bottom waters at MU-A85 for all cruises 5-16

5.8 Relationship between oxygen and nutrient concentrations at MU-A85 for all cruises 5-17

5.9 Summary of the temperatures (°C) and salinities for surface, mid, and bottom waters at HI-A389 for Cruises 1 and 2 5-18

5.10 Summary of dissolved oxygen concentrations (mL/L) for surface, mid-, and bottom waters at HI-A389 for Cruise 2 5-19

5.11 Summary of phosphate and nitrate concentrations QiM) for surface, mid-, and bottom waters at HI-A389 for Cruise 2 5-20

5.12 Relationship between oxygen and nutrient concentrations at

HI-A389 for all cruises 5-21

xiv
5.13 Summary of sediment grain size at MAI-686 by distance

from the platform 5-23

5.14 Summary of sediment grain size at MU-A85 by distance

from the platform 5-24

5.15 Summary of sediment grain size at HI-A389 by distance

from the platform 5-25

5.16 Variability in mean sand content (%) with distance from the

platform by cruise at MAI-686 5-26

5.17 Areal distribution of mean sand content (%) as a composite

of all four cruises 5-28

5.18 Variability in mean sand content (%) with distance from the

platform by cruise at MIJ-A85 5-29

5.19 Variability in mean sand content (%) with distance from the platform by cruise at HI-A389 5-30

5.20 X-ray diffractograms of sediments from the study area 5-33

5.21 Variability in mean total organic carbon content (%) in

sediments with distance from the platform by cruise at MAJ686 5-36

5.22 Areal distribution of mean total organic carbon content (%) as a composite of all four cruises 5-37

5.23 Variability in mean total organic carbon content (%) in

sediments with distance from the platform by cruise at MUASS 5-38

5.24 Variability in mean total organic carbon content (%) in

sediments with distance from the platform by cruise at HIA389 5-39

5.25 Relationship between sand and total organic carbon content (%) in sediments at all sites for all cruises 5-40

5.26 Variability in mean total inorganic carbon content (%) in

sediments with distance from the platform by cruise at MAI686 5-41

5.27 Areal distribution of mean total inorganic carbon content (%) as a composite of all four cruises 5-42
5.28 Variability in mean total inorganic carbon content (%) in

sediments with distance from the platform by cruise at MUA85 5-43

5.29 Variability in mean total inorganic carbon content (%) in

sediments with distance from the platform by cruise at HIA389 5-44

5.30 Relationship between sand and total inorganic carbon

content (%) in sediments at all sites for all cruises 5-46

5.31 Relationship between organic and inorganic carbon content (%) in sediments at all sites for all cruises 5-47

5.32 Variability in mean redox potential (mV) in sediments with

distance from the platform by cruise at MAI-686 5-48

5.33 Meal distribution of mean redox potential (mV) as a

composite of all four cruises 5-49

5.34 Variability in mean redox potential (my) in sediments with

distance from the platform by cruise at MU-A85 5-50

5.35 Variability in mean redox potential (mV) in sediments with

distance from the platform by cruise at HI-A389 5-51

5.36 Variability in mean total PAH concentrations (ppb) in

sediments with distance from the platform by cruise at MAT686 5-53

5.37 Variability in mean total PAH concentrations (ppb) in

sediments with distance from the platform by cruise at MUA85 5-54

5.38 Variability in mean total PAH concentrations (ppb) in

sediments with distance from the platform by cruise at HIA389 5-55

5.39 Variability in mean total alkane concentrations (ppb) in

sediments with distance from the platform by cruise at MAT686 5-56

5.40 Variability in mean total alkane concentrations (ppb) in

sediments with distance from the platform by cruise at MUA85 5-57

5.41 Variability in mean total alkane concentrations (ppb) in

sediments with distance from the platform by cruise at HIA389 5-58
5.42 Variability in mean total UCM concentrations (ppm) in

sediments with distance from the platform by cruise at MAI686 5-59

5.43 Variability in mean total UCM concentrations (ppm) in

sediments with distance from the platform by cruise at MUASS 5-60

5.44 Variability in mean total UCM concentrations (ppm) in

sediments with distance from the platform by cruise at HIA389 5-61

5.45 Meal distribution of mean total PAH concentrations (ppb) in

sediments as a composite of all four cruises 5-62

5.46 Meal distribution of mean total aliphatic hydrocarbon

concentrations (ppb) in sediments as a composite of all four cruises 5-63

5.47 Meal distribution of mean total UCM concentrations (ppm)

in sediments as a composite of all four cruises 5-64

5.48 Gas chromatograms (flame ionization detection) of sediment

extracts from MAI-686 5-65

5.49 Gas chromatograms (flame ionization detection) of sediment

extracts from Fll-A389 5-66

5.50 Gas chromatograms (flame ionization detection) of sediment extracts from MU-A85 5-67

5.51 Variability in mean iron concentrations (ppm) in sediments with distance from the platform by cruise at MAI-686 5-70

5.52 Variability in mean iron concentrations (ppm) in sediments with distance from the platform by cruise at MU-A85 5-71

5.53 Variability in mean iron concentrations (ppm) in sediments with distance from the platform by cruise at HI-A389 5-72

5.54 Variability in mean aluminum concentrations (ppm) in

sediments with distance from the platform by cruise at MAI686 5-73

5.55 Variability in mean aluminum concentrations (ppm) in

sediments with distance from the platform by cruise at MUA85 5-74
5.56 Variability in mean aluminum concentrations (ppm) in

sediments with distance from the platform by cruise at HIA389 5-75

5.57 Variability in mean barium concentrations (ppm) in

sediments with distance from the platform by cruise at MA!-

686 5-76

5.58 Variability in mean barium concentrations (ppm) in

sediments with distance from the platform by cruise at MUA85 5-77

5.59 Variability in mean barium concentrations (ppm) in

sediments with distance from the platform by cruise at HIA389 5-78

5.60 Variability in mean cadmium concentrations (ppm) in

sediments with distance from the platform by cruise at MAT686 5-79

5.61 Variability in mean cadmium concentrations (ppm) in

sediments with distance from the platform by cruise at MUASS 5-80

5.62 Variability in mean cadmium concentrations (ppm) in

sediments with distance from the platform by cruise at HIA389 5-81

5.63 Areal distribution of mean iron concentrations (ppm) in

sediments as a composite of all four cruises 5-82

5.64 Areal distribution of mean aluminum concentrations (ppm)

in sediments as a composite of all four cruises 5-83

5.65 Area! distribution of mean barium concentrations (ppm) in

sediments as a composite of all four cruises 5-84

5.66 Area! distribution of mean cadmium concentrations (ppm)

in sediments as a composite for all four cruises 5-85

5.67 Correlation between mercury (Hg) and barium (Ba) concentrations in sediments at all sites for all cruises 5-88

5.68 Correlation between cadmium (Cd) and barium (Ba) concentrations in sediments at all sites for all cruises 5-89

5.69 Correlation between lead (Pb) and barium (Ba)

concentrations in sediments at all sites for all cruises 5-90
5.70 Correlation between zinc (Zn) and barium (Ba)

concentrations in sediments at all sites for all cruises 5-91

5.71 Correlation between copper (Cu) and barium (Ba)

concentrations in sediments at all sites for all cruises 5-92

5.72 Variability of mean total PAH concentrations (ppb) in tissues by type, cruise, and distance from the platform at MAI-686 5-93

5.73 Variability of mean total PAH concentrations (ppb) in tissues by type, cruise, and distance from the platform at MU-A85 5-94

5.74 Variability of mean total PAM concentrations (ppb) in tissues by type, cruise, and distance from the platform at HI-A389 5-95

5.75 Summary of mean metal concentrations in fish liver tissues

at MAT-686 as a composite of all four cruises 5-97

5.76 Summary of mean metal concentrations in fish liver tissues

at MU-A85 as a composite of all four cruises 5-98

5.77 Summary of mean metal concentrations in fish liver tissues

at HI-A389 as a composite of all four cruises 5.-99

5.78 Summary of mean metal concentrations in invertebrate soft

tissues at MAI-686 as a composite of all four cruises 5-100

5.79 Summary of mean metal concentrations in invertebrate soft

tissues at MIJ-A85 as a composite of all four cruises 5-101

5.80 Summary of mean metal concentrations in invertebrate soft

tissues at HI-A389 as a composite of all four cruises 5-102

5.81 Summary of mean metal concentrations in fish stomach

contents at MAT-686 as a composite of all four cruises 5-103

5.82 Summary of mean metal concentrations in fish stomach

contents at MU-A85 as a composite of all four cruises 5-104

5.83 Summary of mean metal concentrations in fish stomach

contents at HI-A389 as a composite of all four cruises 5-105

5.84 Areal distribution of mean meiofauna density (ind/lO cm2)

as a composite of all four cruises 5-110

5.85 Meal distribution of mean nematode density (n x 10 cm2)

as a composite of all four cruises 5-11 1

xix
5.86 Areal distribution of mean harpacticoid density (n x 10

cm2) as a composite of all four cruises 5-112

5.87 Area! distribution of mean "other meiofauna" density

(ind/ 10 cm2) as a composite of all four cruises 5-113

5.88 Areal distribution of mean nematode biomass (mg wet

weight x 10 cm2) as a composite of all four cruises 5-114

5.89 Area! distribution of mean nematode:copepod ratio (N:C

ratio) as a composite of all four cruises 5-115

5.90 Area! distribution of mean nematode diversity (H') as a

composite of all four cruises 5-116

5.91 Areal distribution of mean harpacticoid diversity (H') as a

composite of all four cruises 5-117

5.92 Composition of feeding groups based on the mean numbers of individuals for the nematode community at MAT-686 by

distance from the platform 5-128

5.93 Composition of feeding groups based on the mean biomass

for the nematode community at MAI-686 by distance from

the platform 5-129

5.94 Composition of feeding groups based on the mean numbers of individuals for the nematode community at MU-A85 by

distance from the platform 5-130

5.95 Composition of feeding groups based on the mean biomass

for the nematode community at MU-A85 by distance from

the platform 5-131

5.96 Composition of feeding groups based on the mean numbers of individuals for the nematode community at HI-A389 by

distance from the platform 5-132

5.97 Composition of feeding groups based on the mean biomass

for the nematode community at HI-A389 by distance from

the platform 5-133

5.98 Average predicted production for the meiofaunal community

at MAI-686 over the timeframe of the study sampling

efforts 5-135

5.99 Average predicted production for the meiofaunal community

at MU-ASS over the timeframe of the study sampling efforts 5-136
5.100 Average predicted production for the meiofaunai community

at HI-A389 over the timeframe of the study sampling efforts 5-137

5.101 Average production efficiency for the meiofaunal community

at MAI-686 over the timeframe of the study sampling

efforts 5-138

5.102 Average production efficiency for the meiofaunal community

at MU-A85 over the timeframe of the study sampling efforts 5-139

5.103 Average production efficiency for the meiofaunal community

at HI-A389 over the timeframe of the study sampling efforts 5-140

5.104 Comparison of seasonal trends in mean numbers of

individuals of macroinfauna at all sites 5-155

5.105 Summary of the mean number of macroinfaunal species by

distance from the platforms 5-156

5.106 Meal distribution of the number of macroinfaunal species as a composite of all four cruises 5-157

5.107 Summary of the mean index of diversity (if) for

macroinfauna by distance from the platforms 5-159

5.108 Meal distribution of the mean index of diversity (H') for macroinfauna as a composite of all four cruises 5-160

5.109 Summary of the mean number of macroinfauna by distance

from the platforms 5-161

5.110 Areal distribution of the mean abundances of macroinfaunal

individuals as a composite of all four cruises 5-163

5.111 Summary of the mean abundances of polycbaetes by distance

from the platforms 5-164

5.112 Summary of the mean abundances of amphipods by distance

from the platforms 5-165

5.113 Summary of the mean abundances of nemerteans by

distance from the platforms 5-167

5.114 Summary of the mean abundances of bivalves by distance

from the platforms 5-168

5.115 Summary of the mean abundances of decapods by distance

from the platforms 5-169
5.116 Summary of the mean abundances of isopods by distance

from the platforms

5.117 Summary of the mean abundances of forams by distance

from the platforms

5.118 Summary of the mean abundances of ophiuroids by distance

from the platfonns

5.119 Size frequency distributions for the mollusc Amusium

pap yraceum at MU-A85

5.120 Size frequency distributions for Astropecten duplicatus at

MAJ-686

5.121 Size frequency distributions for Solenocera attantidis at MUABS

5.122 Body wet weight versus egg wet weight of Callirtectes

similis

5.123 Results of splenic macrophage aggregate analysis of fishes collected from MAI-686, MU-A85, and HI-A389 for all

cruises

5.124 Mean hepatic EROD activities in various fish species

5.125 Catalytic enzyme activities and biliary metabolite

concentrations in Ancyclopsetta dilecta.

5.126 Catalytic enzyme activities and biliary

concentrations in Ancyclopsetta quadrocellata

5.127 Catalytic enzyme activities and biliary

concentrations in Caulolatilus intermedtus

5.128

metab olite

metabolite

Catalytic enzyme activities and biliary

concentrations in Centropristis philadeiphica

metab olite

5.129 Catalytic enzyme activities and biliary metabolite

concentrations in Cyrioscion areriarws

5.130 Catalytic enzyme activities and biliary metabolite

concentrations in Cyclopsetta chiliencleni

5.131 Catalytic enzyme activities and biliary metabolite

concentrations in Lagcion rhomboides

5-170

-171

5-172

5-189

5-190

5-191

5-200

5-226

5-230

5-233

5-234

5-235

5-236

5-237

5-238

5-239
5.132 Catalytic enzyme activities and biliary metabolite

concentrations in Lutjanus camprechanus 5-240

5.133 Catalytic enzyme activities and biliary metabolite

concentrations in Ogcocephalus declivtrostris 5-241

5.134 Catalytic enzyme activities and biliary metabolite

concentrations in Paratichthys Lethostigma 5-242

5.135 Catalytic enzyme activities and biliary metabolite

concentrations iii Pontinus longispinis 5-243

5.136 Catalytic enzyme activities and biliary metabolite

concentrations in Pristipomoides aquilorwzns 5-244

5.137 Catalytic enzyme activities and biliary metabolite

concentrations in Syacium gzrnterL 5-245

5.138 Catalytic enzyme activities and biliary metabolite

concentrations in Synodus foetens 5-246

5.139 Catalytic enzyme activities and biliary metabolite

concentrations in Trichopsetta veritralis 5-247

5.140 Catalytic enzyme activities and biliary metabolite

concentrations in Urophycis spp. 5-248

5.141 Correlation between EROD and AHH activities in fish

captured on Cruises 1 and 2 (excluding Lagodon

rhombotdes) 5-249

5.142 Species variations in mean biliary metabolite

concentrations 5-251

5.143 Species difference in rat hepatoma H-411E cell bioassayderived TEQ5 5-252

5.144 TEQs derived from rat bepatoma H-411E cells dosed with Trachypenaeus simitis extracts 5-253

5.145 TEQ5 derived from rat hepatoma H-411E cells dosed with

Solenocera atlantidis extracts 5-254

5.146 TEQs derived from rat hepatoma H-411E cells dosed with

&uil1aernpusa extracts 5-255

5.147 TEQs derived from rat hepatoma H-411E cells dosed with

CalLinectes simiLis extracts 5-256
5.148 TEQs derived from rat hepatoma H-411E cells dosed with

Penaeus azt is extracts 5-257

5.149 Northern blot analysis of CYP1A mRNA in A: marine fish; and B: lizard fish from near and far stations 5-2 58

5.150 Summary of sea urchin embryological development and

fertilization porewater toxicity tests for sediments from

Cruise 1 5-260

5.151 Summary of sea urchin embryological development porewater toxicity tests for sediments from Cruise 2 5-262

6.1 Relationship between ChemPC 1 and ChemPC2 for sediment contaminant data coded by distance and grouped by site 6-36

6.2 Distribution of barium concentrations (ppm) with depth in

the sediment colunm at all three sites 6-50

6.3 Comparison of sediment PAH concentrations at GOOMEX

sites to the NOAA-National Status & Trends and EPA

Environmental Monitoring and Assessment (EMAP)

databases for coastal Gulf of Mexico sites 6-53

6.4 Relationship between sediment iron concentrations and A: aluminum concentrations; and B: distance from the platform

at MAI-686 at two samples 14 years apart 6-56

6.5 Relationship between sediment barium and lead

concentrations and distance from the platform at MAI-686

at two samplings 14 years apart. 6-57

6.6 Relationship between barium concentrations in sediment collected immediately (HI-A34 1, V-32 1, HI-A384) and 5- 10 years after (MU-A85, HI-A389) cessation of drilling

activilies 6-58

6.7 Relationship between lead concentrations in sediment collected immediately (HI-A341, V-321) and 5-10 years after (MU-A85, HI-A389) cessation of driUing activities 6-60

6.8 Relationship between nickel and cadmium concentrations and aluminum concentrations in sediments from HI-A389,

MU-A85, and EMAP-NC coastal samplings 6-62

6.9 Relationship between lead and zinc concentrations and

aluminum concentrations in sediments from HI-A389, MUA85, and EMAP-NC coastal samplings 6-63
6.10 Relationship between mercury and aluminum

concentrations in sediments from HI-A389 and EMAP-NC

coastal samplings 6-64

6.11 Relationship between iron and chromium concentrations and aluminum concentrations in sediments from HI-A389,

MU.-A85, and EMAP-NC coastal samplings 6-65

6.12 Comparison of the ranges of selected trace metal concentrations in sediments from the GOOMEX study sites, EMAP-NC data, and Long and Morgan (1990) 10 % and

50 % biological effects threshold 6-67

6.13 Percent of samples from the GOOMEX sites that exceeded

the Long and Morgan (1990) A: 50 % and B: 10 % bioeffects

criteria 6-68

6.14 Comparison of STOCS and GOOMEX organism trace metal data in Li4f anus campechanus (Red Snapper) liver tissue 6-74

6.15 Comparison of STOCS and GOOMEX organism trace metal data for Piistipomokles aquilonaiis (Wenchman) liver tissue 6-75

6.16 Comparison of STOCS and GOOMEX organism trace metal data for Squitla empusa (Mantis Shrimp) soft tissue 6-77

6.17 Comparison of STOCS and GOOMEX organism trace metal

data for fish liver tissue 6-78

6.18 Comparison of STOCS and GOOMEX organism trace metal

data for shrimp soft tissues 6-79

6.19 Principal components analysis (PCA) of harpacticoid species

for entire sampling design by platform 6-92

6.20 Principal components analysis (PCA) of nematode species

for entire sampling design by platform 6-93

6.21 Principal components analysis (PCA) of harpacticoid species

at MAI-686 by distance from the platform 6-94

6.22 Principal components analysis (PCA) of harpacticoid species

at MU-A85 by distance from the platform 6-95

6.23 Principal components analysis (PCA) of harpacticoid species

at HI-A389 by distance from the platform 6-96

6.24 Principal components analysis (PCA) of nematode species at

MAT-686 by distance from the platform 6-97
6.25 Principal components analysis (PCA) of nematode species at MU-A85 by distance from the platform 6-98

6.26 Principal components analysis (PCA) of nematode species at

HI-A389 by distance from the platform 6-99

6.27 Mean reproductive effort among all cruises, platforms, and

three species 6-110

6.28 Average clutch size among all cruises, platforms, and three

species 6-111

6.29 Harpacticoid life history stages mean density (n x core-1) for

all platforms, cruises, stations, and species 6-113

6.30 Harpacticoid life history stage density (n x core-') for all cruises, stations, and species at MAI-686 6-115

6.31 Harpacticoid life history stage density (n x core-1) for all

cruises, stations, and species at MU-A85 6-116

6.32 Harpacticoid life history stage density (n x core-1) for all

cruises, stations, and species at HI-A389 6-117

6.33 Harpacticoid life history percent composition for all

platforms, stations, and species 6-118

6.34 Harpacticoid life history stage percent composition for all cruises, stations, and species at MAI-686 6-119

6.35 Harpacticoid life history stage percent composition for all cruises, stations, and species at MU-A85 6-120

6.36 Harpacticoid life history stage percent composition for all cruises, stations, and species at HI-A389 6-121

6.37 Mean density (n x core-i) of gravid barpacticoid females for

all platforms, stations and species 6-122

6.38 Mean body lengths (jtm) of Longipedia americana, weighted

for sexual differences, at all platforms and stations 6-125

6.39 Mean body lengths (pm) of Diathrodes sp., weighted for

sexual differences, at all platforms and stations 6-126
6.40 Mean body lengths (tim) of Cletodes pseudodissimitis, weighted for sexual differences for all platforms and

stations 6-127

6.41 Genetic variability of harpacticoid copepods by species for all platforms and cruises 6-130

6.42 Genetic variability of harpacticoid copepods by platform for

all species and cruises 6-132

6.43 Genetic variability of harpacticoid copepods by cruise for all

species and platforms 6-133

6.44 Relationship between haplotype diversity for all species, platforms, and cruises and the environmental variables PCi (ChemPCl) by distance from the platform 6-142

6.45 PCA of total macroinfauna species community structure by

platform 6-155

6.46 PCA of total macroinfauna species community structure at

MAI-686 6-156

6.47 PCA of total macroinfauna species community structure at

MU-A85 6-157

648 PCA of total macroinfauna species community structure at

HI-A389 6-158

6.49 PCA of amphipod species community structure by platform 6-159

6.50 PCA of amphipod species community structure at MAI-686 6-160

6.51 PCA of amphipod species community structure at MU-A85 6-16 1

6.52 PCA of amphipod species community structure at HI-A389 6-162

6.53 PCA of polychacte species community structure by platform 6-163

6.54 PCA of polychaete species community structure at MAT-686 6-164

6.55 PCA of polychaete species community structure at MU-A85 6-165

6.56 PCA of polycbaete species community structure at HI-A389 6-166

657 Average GSI of P. spinicarpus at MU-A85 and HI-A389 6-187

6.58 Biomarkers used in GOOMEX 6-196
6.59 Molecular mechanism of action of TCDD and related PAHs

and HAHs 6-205

6.60 Ah receptor proffle in Syrtodusfoetens (lizard fish) 6-206

6.61 Ah receptor profile in Lagodort rhomboides (pin fish) 6-207

6.62 Whole sediment A: zinc; and B: lead concentrations and pore water toxicity at HI-A389 6-212

6.63 Whole sediment A: cadmium; and 13: barium concentrations

and pore water toxicity at HI-A389 6-2 13

6.64 Whole sediment total PAH concentrations and pore water

toxicity at HI-A389 6-214

7.1 Correlation between total PAH concentrations in sediments

and hepatic EROD activities in fish 7-7

7.2 Significance of the relationships between SQT components 7-25

7.3 Relationship between the first two principal components of

the meiofauna abundance data and the environmental

variables PCi 727

7.4 Relationship between the first two principai components of

the macroinfauna abundance data and the environmental

variables Pci 7-28

7.5 Relationship between survivability in the sea urchin embryo

pore water assays (MDEVEL) and the environmental variable

PCi (ChemPCi) 7-30

7.6 Comparison of PCA at the species and family levels for

harpacticoid families for all platforms 7-35

7.7 Comparison of PCA at the species and family levels for nematode families for all platforms 7-36

7.8 Comparison of PCA at the species and family levels for harpacticoid families at MAI-686 7-37

7.9 Comparison of PCA at the species and family levels for harpacticoid families at MU-A85 7-38

7.10 Comparison of PCA at the species and family levels for

harpacticoid families at l-JJ-A389 7-39
7.11 Comparison of PCA at the species and family levels for nematode families at MAI-686 7-40

7.12 Comparison of PCA at the species and family levels for

nexnatode families at MU-A85 7-41

7.13 Comparison of PCA at the species and family levels for

nematode families at HI-A389 7-42

7.14 Comparison of PCA at the species and family levels for macrotofauna families for all platforms 7-43

7.15 Comparison of PCA at the species and family levels for macroirifauna families for MAI-686 7-44

7.16 Comparison of PCA at the species and family levels for macroinfauna families at MU-A85 7-45

7.17 Comparison of PCA at the species and family levels for macroinfauna families at HI-A389 7-46

7.18 Median variance of selected variables between subcores

within a boxcore by distance from the platform 7-53
LIST OF TABLES

Table Page

1 Summaxy of GOOMEX Phase I Work Elements 2

2 Summary of recommendations for further study at platform

sites 16

1.1 Summary of GOOMEX Phase I Work Elements 1-3

1.2 Summary of significant Spearman correlations in sediment

Irace element data from Cruise 1 1-12

1.3 Summary of the drilling history and associated discharges at

the Matagorda Island Block 686 site through 1980 1-13

1.4 A summary of drilling discharges form the first six wells at

Mustang Island Block A-85 1-16

2.1 Different analysis categories for different subsets to examine

the total design and interactions within the design 2-3

2.2 ANOVA table for total design analysis 2-5

2.3 ANOVA table for by platform analysis 2-6

2.4 ANOVA table for by cruise analyses 2-6

2.5 ANOVA table for by cruise-platform analyses 2-8

2.6 Partial list of variables being used in the GOOMEX study 2-18

2.7 Variance components analysis for boxcore data 2-20

2.8 Power analysis for boxcore data based on two replicate

subcores from two boxcores taken at two stations at all five

platforms during the first cruise 2-22

3.1 Visual reproductive development for female shrimp 3-18

3.2 Visual reproductive development for female crabs 3-18

4.1 Analytical conditions for aliphatic hydrocarbon analysis 4-13

4.2 Aliphatic hydrocarbons (AH) of interest 4-13
4.3 Target polycyclic aromatic hydrocarbon analytes 4-14

4.4 Trace element analytical methodologies by matrix 4-17

4.5 Major meiofauna taxonomic categories 4-21

4.6 Formulas used in the model for predicting platform effects on deposit-feeding nematode standing stock 4-29

4.7 The best fit parameters of model for platform HI-A389 after

6,000 calibrating rux 4-30

4.8 Parameters of model for platform MAT-686 4-31

4.9 Parameters of model for platform MU-A85 4-32

4.10 A standard embedding procedure for histological analysis 4-37

4.11 Standard hematoxylin-eosin procedure to stain slides 4-38

4.12 Histological reproductive development scale for crabs 4-39

4.13 Histological reproductive development scale for shrimp 4-40

4.14 Histological reproductive development stages for scallops 4-41

4.15 Histological reproductive development stages for starfish

and stomatopods 4-42

4.16 Summary of immunization protocol 4-43

5.1 Summary of CTD and discrete bottle data measured at MAT- 686 during Cruise 1 5-2

5.2 Summary of CTh and discrete bottle data measured at MA!- 686 during Cruise 2 5-2

5.3 Summary of CTD and discrete bottle data measured at MA!- 686 during Cruise 3 5-3

5.4 Summary of CTD and discrete bottle data measured at IVIAT- 686 during Cruise 4 5-3

5.5 Summary of CTD and discrete bottle data measured at MU- A85 during Cruise 1 5-4

5.6 Summary of CTD and discrete bottle data measured at MU- A85 during Cruise 2 5-4
5.7 Summary of CTD and discrete bottle data measured at MU- A85 during Cruise 3 5-5

5.8 Summary of CTD and discrete bottle data measured at MU- A85 during Cruise 4 5-5

5.9 Summary of CTD and discrete bottle data measured at HIA389 during Cruise 1 5-6

5.10 Summary of CTD and discrete bottle data measured at HI- A389 during Cruise 2 5-6

5.11 Summary of CTD and discrete bottle data measured at HIA389 during Cruise 3 5-7

5.12 Summary of CTD and discrete bottle data measured at HI- A389 during Cruise 4 5-7

5.13 Range values of total organic carbon (TOC) and inorganic carbon (TIC) concentrations at the three sites in percent (%) carbon 5-35

5.14 Summary of the ranges in Eh potential (mV) at the three

study sites measured by platinum electrode 5-45

5.15 The ranges in metal concentrations (ppm) in surficial sediments from GOOMEX study sites 5-69

5.16 Matrix of correlation coefficients between individual metal

concentrations measured in sediments at all study sites

from all cruises 5-87

5.17 Continental shelf meiofauna densities reported in the periodic literature 5-107

5.18 Vertical distribution of meiofauna in the Gulf of Mexico 5-107

5.19 The overall average abundance and diversity for meiofauna variables at all platforms, stations, and cruises 5-109

5.20 Mean density (n x 10 cm2) for Copepoda species found at

all three platforms for all cruises 5-1 19

5.21 Mean density (n x 10 cm-2) for Nematoda species found at

all three platforms for all cruises 5-123

5.22 The overall average abundance of Nematoda feeding group

variables at the three platforms 5-127
5.23 The predicted average production (.tg WW x 10 cm2 x month-1) and production efficiency based on the long-term

model simulation of deposit feeding nematode 5-141

5.24 The number and mean lengths of fish used in stomach

contents analyses and mean number of organisms in

stomachs for fish caught during the third and fourth cruises

for all sites 5-142

5.25 The number and mean length of fish used in stomach

content analyses and the mean number of organisms in the

stomachs 5-143

5.26 Average harpacticoid reproductive effort based on

frequency, least square (LS) clutch size and least square (LS) clutch volume for all species of gravid females encountered

on all cruises 5-145

5.27 Life history stage densities for all harpacticoids 5-147

5.28 Population composition for all harpacticoids 5-147

5.29 Meiofauna genetic variability for Normanella sp. at three platforms and two cruises 5-148

5.30 Meiofauna genetic variability for Ctetodes sp. at three platforms and two cruises 5-149

5.31 Meiofauna genetic variability for Enhydrosoma peiicoense at three platforms and two cruises 5-150

5.32 Meiofauna genetic variability for Robertsonia sp. at three platforms and two cruises 5-151

5.33 Meiofauna genetic variability for Tachidiella sp. at three platforms and one cruise 5-152

5.34 Numbers of stations having unique species assemblages in

each of the three subcores collected 5-154

5.35 The number of individuals collected for each species at the Near and Far stations during Cruise 1 5-174

5.36 The number of individuals collected for each species at the Near and Far stations during Cruise 2 5-175

5.37 The number of individuals collected for each species at the

Near and Far stations during Cruise 3 5-176
5.38 The number of individuals collected for each species at the

Near and Far stations during Cruise 4 5-177

5.39 Catch per unit effort (CPUE, individuals rn-2) for each trawl

and overlapping species collected during Cruise 3 5-179

5.40 Catch per unit effort (CPUE, individuals rn-2) for each trawl

and overlapping species collected during Cruise 4 5- 181

5.41 Summary data for overlapping species collected from each

platform during Cruise 1 5-183

5:42 Summary of the numbers of individuals collected and size

range for overlapping species at each platform during Cruise

2 5-184

5.43 Summary of the numbers of individuals collected and size

range for overlapping species at each platform during Cruise

3 5-186

5.44 Summary of the numbers of individuals collected for overlapping species at each platform during Cruise 4 5- 187

5.45 Prevalence and intensity of each parasite and pathology in

the shrimp species collected during all four cruises 5-192

5.46 Prevalence and intensity of parasitism and pathologies in

the crab species collected on all four cruises 5-195

5.47 Prevalence and intensity of parasitism and pathologies of starfish and scallop tissues collected on all four GOOMEX

cruises 5-196

5.48 Maie:Female ratios for species collected at Near and Far

stations 5-197

5.49 The percent of female crabs collected that were gravid and

average wet weight (g) of the egg sacs at each site for each

cruise 5-199

5.50 Egg protein, percent water and gonadal somatic index (GSI)

for egg sacs collected from gravid female crabs 5-201

5.51 Results of visual inspection and gross dissection for the determination of stage of reproductive development in

females of shrimp and crab species collected during Cruises

2, 3. and4 5-203
5.52 Sex and stage of reproductive development for overlapping

species collected at each platform for histological examination during Cruise 2 5-206

5.53 Sex and stage of reproductive development for overlapping

species collected at each platform for histological examination during Cruise 3 5-208

5.54 Sex and stage of reproductive development for overlapping

species collected at each platform for histological examination during Cruise 4 5-210

5.55 Summary data for immunological probe results for non- gravidfemalecmbs 5-213

5.56 Fish species employed (x) in the food analyses during all four cruises and showing the cruise number and collecting

sites represented by each species 5-214

5.57 Results of stomach food analyses from Cruise 1 fish 5-216

5.58 Results of stomach food analyses from Cruise 2 fish 5-217

5.59 Results of stomach food analyses for Cruise 3 fish 5-218

5.60 Results of stomach food analyses for Cruise 4 fish 5-219

5.61 Results of Chi-Square comparisons of the food of fishes

taken at Near and Far stations for sites on each of the four

cruises 5-220

5.62 Pathological abnormalities in liver and spleen 5-225

5.63 Fish species captured at both Near and Far stations of at

least one platform 5-227

5.64 Invertebrate species captured at both Near and Far stations of at least one platform 5-228

5.65 AHH activities of invertebrates collected on Cruise 1 5-228

5.66 Mean of EROD and AHH activities and mean biliary PAR metabolite concentrations for those species of fish captured

atNearandFarstations 5-231

5.67 Results of tests for three species exposed to pore water

from selected stations at FJI-A389, Cruise 1 5-265
6.1 Summary of significance of interactions for the overall study

design based on physicochemical data 6-2

6.2 Tukey!s multiple comparison test results by distance for the overall study design based on physicochemical data for

surface waters 6-3

6.3 Tukey's multiple comparison test results by distance for the overall study design based on physicochemical data for midwater 6-4

6.4 Tukey's multiple comparison test results by distance for the overall study design based on physicochemical data for

bottom waters 6-5

6.5 Tukey's multiple comparison test results by site (platform)

for the overall study design based on physicochemical data

for surface waters 6-6

6.6 Tukey's multiple comparison test results by site (platform)

for the overall study design based on physicochemical data

for mid-waters 6-7

6.7 Tukey's multiple comparison test results by site (platform)

for the overall study design based on physicochemical data

for bottom waters 6-8

6.8 Summary of the significance of interactions for

physicochemical data at MAI-686 6-9

6.9 Summary of the significance of interactions for

physicochemical data at MU-A85 6-10

6.10 Summary of the significance of interactions for

physicochemical data at Fll-A389 6-11

6.11 Tukey's multiple comparison test results at each site and water depth by distance and by cruise for temperature (°C) 6-14

6.12 Tukey's multiple comparison test results for each site and water depth by distance and cruise for salinity for the

overall study design 6-17

6.13 Tukey's multiple comparison test results for each site and water depth by distance and cruise for water column

phosphate concentrations (p.M) 6-20

6.14 Tukey's multiple comparison test results for each site and water depth by distance and cruise for nitrate (jiM) 6-22
6.15 Tukey's multiple comparison test results for each site and water depth by distance and by cruise for silicate

concentrations (pM) 6-24

6.16 Tukey's multiple comparison test results for each site and water depth by distance and cruise for dissolved 02

concentrations (mL/L) 6-26

6.17 TukeyTs multiple comparison test results for each site and water depth by distance and by cruise for transmittance

(%) 6-29

6.18 Principal Component Analysis (PCA) factor patterns for

reduced and combined sediment and contaminant variables 6-35

6.19 Summary of the significance of interactions by distance at all platforms for the overall study design based on

sedixnentology and contaminant data 6-37

6.20 Summary of the significance of interactions by platform for

the overall study design based on sedimentology and

contaminant data 6-38

6.21 Summary of the significance of distance at platforms based

on sedimentology and contaminant data 6-39

6.22 Tukey's multiple comparison test results by distance for the overall study design based on sedimentology and

contaminant data 6-41

6.23 Tukey's multiple comparison test results by platform for the overall study design based on sedimentology and

contaminant data 6-42

6.24 Tukey's multiple comparison test results by distance based

on sedimentology and contaminant data at MAI-686 6-45

6.25 Tukey's multiple comparison test results by distance based

on sedimentology and contaminant data at MU-A85 6-46

6.26 Tukey's multiple comparison test results by distance based

on sedimentology and contaminant data at HI-A389 6-48

6.27 General characteristics of the study sites 6-49

6.28 A mass balance of excess barium in sediments at the three

study sites 6-51
6.29 Summary of the significance of interactions for the overall study design based on contaminants in fish livers 6-71

6.30 Summary of the significance of interactions for the overall study design based on contaminants in fish stomach

content 6-71

6.31 Summary of the significance of interactions for the overall study design based on contaminants in invertebrate soft

tissues 6-72

6.32 Summary of the significance of interactions for different

tissue types at MAI-686 based on contaminants 6-72

6.33 Summary of the significance of interactions for different

tissue types at MU-A85 based on contaminants 6-73

6.34 Summary of the significance of interactions for different

tissue types at HI-A389 based on contaminants 6-73

6.35 Summary of the significance of interactions for the overall sample design based on meiofaunal data 6-83

6.36 Summary of tests of the main effects for overall sample

design based on meiofaurial data. 6-84

6.37 Summary of the significance of interactions by platform

based on meiofaunal data 6-84

6.38 Summary of the interpretations of interactions for analysis of variance by platform based on meiofaunal data 6-84

6.39 Tukey's multiple comparison test results by distance at MAT686 based on meiofaunal data 6-86

6.40 Tukey's multiple comparison test results by distance at MUA85 based on meiofaunal data 6-87

6.41 Tukey's multiple comparison test results by distance at HIA389 based on meiofaunal data 6-88

6.42 Tukey's multiple comparison test results by cruise at MA!-

686 based on meiofaunal data 6-89

6.43 Tukey's multiple comparison test results by cruise at MUA85 based on meiofaunal data 6-90

6.44 Tukey's multiple comparison test results by cruise at HIA389 based on meiofaunal data 6-91
6.45 Multiple analysis of variance for nematode feeding groups

for the overall study design 6-102

6.46 Multiple anaiysis of variance for nematode density by feeding

groupbyplatform 6-103

6.47 Multiple analysis of variance for nematode biomass by

feeding group by platform 6-104

6.48 Analysis of covariance on fish stomach contents 6-107

6.49 Life history stage densities for all barpacticoids 6-1 12

6.50 Life history stages for all harpacticoids by platform 6-112

6.51 Population composition for all harpacticoids 6-114

6.52 Population composition for all harpacticoids by platform 6-123

6.53 Summary of harpacticoid haplotype diversity 6-13 1

6.54 Correlation between meiofaunal variables and environmental

factors for all sites 6-135

6.55 Correlation between meiofaunal variables and environmental

factorsbysite 6-135

6.56 Correlation between nematode feeding group variables and

environmental factors for all sites 6-137

6.57 Correlation of between nematode feeding group variables and environmental factors by site 6-138

6.58 Correlation of reproduction variables with axes of the

principal component analysis (PCA) 6-138

6.59 Correlation of life history stage densities for all

harpacticoids encountered with axes from the chemistry

principal component analysis (PCA) 6-139

6.60 Correlation of body lengths with axes of principal component analysis 6-140

6.61 Summary of the significance of interactions for the overall sample design based on macroinfaunal data 6-146

6.62 Summary of tests of the main effects for overall sample design 6-146

xl
6.63 Tukeyts multiple comparison test results by distance for the overall study design based on macroinfaunal variables 6-147

6.64 Tukey's multiple comparison test results by platform for the

overall study design based on macroinfaunal variables 6-149

6.65 Summary of the significance of interaction tests by platform

based on macroinfaunal data. 6-150

6.66 Summary of the significance of main effects tests by

platform based on macroinfaunal data 6-150

6.67 TukeyTs multiple comparison test results by distance at MAT686 based on macroinfaunal data 6-151

6.68 TukeyTs multiple comparison test results by distance at MUA85 based on macroinfaunal data 6-152

6.69 TukeyTs multiple comparison test results by distance at HIA389 based on macroinfauna:1 data 6-153

6.70 Correlation between macroinfauna variables and

environmental factors for all sites 6-168

6.71 Correlation between macroinfauna variables and

environmental factors by site 6-169

6.72 Differences in catch per unit effort (CPUE) for species collected from the Near and Far Stations at each platform 6-172

6.73 Species collected at each platform that had a significant relationship between individual size and the time of

collection 6-174

6.74 Results of multiple analysis of covariance determining whether individuals are significantly larger at the Near or Far site at each platform 6-175

6.75 Results of MANCOVA analysis determining whether a

relationship exists between individual size and the cruise on

which the individual was collected 6-177

6.76 Results of histopathological analysis of tissues to determine whether a significant relationship exists between the

intensity of parasitism and the distance from the platform 6-179

6.77 Results of MANCOVA analysis to determine which species have a significant relationship between sex and distance

from the platform 6-182

xli
6.78 Results of stage of reproductive development determined

through visual inspection 6-184

6.79 Results of stage of reproductive development determined

through histological analysis 6-185

6.80 Comparisons of results of reproductive effort studies comparing visual inspection, histological analysis and

immunological probe 6-189

6.81 Results of histopathological analysis of tissues to determine

whether a relationship exists between prevalence of parasitism and stage of reproductive development 6-190

6.82 Summary of literature values for biliary metabolite

concentrations versus sediment PAH concentration 6-201

6.83 EROD activity and BaP metabolite concentrations in L. Rhomboides dosed with benzo[a]pyrene 6-208

6.84 EROD activity and BaP metabolite levels in Fundulus sp. dosedwithBaP 6-209

6.85 Summary of the significance of interactions for the overall design and by site based on pore water toxicity tests of percent successful development of sea urchin embryos 6-210

6.86 Summary of porewater toxicity testing results 6-210

7.1 EROD induction in relationship to environmental

contamination 7-8

7.2 Summary of suspected constitutive levels of EROD enzyme

activities in various species of fish 7-10

7.3 Effects of anthropogenic pollution on benthic communities

in the marine environment 7-15

7.4 Summary of correlation coefficients among SQT biological and toxicological and chemical components 7-29

7.5 Summary of heterogeneity of variance 7-52

7.6 Summary of recommendations for further study at platform

sites 7-56
ACKNOWLEDGMENTS

This report is the product of the contribution of many people. The

GOOMEX Phase I principal investigators and their associates provided input

for their work elements: Dr. Denis Wiesenburg, Mr. Frank Kelly, and Mr.

Steve Sweet-Physicochemical Studies; Dr. Richard Rezak-Sedimentology;

Drs. James Brooks, Teny Wade, B.J. Presley, and Paul Boothe-Contaminants;

Dr. Don Harper-Macroinfauna; Drs. Paul Montagna, Jian Li, Mr. Mark Lanzott

and Mr. Greg Street-Meiofauna; Dr. Eric Powell, Mr. Matt Effis, and Dr. Bess

Wilson- Orinond-Macroinvertebrates; Dr. Rezneat Darriell and Ms. Hera

Konstantinou-Demersal Fish Food Studies; Dr. John Fournie and Mr. Lee

Courtney-Fish Histopathology; Drs. Stephen SaSe, Sue McDonald, and Ms.

Kristi Willett-Detoxification Response; Dr. Scott Carr and Mr. Duane

Chapman-Pore Water Toxicity Testing; Dr. John McEachran-Fish Taxonomy;

Dr. Roger Fay-Field Logistics; Dr. Gary Wolff-Data Management; and Dr.

Roger Green-Study Design and Data Synthesis. I would also like to recognize

the advice and counsel provided by the GOOMEX Scientific Review Board,

Dr. Robert Camey, Dr. Robert Spies, Dr. Donald Boesch, and Dr. James Ray.

I would also like to acknowledge those who participated in the cruises and

made these complex operations work - Mr. Jim Campbell, Mr. Hugh Barnett,

Mr. Jim Jobling, Mr. Paul Stine, Mr. Richard Kalke, Mr. Steve Sweet, Dr. Sue

McDonald, Mr. Logan Respness, Dr. Bess Wilson-Ormond, Ms. Hera

Konstantinou, Dr. Paul Montagna, Mr. Mike Fredericks, Mr. Blake Mackan,

Ms. Tamara Davis, Mr. Roy Davis, Ms. Kate Foster-Springer, Mr. Matt Ellis,

and Mr. Shawn Powers. The land-based support by Mr. K.J. Morgan and Mr.

Bffly Boim in equipment maintenance, fabrication, and staging of cruises was

invaluable. I would also like to thank the crew and Captain of the J.W. Powell

for their support and help at sea. Secretarial, editorial, graphics and data

analysis support was provided by Ms. Debbie Paul, Ms. Helen Cyr, Mr. Dave

Martin, Mr. Neal Kirk, and Mr. Eric Owen, respectively.

Finally the MMS personnel, Dr. Pasquale Roscigno (COTR), Dr. James

Kendall and Dr. Tom Ahifeld of the MMS, and Mr. Joseph McHugh (CO) of

the NBS, have been very supportive throughout the program.
EXECUTWE SUMMARY

The Gulf of Mexico Offshore Operations Monitoring Experiment

(GOOMEX): Phase I was designed to assess the nature and extent of chronic

sublethal effects associated with the exposure of marine organisms to

contaminants at three sites of long-term offshore oil and gas exploration and

development. The findings of this experiment will be used to design further

studies that will ultimately provide a scientific basis for developing

monitoring techniques and strategies to assess environmental changes

associated with the long-term presence of offshore oil and gas platforms. A

chronic impact was defined as the cumulative effects of long duration

contaminant exposure on the endemic benthos. Long duration sites were

defined as sites where platforms had been continuously present and actively

producing for more than ten years. The most common contaminants

discharged at platforms are hydrocarbons and trace metals. The underlying

sediments were assumed to be the long-term repository for these

contaminants. Contaminant surveys described the quantity and spatial and

temporal variability of contaminants in sediments, biota, and pore waters.

Biological studies measured life history, reproductive success, reproductive

effort and assemblage composition for a variety of organisms from meiofauna

to megafauna. The induction of detoxification enzymes in megafauna was

also evaluated (Table 1).

THE STUDY DESIGN

To address the many goals of the Phase I program two related study

designs were adopted. One approach was designed to analyze benthic

sediment samples taken in a radial pattern around each platform. This

design tested the hypothesis that the benthic environment varied with

distance from a platform and whether the observed patterns covaried with

the platform-generated contaminant-field. Intensive sampling within the

near-field defined the spatial pattern of the contaminant field. The

sampling pattern included comparison with control stations by extension of

each radius beyond most detectable sedimentary contamination ( 3,000

meters). Studies included assessment of the abundance, diversity, and

community structure of meiofauna and macroinfauna; meiofaunal life history,

1
Table 1. Summary of GOOMEX Phase I Work Elements

Work Element Variables

INDEPENDENT VARIABLES - SEDIMENTS/WATER COLUMN

Physicochemical - salinity, oxygen, nutrients, light transmittance

Sedimentology - grain size, carbon content (organic and

inorganic), mineralogy, redox condition

Contaminants - hydrocarbons, metals

INDEPENDENT VARIABLES - BIOTA

Contaminants - hydrocarbons and metals in fish livers, fish

stomach contents, and invertebrate soft tissues

Physiological - percent moisture, lipid content

INDEPENDENT VARIABLES - PORE WATERS

Contaminants - hydrocarbons and trace metals

DEPENDENT VARIABLESa

Melofaunab - abundance, diversity, community structure, nematode trophic dynamics, life history and

reproduction, genetic diversity

MacroinfaunaC - abundance, diversity, and community structure

Megafauna Invertebrates - catch per unit effort, size and size frequency,

histopathology, reproductive effort, reproductive development, and detoxification

responseCi

Megafauna - Fish - fish food analysis, histopathology. and

detoxification responsee

afor the purposes of determining if there were relationships between contaminant dose and

biological responses the biological measurement were considered dependent variables.

balso pore water toxicity testingbloassays with melobenthic species.

Calso pore water toxicity testingsea urchin fertilization and embryological development

test,

ddeto,cjficafion responseAHH activity, in vitro rat hepatoma H-411E cell assays.

edetoxification responseEROD and AHH activity, biliaiy PMI metabolites, CYP1A mRNA

levels, laboratory dosing experiments.

2
reproduction, and genetic diversity; contaminant distributions in sediments

and pore waters; and testing of pore water toxicity by bioassay (Table 1).

The sampling technique of choice for this design was the boxcorer.

A second approach provided for Near- (impacted) and Far-

(unimpacted) field, pairwise comparisons of suspected indicators of

exposure. These studies included assessment of community health based on

megafaunal invertebrate life history and reproduction studies, histopathology

of invertebrates and fish, contaminant distributions in invertebrate and fish

tissues, the presence and intensity of detoxification responses in fish, and in

vitro toxicological assessment of contaminants in invertebrates by bioassay

(Table 1). The sampling technique of choice for this design was the otter

trawl.

SUMMARY OF STUDY RESULTh AND CONCLUSIONS

Study sites were chosen based on a set of criteria that included active

oil and/or gas development and production activities for more than ten

years, a location outside of the influence of the Mississippi River plume, the

availability of appropriate controls, availability of previous data, and

confirmed contaminant gradients. The study sites were not chosen to be

typical or representative of platforms in general and the number of study

sites was not sufficient to allow for conclusions about platform attributes or

discharge histories. Two of the sites (HI-A389 and MU-A85) are somewhat

unusual in that platform discharges were shunted near to the seabottom due

to adjacent topographic features. Therefore, extrapolation of conclusions to

platforms other than those studied should be done with caution.

The program consisted of four field activities over a one and one-half

year period (January 1993 to June 1994). Initially, five study sites were

sampled with a reduction to the three most suitable sites for long-term

study after a screening cruise (Figure 1). The final sites were selected

primarily on the basis of confirming evidence of a contaminant gradient and

were MAI-686, MU-A85, and HI-A389. The three sites are situated in the

northwestern Gulf of Mexico in water depths from 29 to 125 m.

3
// ... MAI-686 (2) a Miles 0 10 25 50 - Kilometers 0 25 50 A-288 (5) .2OOm ................ 250rn ':7 HI-A38

J. MAI-622 (3) Figure 1. Location of the original five study sites sampled on Cruise 1.
PHYSICOCHEMIC.AL

In general. the physicochemical properties of the water column were

unaffected by the presence of platforms. For example, salinity and

temperature were controlled by regional phenomenon unrelated to the

platform. An exception was the nutrient and oxygen content of bottom

waters close to two of the platforms. Changes in bottom water oxygen and

nutrient levels were observed. The development of bottom water hypoxia

near a platform occurred when the water column was highly stratified.

In summary,

Platforms had little effect on most ambient water properties.

Hypoxia in the summer was observed near the platforms at MAI-686

and M1J-A85 and occurred during periods of highly-stratified water

columns.

Nutrient regeneration (i.e., NO3, PO4, SiO3) co-occurred with the

hypoxic events.

Water depth and time of year exerted the greatest effect on water

column physicochemical properties.

SEDIMENTOLOGY

Sediment texture was strongly correlated with distance from the

platform with sediments close to the platform highly enriched in sand.

Based on visual expmination and chemical analysis, most of the increase in

sand content appeared to be related to disposal of cuttings during drilling

activities. The increase in sand paralleled a decrease in organic carbon

content. Inorganic carbon generally increased near the platforms most

likely due to deposition of calcareous debris from platform associated fauna

and the disposal of carbonate-containing cuttings.

In summary,

All three study sites studied exhibited a significant enhancement of

sand close to the platform (from 25 to 60 % enhancement over a few

hundred meters). The increase in sand content was often detectable

well beyond 500 meters distance.

The sand was primarily deposited by discharge of cuttings during

drilling activities.

5
Organic carbon was decreased near platforms, but not in proportion

to the increased sand content.

Inorganic carbon increased close to the platform due to platform

related sources such as biogenic debris (calcareous remains) and

disposal of carbonate-containing cuttings.

CONTAMINANTS

Contaminants near platforms include hydrocarbons and metals. As a

direct consequence of the disposal of drill muds and cuttings, a close

association between these contaminants is a general feature at all three sites.

This resulted in an unusual situation in which contaminant concentrations

were highest in the coarsest sediments. Hydrocarbons were elevated at HIA389 and MU-A85 in sediments close to the platforms and rapidly

decreased over a distance of 100 to 200-rn from the platform. Spatial

patterns exhibited a strong directional orientation reflecting a redistribution

by currents after the discharge events. Most hydrocarbons were

biodegraded with the exception of several stations at MAI-686, which were

rich in n-alkanes. Between cruise variations at the deeper water sites were

small suggesting that the benthic hydrocarbon contaminant field was stable

over a period of years. Polycyclic aromatic hydrocarbons (PAH) levels in

sediments were well below levels known to be associated with toxic

biological effects (< 4,000 ppb). No significant enhancement of

bioaccumulation of hydrocarbons was observed in megafaunal invertebrates

(soft tissues) or fish (livers and stomach contents) that resided near

platforms.

Sediments at two of the three study sites (HI-A389 and MU-A85)

exhibited strong gradients in certain metal concentrations (Ba, Ag, Cd, Hg,

Pb, Sb, and Zn). Metals that decreased with distance from the platform

were generally correlated with barium concentrations. These metals (Cu,

Hg, and Sb) appear to be constituents of the original barite ore used in the

drilling muds. Other metals (Cd, Pb, and Zn) had significant non-drilling

discharge sources. At HI-A389, metal concentrations (Pb, Cd, and Zn) in

sediments close to the platform contained concentrations of metals that are

known to elicit biological effects. As with hydrocarbons, no significant

6
enhancement in bioaccumulation of metals in invertebrates or fish was

associated with proximity to the platform.

In summaly,

A suite of contaminants was associated with the platforms -- trace

metals, hydrocarbons and sand.

Contaminants were closely associated with coarse sediments at

platforms.

Distance and direction were the most important main effects in

defining contaminant distributions.

Petroleum contaminant indicators were high nearest a platform and

decreased rapidly with distance away from a platform.

Sediment hydrocarbon contamination was predominantly related to

disposal practices during the drilling phase.

Compared to marine settings impacted by spills and coastal areas

that experience long-term non-point source chronic contamination,

sediment hydrocarbon concentrations were low at the sites studied.

Sediment PAIl levels were below documented biological effects

thresholds for marine biota.

Sediment trace metal concentrations at several locations exceeded

levels known to elicit biological effects.

The extent of a discernable contaminant plume was contaminant

dependent (i.e., PAR to 200-rn, barium to > 500-rn, sand to 200 to

500-m).

No enhanced bioaccumulation of contaminants was observed in

megafauna (invertebrates and demersal fish) residing close to

platforms.

Sediment properties such as Al content decreased near the platform

due to dilution with sand.

Several metals appeared to have sources other than the cutting/drill mud discharged during drilling (i.e., Pb, Zn, and Cd).

An evaluation of the three-dimensional distribution of contaminants

demonstrated the presence of subsurface maxima in contaminant concentrations (down to 10 to 20 cm)-

7
A comparison of samplings fourteen (14) years apart at the MM-686

site confirmed an ongoing loss of fine particulates and contaminants at this site.

At all three sites, lead (Pb) was shown to continue to accumulate in

sediments near the platform over a period of years. Contaminant concentrations increased to levels known to elicit biological

responses.

At deeper water sites (> 80-rn) the contaminant field was stable over

time periods of years (an exception was the observed increase in

lead).

Chromium and iron concentrations suggested there was a platform

related source of these metals.

Comparison of tissue metal concentrations with historical background data suggested that metals in fish livers from animals near platforms were comparable to background levels.

Comparison of contaminant levels in invertebrates from the

continental shelf in general with those at the present study sites, suggested that body burdens of some metals (i.e., Cd, Pb) increased

in response to increased concentrations of metals in sediments.

POREWATER TOXICITY

Sea urchin embryological development assays using pore waters

exhibited significant toxicity for 12 % of sediment pore waters tested during

the first cruise and this toxicity was similar for the second cruise. All of the

significant toxicity was observed within 100-rn of a platform. Two other

bioassays using a polychaete and an indigenous meiofauna species with

different endpoints, confirmed the sea urchin results. Correlation of data

indicates a covariation in toxicity and sediment trace metal concentrations.

In summary,

When observed, toxic sediments were generally within 100-rn of a platform.

A consistent toxic response was observed for two samplings over a one year time period.

There was excellent agreement among the toxic responses for three different test species and end-points.

8
There was a significant correlation between the concentrations of

metal contaminants and the observed toxicities.

MEIOFAUNA

Meiofaunal communities provided sensitive indicators of stress and

exposure. Harpacticoids exhibited sublethal responses at the population and

genetic levels of biological organization. The abundance of total nematodes

was enhanced near platforms by about a factor of two at MU-A85 and HIA389. Nematode abundance at MAJ-686 was lowest near the platform. At all

three platforms non-selective deposit feeders were enhanced in biomass

close to the platform typically by more than a factor of five; consistent with

the effects of modest organic enrichment. Harpacticoid copepod abundance

was consistently depressed near platforms. The effect was most intense at

the HI-A389 site, where contaminants were highest. This pattern is

consistent with previous studies showing the sensitivity of barpacticoid

copepods to toxic chemicals. As a consequence of the differential response

in meiofaunal species, the ratio of nematodes to copepods was a good

discriminator of distance from the platform.

In sumiliary,

Harpacticoid diversity was a sensitive measurement of impact.

Diversity decreased near platforms.

Meiofauna community responses were consistent with patterns observed in cases of modest organic enrichment and contaminant

discharge.

Abundance of total nematodes was enhanced near platforms at MU- A85 and HI-A389. Total abundance was lowest close to MAI-686.

Biomass of nonselective deposit feeding nematodes was enhanced

near all three platforms.

Abundance of total harpacticoids was lowest near ail three platforms.

The nematode:copepod ratio increased near platforms.

Harpacticoids appeared to have reduced reproductive success near platforms as reflected in greater reproductive effort and less

successful recruitment.

Harpacticoids exhibited a toxic response on exposure to some of the

porewaters from sediments collected near platforms.

9
Harpacticoid genetic haplotype diversity decreased with increasing

conthmination.

MACROINFAUTA

Macroinfaunal abundance and numbers of macroinfaunal species were

generally enhanced near platforms. Polychaetes were enhanced and

amphipods were depressed near platforms. Enhancement of biomass was

mainly attributed to increased abundances of polychaetes. This pattern was

not significant at the shallowest site, MAI-686. Amphipod abundances were

depressed around the platforms with effects confined within 100-rn at MAT686 and MU-A85 and extending to at least to 500-rn distance at HI-A389.

The reduction in amphipod abundance is consistent with a biological

response to toxic contaminant exposure.

In summary,

The greatest macroinfaunal abundances were found in close

proximity to the platform.

Diversity patterns were less uniform than abundance patterns. However, the largest numbers of species were within 100-rn of the platform.

Polychaetous anneids were the numerically dominant macroinfauna and therefore, macroinfaunal abundance trends were primarily due

to polychaete abundances.

Nemerteans, bivalves, decapods, and isopods abundances were highest near platforms.

Amphipoda and foraminifera had low abundances adjacent to

platforms and higher abundances in the far-field.

The polychaete/amphipod ratio was correlated with intensity of contanilnation.

MEGAFAUNA

Few effects on megafaunal invertebrate populations were noted that

could be unambiguously attributed to proximity to platforms or contaminant

exposure. Each platform appeared to affect megafaunal populations in

different and unique ways. The prevalence of parasites and pathologies in

10
megafauna were significantly related to distance from the platform but no

consistent Near/Far patterns were observed. While differences in

megafaunal populations residing in close proximity to offshore platforms

were observed, the most significant observation was that each platform

exhibited unique patterns. Among the various biological variables measured

for megafaunal invertebrates, size and histopathology exhibited the most

significant differences. Differences in catch per unit effort (CPUE) were

rare and differences in reproductive stage were minor in comparison to size

and health (histopathology). The presence of a platform did not appear to

exert an overriding influence on megafaunal invertebrate population

dynamics. Histopathological evaluations of fish found no increase in

contaminant related liver lesions near platforms.

In summary,

Few effects were noted in megafaunal invertebrates in relation to

distance from the platform except as related to size.

Differences in gonadal protein content were noted with proximity to

the platforms, however, results were species and platform specific.

The prevalence of parasites and pathologies had a strong effect on

reproductive stage at one site (MLJ-A85).

No contziminant related lesions were observed in demersal fish.

Parasites and parasite related lesions were common in demersal fish

but were unrelated to proimity to a platform.

Macrophage aggregate size and percent area in fish occupied were not significantly related to distance from the platform.

DETOXIFICATION

The detoxification work element concentrated on in vivo and in vitro

indicators of organic contaminant exposure. In vivo assays were used to

determine CYP 1A induction in fish and included ethoxyresorufin 0-

deethylase (EROD) activity, aryl hydrocarbon hydroxylase (AHH) activity and

CYP1A mRNA levels in livers. The production of PAH metabolites in fish bile

was also monitored. AHH activity was low or non-detected in invertebrate

tissues indicating little or no induction or no exposure. In vitro bioassays

using rat hepatoma H4IIE cells were conducted to evaluate the toxicities

11
and potencies of contaminant extracted from invertebrate tissues. No

significant activities were induced by invertebrate contaminant extracts.

There were no statistically significant differences in catalytic enzyme

activities, biliary PAH metabolite levels, and CYP 1A mRNA of any species of

fish for Near and Far station pairwise comparisons at the three sites. There

was an excellent correlation between AHH and EROD activity for most fish

species, which confirms that these two assays measure the same effect (i.e.,

CYP1A induction). Laboratory dosing experiments confirmed the presence

of a nuclear Ah receptor in two species of fish captured at GOOMEX sites.

In summary,

No significant differences in bepatic AUH and EROD activities and biliaxy PAH metabolite concentrations of fish were observed that were related to distance from the platform.

Very low to non-detectable enzyme activity was observed in

invertebrate microsome samples.

CYP lA-dependent enzyme activities were most likely basal or constitutive levels and levels were species dependent.

Ai and EROD activities were highly correlated in most species.

The nuclear Ah receptor complex necessary for transcription was

identified in pinfish and lizard fish.

Northern blot analysis demonstrated that CYP1A mRNA was present

in all of the fish species examined.

Gel electrophoresis indicated that CYP1A mRNA transcripts were

similar for all of the fish species examined.

The lack of CYP1A induction and differences in biliary PAIl metabolite concentrations in fish enzymes are consistent with low

levels of sediment PAIl and lack of significant bioaccumulation of contaminants in the tissues of fauna near platforms.

CROSS-WORK ELEMENT SYNTHESIS

One of the strengths of the GOOMEX Phase I program was the

adherence to a statistically rigorous study design supported by a coordinated

sample collection plan. In order to verify the soundness of the scientific

interpretations, concordance across diverse elements was closely examined.

12
In general, multiple lines of evidence were available to support the

conclusions.

In summary,

Covariation in environmental variables with distance from platforms

could be reduced to four categories of potential importance in

driving biological responses near platforms: sand enrichment,

hydrocarbon contamination, metal contamination, and organic

enrichment.

The observed increase in the abundance of polycbaetes, (especially

intense among deposit feeders), an increase in nematodes relative to

harpacticoids and an absolute increase in the density of non-selective deposit-feeding nematodes is consistent with species-specific effects

on benthic communities.

The pattern of increase in deposit-feeding polychaetes and nonselective deposit-feeding nematodes in the near-field around

platforms was contrary to the trend expected to accompany an

increase in sediment-sizeA decrease in abundance of amphipods and harpacticoid copepods

was best explained as a consequence of sediment toxicity near

platforms.

The relatively low levels of substantially degraded hydrocarbons

suggested that hydrocarbons are not the primary source of toxicity in

the benthos.

The lack of an enhanced induction of the CYP1A detoxification

systems in the near-field supported the conclusion that hydrocarbon

exposure was low.

Increased metal concentrations near one platform were at levels at which toxic effects may be expected. Bioassays using sea urchin

development and harpacticoid survival showed that porewater from

these stations was toxic.

An evaluation of sediment contaminant levels, benthic community

data, and results of porewater toxicity tests demonstrated a high

degree of concordance among the three variables.

Hypoxia in bottom waters near shallow platforms was tightly coupled with enhanced nutrient regeneration and interpreted to be a

consequence of organic enrichment.

The use of multivariate techniques to evaluate community response of either macroinfauna or meiofauna to environmental gradients has

13
been shown to be an especially sensitive tool for detection of

significant biological responses.

The overall biological impact at these study sites was low compared

to impacts near platforms in the North Sea. Compared to other anthropogenic discharges of treated municipal wastewater and

industrial discharges, responses at the study sites were low.

Variance in response variables was higher near platforms due to

small scale heterogeneity and provided an additional indication of

impact.

Comparisons of genetic variability may be a useful technique to

identify sublethal chronic impacts that occur as a result of environmental disturbance.

Analysis of benthic fauna at the family level should be undertaken with caution and may not be generally applicable due to loss of

information provided at the species level of identification.

RECOMMENDATIONS

From a close evaluation of the study design, the variables measured,

the trends observed, and the information gained in GOOMEX Phase I, a

number of recommendations and conclusions are provided. These

observations set the stage for developing the follow-on phases of the

GOOMEX Program.

In summary,

An integrated approach at several levels of biological organization

(molecular to community) and organism size (bacteria to fish) is needed to assess the state of a system.

Rigorous statistical design, objective site selection, and high quality

data generation are the underpinnings of a successful program.

The major discontinuity at the seawater/sediment requires that very different approaches and interpretations be applied to results based on benthic and epibenthic indicators of exposure and response. Interactions across this discontinuity are also important.

A threshold response in organisms leading to rapid deterioration, may be a more appropriate model than a gradual and continuous dose-response model.

14
Contaminants are not regularly distributed in sediments and are heterogeneous (small scale variability) in impacted areas. Steep and

abrupt gradients are often observed and distance is not always an

adequate surrogate for distance.

"Control't type comparisons may not be optimal. Incidence, prevalence, and intensity of indicators of impact over a range of exposures may more accurately predict impact. The spatial and

temporal scales of populations are not well-defined, particularly in

mobile megafaunal communities.

Strong covaxiation of multiple environmental variables may make it

difficult if not impossible to identify cause and effect from field

observations alone. Manipulative field and laboratory studies are needed to more directly address questions of causation.

Comparison of field observations with laboratory and other controlled

exposure experiments is necessary to assess the relative importance

of the observed responses (i.e., the dynamic range of indicators must

be established).

Integrated, multidisciplinary approaches imply that appropriate multivariate statistical analyses be developed to provide optimal utilization of the data produced.

The results from Phase I lay the groundwork for continuing studies

directed at determining the mechanistic explanations for the patterns

observed. A series of recommendations are made in Table 2 for the

structure and content of follow-on studies. Definitive testing of the patterns

associated with platforms and development of a sound scientific basis for

identifying the most appropriate and sensitive variables for future

monitoring and management of activities associated with offshore oil and gas

exploration and development are a primary goal for Phase II. A variety of

design approaches will be needed to provide for the multiple goals of Phase

II including: tests of generality of trends and patterns, continued

development of promising Phase I indicators, introduction and testing of

new more appropriate indicators, laboratory verification of causation,

measurement of process variables (i.e., fluxes measured by benthic

chambers, pore water proffles, and sediment trays), and in-field sampling to

verify responses under well-characterized contaminant settings (including

manipulative experiments, i.e., transplants, sediment trays, etc.).

15
Table 2. Summary of recommendations for further study at platform sites.

Work Element Recommendations

Physicochemical *Provjde a synoptic view of each site to more fully delineate platform related effects on water column

oxygen and nutrient conditions and thus organic enrichment.

Sedimentology *Provide a mass balance of the sediments based on origins

(cuttings, in. situ sand, terrigenous materials, etc.), not

just particle size or bulk chemistry. *Discontinue x-ray diffraction

Contaminant Chemistry *Chemistiy must be closely coupled with biological effects

studies (no baselines or surveys) - *Proyide an integrated concentration/area or volume

estimation of the contaminant field to various,

appropriate depths (0-2 cm, 0-10 cm).

*Define bioavailable contaminants more effectively - pore water chemistry must be carefully and accurately defined

especially for metals with particular reference to redox

conditions and speciation. *To truly understand the chemistry of contaminants, flux measurements may be needed based on porewater proffles and benthic chamber data.

(4) Meiofauna *Target the most useful and sensitive indicators of impact such as harpacticoid diversity. *Measu.re the temporal distribution of nematodes (e.g., for one year) to more accurately predict long-term changes in

population. *Pursue genetic diversity studies in situ and in the lab by

simulating exposure scenarios on appropriate time

frames.

Macroinfauna *Target the most useful and sensitive indicator species for enumeration.

*Develop and apply reproductive effort, life history, and other studies analogous to the meio and megafaunal work

efforts (targeted at specific species). *Investigate the utility of genetic diversity studies.

Megafauna Invertebrates *Concentrate on a few abundant species especially for histopathology

*Closely couple with contaminant measurements of more

appropriate tissues (i.e., eggs). *Genetic diversity

*Institute transplanted animal experiments to constrain

their range and thus exposure.

zExtend reproduction studies to egg quality.

Mega.fauna fish food studies.

*Discontinue histopathology.

16
Work Element Recommendations

Detoxification

Pore Water Toxicity

Bioassays

Study Design

Table 2. (Cont.)

*Emphasize toxic responses to trace metals (i.e.,

metallothioneins). *Extend in vitro assays to a more comprehensive testing of

invertebrates in coordination with contaminant

measurements and pore water toxicity testing.

4Focus studies intensively on a few of the more

appropriate species. *pursue invertebrate bioindicators of exposure *Evaluate other potential biomarkers of contamination

such as heat shock proteins. *thtegrate laboratory studies with in-field exposures

(transplanted animal experiments) to define the dynamic

range of the indicators.

*Additional standard bioassays for comparison including

whole sediment.

*Momtor contaminant concentrations during the assays

and in situ to more effectively delineate the causative

agents. *Coordinate bioassays of animals with in vitro

toxicological assays. *Deslgn dosing experiments to develop cause and toxic

effects linkages in the laboratory.

*Test generality of observed trends. *Develop a more comprehensive sediment quality model incorporating more extensive toxicological and bioassay

results.

*Expand the surveys to oil platforms. *Consider discarding the radial pattern and utilize a

evenly spaced grid approach. *Develop a fully integrated model of response which will ultimately provide a plan for actual monitoring

programs.

17
1.0 INTRODUCTION

A mandate to conduct studies to predict, assess, and manage the effect

of Outer Continental Shelf (OCS) oil and gas development activities on the

marine environment is provided to the MMS under the OCS Lands Act

Amendments. In response to this mandate, the MMS Environmental

Studies Program has sponsored a series of ecosystem investigations and

monitoring studies of drilling discharges and production activities in the

Gulf of Mexico, Pacific, and Atlantic OCS Regions. At the present time, the

most significant unanswered questions related to the environmental impacts

of offshore oil and gas development and production are those involving

chronic, low-level stresses on ecosystems. These stresses result from

discharges, spills, and leaks associated with the long-term development of

energy resources (Boesch et al. 1987; Aurand 1988; Ahifeld 1990; Kendall

1990). The Gulf of Mexico Offshore Operations Monitoring Experiment

(GOOMEX) is a three-phase study to test and evaluate a range of biological,

biochemical, and chemical methodologies that may indicate chronic

sublethal exposure to contaminants associated with OCS oil and gas

development and production. Program results will be used to formulate and

recommend an approach to assess the importance of environmental changes

associated with the long-term development of energy resources on the US

OCS based on sound scientific evidence.

The primary objective of Phase I of GOOMEX was to document

responses in resident fauna that were the result of exposure to contaminants

at long-term OCS production sites. GOOMEX Phase I combined "state-ofthe-art" determinations of chemical contaminant distributions with

advanced studies of organismal response to contaminants. Study

components included the analysis of contaminants (trace metals and

hydrocarbons) in sediments, pore waters, and biological tissues; assemblage

analysis of benthic meiofauna, macroinfauna, and megafauna; meiofauna and

megafauna invertebrate life history and reproduction studies; and the

presence and intensity of inducible detoxification responses in megafaunal

biota (Figure 1.1; Table 1.1). All study components were linked by a

common, statistically rigorous study design.

A "chronic'T impact was defined as the cumulative effects on

ecosystems caused by long duration exposure to chemicals in the

1-1
Management Group Leader Dr Mahlon C. Kennicult II HH Field Lo.istics Dr. Roger A. Fay Data Management Dr. Gary A Wolff Reports ClerlcallSecrefattal Stat I Data Analysis Group Dr. Roger H. Green Dr. Don Boesch Dr. Robert Carney Dr. James P. Ray Dr. Robert Spies Chemistry & Sedimentotogy Group Leader Dr. James M. Brooks Hydrocarbons Dr, Terry Wade Trace Metals Dr. B, J. Presley, Dr. P. Soothe Bed imenlology Dr. Dick Rexak Aticillary Parameters Dr. Jennifer Wong Benihic Biology Group Leader Dr Paul MonlagnaPro.ram Director Deputy Proect Director Meio(aurna Dr. Paul Montagna tnlauna I Epileuna Dr. Don Harper Metofauna Lile History & Population Genetics Dr. Paul Montagtta MsaIaUnsl lnerielate Life History Dr. Eric N. Powell Dr. Pasquato Roscigno Dr. Rezneat Darnoli Immirnological Probe Dr. Eric N Powell Mobile Invertebrates & Dernersal Fish Dr. Reznoal Darnell H Fish Food Dr. Rezneai Darnell Demersal Fish Taxonomy Dr. John McEachrarr Megalaurie Taxonomy Dr. Don Harper TAMRFNecropsies & Hislopalliology Dr. John W. Fournie Do to a iii Ca lie a Response Dr. Sieve Safe Dr. Sue J. McDonald Biliary Metaljoliles Dr. Sue J. McDonald Melolaune Bioassay Dr. Paul Montagna Dr. Scott Carr Sediment Pore Water Tosicity Testing Dr. Scott Cart 

FIgure 1.1. Program organizational chart. D. Mahion C. Kennicutt II Project Specialist
Table 1.1 Summary of GOOMEX Phase I Work Elements

Work Element Variables

INDEPENDENT VARIABLES - SEDIMENTS/WATER COLUMN

Physicochemical - salinity, oxygen, nutrients, light transmittance

Sedimentology - grain size, carbon content (organic and

inorganic), mineralogy, redox condition

Contaminants - hydrocarbons, metals

INDEPENDENT VARIABLES - BIOTA

Contaminants - hydrocarbons and metals in fish livers, fish

stomach contents, and invertebrate soft tissues

Physiological - percent moisture, lipid content

INDEPENDENT VARIABLES - PORE WATERS

Contaminants - hydrocarbons and trace metals

DEPENDENT VARIABLESa

Megafauna - Fish - fish food analysis, histopathology, and

detoxification responsee

afor the purposes of determining if there were relationships between contaminant dose and

biological responses the biological measurement were considered dependent variables.

balso pore water toxicity tesfingbioassays with meiobenthic species.

Calso pore water toxicity testingsea urchin fertilization and embryological development

test,

ddetoxificatjon responseAHH activity, in vitro rat hepatoma H-411E cell assays.

edetoxification responseEROD and AHR activity, biliary PAR metabolites, CYP1A mRNA

levels, laboratory dosing experiments.

Meiofaunab abundance, diversity, community structure, nematode trophic dynamics, life history and

reproduction, genetic diversity

MacroinfaunaC abundance, diversity, and community structure

Megafauna Invertebrates - catch per unit effort, size and size frequency, histopathology, reproductive effort, reproductive development, and detoxification

responsed
environment. Long duration was defined as sites where platforms were

present and actively producing for more than ten (10) years. Contaminants

released from a point-source over a period of years might reach a "steady

state" spatial pattern in the adjacent sediments, thereby setting the stage for

chronic effects. However, other processes including cessation of

discharges, chemical transformation, sedimentation, biological oxidation,

and erosion tend to disperse or dilute contaminants with time.

Detection of impacts or biological effects responding to contaminant

exposure requires confirmation that the exposure has taken place and that

the observed "biological patterns" are beyond those attributable to natural

variations (Carney 1987). It is also imperative that dose is measured directly

and not inferred from response or estimated from a surrogate (distance).

Biological response to exposure can be highly variable in both mechanism

and intensity. Biological changes can have a short time-span (i.e., induced

detoxification or reduced reproductive effort in an individual) or a long

time-span (i.e., compositional shifts in communities). The impact of a

particular contaminant event can be expected to manifest itself differently

from species to species and from population to population due to differences

in the history of exposure and organismal response to exposure.

GOOMEX Phase I was designed to provide an integrated assessment of

biological effects covering a range of important marine species including

meiofauna, macroinfauna and megafaunal invertebrates and fish. Biological

indicators of impact or effect covered a range of potential markers from the

molecular to the population and ecosystem level of biological organization

(Table 1.1). Assemblage data were collected for meiofauna and

macroinfauna. Reproduction and life history studies concentrated on

meiofaunal and megafaunal invertebrates including an emphasis on

barpacticoid life histories. Megafaunal invertebrate reproductive effort and

development studies provided indicators of community health and energy

flow. Demersal fish were examined for chronic impacts at several levels of

detail including necropsies (gross pathology), histopathology of

representative tissues, stomach-content analysis, liver and stomach-content

contaminant analysis, and fish biliary hydrocarbon metabolites. Biological

analyses were closely coordinated with measurements of contaminant levels

in appropriate tissues.
Detoxification responses were monitored by measuring biological

indicators that demonstrate that toxicants have entered an organism, have

partitioned into their tissues, and are eliciting a chemical response.

Indicators of contaminant exposure were mechanistic-based and included

assays for the inducible detoxification systems ethoxyresorufin 0-deethylase

(EROD), aryl hydrocarbon hydroxylase (AHH), and CYP1A mRNA levels in

hepatic tissues of demersal fish. The detoxification studies were closely

coordinated with measurement of contaminants in the appropriate tissues.

Several new techniques, or techniques not previously applied to a

marine setting, were also evaluated including:

an immunological probe to measure the rate of synthesis of

gonadal protein in selected megafaunal invertebrates

(reproductive effort);

genetic variations in metofauna populations as indicators of

stress;

development of bioassays utilizing indigenous meiofaunal organisms to provide direct evidence of impact or potential

for injury; and

in vitro assays of contaminants extracted from a variety of matrices (including invertebrate tissues) with sensitized cell

lines to indicate toxicities and potencies.

The GOOMEX program was designed to provide an adequate number

of measurements to statistically test a series of fundamental hypotheses.

Rigorous statistical design prior to sampling and maintenance of the

continuity of the study design throughout the program guaranteed that

statistically valid conclusions could be drawn. The GOOMEX Phase I results

will be used to formulate a series of focused, process-oriented studies to be

pursued during Phases II of the GOOMEX Program.

1.1 Study Site Selection

Initially, five sites were sampled during Cruise 1 (Figure 1.2). After

evaluation of Cruise 1 results, three sites were selected for final study. The

criteria for site selection included:

(1) The site must be located in an area with a long history of oil and/or gas development and production must have been active

for no less than ten years.
Figure 1.2. Location of the original five study sites sampled on Cruise 1.
The site must be located in the western and/or central Gulf of

Mexico far enough to the west to be outside the perpetual. confounding influence of the Mississippi River plume.

Comparison stations (controls) must be available that are located

away from suspected present or past influences of any platform

or pipeline and be similar to the near platform stations in depth,

sediment characteristics, physico chemical parameters, ambient current regime, and benthic fauna.

Mississippi River discharge causes fluctuations in physical and

sedimentological that lead to significant variability over time and space in

the benthic setting. It was deemed important to choose sites outside of the

confounding influence of the Mississippi River Plume to enhance one's

ability to recognize a perturbation. In this particular study, "river'T influence

was primarily judged based on homogeneity of benthic substrate. However,

it is recognized that the Mississippi River has substantial influence on water

masses throughout the Gulf of Mexico. Based on these criteria and the

regional occurrence of major petroleum producing reservoirs, site selection

was restricted to the western Gulf of Mexico which is primarily a

gas/condensate producing region. As such, "oil" platform sites per se were

not included in the study. Long-term production activity and water depth

were also constraining factors in site selection. Other secondary

considerations in site selection included the availability of data from the

sites and the confirmed presence of a detectable, chemical contaminant

gradient.

The five sites chosen were Mustang Island Block-A85, Matagorda

Island Block-686, Matagorda Island Block-622, High Island Block-A389, and

Galveston Area Block-288 (Buccaneer Gas and Oil Field; Figure 1.2). Due to

the short time between GOOMEX Cruises 1 and 2, only preliminary results

were available to select the final three study sites. A primary consideration

was the documentation of a gradient in chemical contaminants in sediments

surrounding the platform sites. The presence of a detectable spatial

contaminant gradient was seen as the most important factor in selecting the

final three study sites. The underlying assumption was that the stronger

(steeper) the gradient, the greater the likelihood of observing statistically

significant biological effects between near- and far-field samples.
A comparison of indicators of hydrocarbon contamination clearly

demonstrated the highest contaminant concentrations were at MU-A85 and

HI-A389 (Figure 1.3). MAJ-686 and MAI-622 were similar and MAI-686

exhibited elevated alkanes due to the leakage of condensate near the

platform. GA-288 exhibited little or no gradient in hydrocarbons. Metal

distributions, especially barium, exhibited contaminant gradients similar to

those observed for hydrocarbons (petroleum; Figure 1.4). Barite (barium

sulfate) is a major component of drilling fluids and has been used as a tracer

of the settleable fraction of drilling discharges. One criteria for final site

selection was the magnitude and areal extent of the barium plume at the

platforms and the correlations observed between barium and other metals.

The steepest gradients in barium were at MU-A85 and HI-A389. Metal

contaminants at both sites were significantly elevated. It should be noted

that both of these sites are somewhat atypical for the Gulf of Mexico in that

drill muds and cuttings were shunted near to the seafloor due to the

proximity of shallow fishing banks and/or coral reefs. GA-288 showed little

trend in barium concentrations with the most distant stations being slightly

elevated over the near-field stations. GA-288 was dropped from further

consideration as a study site. MAI-686 and 622 were similar in sediment

contaminant levels; however a more consistent metal contaminant field was

present at MAI-686 than MAI-622 and several metals co-varied with barium

as well (Table 1.2).

Most biological measurements were preliminary at the time of final

site selection and could only be used in a qualitative sense. Cluster analysis

of macroinfauna data from the five sites resulted in a dendrogram having two

site groups. One site group consisted of the three shallower sites, GA-288,

MAI-686, and MAJ-622. The two deeper sites, MU-A85 and HI-A389,

formed a second site group Therefore, a range of benthic settings were

provided by the choice of MAI-686, MU-A85, and HI-A389. Meiofauna

results were similar.

Based primarily on the existence of chemical gradients; as confirmed

by Cruise 1 results; MU-A85, MAI-686, and HI-A389 were chosen as the

final study sites. The data from all five sites sampled during Cruise 1 are

used to test hypotheses when appropriate. The data collected for all

parameters at all sites are available through the National Oceanographic Data

Center, Washington, DC (NODC).

1-8
50

40

10

0

a 70 .30

GO 0

F

I

I

Figure 1.3. Frequency distribution of the total unresolved complex mixture

(UCM, ppm), total alkane (C10-C34, ppb), arid total polycycic

aromatic (PAH, ppb) concentrations in sediments for Cruise 1.

1-9

-,A &7Isk

__f___._

AAAA_-

__-

.__;

Figure 1.4 (Oflt.). bariUtfl COflCentrafibl ppil1) in sediTitS

from C se 1 by radli d distance from the plat1Or
Table 1.2. Summary of significant Spearman correlations in sediment trace

element data from Cruise 1.

HI-A389 Ba, Ag, Cd, Cu, Hg, Pb, Sb, Zn Ag, Cd, Cu, Hg, Pb, Sb, Zn

MU-A85 Ba, Ag, Cd, Hg, Pb, Sb, Zn Ag, Cd, Hg, Pb, Sb, Zn

MAI-686 Cd, Hg, Pb, Zn

MAI-622 Ba

GA-288 Ag, As, Cu, Pb

1.2 History of Operations at the Study Sites

The final study sites for the GOOMEX Phase I field program were

Matagorda Island Block 686 (MAT-686-2), Mustang Island Block A85 (MUA85-1), and High Island A389-East Flower Garden Bank (HI-A389-4).

Presented below are limited descriptions of production histories at these

three sites.

1.2.1 Matagorda Island Area Block 686 (MAI-686)

The Matagorda Island Block 686 (MAI-686) platform is operated by

Occidental Oil Company. Between 1977 and 1981, a total of 12 wells were

drilled. This gas field produces from depths of 9,152 to 12,260 ft. A

summary of the drilling history and associated discharges until 1980 is

provided in Table 1.3. Monthly production of condensate, gas, and water is

summarized in Figure 1.5.

1.2.2 Mustang Island Area Block A85 (MU-A85)

The Mustang Island-A85 (MU-A85) field was first drilled by Conoco,

Inc., and is currently operated by Amerada-Hess. Drilling occurred as

recently as 1986, and a total of 18 wells have been spudded. Discharges

associated with the first six wells are summarized in Table 1.4 (Gettleson

1-12

Significant (p < 0.01) Negative Significant Positive Correlation Site Correlation with Distance from Site with Barium
Table 1.3. Summary of the drilling history and

associated discharges at the Matagorda Island Block 686 site through 1980 (after Boothe

and Presley 1985).

Characteristic Matagorda 686

Type of drilling activity Development

Type of wells Gas

Number of wells 8

(4 additional wells

drilled after 1980)

Total well depth (sum of all wells, m) 24,938

Total volume of cuttings dischargeda 3130

(sum of all wells, m3)

Drill mud components used (total of all wells 5334

inkgx 103)b

Total barite used (total of all wells in kg x 10, 4547(85)

percent of total components used)

Total barium used (TBU, total of all wells in 2326

kgxlO3)C

Discharge pipe location bearing in °T from rIg 022 (-6)

(± water surface, m)

Number of adjacent drilling sites (number of 1 (1)

wells drilled within 3000 m radius of

study rig

Nearest adjacent drilling site to study site 1500 (095)

(m,°T)

aEsrimated as 1.1 times total volume all wells

bMud systems used: Seawater/gel (to 900 m), Ligrilte/lignosulfonate

(below 900 m)

Csung the barite used was 87 % BaSO4 and that the percent composition of Ba

in BaSO4 is 58.8 %..
30000-

25000 -

20000 -

U, - _J 15000-

10000 -

5000:

3500000

:

3000000 -

2500000 -

u_ 2000000-

C)

1500000-

1000000-E

500000 -

0

1982

100000 :

90000 -

80000 -

70000 -

U, 60000-i

50000-e

m 40000-i

30000 -

20000 -

10000 -E

0-

1982

0

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993

\ \.

as

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993

Figure 1.5. Monthly production of condensate, gas, and water at

MAT-686.

1-14
and Laird 1980). Monthly production of condensate, gas, and water is

summarized in Figure 1.6. Exploratory wells No. 1, No. 2, and No. 3 were

drilled between 1976 arid 1978. In most instances drilling muds and

cuttings were discharged near the seafloor due to the proximity of the drillsite to Baker Bank, a topographic high that serves as a fishing bank on the

OCS. Pre- and post-drilling sediment barium surveys documented a benthic

barium plume extending 1,000 meters from the drill site.

1.2.3 High Island A389 (HI-A389)-East Flower Garden Bank

The High Island A389 (HI-A389) platform is operated by Mobil Oil

Exploration and Producing U.S., Inc., and Union is a 50% partner. The

platform has six wells, and current production is 22.0 MMCFD of natural gas.

A comprehensive history of hydrocarbon development at the site is given by

Boland et at. (1983). Preliminary exploratory drilling near the East Flower

Garden Bank took place in the spring of 1975. Drilling continued in the fall

of 1977 in 129 m of water. A total of 129,000 L of drilling fluid and

1,035,000 kg of drill cuttings were discharged during October and

November 1977. Residues from the fluids and cuttings were detected up to

1000 m from the drill site by CSA (1985), but not on the reef monitoring

stations 2000 m away. Results of the exploratory phases indicated the

presence of commercial quantities of natural gas. The present platform was

installed in October 1981, approximately midway between the two

exploratory wells.

Additional drilling began on 26 April 1982 and continued into 1983.

Drill fluid and cuttings were shunted to within 10 m of the bottom prior to

release. This was required because the platform is located within the

"shunting and monitoring' zone around the East Flower Garden Bank.

Discharges were stopped when operations required oil-based drill fluids.

Oil-based fluid drilling requires a closed system. Cuttings, muds, and

discharge water were barged for disposal elsewhere. Six production wells

were drilled. The last driffing occurred on 19 April 1983. Depth of the six

wells ranged from 1827 to 4313 m. Monthly production of condensate, gas,

and water is summarized in Figure 1.7
Table 1.4. A summary of drilling discharges from the first six wells at Mustang Island Block A-85 (from Gettleson and Laird 1980).

Well Amount of

Muds Used

(lbs.)

Percent

Barite by

Weight of Mud

Used

Weight of

Cuttings

Dischargeda

(lbs.)

Weight of Mud

Discharged

(lbs.)

Weight of Barium

Discharged

(lbs.)

aEsilmated from mean (mud discharged/mud used) of Platform A Well No.'s A-3, 4 and 5 (A-6

judged atypical).

bEstated from barium content of muds discharged from Platform A Well No.'s A-5 arid 6

No Data

No.1

Block A-85 4,157,000 2,536,916a

No.2

Block A-85 1,875,000 1, 144,267a

Platform A

No. A-3

through A-6

Block A-85 8,798,636 87 7,696,087 4,070,465 509,852b
30000

25000

20000

U, -J

15000

10000

5000

0

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993

3500000

3000000

2500000

LI.. 2000000

()

1500000

1000000

500000

100000

= 90000

80000 -

70000 -

60000-E

50000-i

m 40000-

30000 -

20000 -

10000 -

0-

\\' ',\

O \ N\ \

I I I 1 I I ( I 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993

E

Water

LA

Figure 1.6. Monthly production of condensate, gas, and water at

MIJ-A85.

1-17

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993
30000:

3000000-

2500000 -

j. 2000000

C)

15000o0:

100000 :

90000-

B0000-E

70000 -

60000-

50000-

40000-

30000-

20000 -

1982 1983

25000:

20000:

15000 -

10000-

5000-J

0

1982

3500000

Data Not Available

1983 1984 1985

Data Not Available

1983 1984 1985

Data Not Available

1987 1988 1989 1990 1991 1992 1993

I I I I I 1984 1985 1986 1987 1988 1989 1990 1991

Water

*4

1992 1993

Figure 1.7. Monthly production of condensate, gas, and water at HI-A389.
2.0 STUDY DESIGN AND STATISTICAL MODEL

The primary goal of the GOOMEX Phase I program was to collect a set

of data that would rigorously test the major programmatic hypotheses. The

null hypotheses to be addressed by GOOMEX Phase I, as originally cast,

were:

H0: There are no differences in any chemical and/or biological parameters measured between platform stations (at distances less

than 2,000 meters from the platform, or platform group) and

comparison stations (located a minimum distance of 3,000 meters

from any present or historic platform, or platform group).

H0: There are no differences in assays for primary detoxification

responses of the resident biota between platform stations (at distances less than 2,000 meters from the platform, or platform

group) and comparison stations (located a minimum distance of 3,000 meters from any present or historic platform, or platform

group).

H0: There are no differences in the reproductive indices of the

resident biota between platform stations (at distances less than 2000 meters from the platform, or platform group) and

comparison stations (located a minimum distance of 3,000 meters

from any present or historic platform, or platform group).

The null hypotheses as stated define spatial variability in the design,

but lack generality. In these hypotheses, "platform-stations" were defined as

those stations that are at distances less than 2,000 m from the platform (or

platform group). "Comparison-stations" were defined as stations 3,000 m

away from the platform (or platform group). As originally stated, the null

hypotheses do not allow for an a priori test to answer the question: how far

away from platforms do effects extend? Also, it is possible that platform

effects occur, but do not extend out to a distance of 2,000 m, and may not

be detected if the general criteria of the original null hypotheses were used.

Two, more general, null hypotheses provided a more powerful test for

differences among station at multiple distances from the platform site. The

following are the null hypotheses that were used to guide the development

of the statistical models for the analysis of the variables measured during

GOOMEX Phase I:
H0: There are no differences in any sedimentological, chemical, community, population, reproductive, toxic or detoxification

variables between seasons, among platforms (or platform groups), or with distance or direction away from platforms (or platform

groups).

H0: There are no functional relationships between chemical contaminant gradients and community, population, reproductive, toxic or detoxification measures of biological response.

The approach to test the first hypothesis is univariate analysis of

variance (ANOVA) for all variables being measured at all stations in the study

design. However, the categorical variables in such a design, particularly

distance from the platform, are surrogates for the contaminant gradients

that might exist among and within platform-stations. Therefore, the

approach to test the second hypothesis is a multivariate approach that

includes a direct measure of contaminant exposure or dose. Some data

elements required additional analyses that were unique to their particular

area of science (e.g., size frequency analysis for the life hlstoiy analyses).

2.1 Statistical Model Development - Univariate Analysis

The study design is based on a dose-response model. The doseresponse model determines the dependent and independent variables, all

independent variables are dose or dose-related while all dependent variables

are response or response-related. Contaminant concentrations (i.e., dose)

were expected to decline exponentially with distance away from a platform.

Biological variables should react to the contaminant gradient (i.e., response),

thus the magnitude of the biological response is expected to decrease with

increasing distance from a platform as well. The basic form of the doseresponse model is:

Y = eX

where Y is the response, and X is the dose. This non-linear response can be

reformulated, so that a linear model can be used to analyze the data:

LrtY=a+bX

Four different views of the study design are useful for interpreting the

GOOMEX Phase I results. The primary view is the data set in its entirety.

2-2
Subviews, or decomposed views, exist to explore interactions among design

elements. These different views of the study design and the relationship

among these categories are summarized in Table 2.1.

Table 2.1. Different analysis categories for different subsets to examine the

total design and interactions within the design.

Number of Number of Platforms (F)

Cruises (C) 3 1

4 Total Design Analyses By Platform Analyses

1 By Cruise Analyses By C*P Analyses

The standard SAS notation and conventions are used to simplify the

presentation (SAS Institute Inc. 1990). The notation for the independent

variables is as follows:

Variable Variable Notation

Cruise C

Platform P

Radial R

Distance D

Interaction terms are used to indicate that the variables are crossed

and are designated with an asterisk (1:

CP = an interaction term for C and P.

For crossed variables, every level of a variable occurs in every level of the

other variable. For example, every platform was sampled on every cruise.

Nested terms are used to indicate that the variables are hierarchical and are

designated with parentheses.

P(R) = a nested term where R is nested within (or is unique to) P

For hierarchical variables, the nested term occurs only once in each level.

For example, each radii is unique to a platform. Radius A at one platform has

no relationship to Radius A at another platform. In this sense, radii (R) are a

random effect, and represent a form of replication. In contrast, platforms

2-3
(P) are fixed variables. The terms random and fixed are important in

determining the expected mean squares, and thus the appropriate

denominators for F-tests.

Error in data of the type collected in this program can arise from

several levels: (1) analytical error, (2) small-scale variation within boxcores,

(3) sampling error (i.e, among boxcores), and (4) location error (large-scale

spatial variation that is not related to distance or direction). It is essential

that the appropriate error be used for testing hypotheses. Parametric

statistical tests with more than about 10 error degrees of freedom (df)

provide the needed robustness to failures of assumptions (Harris 1975).

Multiple terms in a linear model are summed, but in SAS notation

there is just a blank space where a plus or addition sign is intended. In SAS,

"I is a short hand notation to indicate all possible interactions. Therefore,

C I P indicates C and P and all possible interactions with C and P. In this

simple example, there is only one, C*P, but in complex three- and four-way

interactions, this short hand notation is useful. All text in capitol letters

signifies that it is written in SAS syntax.

C, P. and R are categorical main effects. However, D could be a

continuous variable (i.e., the actual distance from the platform is used in the

analysis). Since the use of a. logarithm transformation is already used for all

data as a surrogate for a dose-response model, all variables, including D are

treated as categorical. In the discussions below, Y is used to indicate any

dependent variable.

2.1.1 Total Design Analyses

This is the first analysis model, with all P and all C included (Table

2.2). It is used to demonstrate that platforms are heterogeneous, and

whether the model should be decomposed to perform "by F' analyses. R is

nested within P. Here D and C are crossed with both P and R(P). The

appropriate SAS model is:

Y = C P C*P R(P) C*R(P) D P*D D*R(P) D*C P*D*C D*C*R(P),

or Y= C I P I D I R(P)
Table 2.2. ANOVA table for total design analysis. Model: Y = C P C*P R(P)

C*R(P) D P*D D*R(P) D*C P*D*C D*c*R(p), where R(P), C*R(P),

R is a random effect, and C, P and D are fixed effects. P is tested against

R(P), and D and P*D against D*R(P). C and P*C are tested against D*C*R(P).

R(P), D*R(P), CR(P) and D*C*R(P) are tested against replicate error.

2.1.2 By Platform Analyses

This is the P-by-P analysis model, with more than one cruise involved

(Table 2.3). It is used to test and describe distance and direction effects at

each Platfonn, given that the total design model, which includes P in it,

shows significant interactions involving P. This is a fully crossed model,

because now levels of R are sampled at all C and D. When the data set is

analyzed BY P. the appropriate SAS model is:

Y= CR C*RD C*DR*D C*R*D,

orY=CIRID

Although R is now a crossed variable, it is still a random effect. So, C

is tested against C*R, R is tested against a composite error term, and D is

tested against R*D. The double interaction terms, C*R, C*D, R*D are tested

D*R(P) and D*C*R(P) are declared random.

Source df Test Against df if D is

continuous

1 P 3-1=2 2 2

2 R(P) (5-1)3=12 (7+8)-li 12

3 D 5-1=4 7 1

4 C 4-1=3 8 4

5 PD (3-l)(5-1)=8 7 2

6 P*C (3-1)(4-1)=6 8 6

7 DR(P) (5-1)(5-1)3=48 ii 12

8 C*R(P) (4-1)(5-i)3=36 11 36

9 D&C (5-1)(4-i)=12 11 3

10 P*D*C (3-i)(5-1)(4-i)=24 ii 24

11 DCtR(P) (5-1)(4-1)(5-1)3=144 12 36

12 Rep. error (3)(4)(5)(5)(2-i)300 461

Total (3)(4)(5)(5)(2)-1=599 599
Table 2.3. ANOVA table for by platform analysis. Model: Y = C R C*R D C*D R*D C*R*D, where R, C*R, R*D, and C*R*D are declared

random.

against the triple interaction term C*R*D. The triple interaction term is

tested against replicate error.

2. 1..3 By Cruise Analyses

There are three uses for the by cruise analysis: (1) examine the power

of the sampling design where replicate boxcores were taken, (2) where

more than three platforms were sampled on a single cruise, and (3) where

seasonal or interannual interactions are occurring (Table 2.4). It is

necessary to analyze each cruise separately if there are significant seasonal

or temporal interactions. For example, if the populations being measured

change through time.

Table 2.4. ANOVA table for by cruise analyses. Model: Y = P R(P) D P*D

J1)tR(P), where R(P) and D*R(P) is declared random.

i p 5-1=4 2 4

2 R(P) (5- 1)5=20 5 20 3 D 5-1=4 5 1 4 PD (5-1)(5-1)=16 5 4

5 DR(P) (5-1)(5-1)5=80 6 20

6 Rep. error (5)(5)(5)(2-1)= 125 200

Total (5)(5)(5)(2)- 1=249

Source df Test Against df if D is

continuous

1 C 4-1=3 4 3

2 R 5-1=4 4+6-7 4

3 D 5-1=4 6 1

4 CR (4-1)(5-1)=12 7 12

5 CD (4-1)(5-1)=12 7 3

6 R*D (5-1)(5-1)=16 7 4

7 CR9) (4-1)(5-l)(5-1)=48 8 24

8 Rep. error (4)(5)(5)(2-1)=100 197

Total (4)(5)(5)(2-1)=100 249

Source df Test Against dfifD is

continuous
Power and variance components analysis is a special case applicable

only to the first cruise where there are two replicate boxcores for power

analysis. D reduces to two levels, Near (N) and Far (F). It is not necessary to

designate R. The design is fully hierarchical with D nested within F, the

replicate boxcores (B) are nested within D. Among versus within boxcore

variation are compared to see how many boxcores are needed to detect

differences between particular P. R and D combinations at a given time, or

between two times for a particular P. R and D combination. The appropriate

SAS model is:

Y=PD(P)B(PD)

P is tested by D(P), D(P) is tested by B(P D), and B(P D) is tested by the

error.

Multiple platform analysis would have to be done on data from a single

cruise. However, the importance of this analysis model is questionable, at

least in the end, because more can be done with the data by analyzing

multiple cruises together. The R are unique to a particular P, so R is nested

within P. The D, on the other band, are crossed with both P and R(P). For

BY C analyses, the appropriate SAS model is:

Y = P R(P) D P*D D*R(P),

or in SAS shorthand:

Y=PIDIR(P)

P is tested against R(P) which tacitly assumes R are random within a P. D

and P*D are tested against D*R(P). R(P) and D*R(P) are tested against

replicate error.

2.1.4 By Cruise*Platform Analyses

This is a trivial case with limited usefulness. It is only useful for

specific questions about R and D patterns at a specific platform at a specific

time (Table 2.5). It implies there is no generality. It is also the simplest

case. It is performed BY P C, and described by the model:

Y=RDR*D
Table 2.5. ANOVA table for by cruise-platform analyses. Model: Y= R D R*D, where R is declared a random effect.

1 R 5-1=4 3 4

2 D 5-1=4 4 1

3 WD (5-1)(5-1)=16 4 4

4 Rep. error (5)(5)(2-1)=25 40

Total (5)(5)(2)-1=49 49

This model can be used to discover directional (i.e., R) effects at specific

platforms that are different during each cruise. All terms are tested against

the error term.

2.1.5 Decomposition of Models for Trawl Data

All data from box cores (e.g., contaminant concentrations, grain size,

meiofauna, macroinfauna, and pore water toxicity tests) were analyzed using

the same statistical procedures. Data from trawls (e.g., metabolic induction

or macroinvertebrate reproductive effort) are a subset of the same design.

The preceding sections developed full statistical models where there

were 25 stations, i.e., 25 R*D combinations. This was true for all boxcore

samples. However, trawling occurred at only 2 R*D combinations, i.e., there

was only two stations. There is no need to specify R and 1), since there are

no replicates and this designation decomposes to just 2 stations (S), which

have been designated Near and Far. The following is a modification for each

model where R and D have been replaced by stations (S). In these

instances, P, C, and S are always crossed variables, and fixed effects.

Therefore, the effects are always tested against the mean square error term.

In the total design analyses P. C and S are crossed. The appropriate

SAS model is:

Y C P C*P S CS p5 CP'S,

orY=CIPIS

When the data set is analyzed by platform, the appropriate SAS model is:

Source df Test Against df if D is

continuous
Y= Cs C*S,

When the data set is analyzed by cruise, the appropriate SAS model is:

Y= PSP5

Analyses are performed by platform and cruise, and described by the model:

Y=s

2.2 Multivariate Analyses

The univariate analyses are adequate for testing the first revised null

hypothesis, where distance from the platform is the most interesting main

effect. A second issue is how all the variables measured, and there are

almost 200, relate to one another. In addition, many of the variables

measured came from a specific sample, meaning that a true multivariate

sampling design was followed. Also, distance is simply used as a surrogate

for the actual environmental gradient or contaminant exposure at each

platform. It is expected that the platform effect will cause many of the

variables to covaty with distance from the platform. Also, the platform effect

may not be symmetric around the platform, even though it is easiest to

sample that way. A directional effect would cause significant interactions,

which makes interpretation of the univariate ANOVA difficult. Concordance

of biological responses with increasing measures of contamination would be

strong circumstantial evidence that contaminants are causing the changes

that might be observed near platforms. Experiment-wise error rates must

be controlled, therefore a huge matrix of t-tests is not appropriate. The

second null hypothesis can be tested using multivariate statistical

techniques. Many exist, but Principal Components Analysis (PCA) was

chosen. This allowed the large data set of 91 abiotic variables to be reduced

to two factors that represent the first and second principal components

(PCi and PC2) that contain most of the variability in the data set. Then

regression or correlation analysis was used where PCi and PC2 were the

independent variables representing the covarying variables that make up the

contamination gradient and biotic responses were the dependent variables.

Within the contaminant gradient other gradients may be present that covary

with distance or direction from platforms, e.g., sediment grain size. The

2-9
data set was prepared for PCA by merging the means of all the transformed

pseudoreplicates according to the boxcore from which the data was derived.

This produced a data set with 300 observations (4C X 3P X 5D X 5R), one for

each boxcore sample.

2.3 The Sampling Design

The notation used in this description follows the standard practice of

using capital letters to denote a variable, and a lowercase letter to denote

the level or number of levels within a variable. The sampling plan was

designed to detect near-field impacts and contaminant gradients extending

out from a platform (P). The sampling design included a radial (R) pattern to

3,000 m distance (D) to define the platform's contamination gradient.

Oversampling within the near-field was designed to define the spatial scale

of the impact. There was an assumption that there was an exponential

decline in contaminant concentrations away from a platform. Two sampling

designs formed the basis of the GOOMEX Phase I program. Both rely on the

dose/response model but differ in details of the sampling design.

The first design provided for an assessment of the benthos and

included r radii (r=5), d distances per radii (d=5) and n pseudoreplicates

(rt= 2, or 3) per each R*D combination, which was defined as a station (S).

Since replicate cores come from within boxcores, the samples replicate box

cores, so box cores and stations are confounded. Therefore replicates are

considered pseudoreplicates (Hurlbert 1971). The number of r and d was as

high as possible, as these replicates were needed to test for directional and

distance patterns. The number of r and d were chosen based on the relative

benefits of high power compared to the cost associated with a large number

of replicates. It was determined that five (5) was the best number of radii

and distances to minimize costs and maximize samplings, given the

constraints of the total cost of the project. The total number of stations per

platform was 25 and the total number of measurements was 50 (for

meiofauna or chemical analyses) or 75 (for macroinfaunal analyses). The

overall sampling strategy provided a total sampling effort of 150 (or 225)

field samples per sampling time, or 600 (or 900) provided by four sampling

events or cruises (C). The design emphasized description of spatial patterns

(especially distance and direction from a platform) and estimation of

2-10
patchiness on spatial scales covered by replicate samplings at sites. The

sampling locations at the three study sites are summarized in Figures 2.1-

2.3.

The second study design employed a Near (or impacted) versus Far (or

unimpacted) pairwise comparison of indicators of contaminant exposure.

Due to the need for large amounts of biomass for the various work elements,

boxcorers were insufficient as a collection technique. Therefore, sample

collection primarily relied on otter trawis. Samples were taken as close as

possible to the platform (< 100 m) and at a comparison station ( 3000 m).

The studies utilizing this design employed laboratory techniques that were

generally time intensive, and/or relatively untested so that they were only

evaluated at the presumed extremes of exposure.

