NOAA Technical Memorandum NOS OMA 45 s %rES o* ^ AN EVALUATION OF CANDIDATE MEASURES OF BIOLOGICAL EFFECTS FOR THE NATIONAL STATUS AND TRENDS PROGRAM Seattle, Washington April 1989 noaa NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION a? Id "A National Ocean Service DOCUMENT LIBRARY Woods Hole Oceanographic Institution Office of Oceanography and Marine Assessment National Ocean Service National Oceanic and Atmospheric Administration U.S. Department of Commerce The Office of Oceanography and Marine Assessment (OMA) provides decisionmakers comprehensive, scientific information on characteristics of the oceans, coastal areas, and estuaries of the USA. The information ranges from strategic, national assessments of coastal and estuarine environmental quality to real-time information for navigation or hazardous materials spill response. For example, OMA monitors the rise and fall of water levels at about 200 coastal locations of the USA (including the Great Lakes); predicts the times and heights of high and low tides; and provides information critical to national defense, safe navigation, marine boundary determination, environmental management, and coastal engineering. Currently, OMA is installing the Next Generation Water Level Measurement System that will replace by 1992 exisiting water level measurement and data processing technologies. Through its National Status and Trends Program, OMA uses uniform techniques to monitor toxic chemical contamination of bottom-feeding fish, mussels and oysters, and sediments at about 150 locations throughout the USA. A related OMA program of directed research examines the relationships between contaminant exposure and indicators of biological responses in fish and shellfish. OMA uses computer-based circulation models and innovative measurement technologies to develop new information products, including real-time circulation data, circulation fore- casts under various meteorological conditions, and circulation data atlases. OMA provides critical scientific support to the U.S. Coast Guard during spills of oil or hazardous materials into marine or estuarine environments. This support includes spill trajectory predictions, chemical hazard analyses, and assessments of the sensitivity of marine and estuarine environments to spills. The program provides similar support to the U.S. Environmental Protection Agency's Superfund Program during emergency responses at, and for the cleanup of, abandoned hazardous waste sites in coastal areas. To fulfill the responsibilities of the Secretary of Commerce as a trustee for living marine resources, OMA conducts comprehensive assessments of damages to coastal and marine resources from discharges of oil and hazardous materials. OMA collects, synthesizes, and distributes information on the use of the coastal and oceanic resources of the USA to identify compatibilities and conflicts and to determine research needs and priorities. It conducts comprehensive, strategic assessments of multiple resource uses in coastal, estuarine, and oceanic areas for decisionmaking by NOAA, other Federal agencies, state agencies, Congress, industry, and public interest groups. It publishes a series of thematic data atlases on major regions of the U.S. Exclusive Economic Zone and on selected characteristics of major U.S. estuaries. It also manages, for the U.S. Department of the Interior, a program of environmental assessments of the effects of oil and gas devel- opment on the Alaskan outer continental shelf. OMA implements NOAA responsibilities under Title II of the Marine Protection, J Research, and Sanctuaries Act of 1972; Section 6 of the National Ocean Pollution ^ Planning Act of 1978; and other Federal laws. It has three major line organizations: g__ The Physical Oceanography Division, the Ocean Assessments Division, and the ^^^n Ocean Systems Division. g m ru 3" □ m NOAA Technical Memorandum NOS OMA 45 AN EVALUATION OF CANDIDATE MEASURES OF BIOLOGICAL EFFECTS FOR THE NATIONAL STATUS AND TRENDS PROGRAM Edward R. Long and Michael F. Buchman Seattle, Washington April 1989 DOCUMENT LIBRARY Woods Hole Oceanographic Institution United States Department of Commerce Robert A. Mosbacher Secretary National Oceanic and Atmospheric Administration William Evans Deputy Administrator National Ocean Service John Carey Acting Assistant Administrator for Ocean Services and Coastal Zone Management Coastal and Estuarine Assessment Branch Ocean Assessments Division Office of Oceanography and Marine Assessment National Ocean Service National Oceanic and Atmospheric Administration U.S. Department of Commerce Rockville, Maryland NOTICE This report has been reviewed by the National Ocean Service of the National Oceanic and Atmospheric Administration (NOAA) and approved for publication. Such approval does not signify that the contents of this report necessarily represent the official position of NOAA or of the Government of the United States, nor does mention of trade names or commercial products constitute endorsement or recommendation for their use. AN EVALUATION OF CANDIDATE MEASURES OF BIOLOGICAL EFFECTS FOR THE NATIONAL STATUS AND TRENDS PROGRAM Edward R. Long, Michael F. Buchman Pacific Office, Ocean Assessments Division, National Oceanic and Atmospheric Administration 7600 Sand Point Way Northeast Seattle, WA. 98115 CONTRIBUTORS: Arthur M. Barnett Marine Ecological Consultants 531 Encinitas Boulevard, Suite 110 Encinitas, CA 92024 Steven M. Bay, Jeffrey N. Cross Southern California Coastal Water Research Project 646 West Pacific Coast Highway Long Beach, CA. 90806 Ronald J. Breteler Springborn Life Sciences, Inc. 790 Main Street Wareham, MA. 02571 R. Scott Carr Battelle Dept. of Ocean Sciences and Technology 397 Washington Street Duxbury, MA. 02332 Peter M. Chapman r* \t o r* 1« — •- ERRATA FOR TECHNICAL MEMORANDUM NOA OMA 45 AN EVALUATION OF CANDIDATE MEASURES OF BIOLOGICAL EFFECTS FOR THE NATIONAL STATUS AND TRENDS PROGRAM Reference to Table 25 in second paragraph on page 41 should be Table 14. Reference to Table 10 in first and second paragraphs on page 44 should be Table 17. Robert B. Spies Environmental Sciences Division Lawrence Livermore National Laboratory Livermore, CA 94550 John J. Stegeman Department of Biology Woods Hole Oceanographic Institution Woods Hole, MA 02543 Douglas A. Wolfe Ocean Assessments Division National Oceanic and Atmospheric Administration 11400 Rockville Pike Rockville, MD 20852 Coastal and Estuarine Assessment Branch Ocean Assessments Division Office of Oceanography and Marine Assessment National Ocean Service National Oceanic and Atmospheric Administration U.S. Department of Commerce Rockville, Maryland NOTICE This report has been reviewed by the National Ocean Service of the National Oceanic and Atmospheric Administration (NOAA) and approved for publication. Such approval does not signify that the contents of this report necessarily represent the official position of NOAA or of the Government of the United States, nor does mention of trade names or commercial products constitute endorsement or recommendation for their use. AN EVALUATION OF CANDIDATE MEASURES OF BIOLOGICAL EFFECTS FOR THE NATIONAL STATUS AND TRENDS PROGRAM Edward R. Long, Michael F. Buchman Pacific Office, Ocean Assessments Division, National Oceanic and Atmospheric Administration 7600 Sand Point Way Northeast Seattle, WA. 98115 CONTRIBUTORS: Arthur M. Barnett Marine Ecological Consultants 531 Encinitas Boulevard, Suite 110 Encinitas, CA 92024 Steven M. Bay, Jeffrey N. Cross Southern California Coastal Water Research Project 646 West Pacific Coast Highway Long Beach, CA. 90806 Ronald J. Breteler Springborn Life Sciences, Inc. 790 Main Street Wareham, MA. 02571 R. Scott Carr Battelle Dept. of Ocean Sciences and Technology 397 Washington Street Duxbury, MA. 02332 Peter M. Chapman E.V.S. Consultants 195 Pemberton Avenue North Vancouver, British Columbia, Canada V7P 2R4 Jo Ellen Hose Occidental College Los Angeles, C A. 90041 Andrew L. Lissner Science Applications International Corporation 4224 Campus Point Ct., San Diego, CA. 92121 Donald C. Rhoads Science Applications International Corporation Admiral's Gate 221 Third Street Newport, RI 02840 John Scott Science Applications International Corporation c/o U.S. EPA South Ferry Road Narragansett, RI 02882 Robert B. Spies Environmental Sciences Division Lawrence Livermore National Laboratory