2.4 Variables and Transformations Used in the Study Design

Dependent and independent variables were measured (Table 2.6 and

Table 1.1). As mentioned, the underlying dose-response model determines

that dose or dose-related variables are independent variables and response

or response-related variables are dependent. Biological responses can be

considered as related to aspects of the environment that may be causing or

inducing the observed change or difference. Therefore, the biological

response parameters in this study design are dependent variables. The

spatial and temporal aspects of the design were considered independent

environmental variables that may be causing or co-varying with the

dependent biological responses.

The dose-response model coupled with an exponential decrease with

distance from the point-source indicates that contaminant concentration

and organism abundance variables should be transformed using the natural

logarithm. Percentage data, e.g. percent sand, or toxicity test results should

receive a special treatment, the "arcsin square root" transformation. Log

transformation of the variables was also appropriate for another independent

reason. An important assumption in the analysis of variance (ANOVA) is that

sample variances are homogeneous. This means that the variance of each

sample should be the same. A common feature of benthic organism
96°36W

5E

S5D

Matagorda Island-686 (2)

5A

5B

\

Feet 0 500 1000

I- - II Meters 0 100 200 300 400

Figure 2.1. Suimmaiy of boxcorer and trawl locations at MAI-686

for Cruises 1 (January 1993) and 2 (June 1993).

2-12

96°31W

28OON

Miles 0 0.5 \

Kilometers 0

27°5k

Cruisel n

BC Trawl Cruise 2
9636W

5Ea

Miles 0 0.5

I I Kilometers 0 1

Matagorda Island-686 (2)

5A

C]

N

N

N

N

N

N

N

5C

N

a5B

\

N

N

N

N

Cruise3 U

BC Trawl Cruise 4 C)

Figure 2.1 (cont).

9631 W

28°OON

N

27°5'S1

N

N

Summary of boxcorer arid trawl locations at MAI-686 for Cruises 3 (Janiiry 1994) and 4

(June 1994).

2-13

Feet 0 500 1000 - - I

Meters 0 100 200 300 400

a

5D
9614W 95°9W

.- Mustang Island-A85 (1) 2748N

70 m

Miles 0 05 1 Kilometers 0

Cruise 1 U

BC TrswI Cruise 2 A

4D

2-14

1Ec

3E

2D

3D, 2C

1D

Feet 0 500 1000

I- - I1 Meters 0 100 200 300 400

4A

\

27°46N

N

N

N

4B

Figure 2.2. Summary of boxcorer and trawl locations at MEJ-A85

for Cruises 1 (January 1993) and 2 (June 1993).
96°14W

Mustang Island-A85 (1)

70 m

70 m

80 m

MIes 0 0.5 -I

r

Kilometers 0

Crthse3

BC Trasi Cruise4 0

4D

D5A

Sc

El

2-15

SB El

1Er

3E !

3D 0 2C

1D

96°9W

27°46N

27°46N

4A

4C

Figure 2.2 (cant). Summary of boxcorer and trawl locations at

MIJ-A85 for Cruises 3 (Janll2ry 1994) and 4

(June 1994).

Feet 0 500 1000 - - I Meters 0 100 200 300 400
93°3630W 93°31 '30W

27°5630N High Island-A389 (4) SA

50 m

50m

Miles 0 0.5

Kilometei 0 1 Cruise 1 U

BC Trawl Cruise 2

lOOm

N

N

N

5D

4E

Feet 0 500 1000 - - I

Meters 0 100 200 300 400

Figure 2.3. Summary of boxcorer and trawl locations at H1-A389

for Cruises 1 (January 1993) and 2 (June 1993).

2-16

NSC

V

N

N

N

S58

N

N

N

N

N

N

N
93°3630W

High Islan

5Cm

50m

E

Cruise 4 0

Figure 2.3 (cont).

d-A389 (4)

lOOm

N

N

N

0 SD

N

N

N

N

4E

2-17

C

1D

B

N

27°5K15"N N

Summaxy of boxcorer and trawl locations at

HI-A389 for Cruises 3 (January 1994) and 4

(June 1994).

93°31 30'W

27°5630N

aSB

N

N

N

N

N

N

N

N

N

N

Miles 0 0.5

10Cm

N

N

Kilometers 0

4A

C

Cruise3

BC Trawl

FeeL 0 500 1000 - - I

Meters 0 100 200 300 400
Table 2.6. Partial list of variables being measured in the GOOMEX study (for details see Table 1.1).

Tissue Trace Metal Content

Tissue Hydrocarbon Content Pathology Bile Metabolites

MFO/P450 Induction

Pore Water Toxicity Tests Macrofaunal Abundance/Structure

Melofaunal Abundance/Structure

Ha.rpacticoid Life History Characteristics

Harpacticoid Genetic Diversity Macrofauna Reproduction Effort

abundance and chemical concentration data is that the mean and variance

are correlated, which violates the assumption of homogeneity of variances.

It is common in these cases to use a logarithmic transformation. The data

from the first two cruises was tested and it was found that the variances of

contaminant and organism abundance variables were stabilized by log

transformation.

2.5 Power Analysis

Power of the sampling design can be calculated where there is true

error replication. This is only true where multiple boxcores were taken,

such as at the Near and Far stations during the fIrst cruise. The design of

this analysis is already described. The most direct approach that is

compatible with the study design is to determine the detectable change in

the population at a given power (1-13) and sample size (n) calculated by:

(ta + t13)xSDx

Pore Water/Sediment Trace Metals

Pore Water/Sediment Hydrocarbons Mineralogy Sediment Grain Size

TOC/Carbonates

Sediment Redox

Water Dissolved Oxygen

Water Nutrients

Water Salinity

Distance From Platforms

Seasonal Variability

2

TI

where \ is the percent change in the population, SD is the pooled standard

deviation, ta and tj are tabled values for a two-tailed test assuming a pooled

estimate of variance from a large sample size, and X is the sample mean.

Values of a = 0.05, and powers of 0.95, 0.80, 0.50 are used in the analysis.

Dependent Variables Independent Covariates
During the first cruise, two stations at each platform were sampled

twice to test our ability to detect change with the sampling design being

adopted for the program. One station was in the inner ring, and one station

was at the outer ring. These stations were labeled Near and Far. A second

boxcore (BOX) was taken at each station. Therefore, there were 40 samples

(5 platforms X 2 distances X 2 boxcores X 2 subcores). This design is a fully

hierarchical sampling design described by the following SAS notation:

Y = P D(P) BOX(P D).

Platforms are unique, stations are unique to platforms, and each box is

unique to a station. As in all design, replicate (i.e., subcore) error is fully

nested. Y represents any variable measured from the boxcore. In each

boxcore, abiotic (e.g.. sediment grain size, trace metal concentration, and

hydrocarbon concentration) and biotic variables (e.g., meiofauna and

macrofauna populations) were measured. Using the above statistical model,

the variance components of each source of variation were calculated and

converted to a percent of the variance due to that component. All variables,

except for sediment grain size were transformed using the natural

logarithm.

The results of these calculations are found in Table 2.7. Station

differences, i.e., Near vs. Far differences, accounted for most of the

vai-iabffity. In most cases, except for sediment grain size, replication error

(i.e., error associated with subcores taken within boxes) accounted for more

error variance than between boxcore variance. All abiotic measures had

similar responses, i.e., most of the variation was among stations. However,

the fauna had a different response, with most of the variation at the platform

level of variance. The low composition of variance due to taking multiple

boxcores demonstrates that little precision is lost by taking two

pseudoreplicates from one boxcore.

The change in the variables response that can be detected with the

current sampling design can also be calculated. This is a power analysis.

The percent detectable decrease ()is calculated by:

= (ta+t)s[2/n.
Table 2.7. Variance components anaiysis for boxcore data. Results based on

two boxcores taken at 2 stations at all five platforms during the

first cruise.

apercent of variance due to each source. Calculated using a fully hierarchical model. All

variables, except sediment grain size, were transformed using natural logarithm.

2-20

Variable

Vax-lance Sourcea

Platform Station Boxcore Error

Sand 0 98 1 1

Silt 5 81 13 2

Clay 0 86 12 2

Sed Avg. 1.7 88.3 8.7 1.7

TotaIALK 0 89 4 7

UCM 0 83 2 15

Tota1PAH 7 75 0 18

HG Avg. 2.3 82.3 2.0 13.3

Al 0 96 2 2

Ag 0 86 5 9

As 0 92 4 4

Ba 0 98 2 0

Cd 25 73 1 1

Cr 29 59 3 9

01 3 90 4 3

Fe 44 46 5 5

Hg 22 73 1 4

Mn 0 90 2 8

Ni 0 94 4 2

Pb 3 51 9 37

Sb 23 3 2 72

Se 48 24 8 20

Sn 14 78 0 8

V 0 95 2 3

Zn 24 71 2 3

TM Avg. 13.8 71.7 3.3 11.2

Tot Meiofauna 61 29 2 8

Nematodes 60 31 1 8

llarpacticoids 63 12 7 18

Other Meiofauna 70 12 0 18

Macrofauna 46 19 5 30
Where t is the students t value at a = 0.05 (approximately 1.96), t13 is the t

value for the power of the test (1-0.8) at 0.2, $ is the root of the sample

variance, and n. is the sample size. The s value came from the variance

components analysis. Power analysis was calculated for two cases, where

two boxcores were taken (between box variation), or where two subcores

from within a box are taken. To calculate the percent detectable increase

(Aj) the following formula is used:

= 100[100/(100-4)-11.

Two replicates from within one boxcore are able to detect from 18 %

to 96 % change in the variables measured (Table 2.8). The sediment grain

size variables have the greatest discrimination at 18 %. Most other variables

are higher. As was found in the variance components analysis, little

precision was lost by using two pseudorepLtcates rather than two replicate

boxcores. For example, an 88% decrease could be detected for PAB with

two boxcores, and a 90% decrease could be detected with two subcores.

The use of pseudoreplicates does not compromise hypothesis testing

because interaction terms are used as the error terms for almost all tests

(Tables 2.2 to 2.5). The time level of replication is among radii and cruises.

The pseudoreplicates are used to improve estimates of values within

boxcores for multivariate analyses.
aThe % decrease detectable for each source of variance, i.e., between or within boxcores. Mean

square error term was calculated using a fully hierarchical model. All variables, except

sediment grain size was transformed using natural logarithm.

Table 2.8. Power analysis for boxcore data based on two replicate subcores

from two boxcores taken at two stations at all five platforms during the first cruise.

% Decrease Detectablea

Variable Between Box Within Box

Sand 28 18

Total ALK 87 74

UCM 98 97

Total PAIl 88 90

Al 38 26

Ag 81 68

As 59 40

Ba 86 30

Cd 80 58

Cr 49 42

Cu 58 35

Fe 55 36

Hg 63 58

Mn 56 49

Ni 54 32

Pb 98 95

Sb 93 93

Se 98 96

Sn 54 58

V 49 39

Zn 69 54

Total Melofauna 90 85

Nematodes 89 86

Harpacticoids 99 96

Other Meiofauna 93 93

Macrofauna 98 96
3.0 FIELD METHODS

This section provides a detailed description of how stations were

located and samples were taken and processed during the field collection

activities of GOOMEX Phase I.

3.1 Navigation

The Global Positioning System (GPS) was used for general navigation.

Selective Availability (SA) reduces the accuracy of GPS to approximately

100 m. To increase the accuracy of GPS, the Skyfix Precision Positioning

Service was used. Skyfix provided Differential GPS (DGPS) pseudo-range

corrections via INMARSAT-A satellite links to increase positioning accuracy

to ±3 m. The DGPS system was coupled to a computerized navigation

system that logged all sample locations as the samples were taken.

3.2 Hydrocasts and CTD Proffler

Continuous proffles of the following parameters were collected at each

station: salinity, temperature, and light transmittance (Figure 3.1). Also, at

each station, water was sampled from three depths: within the surface

mixed layer, below the mixed layer, and near the bottom. Discrete samples

were collected using PVC Niskin bottles attached to the CTD cable. Water

samples were collected for nutrient, salinity, and oxygen analyses. A

complete suite of duplicate samples was drawn from three stations at each

site for QAIQC purposes. Salinity samples were stored in air-tight glass

bottles and nutrient samples were frozen immediately in 50-mL seasoned

Nalgene bottles. The discrete salinity and nutrient samples were returned to

shore and analyzed by the Marine Technical Services Group of the Texas

A&M University Department of Oceanography. Salinity was measured on an

Autosal and concentrations of inorganic nutrients were determined using

AutoAnalyzer techniques. The cruise chemist analyzed the oxygen samples

at-sea using a modified Winkler technique.

The primary data collection device for water column physicochemical

measurements was a Sea-Bird Electronics, Inc. SBE-19 conductivitytemperature-depth (CTD) system, which outputs data to an IBM-compatible

3-1
Water Column

Profile Samples

-1

H

Nutrients

Oxygen

Salinity

SEACAT

Cast

Arrive on

Station

Y

Record

Station

Parameters

QUANTITATIVE

BOX

CORE

Evaluate for

Acceptability

Dismantle

Boxcore

+

Quantitative

Subcores

(# of subcores)

Relocate

Measure Redox

(if necessary)

Hydrocarbons I TOC

Trace Metals

Grain Size

Meiofauna

Pore Water Toxicity

IMacroinfauna

Figure 3.1. Activities at each quantitative boxcoring station including

sampling protocols for water column and boxcore samples.

3-2

(2)

(2)

(2)

(2)
computer for data processing and storage. This system is called a SEACAT

profiler. The SEACAT was operated with a variety of externally mounted in

situ sensors using proven hardware and software. Two SEACATs were

provided for each cruise to ensure that a complete backup system was

available. The system collected continuous profiles of conductivity,

temperature, and pressure from which salinity and density were calculated.

The auxiliary analog-to-digital channels on the SBE-19 were used to

continuously measure beam attenuation coefficient light transmittance (SeaTech, Inc., 25-cm transmissometer).

The SEACAT used temperature and conductivity sensors which have

an established record for reliability and long-term dependability. A pump

supplied water to the conductivity sensor in order to match the dynamic

response of the conductivity sensor to that of the temperature sensor. A

strain gauge supplied pressure/depth information. All sensors output

frequency signals were individually digitized twice per second. The SEACAT

records the digitized data internally in solid state memory. When the

SEACAT was brought back onboard, it was connected to a PC computer that

downloaded the data to disk. Sea-Bird software combines instrument

calibration data and sensor algorithms to compute temperature,

conductivity, salinity, and depth. The cruise chemist processed the CTD

data at sea and plots of vertical proffles of the raw data and the 1 -m averaged

data were generated on a Hewlett-Packard 7475A plotter.

3.3 Boxcoring and Trawling

A boxcorer was the technique of choice to quantitatively sample

sediments. The boxcorer was an Ocean Instruments BX-600 Deep Ocean

Corer outfitted with an extra spade; teflon-coated inner core box head;

stainless steel boxes fitted with stainless steel vegematic frame, rods, and

bolts; two sets each of 25 aluminum-anodized vegematic core tubes and

stainless steel screens with PVC frames to fit the core tubes; jacking dollies;

vent doors; and lifting and closing cables. The boxcorer provides an

effective penetration of up to 50 cm depending on sediment texture and the

water depth of deployment. Two complete boxcorer systems were provided

on each cruise. The 0.25-rn2 boxcore was subdivided into twenty-five

100-cm2 compartments and used to sample sediment for each study

3-3
element. To avoid bow waves, which can disrupt surficial sediments, the

boxcore was deployed by stopping just above the sediment/water interface

followed by a free fall to the seabottom. The allocation of subcores to

individual work elements is depicted in Figure 3.2.

The subcores around the perimeter of the boxcore were used for pore

water toxicity testing. The nine interior subcores were distributed among

the chemistry (4), macroinfauna (3), and grain size/mineralogy (2) work

elements. Meiofauna samples were extruded from subcores placed in the

grain size subeore section. The assignment of cores was determined by a

random ordering of the nine interior subcore locations. The random

number generation function used for determining the ordering of the

subcores is called RAN3. RAN3 is Knuth's (1981) suggestion for a portable

random number generation routine and is a subtractive method rather than

a linear congruential model.

A boxcorer configuration form was used to record the condition of the

boxcore and provide assignment of subcores to work elements. These forms

were bound and consecutively assigned to boxcores as they were taken. atsea. The condition of the boxcore was determined on a qualitative scale:

Good (G) - Acceptable (A) -

Poor (P)

Undisturbed surface in the core.

A slight amount of disturbance of the core's surface with little perturbation (mixing) of the vertical structure (integrity) of the sample.

Considerable vertical perturbation of the core's vertical structure of the core. Boxcores

determined to be poor were resampled.

Invertebrates and demersal fish were collected by otter trawl. The

primary purpose of trawling was to collect specimens for chemical

contaminant analysis, megafaunal invertebrate biological studies,

detoxification, histopathology, and stomach content analyses. Trawl samples

were sorted and target species were selected by the onboard taxonomists

(Figure 3.3). Otter trawls were of the semi-balloon type. The mesh

measured 4.04 cm (1.5") and the mouth opening was 17.58 m (50'). The

trawls were deployed with 67.58 m (200') bridles and were spread with

1.830 m X 0.9 15 in (6' X 3') wood doors. A spare set of smaller doors 1.525

m X 0.9 15 in (5' X 3'), was carried on-board the ship as backup. Trawls
50cm

50cm

I0 Meiofauna Core Tubes

Figure 3.2. Boxcore illustrating "vegematic" partitioning. Sub samples were

randonily assigned to the inner boxes. (MACRO=macroinfauna;

PW/TOX=pore water toxicity testing; tIC CHEMhydrocarbon

chemistry; TM CHEM=trace metal chemistry; GPN SZ=grain size).

3-5

pwI TOX

Area of Greatest

PwI

TOX

Potential

pw/ TOX

Edge Effect

PwI

TOX

PwI

TOX

MACRO MACRO GRN

SZ0

PW I

TOX

MACRO HC

CHEM

TM

CHEM

PW/

TOX

PWI

TOX

GRN

SZ0

HC

CHEM

TM

CHEM

PWI

TOX

pwI TOX pwI TOX pwI TOX pwI

TOX

Pw/

TOX
Invertebrates

All Gravid

Invertebrates

Presented

Target

HTrace Metals

Hydrocarbons

7

SORT

Target

H Histopathology

-1 MFO

H Bile

-J Hydrocarbons

-j Trace Metals

-i Voucher

Specimens

Fish

Non-Target

Archive

Figure 33. Sample processing protocol for trawl collections.

3-6

Arrive on

Station

Record

Station

Parameters

Boxcore

Conduct

Trawis

Non-Target

Archive

MFO

-f Reproductive

Effort
were made perpendicular to the radials around the rig when possible at a

distance of 100 m or less from the platform allowing for safety

considerations. Trawl times on bottom varied from 10 to 15 mm. at 0.5

knots, the object being to recover a sufficient number of live specimens.

Shorter durations did not recover sufficient quantities and longer trawis bad

a high degree of mortality in the catch.

3.4 Sedimentology

Sediment samples for sedimentological analyses were taken from two

subcores at each quantitative boxcore station (Figure 3.2). The top 2 cm was

sampled using a spatula or scoop. A minimum of 50 g of sample was

collected in a plastic bag and stored refrigerated (4 °C), not frozen. This

sample was used for mineralogy and grain size analyses.

Redox potential (mV) was measured by direct insertion of a

combination platinum electrode into sediment. The electrode was

calibrated with a ferrous-ferric solution every six hours and polished to

expose a bright surface alter each reading. The electrode was inserted to a

uniform sediment depth of 2 cm. Two readings were taken per boxcore

from the subcores used for sedimentology.

3.5 Sediment Samples for Contaminant Chemistry

Duplicate sediment samples for trace metals and hydrocarbons were

taken from each boxcore (Figure 3.2). Between samplings the subcorers for

organic contaminants were thoroughly rinsed with water, dried with

acetone, cleaned with metbylene chloride between samplings, arid covered

with combusted aluminum foil after cleaning to minimize airborne

contamination. Samples were taken from the upper 2 cm of the sediment

with a teflon-coated scoop. The scoop was rinsed with distilled water,

acetone, and methylene chloride prior to each sampling. Separate samples

were taken for hydrocarbons and trace metals. Total organic and inorganic

carbon were measured on a subsample of the hydrocarbon sample.

Hydrocarbon subsamples were immediately placed into precleaned

(combusted at 425 °C) 1/2-pint glass jars with teflon-lined lids (-150 g).

Trace metal samples were immediately placed into plastic bags (-150 g).

3-7
All sediment samples for contaminant chemistry were stored frozen

(-20 °C).

3.6 Biological Tissue Sampling for Chemistry and Toxicology

The goal was to sample enough biomass of common macroinfauna,

mobile invertebrates, and fish at both Near and Far stations to supply all

study components with the tissues needed. Megafaunal invertebrates and

demersal fish were collected by trawling. As far as possible, the organisms

processed at the Near and Far stations were the same species. The goal for

chemistry/detoxification samples was five species of megafaunal

invertebrates and three species of demersal fish.

3.6.1 Megafauna - Invertebrates

3.6.1.1 Taxonomic Identification and Sorting

The procedures followed for processing megafaunal invertebrates are

outlined in Figure 3.4. For Cruise 1, invertebrates were collected by trawl

and boxcore; however, on subsequent cruises, megafaunal invertebrates were

exclusively collected by trawl. The specimens were roughly sorted (crabs,

shrimp, etc.), taxonomicafly identified, and the target species designated.

All dissections were performed with solvent-cleaned utensils in a clean

environment. Collections were repeated until sufficient biomass of the

target species was collected. Within practical limits, specimens of the

target species that were collected were of approximately the same size class.

Voucher specimens of target and non-target invertebrate species were

preserved in 10 % buffered formalin and returned to the laboratory for final

identification.

3.6.1.2 Chemistry and Toxicology

Invertebrate species for the chemical and detoxification studies were

individually tagged and maintained alive until processing. Some species of

invertebrates required different tissues for trace contaminant and

detoxification analyses (Figure 3.5). All animals were rinsed with reagent

water to remove extraneous materials prior to sampling. For detoxification
Reproductive Effort See Fig. 3.7 I Target Species I Specimens for Toxicology and Chemical Analysis See Fig. 3.5 Remove Tissues Preserve Remains of Specimens in Buffered Formalin and Rurn to the LabMEGAFAUNAL INVERTEBRATES All Gravid invertebrates Preserved Identhy Target SpeciesField Collections SORT Voucher Specimens Preserve Specimens lnBtiferedFormalin and Rurn to the Lab DEMERSAL FISH Non-Target Species Preserve Specimens In Buffered Formalin and Rdurn to the Lab Figure 3.4. Sample processtig protocol for megafaunal Inveitebrates from trawis.
HE PAID- PANCREAS GREEN GLAND REMAINS SOFT I1SSUE Contaminant Chemistry/Toxicology Trawl Place in Seawater Refrigerate Taxonomicaily Sort Target: Megainfauna 3 SpecIes x 3 Replicates x 2 Slatlons / Site Mobile invertebrates & Demersai Fish 5 Species x 3 Replicates x 2 Stations / Site Figure 3.5. Sample processing protocol for megafaunal invertebrate and demersal fish tiss

contaminant chemistry and toxicology. GALL BLADDER STOMACH CONTENTS UVERS 

MFO HC/Th 

-20°C -20°C liq. N2 -20°C 10Oii 30g 5g 30g MEGAINFAUNAL DEMERSAL ASH INVERTEBRATES __J Taxonomlc Idenlificatton Taxonomic identification Archive Non. Target Organism Identify I TargetSpecies Archive Non- Target Organiam identity Target Species Voucher I 

DISSECT DISSECT
studies, large animals were dissected and small specimens were sampled

whole. Only the hepatopancreas from crabs, scallops, and gastropods and

the green gland from shrimp were used in detoxification studies. All

dissections were carried out on ice and samples were immediately frozen in

liquid nitrogen. For trace contaminant analyses, the residual tissues not

used in detoxification studies and/or additional whole samples were placed

in clean glass jars with teflon-lined lids (organic) or acid-cleaned plastic

containers (trace metals) and stored frozen (-20 °C). Individual species

were sampled in triplicate when possible. Voucher specimens were

collected and preserved for all target organisms.

3.6.2 Megafauna - Demersal Fish

Procedures for processing demersal fish are outlined in Figure 3.6. All

tissue sampling was conducted in a clean environment and all utensils were

precleaned by water, acetone, and metbylene chloride rinses. Once the

trawl was onboard, the fish were separated from the invertebrates and

sorted. Live fish were placed in cool, aerated seawater in large coolers. The

fish were taxonomically identified and the target species designated.

Trawling was repeated until sufficient biomass of the target species was

collected. At each site, 20 individuals of the target species were collected

for histopathology.

At each station, all fish taken in each trawl were examined to assay for

gross pathological abnormalities. All specimens were preserved in

Dietrich's fixative. A thorough external inspection of the body surfaces, fins,

eyes, branchial chamber, and buccal cavity was performed on preserved

samples upon arrival in the laboratory. All observations and measurements

were recorded on a data sheet.

The following instructions were followed:

Body surfaces and fins: Any discolorations of body surfaces (i.e., darkening, hemorrhaging, cloudiness), raised scales, white

spots, or parasites visible to the naked eye were noted. Any

lumps, bumps, or other growths, ulcerations, fin erosion, skeletal deformities, swelling of the anus, or any other abnormal conditions were noted as well.

Eyes: The eyes were checked for cloudiness, hemorrhage, exopbthalmia (i.e., pop eye), and/or depression in the orbits.

3-li
MEGAFAUNAL INVERTEBRATES See Fig. 3.5 Examine for pathology & remove tissues Preserve remains of specimens In buffered formalin and return to the lab DEMERSAL FISH Identify Target Species Target Species Preserve specimens in buffered formalin and return to the lab Figure 3.6. Sample processing protocol for fish taken from trawls. I I Histopathology Specimens for toxicology and chemical analysis Stomach food analysis Voucher specimens Field Collections SORT Non-Tar

Preserve 

in buffer

and retur
(C) Branchial chamber: The opercula were lifted and the branchial chambers examined for any perforations or deformities. Color,

erosion, deformities, and parasitic infestations in the gills were noted. The chambers internal surfaces were examined for

lumps, bumps or other growths, ulcerations, or any other abnormal conditions.

(D) Buccal cavity: The mouth was examined for any deformities, ulcerations, and/or growths.

(E) All specimens with gross lesions or other suspect conditions, as

identified above, were processed and coded individually.

The entire length of the abdominal cavity was cut open

using scissors or a sharp knife. The scissors were gently

inserted into the abdomen near the anus and an incision to

the operculum was made. Care was taken not to injure the visceral organs.

For fishes smaller than 15 cm, the entire fish was saved.

Tissue samples (visceral cavity and abnormalities excised) were placed in Ziplock® bags with sufficient perforations.to permit a flow of fixative thiough the bag. Whole fish and

heads were tagged with all pertinent information and placed directly into the fixative. Specimens were fixed in Dietrich's fixative.

The pertinent information relating to each individual sample was carefully recorded on data sheets.

(F) In addition to those specimens collected with visual

abnormalities, a random, representative subset of specimens was collected from those fish without visual abnormalities. From

specimens of target fish species that "passed" the gross pathological inspection, a maximum of 20 individual fishes were preserved.

Proper fixation of specimens was critical to the ultimate quality of the

data obtained. Fish were examined and fixed while still alive or shortly after

death.

Stomach contents were collected for as many species as possible that

were also collected for trace contaminant analysis. Stomachs were

preserved in 10 % buffered formalin For toxicology, bile was removed using

vacutainers and stored at -20 °C until analysis. Next, livers were removed

and placed on ice and either subsampled individually or pooled depending

on the size of the livers. Samples for enzyme assays and P450 1A mRNA

3-13
were frozen in liquid nitrogen (LN2) until analysis. Both livers and stomach

contents were sampled from fish and used for hydrocarbon and trace metal

analyses. Hydrocarbon samples were placed in a combusted glass jar with a

teflon-lined lid. Trace metal samples were placed in clean plastic

containers. All tissue samples for contaminant analysis were stored frozen

(-20 °C). When practical, individuals of approximately the same size were

collected.

All target and non-target specimens were preserved in 10 % buffered

formalin and returned to the laboratory for final identification. In any single

collection, if the amount of non-target specimens occupied more than one

five gallon sample container, then a representative subsample was taken.

Specimens are retained as voucher specimens at the Texas Cooperative

Wildlife Collection (TCWC).

3.7 Meiofauna

Two core samples were taken from each boxcore sample and stored

for meiofaunal community analysis. Each core sample was from a different

randomized subcore (Figure 3.2) to minimize autocorrelation among the

replicates (Eckman 1979). Meiofauna were collected by a 1.9-cm i.d. core

tube (Montagna 1991). The two core tubes were mounted inside a subcore.

A mounted core tube ensures that the meiofauna are collected from an

undisturbed surface. Taking the sample from inner subcores reduces edge

effects (Eckman and Thistle 1988). Bow waves of sampling devices in deep

water can have an enormous impact on surface dwelling meiofauna (Hulings

and Gray 1971). The 0 to 2 cm section of sediment was extruded out of the

core tube and placed into a 50 cc plastic centrifuge tube. The meiofauna

were anesthetized by adding 7 % MgC12 and waiting about 5 mm. The

sample was then preserved with an equal volume of 10 % buffered formalin

(yielding a final concentration of 5 % formalin) Recovery of the animals for

community analyses was performed at a land-based.

For life history and reproduction analyses, three species of

harpacticoids were chosen from the materials obtained in the meiobenthic

community structure study. No additional sampling was required. For the

meiofauna genetic variation analysis, further aliquots of sediment were

collected. Since the meiofauna core tubes are about 4 cm2, there was about
90 cm2 remaining in each subcore. The 0 to 2 cm of the remaining

sediment in each subcore was collected at 50 m and 3000 m stations. The

sediment was preserved with EDTA buffered alcohol and stored at 4°C

(Dessauer et aL 1990). Meiofauna were extracted at a shore-based laboratory

for DNA analysis.

Sediments were collected during GOOMEX Cruise 2 to provide live

meiofauna for toxicity testing. The surface 2 cm of sediment remaining in

the boxcorer subcores after the community samples were removed were

retained and kept fresh by aeration. Live meiofauna were extracted at a

shore-based laboratory to attempt toxicity testing on indigenous species.

3.8 Macroinfauna Community Studies

Three subcores were used for analysis of macroinfauna. To minimize

the effects of disturbance, only the nine central compartments were used

for macroinfaunal samples. The three subcores, or samples, to be used for

analysis were randomly chosen prior to deploying the boxcore. Each of the

subcores was carefully extruded to a depth of 10 cm and placed in a shallow

pan. The 10-cm depth was chosen because extensive prior experience in

the northern Gulf of Mexico, in addition to extensive documentation in the

periodical literature, indicates that the majority of small infaunai organisms,

which constitute the majority of specimens collected, are found in the

upper 1-2 cm of sediment. Very few deep-burrowing organisms are missed

by this process. In addition, past experience, especially in deeper water,

has shown that sediments below 10 cm tend to be thick clays which require

a great deal of processing and yield little additional biological information.

The sample was then placed on a 0.5-mm mesh sieve, submersed in a pan of

seawater, and the sieve was rotated and agitated until all sediments smaller

than 0.5-mm passed through the mesh. The remaining deeper sediments

were examined for the presence of large, deep-burrowing organisms.

Material retained on the sieve was placed in a prelabeled plastic jar and

fixed with 5% buffered seawater-forrnalin. The outside label (site, station,

date, replicate) was written with grease pencil. The inside label (same

information) was a plastic Dymo label. These labels were used instead of

paper labels because of the probability that paper labels would be abraded by

shell hash, sand, or gravel.
3.9 Megafauna - Invertebrate Reproductive Studies

The protocol for field collection for the megafaunal invertebrate

reproduction study was greatly revised from the original plan due to

difficulties in collecting sufficient numbers of individuals and species during

Cruise 1. The original target for this work effort was 10 individuals from 10

different species. Five species were to be taken from boxcore samples and

five species from trawis. To fulfill this requirement, one entire boxcore was

dedicated to this work element on Cruise 1 and animals were taken from

multiple trawis. However, very few animals were obtained from the boxcore

and further boxcoring did not significantly increase the number of

individuals or biomass collected. Therefore, the sampling of megafauna from

the boxcores for the reproductive effort was discontinued after Cruise 1.

The number of trawis was increased to provide more individuals and to

increase the likelihood of overlap of species between the Near and Far

stations.

After retrieving each trawl, the catch was rinsed and roughly sorted

into four groups: echinoderms, molluscs, shrimp, and crabs. The animals

were stored at 4 °C, if immediate fixation was not possible. The

echinoderms, molluscs, and shrimp were kept in seawater and the crabs

were placed in isotonic MgC12 to relax them. All individuals were placed in

fixative within three hours of collection to minimize autolysis from digestive

enzymes and the effects of capture. Egg sacs from all gravid crabs were

either immediately frozen in liquid nitrogen to be processed for the

immunological probe study or were placed in fixative for later microscopic

and histological examination.

Size structure was used as a surrogate for age structure because

growth curves were not available for most of the invertebrate species.

Therefore, all specimens of the target species were counted and measured

in the field (to the nearest mm). The dimensions measured were: bivalves,

maximum posterior to anterior length; crabs, maximum carapace width;

shrimp, tip of rostrum to the rear of the carapace; mantis shrimp

(stomatopods), maximum length (during Cruise 1 the measurement was

made from the eyes to the rear of the carapace); starfish, central disc width.

For Cruise 2, individuals for each species were randomly chosen and length

was measured for up to a maximum of 50 individuals. If larger numbers of

3-16
shrimps or crabs were collected in a single trawl and a gravid (external eggs

visible) female was found, all individuals were measured regardless of the

final numerical total. On Cruises 3 and 4, all individuals of the target species

were measured from every trawl to determine catch per unit effort. Catch

per unit effort was calculated as follows:

cpus total number of indivithiaLs caught tn a trawl

distance ti-awled X width of ti-awl

During CruIse 2 several additional observations were initiated at the

time of collection to determine the sex and to qualitatively describe the

stage of reproductive development for individuals of all shrimp and crab

species. For each shrimp collected, an external determination of sex was

made based on the presence of the thyleca in females or the claspers in

males (King 1948). Each female was further examined and a numerical

value for the stage of reproductive development was assigned based on the

size and color of the ovary visible through the carapace (Chamberlain and

Lawrence 1983). The characteristics used to determine the stage of

reproductive development based on the appearance of the ovary are

summarized in Table 3.1. Crabs were sexed based on the appearance of the

ventral carapace (Hill et al. 1989). The dorsal carapace of females, not

preserved for histological analysis, was removed and a visual determination

of reproductive stage was made based on the development and color of the

ovary (Hard 1942). Definitions of the developmental stages used for female

crabs are summarized in Table 3.2. Beginning on Cruise 3, stomatopods and

hermit crabs were also sexed externally by visual inspection. External

determination of sex in stomatopods was made based on the presence of

claspers at the base of the sixth set of legs, indicating a male or, in their

absence, a female. Hermit crabs were sexed according to the presence of

gonopores on the third set of legs, for females, or their absence, for males.

Preparation for fixation depended on the species (Figure 3.7). For

crabs, a portion of the dorsal carapace was removed to allow penetration of

the fixative into the tissues. For shrimp, during Cruise 1, the tail end was

cut off just behind the carapace and discarded; only the head and thorax

were preserved. Based on histological analysis, a new procedure was

developed for shrimp after Cruise 1. The tail of the shrimp was sliced open
Table 3.1. Visual reproductive development for female shrimp (after Chamberlain and Lawrence 1983).

Numerical Developmental Stage Appearance of Ovary Designator

1 Undeveloped No ovary visible externally, no pigmentation.

2 Beginning Development Anterior and posterior lobes of ovary faintly

visible.

3 Nearly rnpe Ovaries easily recognizable externally, anterior and posterior lobes enlarged and

pigmented.

4 Ripe Anterior and posterior lobes of ovary appear broad and dark, may even determine recent mating if the spermatophore is still visible in

thylecum.

5 Spent Difficult to distinguish from Stage 2 without dissection, posterior lobe may still be

pigmented and slightly enlarged.

Table 3.2. Visual reproductive development for female crabs (after Hard

1942).

Numerical

Designator Developmental Stage Appearance of Ovary

3-18

1 Undeveloped Ovary small and inconspicuous, white in color, spermathecae large and pink in color.

2 Early Development Ovaries Increased in length and diameter, orange

in color, spermathecae decreased in size.

3 Mature Ovary bright orange and large, no sponge or egg

remnants on swimmeretes.

4 Spawned Ovary bright orange and somewhat smaller than

stage 3, sponge or egg remnants found on

swimmerets.

5 Spent Ovary collapsed, grey or brownish in color, sponge or egg remnants found on swimmeretes.
on the ventral surface, a piece of the carapace removed, and the head split

open ventrally. This allowed for better penetration of the fixative, ensuring

better preservation of the digestive tract and fixation of the complete

reproductive system. Hermit crabs were carefully extracted from the shell

and a small cut was made along the dorsal carapace. For starfish, one arm

was removed flush with the central disc. After Cruise 1, this procedure was

changed and a minimum of two arms (depending on the size of the

individual) were cut off to ensure proper preservation and decalcification of

the individual animals collected. Scallops were placed in cold water until

they relaxed and gaped. allowing a blade to be slipped between the valves to

cut the adductor muscle. Tissues were removed from the shell for fixation.

For stomatopods, the tail was sliced open on the ventral surface.

Individuals were preserved in Bouin's fixative. On Cruise 1, the largest

individuals of each species were preserved. On subsequent cruises, an effort

was made to preserve equal numbers of males and females (5 each), again

retaining the largest individuals of each sex. The samples in fixative were

stored in the refrigerator aboard ship for 48 hours, after which the jars were

sealed and stored at room temperature.

Any female portunid crabs not used for histological analysis were

frozen in liquid nitrogen for gonadal analysis using the iimnunological probe.

3.9.1 Immunological Probe Development and Incubation

The goals of this portion of the program were two-fold. First, to

produce immunological probes that react to egg protein in specific species

of invertebrates. Those probes be used to determine the quantitative state

of reproductive development in individuals and second, to use the probe to

determine instantaneous rates of reproduction in these species by assessing

the incorporation of labeled leucine into egg protein over time.

The development of immunological probes sensitive to egg and sperm

protein for invertebrate species depends on the collection of sufficient eggs

or sperm from the species of interest. During Cruise 1, all egg sacs from

crab species were collected for the immunological probe study. Females of

other species found to be gravid were also sampled. For example, the ovary

and testis of scallops were removed and frozen separately in liquid nitrogen.

These samples were returned to the laboratory to be used in the

3-19
Trawl

Collection

Measure All Individuals

Crab

Shrimp

Echinoderms

Molluscs

Arms removed

Crack shell

Gastropod

Select Gravid

Individuals and

' Place Gonads or

Eggs in LN2

Piece of dorsal carapace removed

Cut tail open & remove small piece of

dorsal carapace

Cut collumellar muscle

Bivalve J Cut adductor muscle

L70° EtOH (4 to 8 hr x 2)1

Store in 70% EtOH

Figure 3.7. Megauna1 invertebrate life history sampling protocol.

3-20

48hr fixation in cold Bouin1s

Wash tissue at room temperature

150%EtOH(4to8hrx2
development of an immunological probe for quantitative reproductive effort

studies. The specific details for the laboratory development of the

immunological probe are presented in Section 3.7.3.

Once developed, the immunological probe can be used to separate

gonadal protein from somatic protein to determine the instantaneous rate of

reproductive development. Inoculation experiments were conducted on

Cruise 2 at two of the three sites to determine instantaneous reproductive

effort. A portunid crab and scallop were chosen. Twenty individuals of two

different species were injected with 2 mCi of 14C leucine. Subsets of five

individuals of each species were incubated separately for 1, 2, 5 and 10 h in

seawater at ambient temperature, after which they were immediately frozen

in liquid nitrogen. Use of the immunological probe in the treatment of

these samples for determination of instantaneous reproductive rate is

described in Section 3.7.3.

3.10 Pore Water for Toxicity Testing

A composite of 16 subcores was used to provide a sample for pore

water toxicity testing (Figure 3.2). The top 2 cm of sediment from each

subcore was carefully removed with a teflon-coated scoop and placed in a 4-

liter precleaned polyethylene container. The containers were stored at 4 °C

until transported to the shore-based laboratory.
4.0 LABORATORY METHODS

This section provides a detailed discussion of laboratory protocols and

procedures used to produce the analytical results and data for GOOMEX

Phase I.

4.1 Physicochemical Measurements

4.1.1 Nutrients

Water samples were analyzed for phosphate, silicate, and nitrate using

an Alpchem Analyzer or a Technicon AutoAnalyzer. The system was

standardized by analyzing calibration standards of all nutrients prior to and

after each set of samples. The peak height data were collected with a PC

and peak heights from the AutoAnalyzer were converted to nutrient

concentrations in iM by linear interpolation from absorbance relative to the

calibration standards.

Silicate was determined by the ammonium molybdate. tartaric acid,

stannous chloride method; phosphate by ainmonium molybdate, hydrazine

method; and nitrate by sulfanilainide, NEDA method (after reduction to

nitrite with a cadmium reduction column). All of these analyses except

phosphate. which was heated in a 70 °C bath, were conducted at room

temperature (25 'C). Colorimeter interference filters in the spectrophotometers of the AutoAnalyzer were 660 nm (sificate), 880 nm (phosphate) and

550 nm (nitrate and nitrite).

For each cruise, the precision and accuracy of the analysis of each

nutrient analytical technique was evaluated by analyzing at least 20 replicates

of the highest calibration standard. The standard deviation in pM was 0.05

for a 6-.tM nitrate standard, 0.005 for a 0.50-jiM phosphate standard, 0.05

for a 6.5-p.M nitrate standard, and 0.005 for a 0.50-p.M nitrite standard. The

coefficient of variation was 1 % for each group of replicates.

4.1.2 Salinity

Salinity samples were analyzed using a Guildline Model 8400 Autosal

Laboratory Salinometer. The specffications of the Autosal are as follows:
The Autosal system uses conductivity to directly determine salinity. Each

sample was analyzed three times to ensure an accurate analysis and the

mean was reported. The sample was held at a constant temperature in a

water bath while the conductivity was measured. The conductivity and

temperature were then used to calculate salinity based on the practical

salinity scale.

4.1.3 Dissolved Oxygen

Samples were collected and analyzed for dissolved oxygen by the

microWinkier technique (Carpenter 1965). Oxygen samples were the first

samples drawn from the Niskin bottle. After rinsing with an aliquot of

seawater, the oxygen (iodine) flasks were filled using a seasoned piece of

tygon tubing from the bottom of the flask. The samples were preserved

using a divalent manganese solution, followed by the addition of strong alkali

to each sample. Care was taken to avoid introduction of any bubbles into the

iodine flasks along with these reagents. The precipitated manganous

hydroxide was dispersed evenly throughout the seawater sample, which

completely filled the stoppered flask. Any dissolved oxygen rapidly oxidizes

an equivalent amount of divalent manganese to basic hydroxides of higher

valency states. When the solution is acidified in the presence of iodide, the

oxidized manganese again reverts to the divalent state, and iodine,

equivalent to the original dissolved oxygen content of the water, is liberated.

This iodine is titrated using standardized sodium thiosulfate and the oxygen

content in each sample is calculated. The microWinkler method has a

precision of 0.01-mL/L oxygen at STP. Oxygen concentrations were

measured at sea by the onboard chemist.

4.1.4 QualIty Assurance

Quality assurance activities include proper care and maintenance of

instrumentation, pre-cruise calibration of instruments, and calibration

Range: 0 to 40

Accuracy: ±0.003

Temperature Compensation: ±0.0007/ °C
checks for parameters during the cruises. Care was taken to ensure that all

instruments were in calibration before each cruise. The Sea-Bird SEACAT

SBE- 19 is calibrated by returning it to Sea-Bird. Sea-Bird has the SEACAT

calibrated by the Northwest Regional Calibration Center, which is operated

under contract to NOAA.

4.2 Sedimentology

Sediment ancillary data included mineralogy, grain size, total organic

carbon content, total inorganic carbon content, and redox potential (Eh).

The analytical protocols utilized are compatible with those currently used in

the NOAA National Status and Trends Program (NS&T).

4.2.1 Grain Size

Fifteen (15) to 20 g of sample were placed in a large glass jar. This

sample size minimizes the interaction of individual grains with each other

during settling, avoids flocculation, and maximizes the amount of material to

be weighed (i.e., small sample size increases errors in weighing). The

sample was treated with between 50 to 100 mL of 30 % hydrogen peroxide

for 12 hours prior to analysis in order to oxidize organic matter. The

amount of hydrogen peroxide added varies with the amount of organic

material present in the sample. In general, hydrogen peroxide solution is

slowly added to the sample until effervescence is no longer observed. The

sample was washed with distilled water to remove soluble salts. Four

hundred (400) mL of sodium hexametaphosphate solution (-5.5 gIL) was

added to disperse the sample, followed by shaking for -24 hours on a shaker

table. A 62.5 p. screen was placed over a 1-liter graduated cylinder. The

dispersed sediment was poured over the screen and washed with dispersant

to rinse any remaining fine-grained sediment into the cylinder. This

procedure separates the gravel/sand fraction (on the screen) from the

silt/clay fraction (in the cylinder). The coarse fraction was washed into a

preweighed beaker with distilled water and placed in an oven (100 to 130

°C) for 24 h. The beaker was removed from the oven and left to cool. The

beaker was allowed to equffibrate with moisture in the air. The beaker was

weighed to 0.1 mg with an analytical balance. The sand fraction was dry

4-3
sieved at 2-mm (1 phi) and 62.5-p. (4 phi) intervals to separate gravel from

sand-sized material. The weights of the gravel (> 2 mm) and sand-sized

(62.5-p. to 2 mm) material were recorded on data sheets.

The graduated cylinder containing the silt/clay material was filled to

exactly one liter of dispersant solution. The cylinder was stirred vigorously

and left to stand for one day. If the cylinder showed no sign of flocculation,

analysis was continued. If the sample flocculated, the sample was discarded

and the procedure was repeated. The fine fraction was analyzed at 4-phi

and 8-phi intervals. Two labelled beakers were preweighed to 0.1 mg. The

cylinder was stirred vigorously starting at the bottom and working up until

all the sediment was uniformly distributed throughout the cylinder. At the

end of the vigorous stirring, long smooth strokes of a rod the full length of

the cylinder from the bottom until the stirring rod breaks the surface, were

used to homogenize the suspension. As soon as the rod emerged for the last

time, the timer was started. At the end of 20 seconds a pipette was

inserted to a depth of 20 cm. Exactly 20 mL was withdrawn;this is the 4-

phi aliquot. The suspension was pipetted into a preweighed beaker, the

pipette rinsed with 20-mL of distilled water and the rinse water was added

to the same beaker. At the 2:03:00 (two h, 3 mm.) time, a 20-mL aliquot

was withdrawn at a depth of 10 cm; this was the 8-phi aliquot. The

suspension was pipetted into a second preweighed beaker. The pipette was

rinsed with 20 mL of distilled water and the rinse water was added to the

beaker. The beakers were placed in an oven and evaporated to dryness for

at least 24 hours at 100 to 130 °C. After 24 h the samples were removed

from the oven and allowed to cool to room temperature. The sample was

allowed to come to equffibrium with the moisture content of the ambient air.

The beakers were weighed to 0.1 mg with an analytical balance, and the

weights recorded on a data sheet.

The 4- and 8-phi dry weights include the weight of the added

dispersant. The dispersant weight (gIL) was multiplied by the fraction of

the total solution removed (20/1000) and subtracted from the aliquot

weight. This total was then multiplied by 50 (1000 mL/20 mL) to yield the

sample weight of the silt clay fraction.

Three weights (wt) are needed to calculate the total dry sample

weight.
wt. sand (2 mm to 62.5 u size range) + wt. gravel (2 mm and greater size

range) + wt. of 4-phi residue total dry sample weight

% gravel - weight gravel fraction

total dry sample wt

wt sand fraction %sand= total dry sample wt

% silt [(wt 8- phi residue - dispersant) X 50]

total dry sample wt

%clay ([(wt4-phi- 8-phi) - dispersant]X50]

total dry sample wt

Duplicate samples were run every 20 samples. Results were reported

to three (3) significant figures.

4.2.2 Mineralogy

X-ray diffraction analysis was conducted to characterize the bulk

mineralogy of the sediments. The preparation procedure consisted of gently

crushing the sample, reducing skeletal and other coarse grains to a uniform

fine silt particle size, without causing changes in the carbonate or clay

phases. The sample powder was packed into a "dry powder type" sample

holder using the back-loading method of Moore and Reynolds (1989). This

method of sample preparation results in maximum random orientation of

mineral crystallites.

Each sample was subjected to Cu Ka radiation and scanned from 2° to

60° 2q on a computer automated Rigaku X-ray diffractometer. After several

preliminary analyses, the optimal scan speed, sampling interval, and slit

sizes for the sediments were selected. Binary intensity data was stored on

5.25' IBM-type floppy disks. The data were converted to an ASCII format.

For each sample analysis a standard plot of intensity (in counts per second)

vs. ° 2q was generated. All major mineral phases in each sample were

identified and listed in order of decreasing abundance.
4.2.3 Total Organic Carbon and Total Carbon

Carbon concentrations were determined on freeze-dried (or ovendried at 40 to 50 °C) sediment using a LECO Model 523-300 induction

furnace (or equivalent) to burn samples in an oxygen atmosphere. One

hundred (100) to 500 mg (to the nearest milligram) of freeze dried (or oven

dried), finely ground, homogenized sediment was weighed into a tared,

carbon-free combustion crucible. The amount of sample depended upon the

expected carbon concentration. Ideally, between 0.5 mg and 8.6 mg of

carbon was combusted to fall within the range of the standard curve. One

scoop of copper and iron chip accelerator was added to the crucible

containing the samples. All crucibles were kept covered with aluminum foil

prior to analysis. The crucible was placed on the oven pedestal, the oven

closed, and oxygen allowed to flow. The carbon dioxide produced was swept

from the furnace's combustion chamber with the oxygen flow. The gases

then passed through a dust trap and two reaction tubes. The first reaction

tube was a two-stage chamber with the first stage consisting of manganese

dioxide. The manganese dioxide absorbed the sulfur oxides that form during

combustion. The second stage contained anhydrone, which removed water

vapor from the gas stream. The second tube, filled with platirilzed silica,

was maintained at an elevated temperature by an external heating jacket.

The contents of this tube acted as a catalyst to convert carbon monoxide to

carbon dioxide. Carbon dioxide was detected and quantified with a Horiba

PIR-2000 infrared detector. The output signal from the Horiba was

recorded by an HP 3396A integrator which calculated the quantity of carbon

dioxide based on peak area. Standard LECO pin and ring carbon standards

were placed into an empty crucible with one scoop of copper accelerator.

Standards were analyzed by the same procedure as a sample to calibrate the

detector.

The appropriate amount of freeze dried (or oven dried) sample was

acidified with small amounts of 10 % HC1 in methanol solution. The treated

samples were dried overnight at 50 °C in the drying oven. Carbonate

content was determined by subtracting the total organic carbon

concentration from the total carbon concentration. To express as percent

calcium carbonate, the total carbonate carbon content is multiplied by 8.33.
Quality control samples were processed the same as samples. A

method blank was run with every 20 samples, or with every sample set,

whichever was more frequent. Blank levels were maintained at less than

three times the method detection limit (MDL). Duplicate samples were

analyzed every 20 samples, or with every sample set. Duplicates were

maintained at ±20 % for low level (< 1.0 % carbon) samples and ±10 % for

normal/high level (> 1.0 % carbon) samples. Duplicates were less precise

for large grain size samples. Reporting units were percent organic carbon

(on a dry weight basis) and percent carbonate carbon (on a dry weight basis).

The minimum method performance standard for the method is detection of

0.02 % carbon in a sample. Results were reported to two (2) significant

figures. All duplicate anaiyses were reported.

4.2.4 Redox

An estimate of the redox condition of the sediments was obtained by

Eh (mV) measurements [Whitfield 1969). Eb measurements were

performed by direct insertion of a combination platinum electrode into the

top 2 cm of the sediment and reading a pH/mV meter. The Eh probe was

inserted directly in the subcore before disassembly of the boxcore. The

overlying water was retained in-place to minimize sediment disturbance and

mixing with air. Readings were converted to values on the hydrogen scale

(Whitfield 1969). The platinum electrode was calibrated prior to each

sample with a ferrous-ferric solution (Light 1972) and was polished to

expose a bright surface before each reading.

4.3 Contaminant Analyses

The contaminants measured in this study included hydrocarbons and

trace metals.

4.3.1 Hydrocarbons

Aliphatic and aromatic hydrocarbons were quantitatively measured in

sediments, pore waters, and biological tissues. The protocols and

procedures used in this study (Figure 4.1) are identical to those presently
[ Dry

weight1

TISSUE ( SEDIMENT )

Warm to room

temperature

Homogenize

Additon of

surrogates

Concentrate

'Alumina/silica gel

_chromatography

Concentrate

HPLC/GPC

Concentrate

Cold Extraction

CH2Cl2 3xlOOmI

Na2SO4 50g

( Centrifuge )

Add internal

standard

(Dry

weight

Data reduction

analysis I)

Aliquot

( Homogenize )

( Dry with

NaSO4

Addition of

__surrogates

Extraction

With Cu

4-8hrs

Concentrate )

( Alumina

1L chromatography

Concentrate J

GC/FID

Add internal

standard

Figure 4.1. Summary of hydrocarbon analytical protocols.

4-8
used in the NOAA National Status and Trends Program and EPA's EMAP

Program.

4.3.1.1 Clean Procedures

All glassware was cleaned by detergent (micro cleaning solution),

washed with water, and rinsed with tap water. The glassware was then

combusted in a muffle furnace at 400 °C for at least 4 hours. Solvent rinses

with acetone used to remove residual moisture followed by methylene

chloride were substituted for the muffle furnace heating when determined

to be appropriate by the analyst. After drying and cooling, glassware was

sealed with combusted aluminum foil and stored in a clean environment to

prevent the accumulation of dust or other contaminants.

4.3.1.2 Sediment Extraction

A one (1) g sediment subsample was weighed, oven-dried, and

reweighed to obtain percent moisture. A ten (10) g sediment subsample

was chemically dried with thirty (30) g anhydrous sodium sulfate and added

to an extraction thimble. A ball of copper wire was successively cleaned

with HC1, water, methanol, and methylene chloride and placed in a 250-mL

extraction flask with 150 mL of methylene chloride and one to two boiling

chips. Fifty (50) mL of methylene chloride was added to the thimble, the

appropriate amount of surrogate was added and the sample was soxhletextracted with 150 mL of inethylene chloride for four (4) to eight (8) hours,

recycling every ten (10) minutes. The extract was concentrated by

Kuderna-Danish techniques to two (2) mL hexane.

4.3.1.3 Sediment Extract Purification

A plug of glass wool and 2 cm of combusted sand were placed in a

glass chromatographic column and the column was filled with hexane. Ten

(10) g of combusted neutral alumina were added and allowed to settle. One

(1) g of anhydrous sodium sulfate and ten (10) g of activated copper were

added to the top of the column. The hexane was drained to the top of the

column and the sample extract was transferred onto the column. The
extract vial was rinsed with two 1-mL rinses of methylene chloride. The

rinses were each added to the column and drained to the top of the colunm.

One hundred (100) mL of methylene chloride were added, eluted at one (1)

mL/min., and collected in a 250-mL flat bottom flask. The eluent contained

the aliphatic and aromatic hydrocarbons. The extract was concentrated by

Kuderna-Danish techniques to one (1) mL of methylene chloride.

4.3.1.4 Tissue Extraction

All tissue samples were mechanically macerated prior to extraction. If

necessary, organisms were rinsed with reagent water to remove extraneous

material. The macerated tissue was weighed into a centrifuge tube (2 to 15

g wet weight). A separate one (1) g aliquot of macerated tissue was

removed, placed in a tared weighing pan, and weighed. The tissue was

dried at 50 °C to a constant weight, allowed to cool, and then reweighed to

obtain percent moisture. One hundred (100) mL CH2C12, 50-g Na2SO4 and

the appropriate amount of surrogate was added to each sample. The tissue

was macerated for three (3) minutes with a Tissumizer. The CH2C12 was

decanted into a 500 mL flat bottom flask (centrifuged at -2000 rpm for 5

minutes, if necessary). The extraction was repeated two more times with

100-mL aflquots of CH2CJ2. The CH2C12 aliquots were combined in a 500-

mL flat bottom flask. The extract was concentrated as described for

sediments above.

4.3.1.5 Tissue Extract Purification

A plug of glass wool and 2 cm of combusted sand were placed in a

glass chromatographic column and the column was filled with hexane. Ten

(10) g of alumina (deactivated 1 % with water) in CH2C12 was slurry-packed

into the column and allowed to settle. Twenty (20) g of silica gel

(deactivated 5 % with water) in CH2 Cl2 was slurry packed into the column

and allowed to settle. One (1) cm of combusted sand was added on top of

the packed column and the CH2 Cl2 was allowed to drain to the top of the

sand. Fifty (50) mL of pentane was added to the column and drained to the

top of the sand. A 500-mL flat bottom flask was placed under the column.

The sample extract was transferred to the column in hexane. The colunm

4-10
was drained to the top of the sand. The concentrator tube was rinsed twice

with one (1) mL of 50:50 pentane:CH2CL2 solution that was added to the

column. The column was drained to the sand layer. Two hundred (200) mL

of 50:50 pentane:CH2C12 solution was added to the column, eluted at one (1)

mL/min., and collected. This fraction contains the hydrocarbons. The

extract was concentrated as described previously.

The aromatic fraction was further purified by high performance liquid

chromatography (HPLC) using a Spectra-Physics SP8000 ternary pump, two

size exclusion columns connected in series (22.5 X 250 mm Phenogel 100 A

columns), and a precolunm (8 X 50 mm Phenogel 100 A). Filtered (0.45-

j.tM) dicbloromethane was used as the mobile phase. The sample was

injected onto the columns with an autosampler (Gilson Model 321). The

HPLC unit was equipped with a UV absorbance detector (Model Water 440-

Millipore). The fractions containing the compounds of interest were

collected in 50-mL vials using the LKB Bromma 2211 fraction collector.

The time interval in which the desired fraction was collected was based on

the retention times of (4,4') dibromooctafluro-biphenyl (DBOFB) and

perylene. These retention time markers were analyzed three times.

Collection of the sample fraction began 1.5 mlxi. before the elution of DBOFB

and ended two (2) miii. after the elution of perylene. Assuming a constant

isocratic flow of the mobile phase of seven (7) mL/min, the total time

needed to collect the fraction was -7 mlxi. At the end of every batch of ten

samples, the marker standard mixture was analyzed again to check

retention time. Mter running a batch of samples (20), the columns were

flushed and the precolumn was backflushed to remove sample matrix

contamination from the system. On average, time for purification was -35

mlxi. The extract was then concentrated to one (1) mL.

4.3.1.6 Quantitative Determination of Aliphatic Hydrocarbons and the Unresolved Complex Mixture (UCM) - Sediment Only

This method quantitatively determines compounds from fl-Cio to

n-C34 and is based on high resolution, capillary gas chromatography using

flame ionization detection (GC/FID). A gas chromatograph with a

split/splitless injection system, capillary column capability, and a flame

ionization detector (FID) was utilized. The output from the detector was
collected and processed by an automated HP-LAS 3357 data acquisition

software package. A 30-rn X 0.32-mm I.D. fused silica capifiary column with

DB-5 bonded phase (J&W Scientific or equivalent) was used. The analytical

conditions are summarized in Table 4.1.

Calibration solutions were comprised of the n-alkanes and isoprenoids

listed in Table 4.2. Calibration standards were prepared in the

concentration range from 1.25 to 50 mg/mL (at five concentrations). The

surrogate compounds for all sample types was deuterated n-alkanes with 12,

20, 24, and 30 carbons. A surrogate solution is made by weighing an

appropriate amount of pure standard into a volumetric flask and diluting to

volume with methylene chloride. The internal standard for this analysis was

deuterated n-C16. The matrix spiking solution consists of alkanes from with

10 to 34 carbons and pristane (Table 4.1). The matrix spike was added to

samples at a concentration of -10 X the MDL. The calibration mixture was

also used as a retention index solution.

4.3.1.7 Quantitative Determination of Polynuclear Aromatic Hydrocarbons (PAH) - Sediments, Pore Waters, and Tissues

The method described determines the concentration of polynuclear

aromatic hydrocarbons (PAH) and their alkylated homologues In extracts of

water, tissues, and sediments. Quantitation was performed by gas

chromatography-mass spectrometry (GC/MS) in the selected ion monitoring

mode (SIM). Target analytes and confirmation criteria are listed in Table

4.3. The analytical systems included a temperature programmable gas

chromatograph (Hewlett-Packard 5890A, or equivalent) and all accessories

including syringes, analytical columns, and gases. Analyses were performed

in a splitless mode. A 30-rn X 0.32-mm I.D. fused sffica capillary column

with DB5-MS bonded phase (J&W Scientific) was used. The autosampler

was capable of making 1 to 4 p.L injections. The mass spectrometer

(HP/MSD) operated at 70-eV electron energy in the electron impact

ionization mode and was tuned to maximize the sensitivity of the instrument

based on manufacturer specfficatioris. The GC capillary column was directly

inserted into the ion source of the mass spectrometer. The mass

spectrometer computer system allowed for continuous acquisition and

storage of all data during the chromatographic analyses. Computer software

4-12
Table 4.1. Analytical conditions for aliphatic hydrocarbon analysis.

Instrument: Hewlett-Packard 5880A or HP 5890 Gas Chromatograph

Features: Split/splitless capillaiy inlet system, HP- 1000 LAS 3357

data acquisition system

Inlet: Splitless

Detector: Flame ionization

Column: 0.32-mm I D X 30-rn DB-5 fused silica capillary column

(J&W Scientific)

Gases:

Carrier: Helium 2 mL/min.

Make-Up: Helium 33 mL/niin.

Detector: Air 360 mL/mun. Hydrogen 33 mL/min.

Temperatures: Injection port: 300 °C

Detector: 300 °C

Oven Program: 60°C for 1 miii. then 6 °C/min. to 300 °C, hold 5 miii.

Daily Calibration: Mid-level calibration solution; Retention index solution (20

mg/mL)

Quantification: Internal standard/calibration

Table 4.2. Aliphatic hydrocarbons (AR) of interest.

Compounds of Interest

N-Cia

N-Cu

N-C12

N-C13

N-C14

N-C15

N-C16

N-C 17

Pristane

N-C18

Phytane

N-C19

N-C20

N-C21

N-C22

N-C23

N-C24

N-C25

N-C26

N-C27

N-C28

N-C29

N-Ceo

N-C32

N-C
Table 4.3. Target polycyclic aromatic hydrocarbon analytes.

4-14

Analyte

Quantification

Ion

Confirmation

Ion

% Relative

Abundance of

Confirmation Ion

d8-Naphthalene 136 134 15

Naphthalene 128 127 15

Ci-Naphthalenes (including isomers) 142 141 80

C2-Naphthalenes 156 141 ND

C3-Naphthalenes 170 155 ND

C4-Naphthalenes 184 169,141 ND

diO-Acenaphthene 164 162 95

Acenaphthylene 152 153 15

Biphenyl 154 152 30

Acenaphthene 154 153 98

dio-Fluorene 176 174 85

Fluorene 166 165 95

CiFluorenes 180 165 100

C2-Fluorenes 194 179 25

C-F1uorenes 208 193 ND

diO-Phenarithrene 188 184 ND

Phenanthrene 178 176 20

Anthracene 178 176 20

Ci-Phenanthrenes/axithracenes 192 191 60

C2-Phenanthrenes/anthracenes 206 191 ND

C3-Phenanthrenes/anthracenes 220 205 ND

C4-Phenanthrenes/arlthracenes 234 219,191 ND

Dibenzothiophene 184 152,139 15

Ci-Dibenzothiophenes 198 184,197 25

C2-Dibenzothiophenes 212 197 ND

C3-Dibenzothiophenes 226 211 ND

Fluoranthene 202 101 15

d12-Chrysene 240 236 ND

Pyrene 202 101 15

Ci-Fluoranthenes/pyrenes 216 215 60

Benzo [a] anthracene 228 226 20

Chiysene 228 226 30

Ci-Chxysenes 242 241 ND

C2-Chrysenes 256 241 ND

C3-Chrysenes 270 255 ND

C4-Chrysenes 284 269,241 ND

d12Benz (a)pyrene 264 260 20

Benzo [bi fluoranthene 252 253,125 30, 10

Benzo [k] fluoranthene 252 253, 125 30, 10

Benzo (e) pyrene 252 253 30, 10 Perylene 264 253 20

d12-Perylene 264 260 ND

Benzo La] pyrene 252 253, 125 30, 10

Indeno[1,2,3-c,d]pyrene 276 277, 138 25,30

Dibenzo [a,hJ anthracene 278 279. 139 25,20

Benzo Ig,h,ijperylene 276 277, 138 25,20

ND = Not determined
allowed display of any GC/MS data file for ions of a specific mass and plotting

ion abundances versus time or scan number. Extracts were injected onto

the capillary column of the gas chromatograph using the following

conditions:

Qualitative identification of target compounds was based on relative

retention time (RRT) criteria. RRT windows for alkyl homologues were

based on analysis of National Institute of Standards and Technology (NIST)

SRM 1582 or other suitable reference oil. Just prior to analysis, an aliquot

of internal standard solution was added to the sample.

The compounds in the surrogate solution were naphtbalene-d,

acenaphthene-dio, phenanthrene-dio, chTysene-d12, and perylene-d12. All

sample analyte concentrations were corrected for surrogate recoveries. The

internal standards were resolved from all, but elute in close proximity to,

the analytes of interest. The internal standards were fluorene-dio and

benzo(a)pyrene-d12. A solution containing 2 to 5-ring PAH compounds was

used to fortify matrix spike samples.

A five-point response factor calibration curve was established to

demonstrate the linear range of the detector. The standard concentrations

were 20, 100, 250, 500, 1000 ng/mL. The percent relative standard

deviation for all calibrated analytes did not exceed ±15 % with an R> 0.99

with a first degree fit of the data. After every 6 to 8 samples, the mass

spectrometer response for each PAH relative to the internal standard was

determined using check standards at concentrations of 250 ng/mL. Daily

response factors for each compound were compared to the initial calibration

curve. If the average daily response factors for all analytes were within ±15

% of the calibration value, analyses proceeded. If, for any analyte, the daily

response factor exceeded ±35 % of calibration value, a five-point calibration

was repeated for that compound prior to the analysis of samples.

Injector Temp: 300 °C

Transfer Line Temp: 280 °C

Initial Oven Temp: 40°C

Initial Hold Time: 0 mixi.

Ramp Rate: 10°C

Final Temperature: 300 °C

Final Time: 4mm.
4.3.1.8 Quality Control

The methods employed were equivalent to NOAA National Status and

Trends methodologies and the associated quality assurance is the same as

for the NOAA methods. A method blank was run with every 20 samples, or

with every sample set, whichever was more frequent. Blank levels were no

more than three times the method detection limit (MDL). If blank levels for

any component are above three times the MDL, samples analyzed in that

sample set were re-extracted and reanalyzed. If insufficient sample was

available for re-extraction, the data were reported and appropriately

qualified. Matrix spike/matrix spike duplicate (MS/MSD) samples were run

with every 20 samples, or with every sample set, whichever was more

frequent. The appropriate spiking level was ten times the MDL. Surrogate

materials were spiked into every sample and QC sample. The appropriate

spiking level was ten times the MDL. Surrogate and matrix spike recovery

acceptance criteria are described in the instrumental section.

Method interferences may be caused by contaminants in solvents,

reagents, glassware, and other sample processing hardware and can lead to

false positives during instrumental analysis. All materials used in this

method are routinely demonstrated to be free from interferences by

processing procedural blanks identical to samples (one blank per 20

samples or each batch, whichever was more frequent). Matrix interferences

result from co-extraction of compounds other than the analytes of interest.

4.3.2 Trace Metals

Total trace element concentrations were determined in sediments,

biological tissues, and pore waters from each study site. The analytical

methods were optimized for the each element/matrix type to ensure high

quality data. The analytical methods used are summarized in Table 4.4.

4.3.2.1 Sample Preparation

All samples were received frozen. Sediment samples were thawed,

homogenized, and a representative aliquot taken for freeze-drying. After

freeze-drying, the samples were homogenized by grinding to a powder prior

4-16
Table 4.4. Trace element analytical methodologies bymatrixa. al3i-tical methods are flame atomic absorption spectrophotometry (FAAS), graphite furnace or flameless AAS (GFAAS), instrumental neutron activation analysis (INAA), direct current plasma atomic emIssion spectroscopy (DCP-AES), and cold vapor AAS (CVAAS), --- not analyzed. todigestion. Fish liver and stomach content tissue samples were sub- sampled inthe field and were received ready for freeze-drying. For whole organism samples (e.g., shrimp, crabs, gastropods), the soft tissues were separated prior tofreeze-drying. After freeze-drying, all tissue samples were homogenized bygrinding toapowder prior todigestion. Pore water samples were prepared for analysis byacidification topH<2with ultrapure nitric acid. 43.2.2 Sample Digestion and Analysis For most elements insediments and tissues, NOAA National Status and Trends Mussel Watch methodologies, which incorporate

aclosed teflon bomb acid digestion, were used (Lauenstein et al. 1993). These are sensitive (low detection limit), total digestion methods (i.e., MDL's for most elements inthe 0.01 to1.0 ppb dry wt. range) developed for use inbaseline monitoring programs. These methods are capable of accurately measuring trace element levels inuncontaminated, pristine areas. Mercury was determined according toEPA method 245.1 (U.S. EPA 1991), which 4-17 Element Sediment Tissue Pore Water Al FAAS Ag GFAAS GFAAS As GFAAS GFAAS Ba INAA DCP-AES DCP-AES Cd GFAAS GFAAS GFAAS Cr INAA GFAAS GFAAS GFAAS GFAAS Fe INAA FAAS Hg CVAAS CVAAS CVAAS Ni GFAAS GFAAS Pb GFAAS GFAAS GFAAS SbINAA-- Se GFAAS GFAAS Sn GFAAS GFAAS

VDCP-AES DCP-AES GFAAS Zn FAAS FAAS GFAAS
involves a separate sulfuric/nitric acid and permanganate/persulfate

digestion followed by cold vapor atomic absorption spectrophotometry

(CVAAS).

For certain elements of special interest to this study (e.g., Ba, V),

specialized analytical techniques were used. For example, sediment barium

is the most important elemental tracer of drilling mud discharges and was a

critical parameter for interpreting the chemical gradients observed in the

vicinity of the platform sites. To maximize data quality, sediment barium

concentrations were detennined by instrumental neutron activation analysis

(INAA). INAA is the analytical method of choice for sediment barium

determination because barium is difficult dissolve by normal acid digestion

procedures. INAA is a nuclear technique that is free of chemical

interferences, and has an essentially unlimited linear dynamic range. This

characteristic was especially important for this study because sediment

barium concentrations which ranged over four (4) orders of magnitude (i.e.,

200 to 200,000 ppm dry wt). The INAA determinations were made using

the method of Boothe and James (1985), which is optimized for marine

sediments. Other elements (Cr, Fe, Sb) were determined simultaneously by

this multi-element technique. In tissue and pore water samples, with very

low barium and vanadium concentrations, atomic emission spectroscopy,

which is especially sensitive for these elements, was used.

4.3.2.3 Quality Control/Assurance Procedures

Trace element analyses were conducted under a comprehensive

Quality Assurance project plan designed to consistently produce high

quality, verifiable data. All sample processing and analysis procedures were

performed to minimize contamination and maximize data quality (accuracy

and precision). All procedures were conducted by properly trained

personnel according to approved laboratory standard operating procedures

(SOPs). Good laboratory practices (e.g., daily refrigerator/freezer

temperature checks, balance calibrations, etc.) were consistently followed.

All sample handling was done using new or acid-cleaned, metal-free

containers and implements. Cleaning procedures and sample processing

were perfonned in a clean room to avoid sample contamination. Also, all

containers were kept closed or covered except when material was being

4-18
added or removed. Distilled-deionized high purity water was used to

prepare all detergent and acid cleaning solutions and for all rinses during

cleaning procedures. Double-distilled, ultra-pure water was used for all

dilutions and to prepare all sample digestion/processing reagents. Ultrapure reagents were used whenever necessary to ensure that the procedural

blank for a given analytical procedure was below the method detection limit

for that procedure.

A detailed log was prepared for each digestion, specifying all aspects

of the procedure (e.g., SOP to be used, matrix spike levels, QA samples,

etc.). As the digestion was performed, all information was recorded in a

bound, pre-printed logbook for the specific digestion procedure being used.

A full suite of laboratory quality assurance (QA) samples was run with each

set of 30 to 45 samples digested. These include certified reference

materials ( 5 %), laboratory control samples (blank spikes, 5 %), matrix

spikes ( 5 %), laboratory duplicates ( 5 %) and procedural blanks ( 5 %).

For the entire GOOMEX study over 35 % of all samples analyzed were QA

samples.

All standards used were traceable to National Institute of Standards

and Technology standards and within expiration dates. The preparation of

all standard solutions (including lot numbers, measuring devices, and

amounts used, etc.) was recorded in a single log book and all solutions were

clearly labeled and traceable to a logbook entry.

During each analytical procedure, the instrument was calibrated at the

beginning of the run and the calibration was checked (or re-calibrated)

frequently during the run. Full re-calibrations were performed as necessary

if the calibration changed more than 5 % between any two checks. All data

entered were verified independently by a second person.

Each analytical batch was also evaluated based on the results of the QA

samples and stringent QA acceptance criteria consistent with those

recommended by the EPA (U.S. EPA 1989). The acceptance criterion for

percent recovery (i.e., QA parameter for CIM, matrix spikes, blank spikes)

was 80 to 120 %. The acceptance criterion for relative percent difference

for duplicates at ten times the MDL was 20 %. The acceptance criterion

for procedural blanks was less than twice the MDL. Finally. 95 % of all QA

analyses performed for each batch of samples had to meet these acceptance

criteria. When one or more QA parameters fell outside the acceptance

4-19
criteria for a given digestion set and element, the samples were re-analyzed.

If re-analysis did not bring the QA parameter(s) within acceptable ranges,

the samples were re-digested and re-analyzed. All final metal data for the

GOOMEX Study met these QA requirements.

4.4 Meiofauna

Extraction of meiofauna from sediment was performed using the

decantation technique (Pfannkuche and Thiel 1988). The sediment was

dispersed and allowed to setfie for a few seconds before meiofauna were

rinsed onto a sieve. This process was repeated several times until all

animals were removed. Meiofauna were those animals retained on a 0.063-

mm sieve.

Samples were counted to major metazoan taxonomic category and all

harpacticoid copepods were sorted using the subsampling techniques

described in Sherman et al. (1984). All barpacticoid copepods were

identified to the species level. A subset of nematodes was identified to the

species level. The first 50 nematodes encountered were mounted in a drop

of glycerin on a slide for taxonomic analyses. The formalin-ethanol-glycerol

transfer technique was used to protect specimens from collapse (Seinhorst

1959). On rare occasions, less than 50 nematodes were encountered in a

sample. In these cases, all nematodes were identified to the species level.

After nematodes and harpacticoids, the remaining taxa (usually 1 to 5 % of

the total fauna) were identified to the major taxonomic level. The major

meiofauna taxonomic categories are listed in Table 4.5.

4.4.1 Nematode Feeding Types

Marine nematodes can be classified into four feeding types based on

mouth part morphology (Wieser 1953). These are the selective and nonselective deposit feeders (collectively referred to as the deposit feeders) and

the epigrowth feeders and onmivore-predators (collectively referred to as

toothed nematodes). Deposit feeders are defined as nematodes without

teeth. Deposit feeders take in food actively by engulfing particles, or

passively by pumping the phaiynx (Romeyn and Bouwman 1983). Selectivedeposit feeders (hereafter referred to as the "1K group) have a greatly

4-20
Table 4.5. Major meiofauna taxonomic categories.

Kinorbyncha Gastrotricha

Rhyncocoela Nematoda

Arthropoda Crustacea Copepoda (Harpacticoida)

Ostracoda

Amphipoda

Isopoda Tanaida

Cumacea

Annelida Polychaeta

Mollusca

- diminished or total Jack of a buccal cavity. Selective deposit feeders can

utilize only small, bacteria-sized particles. Non-selective deposit feeders

(1B) have a wide buccal cavity and can feed on particles up to diatom size

(Romeyn and Bouwman 1983). Nematodes with teeth are classified as

either epigrowth feeders (2A) or omnivore-predators (2B). Epigrowth

feeders have a small buccal cavity that is armed with one or more simple

teeth. Epigrowth feeders use these teeth to puncture the frustule of

diatoms and suck out the cell contents (Romeyn and Bouwrnan 1983;

Jensen 1987). Omnivore-predators have a wide buccal cavity armed with

claws, mandibles, or gland-equipped teeth. Prey items are captured by

these armaments or simply engulfed (Wieser 1953). Excretions from

esophageal salivary glands can accelerate digestion (Jensen 1987).

Jensen (1986) suggested updating Wieser's (1953) classification

system. Under Jensen's classification system, deposit feeders are not subdivided into two groups. In addition, a new group, the scavengers, are

formed from two families, the Onchotaimidae and the Ertchelidtidae,

formerly classified as omnivore-predators. The justification for the creation

of the scavenger feeding type is that these two families can feed on dissolved

organic matter. However, older juveniles and adults of these families can

continue to feed on animals (Jensen 1987). The nematodes identified for

the GOOMEX Phase I study contained only a few members of the

Oncholaimidae (e.g., Viscosia spp.). For this reason, Wieser's (1953)

classification system is suitable for the present study.

4-21

Phylum Class Order
The four different nematode feeding types are thought to have

different respiration rates and production efficiencies (Li et al. 1995a,b).

Differences utilize different food sources, or digest the same food source

using different mechanisms. Thus, Wieser's (1953) classification system,

which is based on morphology, does have ecological relevance to

determining the trophic structure of nematode communities and the

relationship between these communities and their environment.

4.4.2 Nematode Biomass

The biomass of nematodes (B) was calculated from the measurement

of nematode body sizes as follows:

- 1600000

Where a is the body width (p.m) at the widest point, b is the body length

(mm), and 1600000 is a conversion factor (Andrassy 1956). B is the

expected wet weight in milligrams (mg).

4.4.3 Harpacticoid Life History and Reproduction Study

Three species of harpacticoida were chosen for the meiofauna life

history and reproduction studies. The harpacticoids come from the material

obtained in the meiobenthic community structure studies. The three

species chosen are different in terms of their suspected food requirements

or in potential niche and habitat choices based on body morphology (Coull

1977; Montagna 1981). The body shape nomenclature, as recently revised

by Warwick and Gee (1984), was used for these purposes. Cietodes

pseudodisstmt its is a semi-cylindrical depressed form from the family

Cletodidae. It is a typical burrower. The second organism is Longipedia

americana. It exhibits a pyriform body, which suggests a more epibenthic

lifestyle. This species is being used for the meiofauna toxicity tests. The

third organism is a species of Diathrodes, family Thalestridae, which is

another epibenthic form. All three of the species used in the life history

study are semi-cylindrical in shape. For every individual of the three

4-22
species, the copepodite stage class was used to determine the structure of

the population and the number of sexually mature males and females was

determined. For all mature males and females, individual body size and the

number of gravid females were determined. For each gravid female, the

number of eggs per gravid female and the size of eggs in clutches was

determined to calculate clutch volume.

All life history and reproductive measurements were made by placing

individuals in drops of lactic acid and examining them using a Zeiss phasecontrast microscope. Body size was determined using a calibrated ocular

micrometer with resolution of 5-j.t at 100 X. Egg number (clutch size),

diameter, and volume were measured with a resolution of 1-p. at 400 X.

Total clutch volume was determined by assuming the eggs were spherical.

This assumption allowed egg radius (r) measures to be converted to volume

(V) estimates using the formula:

V= irr

Individual egg volume values (Vi) from each clutch were then summed

to generate a measure of total reproductive effort (RE) for each gravid

female.

RE = V1

Life history stages were determined by enumerating the number of

body segments in the abdomen of harpacticoid copepodites. Harpacticoid

copepodites add abdominal segments with each molt up to the adult stage,

which has six abdominal segments. Thus, the first stage is called "Cl" with

one abdominal segment, the second stage is called "C2" with 2 abdominal

segments, etc., until the sixth and last segment is added which is the adult

stage. Only adults, i.e., C6 copepodites, are sexually dimorphic. Meiofauna

were preserved in 70 % alcohol and 10 % glycerin. Voucher specimens

were retained.

4.4.4 Harpacticoid Toxicity Testing

Pore water was extracted from Cruise 1 samples, using the

pressurized squeeze-extraction method described elsewhere. Pore water

was then centrifuged and at least 4 aliquots of each water sample were

4-23
frozen separately. One aliquot was used for chemical analysis, and another

was used in the copepod toxicity test. Water samples used in the toxicity

test were kept in the freezer for two days before the test, and then they

were placed in the refrigerator to thaw slowly. The day before the test, pore

water samples were mixed and water quality measurements were taken.

Samples were then refrigerated overnight before the test was conducted.

The copepods used in the test was Longipedia americana, were

collected from the Port Aransas ship channel and maintained in the

laboratory until the females became gravid. Gravid females were collected

and isolated into a separate culture container, less than 48 hours before a

test, until the eggs batched. Therefore, all nauplil were less than 48 hours

old at the start of a test. The nauplii, which are phototactic, were

concentrated in the culture dish by using a point source of light. A pipette

was used to transfer the nauplii to a small counting dish. Five nauplil were

transferred from the counting dish into each testing chamber, and three

replicates of each treatment were performed. The number of samples tested

from each platform was 18, 3, 6, 9, and 2 from HI-A389, MU-A85, GA-288,

MAI-686, and MAI-622, respectively. The Far sites at each platform were

used as a control. Test chambers were standard petri dishes containing 10

mL of pore water. Nauplii were fed a mixture of three types of algae

(Dunatiella, Thalassioira, and Isochrysis, approximately 20,000, 30,000, and

120,000 cells per replicate, respectively). Test chambers were incubated at

22 °C for 96 hours; then the test was terminated and the number of

surviving nauplil was determined for each chamber.

4.4.5 Diversity Analysis

Species composition and diversity was analyzed by computing

techniques given in Ludwig and Reynolds (1988). Two diversity indices

were calculated for each boxcore at each station. Replicates within boxcores

were pooled to avoid artificially high diversity values due to low sample

numbers. One method is HillTs diversity number one, Ni (Hifi 1973). Ni is

a measure of the effective number of species in a sample, and indicates the

number of abundant species. It is calculated as the exponentiated form of

the Shannon diversity index:
Ni = eH'

As diversity decreases, Ni will tend toward 1. The Shannon index is the

average uncertainty per species in an inflnite community made up of species

with known proportional abundances (Shannon and Weaver 1949). The

Shannon index is calculated by:

SI

H' = [jLJ CD] i1

where nj is the number of individuals belonging to the ith of S species in the

sample and ii is the total number of individuals in the sample. This index is

based on information theory and is a measure of the average degree of

uncertainty in predicting what species and individual will belong.

Therefore, it is biased toward common species, whereas the Ni indicates

the degree of species dominance.

How equally component species are represented is expressed as an

index of eveness. Eveness is a component of diversity. Two eveness indices,

El and E5, have been calculated. El is probably the most common; it is the

familiar J' of Pielou (1975). It expresses H' relative to the maximum value of

H':

H' ln(N1) Ei= =

in(S) ln(NO)

El is sensitive to species richness. E5 is an index that is not sensitive to

species richness. E5 is a modffied Hill's ratio (Alatalo 1981):

E5- (i/X)-i

Ni-i

where, -' n.(n-1)

i=i

A. is the Simpson (1949) diversity index. E5 approaches zero as a single

species becomes more and more dominant.
4.4.6 Fish Predation on Melofauna

During the third and fourth cruises, 570 small fish (< 10 cm) were

collected from trawis to study the predation pressure of small fish on

meiofauna. The specimens were preserved on-board ship and analyzed in

the laboratory. Fish standard body lengths were measured from the tip of

the nose to the flute of the tail. The stomachs were removed from the fish

and cut open, and their contents examined under a dissecting microscope.

Organisms found inside the guts were placed in the following taxonomic

categories: nematodes, harpacticoids, calanoids, shrimp, amphipods,

isopods, mysid, crabs, ostracods, polychaetes, fish, gastropods, bivalves, and

squid. These categories were then grouped into habitat categories as

follows: meiofauna, macroinfauna, epifauna, or pelagic. Meiofauna are the

sum of nematodes, harpacticoids, and ostracods. Macroinfauna are the

amphipods, isopods, polychaetes, gastropods, and bivalves. Shrimp, crabs,

and mysids make up the epifauna group. The pelagic group is the sum of

calanoids, fish and squid. A nematode specialist checked all the riematodes

and made sure that parasitic types were not counted as food.

4.4.7 Nematode Production Modeling

Deposit feeding nematodes are the dominant feeding group at all three

platforms, composing 53-70 % of total nematode biomass, and 51-67 % of

total nematode abundance. Deposit feeding nematodes feed predominantly

on particulate organic matter by non-selectively engulfing whole particles.

Therefore, it is relatively easy to model the trophic dynamics and

productivity of the deposit feeders. Unlike other nematode feeding groups,

information about resident meiofauna are not needed in order to construct

models for deposit feeders. A time dynamic model was used to predict

energy flow through the biomass of nematode deposit feeders. Four

processes were considered for this model: input, assimilation, predatory

death, and other losses (including respiration, excretion, and non-predatory

death; Figure 4.2). Based on this model, the change in nematode biomass

(D) over one month (t=time) is calculated by following formula:

d(D) (1XP12) -L-P d(t) - 4-26
Temp=temperature; TOC=% tots? organic carbon; Zinc=zinc as proxy for all metals; Mac=macrobenthos abundance; F=food sources; Depn=deposit-teedrng nematode biomass; 1=intake of food; A=assimilation; P=predation losses; L=other losses (respiration, excretion, natural death). Figure 4.2. The model for predicting platform effects on deposit-feeding nematode st
where I monthly intake of food by deposit feeding nematodes, P12 =

assimilation efficiency, L = monthly loss due to respiration, excretion, and

natural death, and P = monthly losses of nematodes due to predation by

macrobenthos. Detailed formulas for each of these processes can be found

in Table 4.6.

The model was created in FORTRAN 77 language, and facilitated by

the PC software package, SENECA, a Simulation ENvironmenta:1 ECological

Application (de Hoop et at. 1989). SENECA simplifies the model setup and

allows for easy calibration by estimating the best fit parameter values

according to a goodness-of-fit test. The model included 75 stations (3

platforms, 5 distances, and 5 radii) over 16 months (January 1993 to June

1994). Simulated variables included the biomass, monthly production, and

production efficiency of deposit-feeding nematodes (Table 4.6). Inputs to

the model were temperature, TOC, macrobenthos abundance, and zinc

concentrations (as a proxy for total trace metal contaminants).

The calibrations for the model were based on the biomass data of

deposit-feeding nematodes for all four cruises. The initial range of

parameters were large to account for all possibilities reported in the

literature. Data sets from each platform were used independently to

calibrate the model three times. The calibration provides three groups of

new parameter ranges that best fit the model. In this study, the best fit

parameters and new parameter ranges were based on over 6000 calibrations

analyses for each platform (Tables 4.7 to 4.9). The simulation of total

nematodes are based on the best fit parameters at each station [(INIP(I),

where 1=1 to 25)] from each of the three platforms. Therefore, the different

simulations on deposit-feeding nematodes alone (e.g., production and

production efficiencies) among platforms and among distances are based on

nematode data, environmental data, and energy conservation, and are used

to predict platform effects on nematode trophic dynamics.

4.5 Meiofauna Genetic Variability

Five species of harpacticoida were chosen for the genetic diversity

study: NormaneUa sp., Enhydrosoma pertcoense, Ctetodes sp., Robertsonia

sp. and Tachidiella sp. Of the five species, only E. pericoense has been

previously described, and therefore assigned a species name. Species were

4-28
Table 4.6 Formulas used in the model for predicting platform effects on

deposit-feeding nematode standing stock.

Forrnulasa

F= (TOCxP2)-(MACXP1) T-20 TF2MAC=P6( 20

TENEM p10(T20)

F x P4 x TE1VEM"T

DP11

D

F + P3 J]J

P9 L=DxP5xTENMxZri°5

P=MACxP1xP8xDxey)xTEMAC

PROD=IxP12-L

PROD/L= I

aVuab1es: F food source for deposit-feeding nematodes, TOC = composition of total organic

matter in the sediment, MAC = abundance of inacrobenthos, TEMAC = temperature effects on macrobenthos, T = temperature, TENEM = temperature effects on nematodes, I = monthly food

intake by deposit feeding nematodes, D = biomass of deposit-feeding nematodes, L = other

losses (respiration, excretion, and natural death), Zn = concentration of zinc (as a proxy for all

trace metals), P losses due to predation, PROD = productivity. Parameters: P1 =

transformation of macroinlauna abundance to biomass, P2 = mg wet weight * cm3 sediment,

P3 = half intake rate of food concentration, P4 maximum daily intake rate, P5 = maximum

daily loss rate, P6 = QlO of macrobenthos. P7 = parameter related to regression effect on

nematodes, P8 = macrobenthos grazing rate, P9 = trace metal effect on increasing loss rate,

P10 = QlO for nematodes, P11 = parameter related to food limitations, P12 = assimilation

efficiency of nematodes.
Table 4.7. The best fit parameters of model for platform HI-A389 after 6,000 calibrating runs, where the new parameter has goodness

of fit ranging from 0.13 13238 to 0.1327957.

a(INIp(I) = a parameter to calibrate the initial observed nematode biomass at 25 stations. Parameters P 1-12 are defined in Table 4.6.

4-30

Parametera Best Reduction New Range Initial Range

INIP(1) 0.9361043 0.676 0.5424589 1.028764 0.5 2.0

INIP(2) 1.2548680 0.810 1.225867 1.510679 0.5 2.0

INIP(3) 0.5074684 0.450 0.507185 1.332499 0.5 2.0

INIP(4) 1.5847950 0.948 1.506373 1.584795 0.5 2.0

INIP(5) 1.4786050 0.722 1.441152 1.857598 0.5 2.0

INIP(6) 1.0676830 0.832 0.9090889 1.160968 0.5 2.0

INIP(7) 0.6141453 0.908 0.5849091 0.7222145 0.5 2.0

INIP(8) 1.1500900 0.793 0.9149311 1.225619 0.5 2.0

INIP(9) 0.9571383 0.787 (19275897 1.247702 0.5 2.0

INIP(10) 1.0810150 0.863 1.066609 1.271845 0.5 2.0

INIP(1 1) 1.5271690 0.937 1.527169 1.622284 0.5 2.0

INIP(12) 1.5485610 0.412 0.7544864 1.636125 0.5 2.0

INIP(13) 1.3199690 0.746 1.155985 1.536358 0.5 2.0

INIP(14) 1.8346610 0.854 1.66701 1.886112 0.5 2.0

INIP(15) 1.4899490 0.929 1.450695 1.556915 0.5 2.0

INIP(16) 1.1772290 0.874 1.177229 1.365997 0.5 2.0

INIP(17) 0.7429799 0.817 0.5444198 0.8193204 0.5 2.0

INIP(18) 0.7475748 (1414 0.6660943 1.544794 0.5 2.0

INIP(19) 1.3526970 0.545 0.7899158 1.472353 0.5 2.0

INIP(20) 1.0927740 0.666 0.9609983 1.461972 0.5 2.0

INIP(21) 1.1441420 0.736 0.9688078 1.364944 0.5 2.0

INIP(22) 1.4230840 0.640 0.978984 1.518411 0.5 2.0

INIP(23) 1.2528330 0.819 1.233783 1.50482 0.5 2.0

INIP(24) 0.5241628 0.389 0.5072048 1.423935 0.5 2.0

INIP(25) 0.8827865 0.550 0.7503395 1.425961 0.5 2.0

P1 0.0010400 0.964 1.04E-03 1.37E-03 0.0 0.0

P2 13.7638000 0.886 10.19716 14.74051 10.0 50.0

P3 9.65e07 0.93 1 9.20E-i-07 9.89E-i-07 1.OE-i-05 1.OE08

P4 1.2099420 0.649 1.109215 1.459813 1.0 2.0

P5 0.0143797 0.927 0.01043488 0.014815 0.0 0.1

P6 2.9950710 0.829 2.824108 2.995275 2.0 3.0

P7 204.0115000 0.940 184.6213 208.6834 0.0 400.0

P8 9.7479710 0.749 7.44383 9.951478 0.0 10.0

P9 8.2228670 0.813 8. 188109 8.934392 8.0 12.0

P10 2.8902760 0.745 2.676807 2.932302 2.0 3.0

P11 0. 1782269 0.773 4.93E-03 0.2320168 0.0 1.0

P12 0.2698020 0.878 0.2649387 0.2698069 0.2 0.3
Table 4.8. Parameters of model for platform MAI-686. nest fit after 6,000

calibrating runs, where the new parameter range has a goodness of fit ranging from 0.1737823 to 0.1782664.

aSee Tables 4.6 and 4.7 for definition of parameters.

Parainetera Best Reduction New Range Imtial Range

INIP(26) 0.787178 0.195 0.568246 1.775283 0.5 2.0

INIP(27) 0.734622 0.541 0.507121 1.195570 0.5 2.0

INIP(28) 1.000626 0.763 0.804389 1.159595 0.5 2.0

INIP(29) 1.017869 0.506 0.976372 1.717177 0.5 2.0

INIP(30) 0.618092 0.338 0.507255 1.500551 0.5 2.0

INIP(3 1) 1.641609 0.270 0.626015 1.720911 0.5 2.0

INIP(32) 1.150913 0.304 0.609408 1.654071 0.5 2.0

INIP(33) 0.78 1886 0.696 0.507339 0.963048 0.5 2.0

INIP(34) 1.659900 0.727 1.56607 1 1.974927 0.5 2.0

INIP(35) 1.532813 0.393 0.721394 1.631522 0.5 2.0

INIP(36) 1.283881 0.743 1. 181829 1.566752 0.5 2.0

INIP(37) 1.500102 0.788 1.389735 1.707566 0.5 2.0

INIP(38) 1.356195 0.231 0.507428 1.661371 0.5 2.0

INIP(39) 1.324965 0.482 0.597160 1.373497 0.5 2.0

INIP(40) 1.48093 1 0.884 1.456288 1.629766 0.5 2.0

INIP(4 1) 1.212993 0.373 0.933311 1.873757 0.5 2.0

INIP(42) 1.379516 0.484 0.860670 1.635332 0.5 2.0

INIP(43) 0.507490 0.188 0.506695 1.725278 0.5 2.0

INIP(44) 1.421562 0.590 0.927627 1.543347 0.5 2.0

INIP(45) 1.479420 0.485 1.011199 1.782992 0.5 2.0

INIP(46) 1.288508 0.195 0.507207 1.714884 0.5 2.0

INIP(47) 1.509393 0.785 1.386894 1.710140 0.5 2.0

INIP(48) 1.532623 0.242 0.856077 1.992650 0.5 2.0

INIP(49) 0.805555 0.376 0.684776 1.620163 0.5 2.0

INIP(50) 1.528447 0.690 1.175900 1.641003 0.5 2.0

P1 0.008070 0.215 0. 002770 0.009830 0.0 0.0

P2 36.785340 0.639 35.169520 49.594200 10.0 50.0

PS 9.34e+07 0.892 8.87e07 9.95e+07 1.OE-i-05 1.OE08

P4 1.534280 0.607 1.449959 1.842921 1.0 2.0

P5 0.010697 0.970 0.010298 0.012098 0.0 0.1

P6 2.984037 0.528 2.523217 2. 995256 2.0 3.0

P7 386.804200 0.958 381.350200 398.003100 0.0 400.0

P8 0.483498 0.769 0.411571 2.719052 0.0 10.0

pg 11.682260 0.378 9.334862 11.822620 8.0 12.0

P10 2.528471 0.379 2.261208 2.882230 2.0 3.0

P11 0.5241 14 0.205 0.004960 0.799774 0.0 1.0

P12 0.231563 0.769 0.230888 0.240137 0.2 0.3
Table 4.9. Parameters of model for platform MU-A85. Best fit after 6,000

calibrating runs, where the new parameter range has a goodness of fit ranging from 0.1266568 to 0.129108.

aSee Tables 4.6 and 4.7 for definition of parameters.

Parametera Best Reduction New Range Initial Range

INIP(51) 1.365014 0.781 1.132753 1.461522 0.5 2.0

INIP(52) 1.472296 0.913 1.441750 1.57 1882 0.5 2.0

INIP(53) 0.702359 0.571 0.516049 1.159231 0.5 2.0

INIP(54) 0.953722 0.677 0.709280 1.194510 0.5 2.0

INIP(55) 1.424662 0.807 1.248380 1.537863 0.5 2.0

INIP(56) 0.861547 0.596 0.67 1945 1.278293 0.5 2.0

INIP(57) 1.026084 0.796 0.954036 1.260379 0.5 2.0

INIP(58) 1.368381 0.823 1.3 17784 1.582814 0.5 2.0

INIP(59) 0.679144 0.89 0.654537 0.819603 0.5 2.0

INIP(60) 0.618613 0.904 0.564922 0.708398 0.5 2.0

INIP(6 1) 0.96743 1 0.855 0.928181 1. 145470 0.5 2.0

INIP(62) 1.414623 0.803 1.306570 1.602253 0.5 2.0

INIP(63) 0.511540 0.821 0.507648 0.775528 0.5 2.0

INIP(64) 0.585186 0.781 0.510507 0.839273 0.5 2.0

INIP(65) 1.519279 0.832 1.292134 1.543693 0.5 2.0

INIP(66) 1.53728 1 0.893 1.468087 1.629288 0.5 2.0

INIP(67) 1.362997 0.895 1.319530 1.477052 0.5 2.0

INXP(68) 1.259910 0.536 0.698133 1.394772 0.5 2.0

INIP(69) 1.230649 0.748 1. 173548 1.55206 1 0.5 2.0

INIP(70) 0.656314 0.711 0.591527 1.024937 0.5 2.0

INIP(71) 0.615935 0.899 0.507486 0.658928 0.5 2.0

INIP(72) 0.507499 0.89 0.507357 0.672533 0.5 2.0

INIP(73) 1.106946 0.479 0. 507302 1.288762 0.5 2.0

INIP(74) 0.604189 0.776 0.526370 0.861635 0.5 2.0

INIP(75) 1.248599 0.819 1.058088 1.330311 0.5 2.0

P1 0.003420 0.348 0.001780 0.007650 0.0 0.0

P2 18.333480 0.929 17.775540 20.624800 10.0 50.0

P3 9.86e+07 0.927 9.22e+07 9.95e+07 1.OE+05 1.OE08

P4 1.153606 0.895 1.084593 1.189447 1.0 2.0

P5 0.010980 0.99 0.010661 0.011263 0.0 0.1

P6 2.840917 0.395 2.374043 2.978718 2.0 3.0

P7 283.671600 0.817 268.804400 341.858800 0.0 400.0

P8 0.922790 0.897 0.646343 1.678361 0.0 10.0

P9 9.749 174 0.614 9.416418 10.960470 8.0 12.0

P10 2.481387 0.578 2.380938 2.803078 2.0 3.0

P11 0.084598 0.666 0.004780 0.339168 0.0 1.0

P12 0.251372 0.614 0.239325 0.254782 0.2 0.3
selected based on abundance at all three platforms and ease of identification,

thereby limiting confounding population effects due to differences between

cryptic species.

Genetic diversity was estimated for populations of harpacticoida at the

50-rn and 3000-rn stations at the three platforms during Cruises 2 and 3.

Genetic diversity was estimated by performing restriction fragment length

polymorphisms (RFLP) on 165 rRNA mitochondrial DNA (mtDNA) generated

by the polymerase chain reaction (PCR) from individual harpacticoids (Karl

and Avise 1993). PCR was necessary in order to generate enough genetic

material from a single copepod to use for analysis. Originally, three

mitochondrial loci were examined for optimization purposes, 16S rRNA,

cytochrome b, and the control region. The most consistent amplification

was obtained for the 165 rRNA locus, which was used for all samples.

Following PCR, RFLPs were used to estimate an index of genetic variability

for each station.

Specific reaction conditions are as follows. Harpacticoids were

preserved in ethanol buffered with disodium ethylenediamine tetraacetate

(EDTA) and refrigerated (Dessauer et al. 1990). Individuals were rinsed,

ground under a dissecting scope, and placed in a microfuge tube with 33.8-

jiL dH2O, 5-pL of 2-mM dNTPs, 3-pL of 25-mM Mg2, and 5-p.L of 10 X PCR

buffer. One pL each of 2-mM upstream and downstream primers (Bucklin et

al. 1992), and one unit (0.2-j.tL) of Taq polymerase was added last, for a total

volume of 5O-pL. Thirty-six rounds of PCR were performed in a MJ

Researcher, model PTC-150-16, thermal cycler. Products were visualized

on a 2 % Tris-acetate-EDTA agarose gel stained with ethidium bromide.

Bands of the appropriate size range (500 bp) were cored and subjected to a

second round of PCR. Four restriction enzymes, Rsa I, Hae III, Msp I, and

Taq I were used to digest the second round PCR products for RFLP,

following manufacturer's instructions (Sigma Chemical and GIBCO - BRL).

Haplotypes were scored by analyzing restriction fragments on

ethidium bromide stained, 2 % Tris-acetate-EDTA agarose electrophoresis

gels.

The index of genetic variability used was haplotype diversity,
where h = haplotype diversity, x1 = the frequency of the ith haplotype, and i

= the number of haplotypes (Nei 1987).

Although there are molecular techniques that can provide finer

resolution (e.g.. direct sequencing, end-labeling; Avise 1994), the rationale

in this study was to develop an approach for detecting sublethal effects in

populations. In keeping with this strategy, it was necessary to process a

large number of samples (> 1000), at a low cost, in a short amount of time.

A chronological summary of the steps in the genetic analysis

procedure is outlined below:

DNA extraction from individuals

PCR amplillcation of mtDNA 165 rRNA locus

Agarose gel electrophoresis to determine success of

amplification Second PCR amplification to purify the target DNA sample Restriction digest Agarose gel electrophoresis to generate RFLPs Estimation of haplotype diversity by station

4.6 Macroinfauna

Macroinfaunal samples remained in buffered formalin until they were

returned to the laboratory. Samples were washed with fresh water on a 0.5-

mm mesh sieve to remove formalin and any remaining sediments, and then

placed in rose bengal stained 70 % ethanol. The samples remained in the

stain-alcohol mixture for at least 24 hours to permit the stain to penetrate

the more dense exoskeletons of benthic arthropods. Samples were then

examined using dissecting microscopes. All organisms were removed from

the shell hash or debris in the sample and were placed in clean 70 %

ethanol, a process that allowed some destaining prior to identification. The

sorter initialed and noted the date on the tracking sheet, and then returned

all materials to the sample jar. The sample was subsequently re-examined

by another sorter who removed any organisms missed by the first sorter.

When the tracking sheet indicated that a sample had been examined twice,

the organisms were sorted to polychaete and non-polychaete categories and

placed these organisms in separate vials. The specimens were then

identified and counted. All specimens of each species were placed in a vial

with a label bearing species name, station number, and date. Notes were

4-34
made regarding the presence of ovigerous females, sex, and numbers of

young specimens (based on general knowledge of sizes of adult organisms)

in the population. The data were recorded on printed data sheets.

Macroinfauna diversity calculations were calculated the same as for

meiofauna data (Section 4.4.6).

4.7 Megafauna Invertebrates

At least five individuals (10 when possible) of the most abundant

species of macroinvertebrates common to the platform and comparison sites

were targeted for analysis. Most of the megainvertebrates collected were

fairly large, easily identifiable species. Therefore, most specimens were

identifiable on shipboard with existing taxonomic keys.

4.7.1 Reproductive Effort

Upon return to the laboratory, all preserved animals were rinsed in

fresh water at room temperature for 6 to 12 hrs to remove the Bouin's

fixative. The samples were then dehydrated by rinsing twice each in 50 %

and 70 % ethyl alcohol for 4 to 8 hrs and were then stored in 70 % alcohol

until further processing.

The methods used and the tissues selected and prepared for

histological embedding were specific to species. For shrimp, the tail was

cut off behind the carapace. The exoskeleton and all exterior appendages

were removed. The heads were then longitudinally cut in half. After

dehydration and paraffin infusion (see below), shrimp were placed with the

sagittal cut facing the bottom of the mold to be cast. Crabs were

longitudinally cut in half. The exoskeleton and all exterior appendages were

removed from one side of the skeleton. Crabs were oriented upside-down in

the paraffin mold so that the gonad/digestive tissue was next to the bottom

of the mold. Starfish were cut so that all arms were removed from the

central body disc. Starfish were further decalcified at this point if the

skeleton had not been completely dissolved by the Bouin's fixative. Starfish

legs were positioned in the paraffin mold so that the oral ends were next to

the bottom of the mold. For scallops; the stomach, gonad, gills, and a

portion of the mantle tissue were excised from the adductor muscle and

4-35
other viscera. Scallops were placed so that the entire section was oriented

horizontally in the mold. For stomatopods the ventral exoskeleton, head, and

appendages were removed. After dehydration and paraffin infusion, the

dorsal exoskeleton was removed. Each stomatopod specimen was then cut

into four serial segments and embedded with the distal end of each section

facing downward in the paraffin mold. Hermit crabs were dissected so that

their tail section was separated from the body. The exterior integument

covering the tail was cut in several places to allow adequate dehydration and

diffusion of paraffin into the tissue. Hermit crabs were cut serially into as

many sections as required, usually three or four. The distal end of each

section was placed facing down in the paraffin mold.

All animal tissues were dehydrated before being embedded in paraffin

for histological analysis. Samples were processed using an MX-200

TissueTek automated histological preparation machine. A standard

embedding procedure is summarized in Table 4.10. Once the samples were

processed by the TissueTek, they were placed in paraffin in a vacuum oven

overnight. The next day, individual tissues were placed into a mold and cast

in fresh paraffin, as previously discussed. The paraffin blocks were sliced at

10-jxM on an AO microtome. The sections were affIxed to microscope slides

using albumin adhesive by standard methods, and placed on a warming tray

for 6 hrs to smooth the sections. Two or three sections, depending on size,

were placed on each slide and triplicate slides were made of each sample.