Livermore, CA 94550 John J. Stegeman Department of Biology Woods Hole Oceanographic Institution Woods Hole, MA 02543 Douglas A. Wolfe Ocean Assessments Division National Oceanic and Atmospheric Administration 11400 Rockville Pike Rockville, MD 20852 CONTENTS PAGE ACKNOWLEDGMENTS vi EXECUTIVE SUMMARY v INTRODUCTION 1 APPPROACH l METHODS 6 RESULTS 30 DISCUSSION AND CONCLUSIONS 79 RECOMMENDATIONS 95 REFERENCES " APPENDIX A. Sediment Toxicity Test Data A-l APPENDIX B. Sediment Physical and Chemical Data B-l APPENDIX C. Measures of effects data for P. stellatus C-l APPENDIX D. Chemical Data (ug/kg wet weight) for P. stellatus D-l APPENDIX E. Chemical Data (ug/kg lipid weight) for P. stellatus E-l ACKNOWLEDGMENTS Mr. Rick Wright and Mr. Nick Rottunda (SAIC) collected the sediment and benthos samples. Dr. David Rice, Jr. (LLNL) performed chemical analyses of the fish. Dr. Peter Thomas (University of Texas) performed hormone analyses of fish plasma. Dr. Loveday Conquest (University of Washington) provided advice on statistical methods for data analyses. Mr. Kirk Van Ness (NOAA) assisted in sampling site selection. Ms. Charlene Swartzell (NOAA) typed the manuscript and revised it innumerable times. CDR Stewart McGee (NOAA) assisted in arranging vessel logistics. The following performed the chemical analyses of sediments at SAIC: Dr. James Payne, Dr. John Clayton, Mr. Gary Farmer, Mr. Dan McNabb, Mr. Mike Guttman (organics); and Mr. R. Sims (trace metals). Ms. Roxanne Rousseau and Mr. Ian Watson (E.V.S. Consultants) assisted in the performance of the tests with Rhepoxynius and Mytilus. Mr. Darrin Greenstein, Ms. Karen Rosenthal, and Ms. Valerie Raco (SCCWRP) assisted in conducting tests with Strongylocentrotus. Ms. Susan Shepard and Ms. Michele Redmond helped conduct the tests with Ampelisca. Mr. John Williams and Mr. Carlos T. B. Frigata (Battelle Ocean Sciences Division) helped perform tests with Dinophilus. Ms. Susan Garner, Mr. Lawrence Lovell, Ms. Susan Watts, and Ms. Janice Callahan (MEC) conducted various tasks in the taxonomic analyses of benthic samples. Mr. Eugene Revelas and Drs. Joseph Germano and Robert Merten (SAIC) assisted in the performance of the sediment profiling survey of San Francisco Bay. Dr. Howard Harris (NOAA) provided helpful comments on an initial draft of the manuscript. EXECUTIVE SUMMARY An evaluation of the response and sensitivity of candidate measures of biological effects to a range in contaminant concentrations was performed in the San Francisco Bay area in 1987. The evaluation was performed to determine which, if any, of the candidate measures may be useful in the National Status and Trends (NS&T) Program of the National Oceanic and Atmospheric Administration (NOAA). The NS&T Program analyzes three media— sediments, bottomfish, and bivalves— routinely at sites nationwide. The present evaluation included biological tests of two of those media: sediments and fish. The overall approach chosen for the evaluation involved analyses of samples collected in the field at sites that were presumed to represent a range in chemical contamination. The biological tests were performed with subsamples of samples that were also analyzed for chemical concentrations. All the tests were performed "blind," i.e., without knowledge of the origin of the samples. Data from the various biological tests were then compared with each other and with the chemical data in various statistical procedures. It was presumed and hypothesized before the evaluation begarT^hat biological tests most applicable to the NS&T Program would be those that were able to indicate differences among sampling locations over a range in chemical contamination and/or between sampling locations and laboratory controls, had relatively large ranges in response among mean values for the sampling locations, had relatively small analytical errors, and indicated patterns in biological response that generally paralleled the pattern in chemical contamination. The relative sensitivity, analytical precision, discriminatory power, and concordance among end-points and with sediment chemistry were compared among multiple end-points of five types of sediment toxicity tests. The tests were performed with aliquots of 15 composited, homogenized samples collected in San Francisco Bay and Tomales Bay, California. Each sample was also tested for trace metal and organic compound concentration, organic carbon content, and texture. The end-points evaluated were: survival and avoidance of solid phase sediments by the amphipods Rhepoxynius abronius and Ampelisca abdita; survival and abnormal development in the embryos of the mussel Mytilus edulis exposed to elutriates; fertilization success, abnormal development, echinochrome pigment content, incidences of abnormal mitotic division, micronuclei, cytological abnormalities and mitoses per embryo in the embryos of the urchin Strongylocentrotus purpuratus exposed to elutriates; and survival and egg production in the polychaete Dinophilus gyrociliatus exposed to interstitial (pore) water. Among the end-points evaluated, abnormal development of M. edulis embryos was the most sensitive to the samples relative to controls and had the highest precision and discriminatory power. Survival of R. abronius was the second most sensitive and also had a high range in response and discriminatory power. The results of both end-points (along with those of M. edulis survival), however, were more highly correlated with sedimentological variables than with the concentrations of chemical contaminants. The end-point of A. abdita survival had relatively high analytical precision, moderate discriminatory power and was relatively highly correlated with several chemicals, but had comparatively low sensitivity relative to controls. Abnormal development and echinochrome content in S. purpuratus had relatively high precision and results were relatively highly correlated with several chemicals, but discriminatory power was moderate and the abnormal development results contradicted those of many of the other end-points. Several of the cytological/cytogenetic end-points of this test measured in only five samples indicated a wide range in response and strong correlations with chemical data, but precision was relatively low. The test of D. gyrociliatus egg production was intermediate in sensitivity, had relatively low precision and discriminatory power, and was highly correlated with several organic chemical groups. The results of this pore water test were not highly correlated with those of the solid phase and elutriate tests. The authors conclude that, since different toxicological mechanisms may occur in the responses of organisms to complex media such as sediments, multiple toxicity tests are needed to comprehensively assess the quality of marine sediments. Analyses of benthic communities were performed with two methods: "traditional" taxonomic analyses of animals collected with a grab sampler and retained on a 1-millimeter (mm) screen; and analyses of horizontal sediment profiling photographs taken with a remotely operated camera. The taxonomic analyses showed that the benthos were very similar among the three stations sampled at each site, but quite distinct among the sites. Total abundance, species richness, measures of total biomass, and indices of dominance and species diversity all indicated significant differences among sites. Molluscs were dominant at one site, polychaetes at another (the reference site), and crustaceans were dominant at two others. No data are available thus far for the most contaminated site. The major differences in benthos composition among sites could be attributable to "natural" types of stress such as periods of lowered salinity or scouring, as well as to differences in chemical contamination. A survey of 69 sites in the San Francisco Bay estuary was performed with a sediment profiling camera. A variety of sedimentological and biological parameters was recorded during analyses of the photographs. There were 4 of the 69 sites which corresponded with those sampled for bioassays, benthos, and chemical analyses. Signs of sediment organic enrichment or anoxia were recorded at very few of the sites. Some sites in the peripheral waterways of Redwood Creek, Oakland Inner Harbor, and Richmond Harbor showed indications of enriched sediments. Among the four sites sampled for toxicity, benthos, and chemical analyses the most contaminated site showed several indications of slightly elevated organic enrichment and contamination by bacterial indicators of sewage. The successional stage in benthic communities at that site, however, was not remarkably different from that at the other three sites. The sediment profiling photography technique provided data quickly on important characteristics of the surficial sediments. The starry flounder (Platichthys stellatus), a bottom-dwelling flatfish, was collected at six sites and tested for contamination of the tissues by chlorinated hydrocarbons and a variety of measures of the health of the fish. The biological measures included analyses of hepatic aryl hydrocarbon hydroxylase (AHH) activity, counts of micronucleated erythrocytes in the blood, analyses of steroid hormone content in the plasma, and analyses of the induction of the hepatic cytochrome P-450 enzyme system. All were performed on subsamples of the same fish. Fish were collected during two periods: November and December 1986 and January and February 1987. Fish caught in the latter period were spawned to also determine impaired reproductive success in addition to the other measures. Fish from two sites in San Francisco Bay were generally more contaminated with a mixture of compounds than those from a coastal reference site and a reference site in the Bay. However, the distinction in the chemical concentrations between sites was not as clear as with the sediments. The range in contaminant concentrations and the absolute values were not particularly high among the sampling sites for both fish and sediments. This observation corroborated the conditions that were anticipated, based upon previous knowledge of contamination of San Francisco Bay and vicinity. It was presumed that the sensitivity of various candidate measures of effects could be tested most accurately by sampling locations that would not be grossly contaminated (i.e., where even the least sensitive tests would indicate effects) and that would generally mimic conditions often encountered in the NS&T Program (which, thus far, has mostly avoided highly contaminated areas). The incidence of micronucleated erythrocytes in the fish was significantly lower in fish from the coastal reference site than in fish from most of the sites in San Francisco Bay. Incidences in fish among the sites in San Francisco Bay were not distinguishable. The measures of micronuclei formation (especially detached micronuclei) appear to be sensitive, applicable to several species, relatively high in between-site discriminatory power in some species, and correlated with the concentrations of organic compounds, but also are relatively highly variable among fish caught at the same site. Cytochrome "P-450E" content and ethoxyresorufin-O-deethylase (EROD) activities in the liver microsomes of the fish were significantly higher in fish from sites near urban centers than in fish from a coastal reference site. The suite of cytochrome P-450/EROD/P-450E measures appear to be sensitive, relatively low in within-site variability, relatively high in between-site discriminatory power, correlated with contaminant concentrations, and have indicated a similar pattern in response among species. Fish from the most contaminated sites often had the highest AHH activity, but differences between sites were not significant. Compared to the other measures performed with fish, the AHH activity analyses were less sensitive, had moderate within- site variability, had moderate between-site discriminatory power, but were correlated with chemical concentrations. Data from tests of plasma steroid hormone analyses did not show any significant differences among sites. Interpretation of the results of measures of impaired reproductive success in the fish was confounded by small sample sizes. Generally, there was good concordance between the biological measures and the data for some chemicals. Also, there generally was good, but not significant, concordance among the measures of cytochrome P-450 induction, AHH activity, and micronuclei incidence. It is apparent from this evaluation and previous use of the tests that most of the biological measures generally perform well and could qualify as candidates for future use in the NS&T Program. However, certain of the tests appear to better meet the criteria for inclusion in the Program. They include the tests of acute toxicity of sediments with bivalve larvae and amphipods; tests of mutagenicity/genotoxicity in echinoderm larvae exposed to sediments; AHH and EROD activities and cytochrome P-450 content in liver microsomes of fish; and counts of erythrocyte micronuclei in fish. The use of sediment photography profiling techniques is best suited for evaluations of organic enrichment of depositional sediments and assessments of recovery of disturbed benthic habitats. The pore water bioassay needs further testing and evaluation to fully develop this very promising technique. Plasma steroid hormone content in fish can be influenced by a wide variety of factors. The data gathered in the present evaluation did not indicate significiant differences between sites under the conditions extant at that time. Although tests of impairment of reproductive success through spawning studies have provided useful and pollution-sensitive information in research with P. stelktus and other bottomfish, they were difficult to evaluate in this study because of the small sample sizes. It is also apparent from this evaluation and that performed at the Group of Experts on the Effects of Pollutants (GEEP) workshop that no single measure of biological effects can suffice for determining the biological effects of pollution. The complexity and multitude of biological responses to contaminants cannot be expressed with any single test, just as the complex mixture of chemicals in most urban areas cannot be indicated with the quantification of any single chemical. A suite of complementary tests can be selected from those evaluated in this study and tailored to meet specific programmatic needs and used to assess the occurrence and severity of effects associated with elevated contaminant levels. Therefore, in order to maintain flexibility needed to satisfy various (unforeseen) programmatic objectives, all of the biological measures should be considered as potential candidates and none should be eliminated from future potential use. All have certain strengths and weakness that should be considered in selection of a suite of tests to meet specific objectives. INTRODUCTION The goal of the National Status and Trends (NS&T) Program is to determine the status of and trends in environmental quality of marine and estuarine areas of the United States. To satisfy that goal, NOAA has begun monitoring the concentration of selected, potentially toxic, chemical contaminants (e.g., NOAA, 1987). The NS&T Program is currently analyzing sediment samples from about 200 sites, bivalve samples from about 150 sites, and fish samples from 50 sites nationwide for chemical contaminants. Quantitative data are generated for a large suite of potentially toxic contaminants at each of these sites annually. The analyses, however, include only very limited tests of biological significance of the contaminants that are found in the test media. There are no standards with which to judge the biological relevance of the contaminant data from sediments, bivalves, and biota. Until such standards are developed and accepted, additional empirical evidence is needed to determine which sites are sufficiently contaminated to be of some biological concern. An evaluation of prospective measures of biological effects was initiated in San Francisco Bay in 1987 to determine the relative attributes or performance of selected tests that may be most useful in the NS&T Program. Those measures of effects that are most promising will be used on a broader scale as a part of the NS&T Program testing protocols. This report summarizes the results of that evaluation. APPROACH The overall approach taken was to solicit the scientific community for suggested measures of biological effects, select those candidates that best met specific programmatic criteria, and evaluate their performance over a range in contamination in a selected location. This approach was roughly analogous to that taken by the Group of Experts