The slides were then exposed to forinalin fumes overnight to harden the

albumin adhesive. The slides were stained using a standard hematoxylineosin (H&E) procedure following Preece (1972; Table 4.11)

After staining, tissue sections were analyzed for sex and stage of

reproduction. No scales for stages of reproductive development were

available for most crab and shrimp species. Scales were developed based on

literature information and observations. The stages of reproduction were

based on the size and development of eggs and the overall density of

gametes. The reproductive scale for crabs was based on Johnson (1980) and

is summarized in Table 4.12.

The scale for reproductive development was similar for shrimp

species and is based on Bell and Lightner (1988). More information was

available for the stages of reproductive development in penaeid shrimp,

especially for females, so the scale for shrimp (Table 4.13) was more

4-36
Table 4.10. A standard embedding procedure for histological analysis.

Procedure Treatment Time

Dehydration 80%EtOH lh

95%EtOH 2h

95%EtOH 2h

100%EtOH 2h

100%EtOH 2h

100%EtOH 2h

100%EtOH lb

Clearing xylene ih

2b

2h

Infiltration 50:50, xylene and paraffin 2 h

paraffin 2h
Table 4.11. Standard hematoxylin-eosin procedure to stain slides (after Preece 1972).

Staining Hams' bematoxylin 8 mill.

lmnsing Water wash 5 mm.

Decolorizing Acid alcohol 3 quick dips

Rinsing Water wash 1 mm.

Bluing Lithium carbonate .5 mm.

Washing Water wash 2 mm.

Counterstatning Picro-eosin/Navy eosin 1 mm.

Dehydration 95 % EtOH 2 dips 95%EtOH 3dips

100%EtOH 1mm.

100%EtOH 1mm.

100%EtOH imin.

Clearing Xylene 5 min

Xylene 5 mm

Mounting Permount 24 h to diy

Procedure Treatment Time

Deparaffinization Xylene 5 mill.

Xylene 5 mm.

100%EtOH 5mm.

100%EtOH 5mm.

Colloidionization Celloidin solution quick dip

Hydration 80%EtOH 2mlm

50%EtOH 2mm.

30%EtOH 2mm.

Water wash 5 mm.
Table 4.12. Histological reproductive development scale for crabs (after

Johnson 1980).

Numerical

Designator Reproductive Stage Characteristics of Stage

FEMALE

1 Early Few eggs or sperm present, but few

and very small

2 Mid Ova do not fill cyst, loosely

arranged

3 Mature Ova fill space, closely packed, nucleated

4 Fertilized Sperinatophore present

MALE

1 Early Small loosely packed spermatids

2 Mid Mixed ages of sperm

3 Mature Closely packed sperm, sperm in

ducts

4 Spawning Spermatophores in anterior vas

deferens

detailed than that for crabs. The scale used for scallops (Table 4.14)

analyzed was the same scale used for oysters as more fully described in Craig

et al. (1989) and used by Wilson et al. (1992). Little information is available

on the reproductive cycles of starfish and stomatopods so the sex was

determined and an approximate stage of reproductive maturity assigned

(Table 4.15) based on the size of eggs and the overall density of gametes

(Freeman and Bracegirdle 1971).

Histopathological analyses of tissue samples were conducted on ten

(10) individuals of each target species. After Cruise 1, an effort was made to

preserve the five (5) largest female and five largest male individuals for

histopathological analyses. Analysis of parasitism and disease was hampered

by a lack of scales to describe the severity of parasitism or pathologies found

in these species. Each tissue section was scanned and the total number of

occurrences of each specific parasite and pathology was counted.
Table 4.13. Histological reproductive development scale for shrimp (after Bell and Lightner 1988).

Numerical

Designator Reproductive Stage Characteristics of Stage

FEMALE

1 Undeveloped Ovary barely noticeable

2 Early Ova do not fill cyst, loosely

arranged

3 Late Ova fill space, closely packed, no

rod-shaped peripheral bodies visible

4 Ripe Peripheral bodies visible in ova

5 Spawning peripheral bodies visible in

remaining ova, spaces left by

spawned ova visible

6 Spent Few ripe ova left, remnants of

follicles

7 Resorbing Disorganized zone of resorption

present in core of cyst, some ripe ova visible

MALE

1 Undeveloped Vas deferens visible but no sperm

found

2 Early Few sperm, loose packed

3 Late Dense sperm

4 Mature Very dense sperm, sperm in ducts

4-40
Table 4.14. Histological reproductive development stages for scallops.

Numerical

Designator Reproductive Stage Characteristics of Stage

1 Undifferentiated Little or no gonadal tissue visible

2 Early Follicles beginning to expand

3 Mid Follicles expanded and beginning coalesce; no mature gametes

present

4 Late Follicles greatly expanded, coalesced, but considerable

connective tissue remaining; some

mature gametes present

5 Fully developed Most gametes mature; little

connective tissue remaining

6 Spawning Gametes visible in gonoducts

7 Spawned Reduced number of gametes; some mature gametes still remaining; evidence of renewed reproductive activity

8 Spawned Few or no gametes visible, gonadal

tissue atrophying
Table 4.15. Histological reproductive development stages for starfish and

stomatopods.

Numerical

Designator Reproductive Stage Characteristics of Stage

1

2

3

4

Early Eggs very small; and few eggs or

sperm present

Mid Eggs larger and more mature;

gametes more dense

Late Eggs larger and mature; gametes

very dense

Spawning Number of eggs present are

reduced; some mature gametes still

remaining; evidence of renewed

reproductive activity

Two common descriptors of parasitism and disease, prevalence and

infection intensity, were calculated to describe the frequency and severity of

parasitism and disease in these populations. Prevalence (P) describes the

proportion of individuals in the population that were infected by a specific

parasite or pathology and was calculated as:

(number of individuals with the parasite or pathology > 100 number of individuals analyzed )

Intensity (I) of parasitism was calculated for each of the major

categories of parasites and pathologies and is a measure of the relative

severity of infection within the population. Tabulated values of intensity (I)

represent the mean condition in the infected individuals and was calculated

for each species at each site as:

total number of occurrences of a parasite or pathology

number of individuals that have the parasite

For statistical analysis of intensity, uninfected individuals were also included.

4.7.2 Immunological Probe

The protocol for developing the antibody to egg protein is described.

New Zealand white rabbits were used as the host animal to raise antibodies
against egg protein for each species selected. Three portunid crab species

were chosen (Portunus gibbesit, CalUnectes simtlis, and CaUinectes

spinicarpus). Eggs were obtained from gravid females and prepared for

injection as described by Choi et al. (1994). Freund's adjuvant complete,

which contains a water-in-oil emulsion and a mycobacteria cell suspension

as an antibody production stimulant, was used for the initial injection.

Subsequent injections used Freund's adjuvant incomplete, which lacks

mycobacteria. For injection, the antigen (i.e., egg protein) was well-mixed

with FreundTs adjuvant and injected into the rabbit subcutaneously at the

hind legs. The total volume of injected material was adjusted to 1 mL. This

1 mL was injected in 200-pL aliquots at several different sites around the

hind legs. The injection schedule and protocol used in the production of

antiserum is suimnanzed in Table 4.16.

Table 4.16. Summary of immunization protocol.

1st Week

2nd Week

3rd Week

4th Week

5th Week

6th Week

7th Week

8th Week

Initial injection Booster

None

Booster and test bleeding

Booster

Booster

None

Test bleeding

4-43

1-mg Antigen in 500 j.iL + 500-jiL FAC

500 -pg Antigen in 500-jiL + 500-pL FAT

None

500 -pg Antigen In 500-pL + 500-pL FAT

500-pg Antigen in 500-pL + 500-p.L FAT

500-pg Antigen in 500-pL + 500-IlL FAT

None

None

FAC: Freund's adjuvant complete. FAT: Freund's adjuvant incomplete.

At the 4th and 8th week after injection, 10-mL of test blood was

withdrawn from the rabbit and the antiserum isolated from the red blood

cells. To do this, the blood was collected in a clotting vial, which was then

stored at 4 °C overnight or at room temperature for 10 b. After clotting, the

blood was centrifuged at 700 pg for 15 miii., the antiserum pipetted into a

centrifuge tube, and stored at 4 °C.

To determine percent water, and to store egg masses, each egg mass

was weighed, frozen, lyophiized and reweighed for 24 h. Percent water was

calculated as lyophilized wt/wet wt.

Egg protein content was determined by adding a known quantity of

lyophilized eggs to a 50-mL polystyrene centrifuge tube and mixing with a

known quantity of PBS solution (0.15 M NaC1, 0.003 M KC1, 0.01 M

Time Activity Treatment
NaH2PO4, 0.01 M KH2PO4, pH 7.4). Eggs in PBS were sonicated using a

Branson Sonifier 250 equipped with a microtip set at level 6 for 2 mm. To

prevent excessive warming during sonication, the tube was placed in an icefilled beaker. After sonication, the egg homogenate was centrifuged at 7000

X g for 20 mm to precipitate the insoluble material. The quantity of soluble

protein contained in the egg homogenate was determined using the BCA

Protein Assay.

The immune response of the rabbit to the egg protein was followed

using a passive hemagglutmnation technique as described by Choi et al.

(1993). Polyclonal antibodies often exhibit cross-reactions with non-target

tissues. Cross-reactions were assessed using Ouctherlony's double diffusion

method using gill, muscle, and stomach tissues. The method is described in

detail in Choi et al. (1993). Cross-reactions were not observed. Tests of

cross-reactivity between species showed that all three egg antibody

preparations from the three species strongly cross-reacted. Very likely,

antibodies made against egg protein from any one species can be used in

assays for all three. Nevertheless, species specificity was retained in all

assays by only using antibodies raised against egg protein from one species

for assays on that species.

The assay used to determine the quantity of egg protein present was

the single ring immunodiffusion method described by Choi et at. (1993).

Crabs to be analyzed were weighed and the gonad/digestive gland complex

removed and weighed. Tissues were first homogenized using a glass

syringe-piston tissue grinder and further homogenized using an

ultrasonicator. The crab homogenate was placed in an ice-filled beaker

during somcation. After 3-mm. sonication, the homogenate was centrifuged

at 900-jig for 15 mm and the volume of supernatant was recorded. Then,

one (1) mL of supernatant was concentrated by lyophiization to permit

detection of lower concentrations of gonadal protein. After lypholization, a

known amount of PBS was added for resuspension.

Twenty (20) mL of agarose gel in barbital buffer was liquefied by

placing the gel in boiling water. The tube containing gel was then placed in a

water bath adjusted to 50 °C. Above 56 °C, antiserum can be denatured and

can lose its specificity. Two (2) mL of antiserum was added to the gel tube

and agitated until the serum was completely mixed with the gel. A 10-cm X

10-cm glass plate was placed on a horizontal table and the plate was leveled.

4-44
The gel containing antiserum was poured on the plate and allowed to solidify

for 10 mm. The plate coated with gel was then placed at 4 °C for 15 mm. to

further solidify the gel. Four (4) mm diameter wells were made in the gel

plate using a gel puncher connected to an aspirator. Each well was 1.8-mm

in depth and 4-mm in diameter, and held up to 25 j.iL antigen.

Twenty j.tL of antigen were added to each well. The plate was placed in

a humid chamber, and incubated at 4 °C for 3 to 6 days. Each plate

contained standards and the samples to be analyzed. Standards were

prepared using egg protein in a range of 10 to 100-pg/mL by making serial.

two-fold dilutions.

After incubation, the plate was washed with distilled water to remove

any residual antigen in each well and a 10.2-cm X 10.2-cm wet ifiter paper

was placed on the plate. The plate was then placed on a 0.5 cm thick layer

of paper towels and covered with a layer of paper towels 2.5 cm thick. The

plate was pressed with several volumes of books for 1 h. The plate was

dried at 45 °C until the filter paper could be pulled off. The plate was

stained with 0.5 % Coomassie brilliant blue staining solution for 2 to 3 h and

destained with destaining solution for 1 to 2 h.

The diameter of the precipitation ring was measured to 0.1 mm using

a vernier caliper. A standard curve was constructed using the ring diameter

squared (mm2) versus the standard concentration (mg/mL). The

concentration of gonadal protein was interpolated from the standard curve

and expressed as milligram of gonadal protein per milliliter of crab

homogenate.

The total amount of gonadal protein was estimated by multiplying the

SRID value (mg gonadal protein per mL crab homogenate) by the total

homogenate volume (mL). The total dry weight of eggs was estimated by

dividing the total amount of gonadal egg protein measured from SRID by the

average percent weight of egg protein.

4.8 Megafaima - Demersal Fish

Most of the demersal fish collected were easily identifiable species.

Most specimens of interest in the present study were identified on

shipboard with existing taxonomic keys immediately after they had been

captured. Following appropriate necropsies and removal of stomachs, bile,
and tissue samples, these specimens were immediately preserved in 10 %

buffered formalin and returned to the laboratory for taxonomic confirmation.

Each specimen identified on shipboard was individually tagged, numbered,

and re-identified on-shore. Since each tissue sample and stomach removed

bears the same number as the fish from which it was removed, subsequent

taxonomic changes could be made without ambiguity.

4.8.1 Necropsies

All individuals of each target species were examined externally for

gross pathological disorders including skin ulcers, fin erosion, gill

abnormalities, visible tumors, cataracts, or vertebral abnormalities. Fish

found to have pathological defects were preserved for detailed

histopathological examination.

4.8.2 Histopathology and Splenic Macrophage Aggregate Analysis Methods

Samples of the liver and spleen were taken from all specimens and

processed for histopathological analysis. Tissue samples were dehydrated in

an ethanol gradient, cleared in xylene, and infiltrated and embedded in

paraffin. Sections were cut at 6-i.LM on a rotary microtome and slides were

stained with Harris' hematoxylin and eosin. Stained slides were examined

microscopically by fish pathologists. Results were tabulated to identify any

pathological abnormalities and to create a baseline of histopathological data.

Splenic macrophage aggregate (MA) analysis was performed on tissue

sections of spleen prepared for histological evaluation as described above.

Data are generated using a true color (HSI imaging) Particle Analysis

package (Microcomp Image Analysis System with Sony 3CCJ) color video

camera input). The system was calibrated and data collected at 10 X

magnification. Three fields of view (screens) were randomly selected, and

analyzed from each spleen sample. Mter a screen was randomly selected

minor adjustments of the microscope stage position were made so that no

MAs are lying on the edge of the counting field. Then, the full color image

was captured as a digital image. Analysis was performed on images

generated by computer-produced masks of the MAs in each screen with the

number of MAs per screen and the area in J.LM2 of each MA recorded and
stored under an appropriate file name for future statistical analysis. A size

discriminator was used to eliminate objects < 50-p.M2 (-size of three

aggregated macrophages). Total screen area counted was also determined

for calculation of percent area occupied by MAs.

4.8.3 Analysis of Fish Food

Fish food analysis was conducted for fish species whose food was also

analyzed for chemical contaminants. On shipboard, specimens for food

analysis were identified, labeled, and preserved in 10 % buffered formalin.

In the laboratory, these specimens were re-identified, the stomachs were

removed, rinsed in water overnight, and transferred to 70 % ethanol for

storage. Food analysis procedures followed those of Darnell (1958) and

Rogers (1977). Food volumes were determined by volume displacement.

Stomach contents were then transferred to a petri dish containing a bottom

grid so that the percentage composition of each food group could be visually

estimated. Identification of food items was made to the lowest reasonable

taxonomic level. Results were reported in tenns of pooled data (i.e., all

individuals examined from the Near station at a site or Far were pooled).

4.9 Detoxification

CYP lA-catalyzed enzyme assays (ethoxyresorufin o-deethylase, EROD

and aryl hydrocarbon hydroxylase AHH) were optimized with respect to pH,

temperature, protein content, substrate concentration, and length of time

for linearity for fish. Microsomal preparations were made from all samples

as noted in Section 4.9.1. Microsomal protein content was anal,rzed by the

method of Bradford (1976). After removal from liquid nitrogen, samples

were kept on ice during all processing steps. The samples were

homogenized using a Polytron in an appropriate buffer.

4.9.1 Crustaceans

The green gland, or hepatopancreas, was homogenized in a buffer

containing 0.1 M potassium phosphate, pH 7.4, 0. 1-M KC1, 1-mM EDTA,

0.1-mM phenanthroline, 1.0 mM dithiothreitol and 1.0 mg/mL trypsin

inhibitor. The samples were then centrifuged at 600 X g for 20 mm, 10,000

X g for 20 mm and finally 100,000 X g for 60 min. The microsomal pellets

were resuspended in a buffer containing 0. 1-mM potassium phosphate, pH

4-47
7.4, 1.0 mM EDTA, 1.0-mM dithiothreitol, 0.1 mM phenanthroline, 1.0

mg/mL trypsin inhibitor and 15 % glycerol. Microsomes were immediately

frozen in liquid nitrogen until enzyme assays were conducted.

4.9.2 Annelids

Whole annelids were homogenized in a buffer containing 50-mM Tris

at pH 7.5, 0.15-M KC1, 0.25-M sucrose. Following homogenization, samples

were centrifuged at 700 X g for 10 mm.; 8000 X g for 10 mm.; and 100,000

X g for GO-mm. Microsomal pellets were resuspended in a buffer containing

50-mM Tris at pH 7.5, and 1-mM EDTA in 20 % glycerol and immediately

frozen in liquid nitrogen until analysis.

4.9.3 Molluscs

The hepatopancreas was homogenized in a buffer containing 20-mM

Tris at pH=7.6, 0.5-M sucrose, 0. 15-M KC1, and 1-mM EDTA. Samples were

centrifuged at 500 X g for 1 b; 10,000 X g for 45 min.: and 100,000 X g for

90-mm. The microsomal pellets were resuspended in a buffer containing

20 mM Tris at pH=7.6, 1-mM EDTA, and 20 % glycerol. Samples were

immediately frozen and stored in liquid nitrogen until analyses.

4.9.4 Fish

Livers were homogenized in a buffer containing a 0. 1-M Ti-is at pH=7.4

containing 0.25-M sucrose and centrifuged at 600 X g for 10 miri.; 5000 X g,

for 10 mm.; 13,000 X g for 10 mm.; and 100,000 X g for 60 mm. The

microsomal pellet was resuspended in a 50-mM Ti-is at pH=7.5 containing

1-mM EDTA in 20 % glycerol. Samples were immediately frozen in liquid

nitrogen until enzyme assays were conducted.

4.9.5 Ethoxyresorufin 0-deethylase (EROD) Assay for Fish

EROD activity was measured in fish hepatic samples fluorometrically as

described by Pobl and Fouts (1980) with modifications. The assays were

conducted in 1. 15-mL incubation mixtures consisting of 0. 1-M HEPES at

pH=8.0, 0.1-mg NADPH, 0.1-mg NADH, 0.7-mg BSA, 0.7-mg of MgSO4, and

50-pL of microsomes (200 to 250-pg microsomal protein). The samples

were preincubated for 2-mm. at 30 °C. The reactions were initiated by the

4-48
addition of 50-.tL of 100-mM ethoxyresorufin. The samples were allowed to

incubate for 10 or 15-mim and stopped with the addition of 2.5-mL of

methanol. The samples were allowed to sit in the incubator for 5-mim, after

which they were centrifuged for 15-mm to pellet the flocculated protein.

Samples were read on a spectrofluorometer at 550-nm excitation and 585-

nm emission wavelength settings.

4.9.6 Aryl Hydrocarbon Hydroxylase (AHH) Assay for Fish and

Invertebrates

AHH activity was assayed in both fish and invertebrates as described by

Nebert and Gelboin (1968) with modifications. For fish the assays were

conducted in 1.0 mL of reaction mixture containing 0.1 -M HEPES at

pH8.0, 0.4-mM NADPH, and 500-jig of microsomal protein. The samples

were preincubated at 30 °C. The reaction was initiated with the addition of

80-pM benzo[a]pyrene (BaP) in 40-j.tL of methanol. The samples were

incubated for 10 or 15 miii and stopped with the addition of 1-mL cold

acetone, after which 3.25 mL of hexane was added. The samples were

shaken and then two (2) mL of the organic layer was withdrawn and

extracted with five (5) mL of NaOH. The samples were shaken again and a

NaOH aliquot was read on a spectrofluorometer at 396 excitation and 522

emission wavelength settings. The spectrofluorometer was calibrated using

an authentic 3-hydroxy BaP standard. This assay was slightly modified for

the invertebrate assays. The reaction mixture consisted of 50 mM Tris at

pH=7.6, 0.1-mM NADPH and 50OO-pg protein. The reaction was initiated by

the addition of 60-jiM BaP in methanol. The samples were incubated for 15

miii at 30 °C and stopped with the addition of 1-mL of cold acetone. The

extraction procedure and instrument analysis were as described for fish.

4.9.7 Rat Hepatoma H-411E Assay

Invertebrate tissues were extracted using a Tissumizer with 50-g of

NaSO4 and 100-mL of CFI2CJ2 in 200-mL centrifuge tubes and described in

the contaminant section. The extraction was repeated two more times with

100 mL of CH2C12. The extracts were combined and concentrated. The

concentrates were purified using silica gel/alumina columns and HPLC to

remove matrix interferences. The purified extracts were then evaporated to

near dryness and redissolved in a known volume of DMSO.

4-49
Rat hepatoma H-411E cells were grown as a continuous cell line in aminimum essential media supplemented with 2.2-gIL sodium bicarbonate,

10 % fetal bovine serum, and 1O-mL/L antibiotic/antimycotic solution

(Sigma Chemical Co.). Stock culture cells were grown in 150-cm2 plates at

37 °C in a humidified air/carbon dioxide (95 %/5 %) atmosphere. After

confluency, cells from one plate were trypsinized and seeded in six 6-well

plates of two (2) mL medium per well. After 24 h, cells were dosed with the

5-mL test extracts so that the final concentration of DMSO was 0.25 %.

Each sample was dosed in triplicate wells. For maximum induction

measurements, cells were treated with 1-nM 2,3,7,8-TCDD. After 24 h

incubation, media was removed from the cells (approximately 106

cells/well). Cultures were washed with 2-mL Hanks' solution (Hanks'

balanced salts, 0.35-g/L sodium bicarbonate at pH=7.4). Cells were

harvested by scraping in 4-mL of Tris and sucrose solution (Tris base 6.05

gIL, sucrose 59.45 g/L, pH 8.0). The cellular pellet was isolated after

centrifuging for 5 mm at 1000 rpm at 4 °C. Cells were resuspended in 200-

pL Tris and sucrose solution of which 50-jiL was used for protein

determination and 50-jiL for EROD analysis.

4.9.8 mRNA Method

4.9.8.1 Isolation of RNA

Total JNA was isolated from homogenized liver samples in one (1)-mL

of solution D (4-M guanidinium thiocyanate, 100-niM NaOAc, 0.5 % sarcosyl

at pH=5.5 and 0. 1-M 2-mercaptoethanol) by the method of Chomczynski and

Sacchi (1987) with modifications. RNA was extracted by adding 50 pL of 2

M sodium acetate to 125 to 500-pL of sample to which 500-.tL of watersaturated phenol, 200-1L water, and 200-pL of Sevag (24:1

chloroform:isoamyl alcohol) was added. The samples were vortexed and

centrifuged for 15 mm. at 12,000 X g. This extraction was repeated three

times. The final aqueous layer was added to one volume of isopropyl alcohol

and precipitated overnight at -20 °C. The resulting precipitate was

centrifuged at 12,000 X g for 15 mm, supernatant decanted, and the pellet

washed with two 70 % washes and one 100 % ethyl alcohol wash. The dried

pellet was resuspended in 15 to 50-j.tL formamide by heating at 55 °C. The

RNA was quantitated by UV absorption at the 260 nm wavelength.

4-50
4.9.8.2 Northern Blot

A sample containing 20-jig RNA in 2 X sample loading buffer (35 %

formaldehyde, 10 % 10 X SPC, 25 % TE, and 30 % 6 X tracking dye; the TE

solution was 10-mM TRIS and 1 mM EDTA at pH=8 and the dye was 0.25

%-xylene cyanol, 0.25 %-bromophenol blue, 25 %-ficoll, and 0. 1-M EDTA)

was loaded onto a 1.2 % agarose gel (0.66-M formaldehyde) and analyzed at

50-75 V for 3-4 h in 1 X SPC buffer (10 X SPC contained 200-mM Na2HPO4

and 20-mM EE)TA at pH=6.8). The gel was stained with ethidium bromide,

washed, and transferred to a HybondTM-N+nucleic acid transfer membrane

for a minimum of 12 h. The membrane was washed in 0.1 X SPC, crosslinked by UV exposure and baked for 1 to 2 b at 80 °C. The membrane was

prehybndized in t)enhardts (20 % 5 X SSPE, 1 % SDS, 10 % dextran

sulfate, and 0.1 % of each polyvinylpyrolidone. bovine serum albumin, and

ficoll; the 20 X SSPE contained 3.0-M NaC1, 0.2-M NaPO4, and 0.02

Na2EDTA) for 12 h at 42 °C. Membranes were hybridized for approximately

24 hr in the prehybridizing solution with the addition of 106 cpm/mL 32P

randomly labeled freshwater rainbow trout probe for P450 JA. The trout

CYP1A1 cDNA plasmid (pfP 14503) was a gift from Dr. John Lech (Medical

College of Wisconsin, Milwaukee). The plasrnid was transfected into DH5 a

competent cells (amp R) and the plasmids were amplified. A 1.4 kb size

cDNA fragment was obtained by excising with Eco RI and PST I. The levels

of CYP1A were standardized against f3-Tubulin using human fetal brain f3-

Tubuliri plasmid HFBA18 (ATCC). a 1.5 kb cDNA fragment was obtained by

excising from transfected Ecoli ELi-Blue with EcoRI. After hybridization,

membranes were washed twice at ambient temperature in 2 X SSC for 10

mm. Two additional washes were carried out at 50 °C for 45-mm each in 2

X SSC and 0.1 % SDS. Membranes were washed twice more for 30 min at

room temperature in 0.1 X SSC. The membranes were quantitated on a

l3etagen Betascope 603 Blot Analyzer imaging system. Finally, the

membranes were exposed to X-OMAT imaging film (Kodak) and

photographed. Membranes were stripped by washing twice in stripping

buffer (0.1 X SSPE and 1 % SDS) at 100 °C.
4.9.9 PAH Metabolites in Bile

Biliary PAH metabolites were analyzed by HPLC/fluorescence

detection, which has been described in detail elsewhere (Krahn et al. 1984;

1986a,b). Bile was injected into an HPLC. Metabolites were resolved using a

C-18 reverse-phase column and fluorometrically quantified. Aromatic

compounds fluorescing at naphtbalene (290/335), phenanthrene

(260/380), and BaP (380/430) excitation/emission wavelengths were

analyzed. Metabolites eluting from the column within specific retention

times were summed to yield total fluorescence based on equivalents of

known amounts of naphthalene, phenanthrene, and benzo[a]pyrene

standards.

4.9.10 Dosing Experiments

Fish used in dosing experiments were captured by trawling. Fish were

maintained in flow-through tanks on the deck of the ship. Fish were

acclimated for 2 days prior to dosing with 3[HJTCDD.

4.9.11 Ah Receptor Binding

3[H]TCDD synthesized in this laboratory to 95 % purity (30 Ci/nmol) in

corn oil was administered to Lagodort rhomboides and Synodus foetens in a

single i.p. injection (1 jiL/g fish to equal 2.5 .g/kg). Nuclear extract

baselines were obtained by cotreatment with 100-fold excess unlabeled

TCDD. Four fish of each species were used for both completed and

uncompleted trials. Fish were maintained in tanks for 4 h prior to sacrifice.

Livers were isolated, resuspended in HEGD (25 mM HEPES, 1.5 mM EDTA,

1.0 mM dithiothreitol, 10 % glycerol (v/v), pH 7.6 buffer), homogenized

using a teflon pestle/drill apparatus and centrifuged at 4000 x g for 10 mm

at 4 °C. The resulting nuclear pellet was washed twice with 10 mL HEGD

and was resuspended in HEGD buffer, containing 0.5 M potassium chloride

and incubated at 4 °C for 1 hr. Samples were frozen in liquid nitrogen and

returned to the laboratory for further processing. Upon receipt in the

laboratory, samples were thawed and after a 30 mm, 105,000 x g spin at 4

°C, unbound and loosely bound 3[H]TCDt) was removed by incubating with

4-52
dextran coated charcoal (0.5 mL of 0.01:0.001 % charcoal:dextran per mL of

nuclear extract) for 10 mill at 4 °C. Protein concentrations were

determined by the method of Bradford (1976).

Aliquots (400 .tg of protein) of sample were layered onto linear

sucrose density gradients (5 to 25 %) prepared in HFDG buffer containing

0.5 M potassium chloride and centrifuged at 4 °C for 2.5 h at 404,000 x g.

After centrifugation, 30 fractions were collected from each gradient, 0.5 mL

of tissue solubilizer (DuPont) was added and samples were then incubated at

50 °C for 4 h before counting the radioactivity in each fraction. [14C]labeled

bovine serum albumin (4.4 5) and catalase (11.3 5) were used as external

standards.

4.10 Pore Water Toxicity Testing

As soon as possible after the sediment samples arrived in the lab, pore

waters were pressure extracted, centrifuged to remove fines, particulates,

and frozen. Recent studies have demonstrated that if the suspended

particulate material is removed prior to freezing, there is no difference in

toxicity between fresh and frozen/thawed samples (Carr 1993; Carr and

Chapman 1995). A separate aliquot of each pore water sample was frozen

for later chemical analysis. Pore water was stored frozen until two days

before the start of the toxicity test, at which time samples were removed

from the freezer and placed in a refrigerator to thaw slowly overnight.

Samples that remained partially frozen in the morning were allowed to thaw

at room temperature or in a tepid water bath. Water quality measurements

(dissolved oxygen, pH, temperature, hydrogen sulfide, and ammonia) were

then made, and the salinity of the samples adjusted to 35 ±1 %o, if

necessary. Hypersaline brine (-100 %o) and bottled purified water (Baker

water for HPLC) were used to adjust sample salinity. If the dissolved oxygen

concentration was below 80 % saturation, samples were gently aerated until

this concentration was achieved. Samples were then stored refrigerated

overnight and returned to 20 °C before the start of the tests.
4.10.1 Sea Urchin Tests

The toxicity of the sediment pore waters was determined using two

different tests with the sea urchin Arbacia punctulata; the fertilization test

and the embryological development test (Oshida et al. 1981; Carr and

Chapman 1992). The fertilization test consisted of exposing a known

quantity of sea urchin sperm in a 5-mL pore water sample in a scintillation

vial for 30 mm., followed by the addition of a predetermined number of eggs

and an additional 30 mm. incubation. After the incubation, the test was

terminated with the addition of 10 % buffered formalin and the percentage

of fertilized eggs was determined. Five replicates of each treatment were

performed. Treatments that produced statistically significant reduced

fertilization, compared to a control, are considered toxic. The

embryological development test is similar, except that the eggs were added

first, followed immediately by the sperm. The embryos were allowed to

develop for 48 hours before the test was fixed with formalin. Treatments

that significantly reduced development to the pluteus stage, compared to a

control, were considered toxic. Both tests were perfonned on samples from

the first cruise. Only the embryological development test was performed on

samples from the second cruise. A reference pore water collected in

Redfish Bay near Port Aransas, Texas, was included with each toxicity test.

This site is far removed from any known sources of contamination and has

been used previously as a reference site (Cart 1993; Carr and Chapman

1992; U.S. FWS 1992).

In addition, a dilution series test with sodium dodecyl sulphate (SDS)

was also conducted with each test as a positive control and the EC50

determined in order to maintain a record of gamete viability and test

acceptabffity. Filtered (0.45-iM) seawater and seawater reconstituted from

brine and bottled water were also included as controls with each test.

These methods have been used in several sediment quality assessment

surveys (i.e., Tampa Bay, Florida 1991 and 1992; Galveston Bay, Texas, 1991;

Pensacola and St. Andrew Bay, Florida, 1993).

Dunnett's one tailed t-test, a=00 1, was used to determine significant

difference in fertilization (fertilization test) and development to the pluteus

stage (embryological development test) between samples and the reference

pore water. The Spearman-Karber method, with Abbott's correction,

4-54
(Hamilton et al. 1977) was used to determine the EC50 in the SDS dilution

series.

4.10.2 Tests with Meiobenthic Species

Longipedia americana adults were collected from the Port Aransas

ship channel and maintained in the laboratory until females became gra1rid.

No earlier than 48 hours before a test, gravid females were isolated in a

separate culture container until the eggs hatched. In this manner, it was

ensured that all nauplii were less than 48 hours old at the start of a test.

The naupifi, which are phototactic, were concentrated in the culture dish by

means of a point source of light. A pipette was used to transfer the nauplii

to a small counting dish. Five naupiti were transferred from the counting

dish into each test chamber. Test chambers were stender dishes containing

10 mL of pore water. Nauplil were fed a mixture of three types of algae

(Dunatiella, Thatassiosira, and Isochrysis, approximately 20,000, 3000, and

120,000 cells per replicate, respectively). Test chambers were incubated at

20 °C for 96 b, then the test was terminated and the number of surviving

nauplii was determined for each chamber. At the end of the test, water

from all replicates was pooled and dissolved oxygen and salinity of the

pooled sample were measured.

Three replicates of each treatment were performed. A larger number

of replicates or animals per replicate was not possible because of the

difficulty in obtaining a sufficient number of test animals. On the first test

occasion, five pore water samples from the High Island A-389 platform were

tested. On the second occasion, nine samples were tested. The number of

samples tested was dictated by the number of naupffi available.

Dinophilus gyroctliatus used in the test were obtained from laboratory

cultures that have been maintained by the National Biological Survey at the

Marine Science Institute in Port Aransas, Texas for over two years. The test

was performed using the methods of Carr et al. (1989). The test was begun

with four newly hatched juvenile female polychaetes per replicate. Five

replicates per treatment were performed. The endpoint measured was the

number of eggs produced per female after 7 days of exposure at 20 °C. The

test was performed in conjunction with the first copepod test. All samples

(15) from High Island A-389 transects A, C, and E were tested.

4-55
5.0 DESCRIPTIVE RESULTS

The following section provides a detailed and descriptive review of the

data produced during Phase I of GOOMEX. As appropriate, data are

presented in tabular and graphic formats. Graphical presentations include

crossplots of variables, histograms, ternary diagrams, and plan-view contour

plots. The data are described in detail to set the foundation for later

statistical analysis and integrated synthesis of project results in Sections 6.0

and 7.0.

5.1 Physicochemical Characteristics of the Study Sites

The physicochemical variables documented at each site are

summarized in Tables 5.1 to 5.12. Data derived from Niskin bottle sampling

were integrated into the dataset by matching laboratory measured salinities

with CTD-denved salinities to determine a more accurate depth of sampling

than length of "wire-out" Salinity values are reported using the practical

salinity scale which is a unitless variable. The physicochemical work

element included the collection and analysis of 350 CTD/transmissometry

profiles, 1171 salinity samples, 1163 nutrient samples, and 1173 oxygen

samples.

MAII-686 was the shallowest of the three sites studied (water depth =

29 m). Cruises 1 and 3 and Cruises 2 and 4 exhibited well-mixed and

stratified water columns, respectively (Figure 5.1). Salinities ranged from

31.9 to 34.9 and 28.3 to 35.5 for Cruises 1 and 3 and Cruises 2 and 4,

respectively. Water temperatures were lower during Cruises 1 and 3:

(Cruise 1: 15.8 °C to 17.8 °C; Cruise 3: 15.0 °C to 16.3 °C) than Cruises 2 and

4 (Cruise 2: 22.4 °C to 26.9 °C; Cruise 4: 21.8 °C to 28.2 °C). Bottom water

temperatures and salinities were most variable during Cruises 2 and 4. This

variability was due to a thin layer of low temperature, high salinity bottom

water. An extended period of calm had produced a well stratified water

column during Cruise 4. While hypoxic conditions clearly existed in bottom

waters during Cruise 4, the areal extent of hypoxia could not be completely

discerned as the pycnocline/oxydline deteriorated with time, thus

preventing a systematic sampling of the bottom water layer. Patterns in the

data can result from bottle placement relative to the bottom water layer.

5-1
Table 5.1. Summary of CTD and discrete bottle data measured at MAI-686

during Cruise 1.

*Temp = Temperature, Sigma-t = (Density-i) X 1000; XMISS = Transmissivity; SOUNDV

Sound Velocity

Table 5.2. Sumxnary of CTD and discrete bottle data measured at MAI-686

during Cruise 2.

*Temp = Temperature, Sigma-t = (Density-i) X 1000; XMISS = Transmissivity; SOUNDV =

Sound Velocity

Variable* N Mean StdDev Minimum Maximum

Temp ( °C) 563 16.92 0.48 15.78 17.82

Salinity 563 33.61 0.81 31.93 34.90

Sigma-t 563 24.47 0.52 23.37 25.24

XMISS (%) 563 69.87 11.40 7.00 88.00

SOUNDV(m/s) 563 1511.2 2.46 1505.8 1515.5

PO4 (p.M) 74 0.07 0.04 0.00 0.21

NO3 (PM) 74 0.42 0.43 0.00 2.18

NO2 (jiM) 74 0.09 0.04 0.03 0.20

Sb3 (jiM) 74 1.98 0.65 1.21 4.31

02 (rnL/L) 74 5.54 0.09 5.37 5.82

Salinity (from Niskin bottle) 74 33.49 089 31.56 34.78

Variable* N Mean StdDev Minimum Maximum

Temp ( °C) 652 25.62 1.31 22.44 26.89

Salinity 652 30.97 2.20 2833 35.50

Sigma-t 654 20.11 L99 17.93 24.48

XMISS (%) 654 71.59 21.92 1.80 88.40

SOUNDV (m/s) 654 1531.7 1.73 1528.5 1535.0

PU4 (jiM) 74 0.09 0.13 0.01 0.63

NO3 (jiM) 74 065 1.32 0.00 6.03

NO2 (jiM) 74 0.15 0.20 0.00 0.89

5103 (jiM) 74 5.70 3.93 2.99 21.86

02 (mL/L) 74 469 0.60 2.47 5.27

Salinity (from Niskin bottle) 73 30.61 1.86 28.33 34.98
Table 5.3. Summary of CTD and discrete bottle data measured at MAI-686

during Cruise 3.

*Temp = Temperature, Sigma-t = (Density-i) X 1000; XMISS = Transmissivity; SOUNDV =

Sound Velocity

Sound Velocity

Table 5.4. Summary of CTD and discrete bottle data measured at MAI-686

during Cruise 4.

Variable* N Mean StdDev Minimum Maximum

Temp(°C) 659 25.96 2.01 21.77 28.38

Salinity 659 31.03 2.27 27.67 35.01

Sigma-t 659 20.05 2.31 16.91 24.26

XMISS (%) 659 78.70 13.89 18.73 88.02

SOIJNDV (m/s) 659 1532.6 2.50 1526.6 1535.9

PO4 (jiM) 75 0.19 0.21 0.01 0.88

NO3 (pM) 75 1.28 2.41 0.01 10.19

NO2 (jiM) 75 0.63 1.00 0.00 3.81

5103 (pM) 75 7.66 12.76 0.47 51.23

02 (mL/L) 75 4.12 1.28 0.45 5.34

Salinity (from Niskin bottle) 75 30.61 2.18 28.32 34.64

*Temp = Temperature, Sigma-t (Density-i) X 1000; XMISS = Transmissivity; SOUNDV =

Vadable* N Mean StdDev Minimum Maximum

Temp(°C) 668 15.58 0.19 15.02 16.29

Salinity 668 34.12 0.37 30.39 34.75

Sigma-t 668 25.16 0.29 22.30 25.58

XMISS (%) 668 54.95 13.18 1.09 73.66

SOUNDV(m/s) 668 1507.7 0.77 1503.1 1509.5

PO4 (jiM) 73 0.16 0.04 0.01 0.29

NO3 (jiM) 73 0.32 0.10 0.05 0.55

NO2 (jiM) 73 0.49 0.17 0.03 1.07

5103 (jiM) 73 3.66 0.98 2.02 8.16

02 (mL/L) 70 5.89 0.20 5.56 6.43

Salinity (from Niskin bottle) 72 34.03 0.53 31.56 34.67
Table 5.5. Summary of CTD and discrete bottle data measured at MU-A85

during Cruise 1.

sTemp = Temperature. Sigma-t = (Density-i) X 1000; XMISS = Transmissivity; SOUNDV =

Sound Velocity

Table 5.6. Summary of CTD and discrete bottle data measured at MU-A85

during Cruise 2.

zTemp = Temperature, Sigma-t = (Density-i) X 1000; XMISS Transmissivlty; SOUNDV =

Sound Velocity

Variable* N Mean StdDev Minimum Maximum

Temp (°C) 1849 24.25 1.90 20.44 27.13

Salinity 1849 34.73 2.06 30.22 36.54

Sigma-t 1849 23.36 2.04 19.16 25.67

XMISS (%) 1849 77.37 382 55.77 82.55

SOUNJV (mis) 1849 1532.8 290 1525.2 1537.3

PO4 (jiM) 74 0.11 0.11 0.00 0.55

NO3 (jiM) 74 1.11 1.46 0.02 3.93

NO2 (jiM) 74 0.19 0.25 0.00 1.14

Sb3 (jiM) 74 3.88 2.58 2.06 9.96

02 (rnL/L) 74 4.51 0.44 3.82 5.26

Salinity (from Niskin bottle) 74 34.17 2.42 30.35 36.20

Variable* N Mean Std Minimum Maximum

Temp(°C) 1801 20.57 0.27 19.36 21.07

Salinity 1801 35.85 0.05 35.75 36.00

Sigma-t 1801 25.26 010 25.10 25.62

XMISS (%) 1801 86.13 268 47.00 89.00

SOUNDV(m/s) 1801 1524.6 0A9 1521.8 1525.8

PO4 (riM) 74 0.04 0.03 0.00 0.11

NO3 (jiM) 74 0.23 0.32 000 191

NO2 (pM) 74 0.08 0.08 0.00 0.25

S103 (jiM) 74 2.49 0.62 L35 4.80

02 (rnL/L) 69 5.07 007 4.76 5.20

Salinity (from Nisldn bottle) 74 35.87 0.05 35.79 35.96
Table 5.7. Summary of CTD and discrete bottle data measured at MU-A85

during Cruise 3.

*Temp = Temperature, Sigma-t = (Density-i) X 1000; XMISS = Transmissivity; SOUNDV =

Sound Velocity

Table 5.8. Summary of CTD and discrete bottle data measured at MU-A85

during Cruise 4.

sTemp Temperature, Sigma-t = (Density-i) X 1000; XMISS = Transmissivity; SOUNDV =

Sound Velocity

Variable* N Mean StdDev Minimum Maximum

Temp(°C) 1921 17.41 0.80 15.87 18.81

Salinity 1921 35.44 0.37 34.23 35.91

Sigma-t 1921 25.75 0.17 24.90 26.06

XMISS (%) 1921 81.51 4.86 27.85 87.56

SOUNDV(m/s) 1921 1515.2 2.81 1508.7 1519.5

PO4 (jiM) 74 0.12 0.05 0.05 0.27

NO3 (jiM) 74 0.16 0.11 0.01 0.48

NO2 (jiM) 74 0.43 0.18 0.12 0.73

S103 (jiM) 73 2.11 0.40 1.35 3.92

02 (mL/L) 73 5.37 0J7 5.10 5.79

Salinity (from Niskin bottle) 74 35.45 0.38 34.57 35.91

Variable* N Mean StdDev Minimum Maximum

Temp (°C) 1876 22.09 3.07 19.14 28.84

Salinity 1876 34.57 2.71 27.75 36.40

Sigma-t 1876 23.84 2.93 16.69 25.98

XMiSS (%) 1876 83.46 6.23 19.60 91.22

SOUTIDV (mis) 1876 1527.0 4.59 1514.5 1536.8

PO4 (jiM) 74 0.13 0.13 0.00 0.56

NO3 (jiM) 74 L83 2.07 0.02 6.40

NO2 (pM) 74 0.13 0.17 0.00 0.52

Sb3 (jiM) 74 1.85 1.65 0.15 5.77

02 (mL/L) 74 4.48 0.45 3.55 5.56

Salinity (from Niskin bottle) 74 33.46 3.63 28.04 36.25
Table 5.9. Summary of CTD and discrete bottle data measured at HI-A389

during Cruise 1.

*Temp = Temperature. Sigma-t = (Density-i) X 1000; XMISS = Transinissivity; SOUNDV =

Sound Velocity

Table 5.10. Summary of CTD and discrete bottle data measured at HI-A389

during Cruise 2.

*Temp Temperature, Sigma-t = (Density-i) x 1000; XMISS = Transmissivity; SOUNDV =

Sound Velocity

Variable* N Mean StdDev Minimum Maximum

Temp(°C) 2921 20.59 1.01 15.36 21.35

Salinity 2921 36.08 0.10 35.10 36.42

Sigma-t 2921 25.43 0.32 24.88 26.63

XMISS (%) 2921 77.30 7.55 3.00 89.00

SOTJNIDV (mIs) 2921 1525.3 2.43 1510.5 1527.5

PO4 (tiM) 74 0.23 0.29 0.00 0.88

NO3 (jiM) 74 3.84 5.36 0.01 14.24

NO2 (pM) 74 0.03 0.02 0.00 0.06

S103 (j.tMj 74 2.97 1.53 1.06 6.03

02 (mL/L) 74 4.37 1.01 2.70 5.56

Salinity (from Niskin bottle) 74 36.15 0.14 36.02 36.47

Variable* N Mean StdDev Minimum Maximum

Temp(°C) 3158 21.08 3.14 15.84 27.11

Salinity 3158 35.61 0.99 33.04 36.41

Sigma-t 3158 24.90 1.59 21.29 26.62

XMISS (%) 3158 77.13 4.07 51.70 83.30

SOTJIDV(m/s) 3158 1525.8 6.73 1513.1 1537.5

PO4 (jiM) 75 0.29 0.38 0.00 0.93

NO3 (jiM) 75 4.50 6.23 0.01 14.12

NO2 (jiM) 75 0.02 0.02 0.00 0.07

Sb3 (pM) 75 3.50 2.46 L22 9.64

02 (milL) 75 4.27 0.96 2.87 5.15

Salinity (from Niskin bottle) 75 35.16 1.25 33.16 36.32
Table 5.11. Summary of CTD and discrete bottle data measured at HI-A389

during Cruise 3.

tTemp Temperature, Sigma-t = (Density-i) X 1000; XMISS Transmissivity; SOUNDV =

Sound Velocity

Table 5.12. Summary of CTD and discrete bottle data measured at HI-A389

during Cruise 4.

*Temp = Temperature, Sigma-t = (Density-i) X 1000; XMISS = Transrnissivity; SOUNDV =

Sound velocity

Variable* N Mean StdDev Minimum Maximum

Temp(°C) 3166 21.24 3.18 15.52 28.77

Salinity 3166 35.71 1.27 30.78 36.52

Sigma-t 3166 24.94 1.81 19.00 26.75

XMISS (%) 2295 87.35 4.19 12.08 93.01

SOUNDV (m/s) 3166 1526.4 6.48 1512.2 1539.8

PO4 (tiM) 72 0.26 0.30 0.00 0.85

NO3 (jiM) 72 3.53 5.29 0.02 14.65

NO2 (jiM) 72 0.05 0.07 0.00 0.45

S103 (jiM) 72 2.42 2.17 0.29 11.20

02 (mL/L) 72 4.40 0.88 2.95 5.25

Salinity (from Niskin bottle) 72 34.68 2.15 30.86 36.33

Variable* N Mean StdDev Minimum Maximum

Temp (°C) 3119 19.39 1.03 15.61 21.01

Salinity 3119 36.14 0.07 35.39 36.50

Sigma-t 3119 25.79 0.26 25.27 26.65

XMISS (%) 3119 85.85 2.98 60.65 89.19

SOUNDV (m/s) 3119 1522.1 2.42 1512.4 1525.7

PU4 (j.iM) 74 0.27 0.29 0.05 0.92

NO3 (jiM) 74 4.20 5.53 0.10 16.07

NO2 (''J 74 0.19 0.16 0.00 0.61

Sb3 (jiM) 74 3.69 1.98 1.84 8.40

02 (mL/L) 74 4.55 0.089 2.82 5.49

Salinity (from Niskin bottle) 74 36.17 0.06 36.10 36.46
Figure 5.1. Summary of the temperatures (°C) and salinities for surface, mid-, arid bo

at MAJ-686 for Cruises 1 and 4. Surface 0 Mid- Bottom 30 

C-) a) a) 0. Ea) I-EU) 3020- 300Dm 50Gm 50-200m C.) 0 25- a) 1I-a)a. 20- E 15 U . UU Iuii 5Gm lOOm 4e U .1 U. 20Dm 

15215/93 ' I 2/6193 2/7/93 2/6/93 616194 35 617194 35 - 30-- 3000m 50Dm S0-200m IIQQI.. - E 30-- U) 25 I . U U U U °0q0 5Dm lOOm I U.I

00 0 dj 20Gm 

25 I I I I 2/5/93 2/6/93 2/7/93 218/93 6/6194 6/7/94 

Cruise 1 Cruise 4
However, the patterns observed during Cruises 2 and 4 strongly suggest that

near platform hypoxia (Figure 5.2) in bottom waters develops in response to

stratified water column conditions (Figure 5.1).

Inorganic nutrients at MAI-686 during Cruises 1 and 3 were elevated

in surface waters with low salinity. Conversely, nutrients from Cruises 2 and

4 were elevated in bottom waters with low oxygen concentrations. Silicate

concentrations ranged from 1.2 to 8.2 p.M during Cruises 1 and 3 and from

0.5 to 51.2 p.M during Cruises 2 and 4. Elevated sfficate concentrations in

surface and mid-waters during Cruises 1 and 3 were associated with low

salinity water. The highest sfficate concentrations encountered during all

samplings were associated with low oxygen bottom waters sampled during

Cruises 2 and 4. Nitrate concentrations ranged from 0.0 to 2.2 p.M for

Cruises 1 and 3 and from 0.0 to 10.2 p.M for Cruises 2 and 4. The highest

nitrate concentrations were associated with low oxygen bottom waters

during the Cruises 2 and 4. Regeneration of nutrients in bottom waters was

apparent during Cruises 2 and 4 at MAI-686 (Figure 5.3).

MU-A85 is located in 80 m of water. Physicochemical characteristics

at MU-A85 were similar to those at MAI-686 (Figure 5.4). The water

column during Cruises 1 and 3 was well mixed or weakly stratified while

during Cruises 2 and 4 the water column was strongly stratified. The

salinity range (34.2 to 36.0) was smaller for Cruises 1 and 3 as compared to

Cruises 2 and 4 (27.8 to 36.5). The dynamic nature of water masses was

illustrated by the increased salinities during the latter half of sampling

during Cruise 3 (Figure 5.5). During a sampling hiatus, the water mass at

MU-A85 changed due to the passage of a front. The effects of vertical

mixing on the salinity structure in the upper 40 m of the water column are

clearly evident in Figure 5.5. Initially, salinities from surface and mid waters

(approximately 39 m at MU-A85) differed by 0.77 while at the end of the

first sampling period the difference was reduced to 0.14. During this time,

the sea state worsened and the depth of the mixed layer increased (from 22

m to 40 m). The temperature and the temperatures range was greatest

during the Cruises 1 and 3. Dissolved oxygen concentrations varied between

4.8 to 5.8 mL/L for all depths for Cruises 1 and 3. Near bottom oxygen

concentrations were generally 1 mL/L lower than mid- and surface water

during summer samplings (Figure 5.6). As at MAI-686, though not as

dramatic, reduced oxygen levels were observed in bottom waters during the

5-9
Cruise 3 Cruise 4 Figure 5.2. Summary of dissolved oxygen concentrations (mL/L) for surface, mid-, an

waters at MAI-686 for all cruises. Surface a Mid- U Bottom 8 8 300Dm 50Dm 50-200m _J 6-- _J - - E E = .0 

C0) C) --- CC) C) --- . .. >1)(0 - 2-- >1X0 - 2-- 3000m 5Cm 20Cm SOOm 

0 0_ I I i I t 

2/5193 2/6/93 2(7193 2/8/93 6/6/93 6/7/93 6/8/93 

Cruise 1 Cruise 2 8 8 : lOOm 50m 20Dm 

._. 6- - -- E'.. - 4- 50-i 0Dm 200-50Cm 500-3000m EC : OcflE!.s , U 0) C) -- 0) C) -- . >1X - 2- . U U. 0- 0- . U 0_ . 1 I I I I I I 1/27/94 1/28/94 1/29/94 1/30/94 1/31/94 6/6/94 6/7/94 
Figure 5.3. Relationship between oxygen and nutrient concentrations

at MAT-686 for all cruises.

5-11
Surface 0 Mid I Bottom 2826- C) 0 24- 3000m 28 Figure 5.4. Summary of the temperatures (°C) and salinities for surface, mid-, and bo

at MU-A85 for Cruises 1 and 2. I.. 0) Q. E =-- 50-lOOm 00r1 50Dm .II. 3000m 5Dm . . lOom 50Dm 20

18 18 ' I ' I ' I 2/7/93 2/8/93 2/9/93 2/10/93 6110193 6/11/93 6/12193 

38 36 3000m 3000m 50m 1 OOm,500m 20

50-lOOm 00n 50Dm . 36- U d 0 . C - > - E . 34- Ct - U) - 32- N 30 I I I I 30 I I I 2/7/93 2/8/93 2/9/93 2/10/93 6/10/93 6/11/93 6/12/93 

Cruise 1 Cruise 2 +.! I*s+ . 0 0 0
Surface 0 Mid Bottom 36.0 35.5- 35.0- 20Gm .ul. .uuI.. C 0 0 C + 4 10Gmoo 0 0 50m S 

34.51/31/94 I ' I 2/1/94 2/2194 Cruise 3 Figure 5.5. SalinIty values for surface, mid-, and bottom waters at MU-A85 for C

. 5Gm + 
Surface 0 Mid Bottom 8 3000m 50-lOOm 200ni 500m 7- E6 FIgure 5.6. Summary of dissolved oxygen concentrations (mL/L) for surface, mid-, an

waters at MU-A85 for all cruises. 0) - 04: CW 5- 0)-- >x - 04-3_ . IU 300Dm 50m 0 0U. lOOm500m 200

3_ I 217193 2/8/93 1 I I Cruise 1 2/9/93 2/10/93 86/10193 I I I I 6/11/93 6/12/93 Cruise 2 87- -JE 6- ) !- 0)--- 0 4- .wIe. . 200m O0tir 5Dm hp 50m 8°Q 7- -JE6 Co 5-. a) - >1 - 04-3 10Dm 50m0 . .. cQ° C U Ii . .0 200m 500

. 

3_, I 1 1/31/94 2/1/94 I I I 2/2/94 I 2/3194 6/8(94 I J 619/94 Cruise 3 Cruise 4
summer samplings. Nitrate concentrations during Cruises 2 and 4 were

much higher in the bottom waters compared to surface and mid-waters.

Nitrate concentrations were much lower in bottom waters during the

Cruises 1 and 3 as compared to Cruises 2 and 4 (Figure 5.7). Silicate

concentrations during Cruise 1 were fairly uniform throughout the water

column; while during Cruise 3, the silicate concentrations were about 1-jiM

higher in bottom water as compared to surface and mid-waters. During

Cruises 2 and 4, silicate concentrations in bottom waters were 1.5 to 3

times higher than in the surface or mid-water. The relationship between

dissolved oxygen, bottom water silicate, and phosphate was similar to that

observed at MAI-686 (Figure 5.8).

The deepest site sampled was HI-A389 with bottom depths ranging

from 110 to 157 m. Physicochemical variables at HI-A389 are summarized

in Tables 5.9 to 5.12. During Cruises 1 and 3, the water column was well

mixed down to approximately 100 m. During Cruises 2 and 4, the water

column was strongly stratified (Figure 5.9). The temperature was lower for

near-surface and mid-waters during the winter (20 °C to 21.4 °C, 19.2 °C to

21.4 °C; top, mid-water) as compared to the summer (26.2 °C to 28.8 °C,

19.9 °C to 24.0 °C) while the bottom water was similar for all cruises (15.4

°C to 18.9 °C). For all depths during Cruises 1 and 3, salinities ranged

between 36.0 and 36.4. The stations at 5000-rn distance on Cruise 3 were

influenced by a tongue of high salinity water at a depth of 60 to 100 m.

Surface salinities were significantly lower for Cruises 2 and 4 as compared to

Cruises 1 and 3, probably due to local precipitation. Bottom salinities were

similar for all four cruises. Dissolved oxygen profiles for all cruises were

similar; surface and mid-water concentrations were -5-mL/L and bottom

water concentrations were -3-mL/L (Figure 5.10). Nitrate, silicate, and

phosphate concentrations were generally low in surface and mid-water

samples and enriched in bottom waters (Figures 5.11 and 5.12).

5.2 Sedimentology

Substantial heterogeneity in sediment texture; as expressed in grain

size, mineralogy, and carbon content; was apparent at all of the sites studied.

Redox potential, as measured by platinum Eh electrode, was also highly

variable. The sedimentologic setting at each site is described in detail in

5-15
Surface 0 Mid Bottom 6 2/8/93 2/9/93 Cruise 1 2/10/93 . Figure 5.7. Summary of nitrate (iiM) concentrations for surface, mid-, and bottom wat

for all cruises. :1w(U.-5:--4 -- - -- 0 - 3000m I A 5Oni I I U lOOm,500m .1i. 20

6110193 7 I 6(11/93 6/12193 Cruise 2 6- 50m I 20Dm 50

S. I- 1 20Dm lOOm 50m 50m 2 4 U) (U 3 I-z 2-0 U U 1 OOm 0d0 00.#..4U.. 0 0 0 I .-wEES c00

01/31(94 2/1194 212194 213/94 6/8/94 619194 

CruIse 3 Cruise 4
7

3

Bottom

Mid-

.

. U

U. 00 h.

. .. ci'0o60

0

. U.

U

Bottom Water

rO.41

Surface

-' 6-

Oxygen (mLJL)

/

'U = Bottom -... .11.

a42- ... U

=-:-

- z 2M- 0 °:

:Surface

-

Bottom Water

r2=O.89

6

Figure 5.8. Relationship between oxygen and nutrient concentrations

at MU-A85 for all cruises.

5-17

w0

(I)

12

10

8

6

4

2

0

3

/

Surface 0 Mid Bottom

w

0

0.

0.6

0.5--

0.4-

0.3-

0.2

o.1-

0.0

Bottom

Mid--

. . .

.

. .

0UQU

0

'

Bottom Water

r2= 0.52

Surface U

I 00

0

4 5 6
Surface 0 Mid- U Bottom 3000m lOOm 200m S. .. .t% .qf. 0Dm 50m 211193 2/2193 500rn 5Cm, ......rnuii 1/29/93 I I I I I I I I 37 0 o QX9 dcçs90 5Dm lOOm, 300Cm 20Dm .. U 

c9 .4 

36- 336/13/93 6/14/93 6/15/93 Cruise 2 

Figure 5.9. Summary of the temperatures (°C) and sailnitles for surface, mid, and bo

at HI-A389 for Cruises 1 and 2. E(0cn 15371129193 I 1/30/93I I I I 1/31/93 36--- 35-- 34- 33 300Dm '1 I I 0 50m lOOm, 3000m 20Dm 1/30/93 1/31/93 2/1/93 2/2/93 Cruise 1 15 1 I I 6/13/93 6/14/93 6/1 5/93 lOOm +20Dm
Figure 5.10. Summary of dissolved oxygen concentrations (mL/L) for surface, mid, a

waters at HI-A389 for CruIse 2. Surface 0 Mid Bottom 65 - _J -- E - a) 0 32 050m U I o 0++. , lOOm, 3000mU N I 200m 4. 0 0 + 500m N 6/13193 1 I I I 6/14/93 6/15/93 Cruise 2 
Surface 0 Mid Bottom

1.0

0.8-

0.7:

0.6-

0.4: 0 - a- O.3-

0.2 -

0.1

0.0

6/13/93

15

a

z

12 -

50m

.

lOOm, 3000m 200m 500m

0

6/13193

.

50m

e1A

6/14/93

lOOm, 3000m

6/15/93

200m 500m

6/16/93

Figure 5.11. Summary of phosphate and nitrate concentrations (jiM) for

surface, mid-, and bottom waters at HI-A389 for Cruise 2.

5-20

6/14/93 6/15/93 6/16/93

Cruise 2
Figure 5.12. Relationship between oxygen and nutrient concentrations

at HI-A389 for all cruises.

5-21
the following sections. The sedimentology work element included the

collection and analysis of 718 grain size, 125 mineralogy, 760 carbon, and

720 Eb samples.

5.2.1 Grain Size

Grain size data by study site is summarized in Figures 5.13 to 5.15.

The most dramatic feature was the relationship between sand content (%)

and distance from the platform. Stations out to a distance of 100 m were

clearly enhanced in sand content. Stations between 200 and 500 m were

impacted to varying degrees, apparently depending on water depth,

discharge location (i.e., near-bottom shunting), and the volume of the

discharge. The sand content of sediments at the near-field stations was

increased above background sediment by 35 to 60 % depending on the site.

All indications were that most of this increase in sand size materials was the

result of disposal of drill cuttings and muds during the drilling phase of the

platformTs history. Sand content is also enhanced by winilowing of fine

particles by bottom currents from sediments adjacent to a structure, sand

disposal during sand blasting activities, and deposition of large carbonate

skeletal fragments from platform-associated biota. It should be noted that

the shallowest, highest energy site exhibited the greatest enhancement in

sand. However, the mechanics of effluent discharge and the magnitude of

the discharge are important controls on the sand content observed in

sediments adjacent to a platform.

During Cruise 1, all samples from MAI-686 at 500 and 3000 m

distance were sandy muds with percent sand ranging from 19 to 50 % for

the 3000 m sample, and 25 to 39 % for the 500 m samples (Figure 5.16).

All samples from 200-rn distance were also sandy muds, with the exception

of sample 1D, a muddy sand. Sand percentages ranged from 28 to 34 %

except for 1D which was about 70 % sand. All remaining samples from rings

100-rn distance were muddy sands and varied from 61 to 84 % sand. On

Cruise 2, samples from 500 and 3000 meters distance were all sandy muds,

with sand varying from 15 to 39 %. The 200-rn stations were also sandy

muds except for the station on the D radial which had a sand content of 74

%, slightly higher than the Cruise 1 samples from the same station. The

sample from the E radial at 200 m falls on the boundary between sandy mud

5-22
Figure 5.13. Summary of sediment grain size at MAI-686 by distance from the p
Figure 5,14. Summary of sediment grain size at MU-A85 by distance from the p
Figure 5.15. Summary of sediment grain size at H1-A389 by distance from the p
Figure 5.16. VarIability in mean sand content (%) with distance from the platform by cr
and muddy sand. Sediments 100-rn distance from the platform were

much the same during the first two cruises except for stations 2A and 3C.

At station 3C, the Cruise 1 sample was a muddy sand. On Cruise 2, the same

station yielded a sample that was sandy mud. The difference was about 14 %

less sand in the Cruise 2 sample, from 60 % to 46 %. The boundary

between the two sedimentary classifications is 50 %. However, on Cruises 3

and 4 the same station yielded sandy muds with 45 % and 37 % sand,

respectively. Sediments with a high percentage of sand form an irregular

elongate shape around the platform oriented in a southwest/northeast

direction with the highest amounts of sand close to the platform (Figure

5.17). This pattern reflects the southwesterly flowing currents that

transported the sand away from the drill site.

At MU-A85, sediments at 3000-rn distance were sandy muds except

for station SD which contained only 8 % sand and was classified as a mud

(Figures 5.17 and 5.18). Sediments at 500 m distance were also sandy muds

except station 4A which was classified as a mud and contained at least 6.1 %

sand (i.e., 3.9 % below the boundary between mud and sandy mud). All

samples from the 200 m distance were sandy muds. At 100-m distance,

four samples were muddy sands and one station, 3E, was sandy mud

containing 45 % sand. Sediments closest to the platform were muddy sands

containing between 28 and 40 % mud. Samples collected during Cruises 2,

3, and 4 were generally within a few percent of the grain size compositions

observed for Cruise 1. Station 4C (500 m) was an exception; it was a sandy

mud during Cruise 1 and a mud during Cruise 2. However, this was not a

significant difference as sand content at station 4C of Cruise 1 was 13.5 and

13.9 % and the equivalent sample from Cruise 2 was 9.5 and 8.9 % sand.

The boundary between sandy mud and mud is 10 % sand. The two samples

from Cruise 2 lie within the mud field by only 0.5 and 1.1 %; respectively. A

similar relationship was seen between samples 3D and 3E (100 m distance).

Samples from these stations during Cruises 2 and 3 were sandy muds, but

during Cruise 4 only 3D was classified as a sandy mud. The sand content

isopleths indicated an easterly orientation to the sand halo (Figure 5.17).

This could be due to transport by the prevailing currents.

Sediments collected at FU-A389 during Cruise 1 at a distance of 500

and 5000 m were all muds (Figure 5.17 arid 5.19) except for station 4E

which was borderline between mud and sandy mud. Samples at 200 m

5-27
E

0

a.E0

a

0

C

. -ao

a, a

S

N

E

E

0

a.E

0

Ia

U

C

33)

0

S

MAI-686 Sand Content %

an

MU-A85 Sand Content % HI-A389 Sand Content %

N N

a

S

3)0

Figure 5.17. Meal distribution of sand content (%) in sediments as a

composite of all four cruises.

5-28

-3)0 0 3)0 w Distance from Platform (m) £

-an 0 W Distance from Platform (m) E

-ax 0 300 W Distance from Platform (m) E
Figure 5.18. VarIability In mean sand content (%) with distance from the platform by cr
Figure . 19. Variability In mean sand content (%) with distance from the platform by cr
distance from the platform were muds or sandy muds. Samples from all five

locations at 100 m distance were sandy muds. The closest samples at

stations 2A, 2B, and 2C were sandy muds but stations 2D and 2E were

muddy sands. With only one exception, the analyses of samples taken at the

same station varied by less than 11 % in sand content and most samples

between cruises varied by only a few percent (Figure 5.19). On Cruise 2,

samples from 200 to 5000-rn distance on radii A, B, and C were all muds.

The 50 and 100 m stations were all sandy muds except for the samples from

50-rn distance on radial 13 which were muddy sands. On radial D, samples

from 5000 and 500 m were both muds, samples from 200 and 100 m

distance were sandy muds, and from 50 m distance were muddy sands. On

radial E, the 500 and 5000 m stations were muds and the 50, 100, and 200

m stations were sandy muds. On Cruise 3, all ten samples from the 500-rn

and 5000-rn distance were muds. All ten samples at 500 and 5000 m from

Cruise 4 were muds except for station 5A which was a sandy mud. On the

last two cruises, the sediments at the 200-rn sampling stations were all

muds except for Cruise 3, stations lB and 1E and Cruise 4, station 1D which

was sandy mud. All of the samples from the 100 m distance on both cruises

were sandy muds except from station 3C which were muddy sands. During

both cruises the 50-rn samples were sandy muds except for station 2D

which was a muddy sand.

An examination of sand fractions from all three sites, using a

stereoscopic microscope and reflected light, indicates the presence of drifi

cuttings in samples from the innermost stations at all three sites. The

cuttings were characterized as very large rounded quartz-sand grains (two to

three times as large as grains in background sediments from the area) and

lithoclasts (fossiliferous limestones, chert and/or fine grained limestone).

In addition, there were some angular, very fine, quartz-sand grains that may

have been derived from sand blasting of the platform during rust-control

programs. Small sand-size metallic spheres were interpreted to be droplets

of molten metal from welders or cutting torches that fell into and were

quenched by seawater. Also visible were fragmented carbonate skeletal

material derived from organisms that encrust the underwater parts of the

platform. The most abundant skeletal remains were polychaete worm tubes

and barnacles. The enhancement in sand size particles was clear at all three

sites and was consistent with previous studies around platforms. The

5-31
addition of sand-sized particles to the adjacent sediments as part of drilling

disposal practices has been well documented. At HI-A389, an enhanced silt

fraction was also evident in a cluster of samples closest to the platform

(Figure 5.15). This indicated an addition of silt-size materials as the result

of drill mud disposal. Sediments at HI-A389 within 50 m of the platform

were more than 40 % barite in some instances.

5.2.2 Mineralogy

Mineralogic analysis was only conducted for Cruise 1 samples and is

summarized by site. At MAI-686, quartz, clays, and feldspar were the

dominant minerals (Figures 5.20D and E). Quartz, clays, and feldspars were

the only minerals identified on the X-ray diffraction patterns of samples

taken at MAI-686. At MU-A85, 500-rn and 3000-rn distance from the

platform, the sequence of minerals was generally clays, quartz, feldspar, and

calcite, in order of abundance with the exception of samples 5A, 58, and 5C

which had about equal amounts of quartz and clays. Barite was detected in

samples 3D, 2D, and 2E (Figure 5.20). The mineralogy of samples at HIA389 at 500-rn and 5000-rn distance was typical of sediments on this side of

the East Flower Garden Bank (Figures 5.20F and G). Clays dominate the clay

size fraction while quartz and calcite were distributed in varying proportions

in the sand- and silt-size fractions. The sand-size fraction consisted mostly

of planktonic foraminifera and eroded debris from dead coralline algae

patchreefs that are scattered over the bottom at these depths. The silt-size

fraction is mostly a mixture of quartz and tests of foraminifera. The

presence of feldspar and dolomite at this distance from the platform is most

probably because of the erosion of seafloor outcrops of Pleistocene and/or

older sediments. Such outcrops have been documented in the general area

(Rezak et al. 1985). Sediments 200-rn distance from the HI-A389 platform

began to show the effects of drilling activity with traces of bante at stations

1A, 18, 1D, and 1E. The aragonite in sample 1D is probably a mollusc

fragment derived from the nearby bank. Barite was also detected at 100-rn

distance at stations 3A, 3B, and 3E in about the same relative amounts. Also,

quartz was the most abundant mineral within 100-rn of the platform because

of the shunting of drill cuttings. The relative amount of barite increased at

stations 2A, 2B, and 2C. At station 2E, there was no increase in barite
Figure 5.20.

CI F

CI

a

Q

Degrees 20

5-33

MU-A85

Station 1D

MU-A85

Station 2D

MAI-686

Station 2A

X-ray diffractograms of sediments from the study area. (B=barite,

Ca=calcite, C1c1ay, F=feldspar, Hhalite. Ii11ite, Qquartz). A: M1T-A85, station

1D; B: MU-A85, station 2D (note small main barite peak at 25.8°); C: Enlargement of B showing the barite peak; D: MAI-686, station 2A.

5 10 15 20 25

10 20 30 40 50 60

a

F CI CI

MU-A85

Station 2D

0 10 20 30 40 50 60

F CI
CI

QB

a

B

Ca H B

5-34

B Ca

HI-A389

Station 2A

H I-A389

Station 5A

Figure 5.20 (contj. E MAI-686, station 5A F: HI-A389, station 2A (note the

main barite peak at 25.8°); G: HI-A389, station 5A (the halite

is an artifact of the evaporation of interstitial seawater).

a MAI-686

Station 5A

F H CI

B

V

40 50 60

I I I 10 20 30

Degrees 20
content over that present at station 3E. The distribution of barite around

this platform supports the conclusion that the predominant bottom currentdirection near this site is towards the northeast (Rezak et al. 1985);

however transport of materials has occurred in both directions (i.e.,

southwest).

The mineralogy of the sediments on the Texas OCS has been

investigated in considerable detail. The primaiy role of the X-ray diffraction

in this study was to determine if barite could be identified. The limit of

sensitivity of the technique was about 5 % barite. X-ray diffraction was able

to identify barite at two of the study sites. Neutron activation analysis for

barium is a much more sensitive technique than x-ray diffraction and

therefore, it is more effective in determining the presence and amount of

barite in sediments.

5.2.3 Carbon Content

Organic and inorganic carbon content in sediments varied depending

upon a number of factors including sedimentation rates, water depth, water

colunm primary productivity, influx of land-derived detritus, sediment redox

conditions (preservation), in situ production (bacterial), and anthropogenic

inputs (i.e., cuttings). The organic carbon content of sediments at the study

sites was generally within the range found on the Texas OCS (Table 5.13).

Table 5.13 Range values of total organic carbon (TOC) and inorganic carbon

(TIC) concentrations at the three sites in percent (%) carbon.

MAI-A686 0.ltol.5 00to3.4

MU-A85 0.2 to 1.5 0.3 to 2.2

HI-A389 0.4 to 2.5 0.0 to 5.0

The areal distribution of total organic carbon (TOC) was often quite

complex around the platform (Figures 5.21 to 5.24). However, in general,

TOC content in sediments decreased near the platform. The addition of

sand sized particles reduced TOC content by dilution (Figure 5.25).

Total inorganic carbon (TIC) enrichment near the platform included

debris deposited by platform-associated biota (Figures 5.26 to 5.29). There

5-35

Site TOC (%) Range TIC (%) Range
'a 

9-y 

1/ 

Total Organic CarOfl 

(%) 

:' P 

, .cc 

piiiiìiiIiiic1 

4 

I V/////////f///" 

/ 
N

E

E

0

S

a.E0IS

0

. -3)0 S

$ -3)0

-6)0w

300

MAI-686 Total 0 anic Content %

MU-ASS Total 0 . anic Content % HI-A389 Total Or. anic Content %

Figure 5.22. Meal distribution of mean total organic cathon content (%) in

sediments as a composite of all four cruises.

5-37

-300 0 300 w Distance from Platform (m) E

3)0

Distance from Platform (m) E

-3)0 0 300 W Distance from Platform (m) E
Figure 5.23. VarIability in mean total organic carbon content (%) in sediments with di

the platform by cruise at MU-A85.
1! 

ød 

I 1%%'/// 

1 

I. 

Total OrganiC Carbon 

(%) 

\ 
Figure 5.25. Relationship between sand and total organic carbon content (%) In sedim

sites for all cruises. oC0C 32- 0 ---U-- . < x x : --U U I.U U U UU . x 0 MAI-686 >< MU A85 U 

U - x .o5

M

0 I 110 I I 20 I I I I I I 30 I I I 1 I I I I 40Sand (%) I 60 70
IT7 

I / 

Total 

Inorganic Carbon 

(%) 

I '///////////V' 

_ 

I VAj4 

I 7//////////, 
N

E

E

I

. -200 a

S

MU-A85 Total Inor. nic Carbon

MAI-686 Total Inor. nic Carbon %

-200 0 3)0 w Distance from Platform (m) E

N

E

E

I

-3D0

S

Hl-A389 Total lnoranic Carbon %

Figure 5.27. Areal distribution of mean total inorganic carbon content (%)

in sediments as a composite of all four cruises.

5-42

-200 0 200 0)0 w Distance from Platform (m) E

-3)0 0 200 w Distance from Platform (m) E
Figure 5.28. Variability in mean total Inorganic carbon content (%) in sediments with 

the platform by cruise at MU-A85.
"I 

Carbon (%) 

Total Inorganic 

,, p., 

//////// 
was also a source of inorganic carbon in the discharged cuttings. TIC

content closely correlated with sand and suggested that the sand-sized

particles contain carbonate (Figure 5.30). TIC and TOC content were also

correlated with TOC. TOC content decreased as TIC increased suggesting a

dilution of TOC similar to the trend observed with sand (Figure 53 1).

5.2.4 Redox Conditions (Eh)

The range in redox potential, as measured by a platinum electrode at

each site, is summarized in Table 5.14. The areal distribution of redox

potentials at each site are summarized in Figures 5.32 to 5.35. Redox

potential as measured as Eh (my) was highly variable at the study sites.

Redox conditions showed significant variations among cruises and among

sites (Table 5.14). Trends with distance from the platform were also highly

variable and difficult to interpret. More detailed and rigorous studies will be

needed to fully understand the influence of redox conditions on benthic

animals and contaminant disturbances.

Table 5.14. Summary of the ranges in Eh-potential (mVJ at the three study

sites measured by platinum electrode.

5.3 Contaminants

The contaminant portion of this study included the analysis of a suite

of organic and inorganic analytes previously detected near platforms.

Organic anaiytes included aJiphatic and aromatic hydrocarbons in sediments.

Polycyclic aromatic hydrocarbon (PAH) concentrations were also

determined in megafaunal tissues (invertebrates and demersal fish) and pore

waters. A suite of major and trace metals were analyzed in tissues,

sediments, and pore waters. The methods employed are those utilized by

the NOAA National Status and Trends Program and the EPA-EMAP program,

making the results presented here directly comparable to these large

environmental databases. The contaminant work element collected and

5-45

Site Eh(mV)

MAI-686 -93 to +204.0

MU-A85 -93 to +268.5

HI-A389 -92 to +233.0
Figure 5.30. Relationship between sand and total inorganic carbon content (%) in sed

sites for all cruises.
Figure 5.31. Relationship between organic and inorganic carbon content (%) in sedim

sites for all cruises.
Figure 5.32. Variability in mean redox potential (mV) in sediments with distance from 

by cruise at MAI-686.
NE

EI-0

E

C

0

S

N

E

0

S

MAL-686

N

Redox Potential m

E

0

S.

E

0

a

C

. -330 00

S -

- -3)0 0 3(X)

Figure 5.38. Area! disiribution of mean redox potential (mV) in sediments

as a composite of all four cruises.

5-49

-aDo -330 0 3)0

W Distance from Platform (m) E W Distance from Platform (m) E

- -3)0 0 3X)

w Distance from Platform (m) E

MU-ASS Redox Potential m HI-A389 Redox Potential m
Figure 5.34. VariabilIty in mean redox potential (mV) in sediments with distance from 

by cruise at MU-A85.
CD 

01 

I 

H 

0 

a 

a 

rj 

CD 

CD 

ci) 

ci) 

I 

I 

CPQ. 

RedoX Potential (mV) 

'77 - 
analyzed 760 sediments, 810 tissues, and 60 pore waters for hydrocarbons

and metals.

5.3.1 Hydrocarbons in Sediments

Total polycyclic aromatic hydrocarbons (PAH), a]iphatic hydrocarbons

(AH), and the unresolved complex mixture (UCM) concentrations are

summarized by cruise for each site in Figures 5.36 to 5.44. At MAJ-686,

total alkanes, total PAH, and total UCM concentrations varied from 72 to

9,568 (mean=800) ppb; 7.8 to 588 (mean=53) ppb; and 0.0 to 119.4

(mean=7.5) ppm, respectively. At MU-A85, the same parameters varied

from 68 to 13,960 (mean=789) ppb; 12.7 to 6,358.5 (mean=162) ppb; and

0.0 to 381.8 (mean=27.8) ppm, respectively. At HI-A389, the same

parameters varied from 63 to 15,927 (mean=571) ppb; 11.4 to 1,238.1

(mean=14t3.5) ppb; and 0.0 to 406.1 (mean=26.7) ppm, respectively. A

weak gradient in petroleum related variables was observed at MAI-686

(Figure 5.36). Steeper gradients with distance from the platform were

observed in total alkane, UCM, and PAH concentrations at the MU-A85 and

HI-A389 sites (Figures 5.36 and 5.44).

Sediments from most stations contained little or no evidence of

petroleum contamination. Concentrations for UCM, total PAH and total

alkanes at most stations were less than 10 ppm, 150 ppb, and 500 ppb,

respectively. The method detection limit for total PAH in sediment is

approximately 100 to 150 ppb. The areal distribution of the hydrocarbon

contaminants was not symmetrical around the platforms with concentration

gradients varying in steepness among radii (Figures 5.45 to 5.47).

Concentrations generally reached constant, background levels at distances of

100 to 200 m from the platform (Figures 5.36 to 544). Two exceptions

were noted for total alkanes at MAJ-686 and PAH at HI-A389 which were

enhanced above background to a distance of 200 m (Figure 5.46,

respectively). At MAI-686 a few stations exhibited gas chromatograms

typical of fresh condensate contamination (predominance of lower molecular

weight n-alkaiies and no UCM) during all four cruises, suggesting a recent

and continuing influx of hydrocarbons (i.e., pipeline leak or an active seep;

Figure 5.48). In contrast, the contaminants at most stations at MU-A85 and

HI-A389 lacked n-alkanes and exhibited a large UCM (Figures 5.49 and

4.50). Sediment extracts at HI-A389 exhibited a range of compositions

5-52
Figure 5.36. Variability In mean total PAH concentrations (ppb) in sediments with dist

the platform by cruise at MAI-686.
Figure 5.37. VariabIlity in mean total PAR concentrations (ppb) in sediments with dist

the platform by cruise at MU-A85.
Figure 5.38, VaabIIi In mean tot P Concenatjons (ppb) In sediments dth 

tce 

the platform by cruise at HI-A389.
Figure 5.39. VariabIlity In mean total alkane concentrations (ppb) In sediments with d

the platform by cruise at MAI-686.
Figure 5.40. VariabilIty In mean total alkane concentrations (ppb) In sediments with d

the platform by cruise at MU-A85.
Figure 5.41. VarIability in mean total alkane concentrations (ppb) in sediments with di

the platform by cruise at HI-A839.
Figure 5.42. Variability in mean total UCM concentrations (ppm) in sediments with di

the platform by cruise at MAI-686.
Figure 5.43. VarIability in mean total UCM concentratIons (ppm) In sediments with dis

the platform by cruise at MU-A85.
Figure 5.44. Variability In mean total UCM concentrations (ppm) in sediments with di

the platform by cruise at HI-A389.
NE

E

a

S

MU-A85

NE'-S

E

I

a

S

ax3

MAk686 Total PAH

Total PAH

W Distance from Platform (m) E

Figure 5.45. Areal distribution of mean total PAH concentrations (ppb) in

sediments as a composite of all four cruises.

5-62

-ao 0 w Distance from Platform (m) E

0

W Distance from Platform (m) E
N

33o EI-0

0.

E

0

I0

a3o

S

-830w

N

S

MU.-A85 Total All. hatic H drocarbons

MAI-686 Total All. hatic H drocarbons

NE

EI-0

S

a.E

S

a

. -330 S

a

S

HI-A389 Total All. hatic H drocarbons

-coo -ma 0 ma

Figure 5.46. Areal distribution of mean total aliphatic hydrocaibon concenirations

(ppb) in sediments as a composite of all four cruises.

5-63

-830 -330 C) 330 w Distance from Platform (m) E

coo Distance from Platform (m)

0 ma E W Distance from Platform (m) E
N

N

E

E

I

2 -300 VI C

S

MUA85 Total UCM

MAI-686 Total UCM

-8)0 -an) 0 300

E

N

E

EI-0

a, a-E

2

a, C

S

HIA389 Total UCM

Figure 5.47. Areal disiribution of mean total UCM concentrations (ppm) in

sediments as a composite of all four cruises.

5-64

- 0 W Distance from Platform (m) E

W Distance from Platform (m) E

Distance from Platform (m)

S

-8)0 -3)0 0 300 w
0 5 10

II1IIIIII Ii II

30 35 40 45

Station 3D Cruise 2

Station 3D Cruise 1

CFJ C

c'j

C

III III I 1111111 PIj F 15 20 25 30 35 40 45

Retention Time (minutes)

Figure 5.48. Gas chromatograms (flame ionization detection) of

sediment extracts from MAI-686.

5-65

32

28-

24- C

0

C

C

20-

C

16-

12 11111 iIII-I-i I I ii

0 5 10 15 20 25

64 IC 0

54- 0)

0

C

34-

24-

14 I I

I I III!! 1111111
0

34-

30-

26-

22-

18-

14

Station 2B Cruise 1

r

I 1111111

5 10 15 20 25 30 35 40 45

C)

0

9

Station 3E Cruise 1

ii 11111 I IllIlIllIll r I Il I I I I

I I I I ! 1I I 0 5 10 15 20 25 30 35 40 45

Retention Time (minutes)

Figure 549. Gas chromatograms (flame ionization detection) of

sediment extracts from HI-A389.

5-66

93

83

63.:

43

33

23

13-c I 111111 Fl1 ii'
36

32-

28-

24-

20-

16-

74-

54-

44-

34-

24-

14 -

0

Station 2B Cruise 1

a)

12 I I

I I 1 I 1111111 I 0 5 10 15 20 25 30

Station 2D Cruise 1

a)

0

35 40 45

10 15 20 25 30 35 40 45

Retention Time (minutes)

Figure 5.50. Gas chromatograms (flame ionization detection) of

sediment extracts from MU-A85.

5-67
probably resulting from differential input from multiple sources of

hydrocarbon contaminants. One station appeared to be contaminated with a

low molecular weight fluid. Other stations exhibited a bimodal UCM

suggesting that possibly two or more sources of petroleum were present in

the area (Figure 5.50).

Hydrocarbon concentrations were similar between cruises, suggesting

that the low level contamination observed was relatively stable over time.

The greatest variations between cruises were detected at stations nearest to

the platform, reflecting steep, near-platform gradients and the

heterogeneous distribution of hydrocarbons in sediments.

5.3.2 Trace Metals in Sediments

Metal concentrations are summarized in Table 5.15. Variations in

metal concentrations (on a dry wt basis) among cruises are illustrated for

selected metals in Figures 5.51 to 562. Contour plots are presented for

aluminum and iron, which are major elemental constituents of the alumino

silicate minerals, and cadmium (Cd) and barium (Ba), which are typical

metal contaminants (Figures 5.63 to 5.66). In regard to the level of

contamination by metals among sites MAI-686 site was lowest, MU-A85 was

intermediate and HI-A389 was highest, the same order observed for

hydrocarbon contamination. Metals exhibited one of three distributions: (1)

metal concentrations that increased near the platform, (2) metal

concentrations that decreased near the platform, and (3) metal

concentrations that bad no detectable change in concentration in relation to

the platform. The metals with near uniform distributions include silver,

arsenic, copper, mercury, antimony, selenium, and tin. These metals show

little change relative to distance from the platform. An exception to this

relatively uniform pattern was an increase for a few of the metals (Ag, As, Ca,

and Hg) near the platform at HI-A389 where the very highest metal levels

were observed. Since a dilution of the sediments with 35 to 60 % of sand

has occurred, uniform concentrations suggest that a platform-related source

must be present to counteract the documented dilution event. In support of

this interpretation, several metals show a decrease near the platform

including aluminum, chromium (occasionally), iron, nickel, and vanadium.

The remaining metals; barium, cadmium, lead, and zinc; increase in

5-68
Table 5.15. The ranges in metal concentrations (ppm) in surficial sediments (0 to 2 cm) from GOOMEX study sites.

Metal MAI-686 MU-A85 HI-A389

(ppm) (ppm) (ppm)

Ag 0.1-1.7 0.0-1.0 0.0-3.8

Al 17,700-71,000 29,100-121,626 11,359-75,037

As 4.2-21.6 3.6-39.1 3.4-32.2

Ba 653-4680 720-26,250 785-280,220

Cd 0.0-1.6 0.0-2.3 0.1-63.7

Cr 25.5-82.0 37.8-131.0 35.0-171.0

3.8-48.9 5.5-36.2 9.0-106.1

Fe 11,940-30,280 13,680-69,940 15,400-36,590

Hg 0.0-0.1 0.0-0.3 0.0-3.5

Ni 0.5-28.5 7.5-28.5 9.2-35.4

Pb 0.2-555 15. 2-436 02-694.8

Sb 0.3-2.4 0.3-5.5 0.4-7.5

Se 0.0-0.3 0.1-0.8 0.2-0.8

Sn 0.2-3.0 0.7-79.5 0.5-3.2

V 43.3-119.5 27.8-208.5 3.41-145.5

Zn 43.1-3850 54.6-1440 65.741,444
t'V 

o1it3w 
Figure 5.52. Variability in mean iron concentrations (ppm) In sediments with distance 

platform by cruise at MU-A85.
Figure 5.53. Variability in mean Iron concentrations (ppm) in sediments with distance 

platform by cruise at HI-A389.
Figure 5.54. Variability in mean aluminum concentrations (ppm) In sediments with d

the platform by cruise at MAI-686.
Figure 5.55. Variability In mean aluminum concentrations (ppm) in sediments with di

the platform by cruise at MU-A85.
Qi Qi Figure 5.56. VarIability In mean aluminum concentrations (ppm) In sediments with d

the platform by cruise at HI-A839.
Figure 5.57. VarIability in mean barium concentrations (ppm) In sediments with distan

platform by cruise at MAI-686.
Figure 5.58. VariabIlity in mean barium concentrations (ppm) in sediments with dista

platform by cruise at MU-A85.
Figure 5.59. Variability in mean barium concentrations (ppm) in sediments with distan

platform by cruise at HI-A389.
Figure 5.60. VariabilIty in mean cadmium concentrations (ppm) In sediments with dis

the platform by cruise at MAI-686.
Figure 5.61, Variability in mean cadmium concentrations (ppm) in sediments with dis

the platform by cruise at MU-A85.
Figure 5.62. VariabIlity in mean cadmium concentrations (ppm) In sediments with dis

the platform by cruise at H1-A389.
N

-S

E

E

$ -330

0

S

MU-A85

NE

EI-0

a.E

0

C

0

2 -3)0

0

S

330

Iron N

E

0

a.E0I0

2

0

S

Figure 5.63. Area distribution of mean iron concenirations (ppm) in sediments as a composite of all four cruises.

5-82

-330 -330 0 3)0

W Distance from Platform (m) E

-330 0 3)0 -3)0 - 0 330 w Distance from Platform (m) E W Distance from Platform (m) E
MU-A85 Aluminum

MAI-686 Aluminum

N

E

E

I

S

HI-A389 Aluminum

Figure 5.64. Areal distribution of mean aluminum concentrations (ppm) in

sediments as a composite of afl four cruises.

5-83

- -330 0 330 W Distance from Platform (m) E

- 0 Distance from Platform (m) E

-330 0 330 W Distance from Platform (m) E
MU-A85

3)0-

2500

N

-%

E

E

I-0

a.E

2

a

U

a

a

0

S

Barium (ppm)

- -3)0 0 3)0 000

N

£

E

0

a-E

0

1a

C, C

a

a

0

S

Figure 5.65. Areai distribution of mean barium concenirations (ppm) in

sediments as a composite of all four cruises.

5-84

W Distance from Platform (m) E W Distance from Platform (m) E

-3)0 0 Distance from Platform (m) E
Distance from Platform (m) E

W Distance from Platform (m) E

N

E

0

0.

E

$ -&XD w

HIA389 Cadmium

-3)0 0 X)

Distance from Platform (m) E

Figure 5.66. Areal distrtbution of mean cadmium concenirations (ppm) in

sediments as a composite of a] four cruises.

5-85

-3)0 0 3)0 5)0
sediments near platforms. The magnitude of the increase is determined in

part by the metal content of the original materials discharged at each site.

A covai-jate analysis of metal concentrates delineates those metals that

strongly covary (r> 0.4) with barium; these metals are silver, cadmium,

mercury, lead, and zinc (Table 5.16; Figures 5.67 to 5.70). Linear regression

best fit lines are provided on each figure based on the data by site. These

metals are common constituents of the barite ore used as a drill mud

additive. Therefore, these metals acts as a suite of contaminants, reflecting

the distribution of discharged drill muds. The concentrations for each

metal is determined by the original metal content of the metal ore and the

amount of barite discharged at the site. Metals that occur at low

concentrations in the ore were only weakly correlated with barium. For lead

and zinc, metal concentrations in excess of that attributable to the ore were

present at some stations. Lead and zinc have been detected in produced

waters and are thought to be derived from corrosion of galvanized structures

on the platform. The weak correlation between barium, antimony, and

copper suggests additional sources for these metals including background

sediments (Figure 5.71). Other metals (i.e., Al, Fe, Cr, Ni, Se, and V),

associated with indigenous sediments show weak, if any, correlation with

barium. If platform related inputs are low for these metals, they should

negatively correlate with sand due to dilution. Arsenic, copper, and tin are

of mixed origins based on correlations with barium and background

sediment metals. For copper, the correlation with barium was weak except

at high barium levels, suggesting low copper concentrations were present in

the original ore (Figure 5.71).

5.3.3 Hydrocarbons in Fish Livers, Fish Stomach Contents, and

Invertebrate Soft Tissues

The ranges in the mean PAH concentrations by tissue type and

distance from the platform and site are summarized in Figures 5.72 to 5.74.

The majority of the PM! concentrations were at or below the method

detection limit and indicate little or no enhanced accumulation of PAH

related to distance from the platform. Further discussions of this data are

reserved for the later statistical analyses in Section 6.3.
Table 5.16. Matrix of correlation coefficients between individual metal concentrations measured in sediments at all study sites from 

based on logio-transforrned data, correlation coefficients > 0.4 are highlighted In bold type). Variable AG AL AS BA CD CR CU FE HG Ni PB SB SE SN

V ZN 

CLAYP 0.18 0.84 0.00 0.08 0.18 0.23 0.02 0.49 0.04 0.55 0.19 0.04 0.27 0.13 0.78 0.0

SILTP 0.00 0.22 0.08 0.01 0.00 0.45 0.19 0.47 0.04 0.36 0.00 0.04 0.31 0.06 0.47 0.0

SANDP 0.08 0.45 0.04 0.01 0.07 0.40 0.11 0.62 0.00 0.59 0.08 0.00 0.42 0.13 0.80 0.0

ZN 0.68 0.30 0.29 065 0.B7 0.14 0.55 0.02 0.73 0.03 0.64 0.55 0.09 0.04 0.07

V 0.18 0.65 0.02 0.06 0.17 0.33 0.03 0.60 0.02 0.64 0.15 0.02 0.23 0.17 SN 0.07 0.24 0.00 0.05 0.10 0.13 0.01 0.20 0.05 0.16 0.01 0.02 0.01 SE 0.00 0.03 0.16 0.09 0.05 0.32 0.34 0.33 0.10 0.26 0.01 0.08 sn 0.39 0.18 0.25 0.37 0.48 0.15 0.40 0.04 0.51 0,00 0.36 PD 0.50 0.31 0.12 0.47 0.81 0.06 0.29 0.00 0.48 0.07 MI 0.13 0.49 0.02 0.03 0.09 0.30 0.06 0.51 0.01 HG 0.88 0.27 0.31 0.60 0.70 0.14 0.82 0.02 FE 0.00 0.29 0.23 0.00 0.00 0.65 0.32 CU 0.31 0.01 0.43 0.31 0.40 0.43 CR 0.04 0.11 0.19 0.11 0.05 CD 0.65 0.42 0.19 0.72 BA 0.48 0.27 0.11 AS 0.17 0.02 AL 0.32 AG
1413121110 0 MAI-686 X MU-A85 HI-A389 9 x x0 I I I I . x Log10 (Hg] MU-A85 I 

HI-A389 MAI-686 Figure 5.67. Correlation between mercury (Hg) and barium (Ba) concentrations In sed

sites for all cruises. -4 -3 -2 -1 0 
Figure 5.68. Correlation between cadmium (Cd) and barium (Ba) concentrations in se

sties for all cruises.
Figure 5.69. Correlation between lead (Pb) and barium (Ba) concentrations In sedimen

for all cruises. I-CD 14 

i11- lo-- 8--= 7 _6--- 5. 4 0 MAI-686 X MU-A85 I HI-A389 1 I 0;or HI..Aa89\

11111 _..,.... ).x >> )<X x3E x0 90 . o 0 0 0 M

0 0 

0 MU-A85 .-.- - -2 I I I I I -1 I I I I 0 I I I I I I I I I 1 2 3 Log10 [Pb] I I I I I I I I I I 

4 5 
Figure 5.70. CorrelatIon between zinc (Zn) and barium (Ba) concentrations in sedime

for all cruises.
1413121110 o 9 C, 0-J 876 0 MAI-686 X MU-A85 U H1-A389I.. 7 MAI-686 1 2 3 Log10 [Cu] Figure 5.71. Correlation between copper (Cu) and barium (Ba) concentrations in sedim

sites for all cruises, 54 I r 4 
ir

111k

IIIF"

(qdd) UO7C4O

a

/

/k
Figure 5.73. VariabIlity of mean total PAH concentrations (ppb) in tissues by type, 

distance from the platform at MU-A85.
FIgure 5.74. Variability of mean total PAH concentrations (ppb) In tissues by type, 

distance from the platform at HI-A389.
5.3.4 Trace Metals in Fish Livers, Fish Stomach Contents, and

Invertebrate Soft Tissues

Invertebrate soft tissue (278 samples; shrimp, crabs, bivalves,

polychaetes), fish livers (248 samples), and fish stomach contents (321

samples) were analyzed for a suite of metals. The metal data from all cruises

for the various tissue types are summarized by site in Figures 5.75 to 5.83.

Again, little if any enhanced bioaccumuiation of metals could be attributed to

proximity to a platform. As with the hydrocarbon tissue data further

discussions of the tissue metal data is deferred to the statistical analyses in

Section 6.3.

5.3.5 Sediment Interstitial (Pore) Water

Hydrocarbon and metal concentrations were measured in 60 selected

pore water samples from each of the first two cruises to provide potential

chemical correlates for the pore water toxicity testing work element. The

pore water samples were filtered prior to analysis to provide a measure of

the dissolved contaminants. The pore water data did not significantly

correlate with the pore water toxicity results. Also, the correlation between

pore water and solid phase levels was weak. This lack of correlation may be

valid but it could be the result of sampling and/or analytical artifacts. Jt was

not possible to collect the pore water samples using "clean chemistry"

methodologies. This limitation can result in either an overestimation (i.e.,

contamination) or under-estimation (adsorptive loss) of the actual dissolved

contaminants present. Clean chemistry techniques are required to obtain

accurate dissolved contaminant data (especially in seawater) and guidance to

implement this approach as a requirement for compliance monitoring is

currently being developed (U.S. EPA 1994a,b). If properly sampled, pore

water measurements can provide a quantitative estimate of the dissolved

contaminant concentrations to which infaunal organisms are exposed. Pore

water chemical measurements should be expanded and more rigorously

applied in future studies.
I ConcefltfatbolP (ppm) 00 07 0 Concentration (ppm) Concentration (ppm) Concentration (ppm) Pppoo concefltratb0l (ppm) ConC8fltrtb0r (ppm)
1! Concentration (ppm) Concentration (Ppm) Concentratbohl (ppm) bcn00 Concentration (ppm) Con centr8tI0l (ppm) c0nrratb0t (ppm)
04 0flCeflttl0t (ppm) 00000 Concentration (ppm) CancCfltratbonl (ppm) p.) . 0) a0 . C) 00 Concentration (ppm) concenfrtb0h1 (ppm) a a a a - - Concentration (ppm)
I Crtoolocn Concentration (ppm) Concenfrat!on (ppm) Concefltratbohl (ppm) Concentration (Ppm) ConcefltrBtbolT (ppm) a a cn a cn Concefltratbohl (ppm)
1! Concentration (ppm) Concentration (ppm) Concentration (ppm) Coflc8' (ppm) ConCefltjatb0n (ppm) a a a a ConCefltraibl' (ppm) a -A
5-102

Figure 5.80. Suminaiy of mean metal concentrations in invertebrate

soft tissues at FH-A389 as a composite of all four

cruises.
IUUU. 0 CD Concentration (ppm) 0 0 Concentration (ppm) Concentration (ppm) 0 0 con cenIrat10" (ppm) CoflCCflt0t (ppm) Conc8flt8tl0hl (ppm)
I 0centr8tb0t (ppm) Concentration (ppm) ConCeflt8tl0tJ (ppm) -a Concentration (ppm) Concentratb01 (ppm) c,'PPPPpoo Concentration ('ppm 0 0 a
Figure 5.83. Summary of mean metal concentrations in fish stomach

contents at HI-A389 as a composite of all four cruises.

5-105
5.4 Meiofauna

Most of what is known about meiofauna is from studies of shallow

water systems. Many studies have also been done in the deep sea, but there

have been few studies of continental shelf or slope meiofaunai communities

(Coull et al. 1982). Studies where meiofauna have been sampled seasonally

from shelf sediments are rare. Meiofauna abundances decrease with water

depth (Thiel 1978; Coull et aT. 1982; Montagna 1991) and average about 800

individuals per 10 cm2 (Table 5.17). Nematodes are generally the dominant

taxa, comprising between 50 and 95 % of the community, followed by

harpacticoid copepods, which comprise between 5 and 20 % of the

community (Coull et al. 1977; Coull et aT. 1982; Montagna 1991).

5.4.1 Vertical Distribution and Power

Little information is available about the vertical distribution of

meiofauna on the Gulf of Mexico continental shelf. To determine the

appropriate sampling depth, sediments near Port Aransas in Matagorda

Island Block 746 in a water depth of 18 m were sampled. Seventy-one (71)

percent of the fauna were in the top 2 cm and 93 % were in the top 4 cm

(Table 5.18). Almost all (95 %) harpacticoids were in the top one (1) cm of

sediment. Since little information is gained by sampling below two (2) cm,

all samples were taken from the 0 to 2 cm depth interval. The observed

total density to 4 cm (3,743 individuals X 10 cm-2) is much higher than

values previously reported in the literature (Table 5.17).

A major assumption that formed the basis of the sampling protocol was

verified during the first cruise (i.e., two replicate cores per boxcore were

sufficient for the study design). Two stations at each platform, one within

50 m of the platform and one at 3000 m distance, were oversampled to

test this assumption. A second boxcore was taken at this subset of stations

to determine the power of the sampling design. The second boxcore at the

ten paired boxcore stations was used to document between boxcore

replication. The overall average density was 722 individuals X core1 and the

mean square error was 62,983. The mean population size was converted to

1.00 so that the percentage change of population size could be calculated.

The change of population density increases with decreasing numbers of
Table 5.17. Continental shelf melofauna densities reported in the periodic

literature.

sthtes sediment depth of 10 cm.

adepth in meters, meiofaunal density in nX 10 cm2 to a sediment depth of 10 cm.

Table 5.18. Vertical distribution of nieiofauna in the Gull of Mexico (18 m

water depth).

aThe average of three replicates, density in n X 10 cui2, and n X cor&* (NEMA Nematoda,

HARP = Harpacticoida. NAIJP = harpacticoid naupifi, and OTHER other taxa)

Depth

(cm)

Totala NEMAa pAJ?,pa NAUPa QflF(a.

Totaja

(nX 10 -2) (nX cored)

0-1 2088 592 216 116 80 180

1-2 778 221 186 3 0 32

2-3 476 135 121 1 0 13

3-4 401 114 101 1 0 12

4-5 150 43 38 0 0 5

5-6 69 20 18 1 0 1

6-7 32 9 4 0 0 5

7-8 6 2 1 0 0 1

8-9

9-10

6

4

2

1

1

0

0

0

0

o

1

i

0-10 4010 1139 686 122 80 251

Ocean Shelf Location Deptha Densitya Author

E Pacific Santa Maria Basin 90-410 1900 Montagna 1991

E Pacific Santa Maria Basin 565 97 Montagna 1991

E Pacific Santa Barbara Channel 18 1750 Montagnaetal. 1989

Gulf of Mexico Louisiana 8-13 1810 Murrell and Fleeger 1989

Gulf of Mexico Louisiana 355 580 Pequegnat et al. 1990

Gull of Mexico E Flower Gardens 72 *98 Powell et al. 1983

Gulf of Mexico S Texas 10-82 Pequegnat and Silcora 1979

Gulf of Mexico S Texas 91-134 *50 Pequegnat and Slkora 1979
samples. At any given number of samples (ri), certainty about change

increases with increasing differences. There is a break in the curve at about

four samples, meaning more than four samples does little to increase

resolving power. Most tests will be based on 20 samples (=2 replicates X 5

radii X 2 distances) allowing detection of a 40 % change with 0.80 power

(b=0.20). With just two samples, i.e. two replicates per boxcore, a 100 %

change (which is a doubling) among stations is detectable. An analysis of

variance components was performed to determine if using subcores as

replicates from one box core was sufficient. Most of the variability in the

study is among platforms (54 %) and the platform*station interaction (33

%). Practically, none of the variability was due to replicate boxcores (0.1 %).

Therefore, one boxcore per station and two replicate subcores was a

sufficient sampling protocol for the meiofaunal studies.

5.42 Community Abundance and Diversity

Melofaunal communities were sampled by a boxcorer. Six hundred

(600) samples were analyzed from four cruises, three platforms, twenty-five

stations at each platform, and two replicates (area=2.8 cm2) from each

boxcore. Eight different variables were examined: total meiofauna density,

Nematoda density, Harpacticoida density, other meiofauna taxa density, the

nematode:copepod (NC) ratio, nematode biomass, nematode diversity, and

harpacticoid diversity. Diversity was computed using the Shannon-Weaver

index, H'. The abundances were transformed using the logarithm to the

base 10 and all values reported here are detransformed. Because geometric

means are computed and round off errors occur, component means will not

add up to overall means.

The overall detransformed, average density for the meiofauna

community was 1170 individuals X 10 cm2 in the top 2 cm of sediment

(Table 5.19). This is equivalent to densities recorded for continental shelf

sediments in other areas (Table 5.18). Sixty-nine (69) percent of the Gulf of

Mexico community was composed of nematodes, which averaged 757

individuals X 10 cm2. Fifteen (15) percent of the community was composed

of harpacticoids, which averaged 161 individuals X 10 cm2. The remaining

16 percent of the community was composed of 11 "other" taxa, which

averaged 182 individuals X 10 cm2. The "other" taxa were Kinoryncha,
Table 5.19. The overall average abundance and diversity for meiofauna variables at alJ platforms, stations, and cruises.

aNbers for density (individuals X 10 cm2 and for biomass (mg wet weight X 10 cm2) are

detransformed from log10. Diversity values are the Shannon-Weaver index (H'). Averages for

600 samples.

Polychaeta, Ostracoda, Mollusca, Rhyncocoela, Amphipoda, Isopoda,

Tanaidacean, Cumacea, Priapulida and unknown or unidentifiable soft body

taxa. None of these "other" taxa occur in large numbers. Nematode biomass

averaged 1.00 ing wet weight X 10 cm2 in the Gulf of Mexico. Nematode

communities were more diverse (H' of 3.06) than harpacticoid communities

(H' of 2.36). However, H' is sensitive to sample size so the diversity of

nematodes was higher than harpacticoids because nematode density was

higher than barpacticoids.

Contours of density, biomass, and diversity gradients were produced to

illustrate gradients (Figures 5.84 to 5.91). The strongest gradient for total

meiofauna density around a platform was found at MAI-686 (Figure 5.84).

The gradient was relatively uniform around the platform (i.e., there is no

strong directional influence). There was no significant pattern evident

around MU-A85 for total meiofauna (Figure 5.84). There was a significant

gradient around HI-A389, but its distribution was not symmetrical (Figure

5.84). There was a large increase in density, relative to background levels,

southwest of the platform. MAI-686 was also unique in that there was a

significant difference between cruises. This was due to lower meiofauna

densities near the platform during Cruises 2 and 4 than in Cruises 1 and 3.