on the Effects of Pollutants (GEEP) of the Intergovernmental Oceanographic Commission (IOC) in a practical workshop on biological effects of contaminants held in Oslo, Norway in August, 1986 (Bayne et al, 1988). In that workshop, a wide variety of biological tests was evaluated, including some that were evaluated in this study. The relative sensitivities of a variety of animals for use in sediment toxicity tests have been evaluated in previous studies (e.g., Swartz et al. 1979; Williams et al, 1986; Chapman et ah, 1984; Chapman, 1987; Giesy et al, 1988). Acute mortality, measures of abnormal larval development, impaired physiological functions, altered behavior, and chromosomal damage were recorded in these previous evaluations of toxicity tests. Some tests evaluated in this study, notably the 10-d solid phase test with R. abronius (Swartz et al, 1985) and the 48-h elutriate test with bivalve embryos (Chapman and Morgan 1983), have been used in many regional assessments of sediment toxicity (e.g., Williams et al, 1986; Swartz et al, 1982; Chapman et al, 1987; Swartz et al, 1986). Some others are relatively new and had not been evaluated previously. The solicitation was issued in 1986 and required that suggested tests meet, as well as possible, eight criteria. Those criteria specified that the biological tests: (1) Include end-point(s) that is (are) of significance to the longevity (survival) or reproductive success of the organism(s); (2) Be usable in distinguishing spatial gradients among sampling sites and long-term trends at each site in effects of exposure to chemical contaminants; (3) Be sensitive indicators of exposure to mixtures of toxic chemicals; (4) Be of marine or estuarine organisms; (5) Be applicable throughout most of a broad biogeographic zone along any of the three U. S. coastlines; (6) Be relatively insensitive to natural environmental variables or include some means of accounting for the contributory influence of those variables; (7) Be feasible during all seasons, from a variety of vessels and operating conditions and in a variety of environments; and (8) Be inexpensive and feasible by more than one laboratory. The solicitation for proposals was issued by NOAA in 1986 and resulted in the submittal of 47 proposals. Eight of those were selected as best meeting the criteria. In addition, three other types of analyses were funded to support and augment the biological tests. In total, the following numerous tests and analyses were performed by the following contractors: (1) Collection and chemical analyses of surficial sediments (Battelle New England Ocean Sciences Division and Science Applications International Corporation (SAIC)); (2) Solid phase sediment toxicity test with the amphipod Rhepoxynius abronius (E.V.S. Consultants); (3) Solid phase sediment toxicity test with the amphipod Ampelisca abdita (Springborn-Life Sciences and SAIC); (4) Sediment elutriate toxicity test with the larvae of the mussel Mytilus edulis (E.V.S. Consultants); (5) Sediment elutriate toxicity test with the larvae of the sea urchins Strongylocentrotus purpuratus, S. droebachiensis, and Lytechinus pictus (Southern California Coastal Water Research Project (SCCWRP)); (6) Sediment pore water toxicity test with the polychaete Dinophilus gyrociliatus (Battelle New England Ocean Sciences Division); (7) Taxonomic analyses of benthic community structure (SAIC and Marine Ecological Consultants (MEC)); (8) Analyses of sedimentological and biological characteristics with sediment profiling photography (SAIC); (9) Fish collection, tissue chemical analyses, aryl hydrocarbon hydroxylase (AHH) analyses, (Lawrence Livermore National Laboratory (LLNL)) and plasma steroid hormone analyses (University of Texas); (10) Fish blood micronucleated erythrocyte analyses (SCCWRP); and (11) Fish liver cytochrome P-450 and ethoyresorufinn-O-deethylase (EROD) enzyme analyses (Woods Hole Oceanographic Institution (WHOD). Among the three media (sediments, fish, and bivalves) that NOAA routinely analyzes in the NS&T Program, candidate measures of effects were evaluated for two: sediments and fish. All the tests under evaluation had been developed and tested to varying degrees in laboratory and field research. Field sampling logistics, sample handling, and data analyses were performed separately for the work with fish and sediments, though some of the sites overlapped. Sampling sites were selected to represent a range in contamination from relatively highly contaminated conditions to pristine. Data from previous studies, including those by the NS&T Program (e.g., NOAA, 1987), were used to select the sampling sites. In an attempt to reduce costs, as many sediment sampling sites as possible that are routinely sampled in the NS&T Program annually were used in the evaluation. As a result, the sediments were sampled using the NS&T Program protocol: three stations sampled at each site. Four sites from the NS&T Program were sampled in the San Francisco Bay area: Yerba Buena Island (YB), San Pablo Bay (SP), Vallejo (VA), and Tomales Bay (TB). Three samples (numbers 1, 2, and 3) from the Oakland Inner Harbor (near 37°47'11"N, 122°14'50"W) were expected to be relatively highly contaminated. Three samples each collected near Yerba Buena Island (numbers 4, 5, and 6; near 37°50T6"N, 122°20"W), near Vallejo (numbers 7, 8, and 9; near 38°04'10"N, 122°14'17"W), and in southwestern San Pablo Bay (numbers 10, 11, and 12; near 38°01'35"N, 122°25'36"W) were expected to be moderately contaminated. Three samples (numbers 13, 14, and 15) from Tomales Bay (near 38°09'02"N, 122°53'55"W), a remote embayment located north of San Francisco Bay, were expected to be minimally contaminated. The locations of the sites are illustrated in Figure 1. In the data evaluation, the 15 samples were treated either as (1) 15 independent sampling stations or (2) three replicates of each of the five sites in accordance with NS&T Program sampling protocols. Tests of samples from the respective animal collection sites were also performed concurrently with each toxicity test and treated as laboratory controls. Since the participating laboratories were scattered, the same material was not used as controls for all the toxicity tests. This disparity is recognized as a weakness in the study design, especially since none of the control samples was analyzed for chemical concentrations. Nevertheless, the controls served as independent test media for evaluating the viability and internal consistency of the test organisms and for determining which test samples were "toxic", i.e., significantly different from respective controls. Five separate grab samples were collected at each station for the benthic community analyses. Finally, an independent survey of 69 sites in the San Francisco Bay estuary was performed, using a sediment profiling camera. The fish sampling sites were: in the Oakland Outer Harbor (OK), off Berkeley (BK), in San Pablo Bay (SP), off Vallejo (VJ), off the mouth of the Russian River (RR) (reference site), and off Santa Cruz (SC) in Monterey Bay. The former two (OK, BK) were expected to be relatively highly contaminated, VJ was expected to be moderately contaminated, and RR, SP, and SC were expected to be minimally contaminated reference sites. The species selected for the fish analyses was the Platichthys stellatus. It had been the subject of extensive research on availability, contamination, and measures of biological effects in the Bay (Spies and Rice, 1988). All analyses were performed "blind," i.e., without knowledge of the station or site from which the samples were collected. Following the calculation of mean values for each station or site for each measure, the data were subjected to a variety of statistical procedures to comparatively evaluate the performance of the biological measures. All measures of biological effects performed with feral organisms or complex environmental samples (e.g., sediments) are subject to several sources of variability. Each species has different degrees of tolerance to contaminants and natural factors. Also, the tolerance of individual organisms varies depending upon age, condition, natural sources of stress, genotype, etc. Chemical analyses of environmental samples do not provide information for all chemicals that are potentially toxic. They do not indicate which chemicals or portions of chemical concentrations