These low densities occurred coincidentally with an hypoxic event near this

platform each summer.

5-109

Variablesa Hl-A389 MAI-686 MU-A85 Mean

Meiofaunal density 734 2571 846 1169

Nematode density 481 1864 482 757

Harpacticoid density 85 283 171 161

Other meiofaunal density 100 369 164 182

Nematode biomass 0.674 1.084 1.280 1.000

Nematode:Copepod ratio 5.64 6.60 2.81 5.02

Nematode diversity 2.74 3.12 3.31 3.06

Harpacticoid diversity 2.00 2.56 2.52 2.36
N

E

EI-0

a.

E

C2 -o U, S

N

E 300

-330 0 w Distance from Platform (m) E

MAI-686 Meiofauna Densi ind/lOc

Figure 5.84. Areal distribution of mean meiofauna density (md/b cm2)

as a composite of all four cruises.

5-110

-630 -300 0 W Distance from Platform (m) E

MU-A85 Mejofuna Dens indJlOc HI-A389 Meiofauna Dens indjlOc

-300 0 30) 530 w Distance from Platform (m) E
330

MUA85 Nematode DenS - n x locnr

MAI-686 Nematode Densi n x lOcrTr

30

HI-A389 Nematode Deni n x lOcnr

-630 -330 0 330 W Distance from Platform (m) E

Figure 5.85. Meal distribution of mean neimtode density (ii x 10 cm2) as

a composite of all four cniises.

5-111

-630 -330 0 w Distance from Platform (m) E

- 0 330 Distance from Platform (m) E
MAI-686 Ha -cticoidDensft nxl0cm

-ff10 -31) 0 3)0

W Distance from Platform (m) E

MU-A85 Har . acticoid Den& n x 10cm Hl-A389 Har. cticoid Dens n x lQcm

-3)) 0 300 Distance from Platform (m) E

Figure 5.86. Areal distribution of mean baipaclicoid density (n x 10 cnr2)

as a ccznposite of all four cruises.

5-112

0 300 600 W Distance from Platform (m) E

N

E

3)0

E

. -31

0)

C

S

NE

3)0

E

. -3)0

S
N

E

EI-0

0.

E

. -3)0

0

S

3)0

-OX) - 0 3)0

W Distance from Platform (m)

MAI-686 'Other Meiofauna" Dens ind/lO c

-3)0 0 3)0

W Distance from Platform (m) E MUMS "Other Meiofauna" Dens nd/b C HIA389 "Other Meiofauna" Den$ indIlO C

E

N

E

S

w

-3)0 0 Distance from Platform (m)

OX)

E

Figure 5.87. Area! distribution of mean "other meiofauna" density (md! 10 cm2)

as a composite of all four cruises.

5-1 13
N

E

I-0

S

0.

E

0

I

S

3)0

-3)0

MA-686 Nematode Biomass wet wtx 10

Distance from Platform (m) E

MU-A85 Nematode Biomass wet wtxl0 cm- HI-A389 Nenwtode Biomass wetwtxlo cmN

E

EI-0

0.

E

0

S

C) CS

S

a

S

Distance from Platform (m)

Figure 5.88. Meal distribution of mean nematode biomass (mg wet weight x 10

crn2) as a ccinposite of all four cruises.

5-114

-3)0 0 3)0 600

w

-300 0 300 Distance from Platform (m) E
N

E

0

$ -&0

- 0 300

Figure 5.89. Area! distribution of mean nematode:copepod ratio (N:C ratio)

as a composite of all four cruises.

5-115

-ao 0 300 Distance from Platform (m) E

w

-300 0 300 Distance from Platform (m) E

HI-A389 Nematode:CO e... Ratio

W Distance from Platform (m) E
N

E

0.

E

V

0

3J0

S

MU-ASS Nematode Divers

w

.3O 0 Distance from Platform (m) E

MAI-686 Nematode Divers

HI-A389 Nemtode Divers

E

Figure 5.90. Areal distribution of mean nernatode diversity (if) as a composite

of all four cruises.

5-116

a w Distance from Platform (m) E

-ma -ax 0 W Distance from Platform (m)
NE

E

0

0

E

2

0

2U, S

N

-S

E

E

S

MU-A85 Har. cticoicl Diversi

-ax) 0 3)0

MAI-686 Ha acticoid Divers

HI-A389 liar cticoid Divers

Figure 5.91. Meal distribution of mean harpacticoid diveisity (H') as a composite

of all four cruises.

5-117

W Distance from Platform (m) E

Distance from Platform (m) E W Distance from Platform (m) E
Since nematodes were the dominant taxa, the trends observed for

total inelofauna were very similar for nematode abundance (Figure 5.85).

Nematode density changes with distance at platforms MAI-686 and HIA389, but not at MU-A85. Harpacticoid abundance also decreased uniformly

away from MAI-686 (Figure 5.86). There was no obvious trend with distance

from MU-A85 for harpacticoids (Figure 5.86). As with nematodes,

harpacticoid density was highest southwest of platform HI-A389 (Figure

5.86). The trend for other meiofauna taxa was strongest at platform MAI686 (Figures 5.87). Response of nematode biomass was slightly different

from the trend observed for nematode density (Figure 5.88). Like

abundance, nematode biomass increased uniformly with distance away from

platform MAL-686 (Figure 5.88). At MU-A85 and HI-A389. nematode

biomass decreased with distance from the platforms (Figures 5.88).

The nematode:copepod (NC) ratio has been suggested as an index of

organic enrichment (Figures 5.89). Some studies show that this index also

increases along contaminant gradients. There was a weak gradient of

decreasing NC ratio away from MAI-686 (Figure 5.89). In contrast, the NC

ratio at MU-A85 significantly increased with distance from the platform

(Figure 5.89). There was a strong decrease in the NC ratio away from HIA389 (Figure 5.89).

Nematode diversity appeared to be relatively uniform near platforms at

MAI-686 and MU-A85 (Figures 5.90). Nematode diversity (H') decreased

near HI-A389 (Figure 5.90). Harpacticoid diversity (H') increases with

distance away from platforms MAI-686 and HI-A389 (Figures 5.91). There

was no significant directionality to diversity trends at MU-A85 and MAI-686,

but there was significant directionality at HI-A389 (Figures 5.91).

Harpacticoid diversity at HI-A389 was low near the platform (Figure 5.91).

5.4.3 Community Structure

The harpacticoid community was very diverse. A total of 154 species

of harpacticoids was found (Table 5.20). Only nine of the species were easily

distinguished as described species. The rest are either new or a Gulf of

Mexico variant that is undescribed. Members of the Ectinosomidae

dominated the fauna. This family has long, torpedo-like body shapes, and

most members are very small. For many of the species, genus designation

5-118
Table 5.20. Mean density (n X 10 cm-2) for Copepoda species found at all

three platforms for all cruises.

Taxa MAI-686 MU-A85 HI-A389

Copepoda

Harp acticoida Longipediidae

Longipedia americana 0.63 1.38 0.44

Canuellidae

Ellucana secunda 0.04 0.00 0.02

Ectinosomldae

Ectinosomid sp. 6 0.04 0.16 004

Ectinosorrud sp. 8 2.54 2.70 3.44

Ectinosornid sp. 12 0.00 0.11 0.00

Ectinosornid sp. 32 0.00 0.00 0.05

Ectinosomid sp. 34 2.13 0.16 0.12

Ectinosomid sp. 35 0.14 0.04 0.12

Ecttnosomid sp. 51 1.46 0.00 0.00

Ectinosomid sp. 52 1.34 0.02 0.04

Ectinosomid sp. 55-B 0.00 0.04 0.19

Ectinosomid sp. 68-E 0.00 0.07 0.02

Ectinosomid sp. 82 0.00 0.00 0.18

Ectiriosomid sp. 83 0.00 0.00 0.09

Ectinosomid sp. 87 L15 0.55 0.35

Ectinosomid sp. 88-U 0.00 0.00 0.04

Ectinosornid sp. 92-M 0.00 0.00 0.04

Ectinosomid sp. 96-AA 0.02 0.00 0.07

Ecttnosornid sp. 97-AB 0.11 0.19 0.05

Ectinosomid sp. 98-AC 0.04 0.00 0.25

Ectinosomid sp. 102-A0 0.00 0.00 0.04

Ectinosomid sp. 104-AL 0.00 0.02 0.02

Ectinosomid sp. 107-AT 0.00 0.02 0.02

Ectinosomid sp. 109-AY 0.00 0.00 0.02

Ectinosomid sp. 110-AZ 0.02 0.00 0.30

Ectinosomid sp. 1 13-BF 0.00 0.00 0.02

Ectinosomid sp. 1 15-BH 0.04 0.00 0.02

Ectixiosomid sp. 122-BT 0.04 0.00 0.02

Ectinosornid sp. 124-BW 0.05 0.00 0.02

Ectinosomid sp. 126-BZ 0.00 0.00 0.09

Ectinosornid sp. 129-MB 16.01 3.53 2.77

Ectinosomid sp. 130 8.32 0.95 0.11

Ectinosomid sp. 133-MH 1.75 1.02 0.46

Ectinosomid sp. 134-ME 3.69 0.19 0.12

Ectinosomid sp. 135-MT 7.53 0.00 0.00

Ectinosomid sp. 137-ML 0.51 0.11 0.00

Ectinosomid sp. 138-MM 15.18 1.82 1.23

Ectinosomid sp. 139-MO 1.34 0.99 0.28

Ectinosomki sp. 140-MP 0.32 0.04 0.00

Ectinosomid sp. 142-MI 0.05 0.02 0.00

Ectinosomid sp. 143-MQ 0.00 0.02 0.04

Ecttnosomid BP 1.45 0.12 0.18

Ectinosomtd (unidentified) 8.01 10.55 5.59
Table 5.20. (Cont.)

Taxa MAI-686 MU-A85 HI-A389

Tachiidae

Euterpina acutfrans 0.00 0.00 0.04 Tisbidae

Tisbe sp. i 0.00 0.04 0.00

Zosime n sp. A 0.00 0.30 0.25

Zosime n sp. B 0.00 0.04 0.11

Zosime n sp. 54-C 0.18 1.45 2.43

Idyella sp. 0.04 0.02 0.04

Tachidiella sp. 86-BL 7.95 1.90 1.66

Genus A 0.00 0.02 0.05 Thalestridae

Diarthrodes sp. 5.61 1.90 0.04

Diosaccidae

StenheUa (Stenhelia) sp. 37 1.08 0.00 0.00

Stenhelia (Delavalia) sp. 2 7.05 0.39 0.00

Stenhelia (Delavalia) sp. 81 0.00 0.04 0.26

StenheUa (Delavalia) sp. 31 3.14 0.04 0.05

Sterthelia (Delavalia) sp. 44 0.00 0.04 0.00

Stenhelia (Delavaila) sp. 48 0.00 0.07 0.00

Stenhelia (Delavalia) sp. 101-AG 0.00 0.00 0.18

Stenheiia (Delavalia) sp. 118-BU 0.00 0.00 0.12

Stenheha (Delavalia) sp. 1 19-BO 0.00 0.32 0.18

StenheUa (Delavalia) sp. 120-By 0.00 0.00 0.05

Stenhelia sp. 0.67 1.09 1.23

Robe rtsoriia n sp. A 0.30 0.26 0.00

Amphiascus sp. (mmutas group) 0.63 0.21 0.32

Robertgw-neya sp. A 3.77 0.46 0.19

Robertgurrieya sp. B 0.14 0.09 0.00

Robertgurneyasp. C 0.60 0.18 0.00

Typhlamphio.scus sp. 2.70 0.14 0.00

Arnphiascoides sp. A 1.06 0.11 0.04

Amphiascoides sp. B 0.14 0.05 0.00

Haloschizopera sp. 2.59 0.74 0.04

Diosaccid sp. 5 0.09 0.00 0.05

Diosaccid sp. 42 0.00 0.02 0.00

Diosaccici sp. 45 1.25 0.35 0.04

Diosaccldsp. 46 0.67 1.15 0.07

Diosaccid sp. 53 0.00 0.04 0.12

Diosaccid sp. 65 0.00 0.39 0.07

Diosacciti sp. 66-F 0.07 0.44 0.51

Diosaccid sp. 67 0.00 0.00 0.05

Diosaccid sp. 89-S 0.00 0.07 0.12

Dioso.ccjd sp. 91-J 0.00 0.00 0.02

Diosaccid sp. 95-X 0.00 0.02 0.05

Diosaccid sp. 99-Al) 0.00 0.00 0.05

Diosaccid sp. 100-AE 0.00 0.93 0.05

Diosaccid sp. 103-AP 0.00 0.00 0.05

Diosaccid sp. 105-AV 0.00 0.00 0.07

Diosaccfrl sp. 106-AW 0.00 0.00 0.05

Diosaccki sp. 108-AX 0.00 0.00 0.05
Table 5.20. (Cont.)

Taxa MAI-686 MU-A85 HI-A389

Diosaccidsp. 111-BC 0.07 0.00 0.07

Diosaccid sp. 1 14-BG 0.00 0.02 0.04

Diosaccid sp. 121-BS 0.00 0.02 0.04

Diosaecid sp. 131-MF 0.00 0.00 0.02

Diosaccid sp. 132-MG 0.28 0.00 0.04

Diosaccid (unidentified) 9.03 7.41 1.85

Ameiridae

Ameiridae sp. 79 9.13 3.60 2.68

Pseudameira sp. 8.34 3.23 1.76

Anoplosoma sp. A 0.00 0.00 0.02

Anoplosoma sp. B 0.00 0.00 0.11

Ameirid sp. 79 0.00 0.37 0.78

Tetragonicipitidae

Genus A. 0.00 0.00 0.05

Canthocamptidae Canthocamptidae (unidentified) 0.12 0.18 0.14

Genus A. 0.00 0.09 0.51

Genus B. 0.00 0.02 0.04

Genus C. 0.00 0.00 0.04

Cletodidae

Cletodes aff. macrum -61 0.00 0.60 0.71

Cletodes aff. tuberculatas 9.65 0.67 0.00

Cletodes pseudodissimilis 6.75 0.11 0.04

Cletodes sp. A-AJ 0.00 0.00 Odi

En.hydrosoma pericoense 21.16 0.18 0.58

StyUcletodes aff. longicaudata 0.00 0.04 0.44

Cletodicl copepodid 0.02 0.00 0.11

Cletodidsp. 128 0.72 0.04 0.00

GenusA -41 0.05 0.37 1.52

Genus B. -62-AS 0.00 1.46 1.82

Cletodid (unidentified) 0.56 0.37 0.32

Argestidae Eurycletodes sp. -75 0.00 0.69 0.26

Leptocletodes sp. T 0.00 0.11 0.11

Laophontidae Paralaophonte aff. pacflca 0.11 0.00 0.00

Genus A 0.12 0.04 0.02

Laophontid (unidentfted) 0.00 0.00 0.14

Normanellidae

Normanefla sp. A 6.40 0.37 0.11

Normanella sp. B 3.53 0.11 0.07

NormaneUa sp. C 0.14 0.34 0.21

Cletopsyllr's sp. A 0.00 0.16 0.05

Genus A 0.00 0.00 0.09

Families uncertain

Harpacticoid sp. 50 0.04 0.02 0.00

Harpacticoid sp. 56 0.00 0.04 0.16

Harpacticoid sp. 57 0.00 0.04 1.48

Harpacticoid sp. 58 0.00 0.21 0.65

Tfarpacticoid sp. 59 0.00 0.02 0.14
Harpacticoid

Harpacticoki

Uai-pacticoid

Harpacticoid

Jiarpo.cticoid

Harpacticold

Harpacticoid

Harpacticoid

Harpacticoid

Harpacticoid

1-larpacticoid

Harpacticoid

Harpacticoid

Harpacticoid

Harpacticold

Harpacticold

Harpacticold

Harpacticold

Harpacticoid Cyclopoida

Cyclopoid sp.

Cyclopoid sp.

Cyclopoid (un

Table 5.20. (Cont.)

sp. 60

sp. 63

sp. 64

sp. 73

sp. 74

sp. 78

sp. 80

sp. 84

sp. 90

sp. 93

sp. 94

sp. 112

sp. 116

sp. 117

sp. 123

sp. 125

sp. 127

139-B

(unidentified)

1-69

2-77

identified)

was unsure. At HI-A389, the dominant species (In order of abundance) were

Ameridae sp. 79, Ectirtosomid sp. 129-MB, Pseudameira sp., and

Ectinoso mid sp. 8. At MAI-686, the dominant species (in order of

abundance) were Enhydrosoma pertcoense, Ecttnosomtd sp. 129-MB,

Ectinosomid sp. 138-MM, and Ameridae sp. 79. Of the dominant species,

Enhydrosoma pericoense was the only one restricted to shallow water

depths. The other species were fairly common throughout the study sites.

The nematode community was also very diverse, containing 130

species (Table 5.21). The community was also more cosmopolitan, 31

species were previously described species. Again, the rest of the species

were new or unknown Gulf of Mexico variants. No one family dominated the

nematode fauna as in the barpacticoids. However, dominance by a single

species was characteristic of HI-A389 and MAI-686. At HI-A389 the

dominant species was Molgolaimus tw-gofrons followed by Scthattieria omatcz

Linhomoeus gittingsi, and Halalaimus meyeri. At MAI-686, the dominant

species was Desmodora curvispicutum followed by Acttnoriema sp. 1,

Microlaimus sp. 1, and Tricocoma filipjevi. At MU-A85, dominance was

5-122

0.00 0.42 0.51

0.00 0.07 0.41

0.00 0.07 0.23

0.00 0.00 0.09

0.00 0.00 0.02

0.00 0.00 0.02

0.42 1.50 0.23

0.00 0.00 0.19

0.04 0.00 0.04

0.00 0.04 0.09

0.00 0.02 0.07

0.00 0.00 0.04

0.00 0.00 0.04

0.00 0.00 0.02

0.00 0.00 0.02

0.00 0.02 0.00

0.00 0.00 0.02

0.00 0.00 0.02

7.14 8.54 8.94

0.09 0.11 0.53

0.11 0.34 0.72

0.72 4.09 2.65

Taxa MAI-686 MU-A85 HI-A389
Table 5.21. Mean density (n X 10 cm-2) for Nematoda species found at

three platforms for all cruises.

Taxa MAI-686 MU-A85 HI-A389

Adenophorea Enoplida Tboracostomopsidae

Enoploicles Sp. 1 1.14 3.55 2.58

Phanodermatidae

Crenophanjnxsp. 1 0.00 0.10 0.00

Anticomidae

Cephak.zrtticoma sp. 1 0.19 0.08 0.00

Odontanticoma sp. 1 0.20 0.00 0.00

Ironidae

Trissonchutus sp. 1 8.67 0.13 0.08

Trissortchulus sp. 2 0.88 0.20 0.27

Oxistominidae

Nemariemasp. 1 0.45 1.70 2.23

Oxystornina sp. 1 1.51 3.89 6.79

Halalaimus tholn-sstnus 97.06 33.50 29.09

Halolaimus meyersi 21.90 12.15 5.55

Halolaimus sp. 1 2.58 1.82 1.22

Hakilaimus sp. 2 10.23 3.67 0.93

He*ilnimus sp. 3 0.84 6.86 6.32

Oncholaimidae

Viscosia sp. 1 4.84 2.35 9.04

Viscosia macramphida 14.85 10.18 7.53

Viscosia sp. 3 0.59 0.09 0.00

Metoncholaimus sp. 1 14.96 0.82 8.69

Pontonerna sp. 1 0.00 0.62 0.39

Oncholaimellus sp. 1 0.56 0.35 0.35

Encbelidiidae

Pareurystomina scilloniensis 0.36 0.54 0.18

Calyptronema sp. 1 0.99 2.71 0.09

Polygastrophora sp. 1 0.45 2.34 1.65

Tnpyloididae Bathylaimus sp. 1 0.00 0.33 1.37

Trtpyloides sp. 1 2.80 0.42 0.53

Trefusiida

Trefusildae

T)efusiasp. 1 2.86 1.99 26.93

Chromadorida

Cbromadoridae

Acantholaimus sp. 1 0.28 0.57 12.00

Actinonema sp. 1 165.02 7.65 11.02

Actinortema longicandata 1.73 0.96 1.04

Rhips sp. 1 0.40 0.13 0.08

Chromaclorita chitwoodi 4226 0.58 0.16

Chromadorita sp. 1 5.60 0.51 0.33

Spilophorella paradoxa 9.52 1.97 1.29

Ptycholalmellus sp. 1 16.24 3.37 0.77

Hypedontolaimus sp. 1 4.10 17.08 6.81
Table 5.21. (Cont)

Taxa MAI-686 MU-A85 HX-A389

Neochromadora sp. 1 77.55 3.50 1.20

Neochromadora sp. 2 25.55 2.37 1.41

Dichrortaciora sp. 1 2.29 4.10 2.69

Parapinnanerna sp. 1 0.41 2.67 0.65

Comesomatidae

Setosabatieria hilw-ula 21.41 10.50 7.10

Sabatieria omata 30.85 18.39 53.98

Sabatieria punctata 77.84 22.64 26.31

Sabatieria sp. 1 0.51 0.11 0.46

Pierrickta sp. 1 5.09 1.33 1.43

Laimella sp. 1 4.83 0.94 1.75

Cervonema sp. 1 13.45 18.24 15.55

Cervonema SF. 3 21.21 20.81 11.29

Dorylaimopsis punctata 2.21 4.44 2.33

Hopperia sp. 1 18.44 1.36 0.60

Comesoma sp. 1 1.40 0.00 0.64

Ethmolaimidae

Cornesa sp. 1 10.42 5.10 2.48

Cyatholaimidae Metacyatholairrtus sp. 1 13.88 5.41 2.10

Paracanthonchus platypus L85 1.57 0.52

Marylynnta johanseni 42.50 3.98 0.95

Marynnia punctata 1.91 2.27 0.85

Longicyatholatmus sp. 1 1.78 2.20 1.73

Minolaimus sp. 1 0.61 0.37 0.00

Selach!nematidae

Cheironchus SF. 1 0.59 2.00 0.90

Richtersia sp. 1 0.61 1.80 1.27

Richtersia sp. 2 0.88 005 0.09

Halichoanolaimus duodecimpapill 0.23 1.98 1.45

Hatichoanolaimus sp. 1 0.77 4.86 2.48

Loironema sp. 1 0.12 2.74 0.50

Synonchiella sp. 1 4.00 2.01 0.69

Desmodoridae

Acanthopharyngotdes chitwoodi 0.26 4.39 0.31

Desmodora curvispiculum 309.76 18.51 9.48

Desmodora sp. 1 1.29 0.21 0.23

Desmodora sp. 2 3.51 11.63 5.75

Metachrom.adora sp. 1 56.29 1.38 0.73

Molgolairnus turgofrons 22.16 3.80 313.95

Onyssp. 1 0.77 0.00 0.11

Microlaimidae

Draconema sp. 1 0.00 5.45 0.41

Ceramonematidae

Microlaimus sp. 1 138.79 18.26 8.87

Microlaitnus sp. 2 7.58 0.11 0.18

.Bolbolaimus sp. 1 5.15 3.05 1.40

Aegialoalaimidae

Pterygonema sp. 1 0.00 0.18 0.00

Pselionema sp. 1 22.86 33.47 20.38

Pseliortema sp. 2 1.41 7.41 3.85
Table 5.21. (Cont.)

Taxa MAI-686 MU-A85 HI-A389

Leptolaimidae Cyartonema sp. 1 7.31 1.86 1.48

Tubolaimoididae

Leptoriema sp. 1 26.49 11.73 21.09

Leptonema sp. 2 6.24 0.44 2.11

Antomicron sp. 1 3.42 0.92 0.27

Antomicron sp. 2 1.55 0.74 0.24

Desmoscolecidae

Tubolairnoides sp. 1 0.70 0.14 0.03

Desmoscolecidae

Greefflella sp. 1 0.00 0.25 0.16

Pareiirk'smoscolexsp. 1 29.83 7.15 3.79

Desmoscolex nhsthILs 21.71 14.39 8.53

Desmoscolex sp. 1 2.94 1.03 1.39

Tricoma fiUpjevt 115.15 9.13 4.39

Tricoma sp. inosotdes 81.90 7.06 1.80

Thcorna sp. 1 17.08 1.50 1.74

Tricoma sp. 2 3.05 0.49 0.00

Thcoma sp. 4 4.90 0.61 0.66

Desmoloren.zenin sp. 1 10.90 1.15 0.72

Monhysterida Xyalidae Daptonema buetschlioides 11.10 0.20 1.81

Daptonema trabeculostus 35.73 0.76 0.02

Daptonerna sp. 3 4.68 1.66 1.96

Theristus copulatus 3659 5.55 2.86

Theristus rezaki 8.33 1.53 0.80

Thei-tstus sp. 1 4.84 0.48 1.86

Paramonhystera sp. 1 55.19 5.37 3.80

Pararrwnhystera sp. 2 31.90 5.15 4.27

Retrotheristus sp. 1 2.30 1.14 1.39

Elzaliasp. 1 13.27 21.32 14.18

Griomoryala sp. 1 2.36 3.45 6.58

Steineria sp. 1 3.53 1.49 5.12

AmphtmonthystreUa sp. 1 1.07 2.54 3.40

Goraonchus interrnedius 0.36 0.39 0.32

Sphaerolaimidae Sphaerolaimidae sp. 1 3.36 5.09 2.02

Sphaerolwmirk7e sp. 2 8.30 5.52 3.70

Siphonolaimidae Siphonolaimidae sp. 1 17.89 1.37 2.82

Siphonotaimtdae sp. 2 340 2.05 0.47

Linbomeidae

Linhomoeus gittingsi 15.47 1.19 31.18

Linhomoeus iaiquus 5.29 3.35 6.81

Lirthomoeus sp. 1 104.38 1.22 8.55

Metalihomoeus sp. 1 17.05 1.26 3.54

Desmolaimoides thiobioticus 1.09 0.09 0.06

Eieutherotairnus sp. 1 36.63 2.36 0.82

Terschellingia longispiculata 18.20 2.26 6.87
shared by about 12 species. The most dominant species (in order of

Ectinosomid sp. 6, Ectinosomid sp. 129-MB, Ameridae sp. 79, and Zosime

sp. 54-C. At MU-A85, the dominant species (in order of abundance) were

abundance) Hatalaimus thatassirtus, Pselionema sp. 1, Sabatieria punctata,

Etzalia sp. 1, and Cervonema sp. 3. There was no overlap of dominant

species at the three platforms.

5.4.4 Nematode Trophic Dynamics

In general, harpacticoids are mostly grazers, eating diatoms and

bacteria, but some are also omnivorous. So, harpacticoids probably

represent only one trophic group. In contrast, nematodes have more varied

eating habits and include some deposit feeders. Because biomass was

measured for nematodes, trophic group dominance may be based on

abundance or biomass. Deposit-feeding nematodes dominated the density

and biomass of the community (Table 5.22). Non-selective deposit feeders

accounted for 31 % of the density, but 50 % of the biomass, indicating this

trophic group was important in Gulf of Mexico shelf sediments.

Predators accounted for only 6 % of the density and 13 % of the

biomass (Table 5.22). The distributions of trophic groups are shown in

Figures 5.92 to 5.97. The general pattern was that epigrowth feeder density

was highest near the platform and deposit feeder biomass was highest near

Table 5.21. (Cont.)

Taxa MAI-686 MU-A85 1ThA389

Terschellingia longicaudata 19.24 2.72 11.01

Didelta sp. 1 0.00 0.00 0.43

Axonolaimida

Axonolaimus sp. 1 1.58 8.47 0.38

Odontophora sp. 1 2.08 2.88 0.08

Paraodontotaimus sp. 1 14.11 0.19 0.00

Ascolairnus sp. 1 0.93 1.55 1.38

Diplopeltidae

Campyloimus sp. 1 25.71 14.04 4.24

Campylaimus sp. 2 0.67 0.14 0.23

Araeotatmus sp. 1 11.01 3.54 1.83

Diplopettula sp. 1 0.43 0.08 0.14

Dtplopeltula sp. 3 0.58 0.44 0.17

Diplopeltula sp. 4 13.78 6.80 4.72
Table 5.22. The overall average abundance of nematode feeding groups at

the three platforms.

aDensity (individual X 10 cm2) and biomass (mg wet weight X 10 cm2) are detransformed

from logo, total number of samples 600.

Variables

Abundancea

HI-A389 MAI-686 MU-A 85 Mean

Density (individual X 10 cm2) Selective deposit feeder 121 421 146 196

Non-selective deposit feeder 136 445 138 204

Eplgrowth feeder 121 758 108 216

Predator 27 69 32 39

Biomass (mg wet weight 10 X cm2)

Selective deposit feeder 0.047 0.129 0.045 0.065

Non-selective deposit feeder 0.156 0.532 0.171 0.243

Eplgrowth feeder 0.055 0.420 0.063 0.114

Predator 0.033 0.151 0.046 0.062

Density Composition (%) Selective deposit feeder 30 25 34 30

Non-selective deposit feeder 34 26 33 31

Epigrowth feeder 30 45 25 33

Predator 6 4 8 6

Biomass Composition (%) Selective deposit feeder 16 10 14 13

Non-selective deposit feeder 54 43 53 50

Epigrowth feeder 19 34 19 24

Predator 11 13 14 13
Figure 5.92. CompositIon of feeding groups based on the mean numbers of individua

nematode community at MAI-686 by distance from the platform.
Figure 5.93. Composition of feeding groups based on the mean biomass for the nema

community at MAI-686 by distance from the platform.
IIIIII1! 

4 7

IIIIII4gff/

iiiiIrf'rarvqq#

'liiiVaJVfffar/f/a

/

11114

IIIII""4'4.

II &_PJR

c U, u

() Aj,suea

F
Figure 5.95. Composition of feeding groups based on the mean biomass for the nem

community at MU-A85 by distance from the platform.
Figure 5.96. CompositIon of feeding groups based on the mean numbers of Indlvidua

nematode community at HI-A389 by distance from the platform.
Figure 5.97. Composition of feeding groups based on the mean blomass for the nema

community at HI-A389 by distance from the platform.
the platform. Selective deposit feeders increased in dominance away from

the platform in density and biomass while non-selective deposit feeders

were increasingly dominant near the platform. Epigrowth feeders and

predators were also increasingly dominant away from the platform. In

general, the proportion of deposit feeders increased nearer the platform.

At MU-A85, selective deposit feeders were increasingly dominant away

from the platform in density (Figure 5.94) and biomass (Figure 5.95), while

non-selective deposit feeders were increasingly dominant near the platform.

Epigrowth feeders were increasingly dominant nearer the platform.

Predator density and biomass were increased near the platform. In general,

the proportion of deposit feeders increased near the platform. At HI-A389,

deposit-feeders' density was least dominant southwest of the platform and

epigrowth feeders' density was most dominant in this area. Non-selective

deposit feeders were more dominant in terms of biomass. Predator biomass

was prominent south of the platform (Figures 596 and 5.97).

5.4.4.1 Modeling of Nematode Trophic Dynamics

These results are based on a simulation of the 16 months during

which sampling was performed. A simulation run for 120 months, based on

data for the first 16 months, yields stable, average predicted production and

production efficiency values (Table 5.23). The long-term simulation

suggests that production of deposit-feeding nematodes was lower at near

stations than at far stations for HI-A389 and MAI-686. No differences with

distance from the platform site were found for MU-A85.

Modeling deposit-feeding nematode trophic dynamics suggests that

MAI-686 had a higher monthly production than HI-A389 or MU-A85

(Figures 5.98 to 5.103). MAI-686 had higher production because of a higher

production efficiency (Figures 5.98 and 5.101). Among distances, significant

differences existed for production only at MAI-686. At MAI-686, production

was higher at 500 to 3000 m than it was at 50 to 200 m from the platform

(Figure 5.98). This result was due to the higher production efficiency at the

far stations (Figure 5.98).
,-' 160 - C 140- 120- oo 100-i ,/ 80- 4/ 

- - 

Figure 5.98. Average predicted production for the melofaunal community at MAI-

timeframe of the study sampling efforts (O=February 1993). 6 8 10 12 

Time (months) 0 2 4
Figure 5.99. Average predicted production for the meiofaunal community at MU-A8

timeframe of the study sampling efforts (O=February 1993).
Figure 5.100. Average predicted production for the meiofaunal community at HI-A3

timeframe of the study sampling efforts (O=February 1993).
Figure 5.101. Average production efficiency for the meiofaunal community at MAI-6

timeframe of the study sampling efforts (O=February 1993).

Figure 5.103. Average production efficiency for the melofaunal community at HI-A3

timeframe of the study sampling efforts (O=February 1993). o0)t 1.0 

:: -0.5 ---- .1.0- -1.5- 50mlOOm 200m 50Cm 5000m 0 I 2 I I I I 4 I I I I 6 8 Time (months) 10 I I I I 12 I r 
Table 5.23. The predicted average production (j.tg WW X 10 cm'2 X

month-1) and production efficiency based on the long-term

model simulation of deposit feeding nematode.

5.4.5 Predation on Meiofauna

The feeding habits of the eight species of small fish were examined in

this study (Tables 5.24 and 5.25). Three of the eight species of fish were

primarily benthic feeders: Syactum gunteri, HaUeuttchthys aculeatus, and

Ogcocephalus radtatus. The remaining species fed primarily on pelagic

fauna

Only one fish, Syacium gunteri, had a feeding preference for

meiofauna, and it fed mostly on nematodes. This species also fed on

macroinfauna, such as, amphipods, and polychaetes. Epifauna eaten by

Syactum gunteri included shrimp, mysid, and crabs. A total of 122

specimens were dissected with an average size of 7.8 cm. Syacium gunterL

also had the highest numbers of meiofauna in their guts of all the fish

studied.

Halteutichthys aculeatus fed mostly on macroinfauna, e.g., gastropods

and polychaetes, but also ate large numbers of nematodes and ostracods.

Crabs, mysids and shrimp were the epifauna eaten by this species. The

average size of the 129 specimens of H. aculeatus was 5.5 cm. Only three

Ogcocephatus radtatus were dissected, and bad only macroinfauna in their

guts.

5-14 1

Distances 50 in 100 m 200 m 1000 m 3000 m

HI-A389

Production 1.05 1.27 3.43 0.83 3.19

Efficiency -0.12 -0.41 -0.13 -0.10 1.8E-4

MAT- 686

Production 42.1 14.1 13.0 50.9 52.0

Efficiency 0.45 -4.9E-2 0.14 0.50 0.48

MU-A85

Production 3.1 -0.2 -7.2E--2 2.0 1.9

Efficiency 0.01 -0.55 -0.32 5.11-3 -5.3E-3
Table 5.24. The number and mean lengths of fish used in stomach contents analyses and mean number of organisms in stomachs for fish

caught during the third and fourth cruises for all sites.

5-142

Predator Prey

Number Total Length (cm) MEIO MACR

Cynoscion arenarius 84 8.3(2.1) 0.40(0.95) 0.20(0.53)

Halieuticthys aculeatus 129 5.5 (0.6) 0.78 (1.16) 1.54(1.79)

Hoplumnis sp. 11 34.2(6.2) 0(0) 0.36(0.67)

Ogcocephalus radiatus 3 7.1 (0.2) 0(0) 1.67 (2.08)

Prionotus stearrist 88 8.1 (0.9) 0.18(0.56) 0.11 (0.58)

Saunida brasiliensis 101 6.6(1.9) 0.04 (0.20) 0.07(0.29)

Syacium guriteri 122 7.8(2.0) 1.88 (2.85) 1.10(1.50)

Synodus foetens 32 8.6(2.0) 0.03 (0.18) 0.06(0.25)

Predator Prey

Number Total Length (cm) EPIF PELA

Cynoscion arenarius 84 8.3 (2.1) 6.76(10.83) 15.25 (22.73)

Holieuticthys acuteatus 129 5.5(0.6) 0.72 (1.43) 0.02(0.12)

Hoplumnis sp. 11 34.2 (6.2) 0.73 (1.49) 0.36(0.67)

Ogcocephalus radiatus 3 7.1 (0.2) 0(0) 0(0)

Prionotus stearnsi 88 8.1 (0.9) 0.20 (0.55) 0.69(0.72)

Saunida brasiliensis 101 6.6(1.9) 0.07 (0.26) 0.61 (0.66)

Syacwm gunteri 122 7.8(2.0) 1.08 (1.28) 0.05(0.22)

Synodus foetens 32 8.6 (2.0) 0.19 (0.47) 0.41 (0.50)

aThe mean is presented with the standard deviation in parentheses, MEIO=Meiofauna, MACR=Macrofauna, EPIFEpi1auna, PELA=Pelagic.
Table 5.25. The number and mean length of fish used in stomach content analyses and the mean number of organisms in the stomachs.

A. Halleutichthys aculeatus

B. Saunida brasiliensis

C. Syaclum guntert

D. Prionotus stearrtsi

MAJ-686 MU-A85 HI-A389

Near Far Near Far Near Far

Sample Size (n) 10 25 51 43

Total Length (cm) 4.6(0.7) 5.0 (0.4) 5.5(0.4) 5.9(0.4)

Meiofauna 1.30(1.25) 1.08 (1.26) 0.45(1.12) 0.86(1.06)

Macroinfauna 0.70(0.82) 0.16 (0.37) 1.94(1.79) 2.07(1.97) Epifauna 0.20(0.42) 0.12(0.33) 1.38 (2.00) 0.47(0.76)

Pelagic 0(0) 0(0) 0(0) 0.05(0.21)

MAI-686 MU-A85 HI -A3 89

Near Far Near Far Near Far

Sample Size (n) 53 59

Total Length (cm) 7.4(1.9) 8.3(1.9)

Meiofauna 1.22 (1.49) 258 (3.70)

Macromfauna 1.62 (1.80) 0.54 (0.77)

Epilauna 1.17(1.26) 0.48 (1.29)

PelagIc 0.05 (0.21) 0.05 (0.22)

MAI-686 MU-ASS HI-A389

Near Far Near Far Near Far

Sample Size (n) 64 20 17

Total Length (cm) 7.3(2.0) 5.7(0.6) 5.2(0.7)

Meiofauna 0.03 (0.18) 0.05 (0.22) 0.06(0.24)

Macroinfauna 0.08(0.32) 0.10(0.31) 0(0)

Epifauna 0.09 (0-29) 0.05 (0.22) 0(0)

Pelagic 0.69 (0.73) 0.55(0.51) 0.41 (0.51)

MAI- 686 MU-A85 l-ll-A389

Near Far Near Far Near Far

Sample Size (n) 25 45 18

Total Length (cm) 7.5(0.6) 8.4(0.9) 8.3(0.9)

Melofauna 0.20(0.65) 0.16(0.42) 0.22(0.73)

Macroinfauna 0(0) 0.20 (0.79) 0.06 (0.24)

Epifauna 0.24(0.66) 0.22(0.55) 0.11 (0.32)

Pelagic 0.60(0.82) 0.71 (0.73) 0.78(0.55)
Five of the eight species were pelagic feeders and were not feeding

primarily on benthos. Four species occasionally ate meiofauna. The

meiofauna that Prtonotus stearnsi fed upon most often were nematodes and

ostrocods. This species fed primarily on pelagic organisms, mainly small

fish. There were 88 specimens collected and they had an average length of

8.1 cm. Cynoscion arenartus is a pelagic feeder eating mostly calanoids. The

average size of the 84 species dissected was 8.3 cm. Hop Iumnis sp.

surveyed ate mostly pelagic fish and macroinfaunal polychaetes. The average

length was 34.2 cm and 11 fish were dissected. Saunida brasWertsis fed

mostly on fish, calanoids, amphipods, and shrimp. The sample size was 101

individuals and the average length was 6.6 cm.

5.4.6 Life History arid Reproduction

5.4.6.1 Reproduction

Measures of reproductive effort (clutch volumes and clutch sizes) were

determined at Near and Far stations for all gravid females encountered.

Near stations represent those samples which came from the 50 m radii, and

Far stations represent the combination of all remaining radii. This pooling

of radii was performed to alleviate a shortage of specimens at some

individual radii, and to increase overall sample size to increase the power of

statistical tests.

No one species dominated the frequency distribution of all gravid

females (Table 5.26). A species of Tachidiella was the most abundant of all

with a frequency of 12, or less than 10 % of all gravid females encountered.

This frequency distribution of animals demonstrates the diversity of species

measured for analysis of reproductive effort and negates the possibility that a

single or even groups of species can be utilized for this analysis. For this

reason, all species were pooled and average clutch size and clutch volume

were adjusted for body length for statistical analysis

5.4.6.2 Life History Characteristics

Analysis of life history characteristics were performed on all

harpacticoids encountered in the study. Harpacticoids were identified and

assigned accordingly into females, gravid females, males, and copepodites.

The copepodite category included all nauplii and copepodite stages (Tables

5.27 and 5.28).

5-144
Table 5.26. Average harpacticoid reproductive effort based on frequency, least square (LS) clutch size and least square (LS) clutch

volume for all species of gravid females encountered on all cruises. Groupings are done by Near and Far stations (n=170).

Platform Species Names Frequency LS Mean LS Mean Clutch

Station Clutch Size Volume (mm3)

HI-A389 Diosaccid sp. 67 2 6 1.77e-03

Far Ectinosomid BP 1 2 L23e-04

Ectinosornid sp. 8 1 2 1.80e-05

Enhydrosoma pei-icoense 1 15 3.05e-04

$tenhelia (Delavalia) sp. 31 1 15 3.05e-04

Zosime n sp. 54-C 1 6 1.74e-04

Unknown 2 8 1.38e-04

Near Diosaccidsp. 111-BC 2 1 3.lOe-05

Ectirtosomid sp. 110-AZ 2 5 6.40e-05

Ectinosomid sp. 87 2 8 5.93e-04

GenusA.-41 1 8 5.80e-04

Tachidiella sp. 86-BL 4 12 3.79e-04

MAJ-686 Ameiridae sp. 79 1 4 1.79e-04

Far Amphiascoides sp. A 1 1 1.44e-04

Amphiascus sp. (rninutas) 1 2 8.82e-04

Thpyrida (unidentifIed) 1 1 4.94e-02

Cletodes aff tubercuiatas 2 4 2.37e-04

Cletodes pseudodissimths 1 5 2.35e-04

Diosaccid sp. 45 2 2 1.73e-04

Diosaccid sp. 46 1 7 3.52e-04

Ectinosornid BP 1 3 1.30e-04

Ectinosomid sp. 129-MB 9 4 1.56e-04

Ectinosomid sp. 130 7 4 1.96e-04

Ectinosomld sp. 133-MH 1 7 8.30e-04

Ectinosomid sp. 134-ME 2 2 1.58e-04

Ectinosomid sp. 139-MO 1 3 9.90e-05

Ectinosomid sp. 34 5 6 1.60e-03

Ectinosomid sp. 52 1 3 3.62e-04

Ectinosomid sp. 8 1 3 6.70e-05

Erthydrosoma pertcoense 3 5 1.06e-04

Haloschizopera sp. 2 2 1.25e-04

Harpacticoid sp. 56 1 2 2.Ole-04

Noi-manella sp. A 2 5 2.12e-04

Normanella sp. B 2 4 1.47e-04

Normanella sp. C 1 3 1.17e-04

Pseudamira sp. 3 7 2.65e-04

Pyramidella sp. 1 15 3.23e-04

Robertgumeya sp. A 6 3 1.89e-04

Robertgw-neya sp. C 1 5 1.43e-04

Stenhelta (Delavalia sp. 2 4 7 2.70e-04

StenheUa (Stenhelia) sp. 37 1 4 6.90e-04

Tachidiella sp. 86-BL 12 9 1.85e-04

Typhtamphiascus sp. 3 3 2.81e-04

Unknown 5 4 1.32e-04
Table 526. (Cont.)

Platform Species Names Frequency LS Mean LS Mean Clutch

Station Clutch Size Volume (mm3)

Near Ameiridae sp. 79 2 6 2.38e-04

Ecttnosomid (unidentified) 1 4 2.74e-04

Ectinosomid sp. 124-BW 1 4 1.61e-04

Ectinosomid sp. 129-MB 1 4 1.79e-04

Ectinosomid sp. 130 2 3 1.39e-04

Ectinosomid sp. 133-MH 1 8 3.45e-04

Ectinosomid sp. 134-ME 3 3 1.31e-04

Ectinosomid sp. 135-MT 2 5 2.91e-04

Ectinosomid sp. 34 I 7 8.95e-04

Ectinosomid sp. 52 1 7 2.94e-04

Microarthridion sp. 1 4 1.11e-04

Normanella sp. B 2 5 2.32e-04

Robertgurneya sp. A 5 4 1.83e-04

Stenhelta (Delava1ia sp. 2 1 10 3.Ole-04

Tachidiella sp. 86-BL 2 7 1.70e-04

Unknown 2 5 1.38e-04

MU-A85 Ameiridae sp. 79 1 2 3.36e-04

Far Diarthrodes sp. 1 7 7.35e-04

Ectinosomid sp. 129-MB 4 5 1.70e-04

Robert9urneya sp. C 1 19 9.39e-04

Unknown 3 8 4.09e-04

Near Ectinosomid sp. 129-MB 4 5 1.Ole-04

Ectinosomid sp. 133-MH 2 11 4.03e-04

Ectinosomid sp. 134-ME 1 7 2.05e-04

Ectlnosomid sp. 139-MO 2 7 3.97e-04

EctinosorrUd sp. 143-MQ 1 20 9.67e-04

Ectinosomid sp. 34 1 11 8.84e-04

Stenhelia (Delavaila) sp. 2 1 4 8.95e-05

Tachidiella sp. 86-BL 4 10 3.18e-04

Unknown 5 7 8.48e-04
Table 5.27. Life history stage densities for all harpacticoids.

5.4.7 Genetic Variability

Each of the five species of harpacticoid copepod used in the genetic

variability study displayed the same haplotype pattern (Tables 5.29 to 5.33).

Populations were composed of a single, ubiquitous baplotype. and numerous

unique baplotypes. Halotype is defined as a region of DNA with a particular

sequence and roughly corresponds to the "allele" of classic genetics (Nei

1987). The dominant baplotype occurred in more than half of the

indMduals in the study, and occurred at all platforms and cruises. A heavily

skewed genotype frequency is consistent with observations from other

populations of marine crustacea, such as calanoid copepods (A. Bucklin,

pers. comm), harpacticoid copepods (Burton and Feldman 1981), and

decapods (Silbermari et al. 1994).

5.5 Macroinfauna

Many subsamples for the macroinfaunal work element yielded small

numbers of individuals and species, especially during Cruises 1 and 4. At 33

of 300 stations (11 %) the faunal composition of each of the three subcores

Station Mean Density

Table 5.28. Population composition for all harpacticoids.

Mean % Composition

5-147

Female 0.0001 8.47 13.27

Gravid Females 0.0001 0.85 0.41

Males 0.000 1 5.83 8.66

Copepodites 0.0001 10.57 15.15

Stage Near Far

Female 0.35 0.35

Gravid Females 003 0.01

Males 0.23 0.21

Copepodites 0.39 0.43

Stage P Near Far
Table 5.29. Meiofauna genetic variability for NormarteUa sp. at three platforms and 

number of Individuals with the dominant haplotype, the number of individuhaplotype, and haplotype diversity (h) are presented. Statlona Near Fa

Platform Cruise Variable Obs 1 2 3 4 5 1 2 3 MU-A85 2 #domlnant 4 7 10 8 1 6 1

#unlque 1 2 0 2 1 2 6 h 0.32 0.37 0.00 0.34 0.50 0.41 0.5

3 #domlnant 11 1 4 3 5 . 2 

#unlque 3 0 1 1 1 . 1 h 0.37 0.00 0.32 0.38 0.28 0.4

MAI-686 2 #domlnant 10 10 6 4 3 12 9 6 

#unlque 5 1 1 0 1 3 4 3 h 0.53 0.17 0.24 0.00 0.38 0.35 0.50 0.5

3 #dominant 1 5 5 7 3 1 6 8 

#unlque 0 1 1 1 0 0 1 3 

0 0.28 0.28 0.22 0.00 0.00 0.25 0.4

HI-A389 2 #domlnant 8 14 2 8 , 9 

#unique 1 3 0 2 2 h . 0.20 0.31 0.00 0.34 . 0.3

3 #domlnant 6 4 2 10 10 10 4 

#unlque 0 0 0 2 3 3 1 h 0.00 0.00 0.00 0.29 0,39 0.39 0.3

aSples in which no Individuals of the appropriate species were collected are indicated by a period.
Table 5.30. Meiofauna genetic variability for CLetodes sp. at three platforms and t

number of individuals with the dominant haplotype, the number of Individhaplotype, and haplotype diversity (h) are presented. apedod indicates no data. Samples In which no individuals of the appropriate species were collected are in

Statlona Near Fa

Platform Cruise Variable Obs 1 2 3 4 5 1 2 3 MU-A85 2 #domlnant 5 8 6 7 10 4 9 

#unlque 0 3 0 1 3 1 3 

Ii 0.00 0.45 0.00 . 0.22 0.39 0.32 0.4

3 #domlnant 3 7 5 8 10 3 

#unique 1 3 0 1 3 0 

h 0,38 0.48 0.00 0.20 0.39 0.00 

MAI-686 2 #dominant 7 2 10 9 10 8 9 

#unlque 3 0 2 2 0 2 1 

h 0.48 0.00 . 0.29 0.31 0.00 0.34 0.1

3 #dominant 3 1 6 10 4 10 9 

#unlque 1 0 0 0 1 1 4 

h 0.38 0.00 0.00 0.00 0.32 0.17 0.50 

H1-A389 2 #domlnant * 7 8 8 10 1

#unique 0 0 1 2 2 

h . 0.00 0.00 0.20 0.29 . . 0.2

3 #domlnant 10 2 1 10 8 4 4 

#unique 2 1 0 1 0 1 1 

h 0.29 0.44 0.00 0.17 0.00 0.32 0.32 
Table 5,31. Meiofauna genetic variability for Erthydrosoma pericoense at three platform

The number of individuals with the dominant haplotype, the number of i

unique haplotype, and haplotype diversity (h) are presented. aSamples in which no Individuals of the appropriate species were collected are Indicated by a period. Stattona Near Fa

Platform Cruise Variable Obs 1 2 3 4 5 1 2 3 MU-A85 2 #dominant #unique 3 1I. #dominant 4 10 ,10 26 6 

#unique 1 2 4 14 1 h 0.32 0.29 0.47 0.57 0.2

MAI-686 2 #dominant 10 5 1 7 10 5 11 6 

#unlque 2 0 0 1 0 1 0 3 h 0.29 0.00 0.00 0.22 0.00 0.28 0.00 0.5

3 #domlnant 3 2 70 14 14 24 12 4 

#unique 2 0 11 0 2 3 1 2 h 0.56 0.00 0.25 0.00 0.23 0.21 0.14 0.5

HI-A389 2 #dominant #unique h . . . 3 #domlnant 3 7 12 8 

#unique 0 1 5 3 

0.00 0.22 0.48 0.4
Table 5.32. Meiofauna genetic variability for Robertsonia sp. at three platforms and 

number of individuals with the dominant haplotype, the number of individhaplotype, and haplotype diversity (h) are presented. Stationa Near Fa

Platform Cruise Variable Ops 1 2 3 4 5 1 2 3 MU-A85 2 #domlnant 5 10 4 5 8 9 10 1

#unique 1 2 3 0 0 2 3 0 

0.28 0.29 0.61 0.00 0.00 0.31 0.39 0.0

3 #dominant 1 3 10 4 

#unlque 0 1 3 1 

Ii 0.00 0.38 0.39 0.3

MAI-686 2 #domlnant #unique h 3 #dominarit 2 6 6 #unique 0 1 2 h 0.00 0.24 0.4HI-A389 2 #dominant 13 10 4 12 10 1

#unlque 3 1 1 2 3 4 

h . 0.33 0.17 0,32 0.26 0.39 0.4

3 #dominant 3 3 4 

#unique 0 1 1 h 0.00 0.38 0.3

aSamples in which no individuals of the appropriate species were collected are indicated by a period.
Table 5.33. Melofauna genetic variability for Tachidiella sp. at three platforms and 

number of Individuals with the dominant haplotype, the number of individuhaplotype, and haplotype diversity (h) are presented. Stationa Near Fa

Platform Cruise Variable Obs 1 2 3 4 5 1 2 3 MU-A85 3 #domtnant 1 2 2 6 11 6 3 

#unlque 0 0 0 2 3 0 1 h 0.00 0.00 0.00 0,41 0.37 0.00 0.3

MAI-686 3 #domtnant 3 1 22 3 1 

#untque 0 0 5 0 0 h 0.00 0.00 0.33 0.00 0.00 

HI-A389 3 #domlnant 4 1 1 3 9 8 #unique 1 0 0 0 4 2 h 0.32 0.00 0.00 0.00 0.50 0.3

aSmples in which no Individuals of the appropriate species were collected are indicated by a period.
was unique; no species was common to two or more subcores (Table 5.34).

This occurred most frequently at MU-A85 and HI-A389 during Cruise 1 and

at MAI-686 during Cruise 4. These results suggest that a larger sample size

may have been needed; however, pooling results from the three replicates

minimized the effects of small sample sizes.

5-5.1 Seasonal Trends

Seasonal trends in abundance at MAI-686 and MU-A89 were similar

(Figure 5.104). Between 700 and 900 total individuals were collected in

winter 1993 and summer 1993 (Cruises 1 and 2). Both sites experienced a

marked increase (1500 to 1800 individuals) in the winter of 1994 (Cruise 3)

and then declined again to about 600 to 700 individuals in June of 1994

(Cruise 4). Abundances at HI-A389 underwent a more gradual increase and

decrease, beginning with about 900 individuals, increasing to 1200

individuals, and then decreasing to about 600 individuals. These trends in

abundance were unusual because highest abundances occur in the winterspring period and are lowest during the summer and fall. The numbers. of

individuals collected during the winter of 1993 (Cruise 1) were much lower

than expected and, at two of the three platforms were lower than

abundances the following summer. The data suggests that this was a

widespread phenomenon because a relatively low number of animals was

collected at all three study sites. The cause of this low abundance is not

known.

5.5.2 Diversity

When the total numbers of species were considered in relation to

distance from the platform, there was a general trend of the highest

numbers of species occurring close to the platform (Figure 5.105). The

largest mean number of species occurred at the 50-m stations. In all cases,

the largest mean number of species occurred close to the platform. The

total numbers of species per station are presented as contour plots in Figure

5.106. At MAI-686, most stations bad between 40 and 60 species of

macroinfauna and the numbers varied with distance from the platform

(Figure 5.106). The only deviation from this pattern occurred to the

northwest where there was a pronounced decrease in the number of species

5-153
Table 5.34. Numbers of stations having unique species assemblages in each of the three subcores collected. Each distance had five

stations.

Distance Cruise 1 Cruise 2 Cruise 3 Cruise 4

MAI-686

50m 0 0 0 0

lOOm 0 0 1 1

200m 1 1 0 1

500m 0 0 0 2

3000m 0 0 1 2

Total= 1 1 2 6

MU-A85

50m 1 1 0 0

lOOm 1 0 0 0

200m 2 0 0 1

500m 3 0 0 0

3000m 1 0 0 0

Total 8 1 0 1

HI-A389

50m 3 1 0 0

lOOm 0 0 0 1

200m 1 0 0 0

500m 3 2 0 2

5000m 0 0 0 1

Total= 7 3 0 4
Figure 5.104. ComparIson of seasonal trends In mean numbers of Individuals of m

all sites.
Figure 5.105. Summary of the mean number of macroinfaunal species by distance 

platforms.
N

E10

E

CS

S

N

E

. -ao 0

S

MAI-686 Macroinfaunal S. - des

-3J0 0

w Distance from Platform (m) E

MU-A85 Macroinfaunal S. - ies # HI-A389 Macroinfaunal S. - les

N

E

E

I

. -3:o

0

S - w

0 300 Distance from Platform (m) E

Figure 5.106. Area! distribution of the number of macroinfaunal species as

a composite of all four cruises.

5-157

w Distance from Platform (m) E
with increased distance from the platform (Figure 5.106). Distinct regional

trends in the number of species were also observed at MU-A85 (Figure

5.106). The 95-species isopleth included most of the 50- and 100-rn

stations. Highest numbers of species were observed toward the west. At HIA389, the numbers of species were higher at the 50-rn stations (Figure

5.106). Three stations to the northeast and east had reduced numbers of

species compared to the surrounding stations.

The Shannon-Weaver Index of Diversity (H') was calculated for each

station based on pooled data (Figure 5.107). H' along transects at MAI-686

changed little with distance (Figure 5.108). The areal distribution of H'

values at MAI-686 suggests a region of slightly higher values to the

southwest at 200-rn distance. The only exception was a slightly higher H' at

one station 500-rn distance from the platform. At MU-A85, H' was generally

highest at the 100-rn stations (Figure 5.108). On three transects there was

a trend of decreasing H' beyond the 100-rn stations. On two transects the

200- and 500-rn stations had a lower H' than the other stations. H' values at

MU-A85 were fairly uniform with no particular trend except one area of

lower values. At HI-A389, H' is low at the 50-rn stations at two stations

(Figure 5.108). The other stations at this site had similar H' values. The

large abundances of infauna close to the platform (50 m), relative to the rest

of the stations, contributed to a region of low H' values which trends

northeast to southwest at HI-A389. Outside of the 50-rn distance, the area

had fairly uniform I-I' values. There was little difference between distances

or sites in regard to mean H' values.

5.5.3 Abundance

Trends in macroinfaunal abundance with distance from the platform

were different at MAI-686 than at the two deeper sites. At MAI-686, the

number of individuals increased away from the platform on four of the five

radii. Large numbers of individuals were collected at one station (50 m) as

compared with the other four stations near the platform (Figure 5.109). At

the two deeper sites, macroinfaunal abundances were higher close to the

platform and decreased rapidly with increasing distance from the platform.

Abundances decreased rapidly and were generally very low far from the

platform. Mean abundances at MAI-686 were greatest at the 50-rn station,

but only because of the large number of individuals collected at one station.

5-158
Figure 5.107. SummarY of the mean Index of diversitY (H') for macrolnfaufla by dis

platforms.
NE

EI-0

0.

E

.5

S

MU-A85 Macroinfauna Dlversi

-8)0 -3J0 0 3)0

W Distance from Platform (m) E

MAI-686 Macroinfauna Divers

W Distance from Platform (m) E

3)0

HI-A389 Macroinfauna Divers

-3)0 0 Distance from Platform (m) E

Figure 5.108. Meal distribution of the mean index of diveisity (H') for

macroin&una as a composite of all four cruises.

5-160
Figure 5,109. Summary of the mean number of macroinfauna by distance from 
Mean abundances at the 200-, 500-, and 3000-rn stations were nearly the

same as those at the 100-rn stations. In contrast, mean abundances were

considerably higher at the 50-rn station as compared to the 3000-rn

stations. At MU-A85, mean abundances at the 50- and 100-rn stations were

nearly identical, about 200 individuals, while the 200 to 3000-rn stations

had a nearly uniform number of individuals (n=135 to 140). Mean

abundances at HI-A389 decreased logarithmically with distance from the

platform.

Abundance data are also presented as contour maps for each study site

in Figure 5.110. A regional high in macroinfauna was apparent to the

southwest of platform MAI-686 (n > 300; Figure 5.110). To the northwest,

there was a three-station area of reduced numbers of individuals (< 100)

relative to the other stations. At MU-A85, the 190 individual isodeme and

the 130 individual isodeme included all 50- and 100-rn stations, and

extended out to the 200-rn stations at two stations (Figure 5.110). There

was an area of increased abundances that was nearly symmetrical around the

platform. The mean number of individuals at HI-A389 was quite high at the

50-rn stations. The contour map illustrates a region of high abundance (n>

200) that paralleled the 100-rn isobath (Figure 5.110). Note that to the

southwest, the 100-individual isoderne extended to the 500-rn station.

5.5.4 Comparison of Abundances of Numerically Dominant Taxa

The two most abundant macroinfaunal taxa were polycbaetous annelids

and amphipoda. Polychaetous annelids were the overall numerically

dominant taxonomic group at all sites. Their dominance is shown by

comparing the mean numbers of individuals by distance from the platform

(Figure 5.111). The largest number of polychaetes occurred either at the

50-rn (MAI-686, HI-A389) or the 100-rn (MU-A85) stations. Note that the

mean number of polychaetes was similar at all distances at MAI-686,

whereas there is a decrease in numbers with increased distance at MU-A85

and HI-A389. The trend of mean abundances of amphipods (Crustacea:

Peracanda), the second most abundant overall group, was the inverse of the

polychaetous annelid distribution. Abundances were lowest at the 50-rn or

100-rn stations and increased with increased distance from the platform

(Figure 5.112). Amphipods were much more abundant at the shallowest site

(MAI-686). Amphipods. particularly in the Family Ampeliscidae, appear to

5-162
Figure 5.110. Areal distribution of the mean abundances of macroinfaunal

individuals as a composite of all four cruises.

5-163
Figure 5.111. Summary of the mean abundances of polycha?tes by distance from 
Figure 5.112. Summary of the mean abundances of amphipods by distance from 
be sensitive to environmental perturbations. Amphipods were completely

eliminated following a major hypoxic event on the upper Texas coast

(Harper et al. 1981a, 1991) and remained absent for four years from a

Galveston beach following an oil spill (unpublished data). Amphipods lack

planktonic larvae, and thus must rely on migration of adult or young

members to repopulate an area.

Other taxa of lesser abundance included Nemertea, Bivalvia, t)ecapoda,

Isopoda, Foraminera, and Ophiuroidea. Nemerteans were most abundant at

the MU-A85 site (Figure 5.113). Mean abundances were highest at the 50-

or 100-rn stations. There was an especially strong gradient at MU-A85 with

increasing distance from the platform. There was a pronounced decrease in

mean abundances of bivalves (Mollusca) with increasing distance from

platform HI-A389 (Figure 5.114). At the other two sites there was no clear

trend. Mean abundances at some far stations were equal to, or similar to,

abundances at the near stations. Decapod crustacean mean abundances

varied depending on water depth (Figure 5.115). At MAI-686, there was

virtually no difference in abundance with distance from the platform and the

overall numbers of decapods collected was low. At the deeper MU-A85 and

HI-A389 sites, the greatest mean abundances occurred at the 50-m stations

and there were large step-wise reductions in abundance with increased

distance from the platforms. Isopods (Crustacea:Peracarida) were absent at

the shallowest site (MAI-686; Figure 5.116). There was a pronounced

abundance gradient at MU-A85 with fewer individuals collected at greater

distances from the platform. Isopods were infrequently collected at HIA389, and were most abundant at the 100- and 200-rn stations.

Foraminiferans were absent at the MAI-686 site (Figure 5.117). At the

deeper sites, the foraminifera displayed abundance trends similar to the

amphipods; the mean numbers of individuals increased with increased

distance from the platforms. Mean abundances were highest at the 500-rn

stations at the MU-A85 site and at the 5000-rn stations at the HI-A389 site.

Ophiuroids (Echinoderinata: Stelleroidea) were not among the numerically

dominant groups, but are included because they are the only echinoderm

group represented in the infaunal assemblages, and serve as the echinoderm

surrogate for comparison with the pore water toxicity tests. Mean

abundances of brittlestars were lowest at the 200-rn stations at MU-A85 and

HI-A389 sites (Figure 5.118). At MAI-686 there was a general decrease in

5-166
Figure 5.113. Summ of the mean abundac of nemertes by distance from 
Figure 5,114. Summary of the mean abundances of bivalves by distance from t
Figure 5.115. Summary of the mean abundances of decapods by distance from 
FIgure 5.116. Summary of the mean abundances of Isopods by distance from t
Figure 5.117. Summary of the mean abundances of forams by distance from th
Figure 5.118. Summary of the mean abundances of ophiuroids by distance from 
mean abundance with increasing distance from the platform. Echinoderms

were absent at the 3000-rn stations.

5.6 Megafauna - Invertebrates

Physiological and environmental parameters including: salinity,

temperature, food availability, disease, parasitism and exposure to

environmental contaminants can affect the health and productivity of marine

invertebrates (Peterson and Black 1988; Sindermann 1983). In this section

abundance, catch per unit effort, size and sex distributions, stage of

reproductive development, and the health of the populations based on the

presence or absence of parasites and disease are presented for megafaunal

invertebrates.

Target species were chosen based on the most abundant invertebrates

collected in trawis to provide pair-wise comparisons between the Near and

Far stations and also to represent a variety of taxa. The goal was to target

between 5 and 10 species at each platform for analysis. A second

consideration was to include species that represented the major taxa

collected, including decapods, molluscs, and echinoderms. Therefore, not

only was overlap between the Near and Far stations important, but the

distribution of species among important taxa was also considered in

selecting target species. Species overlap between the Near and Far sites

was poor for Cruise 1, particularly at HI-A389. Increased and improved

trawling activities during subsequent cruises improved the number of

individuals caught as well as the species overlap between the Near and Far

stations.

The species collected at each platform and the extent of overlap

between the Near and Far stations achieved during the four cruises are

summarized in Tables 5.35 to 5.38. Similar species were collected at each

platform during each cruise, but some differences in species composition

existed among platforms. In general, species collected at MAI-686 and MUA85 were similar, whereas species collected at HI-A389 were different from

those at the other platforms. This between-platform difference resulted

primarily from differences in water depths at the sites. MAI-686 and MUA85 are located in relatively shallow water, 29 and 75 m respectively,

whereas HI-A389 is located in much deeper water (-125 m). This

difference in water depth results in a different assemblage of animals being

5-173
Table 5.35. The number of individuals collected for each species at the Near and Far station

cji a' Indicates no data. Number of Individualsa Site GA-288 HI-A389 MAI-686 MAI-622 

Species Station Near Far Near Far Near Far Near Far 

Shrimp Penaeusaztecus - 10 - 10 10 10 10 

Trachypenaeus simiLis 10 10 9 - 10 10 10 10 Sicyonia dorsaUs 10 10 - - 10 10 10 Sicyonta brevirostris - 10 - - - Crabs CalUnectes similis 8 10 - 5 10 10 10 

Portunus gibbesu 6 4 - - 10 10 10 10 

Portunus spinicarpus 10 10 - - - - 

Acanthocarpus alexandria - 10 10 - - - 

Myropsis quinquesptnosa - - 10 10 - - - 

Dromida antiUenss - - - 9 - - 

Rannoides loufskrnensts - - - - - - - - 

Mwiida irrasa - 10 Hermit crab (spp.) - - 8 - - - - - 

Molluscs Amusium papyraceum - - - - - - 

Anadara transuersa - - - - - 

Pitar cordatus - - - - - - - 

Murexfuivescens - - 10 - - - - 

Polystira albida - - - - - 

Echinodenna Astropecten c(ngulatus - 6 - 

Astropecten dupUcatus - - - 10 10 - - 

Echinocardium flavescens - - - 9 Brittle star (spp.) 10 4 Stomatopads SquiUa empusa 6 10 - - - 10 10 9
Table 5.36. The number of individuals collected for each species at the Near and Far station

Shrimp Penoeus aztecus 10 10 10 10 - Trachypenaeus sImilts 3 10 10 10 Soenocera atlanttdis 10 10 10 6 Crabs Calltnectes similts 3 9 10 10 Portunus gibbesU - - 10 - - Portunus sptntcarpus 10 10 - 10 2 Port unus spinimanus 10 - Acanthocarpus alexandria - - 5 10 Myropsls quLnquespfrtosa - - 3 10 Hermit crab (spp.) 10 10 01 Molluscs Amusiumpapyraceum 10 10 PoysUra atbida 10 10 - - 01 Echinoderms Astropecten cingutatus 7 9 - 5 5 Stomatopods Squilla empusa - 10 10 - SquiUa chydaea 10 10 Squilla edentata - - 7 10 a'i' Indicates no data. Number of Individualsa Site MU-A85 MAI-686 1-H-A389 Species Station Near Far Near Far Near Far
Table 5.37. The number of individuals collected for each species at the Near and Far station

a.. indicates no data. Number of lndivlduaisa Site MU-A85 MAI-686 H1-A389 Species Station Near Far Near Far Near F

Shrimp Penneusaztecus 10 10 9 10 Trachypenaeus s(rntUs 7 10 10 10 Solenocera atlantidis 10 10 - - 10 

Sicyonta dorsaUs 10 - 10 - 

Parapenaeus simills - - - 10 

Crabs CaUlnectes slrnWs - 7 10 - 

Porturtus gibbesU - 8 10 Portunus spinicarpus 10 10 - 10 

Acanthocarpus alexandria - - - 1 

Myropsis quinquespinosa - - - - - 

Hennit crab (spp.) - - - 6 

Molluscs Amus(utn papyraceum 10 10 - Echinoderms Astropecten clngutatus 10 - - - 

Astropecten dupUcaWs - 2 10 10 Stomatopods Squtila empusa - 10 10 - Squtila chydaea 10 1 7 10 2 SqutUa edentata - - - 2 
Table 5.38. The number of individuals collected for each species at the Near and Far station

a' Indicates no data Number of Individualsa Site MU-A85 MAI-686 HI-A389 Species Station Near Far Near Far Near F

Shrimp Penaeus aztecus 9 10 10 10 - Trachypenaeus simtlls - - 10 10 Sotenocera atiantidts 10 10 - - 10 

Crabs CaUtnectes stmllts - 10 10 Portunus gthbesu - - 10 10 Portunus spinicarpus 10 10 - 4 Acanthocarpus a!exandr(a - - - 9 

Mjropsis quinquespinosa - - - - 9 

Hermit crab (spp.) - - - 3 

Molluscs Arnus um pap yraceum 10 10 Echinoderms Astropecten cingulatus 8 10 - 5 

Astropecten dupilcatus - - 10 10 Stomatopods SquiUa empusa - - 10 10 Squllia chydaea 10 4 10 10
found at HI-A389. The target species collected during the majority of the

cruises included three species of shrimp (Pertaeus aztecus, Trachypertaeus

stmths and Solenocera atlantidis), three portunid crabs (Callirtectes similis,

Portunus spinicarpus and Portunus gtbbesii), two starfish (Astropecten

ctngutatus and Astropecten dupUcatus), a scallop (Amusium papyraceum),

and three species of stomatopods (Squilla empusa, Squilla chydaea and

Squilla edentata). These species were typically collected with sufficient site

overlap to provide pair-wise comparisons between Near and Far stations and

represented each of the major taxa present.

5.6.1 Catch Per Unit Effort

Catch per unit effort (CPUE) is one measure of species abundance.

High values indicate that more individuals were collected per trawled area

and that the species is more abundant than organisms caught in lower

numbers. It should be noted that this assumes equal collection success for

all of the species inventoried and that other processes (such as schooling)

do not create sampling artifacts. These assumptions may be more or less

important depending on the species.

CPUE was calculated for the target species on Cruises 3 and 4 by

dividing the number of individuals of a specific species collected in a trawl

by the distance on bottom for the trawl as determined by shipboard

navigation. Values of CPUE for each of the overlapping species collected at

each platform and on each trawl are given in Tables 5.39 and 5.40. Shrimp

were typically the most abundant species collected, regardless of platform,

cruise, or station. T. stmtlis was collected in extremely high numbers with

CPUE values as high as 5.1 rn-2 at the Near station and 10.5 rn-2 at the Far

station. Brusher et al. (1972) also recorded large catches of T. similis from

the northwest Gulf of Mexico. Callinectes simtlis was the most abundant crab

species with CPUE as high as 4.0 rn-2 at MAI-686 on Cruise 4. Species at

HI-A389 were usually less abundant than species collected at the other sites.

5.6.2 Individual Size and Size Frequency Distributions

The differences between the size frequency distributions of individuals

collected at the Near and Far stations for overlapping species on each cruise

are summarized in Tables 5.41 to 5.44. Those individuals collected and
Table 5.39. Catch per unit effort (CPUE, individuals rn2) for each trawl and overlapping species collect

MAI.886a

I aDashes (--) Indicate trawis during which no invertebrates were collected; zeroes indicate that no Individuals of that species we

Asterisks indicate that the species may have been collected during that trawl but individuals were not counted or measured. Solid imore trawls were done at that site. Mean is the average CPUE for all trawls; S.D. Is the standard deviation. Peno.eus aztecus Trachypenaeus simiUs CaWnectes slmths SquiUa empusa Squilla chydaea 

Trawl Near Far Near Far Near Far Near Far Near Far 

1 0 -- 0.011 -- 0 -- 0 -- 0 -- 2 0 0.034 0.053 5.888 0 0.023 0.011 0.023 0 0.034 3 0 0.006 0 0.324 0 0 0.009 0.006 0 0.019 4 0.011 0.091 0.021 8.634 0 0 0.011 0.082 0 0.055 5 0 0.052 0 2.199 0 0.017 0 0.172 0 0.129 6 0 0.132 0.010 10.461 0 0.011 0.010 0.449 0.010 0.153 7 0.009 0.131 0.118 2.231 0 0.113 0.018 0.105 0 0.113 8 0.015 0.010 0.095 4.758 0 0.019 0.058 0.268 0 0.099 9 0.021 0 0.563 0 0 0.031 0 0.021 0.008 

10 0.034 0 2.941

* 0.034 0 0.147 0 0 0 

11 0.046 0.017 5.059

* 0.015 0 0.169 0 0 0 

12 0 0 3.398 0 0 0.135 0 0 0.007 13 0.015 0 2.536 * 0.015 0.069 0.077 0 0 0 14 0.031 0 2.381 0.031 0 0.122 0 0.031 0 

15 -- -- -- -- -- 16 0.039 1.573 0 0.146 0.0 10 17 0.0 13 1.2 16 0 0.254 0.040 18 0.025 1.957 0 0.226 0 

Mean 0.015 0.036 1.290 4.928 0.007 0.019 0.084 0.085 0.007 0.047 

S. D. 0.015 0.048 1.489 3.406 0.012 0.033 0.081 0.132 0.012 0.054 
Table 5.39. (Cont.) MuA85a mA389a Solenocera Parapenaeus sErnills Port unus Acanthocarpus Hermit crab SqulUa chy

atlantidts spinicarpus alexandria 0 aDashes (--) indicate trawls during which no Invertebrates were collected: zeroes indicate that no Individuals of that species were collec

Indicate that the species may have been collec led during that trawl but individuals were not counted or measured. Solid lines under siwere done at that site. Mean is the average CPUE for all trawis; S.D. is the standard deviation. Trawl Near Far Near Far Near Far Near Far Near Far Near 

2 0 0.049 0.123 0.017 0 0.017 0 0 0.012 0 0 3 0 0.058 0.041 0.047 0 0 0 0.070 0 0.058 0 4 0 0.015 0.111 0 0 0 0.009 0 0.009 0 0 

5 0 0.047 0.008 0.066 0.105 0 0 0 0 0 0.015 

6 0.084 0.042 0.274 0.084 0.008 0 0 0.0 14 0.030 0.014 0.023 7 0.032 0 0.333 0 0.011 0 0 0 0 0 0 8 0 0 0 0.016 0.008 9 0 0 0 0.007 0.007 

10 0 0 0 0 0 11 0.089 0.032 0 0 0 12 0.125 0.055 0 0 0.008 13 0.168 0.232 0 0 0 14 0.051 0.110 0 0 0.007 

Mean 0.019 0.049 0.148 0.049 0.021 0.001 0.002 0.008 0.009 0.008 0.006 

S.D. 0.031 0.050 0.118 0.063 0.038 0.005 0.003 0.019 0.011 0.015 0.009 

Penaeus a2tecus Solenocera atlant(ths Portunus spintcarpus Squilla chydaea Amusium 

Trawl Near Far Near Far Near Far Near Far Near 

1 0024 0.032 0.024 0 -- 

2 -- 0.049 0.059 - 0 0 3 -- 0.025 -- 0.049 -- 0.008 -- 0.008 - 4 0 0.018 0 0.071 0 0.018 0 0 0.010 5 0.009 0 0 0 0 0 0 0 0.018 6 0.039 0.020 0.039 0 0 0 0.026 0 0.039 7 0.038 0.011 0.086 0 0 0.011 0.076 0 0.009 8 0.029 0.011 0.252 0 0.281 0 0.029 0 0.029 9 0 0.025 0.026 0 0.197 0.012 0.105 0 0.026 

10 0.042 0.054 0.266 0.161 0.337 0 0.224 0 0.084 11 0.084 0.065 0.336 0.285 0.322 0.013 0.126 0 0.028 12 0.160 0.055 0.027 0.088 0.147 0.055 0 0 0.027 13 0.114 0.106 0.149 0.071 0 0.018 0.069 0 0.046 14 0.124 0.172 0.019 0 

Mean 0.052 0.042 0.118 0.071 0.128 0.013 0.066 0.001 0.032 

S.D. 0.049 0.035 0.118 0.081 0.138 0.014 0.068 0.002 0.021 
Table 5.40. Catch per unit effort (CPUE, individuals rn-2) for each trawl and overlapping species collect

MA16S6a aDashes (--) indicate trawis during which no invertebrates were collected; zeroes Indicate that no individuals of that species we

Asterisks (1 indicate that the species may have been collected during that trawl but individuals were not counted or measured. Soli

no more trawls were done at that site. Mean is the average CPUE for all trawls; S.D. is the standard deviation. Penaeus aztecus Trachypenaeus simiUs Callinectes sirnllls Portunus gibbesU SquiUa empusa SquUta chyd

Trawl Near Far Near Far Near Far Near Far Near Far Near F

1 0.011 0.064 0.023 0.231 1.592 0.208 0.068 0.008 0.046 0 0.011 0.0

2 0 0.121 0.101 0.336 1.234 0.316 0.038 0.040 0.063 0 0 3 0 0.126 0.081 0.498 1.881 0.442 0.041 0.049 0.081 0.007 0 0.04 0.011 0.121 0.011 1.211 0.554 1.173 0.064 0.006 0.011 0 0.011 5 0 0.084 0.139 0.318 1.960 0.684 0.043 0.018 0.075 0 0 6 0 0.116 0.389 0.569 4.218 0.436 0.139 0.018 0.129 0 0.030 7 0.012 0.043 0.257 0.219 2.218 0.336 0.105 0.024 0.164 0.024 0 8 0.110 0.774 0.606 0.045 0.026 0.09 0.092 0.763 0.513 0.033 0.026 

10 0.185 3.749 0.678 0.022 0.316 0.011 * * 0.229 0 

Mean 0.005 0.106 0.143 0.867 1.951 0.511 0.071 0.026 0.081 0.036 0.007 0.0

S.D. 0.006 0.037 0.126 1.004 1.056 0.262 0.035 0.014 0.047 0.089 0.010 0.0

MUA85a Pertcxeus aztecus Solenocera atlanUdts Portunus sptnlcarpus SqutUa chydaea Amusium pap yraceum 

Trawl Near Far Near Far Near Far Near Far Near Far 

Qi 1 0.011 0 -- 0 -- 0 0.039 OD 2 0.006 0 0.017 0 0.296 

3 -- 0.033 -- 0.0 17 -- 0,050 -- 0.0 11 -- 0.326 4 0 0.0 19 0.028 0.240 0 0,221 0.028 0.013 0.041 0.366 

5 0 0.025 0 0.225 0 0.119 0 0 0.080 0.244 

6 0 0.056 0 0.365 0.011 0.167 0 0 0.044 0.303 

7 0 0 0 0 0.019 

8 0 0.365 0 0.037 0.182 9 0.029 1.381 0.045 0.089 0.223 

10 0.019 0.516 0.029 0.038 0.029 11 0.031 0.677 0.041 0.062 0.051 12 0.019 0.548 0.049 0.039 0.039 

Mean 0.011 0.025 0.391 0.141 0.019 0.096 0.033 0.004 0.079 0.262 

S.D. 0.013 0.016 0.434 0.143 0.020 0.080 0.029 0.006 0.069 0.106 
Table 5.40. (Cont.) mA3s9a aDashes (--) Indicate trawls during which no Invertebrates were collected: zeroes indicate that no individuals of that species w

Asterisks (1 IndIcate that the species may have been collected during that trawl but individuals were not counted or meindicate that no more trawls were done at that site. Mean is the average CPUE for all trawls; S.D. Is the standard deviation. Solenocera atiarittdls Myropsls qtdnquespinosa Acanthocarpus alexandria Hermit crab Ast

Trawl Near Far Near Far Near Far Near Far N

Ii-- -- -- 2 0 0 0 0.006 0 0 0 0 0

3 0 0 0 0 0 0 0 0 04 0 0.022 0.011 0.007 0.011 0 0.011 0 0

5 0 0.027 0 0 0 0 0 0 

6 0 0.091 0.009 0 0 0.008 0.009 0.015 7 0.014 0.026 0.007 0.026 0.007 0.059 0 0.009 

8 0.049 0 0.028 0.021 0 0.02 1 0 0 

9 0.057 0 0.014 0.007 0.014 0.019 0.007 0 0

10 0.183 0 0.007 0 0.007 0 0 0 0Il 0.153 0 0 0 0.009 0.012 0.009 0 12 0.03 1 0 0.008 0.006 0.023 0.012 0 0 

Mean 0.044 0.015 0.008 0.007 0.006 0.012 0.003 0.002 0

S.D. 0.062 0.026 0.008 0.009 0.007 0.017 0.004 0.005 0
Table 5.41. Summary data for overlapping species collected from each

platform during Cruise 1.

b measurements are in mm.

Cpge presents the largest and smallest Individual collected.

5-183

Platform Species

Total

Stationa Collected

Mean

Sjzeb

SFze nangeC Standard

Laigest Smallest Deviation

GA-288 T. sirnihs N 50 27.8 35 18 5.6

F 50 28.2 36 11 6.7

GA-288 S. dorsalis N 50 17.0 20 15 1.3

F 53 17.1 21 11 1.7

GA-288 C. similis N 8 42.6 46 38 3.2

F 12 45.5 58 35 6.8

GA-288 P. gibbestt N 8 44.5 54 30 6.9

F 4 41.0 42 40 1.0

GA-288 S. empusa N 6 30.8 35 26 3.4

F 16 25.3 33 18 3.8

GA-288 Brittle star N 10 12.5 17 9 2.7

F 4 11.8 14 9 1.8

HI-A389 M. qunquespLnosa N 10 16.7 23 14 2.8

F 11 27.0 38 17 7.3

MAI-622 P. aztecus N 16 41.2 45 35 3.5

F 13 40.5 48 28 4.9

MAI-622 T. sirnhlis N 50 28.9 36 15 5.3

F 50 30.1 36 18 4.2

MAI-622 S. dorsolis N 18 13.4 16 8 2.1

F 50 15.1 18 13 2.3

MAI-622 C. stratUs N 11 48.6 55 42 3.9

F 18 52.1 73 41 8.9

MA[-622 P. gibbesit N 10 40.8 45 30 4.4

F 11 39.5 47 28 4.8

MAi-622 S. empusa N 14 20.9 26 16 3.7

F 9 20.9 23 19 1.5

MAI-686 P. aztecus N 10 41.8 52 33 6.2

F 10 43.5 48 37 3.6

MAI-686 T. stratus N 50 29.4 36 17 4.8

F 52 28.9 35 17 4.5

MAI-686 C. stratus N 5 55.0 61 51 3.4

F 27 56.9 81 40 9.6

MAI-686 P. gibbesli N 10 43.0 53 27 7.2

F 10 44.4 53 36 5.4

MAJ-686 A. duplicatus N 17 13.0 15 12 0.8

F 15 12.1 15 9 1.7

MU-A85 P. aztecus N 14 54.1 63 40 5.9

F 12 57.4 66 50 5.8

MU-A85 P. spinicarpus N 38 40.9 56 31 6.1

F 26 47.0 56 33 6.0

MU-A85 A. papyraceum N 16 50.9 61 38 6.4

F 50 50.4 62 35 5.8

MU-A85 A. duplicatus N 15 15.5 27 10 5.5

F 12 8.3 10 7 1.0

aN..ne field station; F=far-field station.
Table 5.42. Summary of the numbers of individuals collected and size range for overlapping spe

during CruIse 2. aNne.field station; F=far-fieid station. bj1 measurements In mm, - Indicates no data. Number Collected Mean Size Range 

Sizeb Male Female 

Platform Species Statlona Male Female Male Female High Low High LoMAI-686 P. aztecus N 6 15 32.8 33.1 35 31 50 2

F 21 29 38.0 43.2 48 25 55 3

MAI-686 T. slmths N 2 31 18.5 28.7 20 17 36 2

F 4 83 21.8 29.9 26 18 37 2

MA1-686 C. sirniUs N 127 22 40.6 51.3 79 27 75 2

F 119 15 40.9 63.2 100 27 72 5

MU-A85 P. aztecus N 23 27 48.8 58.6 57 40 78 4

F 16 34 50.5 58.9 65 41 71 4

MU-A85 T. slmitis N 0 3 - 33.7 - - 36 3

F 2 41 22.0 33.8 23 21 38 2

MU-A85 S. attanttdis N 19 29 14.5 20.9 20 12 31 1

F 14 39 14.1 21.7 20 11 32 1

MU-A85 C. sfrntUs N 10 0 42.6 - 75 29 - 

F 9 0 40.6 - 48 36 - 

MU-ABS P. sptaicarpus N 8 42 47.0 41.0 51 37 55 2

F 1 73 41.0 36.7 41 41 56 1

HL-A389 S. atlanttdis N 21 10 14.6 21.0 17 13 30 1

F 3 3 15.3 25.0 16 15 30 1

HI-A389 P. spiraicarpus N 15 17 52.4 51.9 60 42 60 4

F 0 2 - 46.5 - - 47 4

HI-A389 M. quinquespinosa N 1 2 17.0 24.0 17 17 26 2

F 7 7 23.0 21.7 28 17 33 1

HI-A389 A. a'exandria N 2 3 27.5 24.7 33 22 27 2

F 13 8 31.3 27.6 41 13 34 2
Table 5.42. (Cont.) aN...nearfleid station; F=far-fleld station. bpj1 measurements in mm, indicates no data. Platform Species Stationa Number Collected Mean Size Range Standard Sizeb High Low Deviation MAI-686 S. empusa N 50 113.8 142 82 11.7 F 50 115.0 135 55 14.0 MU-A85 S. empusa N 13 109.8 133 48 22.4 F 11 111.3 128 85 15.7 MU-A85 A. ctrtguiatus N 7 15.7 25 10 15.7 F 9 15.3 21 9 15.3 MU-A85 A, papyraceum N 50 46.3 66 22 11.5 F 50 35.6 57 25 7.7 MU-A85 P. olblda N 18 52.9 64 41 7.1 F 50 52.2 69 40 6.8 Hl-A389 Hermit crabs N 22 11.5 23 7 11.5 F 24 12.9 23 7 4.6 HI-A389 S. empusa N 25 111.5 167 75 24.6 F 7 143.0 164 100 20.6 Hl-A389 A. clnguiatus N 5 12.2 22 3 7.4 F 5 15.6 18 13 2.3
Table 5.43. Summary of the numbers of Individuals collected and size range for overlapping species at each plat

aNnefleld station; F=far-field station. measurements in mm, indicates no data. cSpecles listed at bottom of table were not sexed based on external characteristics fri the field so the results inclu

males and females. Number Collected Mean Sizeb Size Range Male Female 

D

Platform Species Statlona Male Female Male Female High Low High Low MalMAI-686 P. aztecus

N 13 9 41.1 39.6 56 33 48 31 6.0 F 24 28 42.5 44.7 57 35 61 35 5.9 

MAI-686 T. s&nIiIs

N 71 1210 18.2 29.1 24 11 39 12 2.8 

F 318 1228 16.2 26.8 31 10 39 9 3.4 

MAI-686 C. slmffls

N 3 4 44.7 46.5 50 38 52 38 6.1 F 19 9 59.2 47.3 83 41 67 38 13.2 

MAI-686 P. gtbbesli

N 0 9 - 46.2 - 59 30 8.3 F 0 57 - 42.5 - 84 30 10.4 

MAI-686 S. empusa

N 67 50 101.7 101.4 125 60 135 64 12.1 F 56 55 93.5 95.8 113 57 126 56 12.6 

MAI-686 S. chydaea

N 4 5 67.8 73.6 78 63 78 71 6.9 F 19 47 66.9 70.4 78 56 93 50 5.9 

MU-A85 P. aztecus

N 10 31 52.2 61.0 57 46 73 54 2.9 F 22 36 54.0 61.9 63 46 80 54 3.8 

MU-A85 T. slmlUs

N 2 7 17.5 25.1 18 17 28 20 0.7 F 3 19 16.0 23.0 16 16 31 18 0.0 

MU-A85 S. atlantidts

N 33 56 14.1 20.2 20 8 30 6 2.3 F' 35 57 14.6 20.7 25 10 30 10 2.5 

MU-A85 P. sptricarpus

N 0 91 - 33.9 - 46 20 F' 0 18 - 40.7 - - 61 44 - 

MU-A85 S. chyi*wa

N 22 29 84.1 90.4 112 13 118 52 24.5 F 0 1 - 127.0 - - 127 127 - 

HI-A389 S. atlantldts

N 6 8 15.3 23.1 17 14 33 18 1.5 F 33 39 16.2 22.8 19 13 32 12 1.6 

HI-A389 P. sfrnlUs

N 7 89 13.0 21.0 14 11 31 9 1.2 F 8 65 13.3 21.3 18 9 30 8 3.1 

HI-A389 P. sptnicarpus

N 0 16 - 50.8 - 61 45 F 0 1 - 31.0 - - 31 31 HI-A389 A. alexandriaN 1 0 24.0 - 24 24 - - F 7 3 30.0 26.0 40 18 30 20 8.2 

HI-A389 Hermit crabs

N 2 4 10.0 6.3 11 9 8 5 1.4 F 6 4 11.8 9.8 16 9 13 6 2.9 

HI-A389 S. chydna

N 1 4 118.0 107.3 118 118 110 102 F 1 1 105.0 83.0 105 105 83 83 - HI-A389 S. edentataN 2 0 98.5 - 121 76 - - 31.8F 3 1 119.3 137.0 130 108 137 137 11.0 Number Mean Size Range Standard Platform SpeclesC Station Collected Size High Low Deviation MAI-686 A. dupilcatus

N 16 8.4 12 5 2.4F 351 6.6 17 3 1.8 MU-A85 A. papyracewnN 27 45.6 65 29 8.5F 149 50.6 65 26 7.1
aMmale; F=Female: lnt.=intermedlate, immature stage for crab species. bN=nearfleld station; F=far-fleld station. CJJl measurements are in mm, '- indicates no data. dSpecies listed at end of table were not sexed through external observation and therefore contain both males and females. Table 5.44. Summary of the number of individuals collected for overlapping species at each platform d

Platform Species Number Collecteda Mean Size Size Rangec 

Male Female Int. 

Stationb

M

F Int.

M

F mt. High Low High Low High Low

MAI-686 P. uztecus

N 5 4 - 35.8 36.0 40 30 40 32 - F 51 63 - 33.9 36.3 - 41 25 46 23 - - 

MAI-686 T. strnths

N 20 72 - 20.1 28.3 - 22 18 34 20 - - F 28 301 20.4 28.4 - 22 16 38 16 - - 

MAI-686 C. simiUs

N 200 12 165 44.9 62.6 40.1 93 29 75 52 67 22 F 77 28 30 59.2 66.3 41.6 107 30 78 53 64 31 

MA-686 P. gtbbesu

N 0 35 10 40.6 35.2 - - 57 30 45 27 F 6 23 10 48.5 43.6 42.6 57 41 52 30 52 28 

MAI-686 S. empusa N 17 33 - 91.8 92.8 - 100 78 127 79 - - 

F 41 30 - 95.4 99.3 - 122 100 192 72 - - 

MAI-686 S. chydaea

N 0 5 - 79.6 - - 89 73 - F 0 7 82.4 - - 90 72 - - 

MU-A85 P. aztecus

N 0 9 - - 70.6 - - 79 65 - F 8 17 - 57.0 71.1 - 60 52 80 64 - - 

MU-ASS S. atlantidis

N 63 52 - 15.7 24.4 - 19 11 31 14 - F 44 92 - 17.0 26.1 - 20 14 35 15 - - 

MU-A85 P. spinicarpus

N 0 4 12 - 45.8 41.0 - - 50 40 53 32 F 0 40 53 - 48.0 48.5 - - 56 40 60 25 

MU-A85 S. chydaea

N 13 11 - 94.8 87.7 - 131 54 132 50 - - F 1 3 - 90.0 111.7 - 90 90 133 89 - 

Hl-A389 S. allantidis

N 24 41 - 15.1 23.9 - 19 10 35 15 - F 7 15 - 16.9 25.5 - 20 14 35 18 

HI-A389 M. quinquespinosa

N 8 3 - 19.0 20.7 - 25 16 26 18 - - F 6 4 - 23.0 25.0 - 28 16 36 15 - 

Hl-A389 A. alexandria

N 7 2 - 29.3 34.0 38 22 36 32 F 11 6 - 21.3 29.7 - 44 12 36 13 - 

H1-A389 Hennit crabs

N 4 0 - 12.8 - - 18 10 - - F 2 1 - 18.5 14.0 - 22 15 14 14 - 

Number Mean Size Range Standard Platform SpeciesCi Station Collected Size High Low Deviation MAI-686 A. dupUcatus

N 129 9.8 15 6 9.8F 128 9.3 16 7 1.9 MU-ABS A. cingulatusN 8 12.0 26 6 7.6F 44 13.9 23 7 3.5 MU-A85 A. papyraceumN 53 30.2 66 21 8.5F 117 45.7 67 20 13.7 H1-A389 A. clngulatus

N 6 16.5 22 10 4.6

F 14 12.0 17 9 2.5
measured on Cruise 1 were not separated by sex, so the results include both

males and females. Three generalities were apparent from these data. First,

for several species, a difference in mean size of individuals existed between

the Near and Far stations. Second, for several species, individuals of one sex

had a different mean size than individuals of the other sex. Third, for

several species, more individuals of one sex were collected as compared to

the other sex.

Size frequency histograms were constructed for each species from the

field measurements of individuals collected at both the Near and Farstations

at each platform. Three examples of size-frequency distributions are

presented as histograms in Figures 5.119 to 5.121. Examples show that A.

duplicatus at MAI-686 were larger at the Near station, whereas individual S.

atlantidis at HI-A389 and A. pap yraceum at MU-A85 were larger at the Far

station. A more detailed statistical analysis is provided in Section 6.4.

5.6.3 Histopathology

Little information exists in the periodical literature on the normal

histology or bistopathology of many of the offshore species collected. P.

aztecus is an important exception in that information on common parasites

and pathologies was available, due mostly to its commercial value

(Murchelano and MacLean 1990). Common parasites observed in shrimp

tissues were nematodes, cestodes, and a virus cf. l3aculovirus and common

pathologies included gut inflammations and cysts in muscle or connective

tissue (see also Overstreet 1978). Crabs were also parasitized by nematodes

and had maladies of the gills such as malformed gill filaments and gill

filaments with inclusive bodies. Starfish were often highly parasitized by

nematodes. Scallops were also parasitized by nematodes, and a few

individuals had unidentified encysted masses in the mantle tissue. Parasites

and pathologies were not recognized in the species of mantis shrimp

collected.

Prevalence and intensity of infection were calculated for each of the

main categories of parasites and pathologies for each species at both the

Near and Far stations for each platform. P. aztecus was consistently the

most highly parasitized species at any of the platforms (Table 5.45). Nearly

every individual of P. aztecus analyzed had at least one of the major parasites

or pathologies present. Prevalence of nematodes in P. aztecus ranged from

5-188
S 

/4 

f 
FIgure 5.120. SIze frequency distributions for Astropecten dupUcatus at M
inii c j g S1P11UD1D viaouao ioj suonqjqsjp Aounboij 

1J
Pathology/Parasitea

Inflamed Baculoap = Preva1ence (% of individuals with the parasite or pathology); I = Intensity (average number of occurrences of parasite or pathology in those individuals that exhibit the parasite or pathology; indicates no data).

Cruise Site/Station

Nematode Cestode Gut virus Cyst

P I P I P I p i P

1 MAI-686 Near 40 6.0 40 1.0 40 1.0 0 0

Far 80 6.8 0 0 0 0 40 2.5

1 MU-A85 Near 80 3.3 o o 20 2.0 20 45 20 1.0

Far 80 2.3 20 2.0 80 1.3 0 0 40 1.0

1 MAI-622 Near 100 2.2 19 1.0 60 2.0

Far 60 1.7 40 1.0 0 0

2 MAI-686 Near 70 3.3 30 2.0 20 10 30 1.0

Far 80 8.4 40 1.3 40 1.5 20 1.0

2 MU-A85 Near 100 5.7 10 1.0 20 1.0 50 24 30 1.3

Far 70 6.1 10 1.0 10 3.0 60 121 60 2.2

3 MAI-686 Near 50 3.4 20 1.0 30 1.0 0 0

Far 60 6.2 30 1.0 11 3.0 11 2.0

3 MU-A85 Near 80 28 10 1.0 20 1.0

Far 100 26 11 3.0 11 2.0

4 MAI-686 Near 60 6.2 40 1.3 20 1.5

Far 80 1.8 20 1.0 30 2.3

4 MU-A85 Near 100 19 0 0 11 1.0 - 11 1.0

Far 80 13 10 1.0 10 1.0 - 0 0

Trachypenacus similis

1 MAI-686 Near 40 1.0 - - 0 0 0 0

Far 20 1.0 - - 20 1.0 20 38

1 MAI-622 Near 20 1.0 20 1.0 0 0

Far 25 1.0 0 0 25 1.0

2 MAI-686 Near 50 2.2 30 1.0 0 0 0 0 20 1.0

Far 60 3.2 10 1.0 30 1.3 10 4.0 20 1.0

2 MU-A85 Near 100 4.0 0 0 - Far 40 1.8 10 1.0 - 3 MAI-686 Near 20 1.0 20 1.0 10 1.0

Far 10 3.0 0 0 10 1.0

3 MIJ-A85 Near - 0 0 0 0

Far - - 10 2.0 10 2.0

4 MA[-686 Near 20 1.0 60 1.3 20 1.0

Far 10 1.0 20 1.0 0 0

Table 5.45. Prevalence and intensity of each parasite and pathology in the

shrimp species collected during all four cruises.
Table 5.45. (Cont.)

5-193

Pathology/Parasitea

ap = Prevalence (% of individuals with the parasite or pathology); I Intensity (average number of occurrences of parasite or pathology in those individuals that exhibit the parasite or pathology; "-" indicates no data).

40 % to 100 %. The highest mean intensities were 26 (Far) and 28 (Near)

nematodes per individual at MU-A85 on Cruise 3. Specific individuals

collected from MU-A85 on Cruise 3 were parasitized at the rate of 131 and

146 nematodes. respectively. The other common parasites and pathologies

were present but in much lower prevalences and intensities. At least one

epizootic of cf. Baculovirus was sampled in P. aztecus at MU-A85 (Cruise 2).

This epizootic occurred at both the Near and Far stations, suggesting a widespread viral outbreak in the population. Viruses such as cf. Baculovirus

(Murchelano and MacLean 1990) can cause mass mortalities in populations

contained in mariculture conditions. Cysts and gut inflammations were

present in the population in low to medium prevalences. Intensities were

also typically low, usually averaging only 1 to 3 occurrences per individual.

T. similis and S. atlantidis were also frequently parasitized by nematodes,

however, intensities were typically low. High prevalences of cf. Baculo virus

were also observed in T. simtlts at MAT-686 during both Cruises 1 and 2.

Cruise Site/Station

Nematode Cestode

Inflamed DaculoGut vtrus Cyst

P I P I P P I p

Solenocera atlantidis

2 MU-A55 Near 20 2.0 - - - Far 30 1.0 - - - 2 HI-A389 Near 20 1.0 10 1.0 - Far 0 0 0 0 - 3 MU-A85 Near 30 2.3 - - 20 1.0 - Far 0 0 - - 0 0 - 3 HI-A389 Near 10 1.0 0 0

Far 10 1.0 10 1.0 - 4 MU-A85 Near 30 1.7 - - - Far 50 3.2 - - - 4 HI-A389 Near 30 1.3 10 1.0 0 0

Far 0 0 20 1.0 10 1.0

Parapenaeus sirnilis

3 HI-A389Near 0 0 0 0

Far 0 0 10 1.0
Unlike the epizootic noted in P. aztecus, cf. Baculovirus was only found at the

Far stations, suggesting that the Near and Far stations were separate

populations.

In general. parasites and pathologies occurred infrequently in crabs

(Table 5.46).. For example, the prevalence of nematode infection was never

greater than 40 % and many stations had no individuals parasitized by

nematodes. In all species of crabs gill maladies were more common than

parasitism by nematodes. Prevalence of malformed gill filaments reached

highs of 67 % at Near stations and 60 % at Far stations, and the prevalence

of gill filaments with inclusive bodies ranged from 60 % at Near stations to

30 % at Far stations.

Nematodes were the only parasite or pathology recognized in species

of starfish (Table 5.47). A. cingulatus had prevalences as high as 60 % with

intensities as high as 5 per individual. A. duplicatus collected from MAI-686

were more highly parasitized. Prevalence was never less than 90 % on

either Cruise 3 or 4. In both cases, prevalence was 100 % at the Far station.

Intensities were also high, with means as high as 13.6 nematodes per

individual, at the Far station. Scallops were also parasitized by nematodes

but prevalence and intensity were typically low at both the Near and Far

stations.

5.6.4 Reproductive Effort

Little is known about the reproductive effort of most continental shelf

invertebrates. Shrimp species such as P. aztecus and P. settferus and the

blue crab, Callinectes sapidus, have been well studied because of their

commercial value (Chamberlain and Lawrence 1983; King 1948; Hard

1942). Several methods were utilized to assess differences in the

reproductive effort of invertebrate species living near and far from

platforms. Differences in male-to-female ratios; percent gravid females

(crab species); and stage of reproductive development determined by visual

inspection, histological analysis, and immunological probe were used as

indicators of possible sublethal effects of exposure to chemical contaminants

or other platform related factors.
Table 5.46. Prevalence and intensity of parasitism and pathologies in the

crab species collected on all four cruises.

ap=prevalence (% of individuals with the parasite or pathology); Iintensity (average number of occurrences of parasite or pathology in those individuals that exhibit the parasite or

pathology); "-" indicates no data.

Parasite/Patholoya

Malformed Gill

gill filament

Nematode filaments with body

Cruise Site/Station Species P I P I P I

1 MAI-686 Near Callinectes similis - - 0 0 0 0

Far - - 40 3.0 20 2.0

GA-288 Near CalUnectes similis 0 0 - - - Far 33 1.0 - - - 2 MAI-686 Near CalUnectes similis 10 1.0 40 3.0 - Far 0 0 20 2.5 - 2 MU-A85 Near Calltnectes similis - - 67 1.0 - Far - - 20 2.5 - 3 MAI-686 Near Callinectes similis - - 14 1.0 14 1.0

Far - - 10 3.0 10 1.0

4 MAI-686 Near Callinectes simllis - - 40 3.3 20 2.0

Far - - 40 2.0 30 1.0

1 MU-A85 Near Portunus spintcarpus 40 1.0 20 2.0 60 2.0

Far 0 0 0 0 0 0

2 MU-A85 Near Portunus spinicarpus 40 2.3 0 0 10 1.0

Far 40 3.3 10 1.0 0 0

3 MU-A85 Near Portunus spinicarpus - - 10 1.0 10 1.0

Far - - 0 0 0 0

4 MU-A85 Near Portunus spinicarpus 20 2.5 0 0 30 1.7

Far 20 1.5 0 0 0 0

1 MAI-686 Near Portunus gibbesii 20 1.0 0 0 - Far 0 0 20 3.0 - 1 MAI-622 Near Portunus gibbesii - - 20 1.0 20 1.0

Far - - 0 0 20 2.0

3 MA1-686 Near Portunus gibbestt - - 25 3.0 13 1.0

Far - - 60 1.5 20 2.0

4 MAI-686 Near Portunus gfbbesii 10 1.0 30 2.3 0 0

Far 0 0 10 3.0 10 1.0

2 HI-A389 Near Hermit crabs 9 1.0 - - - Far 23 3.0 - - - 3 HI-A389 Near Hermit crabs 33 1.5 - - - Far 40 2.0 - - 2 HI-A389 Near M. quinquespinosa 0 0 - 0 0

Far 10 8.0 - 10 1.0

4 HI-A389 Near M. quinquespinosa 11 2.0 - - - Far 11 2.0 -
aprevalence is the percent of individuals infected with a particular parasite or pathology.

bintensityis the average number of occurrences of the parasite or pathology in those

individuals exhibiting the parasite or pathology.

5.6.5 Male-to-Female Ratios and Percent Gravid Females

Immediately after collection, individuals of target species were sexed

by visual inspection. Only species with obvious external sexual

characteristics, such as shrimp (presence of thyleca or claspers), crabs

(shape of ventral carapace), and stomatopods (presence of claspers) were

sexed in this way. For species of shrimp, individuals collected at both the

Near and Far stations were overwhelmingly female, with male:female ratios

as low as 1:17 (T. simitis, MAT-686, far-field, Table 5.48). More male than

female crabs and stomatopods were typically collected, particularly at HIA389, but the number of males was not overwhelming compared to the

number of females. The fact that the majority of shrimp collected were

female may result from the females being larger, and therefore females may

be retained more efficiently by the trawl nets. Brusher et al. (1972)

collected female T. similis in numbers as high as 50 times that of males and

also suggested that males were not easily retained in the net because of their

small size. Alternatively, females may simply outnumber males in the natural

populations.

5-196

Table 5.47. Prevalence and intensity of parasitism and pathologies of starfish and scallop tissues collected on all four GOOMEX

cruises.

Nematodes

Cruise Site Station Species Prevalence8- Intensity1

2 MU-A85 Near Astropecten ctrtgulatus 0 0

Far 11 5.0

4 MU-A85 Near Astropecten cingutatus 60 1

Far 30 4

4 HI-A389 Near Astropectert cingulatus 0 0

Far 10 2

3 MAI-686 Near Astropecten .duplicatus 90 3

Far 100 8

4 MAI-686 Near Astropecten duplicatus 90 7

Far 100 14

2 MU-A85 Near Amusium pap yraceurn 10 3

Far 30 3

4 MU-A85 Near Amusium papyraceum 10 3

Far 20 3
Table 5.48. Male:Female ratios for species collected at Near and Far stations. Only species with obvious external sexual characteristics were included in this analysis.