are bioavailable. Good reliable measures of effects are needed to stand alone as independent indicators of biologically significant stress without the benefit of or confusion with synoptic chemical data. Nevertheless, the most powerful biological measures will be those which provide significant indications of effects over, say, order-of-magnitude gradients or differences in contamination. Therefore, the evaluation of the performance of these tests mainly focused upon their sensitivity, precision, and discriminatory power, and, to a lesser extent, upon their concordance with the matching chemical data. RUSSIAN RIVER SAN FRANCISCO. ? VALLE JO Berkeley!! yerbabuena; oakland outer harbor oakland inner harbor SAN FRANCISCO< BAY • SEDIMENT SAMPLING SITES A FISH SAMPLING SITES SANTA CRUZ:;:H:;:;:;:;:ix::H SANTA CRUZ MONTEREY BAY Figure 1. Fish and sediment sampling sites in the San Francisco Bay area. METHODS Sediment Sampling The NS&T Program protocols include collection of sediments at each of three stations per sampling site. Accordingly, in this evaluation, three stations, generally separated by 50 to 100 meters, were sampled at each site. Samples were collected with a O.lm^ Young grab sampler (similar to a modified Van Veen grab sampler). Multiple (usually 6 to 10) grab samples were taken at each station and the upper 1 centimeter (cm) of sediment was removed with a Teflon-lined, stainless-steel, calibrated scoop. These 1-cm thick samples were collected in a stainless steel, Teflon-lined basin until about 7 liters (L) of sediment had been accumulated and composited from each station. The sediments then were homogenized for approximately 5 min. with a Teflon-lined steel spoon until the composited sample appeared homogeneous. Portions of varying sizes of the composited sample from each station then were removed for each of the chemical and sedimentological analyses and toxicity tests. Care was taken to avoid contamination of the samples. Sampling was conducted in February 1987. All toxicity tests were performed with five laboratory replicates or aliquots of the composited sediments per station. The sediment samples for chemical analyses were frozen at -40°C and stored for a maximum of 60 days until the analyses were performed. The toxicity tests were performed on three phases of the sediments: solid, elutriate, and pore water. All except the pore water test were conducted on nonfrozen samples held for no more than 5 days. Fish Sampling Starry founder (Platichthys stelktus) were collected twice: in November/ December 1986 when fish were anticipated to be late in the reproductive cycle but not yet ready to spawn, and January/February 1987 when the fish were expected to be sexually mature. Fish were captured with 5- and 7-m otter trawls towed for 20 min. in water depths of 2.5 to 7 meters behind a research vessel. A target of 30 and 10 to 15 fish per site was set for each sampling period, respectively, to facilitate determinations of between-site differences in measures of effects. Fish less than 20 cm were not retained. When more than 15 fish were caught at a station, more of the larger, sexually mature individuals were kept. Immediately upon capture of the fish, they were bled from either the caudal vein, gill arch, or heart to obtain samples for the micronuclei and hormone analyses. A 1-milliliter (mL) blood sample was centrifuged in the field and frozen at -76°C for the future hormone analyses. A blood smear was prepared on a slide, fixed in alcohol, and kept in cold storage for the micronuclei analyses. Captured fish were maintained on the vessel in flowing bay water until transported to the recirculating marine aquaria at LLNL. Fish were sacrificed the day following capture. Solvent-rinsed tools were used to remove livers and the gonads, which were weighed and aliquots of each put aside for subsequent analyses. For each fish, the gonadosomatic index (GSI) was calculated as [gonad weight/(body weight - gonad weight)] x 1,000. The hepatosomatic index (HSI) was calculated similarly. Standard length was determined for each fish. The fish were kept alive until just before necropsy. Liver and ovary were removed and frozen at -76°C for enzyme and chemical analyses. An additional subsample of ovary was collected and fixed in Davidson's fluid for histological examination. Female fish captured in January/February were taken to the laboratory in Livermore to be spawned for an evaluation of measures of reproductive success. Solid Phase Sediment Toxicity Test with the Amphipod Rhepoxynius abronius This toxicity test has been tested and evaluated extensively (Swartz et al, 1985; Mearns et al, 1986; DeVVitt et al, 1988) and used in many environmental surveys (Williams et al, 1986; Swartz et al, 1982; Swartz et al, 1986), primarily in the Pacific Northwest. Animal collections. The burrowing infaunal amphipods, Rhepoxynius abronius, were collected subtidally from West Beach, a relatively remote site on Whidbey Island (Washington State), using a bottom trawl. Test Procedures. Following their arrival in the laboratory, amphipods were kept in holding containers filled with fresh seawater (28 parts per thousand (ppt) salinity) and maintained at 15 ± 1°C under continuous light until used in testing. Cultures were aerated but not fed during acclimation and were held for 5 days prior to testing. Amphipods were hand sorted from sediments and identifications were confirmed using a Wild M5 dissecting microscope. Individuals that were damaged, dead, or unable to rebury in acclimation sediments were discarded. Acute lethality of sediments was measured in a 10-day exposure to test sediments following the methodology of Swartz et al (1985) as amended by Chapman and Becker (1986). A 2-cm layer of test sediment was placed in 1-L glass jars and covered with 800 mL of clean seawater (28 ppt salinity). The interstitial salinities of all test containers were measured after seawater addition and found to be 27 + 2 ppt. Each beaker was seeded randomly and without knowledge of station identification with 20 amphipods, covered, and aerated. Six replicates were run per station. Five beakers were used to determine toxicity, while a sixth beaker was used to measure water chemistry daily (pH, dissolved oxygen, salinity, temperature). Containers were checked daily to establish trends in mortality and sediment avoidance, and also to gently sink any amphipods which had emerged from the sediment overnight and become trapped by surface tension at the air/water interface. A control sediment from the amphipod collection site was tested concurrently with the sediments from the five sites. This site had been previously documented to be nontoxic to amphipods (Terra Tech, 1985). After 10 days, sediments were sieved (0.5-mm screen), and live and dead amphipods were removed and counted. Amphipods were considered dead when there was no response to physical stimulation and microscopic examination revealed no evidence of pleopod or other movement. Missing amphipods were assumed to have died and decomposed prior to the termination of the bioassay (Swartz et al, 1982; 1985). The amphipod avoidance end-point was determined from daily counts of amphipods that had emerged from the sediments. At the end of the 10-d exposure, live amphipods were transferred to a fingerbowl containing a 2- cm deep layer of control sediment and clean bioassay water. The number of individuals that had reburied within 1 hour was recorded to determine the percent reburial end-point. All but sample numbers 8 and 9 were tested in the first batch. Parallel reference toxicant bioassays (96-h LC50 tests in clean water without sediment) were conducted using sodium pentachlorophenate (NaPCP). A 100 parts per million (ppm) stock solution of NaPCP was prepared in a 0.04 mole (mol) solution of sodium hydroxide using anhydrous grade pentachlorophenol (Sigma Chemicals), following procedures described in Niimi and McFadden (1982). Bioassay concentrations were prepared in duplicate by volumetric dilution of the NaPCP stock solution with filtered seawater. The concentrations of NaPCP tested were: 1,000, 750, 560, 320, 180, and 100 ug/L. Solid Phase Sediment Toxicity Test with the Amphipod Ampelisca abdita This toxcicity test has been developed in New England by Scott and Redmond (in press) and has thus far been used on a limited basis in environmental surveys (Gentile et al, 1987). Animal collections. Tube-forming amphipods, Ampehsca abdita, were obtained from tidal flats in Bourne Cove, a small inlet in Buzzards Bay, Massachusetts by collecting sediments and sieving them through a 0.5-mm screen. A. abdita were collected by flotation from the air/ water interface (Gentile et al., 1987). The animals were transferred to 3-L jars containing approximately 5 to 7 cm of collection site sediment in aerated ambient seawater. The amphipods were gradually acclimated under static seawater conditions at 1-3°C per day to the test temperature of 20°C. During acclimation, they were fed Skeletonema sp. (1.0 x lO'' cells per mL) at the rate of 200 mL of algae per 3-L jar daily. Temperature, dissolved oxygen, salinity, and pH were measured in alternating jars daily during acclimation. Test Procedures. Dense populations of native Ampehsca abdita had been previously observed at many locations in San Francisco Bay (Chapman et al, 1987; Hopkins, 1986) Therefore, sediments were press-sieved wet through 2-mm mesh in an attempt to remove any native animals. If additional amphipods or tubes were observed in the samples, they were removed. Approximately 12 h prior to the initiation of the test, 200 mL (about 4 cm) of the test sediment was placed into the exposure chambers with flowing, gently aerated seawater. Test animals were sieved from the holding sediments. Twenty healthy amphipods of uniform size were placed into each exposure chamber. Moribund or outsized animals were replaced. Test animals were either subadults or females to avoid the natural mortality of males associated with reproductive activity. The test organisms were not fed during the 10-d exposure. The exposure chambers were 1-L mason jars with a 2-cm diameter overflow hole covered with a 0.5-mm mesh Nitex screen near the top. An inverted 9-cm finger bowl with a 2-cm diameter hole functioned as a lid. Air delivery and seawater delivery tubes were fixed through the hole in the lid and positioned to minimize sediment disturbance. Inflowing filtered seawater was delivered via an intermittent flow system at a rate of about 18 turnovers per vessel per day. The 90 percent volume replacement time was estimated to be approximately 3 h according to the method of Sprague, 1973. Tests under static exposure conditions similar to those used with the R. abronius test were set up for aliquots from 3 of the 15 stations. A capillary tube was inserted through each lid for air delivery. The exposure chambers were monitored daily for dead and emerged amphipods. Dead animals were removed and the number recorded. Additionally, the number of emerged animals (on the sediment or water surface) and molts were recorded daily for each test chamber and the molts were removed. At the end of the 10-d exposure, all sediments were sieved through a 0.5-mm mesh screen. All survivors were enumerated and those unaccounted for were counted as dead. In order to minimize sample storage time, two batches of samples were tested: The first batch consisting of sample numbers 1, 2, 3, 4, 5, 6, 7, 8, and 9; the second consisting of sample numbers 10, 11, 12, 13, 14, and 15. Static and flow-through tests were performed concurrently in the same manner on samples from the amphipod collection site (Bourne Cove) which were regarded as control samples. Water temperature and salinity were measured daily in the batch controls and maintained at 20 ± 1°C and 31 to 34 ppt, respectively. Deionized water was added to all samples in a batch if the salinity in the respective batch controls reached 34 ppt. The dissolved oxygen concentration and pH were measured each day in one of the five replicates of each sample on a rotating basis so that these parameters were measured twice in each replicate during the 10-d exposures. Based upon all of the measurements, the dissolved oxygen concentration and pH ranged from 6.2 to 8.2 mg/L and 7.3 to 8.3, respectively. Sediment Elutriate Toxicity Test with Embryos of the Mussel Mytilus edulis This toxicity test was developed for use in Puget Sound (Chapman and Morgan, 1983) and has been used in many environmental surveys (Chapman et al., 1987; Tetra Tech, 1985; Williams et al, 1986). Animal collections. Adult mussels (M. edulis) were collected from Deep Cove, Indian Arm, British Columbia. Mussels were placed in a 70-L polypropylene conditioning tray to permit 8 gonadal maturation, and were thermally conditioned for 4 weeks in unfiltered seawater at 14 ±- 1°C. The mussels were fed a daily diet of a marine diatom culture (Phaeodactylum tricornutwn). Prior to spawning, 30 mussels were stored moist at 5°C for 24 hours. Spawning was induced by placing the chilled mussels in individual Pyrex™ dishes containing 250 mL of 1 |im filtered seawater at 20°C. Fertilization was accomplished within 1 h of spawning initiation by combining eggs and sperm in a 1-L Nalgene beaker. The fertilized eggs were then washed through a 250 urn Nitex screen to remove excess gonadal material and suspended in 2 L of filtered seawater at incubating temperature 20°C. The embryos were kept suspended prior to testing by frequent agitation with a perforated plunger. When microscopic examination of fertilized eggs revealed the formation of polar bodies, triplicate counts were made of the number of eggs in 1.0 mL samples of a 1:99 dilution of the homogeneous egg suspension. Elutriate Preparation. Sediment toxicity tests were conducted in clean, distilled water-rinsed 1-L polyethylene bottles. Twenty grams (g) (wet weight (ww)) of sediment was added to each bottle and the volume brought up to 1 L with filtered seawater (30 ppt salinity) to make a final concentration in all containers of 20 g (ww) of sediment per liter of seawater. The sediments were suspended by vigorous shaking for 10 seconds and were allowed to settle at incubation temperature for 1 hour prior to adding the embryos. No additional agitation was provided after inoculation. Test Procedures. Toxicity testing was conducted following the standardized procedures of Chapman and Morgan (1983), updated by Chapman and Becker (1986). Within 2 hours after fertilization, approximately 15,000 developing mussel embryos were inoculated by automatic pipette into each container, resulting in a concentration of about 15 per mL. The containers were covered and incubated in a temperature-controlled room for 48 hours at 17+ 0.5°C under a 14-h light:10-h dark photoperiod. Test vessels were not aerated during the test. After 48 hours, surviving larvae were removed from the water column of each container by automatic pipette. Repeated, gentle mixing with a perforated plunger was used to ensure that the larvae were homogeneously suspended prior to removal of a 7-mL aliquot. The bottom sediments were not disturbed during the subsampling as bivalve larvae are pelagic and do not associate with the benthos until metamorphosis occurs. Previous experience has shown that larvae found in the sediments invariably are dead. Live larvae were transferred to 8-mL screw-cap glass vials and preserved in 5 percent buffered formalin. The preserved samples (equal in volume to that containing at least 100 larvae in controls) were examined in Sedgewick-Rafter cells under 100 times magnification. As bivalve larvae sink after preservation (ASTM, 1985), half of the water was discarded from the vials before examining the residual volume containing the larvae. Control sediments collected off West Beach in Puget Sound, Washington (the collection site for the amphipod Rhepoxynius abronius test animals) were tested in the same manner. Normal and abnormal prodissoconch I larvae were enumerated to determine percent survival and percent abnormality. Percent survival in the 15 samples was determined as the number of normal and abnormal prodissoconch I larvae surviving in each test container relative to the number surviving in the seawater control, which was assigned a survival value of 100 percent. Larvae which failed to transform to the fully shelled, straight-hinged, "D" shaped prodissoconch I stage were considered abnormal. The weighted rather than arithmetic method was used to calculate mean larval abnormality for a given station (including controls) because numbers of larvae vary within treatments and abnormality tends to increase as mortality increases (ASTM, 1985). This method involves multiplying the percent abnormal value for