Male:Femalea

Platform Species Near Far

a -" indicates no data

Cruise 1

Not measured

Cruise 2

5-197

MAI-686 T. stmills 2:31 4:84

P. aztecus 6:15 21:29

C. similis 127:22 1:73

MU-A85 T. simiUs 0:3 2:41

P. aztecus 23:27 16:34

S. atlantidis 18:29 14:39

C. simtUs 10:0 9:0

P. spinicarpus 8:42 1 :73

HI-A389 S. atlantidis 22: 10 3:3

M. quinquespinosa 1:2 7:7

A. alexandria 2:3 13:8

P. spinicaipus 15:17 0:2

Cruise 3

MAI-686 T. similis 35:586 339: 1342

P. aztecus 4:3 23:25

C. simiUs 3:4 3:2

P. gibbesti 0:9 0:53

S. empusa 67: 50 1: 1

S. chydaea 4:5 9:23

MU-A85 T. similis 2:7 1:3

P.aztecus 10:31 11:18

& atlantidis 33:56 33:57

P. sptnicarpus 0:91 0: 18

HI-A389 S. atlantkEs 3:4 11: 13

P. similis 7:89 8:65

Hermitcrabs 1:2 3:2

Cruise 4

MAI-686 T. strntUs 5: 18 14: 151

P.aztecus 5:4 51:63

P. gibbesti 13:32 16:25

S.chydaea 13:16 1:11

S.empusa 17:33 41:30

MU-A85 P. aztecus 0:9 8:17

S. atlantidis 31:26 11:23

P. spinicarpus 3:1 57:39

S. chydaea 13:11 1:3

HI-A389 S. atlantidis 23:41 7: 15

P. spinicarpus 1:4 - M. quinquespinosa 8:3 3:2

A. aleKandria 7:2 11:6

Flerrnitcrabs 4:0 2:1
Differences in the percentage of gravid female crabs were determined for

each species collected at both the Near and Far stations (Table 549). A

gravid female crab was one collected 'in sponge', that is, with a visible egg

sac. When a difference in the percent gravid females existed between the

Near and Far station, more gravid females were collected more frequently at

the Far station, however this difference was not statistically significant.

Each egg mass collected from gravid females was immediately frozen in

liquid nitrogen. In the laboratory, the egg masses were weighed, lyophilized

and reweighed. The average wet weight (g) of the egg sacs for each species

is presented in Table 5.49. Where differences in egg sac weights exist

between the Near and Far stations, the egg sacs were heaviest at the Far

station regardless of species or platform.

Differences in weight could result from differences in fecundity, egg

size, or time since spawning. Generally, larger individuals should have

larger egg sacs (Somers 1991; Wenner et aL 1991). A good relationship

exists between the wet weight of egg sacs and the body size of individuals.

An example of the relationship between the wet weight of the egg sac and

body length for C. süniUs collected from MAT-686 is shown in Figure 5.122.

Because of this relationship, a gonadal-somatic index (GSI) was calculated

using the relationship between egg sac dry weight and body dry weight and

then, body weight-specific changes in egg sac weight were examined. GSI

was calculated for individuals collected during the last two cruises (Table

5.50).

Changes in egg composition have been related to egg quality and,

ultimately, juvenile survivorship. As eggs mature, the chemical composition

also changes. Older eggs may have less protein because the yolk protein is

being metabolized, for instance. Time-dependent changes in egg

composition are unknown for these portunid crabs, so the two alternatives

cannot be distinguished. Nevertheless, egg sacs collected from gravid

females were analyzed for percent protein and percent water. In the three

cases where overlap between the Near and Far station existed for a species,

the site with the highest GSI also had the lowest percent protein in the egg

sacs. Higher GSI indicates that the egg mass was heavier in comparison to

the body weight of the individual. Decreased protein could indicate

differences in maturity, but then, a consistent relationship with GSI might

not be expected.

5-198
Table 5.49. The percent of female crabs collected that were gravid and

average wet weight (g) of the egg sacs at each site for each

cruise.

MAI-686 MU-A85 HI-A389

Species Near Far Near Far Near Far

C. simiUs

P. gibbesil

P. spirticarpus

A. alexandria

hermit crabs

Cruise 1

C. stmttis 0.0 4.0 NC 22.0

2.05 - 4.48

P. gibbesil 60.0 38.0 - - 0.88 0.60

P. spinicarpus 0.0 13.0

0.78

Cruise 2

C. simitis 13.0 13.0 0.0 0.0

1.66 3.58 - - - P. gibbesil 12.0 NC

0.93 - P. spinicarpus - - 7.0 1.0 0.0 0.0

- - 0.62 0.69

Cruise 3

C. simitis 0.0 0.0 - - - P. gibbesil 11.0 2.0 - - 1.20 0.45 - - P. spinicarpus - - 1.0 6.0 44.0 0.0

0.40 1.14 1.43

A. alexandria - - - 0.0 0.0

hermit crabs - - - 0.0 20.0

Cruise 4

Site'-

0.0 1.0 20.0 NC

- - - 0.75 2.40 - - - - - 0.0 6.0

- - - 0.0 0.0

no females of that species were collected. Zeroes indicate that females were collected at

that station but none were gravid; "-" indicates no data)

5-199

1.0 8.0

3.63 4.45

11.0 25.0

0.94 0.97
Figure 5.122. Body wet weight versus egg wet weight of CalUnectes simi
Table 5.50. Egg protein, percent water and gonadal somatic index (GSI) for egg sa

gravid female crabs. adata from single individuals, "-" indicates no data. Cruise Platform Site Species Average carapace width (mm)a % Protein in Eggsa % Water in Eggsa 

egg 

body 

1 MAI-686 Near P. gthbesll 36.6 30.9 HI-A389 Near P. sptntcarpus 30.4 25.7 3 MAI-686 Far P. gtbbestt 43.7 28.9 32.9 0

MU-A85 Near P. sptn(carpus 379* 38.9* 349* 0MU-A85 Far P. sptnicarpus 44,4* 19.0* 22.2* 0H1-A389 Near P. sptriicarpus 48.9 29.7 24.0 0

4 MAI-686 Near C. stmitis 60.7 23,0 25.7 0

MAI-686 Far C. stmllt.s 64.1 27.1 23,0 0MAI-686 Near P. yibbesit 41.7 25.5 25.4 0MAI-686 Far P. gibbesit 42.8 34.2 25.8 0

MU-A85 Far P. spnicarpus 4 1.4* 36.9* 18.0* 0HL-A389 Near P. sptncarpus 56.8* 21.0* 30.9* 0
5.6.6 Stage of Reproductive Development

For most species collected, stage of reproductive development was

evaluated by two methods; visual inspection and histological analysis. In

portunid crabs, an immunological probe was also used. The three methods

employed all have unique benefits and complement one another. Visual

inspection can be done shipboard, is rapid, provides inimediate results, and

allows a large number of individuals to be analyzed. However, stage

identification is less precise because fewer stages can be discriminated.

Histological examination provides more detail because more stages can be

discriminated and also allows a relationship with parasitism and pathology to

be determined. However, quantification is difficult and only a few

individuals can be assayed. The immunological probe provides quantification

and a larger number of individuals can be analyzed using a subsample of the

homogenate prepared for chemical analyses, but histopathology cannot be

assessed. Hence, all three approaches provide useful, albeit different, views

of reproductive status.

5.6.6.1 Visual Inspection

The reproductive development stage was determined through visual

inspection and gross dissection for all females of the shrimp and crab

species. The results of determination of the stage of reproductive

development for Cruises 2 through 4 is summarized in Table 5.51. For most

of the species at most of the platforms, females were early in their

reproductive development. T. strnilis on Cruises 2 and 4 at MAI-686 had

individuals that were ripe and nearly ready to spawn. These results agree

with the increased frequency of ripe T. simiUs collected during June, July,

and September by Brusher et al. (1972), suggesting a mid-summer to early

fall spawning season for T. simitis in the northwest Gull of Mexico. C. sirnilis

and P. gibbesti, also collected at MAI-686 (Cruise 4), were also mature and

preparing to spawn. These results agree with the relatively high percentage

of gravid females at this site (Table 5.49).

5.6.6.2 Histological Analysis

The reproductive development stage was determined through

histological examination for both males and females of target species and the
Table 5.51. Results of visual inspection and gross dissection for the

determination of stage of reproductive development in females of shrimp and crab species collected during Cruises 2, 3, and

4.

Cruise 2

P.aztecus 1 4 16 9 18

2 3 7 11 8

3 0 0 1 1

4 0 0 1 0

5 0 0 0 0

T. similis 1 15 47 8 1

2 1 11 14 2 - - 3 3 12 11 0 - - 4 2 3 0 0 - - 5 0 0 0 0 - - S. atlantidis 1 - 3 26 7 1

2 - - 2 8 3 2

3 - 0 2 0 0

4 - - 0 0 0 0

5 - - 0 0 0 0

C.similis 1 1 2 - - - - 2 3 1 - - - - 3 0 1 - - - - 4 0 0 - - - - 5 0 2 - - - - P. spinicarpus 1 - - 27 18 - - 2 - - 7 3 - - 3 - - 0 0 - - 4 - - 0 0 - - 5 - - 0 0 - - Cruise 3

P. aztecus 1 7 15 23 25 - - 2 2 11 8 10 - - 3 0 0 0 0 - 4 0 0 0 0 - - 5 0 0 0 0 - - T. simiUs 1 94 19 4 18 - - 2 26 31 1 1 - 3 0 0 2 0 - - 4 0 0 0 0 - 5 0 0 0 0 - aNepc rankings of the reproductive stage are described in the text; "-" Indicates no data).

5-203

MAI-686 MU-A85 HL-A389

Frequency Frequency Frequency

Species Stagea Near Far Near Far Near Far
Table 5.51. (Cont.)

S. atlantidis 1 30 35 8 25

2 - - 22 16 0 10

3 - 3 2 0 4

4 - - 0 3 0 0

5 - - 0 0 0 0

P. stmilis 1 - - - 43 23

2 - - - - 32 25

3 - - - 12 12

4 - - - 1 4

5 - - - - 0 0

C.stmiLis 1 0 0

2 3 6

3 1 3

4 0 0

5 0 0

P. gibbesii 1 0 0

2 4 28

3 4 27

4 0 0

5 0 0

Cruise 4

P. aztecus

T. similis

C.similis 1 1 1

2 4 5

3 2 4

4 0 0

5 7 18

1 3 38 1 3

2 1 25 2 10

3 0 0 6 4

4 0 0 0 0

5 0 0 0 0

1 32 157 - 2 25 105 - 3 9 29

4 6 9

5 0 0 - S. atlantidis 1 - - 23 36 29 8

2 - 18 39 9 3

3 - - 10 17 3 4

4 - - 1 0 0 0

5 - - 0 0 0 0

aNumepc rankings of the reproductive stage are described in the text; -" indicates no data).

MAI-686 MU-A85 m-A389

Frequency Frequency Frequency

Species Stagea Near Far Near Far Near Far
Table 5.51. (Cont.)

aNei.ic rankings of the reproductive stage are described in the text; '-" Indicates no data).

results are summarized in Tables 5.52 to 5.54. On Cruise 1, only 5

individuals were histologically analyzed. On subsequent cruises, 10

individuals were analyzed however an effort was made to examine 5 females

and 5 males. Therefore, the number of individuals analyzed histologically

was much smaller than that analyzed by visual inspection. The results of

histological analysis indicated that most individuals were in the middle

stages of their reproductive development. These results typically assigned a

higher stage to reproductive development than the results of visual

inspection of individuals obtained at the same platform and station. Visual

inspection is a three-dimensional determination of gonad size and stage,

based on color (Chamberlain and Lawrence 1983), whereas histological

examination examines the size and maturity of individual eggs in a

microscopic field but does not address the volumetric size of the gonad.

Since most of these species had eggs and sperm of different maturities

present in the gonad at the same time, and since the volumetric size of the

gonad and the developmental stage of the gametes were not necessarily

correlated if the same gonadal sections are examined visually and

histologically as was done in this study, the results of the two analyses

provided different views of the stage of reproductive development.

MAI-686 MU-A85 m-A389

Frequency Frequency Frequency

Species Stage1 Near Far Near Far Near Far

P.gibbesit 1 5 2

2 10 7

3 6 5

4 0 0

5 11 10

P. spinicarpus 1 - - 2 13

2 - - 1 19

3 - - 1 7

4 - - 0 0

5 - - 0 0
Table 5.52. Sex and stage of reproductive development for overlapping

species collected at each platform for histological examination

during Cruise 2.

P. aztecus 1 0001 0 0 0 0

2 8242 1 0 0 0

3 0021 1 2 2 2

4 0000 3 3 2 2

5 0000 0 0 2 0

T. simtlis 1 0 0 0 0 0 0 0 0

2 4050 0 0 1 0

3 2040 0 0 0 0

4 4010 3 0 7 2

5 0000 0 0 0 0

C.similis 1 1 0 0 0 0 0 0 9

2 121 1 0 1 0 0

3 3326 0 2 0 0

4 0000 0 0 0 0

5 0 0 0

P.spinicw-pus 1 - - 0 0 0 0

2 - - 1 3 3 4

3 - - - 1 5 3 0

4 - - - 0 0 0 0

5 - - 0 0 0 0

S. atlantidis 1 - - - 0 0 0 0 0 0 0 0

2 - - 0 2 0 05500

3 - - 3 3 5 40003

4 - - - 2 0 1 00010

5 - - - 0 0 0 00020

M. quinquespinosa 1 - - - - - - 1 0 0 0

2 - - - - - - 1 134

3 - - - -0021

4 - - - - -0000

5

A.a1ecandria 1 - - 0 0 1 0

2 - - - - -2201

3 - - - - - 0035

4 - - - - - -0000

5 - - - Hermit crab 1 - - - - 0 2 0 4

2 - - - -1123

3 - - - - - 1430

4 - - - -0201

5 - - -0000

aMme; F=female; stages of reproductive development are defined in the laboratory methods

section; "-" indicates no data.

MAI-686 MIJ-A85 ffl-A389

Near Far Near Far Near Far

Species StageaFMFM F M F MF MFM
Table 5.52. (Cont.)

5-207

aMmale; F=female; stages of reproductive development are defIned in the laboratory methods

section; "-a indicates no data.

Species

MAI-686 MU-A85 ffl-A389

Near Far Near Far Near Far

stagea F M F M F M F M F M F M

A. cirigulatus

S.empusa

S. chyrlaea

S. edentata

A. papyraceurn

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

5

6

7

8

-

-

-0

-

-

-

-

--

-

-

-

-

-

-

-

0121

-

-

-0

-

-

-

-

--

-

-

-

-

-

-

-

4525 0000

-

-

-

-0

-

-

-

-

-

-

-

-

-

-

-

--

-

--

-0

-

-

-

--

-

-

-

-

-

-

-

-

-.-

0

1

0

0

0

2

1

0

-

-Lf

4

2

0

0

0

6

1

0

-

-

-

2

0

0

0

0

5

1

1

-

-

- rnLf

0

0

6

0

2

2

0

0

6

0

1

2

0

-

2

0

10000 00000

-2013 -4141 -0010

3

0

2

0

3

0

0

0

3

4

3

1

0

0
Table 5.53. Sex and stage of reproductive development for overlapping

species collected at each platform for histological examination during Cruise 3.

T. stmtUs

MAI-686 MU-A85 HI-A389

Near Far Near Far Near Far StageaF M FM F MF M FM FM

1 0000 0 0 0 0

2 2514 0 0 1 3

3 2031 2 4 3 2

4 0010 3 1 1 0

5 0000 0 0 0 0

1 0 0 0

2 0423 4 1 2 2

3 2132 0 1 4 1

4 3000 1 0 1 0

5 0000 0 0 0 0

C.sImiUs 1 3 0 1 1

2 1332

3 0012

4 0000

5

P. sptntcai-pus 1 - - - 2 0 0 0

2 - - - 3 4 1 3

3 - - - 0 1 0 6

4 - - - 0 0 0 0

5 - - - 0 0 0 0

P.gibbesii 1 0 0 0 0

2 4316

3 1003

4 0000

5

Hermitcrab 1 - - - - 2 - - - - - 3 - - - - - 4 - - - - - 5 - - - - - -

5-208

S. atlantidis 1 - - - 0 0 0 0 0 0 0 0

2 - - - 1 2 1 53403

3 - - - 4 3 4 02152

4 - - - 0 0 0 00000

5 - - - 0 0 0 00000

P. sirniiis 1 - - - - 0 0 0 0

2 - - - - 141 1

3 - - - -4132

4 - - - - -0030

5 - - - - -0000

1002 2223 1031 0000 0000

aMma1e; F=female; stages of reproductive development are defined in laboratory methods

section; '-" indicates no data.

Species

P. aztecus
Table 5.53. (Cont.)

5-209

aMmaie; F=female; stages of reproductive development are defined in laboratory methods

section; "-" indicates no data.

Species

MAI-686 MU-A85 m-A389

Near Far Near Far Near Far

Stagea F M F M F M F M F M F M

A.duplicatus 1 0 1 0 0

2 3230

3 3143

4 0000

S.empusa 1 0 0 0 0

2 0504 - - - - - 3 001 1

4 5040

S. chycLaea 1 - - - - 0 0 0 0 - 2 - - 1 4 0 5-

3 - - - - 2 0 1 0-

4 - - - - 0 0 4 0

rnJZ rnLf

A. papyraceurn 1 - - - - 2 0 - 2 - - - - 6 5 - 3 - - - - 1 4 - 4 - - - 1 1 - 5 - - - - 0 0 - 6 - - 0 0 - 7 - - - - 0 0 - 8 - - - - 0 0 -
Table 5.54. Sex and stage of reproductive development for overlapping

species collected at each platform for histological examination during Cruise 4.

P. aztecus

T. stmtlis

& atlantidis

P. similis

1 0000 0 0 0 0

2 2514 0 0 1 3

3 2031 2 4 3 2

4 0010 3 1 1 0

5 0000 0 0 0 0

1 0 0 0

2 0423 4 1 2 2

3 2132 0 1 4 1

4 3000 1 0 1 0

5 0000 0 0 0 0

1 - - - 0 0 0 0

2 - - 1 2 1 5

3 - - - 4 3 4 0

4 - 0 0 0 0

5 - - - 0 0 0 0

5-210

0000 3403 2152 0000 0000 -0000 - 141 1 -4132 -0030 -0000

C. sirnilis 1 3 0 1 1 - - - - - - 2 1332 - - - - - - 3 0012 - - - - - 4 0000 - - 5 - - P. spinlcarpus 1 - - - 2 0 0 0 - - 2 - - 3 4 1 3--

3 - - - 0 1 0 6--

4 - 0 0 0 0--

5 - - 0 0 0 0--

P. gibbesii 1 0 0 0 0 - - - 2 4316 - - - - 3 1003 - - - - 4 0000 - - - - 5 0000 - - - - Hermit crab 1 - - - - - - 1 0 0 2

2 - - - 2223

3 - - - - - 1031

4 - - - - - 0000

5 - - - - - 0000

aMmale; F=female; stages of reproductive development are defined in laboratory methods

section; -" indicates no data.

MAI-686 MU-A85 m-A389

Near Far Near Far Near Far

Species stageaF M FM F M F M F MF M

1

2

3

4

5
Table 5.54. (Cont.)

5-2 11

aM=me; F=female; stages of reproductive development are defined in laboratory methods

section; "-" indicates no data.

Species

MAI-686 MU-A85 HI-A389

Near Far Near Far Near Far stageaFMFM F M F MFMFM

A. duplicatus 1 0100

2 3230

3 3143

4 0000

S. empusa 1 0000

2 0504

3 0011

4 5040

S. chydoi'a 1 0000

2 1415

3 2040

4 0000

S. chydnea 1 - - - - 0 0 o 0--

2 - - - 2 6 5 1 - - 3 - - - - 1 1 1 2- - 4 - - - - 0 0 1 0- - S. edentata 1 - - - - -00 00

2 - -

- - - -20 13

3 - -

- - - -41 41

4 - - -

- - -00 10

rnLf rnLf

A. pap yraceum 1 - - - - 0 0

2 - - - - 0 0

3 - - - - 3 6

4 - - 4 0

5 - 3 2

6 - - - 1 2

7 - - - 0 0

8 - - - - 0 0
5.6.6.3 Immunological Probe

Immunological probes active against egg protein were developed for

the three species of portunid crabs collected during this study; C. similis, P.

sptnicarpus, and P. gibbe sit. With these probes, the quantity of gonadal

protein can be determined for females that are in the midst of their

reproductive cycle; that is, they are not yet in sponge. The probe provides a

measure of total gametic protein present. Comparison of gonadal weight in

animals ready to spawn, as measured by the probe, to the weight of protein

in egg masses collected from gravid females, yielded equivalent results,

indicating that the probe satisfactorily measured total egg protein

concentration in gonadal tissues.

Results of the gonadal protein assays are summarized in Table 5.55. As

these analyses were done on individuals left after histopathological needs

had been met, the number of assays was limited to the larger collections,

most of which took place on Cruises 2 and 4. GSI, gonadal somatic index, is

another measure of the relationship between the amount of egg present (dry

weight) and the weight of the individual. High values of GSI would suggest

an individual with a high gonadal weight compared to its own body weight.

5.7 Megafauna - Demersal Fish

For the various tasks and analyses performed, large numbers of fish

were required. During each cruise, trawl collections were made at Near and

Far sites for each platform site until sufficient biomass was obtained. For all

four cruises a total of 42,884 fish specimens was obtained, representing 52

families and 125 species. The catches by individual cruise were as follows:

Cruise 1-3,500 fish, 38 families and 89 species; Cruise 2-15,411 fish, 45

families and 95 species; Cruise 3-13,607 fish, 29 families and 59 species;

Cruise 4-10,366 fish, 41 families and 90 species. After shipboard

identification, specimens were provided for the various test procedures and

representative specimens were preserved and returned to the laboratory.

Final taxonomic identifications were made, specimens were provided for

stomach food analysis, and voucher specimens were labeled and stored in

the Texas Cooperative Wildlife Museum.

The most abundant species captured during each cruise were as

follows: Cruise 1 -Halieutichthys aculeatus, Pontirius longtspinis, Serranus

5-2 12
a*data from single individual

atrobranchus, Pristipomoides aquilonaris, and Syacium gurttert; Cruise 2-

Saurida brasiliensis, Orthopris tis chrysoptera, Uperteus parvus, Pep rilus

burti, and Syactum gunteri Cruise 3-Sen-anus atrobranchus, Pristipomoides

aquilonaris, Cynoscion areriarius, and Syacium gunteri; Cruise 4-

Pristipomoides aquilonaris, Lagodon rhomboides, Peprilus burti, and

Syactum gunterL

One species of squirrel fish captured during the first cruise at the MUA85 (far) site appears to be a new record for the Gulf of Mexico. This

species, Comiger spinosus, has previously been reported to range along the

Atlantic coast from South Carolina to Brazil as well as the Canary Islands and

off Benin from the west coast of Africa. One problematic species of seabass

was sent to Dr. Carol Baldwin of the Smithsonian Institution and was

identified as Hemanthias Leptus.

5.7.1 Fish Food Analysis

The food of twenty-three (23) species of fish was analyzed and

quantified on a volumetric basis. A complete listing of these species giving

the cruises and stations, is presented in Table 5.56. For the four cruises,

943 stomach contents were analyzed. The number of species and total

number of stomachs (given in parentheses) was as follows: Cruise 1, 19 spp.

(218); Cruise 2, 9 spp. (269); Cruise 3, 10 spp. (230); and Cruise 4, 17 spp.

5-213

Table 5.55. Summary data for immunological probe results for non-gravid

female crabs.

Cruise Platform Site Species Gonadal proteina

(mg/animal)

GSI

egg dxywt igi

body dry wt (g)

2 MU-A85 Near P. spinicarpus 2.498 0.00457

MU-A85 Far 0.863 0.00191

HI-A389 Near 20.139 0.02092

3 MAI-686 Far P. gibbesit 9.136 0.02323

4 MAI-686 Near C. stratUs 86.621 0.06874

MAI-686 Far C. sirnilis 163.432 0.11112

MAI-686 Near P. gibbesu 29.306 0.06229

MAI-686 Far P. gibbesii 23.397 0.02800

MU-A85 Far P. sptnicarpus 1.826* 0.00274*
Table 5.56. Fish species employed (x) in the food analyses during all four cruises and showing the cruise nu

sites represented by each species. Cruise Site Synodontidae Synod us foetens x x x x x x x Gadidae Urophycis cirrata x x x x x UrophycEs fioridana x x x Ogcocephalldae Ogcocephalus dedllvfrostr(s x x x Scarpaenidae Porttnus longtsplrLis x x x x x Serranidae Centroprlst(s phlladelphca x x x x Malacanthldae Caulolatllus intermedus x x Lutjanldae Anthkissp. x x Lutfanus campechanus x x x x x PrstEpornodes aquflonar(s x x x x x x Haemuildae Haernu!on auroUneatum x OrthoprLsts chrysoptera x Spa rid ae Archosargus probatocephalus x x Logodon rhomboides x x Sclaenidae Cynosc tort arenarlus x x x x x x Equetus wnbrosus x x Pogontas chromts x x BoUildae Ancylopsetta. dtlecta x x x x Cycopsetta chttendent x x x Parallchthys albigutta x x Parallchthys tethostigrna x x Syaciwnguritert x x x x Trichopsetta uentralls x x x Fish Species 1 2 3 4 MAI-686 MU-A85 HI-A389
(226). Results of the stomach food analyses by cruise are provided in Tables

5.57 to 5.60. Shrimp, fish, crabs, and squids made up the bulk of the food

observed, and identification to lower taxonoinic levels is available.

Miscellaneous food items of low abundance include algae, bryozoans,

polychaetes, snails, copepods, amphipods, mantis shrimp, and

undetermined organic matter.

The food analyses were primarily performed to provide information for

interpretation of the stomach content contaminant study. However, it is of

interest to determine whether the food of a given species differs

significantly in Near/Far comparisons for a given site on each cruise. For

those species with sufficient numbers for comparison, the significance of

the Near/Far differences is summarized in Table 5.61. The data show that at

the shallower station (MAI-686, 29-rn depth) differences were not

significant; but for all the species compared at the two deeper stations (MUA85 and HI-A389 m) all of the Near/Far differences were significant. For a

given species it is assumed that the food intake is related to food availability

within the range of food items consumed by the species.

As an aid in the interpretation of the food contaminant studies, a brief

sketch of pertinent life history information is provided for each species

analyzed.

Synodus foetens (inshore lizardfish) - As shown in Table 5.56,

specimens of this species were analyzed for food content for all four cruises

at all sites. Its distribution includes the entire continental shelf, but the

species is most abundant in the 60 to 80 m depth range. This fish regularly

buries itself in the sediments. It is a predator. During the present study, it

was found that squids comprise about a third of the food, fish about twothirds, and shrimp were only a trace. The species is regularly cannibalistic,

consuming other synodontids as well as its own young.

Urophycis cirrata (gulf hake) - The gulf hake was analyzed from all but

the second cruise, and it was studied at MU-A85 and HI-A389. This is a

deep-water member of the codfish family and is largely limited to the outer

continental shelf beyond a depth of 80 m, although during winter it

occasionally appears in shallower water. The species remains close to the

bottom where it feeds on benthic invertebrates and fish. In the present

study, the food was about half penaeid shrimp and half fish with a small

percentage of mantis shrimp. This is one of the top carnivores of the

5-2 15
Table 5.57. Results of stomach food analyses from Cruise I fish. Numbers represent the percent composillon by volume for each food categm

stomachs were empty. Crustaceans Station Fish Species Number of Silt, Tubes Poiychaete Squids Copepods Amphipods Shrimp C

Number Individuals Sand (Polych.. amphip.) Worms MU-A85 Certtropristts phitadelphica 2 90 

Near Equetus umbrosus 28 ioo Pogonas cromis 3 50 

Cyciopsetta chittendent 2-e MU-ASS Synod us foetens 2-e Far Urophycts cirrata 3 t 95 Centroprtstts phikideiphica 7 90 

Trtchopsetta ventraUs 5 10 20 

MAJ-686 LutJanus campecho.nus 10 100 Near Archosargus probatocephakis 9 10 t 86 

Cynoscton arennrtus 3 100 Parallchthys atbtgutta 2 99 Syactum guntert 11 27 6 67 MAI-686 Syaciuni guntert 6 t t 2 98 Far 4-N Ogcocephalus decUulrostris 10 80 

H]-A369 Urophycis cirrata 10-c Near Ponttnus IorLgtspinls 4-e Cauiolatilus Intermedius 3 95 1 4 Hemanthtas leptus 7 100 Prstipomotdes aqutlonarts 10 70 HI-A389 Urophycis cirrata 7-c Far Pontinus iongtsptrtts 10 1 9 

Prstipomokies aqullonarLs 10-e
01 Table 5.58. Results of stomach food analyses from CruIse 2 fish. category, Trace amounts are denoted as t'. Numbers represent the percent composition 

Site and Species Stomachs Examined With Food Sargassum Polychaetes Squids Amphipods Shrimp Cr

Food Volume (mL} Leaf 

MAI-6 86-Near C. arenarius 20 13 90 t 2 

S. guntert 20 13 1.3 t t 100 MA1-888-Far C. arenarius 20 14 5.5 S. guritert 20 19 3.0 t t 100 MU-A85-Near A. dtlecta 5 4 2.4 t S.foetens 16 6 16.0 100 

P. aquUonars 20 6 <0.5 18 t 

MU-A85 -Far A. dilecta 2 2 1.3 40 

S.faetens 17 7 23.5 5 

C. chUtendeni 1 0 L. cwnpechanus 12 6 2.5 2 50 

IH-A389-Near A. dilecta 20 13 2.5 13 P. longispEn(s 14 10 2.0 4

P. aquilonarts 20 9 1.5 60 P. lethosttrna 2 1 52.0 

HIA389-Far A. dtlecta 20 15 4.5 t t 70 1

P. iongisp(nfs 20 11 4.0 9

P. aquUonarls 20 6 0.5 5 5
Table 5.59. Results of stomach analyses for CruIse 3 fish. The values represent percent composition by volum

Trace amounts are denoted as 'U. Qi Station number and fish species Stomachs examined with food Food volume (mL) Polychaetes Snails Squids Copepods Amphipods Shrimp Crabs 

MAI-686-Near Lutjaniis campeclwnus Cljnosc(on arenarius MU-AS 5-N e ax Synodusfoetens Lutjaaus campethanus Cynoscion arenartus MU-ASS-Far Synodusfoetens Centropristis phlladeiphca Prtst (porno fries aquilonarts HI-A389-Near Urophycts ctrrata Urophycts floridana O.gcocephaius decUvirostrts Pontinus long(sp(nis Pristipomokies aqullonar(s Ancylopsetta dUecta m-A389 -Fax Synodusfoetens Urophyc(s c(rrata Urophyc(s fiorfdana Ponttnus longtspnis Pr(stipomo(des aquUonar(s Ancylopsetta diiecta 20/7 20/13 17/4 20/7 16/5 8/6 14/7 i/O2/1 1/0 17/7 20/15 20/3 3/2 1/1 2/1 1/1 20/9 20/5 7/6 0.5 7.5 5.0 16.4 7.6 16.8 2.0 <0.5 1.6 3.6 1.3 0.7 4.0 1.1 1.0 1.1 0.5 3.6 40 513 2545992551580 t t5 75101216047123085 4812556055085 
Table 5.60. Results of stomach food analyses for Cruise 4 fish. The values represent percent composition byvolume for 

amounts are denoted as t. Station Number and Fish S. ecies Stomachs Examined With Food Food Volume mL) Bryozoa Polychaetes Squids Amphipods Shrimp Cra

MAI-688-Near LutJanus carnpethanus 12/5 5 16 4 

MAI-8 88-Far Synod usfoetens 20/10 5.5 1 SYaCIUFTL gunteri 20/3 1.4 1 1 

MU-A85-Near Lagodon rhornho(des 20/7 3.3 t t 85 

Cynoscion arenartus 5/5 6.7 5 60 t 

MU-A85 -Far Synod us foetens 9/0 Urophycts c(rrata 20/19 6.9 t 50 t 

Centropristis phlladeiphca m-A389-Near 19/5 8.5 20 

UropFujcts c(rrata 2/0 Urophycls flor(dana 3/2 3.5 60 50 Poratinus IongLspints Pr(stipomotdes aquUonar(s Ancyopsetta dilecta ffl-A289-Fur 20/12 20/11 2/2 5.0 6.6 2.0 25 Urophycts ctrrata 1/I 1.0 100 Urophycts fioridana Pontlnus tonglspints Prlstlpomoides aqullonarts 7/5 20/9 20/2 14.5 1.8 0.5 38 4t3 14 7095 
Table 5.61. Results of Chi-Square comparisons of the food of fishes taken at Near and Far stations for sites on each of the four cruises. Only

those species for which at least fourteen specimens were

analyzed at both near and far stations are included.

ZFood composition was identical at both near and far stations

bottom community of the outer shelf.

Urophycis floridana (southern hake) - This cod was analyzed for the

last two cruises and only at HI-A389. As in the previous species, the

southern hake is normally Jinilted to the outer shelf, but in cooler weather it

occurs across the shelf. This is a bottom living species which takes in

benthic invertebrates and fish. In the present study, the southern hake

showed a varied diet including penaeid shrimp and fish with lesser amounts

of squids, crabs, and mantis shrimp. This is one of the top predators of the

bottom community of the outer shelf.

Ogcocephalus declivirostris (slantbrow batfish) - This batfish was

analyzed on the first and third cruises and only at HI-A389. It appears to be

limited to the outer continental shelf where it lives on the bottom and feeds

upon small benthic invertebrates and fishes. In the present study,

polychaetes and fish each made up somewhat less than half the food, snails

made up 13 %, and shrimp and crabs made up about 1 % each. Since this

batfish ingests polychaetes and other benthic invertebrates, it frequently

takes in quantities of bottom sediments with its food.

Poritinus longispinis (longspine scorpionfish) - This species was

studied on all four cruises at HI-A389. It is limited to deep water beyond

the 80-m depth contour. In the present study it was found to consume

5-220

Cruise Site Species

Number

Anaiyzed

(near/far)

PC2

Differences

are

Significant

2 MAI-686 Cynoscion arenarius 20/20 0.157 No

2 MAI-686 Syacium gunteri 20/20 1.00* No

2 MU-A85 Synodusfoetens 16/17 <0.001 Yes

2 HI-A389 Pontinus long ispinis 14/20 <0.001 Yes

2 HI-A389 Pristipomotdes aquilonaris 20/20 <0.001 Yes

2 HI-A389 Artcylopsetta dilecta 20/20 <0.001 Yes

3 HI-A389 Pontinus longispinis 20/20 <0.001 Yes

3 HI-A389 Pristipornoides aquilonaris 20/20 <0.001 Yes

4 HI-A389 Pontinus longisptnts 20/20 <0.001 Yes

4 HI-A389 Pristipomoides aquilonaris 20/20 <0.001 Yes
fishes 55 %, crabs 31 %, squids 12 %, and very small amounts of

polychaetes and penaeid shrimp. This outer shelf carnivore is one of the

few species in which crabs made up about a third of the diet.

Centropristts phitadeiphica (rock sea bass) - The rock sea bass was

analyzed for all but the second cruise at MU-A85. This species occurs at all

depths but is most abundant in the 40 to 80-rn depth range. In the present

study, the food was found to be largely penaeid shrimp with modest amounts

of fish and crabs and traces of snails. This small, active predator of the

lower water column seldom ingests bottom sediments

Cautotatilus tntermedius (anchor tilefish) - This tilefish was studied on

the first cruise at HJ-A389. This is an outer shelf species that seldom

occurs at depths shallower than 100 m. It was found to feed largely on

polychaete worms (95 %) with small percentages of amphipods and shrimp.

The anchor tilefish lives in burrows in the bottom sediments and consumes

largely polychaete worms.

Anthias sp. (seabass) - This fish was examined on the first cruise at HIA389. Apparently it is an outer shelf species. Shrimp made up 100 % of the

food encountered. Since the species was not completely identified, nothing

can be said about its habits.

Luqanus campechanus (red snapper) - The red snapper was analyzed

on all but the second cruise at MAI-686 and MU-A85. This is essentially a

mid-shelf species that rarely occurs inshore or beyond a depth of 100 m.

Penaeid shrimp made up 50 % of the food, fish made up 38 %, and squids

and mantis shrimp made up less than 10 % each. This lower water column

predator mostly consumes shrimp and small fish. It is known to reside

around platform bases.

Pristipomotdes aquitonaris (wenchman) - Food from this small

snapper was examined during all four cruises at MU-A85 and HI-A389. This

is the most abundant fish species in trawl catches on the OCS, and it is

rarely taken at depths shallower than 80 m. Shrimp and fish each made up

about a third of the food, crabs about 20 %, and squids 10 %. This is a

small, active predator of the outer shelf.

Archosargus p ro batocep hat us (sheepshead) - The sheepshead was

analyzed from MAI-686 on the first cruise. Young sbeepsbead frequent bays

and estuaries, but adults range widely across the continental shelf. In the

present study, shrimp made up 85 % of the food with polychaetes,

5-22 1
amphipods, and crabs each contributing small amounts. This species often

occurs around jetties, platforms, and other structures where it consumes

invertebrates attached to hard substrates. However, it also roams freely and

consumes infauna such as polychaetes and epifauna and demersal forms such

as shrimp and crabs.

Lagodon rhomboides (pinfish) - The pinfish was examined on Cruise 4

at MU-A85. Young of pinfish inhabit beds of submerged and emergent

vegetation in the bays and estuaries but the adults range across the shelf into

deep water. In the present study, the food was found to be shrimp (85 %)

and fish (15 %), with trace amounts of bryozoans and polychaetes. Food

habits of the pinfish are much like those of the previous species.

Cynoscion arenartus (sand seatrout) - This species was examined on all

four cruises at MAI-686 and MU-A85. This is one of the most abundant and

widespread fish species of the northwestern Gulf shelf. Young are generally

found in the bays and estuaries but adults roam throughout the continental

shelf at all seasons. They are particularly abundant off passes. In the

present study fish made up 44 % of the food, penaeid shrimp made up 33

%, and squids made up 22 %, with trace amounts of polycbaetes and mantis

shrimp.

Equetus umbrosus (cubbyu) - This druinfish was studied at MU-A85 on

the first cruise. The species, which is rarely taken in the northwestern

Gulf, tends to occur on the middle to outer shelf. In the present study,

penaeid shrimp made up 100 % of the food.

Pogonias cromis (black drum) - The black drum was analyzed on the

first cruise at MU-A85. The young are found primarily in the bays, estuaries,

and the shallow Gulf shelf. Adults range widely in the bays and across the

shelf. This species feeds largely on clams and oysters, but it will take

crustaceans and other invertebrates. In the present study, only three

specimens were analyzed, and these contained crabs (40 %), tubes of

polychaetes or amphipods (25 %), shrimp 15 %, and undetermined matter

(20 %L

Ancylopsetta dilecta (three-eye flounder) - This flounder was

examined on the second and fourth cruises at MU-A85 and HI-A389. It is an

outer continental shelf species that rarely strays onto the middle shelf. In

the present study fish made up 73 %, shrimp (25 %), and crabs made up

less than 3 % of the food observed. This small carnivore feeds near the

5-222
bottom.

Cyclopsetta chittendent (Mexican flounder) - The Mexican flounder

was analyzed for the first and second cruises at MU-A85. The species

occurs across the middle and outer shelf and is most abundant in the 40 to

80 m depth range. All stomachs examined were empty. The species is a

carnivore that feeds on small benthic invertebrates and fish.

Paralichthys atbigutta (gulf flounder) - This species was analyzed on

the first cruise at MAI-686. This is a rare species but it occurs at all depths

on the continental shelf. Food consisted of shrimp (99 %) and fish (1 %).

Paralichthys let hostigrna (southern flounder) - This flounder was

studied on the second cruise at HI-A389. Young are found in bays and

estuaries but adults are found across the continental shell. In the present

study, fish made up 100 % of the food.

Syacium gunteri (shoal flounder) - This flounder was analyzed on the

first, second, and fourth cruises at MAI-686. Although the species occurs in

bays and estuaries and across the shelf, it is most abundant in the 10 to 40

m depth range. Food consisted of shrimp (64 %), polycbaetes (16 %), fish

(12 %), crabs (7 %), and amphipods (1 %). Stomachs often contained

quantities of silt and sand apparently ingested while digging for polychaetes.

Trichopsetta ventratis (sash flounder) - This species was examined on

the first cruise at MU-A85. It is an outer shelf species that occasionally

occurs as shallow as 40-rn. In the present study, fish made up 50 % of the

food, shrimp and crabs made up 20 % each, and amphipods made up 10 %.

5.7.2 Histopathology

Histopathological evaluations were performed on liver and spleen

samples taken from 543 fish specimens. This reflected 189, 126, 122, and

106 fishes from Cruise 1, 2, 3, and 4; respectively. Species collected for

histopathological examination were Syacium gunteri (site MAI-686, all

cruises), Trtchopsetta ventratis (site HI-A389, Cruises 2 to 4 and site MUA85, all cruises) and Pontinus longispinis (site HI-A389, Cruise 1). Liver and

spleen samples were taken from all specimens and processed for

histopathological analysis. Tissue samples were processed for routine

paraffin histology. Sections were cut at 6 l.Lm, stained with Harris'

hematoxylin and eosin, and examined microscopically by fish pathologists.

No contaminant-related liver lesions (e.g.. hydropic vacuolation, hepatic

5-223
megalocytosis and hepatocellular neoplasms) were observed in any of the

tissues examined. However, a number of other pathological findings were

noted (Table 5.62). Parasitic infections were the most common

abnormalities, with microsporidians being the most prevalent. Two other

prevalent lesions included inflammatory foci and granulomatous

inflammation. These lesions were usually associated with parasitic

infections (e.g., nematodes) and were not related to the study sites.

Splenic MA analyses are performed on 416 flatfishes collected from

sites MAI-686, HI-A389, and MU-A85 during Phase 1 sampling. The

number of MAs per mm2, average size of MAs in jim2, and percent area

occupied by MAs for each site/station and cruise are summarized in Figure

5.123.

5.8 Detoxification

The detoxification work element evaluated 31 species of fish and 14

invertebrate species for evidence of PAR exposure. Of this group. only 16

species of fish and 5 invertebrate species were collected at both Near and

Far stations for at least one of the three study sites (Tables 5.63 and 5.64).

Only two species of fish, Synodus foeterts (lizard fish) and Paralichthys

lethosttgma (southern flounder), were captured at all stations. No

invertebrate species were collected at all study sites. The best overlap in

species between Near and Far stations was collected at MU-A85 and HIA389. The following fish species were collected at both Near and Far

stations at these two sites: Ancyclopsetta dilecta (three-eyed flounder),

Caulolattlus intermedius (tile fish), Cynoscion arenartus (sand sea trout),

Paraltchthys lethostigma (southern flounder), Pris tipomoides aquilonaris

(wenchman), Synodus foetens (lizard fish), Trichopsetta ventralts (sash

flounder), and Urophycis spp. (hake)

Over 1500 detoxification analyses/assays were conducted as part of the

detoxification effort, including 266 and 543 assays for AHH and EROD

activity, respectively and 178 assays for CYP1A mRNA levels derived from

fish liver preparations. In addition, 81 AHH assays of invertebrates and 384

bile metabolite analyses were conducted. Nearly 100 invertebrate tissue

extracts were used to dose rat Hepatoma H4IIE cells to derive toxic

equivalent values (TEQs). AHH activity was measured in both fish liver and

invertebrate digestive tissue for Cruise 1 samples. AHH activity was also

5-224
Table 5.62. Pathological abnormalities in liver and spleen.

aN = near station; F = far station

5-225

% Prevalence for Cruise

Site Stationa Species Lesion 1 2 3 4

MAI-686 N Syacium gunteri Granulomas 5.0 0.0 0.0 0.0

Inflammatory foci 35.0 0.0 0.0 0.0

Microsporidians 35.0 64.7 21.1 40.0

Nematodes 5.0 17.6 10.5 6.7

Sporozoan (?) 10.0 0.0 5.3 6.7

F Syacium gunteri Granulomas 0.0 0.0 10.5 0.0

Inflammatory foci 15.0 0.0 10.5 0.0

Microsporidians 0.0 54.2 52.6 25.0

Nematodes 0.0 4.2 5.3 10.0

Sporozoan (?) 0.0 12.5 10.5 10.0

HI-A389 N Trtchopsetta ventraLis Granulomas 15.0 25.0 10.0

Inflammatory foci 10.0 15.0 40.0

Microsporidians 10.0 0.0 0.0

Nematodes 0.0 5.0 5.0

Sporozoan (?) 0.0 10.0 0.0

F Trichopsetta ventralis Granulomas 5.0 27.3 10.0

Inflammatory foci 5.0 18.2 0.0

Microsporidia.ns 25.0 13.6 0.0

Nematodes 15.0 9.1 5.0

MU-A85 N Trichopsetta ventralis Granulomas 30.0 31.8 30.0 10.0

Inflammatory foci 0.0 13.6 5.0 20.0

Microsporidians 20.0 27.3 60.0 0.0

Nematodes 25.0 5.5 10.0 0.0

Sporozoan (?) 10.5 10.0 20.0 0.0

F Trichopsetta ventraiis Granulomas 31.6 21.7 34.8 38.1

Inflammatory foci 47.4 34.8 26.1 19.0

Microsporidians 10.5 26.1 26.1 19.0

Nematodes 5.3 8.7 4.3 0.0

Sporozoan (?) 0.0 4.3 13.0 0.0
40/

30-E

=

= CI) :-= ° 15 -

I

8000-/

7000-i

6000-i 0

C,

400O3000-E

2000-E

1000 -

0:,

r

B

C

4

'a,

.1 2 3 04

,

A

4

MAI-686N MAI-686F MU-A85N MU-A85F Hl-A389N Hl-A389F

Platform & Distance

Figure 5.123. Results of splenic macrophage aggregate analysis of fishes

collected from MAI-686, MU-A85, and HI-A389 for all cruises.

The species examined at MAI-686 was Sgactum guntert at MUA85 and HI-A389 was Trichopsetta ventralis. A: Number of

macrophage aggregates per mm2 of splenic tissue sections; B:

Percent area of splenic tissue sections occupied by macrophage

aggregates; C: Average size of macrophage aggregates (jim2).

5-226

C) 0 10-U

8-

4 6- w 4

a) 0. 2-'

0

16

.w 14-

a. 12-
Table 5.63. Fish species captured at both Near and Far stations of at least one platform.

Scientific Name Common Name Stations Captured N

Ancyclopsetta dtlecta 3-eyed flounder MU-A85 9

HI-A389 18

Caulolatilus intei-rnedius Tile fish MU-A85 10

HI-A389 15

Cent roprLstis phtlo.delphica Rock sea bass MU-A85 14

Cynoscion arenartus Sand sea trout MAI-686 21

MU-A85 11

Cyclopsetta chittendeni MexIcan flounder MU-A85 15

Lagodon rhomboides Pinfish MU-A85 14

Ogcocephalus declivtrostris Batfish HI-A389 10

Paraltchthys let hostigma Southern Flounder HI-A389 14

MAI-686 5

MU-A85 7

Pontinus longispinis Scorpion fish HI-A389 36

Prtsttpomotdes aquilonaris Wenchman MU-A85 22

HI-A389 39

Syacium gunteri Shoal flounder MAI-686 34

Synodus foetens Lizard fish MU-A85 28

HI-A389 16

MAI-686 12

Trichopsetta ventralis Sash flounder MU-A85 14

HI-A389 18

Urophycis spp. Hake MU-A85 12

HI-A389 25

Ancyclopsetta quadrocellata Ocellated flounder MAI-686 3

Lujanus campechanus Red snapper MU-A85 16

MAI-686 19
Table 5.64. Invertebrate species captured at both Near and Far stations of

at least one platform.

Table 565. AHH activities of invertebrates collected on Cruise 1.

5-228

Site Station Species A}IH (pmol/min/mg)

X-lIA389 Near Trachypenaeus simitis 1.9±3.2

HI-A389 Far Spider crab 0

Mixed fauna 0

MAI-686 Near Trachypenaeus simiUs 3.0±4.2

WelJc 0

Mixed infauna 0. 1±0.1

MAI-686 Far Trachypenaeus sImiUs 0

Callinectes stmiUs 0

Welk

MU-A85 Near Bristle worm 0

Brown shrimp 1.2

MU-A85 Amusium pap yraceurn 0

Periaeus aztecus 1.1±0.9

Mixed Inlauna 0

Scientific Name Common Name Stations Captured N

Trachypenaeus sirnilis Shrimp MAP686 17

SquWa empusa Mantis shrimp MAI-686 15

Peneaus aztecus Brown shrimp MAI-686 10

MU-A85 16

CalUrtectes simiUs Crab MAi-686 13

Solenocera atlanticus Shrimp MU-A85 12
measured in hepatic fish samples collected on Cruise 2. EROD activity and

biliary PAIl metabolite concentrations were measured in fish collected on all

four cruises. CYP1A mRNA levels were determined on selected fish samples

from Cruises 2, 3, and 4.

5.8.1 AHH Activity in Invertebrates

AHH activity was measured in selected invertebrate tissues collected

during Cruise 1. Activities were low to non-detectable for several species of

infauna and epifauna (Table 5.65). In vtvo invertebrate assays were

discontinued for subsequent cruises due to the very low activities observed

for Cruise 1 samples.

5.8.2 EROD and AHH Activity in Fish

Although approximately 600 fish were analyzed, statistical evaluations

were conducted on a more limited data set. Included in this data is

information collected only for those species captured at both Near and Far

station for at least one of the three study sites. No consistent differences

were detected in EROD and AHH activities between the four cruises,

therefore, the cruises were considered replicates.

EROD activities in various fish species were highly variable and

species-dependent (Figure 5.124: Table 5.66). Activities ranges from nondetectable to 345 pmol/min/mg. The highest EROD activities were

consistently measured in Lagodon rhomboides (pinfish; 7 to 348

pmol/min/mg) and Caulolatilus intermedius (tilefish; 15.1 to 182

pmol/min/mg). Consistently lower EROD activities were measured for

Cent ropristis philadeiphica (rock seabass) and Ancyclopsetta dilecta (threeeyed flounder; Figure 5.124). However, no difference was observed between

Near/Far stations for any of the species evaluated (Figures 5.125 to 5.140).

AHH activity was measured in all fish collected on Cruises 1 and 2.

The assay for this activity was discontinued for subsequent cruises because a

highly significant correlation between the two assays (EROD vs. AHH) was

established for most species (Figure 5.141). Other studies have shown a

similar relationship between the two assays for several fish species (Collier

et aT. 1992). The two assays measure the activity of the same enzyme (i.e.,

CYP1A); however, the EROD assay is typically more sensitive and uses a less

toxic substrate than the AHH assay. AHH and EROD activities were not

5-229
50 100 150 200 

EROD (pmol/min/mg) Figure 5.124. Mean hepatic EROD activities in various fish species. Pristipomoides aquilonaris Caulolatilus intermedius Paralichthys Jethostigma Syacium gunteri Pontinus longispinis Trichopsetta ventralis Cynoscion arenarius Centropristis philadelphica S Lutjanus campechanus Lagodon rhomboides Ancyclopsetta quadrocellata Cyclopsetta chittendeni Synodus foetens Urophycis spp. Ogcocephalus declivirostris Ancyc/opsetta dilecta
Table 5.66. Mean (± SD) of EROD and AHH activities and mean biliary PAH metabolite concentra

of fish captured at Near (N) and Far (F) stations. Species Site CYP lA-Catalyzed Enzymes Bile PAH Metabo

EROD (pmol/min/mg) AHH (prnol/mln/mg) Nap hthalene (ng/g) Phenanthren

(ng/g) 

Ancyclopsetta dilecta MU-A85N 6.8±0.8 0 MU-A85F 4.3±3.4 0 HI-A389N 6.6±2.6 0 H!-A389F 7.1±4 0 Cautolatilus interrnedfus MU-A85N 69.6±37.9 200000 40000 

MU-A85F 66±38.5 130000±67000 17000±6500 HI-A389N 56.7±59.1 150000±33000 37000± 14000 HI-A389F 26. 1±10.5 68000±22000 11000±3000 

Centroprists piilade1pttca MU-A85N 6.8±1 4±3.9 140000±49000 27000±10000 

MU-A85F 6.2±1.4 1.2±1.6 70000±35000 9900±3500 

Cynosc(on areriarius MU-A85N 8.4±2.3 88000±33000 18000±8400 

MU-A85F 6.4±2.4 130000±74000 21000±9200 

MA!-686N 10.7±5.2 100000±35000 19000±8800 MAI-686F 9.8±1.7 110000±60000 19000±7400 

Cyctopsetta chttendeni MU-A85N 12.7±11.3 0.7±1.1 54000±11000 12000±4700 

MU-A85F 15.6±8.1 6.8±9.2 68000±30000 15000±9400 

Logondon thornbotdes MU-A85N 140.5±101.4 11.3±14 190000±71 O00 49000±25000 

MU-A8SF 156.9±132,9 51±21.4 190000±95000 35000±20000 

Ogcocephaius dectivirostris HI-A389N 26.2±4.9 33000±18000 7900±4300 

HI-A389F 34.8±29.6 73000 15000 

Parattchthys tethosUgrna Hl-A389N 9.7±10.7 H1-A389F 6.9±3.3 MAI-686N 10.8±4.8 MAI-686F 6.5±0 MIJ-A85N 7. 5±2.6 MIJ-A85F 7.2±0.7 Pontnus longisptnis H1-A389N 9.8±1.5 0 120000±56000 29000±22000 

HI-A389F 10.4±3.6 0.2±0,4 120000±60000 33000±31000 

Prtstipomoides aquaonarts MU-A85N 10.7±5.3 82000± 10000 16000±1400 

MU-A85F 8.3±1.6 90000±33000 16000±4800 HI-A389N 10.8±3.5 79000±42000 18000±12000 HI-A389F 9.9±2.5 10000±5000 20000± 12000 
Table 5.66. (Cont.) Species Site CYP lA-Catalyzed Enzymes Bile PAH Metabolites EROD (pmol/mln/mg) AHH (pmol/min/mg) Naphthalene (ngfg) Phenanthrene (ng/ 

Syadum guntert MAI-686N 21.6±15.6 15.4±15.4 MAI-686F 28.2±23.4 21.3±26.6 Synod us foetens HI-A389N 12.3±14 0 57000±25000 11000±4500 

HI-A389F 8.9±3.5 0 88000±45000 16000±9400 MU-A85N 8±1.7 0 110000±53000 190 00±9 700 

NU-A85F 6.4±1.6 0 83000±35000 17000±7200 

MAI-686N 22.4±8.8 0 180000 42000 

MAI-686F 12.6±6.6 0 140000 23000 

Tr(copsetta ventraUs MU-A85N 10.5±5 0 MU-A85F 9.3±3.7 0 HI-A389N 13±4.9 0 H1-A389F 15.5±7.8 0 Urophycts spp. MU-A85N 10.6±3.8 0 MU-A85F 10.9±6.4 0 HI-A389N 10.5±7.1 1.2±2 HI-A389F 11.7±10.5 2±2.8 Ancyciopsetta quadrocellata MAI-686N 11.3±0 MAI-686F 8.4±1.6 Lutjanus camprechanus MU-A85N 14. 1±4.3 MIJ-A85F 14. 1±5.6 MAI-686N 13.2±7.3 MAI-686F 8±0.8
Figure 5.125. Catalytic enzyme activities and blilary metabollte concentrations in A

clilecta.
FIgure 5.126. CatalytIc enzyme activitIes and billary metaboilte concentrations in Ancy

quadrocellata.
Figure 5.127. Catalytic enzyme activities arid billary metabolite concentrations in C

irttermedius.
Figure 5.128. Catalytic enzyme activities and biliary metabolite concentrations in C

phUadeiphica.
Figure 5.129. CatalytIc enzyme activities and billary metabolite concentrations in C

arertarius.
Figure 5.130. CatalytIc enzyme activities and blilary metaboilte concentrations In C

chittendent
Figure 5.131. CatalytIc enzyme activities and bifiary metabolite concentrations in L

rhombo fries.
Figure 5.132. Catalytic enzyme activities and biliary metabolite concentrations in 

camprechanus.
Figure 5.133. Catalytic enzyme activities and billary metabolite concentrations In Ogc

dedllvirostrts.
Figure 5.134. Catalytic enzyme activities and biliary metabolite concentrations in P

iethostignia.
Figure 5.135. Catalytic enzyme activities and biliary metabolite concentrations in 

longispinis.
Figure 5.136. Catallytic enzyme activities and biliary metabolite concentrations in Pris

aqullonaris.
12 uummuu15 0 A Figure 5.137. Catalytic enzyme activities and biliary metabolite concentrations in Sya
1

V

tio1j

U%
Figure 5.139. CatalytIc enzyme activities and biliary metabolite concentrations in Th

ventratis.
Figure 5.140. CatalytIc enzyme activities and biliary metabolite concentrations in Uro
Figure 5.141. Correlation between EROD and AHH activities In fish captured on Crui

(excluding Lagodon rhornboides).
closely correlated for two species: Lagodort rhomboides (pinfish) and Anus

felts (hardhead catfish), for which EROD activity was significantly higher

than the AHH activities for these two species. The fish that do not exhibit a

coordinated induction of AHH and EROD activity (i.e., EROD >> AHH) may

express an altered CYP1A protein compared to other fish species studied.

5.8.3 Biiary PAH Metabolites in Fish

Significant species differences were observed in biliary PAR

metabolite concentrations (Figure 5.142; Table 566). The concentrations of

napbtbalene and phenanthrene-equivalent metabolites were higher in

Lagodon rhombotdes (pinfish). Benzo(a)pyrene-equivalent metabolite

concentrations were higher in Urophycis spp. (bake). No significant

Near/Far differences in biliary PAH metabolites concentrations were

detected for any species.

5.84 Rat Hepatoma H-411E Bioassays

The highest TEQ values were derived from rat hepatoma cells treated

with Amustum pap yraceum (scallop) extracts (Figure 5.143). The TEQs for

these extracts were nearly ten times higher than observed for extracts from

other species, which is consistent with the expected higher levels of

contaminant accumulation in bivalves. However, a Near/Far station

comparison was not possible because scallops were unavailable from the

Near station for this assay. The only significant station difference observed

was at MAT-686 for extracts of Penaeus aztecus (brown shrimp) collected at

the Near station. These shrimp exhibited higher TEQ values (Figures 5.144

to 5A48).

5.8.5 CYP1A mRNA

Regardless of species, the CYP1A mRNA gel electrophoretic

transcripts were similar for the fish sampled as shown in Figure 5.149. The

Figure shows CYP1A1 transcripts for eight representative species caught on

the fourth cruise. Hepatic CYP1A1 levels were determined in 48, 85, and

45 fish samples for Cruises 2, 3, and 4, respectively. Thirteen different fish

species were sampled.
S ! 9UO11" uoiV°'°° ojoqW £113fl.lq II 

F"F0 , 0000 A 0000ti 00009 00008 0000t? 0000 V000009. 00Q00 A400008.
Portunus spinicarpus Trachypenaeus similis Solenocera atlanticus Squilla empusa Penaeus aztecus Callinectes simi/is Amusium papyraceum Figure 5.143. SpecIes difference in rat hepatoma H-4 I 1E cell bioassay-derived 

0 0.5 15 2 

TEQ (ng/g)
MAI-686N MAI-686FU 01 02 03 04 05 

TEQ (ng/g) Figure 5.144. TEQs derived from rat hepatoma H-411E cells dosed with Trachypen

extracts.
Cl) MU-A85N MU-A85F TEQ (nglg) Figure 5.145. TEQs derived from rat hepatoma H-411E cells dosed with Solenocera 

extracts. 0 I I I I I 0.1 I I I 02 I I I I 03 I I I 04 I I I I I 05 I I I I I I fl
MAI-686N MAI-686F 02 04 06 08 

TEQ (nglg) Figure 5.146. TEQs derived from rat hepatoma H-411E cells dosed with Squilla emp
I I I I I I I I I I I I I I I I I I I 1 1 I I I I 1 

0 01 02 0 

Figure 5.147. TEQs derived from rat hepatoma H-411E cells dosed with Callirtectes sim
MU-A85N MAI-686N MAI-686F MU-AB5F TEQ (ng/g) 

Figure 5.148. TEQs derived from rat hepatoma H-411E cells dosed with Penaeus azte

II ).00 0.25 1 I I 0.50 I I I I 0.75 I I I I I 1.00 I I I 1.25 I I I I 1Q 
LLL1

Co CO to

CO COCO CO

Figure 5.149. Northern blot analysis of CYP1A mRNA in A: marine fish; and B: lizard fish from near and far stations.

5-258

Ii CYP1A

qi!. f3Tubulin

C)

1.

1 A

C) C

LL 0. Cl) oc

2

Cl) C)ciZ >Io 2- L .E'j 3 X a (1) 0. Cl)
5.9 Sediment Porewater Toxicity Testing

Sediment samples were received for processing in two groups from

each of the first two cruises and extracted within 10 days of the time of

collection. The water quality parameters for the pore waters were very

similar among all stations from both cruises. All Cruise 1 porewater

salinities were between 34 and 37 %o, therefore very few samples required

dilution to reach the target salinity (35 ± 1 %o) for the tests. No dilution of

samples was required for Cruise 2 samples, since the salinities of all samples

were between 34 and 36 %o. Hydrogen sulfide concentrations were below

the detection limit (0.01 j.g/L) in all pore water assayed.

5.9.1 Sea Urchin Tests

Porewater toxicity was observed at 14 of 150 stations as detected by

the sea urchin embryological development assay and at three of 75 stations

by the sea urchin fertilization test (Figure 5.150). All stations showing

reduced fertilization also exhibited impaired development in the

embryological development assay. All but three of the toxic stations were

within 100 meters of a platform. Significant toxicity was observed in the

vicinity of two of the three platforms sampled during the second cruise

(Figure 5.151). As in the first cruise, no toxicity was observed near the MUA85 platform, but toxicity was observed at one of the distant stations (5C).

Three of the five stations closest to the platform were toxic at MAI-686.

Four stations near the platform exhibited significant toxicity at HI-A389 and

corresponded with four of the six stations observed to be toxic during the

first cruise. Of the 75 samples collected during Cruise 2, significant toxicity

was observed at eight (8) stations based on the sea urchin embryological

development assay. Stations that were toxic in the bioassays (except the one

reference station at MU-A85) were within -100-m of a platform.

The EC50s for sodium dodecyl sulfate (SDS) in the fertilization (6.29

mg/L-Cruise 1) and embryological development tests (Cruise 1-3.9 1 mg/L

and Cruise 2-4.65 mg/L) indicate normal gamete viability. Filtered seawater

and reconstituted seawater controls were not statistically different from

reference pore water in any test.
E .

D

D

EE U

S Plalfom,

U DNcne

Devet. p0.01

DeI. p.05

0

Feet 0 500 1000

Meters 0

- -

100 200 300 400

DC

5-260

C

Feet 0 500 1000 - - I Meters 0 100 200 300 400

Figure 5.150. Summary of sea urchin embryological development

and fertilization porewater toxicity tests for sediments

from Cruise 1 at A: MAJ-686; and B: MU-A85.

A MAI-686

Cruise 1

A

U

B MU-A85

Cruise 1

A

0

D

00'EJO 0

U

Eo

D

D0
C

0

A

H I-A389

Cruise 1

0 B

5-26 1

E 0

D

Plalknn

El None

Feet 0 500 1000 U Deve .01 - - _J A Dev. 101

Meters 0 100 200 300 400 Fett p0.05

Figure 5.150 (cont.). Summary of sea urchin embiyological development

and fertilization porewater toxicity tests for

sediments from Cruise 1 at C: FJI-A389.

0 C
E E

D°

Feet 0

Meters 0-

Ei

0

0

0

0

0

D°

0

oB

5-262

LIC Plaffaffn 500 1000 - I 0 None

100 200 300 400

C

Platform Feet 0 500 1000

LII None

Meters 0

-

100 200-300

_J

400 p0-o1

Figure 5.:151. Summary of sea urchin embxyologicall development

porewater toxicity tests for sediments from Cruise 2 at A: MAI-686; and B: MU-A85.

A MAI-686

Cruise 2

A

B MU-A85

Cruise 2

A
C

-

H I-A389

Cruise 2

A

E

C

5-263

E D

D Platfom, Feet 0 500 1000

None

Meters 0-100 200-300

1 400 . p=0.01

Figure 5.151 (cont.). Summary of sea urchin embryological development porewater toxicity tests for sediments from Cruise 2

at C: HI-A389.
5.9.2 Tests with Meiobenthic Species

The response of two melobenthic invertebrates to selected pore

waters from High Island A-389 was evaluated and compared to the results of

the sea urchin tests. One species, Dtrtophilus gyroctUatus - a small

polychaete, has been previously used in toxicity testing. The techniques for

the culture and testing of this organism are well established and the

sensitivity of the reproductive endpoint has been demonstrated. The other

species, Longipedia americana. a benthic harpacticoid copepod, has not

been previously cultured or used in toxicity testing.

Dissolved oxygen was above 90 % saturation in all samples both before

and after the tests. Salinity, 35 to 36%o at test start, increased by up to 1%o

by test end in the 96 hour test and by up to 2%o in the seven day test.

Sample pH was between 8.0 and 8.2 both at the beginning and end of the

tests. Total ammonia-nitrogen was measured at the beginning and end of

the Dinophilus test and these values were well below the concentrations

known to produce an adverse effect for this species. Results of copepod and

polychaete tests are shown in Table 5.67. Results of the sea urchin

embryological development test are shown for comparison. With the

exception of site 3A, which was toxic only in the sea urchin embryological

development test, there was close agreement between the three tests. That

is, sites which were toxic in one test were toxic for the other tests

performed. Toxicity was observed at stations close to the platform. All sites

which were toxic in the melobenthic animal tests were also toxic in the sea

urchin embryological development test. The copepod nauplii were quite

sensitive test organisms, but a high rate of control mortality and the few

numbers of nauplii available for the test reduced its statistical power. In an

attempt to increase control survivability (and also the potential duration of

the test), a variety of conditions were tested, including different feeds, test

containers, stocking densities, salinities and the use of an antibiotic. None

of these variations in the technique produced appreciably greater control

survival. One problem which must be overcome if tests of greater duration

are to be performed is that naupill easily become attached to the surface film

after molting. The first molt usually occurs at about 96 hours. Nauplii which

are attached to the surface film cannot forage effectively and apparently

starve.
Table 5.67. Results of tests for three species exposed to pore water from

selected stations at HI-A389, Cruise 1.

aSificant differences between 3000 m sites (5A, 5C, 5E) and other sites as determined by

Ryans Q test indicated by asterisks.; (a 0.05); ** (a 0.01) on that sample.

There was a high degree of agreement between the two melobenthic

tests and the sea urchin embryological development test performed

previously. The sea urchin embryological development test appears to be

similar in sensitivity, or slightly more sensitive, than the two meiobenthic

tests and is more reliable, cost efficient, and simpler to conduct. The

urchin assay can be used as a surrogate for assessment of the potential

impacts of contaminated pore waters.

Station

Approx. distance

from platform

center

(m)

Sea urchin

development to

pluteus larvae

(% ± SD)a

Polychaete number

eggs/female

(mean ± SD)a

Copepod

survival

(% ± SD)a

5A 64.6±6.9 2.6 ± 0.6 53.3 ± 23.1

SC 3000 73.0 ± 6.2 2.4 ± 0.6 60±0

5E 74.6 ± 3.8 2.4 ± 0.6 46.7± 11.5

4A 67.2 ± 5.3 2.1± 0.6

4C 500 75.0 ± 3.2 1.5 ± 0.7

4E 74.8 ± 4.8 2.2 ± 0.7

1A 62.0 ±4.6 1.5± 1.2 40.0 ± 20.0

'C 200 65.2 ± 6.0 1.1± 0.1

1E 61.2 ± 2.4 1.7± 1.3 40±0

3A 43.2 ± 8.2** 1.1 ± 1.2 60.0 ± 20.0

3B 100 44.6 ± 5.1** 13.3± 11.5*

3C

3E

67.6± 1.5

20.6 ± 8.5

1.5 ± 0.6

o ±

33.3± 11.5

o ±

2A 3.4 ± 32 0 ± 0± 0**

2B 9.8 ± 5.5 0± 0**

2C 50 73.8 ± 4.6 1.6 ± 0.5 20.0 ± 20.0

2D

2E

73.6 ± 6.2

0± 0** o ± cr

26.7 ± 23.1

o ±
6.0 DISCUSSION

This section provides a work element-by-work element test of the

program's guiding hypotheses. Extended discussions of the rainilIcations of

the patterns observed are included. Each variable is also described in the

broader context of the 'Tnatural" processes that control or contribute to the

observed variations. Selected passages in the text are in bold-face type to

draw the reader's attention to significant programmatic conclusions.

6.1 Physicochemical Parameters

Physicochemical parameters were measured to address three

objectives:

describe the GOOMEX sites within the broader context of

northern Gulf of Mexico continental shelf oceanography;

document variations in water column characteristics that could be

related to the presence of a platform; and

characterize variations in water column parameters that are

associated with potentially confounding influences on patterns observed in the underlying benthos (i.e., hypoxia, nutrient regeneration, etc.).

Based on ANOVA analysis of the physicochernical data, no significant (p

0.01) variations with distance (D) from the platform were detected when

testing the overall study design (Table 6.1). In contrast, many significant

interactions among platforms (P) and cruises (C) were apparent. The trends

were similar for all water depths (Table 6.1). Where main effects were

testable, no distance effects were significant. Based on a Tukey's test of the

overall study design, water properties are relatively uniform with regard to

distance from the platform (Table 6.2 to 6.4). In contrast, the sites were

unique from each other based on many of the hydrographic variables

measured (Tables 6.5 to 6.7). Based on differences in hydrographic

properties platform sites were ordered by water depth by Tukey's tests.

Analysis of individual platform sites provides insight into variations in

water column characteristics at each site (Tables 6.8 to 6.10). As in the test

of the overall design, many significant interactions among cruises and

distances were observed (i.e., season). Distance effects could be tested

6-1
Table 6.1. Summary of the significance of interactions for the overall study

design based on physicochemical data.

Variablea C*D D*R PtD P*C*D D

surface water

T Yes No Yes Yes

Sal Yes No Yes Yes

Sigma-t Yes No No Yes

Pa4 No No No No No

NO3 Yes No Yes Yes

NO2 Yes No Yes Yes

SiO3 Yes No Yes Yes

TXMISS Yes No Yes Yes

02 Yes No Yes Yes

mid-water

T Yes No Yes Yes

Sal Yes No Yes Yes

Sigma-t Yes No Yes Yes

PO4 No No No Yes

NO3 Yes No Yes Yes

NO2 Yes No Yes Yes

SiO3 No No Yes Yes

TXMISS Yes No No Yes

02 No No No No No

bottom water

T Yes Yes Yes Yes

Sal Yes No Yes Yes

Sigma-t Yes No Yes Yes

PO4 Yes No Yes Yes

NO3 Yes No Yes Yes

NO2 Yes No Yes Yes

SlOg Yes No Yes Yes

TXMISS No No No No No

02 Yes No Yes Yes

aTtemperate (°C), sal=salimty, PO4=phospbate (jiM), NOgni1rate (jiM), NO2=nitrite (jiM),

SO3=silicate (jiM), TXMISS=% light transmittance (%), 02=dissolved oxygen (mL/L).

bpplatform, CCruise, D=Distance, Rzradius; Yes=significant, pO.Ol; No=not significant,

pO.O 1; ---not testable due to higher interactions.

Xnteractionb
Table 6.2. Tukeyts multiple comparison test results by distance for the overall study design based on physicochemical data for surface

waters.

Variablea Distanceb

T 3000m 500m 50m 200m lOOm

(°C) (22.7) (22.7) (22.5) (22.4) (22.3)

Sal 500 in 3000 in 200 in 100 m 50 in

(32.97) (32.76) (32.47) (32.53) (32.38)

Sigiva-t No difference

(22.2)

PO4 No difference

(jiM) (0.06)

NO3 50 m 200 m 500 m 100 in 3000 in

(jiM) (0.21) (0.20) (0.20) (0.20) (0.15)

NO2 500 m 200 in 100 in 50 in 3000 m

(jiM) (0.09) (0.08) (0.08) (0.07) (0.07)

5103 200 in 50 m 100 m 500 m 3000 in

(jiM) (2.23) (2.19) (2.16) (2.01) (1.92)

TXMISS No difference

(%) (78.3)

02 100 in 50 in 200 in 3000 m 500 m

(mL/L) (5.19) (5.15) (5.14) (5.10) (5.08)

aSee Table 6.1 for definition of variables.

means are presented (x) and means that are underlined are not

different at the 0.05 level.
Table 6.3. Tukeys multiple comparison test results by distance for the overall study design based on physicochemical data for midwater.

Variablea

T

(°C)

3000 m

(21.1)

Sal 500m

(34.69)

Sigma-t 500 m

(24.1)

PO4

(MM)

NO3

(i.LM)

NO2 lOOm 500m

(IIM) (0.19) (0.19)

200 m

(34.42)

200 m

(23.9)

Distanceb

3000 m

(34.40)

lOOm

(23.9)

No difference

(0.08)

No difference

(0.30)

200 m

(0.17)

lOOm

(34.31)

3000 m

(23.8)

50 m

(0.13)

50m

(34.20)

50 m

(23.7)

3000 m

(0.13)

aSee Table 6.1 for definition of variables.

bDetj.ansfoed means are presented (x) and means that are underlined are not different at the 0.05 level.

Sb3 No difference

(p.M) (2.00)

TXMISS No difference

(%) (80.0)

02 No difference

(rnL/L) (5.1)

500 m 50 m 200 m lOOm

(21.0) (20.9) (20.9) (20.7)
Table 6.4. Tukey's multiple companson test results by distance for the overall study design based on physicochemical data for bottom

waters.

T 50m

(°C) (19.1)

Sal 50m

(35.38)

Sigma-t

PO4

(I.LM)

NO3 50m

(pM) (3.06)

NO2 lOOm

(M) (0.33)

S103

(tiM)

TXMISS

(%)

02 3000m

(mL/L) (4.25)

lOOm

(19.1)

500m

(19.0)

500 m 3000 m 200 m 100 m

(35.38) (35.24) (35.20) (35.10)

No difference

(25.1)

No difference

(0.33)

200m lOOm 3000m

(3.03) (2.66) (2.57)

200 m

(18.9)

3000 m

(18.9)

500 m

(2.52)

50m 3000m 200m 500m

(0.32) (0.26) (0.26) (0.24)

No difference

(4.70)

No difference

(71.0)

500m lOOm 200m 50m

(4.13) (4.10) (4.02) (3.9)

aSee Table 6.1 for definition of variables.

bDetransformed means are presented (x) and means that are underlined are not

different at the 0.05 level.

Variablea Distanceb
Table 6.5. Tukey's multiple comparison test results by site (platform) for

the overall study design based on physicochemical data for surface waters.

aSee Table 6.1 for definition of variables.

bDefraj.1sfoed means are presented (x) and means that are underlined are not different at the 0.05 level.

Variab1ea Platformb

T HI-A389 MU-A85 MAI-686

(°C) (23.9) (22.9) (20.9)

Sal HI-A389 MU-A85 MAI-686

(34.29) (32.40) (31.19)

Sigma-t HI-A389 MU-A85 MAI-686

(23.1) (22.0) (21.6)

PO4 MAJ-686 MU-A85 HI-A389

(jtM) (0.09) (0.05) (0.05)

N0 MAI-686 HI-A389 MU-A85

(tM) (0.25) (0.23) (0.14)

NO2 MAI-686 MU-ASS HI-A389

(jtM) (0.13) (0.08) (0.04)

S103 MAI-686 MU-A85 HI-A389

(j.tM) (2.50) (2.14) (1.89)

TXMISS MU-A85 HI-A389 MAI-686

(%) (79.4) (79.4) (73.2)

02 MAE-686 MU-A85 HI-A389

(mL7L) (5.39) (5.07) (4.96)
Table 6.6. Tukey's multiple comparison test results by site (platform) for

the overall study design based on physicochemical data for midwaters.

aSee Table 6.1 for definition of variables.

bfletransformed means are presented (x) and means that are underlined are not different at the 0.05 level.

Variablea Platformb

T no difference

(°C) (20.9)

Sal HI-A389 MU-A85 MAJ-686

(36.05) (35.64) (31.70)

Sigma-t HI-A389 MU-A85 MAI-686

(25.3) (24.9) (21.6)

PO4 MAI-686 MU-A85 HI-A389

(i.LM) (0.09) (0.08) (0.06)

NO3 HI-A389 MU-A85 MAI-686

(MM) (0.34) (0.30) (0.23)

NO2 MU-A85 MAI-686 HI-A389

(J.LM) (0.23) (0.15) (0.11)

S103 MAI-686 MU-A85 HI-A389

(jiM) (2.36) (1.85) (1.76)

TXMISS MU-A85 HI-A389 MAX-686

(%) (83.9) (82.3) (74.3)

02 MAJ-686 HI-A389 MU-A85

(rnL/L) (5.29) (5.02) (4.99)
Table 6.7. Tukey's multiple comparison test results by site (platform) for

the overall study design based on physicochemical data for bottom waters.

aSee Table 6.1 for definition of variables.

bDetr1sfo1ed means are presented (x) and means that are underlined are not different at the 0.05 level.

Variablea Platforrnb

T MAI-656 MU-A85 HI-A389

(°C) (20.0) (19.4) (17.6)

Sal HI-A389 MU-A85 MAI-686

(36.26) (36.01) (33.58)

Sigma-t HI-A389 MU-A85 MAI-686

(26.3) (25.7) (23.5)

PO4 HI-A389 MAI-686 MU-A85

(j.tM) (0.65) (0.20) (0.18)

NOg liI-A389 MU-A85 MAI-686

(p.M) (10.34) (1.49) (0.91)

NO2 MAI-686 MU-A85 Hl-A389

(jiM) (0.58) (0.26) (0.06)

SiO3 HI-A389 MAI-686 MU-A85

(jiM) (5.48) (5.29) (3.34)

TXMISS MU-A85 HI-A389 MAt-686

(%) (76.5) (76.6) (62.4)

02 MU-A85 MAI-686 HI-A389

(mL/L) (4.53) (4.50) (3.29)
Table 6.8. Summary of the significance of interactions for physicochemical

data at MAJ-686.

Variablea C*D D*R D C

surface water

T Yes No

Sal Yes No

Sigma-t Yes No

PO4 No No No Yes

N0 Yes No

NO2 Yes No

SiO3 Yes No

TXMISS No No No Yes

02 Yes No

mid-water

interactionsb

T Yes No

Sal Yes No

Sigma-t Yes No

PO4 Yes No

NO3 Yes No

NO2 Yes No

SiO3 Yes No

TXMISS No No No Yes

02 No No No Yes

bottom water

T Yes No

Sal Yes No

Sigma-t Yes No

PO4 Yes No

NO3 Yes No

NO2 Yes No

Sb3 Yes No

TXMISS No No No Yes

02 Yes No

aSee Table 6.1 for definition of variables.

bSee Table 6.1 for definition of variables and symbols.
Table 6.9. Sunmiary of the significance of interactions for physicochemical data at MU-A85.

surface water

T Yes No

Sal Yes No

Sigma-t No No No Yes

PO4 No No No Yes

NO3 Yes No

NO2 Yes No

SiO3 Yes No

TXMISS Yes No

02 Yes No

mid-water

T Yes No

Sal Yes No

Sigma-t Yes No

PO4 Yes No

NO3 Yes No

NO2 Yes No

S103 No No Yes Yes

TXMISS Yes No

02 Yes No

bottom water

Interactionsb

T Yes No

Sal Yes No

Sigma-t Yes No

PO4 Yes No

NO3 No No No Yes

NO2 Yes No --- S!03 No No No Yes

TXMISS No No No Yes

02 No No No Yes

aSee Table 6.1 for definition of variables.

bSee Table 6.1 for definition of variables and symbols.

6-10

Variables- C*D D*R D C
Table 6.10. Summary of the significance of interactions for physicochemical

data at HI-A389.

surface water

T Yes No -- Sal Yes No

Sigma-t No No No No

PO4 Yes No

NO3 Yes No

NO2 Yes No -- S103 Yes No

TXMISS Yes No

02 Yes No

mid-water

T Yes No

Sal No No No Yes

Sigma-t Yes No

PO4 No No Yes Yes

NO3 No No No Yes

NO2 Yes No

5103 Yes No

TXMISS Yes No

No No No No

bottom water

T Yes Yes

Sal No No No Yes

Sigma-t Yes No

PO4 Yes No

NO3 Yes No

NO2 Yes No

S103 Yes No

TXMISS No No No No

02 Yes No

Interactlonsb

aSee Table 6.1 for definition of variables.

bSee Table 6.1 for definition of variables and symbols.

Variablea C*D D*R D C
directly in 19 of 81 cases and were significant in only two cases. Silicate

values for mid-water samples at MU-A85 arid phosphate values at HI-A389

exhibited a significant distance effect. These variations may be related to

the juxtaposition of topographic features to the west of these platforms that

rise to mid-water depths. Significant cruise differences were noted in 16 of

19 cases where it could be directly tested. Oxygen depletion previously

noted at MAI-686 is most significant as a cruise effect rather than a distance

effect, possibly due to its location along only one radial and its relationship

to stratified water column conditions.

6.1.1 Water Temperature

The spatial and temporal variability of water temperature on the

Texas-Louisiana shelf is caused by advection, turbulent and convective

mixing, and air-sea exchange processes. Temperature is the most

frequently measured hydrographic variable. Variability in water temperature

on the Texas-Louisiana shelf is well documented. Temple et aL (1977)

reported monthly data from the Gus III cruises; Robinson (1973) and Etter

and Cochrane (1975) produced mean temperature maps from largely

independent data sets; Ulm (1983) prepared a volumetric T-S census for

the waters of the shelf; subsurface temperature time series were reported

from multi-year studies at the various DOE/SPR brine disposal sites along

the inner shelf and the MMS environmental studies at the Flower Gardens

on the outer shelf; and analyses of thermal imagery from satellites described

synoptic-scale spatial variability of sea surface temperatures (Rezak et al.

1985).

Monthly mean sea surface temperatures for the northwestern Gulf of

Mexico (Robinson 1973) illustrate the seasonal cycle of temperature. Shelf

waters cool from summer highs near 29-30 °C to inshore lows of about 14 °C

in January and offshore lows of about 20 °C in February. Warming occurs

from March through July. The eastern half of the shelf warms more rapidly

and reaches higher temperatures than the western half because of upwelling

that begins along the lower Texas coast in May, reaching the west Louisiana

coast by July. Over the eastern shelf a warm region extends offshore in July

and August. Huh et aL (1981) described the seasonal cycle of sea surface
temperature in the northeastern Gulf, including the Mississippi Bight, for

1976 to 1977 using a time series of NOAA sateffite data.

Bottom temperatures over the inner half of the shelf vary with seasurface temperatures to the extent that the mixed-layer depth reaches the

bottom. However, seaward of about the 75-rn isobath, bottom water

temperatures reflect the annual variations in the off-shelf Gulf. Seaward of

about the 120-rn isobath, bottom water temperatures vary only slightly

(Etter and Cochrane 1975). Mean summer temperatures near the bottom

are higher nearshore than offshore, with isotherms closely paralleling

isobaths. During fall and winter, nearshore and offshore mean bottom

temperatures are low with somewhat higher temperatures in-between.

The physicochemical parameters were analyzed statistically to

determine if variability can be attributed to proximity to a platform. Each

water depth (near surface, above the thermocline, and near bottom) was

analyzed as a discrete set of data. Temperature data is summarized and

described in detail in Section 5.1. For temperature, no significant variations

related to distance from the platform were detected (Table 6.11) Most

temperature variations could be related to the time of year of the sampling.

The winter cruises (Cruises 2 and 4) were lowest in temperature compared

to the summer cruises (Cruises 1 and 3). The significance of this difference

decreased with water depth with near bottom water at the two deeper sites,

exhibiting little or no discernable seasonality.

6.1.2 Salinity

Wind-driven currents and freshwater influx from the MississippiAtchafalaya River system determine much of the spatial distribution and

temporal variability of salinity on the shelf. A band of low-salinity water lies

along the coast from September through June, carried by the inshore limb

of the gyre of cyclonic circulation that prevails on the shelf during this time.

Minimum salinities occur all along the coast in May after the spring flood of

the Mississippi in April. The May distribution also shows less saline water,

extending northwest, and covering the shelf from the south Texas coast to

the outer edge. This pattern is attributed to convergence in the wind stress

and current fields near the coast and to the offshore limb of the cyclonic

gyre. The band recedes upcoast in June and disappears by August, although

6-13
Table 6.11. Tukey's multiple comparison test results at each site and water depth by distance and by cruise for temperature (°C).

6-14

aDeansfoi-med means are presented (x) and means that are underlined are not different at

the 0.05 level.

Site/Water Depth Distance2-

MAJ-686

surface water 3000 m 100 m 50 m 500 m 200 m

(21.1) (20.9) (20.9) (20.9) (20.8)

mid-water 50 m 200 m 3000 m 500 m 100 m

bottom water

(21.1) (21.0) (20.9) (20.9) (20.7)

No difference

(20.0)

MU-A85

surface water 500 m 3000 m 50 m 200 m 100 m

(23.3) (23.1) (22.9) (22.5) (22.4)

mid-water 3000 m 500m 50m lOOm 200m

(21.2) (21.2) (20.9) (20.5) (20.5)

bottom water 3000 m 500m 50m lOOm 200m

(19.7) (19.5) (19.4) (19.3) (19.3)

HI-A389

surface water 500 m 5000m 200m 50m lOOm

(24.0) (24.0) (23.9) (23.9) (23.8)

mid-water 5000 m 200 m lOOm 500m 50 m

(21.2) (20.9) (20.9) (20.9) (20.8)

bottom water 100 m 50 m 200 m 500 m 5000 m

(18.0) (18.0) (17.5) (17.5) (17.0)
Table 6.11. (Cont.)

aDettansfoed means are presented (x) and means that are underlined are not different at the 0.05 level.

brackish water remains along the coast from the Mississippi delta to about

92°W and in a region extending seaward over the shelf. The absence of lowsalinity water west of about 92.5°W in July is caused by upcoast currents and

upwelling driven by the upcoast wind stress. In September, currents all

along the coast rapidly return to prevailing downcoast flow, bringing with

them a coastal band of low-salinity water.

At most sites during the first cruise, the 25 CTD casts oversampled

the 28 to 78 km2 of area around each platform. For example, salinity values

at MU-A85 ranged between 35.75 and 36.00, with a mean of 35.85. This

smafl range reflects a uniform water mass. However, at MAT-686 the salinity

range was considerably greater: 31.56 to 34.90. The larger salinity range at

6-15

Site/Water Depth Cruis&-

MAI-686

surface water 4 2 1 3

(27.8) (26.5) (16.5) (15.6)

mid-water 4 2 1 3

(27.2) (26.3) (16.8) (15.5)

bottom water 2 4 1 3

(24.8) (23.9) (17.3) (15.6)

MU-A85

surface water 4 2 1 3

(27.9) (26.5) (20.8) (17.2)

mid-water 2 4 1 3

(24.8) (21.1) (20.7) (17.5)

bottom 2 1 4 3

(21.2) (19.9) (19.6) (17.4)

HI-A389

surface water 4 2 1 3

(28.3) (26.7) (21.0) (20.6)

mid-water 2 4 1 3

(22.4) (21.0) (21.0) (19.4)

bottom water 1 3 4 2

(18.2) (17.6) (17.5) (17.1)
MAI-686 was caused by a combination of vertical stratification and spatial

variability. The site was influenced by the brackish coastal jet that hugs the

Texas coast during September through May (Cochrane and Kelly 1986).

No salinity differences could be attributed to the presence of a

platform (Table 6.12). The few associations with distance as determined by

TukeyTs test can be attributed to a time aiiasing effect. Stations were not

occupied in random order, with all stations at a given distance often

sampled together. Sampling generally extended over a 2 to 3 day period;

therefore, variables that vary in this timefranie may be similar due to time of

sampling not other design variables (Le, distance). As with temperature the

most significant effect was the time of year during which the sampling event

occurred. Salinity data is summarized and described in detail in Section 5.1.

The relationship to time of year becomes less significant with increasing

water depth.

6.1.3 Nutrients

Concentrations of nutrients, such as nitrate, nitrite, phosphate, and

sfficate on the Texas-Louisiana shelf are controlled by both biological and

physical processes. The interaction of these processes results in lownutrient concentrations in the surface water of the open Gulf (Barnard and

Froelich 1981) and higher concentrations nearshore, especially near river

mouths (Ho and Barrett 1977). Processes affecting nutrient concentrations

on the shelf include river discharge, coastal currents and winds, intrusions

of open Gulf waters, upwelling, biological actMty, rainfall, and proximity to

coastal marshes (Ho and Barrett 1977; Barrett et al. 1978; Brooks 1980;

Flint and Rabalais 1980; Dagg 1988). Nutrient concentrations in coastal

waters generally decrease in a westward direction from high values found

near the Mississippi River (Riley 1937).

There is a general seasonal pattern in the shelf nutrient

concentrations. On the Texas shelf, concentrations reach peaks in the

spring and then are consumed by phytoplankton blooms, resulting in low

concentrations for the remainder of the spring and summer. Nutrient

replenishment occurs in the fall and winter (Flint and Rabalais 1980). A

similar seasonal variation occurs on the Louisiana shelf where the spring

peak is due to high river flow (Sklar and Turner 1981) that brings the high

6-16
Table 6.12. Tukey's multiple comparison test results for each site and water depth by distance and cruise for salinity for the overall study

design.

aDeansfoed means are presented (x) and means that are underlined are not different at

the 0.05 level.

6-17

Site/Water Depth Distancea

MAI-686

surface water 500 m 3000 m 200m lOOm 50m

(31.99) (31.36) (31.06) (30.93) (30.62)

mid-water 500 m 200 m 3000m lOOm 50m

(32.47) (31.65) (31.60) (31.58) (31.07)

bottom water 500 m 50 m 3000m 200m lOOm

(33.93) (33.89) (33.53) (33.45) (33.16)

MU-A85

surface water 100 m 500 m 3000m 50m 200m

(32.60) (32.57) (32.47) (32.37) (32.27)

mid-water 3000 m 500 m 50m 200m lOOm

(35.72) (35.72) (35.64) (35.60) (35.58)

bottom water 3000m 500m 50 lOOm 200m

(36.06) (36.03) (36.02) (3697) (36.95)

HI-A389

surface water 3000 m 500 m 50 m 200 m 100 m

(34.53) (34.39) (34.25) (34.17) (34.14)

mid-water No difference

(36.0)

bottom water 200 m 50 m 100 m 500 m 5000 m

(36.28) (36.27) (36.26) (36.26) (36.22)
Table 6.12. (Cont.)

6-18

aDetsfoi-med means are presented (x) and means that are underlined are not different at the 0.05 level.

nitrate and silicate concentrations that are strongly associated with lowsalinity nearshore waters (Wiseman et al. 1986).

Coastal wind-induced upwelling has been identified as a mechanism by

which surface water nutrients in the coastal boundary layer are transported

to the middle shelf (Dagg 1988). In slope and deep Gulf waters, nutrient

maxima occur at about 400 to 600 m (Paskausky and Nowlin 1968; Morrison

et al. 1983). At the shelf-edge. bottom Ekman upwelling can raise water

with high nutrient concentrations (from near the depth of the maximum) to

the shelf. This is an idea developed by Cocbrane (1969) for the Campeche

Bank, which has analogous currents along the shelf-edge.

Site/Water Depth Cruisea

MAI-686

surface water 3 1 2 4

(33.81) (32.87) (29.78) (28.59)

mid-water 3 1 2 4

(34.09) (33.40) (29.92) (29.70)

bottom water 1 3 4 2

(34.32) (34.28) (33.51) (32.25)

MU-A85

surface water 1 3 2 4

(35.83) (35.21) (30.91) (28.28)

mid-water 1 4 2 3

(35.82) (35.73) (35.61) (35.43)

bottom water 2 4 1 3

(36.21) (36.20) (35.92) (35.70)

HI -A3 89,

surface water 3 1 2 4

(37.14) (37.01) (34.41) (32.80)

mid-water 4 3 1 2

(36.19) (36.14) (36.04) (35.82)

bottom water 1 4 2 3

(36.32) (36.30) (36.22) (36.21)
Phosphate concentrations showed little or no relationship to distance

from the platform (Table 6.13). One location of increased phosphate was in

near bottom water adjacent to the platform at MAE-686 during Cruise 4.

Increases in bottom water phosphate during summer cruises were observed

at MU-A85. Nitrate concentrations also exhibited little relationship to

distance from the platform other than at MAI-686 where bottom waters

were enhanced in nitrate during the summer cruises (Table 6.14). An

increase in bottom water silicate near the platform at MAI-686 and MU-A85

was observed during summer cruises (Table 6.15). A similar though less

dramatic increase in silicate concentrations in bottom waters during the

summer was also observed at MU-A85. Nutrient data is summarized and

described in detail in Section 5.1.

6.1.4 Dissolved Oxygen

Dissolved oxygen concentrations on the shelf vary from welloxygenated to bypoxic (less than 2-mg L-1 dissolved oxygen). Hypoxic

bottom waters occur almost annually in the summer in the Mississippi Bight

(Turner and Allen 1982) and frequently extend into west Louisiana (SATC

1989) and Texas waters (Harper et al. 1981a; Rabalais 1988). Hypoxia

develops as early as April and continues to as late as October, covering areas

of up to 10,000 km2 (Boescb and Rabalais 1988).

Near-bottom oxygen concentrations on the inner shelf drop when

strong vertical stratification develops. Such stratification may be caused by

less dense coastal water overriding denser shelf water. Boescb and Rabalais

(1988) suggest that the increasing nitrate enrichment by Mississippi River

discharge contributes to observed increases in frequency and intensity of

shelf hypoxia since the 1960s. Nitrate increase is attributable to increased

use of agricultural fertilizers, waste discharge, and atmospheric

precipitation.

Low values of dissolved oxygen (less than 3 mL/L) were observed in

bottom waters at HI-A389 during all cruises (Table 6.16). The low oxygen

concentrations at the m-A389 were caused by impingement of the oxygen

minimum layer on the outer shelf. In contrast, the low oxygen

concentrations observed at MAI-686 and MIJ-A85 were related to summer

vertical stratification. Time aliasing could account for some of the observed

6-19
Table 6.13. Tukey's multiple comparison test results for each site and water depth by distance and cruise for water column phosphate

concentrations (jiM)- Site/Water Depth Distancea

MAI-686

surface water No difference

(0.08)

mid-water No difference

(0.09)

bottom water 50 m 100 m 200 m 500 m 3000 m

(0.30) (0.23) (0.18) (0.15) (0.14)

MU-A85

mid-water 5000 m 200 m 100 m 50 m 500 m

(0-07) (0.07) (0.06) (0.05) (0-04)

bottom water 5000 m 200 m 500 m 50 m 100 m

(0.78) (0.73) (0.71) (0.67) (0.57)

aDettansfoi-med means are presented (x) and means that are underlined are not different at

the 0.05 level.

6-20

surface water No difference

(0.05)

mid-water No difference

(005)

bottom water No difference

(0.17)

HI-A389

surface water 100 m 200 m 50 m 500 m 5000 m

(0-06) (0.06) (0.05) (0.04) (0.04)
Table 6.13. (Cont.)

aDetrsfoi-med means are presented (x) and means that are underlined are

not different at the 0.05 level.

Site/Water Depth Cruisea

MAI-686

surface water 3 4 1 2

(0.15) (0.08) (0.06) (0.05)

mid-water 3 4 1 2

(0.16) (0.09) (0.07) (0.04

bottom water 4 3 2 1

(0.37) (0.19) (0.18) (0.07)

MU-A85

surface water 3 2 4 1

(0.09) (0.04) (0.04) (0.03)

mid-water 3 4 2 1

(0.11) (0.06) (0.05) (0.03)

bottom water 4 2 3

(0.29) (0.24) (0.1) (0.0)

HI-A389

nearsurface 3 4 1 2

(0.08) (0.06) (0.03) (0.02)

mid-water 3 4 1 2

(0.11) (0.07) (0.03) (0.02)

bottom water 2 4 1 3

(0.82) (0.65) (0.63) (0.61)
Table 6.14. Tukeyts multiple comparison test results for each site and water depth by distance and cruise for nitrate (jiM).

6-22

aDetransfol-med means are presented (x) and means that are underlined are not different at

the 0.05 level.

Site/Water Depth Distancea

MAI-686

surface water 500 m 200m lOOm 50m 3000m

(0.29) (0.28) (0.26) (0.26) (0.17)

mid-water 100 m 50m 200m 500rn 3000m

(0.31) (0.26) (0.23) (0.21) (0.16)

bottom water 50 m lOOm 200m 3000m 500 m

(1.53) (1.19) (0.94) (0.58) (0.49)

MUA85

surface water 3000 m 500 m 100 m 50 m 200 m

(0.15) (0.11) (0.10) (OJO) (0.06)

mid-water lOOm 3000m 50m 500ni 200m

bottom water

(0.36) (0.32) (027) (0.23) (0.12)

No difference

(2.50)

HI-A389

surface water 50 m 200 m 100 m 500 m 5000 m

(0.29) (0.28) (0.23) (0.21) (0.13)

mid-water 5000 m 200 m 50m lOOm 500m

(0.50) (0.44) (0.26) (0.21) (0.21)

bottom water 5000 m 200 m SOOm 50m lOOm

(12.91) (12.54) (12.51) (10.26) (8.21)
Table 6.14. (Cont.)

aDeansfo1.med means are presented (x) and means that are underlined are

not different at the 0.05 level.

6-23

Site/Water Depth Cruisea

MAI-686

nearsurface 1 3 2 4

(0.56) (0.28) (0.14) (0.08)

mid-water 1 3 2 4

(0.43) (0.31) (0.15) (0.07)

nearbottom 4 2 3 1

(2.78) (1.18) (0.36) (0.17)

MU-A85

nearsurface 3 2 4 1

(0.13) (0.13) (0.10) (0.07)

mid-water 4 1 3 2

(0.71) (0.14) (0.14) (0.12)

near bottom 4 2 1 3

(4.42) (3.10) (0.41) (0.22)

HI-A389

near surface 3 1 2 4

(0.57) (0.18) (0.14) (0.07)

mid-water 3 1 2 4

(0.91) (0.22) (0.12) (0.15)

nearbottom 2 1 3 4

(13.24) (11.27) (10.09) (9.95)
Table 6.15. Tukey's multiple comparison test results for each site and water depth by distance and by cruise for silicate concentrations (j.tM).

aDeansfoed means are presented (x) and means that are underlined are not different

at the 0.05 level.

Site/Water Depth Distancea

MAT- 68 6

surface water 50 m 200 m 3000m 500m lOOm

mid-water

(2.87) (2.54) (2.45) (2.33) (2.31)

No difference

(3.30)

bottom water 50m lOOm 200 m 3000 m 500 m

(7.78) (6.48) (5.38) (463) (3.90)

MU-A85

surface water 100 m 200 m 50 m 500 m 3000 m

(2.28) (1.98) (1.90) (1.86) (1.74)

mid-water 3000 m 100 m 50 m 500 m 200 m

bottom water

(2.45) (2.14) (1.75) (1.65) (1.62)

No difference

(3.4)

HI-A389

surface water 200 in 50 in 100 in 500 m 5000 m

(2.19) (1.91) (1.90) (1.86) (1.62)

mid-water 200 m 100 m 50 m 500 in 5000 m

(2J4) (1.75) (1.60) (1.59) (1.57)

bottom water 200 m 500 m 5000 m 50 m 100 m

(6.27) (6.01) (5.78) (5.04) (4.74)
Table 6.15. (Cont.)

aDettsfoi-med means are presented (x) and means that are underlined are not different at the 0.05 level.

6-25

Site/Water Depth Cruisea

MAT- 686

surface water 2 3 1 4

(4.14) (3.92) (2.18) (0.86)

mid-water 2 3 1 4

(4.21) (3.29) (1.94) (0.96)

bottom water 4 2 3 1

(16.19) (7.49) (3.53) (1.66)

MU-A85

surface water 2 1 3 4

(3.39) (2.28) (1.96) (0.74)

mid-water 2 1 3 4

(2.69) (2.38) (1.83) (0.88)

bottom water 2 4 1 3

(5.37) (4.53) (2.66) (2.37)

HT.A389

surface water 3 1 2 4

(2.52) (1.92) (1.86) (1.38)

mid-water 3 1 2 4

(2.43) (1.96) (1.72) (0.95)

bottom water 2 3 1 4

(6.89) (5.99) (5.01) (4.44)
Table 6.16. Tukey's multiple comparison test results for each site and water depth by distance and cruise for dissolved 02 concentrations

(mL/L).

aDeansfoed means are presented (x) and means that are underlined are not different at

the 0.05 level.

6-26

Site/Water Depth Distancea

MAT- 686

surface water 100 in 50 m 3000 m 500 m 200 m

(5.51) (5.28) (5.33) (5.31) (5.30)

mid-water 100 in 50 m 500 m 3000 m 200 m

(5.36) (5.32) (5.29) (5.29) (5.20)

bottom water 500 m 3000 m 200 m 100 m 50 m

(4.93) (4.82) (4.55) (4.32) (3.88)

MU-A85

surface water 50 m 200 m 100 m 3000 m 500 m

(5.15) (5.11) (5.09) (5.02) (5.00)

mid-water 50 m 200 m 3000 m 100 m 500 m

(5.05) (5.02) (4.96) (4.88) (4.87)

bottom water No difference

(4.5)

HI-A389

surface water No difference

mid-water

(5.0)

No difference

(5.0)

bottom water 100 m 5000 m 50 m 200 m 500 in

(3.43) (3.34) (3.26) (2.97) (2.96)
Table 6.16. (Cont.)

aDefransfoed means are presented (x) and means that are underlined are not

different at the 0.05 level.

distance effects because the stations were sampled in order by distance as

previously mentioned. However, such aliasing would require rapid, massive

movement of bottom waters during the sampling period and there is no

evidence for such transport at MAI-686. CTD profiles documented a

pronounced pycnocline at 7 to 8 m above the bottom close to the platform

and 3 to 5 m above the bottom more distant (> 100 m) from the platform.

There was a strong (p 0.01) correlation between high silicate, nitrate, and

phosphate concentrations and the low oxygen (see Section 5.1). The

hypoxic events detected at MAI-686 were masked in the statistical analyses

by strong seasonal and directional (radial) interactions. A lowering of oxygen

6-27

Site/Water Depth Cruisea

MAI-686

surface water 3 1 2 4

(5.94) (5.63) (5.03) (4.87)

mid-water 3 1 2 4

(5.90) (5.54) (4.92) (4.85)

bottom water 3 1 2 4

(5.83) (5.46) (4.11) (2.65)

MU-A85

surface water 3 1 2 4

(5.49) (5.11) (4.88) (4.84)

mid-water 3 1 2 4

(5.37) (5.09) (4.70) (4.67)

bottom water 3 1 2 4

(5.25) (5.01) (3.94) (3.93)

HI-A389

surface water 3 1 4 2

(5.12) (5.07) (4.88) (4.84)

mid-water No difference

(5.05)

near bottom 3 4 1 2

(3.71) (3.20) (2.94) (2.93)
concentrations during the summer samplings was also apparent at MU-A85

suggesting that platform-related hypoxia may be a common feature

associated with organic enrichment driven by the "reef effect" of the

platform structure. The oxygen data is summarized and described in

Section 5.1.

6.1.5 Suspended Particulate Matter

Much of the suspended sediment observed in shelf waters enters the

Gulf via the Mississippi and Atchafalaya Rivers, with smaller amounts

contributed by other rivers, bay discharges, and coastal erosion. Most of

these sediments are initially deposited close to the point where they

entered the Gulf. Shelf currents resuspend the sediments, resulting in

westward transport of the fixie-grained fraction by the mean flow (Adams et

al. 1982). Suspended sediments can be examined using light scattering data

(Plank et al. 1972). Light transmission is another technique (Pak and

Zaneveld 1977) that has been used on the Texas-Louisiana shelf. Continuous

measurements of light transmission (beam attenuation coefficient) show that

suspended sediment is often concentrated in layers within the water

column. Called nepheloid layers, these have relatively high light scattering

and low light transmission. On the Texas shelf, suspended sediment is often

concentrated into surface nepheloid layers associated with Texas river and

bay discharges, in bottom nepheloid layers across the shelf due to sediment

resuspension and advection by shelf currents, and in intermediate nepheloid

layers over the slope, resulting from off-shelf transport of the bottom

nepheloid layer (Shideler 1981; McGrail and Carnes 1983; Sahi and Merrell

1987; Halper et al. 1988). On the Texas-Louisiana shelf several processes

have been identified as important in nepheloid layer transport, which are:

(1) lateral shelf water exchange processes (Shideler 1979); (2) diffusion and

ebb-tide discharge from coastal inlets (Shideler 1978); (3) coastal currents

associated with the passage of meteorological fronts (Holmes 1982); and (4)

bottom Ekman upwelling at the shelf edge.

Few differences in percent light transmittance were apparent in

relation to distance from the platform or cruise (Table 6.17). At MU-A85

transmittance was lower in close proximity to the platform and higher close

to the platform at HI-A389 in mid and surface waters. Little cruise effect

6-28
Table 6.17. Tukey's multiple comparison test results for each site and water depth by distance and by cruise for transmittance (%).

MAI-686

near surface No difference

mid-water No difference

near bottom No difference

(64)

MU-A85

near surface 500 m 200 m 3000 m 50 m 100 m

(84.3) (83.9) (83.7) (81.0) (79.8)

mid-water 500 m 200 m 3000 m 50 in 100 m

(85.6) (84.9) (84.8) (83.3) (81.1)

near bottom No difference

(77.0)

HI-A389

near surface

mid-water

near bottom

lOOm 50m 3000m 20Cm 500m

(84.1) (81.6) (77.7) (78.0) (73.9)

lOOm 50 m 200 m 500 in 5000 in

(84.7) (82.1) (82.1) (81.4) (81.1)

No difference

(78.0)

aDeansfoed means are presented (x) and means that are underlined are not different at

the 0.05 level.

6-29

Site/Water Depth Distaneea
Table 6.17. (Cont.)

(77.0)

aDefransfoed means are presented (x) and means that are underlined

are not different at the 0.05 level.

was apparent in transmittance in the summer samplings at MAI-686.

Transmittance decreased in bottom waters compared to surface waters at all

sites, reflecting the presence of a near bottom nepheloid layers.

Transmittance data is summarized and described in detail in Section 5.1.