each replicate by the ratio between the percent abnormals in the replicate and the total percent abnormals for all five replicates. Parallel reference toxicant bioassays (in clean seawater without sediment) were conducted using sodium pentachlorophenate (NaPCP). A 100 ppm stock solution of NaPCP was prepared in a 0.04 mol solution of sodium hydroxide using anhydrous grade pentachlorophenol (Sigma Chemicals), following procedures described in Niimi and McFadden (1982). Bioassay concentrations were prepared in duplicate by volumetric dilution 9 of the NaPCP stock solution with filtered seawater. The concentrations of NaPCP tested were: 10, 32, 56, 100, and 180 ug/L. Salinity, dissolved oxygen, and pH levels initially were adjusted in each container to 30 ppt, 8.2 mg/L and 7.8, respectively. These parameters were measured again in each container at the termination of the toxicity test. Sediment Elutriate Toxicity Test with Embryos of the Urchin Strongulocentrotus purpuratus Elutriates of samples from all 15 stations were tested for effects on development and echinochrome pigment content of the embryos of the purple sea urchin (Strongylocentrotus purpuratus). Echinochrome pigment synthesis appears to be affected by abnormal embryonic development and this end-point has been shown to be sensitive, less variable, and quicker than the morphological examinations (Bay et al, 1983). Embryos from one station at each of the sites also were examined microscopically for the presence of cytologic and cytogenetic (mitotic) abnormalities. In addition, concurrent testing of elutriates from one station at each site was conducted to determine egg fertilization success. Additional 48-h tests on elutriates from these five stations were conducted with embryos from two additional urchin species, the white urchin (Lytechinus pictus) and the green urchin (Strongylocentrotus drobachiensis). Most aspects of this toxicity test have been developed and applied in analyses of primarily water or effluent samples (Oshida et al, 1981; Dinnel et al, 1982; Dinnel and Stober, 1987). Elutriate preparation. For each replicate tested, a 70-mL aliquot of sediment was washed through a 1-mm mesh screen to remove large organisms, tubes, and debris. A total of 280 mL of laboratory seawater (collected off Redondo Beach, California) was added to the sample (including screening water) to produce a sample dilution of 1:4 (v/v). The sediment/ water mixture then was placed in a 400-mL glass beaker and stirred overnight at 17°C with a 60- rpm teflon/glass paddle. Each sample was allowed to settle for 60 min after stirring. The supernatant was then poured into centrifuge bottles and centrifuged at 2,000 times gravity (G) for 5 min to precipitate suspended particulates. The supernatant was carefully decanted and returned to its respective 400-mL beaker. From this volume, a 10-mL aliquot was removed and used in the sperm cell toxicity testing and a 220-mL aliquot was used in tests of embryos for the other end-points. A total of 220 mL of the elutriates was used in the 400-mL beakers for the embryo exposures. Animal collection. Intertidal adult urchins were collected from Point Dume, in northern Santa Monica Bay, California. Release of the eggs and sperm from gravid sea urchins was induced by injection of 0.5 mL of 0.5 M KC1 into the coelom of each individual. Eggs were shed directly into beakers of chilled seawater and washed twice with seawater before use. Sperm were collected with a minimum of seawater (dry condition) and refrigerated until used. Test procedures. The sperm cell test followed the procedures of Dinnel et al (1987). It was initiated by adding 0.1 mL of sperm stock solution to each 10-mL elutriate sample. After 60 min exposure, 2,000 eggs were added to each elutriate sample. Each sample was allowed 20 min for fertilization to occur and then preserved with formalin for later examination. The formalized eggs were examined using light microscopy (100 times) and a Sedgewick-Rafter counting chamber. The numbers of fertilized and unfertilized eggs in an aliquot of each sperm exposure sample were counted in which the presence of a well-defined fertilization membrane around the egg was the criterion defining successful fertilization. The embryo toxicity test methods were modified from the procedures of Oshida et al. (1981). Exposure of the embryos to the elutriates was initiated by inoculating each 220-mL sample with 7,500 fertilized eggs. Stirrers then were fitted to each beaker, and the sample with its developing eggs was cultured for 48 hours at 17°C. After 48 hours, a 10-mL subsample was removed from each beaker and preserved for later analysis of percentage normal development. A duplicate sample of embryos was taken from some beakers for the 10 cytologic/cytogenetic examinations. The embryos in 200 mL of the remaining solution were removed with a plastic screen (44 urn) and extracted for echinochrome pigment measurement. Microscopic examination was used to determine abnormalities in development of the 48-h embryos. The numbers of embryos in the prism stage that had a normal pyramid shape, a differentiated gut, and well-developed skeletal rods were counted as normal. Embryos exhibiting an unusual pattern of development, such as exogastrulation, blastula filled with cells, or unhatched embryo with abnormal cleavage were classified as abnormal. Embryos that appeared normal, but at a less advanced stage of development (gastrula or earlier) after 48 hours, were counted and classified as retarded. The samples were examined randomly without knowledge of the station identification. To determine echinochrome pigment content, 48-h embryos that had been removed from 200 mL of the test sample were transferred to a centrifuge tube with seawater and concentrated by centrifugation (1,500 x G for 5 min). The overlying water then was removed by aspiration, the pellet was washed with 95 percent ethanol and re-centrifuged. The ethanol then was removed, and 1 mL of acidified ethanol (5 percent HC1) was added to each tube and mixed to extract the echinochrome. The absorbance of the echinochrome-containing supernatant was measured with a spectrophotometer at 475 nanometer (nm), using the methods of Bay et al. (1983). To determine cytologic/cytogenetic abnormalities, preserved 48-h embryos were placed on a glass microscope slide and stained with aceto-orcein solution for 15 min. A glass coverslip was then placed onto the slide and the embryos were squashed into monolayers. Twenty embryos were examined from each replicate sample. The number of mitoses in each embryo was recorded, and all of the cells in each embryo were examined for micronucleated cells, mitotic (anaphase) aberrations, and cytologic abnormalities, following the criteria of Hose (1985). Two batches of samples were tested in order to minimize storage of the sediments before testing: the first with samples from the VA, YB, and OA sites; and the second with samples from the TB and SP sites. Each experiment included two controls; a laboratory seawater control from Redondo Beach, California and an elutriate control (laboratory seawater carried through the elutriate preparation steps). Sediment Pore Water Toxicity Test with the Polychaete Dinophilus gurociliatus Laboratory bioassay data with spiked sediments indicate that sediment toxicity is more highly correlated with interstitial (pore) water contamination than with total sediment concentrations of toxicants (DiToro, in press). This toxicity test had been developed and applied in bioassays of effluents and single chemicals in water (Carr et al, 1986), but had not been used previously in sediment quality assessments. Pore water extraction. A 2- to 3-L aliquot of the homogenized sample from each station was transferred to a Zip-Lock bag, labeled, and stored on ice in a cooler or in a refrigerator at approximately 4°C. Sediments were transferred from the container to a pressurized Teflon- lined steel cylinder for extraction of the pore water on the same day that the samples were collected, using the methods of Carr et al, in press. A porous Teflon filter plate and a 0.7 urn porosity borosilicate glass filter were mounted in the base of the cylinder. The system was pressurized with compressed air supplied from a standard SCUBA cylinder. Pressure was applied to the top of the cylinder chamber via a first-stage regulator and manifold, forcing the top plate downward. The pore water samples emitted from the bottom of the cylinder were collected in amber glass bottles with Teflon-lined lids and stored frozen until they were used in the toxicity tests. Animal collections. A population of Dinophilus gyrociliatus cultured in the laboratory was used in the toxicity tests. 