6.2 Sedimentology and Contaminant Chemistry

A series of independent, abiotic variables were measured in sediments

to aid in defining perturbations related to the presence of a platform and to

provide a framework for the interpretation of concurrent biological studies.

6-30

Site/Water Depth Cruisea

MAT- 68 6

nearsurface 4 2 1 3

(85.3) (80.7) (70.3) (59.4)

mid-water 4 2 1 3

(85.7) (81.4) (72.1) (60.0)

near bottom 4 1 2 3

(72.6) (65.7) (63.3) (49.8)

MU-A85

near surface 1 4 3 2

(87.1) (84.4) (83.6) (75.7)

mid-water 1 4 3 2

(88.1) (85.8) (83.7) (78.3)

near bottom 4 1 2 3

(81.3) (78.3) (73.5) (73.4)

HI-AS 89

near surface 3 4 2 1

(86.4) (81.4) (77.1) (73.8)

mid-water 4 3 2 1

(88.8) (87.4) (77.8) (77.6)

near bottom No difference
Abiotic variables measured in sediments included grain size, mineralogy,

organic and inorganic carbon content, redox potential, and contaminant

concentrations. Data for these variables are summarized and described in

detail in Sections 5.2 and 5.3.

Sediment texture (i.e., grain size) is an important variable in the

evaluation of biological assemblage data and contaminant distributions in

benthic systems. Numerous studies have shown a strong correlation

between biology, chemistry, and sediment texture and quality. In benthic

ecosystem studies, cross-correlations between study sites are often

dependent on substrate characteristics. Correlation of biological response

variables with contaminant exposure can be confounded by the effects of

variations in substrate. The distribution of sands, muds, and hard bottoms

on the OCS off Texas has been known in general for many years. The

sediments on the continental shelf offshore of Texas were deposited by

marine processes of transport and deposition and are largely fluviai in origin.

Sediments consist primarily of quartz sands, silts, and clays with an

additional input of skeletal and fragmentary remains of organisms living on

and in the sediments. Organic and inorganic carbon content of sediments is

another important measure of sediment quality. The carbon content of

sediments near platforms may be influenced by organic enrichment (i.e.,

reef effect), disposal of drill mud and cuttings, and discharges from the

platform. The oxygen content of sediment pore water as measured by redox

potential is also an important factor in determining the quality of the

benthic substrate. Redox conditions also play an important role in the

mobffity and bioavailabffity of metals in the marine environment.

The release of petroleum to the surrounding environment can occur

during drilling as well as in the production phase of a platform's lifetime.

Petroleum hydrocarbons are potentially present in a variety of discharges

including drilling fluids, drill cuttings, produced water, spills, deck

drainage, and other releases. Hydrocarbons are a major constituent of

produced petroleum and as such might be expected to be a contaminant at

platform sites. Hydrocarbons are ubiquitous in the marine environment.

However, petroleum-derived hydrocarbons can be differentiated from

naturally occurring biogenic hydrocarbons (Brassell et aT. 1978; Philp 1985;

Boehm and Requejo 1986; Kennicutt and Comet 1992). Aliphatic

hydrocarbons synthesized by organisms (both planktonic and terrestrial)

6-31
include a suite of normal alkanes with odd numbers of carbons from fifteen

to thirty-three (33). Petroleum contains a homologous series of naikanes with one (1) to more than thirty (30) carbons with odd and even nalkanes present in nearly equal amounts. Petroleum also contains a complex

mixture of branched and cycloalkanes generally not found in organisms.

This complex mixture is detected as an unresolved complex mixture (UCM)

in gas chromatograms. The presence and amount of the UCM is a diagnostic

indicator of petroleum contamination but can also be derived in part from

indigenous biological lipids. Petroleum also contains an extensive suite of

polycyclic aromatic hydrocarbons (PAH) that are known to be toxic to

organisms. PAH are synthesized by organisms; however, petroleum PAH can

be easily differentiated by the structural complexity of the mixture. The

amount and composition of PAH can indicate the amount and type of

petroleum contamination. PAH, as the toxic component of oil, also indicate

the potential for biological effects in resident organisms. Based on

considerations of petroleum chemistry, biological occurrences of

hydrocarbons, and toxicological effects; aliphatic and aromatic hydrocarbons

were chosen as indicators of petroleum contamination near platforms.

Trace metals are also released to the environment in discharges from

offshore petroleum drilling activities. Metals represent a source of

enhanced, chronic contaminant exposure that can potentially impact both

infauna and epifauna in the vicinity of drilling platforms. Many of the trace

metals selected for analysis are priority pollutants (Ag, As, Cd, Cr, Cu, Hg,

Ni, Pb, Sb, Se, and Zn) that are nknown to be toxic to organisms and

discharged in drill muds. Tin (Sn) was included because of its potential

toxicity and its presence in antifouling paints. Barium (Ba) was selected as a

tracer of the particulate, settleable fraction of drilling discharges. Barium

(as bat-lie, barium sulfate) is the dominant component of drill mud (up to 90

% on a dry weight basis). Barium is an ideal tracer of the particulate

(settleable) fraction of discharged drilling fluids and cuttings because it

occurs in high concentrations in drill muds and has a low, natural

background in ambient sediments (200 to 500 ppm dry weight). Aluminum

(Al) and iron (Fe) as representative of alumino-silicate minerals were

monitored to document changes in sediment type. Vanadium (V) was

included because it can occur in high concentrations in crude oil. Sixteen

elements were measured in sediments, fourteen (14) in biota tissues

6-32
(except Al and Sb), and seven (7) in pore waters (Ba, Cd, Cu, Hg, Pb, V and

Zn).

6.2.1 Principal Component Analysis of Sediment and Contaminant

Variables

In order to provide the most effective variables to test covariation of

biological effects with benthic environmental variables, Principal

Components Analysis (PCA; SAS Institute Inc. 1990) was performed on

sedimentologic and contaminant variables together. PCA is effective in

defining interrelationships between sediment texture and contaminant

content and providing effective representation of variance in the data.

Sediment texture and contaminant content are closely coupled at platform

sites. Excess barium in sediments is directly attributable to discharges

during drilling activities. A suite of several metals characteristic of the

barite ore strongly covaty with barium (see Section 5.3). There was strong

evidence based on visual examination and chemical analysis that a major

portion of the hydrocarbons deposited in the sediments were intrinsic

components of the drill cuttings discharged during drilling activities. The

bulk of the sand size particles were visually identifiable as cuttings; thus the

anomaly in sediment sand content was closely coupled to discharges during

drilling (see Section 5.2). Sand may also be deposited with produced waters

or during sand blasting of the platform structure. Additionally, currents may

enhance sand content by preferential winnowing and transport of fines away

from the platform site. Based on these conceptual linkages, principal

components analysis was used to provide a reduced set of variables that

describe the spatial pattern of the platform-associated suite of contaminants.

The contaminant and sedimentologic data used for final PCA analysis

and score calculations were generated by a two-step data reduction

procedure. As previously discussed, many contaminant variables (individual

PAH and metals) strongly covary (see Section 5.3). The sediment trace

element data set was characterized by a strong covariance (both positive and

negative) with barium At both HI-A389 and MU-A85, several metals (Cd,

Hg, Pb, and Zn) showed highly significant, positive correlations with

sediment barium. For metals such as cadmium and mercury, the correlation

with barium suggested a common source in the barite ore. In contrast, the
lesser correlation of lead and zinc with barium suggested that a source (e.g.,

produced water discharges, lubricants, welding operations, etc.) other than

drilling discharges was important. Lead and zinc have been detected in

produced waters and are thought to be derived from the corrosion of

galvanized structures on the platform or the oil-water separator system (Neff

et al. 1981). Zinc is also a major metal in sacrifical anodes. Other metals

(i.e. Al, Fe, Cr, Ni, Se, and V) associated with indigenous sediments showed

weak, if any, correlations with barium. Finally, arsenic, copper, and tin were

of mixed origins based on correlations with both barium and sediment

metals (e.g., Fe). For copper, the correlation with barium was weak except

at high barium concentrations suggesting that the concentration of copper

in the original barite ore was low.

Initial statistical analysis suggested that inclusion of all measured

contaminant parameters might skew the resulting principal components

due to the high degree of variable covariation. To more accurately reflect

the consortium of materials present, strongly covarying parameters were

reduced in number by either summing (TOTPAH) or selecting

representatives of classes of contaminants as defined by statistical

correlations (i.e., barium as a marker of drill muds). This reduced data set

was then analyzed by PCA to provide a set of representative covariates that

could be correlated with results from other study elements (Table 6.18).

However, PCA conducted at all levels of complexity (all variables, reduced

variables, extended sets of variable) produced similar classifications of the

data and thus led to equivalent interpretations. The consistency in the

conclusions drawn from a variety of statistical treatments illustrates the

robustness of the conclusions to changes in analytical design.

An important observation was that sand content positively correlated

with contaminant content. This contrasts with most environmental studies

where contaminants are associated with fine-grained particles. This was a

consequence of the origins of the contaminants, the composition of the

materials discharged, the rapidity of the initial discharge, and the

energetics of sediment transport at the site of deposition. A gradient in

sand content was present at all three sites studied; however, the

contaminant gradient was quite different between sites with little or no

contaminant gradient apparent at MAI-686. This resulted from differential

redistribution of discharged materials based on grain size association,

6-34
Table 6.18. Principal Component Analysis (PCA) factor patterns for reduced

and combined sediment and contaminant variables (all variables

were transformed as summarized in Section 2.0).

discharge history, and discharge technique. At MAI-686 the barium anomaly

was weak, suggesting loss of silt-sized materials due to winnowing. Timing

of discharges, mode of discharge, and the amount of materials discharged

are also important influences on sediment characteristics and cannot be

fully resolved by the present study.

A crossplot of ChemPC 1 versus ChemPC2 clearly differentiates the

stations by distance from plat.form and by site (Figure 6.1). Translated into

the variables measured, contamination increases as ChemPCl increases (i.e.,

near stations are more contaminated with hydrocarbons, metals, and sand

than far stations). Grain size decreases with distance from the platform. As

ChemPC2 increases, fines increase and the sites were classified based on

water depth and depositional setting.

6.2.2 Hypothesis Testing

As demonstrated by statistical analysis, many sediment contaminant

variables covaly. Thus, representative contaminant and sedimentologic

parameters and PC scores were used to test the chemistry component of the

programmatic hypotheses (Tables 6.19 to 6.21) The overall study design

was tested to detect interactions among cruises, platforms, and distances

from platforms (Table 6.19). Higher order interactions prohibited a direct

interpretation of the main study design elements such as distance. The

6-35

Variable ChemPCl ChemPC2

Total PAH 0.60 0.54

Total UCM 0.79 0.38

Total Alkanes 0.79 0.20

% Sand 0.85 -0.48

% Silt -0.61 0.58

% Clay -0.88 0.30

TOC -0.50 0.63

TIC 0.08 0.64

Redox Potential -0.26 0.03

Iron (Fe) -0.61 0.58

Cadmium (Cd) 0.69 0.64

Aluminum (Al) -0.86 -0.05

Barium (Ba) 0.54 0.71

% of Variance 43.6 % 24.7 %
Figure 6.1. Relationship between ChemPC 1 and ChemPC2 for sediment contaminan

distance and grouped by site.
Table 6.19. Summary of the significance of interactions by distance at all

platforms for the overall study design based on sedimentology

and contaminant data.

principal component, ChemPC2-second principal component, TOTPAH-sum of all measured PAIl, TOTUCM- unresolved complex mixture, TOTALK-sum of all resolved alkanes measured, Ba-barium, Fe-iron, Cd-cadmium, Al-aluminum, %

sand-sand content, % silt-silt content, % clay-clay content, TOCtotal organic carbon, TIC-total inorganic carbon, Redox-Eh

measured by platinum electrode.

bppjatform, C=Cruise, D=Distance, R=radius; Yes=significant, p

0-01; No=not significant, p > 0.01.

Interactionsb

Variablea CtD P*D P*C*D D*R(P)

ChemPCl Yes Yes No Yes

ChemPC2 No Yes No Yes

TOTPAH No Yes No Yes

TOTUCM Yes Yes Yes Yes

TOTALK No Yes No Yes

Ba No Yes No Yes

Fe No No No Yes

Cd No Yes No Yes

Al Yes No Yes Yes

%Sand No No No Yes

% Silt No Yes Yes Yes

% Clay No No Yes Yes

TOC Yes No Yes No

TIC Yes No No No

Redox No Yes Yes No
Table 6.20. Summary of the significance of interactions by platform for the overall study design based on sedimentology and contaminant data.

aSee Table 6.19 for variable definition.

bSee Table 6.19 for definition of variables and symbols.

Site

Interactionsb

MAI-686 MU-A85 HI-A389

Variablea C*D D*R C*D*R CtL) D*R C*D*R C*D DSR C*D*R

ChemPCl No Yes Yes No Yes Yes No Yes Yes

ChemPC2 No Yes Yes No Yes Yes No Yes Yes

TOTPAH No No Yes No Yes No No Yes No

TOTUCM No Yes Yes Yes Yes No Yes Yes Yes

TOTALK No Yes Yes No Yes No No Yes No

Ba No Yes Yes No Yes Yes No Yes No

Fe No Yes Yes No Yes Yes No Yes Yes

Cd No Yes No No Yes Yes No Yes Yes

Al No Yes Yes No Yes Yes No Yes Yes

% Sand No Yes Yes No Yes Yes No Yes Yes

% Silt No Yes Yes Yes Yes Yes No Yes Yes

% Clay No Yes Yes Yes Yes Yes No Yes Yes

TOC No Yes Yes Yes No No Yes No Yes

TIC No Yes No No No No Yes Yes No

Redox Yes No Yes No No Yes No No Yes
Table 6.21. Summary of the significance of distance at platforms based on

sedimentology and contaminant data.

Variablea

ChemPCl

ChemPC2

TOTPAH

TOTUCM

TOTALK

Ba

Fe

Cd

Al

%Sand

%Silt

%Clay

TOC

TIC

Redox

Siteb

Yes

aSee Table 6.1 for variable definition

bSee Table 6.29 for definition of variables and symbols, "---" not testable due

to higher interactions

MAI- 686 MU-A85 HI-A389
analysis of hydrocarbons, trace metals, grain size, carbon content, redox

conditions, and PC scores based on contaminants and sedimentology

revealed many two- and three-way interactions (Table 6.19). Significant

interactions due to platform uniqueness were common. Distance and radius

interactions were present for all variables except TOC, TIC, and redox in a

test of the overall study design. This suggested that many parameters vary

not only in relationship to distance from the platform, but also among radii

within a site. Due to extensive higher order interactions, more detailed can

be provided if the data is tested on a site-by-site basis.

On a site-by-site basis, significant distance effects were clearly evident

at all sites (Table 6.20). In general, significant effects related to distance

were independent of the site in that the analysis of data individually at all

three sites gives similar and concordant results. The only variable exhibiting

no higher order interactions was TIC at MU-A85 and distance (D) was

significant (Table 6.21). Few interactions between cruise and distance were

apparent but distance interactions with radius were significant at all sites for

almost all contaminant and sedimentologic variables. This signifies that

most "platform-perturbed" variables had a strong directional orientation

since distances were not equivalent along different radii. While distance was

a significant determinant in variable variances, more direct indicators of

contaminant and sedimentologic properties must be used to investigate

biological associations (i.e., distance is insufficient as a surrogate for

conthmination or exposure).

Another approach for identifying differences among sample means is a

multiple comparison test. The technique of choice was Tukey's multiple

comparisons (see Section 2.0). These comparisons are effective in

summarizing and highlighting among distances and among site differences.

The Tukey's test results succinctly illustrate the attributes of each study site.

An evaluation of the overall study design is presented first in order to assess

the generality of the observed trends. ChemPC 1 clearly ordered the stations

by increasing distance from the platform (Table 6.22). ChemPC2 ordered

the data most effectively by site and reflected the effects of water depth and

the increasing clay and silt content of sediments in deeper waters (Table

6.23). ChemPC2 was confounded in that the distribution of sand was also

related to distance from the platform. Hydrocarbon based variables

differentiated stations out to 500-rn. Stations at greater than 500-rn

6-40
Table 6.22 Tukey's multiple comparison test results by distance for the overall study

design based on sedimentology and contaminant data.

aSee Table 6 19 for definition of variables

bOetransformed means are presented (x) and means that are underlined are not

different at the 0.05 level.

Variablea Distance from the platformb

ChemPCl 50 in 100 m 200 m 500 m 3000 in

(1.32) (0.66) (-0.30) (-0.77) (-0.90)

ChernPC2 200 m 500 m 50 m 3000 m 100 m

(0.17) (0.04) (0.00) (-0.05) (0.16)

TOTPAH 50 in 100 m 200 m 500 m 3000 in

(ppb) (114) (73) (48) (35) (35)

TOT(JCM 50 in 100 m 200 m 500 m 3000 m

(ppm) (29) (14) (6) (3) (3)

TOTALK 50 in 100 m 200 m 500 in 3000 m

(ppb) (925) (433) (265) (199) (179)

Ba 50m lOOm 200m 500m 3000m

(ppm) (10,217) (6065) (4359) (2019) (1149)

Fe 3000 m 500 m 200 m 50 m 100 m

(ppm) (27,900) (27,686) (25,232) (20,436) (19,825)

Cd 50 in 100 m 200 m 500 m 3000 m

(ppm) (0.73) (0.25) (0.13) (0.07) (0.06)

Al 3000 m 500 m 200 m 100 m 50 in

(ppm) (61,248) (61,175) (54,776) (41,680) (33,982)

Sand 50m lOOm 200m 500m 3000m

(%) (60.5) (49.2) (21.9) (13.8) (12.6)

Silt 3000jn 500m 200m lOOm 50m

(%) (36.7) (36.6) (35.4) (24.7) (21.5)

Clay 3000m 500m 200m lOOm 50m

(%) (48.5) (47.4) (40.4) (24.7) (16.8)

TOC > 3000 m 500 m 200 m 100 m 50 m

(%) (1.02) (0.98) (0.89) (0.69) (0.61)

TIC 100 m 50 m 200 in 500 m 3000 m

(%) (1.07) (1.00) (0.83) (0.79) (0.75)

Redox 3000m 200m lOOm 500m SOm

(my) (100.0) (98.4) (82.2) (75.4) (55.1)
Table 6.23. Tukey's multiple comparison test results by platform for the overall study design based on sedimentology and contaminant data.

aSee Table 6.19 for variable definition

bDeansfoed means are presented (x) and means that are

'underlined are not different at the 0.05 level.

6-42

Variablea Platformb

ChemPCl MAJ-686 MU-A85 HI-A389

(0.11) (-0.01) (-0.10)

ChemPC2 HI-A389 MU-A85 MA1-686

(+1.04) (-0.02) (-1.02)

TOTPAH lil-A389 MU-A85 MAI-686

(ppb) (70.7) (60.8) (38.5)

TOTUCM HI-A389 MU-A85 MAI-686

(ppm) (8.7) (8.2) (52)

TOTALK MAI-686 MU-A85 HI-A389

(ppb) (339) (337) (307)

Ba HI-A389 MU-A85 MAI-686

(ppm) (9874) (3693) (1307)

Fe HI-A389 MU-A85 MAI-686

(ppm) (27,244) (23,947) (21,082)

Cd HI-A389 MU-A85 MAI-686

(ppm) (0.40) (0.12) (0.08)

Al MU-A85 HI-A389 MA1-686

(ppm) (51,694) (48,218) (48,016)

Sand MAI-686 MU-A85 HI-A389

(%) (46.2) (31.3) (14.9)

Silt HI-A389 MU-A85 MAI-686

(%) (36.9) (33.4) (22.6)

Clay HI-A389 MU-A85 MAI-686

(%) (44.1) (31.7) (29.3)

TOC HI-A389 MU-A85 MAI-686

(%) (1.2) (0.8) (0.6)

TIC HI-A389 MU-A85 MAT-686

(%) (1.9) (0.8) (0.3)

Redox MU-A85 HI-A389 MAJ-686

(my) (91.5) (91.4) (63.6)
distance from the platform were indistinguishable from each other (i.e.,

background). Barium content differentiated all distances, suggesting a much

wider dispersion of barium. Iron and aluminum, as background sediment

constituents, reflected a near-field dilution caused by the addition of sand.

However iron, in general, was only diluted 30 % compared to a 45 %

dilution in aluminum, suggesting a secondary source of iron near the

platform. Cadmium distributions were similar to those of barium and

differentiated sediments at all distances. The distribution of Cd and Ba was

similar to that observed for sand content. However, note that Ba and Cd

increased by a factor of 10 or more over controls and sand increased by a

factor of 5. Sediment silt and clay content reflected the dilution with sand;

but also exhibited independent behaviors. Sand content differentiated

sediments to 3000 m, whereas silt only differentiated sediments to a

distance of 500-rn. The distance of recognizable differences based on

various size fractions suggested a differential influence of transport

processes related to the hydraulic properties of the materials. Various size

fractions were also influenced to varying degrees by contaminant additions.

both as enhancements and dilutions. To more fully understand the origin of

sediments at the sites, the distributions of selected variables within grain

sizes is needed.

Carbon content distributions also reflected multiple processes. In the

most general case, organic carbon decreased and inorganic carbon increased

toward the platform. Organic carbon may be decreased due to dilution from

sand and/or remineralization. Note that TOC decreased by only 30 % and

yet sand and metals were increased by factors of 5 to 10 or more, suggesting

a possible additional source of TOC at the platforms. Organic carbon

increases in response to the deposition of the remnants of primary

production, enhanced biological productivity associated with the platform.

and perhaps microbial production with the structure acting as a "reef." An

additional source of TOC in cuttings was possible but the importance of this

source is unknown. Total inorganic carbon content (TIC) was subject to the

sand dilution events; however, TIC had an additional source in debris from

platform-associated biota such as barnacles and serpulids. Carbonate

contributions from cuttings were also a source of inorganic carbon as

illustrated by the close correlation between the sand and TIC content in

sediments. TIC was enhanced by 30 % on average for all sites; however, the

6-43
input may be substantially higher since the increase was counteracted by the

sand dilution events.

Redox potential is difficult to interpret but the two deeper sites

appeared to be more oxygenated in general than the shallow water sites.

This is consistent with observed hypoxic events at MAI-686.

A site-by-site analysis of Tukey's test results provides insight into the

attributes of individual sites and are useful in interpreting biological

patterns. The variation in contaminant patterns at MAI-686 confirmed

previous interpretations, PAR were low and not significantly associated with

distance from the platform (Table 6.24). Other hydrocarbon parameters

were somewhat correlated with distance but the association was weak and

most likely primarily related to a pipeline leak or seep previously identified

along radius D that was not a site-wide contaminant event. Metals believed

associated with drill muds (Ba and Cd) were only weakly correlated with

distance: stations within 200-rn were differentiated from stations that were

further away. However, a coherent ordering of stations was not apparent.

Sediment associated metals (Fe and Al) reflected dilution with sand, and the

sand content differentiated sediments out to as far as 3000-rn. As in the

overall design tests, TOC decreased and TIC increased with decreasing

distance from the platform but only weakly at MAI-686. Redox conditions

showed little trend. In general, lower redox potentials were measured at

stations closest to the platform. At this site the increases and decreases in

variables were relatively concordant, suggesting a common depositional

event (i.e., Fe and Al concentrations decreased by 40 %; sand content

increased by a factor of 2.6).

MU-A85 clearly had enhanced contaminants concentrations near the

platform (Table 6.25). Hydrocarbon concentrations were significantly

higher near the platform than away. The effect was most significant to 100-

m. The 200-rn stations were not significantly different from the 500-rn

stations for all hydrocarbon variables other than 11CM which differentiated

sediments to a distance of 500-rn. Barium and cadmium concentrations

differentiated sites to 500-rn and in the case of barium, out to 3000-rn

distance. This distribution was similar to changes in sand content. Iron and

aluminum were diluted in response to the increase in sand content close to

the platform. TOC was lower near the platform ( 100 rn) and TIC was

increased. Sediment redox potential showed little trend but redox potential

6-44
Table 6.24. Tukey's multiple comparison test results by distance based

sedimentology and contaminant data at MAI-686.

aSee Table 6.19 for variable definition

bDefransfol-med means are presented (x) and means that are underlined

are not different at the 0.05 level.

Variablea Distanceb

ChemPCl 50 m 100 in 200 in 500 m 3000 in

(1.00) (0.4) (0.04) (-0.44) (0.49)

ChemPC2 3000 in 500 m 200 m 100 m 50 m

(0.64) (-0.66) (-0.73) (-1.40) (-1.65)

TOTPAH 3000 in 500 m 200 in 50 in 100 m

(ppb) (49) (43) (40) (32) (30

TOTUCM 50 in 200 m 100 in 3000 m 500 in

(ppm) (8.4) (6.3) (5.2) (3.8) (3.8)

TOTALK 50 m 100 in 200 m 500 m 3000 in

(ppb) (596) (382) (362) (236) (231)

Ba 200 m 50 m 100 in 500 in 3000 in

(ppm) (1625) (1459) (1323) (1134) (1072)

Fe 3000 m 500 in 200 in 100 m 50 in

(ppm) (25,563) (24,929) (22,050) (18,882) (15,700)

Cd 50 m 200 m 100 m 500 in 3000 in

(ppm) (0.13) (0.11) (0.09) (0.06) (0.05)

Al 500m 3000m 200m lOOm 50m

(ppm) (59,742) (57,457) (50,599) (42,078) (34,922)

Sand 50 in 100 m 200 in 500 m 3000 m

(%) (72.8) (59.8) (40.8) (30.6) (27.4)

Silt 3000 in 500m 200m lOOm 50m

(%) (30.3) (30.1) (25.5) (16.5) (12.8)

Clay 3000 in 500m 200m lOOm 50m

(%) (41.3) (39.1) (32.7) (22.7) (13.9)

TOC 3000 m 500 in 200 m 100 m 50 m

(%) (0.79) (0.78) (0.65) (0.42) (0.35)

TIC 50 in 100 in 200 in 500 in 3000 in

(%) (0.36) (0.31) (0.30) (0.23) (0.19)

Redox 100 m 50 m 3000 m 200 in 500 m

(my) (85.1) (61.8) (59.9) (58.7) (52.4)
aSee Table 6.19 for variable definition

bDejsfoed means are presented (x) and means that are underlined are

not different at the 0.05 level.

Table 6.25. Tukey's multiple comparison test results by distances based on

sedimentology and contaminant data at MU-A85.

Variablea Distanceb

ChemPCl 50m lOOm 200 m 500m 3000m

(1.47) (1.00) (-0.53) (-0.95) (-1.03)

ChemPC2 200 in 500 m 50 m 3000m lOOm

(0.09) (0.02) (-0.01) (-0.08) (-0.13)

TOTPAH 50 m 100 in 200 in 500 m 3000 m

(ppb) (180.9) (126.4) (42.3) (31.7) (27.1)

TOTUCM 50 m 100 m 200 m 3000 in 500 m

(ppm) (56.4) (30.9) (4.1) (2.2) (2.4)

TOTALK 50 in 100 m 200 m 500 m 3000 m

(ppm) (1473) (601) (205) (171) (142)

Ba 50 m 100 m 200 m 500 m 3000 in

(ppm) (10.064) (9263) (3706) (1817) (1094)

Fe SOOm 3000m 200m 50m lOOm

(ppm) (27,867) (27,587) (25,473) (21,822) (18,429)

Cd 50m lOOm 200m 500m 3000m

(ppm) (0.46) (0.25) (0.07) (0.05) (0.05)

Al 500 m 3000 m 200 m 100 m 50 in

(ppm) 64,119) (63,386) (57,971) (41, 956) (37,339)

Sand 50m lOOm 200m 500m 3000m

(%) (67.0) (54.8) (20.80) (12.2) (11.6)

Silt 500m 3000m 200m lOOm 50m

(%) (43.1) (42.9) (40.7) (26.0) (16.7)

Clay 3000m 500m 200m lOOm 50m

(%) (45.1) (44.4) (38.2) (19.0) (15.8)

TOC 3000 m 500 m 200 m 100 m 50 m

(%) (0.93) (0.92) (0.90) (0.62) (0.55)

TIC 50 m 100 m 500 in 200 m 3000 m

(%) (1.02) (0.86) (0.79) (0.78) (0.77)

Redox 200m 3000m 500m 50m lOOm

(my) 132.0 (111.8) (97.9) (60.7) (55.3)
was generally lower near the platform. At this site sand and barium

concentrations increased by 5 and 10 fold; however Al, Fe, and TOC

decreased are only 25 to 50 %.

HI-A389 sediment characteristics reflected the intensity of the

contaminant discharges, near bottom shunting, and the low energy

environment of deeper water (Table 6.26). Total PAIl concentrations

differentiated sediments to 500-rn, and IJCM concentrations were

significantly different to 5000-rn. Barium and cadmium concentrations

differentiated sediments to a distance of at least 5000-rn. As at the other

sites, iron and aluminum contents reflected dilution by sand. TOC, TIC,

sand, and redox showed little trend at this site; however, the overall pattern

was consistent with that observed at the other sites, although not

statistically significant.

Based on these statistical comparisons the characteristics of each site

are summarized in Table 6.27.

6.2.3 Spatial and Temporal Variations in Sediment Contaminants

Changes in sediment chemistry are long-lasting perturbations that are

associated with the drilling phase of a field's development and production.

The discharges input both coarse (cuttings) and fine-grain (drilling muds)

sediments to areas of the Gulf of Mexico continental shelf that have low

natural sedimentation rates (<< 1 cm per year). No drilling mud discharges

have occurred at these sites for 12 (MAI-686), 7 (MU-A85), or 6 (HI-A389)

years, respectively. These observations are consistent with the permanence

of the sand lens observed at exploratory sites where no further production

occurred and the platform was removed after drilling (Shinn et aT. 1993). At

these sites, enhancement of sand and barium was evident more than ten

years after removal of the platform (see additional historical comparisons

below).

Contamination, and other perturbations at a site, are expected to

exhibit significant three dimensional variability. Subsurface pockets of

contaminants not adequately represented by a 0 to 2 cm sampling interval

could be influencing biotic patterns in the overlying sediments. To define

the three-dimensional distribution of contaminants at each study sites, subsurface samples were taken to a depth of 20 cm in 2 cm intervals along

6-47
aSee Table 6.19 for variable definition

bDefransfojjiied means are presented (x) and means that are underlined

are not different at the 0.05 level.

Table 6.26. Tukey's multiple comparison test results by distance based on

sedimentology and contaminant data at HI-A389.

Varlablea Distance from the Platfonnb

ChemPCl 50 m lOOm 200 m 500 m 5000 m

(1.46) (0.53) (-0.41) (-0.92) (-1.18)

ChemPC2 50 m 200 m 100 m 500 m 5000 m

(1.65) (1.17) (1.05) (0.77) (0.57)

TOTPAH 50 m 100 m 200 m 500 m 5000 m

(ppb) (256) (103) (65) (33) (32)

TOTUCM 50 m 100 m 200 m 500 m 5000 m

(ppm) (51.7) (15.6) (7.8) (3.6) (2.1)

TOTALK

(ppm)

50 m 100 m 200 in 500 m 5000 m

Ba 50 m 100 m 200 m 500 m 5000 m

(ppm) (72,605) (18,196) (13,756) (3993) (1293)

Fe 5000m 500m 200m 50m lOOm

(ppm) (39,794) (30,552) (28,601) (24,911) (22,388)

Cd 50 m 100 m 200 m 500 m 5000 m

(ppm) (6.4) (0.65) (0.29) (0.11) (0.08)

Al 5000 in 500m 200m lOOm 50m

(ppm) (63.082) (59,776) (56,027) (41,011) (30.091)

Sand 50m lOOm 200m 500m S000m

(%) (40.3) (33.4) (8.5) (3.9) (3.5)

Silt 200m 50m 5000m 500m lOOm

(%) (40.6) (37.2) (37.1) (37.0) (32.4)

Clay 5000 m 500 m 200 m 100 m 50 m

(%) (59.1) (58.9) (50.4) (33.1) (21.0)

TOC 5000m 500m 200m lOOm 50m

(%) (1.40) (1.27) (1.19) (1.13) (1.02)

TIC lOOm 50m 200m 500m 5000m

(%) (2.66) (1.96) (1.71) (1.66) (1.62)

Redox 5000m LOOm 200m 500m 50m

(my) (128.2) (106.0) (104.5 (75.80) (42.7)
Table 6.27. General characteristics of the study sites.

radius "C" during Cruise 3. The distribution of barium with depth in the

sediment column is illustrated in Figure 6.2. The discharged drilling muds

and cuttings (enriched in barium) formed a thin veneer of material 10 to 15

cm thick near the platforms which thinned with distance from the platform.

This was also true for the hydrocarbons with most of the hydrocarbons

residing in the top two centimeters of the sediment column. Two sites

(MAI-686 and MIJ-A85) exhibited sub-surface barium maxima illustrating

the heterogeneous nature of contaminant distributions. The threedimensional nature of the contaminant distributions suggest that

assessments of exposure might be more accurately expressed as amount per

square meter of surface area or cubic meters of sediment volume integrated

over a defined near-field area (i.e., out to a distance of 100 m). The

sediment column, especially at the deeper water sites (MU-A85, HJ-A389),

was not well mixed with respect to barium despite the long time since

cessation of drilling activities. This observation confirms that the

sedimentary contaminant field is quite stable over periods of years. Previous

research (Boothe and Presley 1985) has shown fine, undisturbed barite

6-49

MAL- 686 MU-A85 HI-A389

Physical Attributes

-water depth 29-rn 80-rn 125-rn

-offshore nearshore intermediate offshore

-energy setting high med-low low

-seasonal effects medium low

-shunting depth near surface near bottom near bottom

-time since last drilling 12 y 7y 6y

Physicochemical

-oxygen levels in bottom waters seasonal seasonal oxycline

hypoxia hypoxia impingement

-organic carbon decrease Yes Yes maybe

-inorganic carbon enrichment Yes Yes

Contaminants (within 100 m of the platform)

-hydrocarbons low low medium

-trace metals low medium very high

-sand gradient high high high
20

I I I I I I

I I

I

I I II I I 0 200 400 600 800 1000 1200 1400 1600 1800

20

I I I I II I I I I j

I I I I I I I I I I I II I I

Barium (ppm Dry Wt.)

Figure 6.2. Distribution of barium concentrations (ppm) with depth in

the sediment column at all three sites.

6-50

0 1000 2000 3000 4000 5000 6000 7000 8000

0 10000 20000 30000 40000 60000

I I

I I 50000

T I J-1 I I I I I T I I I I II I
laminations in the sediment column up to a decade after the cessation of

drilling discharges.

Based on samples taken in 1980 prior to the cessation of drilling,

Table 6.28 shows that even though more barite was used at the shallow

water sites (MAI-686 and MU-A85), the greatest accumulation of barium

occurred at the deep water HI-A389 site. Also only a small fraction of the

totai barium discharged at any site was retained within the near-field (<500

m distance) sediments. Additional drilling at the sites (i.e. a total of 18, 6

and 12 wells at MU-A85, HI-A389 and MAI-686 respectively) did not

change the relative intensity of the contaminant fields observed at the three

sites in 1980.

Table 6.28. A mass balance of excess barium in sediments at the three study

sites (after Boothe and Presley 1985).

aDrified by 1980

1Tota1 Barium Used (TBIJ) in Drilling Activities 1.000 kg

6.2.4 Comparative Evaluation of Contaminant Levels at Platform Sites

A further evaluation of the contaminant levels observed in this study is

provided by a comparison with other, similar studies and with sediment

levels known to elicit biological effects. While biological effects were

directly measured, comparison with literature values provides an assessment

of potential for effect or impact.

6.2.4.1 Hydrocarbons

The concentration of total PAH at the study sites is presented as a

frequency distribution along with sediment PAH concentrations from the

NOAA National Status and Trends (NS&T) Program and the Environmental

Protection Agency's (EPA) Environmental Monitoring and Assessment

6-51

Site Water

Depth

Welisa TBUb %TBU

50Om

%TBU

@l000m

MU-A85

HI-A389

MAL-686

75

124

29

1

2

8

820

618

2,334

1.3

5.5

0.93

3.8

13.0
Program-Near Coastal (EMAP-NC) programs (Figure 6.3). Sediment total

PAH concentrations at the platform sites were generally less than 1,000 ppb

with only a few exceptions close to the platform at HI-A389 and MU-A85.

The EMAP-NC data represents 183 sites along the Gulf Coast collected on a

probability based sampling design. As expected the median PAH

concentrations in shelf sediments were nearly an order of magnitude lower

than in coastal areas of the Gulf of Mexico. However, at a few locations, PAH

concentrations at the platform sites approached the highest values observed

n coastal bays.

The PAR values observed at the platform sites were significantly below

the Long and Morgan (1990) 10 % biological effects criteria of 4000 ppb

(Figure 6.3). These effects criteria are based on a compilation of chemical

concentrations observed, or predicted, to be associated with biological

effects (broadly defined). Note that the definition of total PAH is highly

variable and that these values only serve as a semi-quantitative guide. The

10 % criteria is defined as the level at which biological effects were

observed 10 % of the time. Long and Morgan (1990) also note that

compounds such as PAH, which may be mutagenic or teratogenic, may not

be toxic in acute tests of mortality.

6.2.4.2 Metals

For sediment metal data two types of comparisons were made. First,

the data were compared with sediment data from previous Gulf of Mexico

platform monitoring studies conducted at sites with similar drilling

histories. This approach aids in determining if the perturbations observed

at the three study sites were similar to perturbations observed elsewhere.

Also, since some of the previous studies were conducted at sites that were

chosen for this study, changes in sediments over time can be evaluated.

Second, the data were compared to nearshore Gulf of Mexico sediment

metal data generated by the U.S. EPA-EMAP-NC program. This comparison

provides an evaluation of the degree to which drilling operations have

altered sediment metal concentrations compared to those found in coastal

sediments.

As previously discussed, trace element concentrations showed strong

correlations with sediment grain size. For example, trace element

6-52
100% 90%80% 70% C)o00. 50% 40% 30% 20%10%0% 1 - ER-L (1 990) GO

V EMA

+ NS&

1 I r I 111111 1 1 111111 111111 

10 100 1000 Total PAH (nglg) 10000 

Figure 6.3. Comparison of sediment PAH concentrations at GOOMEX sites to the NOA

Status & Trends arid EPA Environmental Monitoring and Assessment (EMAdatabases for coastal Gulf of Mexico sites.
concentrations were much higher in fine-grained, clay-rich sediments than

in coarse, sandy ones. This relationship was the result of both physical (i.e.,

surface area) and chemical (alumino-sihcate versus quartz minerals)

differences among the grain-size fractions in typical marine sediments.

Even in pristine, unperturbed sediments, metal concentrations will vary

considerably solely on the basis of differences in sediment texture.

Therefore, sediment contaminant levels must be compared after

normalizing the data to take into account differences in sediment texture.

One accepted normalization approach is to relate metal concentrations to

aluminum content. Aluminum is a major component of the minerals that

comprise most marine sediments (i.e., alumino-silicate clay minerals) and

occurs at concentrations at the percent level. It is unlikely that

anthropogenic inputs of aluminum would be sufficient to significantly alter

the indigenous concentrations of aluminum in sediments. Iron (Fe) is also a

percent level component of sediments and can be used as a normalization

factor for trace metal comparisons. However, a suspected source of iron

related to the platform makes these comparisons less useful. The

relationships between metal concentrations and aluminum content were

used to evaluate the sediment trace metal perturbations observed in the

present study. In the following graphical presentations stations within 100-

in of a platform are distinguished from those further away.

6.2.4.2.1 Comparisons with Previous Platform Monitoring

Studies

Two previous studies, with sufficiently reliable data, were available for

comparison. One study sponsored by the American Petroleum Institute

sampled sediments (40 stations in a radial pattern) surrounding six (6)

drilling sites in 1980 (Boothe and Presley 1985). Barium, chromium, and

iron were determined at all stations and aluminum, cadmium, copper,

mercury, lead, and zinc at a reduced number of stations. A second study,

conducted by Continental Shelf Associates investigated a drilling site at HIA384 near the West Flower Gardens in 1982 (CSA 1983). Barium and iron

were measured at 44 stations arranged in a similar radial pattern.

Chromium was determined at 17 stations.

The MAI-686 site was sampled in 1980 as part of the API study and

resampled as part of this study (1993 to 1994). Eight wells had been drilled

6-54
prior to the 1980 sampling. The characteristics of the ambient sediments

changed significantly during the 14 year period between samplings. Much

of the finer-grained sediment (Al and Fe rich) has been removed (Figure 6.4)

Evaluation of aluminum and iron content clearly showed a significant change

in sediment composition with essentially no overlap in compositions for the

two sampling events. The relationship between iron and distance from the

platform for the two studies confirmed this conclusion (Figure 6.4).

Essentially all of the elevated barium levels observed in 1980 within 125 m

of the platform were no longer present (Figure 6.5)- Barium levels beyond

125-rn were essentially unchanged over the 14 year period. Tb e

concentration of mercury showed the same decline as barium The

concentrations of cadmium, copper, and zinc also appeared to have

decreased between the two sampling events but the decrease was less

dramatic. Lead was the only element which increased over the 14 year

period suggesting a continuing, non-drilling discharge source for lead

(Figure 6.5). The change in sediment texture between 1980 and 1993 to

1994 was the result of a continuing process of sediment resuspension and

transport at this shallow water, high energy site.

Deeper water development and production sites from the 1980 API

study (High Island A341 and Vermifion 321) were selected for comparison

with the two remaining GOOMEX study sites (MU-A85 and HI-A389). The

API sites had similar drilling histories (HI-A341: 8 wells, V-321: 25 wells)

and sediment types (based on Al and Fe concentrations). These data sets

provided a comparison of metal distributions measured soon after the

cessation of drilling (API sites) and again 5 to 10 years later (GOOMEX sites).

The magnitude of the sediment barium enrichments within each pair of

sites was similar (Figure 6.6). The only significant difference in barium

enrichment was the anomalous 18-28 % barium enrichment at the HI-A389

site caused by shunting of the drilling discharges within 10 m of the seafloor

(Figure 6.6). The similarity in barium concentrations suggested that, for

sites with similar drilling histories and in deep water depositional

environments (i.e., 50-70 m and lower energy), there has been little

change in the ambient sediments over time. The temporal stability of

barium at the deeper water sites was also apparent for other elements.

Enrichments in chromium, cadmium copper, mercury, and zinc at the HIA341 and MU-A85 sites were similar. Again, as observed for the MAI-686

6-55
35000:

30000 -

? 25000: a - a - 20000: 0I15000L

10000 -

5000 -

0-

0

45000

40000-:

35000 -

30000 -

25000- a

20000-

2

15000 -

10000 -

5000 -

20000 30000

Aluminum (ppm)

111111111 I 70000 80000 90000

0 I I I 1111111 I I I 111111

1 10 100 1000

Distance (m)

10000

Figure 6.4. Relationship between sediment iron concentrations and

A: aluminum concentrations; and B: distance from the

platform at MAI-686 at two samplings 14 years apart.

6-56
600

500.-

400

=

0

0

200 0 0

0- e

:EAM

100

a0 ERL

Figure 6.5. Relationship between sediment barium arid lead concentrations

and distance from the platform at MAT-686 at two samplings 14

years apart.

6-57

10 100 10000

Distance (m)

100 1000 10000

Distance (m)

(ERL=effects range low; ERMeftects range medium; Long and Morgan, 1990)
E

20000-

15000-

10000 -

5000 -

300000

250000

HI-A389

4' APIV-321

CSA HI-A384

200000

0 I II ItII I II IIlIj

1 10 100 1000

50000-

0 liii I I I II I I III

1 10 100 1000

Distance (m)

Distance (m)

10000

Figure 6.6. Relationship between barium concentrations in sediment

collected immediately (l-II-A341, V-321, HI-A384) and 5-10

years after (MU-A85, HI-A389) cessation of drilling activities.

6-58

III

10000
site, the only exception is lead which was significantly higher at the MLJ-A85

site suggesting a continuing input of this element after the cessation of

drilling discharges (Figure 6.7). The relationship was similar at the more

highly enriched V-321 and HI-A389 sites. Even excluding the high barium

samples, lead levels were several fold higher at the HI-A389 site (Figure

6.7). In addition, cadmium and zinc levels were significantly higher at the

HI-A389 site suggesting a continuing input of these metals after cessation of

drilling operations.

The CSA study in 1982 (CSA 1983) suggested that the magnitude of

surface enrichments from drilling discharges among sites within similar

depositional environments (i.e., judged by water depth) were similar

regardless of the number of wells drilled. Differences in the amount of

drilling resulted in a thicker veneer of metal enriched sediments overlying

the native sediment, but no clear difference in the magnitude of surface

enrichment was apparent. This may indicate that the contaminant to inert

material ratio for the discharges was similar at the sites and that this

original concentration was the highest value possible at a site. The veneer of

materials on top of the indigenous sediments was primarily drilling

discharges. The CSA study sampled around a single exploratory well in lease

block HI-A384 while six wells were drilled at the GOOMEX HI-A389 site.

The two sites are in essentially identical depositional environments and

separated by only about 20-km distance. Both sites are in approximately

100 to 120 m of water and both are located in close proximity to a

topographic feature (West and East Flower Gardens, respectively). Finally,

the drilling discharges were shunted to within 10 m of the seafloor at both

sites. The surficial sediment barium distribution, an indicator of the

distribution of the drilling discharge contaminant field, was essentially

identical at both sites (Figure 6.6). Even the more than 20 % barium

enrichment caused by shunting was present at both sites. This comparison

is another indication of the stability of the contaminant fields at deeper

water sites. The CSA study was conducted immediately after drilling while

the sampling of HI-A389 reported here occurred almost 10 years after the

last drilling event. Although based on only two samples, the levels of

cadmium and lead also appeared to be quite similar and elevated above

suspected drilling discharge levels at the two sites.
450

400 -

350-

300 -

250-

200:

C, - _I - 150-

100 -

50-

0

1

700

600-

500-

200-

ERM

ERL

I I liii

U

U 1

U

U HI-A389

APIV-321

100

0

1 10

Distance (m)

41

11111 1 IIII

100 1000

I I (III

Distance (m)

(ERL=effects range low; ERM=effects range medium; Long and Morgan, 1990)

10000

6-60

Figure 6.7. Relationship between lead concentrations in sediment collected

immediately (HI-A341, V-321) and 5-10 years after (MU-A85,

HI-A389) cessation of drilling activities.

10 100

I I I III

10000

I I 11111

1000
6.2.4.2.2 Comparisons With Other Sedimentary Settings

Sediment samples were systematically collected from bays and

estuaries from the southern tip of Texas to western Florida as part of the

EPA EMAP-NC Program. An average of 168 samples were collected annually

from 199 1-1993 (total of 504 samples) and analyzed for a suite of metals

similar to those measured in the present study, except barium and

vanadium. The EMAP-NC data set provides a baseline of coastal Gulf of

Mexico sediment metal concentrations against which to compare data from

the present study.

Comparison of the this study and EMAP-NC sediment data sets,

normalizing to aluminum concentrations, revealed several conclusions

concerning sediment metal perturbations at the study sites. Significant

elevations in sediment concentrations were restricted to the near field

( 200 in) and did not involve all metals Sediments 200 m from the

platforms are generally indistinguishable from background Gulf of Mexico

sediments for all elements which could be compared (i.e., Ba and V not

determined in EMAP-NC). Several elements (Mn, Ni, Se, Sn) showed no

anomalous enrichments at any distance or platform site. The typical

relationship observed for this group of elements is illustrated for nickel in

Figure 6.8. Barium, lead, zinc, and to a lesser extent, cadmium showed

significant near field enrichments at all three platforms. Examples typical of

this distribution among the three sites are shown in Figures 6.8 and 6.9.

The enrichments are especially striking since they occurred in the coarser

sediments (sand) near the platforms. In undisturbed sandy sediments

(typically < 20,000 ppm Al), background metal concentrations are low. The

HI-A389 site showed significant enrichments for a larger suite of elements

including g, As, Cu, H, and Sb. A typical pattern for this group of

elements is shown in Figure 6.10. At MAI-686 and MU-A85, these elements

showed patterns veiy similar to those of the EMAP-NC sediments. At HIA389 and MU-A85, both chromium and iron concentrations were higher in

near-field sandy sediments relative to aluminum than is typical for

background Gulf of Mexico sediments (Figure 6.1 1). The additional

chromium and iron could be a characteristic of the formation solids

discharged as cuttings. A more likely explanation is that the chromium and
60

50

10

0

o HI-A389lOOm

HI-A389>lOOm

V EMAP

V

. V

1V

V

ERL

X MU-A85lOOm

* MU-A85>lOOm

V EMAP

ERL=5 ppm

ERM =9 ppm

Figure 6.8. Relationship between nickel and cadmium concentrations and

aluminum concentrations in sediments from HI-A389, MU-A85,

and EMAP-NC coastal samplings.

6-62

0 20000 40000 60000 80000 100000 120000

Aluminum (ppm)

0 20000 40000 60000 80000 100000 120000 140000

Aluminum (ppm)

(ERL=effects range low; ERM=effects range medium; Long and Morgan, 1990)

40

E

0.

30

a,

.0

z

20

V ERM

V
700

600-

? 400=- Q. -

-- 300-

200-

100-

0'

L

'I._,. !,u ! .' V

-- - TV ' -V V - -

(I iiv, i-i / /1/ / / I /11/,//fdffS V

I I

I I Aluminum (ppm)

6-63

Figure 6.9. Relationship between lead and zinc concentrations and

aluminum concentrations in sediments from HI-A389, MU-A85,

and EMAP-NC coastal samplings.

0 20000 40000 60000 80000 100000 120000 140000

Aluminum (ppm)

(ERL=effects range low; ERM=effects range medium; Long and Morgan, 1990)

0 20000 40000 60000 80000 100000 120000
4.0 3.5 3.0 V cv, /i AY.fffy7' /ffqffl/ 0 0 V 9 V V 0 V V 

0 V ODDV V V v ci VVV V i,i.!i'. yY-3l V v V 

I V4K77 

20000 40000 60000 80000 100000 

Aluminum (ppm) (ERL=effects range low; ERM=effects range medium; Long and Morgan, 1990) o Hl-A3

HI-A3

V EMAP Figure 6.10. Relationship between mercury and aluminum concentrations in sediments f

and EMAP-NC coastal samplings. D 0 D 0
80000

70000 -

60000 -

50000

E - 40000-

30000-

20000 -

10000- - !' ;1,;'7yv

V

I I

I

I j

I I I

I 0 I I 0 20000 40000 60000 80000 100000 120000

Aluminum (ppm)

0 I I I I

I I I I I I

I

I I I

I

I I I

I 0 20000 40000 60000 80000 100000 120000

Aluminum (ppm)

(ERL=effects range low; ERMeffects range medium; Long and Morgan, 1990)

140000

Figure 6.11. Relationship between iron and chromium concentrations

and aluminum concentrations in sediments from HI-A389,

MU-A85, and EMAP-NC coastal samplings.

6-65
iron are being added to the coarse sediment during the drilling process

probably from drilling fluids.

6.2.4.2.3 The Potential for Biological Effects Associated with the Observed Sediment Metal Levels

To assess the potential for biological effects from the observed nearfield sediment metal enrichments observed the data were compared to the

effects threshold data of Long and Morgan (1990). The ranges in metal

concentrations at the three sites were compared to the Long and Morgan

effects criteria and the EMAP-NC data in Figure 6.12. The percentage of

sediment samples that exceeded the Long and Morgan low (ER-L, 10 %) and

median (ER-M, 50 %) effects ratios were compared to the EPA EMAP-NC

sediment data (Figure 6.13). As expected from the comparisons discussed

above, several metals exceeded the effects levels in many of the near-field

sediment samples. Of these metals, lead and zinc exceeded the EMAP-NC

data at all three sites. The ranges of lead and zinc concentrations at the

sites were compared with those observed for the EMAP-NC data set in

Figures 6.12 to 6.13. These comparisons suggested that a significant

percentage of sediments at the study sites might elicit biological responses.

While these comparisons are informative they are not definitive for

predicting biological effects. Sediment metals may or may not be

bioavailable and a detailed evaluation of redox potential and metal speciation

is needed to determine a causal link between sediment metals and observed

biological effects.

6.3 Biological Accumulation of Contaminants in Megafauna

A second facet of the contaminant studies was documentation of the

contaminant levels in fish livers, fish stomach contents, and invertebrate

soft tissues at the study sites. The sampling scheme was reduced from the

more detailed boxcore design and animals were collected from trawls taken

Near ( 100 m or less) and Far from the platform ( 3000 m). Tissue

contaminant data are summarized and described in Sections 5.3.3 and 5.3.4.

Contaminant concentrations in tissues have been widely used to assess

the bioavailability of contaminants. Tissue contaminant concentrations are
MAI-686 MU-A85 HI-A389 EMAP MAI-686 MU-A85 HI-A389 EMAP MA1-686 MU-A85 Hl-A389 EMAP10% 50% 10 20 30 40 5

Cadmium (ppm) 

Figure 6.12. Comparison of the ranges of selected trace metal concentrations In sedim

GOOMEX study sites, EMAP-NC data, and Long and Morgan (1990) 10 % biological effects threshold. 10 15 20 25 30 Antimony (ppm) 2000 4000 6000 8000 

Zinc (ppm) 0 100 200 300 400 500 600 700 Lead (ppm)
100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

80%

70%

60%

50%

40%

30%

20%

10%

0%

AG

AG AS CD CR CU HG NI PB SB ZN

Metal

AS CD CR CU HG NI PB SB ZN

Metal

irrirl

EMAP' A

MAI-686

MU-A85

I HI-A389

.1

I I I B

EMAP Q MU-A85

O MAI-686 Hl-A389

-I I - J!llrlElI

Figure 6.13. Percent of samples from the GOOMEX sites that exceeded

the Long and Morgan (1990) A: 50 % and B: 10 % bioeffects

criteria.

6-68

100%

90%
determined by the interplay of several factors including uptake, metabolism,

and depuration. These confounding factors can obscure the relationship

between body burden and actual exposure- The rates of uptake, metabolism

and depuration of contaminants are often species, life stage, and sex

dependent- The presence of detoxification enzyme systems in fish provides

an ability to metabolize (transform) and eliminate contaminants, such as

PAH, from their tissues. However, the presence of contaminants in tissues

does confirm recent exposure. The materials analyzed in this study; the soft

tissues of invertebrates, liver tissues from fish, and fish stomach contents;

were chosen for various reasons. Invertebrates may accumulate

contaminants due to their often intimate relationship with sediments. Fish

livers are a primary site of PAH metabolism/storage and thus would be the

most likely tissue to exhibit PAH contamination in contrast to muscle tissue.

The liver is also lipid-rich, compared to muscle tissue, and PAH tend to

preferentially accumulate in lipid-rich organs. Stomach contents were

analyzed to determine if contaminant exposure in fish was due to dietary

sources or ingestion of contaminated sediments. Other routes of potential

exposure include uptake across exposed external organs such as gills.

6.3.1 Hypothesis Testing

To proceed with hypothesis testing a suite of parameters was chosen

based on the consortium of contaminants detected in the adjacent

sediments, the assumed primary source of chronic exposure for organisms.

Total PAH, Cd, Fe, and Ba were chosen as indicators of hydrocarbons,

contaminant metals, sediment, and drilling muds, respectively. Principal

components derived from PCA analysis of the PAH data were of little use due

to the data being close to or below the method detection limits (MDL) - Most

of the variance in the data was due to the procedures followed for data

censoring. Data are reported for a subset of target PAH analytes when values

are below the MDL. Thus, patterns in the data related to data censorship

are created. A majority of the variance in the data was attributable to data

processing methods illustrating the near uniformity of the results obtained.

For hypothesis testing, statistical analysis of variance no longer

considers R (direction), and D was treated as a category. As with the

boxcorer data, the most general case was first tested and then the data set

6-69
was decomposed by other study design classifications (see Section 6.0). In

the test of the overall design, no two-way or higher interactions were

significant (Table 6.29 to 6.31). Consideration of the data by tissue type

across all sites showed significant differences related to cruise for PAH and

barium in stomach contents and barium for invertebrate soft tissues.

Significant differences related to platform site were observed for PAH and

barium in invertebrate soft tissues. Further analysis of the data by site

confu-rned the presence of significant differences due to cruise. However,

no significant differences due to distance from the platform were evident

(Tables 6.32 to 6.34).

In conclusion, no enhanced bioaccumuiation of hydrocarbons or trace

metals in fish livers, fish stomach contents, or invertebrate soft tissues could

be related directly to distance from a platform. Differences related to cruise

and site are most likely due to difference in the species analyzed at each site

and during each cruise. It was difficult to collect the same species at both

the Near and Far stations and was particularly difficult to collect the same

species consistently across all three sites due to differences in water depths.

In general, most of the contaminant levels observed were close to method

detection limits. Random occurrences of bioaccumulation of contaminants

were noted but they were apparently unrelated to distance from the

platform.

6.3.2 Historical Comparisons of Trace Metals in Tissues

The MMS-sponsored South Texas Outer Continental Shelf Baseline

Study (STOCs, 1975-77) provided a survey of background concentrations in

organisms for comparison with the present study (Boothe and Presley

1979). Analyses of the same species provide the most meaningful

comparisons. Three such comparisons were possible utilizing the STOCS

dataset. These species-specific comparisons included two fish and a

burrowing crustacean. Comparisons of metal concentrations in livers from

the commercially important red snapper (Lutjanus campechanus) showed

that the STOCS baseline concentrations were consistently higher (except

Cr; Figure 6.14) than the data from this study. For livers from wenchman

(Pristipomoides aquilon.aris), an epibenthic shelf species (Figure 6.15), the

concentrations were similar. These comparisons suggest that for mobile

6-70
Table 6.29. Summary of the significance of interactions for the overall study

design based on contaminants in fish livers.

Interactionsb

TOTPAH No No

Cd No No

Fe No No

Ba No No

aSee Table 6.19 for definition of variables.

bSee Table 6.19 for definition of variables and symbols.

Table 6.30. Summary of the significance of interactions for the overall study

design based on contaminants in fish stomach content.

Interactionsb

Variablea CtD P*D

TOTPAH No No

Cd No No

Fe No No

Ba No No

aSee Table 6.19 for definition of variables.

bSee Table 6.19 for definition of variables and symbols.

Interactionsb

Variablea P C D

TOTPAH

Cd

Fe

Ba

No

No

No

No

No

No

No

No

No

No

No

No

Interadionsb

Variablea P C D

TOTPAH

Cd

Fe

Ba

No

No

No

No

Yes

No

No

Yes

No

No

No

No

Variablea C*D P*D
Table 6.31. Summary of the significance of interactions for the overall study

design based on contaminants in invertebrate soft tissues.

TOTPAH No No

Cd No No

Fe No No

Ba No No

TOTPAH Yes No No

Cd No No No

Fe No No No

Ba Yes Yes No

aSee Table 6.19 for definition of variables.

bSee Table 6.19 for definition of variables and symbols.

Table 6.32. Summary of the significance of interactions for different tissue

types at MAI-686 based on contaminants.

Liver

TOTPAH No No

Cd No No

Fe No No

Ba No No

Stomach Contents

TOTPAH No No

Cd No No

Fe No No

Ba No No

Invertebrate Soft Tissues

Interactionsb

Interactionsb

TOTPAH No No

Cd No No

Fe No No

Ba No No

aSee Table 6.19 for definition of variables.

bSee Table 6.19 for definition of variables and symbols.

6-72

Variablea p C D

Variablea C*D P*D

Tissue Type Interactionsb

Variablea CtD
Table 6.33. Summary of the significance of interactions for different tissue

types at MU-A85 based on contaminants.

Liver

TOTPAR No No

Cd No No

Fe No No

Ba No No

Stomach Contents

TOTPAH No No

Cd No No

Fe No No

Ba No No

Invertebrate Soft Tissues

TOTPAH No No

Cd No No

Fe No No

Ba No No

aSee Table 6.19 for definition of variables.

bSee Table 6.19 for definition of variables and symbols.

Table 6.34. Summary of the significance of interactions for different tissue

types at HI-A389 based on contaminants.

Liver

TOTPAH No No

Cd No No

Fe No No

Ba No No

Stomach Contents

TOTPAH No No

Cd No No

Fe No No

Ba No No

Invertebrate Soft Tissues

TOTPAH No No

Cd No No

Fe No No

Ba No No

aSee Table 6.19 for definition of variables.

bSee Table 6.19 for definition of variables and symbols.

6-73

Tissue Type Interacionsb

Variablea C*D D

Tissue 'l)'pe Interactionsb

Variablea C*D D
Figure 6.14. Comparison of STOCS and GOOMEX organism trace metal

data in Lutianus campechanus (Red Snapper) liver tissue.

6-74
Figure 6.15. Comparison of STOCS and GOOMEX organism frace metal

data for Pristipomoides aquilonaris (Wenchman) liver tissue.

6-75
species, metal concentrations in tissues near platforms are not elevated over

background values, confirming little or no enhanced bioaccumulation of

metals near platforms. For the less mobile, burrowing mantis shrimp

(Squilta empusa) there was an indication of bioaccumulation related to the

level of sediment contamination (Figure 6.16; Boothe and Presley 1987).

Cadmium levels were significantly higher in Squilla empusa from the two

sites (HI-A389 and MU-A85) with the highest levels of sediment

contamination. Iron levels were also higher in mantis shrimp from alt three

study sites in this study. The cause of this consistent difference in iron was

uncertain but a similar elevation was observed in the STOCS study (Boothe

and Presley 1987).

Broader comparisons involving the pooling of data from many different

species of the same organism type, were also possible with the available data.

Because of inter-species differences, these comparisons have higher

variabffity but they give a more comprehensive picture because of the larger

sample sizes involved (e.g., GOOMEX 340 fish and 120 shrimp samples,

STOCS 150 fish and 65 shrimp samples). The concentrations of seven trace

metals in fish liver tissue from the two studies in are compared in Figure

6.17. As observed with the species-specific comparisons above, the data

were similar from the two studies with the STOCS data generally being

higher than the present data. Again, there was no indication of enhanced

bioaccumulation of metals in near-platform demersal fish populations.

Shrimp soft tissue data is compared in Figure 6.18. Several

commercially important penaeid shrimp species were included in both

pooled data sets. The situation for the shrimp soft tissue data was the same

as that observed for the closely related mantis shrimp. Cadmium body

burdens were significantly higher at the most contaminated sites (HI-A389

and MU-A85). Lead levels were also higher at the sites but the differences

were smaller and not significant. Also the Pb levels did not correlate well

with sediment enrichment at a site. Shrimp from the much less

contaminated MAI-686 site had Pb levels similar to shrimp from the more

contaminated MU-A85 platform. Again, Fe levels are significantly higher at

all three sites compared to the STOCS baseline data.
Figure 6.16. Comparison of STOCS and GOOMEX organism trace metal

data for SquiUa empusa (Mantis Shrimp) soft tissue.

6-77
Figure 6J7. Comparison of STOCS and GOOMEX organism trace metal

data for fish liver tissue.

6-78
Figure 6.18. Comparison of STOCS and GOOMEX organism trace metal

data for shrimp soft tissues.

6-79
6.4 Meiofauna

The term "meiobenthost' was first coined by Mare (1942) to describe

those benthic organisms that are of intermediate size. These are metazoans

that are smaller than macrofauna but larger than the single-celled

microbenthos (e.g., bacteria, microalgae, and protozoans). By convention,

the definition of meiofauna is those animals that pass through a 0.5-mm

sieve but are retained on a 0.063-mm sieve (Coull and Bell 1979).

Meiofaunal communities can be further subdivided into two groups.

Temporary meiofauna are those juveniles of the macrofauna that will

eventually grow into organisms larger than 0.5 mm in body width (e.g.,

polychaetes). Permanent meiofauna are those groups where adults are less

than 0.5 mm in width (e.g., Nematoda, Copepoda, Gastrotricha, Turbellaria,

Acarina., Gnathostomuljda, Kinoryncha, Tardigrada, Ostracoda, and some

Rhyncocoela, Oligochaeta and Polychaeta). In 1971, Thiel suggested that

the grouping of benthic organisms according to size differences had little

taxonomic or ecological justification, except convenience of sample

processing (quoted from Thiel 1975). However, extensive ecological

literature since 1971 has shown that meiofauna are different from

macrofauna, and have different roles in marine ecosystems (for reviews see:

Coull and Bell 1979; Coull and Palmer 1984). Even where meiofauna share

ecological properties with macrofauna, the processes operate on much

smaller spatial and temporal scales for melofauna (Bell 1980). Meiofauna are

good candidates for indicating contaminant exposure for several reasons.

Meiofauna have short generation times thus providing the potential for

exhibiting a rapid response. Meiofauna also live and grow in the benthos

with no planktonic larvae, thus assuring life long exposure to sediment

contaminants and sampling is less labor intensive than for macroinfauna

(Warwick 1988a,b).

Although nematodes are the dominant meiofaunal taxa, harpacticoid

copepods are most suitable for meiobenthic reproductive studies.

Harpacticoids have reproductive characteristics that are easy to measure.

Harpacticoids brood their eggs externally, have five copepodite (or juvenile)

stages that are easily identifiable, and have an adult stage that is sexually

dimorphic. The likelihood of detecting changes in community structure is

very high because this group of organisms is so diverse (Coull 1972).

6-80
Harpacticoids are usually more sensitive to hydrocarbon exposure than

nematodes (Fncke et al. 1981; 80dm and Boucher 1983; Hennig et al.

1983). It has been suggested that nematode:copepod ratios (i.e., decreasing

numbers of harpacticoids) are a good indicator of exposure to hydrocarbons

(Hennig et al. 1983) and organic waste (Raffaelli and Mason 1981; Raffaelli

1982; Amjad and Gray 1983; Shiells and Anderson 1985). However, one

must be careful when applying such an index (e.g., the nematode:copepod

ratio) for comparing exposure at different habitats or different times,

because meiofauna abundances and community structure are dependent on

granulometry and seasonal fluctuations (Coull et al. 1981). All of the needed

ancifiary variables have been measured (i.e., chemical, geological, spatial, and

temporal parameters) to evaluate the usefulness of the nematode:copepod

ratio. Harpacticoids are more sensitive than nematodes to the addition of

barite and sand (Cantelmo et aL 1979). This phenomenon may be difficult to

separate from contaminant exposure. However, granulometry data should be

useful in separating out effects due to toxicity and effects due to changes in

sediment composition. Because harpacticoids disperse at faster rates than

nematodes they are the first colonizers of drilling muds and cuttings. After

an intertidal mud flat was disturbed by turning it over, meiofauna recovered

to predisturbance levels within one tidal cycle (Sherman and Coull 1980).

Meiofauna act like passive particles of sediment, and are resuspended in

proportion to the erosion velocities of surface sediments (Palmer and Gust

1985). Behavior also plays an important role in dispersion. Since

harpacticoids are more often found in surface sediments, they are much

more common in the drifting meiofauna than nematodes (Bell and Sherman

1980; Palmer 1984). This is consistent with the observation that

harpacticoid populations recovered within one week during a colonization

experiment of oiled sediments, but nematodes took up to 90 days to fully

recover (Alongi et al. 1983). Harpacticoids also recolonized azoic trays

faster than nematodes in natural hydrocarbon seep sediments of OCS areas

of California (Palmer et al. 1988).

The meiofauna component included sampling at the community,

population, and genetic level. Eight different variables were examined at the

community level: total meiofauna density, Nematoda density, Harpacticoida

density, "otbef' meiofauna taxa density, the nematode:copepod (NC) ratio,

Nematoda biomass, Nematoda diversity, and Harpacticoida diversity.

6-81
Additionally, nematode trophic dynamics and predation pressure on

meiofauna were also examined. At the population level, the variables

measured included harpacticoid egg clutch volume, clutch size, and life

history stages. The meiofauna porewater toxicity study also falls in this

category. At the genetic level, balotype diversity was estimated for

harpacticoid populations.

6.4.1 Meiofaunal Communities

There was a gradient in meiofauna abundance and diversity among the

platforms. Density of all taxa and harpacticoid diversity decreased from

MAI-686 to MU-A85, to HI-A389. There were three gradients present,

which are confounded. Water depth increases along this gradient,

contamination concentrations increase along this gradient, and sand content

decreases. Therefore, depth, contamination, and sediment texture are

confounded, precluding the simple conclusion that differences among

platforms represent differences in contaminant levels. The nematode data

provided insight into this issue. Both the NC ratio and nematode diversity

did not follow the depth-contaminant-sand trend. Nematode diversity and

biomass was not highest at MAI-686, nor was the NC ratio the lowest. These

data indicated that environmental differences were interacting at platforms

HI-A389 and MAI-686 to produce the observed trends.

6.4.1.1 Meiofaunal Abundance and Diversity

The first statistical analysis of meiofaunal data was performed to test

the overall sample design to detect interactions among cruises, platforms,

and distances from platforms (Table 6.35). Meiofaunal community

abundance and diversity data is summarized and described in detail in

Section 5.4.2. Interactions among cruises, platforms and distances mean

that overall analyses cannot be directly interpreted (i.e., the overall test for a

distance effect is invalid). Harpacticoid diversity was the only variable where

interactions with cruise or platform were not present. Cruise interactions

were significant for all density measures, but not significant for diversity

measures. Significant interactions related to platform uniqueness was

common. Distance interactions were present for all variables. This means

6-82
Table 6.35. Summary of the significance of interactions for the overall sample design based on meiofaunal data.

app1aj-fo, C=Cruise, D=Distance, R=radius; Yes=significant, pO.Ol; no=not significant,

pO.O1;

that there were different responses with respect to distance from the

platforms at all platforms and radii within platforms. and that in general,

platforms should be independently analyzed.

When higher order interactions were not present, then the test for

the main effect (e.g., cruise, distance, or platform) was easily interpreted.

This is summarized in Table 6.36. Harpacticoid diversity exhibited

statistically significant cruise, platform, and distance differences. A Tukey's

test revealed that the 50-rn stations had the lowest diversity of all stations.

The highest diversity was found at distances of 3000-rn from a platform.

There was a significant linear increase in harpacticoid diversity with respect

to distance from a platform (linear contrast) - These results indicated that

harpacicoids were the only response variable for which a general statement

about all platforms could be made.

Each platform was also individually analyzed (Tables 6.37 and 6.38).

SigntfIcant interaction effects were stifi present for many variables. Distance

effects were clearly evident at HI-A389. Every variable, except the density

of "other meiofauna taxa", exhibited a statistically significant response with

respect to distance from the platform. MAI-686 had significant differences

for all abundance measures, harpacticoid diversity, and nematode biomass

(Table 6.37). The platform MU-A85 had only one significant difference with

distance, nematode biomass (Table 6.37). Many significant interactions with

cruise and distance still existed for abundance measures, but not for

harpaticoid diversity (Table 6.37). The effect of distance could be tested for

6-83

Interactionsa

Variable C*D P*D P*C*D D*R(P)

Meiofauna density Yes Yes Yes Yes

Nematode density Yes Yes Yes Yes

Harpacticoid density Yes No Yes Yes

Other meiofauna density Yes Yes Yes Yes

Nematode biomass Yes No No Yes

Nematode±Tarpacticoid ratio No Yes No Yes

Nematode diversity No Yes No Yes

Harpacticoid diversity No No No Yes
Table 6.36. Summary of tests of the main effects for the overall sample design based on meiofaunal data.

Meiofauna density Nematode density

1-Jarpacticoid density

Other meiofauna density

Nematode biomass

Nematode:Harpacticoid ratio Nematode diversity Harpacticoid diversity

aResult of significance tests for the three main effects are reported where

higher order interactions were not significant ("---" = unable to test due to the

significant higher interactions)

Table 6.37. Summary of the significance of interactions by platform based

on meiofaimal data.

aFor definition of variables and symbols see Tables 6.35 and 6.36.

Table 6.38. Summary of the interpretations of interactions for analysis of variance by platform based on meiofauna data.

Platforma

aFor definition of variables and symbols see Tables 6.35 and 6.36.

6-84

Interactionsa

Site MAI-686 MU-A85 l-fl-A389

Variable C*D D*R C*D*R C*D D*R C*D*R C*D D*R C*D*R

Meiofauna density Yes Yes Yes Yes No Yes Yes Yes Yes

Nematode density Yes Yes Yes Yes No Yes Yes Yes Yes

Harpacticoid density Yes Yes Yes No No Yes Yes Yes No

Other meiofauna density Yes Yes Yes Yes No Yes No No No

Nematode biomass Yes No No No No No Yes No No

Nematode:Ha.rpacticoid

ratio

No No No No No No No Yes Yes

Nematode diversity No No Yes Yes No Yes

Harpacticoid diversity No No No No No Yes

Variable2- Platform Cruise Distance

Yes Yes Yes

Variable MAI-686 MU-A85 HI-A389

Meiofauna density

Nematode density Harpacticoid density Other meiofatma density Yes

Nematocle biomass Yes Yes

Nematode:Harpacticoid ratio No no

Nematode diversity No

Harpacticoid diversity Yes No
in only 7 of 32 instances. Significant distance effects were apparent for

harpacticoid diversity and nematode biomass at MAI-686. Tukey multiple

comparisons were performed by platform (Tables 6.39 to 6.44). At MAI686, there was a linear gradient in all density, biomass, and harpacticoid

diversity values, which increased away from the platform (Table 6.39).

Nematode diversity declined at MAJ-686 along this gradient. At MU-A85,

50-rn stations were different and had the lowest values for all variables

measured (Table 6.40). It appeared that "naturaT' or background levels

occur at 100 to 200 m away from the platform. At HI-A389, densities of

harpacticoids were generally higher away from the platform, but nematode

density and biomass was greater near the platform (Table 6.39).

Harpacticoid densities declined in a near linear fashion with distance from

the platform. Since nematodes increased and harpacticoids decreased with

distance, the NC ratio also declined with distance from a platform (Table

6.40).

Tukey's multiple comparisons were also performed to evaluate

between cruise differences (Tables 6.42 to 6.44). Platforms MU-A85 and

HI-A389 had similar responses with generally higher abundance and

diversity values during Cruises 3 and 4 (Tables 6.43 and 6.44). MAI-686 bad

an opposite trend with generally higher values during Cruises 1 and 2 (Table

6.42).

6.4.1.2 Meiofaunal Community Structure

A principal components analysis (PCA) was performed on the

nematodes and barpacticoids species composition data to determine which

environmental factors were correlated with changes in community structure

(Figures 6.19 to 6.26). For harpacticoids (Figure 6.19) and nematodes

(Figure 6.20) differences were mainly due to platforms. Platform MU-A85

had species in common with HI-A389 and MAI-686, which were very

different from one another. Nematode patterns at the two deeper platforms

(MU-A85 and HI-A389) shared some species, but the shallowest water

platform (MAI-686) was very different from the two deeper water platforms.

There were also differences due to station proximity to the platform.

Since so few species were common between platforms, it was more

effective to analyze on a platform-by-platform basis (Figures 6.21 and 6.26).

6-85
aDe1ansfoed means are presented (x) and means that are underlined are not different at the

0.05 level.

6-86

Table 6.39. Tukey's multiple comparison test results by distance at MAT- 686 based on meiofaunal data.

Variable Distance from the Platforma

Total meiofauna density 3000 1000 200 100 50

(nX 10cm-2) (3868) (3534) (2477) (1976) (1681)

Nematode density 3000 1000 200 100 50

(nX 10 -2) (2818) (2589) (2589) (1786) (1451)

Harpacticoid density 3000 1000 200 100 50

(ii X 10 cm2) (449) (402) (297) (205) (164)

Other meiofauna density 3000 1000 200 100 50

(n X 10 cm2) (534) (490) (353) (278) (267)

NC ratio 50 3000 100 1000 200

(nXlOcm2) (15.2) (13.1) (12.6) (11.3) (10.2)

Nematode diversity 50 100 200 1000 3000

(nX 10 -2) (3.16) (3.13) (3.12) (3.11) (3.10)

Harpacticoid diversity 3000 1000 200 100 50

(nX 10 cm) (2.75) (2.73) (2.62) (2.44) (2.24)

Nematode biomass 3000 1000 200 100 50

(nX 10 cm2) (2.48) (1.17) (0.98) (0.85) (0.42)
Table 6.40. Tukey's multiple comparison test results by distance at MU-A85

based on meiofaunal data.

aDe1]sformed means are presented (x) and means that are underlined are not different at the

0.05 level.

6-87

Variable Distance from the Platforma

Total meiofauna density 100 1000 200 3000 50

(nX lOcin2) (1098) (892) (874) (782) (647)

Nematode density 100 1000 200 3000 50

(nX 10cm-2) (660) (533) (525) (434) (326)

Harpacticoid density 100 50 1000 200 3000

(nX 10cm2) (212) (167) (166) (162) (156)

Other meiofauna density 100 1000 3000 200 50

(nXlOcnf2) (191) (180) (173) (162) (125)

NC ratio 200 1000 100 3000 50

(nXlOcm2) (7.1) (6.4) (6.2) (5.7) (4.3)

Nematode diversity 100 200 3000 1000 50

(ii X 10 cm-2) (3.45) (3.37) (3.31) (3.27) (3.18)

liarpacticoid diversity 100 1000 3000 200 50

(nX 10 crn2) (2.69) (2.54) (2.51) (2.48) (2.38)

Nematode biomass 3000 200 1000 100 50

(nX 10cm-2) (2.16) (1.75) (1.63) (1.18) (0.23)
Table 6.41. Tukeys multiple comparison test results by distance at HI-A389

based on meiofaunal data.

aDeti.ansformed means are presented (x) and means that are underlined are not different at the

0.05 level.

6-88

Variable Distance from the Platforma

Total meiofauna density 100 200 50 500 3000

(n X 10 cm2) (929) (805) (751) (636) (597)

Nematode density 100 50 200 500 3000

(n X 10 cnr2) (649) (546) (534) (397) (346)

Harpacticoid density 3000 1000 200 100 50

(n X 10 cm2) (119) (118) (104) (97) (34)

Other meiofauna density 200 1000 3000 100 50

(n X 10 cm2) (119) (115) (112) (93) (70)

NC ratio 50 100 200 1000 3000

(nXlOcm2) (30.3) (23.6) (16.3) (6.3) (6.0)

Nematode diversity 1000 3000 200 100 50

(nX 10 cnr2) (3.21) (3.10) (3.04) (2.58) (1.76)

Harpacticoid diversity 200 3000 1000 100 50

(nX 10 -2) (2.26) (2.26) (2.22) (2.01) (1.25)

Nematode biomass 3000 1000 200 100 50

(nX 10 cm2) (2.48) (0.85) (0.77) (0.13) (0.016)
Table 6.42. Tukey's multiple comparison test results by cruise at MAI-686

based on meiofaunal data.

aDefransfox-med means are presented (x) and means that are underlined are not different at

the 0.05 level.

Variance Cruisea

Melofauna density 1 2 3 4

(nX 10 -2) (3363) (2613) (2343) (2125)

Nematode density 1 2 3 4

(n X 10 -2) (2372) (2001) (1654) (1541)

Harpacticoid density 1 3 2 4

(nX 10 -2) (472) (306) (268) (166)

Other meiofauna density 1 4 3 2

(nX 10 -2) (482) (388) (331) (302)

NCratio 4 2 3 1

(nXlOcnr2) (16.8) (13.4) (10.1) (9.6)

Neinatode diversity 1 2 3 4

(nX 10 -2) (3.19) (3.17) (3.11) (3.01)

Harpacticold diversity 1 2 3 4

(nX 10 -2) (3.00) (2.58) (2.40) (2.25)

Nematode biomass 1 2 3 4

(nX 10 -2) (2.34) (1.93) (0.95) (0.94)
Table 6.43. Tukey's multiple comparison test results by cruise at MU-A85

based on meiofaunal data.

6-90

aDefransfoed means are presented (x) and means that are underlined are not different at

the 0.05 level.

Variable Cruisea

Meiofauna density 3 4 2 1

(nX 10 -2) (950) (937) (850) (677)

Nematode density 3 2 4 1

(nX 10 CTif2) (572) (521) (492) (369)

Harpacticoid density 4 3 2 1

(nX 10 cm2) (199) (186) (154) (152)

Other meiofauna density 4 3 2 1

(nX 10 -2) (232) (162) (143) (136)

NCratio 3 2 1 4

(nXlOcm2) (7.4) (7.0) (4.9) (4.4)

Nematode diversity 4 3 2 1

(nX 10 -2) (3.45) (3.44) (3.34) (3.02)

Fiarpacticoid diversity 1 4 3 2

(nX 10 crir2) (2.81) (2.48) (2.46) (2.33)

Nematode biomass 2 3 1 4

(nX 10 crn2) (0.46) (0.41) (0.33) (0.33)
Table 6.44. Tukey's multiple comparison test results by cruise at HI-A389

based on meiofaunal data.

aDeansfoed means are presented (x) and means that arc underlined are not different at

the 0.05 level.

Variable Cruisea

Meiofauna density 3 4 2 1

(nX 10 -2) (1003) (745) (714) (545)

Nematode density 3 4 2 1

(nX 10 -2) (717) (495) (488) (310)

Harpacticoid density 3 4 2 1

(nX 10 -2) (112) (91) (83) (63)

Other meiofauna density 1 4 2 3

(nX 10 (105) (105) (96) (94)

NC ratio 3 1 4 2

(nX locirr2) (19.4) (16.9) (16.8) (13.0)

Nematode diversity 4 3 2 1

(nX 10 -2) (2.97) (2.93) (2.78) (2.27)

Harpacticoid diversity 1 3 2 4

(nX 10 -2) (2.13) (2-03) (1.96) (1.89)

Nematode biomass 3 4 2 1

(nX 10 -2) (0.46) (0.41) (0.35) (0.22)
Figure 6.19. Piincipal components analysis (PCA) of harpacticoid species for entire 

by platform.
Figure 6.20. Principal components analysis (PCA) of nematode species for entire sa

platform. 2 - 0 

0 cP X 

1- OOc 000 s'. HO !P%

0 Q . 0 >(.1s> - 0 90°O o00 0 0o XX C1Ua. -- 0 0 > > 0 XXX1II> x I<%xXu . 

-1- x - x.xx - 1x U. U. -2- 0 MAI-686 U -- X MU-A85 HI-A389 3 I I I I I I I I I I I I I I I I I I -3 -2 -1 0 pci 1 
3 S S . x U ' I ' I -2 -1 0 0 

Figure 6.21. PrIncipal components analysis tPCA) of harpacticoid species at MAI-686 

from the platform. C1 C-) a. 43- 2- 1-- 0- -1 - x)xfJ 0 0 UsD0 D OX.D U. S. 0 S. Do 0 0 S0 S 

2 3 
Figure 6.22. Principal components analysis (PCA) of harpacticoid species at MU-A8

from the platform.
44 XX XX 0 UI: . U U S>?< 0 0 U0 0 0 X U . 0 

-2 0 I I I I pci I I I 

Figure 6.23. Principal components analysis (PCA) of harpacticoid species at Hl-A38

from the platform. S U S 

0 0 S S. . X 0
30- 4 x 0 S 31 0U II .0 S 0 D 0 U 5c.) 0 S.. o. 0 0 0 !I Xo 0 cx0 S xO 00 r 00 xx0 x0 0 x 0 X 0 x 

pci Figure 6.24. PrIncipal components analysis (PCA) of nematode species at MAI-686 

the platform. 2- a x x0 -2- x -3 --2 2 
3 FIgure 6.25. PrIncipal components analysis (PCA) of nematode species at MU-A85 b

the platform. c1C.) 0. 2- 1.- 0- -1 - 2 X XX XXX X X°.X x ><X0 XX X 00 0 S 0 0 S. ISO U S F' 0 XXDI S0S 0 0 0 0 0.0 0 U 

000. 

' I I -3 -2 -1 0 1 

pci
3 U U

0 5 (9 a S 0 0 0 O 200m 500m 5000m 0 . U 0 5 S U U U 0U0 0 U 0 

-2 I ' I I I I -1 0 1 pci 

Figure 6.26. PrIncipal components analysis (PCA) of nematode species at H1-A389 b

the platform. 2 x x 0 1- x0 0 0 xxx 0 x xxx x 0- xoxx xx C.) a- U .0 0 0 UU X50m o lOOm -2- S
There was a uniform distribution of harpacticoid species at the shallowest

platform, MAI-686. However, there were differences in community

structure at the 50 and 100-rn stations at the two deeper platforms (MUA85 and HI-A389; Figures 6.22, 6.23, 6.25, and 6.26). A similar trend was

also true for nernatode species. The distribution at MAI-686 was partly

uniform, but 50-rn stations clustered together (Figures 6.21 and 6.23). The

50 and 100-rn stations clustered together for the deeper water platforms,

MU-A85 and HI-A389 (Figures 6.22, 6.23, 6.25, and 6.26). Meiofaunal

community structure data is summarized and described in detail in Section

5-4-3.

6.4.1.3 Nematode Trophic Dynamics

Nematodes are sensitive to contaminants such as PCBs, PAHs, and

metals (Tietjen and Lee 1984). Nematodes are used in bioassays, because

their population size decreases in the presence of contaminated sediments

(Tietjen and Lee 1984). Natural populations of nematodes are also thought

to be controlled by predation from macroinfaunal deposit feeders and a

variety of macroepifauna (Li et al. 1995a,b). Macroinfaunal deposit feeders

may engulf nematodes as they process sediment. Therefore, a decrease in

macroinfauna abundance in a contaminated environment may relax

predation pressures on nematodes. Thus, the abundance of nematodes may

actually increase, although nematode diversity may decrease in a

contaminated environment (Bouwman et al. 1984). Predation pressure may

be a stronger force in structuring nematode populations than environmental

parameters such as food availability and temperature (Li et al. 1995a,b). In

estuarine habitats, nematode abundance is thought to increase with a

gradient of increasing sediment grain size (van Damme et al. 1980; Li and

Vincx 1993). The reason for this trend may be that deposit-feeding

macroinfauna abundance increases in muddy sediments. Because nematode

abundance follows an inverse relationship with these deposit feeders, due to

predation, nematodes are often more abundant in sediment with large

particle sizes. Nematode trophic relationships based on biomass

calculations are summarized and described in detail in Section 5.4.4.

Multiple analysis of variance (MANOVA) was performed to determine if

the trophic structure of the nematode community changed over the entire

6-100
study design (Table 6.45). Every term in the model was significant, so byplatform analyses were performed in a multivariate mode. The results for

density (Table 6.46) and bioinass (Table 6.47) of feeding groups were the

same. All the interaction terms at every platform were significant (Tables

6.46 and 6.47). The significant interactions make the MANOVA difficult to

interpret. At HI-A389, there were D*R interactions for both density and

biomass. The patterns at MAI-686 were easier to interpret, because the

D*R interactions were not significant for density arid biomass.

Sediment grain size decreased with distance away from a platform.

Sand content was higher in the near-field, while silt and clay content was

higher at the far-field. Nematode biomass and density also decrease with

distance from a platform. The trend in nematode abundance and biomass

may be related to predation by macroinfaunal deposit feeders. Near the

platforms. the dominant macroinfauna were Cirratulus cirratus, Tharyx cf.

anrtulosus, Paraprionosplo pirtnata, and Mediomastus ca1fomiensis. These

species were predominantly surface deposit feeders (Fauchald and Jumars

1979). Surface deposit-feeders should not exert as intense predation

pressures as deposit-feeders that live deeper in the sediment. Nematodes

are generally affected by surface deposit feeders to sediment depths of less

than 1 cm (Warwick and Gee 1984). Densities and biomass were measured

to a depth of 2 cm in this study. Therefore, even though macroinfauna

abundance increased with proximity to a platform, predation on nematodes

did not correspondingly increase.

Additional evidence to support this theory comes from analyzing

individual platform. MAI-686 bad the highest sand content and the lowest

silt and clay contents. Nematode abundance was higher at MAJ-686 than at

the other two platforms. Therefore, the abundance and distribution

patterns of nematodes around platforms were not due to platform-mediated

contamination by PARs or trace metals. Instead, the sediment grain-size

gradient may have resulted in decreased predation pressures on nematodes

by deposit-feeding macroinfauna (Li et al. 1995a,b). Therefore, nematode

abundance and biomass may not be as good an indicator of platform

contamination effects as nematode diversity.

The proportion of different nematode feeding types in a community is

influenced by environmental factors, particularly sediment grain size (Wieser

1953). The importance of grain size in structuring nematode communities

6-101
Table 6.45. Multiple analysis of variance for nematode feeding groups for

the overall study design.

A. Dependent Variablesa: loglo(1A density + 1) logio(1B density + 1) 1ogo(2A density + 1)

aThe four feeding groups are: selective deposit feeders (1A), non-selective deposit feeders (1B),

epigrowth feeders (2A), and predators (2B). The model is: 1A lB 2A 2B = C P C*P D C*D P1D

C*P*D R(P) C*R(P) D*R(P) where F, D, and C are fixed, and R is random. Table finds P value for

the Pillai's Trace statistic for the null hypothesis that there are no differences In feeding group

structure for the source of variation. A. Log density-i-i. B. Log biomass+1.

6-102

B. Dependent Variables logio(1A biomass + 1) logio(1B biomass + 1) logio(2A blomass + 1)

log(2B biomass + 1)

Source Error Pillai's Trace F Numerator DF Denominator Pr > F

DF

C CR(P) 1.1846 5.7099 12 105 0.0001

P R(P) 1.1775 3.5791 8 20 0.0098

C*R(P) 1.2002 2.5720 24 144 0.0003

D D*R(P) 0.9410 3.6917 16 192 0.0001

C*D MSE 0.2119 2.0234 48 1736 0.0001

P*D D*R(P) 1.0744 2.2033 32 192 0.0006

P*C*D MSE 0.3650 1.8157 96 1736 0.0001

R(P) MSE 0.3995 4.0132 48 1736 0.0001

C*R(P) MSE 0.3763 1.2519 144 1736 0.0271

D*R(P) MSE 0.8080 2.2886 192 1736 0.0001

logio(2B density + 1)

Source Error Pillal's Trace F Numerator DF Denominator DF Pr > F

C CR(P) 1.1000 5.0627 12 105 0.0001

P R(P) 1.3726 5.4691 8 20 0.0010

P*C CR(P) 1.1649 2.4655 24 144 0.0005

D D*R(P) 1.0851 4.4668 16 192 0.0001

C*D MSE 0.2638 2.5541 48 1736 0.0001

P91) D*R(P) 1.09 14 2.2515 32 192 0.0004

P*C*D MSE 0.4142 2.0775 96 1736 0.0001

R(P) MSE 0.4781 4.9093 48 1736 0.0001

CtR(P) MSE 0.3624 1.2011 144 1736 0.0586

D*R(P) MSE 0.8491 2.4367 192 1736 0.0001
Table 6.46. Multiple analysis of variance for nematode density by feeding

group by platfonn.

A. Platform: MAI-686, Dependent Variablesa.: logio(1A density + 1) logio(1B density + 1)

logo(2A density + 1) logio(2B density + 1)

B. Platform: MU-A85, Dependent Variables: logio(1A density + 1) logo(1B density + 1)

logio(2A density + 1) logio(2B density + 1)

C. Platform: HI-A389, Dependent Variables: logo(1A density + 1) logio(1B density + 1)

logio(2A density + 1) logo(2B density + 1)

aFor definitions see Table 6.45.

6-103

Source Error Pifial's Trace F Numerator DF Denominator DF Pr > F

C CR 1.6372 3.3038 12 33 0.0032

R MSE 0.3195 2.1268 16 392 0.0069

CR MSE 0.7070 1.7533 48 392 0.0022

D DtR 1.1643 1.6424 16 64 0.0830

CtD MSE 0.8746 2.2853 48 392 0.000 1

D*R MSE 1.0313 2. 1278 64 392 0.0001

C*D*R MSE 1.7037 1.5148 192 392 0.0001

Source Error Pfflai's Trace F Numerator DF Denominator DF Pr > F

C CR L6372 3.1176 12 33 0.0048

R MSE 0.1519 0.9674 16 392 0.4920

C*R MSE 0.3802 0.8579 48 392 0.7380

D D*R 2.0907 4.3800 16 64 0.0001

C*D MSE 1.0746 2.9998 48 392 0.0001

D*R MSE 0.8997 1.7775 64 392 0.0005

C*D*R MSE 1.6475 1.4298 192 392 0.0017

Source Error Pillal's Trace F Numerator DF Denominator DF Pi> F

C CtR 1.2069 1.8508 12 33 0.0801

R MSE 0.8633 6.6057 16 384 0.0001

C*R MSE 0.7095 1.7249 48 384 0.0030

D D*R 1.2680 1.8565 16 64 0.0423

C*D MSE 0.8709 2.2267 48 384 0.0001

DZR MSE 1.4530 3.4227 64 384 0.0001

C*D*R MSE 1.7088 1.5565 184 384 0.0002
Table 6.47. Multiple ana:Lysis of variance for nematode biomass by feeding

group by platfonn.

A. Platform: MAI-686, Dependent Variablesa: logio(1A biomass + 1) logio(1B biomass + 1)

logo(2A biomass + 1) logio(2B biomass + 1)

B. Platform: MTJ-A85, Dependent Variables: logo(1A biomass + 1) logio(1B blomass + 1)

logio(2A biomass + 1) logio(2B biomass + 1)

C. Platform: FU-A389, Dependent Variables: 1ogo(1A biomass + 1) log1o(1B biomass + 1)

logio(2A biomass + 1) logio2B biomass + 1)

aFor definitions see Table 6.45.

6-104

Source Error Pillais, Trace F Numerator DF Denominator DF Pr> F

C CtR 1.7459 3.8283 12 33 0.0011

R MSE 0.3154 2.0971 16 392 0.0079

C*R MSE 0.7187 1.7887 48 392 0.0016

D D*R 1.1597 1.6332 16 64 0.0854

C*D MSE 0.8495 2.202 1 48 392 0.000 1

DtR MSE 0.8928 1.7599 64 392 0.0007

C*D*R MSE 1.6110 1.3768 192 392 0.0044

Source Error Pillaits Trace F Numerator DF Denominator DF Pr> F

C C*R 1.6447 3.3374 12 33 0.0030

R MSE 0.1883 1.2101 16 392 0.2568

C*R MSE 0.367 1 0.8252 48 392 0.7906

D D*R 2.2990 5.4063 16 64 0.000 1

C*D MSE 0.8569 2.2264 48 392 0.000 1

D*R MSE 0.8220 1.5843 64 392 0.0048

C*D*R MSE 1.5781 1.3303 192 392 0.0097

Source Error PiUals Trace F Numerator DF Denominator DF Pr> F

C C*R 1.438 1 25322 12 33 0.0 172

R MSE 0.7895 5.9022 16 384 0.000 1

C*R MSE 0.6877 1.6611 48 384 0.0053

D DR 1.1266 1.5684 16 64 0.1041

CZD MSE 0.7710 1.9102 48 384 0.0005

D*R MSE 1.3876 3.1871 64 384 0.0001

CtDtR MSE 1.6900 1.5268 184 384 0.0003
seems to increase with depth, because the trend is very strong in the deep

sea (Carman et al. 1987). In general, deposit feeders dominate at muddy

habitats, composing up to 62 % of total nematode abundance, relative to only

11 % in sandy habitats (Wieser 1953). Epigrowth feeders and omnivorepredators dominate in sandy habitats and are rare in muddy habitats.

Deposit-feeding nematodes utilize the same habitat as deposit-feeding

macroinfauna, while epigrowth feeders utilize the same habitat as

harpacticoids.

The proportion of deposit-feeding nematodes was lower and the

proportion of epigrowtb-feeding nematodes was higher at the nearer

stations where there was more sand. Among platforms, deposit feeders

were present in lower abundance and epigrowth feeders were present in

higher abundance at the relatively sandy MAI-686 compared to the other

platforms in the study. At MAI-686, epigrowth feeders composed 34 to 45

% of total nematode abundance and biomass relative to 19 to 30 % for the

other platforms. Deposit-feeding nematodes composed 51 to 53 % of total

nematode abundance and biomass compared to 64 to 70 % at the other

platforms. These results support the idea that sediment grain size was

important in determining nematode community structure.

At HI-A389 and MU-A85, the same trend was not apparent. HI-A389

bad lower sand content than MU-A85, yet the proportion of deposit feeders

and epigrowth feeders was not significantly different at the two stations. A

possible explanation for this observation was that HI-A389 had higher levels

of sediment contaminants than MU-A85. The relatively smaller percent of

epigrowth feeders at HI-A389 may have been related to a contaminant effect

on nematode-feeding type composition.

The relationship between total nematode density, biomass, and

sediment type may be correlated with a contaminant effect or a water depth

effect. MAI-686 had the highest total nematode abundance, the highest

abundance of epigrowth feeders, and the lowest abundance of deposit

feeders. MAJ-686 was also the shallowest and had the lowest trace metal

concentrations of the platforms in this study. Nematode abundance and

feeding type composition at MAI-686 could have been due to the combined

effects of low trace metal concentrations, high sand composition, and

shallow water depth. The trend of nematode feeding types indicated a

platform and a sediment grain-size effect.

6-105
The distribution of harpacticoids around platforms did not follow the

same trends as the nematodes. Harpacticoids were predominantly

epigrowtb feeders, arid would be expected to be more common in sandy

secLiments. However, at all three platforms, sand composition was higher in

the near-field, while barpacticoid abundance was higher in the far-field.

Proximity to a platform seemed to decrease the abundance of harpacticoids.

Most diversity indices are sensitive to samples size, so the significance of

the harpacticoid diversity trends are less than for nematode diversity. The

best bio-indicators of platform contaminant effects, at the meiofauna level,

are harpacticoid abundance and nematode species diversity.

6.4.1.4 Predation Pressure on Meiofauria

To provide insight into the possible effects of grazing on meiofauna

abundance and biomass, stomach contents of selected small fish were

examined. Fish predator data is summarized in Section 5.4.2.1. Five of the

eight species examined were pelagic feeders, and were not feeding

primarily on the benthos. Four species occasionally ate meiofauna.

Prioriotus stearrzst fed upon some nematodes and ostracods, but this species

fed primarily on pelagic organisms, mainly small fish. Eighty-eight (88)

specimens of P. stearnst were collected, averaging 8.1 cm in length.

Cynoscion arenarius was a pelagic feeder that ate mostly calanoids. The

average size of the 84 specimens dissected was 8.3 cm. Hoptumnis sp. ate

mostly pelagic fish and macrofaunal polychaetes. The average length was

34.2 cm and 11 fish were dissected. Saunida brasilterisis fed mostly on fish,

calanoicis, amphipods, and shrimp. The sample size was 101 individuals and

the average length was 6.6 cm.

The total amount of food collected in stomachs was generally not a

function of fish size. An analysis of covariance was performed by fish

species, where the stations were all considered different. Only two fish,

Saunida brastliensis and Syacium gunteri, bad significant covariate

coefficients (Table 6.48). This means that for these two fish, larger fish ate

more prey. In some cases, fish were only found at one station (df=0 in Table

6.48), so the model decomposes to a linear regression.

Four species of fish were found in sufficient abundances to perform

Near versus Far comparisons to determine if more prey items were taken

6-106
Table 6.48. Analysis of covariance on fish stomach contents. All stomach

contents were pooled. Each platform*station combination was

treated as a separate station, thus the design reduces to a oneway ANCOVA,

near platforms. In all cases, the stomach contents of fish from the Near and

Far stations were similar. Only one fish, Halieuticthys aculeatus, had

different stomach contents among stations (ANCOVA, Table 6.45). The

difference was due to more prey items at MU-A85 (average total of 3.60

prey/fish) than at IVLAI-686 (average total 1.60 prey/fish).

6.4.2 Reproduction and Life History

Harpacticoid life history is complex, but reproductive parameters are

easy to measure (Webb and Montagna 1993). Harpacticoids undergo five

naupliar stages and six copepodite stages before they reach maturity,

cohorts are easy to identify. The sixth copepodite stage is the mature adult,

and the adults are sexually dimorphic. Whereas sex ratios of mature adults

are sometimes 1:1, more often females predominate. Copepods brood their

6-107

Fish Species Source df F P

Cynoscion arenarius Station 0 - - Length 1 0.12 0.7315

Halieuticthys aculeatus Station 3 5.21 0.0020

Length 1 0.61 0.4353

Hopturnnis sp. Station 0 - Length 1 0.52 0.4883

Ogcocephalus radiatus Station 0 - - Length 1 0.50 0.6088

Prionotus stearnsi Station 2 0.18 0.8315

Length 1 0.01 0.9069

Saunida brasiliensis Station 2 0.31 0.7328

Length 1 5.32 0.0232

Syactum guntert Station 1 0.35 0.5569

Length 1 11.91 0.0008

Synodus foetens Station 1 0.11 0.7433

Length 1 0.24 0.6289
eggs and have multiple broods, thus embryos can be easily counted and

measured for size differences at the platform and comparison sites, and

through time. Harpacticoids generally have between four to twenty broods

per individual, with four to thirty eggs in each clutch (Hicks and Coull

1983). Egg diameters are in the range of 20 to 150 pM. Adult harpacticoid

body lengths are between 0.3 to 1.5 mm, the smaller sizes being interstitial,

the larger sizes being epibenthic.

Two breeding patterns exist: (1) continuous breeders, where eggs are

produced throughout the year and (2) discontinuous, where breeding is

restricted to seasonal events. Subpopulations of one species have been

shown to have different reproductive patterns, although separated by only 8

m (Palmer and Coull 1980). It is not known why harpacticoids exhibit such

variable life history patterns. One hypothesis suggests food availability and

differential capability of various species to exploit these resources are

important (Hicks 1979).

Development rates are influenced by temperature, food supply and

salinity. Development times will increase with lower temperatures (Feller

1980; Palmer and Coull 1980). A complete life cycle (Hatch to Hatch) can

take from 11 days at 20 °C to 36 days at 8 °C (Muus 1967). Hicks and Coull

(1983) reviewed 31 studies and found all development times less than 42

days except one study that took 167 days (Feller 1980). Development times

and rates of estuarine harpacticoids are modified by changes in salinity

(Hicks and Coull 1983). All of the studies were performed in the laboratory

with estuarine species. Development rates are unknown for Gulf of Mexico

shelf species. However, salinity is constant, temperatures vary within a

narrow range, and the food supply decreases along a gradient away from

Mississippi River influence. Gravid females and juveniles were found

continuously throughout the year (Webb and Montagna 1993). Data related

to meiofauna reproduction is summarized and described in detail in Section

5.4.5.

6.4.2.1 Reproduction

Measures of reproductive effort (total egg volume in a clutch) were

compared for Near and Far stations for the three study sites for all gravid

females encountered. Clutch volumes were significantly (P = .0 14) larger for

6-108
Far stations than at Near stations for MAI-686 (Figure 6.27). Mean clutch

volume was also greater at the Far than Near stations at MU-A85, however,

the lower sample size (n = 39) was probably responsible for the lack of

significance. At HI-A389, Near and Far stations did not follow the same

trends as MAI-686 and MU-A85. HI-A389 Near stations bad greater clutch

volume than Far stations, although sample size was low (n 16 individuals;

Figure 6.27). The reduced clutch volumes at near stations may be a function

of diverted energies from growth and maintenance to detoxification of

contaminants. This diversion of energies results in lower availability of

resources for reproductive efforts and subsequently reduces clutch volumes.

Reduced brood sizes and total reproductive production have been

demonstrated in mesocosm studies using the water soluble fraction of

Louisiana crude oil on harpacticoida copepod, Nitocra affints. In all oilcontaminated tanks, reproductive efforts were diminished relative to

control values (Ustach 1979). This same relationship may be occurring at

MAI-686 and MU-A85 Near stations.

MU-A85 and HJ-A389 Near stations did have slightly reduced clutch

size differences relative to Far stations, they were not statistically significant

(Figure 6.28). A significant relationship between clutch size and water

depth may be explained by changes among the benthic habitats found at the

three different water depths. Therefore the vaxiation in clutch size may

actually be a function of varying species structure within each community,

since slightly different mean clutch sizes were found for all platforms.

6.4.2.2 Life History Characteristics

Analysis of life history characteristics was performed on all

harpacticoids encountered in the study. Harpacticoids were identified as

females. gravid females, males, and copepodites. All nauplii and copepodite

stages (Cl to C5) were assigned in a single category, copepodites. With all

three platforms combined (HI-A389, MU-A85, and MAJ-686), Far station

densities were significantly greater for harpacticoid females (P = 0.0001),

males (P = 0.0001), and copepodites (P = 0.0001; Table 6.49; Figure 6.29).

Using the same analysis, gravid female densities were significantly larger at

Near stations relative to Far stations (P = 0.000 1; Table 6.50).
Figure 6.27. Mean reproductive effort among all cruises, platforms, and three specie

effort is the total clutch volume (mm3).
11 ItAgrvir&. %w\'1ffvAIr1 I)irV'J'JR I U, 'V7- ax's L131fl10
Table 6.49. Life history stage densities for all harpacticoids.

ajo..way ANOVA was performed and P values for station differences is given, with mean

density (n/core) and platforms were pooled.

Table 6.50. Life history stages for all harpacticoids by platform.

aone..way ANOVA was performed to determine station (Near and Far) differences. P value for station differences is given and the station with larger mean density is reported.

6-112

Stage

MUA85a rnA389a

P Station P Station P Station

Female 0.000 1 Far 0.95 13 Near 0.960 Far

Gravid Females 0.881 Near 0.0002 Near 0.006 Near

Males 0.000 1 Far 0.348 Near 0.045 Near

Cop. 0.0003 Far 0.9 18 Near 0.390 Far

Stage Station Mean Density

pa Near Far

Females 0.0001 8.47 13.27

Gravid Females 0.0001 0.85 0.41

Males 0.000 1 5.83 8.66

Cop. 0.0001 10.57 15.15
It______

jV4

II&11II1MT

/

uO!JIS

id sjenP"!P"I

jo

jaqW'N UUat4J

/

c1

CD CD cv c a)

(0
Between station (Near and Far) differences were further analyzed by

site (Figures 6.30 to 32). The density of gravid females was significantly

more abundant at Near than at Far stations at HI-A389 (P=0.006) and MUA85 (P=0.0002). Also, significantly higher densities at Near stations were

found for males (P=0.045) at HI-A389 and males and females at MAJ-686

(P=0.0001). Densities of copepodites were significantly larger at the Far

stations of MAI-686 (Table 6.50).

Analysis was then performed on the proportion that each life history

stage represents of the total population. Population composition was

examined to reduce the possibility that larger sample sizes would skew

mean values. With data from all three study sites combined, significant

(P=0.0001) station differences were found for all life history proportions

(Table 6.51; Figures 6.33). In this analysis, gravid females and males

constituted larger proportions of the populations at Near relative to Far

stations. Copepodites and females' life history stage proportions were

significantly larger at Far relative to Near station.

Table 6.51. Population composition for all harpacticoids.

aplafforms were pooled and a two-way ANOVA was performed on life history

stage proportions. P values are reported for Station differences and mean

values.

Individual platforms were analyzed for between station (Near and Far)

differences in population composition (Figures 6.34 to 6.36). Gravid females

were significantly more abundant at Near stations than at Far stations at

MAI-686 (P = 0.001), and MU-A85 (P = 0.0001; Figure 6.37). Significant

proportion differences were also found for harpacticoid males at MAI-686

(P=O.05) and for both males (P=0.01 1) and copepodites (P=0.034) at HIA389. Far stations had larger proportions of copepodites at HI-A389 and

males at MAI-686. Composition of males at Near stations were larger at HIA389 (Table 6.52).

6-114

Stage

pa

Mean % Composition

Near Far

Female 0.0001 0.35 0.35

Gravid Females 0.0001 0.03 0.01

Males 0.000 1 0.23 0.21

Copepodite 0.0001 0.39 0.43
'Ii

III -

IIIIIIws

IIPIIf___

qv,J(,

4vArAi

U)

uojI3S

51np!A!PLI jo

jaqwflN ueeW

/

I

(c,
Figure 6.31. Harpacticold life history stage density fri x core-') for all cruises, stations, 

at MU-A85.
Figure 6.32. Harpacticoid life history stage density (n x core') for all cruises, stations

at HI-A389.
Figure 6.33. Harpacticoid life history percent composition for all platforms, stations, 
Co0

191013(0 1uaOJdd

¶1

r0

/

I

I
Figure 6.3. Harpacticold life history stage percent composition for all cruises, stations

species at MU-A85.
/

/ __

irAq'

b;var _ sIII, FYMPAk

P7 L /

;1cc

TIII

V

A

IEIO..L JO 1ueoJdd
Figure 6.37. Mean density (n x core') of gravid harpacticoid females for all platforms, 

species.
Table 6.52. Population composition for all harpacticoids by platform.

aOneway ANOVA was performed by platform on life history stage composition to determine

station (Near and Far) differences. P values for Station differences and the Station with larger mean are reported.

The mean density trend indicated that platforms were affecting

harpacticoid abundance. However, life history stage composition was

constant among platforms and between Near and Far stations. So, whatever

is causing population reduction appeared to equally affect all life history

stages. The significantly increased abundances of gravid females for Near

stations could be attributed to organic enrichment from the platforms.

Harpacticoids have been known to breed continuously in situations where

exploitation of abundant food supplies is possible (Hicks 1979). Organic

carbon levels are decreased near the platforms; however, this decrease is

not in proportion to the dilution from the increased sand contents. Also,

organic carbon loading from the platform could be in a labile form and its

assimilation arid regeneration by scavenger organisms would be rapid. This

scenario suggests possible enhanced TOC (total organic carbon) production

resulting from a concentration of organisms associated with the platforms.

Likewise, TIC (total inorganic carbon) from biogénic debris, and possibly

drill cuttings, increases near the platform. An overall increase in the

amount of available carbon is consistent with abundant food resources that

are highly labile. Labile organic carbon enrichment could be sufficient to

drive a continuous breeding pattern for harpacticoids near platforms.

Although this scenario seems plausible, increasing the availability of food

resom-ces has also been linked to overall increases in clutch size (Webb

1984). No significant difference in clutch size was found between Near and

Far stations suggesting that enrichment is not driving continuous breeding

strategies near the platforms. Therefore, the increased density and

proportion of gravid females found at Near stations for all three platforms

was not a function of enrichment based on continuous breeding.

6-123

Stage rn_A389a

P Station P

j...686a

Station

MuA85a

P Station

Female 0.861 Far 0.725 Near 0.856 Near

Gravid Females 0.0821 Near 0.001 Near 0.0001 Near

Males 0.011 Near 0.050 Far 0.523 Near

Copepodite 0.034 Far 0.520 Near 0.150 Far
Some studies suggest increased gravid female abundances may be

latitudinally attributed to a continuous breeding pattern. A few meiofaunal

species have been shown to reproduce throughout the year in tropical

latitudes (Coull 1975). In contrast, Hicks (1977) cites studies that suggest a

seasonal pattern in temperate latitudes, with most harpacticoid copepods

exhibiting a breeding maximum in spring, summer, fall, or winter

depending upon the species. The location of the study site on the "border'T

between temperate and tropical regions in the northern hemisphere may

account for mixed breeding strategies. However, increases in gravid female

life history stage percentages found at Near stations cannot be explained by

varying reproductive strategies between near and far stations on the basis of

latitudinal differences.

6.4.2.3 Body Size

Harpacticoid body sizes were compared between Near and Far stations

for three selected species (JJiathrodes sp., Longipedia americana, and

Cletodes pseudodissimtLis). Weighted body length means were used,

because size differences between males and females exist. Diathrodes sp.

showed no statistically significant differences in body size between stations

at platforms MU-A85 (P = 0.65) and MAI-686 (P = 0.14). Weighted mean

body size was 30 greater for Diathrodes sp. at MU-A85 than at MAI-686.

Only one individual of Diathrodes sp. was found at HI-A389. Longipedia

americana exhibited no statistically significant differences in body sizes

between Near and Far stations for MU-A85 (P = 0.55), MAI-686 (P = 0.46),

or HI-A389 (P = 0.52, Figure 6.38). Longipedia americana body sizes were

relatively constant over all three platforms and between stations (Figure

6.39). Analysis of Ctetodes pseudodissimilis was inhibited because no

individuals were found at near stations for all platforms. Ctetodes

pseudodisstmilis was found only at the MAI-686 Far station (n = 40) and at

the HI-A389 Far station (n = 1; Figure 6.40).

6.4.3 Harpacticoid Genetic Diversity

The objective of this component was to determine if genetic

differences in invertebrate populations can be used to detect and monitor

chronic, sublethal effects of offshore platforms. Generally, this approach is

6-124
11111111

fly.' I'1VffJA

11L

IIIE1r41L

1ff1,,A

'[fly a a

a

(Wi1) d2IS

I

6-125

CD

C
Figure 6.39. Mean body lengths (.tm) of D(athrodes sp., weighted for sexual differen

platforms and stations.
Figure 6.40. Mean body lengths (i.tni) of Cletodes pseudodlsstmifts, weighted for sexual 

for all platforms and stations.
used to determine if selective pressures have increased due to a sublethal

stress. Strong selective pressures may act to lower genetic variability by

eliminating less fit phenotypes and the associated genotypes from a

population (Avise 1994, Burton 1983). Human activities might potentially

create selective pressures of this kind (Alberte et al. 1994; Levinton 1980;

Murdoch and Hebert 1994). Long term stresses associated with offshore oil

and gas platforms might act to reduce the levels of genetic variability in

populations living close to the platforms. The primary hypothesis of this

component was that populations at Near stations will have less genetic

diversity than populations at the Far stations. Although it cannot be directly

tested, it was assumed that increased natural selection at the Near stations

would be responsible for this difference. A secondary hypothesis was that

contaminants associated with offshore drilling and production can be

correlated with this loss of diversity. Support for this hypothesis might

suggest that contaminants can account for increased selection at Near

stations.

The genetic diversity method is a novel approach to measure sublethal

effects. Generally, sublethal effects are of two types. The first approach

demonstrates a sublethal impact by quantifying a detoxification response.

Examples of this approach are measuring cytochrome P450 or bile

metabolite concentrations. An alternative approach is to look for changes in

abundance, diversity, or size of supposedly impacted organisms. Examples

of this approach are the macroinfauna and meiofauna components. The

genetic approach does not target possible responses to a sublethal impact.

However, if a population is responding to a sublethal stress, then natural

selection may cause an impacted population to look different from nonimpacted populations. The disadvantage of this approach is that virtually

nothing is learned about the nature of the sublethal response (e.g., a

detoxification response occurs or reproductive output decreases). However,

the genetic approach is sensitive to a wide variety of sublethal impacts that

might be overlooked by targeting selected responses.

The specific locus that was the focus of this study was the 1 6S (or

large subunit) of ribosomal RNA (rRNA) of the mitochondrial genome.

Mitochondnal DNA (mtDNA) is a useful marker for population studies. It

evolves rapidly, relative to nuclear DNA, and is maternally inherited, thereby

avoiding the confounding effects of recombination (Avise et al. 1987). It is

6-128
not suggested that the mtDNA genes are under rigorous selection because of

platform effects. Rather, mtDNA diversity is serving as an indicator for

population subdivisions that might occur because of selection operating on

specific, but unidentified, alleles that are the products of nuclear genomes

(Hedrick 1986). Frequency differences at the 16S mtRNA should be

regarded as indicators of associated genome-wide differences. The

usefulness of a genetic marker as an indicator of environmental quality is

dependent primarily on a predictable frequency of change in a stressed

population (Changon and Guttman 1989).

Results of the genetic variability study supported the primary

hypothesis of this component. Genetic variability data is summarized and

described in detail in Section 5.4.6. In each of the 30 stations, populations

of all five species were dominated by a single, nearly ubiquitous haplotype,

and a series of unique haplotypes. Halotype is defined as a region of DNA

with a particular sequence and roughly corresponds to the "allele" of classic

genetics (Nei 1987). A heavily skewed genotype frequency is consistent

with observations from other populations of marine crustacea, including

calanoid copepods (Bucklin, per. comm.), harpacticold copepods (Burton

and Feldman 1981), and decapods (Silberman et al. 1994). Despite the

contribution of the dominant haplotype, values of halotype diversity (h) still

varied from station to station. A multiple analysis of variance was performed

on h for each species, using distance (Near vs. Far), platform (HI-A389, MAI686 and MU-A85), and cruise (2 vs. 3) as main effects.

The ft values for three species (Normanella sp., Cletodes sp., and E.

pericoense) near a platform were approximately half the value of populations

away from a platform (Figure 6.41). For Normanella sp., the h value of 0.199

at the Near stations was less than the value of 0.396 at the Far stations (P =

0.0001). Cletodes sp. showed a similar trend with h at Near stations of

0.188 and h at Far stations of 0.315 (P=0.025). The h value for E.

pericoense was 0.170 Near and 0.343 Far from a platform (P=0.014). The

other two species (Robertsonta sp. and TachidieUa sp.) bad the same trend,

but were not significantly different between Near and Far. The lack of

significance was likely a function of the sample size, which was greater than

300 individuals for the three species that were significant, and less than

300 for the two species that were not significant.
Figure 6.41. Genetic variability of harpacticoid copepods by species for all platforms an
There were no significant differences in ft values among species or

between distances by cruise (Figure 6.42). Similarity between cruises taken

at different times of the year suggested that there was no seasonal effect for

any of the five species. Values of h Near were different from values Far from

a platform for all three platforms (Figure 6.43). However, there were no

differences among the Near stations at any platforms, nor among the Far

stations at any platforms. Similarity at all the far stations suggests that the

platforms are having an effect. If populations were merely subdivided over

large geographic scales (relative to the size of a copepod). then the Far

stations at one platform might have a different level of baplotype diversity

from those at another platform. Differences in genetic diversity (Table 6.53)

suggested that offshore oil and gas platforms may have a chronic, sub-lethal

impact on barpacticoid copepod populations. A loss of genetic variability

may reduce fitness by compromising a population's ability to respond to

intense selection.

Table 6.53. Suimnary of harpacticoid haplotype diversity.

Distance: near vs. far Yes 0.001

Platform: all near stations No 0.536

Platform: all far stations No 0.444

Species No 0.464

Cruise:2vs.3 No 0.380

aReS1tS of tests for a significant difference.

6.4.4 Relationship to Environmental Variables

The observed patterns in meiofaunal distributions can be correlated to

changes in the environment due to the presence of platforms. As described

earlier, principal components analysis was performed on all sediment

environmental variables to extract two principal components axes (PCA) to

describe variability in the environmental data. ChemPC 1 is related to

distance, which represents the contaminant and sand gradients associated

with platforms. ChemPC2 is related to differences between platforms

including hydrographic setting. This setting is mostly controlled by the

Test Differencea pa
g9 oinj spododoo pjo3flod.mq Jo Ajq.n 3jPUO ioj uuojjd Aq 

u spds jj 

%7.O '4 'H a
Figure 6.43. Genetic variability of harpacticoid copepods by cruise for all species an
water depth that platform is located in, which is also confounded with the

contaminant gradient among platforms.

6.4.4.1 Meiofauna Community Structure

Except for two cases, all eight meiofauna variables were correlated

with the two sedimentology/contaminant PCA factors (Table 6.54). Many

factors had a significant negative relationship with all meiofauna variables.

This means that in general, as depth and contamination increase, declines

in meiofauna population abundance and diversity will also occur. The only

exceptions were nematode density and biomass which were positively

correlated with ChemPC 1, and increase near a platform. The NC ratio had a

positive relationship with all PCA factors, because harpacticoid abundances

decreased relative to nematode abundance with increasing water depth and

proximity to the platforms. For harpacticoid abundance and diversity, the

strongest relationships occurred with ChemPC2, which represents the

platform differences and gradient across the continental shelf. For

nematode diversity, the strongest negative relationship was with ChemPC 1,

which represents distance from the platform.

The general pattern in nematode trophic dynamics, at all three

platforms was an increase in non-selective deposit feeders and epigrowth

feeders near the platforms, and a decrease in selective deposit feeders and

predators near the platforms. A correlation analysis with the PC axes was

performed to determine which environmental factors were correlated with

changes in trophic community structure (Table 6.55). All biomass and

density values were highly and negatively correlated with ChemPC2, which

indicates a general decline in abundance and diversity with respect to water

depth. There were significant and non-significant correlations with

ChemPCl and ChemPC2. Selective deposit feeder density and biomass was

negatively correlated with ChemPC 1, indicating a decline near platforms

related to the contaminant gradient. Non-selective deposit feeder density

and biomass was positively correlated with ChemPC 1, indicating a declining

density and biomass away from the platform. The results of the correlation

analysis are consistent with results from the MANCOVA.
Table 6.54. Correlation between meiofaunal variables and environmental

factors for all sites.

6-135

aThe variables are the axes from the Principal Component Analysis (PCA) of the

sediment/contaminant data (see Section 6.2)

Table 6.55. Correlation between melofaunal variables and environmental

factors by site.

aThe variables are the axes from the Principal Component Analysis (PCA) of the sediment/contaminant

data (see Section 6.2).

Variables MAI686a MuA85a HIA389a

ChemPC 1 ChemPC2 ChemPC 1 ChemPC2 ChemPC 1 ChemPC2

Meiofauna density -0.496 -0.167 -0.081 -0.067 0.164 -0.219

(0.0001) (0.0966) (0.4241) (0.5079) (0.1037) (0.0287)

Nematode density -0.492 -0.140 -0.119 -0.083 0.208 -0.205

(0.0001) (0.1653) (0.2400) (0.4094) (0.0378) (0.0411)

Harpacticoid density -0.489 -0.400 0.092 -0.107 -0.456 -0.452

(0.0001) (0.0001) (0.3645) (0.2873) (0.0001) (0.0001)

Others meiofauna density -0.40 1 -0.080 -0.2 15 0.0658 -0.297 0.030

(0-0001) (0.4266) (0.0319) (0.5156) (0.0027) (0.7654) NCRatio 0.165 0.467 -0.150 0.0740 0.497 0.242

(0- 1000) (0.0001) (0. 1363) (0.4645) (0.0001) (0.0152) Nematodebiomass -0.269 -0.220 0.373 0.062 0.480 -0.194

(0.0069) (0.0276) (0.0001) (0.5432) (0.0001) (0.0558) Nematode diversity 0.139 -0.318 -0.067 0.004 -0.725 -0.079

(0.1665) (0.0012) (0.5096) (0.9712) (0.0001) (0.4358) Harpacticoid diversity -0.382 -0.390 -0.030 -0.185 -0.556 -0.386

(0.0001) (0.0001) (0.7701) (0.0653) (0.0001) (0.0001)

Variables ChemPCla ChernPC2a

Melofauna density -0.007 -0.472

(0.9077) (0.0001)

Nematode density 0.0 12 -0.431

(0.8337) (0.0001)

Harpacticoid density -0.216 -0.507

(0.0002) (0.0001)

Others meiofauna density -0.141 -0.630

(0.0145) (0.0001)

NC Ratio 0.276 0.221

(0.0001) (0.0001)

Nematode biomass 0.255 -0.417

(0.0001) (0.0001)

Nematode diversity -0.339 -0.380

(0.0001) (0.0001)

Harpacticoid diversity -0.282 -0.420

(0.0001) (0.0001)
6.4.4.2 Harpacticoid Life History

Clutch volume was not significantly correlated to either of the

environmental principal component axes. No statistically significant

difference in clutch size occurred between Near and Far stations at any of

the three study sites. Platforms HI-A389 and MU-A85 exhibited slightly

greater clutch sizes for Far stations than at Near, 0.4 and 1.1 eggs/clutch,

respectively. For MAI-686, there was virtually no difference in the mean

clutch size between Near and Far stations. However, clutch size was

significantly correlated with ChemPCl (P = 0.038) and ChemPC2 (P = 0.003;

Table 6.56). The smaller clutch volumes found at Near stations for MAT-686

could be attributed to physiological factors. Gravid female body length was

not significantly correlated to ChemPCl (Table 6.57). The insignificant

correlation between gravid female body lengths and ChemPC2 diminishes

the likelihood that there is a positive relationship between body lengths and

clutch volumes as found in other harpacticoid copepods (Webb and

Montagna 1993). Density-dependent effects did not seem to affect clutch

volumes, since gravid female abundance at MAI-686 was nearly equal (± 2%)

at MAI-686 Near and Far stations. The lack of influence of body length and

clutch size on clutch volume for MAJ-686 and suggested that a possible

platform effect may be driving reproductive output independently of

physiological parameters.

Clutch size was significantly correlated to ChemPCl (Table 6.58).

Significant positive correlation of PC 1 with clutch size was related to

distance from the platform. This finding is inconsistent with the result that

no significant clutch size differences were found between Near and Far

stations for all platforms. MU-A85 and HI-A389 Near stations had slightly

reduced, but non-significant, clutch sizes relative to Far stations. In

contrast, the Pearson coefficient (0.22) was positive for ChemPCl. The

relationship between clutch size and contamination gradient suggested a

positive correlation between contamination and clutch size. Mean clutch

size was also significantly correlated to CbemPC2, which represents

platform effects. Of all of the components, ChemPC2 was primarily driven

by water depth. A significant relationship between clutch size and water

depth may be explained by changes among benthic habitats found in the

three different depths or platform sites. Therefore, the variation in clutch

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Table 6.56. Correlation between nematode feeding group variables and

environmental factors for all sites.

aThe variables are axes from the Principal Component Analysis (PCA) of the

sediment/contaninant data (see Section 6.2).

Variables ChemPCla ChemPC2a

Density (indivlduai X 10 cm2)

Selective deposit feeder -0.29 1 -0.362

(0.0001) (0.0001)

Non-selective deposit feeder 0.200 -0.387

(0.0005) (0.0001)

Epigrowth feeder 0.161 -0.420

(0.0053) (0.0001)

Predator -0.040 -0.343

(0.4876) (0.0001)

BIomass (mg wet weight X 10 cur2)

Selective deposit feeder -0.225 -0.295

(0.0001) (0.0001)

Non-selective deposit feeder 0.a48 -0.365

(0.0001) (0.0001)

Epigrowth feeder 0.212 -0.485

(0.0002) (0.000 1)

Predator 0.029 -0.417

(0.6141) (0.0001)
Table 6.57. Correlation between nematode feeding group variables and

environmental factors by site.

aThe variables are axes from the Principal Component Analysis (PCA) of the sediment! contaminant data

(see Section 6.2).

Table 6.58. Correlation of reproduction variables with axes of the principal

component analysis (PCA).

aThe variables are axes from the Principal Component Analysis (PCA) of the

sediment/contaminant data (see Section 6.2).

bSamples size is all gravid females encountered on all cruises (n=170

observations). Table gives Pearson correlation coefficients and the

probability the coefficient is equal to zero in parentheses.

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Variables

Density (individual X 10 cm2)

HIA389a MAI686a MUA85a

ChemPCl ChemPC2 ChemPCl ChemPC2 ChemPCl ChemPC2

Selective deposit feeder -0.102 0.011 -0.565 0.092 -0.512 -0.116

(0.3197) (0.9122) (0.0001) (0.3601) (0.0001) (0.2493)

Non-selective deposit 0.328 0.127 -0.158 -0.380 0.315 -0.090

feeder (0.0010) (0.2124) (0.1173) (0.0001) (0.0014) (0.3755)

Epigrowth feeder 0.460 -0.158 -0.514 -0.078 0.091 0.045

(0.0001) (0.1201) (0.0001) (0.4379) (0.3671) (0.6602)

Predator 0.010 -0.345 -0.376 -0.334 -0.036 -0.010

(0.9248) (0.0005) (0.000 1) (0.0007) (0.7238) (0.92 14)

Biomass (mg wet weight X 10 cm2)

Selective deposit feeder 0.088 -0.059 -0.539 0.056 -0.490 -0.111

(0.3900) (0.5664) (0.0001) (0.5831) (0.0001) (0.2698)

Non-selective deposit 0.389 -0.037 0.011 -0.370 0.567 0.015

feeder (0.0001) (0.7174) (0.9104) (0.0002) (0.0001) (0.8862)

Epigrowth feeder 0.403 -0.190 -0.428 0.015 0.425 0.096

(0.0001) (0.0612) (0.0001) (0.8789) (0.0001) (0.3439)

Predator 0.055 -0.326 -0.195 -0.251 -0.036 0.118

(0.5919) (0.0010) (0.0522) (0.01 16) (0.7191) (0.2430)

Axis a Clutch Volumet) Clutch Sizeb

ChemPC 1 -0.126 0.220

(0.238) (0.038)

ChernPC2 0.046 0.305

(0.668) (0.003)
size may actually be a function of varying species structure within each

community, since slightly different mean clutch sizes were found for all

platforms.

Gravid females were more common at near stations at all platforms

and for all cruises. Gravid female abundance was significantly positively

correlated (P = .0007) with ChemPC2 of the environmental variables

principal component analysis (Table 6.57). This correlation with distance

may suggest a possible sediment relationship with gravid female density.

Abundance of all life history stages was significantly negatively correlated (P

= .0001) with ChemPC2 (Table 6.59). This correlation indicates that a

change in community structure is driven by water depth differences among

platforms, since the three experimental platforms are in three different

depth regimes on the continental slope of the Gulf of Mexico. Deeper

stations may be lacking in food, therefore lower reproduction would be

common if predation is food limited.

Table 6.59. Correlation of life history stage densities for all harpacticoids encountered with axes from the chemistry principal component

analysis (PCA).

aThe variables are axes from the Principal Component Analysis (PCA) of the

sediment/contaminant data (see Section 6.2). bcopepyJite life history stage includes all Cl to C5 copepodites. Total samples used: n = 300, 4 Cruises, 3 Platforms, 25 stations. Pearson correlation coefficients and the probability the

coefficient is equal to zero in (parentheses) is provided.

There were significant correlations between body lengths and

ChemPC2 for both Diathrodes sp. (P=0.001) and Cletodes pseudosimtlis (P

= 0.011). Pearson correlation coefficients were positive for both species,

indicating increased body length with increased grain size or contamination.

The fact that highest sand concentrations were found closest to the platform

suggests that male body size may increase with increased proximity to the

platform, suggesting a possible platform effect. No significant PCA

Femalesb Gravidb Malesb Copepoditesb

ChemPCl -0.098 0.194 -0.031 -0.133

(0.092) (0.0007) (0.589) (0.022)

ChemPC2 -0.443 -0.242 -0.382 -0.242

(0.0001) (0.0001) (0.0001) (0.0001)
correlation was found for Lortgipedia amertcana males or females (Table

6.60). Only females of Cletodes pseudodtssimtlis had a negative correlation

with ChemPCl, indicating smaller females near the platforms. There was

little compelling evidence that there are obvious effects on body size related

to distance from a platform or exposure to contaminants.

Table 6.60. Correlation of body lengths with axes of principal component

analysis.

Cletodes

pseudodisstmtUsb Diathrodes spJ Longipedia amerjcanab

aThe variables are axes from the Principal Component Analysis (PCA) of the

sediment/contaminant data (see Section 6.2).

bsample size is n 312 between the three species. Table gives Pearson correlation coefficients and the probabifity the coefficient is equal to zero (in parentheses) is provided.

6.4.4.3 Harpacticoid Genetic Variability

Despite a clear trend of increasing haplotype diversity away from a

platform, it was impossible with the present design to determine what

factors cause this trend. It was possible to correlate changes in genetic

diversity with changes in the physicochemical environment around each

platform. A logistic, linear regression was used to search for a statistical

associations between genetic variability and environmental characteristics

described by the principal components axes (Carson and Templeton 1984).

The logistic regression was useful for this purpose because it can be used to

describe binomial, categorical data (SAS Institute Inc. 1990). The

dependent variable in the logistic model was the number of individuals not

in the dominant haplotype divided by the total number of individuals

surveyed per station. All five species were used in this analysis, since there

were no significant differences between species, and increasing sample size

increases the power to detect change. The independent variables used in

the equation were ChemPC 1 and ChemPC2. Using a forward selection

procedure, ChemPCl was included in the model: y = -0.2431 X PCi - 1.485

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Males Females Males Females Males Females

ChemPCl -0.654 -0.127 -0.041 -0.266 0.213 -0.153

(0.02 1) (0.7 10) (0.811) (0.047) (0-465) (0.520)

ChemPC2 0.609 0.371 0.539 0.106 -0.341 0.370

(0-035) (0.262) (0.001) (0.435) (0.233) (0.109)
(x2 = 18.16, P = 0.000 1). The second principal components axis was not

significant. Frequency of unique genotypes decreases as PCi, which is

primarily driven by contaminant and sand content increases. Frequency of

unique genotypes diversity did not change with CbemPC2, which represents

between-platform variations.

In addition to the logistic, linear regression performed on frequency

of unique genotypes data, a linear regression was used on values of h for all

species, platforms and cruises. ChemPCl was included in the model: y =

-0.063 X PCi + 0.3 19 (R2 0-376; Figure 6.44). The trend was very similar

to that of the logistic, linear regression, and both regression results were

consistent with the ANOVA results.

There was a clear difference between the Near and Far stations (Figure

6.44). Variance at the Near stationswas greater than variance at the Far

stations due, in this case, to the directional nature of benthic patterns

(Hartley's test for homogeneity of the variance). If variance at the Far

stations was greater than variance at the Near stations, then the difference

between Near and Far might be an artifact of sampling areas of two different

sizes. Because variance was higher near a platform, the total area sampled

does not seem to present a problem.

6.5 Macroinfauna

Benthic macroinfaunal organisms are useful for studying both the

general ecology of a region or area, and the acute and chronic effects

associated with human perturbations such as discharges of toxic substances.

Some portions of contaminants eventually settle to the bottom due to their

density relative to sea water or by adsorption onto sediment particles which

then settle. These substances then affect the organisms associated with the

bottom - the infauna and epifauna. The benthic infauna are primarily nonmobile or slow moving, small organisms and tend to be associated with

specific sediment types. This is caused, in many cases, by the larval stages

being induced to metamorphose by specific sediment types or by adults that

are already established. Once established, the organisms tend to remain in

that locality until removed by death or predation.

Environmental stresses in the form of natural events (low

concentrations of dissolved oxygen, changes in salinity and temperature)

6-14 1
y = -0.06251346x + 0.31 87455 R2 = 0.3758722 Figure 6.44. Relationship between haplotype diversity for all species, platforms, and cr

the environmental variables PCi (ChemPCl) by distance from the platform
and human induced stresses (discharges, dredging operations, trawling

acthrities) have some influence on the structure of benthic assemblages,

usually by removing part of the assemblage or causing those organisms that

can migrate to move away from the stress. Infaunal organisms that cannot

tolerate an environmental stress and cannot escape, perish.

Environmental stresses are of two types, acute (short-term, relatively

intense) and chronic (low level exposure over a long period of time). The

acute stress may kill large numbers of organisms, but once the stress is

removed, the bottom is recolonized. If the stress is chronic, larvae of the

"normal" inhabitants may be unable to settle and metamorphose, and the

stressed area thus remains devoid of intolerant species. Changes in benthic

species composition and abundance as one approaches a discharge site is

one indication of stress. Studies in shallow water have demonstrated that

the bottoms around produced water discharges are very depauperate

(Mackin 1971; Armstrong et al. 1979, Nance 1984, 1991). At some

distance beyond the depauperate zone there may be a zone of enhanced

benthic abundances. There has been no evidence of such a zone of

enhancement in offshore marine settings presumably because the greater

water depth and water movement causes discharges to be diluted to levels

that are not as toxic as in shallower, quieter waters.

Studies of benthic organism assemblages inhabiting soft bottoms have

been conducted in the northern and northwestern Gulf of Mexico since the

1950s. These studies have tended to cover wide areas with infrequent

sampling, or limited areas with frequent sampling. The earliest studies

were conducted by Hildebrand (1954) and Parker (1960), who reported on

macroepifauna and infauna, respectively, over broad areas of the shelf. More

regional studies involving infauna have been done on the Louisiana shelf

(Southwest Research Institute 1981; Fitzhugh 1984; McKinney et al. 1984;

Gaston 1985, Rabalais et al. 1991). Macroinfaunal studies on the Texas

continental shelf include studies along the upper Texas coast (Harper and

Case 1975), at the Buccaneer Oil/Gas Field (Harper et al. 1981b), off

Freeport, Texas (Harper et al. 1981a; 1991) and in the vicinity of Matagorda

Island Area Block 622 field (CSA 1989). The South Texas Outer Continental

Shelf Study (Berryhill 1977; Flint and Rabalais 1980) was a shelf-wide study

in the western Gulf of Mexico which had a macroinfaunal component.
These studies indicate several trends. The principal abiotic factors

governing the distribution of macroinfauna appear to be sediment type and

water depth. Water depth manifests itself as increasingly stabile abiotic

factors including temperature, salinity, dissolved oxygen, etc. with

increasing water depth. Shallower water abiotic factors, in contrast, are

much less stable as a result of seasonal variations. Although some species

are ubiquitous, the general trend is for certain infaunal assemblages to be

associated with specific depths. Abundances of infaunal organisms generally

decrease with increasing depth across the continental shelf. Seasonal

variability in species composition and abundance also decreases with

increasing water depth. Although the same species tend to be found

throughout the northern and western Gulf of Mexico, abundances of infaunal

organisms tend to decrease toward the southwest on the Gulf of Mexico

continental shelf. Infaunal assemblages are usually dominated by

polychaetous annelids in soft muddy bottoms whereas mollusks or

crustaceans may dominate in sandy or shelly bottoms.

Studies near oil field discharges in estuaries have indicated that

polychaetous annelids may be better able to tolerate hydrocarbons in the

sediments because they occur in larger numbers close to platforms than

other groups (Mackin 1971, Annstrong et al. 1979). Crustaceans, as a

group, may be least able to tolerate environmental stress. In particular,

ampeliscid atnphipod populations were depressed in the vicinity of both

platforms in the Buccaneer Field Study (Harper et al. 1981a,b). Arnpeliscid

amphipods were considered one of the most affected organisms during the

West Falmouth spill (Sanders et al. 1980). Also, ampeliscid amphipod

populations were reduced to virtually zero in the northwestern Gulf of

Mexico, coinciding with the onset of hypoxia (Harper et al. 1991). These

data suggest that crustaceans in general and ampeliscid amphipods in

particular may be useful as indicators of environmental stress.

The only major systematic offshore study of petroleum production

platforms in the western Gulf of Mexico occurred at the Buccaneer Field

south of Galveston, Texas. During a preliminary study, sediments adjacent to

the platform were found to be heavily oiled (208 ppm hydrocarbons) and

infaunal abundances were depressed at that location. Further studies

showed that both major platforms had a halo of depressed infaunal

abundances. The depression, however, may have been due to scour which

6-144
removed most of the soft sediments and exposed hard clay substrate rather

than toxic effects due to contaminants.

6.5.1 Analysis of the Overall Study Design

The macroinfauna variables measured were total density (n X core-i),

density of 8 taxonomic groups (n X core-1), species diversity (H'), total

number of species and an amphipod:polychaete (AP) ratio. The AP ratio was

designed to be analogous to the nematode:copepod (NC) ratio, since

polychaetes seem to increase with proximity to a platform, possibly due to

enrichment near platforms.

The test of the overall sample design; using all cruises, platforms and

distances; revealed significant interactions between variables (Table 6.61).

These interactions mean that the overall analysis cannot be interpreted for

most of these variables. Because there were different responses with

respect to cruise, platform, radii and distances; platforms should, in

general, be analyzed separately. The three variables that did not have

significant interactions were bivalve density, nemertean density and

ophiuroid density (Table 6.62). The tests for main effects of cruise, platform

and distance on these three macroinfauna variables were easily interpreted.

Ophiuroids exhibited no differences with respect to platform, cruise or

distance from platform. Nemertean density was just the opposite, exhibiting

differences among platforms, cruises and distances. Bivalve density was

different among platforms and cruises, but did not vary with distance from

the platform (Table 6.62). The significant cruise interactions were

attributed to the large number of animals collected during Cruise 3 (winter

1994).

Total macroinfauna density was lower at the farthest stations than at

the 50 m and 100 m stations (Table 6.63). Diversity, measured by H' and

richness (number of species) was higher near platforms. Amphipods and

foraminiferans increased away from the platform. Decapods, isopods,

nemerteans and polychaetes increased towards the platform. Bivalves and

ophiuroids did not change with distance from the platform (Table 6.63).

Because amphipods decreased towards the platforms, and polychaetes

increased towards the platforms, the AP ratio decreased towards the

platform (Table 6.63).

6-145
ap=platfoi-m, C=Cruise, D=Distance, R=radius; Yes=signillcarit, pO.Ol; No=Not

significant, pO.O1.

Table 6.62. Summary of tests of the main effects for overall sample design.

Main Effectsa

Variable Platform Cruise Distance

Total density (n X cored)

Diversity (H')

Number of species (n X core

Amphipod density (n X core1)

Bivalve density (n X core1) Yes Yes No

Decapod density (n X core4)

Foram density (n X core

Isopod density (n X core 1)

Nemertean density (n X core-1) Yes Yes Yes

Ophiurid density (xi X core4) No No No

Polychaete density (n X core 1) Amphipod:Polychaete ratio

aResult of significance tests for the three main effects are reported where higher order interactions were Not significant ("---"Not testable due to

higher interactions).

Table 6.61. Summary of the significance of interactions for the overall sample design based on macroinfaunal data.

Interactionsa

Variable C*D PZD P*C*D D*R(P)

Total density (n X cored) No Yes No No

Diversity (H') Yes No No Yes

Number of species (n X core Yes No No Yes

Amphipod density (n X cored) Yes Yes No No

Bivalve density (n X cored) No No No No

Decapod density (n X core No Yes No No

Foram density (n X core1) Yes Yes Yes No

Isopod density (n X core 1) No Yes No No

Nemertean density (n X core1) No No No No

Ophiurid density (n X cored) No No No No

Polychaete density (xi X core 1) No Yes No No

Amphipod:Polychaete ratio Yes No No No
Table 6.63. Tukey's multiple comparison test results by distance for the overall study design based on macroinfaunal variables.

aDeansformed means are presented (4 and means that are underlined are not different at the

0.05 level.

6-147

Variable Distance from the Platforma

Total density 50 100 200 1000 3000

(n X core') (46) (35) (26) (25) (22)

Diversity (H') 100 200 50 1000 3000

(2.70) (2.53) (2.50) (2.41) (2.34)

Number of species 100 50 200 1000 3000

(n X core-1) (21.7) (21.1) (17.8) (16.0) (15.4)

Amphipod density 1000 3000 200 100 50

(n X core-1) (3.2) (2.9) (2.4) (1.5) (1.5)

Bivalve density 50 100 1000 200 3000

(n X core1) (1.8) (1.6) (1.5) (1.4) (1.4)

Decapod density 50 100 1000 200 3000

(n X core-1) (3.3) (2.2) (1.7) (1.6) (1.6)

Foram density 3000 1000 200 100 50

(nXcore4) (1.7) (1.7) (1.4) (1.2) (1.1)

Isopod density 50 100 200 1000 3000

(n X core-1) (1.3) (1.3) (1.2) (1.1) (1.1)

Nemertean density 100 50 200 1000 3000

(n X cored) (3.1) (3.0) (2.1) (1.9) (1.7)

Ophiurid density 50 1000 100 3000 200

(n X core1) (1.3) (1.2) (1.2) (1.1) (1.1)

Polychaete density 50 100 200 1000 3000

(n X cored) (32.8) (26.0) (18.5) (14.9) (13.1)

Arnphipod:Polychaete 3000 1000 200 100 50

ratio (0.29) (0.28) (0.20) (0.03) (0.03)
There was no difference in species diversity among the three

platforms (Table 6.64). Although several of the respective taxonomic groups

were different at different platforms, total abundance of all macroinfauna was

not different at different platforms (Table 6.64). Polychaete and ophiuroid

densities were not different at any of the platforms.

6.5.2 Analysis by Platform Site

Each platform was individually analyzed (Tables 6.65 and 6.66).

Significant interactions were still present for all variables except bivalve,

decapod, isopod, nernertean and ophiuroid densities (Table 6.65). Note that

no isopods were found at MAI-686. MAI-686 had distance effects only for

diversity and nemertean density (Table 6.66). MAI-686 had cruise effects

for total density, species richness, and polychaete density. MU-A85 had

distance effects for species richness and amphipod. decapod, foraminiferan,

isopod and nemertean density. There were cruise effects for diversity,

richness, and amphipod, bivalve, nemertean and isopod densities. At 111-

A389, there were cruise effects for total density, and forarniniferan and

polychaete densities. Although several variables could not be tested due to

significant interactions, distance effects at HI-A389 were evident for all

variables except for arnphipod and ophiuroid densities. Only ophiuroids and

the AP ratio bad no changes with respect to cruise or distance from a

platform.

Differences between the five distances were tested at each platform

(Table 6.67 to 6.69). At MAI-686 (Table 6.67), there were few significant

differences among distances from the platform. Total abundance was higher

at the 50 m and 100 m stations than at all other stations. There were no

obvious patterns in specific taxa that would account for the increase. Only

amph.ipods and nemerteans showed any significant differences. Amphipods

increased away from MAI-686 and nemerteans increased towards MAI-686.

At MU-A85, the more distance effects were apparent (Table 6.68).

Again, total abundance was higher at 50-rn and 100-rn stations than at all

other distances. The number of species increased towards the platform,

although H' did not. Foraminiferans were significantly lower at the three

farthest distances. Decapods, isopods, nemerteans, and polycbaetes were

higher in abundance near the platform.

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Table 6.64. Tukeyts multiple comparison test results by platform for the

overall study design based on macroinfaunal variables.

aDeansformed means are presented (x) and means that are underlined are

not different at the 0.05 level.

6-149

Variancea Platforma

Total density (n X core'1) MUA85 MAP686 H1A389

(32) (30) (28)

Diversity ('it) MU-A85 MAI-686 HI-A389

(2.82) (2.20) (2.47)

Number of species MU-A85 MAI-686 HI-A389

(nXcore1) (23.3) (14.8) (17.1)

Amphipod density MAI-686 MU-A85 HI-A389

(nXcore1) (3.0) (2.3) (1.5)

Bivalve density MU-A85 MAI686 HI-A389

(nXcore) (2.0) (1.4) (1.3)

Decapod density MU-A85 HI-A389 MAI-686

(nXcore) (2.5) (2.0) (1.6)

Foram density HI-A389 MU-A85 MAI-686

(nXcore1) (1.8) (1.5) (1.0)

Isopod density MU-A85 HI-A389 MAI-686

(nXcore') (1.6) (1.1) (0.0)

Nemertean density MAI-686 HI-A389 MU-A85

(nXcore) (1.7) (2.2) (2.1)

Ophiurid density MU-A85 HI-A389 MAI-686

(nXcore4) (1.2) (1.2) (1.1)

Polycbaete density MAI-686 MU-A85 HI-A389

(nXcore4) (21.7) (19.5) (18.5)

Amphipod:Polychaete MAI-686 MU-A85 H1-A389

ratio (0.30) (0.13) (0.07)
aFor definition of variables and symbols see Tables 6.61 and 6.62.

Table 6.66. Summary of the significance of main effects tests by platform

based on macroinfaunal data.

aFor definition of variables and symbols see Tables 6.61 and 6.62.

6-150

Table 6.65. Summary of the significance of ffiteraction tests by platform

based on macroinlaunal data.

Site

Variable

Interactionsa

MAI-686 MU-A85 HI-A389

C*D D*R C*D DtR C*D D*R

Total density (n X core 1) No No Yes No No No

Diversity (H') No No No No Yes No

Number of species (n X core 1) No No No No Yes No

Ainphipod density (n X cored-) Yes No No No No No

Bivalve density (n X core1-) No No No No No No

Decapod density (n X cored) No No No No No No

Foram density (n X core1) No No No No Yes No

Isopod density (n X core 1) No No No No

Nemertean density (n X core 1) No No No No No No

Ophiurid density (ii X core-1) No No No No No No

Polychaete density (n X core-1) No No Yes No No Yes

Amphipod:Polychaete ratio No No No No Yes No

Sitea MAI-686 MU-A85 HI-A389

Variable C D C D C D

Total density (n X core 1) Yes No Yes Yes

Diversity (H') No Yes Yes No

Number of species (n X core 1) Yes No Yes Yes

Amphipod density (n X core1) Yes Yes No No

Bivalve density (n X core1) No No Yes No No Yes

Decapod density (n X core') No No No Yes No Yes

Foram density (ii X core 1) No No No Yes Yes Yes

Isopod density (n X core 1) Yes Yes

Nemertean density (n X core 1) No Yes Yes No No Yes

Ophiurid density (n X core-1) No No No No No No

Polychaete density (n X core 1) Yes No Yes

Amphlpod:Polychaete ratio No No No No
Table 6.67. Tukey's multiple comparison test results by distance at MA!-

686 based on macroinfaunal data.

aDefransfol-med means are presented (x) and means that are underlined are not different

at the 0.05 level.

6-15 1

Variable Distance from the Platfonna

Total density (n X core1) 1000 50 200 3000 100

(36) (33) (31 (26) (26)

Diversity (if) 50 100 200 1000 3000

(2.44) (2.39 (2.33) (2.02 (1.83)

Number of species 50 200 100 1000 3000

(nXcore) (17.6) (16.1) (15.1) (13.0) (12.2)

Amphipod density 1000 3000 200 50 100

(n X core-1) (5.9) (4.9) (3.2) (2.1) (1.3)

Bivalve density 50 200 1000 100 3000

(nXcore1) (1.6) (1.5) (1.3) (1.3) (1.2)

Decapod density 50 200 100 1000 3000

(nXcore') (1.9) (1.7) (1.6) (1.5) (1.4)

Foram density 200 100 50 1000 3000

(nXcore1) (1.0) (0.0) (0.0) (0.0) (0.0)

Isopod density

(n X core1)

- - - - Nemertean density 50 100 200 100 3000

(nXcore) (4.5) (3.1) (2.5) (2.0) (2.0)

Ophiurid density 50 1000 200 100 3000

(nXcore) (1.2) (1.1) (1.1) (1.1) (0.0)

Polychaete density 1000 50 100 200 3000

(n X core1) (23.8) (23.6) (21.5) (21.3) (18.5)

Amphipod:Polychaete 3000 1000 200 50 100

ratio (0.56) (0.49) (0.33) (0.38) (0.33)
Table 6.68. Tukey's multiple comparison test results by distance at MU- A85 based on macroinlaurial data.

aDellansformed means are presented (x) and means that are underlined are not different

at the 0.05 level.

6-152

Variable Distance from the Platforma.

Total density (n X core-1) 50 100 200 3000 1000

(45) (41) (27) (26) (25)

Diversity (H') 100 50 200 3000 1000

(2.94) (2.92) (2.76) (2.73) (212)

Number of species 100 50 200 1000 3000

(nXcore') (28.2) (26.2) (21.6) (20.6) (19-9)

Amphipod density 3000 200 1000 100 50

(n X core-') (3.0) (2.7) (2.7) (2.2) (1.3)

Bivalve density 1000 100 3000 200 50

(n Xcore1-) (2.2) (2.1) (2.1) (1.8) (1.8)

Decapod density 50 100 1000 200 3000

(nXcore1) (5.7) (3.2) (1.8) (1.8) (1.7)

Foram density 1000 3000 200 50 100

(nX core1) (2.2) (1.8) (1.5) (1.1) (1.1)

Isopod density 50 100 200 1000 3000

(n X C0re1) (2.3) (2.0) (1.3) (1.3) (1.2)

Nemertean density 50 100 1000 200 3000

(nXcore) (2.8) (2.4) (2.0) (1.8) (1.5)

Ophiuroid density 50 100 3000 1000 200

(nXcore4) (L4) (1.3) (1.2) (1.1) (1.1)

Polychaete density 50 100 200 1000 3000

(n X core-1) (27.1) (27.1) (18.5) (14.7) (14.4)

Polychaete:Amphipod 1000 3000 200 100 50

ratio (0.23) (0.18) (0.18) (0.05) (0.02)
Table 6.69 Tukey's multiple comparison test results by distance at HI-A389

based on macroinfauna data.

aDeansfonned means are presented (x) and means that are underlined are not different

at the 0.05 level.

At HI-A389 (Table 6.69), there was a significantly greater total density

of macroinfauna at the 50-rn station than at the 100-rn station. Species

richness was also higher near the platform. Among specific taxa groups,

amphipods and foraminifera had significantly higher densities at far stations

6-153

Variable Distance from the Platfonna

Total density (n X core-1) 50 100 200 1000 3000

(2165) (1327) (696) (547) (805

Diversity (H') 100 200 1000 3000 50

(2.77) (2.50) (2.49 (2.45) (2.14)

Number of species 100 50 200 1000 3000

(nXcore') (22.9) (19.4) (15.7) (14.5) (14.1

Amphipod density 1000 3000 200 50 100

(nXcore1) (34) (22) (21) (6) (6)

Bivalve density 50 100 200 3000 1000

(nXcore4) (37) (15) (4) (2) (1)

Decapod density 50 100 1000 3000 200

(nXcore1) (98) (34) (24) (17) (14)

Foram density 3000 1000 200 100 50

(n X core-1) (60) (37) (26) (21) (6)

Isopod density 100 200 50 1000 3000

(n X core 1) (6) (4) (2) (1) (1)

Nemertean density 100 50 200 1000 3000

(n X core1) (105) (39) (36) (21) (20)

Ophiuroid density 1000 50 100 3000 200

(nXcore1) (11) (8) (5) (4) (1)

Polychaete density 50 100 200 1000 3000

(n X core1) (1807) (1015) (504) (281) (243)

Polychaete:Amphipod 50 100 200 3000 1000

ratio (3.83) (3.29) (2.29) (1.61) (1.55)
( 500-rn). Bivalves, decapods and polychaetes densities were higher at

near stations (50-rn and 100-rn). Isopods, nemerteans, and ophiuroids

abundances were not significantly different among platforms. The AP ratio

did not change with respect to distance. This suggested that the AP ratio

may not be a sensitive indicator of macroiafauna response at platforms.

In summary, the variables that had the highest values near platforms

were total species abundance and species richness (number of species) for

nemerteans, decapods, and polychactes. Densities of ophiuroids and isopods

were low at all sites and did not significantly change with distance.

6.5.3 Macroinfauna Community Structure

A principal components analysis (PCA) was performed on total

macroinfauna density (Figures 6.45 to 6.48), amphipod density (Figures 6.49

to 6.52) and polychaete density (Figures 6.53 to 6.56) to look for species

trends associated with platform or distances. There were 649 total species

used for the total macroinfauna species density PCA. However, of these, 22

species were responsible for 25 % of the variation in the data set analyzed.

Fifty-seven (57) species accounted for 50 % of the variation and 112 species

were responsible for 75 % of the variation in the data. The fact that less

than a quarter of the macroin.fauna species accounted for three quarters of

the variation in the data suggests that trends in macroin.fauna density were

driven by a small number of species, and that approximately 500 of the

species collected and identified did not appreciably change the trend in the

data. There were 42 species of amphipods. Of these, 6 accounted for 25 %

of the variance, 14 accounted for 50 % of the variance, and 24 accounted for

75 % of the variance. There were 310 species of polychaetes identified in

the study. Fifteen (15) of these species accounted for 25 % of the variance

in the data set. Thirty nine (39) species accounted for 50 % of the variance,

and 75 % of the variance can be explained by only 79 species. The vast

majority of total macroinfauna, amphipods and polychaetes were not

distributed in any consistent patterns.

There were platform effects evident for total macroinfauna and

polychaete abundance. For total macroinfauna (Figure 6.45), the clustering

of points on crossplots of the macroinfauna PCi vs. PC2 suggest that both

axes accounted for variations among platforms. MU-A85 had the highest

6-154
Figure 6.45. PCA of total macroinfauna species community structure by pl
Figure 6.46. PCA of total macroinfauna species community structure at M
NC.) . S ]-- U 0 x x 0 0 I I I 0 I I I I 

Figure 6.47. PCA of total macroinfauna species community structure at M

x x x x 0 0xX xr'0 01.0 0 0 SD -2 0 1 2 3 

pci
Figure 6.48. PCA of total macroinfauna species community structure at HI
Figure 6.49. PCA of amphipod species community structure by platfor
Figure 6.50. PCA of amphipod species community structure at MAI-68
3 x ox 0U 0 0 I 00 9D. 0 0 U 

6 -2 0 1 2 T I I I I I I 1 I I I I I I 

Figure 6.51. PCA of amphipod species community structure at MU-A8

4 5 6 
-1 0 1 2 3 4 pci 

Figure 6.52. PCA of amphipod species community structure at HI-A38

c10 42- 0- -4- -6- 8 s00. U x 50m o lOOm o 200m 500m 5000m I I 1 I I I I I I I I I I I I I I I 

5 6 7 
Figure 6.53. PCA of polychaete species community structure by platfor
Figure 6.54. PCA of polychaete species community structure at MAI-6
86- 4- 2- 0- 0 0 0 , S U UX< P1!P' o 0 0 x0x 0 x 

6 -2 PCI Figure 6.55. PCA of polychaete species community structure at MU-A8

0 0 x 50m o lOOm o 200m 500m 3000m -2-4-- I I I 0 1 2 3 
Figure 6.56. PCA of polychaete species community structure at HI-A38
values for PCi, with HI-A389 intermediate, and MAI-686 with the lowest

values for both PCi and PC2. The species that accounted for this trend were

the spionid polycbaetes (Potydora sp., Prionospio sp., Sptophanes cf.

missionensis) and an isopod (Xenanthura brevttelson). All of these species

were associated with the MU-A85 platform. For polychaete species (Figure

6.53) the stations were distributed along PCi suggesting a platform effect.

The MU-A85 platform had higher values for this axis, while MAI-686 was

lowest and HI-A389 was intermediate. PC2 also seemed to show some

platform effect but the separation was not as clear as with PC 1. In addition

to the species mentioned above, the association of Eurythoe sp., Levesenia

reducta, and species of the family Onuphidae with MU-A85 were the

dominant determinant at differences among platforms. For amphipods

(Figure 6.49) there were no strong platform effects. However, amphipod

species and abundance were lower than polychaetes, and the small sample

size could account for the lack of significant trends.

It was necessary to do the analysis by platform to test for species

differences at the five distances from the platforms using a principal

components analysis. There was no consistent separation of species by

distance for amphipods at MAI-686 (Figure 6.46), MU-A85 (Figure 6.47), or

HI-A389 (Figure 4.49 to 4.52). For polychaetes, there was no difference

between species for any distances at MAJ-686 and MIJ-A85, and only a weak

separation of species by distance along PCi at HI-A389 (Figures 6.54 to

6.56). However, at all three platforms, there was more variance at the inner

three distances than at the outer two distances. In summary, there were

species differences among platforms for total macroinfauna and polychaetes.

There were no species differences along distances from platforms for any

6.5.4 Relationship to Environmental Parameters

The demonstrated trends in macroinfauna variables can be correlated

to the principal components axes generated from the environmental data.

When data from all platforms were considered, there was a positive

relationship between ChemPCl and total macroinfauna density and species

richness that was highly significant (P < 0.0001; Table 6.70). As ChemPCl

increased species abundance and richness increased. This trend was most

6-167
Table 6.70. Correlation between rnacroinfaima variables and environmental

factors for all sites.

aThe variables are axes from the Principal Component Analysis (PCA) of the

sediment/contaminant data (see Section 6.2).

likely due to organic enrichment effects near platforms and not contaminant

effects related to ChemPC 1. CbemPC2 was not correlated with species

abundance or richness, and only a slight negative correlation (P = 0.0242)

with species diversity (H').

When platforms were considered independently, a similar trend was

revealed (Table 6.71). ChemPCl was strongly correlated with species

abundance at HI-A389 and MU-A85 at the P < 0.00 1 level, and MAI-686 at

the P < 0.05 level. ChemPC2 was negatively correlated with species

abundance at MAI-686, and MU-A85 only. The interpretation was that

there were more animals in shallow waters than deeper waters. Species

diversity (H') was correlated negatively with ChemPCl at HI-A389. In this

case, macroinfauna could be responding to a contaminant toxic effect and

not the organic enrichment effects. Species diversity was positively

correlated to ChemPCl at the other two platforms. Because these platforms

were less contaminated, organic enrichment was probably responsible for

the observed trend. Diversity showed a significant negative correlation with

ChemPC2 at all platforms. This observation is consistent with diversity

patterns in the continental shelf. In general, diversity increases with depth.

Species richness followed a pattern similar to the diversity index. There

were positive correlations between species richness and ChemPCl, and

negative correlations between richness and ChemPC2. Diversity increased

towards a platform and towards deeper water.

Variable ChemPCla ChemPC2a

Total density 0.427 -0.074

(n X core1) (0.0001) (0.2027)

Diversity 0.023 -0.130

(if) (0.6947) (0.0242)

Number of species 0.253 -0.092

(n X core') (0.0001) (0.1137)
Table 6.71. Correlation between macroinfauna variables and environmental

factors by site.

a-I-he variables are axes from the Principal Component Analysis (PCA) of the sediment/contaminant data

(see Section 6.2).

6.6 Megafauna - Invertebrates

Physiological and environmental parameters such as temperature,

salinity, food availabffity, and exposure to chemical contaminants can affect

the health and productivity of marine invertebrates (Koehn and Bayne 1989;

Peterson and Black 1988; Sindermann 1983). These factors may act alone

or in concert to alter an organisms energy balance, affecting growth rate,

reproductive capacity, and susceptibility to disease and parasitism.

Ultimately, these factors can affect community composition and structure,

the ability to reproduce, and population health (Sindermann 1983).

Measures of community structure, reproductive development, and the

prevalence and intensity of parasites and disease were used to assess the

impact of platforms on the productivity and health of megafaunal

invertebrate species living at the study sites. Megafaunal invertebrate data is

summarized and described in detail in Section 5.7.

Statistical analysis was performed according to the overall data analysis

plan as outlined in Section 2.0. The sampling regime for the megafaunal

invertebrate reproduction work element included samples from Near and

Far stations. Radii were not included in the sampling scheme. Without radii

in the analyses, the statistical approach becomes a multivariate analysis of

covariance (MANCOVA). Each dependent variable was analyzed by

MANCOVA to determine the effect of cruise, distance, platform, and

covariates of reproductive effort and health. All analyses were first

performed using MANCOVA models that included all interaction terms.

6-169

Variable

MAl686a MUA85a HIA389a

ChemPC 1 ChemPC2 CbemPC 1 ChemPC2 ChemPC 1 ChemPC2

Abundance 0.236 -0.399 0.347 -0.493 0.702 0.148

(nXcore1) (0.0180) (0.0001) (0.0004) (0.0001) (0.0001) (0.1404)

Diversity 0.504 -0.220 0.215 -0.346 -0.235 -0.376

(H') (0.0001) (0.0277) (0.0321 (0.0004) (0.0186) (0.0001) Number of species 0.52 1 -0.410 0.287 -0.581 0.285 -0234

(n X core1) (0.000 1) (0.00 1) (0.0037) (0.000 1) (0.0040) (0.0191)
More detailed analyses were performed by platfonn and by sex to eliminate

those interactions what were significant. Dependent variables include size,

sex, stage of reproductive development, prevalence of parasitism and

disease, intensity of parasitism and disease, and catch per unit effort.

Dependent variables were transformed by ranking when appropriate.

Cruise, distance, platform, sex, stage of reproductive development, and time

of collection were treated as class variables. In some models, size was also

used as a covariate. Three MANCOVA models were used for each analysis.

The first analysis was at the level of species. This model included all

information about individuals of each species regardless of platform,

distance, or sex. The second model was sorted by species and platform,

thereby comparing all individuals of each species at each separate platform.

The third level sorted individuals by sex. Particular attention was focused on

differences between Near and Far stations at each platform. Accordingly,

these differences were investigated for each species and, where possible, for

each sex.

Histological analysis limited the number of individuals of each species

at each platform and each distance to ten (10). In some instances, a greater

examined number of individuals was obtained by collectively analyzing

species of the same higher taxon. Four groupings of species were used;

portunid crabs, mantis shrimp, starfish, and penaeid shrimp. The

assumption underlying these groupings is that these species have similar

lifestyles and, thus, should react similarly to environmental gradients. In

combining species into higher groupings, differences in species size were

minimized by normalization to the largest individual. For example,

individual species of shrimp were very different in size (i.e., P. aztecus is

much larger than T. simiUs). The maximum size for each species collected

during all four cruises was determined by univariate analysis. The size of

each individual was then normalized to the maximum individual size. Thus,

in this analysis, size was used as a dependent variable, or a covariate, and

was defined as a proportion of the maximum size collected for that species.

By this means, species with different size ranges could be grouped together

and analyzed. Analyses on groups of species followed the same approach as

for individual species.
6.6.1 Catch Per Unit Effort (CPUE)

Differences in CPUE were compared for each species between the

Near and Far stations using multiple analysis of covariance (Table 6.72).

CPUE is summarized and described in detail in Section 5.6.1. Significant

differences in CPUE between the Near and Far stations were few; however,

more species had significantly different CPUE values at MAI-686. Several

species at MAJ-686 were more abundant at the Far station, including three

species of shrimp and a starfish. Species of crabs and mantis shrimp were

more abundant at the Near station. At MU-A85, the scallop and one species

of shrimp were more abundant at the Far station and a species of mantis

shrimp was more abundant at the Near station. One species of crab and one

shrimp at HI-A389 were significantly more common at the Near station. Of

the seven species that were collected at more than one platform, (T. similis,

P. aztecus, A. duplicatus, S. chydaea, P. spintcarpus, S. atlantidis, and A.

cingulatus), only T. similis had significantly different CPUE values at both

platforms. In both cases, T. stmilis were more common at the Far site. The

absence of additional examples like T. similis suggested that characteristics

specific to individual platforms exert a primary control on species

distributions and abundances.

Many marine invertebrates are more active from dusk to dawn.

Trawling was conducted from noon to midnight to bracket dusk and include

trawling time after dark. CPUE can be biased by the time of day when the

collections were made (Brusher et al. 1972). To determine whether

collections and, therefore, CPUE were biased by time of day, the trawis were

assigned to one of three equal time periods: 1200 to 1559; 1600 to 1959,

and 2000 to 2400. Except durLng the longer spring days, time period 2

bracketed dusk and time period 3 was after sunset. Several species at each

platform had significant relationships between time of collection and CPUE;

those species are designated in Table 6.72. In each of the significant cases,

time period 3 (after dusk) had higher CPUE than the other time periods. In

fact, in every case except A. cingulatus (HI-A389). time period 3 had a

higher CPUE, whether significant or not, suggesting that time of day bad a

significant relationship to the numbers of individuals collected and,

therefore, that measures of abundance increased after dark due to increased

activity in megafaunal species. Thus, overall means include this bias.

6-17 1
Table 6.72. Differences in catch per unit effort (CPUE) for species

collected from the Near and Far Stations at each platform.

T. similis **

S. dorsalis (a')

P. azt.ecus

A. duplicatus

T. similis

A. papyraceurn (a)

MAI-686

C. similis

S. chijdra

MU-A85

A. duplicatus

P. aztecus ()

S. atlantidis (...)

P. spirticarpus (.') A. cingulatus

HI-A389

S. at(antidis (...)

M. quinquespiriosa A. alexandiia

Hermit crabs

A. cingulatus S. chydaea

S. edentnfn

P. gThbesiit"

S. ernpusa (S..)

S. chydaea

P. spinicarpus **

P. simiiis * (a)

atensks (*) designate the level of significance for species that have different CPUE between

the Near and Far stations (MANCOVA, * P 0.05 - 0.01; ** P = 0.01 - 0.001; *** p = 0.001 - 0.0001). Dark circles in parentheses indicate species that have a significant relationship between CPUE and the time of day of collection (MANCOVA, P = 0.05 - 0.01; 'a P = 0.01 - 0.00 1; .a. P =

0.001 - 0.0001).

To determine whether small animals or small species were

discriminated against during collection, the size of the organisms in each

trawl was compared to the time of day they were collected. Species, by sex,

at each platform that had a significant relationship between the time of

collection and the size of individuals collected are listed in Table 6.72.

Although some species at each platform showed a significant relationship

between time of collection and size collected, during no particular time

period were either larger or smaller individuals consistently collected

across all taxa. For example, larger individuals were not always collected

later in the day than smaller individuals for any species or grouped taxon.

CPUE is Higher at the Far No Difference in CPUE CPUE is Higher at the Near Stationa Between Near and Far Stationa

Stationa
Species that had a significant relationship with size are summarized in Table

6.73. These results suggest that size classes were collected equivalently at

all times and that differences in size were probably related to differences in

species' activity patterns, mpking certain sizes more active and available for

collection at different times.

6.6.2 Size-Frequency Distributions

Exposure to environmental stresses, including chemical contaminants,

can reduce growth rates in invertebrate species (Sindermann 1983).

Inspection of the size-frequency distributions, described in Section 5.7.3,

indicated that larger animals were often found farther from the platform

(Table 6.73). This difference was specifically tested using a MANCOVA as

reported in Table 6.74. At MAI-686, almost as many species were

significantly larger near the platform as far from the platform. Female P.

aztecus and most crabs were larger at the Far station whereas T. simiUs and

starfish were larger near the platform. Some of these differences were sex

specific. A different pattern occurred at MU-A85. At this platform, no

species had larger individuals at the Near station. In all significant cases,

larger individuals were collected at the Far station. This was true for both

sexes of S. atlantidis, scallops, some crabs and female stomatopods. The

opposite pattern occurred at HI-A389. At this platform, when significant,

larger animals were collected at the Near station. Species larger near the

platform included female (but not male) crabs and female stomatopods.

These results suggest that, although differences in size exist in some species

between sexes (see also Table 6.74), the differences in sizes observed are

more often related to differences in the size of the individual per se and not

just the preferential distribution of sexes between Near and Far stations.

Changes in size-frequency distributions may be related to season

because spawning and recruitment of younger, smaller individuals into the

population occurs only during certain periods of the year. Sex frequency

data for megafaunal invertebrates is summarized and described in detail in

Section 5.6.2. The difference in individual size between the summer (2 and

4) and winter (1 and 3) cruises was tested for significance using MANCOVA.

Individual size differed between cruises; some species were consistently

larger during the winter cruises as opposed to the summer cruises,

6-173
Table 6.73. Species collected at each platform that bad a significant relationship between individual size and the time of collection.

MAI-686

T. siniilis, Mttt (1), Fttt (2) S. dorsa!is, M (2), F (3)

C. similis, Ft (1) P. aztecus, M (3), F (3)

P. gibbesii. Ft (2) C. similis, M (2), mt (2)

A. duplicatiisttt (1) P. gibbesii, M (3), mt (3)

Portunid crabs, Ft** S. empusa, M (1), F (1)

All starfishttt S. chydru'a, M (2), F (1)

All shrimp, Mttt, F*tt Portunid crabs, M, Tnt

All stomatopods, M, F

MU-A85

aResults are for individuals collected on Cruise 3 and Cruise 4 only. M= male; F=female;

Int=interrnediate stage. Asterisks designate the level of significance, (MANCOVA, * ) =

0.05 - 0.01; tt P 0.01 - 0.001; S** P = 0.001 0.0001). Numbers In parentheses indicate the

tIme period during which the largest lndMduals were collected (1 1200 - 1559: 2= 1600

- 1959;3=2000-2400).

Significant Relationship No Significant Relationship

Between Size and Time of Between Size and Time of

Collectiona Collection5-

S. chydnea. Ft (2) T. similis, M (2), F (3)

A. papyraceumtt (1) S. atlantiths, M (3), F (3)

All stomatopods, F P. aztecus, M (2), F (3)

All shrimp, Mt P. spiriicarpus, F (2), Tnt (3)

S. chydaea. M (3)

A. cingulatus (2)

Portunid crabs, M, F

All stomatopods, M

All starfish

All shrimp, F

HI-A389

P. similis, Mt (2) S. atlantidis, M (2), F (1)

S. edentata. Mt (2) P. simitis, F (1)

P. sptnicarpus, F (3)

M. quinquespinosa, M (1), F (1)

A. alexandria, M (3), F (3)

Hermit crabs, M (1), F (2)

S. chydaea, F (2)

A. cingulatus (2) Porturild crabs, F

All stomatopods, M, F All starfish

All shrimp, M, F
Table 6.74. Results of multiple analysis of covariance determining whether

individuals are significantly larger at the Near or Far site at each platform.

P. aztecus,

C. similis, F*Z

Portunid crabs, M*, F, Intw

S. atlantidis, M**, F*

P. spirucarpus, Int* Portunid crabs, Int

S. chyciaea., F'S

A. papyraceum555

MAJ-686

P. aztecus, M

All shrimp, M, F

C. similis, M, Tnt

P. gibbesii, F, mt

S. empusa, M, F

S. chydaea, M, F

All stomatopods, M, F

MU-A85

T. sirnilis, M, F

P. aztecus, M, F

All shrimp, M, F

C. similis, M

P. spinicai-pus, M, F Portunid crabs, M, F

S. chydaea, M

All stomatopods, M, F A. cingulatus All starfish

HI -A3 89

S. atlantidis, M, F

P. similis, M, F

All shrimp, M, F

M. quinquespinosa. M, F

A. alexandria, M, F

Henmt crabs, M, F

S. edentata, M

All stomatopods. M, F A. cingulatus All starfish

6-175

T. similis, M555, F555

A. duplicatus555

All starfish55t

P. spinica-pus, F555 Portunid crabs, F'

S. chydo.ea, F

aM_.ma[e; F=female; Intinterrnediate stage. Asterisks (5) describe the level of significance:

* P = 0.05 -0.01; P = 0.01=0.001; P = 0.001 - 0.0001.

regardless of distance or platform (Table 6.75). For example, P. aztecus at

MAI-686 and A. pap yraceum at MU-A85 were larger during the winter

cruises at both the Near and Far stations than during the summer cruises,

suggesting a late winter or early spring spawning season in these species at

these platforms. T. similis and starfish at both MAI-686 and MU-A85 were

larger during the summer cruises, indicating that younger, smaller

Individuals are Larger at the Far No Difference in Size Individuals are Larger at

Stationa Between Near and Far the Near Stationa

Stationa
individuals were collected during the winter cruises. This suggested a fall

spawning season for these species. These differences in size based on

cruises may indicate when spawning occurs in these populations. However,

more frequent sampling is required to rigorously assess the timing of

spawning in these populations.

The results of size-frequency distribution and CPUE can be combined

to compare the size and abundance of species at both the Near and Far

stations. Combined results show that not only are some species larger

farther from the platform, but they are also present in higher abundance.

For other species, abundances do not change whereas size distributions do

(Tables 6.73 and 6.75). For example, P. aztecus were more abundant at the

Far station of MAI-686 and the females were also larger. The same is true

for scallops (A. papyraceurn) at MU-A85. In the case of T. similis and A.

dupltcatus at MAI-686, the individuals were larger near the platform, but

were more abundant far from the platform. S. empusa at MAI-686 and P.

similis at HI-A389 were more abundant at the Near station, however sizeclass distributions were unaffected. These distinctly different patterns in

size-class distributions and abundances are thus platform speciflc and are

probably related to unique environmental and chemical conditions locally

present at each platform, rather than the presence of the structure in the

habitat.

6.6.3 Histopathology

Pathologies may be used as indicators of environmental degradation

(Sindermann 1983). Environmental stresses resulting from exposure to

chemical contaminants can affect individual health by altering the

physiological, biochemical, and behavioral processes of an organism, causing

cell and tissue damage, and lowering resistance to disease and parasitism

(Sindermann 1983). Therefore, the increased prevalence or intensity of

parasitism or disease with proximity to platforms could indicate chronic

exposure to chemical contaminants. Megafaunal invertebrate bistopathology

data is summarized and described in detail in Section 5.6.3.

Prevalence of parasitism was compared for each species at both the

Near and Far stations of each platform using multiple analysis of covariance.

Only one species showed significant differences in prevalence of parasitism

6-176
Table 6.75. Results of MANCOVA analysis determining whether a

relationship exists between individual size and the cruise on which the individual was collected.

MAI-686

MU-A85

simiLis (2) C. similis

P. aztecus*** (4) S. chydaea

S. atlafltidiS*** (4) All stomatopods

All shrimp* (4) A. duplicatus

A. crnguLatus (4)

A. papyraceum** (3)

P. spinicwpus (4)

Portunid crabs*** (4)

All starfish*** (4)

HI -AS 89

All shrimp* (4) S. atlantidis

P. spinicwpus*** (4) P. similis

Portunid crabs*** (2) A. alexandria

M. quinquespinosa** (3) S. chgdaea

Hermit crabs** (4) S. edentata

All stomatopods

A. cingu.latus All starfish

(1 represent levels of significance * P = 0.05 0.01; ** P 0.01 - 0.001;

P = 0.001 - 0.000 1. Number in parentheses indicates the cruise on which

the largest individuals were collected. Cruises 2 and 4 are summer cruises,

Cruise 3 is a winter cruise.

Significant Relationship No Significant Relationship

Between Individual Size and Between indMduai Size and

Cruisea Cruisea

P. aztecus (3) 1'. similis

C. simiLis (2) P. gtbbesii

All shrimp*** (3)

Portunid crabs (2)

S. empusa* (3)

chydaea (4)

All stomatopods* (3)

A. dupLicnhic (4)

All starfish*** (4)
between Near and Far stations. A. duplicatus had a significantly higher

prevalence of parasitism at the Far station than at the Near station at MAT686 (MANCOVA, P = 0.000 1). None of the shrimp or crab species analyzed

had significant differences in prevalence of parasitism based on proximity to

the platforms.

Intensity of each individual parasite and pathology was compared for

individual species at both sites and each platform using MANCOVA. The

model compared differences in the intensity of each parasite and pathology

among platforms, distances and cruises. In this model, only two intensities

of parasitism were significantly different between Near and Far stations;

nematodes in T. similis and gill filaments with inclusive bodies in P.

spinicarpus. In both cases, the intensity was higher at the Near station at

MU-A85 (P = 0.036 and 0.025, respectively).

However, size, and therefore age, are normally important in

determining infection intensity. By virtue of their longer life, older

individuals have a higher possibffity of being parasitized or diseased because

of increased exposure to infective agents. Thus, significant differences in

infection might be obscured or enhanced by the substantial size differences

between individuals at Near and Far stations. Accordingly, individual size

was added to the model as a covariate, so that individuals of the same size

were compared to determine whether intensities of parasitism were

different between Near and Far stations. Like differences in size

distributions, the pattern produced by differences in intensity of individual

parasites and pathologies was platform specific (Table 6.76). At MAI-686

and HI-A389, a similar number of parasites or pathologies was found at

higher intensities at Near and Far stations. Many more significant

differences were observed at MAI-686, but the data set was larger. At MUA85, many more parasites and pathologies were found in higher intensity

close to the platform. Thus, only at MU-A85 was the distribution of

parasites and pathologies consistent across megafaunal taxa and across

malady type. Once again, platform-specific effects produced by the local

physical or chemical environment seem to be most important in

determining the health of invertebrate populations.

Most individuals analyzed histologically bad occurrences of more than

one parasite or pathology in their tissues. Little information exists in the

literature concerning the relative effect of any of the parasites observed on

6-178
Table 6.76. Results of histopathological analysis of tissues to determine whether a significant relationship exists between the intensity

of parasitism and the distance from the platform.

MAI-686

T. similts, F* - Bac T. similis, F54 - Gut

P. aztecus, MS - Gut C. similis. M555, F5 - Nem

All starfish, M** - Nem P. aztecus, F5 - Ces

A. ILLPLLCcZtIIS, M55 - Nem C. similis, M5 - GFB

P. aztecus, M5 - Ces

T. similis, F554 - Cyst

MU-A85

HI -A3 89

P. similis, M5, F5 - Ces M. quiriquespinosa, M555 - MGF

aMmajes; Ffemales. Abbreviations are used for the parasite or patholor category: Nem, nematodes; Ces, cestodes; Bac, Baculovirus; Gut, gut inflammations; Cyst, cyst in muscle or

connective tissue; GFB, gill filament with inclusive body; MGF, malformed gifi ifiament.

Asterisks (5) indicate the level of significance determined by MANCOVA: * P = 0.05 - 0.01;

P = 0.01 - 0.001; P 0.001 - 0.0001.

an organisim. Deciding which parasite or pathology has the most

detrimental impact on host health or reproductive effort is difficult. For

example, cestode parasites were much larger than nematode parasites, but

nematodes were typically more abundant in an individual than cestodes.

Therefore, determining whether the larger parasite or the more numerous

parasite had a more detrimental effect is difficult. Consequently, to

determine the cumulative effect of total parasitism and disease on an

individual's health and reproductive effort, the number of occurrences of

each separate parasite were weighed based on the maximum number of

occurrences recorded in that species. In this way, none of the parasites or

pathologies were given more importance than the others. The maximum

number of occurrences of each parasite in each species was divided into

Intensity of Parasitism is Higher intensity of Parasitism is Higher

at the Far Stationa at the Near Stationa

P. aztecus, F4 - Bac A. cingulatus, F - Nem

All starfish, F555 - Nem

P. aztecus, F5 - Ces

P. spinicaipus, M45 - GFB

Portunid crabs, M554 - GFB

C. similts, M4 - MGF

Porturild crabs, M55 - MGF
quartiles; the 2Sth, 50th, 75th, arid lOOth; using univariate analysis. Each

individual was given a score from 0 to 4. Thus, true zeroes were maintained.

The number of occurrences of parasites in each individual was then

allocated to the appropriate quartile and the score assigned. For example,

for nexnatodes in P. aztecus, the 25th quartile had two occurrences, the 50th

three occurrences, the 75tb 10 occurrences and the 100th 146

occurrences. An individual of P. aztecus with 26 occurrences of nematodes

received a score of 4 for nematodes. The scores for each parasite and

pathology were then summed and a single score representing the total

amount of parasitism was obtained. That final score representing the

cumulative effect of all parasitism was considered a measure of overall health

and used in the MANCOVA.

No species had significantly different levels of total parasitism and

disease associated with distance from the platforms. The results of this

model suggest that populations at both Near and Far stations are parasitized

and that the differences observed are parasite specific. Some maladies may

respond to the environmental gradients present while others do not.

Generally, older individuals are more highly parasitized than younger,

smaller individuals. When size was added to the model using cumulative

parasitism (size was assumed to imply age), only female P. aztecus at both

MAI-686 and MU-A85 had a significant relationship between size and

parasitism (P=0.0 197 and 0.0038, respectively). Larger individuals were

more heavily parasitized. P. aztecus is one species in which females are

larger than males. Thus, the result may also suggest a sex difference in

intensity of parasitism, in that females were more highly parasitized than

males.

6.6.4 Reproductive Effort

Little is known about the reproductive effort of most continental shelf

invertebrates. Accordingly. whether reproductive effort is affected m these

species by the presence of a platform is largely unknown. Widdows (1985)

suggested that stress caused by exposure to pollutants reduces fecundity,

egg size, egg lipid content, and larval survivability and growth. Reproductive

responses can therefore serve as an ecologically important measure of

contamination impacts because it influences production and maintenance of

6-180
populations (Widdows 1985). Therefore, several methods were utilized to

assess differences in the reproductive effort of megafaunal invertebrate

species living near and far from platforms. Differences in male-to-female

ratios, percent gravid females (crab species), and stage of reproductive

development determined by visual inspection, histological analysis and by

immunological probe were used to indicate sublethal effects of exposure to

chemical contaminants or other platform related perturbations of

reproductive effort. The relationship between health (as defined by

prevalence and intensity of parasitism and pathologies) and stage of

reproductive development was also examined. Data related to reproductive

effort for megafaunal invertebrates is summarized and described in detail in

Section 5.6.4.

6.6.5 Male-to-Female Ratios and Percent Gravid Females

Differences in the distribution of males and females between Near and

Far stations was determined for all individuals collected using MANCOVA

(Table 6.77). Sex ratios and percent gravid female data are summarized and

described in detail in Section 5.6.5. Although sex was determined for a

number of stomatopod and crab species, significant effects were only

observed for two species of shrimp and one species of crabs. Of the four

significant results, females were more common at the Near station for three

of them; T. simiUs (MAJ-686) and C. similis (MAI-686 and MU-A85). S.

atlantidLs (MU-A85) populations bad significantly more females at the Far

station. Size was added to the model to determine whether a difference

existed unrelated to size. In this case, more species had significantly

different results, and significant results were found in shrimp, crabs, and

stomatopods (Table 6.77). The Near and Far stations at MAJ-686 and MUA85 had similar numbers of species with significantly larger females.

Females were only significantly larger for species collected at the Near

station at HI-A389.

The percentage of gravid female crabs was determined for each

species collected at both the Near and Far stations. A gravid female crab was

one collected "In. sponge"; that is with a visible egg sac. MANCOVA analysis

indicated that no significant difference existed in the number of gravid

females collected related to distance from the platform.
Females more common Far No difference between Near Females more common

Stationa and Far Stationa Near Stationa

aAsterisks (*) indicate the level of significance, * P = 0.05 - 0.01; P = 0.01 - 0.001; P = 0.001

- 0.0001. Dark circles indicate significant differences when size was Included in the model (

P = 0.05 - 0.01; .. P = 0.01 - 0.001; .. P = 0.001 - 0.0001).

A gonadal-somatic index (GSI) was calculated using the relationship

between egg sac dry weight and body dry weight to determine body weightspecific changes in egg sac weight. Larger individuals should have larger egg

sacs. GSI was calculated for individuals collected on the last two cruises.

Only two comparisons could be analyzed statistically, both at MAI-686. At

this site, GSI for C. simtlis was significantly higher at the Near as compared

to the Far station (MANCOVA, P = 0.0318). P. gibbesti also had a higher GSI

at the Near station, however, it was not significant.

6.6.6 Stage of Reproductive Development

The cost of reproduction to an individual can be measured in terms of

energy taken away from basic metabolism and growth for the production of

gametes (Calow 1979). Environmental stresses may alter an organism's

energy budget and thereby, the partitioning of energy between growth and

6-182

Table 6.77. Results of MANCOVA analysis to determine which species have a significant relationship between sex and distance from

the platform.

MAI- 686

P. aztecus (..) S. empusa T. sIrnilis*

P. gibbesll (..) S. cbydaea C similIs***

MU-A85

S. atlanttdist (a..) P. spinicarpus S. atlantidis (')

T. sirnilis (a..) S. chydaea P. aztecus, F (...)

C. shnhlis

HI-A389

S. atlantidis P similis, F ('a.) P. sprnicarpus S. chydaea F (a.) M. quinquespiriosa A. alexandria

S. edentata

Hermit crabs
reproduction, often resulting in delayed reproductive development (Koehn

and J3ayne 1989). However, some species may accelerate their reproductive

effort in the presence of stress to assure the production of the next

generation (Calow 1979). Therefore, differences in the stage of

reproductive, effort between individuals collected from Near and Far stations

could represent different responses to environmental stresses.

Reproductive effort may also be related to the age and size of the organism

which can also be adversely affected by environmental stresses. All data

collected on the stage of reproductive development in megafaunal

invertebrates is summarized in Section 5.6.6.

Stage of reproductive development was determined through visual

inspection of all females of shrimp and crab species. Reproductive

development may be delayed by exposure to contaminants and may also be

related to the size (age) of the individuaL Few significant differences in the

stage of reproductive development with proximity to the platforms were

found (Table 6.78). However, two species of shrimp showed a relationship

between distance from the platform and stage of reproductive development.

S. atlanticlis and P. similis at HI-A389 both were significantly further along in

reproductive development at the Far station, where the largest females were

also collected. Thus, variations in size between populations could obscure

site-to-site differences in reproductive development. Accordingly, size was

added to the model as a covariate. Jn this analysis, stage of reproductive

development varied significantly with distance from the platform for nearly

all species at MAI-686 and for S. atlantidis, at MU-A85. S. atlantidis for

example, bad a higher stage of reproductive development at the Far station

at MU-A85 and T. simitis had a higher stage of reproductive development at

the Far station at MAI-686, even though larger individuals were collected at

the Near station. These results indicated that the largest individuals were

not always the farthest along in reproductive development.

The stage of reproductive development was also determined through

histological examination of both males and females of target species. Again,

few differences in stage of reproductive development were related to

distance from the platform (Table 6.79). Regardless of distance from the

platforms, in each of these species, the larger individuals were farther along

in their reproductive development. If size was included in the analysis,

fewer significant differences occur. These results suggested that size, and

6-183
Table 6.78. Results of stage of reproductive development determined

through visual inspection.

S. atlantidis **Z (a)

P. sirrtilis ** (..)

All shrimp **

MAI-686

T. similis (a.) P. aztecus P. gibbesu (')

All shrimp (a..)

C. stmilis (a)

Portimid crabs (a)

MU-A85

T. simtlis

P. aztecus

All shrimp P. spinicarpus Portunid crabs

HI-A389

P. spinicarpus Portunid crabs

M. quinquesptnosa Hermit crabs

A. ale.xartdria

61S4

S. atlan.tidis (...)

aResults are for females only. Significant differences between stage and proximity to the

platform are indicated by asterisks (1, (MANCOVAt P = 0.05 - 0.01; P 0.01 - 0.001; P

= 0.00 1 - 0.000 1. Species marked by dark circles have a significant relationship between

stage of reproductive development and proximity to the platform when size was added to

the model as a covariate. Level of significance is the same as asterisks.

Stage of Reproductive Stage of Reproductive

Development Is Higher at Development is Higher at

the Far Stationa the Near Stationa
Table 6.79. Results of stage of reproductive development determined

through histological analysis.

A. dup&atus, M* P. aztecu.s, r*

C. similis, F**

All starfish, M*

P. aztecus, M()

P. aztecus, M*

All stomatopods, F(.)

S. atlarLtidiS, M***, r** (.)

All shrimp, M***, Ft

MAI-686

C. simths, M

P. gibbesli, M, F

Portunid crabs, M, F

S. empusa, M, F

chydnea, M, F

A. clupUcatus, F

A. cingulatus, M, F

All stomatopods, M, F All starfish, F

All shrimp, M, F

MU-A85

sirnilis, M, F

P. aztecus, F

S. atlantidis, M, F

C. similLs, F

P. spinicaipus, M. F

S. chydaea, M, F

A. cirigulatus, M, F

A. papyraceum

Portunid crabs, M, F

All shrimp, M, F All stomatopods. M, F All starfish, M, F

HI -A3 89

A. alexandria, M, F

M. quinquespinosa, M(.)

S. edentata, M, F

P. similis, M, F

All stomatopods, M, F All starfish, M, F

6-185

T. similis, F

T. similis, M(.)

All shrimp, M(..)

C. slrnilis, M***

A. cingulatus, M(.')

M. quinquespinosa, M()

asigicant differences between stage and proximity to the platform are determined by

MANCOVA (* P 0.05 = 0.01; 1' P = 0.01 - 0.001; P 0.001 - 0.0001). Species marked with dark circles have a significant relationship between stage of reproductive development and

proximity to the platform when size was added as a covariate. Levels of significance are the

same as asterisks.

Reproductive Stage is No Difference Between the Reproductive Stage Is

Higher at the Far Stationa Near and Far Stationsa Higher at the Near Stationa
not proximity to platforms, was most important in determining the stage of

reproductive development in these species. However, the data were

obtained by selection of the largest individuals, so that statistical tests with

size may be biased.

Immunological probes active against egg protein were developed for

three species of portunid crabs, C. simiUs, P. gtbbesii, and P. spintcarpus.

The quantity of egg protein was determined with these probes for females

that were in the midst of their reproductive cycle; that is, they were not yet

in sponge. The probe provided a measure of total gamete protein present.

Comparison of gamete weight in animals ready to spawn, as measured by the

probe, to the weight of protein in egg masses collected from gravid females

yielded equivalent results, indicated that the probe satisfactorily measured

total egg protein concentrations in gonadal tissues.

Statistical analyses were possible in three cases. On Cruise 2, P.

sptnicarpus from MU-A85 and P. gibbesil at MAI-686 had a higher quantity

of gamete protein measured in individuals collected near the platform. C.

similis from MAI-686 (Cruise 4) showed the opposite pattern with higher

quantity of gonadal protein measured at the Far station. Only for P. gibbesit

was the difference statistically significant.

GSI, or gonadal somatic index, is another measure of the relationship

between the amount of egg present (dry weight) and the weight of the

individual. High values of GSI would suggest an individual with a high

gonadal weight compared to its own body weight. For the three cases, both

P. spinicarpus at MU-A85 and P. gibbesit at MAI-686 had higher GSI at the

Near stations, but neither trend was significant. In one case, P. gibbesil,

these results agreed with the results obtained from analysis of gravid

females. Egg sacs were also heavier at the Near station. The opposite was

true for C. similis at MAJ-686 where the higher GSI was recorded at the Far

station, but the GSI for gravid females was higher at Near stations.

Besides distance effects on GSI, some platform-specific effects also

occurred. The results of GSI analysis for P. sptnicarpus from the Near

stations at both MU-A85 and HI-A389 collected on Cruise 2 are summarized

in Figure 6.57. HI-A389 bad a much higher GSI as compared to MU-A85.

These results agree with the results obtained from visual inspection and

suggest once again that platform-specific characteristics in the physical or
Figure 6.57. Average GSI of P. sptntcarpus at MU'-A85 and HI-A389.
chemical environment effect the reproductive development of resident

organisms.

The results obtained from the three types of reproductive analyses;

visual, histological, and quantitative using the immunological probe; are

compared in Table 6.80. No case occurred where the three analyses

provided opposing conclusions. Numerous cases occurred where one

analysis provided a significant result and another did not. Thus, visual and

histological stage and gamete quantity were different variables. Stage

measures advancement in the reproductive cycle, whereas gamete quantity

measures true fecundity. The strength of the immunological analysis was

that it provides a quantitative measure of fecundity which histological

analysis and visual inspection fail to provide. In all three cases however,

where sampling was adequate, few significant differences were observed.

6.6.7 Histopathology and Stage of Reproductive Development

One of the advantages of determining the stage of reproductive

development by histological analysis is that it allows for comparisons to be

made between the stage of reproductive development and levels of

parasitism and disease in the same individuals (see Section 5.7 for

histological results and Section 5.6.6 for reproductive development data).

Prevalence of parasitism and disease was used in statistical models to

determine whether the presence of parasites had an effect on reproductive

development. Prevalence had a significant relationship with stage of

reproductive development only at MU-A85 (Table 6.81). At this platform,

scallops, male and female starfish, and all shrimp had lower stages of

reproductive development with higher prevalences of infection.

Reproductive stage in crabs was unaffected by parasitism or disease.

Although prevalence was related in a few cases to stage of reproductive

development, intensity of the individual parasites or pathologies was never

significantly related to the stage of reproductive development in any of the

species at any platform. The measure of total parasitism was used in models

to determine whether overall health was related to the stage of reproductive

development. In only two cases, female P. aztecus at MAI-686 (P = 0.0329)

and female A. ctrtgulatus at MU-A85 (P 0.0057), was total parasitism
Table 6.80. Comparisons of results of reproductive effort studies

comparing visual inspection, histological analysis and

immunological probe.

Species

C. sirnilis

P. gibbesti

P. sptnicarpus

Platform

MAI-686 Higher Far Station No Difference between Near

and Far Station

MAI-686 Higher Near Station No Difference between Near

and Far Station

MU-A85 No Difference between Near No Difference between Near

and Far Station and Far Station

Visual Inspection Histological Analysis

Stage of Reproductive Development

6-189

Species Platform

Immunological Probe

Gonadal Protein Gonadal Somatic Index

(GSI)

C. stmiUs MAI-686 No Difference between Near

and Far Station

No Difference between Near

and Far Station

P. gibbesil MAI-686 Higher Near Station No Difference between Near

and Far Station

P. spinicaJpus MU-A85 Higher Near Station No Difference between Near

and Far Station
Table 6.81. Results of histopathological analysis of tissues to determine whether a relationship exists between prevalence of parasitism

and stage of reproductive development.

MAI-686

T. similis, M, F

P. aztecus, M, F

A. duplicatus, M, F

C. simiUs, M, F

P. gibbesi M, F

Portunid crabs, M, F

All starfish, M, F

All shrimp, M, F

MU-A85

A. cinu1atus, M**, F* T. similis, M, F A. papyraceum** P. aztecus, M, F All starfish, M* S. atlarttidLs, M, F All shrimp, M*, F C. simWs, M, F

P. spinicw-pus, M, F Portunid crabs, M, F

All starfish, F

HI-A389

A. alecandria, M, F

Hermit crabs, M, F

A. cin.giilattic, M, F

S. atlantidis, M, F

P. similis, M, F

M. quinquespinosa, M, F All starfish, M, F

All shrimp, M, F

aMterisks indicate the level of significance (MANCOVA, * P = 0.05 - 0.01; P 0.01 -

0.001; W P 0.001 - 0.0001). M = males; F females.

related to stage of reproductive development. In each of these cases, more

heavily infected individuals had lower stages of reproductive development.

6.7 Megafauna - Demersal Fish

While gross fish pathology is a potential response indicator of

environmental status that is easy and economical to measure, it will not

allow the identification of important contaminant-associated pathological

6-190

Prevalence of Parasitism is Prevalence of Parasitism is

Significantly Related to Stage Not Significantly Related to

of Reproductive Developmenta Stage of Reproductive

Developmenta
abnormalities. Histopathological examination of select tissues is widely

recognized as a reliable method for assessing the adverse effects of exposure

to anthropogenic contaminants in marine fishes. For example, certain

pathological conditions in the liver of wild fishes morphologically resemble

lesions induced in fishes by experimental exposure to a variety of toxicants,

including carcinogens. Furthermore, some of these lesions have also been

shown to be positively associated with exposure to xenobiotic chemical

contaminants in field studies. Summary of histopathological observations for

demersal fish is provided in Section 5.7.2.

Macrophage aggregates (MAs), particularly those in the spleen, also

appear to be a good histopathological indicator of contaminant exposure.

MAs are focal accumulations of macrophages found in the spleen, liver and

kidney of fishes that contain the pigments hemosiderin, ceroid/lipofuscin,

and melanin (Wolke 1992). Occurrence of MAs may vary depending on the

size, nutritional status, or health of a particular fish species (Agius 1980;

Wolke et al. 1985). In addition, the number and size of MAs increase with

age in some species (Brown and George 1985; Blazer et al. 1987).

Suggested functions for these aggregates include the centralization of

foreign material and cellular debris for destruction, detoxification or reuse.

Changes in splenic MA parameters (e.g., number, size) in relation to

environmental contamination have been noted by several investigators

(Kranz and Peters 1984; Wolke et al. 1985; Spazier et aT. 1992). Hence, it

has been suggested that these structures may be sensitive, non-specific

indicators of stress. Preliminary studies from the Environmental Monitoring

and Assessment Program in the Gulf of Mexico demonstrated an increase in

splenic MA number and percent of tissue replaced in most species from

contaminated sites. Some species were good indicators of elevated tissue

contaminants while others were good indicators of sediment contaminants

(Blazer et al. 1994).

Analysis of the demersal fish histopathology data indicates four main

points: (1) fish from site MAT-686 bad a statistically greater number of MAs

per mm2 during all cruises except the third cruise, (2) MAs from fish at

site MAJ-686 were generally smaller than those from the other two sites (3)

when analyzed for Near/Far station comparisons, no significant difference

was noted among samples, and (4) the MA size and percent area occupied by
MAs at site HI-A389 were significantly greater than the MAs at either site

MAI-686 or MU-A85.

Histopathological evaluation of tissues samples from study site fish

revealed no lesions attributable to contaminant exposure. Parasitic

infections, predominantly microsporidians and nematodes, were cormnonly

found in fishes at all sites and stations. All pathological findings from these

fishes (i.e., granulomas and inflammatory foci) were associated with parasitic

infections.

The reason fish from MAI-686 had a greater number of MAs per mm2

during three of the four cruises and that MAs in those fish were generally

smaller was probably due to species differences. Syactum guntert was the

only species collected at site MAI-686, whereas T. ventralis was the only

species collected at the other two sites. Since no other data on MAs from S.

gunteri are available for comparison, no difference between Near and Far

stations at site MAI-686 was seen. No apparent correlations were noted

with contaminant data and the MA parameters at site MAI-686. Little can be

said regarding these findings. The lack of Near/Far station differences may

be related to the relative proximity of these sites. The Far station is only

3000-rn from the platform (near site); while this may be sufficient

separation when looking at sediment contaminants, the fish may range over

an area greater than the station separation, thus a single population is

sampled.

Point four above should be viewed as two separate observations, a

statistical difference in MA size and percent area occupied by MAs between

sites HI-A389 and MAJ-686 and between sites HI-A389 and MU-A85.

Examination of the data suggests that the HI-A389 and MAI-686 site

differences reflect the cross-species comparison discussed earlier and

therefore cannot be compared. However, the differences between the

samplings at sites HI-A389 and MU-A85 are statistically significant site

differences within a single species (T. ventraUs). These differences were

also consistent with observations from three cruises. No comparisons were

possible between these two sites during Cruise 1 because no flatfish were

collected from HI-A389. These observations did not correlate with

hydrocarbon or metal sediment contaminant data. Therefore, the

macrophage aggregate data did not indicate any obvious contaminant effects

relative to the study sites and are presently unexplained.

6-192
6.8 Detoxification

Historically, the bioavailabiity of contaminants has been assessed by

measuring contaminant levels sequestered in biological tissues utilizing

standardized analytical procedures. However, it is difficult to correlate tissue

levels of complex chemical mixtures with biological responses.

Consequently, a number of in vitro and in vtvo assays have been developed as

biomarkers of exposure of marine fish and invertebrates to polycyclic and

halogenated aromatic hydrocarbons (PARs and HAHs; Ankley et al. 1991;

Coffier and Varanasi 1991; Collier et al. 1992, 1995; Krahn et al. 1987;

Payne et al. 1987; Stegeman et al. 1981; 1987; Tiffitt et al. 1991a; Van Veld

et al. 1990). In vitro and in vivo bioassays for PAll mixtures are highly

sensitive to these compounds and observed responses are due to the

combined or integrated effects of all the individual compounds in these

mixtures. Hydrocarbon exposure in fish has been correlated with numerous

physiological responses including reproductive impairment (Thomas 1990;

Hose et al. 1989); histologically identifiable diseases, including liver

neoplasms (Malins et al. 1984; Murchelano and Wolke 1985; Baumann et al.

1982; Collier et aT. 1992); and immune dysfunction (Weeks et al. 1992).

Studies have shown that certain PAHs, such as benzo[a]pyrene (BaP), are

carcinogenic in some fish species (Hendricks et al. 1985; Schultz and

Schultz 1982; Metcalfe et al. 1988).

Cytochrome P450 enzymes play a major role in the oxidative

metabolism of xenobiotics and pollutants. P450 enzymes catalyze the

oxidative metabolism of numerous hazardous substances including BaP and

other PAR as well as balogenated aromatic hydrocarbons. The cytochrome

P450 system also metabolizes numerous endogenous substances including

steroids, fat-soluble vitamins, fatty acids, and other natural products.

Cytochrome P450 enzymes are found in every biological kingdom and

virtually all cell types. Cytochrome P450s are a gene super family consisting

of over 200 genes in more than 30 gene families (Nelson et al. 1993). The

ancestral P450 gene is probably more than two billion years old (Nebert and

Gonzalez, 1987; Nebert et al. 1989). The earliest functions of P450 were

probably related to the assimilation of energy-rich organic substrates and

metabolism of steroids and fatty aids. A proliferation of P450 genes

occurred during the past 800 million years that most likely resulted from

6-193
the divergence of plants and animals (Nebert and Gonzalez 1987; Nebert et

al. 1989). Additionally, ancient combustion events (i.e., forest fires) and

diagenesis are linked to the development of P450s capable of metabolizing

combustion products (i.e., PAR). Induction of mammalian CYP1A1

(P4501A1) genes is dependent on initial binding of the chemical

contaminants to a cytosolic protein known as the Ah receptor. These

compounds induce formation of the transformer receptor complex which

translocates into the nucleus and binds to specific regions of genomic DNA

thus transactivating genes. Induction of CYP1A1 gene expression results In

increased CYP1A1 mRNA levels followed by increased CYP1AJ protein and

dependent enzyme activities.

Studies have shown that fish P450 proteins induced by PAR and

related compounds can be classified in the CYP1A subfamily and have

properties similar to the mammalian CYP1A1 subfamily. The presence of

cytosolic and nuclear Ah receptors has been documented in several fish

species suggesting that CYP1A induction in teleost fish is also controlled by

the Ah receptor and consequently the induction of CYP 1A proteins is

preceded by an increase in CYP1A mRNA (Hahn et al. 1994; Wilett et al.

1995). Induction can be assessed by measuring CYP-associated enzyme

activities (i.e., AHH and EROD), CYP1A protein levels, or CYP1A mRNA levels

(Figure 6.58). CYP1A induction can be used to indicate environmental

contamination by pollutants. In many studies it has been shown that there is

a strong correlation between levels of contamination and the enhancement

of CYP1A-dependent activities in various fish species. Although P4501A

induction in fish can be affected by species-specific differences,

reproductive condition, season, and temperature; CYP lA-mediated

responses are largely related to exposures to organic xenobiotics. The

specificity and sensitivity of CYP1A to potential inducers make this response

attractive as a biomarker of environmental contamination.

Invertebrates, particularly sessile mollusks, are routinely utilized as

indicators of environmental contamination by PAHs because these organisms

readily bioconcentrate these compounds from their immediate surroundings

(Geyer et al. 1982; Goldberg et al. 1978). Invertebrate CYP1A induction

responses have been used with only limited success as indicators of

contamination. Although P450 systems have been characterized in some

marine invertebrates, their P450-dependent activities are usually low to

6-194
non-detectable (Lee 1982; Livingstone 1990; James 1989; Livingstone

1991). Moreover, since CYP lA-dependent activities are not routinely

detected or induced in marine invertebrates relatively low metabolism and

increased retention of PAT-I is observed. Although proliferative diseases have

been noted. in mollusks from contaminated sites, the involvement of

procarcinogen activation in invertebrate diseases has not been

demonstrated. Several studies have reported that in some invertebrate

groups the rate of metabolism of BaP to mutagenic and carcinogenic

oxidized metabolites is minimal (Stegeman 1985; Livingstone et al. 1989).

In mammals and fish the induction of cytochrome CYP1A1(A) is regulated by

the Ah receptor. However, studies using photoaffinity labeling techniques

failed to detect the cytosolic Ah receptor in several invertebrate species

(Hahn et al. 1992; 1994). This suggests that unlike most vertebrates,

invertebrates lack a functional Ah receptor. This is consistent with the

failure to observe significant PAH-induced CYP lA-dependent monooxygenase

activity.

CYP1A induction responses were evaluated in both fish and

invertebrate species in this study using several in vitro and in vivo assays

(Figure 6.58). Detoxification data are summarized and described in detail in

Section 4.8. AHH activity was measured for invertebrates collected on

Cruise 1 and fish collected on Cruises 1 and 2. EROD activity and biiary

PAH metabolite concentrations (i.e., naphthalene, phenanthrene, and BaP)

were measured for all fish species collected on Cruises 1, 2, 3, and 4.

CYP1A mRNA levels were determined for selected fish species collected on

Cruises 2, 3, and 4. The activity of invertebrate extracts as inducers of

CYP1A1 was determined utilizing rat hepatoma H4IIE cells.

6.8.1 AHH Activity in Invertebrates

AHH activity was measured in a number of invertebrate species

collected by trawling and boxcoring on Cruise 1. AHH activity was low to

non-detectable in the following invertebrates; Trachypenaeus simitis,

CalIinectes similis, Penaeus c&ztecus, Amustum pap yraceum, a species of

spider crab, an unidentified welk, and mixed infauna from boxcorers. No

significant differences in invertebrate A}LH activity for near/far station

comparisons were observed.

6-195
FIgure 6.58. Blomarkers used In GOOMEX. INVERTEBRATES in vivoDigestive Tissue in v

CYP1A PAH AHH CYP

Induction Metabolites Induc

(EROD, AHH, mRNA) (Naphthalene, Phenanthrene, BaP) (Rat Hep

H4IIE 

Bioas

FISH in vivo Liver Bile
Although the presence of monooxygenase enzymes has been confirmed

in a number of invertebrate species (Lee 1982; James 1989; Livingstone

1991), numerous studies were unable to demonstrate CYP1A induction after

exposure to hydrocarbons (Lee et al. 1972; Payne 1977; James and Little

1984; Kurelec et aL 1986). Other studies reported minimal induction of

AHH activity in invertebrates exposed to hydrocarbons (Anderson 1978;

Livingstone et al. 1985; Schienk and Buhier 1988; den Besten et al. 1990;

1993; Livingstone 1990; 1991). Some forms of P450 have been partially

purified from crustaceans (James and Shiverick 1984), and an

immunoreactive protein has been detected in chiton and mussel tissue by

CYP1A fish antibody (Schienk and Bubler 1989a,b; Parte et al. 1995);

however, their relationship to vertebrate P4501A(1) is unclear. Although, at

present there is limited potential for using P4501A induction responses in

invertebrates to assess hydrocarbon exposure, continuing studies may reveal

some diagnostic inducible responses that could be useful in future

monitoring programs. However, based on the minimal induction of CYP1Adependent responses in Cruise 1 samples, AHH measurements in

invertebrates were discontinued for subsequent cruises.

6.8.2 EROD and AHH Activity in Fish

Of the 25 species of fish collected during the GOOMEX project, 16

were collected at both Near and Far stations for at least one platform. No

consistent difference between the winter and summer cruises were

observed and consequently, the data from all four cruises were pooled. Two

factors that can impact hydrocarbon metabolism in fish are temperature and

reproductive condition. Studies have reported that PAH induction of CYP1A

is suppressed in cold acclimated animals (Spies et al. 1982; Blanek et at.

1989; kloepper-Sams and Stegeman 1992a,b). A strong sex-dependent

difference in P450 and CYP1A content in the livers of spawning fish has also

been observed (Stegeman et at. 1982; Gray et at. 1991). CYP1A mRNA and

protein levels are suppressed in maturing fish and in those treated with

estradiol (Gray et at 1991). For this study, fish were collected by bottom

trawling and bottom water temperatures were fairly consistent between

summer and winter months. Mean bottom water temperatures varied

approximately 1 °C, 2 °C, and 6 °C between summer and winter cruises for

6-197
HI-A389, MU-A85, and MAI-686 respectively. Due to sampling limitations,

fish were not separated by sex; however, virtually all specimens were

reproductively immature. Consequently, it is unlikely that temperature and

reproductive condition significantly contributed to data variability.

A range of EROD activities were determined in fish. The highest

EROD activities were measured in Lagodon rhomboldes (pin fish) and

Caut ot at it us intermedius (tile fish). Lower activities were measured in

Cent ropristis philadelphica (rock sea bass) and Ancyctopsetta dilecta (3-

eyed flounder). Species-dependent differences in catalytic enzyme activities

have been observed in other studies (Collier et al. 1995; Davies et al. 1984).

Both hepatic AHH and EROD activities were measured in all fish species

collected on Cruises 1 and 2. The assay for AHH activity was discontinued

for fish captured on subsequent cruises because a good correlation between

the two assays was established for most species. The assay for EROD activity

uses a less toxic substrate than BaP which is used for determining AHH

activity. However, EROD and AHH activities were not closely correlated for

Lagodon rhomboides and Anus fells (captured only at GA-288 and not

presented). This has been observed in other studies (Foureman et aT. 1983;

James and Bend 1980; Stegeman et al. 1981). In both species, EROD

activity was significantly higher than the corresponding AHH activity. Other

studies have shown a good concordance between bepatic AHH and EROD

activity in fish (Collier et al. 1992; 1995). The two assays measure the

activity of the same enzyme (i.e., CYP1A) and fish that do not exhibit a for

the coordinated induction of AHH and EROD activities may express an

altered CYP1A protein compared to other fish species.

A significant PAR contaminant gradient was detected at IIJ-A389 and

MU-A85; however, no significant differences in catalytic enzyine activities

were observed for fish species captured at these sites. Moreover, EROD and

AHH activities were generally low and these activities may represent basal or

constitutive expression. Several potential factors may have contributed to

the lack of induction of EROD and AHH activities observed in fish. Although

a sediment PAH gradient was detected for two platforms, mean sediment

PAH concentrations were relatively low (for details see Section 5.3). The

mean sediment PAH concentration for the Near and Far stations at MUA85 was 280 ng/g (maximum = 2304 ng/g) and 29 (maximum = 58 ng/g),

respectively and for HI-A389 was 361 ng/g (maximum = 1103 ng/g) and 35

6-198
(maximum 84 n/g) for Near and Far stations, respectively. Additionally,

sediment PAH were highly degraded and contained low to non-detectable

levels of 4-ring PAH, which are strong inducers of P450 1A. Another

potential contributing factor to the lack of induction response may have

been patterns of fish movement which do not correspond to the highly

localized nature of the contaminant field. The populations of fish species

examined may be highly mobile and do not permanently reside at the

platform. Although captured near the platforms, the fish may have fed

elsewhere thereby lacking exposure to the potentially toxic environments.

Other studies have used CYP1A induction responses to evaluate

hydrocarbon contamination associated with offshore oil and gas drilling in

the North Sea and in a region known to have natural hydrocarbon seepage

off the coast of California (Spies et al. 1982; Davies et al. 1984; Renton and

Addison 1992; Goksoyr et al. 1992). Two of three fish species collected

from near stations exhibited significantly higher hepatic AHH activities than

those captured up to 16 km from platforms (Beryl Field) in the northern

area of the North Sea (Davies et aL 1984). The significant differences in

A}IH activity correlated with a dramatic PAR gradient at the North Sea sites

where total sediment PAB concentrations ranged from 997 ppb at 16 km to

> 429,000 ppb at 400 m from the platform (Davies et aL 1984). In another

North Sea study, the Bremerbaven Workshop, no significant differences in

EROD activity, CYP1A protein levels, and CYP1A mRNA levels were observed

in Limanda limanda captured at reference and abandoned drilling sites off

the Netherlands (Renton and Addison 1992; Goksoyr et al. 1992). However,

no significant sediment PAR gradient was observed at this site either. Mean

sediment PAH concentrations (PAH=naphthalene, Cl to C3 naphthalenes,

anthracene, phenanthrene, C 1 phenanthrene, fluoranthene, pyrene,

benz[ajanthracene, chrysenes, triphenylene, benzofluorantbenes,

benzolelpyrene, benzo[a]pyrene, and perylene) at a site collected at the

center of an abandoned exploratory platform and -5000 m away were 305-

ppb and 338-ppb dry weight, respectively (Stebbing et al. 1992).

Additionally, AHH activity was significantly higher in two sand dab species

(Ctharicthys sordidus and C. stigmaeus) collected near natural petroleum

seeps near Santa Barbara, California than in fish collected from a relatively

uncontaminated site in Monterey Bay, California (Spies et al. 1982). These

data suggest that significant exposure to 4-ring PARs results in induction

6-199
of EROD or AHH activity in fish, and the results obtained in the present

study are consistent with the low levels of hydrocarbon contaminants at the

study sites.

6.8.3. Bifiary PAR Metabolites in Fish

PAH exposure in fish was also been assessed by measuring bffiary PAR

metabolite levels. Hepatic PAH metabolites are concentrated in bile for

subsequent elimination (Varanasi et al. 1989), and levels of fluorescent

aromatic metabolites have been correlated with PAIl exposure in fish in both

laboratory and field studies (Coffier and Varanasi 1991; Krahn et aL 1992;

McDonald et al. 1991; 1992). Although no significant near/fax station

differences were observed in fish captured at the study sites, significant

differences among species were observed (see Section 5.9.2 for details).

The concentrations of naphthalene and phenanthrene equivalent

metabolites were consistently higher in the bile of Lagodon rhomboides.

Levels of BaP equivalent metabolites were typically low for all species and

this correlates with the low to non-detectable levels of 4-ring PAHs

measured in sediments and tissues.

Estimating PAH exposure in fish by measuring the production of bffiary

PAR metabolites is not a routine assay; however, several studies have shown

that the technique is sensitive (Willett et aL 1995; McDonald et al. 1992;

1995; Krahn et ai. 1992, 1986a,b; Table 6.82). In laboratory dose- and timecourse experiments with BaP, Fundulus sp. were used as a model to evaluate

the relative sensitivities of several biomarkers of exposure. Biliary

metabolite levels were one of the more sensitive indicators (Wfflett et aT.

1995). Additionally, this technique can be used to estimate exposure to

lower molecular weight PAIls such as di- and tricycic (Le., naphthalenes

and phenanthrenes) compounds which are not potent CYP1A1(I) inducers.

Field studies have also shown that the formation of biliary PAR metabolites

can be used to estimate PAR exposure in fish from both combustion and

petroleum hydrocarbon sources (Krahn et al. 1986a,b; 1992; McDonald et aT.

1991; 1992; 1995).

During the course of this study evidence of sample degradation was

observed in approximately 40 % of the bile samples. The bile of fish

collected at the deeper sites, HI-A389 and MU-A85, was particularly prone

6-200
Table 6.82. Summary of literature values for biliary metaboilte concentrations versus sediment PAH con

Eagle Harbor Duwamish Waterway din ton Inner Everett Harbor Outer Everett Harbor Richmond Beach West Point Carkeek President Point Edmonds Useless Bay Black River Od Woman Creek Parophrys uetulus Parophrys uetulus Parophrys uetu!us Parophnjs vetulus Parophrys uetulus Pawphnjs vetulus Parophrys vetulus Parophrys vetulus Parophnjs vetulus Parophrys vetulus Parophrys vetulus brown bullheads carp brown bullheads carp na -not analyzed; (1) Krahn et al. 1987: 2) Johnston and Baumann 1989; (3) McDonald et al. 1995 310000 2300 n/a 2600 73 n/a 120 13 n/a 5600 <14 n/a 2000 <5 n/a 290 290 n/a 34000 2200 n/a 220 22 n/a 1100 41 n/a 650 34 n/a 130 5 n/a 180000 800 n/a 180000 800 n/a 1170 271 n/a 1170 271 n/a 

Sediment Sediment Bile Bile 

Site Species TotPAH (ng/gl BaP (ng/g) naphthalene phenanthren

Antarctica Palmer Station Bahia Paralso wreck Nototherata coriiceps neglecta 297-668 <5 69000±56000 ng/g 9400±9900 ng

Palmer Station 427-14491 <5 77000±46000 ng/g 11000±8300 n

remote n/a n/a 33000±14000 ng/g 5100±2000 ng

McMurdo Station Winter Quarters Bay Trematomus bernacthll 2848 358 140000±51000 25000±1300

Cape Armitage 255 24 92000±36000 13000±5100 

remote 167 12 51000±27000 7200±3700 

GOOMEX MAI- 686 MU-A85 Hl-A389 Puget Sound Lake Erie n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a
to degradation. The results indicate that bile degrades in fish that are dead

or moribund, and consequently is not useful for determining PAH metabolite

levels. Trawl recovery time and depth cause stress in fish and these factors

may contribute to bile degradation. All fish were alive at the time of

dissection. Results obtained from degraded bile samples were not included

in data analyses.

6.8.4. Rat Hepatoma H4IIE Bioassays

The in vitro rat hepatoma H4IIE cell bioassay was developed to

determine the biological potency of extracts from a variety of environmental

and industrial samples that contain PAH and related chemicals, which

induce CYP lA-dependent activity (Bradlaw and Casterline 1979; Tillitt et al.

199 la,b; 1993; Trotter et al. 1982; Zacharewski et al. 1989). Since these

compounds elicit similar toxic and biochemical responses via the Ah

receptor signal transduction pathway, (Safe 1990) various Ah receptormediated responses, including CYP1A induction, have been used to

determine bioassay-derived toxic equivalents (TEQs) for mixtures of

chemicals (Ankley et al. 1991; 1992; Bradlaw and CasterJine 1979: Krishnan

and Safe 1993; Tillitt et a1. 199 la,b; Trotter et al. 1982). This approach

detects all bioactive components in a mixture and gives an integrated

response for these compounds. Bioassays are also particularly useful for

invertebrates. There is no conclusive evidence showing that the

invertebrate CYP1A system is inducible with exposure to PAH, and thus, it is

difficult to determine any direct induction responses (Lee et aL 1972; Payne

1977; James and Little 1984; Kurelec et al. 1986). However, the activity of

PAH contained in extracts from invertebrates can be readily assessed by

determining their activities in in vitro bioassays.

For Cruises 2, 3, and 4, rat hepatoma H4IIE cells were treated with

invertebrate extracts to determine the induction potential of these extracts.

Seven species of invertebrates were extracted for use in these assays. The

highest induction responses of TEQs were derived from scallop extracts,

and this is consistent with the ready bioaccumulation of contaminants in

filter-feeding mollusks. The only significant station differences were

observed for Penaeus aztecus from MAI-686. Although P. aztecus extracts

from the near station at MAJ-686 had significantly higher TEQs than

6-202
extracts from the far station, a paraflel sediment or tissue contamination

gradient was not observed. A combination of factors may be contributing to

the lack of significant near/far station differences in bioassay-derived TEQs.

Often invertebrate specimens were at a premium and thus replication was

low. Also, no significant differences were measured in tissue PAH burdens

for any of the invertebrate species collected, thus indicating that there was

not a site-dependent difference in hydrocarbon exposure.

Although no significant site-dependent differences were measured for

invertebrates that correlated with sediment contaminant concentrations,

recent studies have correlated the induction of EROD activity and TEQs in

rat hepatoma H4IIE cells with exposure to known levels of PAHs in marine

fish and invertebrate tissues (McDonald et al. 1994; 1995). The activity of

clam (Laterriula elliptica) extracts as inducers of CYP lA-dependent EROD

activities in rat hepatoma H4IIE cells was highly correlated with sediment

contaminant levels in McMurdo Sound, Antarctica (McDonald et aL 1994).

Additionaily, in laboratory experiments a good correlation was established

between hepatic PAH (i.e., BaP, 3-ring PAll, and > 3-ring PAll) levels and

TEQ values of H4IIE cells treated with hepatic extracts of fish dosed with

BaP and diesel fuel (McDonald et al. 1995)

6.8.5 CYP1A m}NA Levels

Exposure to PAHs and related compounds results in increased

CYP1A(1) gene expression. The increased enzyme activities are also

accompanied by increased levels of CYP1A mRNA in target tissues (Whitlock

1986; Safe 1990). Accordingly, increased levels of this transcript can also

be used as a sensitive and specific assay for exposure of marine organisms to

this class of toxicants (Haasch et al. 1989; Hahn and Stegeman 1994;

Courtenay et al. 1993). Haasch and coworkers (1992) detected a three-fold

induction of CYP1A mRNA in killifish sampled at a contaminated site

compared to those taken from a clean site. The cytochrome P450 cDNA

probe used in these studies was isolated and sequenced from the liver of 3-

methyicholanthrene-treated rainbow trout (Salmo gardneri Heilmann et al.

1988). Likewise, in this study, total RNA was isolated from homogenized

liver samples by subcellular fractionation and extraction by a modification of

the method of Chomczynski and Sacchi (1987). CYP1A mRNA levels were

6-203
determined by Northern blot analysis using a eDNA pfP1450-3' probe

(courtesy of Dr. John Lech). CYP1A mRNA levels were standardized relative

to f3-tubulin mRNA in the same sample. No significant differences were

observed in CYP1A mRNA gel electrophorectic transcripts for any of the fish

species sampled. This data is consistent with the other biomarkers

measured for GOOMEX and indicates that there was no significant

differences in hydrocarbon exposure for fish captured at MAI-686, MU-A85,

and HI-A389.

6.8.6 Dosing Experiments

High molecular weight PAHs can act as Ah receptor agonists and PAHs

bind to the intracellular Ah receptor and form a ligand-induced nuclear

transcription factor which binds to specific regions of genomic DNA,

thereby initiating transcription (Figure 6.59). The Ah receptor is a soluble

protein which is necessary for the proper development of the liver and

immune system. The Ah receptor has been previously identified in the

cytosolic fraction of three fish hepatoma cell lines (Lorenzin and Okey 1990;

Swanson and Pewdew 1991; HaIm et al. 1993). The photoafflnity-labeled Ah

receptor was also identified in the hepatic cytosol of seven species of teleost

and elasmobraneb fish (Hahn et. al. 1994). To date, there is no reported

evidence in fish of the nuclear Ah receptor which is necessary for P450 1A

mRNA transcriptionai activation. Lagodon rhomboides (pin fish) and

Synodus foetens (lizard fish) were dosed with PH] TCDD to characterize

their nuclear Ah receptor. The Ah receptor profiles for both L. rhomboides

and S. foetens showed a specifically bound Mi receptor complex which

sedimented at 54S (Figures 6.60 and 6.61). Similar Ah receptor profiles

were also found in laboratoiy experiments using kiflifish (Willett et al. 1995).

Although cartilaginous fish diverged evolutionarily 450 to 550 million years

ago (Carroll 1988), the sedimentation characteristics of the nuclear Ah

receptor in these fish were similar to the mammalian Ah receptor from

several different species, including humans.

L. rho mboides consistently expressed higher constitutive EROD

activities and higher biliary metabolite concentrations than other fish

species captured during this study, therefore dosing experiments were

conducted to investigate potential maximum induction of EROD activity in

6204
* 2,3,78-TCDD and related HAH isomers and PAH AhR/Complex CYTOPLASMrapid!AhR Complex Cytochrome P-4501 Al Induction (AHH, EROD and other monooxygenases) NUCLEUS AhR Complex Plelotropic Responses Nuclear Binding Sites (DR

Ôytochrárne_ ilL illi liii 11l.rII

P-4501A1 mRNA Induced mRNA nduced Proteins Figure 6.59. Molecular mechanism of action of TCDD and related PAHs and HA
0 0 - - - qSirit- 

15 Fraction Number Figure 6.60. Ah receptor profile in Synodusfoetens (lizard fish). 700 600- 500- 400 = 300- 200- 100 - S S SIS S S S -0- -*- [3H]TCDD [3H]TCDD+

5 10 20 25 
Figure 6.61. Ah receptor profile in Lagocion rhomboides (pin fish).
this species. L. i-homboides were collected from MAI-686 near; three

individuals were dosed i.p. with 200 j.tL of corn oil, and seven were injected

with approximately 5-mg/kg body weight of BaP in corn oil (2.5-mg/mL).

Fish were maintained for approximately 65 h in on-board flow-though sea

water tanks. Fish were dissected and the livers and bile were pooled to

determine EROD activity, CYTP1A mRNA, and BaP metabolite levels. The

dosing experiments indicate that there were significant inter-individual

differences in response to a similar BaP dose (Table 6.83).

The significant variability in catalytic enzyme activity and the

production of biliary metabolites observed for individual dosed fish is unusual

but has been observed for other species such as whiting and hardhead

catfish (Davies et al. 1984; Van der Weiden 1993; Kreamer et al. 1991; Hahn

and Stegeman 1994; and unpublished data). Davies et al. (1984) exposed

cod, saithe, and whiting to BaP and found that unlike the other two species,

whiting exhibited variable and relatively low AHH activity. In contrast, other

species of fish (i.e., Fundulus grartdis, F. simitts, and Coritceps neglecta)

dosed with BaP exhibited a more consistent pattern of induction (Wilett et

al. 1995; McDonald et al. 1995). For example, treatment of F. grandis and F.

similts, a small estuarine fish, with BaP gave a dose-response and timedependent induction of EROD activity, bifiary metabolites levels, and CYP1A

mRNA levels and exhibited minimal intra-individual differences in the

responses (Table 6.84). Two Gulf of Mexico fish species that exhibited an

inconsistent induction response to BaP are the same species that do not

exhibit coordinated AHH and EROD activities. These results suggest that

some fish species may not respond uniformly to contaminant exposure.

Table 6.83. EROD activity and BaP metabolite concentrations in L. Rhomboides dosed with benzo[a]pyrene (5 mg/kg for 65 h).

Treatment EROD (pmol/min/mg) BaP ng/g

control

5 mg/kg-A

5 mg/kg-B

5mg/kg-C

29

314

207

1010

14000

94000

380000

1500000
Table 6.84. EROD activity and BaP metabolite levels in Fundulus sp. dosed

with BaP (Wfflett et al. 1995).

Time EROD l3aP(ng/g)

(day) (pmol/mln/mgJ

Dose (mg/kg, EROD relative mRNA BaP (ng/g)

6.9 Pore Water Toxicity

ANOVA analysis of the "percent successful development" test based on

sea urchin embryological development results are summarized in Tables

6.85 and 6.86. Pore water toxicity data are summarized in Section 5.9. The

results confirm other variable distributions related to contamination in that

distance effects are unique to a platform and distance effects within

platforms differ among radii (i.e., directional). The trends observed in the

tests of overall study design are mostly a result of the samples collected at

HI-A389, the site of highest contamination. "Percent successful

development" is depressed at stations within 50 m of the platform and is

not significant at 100 m distance or greater. In the "site-by-site" analysis,

the only significant results were obtained for the HI-A389 sediments.

Highly significant statistical associations were observed between pore

water toxicity and the bulk sediment concentrations of several metals (e.g.,

Zn, Pb, H, and Ag) at the High Island site. MacDonald (1993) determined a

"probable effects level" (PEL) for zinc in whole sediments to be 300 mg/Kg.

All of the toxic High Island sites were near or exceeded this concentration

6-209

after 4 day) (pmol/min/mg) levels

0 189±28 .009±.001 707±26

1 465±31 .008±.002 29,000±5300

5 1174±114 .02±.005 110,000±5800

15 1529±208 .03±.01 140,000±5800

50 1510±95 .04±.01 530,000±180,000

0 136±4 830±140

2 1049±130 78,000±2300

4 1174±197 110,000±5800

8 1812±50 94,000±21,000

14 505±68 48,999 ±25,000
Table 6.85 Summary of the significance of interactions for the overall design and by site based on pore water toxicity tests of percent successful development of sea urchin embryos.

Interactionsa

C*D D*R P*D D

Overall no Yes Yes

MA1-686 no no NA no

MU-A85 no no NA no

HI-A389 no Yes NA

ap=p1atfoim, C=Cruise, DDistance, R=radius; Yes=significant, pO.O 1; no=not

significant, pO.Ol; ---=not testable due to higher interactions.

Table 6.86 Summary of porewater toxicity testing results.a

D % Devel" .95 CL % Devel

D % Devel .95 CL % Devel

HI-A389 79.2 70.2-86.9

MAI-686 86.7 82.4-90.5

MU-A85 89.7 85.8-93.1

*%Develop - percent development based on sea urchin

embryo bioassays, CL- confidence level a P=platform, C=Cruise, D=Distance, R=radlus; Yessignificant, pO.O1; no=not significant, p0.01; ---=not

testable due to higher interactions.

(Figure 6.62). Other meta:ls which appear to be elevated at sites exhibiting

toxicity were lead (Figure 6.62), cadmium and barium (Figure 6.63). The

PELS for lead (160 mg/Kg) and for cadmium (7.5 mg/Kg) are also exceeded

at some sites, and the PEL of silver (2.5 mg/Kg) was exceeded at one site

(2B). However, since the PEL of zinc is far exceeded at all of the sites where

the PEL of other elements are exceeded, it is possible that the toxicity of

the High Island sediments is largely controlled by zinc alone or in

combination with other metals. Hydrocarbon concentrations in whole

6-2 10

50m 76.1 62.6-87.3

lOOm 85.8 77.9-92.2

200 m 88.4 82.5-83.3

500 m 88.3 82.4-93.1

3000 m 87.5 820-92.1
sediment do not appear to be the major source of toxicity. Concentrations

of total PAH, low molecular weight PAH, and high molecular weight PAH in

whole sediments do not approach their respective PELs (Figure 6.64;

MacDonald 1993).
A

Platform

O None

U Devel.

A Devel.

& Fert.

p=0-01

p=o.01

p=O.05

Feet 0 500 1000 - - I

Meters 0 100 200 300 400

203

0

7,50 456

10,542 LU 0205

295

1 ,156 . [12080154

0/0919/112 624

662 253 105

CONTROLS (ppm)

D

5A 90

5B 92

5C 82

5D 91

5E 91

0114

A

0131

HI-A389

Zinc (ppm)

110 [1 B

1020 C

B

Platform

None

DeveL

A DeveL

& Fert.

p0.Ol

p0.01

p=o.05

E°

Feet 0 500 1000

I- - I1 Meters 0 100 200 300 400

587 80 634J A1060

152 cD40

036

130 / 21 '69

76 27 38

45

0

A

028

H I-A389

Lead (ppm)

21 U

B

21 0

CONTROLS (ppm) 023

D

5A 18

5B 18

5C 15

5D 18

5E 19

Figure 6.62. Whole sediment A: zinc; and B: lead concentrations

and pore water toxicity at HI-A389. (Devel.=standard

sea urchin developmental assay; Fert.=standard sea urchin embryo fertilization assay).

6-2 12
A

Ptatforrn

None

Devel.

A Devel.

& Fert.

p=o.O1

p=O.O1

p=O.05

Feet 0

Meters 0-

0.29 0

00.14

358 1.17

H l-A389

Cadmium

A (ppm)

0.100 B

15

0

210 37 015 250J a A35

62. i"EJ22

010

HI-A389

Barium

A (ppt)

06

6-213

E°°21

-

5.86.

3.95 / 028

2.64 0.92

A 0.51

U0.35

'2.89

0.22

00.08

D

0.100 C

CONTROLS (ppm)

5A 0.07

5B 0.08

5C 0.10

5D 0.09

5E 0.10

500

100 200

1000 -300

I 400

E3 04

20C

CONTROLS (ppf)

5A 1 D 5B 1

Feet 0 500 1000 5C 1 - - I 5D 1 Meters 0 100 200 300 400 5E 2

Figure 6.63. Whole sediment A: cadmium; and B: barium

concentrations and pore water toxicity at HI-A389. (DeveL=standard sea urchin developmental assay; Fert.=standard sea urchin embryo fertilization assay).

B

PIatfom

None

Devel. p=0.01

A Devel. p0.01

& Fert. p=0.05
41U

382 liO 511.j A 171

370 \D 55

036

741/48 124 Li 0

66 756 50 220C

Figure 6.64. Whole sediment total PAH concentrations and pore water toxicity at HI-A389. (Devel.standard sea urchin

developmental assay; Fert.=standard sea urchin embryo

fertilization assay).

6-214

E° LI 23

D

CONTROLS (ppb)

5A

5B

20

29

Feet 0 500 1000 - - 50 20

I 5D 26

Meters 0 100 200 300 400 5E 26

Platform HI-A389

J None

p=O.O1

Sediment

A Devel. P=O-01 A PAH (ppb)

& Fert. p=0O5 026
7.0 SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

A number of variables have been evaluated and judged more or less

useful as indicators of perturbations associated with the presence of offshore

platforms on the OCS. While many significant trends were observed, those

related to chronic contaminant exposure are of primary interest. This

section sunirnarizes some of the more important conclusions from the many

work elements, provides an integrated cross-work element interpretation of

study results, and outlines a series of recommendations for the structure

and content of future studies.

7.1 Summary of Major Programmatic Results

The following section provides a brief synopsis of the most significant

findings of the GOOMEX Phase I program on a work element-by-work

element basis. The reader is also referred to items in bold-faced type in

"Section 6.0 Discussion" that highlight programmatic findings. The

"Executive Summary" also provides a synopsis of the program's major

conclusions.

7.1.1 Summary of the Abiotic Setting

At the three sites studied, the presence of a platform or platform

group had little effect on ambient water properties. However, summer

bypoxic events and regeneration of nutrients in bottom waters were

observed close to the platform at two of the sites. Water depth and time of

year exerted the greatest effects on water column physicochemical

properties.

Alteration of the benthic environment adjacent to offshore platforms

was the result of the presence of the structure, materials discharged from

the platform, and the oceanographic setting. Sediments close to platforms

were highly enriched in sand-sized materials derived primarily from

discharged cuttings. Hydrocarbon and trace metal (silver, barium, cadmium,

mercury, lead, and zinc) contaminants were associated with these coarse

grain sediments. Compared to coastal sediments, hydrocarbon

concentrations at platforms were low. The observed PAH concentrations

were below levels known to induce biological responses. At a few locations

close to one platform, a few trace metals occurred at concentrations in

7 1
excess of levels known to induce biological effects. It should be noted that

these metals concentrations are bulk values and it is presently unclear what

fraction of the metals are actually bioavailable. In deep water (> 80 m),

sediment trace metal contaminants were stable for periods of years. A few

metals (lead, cadmium) exhibited evidence of long-term accumulation in

sediments from sources other than discharges during drilling. Significant

perturbations of the benthos adjacent to platforms were generally restricted

to within 100's of meters of the platform. No enhanced bioaccumulation of

contaminants in fish or invertebrates was detected near platforms.

To adequately support an informed interpretation of the observed

biological patterns the abiotic characteristics of the benthic setting must be

adequately described. As noted, contaminants near platforms acted as a

suite of materials and included hydrocarbons, metals, and sand. As a

consequence of the disposal of drill muds and cuttings, a close association

between contaminants and sand-size particles was a general feature at the

three sites studied. The common origins of these materials caused the

unusual covariance of contaminants and coarse grain-sized material. In most

other environmental settings, contaminants are associated with fine grainsized particles. This unusual association provided a framework for

disentangling the multiple effects of toxin exposure, organic enrichment,

and grain size variations. The association amongst the suite of contaminants

was modified over time by redistribution, transportation, dilution,

remineralization, and remobilization processes.

The areal extent of contamination is dependent on many factors

including discharge history (Le., timing), amount and composition of the

discharge, disposal technique, and oceanographic setting. The processes

could not be resolved by the present study design. The contaminant field is

heterogeneous, directionally oriented, and often exhibits abrupt and steep

gradients that are not adequately described by a logarithmically decreasing

model. Distance was not an adequate surrogate for exposure and closely

coordinated measurement of variables was needed for an effective

interpretation of programmatic results.

7.1.2 Summary of Meiofaunal Studies

The responses of the meiofaunal community to the presence of

platforms were generally consistent with patterns observed in cases of

7-2
modest organic enrichment and toxic contamination of the marine

environment. The abundance of total nematodes was enhanced at the 50-

and 100-rn stations by about a factor of two at the two deeper water

platforms, MU-A85 and HI-A389. At the shallow site nematode abundance

was depressed close to the platform. MAI-686 was the highest energy site.

The processes of transport and dispersion that act to remove finer materials

from near the platform, including organic detritus, were strongest at the

MAI-686 site. At all three platforms nonselective deposit-feeders were

enhanced in biomass close to the platform by more than a factor of five, on

average. This enhancement is consistent with the effects of modest organic

enrichment. The response of the nematodes, and especially nonselective

deposit-feeding nematodes, was opposite to that predicted on the basis of

the sediment texture gradient. Non-selective depositing feeding nematodes

typically increase as sediments become finer in size. Consequently, the

enhancement in nematodes near platforms was a particularly noteworthy

pattern. In contrast to the nematodes, total barpacticoid copepods were

depressed near platforms. Total harpacticoid abundance close to the

platform was only 40 % of that at distant stations. The effect was most

intense at the HI-A389 site, where the contaminant gradient was steepest.

This pattern is also consistent with the results of previous studies that

document the sensitivity of harpacticoid copepods to toxic chemicals. As a

consequence, the ratio of nematodes to copepods provided a particularly

effective discriminator of distance from the platform. This pattern in the

nematode to copepod ratio is consistent with the previous suggestions that

the nematode to copepod ratio should respond to pollutant exposure.

Harpacticoids exhibited responses that indicate sublethal effects were

occurring at the population level at the platform sites. Harpacticoid genetic

baplotype diversity decreased with increased contamination, but there were

no differences among platforms or among five different species. This

indicated that there was population subdivision at the genetic level, but

nothing that was morphologically distinct. There appeared to be reduced

reproductive success associated with the contaminant gradient. This is

indicated as increased reproductive effort (in terms of more gravid females

and greater clutch sizes) and decreased recruitment near platforms

(indicated by fewer copepodites and adults). Harpacticoids also exhibited a

toxic response to porewater exposure.

7-3
7.1.3 Summary of Macroinfauna Studies

Abundances of macroinfauna were unexpectedly low duiing the first

cruise. Subsequent data indicated that the normal winter-spring maximum

and summer-fall minimum in abundances occurred. The largest number of

species and individuals were generally found within 100-rn of a platform.

Both diversity and abundances decreased with increased distance from the

platforms. These patterns were generally dictated by abundances of the

numerically dominant group, the polychaetous annelids. The pattern was

most pronounced at the deepest site (HI-A389) and least evident at the

shallowest site (MAT-686). The largest overall abundances, in excess of

3000 individuals per m2, were found adjacent to HI-A389. No patterns were

obvious in the indices of diversity (i.e., H'). Of the numerically dominant

taxa, polychaetes, bivalves, nemerteans, decapods and isopods all displayed a

trend of decreased abundance with increased distance from a platform.

Amphipod and foraminiferan abundance were low close to a platform and

increased with increased distance from a platform.

Statistical testing of the overall sample design using macroinfauna data

revealed significant interactions between cruises, platforms, and distances.

Due to the interactions among variables, analysis by platform was most

effective. Significant variations in abundances with distance were found at

HI-A389, less at MU-A85 and few at MAI-686. Principal component analysis

indicated that because of the numerical dominance of some species of

macroinfauna, less than 25% of the 649 species accounted for 75% of the

variation. Crossplots of the first two principal components indicated that

both axes based on macroinfauna numerical data accounted for variations

among platforms and that water depth was an important determinant of

species composition. PCA for individual platforms indicated that there were

species differences among platforms for total abundance and polychaete

abundance, but no species differences among distances for any of the taxon

enumerated. Organic enrichment near the platforms was considered the

most likely cause of increased overall abundances of macroinfauna near

platforms. The ratio of the abundances of relatively toxin resistant

polychaetes to the toxin sensitive amphipods may be a sensitive indicator of

toxic response. Furthermore, diversity increased toward a given platform

and toward deeper water.

7-4
7.1.4 Summary of Megafauna Studies

The single most significant generality from the megafaunal

invertebrate studies was the platform-specificity of the observed trends.

Forcing factors producing megafaunal patterns at platforms might be water

column chemical anoma:lies, contaminant gradients, or other naturallyoccurring environmental gradients. Many of the environmental variables are

platform specific and opposing gradients are common. The megafaunal taxa

in this study vary considerably in their physiology and behavior and thus

could be expected to respond differently to the varying signals presented by

the platform-specific gradients involved. Even within a species, consistent

trends were rarely observed. Penaeus aztecus, for example, was larger in

the far-field at MAI-686 but not at MU-A85. Squilta chydaea was more

common in the near-field at MU-A85 but not at MAI-686. Thus, even within

a species, platforms failed to produce similar trends. Combined, the taxon

and environmental complexity reduces the likelihood of the existence of

general trends among all species and platforms, and few, if any, were

observed. Each platform produced a distinctive effect on the shelf biota.

The single trend among platforms was the clear decrease in frequency of

near-field/far-field effects with increased water depth and a concomitant

decreased importance of seasonal influence on population structure.

Thus, the single most significant generality from the megafaunal

population studies was that platform-specificity was observed in nearly all

variables. Among the various biological variables measured for megafaunal

invertebrates, size and histopathology exhibited the most significant

differences in pairwise comparison of Near and Far stations. Differences in

CPUE were rare and differences in reproductive stage were minor in

comparison to size and health (histopathology) differences. The presence of

a platform did not exert an overriding influence on megafaunal invertebrate

population dynamics. Although some generalities can be made about the

characteristics of megafaunal invertebrate populations with respect to

proximity to platforms, each platform associated community responded

quite differently. Thus, no generalities among platforms were observed that

could be clearly extrapolated to aU platforms, nor were generalities among

subsets of platforms observed that might be attributed to shallow versus

deep-water platforms. The overwhelming trend was towards specificity of

7-5
site. The forcing factors that produce these site-specific biological patterns

are unclear. Sampling of a larger number of sites is needed to better define

the relationships, if any, between megafauna invertebrate size and health and

specific platform attributes.

7.1.5 Summary of Detoxification Studies

The detoxification study results speak clearly to the question of

whether hydrocarbon contamination had detectable sublethal impacts on

fish at the three study sites. No differences in CYP1A activities in fish livers

existed between Near and Far stations. Measurement of PAR metabolites in

fish bile similarly failed to reveal evidence of any differential exposure to

PARs between Near and Far stations. Measurements of CYP1A mRNA levels

also failed to demonstrate a differential exposure to hydrocarbons as a

function of distance from the platform. The absence of evidence for

hydrocarbon exposure and physiological responses in fish may be due to the

low levels of hydrocarbon contaminants and/or the intrinsic mobility of fish.

Fish may move rapidly across the short distances represented by the

contaminant gradients at the study sites thus minimizing exposure.

Avoidance and other behavioral characteristics may make fish ill-suited as

indicator organisms in open ocean settings.

Comparison of hydrocarbon and CYP1A induction levels between this

study and other similar studies showed that the present study sites were

most similar to uncontaminated sites (Figure 7.1 and Table 7.1). CYP1A

induction has been demonstrated around natural petroleum seeps (Spies et

al. 1982) and around oil production platforms in the North Sea (Davies et al.

1984). The sediment PAH concentrations at these sites greatly exceeded

those documented in the present study. Based on data from these and other

studies, sediment concentrations ranging from 3,000-10,000 ng/g appear to

be required before a significant induction in hepatic EROD activity in fish

can be detected. The relationship between total PAR levels in sediments

and hepatic EROD activities for this compilation of data is significant (P =

0.004, r2 = 0.73). As a comparison, mean sediment PAH concentrations at

the study sites ranged from 20.8 to 428 ng/g. Natural variations in hepatic

EROD activities are caused by differences in sex, water temperature, fish

movement, reproductive stage, timing of feeding, and the analytical

techniques utilized. Consequently, detectable induction of CYP1A7-6
2000

1800

1600

1400

E

C

E

1000

E

0.

800

600

400

200

0

Total PAH (ng/g)

00

Figure 7.1. Correlation between total PAH concentrations in sediments

and hepatic EROD activities in fish. (ER-L: effects level-low

(10%); ER-M: effects level-medium (50%); see Long and

Morgan, 1990; see Table 7.3 for references).

7-7

=

=

=

--

--

--

-

-

PAH ERL

MaxGOOMEX

PAH

Observed

\

(1990)

Value

:

I

I

I

I .1

I

Ii

I

I

I

I1

0 Control

Contaminated

Highest Mean

EROD by Species /

Highest Mean

PAH by Distance

(Hl-A389)

0

. /

.

.

N

I

I I

I I TIIj

1 10

T I ,rirII1 I Ii ItI1II

100 1000

1 Ii iiiii I 10000

1ti,i,t

100
* - significantly different from reference site na - data not available a - data based on wet weight Table 7.1. EROD induction In relationship to environmental contamination. Species Region Site Sediment total PAH (ng/gdrywt.) Contamination total PCBs (ng/gthywt.) EROD (pmol/min/mg) 

Fundulus heterodlltus Rhode island Seekonk River 66,403 237 1±1550 900±70* E

Succotash Salt 1082 2.3±0.9 257±23 Marsh Pseudopleuronectes amertcanus Sydney Harbor Georges Bay na na 233± 107 

Nova Scotia Outer Harbor 610±340 na 234±68.3 Northwest Arm 5450±2210 na 185±89.7 Southeast Bar 10000 na 297±114 South Arm 42500±9300 na 504±130' Leiosromus xanthurus Elizabeth River 1 9 na 230± 100 

Virginia 2 55 na 267±52 3 3100 na 652±207' 4 16000 na 981±678' 5 96000 na 1894±813' 6 43000 na 1292±682' Pleuronectes uetulus Puget Sound Duwamish Waterway 3600a 570a <300>800 

Washington Polnell Point 21a 30a <100
dependent activities above background, constitutive levels in fish require at

least moderate levels of exposure to PAH.

The induction of CYP1A catalytic activities and mRNA levels are also

directly correlated with the chemical structure of the contaminant.

Structure determines the binding affinity of the contaminant for the Au

receptor. Laboratory studies have shown that 2- and 3-ring PAHs (such as

naphthalenes and phenanthrenes) and many 4-ring PAHs, do not bind to the

Ah receptor (Piskorska-Pliszczynska et al. 1986). Therefore, P450-related

biomarkers do not detect the presence of these PAul contaminants. At the

three study sites, not only were PAR contaminant concentrations low, but

when present the PAR were predominantly 2 arid 3-ring aromatics which

are only weak inducers of CYP1A related enzyme activities. Bile metabolites

provided an indicator of exposure that was inducible by a much broader

range of PAR structures than CYP1A mediated enzymes. However,

metabolite production in fish bile was not sensitive enough to detect

significant PAIl exposure at the sites studies.

Based on the low levels of PAR contamination observed, it was

concluded that most variations observed in EROD activities represent

variations in constitutive or basal levels. Constitutive levels of EROD

activities are species-dependent (Table 7.2). Significant interspecies

differences in basal ERO]) activities were also observed in the present study.

Lagodon rhomboides (pinfish) and Caulotatilus intermedius (tile fish)

expressed significantly higher EROD activities compared to other species

but these differences were not attributed to increased exposure to PAR.

There were also no significant differences in fish EROD activities in the

same species collected at Near and Far stations. The reason for differential

enzyme activities is presently unclear; but may be related to differences in

the structure of P450 1A genes and gene products in these species.

7.1.6 Summary of Porewater Toxicity Studies

Based on data from the sea urchin fertilization and embryological

development assays, toxicity was observed at some stations located within

150 m of a platform. There was excellent agreement among the results of

porewater tests that utilized three difference species (sea urchins

embryological development, polychaete reproduction, and copepod nauplii

7-9
Table 7.2. Summary of suspected constitutive levels of EROD enzyme

actMties in various species of fish.

Bluegill sunfish

Lepomis macrochirus

Sergeant major

Abudefduf saxatiUs

French grunt

Haernulon

flavolineatum

English sole

Plew-onectes vetulus

Rock sole

Lepidopsetta bilineata

Starry flounder Platiththys steUatus

Spot Leiostomus

xanthurus

Gizzard Shad

Dorosoma

cepedianum

Killifish

Fundulus heteroctitus

Winder flounder

Pseudopleurenectes

amertcanus

White sucker

Catostomus

commersoni

6-10

150

20

<100

<200

Stream, Oak Ridge.

TN

Ferry Reach, Bermuda

Ferry Reach, Bermuda

Polnell Point

Polnell Point

Jimenezetal. 1988

Stegernan et al. 1990

Stegeman et al. 1990

Coffier et al. 1995

Coffier et aL 1995

Collieretal. 1995

VanVeldetal. 1990

Levine et al. 1995

Elskus and

Stegeman 1989

Addison et al. 1994

Monosson and

Stegeman 1991

Munkittrick et al.

1993

<100 Polnell Point

30 Chesapeake Bay

30 Acton Lake, Ohio

257 - 269 Succotash Salt Marsh

233± 107m 1989 Sydney Harbour, NS

33.4 ±21 in 1990 Sydney Harbour, NS

160 Georges Bank, RI

23.1 Mountain Bay, Lake Superior

Species EROD Site Study

(pmol/mln/mg)
survival). The sediment concentration of several metals were well in excess

of sediment quality assessment guidelines for a number of stations and there

was good agreement between the predicted toxicity and toxicity observed

with the porewater toxicity tests. It appears that the porewater

concentrations for several metals were high enough to account for the

observed toxicity. At these platform sites it appears that the primary

contaminants of concern were the metals. Highly sensitive toxicity test

results suggested that the area for potential contaminant-induced impacts

was limited to the immediate vicinity of a platform.

7.2 Assessment of Benthic-Based Indicators of Biological Response

Operationally two independent, though related approaches were used

to provide an overall assessment of community response and health at

platform sites. The study design, field collections, and ultimate data

interpretations are most effectively considered in two steps. First, those

indicators or responses based on benthic sediment samplings are

considered. Next those indicators or responses based on epibenthic or

trawl samplings are considered. The following section assesses, integrates,

and interprets the results based on benthic samples.

7.2.1 Confounding of Environmental Variables

When several environmental variables strongly covary, it is difficult to

identify which factor, factors, or interaction of factors is responsible for the

observed biological responses, thus the concept of "confounded variables."

This "confounding" of multiple environmental variables is typical of most

anthropogenic discharges into marine environments (Pearson and

Rosenberg 1978). In the present study, sand content, concentrations of

several metals, barium, inorganic carbon, and petroleum hydrocarbons were

all elevated in close proximity to platforms. In an analogous study of the

impacts of North Sea oil production platforms, Gray et al. (1990)

encountered significant covanation in environmental variables, with barium,

mud content, and total hydrocarbon concentrations elevated around

platforms. If the suite of environmental variables associated with a particular

anthropogenic activity always behave in the same way and to the same

7-11
degree, then there is little practical motivation to unravel the effects. In

this situation, causation may be more of an academic interest, however

managers would have what they need to know to regulate. On the other

hand, if various management alternatives can independently control

individual deleterious effects, then an understanding of causation is in the

interest of effective management. The possibility of independently

controlling deleterious effects exists for the management of the complex

operations associated with offshore production platforms. Therefore, it is of

interest to propose supportable hypotheses to unravel the independent

effects of the processes that are extant at platform sites.

The present understanding of benthic community response to

pollution incorporates an implicit recognition that anthropogenic

contaminants can have a range of effects. This range of effects is often

species-specific. Evidence to support an emerging paradigm of differential

benthic biological response to pollution in the marine environment comes

from a review of an extensive suite of studies of marine pollution. It is

difficult to find studies of benthic community response to pollution where

toxicity is the only effect influencing biological patterns. For example,

discharges of treated sewage typically enhance metal concentrations in

sediments. However, organic matter is also enhanced (i.e., the discharge of

sewage to the Palos Verdes Peninsula; Swartz et al. 1986; the Firth of Clyde

in Scotland, Pearson 1987). In the North Sea platform study, sediments

near the platforms that were enriched in hydrocarbons also bad elevated

organic carbon concentrations (Gray et al. 1990). A supply of organic matter

external to the pollutant is not the only source of labile carbon. In virtually

every study of environmental effects of petroleum spills and seeps,

hydrocarbons act as a source of labile carbon as well as toxins (e.g., Spies and

DesMarais 1983, Braddock et al. 1995). Organic enrichment can exceed the

degradation capacity of the indigenous microbes and cause the production of

toxic chemicals (i.e., H2S). Determining the relative effects of organic

enrichment and toxicity is important in. evaluating biological responses to

releases of pollutants (e.g, Spies et al. 1988, Agard et al. 1993).

Cases in which only one of these processes is operative allows for an

independent resolution and assessment of impact. One example of a wellstudied and unconfounded gradient related to a marine discharge is a study

of the effects of cooling water discharge from the San Onofre Nuclear

7-12
Generating Station on the shelf of the Southern California Bight (MRC 1989).

As seawater is used for cooling and discharged onto the shelf, natural

organic detritus is created and discharged in the form of dead

phytoplankton, zooplankton, larval fish, and macerated macrophytes. There

are no detectable toxic chemical contaminants in the discharge or in the

benthos. Also, the organic enrichment from the discharged detritus does

not exceed the capacity of the microbial community. Only slight increases

in sediment organic carbon content and phaeopigment concentrations are

present in the vicinity of the diffusers. However, an increased flux of seston

is clearly evident. In response to this discharge of detritus and modest

organic enrichment of the sediments, increased abundances were detected

hi virtually all major taxa of macroinfauna. These enhancements extended to

3.5 and in some cases to 6.7 kilometers downcoast. As is typical, even of

discharges that include both organic enrichment and toxic chemicals,

polychaetes and nematodes were enhanced in abundance. But unlike

perturbations that include contaminants the crustaceans; including

amphipods, ostracods, tanaids, and mysids; were also enhanced in

abundance. There was also no evidence of a decrease in the abundance of

echinoderms and little observable effect on benthic biomass. The lack of an

effect was most likely a consequence of increased near-field predation due

to the enhanced abundances of most demersal fish species.

The San Onofre example contrasts sharply with the case of Los

Angeles County sewage treatment plants which discharge onto the Palos

Verdes shelf (Swartz et al. 1986; LACSD 1990). The LA County discharge

differs from the San Onofre discharge in that not only is there an organic

enrichment but also an introduction of toxic contaminants. Toxins in this

case include DDT, PCB, H2S, and metals. Polychaetes, as a class, are

enhanced in abundance near the discharge source. The enhancement

response is driven by several opportunistic rather than non-selective deposit

feeders, Tharyx spp., Capitella capitata, Mediomastus spp., and

Schistomeringos longicornis. At very high organic loadings Ophyrotrocha

sp. is enhanced as well. A bivalve mollusc, Parviluctrta tenuiscuipta, is also

enhanced. In this case, which involves toxicity, echinoderms as a group are

grossly depressed around the outfall. The decrease is largely due to

decreases in the abundances of the ophiuroid Amphiodia urtica and the sea

cucumber Parasticopus parvimensus. Other declines include the urchin

7-13
Lytechinus anamensus and the seastar Luidia foliolata (Tetra Tech 1981;

Swartz et al. 1986). Amphipods also decline in abundance near the outfall,

as reflected in decreases in the abundance of the dominant species

(Heterophoxus oculatus). Meiofaunal community responses were not

assessed in this study. The toxic chemicals in the discharge do little to

affect the enhancement of polychaetes in response to organic enrichment,

as seen at San Onofre. Chemical contamination affected the physiologically

sensitive macroinfaunal taxa causing a reduction in ecbinoderms and

amphipods. These differing biological responses to these two discharges

demonstrates the effects of organic enrichment and toxicity on benthic

communities. These observations set the stage for response the

development of a series of indicators based on the ratio of "the tolerant

species to the sensitive species."

Other examples of the effects of anthropogenic discharges into the

marine environment on benthic community biology involve both organic

enrichment and toxic chemical enhancement. A review of these reports is

useful in determining whether the patterns of polychaete and nematode

enhancement and echinoderm and amphipod depression are general

responses. Even though separate causation cannot be unequivocally ascribed

in these cases, a preponderance of typical patterns should be apparent if the

emerging paradigm is supportable. A review of studies on soft-sediment

benthic community response to gradients in organic enrichment and toxic

chemicals is presented in Table 7.3. This includes the effects of oil spills,

natural petroleum seeps, sewage discharges, industrial discharges.

experimental mesocosms, and other field studies. For the macroinfauna, the

pattern of enhancement in polychaetes, especially certain non-selective

deposit feeders, and depression in echinoderms and amphipods is

compellingly consistent and common. For the meiofauna, there appears to

be more need to separately analyze different famffies or trophic groups of

nematodes and harpacticoids. However, there is evidence for a general

enhancement of non-selective feeders among nematodes and declines in

some harpacticoids. One limitation in the application of this paradigm is the

difficulty in objectively defining the feeding status of bulk macroinfauna and

meiofauna feeders. An objective definition of trophic group and what

constitutes an opportunistic life history is an important but challenging goal.

Nevertheless, defining an effective taxonomic criteria for evaluating

7-14
Table 7.3. Effects of anthropogenic pollution on benthic communities in the marine environm

Total polychaetes enhanced as well as Nerels, Nepthys, Polydora, and Lucina In eelgrass beds Total polychaetes enhanced Opportunistic, surface deposit-feeding polychaetes increased, especially Capitelia capttata. Mediomastus arnbiseta Unclear from data available Unclear from data available Unclear from data available Unclear from data available Total polychaetes enhanced, as well as Tharyxspp., Capttella capitata. Mediomastus spp., Schtstorneringos longicornis, and Ophryotrocha spp. Total crustaceans and tota

echinoderms occasionally show reductions (never Increases), while total amphipods declined as weas a crab (Telmessus) and a seastar (Dermosterias) Total echinoderms and total crustaceans declined

as well as amphipods Several ampeliscid amphipods declined Amphipods (Gamrnarus spp.) and Isopods (Idotea spp.) declined An amphipod (Garnmarus oceanlcus) was selectively reduced Amphipods in intertidal and subtidal declined greatly The sea urchin Strong ylocentrotus purpuraus suffered eviden

lethal and sublethal Impacts Total echinodernis reduced, as well as ophiuroid Amphioda urtica, sea cucumber Parastlehopus parvlrnensus, sea urchin Lijtechlrtus ariamensus, and seastar LUtdkL foliolata, amphipod Heterophoxus oculatus also reduced 

Pollution Case Study Organic Enrichment Toxic Chemicals Benthos Enhanced Benthos Suppressed 

A. Mac rolnfauna Ex,con Valdez oil Yes, with evident Yes, with elevated spill stimulation of oil- PAll's, etc. degrading bacteria Amoco Cadiz oil Yes Yes spill Florida oil spill Yes Yes Irini oil spill Yes Yes Arrow oil api11 Yes Yes Esso Essen oil spill Yes Yes Gerteral MC. Meigs Yes Yes oil spill Palos Verdes sewage Yes, with detectable Yes, with DDT, PCB, wastewater organic C, N enhancement heavy metals, and discharge H2S elevated
San Onofre Nuclear Generating Station cooling water discharge Firth of Clyde sewage sludge disposal Swedish pulp mill discharge Antarctic sediment contamination around Winter Quarters Bay Industrial pollution gradient in fjord near Oslo Experimental crude oil adthtion in mesocosni Natural oil seep and refinery discharges in Trinidad Natural oil seep Experimental fuel oil addition in mesocosm Field experiment of crude oil addition to tide pools Meta-analysis of all benthic community data for NE Atlantic Yes, with evident organic C and phaeopigment enhancement Yes, with organic C and N elevated Yes Presumably, In that hydrocarbon levels are elevated Presumably Probably not because of short-term nature of experiment Yes, with organic C elevated Yes, with enhanced microbial production Possibly, given 25 wk exposure to oil Probably not because of short-term nature of experiment Yes No Total polychaetes, total crustaceans, total amphipods, total molluscs all enhanced Yes, with Cd Total polychaetes elevated along with enhanced other metals Unclear Yes, with PCB, hydrocarbons, and heavy metals elevated Yes, heavy metal concentrations elevated Yes Yes, with PAH elevation at seep and reflnery and metals elevated at refinery Yes, with PAR elevation Yes Yes YesTable 7.3. (Cont.) Total polychactes enhanced, especially Cap (teila cap (tata and other opportunistic deposit feeders In most contaminated areas, Capttetkz and Ophryotrocha enhanced, while In modest contamination Tharyx and Haptoscoloplos enhanced Deposit-feeding polychaetes may be elevated None (time frame too short to test) Total polychaetes enhanced especially in blomass at the seep Oligochaetes and many deposit-feeding polychaetes enhanced Time frame probably too short to test Time frame too short to test total polychaetes arc enhanced None Total echinoderms, total crustaceans both depressed Total echinoderms depressed Total crustaceans depressed, especially amphipods, Isopods, tenaids Total echinoderm biomass is clearly depressed, especially an echinoid Total echinoderms, especially the ophiuroid Ophiura afflni.s depressed Unclear from data available The only abundance eclilnoclerm Lytechinus ptctus and the only abundant amphipod Paraphoxus abronius depressed Total amphipod abundanc

declined by 98% Negative effects on amphipods, isopods, tan aids Total echinoderms and total crustaceans are depressed 

Pollution Case Study Organic Enrichment Toxic Chemicals Benthos Enhanced Benthos Suppressed 
Pollution Case Study U. Melofauna Review of marine pollution events Raw domestic sewage discharge Organic enrichment Organic enrichment Natural oil seep Review of organic pollution in marine sediments Industrial pollution gradient In fjord near Oslo Meta-analysls of all benthic community data for NE Atlantic Table 7.3. (Cont.) Organic Enrichment Toxic Chemicals 8enthos Enhanced Benthos Suppressed 

Yes Yes Nematodes are enhanced Harpacticold copepods are depressed Yes Probable The copepod/nematode ratio is enhanced by pollution Yes No The copepod/nematode ratio is enhanced with organic enrichment Yes Probable The copepod/nematode ratio Is enhanced with organic enrichment 

Yes, with enhanced Yes, with PAH The 

microbial production elevation nematode/harpacticoid ratio is enhanced with oil addition 

Yes Usually Yes Non-selective deposit- feeding nematodes generally enhanced Some other nematode groups may be depressed 

Presumably Yes, heavy metal Total nematodes are Unclear from data 

concentrations elevated enhanced as well as some harpacticoid copepod groups available Yes Yes Total nematodes are Harpacticolds, etc. not 

generally enhanced analyzed 
macroinfaunal community response may not require trophic

characterization.

A review of past benthic community responses to maxine pollution and

the emerging paradigm of multiple causation, including impacts of both

organic enrichment and toxin exposure, provide a means of interpreting the

broad suite of environmental and biological responses in the present study.

These interpretations are suggested hypotheses that will require explicit

testing through further study. It is clear that in the present data set, as in

virtually all other data sets on the effects of anthropogenic discharges into

the marine environment, there is tremendous covariance in variable

patterns. Four major types of environmental variables can be delineated as

the important independent forcing variables that control biological patterns

at these sites (e.g., Pearson and Rosenberg 1978).

First, there was an enhancement of barite-enriched sands at all three

platforms. This enhancement varies from background values of about 30 %

to 70 % at MAI-686, from about 10 % to 65 % at MtJ-A85, and from about 5

% to 40 % at HI-A389. The proportion of fine sediments decreases along

this gradient of increased sands and enhancement of silt-sized particles was

apparent close to the FII-A389 platform.

Second, there is evidence of modest hydrocarbon contamination

(PAHs, Ails, and UCM) around the platforms. These contaminants extend,

although not symmetrically, in every direction to 100 or 200-rn depending

on the site. The shallow water platform, MAI-686, did not exhibit

significant evidence of a hydrocarbon gradient. In contrast, the gradients

were clear at MU-A85 and HI-A389. In general, there was little change in

the distribution of hydrocarbons among cruises. The composition of the

hydrocarbons reflected older, degraded sources except in isolated instances.

Third, there was a strong signal of contamination in certain toxic

metals (Ag, Cd, Hg, Pb, and Zn) in sediments near the platforms. Metal

concentrations were lowest at MAI-686, intermediate at MU-A85, and

highest at HI-A389. Again elevated concentrations were restricted to

distances of 100 to 200-rn from the platforms depending on the site.

Concentrations of metals in pore waters, although not well correlated with

solid phase concentrations, probably because of pore-water sampling

constraints, were also elevated at certain sampling sites to a distance of

100-rn from the platform.

7-18
Fourth, there was evidence of organic enrichment near the platforms.

This enrichment was not apparent in organic carbon content because of

dilution with sand. Evidence of organic enrichment around the platforms

primarily comes from the summer cruises at the shallow water platform at

MAI-686. Density stratification of the water column is strong during the

summer. Under these conditions, hypoxia was evident near the platform,

implying that low oxygen may be an occasional stress at that site. Enhanced

production and benthic deposition of organic matter near the platforms is

probably occurring. Organic enrichment was detectable at this site and time

because conditions allowed for the development of low-oxygen bottom

waters. In the bottom waters near platforms, low oxygen was linearly

associated with increased concentrations of inorganic nutrients. This

covariation implies that benthic microbial degradation of organic matter

produced the low oxygen conditions and the concurrent nutrient

enhancements.

The major patterns in biological responses to these environmental

gradients can be interpreted largely as the consequence of two of these four

environmental forcings, organic enrichment and metal toxicity. The

hydrocarbons occur in concentrations that seem too low to be important

contributors to the observed toxicological effects. The pattern of increased

sand content doubtless affects benthic invertebrates but the observed trends

are often opposite to the usual biotic response to sediment texture. The

emergence of patterns in benthic meiofaunal and macroinfaunal

communities that are broadly consistent with other documented responses

to organic enrichment and sediment toxicity, despite the sediment grainsize gradient, leads to the conclusion that sediment grain-size patterns are

not a primary driver of the observed biological responses.

As previously mentioned, metofaunal community responses to the

presence of platforms are consistent with patterns observed during modest

organic and contaminant discharges. The abundance of total nematodes was

enhanced near platforms by about a factor of two at the two deeper water

platforms. At the shallowest site nematode abundance was depressed close

to the platform. At all three platforms non-selective deposit-feeders were

enhanced in biomass close to a platform. This enhancement is consistent

with the effects of modest organic enrichment. The response of the

nematodes is opposite to that predicted on the basis of the sediment texture

7-19
gradient. Non-selective depositing feeding nematodes typically increase as

sediments become finer in size. In contrast to the nematodes, total

harpacticoid copepods are depressed near the platforms. This pattern again

is consistent with the previous studies of the sensitivity of harpacticoid

copepods to toxic chemicals. This pattern in the nematode to copepod ratio

is consistent with the previous suggestions that the nematode to copepod

ratio responds to pollutant exposure (Raffaelli and Mason 1981). The

macroinfaunal community revealed a pattern of change with distance from

the platforms that was also consistent with earlier studies of low-level

organic and chemical discharges to the marine environment. Total

macroinfaunal densities were enhanced at near platforms as a consequence

of enhanced abundances of polychaetes. This pattern was weakest at MAE686. Enhancement of polychaete abundances is typical in cases of modest

organic enrichment in marine environments. It is noteworthy, that the

increase in polychaete abundance occurs despite a gradient in sediment

sand content. Polychaetes are normally more abundant in finer sediments.

In contrast to the polychaetes, amphipod abundances are depressed near

platforms. This effect on amphipods is consistent with modest chemical

contamination. Echinoderms were not sufficiently common at the study

sites to conclusively determine bow they responded to the platforms, but

the patterns observed suggested an absence of any toxicological or density

responses in this group.

Attributing the pattern of amphipods and barpacticoids abundances to

a toxicological cause is supported by the results of porewater toxicity testing.

Toxicity tests on percent normal development and percent fertilization of

sea urchins (Arbacia purtctulata), an echinoderm, revealed a pattern of toxic

responses similar to the pattern of chemical contamination. The

embryological development test proved more sensitive than the fertilization

test, with all cases of significant toxicity in the fertilization test

corresponding to significant toxicities in the development test. The toxicity

results revealed that, with one exception, all cases of significant sediment

toxicity were within 100-rn of a platform. The most compeffing pattern of

toxicity comes from the most contaminated site (HI-A389). Several stations

within 50 m of the HI-A389 platform showed significant toxicity in the sea

urchin development test during two independent samplings.

Concentrations of contaminants in these samples suggested that the

7-20
observed toxicity was most likely a consequence of certain metals (Zn, Cd,

Pb). Concentrations of several metals in sediments at these stations

approached or exceeded probable biological effects levels (Long and Morgan

1990). Results of a novel set of toxicity tests using naupliar survival of the

barpacticoid copepod, Longipedia americana, and egg production for the

meiofaunal polychaete, Dinophilus gyrociliatus, provided further evidence of

toxicity close to the platform. Both of these species proved less sensitive

than the sea urchin to sediment toxicity, but stations that proved toxic to

either of these meiofauna were also toxic in the sea urchin development

tests. These tests confirm the toxicity of some sediments close to the

platforms, especially at HI-A389. These results support the inference that

toxicity is driven by metal contamination. Furthermore, toxicity was

demonstrated using not only standard test species but also species

indigenous to the study region. The demonstrated toxicological effects on a

harpacticoid provides support for the inference that the pattern of

depressed abundances of harpacticoids near the platforms is indeed a

response to the toxicity of the sediments.

Various physiological and genetic results provide further evidence that

the crustaceans around the platforms exhibited sublethal responses to

contaminant exposure. In the pooled data set for all harpacticoid copepods,

the percentage of gravid females was greater and the percentage of juveniles

was reduced at the 50-rn stations around platforms. In addition,

reproductive effort (egg numbers times egg sizes) for those female

harpacticoids carrying eggs was reduced in sediments within 50-rn of the

platforms. These responses could be explained as sublethal physiological

responses to modest levels of stress due to exposure to tox.icants. The

observation that genetic diversity in several species of harpacticoid

copepods was significantly reduced near the platforms also suggests that

this approach is detecting sublethal response.

Although the trawling component of GOOMEX was not designed to

measure how fish and mega-invertebrates varied in abundance with distance

from the platform, the trawl data can still provide some indication of large

abundance differences, if there were any. This question has importance for

interpretation of the benthic community response results. Benthic

abundance patterns can be driven by top-down differences in predation

pressure as well as by bottom-up differences in food supply and toxicity.

7-21
There is little evidence of substantial differences between Near and Far

stations in the abundance of large invertebrates. There may be

enhancement of some fish near platforms (as indicated by the trawl results).

Enhancement of species that utilize the bard substrate "reef' habitat would

be expected. Bottom trawling is not an effective method of quantifying

pelagic species, because they are too large and can avoid the net (pelagic

predators such as king mackerel) and/or they are too closely associated with

the reef structure to be accurately sampled (sheepsbead, snappers, pinfish).

A more accurate and complete census of fish species that utilize the

platform structure as habitat would almost certainly have revealed enhanced

abundances. Analysis of gut contents in small fish showed no differences in

dietary composition or in gut fullness between Near and Far stations.

Nevertheless, increased abundance in fish in the near-field may indicate

somewhat greater predation pressure on macroinfauna near platforms.

Based upon the analogy with other studies of ecosystem response to organic

enrichment, especially the San Onofre power plant study (MRC 1989) and

the Los Angeles County sewage outfall study (Tetra Tech 1981, 1984), it

seems more likely that enhanced demersal fish abundance occurs in

response to food abundance rather than serving as a driver of benthic

abundance patterns. If this were true for platform sites, then increased

polychaete abundances in the near-field may be contributing to some

increase in demersal fish.

7.2.2 Sediment Quality Triad Approach to Integration of Results

As a follow-on to the interpretations provided in Section 7.2.1, a

statistical test of the concordance of programmatic results was considered

an important concept to pursue. The Sediment Quality Triad (SQT) is one

such approach that attempts to integrate concurrently obtained (synoptic)

toxicological, sediment chemistry. and benthic infauna data to describe

degradation of the environment (Chapman and Long 1983; Long and

Chapman 1985; Chapman et al. 1986; Chapman et al. 1987a,b, Chapman

1989; Chapman 1990). In evaluating effects associated with an oil platform,

Chapman et at. (1991) suggested that the SQT "incorporates three essential

components; measures to determine the presence and degree of

anthropogenic contamination (i.e., bulk sediment chemistry); measures that

7-22
demonstrate that substances are present that can interfere with the normal

functioning of at least some biological organisms tested in the laboratory

(i.e., sediment toxicity tests); and, assessments of in situ alteration of

resident biological communities (i.e., measures of benthic infaunal

community structure)." One of the weaknesses of the SQT approach is a

"lack of statistical criteria for the combined Triad components." Green et al.

(1993) pointed out that appropriate statistical methods had not been used

in previous applications of the SQT concept to evaluate environmental

impact. Appropriate statistical methods are those that can relate

conceptually different sets of variables in multivariate data.

Chapman et al. (1991) applied the SQT approach to data obtained from

sampling along three radii centered on Platform "C" of the MAE-622 field, 22

km offshore in water depths ranging from 24 to 26 m. Benthic infaunai

community data obtained from cores provided the biological component.

Limited sediment chemistry data provided the contamination component,

and the toxicological component consisted of an amphipod bioassay, an

assessment of abnormalities in oyster larvae, and Microtox test results. As in

the Chapman et al. (1989) and earlier applications of the SQT, the statistical

analyses were mostly descriptive in nature and applied independently to

each component rather than as an integrated approach that relates several

components. Comparisons in previous studies were often based on a "ratioto-reference" criterion (the ratio of values at possibly impacted stations to

values at an a priori defmed reference station).

An integration of results demonstrating coherence between diverse

work elements provides strong circumstantial evidence of effect or impact.

Therefore, the SQT concept described in Green (1993a,b) was applied to

the data collected in the present study. This additional integration of

results provides a statistically rigorous cross-work element interpretation

based on pollutant exposure and biological response.

For the SQT components the following variables were used:

Biological: abundances of four major meiofaunal and

macroinfaunal taxa.

Chemical: the variables TOTPAH, UCM, TOTALK, SAND, SILT,

CLAY, TOC, TIC, REDOX, Fe, Cd, Al, and Ba.
Toxicological: the test of porewater toxicity using a percentage

successful development of sea urchin embryos as a

criterion.

The sea urchin embryo development assay was done for samples from

all stations on Cruises 1 and 2. Therefore the data analyzed by the SQT

approach were from samples taken on the first two cruises at all stations (n2 cruises X 3 platforms x 5 radii x 5 distances = 50). There is only one

toxicological variable, and the environmental variables have already been

reduced to a PC score (see Section 6.2). Two analyses were carried out, one

based on meiofauna community response and one based on macroinfaunal

community response. For the meiofauna analysis total harpacticoid

abundance and total nematode abundance were used as variables, reflecting

the long standing use of the taxa and their relative abundances as indicators

of environmental impact as previously discussed. Abundances were logtransformed, so a difference between nematode and harpacticoid abundance

represents this ratio. Analogously, the macroinfauna component used total

amphipod abundance and total polychaete abundance. Again abundances

were log-transformed. The SQT analysis was also carried out on all four of

these taxa combined. These combined results were statistically significant

and consistent with the results from the analyses of the melofauna and

macroinfauna separately, but the results of the separate analyses were easier

to interpret. Therefore the combined analysis results were not pursued

further. The SQT analyses were also carried out platform-by-platform.

The statistical analysis procedure was the same for the meiofaunabased analysis as for the macroinfauna-based analysis. First the correlations

among components were calculated. The two correlations involving the

biological component (the correlation between the biological and chemical

components and the correlation between the biological and toxicological

components) were determined by the multiple correlation of the nonbiological component with the two taxa abundances defining the biological

component. The correlation between the chemical and toxicological

components is the simple bivariate correlation coefficient r. Thus the

significance and strength of each of the three between-component

relationships was evaluated, and were placed on the sides of a triangle

representing the SQT (Figure 7.2). Second, the entire among-component

correlation matrix was tested against the null hypothesis H0: "no real

relationships exist among the three SQT components," using Bartlett's

724
Meiofauna

Bio

R=O.31 (p<O.O1) R=O.38 (p<O.Ol)

R=O.52 (pcO.Ol) R=O.43 (p<O,O1)

Figure 7.2. Significance of the relationships between SQT components.

Chem

IrI=O.30 (p<O.Ol)

Tox

Macroinfauna

Blo

Chem Tox

IrI=O.30 (p<O.Ol)
sphericity test. Third, a principal component analysis (PCA) was done on

the correlation matrix to evaluate the structural relationship(s) among the

three SQT components. This was done by a two-step procedure. First a PCA

was done on the two log-transformed taxa abundance variables to derive

size- and shape-PCs. That is. in a PCA on such data one of the PCs (the sizePC) is invariably related (same strength of relationship and same sign) to the

original variables and represents a tendency for two variables to go up and

down together. Here it would represent increases or decreases in

abundance of both taxa, and presumably of the entire meiofaunal or

macroinfaunal community. The other PC will have opposite-signed

relationships to the original variables and in these log-transformed data will

represent changes in the ratio of the abundances of the two taxa. Then the

PC scores for these two PCs (hereafter referred to as BioPCs), which are

expected to have clear interpretations, are used in the final PCA along with

the chemical and toxicological measures.

The results for the meiofauna-based analysis and for the macroinfaunabased analysis are similar. The strength and significance of betweencomponent SQT relationships in the two analyses is shown in Figure 7.2. All

three relationships in both analyses are highly significant (p<O.Ol).

Between-component relationships are illustrated in Figures 7.2 to 7.4. For

both analyses Bartlett's sphericity test is highly significant, with x2 (6 di) =

43.9 (p<zO.Ol) for the meiofauna-based analysis and x2 (6 df) = 78.6 (p<O.Ol)

for the macroinfauna-based analysis. The PCA results are shown in Table 7.4.

In the meiofauna-based analysis, BioPC1 was a size-PC and B1oPC2 was a

shape-PC indicating that fluctuations in the abundance of both taxa together

dominate the abundance variation, with relative abundance changes (changes

in the nematode to barpacticoid ratio) being smaller in magnitude (Figure

7.3). However in the macroinfauna-based analysis the BioPC1 was the shapePC and the BioPC2 was the size-PC, indicating that the relative abundance

changes (the polychaete-to amphipod ratio) dominate the fluctuations In

abundance of both taxa together (Figure 7.4). In the final PCA, for both SQT

analyses there is a dominant PCi (41.5 % of the structure in the meiofaunabased analysis and 45.6% of the structure in the macroinfauna-based

analysis) which can be interpreted as follows (Table 7.4). As chemical

contamination increases (positive relationship with ChemPCl) the

percentage of successful development of sea urchin embryos decreases

7-26
2

0

0

cp

0 0 0 0

00 000

00 0

0 0

,-

'-Jo cPQb 0 06p

BQ

0

0

0

0

-1.5

0

0 0

0

0

°

0Q ;. 00 TOo

0 0

0

0

0

0

8 00

0

0

00000 8°

00

0

0

0

0

I I -1.0 -0.5

1111111 111111 I IllillIllIl iii 111111 1111111

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 30

ChemPCl

II I ll

1.5 2.0

11111 I I 2.5 30

Figure 7.3. Relationship between the first two principal components

of the meiofauria abundance data and the environmental

variables PCi.

7-27

4

3-

0

2-

IC, 0 1-

0

0-

C

2-

3

8°°°

800

0

0

I II I 1.0

I I liii

0.0 0.5

Chem PCi

0

0 0 0

0
4

op ooco

0

0

(300 0

0

0

00 0

C-' D.! ,' d) 0 00

0

0

0

o0 0

0 Lroo

S..

ChemPCl

0

0

0

0

0

0 ;°! 00

0 000

;!D c&c 0 00

0 ocD c0

cø

, 0

0 0

0

0

0

0

7-28

Figure 7.4. Relationship between the first two principal components of

the macroinfauna abundance data and the environmental

variables PCi.

1111 Ill III 11111 III lii 11 IjIlIl

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 30

ChemPCl

lit I [I Ill 11111 III I III IIII9

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 30

0

0

0

0
(negative relationship with the toxicological measure; Figure 7.5). The

biological community responds in the direction of increasing the ratio of the

abundance of the "more tolerant taxon" to the "more sensitive taxon.' Thus,

the same relationships among the SQT components are seen in both the

melofauna-based and the macroinfauna-based SQT analyses, which

strengthens the interpretations and conclusions.

Variation in meiofaunal abundances was dominated by change in total

abundance (nematodes and harpacticoids going up and down together)

whereas variation in macroinfaunal abundances was dominated by relative

abundance changes (changes in the "polychaete to amphipod ratio").

Although neither community shows a strong relationship between

ChemPCl and total abundance (it is mostly between CbemPCl and the

relative abundances of the taxa), such relationship as there is, is a negative

one for the meiofauna and a positive one for the macroinfauna. As previously

discussed, organic enrichment of the macroinfaunal community near the

platform may cause increased total macroinfaunal abundance. If such

enrichment does not affect the meiofaunal community, then most variation

in total meiofaunal abundance would be a contaminant-driven response near

platforms. This is in fact what is seen. In other words, both communities

show impact effects in their ratios of "tolerant to sensitive taxa abundances."

The meiofaunal community also shows some negative response in total

abundance, but in the macroinfaunal community any such response is

overwhelmed by enhancement of total abundance, probably by organic

enrichment near platforms.

7-29

Table 7.4. Summary of correlation coefficients among SQT biological and

toxicological and chemical components

Meiofauna Pci (41.5%)

Chemical Component 0.703

Toxicological Component -0.758

Bio Component (total abundance) -0.267

Blo Component (NEMA/HARP) 0.721

Macroinfauna PCi (45.6%)

Chemical Component 0.782

Toxicological Component -0.706

Blo Component (total abundance) 0.255

Bio Component (NTEMA/HARP) 0.805
Figure 7.5. Relationship between survivability in the sea urchin embryo pore water as

(MDEVEL) and the environmental variable PCi (ChemPCl).
The platform-by-platform analyses indicate that most of the patterns

in tests of the overall study design are due to the intensity of the patterns at

the HI-A389 site. The patterns at the other two platforms are not obviously

different, but they are certainly weaker. At HI-A389, Bartlett's sphericity

test is highly significant and all three SQT relationships are highly

significant for both meiofauna and macroinfauna. At MU-A85, there is no

TOX-CHEM relationship, and no BlO-TOX relationship for either meiofauna

or macroinfauna. There is a significant (p < 0.01) BlO-CHEM relationship

for macroinfauna and a marginally non-significant one (p = 0.11) for

meiofauna. However, the overall test of whether there are any significant

SQT relationships, Bartlett's sphericity test, is not significant for either

meiofauna or macroinfauna at MU-A85. At MAI-686 Bartlett's sphericity test

is highly significant for both meiofauna and macroinfauna, but only the BlOCHEM relationship is significant (p < 0.01, for both meiofauna and

macroinfauna). The BlO-TOX and the TOX-CHEM relationships are nonsignificant for both meiofauna and macroinfauna at MAI-686.

Finally, it should be remembered that the environmental variable score

(ChemPCl), used as a measure of the chemical contaminant SQT

component, is a measure of chemical and substrate grain-size gradient

related to distance from the platform. All interpretations are made with this

reality in mind. However, the same is true for all spatial pattern data in this

study, as well as all environmental impact studies based on observational

data. However, as previously noted, many of the biological patterns are

opposite that expected for grain-size driven ecological trends. The most

common and consistent pattern at all three sites is the enhancement of

sand near the platform. However, despite strong covariance in many of the

independent variables, underlying trends related to toxic response are

discernable.

7.2.3 Utility of Higher Taxonomic Levels

Many different techniques have been utilized to detect changes in

community structure. In the present study, ANOVA of diversity indices and

PCA on species data was used. Thus, both an a piiori univanate technique

(ANOVA), and a post hoc multivariate technique (PCA) was used. Using

these two techniques, it has been demonstrated that both meiofaunal and

7-31
macroinfaunal assemblages change among platforms and with distance from

platforms. The use of these techniques based on data collected at the

species level was powerful. However, significant costs and time was

associated with identification of all organisms to the species level. It is

becoming evident that biological responses to pollution may be detectable at

higher taxonomic levels than species.

For macroinfauna, detection of impacts is possible at the level of the

phylum (Warwick 1988a,b), and at least in some cases phyletic analysis

provides superior discrimination (Warwick and Clarke 1993, Agard et al.

1993). The biological basis for a differential response to pollution, rests

upon intrinsic physiological and ecological differences among higher taxa.

As summarized above, echinoderms and crustaceans, especially amphipods

and some harpacticoid copepods, are relatively more sensitive to toxic

chemicals in their environment than other organisms. It is by design that

standard EPA biotoxicity tests for benthic invertebrates involve an

echinoderm (sea urchin reproductive stages) and an amphipod

(Rhepoxintus) so that testing uses the most sensitive indicators of pollution

toxicity. In analyses of community response to marine pollution that

involves toxicity, echinoderms and crustaceans, at least arnpbipods and

some groups of harpacticoids, typically show large declines. In contrast,

polychaetes and nematodes are not especially sensitive to toxic chemicals

yet include species with both opportunistic life histories and other feeding

types (especially non-selective deposit feeders) that would allow them to

utilize carbon from organic pollution. Consequently, polychaetes and

nematodes (at least non-selective deposit-feeding nematodes) typically show

substantial increases during organic pollution events. It is this unequal

effect of organic pollution upon different groups of benthic meiofauna and

macroinfauna that makes ordination techniques of benthic community

analysis so effective in discriminating the effects of pollution at higher levels

of taxonomic classification, including the phylum level for macroinfauna

(Warwick and Clarke 1993). If higher taxon approaches are to be adopted,

information on effects at the species-level must be preserved (Kingston and

Riddle, 1989).

For both meiofauna and macroinfauna, identification to only the

Suborder or Family level is one possible alternative approach. The GEEP

(Group of Experts on Effects of Pollution) workshop performed an

7-32
intercalibration study and evaluated techniques for the assessment of

pollution in the sea (Bayne et al. 1988). All levels of biological organization

were studied from the molecular to the community, and all biological

components from bacteria to macroinfauna were included. Both mesocosm

and field experiments were performed. In the GEEP mesocosm experiment

Warwick et aT. (1988) found meiofauna to be very sensitive to the treatments.

Harpacticoids exhibited a graded response of decreasing diversity with

increasing exposure to pollutants, but diversity profiles for nematodes were

virtually unaffected. Diversity was not useful in detecting the pollution

gradient in the field study, but community differences were distinct and

species-level data gave no more information for discrimination than did

nematode Suborder or harpacticoid Family groupings (Heip et al. 1988).

Macroinfauna family groupings were just as adequate for distinguishing the

pollution gradient as was species level data (Warwick 1988a). The most

remarkable result from these studies was that identifications at higher

taxonomic levels were as good as species identifications. This indicated that

it may be possible to obtain up to 80% of the information at a cost of less

than 25% of the resources. The results also indicated that meiofauna and

macroinfauna can indicate impacts at different levels in an ecosystem.

Finally, harpacticoid copepod species were the most sensitive indicators of

stress in both field and mesocosm GEEP studies. Higher level

identifications were found to be just as good as species identifications for

detecting pollution gradients in one other study. Macroinfauna family level

identifications were adequate to assess pollutant contaminant impacts on

the Southern California Bight (Ferraro and Cole 1990).

As previously described the nematode:copepod ratio should not

require species identifications to detect anthrop ogenic disturbances

(Raffaelli and Mason 1981; Raffaeffi 1982; Warwick 1988b). The

nematode:copepod ratio was originally conceived to detect gradients of

organic enrichment, e.g., exposure to sewage disposal (Raffaelli and Mason

1981). This was successfully used in Scotland (Raffaelli and Mason 1981)

and Norway (Arnjad and Gray 1983). However, the ratio was not effective in

South Africa (Hennig et al. 1983), or Yugoslavia (Vidakovic 1983). The ratio

has been criticized as being too simplistic. Coull et al. (1981) suggested that

seasonal variation or non-pollution events can cause the observed variations.

Hennig et al. 1983 showed that nematodes and harpacticoids can have

7-33
different responses to different kinds of disturbances. Further analyses have

shown that these criticisms were correct for the Scottish coast. Resampling

by Lambshead (1984), Moore and Pearson (1984), and Shiells and Anderson

(1985) found that seasonal variation and sediment grain-size caused the

ratio to inconsistently vaty, leading to the conclusion that the ratio could not

be used to specifically indicate organic pollution. In oil pollution studies the

ratio was effective, because the presence of the oil decreased the number of

harpacticoids while nematode numbers remained constant or increased

slightly (Montagna et al. 1987; 1989). However, other studies of oil

contamination have produced inconsistent results. The ratio declined,

rather than increased, near a platform in the North Sea and in experimental

mesocosms when drilling muds were added (Moore et at. 1987; Leaver et at.

1987). In the present study, the nematode:copepod ratio successfully

detected near-field effects. The response of the ratio was due to nematode

populations generally increasing or staying the same, while harpacticoid

populations decreased.

To test the generality of responses at the family level for meiofauna

and macroinfauna, species data from the present study was combined at the

family level and reanalyzed. In the meiofauna, the harpacticoids and

nematodes, were reanalyzed separately (Figures 7.6 to 7.13). In the

macroinfauna, the total dataset, arnphipods and polycbaetes were separately

reanalyzed (Figures 7.14 to 7.17).

For harpacticoids at the family level, platform differences were obvious

(Figure 7.6), but not as obvious as at the species level. For nematodes at the

family level differences were not obvious, but they were obvious at the

species level (Figure 7.7). To determine differences attributable to distance

from the platform, PCA was redetermined at each platform. For

harpacticoids analyzed by-platform, distance effects were not noticeable at

MAI[-686 at either the fimily or species level (Figure 7.8). For harpacticoids

analyzed by-platform at MU-A85 distance effects were noticeable at the

family level with high loadings for PCi at stations at 50 and 100 m, but not

at the species level (Figure 7.10). For harpacticoids at HI-A389, differences

were found at the species level, but not as clearly at the family level (Figure

7.10). For nematodes analyzed by platform, distance effects were not

noticeable at the family level for platforms MAI-686 (Figure 7.11) but were

quite evident at MU-A85 (Figure 7.12) and HI-A389 (Figure 7.14). Distance

7-34
Figure 7.6. Comparison of PCA at the species and family levels for

harpacticoid families for all platfonns.

7-35
Figure 7.7. Comparison of PCA at the species and family levels for

nematode families for all platforms.

7-36
7

6-

2-

o-

-2 -

B: By Species.0

0 J00. 5

x

i!a. 00

0 0

p o

. C. 0

0

U

I jI I

I -1 0

pci

.

A: By Family

0

x

0

.

0

.

X50m

o lOOm

0 200m

500m

3000m

S. 0

I -3 -2

-2-

3_ I -2

pci

I I r 2 3 4

Figure 7.8. Comparison of PCA at the species and family levels for

harpacticoid fmiIies at MAI-686.

7-37

4

3-

2-

1-

01 0

0. 0-

0 1 2 3
Figure 7.9. Comparison of PCA at the species and family levels for

harpacticoid faniffies at MU-A85.

7-38
Figure 7.10. Comparison of PCA at the species and family levels for

harpacticoid families at HI-A389.

7-39
5-

4-

3-

2-

C)

-1 -

-2-

X

X

0

0

. 0

0 0 0

0 XX X

'"t:i :

0

X

X50m

o lOOm

o 200m

500m

3000m

0

A: By Family

xX°

X 0

X

X

X B: By Species

PCI

pci

2 3

3

Figure 7.11. Comparison of PCA at the species arid family levels for

nematode families at MAI-686.

7-40

c1 - C)

a. - -1 -

-2-

-3-

-4

0

X

cP

I

' I

3

-2 -1 0

2-

1-

0-

...

.

6 x

-2 -1 0 1 2

Xo0 0 00 x

II. 0

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o)e 0
3

2-

1-

3

A: By Family

X

X50m

o lOOm

o 200m

500m

3000m

0

X 0

X

0

.:s

D0PJ0.

DO % _ .

. S. .

0

-1 -

-2

2-

-4

B: By Species

X

X X

XX

X X

X x

X

X X<

X

X

0 x0 0

x 0

0

o c 0

o

0 0

B

EU U 0 o d'

0

I

. I

0

C"

C-)

0-

-1 -

' pci

pci

I I I I I I

I -1 0 1 2

2

Figure 7.12. Comparison of PCA at the species and family levels for

nematode families at MU-A85.

7-41

x

XX

X

0

2

-3 -2 -1

' I 0 1
3

1

x 50m 0 lOOm 0 200m 500m U 5000m

xxx O0 0

0 0

0 0 cc'B

IPdI. x x0 0

x 0 0

S

.

x

I

B: By Species

3 II -2 -1 0

pci

2

Figure 7. iS. Comparison of PCA at the species and family levels for

nematode families at HI-A389.

7-42

c1

C) 0.

x

I A: By Family

3

-2

I -1 0

pci

1 2

2

1-

0

- -1 -

-2-

x

x

>9

00x

0

0

0

00

S

0

0

0

0

.0 0 -I

0

.US

u

0

0

0

I

U

-1 - . 0.S DID

-2- I.

x 2-
Figure 7.14. Comparison of PCA at the species and family levels for

macroinfauna faniffies for all platforms.

7-43
Figure 7.15. Comparison of PCA at the species and faniily levels for

macroinfauna families for MAI-686.

7-44
Figure 7.16. Comparison of PCA at the species and family levels for

macroiifauna families at MU-A85.

7-45
Figure 7.17. Comparison of PCA at the species and family levels for

macroinfauna families at J-II-A389.

7-46
effects were noticeable at all platforms at the species level for nematodes

(Figures 7.11 to 7.13). The macroinfauna species data exhibited the same

trends as the meiofauna species data. Platform differences were obvious at

the species level, but not as clear at the family level (Figure 7.14). Distance

differences could not be easily discerned at the family level at any of the

sites (Figure 7.15 to 7.17). The conclusion from this exercise is that

analyses of benthic data at the family level should be done with caution and

may not be generally applicable. Information is lost and may not be adequate

to describe among platform differences and differences among distances

from platforms. The most promising groups for higher taxa analysis are

nematode and macroinfauna Families. However, it should be kept in mind

that, in general, the contaminant exposure at the three sites studied is

considered to be low and therefore the dynamic range of the indicators may

not be fully realized at these sites.

7.3 Megafaunal, Epibenthic Organisms as Indicators of Biological Response

Megafaunal community studies offer a range of indications of impact

based on reproductive effort, community structure, and life history. While

infauna were an obvious choice for contaminant, toxicological, and

histopathological techniques, an inability to harvest sufficient biomass to

satisfy methodological needs limited the use of macroinfauna as target

organisms. The use of megafauna as primary target organisms for these

work elements resulted in large part from the realities of field sampling.

Boxcormg as a technique for biomass harvesting was abandoned early in the

program because of the small amounts of biomass recovered. Low recoveries

were due to low biomass densities and difficult identifications. Collection of

megafauna by trawls thus became the focus of many of the Near/Far work

elements as organisms that could be collected in sufficient quantity for

biomass intensive techniques.

The selection of mobile megafauna (epifauna) as target organisms for

study, entails consideration of a variety of influences on biological patterns

that are not as important for benthic-based responses. Site loyalty,

avoidance, range, abffity to detoxify and depurate, and other issues tend to

complicate an interpretation of megafaunal pattern as indicators of exposure.

A near/far comparison design may not be appropriate for studies of fish in

7-47
that the same population may be sampled on the spatial scale of the present

study design (1000's of meters). However, other evidence suggests that

megafaunal invertebrate populations may maintain their integrity over

appropriate time spans and spatial scales to reflect exposure to sediment

contaminants. The degree to which sedimentary contaminants and

epibenthic animals are coupled is still unclear and undoubtedly varies among

megafaunal species depending on feeding habits and ecological niche. Field

observations also need to be carefully evaluated in the context of responses

established in controlled laboratory and/or field exposure experiments.

7.4 Testing the Generality of the Observed Patterns

It is important to realize that the results reported here are only valid

for the three sites studied. Two of the sites are somewhat anomalous in that

drilling discharges were shunted near the seabottom to protect nearby

topographic features. Also, due to other prescribed site requirements, the

study sites are limited to gas production facilities. Therefore, extrapolation

of findings to other platforms and settings must be carefully considered as

the sites chosen for this study were not intended to be typical or

representative of platforms in general. The sampling design described in

Section 2.0 was used throughout this report for hypothesis testing and

interpretation. The sampling design contained the following key

components: three (3) Platforms (if more than one Cruise is included), four

Cruises (times, at half-year intervals), five (5) Distances from platform

within Platforms [m some cases two (2) Distances, Near and Far], and five

Radii (directions) within each Platform leading to 300 observations (600

if pseudoreplicates are included). This sampling design is typical for pointsource pollution studies and incorporates intensive sampling around the

"point-source" (i.e., a platform) to describe the direction and distance

(spatial scale) of impacts in relation to the suspected origin of the

contaminants. This design assumes highest contamination, and thus, impact

would occur close to the source and diminish with distance away from the

source in a regular fashion. Inevitably, in allocating resources, there is a

trade-off between including more point-sources or increasing the intensity

of "oversampling" around each point-source.
Elucidating the pattern of impact (direction and distance) around a

point-source calls for a different approach than one designed to provide

generalizations about impacts from other similar point-sources. Requiring

that a study accomplish both objectives inevitably leads to compromises and

to sub-optimal designs. The present study design adequately describes

impact patterns around each of the three platforms studied. However, with

only three platforms, each of which is environmentally unique, it is not

possible to generalize about among-platform differences. Any attempt to

relate impact differences among platforms to production or environmental

differences among platforms, leads to a regression or correlation based on

only three data points (i.e., three sites). Even if a perfect rank correlation

between impact effect and contaminant intensity at a platform is apparent,

that perfect rank correlation would have a probability of 1-in-6 (0.17) of

occurring by chance. Typically 0.05 is required for a judgment of statistical

significance. Increasing the number of platforms to four provides a 1-in-24

probability of a chance correlation, or 0.04 and with five platforms a 1-in--

120 probability of a chance correlation, or 0.008. Therefore, the addition of

a few platforms greatly improves the power of the experiment to

differentiate differences and minimizes chance correlations. In the present

study, it also happens that the rank order of sites by contaminant levels is

also a perfect rank order by water depth and distance from shore as well as

all environmental variables that are related to these characteristics.

In other words, the present study design describes and tests the

spatial pattern of impact around these three platforms (i.e., platforms

treated as fixed-effect blocks, or strata, in the design), but there is little

ability to generalize to impacts caused by "platforms" as a generic class, or to

describe differences in platform effects caused by "kinds-of-platforms".

Three is simply too few platforms. If the platforms are thought of as a

sample of "platformns-of-a-kind" in the region, then three is too few and

these platforms are too different for any meaningful conclusion to be

reached about "platforms". If each of these three platforms is considered a

representative of a "platform-type" (i.e., contamination levels, water depth,

and distance from shore), then there is no replication within "platformtype" and nothing about impact differences among "platform-types" can be

tested.
To generalize, rather than describe distributions around a platform.

the number of platforms must be increased. Correspondingly the effort

allocated around each platform must necessarily decrease, given fixed

resources. For example, one could propose twelve (12) or more platforms

with sampling at Near and Far distances (50 m and 3000 m in the GOOMEX

Phase I study) along one radius in one direction (preferably the direction of

the maximum contaminant gradient). This provides a paired design, in

which the "Near vs. Far" difference would be tested based on a sample of n

12 platforms. The frequency of sampling and selection of the response

variables to be monitored would be optimized based on previous experience.

GOOMEX Phase I provides the data to support an informed choice of study

design elements for implementation in Phase II studies. The procedure for

selecting platforms is critical. A region must be defined a priori and

objective criteria for a type of platform (or two or three types of platforms)

must be stated. Then all platforms of that type in the region to be studied

must be enumerated, and the ones to be included in the study must be

selected randomly from those enumerated.

Various concerns influence the number of platforms chosen. Twelve

(12) or more platforms are suggested for two reasons. First, robustness of

statistical tests can be assured by having at least 10 error degrees of

freedom (df) for the tests. The error for most tests in this design is the

among-platform variation in the Near vs. Far difference, and the error

degrees of freedom (dfl will be the number of platforms less one (or if there

is more than one type of platform it will be the number of "platform types"

times one less than the number of platforms of each type). Second, power

in tests (ability to detect significant differences) increases with sample size

(number of platforms). Simulations with specified mean Near vs. Far

differences and standard deviations for those differences indicate that

power initially increases rapidly with the number of platforms but then

begins to be less sensitive to increasing numbers of platforms at an n of 10

to 12.

If continuing studies are to have a dual purpose, requiring a

compromise design capable of (a) elucidating patterns of impact around

platforms (such as developing and evaluating new response variables) and (b)

generalizing about impacts to platforms in a region, then the most effective

design will be paired platforms with n 12 for the generality tests, with one

7-50
or more of the platforms (or a platform pair) dedicated to intensive spatial

pattern sampling and method development.

7.5 Heterogeneity of Variance as an Impact Response

It is usual to formulate response variables for impact studies in terms

of mean values of contaminant concentrations, taxa abundances, etc.

However, variances as well as means respond to impacts. The response is

usually "patchy" since the small-scale spatial distribution of the impact (e.g.,

the contaminants) is rarely uniform. This is visually obvious in intertidal

areas after an oil spill. An increased variance among small-scale spatial

replicate samples (cores, quadrants) is the result. This is most often

observed in the data when the data are examined to see whether the

assumptions for Analysis of Variance (ANOVA) are satisfied since one of the

ANOVA assumptions is "homogeneity of error variance." Many

environmental scientists focus on a concern about this ANOVA assumption

for testing whether means differ, without realizing that such variance

heterogeneity can itself be evidence of impact. Green (1 993a,b) discusses

this question, and Underwood (1993) describes an ANOVA design that

incorporates a test of impact-driven variation.

Small-spatial-scale variance in the present study is the "between

subcores within boxcores" variance. Because there is only one boxcore per

station, the variance among boxcores cannot be used. That variance would

include variation attributable to predictors in the model, e.g., among radii.

The transformed scale (e.g., logarithmic for most response variables) is the

appropriate scale for measuring the response, i.e., if percent variation is

appropriate for the evaluation of response mean values then it will also be

appropriate for evaluation of the magnitude of variance. If it is concluded

that variance of contaminant concentrations is higher near a platform

(where contaminant mean concentration is higher), it must be clear that the

relationship between the error variance and the mean, which always exists

in (untransformed) data reflecting percent variation, is not the cause of the

trends observed. Response variable data is typically log-transformed. The

PC scores used to represent the contaminant gradient are calculated from a

linear additive function of appropriately transformed variables, so ChemPC 1

as a synthetic variable is also being measured on the appropriate scale.

7-51
J3etween-subcore within-boxcore variance was estimated for each

distance, pooled over Platforms and Cruises, on the appropriate response

scale, for barium, cadmium, ChemPCl, nematode abundance (NEMA),

harpacticoid abundance (HARP), and nematode/harpacticoid copepod (N/C)

ratio. Macroinfauna data was not used because it is likely that the withinboxcore spatial scale is too small for assessment of macroinfauna patchiness.

Using these variance estimates as the response variables in among-distances

ANOVAs, significant k 0.01) heterogeneity of variance was found for barium

(Ba), cadmium (Cd), and ChemPCl, but not for nematode (NEMA) and

harpacticoid (HARP) abundances (p> 0.05). For the N/C ratio heterogeneity

of variance was significant at p < 0.05. Because of concern about the

distributional properties of the estimated variances used as ANOVA response

variables, ANOVA were repeated as nonparametric ANOVA (Kruskal-Wallis

tests of medians). The significances and non-significances were unchanged.

The estimated median variance for each distance, for these six variables, is

summarized in Table 7.5. For the four variables, with significant

heterogeneity of variance, the pattern is one of increased variance near the

platform. The variances vs. distance relationship for the variables is

ifiustrated in Figure 7.18.

Table 7.5. Summary of heterogeneity of variance.

These results provide additional evidence for platform-derived

impacts. The pattern for barium (Ba), cadmium (Cd), ChemPCl and N/C

suggests that the impact reaches to 200-rn distance from the platform. The

absence of heterogeneity of variance for the two meiofaunal taxa taken by

themselves contrasts with the heterogeneity of variance for the N/C ratio.

This provides additional support for the use of a "ratio of a tolerant-to-asensitive taxa" as an indicator of biological impact.

Median between-subcore variance

D Cd PCi Ba Nema Harp N/C

50m .0491 .0119 .0039 .0770 .0822 .0870

lOOm .0245 .0115 .0021 .0566 .0793 .1184

200m .0167 .0057 .0029 .0940 .0931 .0628

500m .0043 0044 .0010 .0293 .0770 .0463

3000 m .0046 .0033 .0009 .0406 .0543 .04.42
Figure 7.18. MedIan variance of selected variables between subcores within a boxcore b

from the platform.
7.6 Genetic Variabffity as a Measure of Impact

Comparing population genetic variability may be a useful approach to

identifying sublethal, chronic impacts that occur as a result of environmental

disturbance. This approach has several advantages over traditional means of

assessing sublethal impacts. The genetic diversity approach produces

interpretable results that are not dependent upon the species selected or

the location and time of sampling. Unlike approaches which measure the

induction of protein products, a phenotypic response, the genetic variability

approach depends upon changes in DNA sequence, a genotypic response.

Unlike macroinfaunal abundance and diversity studies, estimating genetic

diversity does not require an extensive knowledge of taxonomy or tedious

visual sorting. Molecular techniques, in general, are experiencing an

enormous growth at the present time. Molecular-based methods should

continue to become increasingly automated, inexpensive, and do-able

without extensive training in molecular biology. The genetic variability

approach is especially well suited for use with meiofauna, because meiofauna

are easy to sample and show sensitivity to a variety of environmental

changes. However, this approach may also be applicable to a wide variety of

target organisms. Estimation of genetic variability for environmental

monitoring purposes still requires extensive development, including an

appropriate interpretation of results. However, the ability to link

environmental disturbance to changes at the DNA level should eventually

become a powerful tool for detection and monitoring sublethal effects and

merit further investigation.

7.7 Recommendations for Future Studies

The results obtained during Phase I of the GOOMEX Program set the

stage for advancement toward the longer term goal which is to develop and

implement effective monitoring and management strategies for offshore

oil/gas platforms. Phase I was designed as a broad-ranging program of

measurements of a suite of independent environmental variables coupled

with a diverse suite of suspected dependent indicators of biological response

or impact. As such, Phase I results have lead to a series of revised

hypotheses requiring further study during Phase II. Mechanistic

7-54
explanations for the patterns that have emerged during Phase I are needed

to support informed management decisions. A combination of study designs

will be required to effectively address the multiple goals that will be

important in the next phase of the GOOMEX program. Tests of the

generality of the patterns observed, continued development of promising

Phase I indicators, introduction and testing of new potential indicators,

laboratory verification of cause and effect relationships, and in-field testing

and verification of laboratory results (including manipulative experiments)

should be pursued during the next phase of study (Table 7.6)

The proof of generality of the observed trends is important to the

implementation of comprehensive and effective monitoring programs As

discussed, a test of the observed patterns at a series of "typical" and/or

"representative" platform sites is necessary to assess generality. The

features that effectively describe and determine the character of a platform

and its site must be carefully delineated. Study sites must then be chosen

based on these characteristics and a sampling design of appropriate power

devised. The importance of a variety of platform attributes will need to be

tested (i.e., discharge history, including produced waters; water depth;

duration of drilling; volume and composition of muds and cuttings

discharged; oil vs. gas production; etc.). One critical generality issue is

whether dfferences related to the type of production, oil or gas, exist and

do monitoring programs need to be tailored to production characteristics.

The sites studied here included only platforms producing gas and very little

liquid hydrocarbons. Production of liquid hydrocarbons (oil and condensate)

may imply differing intensities or types of discharges, and thus chronic

exposures, if increased contamination is associated with oil platforms. To

evaluate the consequences of the type of production, further studies should

include oil-producing platforms.

Another important question to be answered is what role does the

simple presence of the platform structure itself play as opposed to chronic

effects associated with contaminant release and accumulation? This test

could be accomplished through a comparison of decommissioned sites with

and without platforms. This question has important practical implications

for management since there is an option of retaining or removing platforms

at the termination of a production site. Another effective test would be to
Table 7.6 Summary of recommendations for further study at platform sites.

Work Element Recommendations

Physicochemical 'Provide a synoptic view of each site to more fully delineate platform related effects on water column oxygen and nutrient conditions and thus organic enrichment.

Sedimentology 'Provide a mass balance of the sediments based on origins

(cuttings, in situ sand, ten-igenous materials, etc.), not

just particle size or bulk chemistry.

'Discontinue x-ray diffraction

Contaminant Chemistry 'Chemistry must be closely coupled with biological effects

studies (no baselines or surveys).

'Provide an integrated concentration/area or volume

estimation of the contaminant field to various,

appropriate depths (0-2 cm, 0-10 cm).

'Define bloavailable contaminants more effectively - pore water chemistry must be carefully and accurately defined

especially for metals with particular reference to redox

conditions and speciation.

'To truly understand the chemistry of contaminants, flux

measurements may be needed based on porewater proffles and benthie chamber data.

Macroinfauna 'Target the most useful and sensitive indicator species for enumeration.

'Develop and apply reproductive effort, life history, and other studies analogous to the meio and megafaunal work

efforts (targeted at specific species).

'Investigate the utility of genetic diversity studies.

Megafauna Invertebrates 'Concentrate on a few abundant species especially for bistopathology

'Closely couple with contaminant measurements of more

appropriate tissues (i.e., eggs).

'Genetic diversity

'Institute transplanted animal experiments to constrain

their range and thus exposure.

'Extend reproduction studies to egg quality.

Megafauna fish 'Discontinue food studies.

'Discontinue histopathology.

7-56

Meiofauna 'Target the most useful and sensitive indicators of impact such as barpacticoid diversity.

'Measure the temporal distribution of nematodes (e.g., for one year) to more accurately predict long-term changes in population.

'Pursue genetic diversity studies in situ and in the lab by

simulating exposure scenarios on appropriate time

frames.
Work Element Recommendations

Detoxification

Pore Water Toxicity Bioassays

Study Design

Table 7.6 (Cont.)

*Emphase toxic responses to trace metals (i.e., metaflothioneins).

sExtend in vitro assays to a more comprehensive testing of

invertebrates in coordination with contaminant

measurements and pore water toxicity testing. zFoCus studies intensively on a few of the more

appropriate species.

*Pursue invertebrate bloindicators of exposure zEvaluate other potential biomarkers of contamination

such as heat shock proteins.

zintegrate laboratory studies with in-field exposures

(transplanted animal experiments) to define the dyrianiic

range of the indicators.

zAdditional standard bloassays for comparison including whole sediment.

4Monitor contaminant concentrations during the assays and in situ to more effectively delineate the causative

agents.

4Coordinate bioassays of animals with in vitro

toxicological assays.

sDeslgn dosing experiments to develop cause and toxic effects linkages in the laboratory. zTest generality of observed trends.

sDevelop a more comprehensive sediment quality model incorporating more extensive toxicological and bioassay

results.

zExpand the surveys to oil platforms.

sconsider discarding the radial pattern and utilize a

evenly spaced grid approach.

sDevelop a fully integrated model of response which will ultimately provide a plan for actual monitoring

programs.

study structures that have had no drilling activities or associated discharges.

This might be include gathering facffities or other large offshore structures.

The covariance of important environmental variables prevents

definitive testing of causation by field observations alone. One means of

decoupling these variables to assess their independent and joint effects

would be to perform various in situ manipulative experiments including

sediment settlement trays and caged animals. Biological responses can be

assessed by evaluating differences in the community structure of

macroinfauna and meiofauna that colonize settlement trays. This is

especially useful in decoupling toxic contaminant effects from variations in

sand content. Settlement trays have been successfully used in benthic

7-57
ecology and could be effectively adapted for use in marine setting. Caged

animal experiments would assure that animals remain in a known

contaminant exposure regime by limiting spatia:1 movements. Uptake of

contaminants and the resultant biological effects on indicators of exposure

would be more directly assessed than with field collections alone. Other

observed responses could be simulated in time-frames compatible with

controlled laboratory exposures (i.e., genetic variability in melofauna).

The speciation and biological availability of metals is an other

important issue. Much of the bulk metals detected may be present in

relatively inert forms. Redox conditions, metal speciation, and bioavailability

need to be more adequately assessed. Dissolved contaminant levels in pore

water provide a more direct indicator of the toxic components. There is a

growing consensus that dissolved metal more closely approximate the

bioavailable fraction of a particular metal than does total recoverable metal

(Prothro 1993). Measurements of water-borne contaminants must be done

using clean chemistry methodologies (U.S. EPA 1994a.b). Careful sampling

and sample storage is a necessity to provide reliable data. The low

concentrations and the possibility of contamination during sampling,

storage, and analysis require stringent sampling and analytical procedures to

obtain consistent and accurate data. It is also clear that further bioassays,

such as pore water toxicity testing, need to be closely coupled with high

quality chemical measurements to delineate the exact agents responsthle for

organismal response. Proper sampling and monitoring of contaminant

chemistries during assays is essential to relate laboratory observations to

field conditions and to assure that the observed toxtcities are not an artifact

of sample handling and/or treatment.

The inclusion of sublethal biological indicators sensitive to trace

metals in Phase II is important since metals have been identified as a likely

cause of toxic response. The most commonly used biological indicator of

metal exposure is a family of low-molecular weight cysteine-rich metal

binding proteins and oligopeptides known as metallothioneins (MT). The

cysteinyl residues function as ligands for the chelation of metals by MT.

Additionally, MT are inducible and their synthesis can be activated by

exposure to metals such as Cd, Cu, Zn, Hg, Co. Ni, Ba, and Ag (Engel and

Brouwer 1989; Bracken and Klaassen 1987). MT are thought to serve a

protective function by binding and thereby limiting the intracellular

7-58
concentration of reactive heavy metals and reducing their potential for

toxicity. In addition to metai exposure, levels of MT are sensitive to a variety

of natural factors including temperature, activity, reproductive cycle, season,

growth, molt cycle, tissue regeneration, food type and habitat (Oh et al.

1978; Engel 1988). Cu and Zn bound to MT are particularly prone to

endogenous factors; whereas, non-essential metals such as Hg, Ag, and Cd

are less likely to be confounded by natural sources of variation. Numerous

studies have correlated the levels of metals bound to MT with elevated metal

concentrations (Roesijadi 1981; Hamilton and Mehrle 1986; Roch and

McCarter 1984; Talbot and Magee 1978; Langston and Zhou 1986; Hylland

et al. 1992). Although MT induction can be confounded by numerous factors

other than metals, data has indicated that MT can be useful indicators of

environmental levels of metals.

The importance of hypoxic events in response to organic enrichment

associated with the "reef effect" of a platform can only be evaluated through

process-oriented studies. These studies would need to establish the flux of

materials to the sediments and the concomitant remineralization and

release of nutrients from the sediments to the overlying water. The flux of

materials (both organic debris and contaminants) as a function of distance

from the platform must be known in order to evaluate the importance of

organic enrichment (reef effect) as well as providing further evidence that

some contaminants are accumulating with time. A combination of benthic

chambers, sediment traps, and pore water profiles should be used to

determine the operative processes that control redox conditions and metal

speciatlon in sediments and ultimately orgartismal exposure and response.

Another important set of processes related to material fluxes need to

be more fully elucidated, that is the role and function of bacteria in the

sediments near platforms. Sedimentary microbial ecology is directly linked

to organic enrichment and mediates oxygen depletion, nutrient

remineralization, and contaminant degradation. Microbial activity needs to

be evaluated by substrate type so that hydrocarbon-degrading and sulfate

reduction rates can be measured to assess the degradation of a variety of

organic substrates. Hydrocarbons role as a source of labile organic carbon

needs to be evaluated further. Hydrocarbon inputs may be rendered

relatively innocuous by rapid rates of microbial degradation. The ability and
capacity of the system to respond to continued chronic inputs of

contaminants is an important characteristic to evaluate.

Several continuing areas of investigation utilizing megafaunal

invertebrates including many commercially important species, may prove

fruitful. Basic principals suggest that megafaunal invertebrates fecundity,

egg viability, growth and survival should decline if a population is impacted.

On the other hand, prevalence and intensity of parasitism and disease

should increase in impacted areas. A more comprehensive test of these

potential responses in megafauna can only be properly tested at a series of

platforms with differing contaminant exposure regimes. Phase I results have

demonstrated a high degree of natural variability resulting in site specific

megafaunal community characteristics. While no generalities were apparent

from the Phase I studies, significant variations in megafaunal population

structure and dynamics were documented. The mobility of higher-level

consumers megafauna makes the use of physiological effects as indicators of

exposure difficult to interpret if field collections alone are used. Therefore

as an adjunct to the in situ field observations, exposures of test organisms in

cages at platform sites are needed to test whether contaminants at a site are

inducing physiological responses. Experimental exposure of indigenous

suspension-feeding bivalves (scallops perhaps) would provide additional

information on the physiological responses to long-term exposure.

In summazy, refinement of our understanding of the patterns observed

in the Phase I study, including establishment of cause and effect

relationships, can only be accomplished through coordinated, processoriented studies. As a first critical step, revised hypotheses must be clearly

defined and stated. Secondly, appropriate statistical designs for sampling

must be devised that provide for meaningful interpretations of

programmatic results. Thirdly, as mentioned above, the selection of

appropriate sites for each study design is critical, recognizing that any one

site may (and probably will) not satisfy all work element goals and that a

series of sites targeted for specific studies may be the optimal design given

the potentially conflicting goals within a comprehensive follow-on study. If a

series of sites are chosen, that are not common across all work elements, a

core of key measurements must be collected in order to provide for the

broadest interpretation of the resultant data. The next phase of studies will

greatly enhance the scientific basis for promulgation and implementation of

7-60
meaningful, and cost-effective monitoring arid management guidelines for

the long-term emplacement and operation of offshore platform facilities.
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The Department of the Interior Mission

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