11 Test procedures. Before toxicity tests were conducted, the pore water samples were measured and adjusted, if necessary, to produce water with temperature of 20° ± 1°C, ammonia concentration of <2mg/L, salinity of 25 ± 1 ppt, pH of 8.0 ± 0.2, and dissolved oxygen of > 80 percent saturation (Battelle, 1987a). Following water quality adjustments, the life-cycle toxicity test with Dinophilus gyrociliatus was conducted to determine mortality and sublethal reproductive effects (i.e., eggs laid per female), using the procedures of Carr et al. (1986; in press; Battelle, 1987b). The tests were conducted in 20-mL Stender dishes with ground glass lids, with 10 mL of pore water per dish. At a minimum, four animals were placed into each dish, following the addition of the pore water. The tests were started with 1- to 2-d old animals. Because the worms reach mature size rapidly, an experienced investigator can easily identify newly released juveniles by their small size. Survival and reproductive data for each chamber were recorded after 1, 4, and 7 days. The reproductive data recorded for each chamber consisted of the total number of female eggs, the number of egg cases, and the number of newly emerged juveniles. All observations and manipulations were performed using a dissecting microscope with fiber optic illumination. The test animals were fed 50 ul of a 0.5 percent spinach food suspension in each dish. Tests were performed in two batches: the first consisting of samples from the TB and SP sites; and the second consisting of the samples from the VA, YB, and OA sites. A control pore water sample from Duxbury Bay, Massachusetts was tested concurrently with each batch of samples. Sediment Chemical Analyses Chemical and texture analyses of the sediments were performed by SAIC. Organic Compounds. The methods were based upon the protocols of the NOAA NS&T Program (MacLeod et al., 1985). A 50-g (ww) sediment sample was divided into aliquots for analyses of organic compounds. Internal standards (to permit assessment of analyte recovery efficiency) were spiked into the sample, which was extracted four times with varying amounts of methanol then dichloromethane. A bottle roller or shaker table was used to mix the sample with the extraction solvents. The combined extracts were concentrated to about 1 mL in a Kuderna-Danish apparatus and solvent-exchanged into hexane in preparation for fractionation. The concentrated extract was loaded onto a precalibrated chromatography column packed with silica gel, alumina, and granular copper. A first fraction (SA1) was eluted with hexane, the second fraction (SA2) with 50 percent dichloromethane in hexane and the third fraction (SA3) with dichloromethane and methanol. Fraction SA1 (containing saturated hydrocarbons) was concentrated for analysis by gas chromatographic-electron capture detector (GC-ECD). Fraction SA2 (containing aromatic and chlorinated hydrocarbons) initially was concentrated and then loaded onto a precalibrated column packed with Sephadex LH-20. A subtraction (SA2-L1) was eluted with a 6:4:3 mixture of cyclohexane-methanol- dichloromethane. This fraction, containing biogenic material, then was concentrated for portion analysis by GC-ECD. A second subfraction (SA2-L2) was eluted with the same solvent mixture. Fraction SA2-L2 was concentrated again, solvent-exchanged into hexane, further concentrated under a stream of nitrogen, and spiked with an additional internal standard (to allow correction for instrument injection volume fluctuations) in preparation for instrument analysis. Fraction SA3 (containing coprostanol, a natural enteric product selected for analysis as a sewage tracer) was concentrated, solvent-exchanged, concentrated again, and spiked with an additional internal standard as described for the SA2-L2 fraction Fraction SA2-L2 was analyzed for polynuclear aromatic hydrocarbons (PAHs) by gas chromatographic-flame ionization detector (GC-FID) and for chlorinated hydrocarbons by GC- ECD. If hexachlorobenzene (HCB) was found in SA2-L2, fraction SA1 also was analyzed (for additional HCB) by GC-ECD. The method detection limits attained in the analyses of organics in sediments are listed in Tables 1 and 2. 12 Table 1. Limits of detection and quantification for polynuclear aromatic hydrocarbons in surface sediments. Compound Sediment MLODa MLOQb Naphthalene 2-Methylnaphthalene 1-Methylnaphthalene Biphenyl 2,6-Dimethylnaphthalene Acenaphthene Fluorene Phenanthrene Anthracene 1-Methylphenanthrene Fluoranthene Pyrene Benz(a)anthracene Chrysene Benzo(e)pyrene Benzo(a)pyrene Perylene Dibenz(a,h)anthracene a MLOD = Method Limit of Detection (ng/g dry weight (dw)) " MLOQ = Method Limit of Quantification (ng/g dw) 0.90 3.0 0.75 2.5 0.90 3.0 0.75 2.5 1.20 4.0 0.45 1.5 0.30 1.0 1.20 4.0 1.65 5.5 2.10 7.0 1.65 5.5 1.95 6.5 1.50 5.0 1.50 5.0 1.35 4.5 0.90 3.0 1.20 4.0 0.90 3.0 13 Table 2. Limits of detection and quantification for pesticides and polychlorinated biphenyls (PCBs) in surface sediments. Compound Sediment MLODa MLOQb Hexachlorobenzene Lindane (gamma-BHC) Heptachlor Aldrin Heptachlor epoxide Alpha-chlordane Trans-nonachlor Dieldrin Mirex o^'-DDE r^rj'-DDE o,p_'-DDD r^rj'-DDD o.ry-DDT p_,p_'-DDT PCBs: Dichloro Trichloro Tetrachloro Pentachloro Hexachloro Heptachloro Octachloro Nonachloro aMLOD = Method Limit of Detection (ng/g dw) ^MLOQ = Method Limit of Quantification (ng/g dw) Metals. For all elements except mercury, samples were thawed, allowed to warm to room temperature, and then wet-homogenized. Sample aliquots were freeze-dried to a constant dry weight and ground to a homogeneous powder. Approximately 0.2 g of dry powdered sediment was digested overnight with concentrated nitric acid, in capped Teflon centrifuge tubes. Samples were later placed in a 95°C water bath for 2 hours and then autoclaved. After cooling, samples were diluted to 50 mL with Milli-Q™ water and stored in polyethylene bottles until analysis. Approximately 20-g aliquots were stored frozen in polyethylene bottles for mercury analysis. Wet samples were used for mercury analysis to avoid possible losses during the drying process. Approximately 1-g ww of the sample was weighed into a borosilicate bottle. Next, 5 mL of concentrated HNO3 and 5 mL of concentrated H2SO4 were added. The sample was heated in a 95 percent water bath for 2 hours, cooled, and a saturated solution of KMNO4 was added (approximately 5 mL) until a purple color persisted. The sample was then heated again, cooled, capped, and refrigerated until analysis. 14 0.80 0.26 0.13 0.43 0.09 0.30 0.14 0.46 0.14 0.46 0.10 0.33 0.10 0.33 0.16 0.53 0.10 0.33 0.26 0.86 0.13 0.45 0.26 0.86 0.26 0.86 0.20 0.66 0.20 0.66 0.40 1.33 0.20 0.67 0.20 0.67 0.20 0.67 0.20 0.67 0.13 0.43 0.13 0.43 0.20 0.67 Trace metal concentrations, except mercury and silicon, were analyzed by atomic absorption spectrophotometry using graphite furnace or flame (Table 3). Mercury was analyzed by cold vapor atomic absorption, and silicon was analyzed colorimetrically using an ultraviolet spectrophotometer. Sediment texture. Sediment texture (grain size) was determined as the percentage (based on dry weight) of gravel, sand, silt, and clay. Coarse and fine fractions initially were separated by wet-sieving. The silt-clay fraction was analyzed by collecting, desiccating, and weighing aqueous aliquots at timed intervals after thorough mixing of the fraction. The sand and gravel fraction, after being dried, was sieved through a 2-mm screen and the weight of gravel and sand subtractions were determined. Total organic carbon and total inorganic carbon. Total organic carbon (TOC) and total inorganic carbon (TIC) in sediments were analyzed by a modification of United States Environmental Protection Agency (EPA) Method 415.5 (Organic Carbon, Total) and Section 4.8 of the O.I. Corporation Model 700 TOC Analyzer Operating Procedures and Service Manual, which describes the analysis of TIC and TOC on the same aliquot of the sample. All samples were thawed, allowed to warm to room temperature, and wet-homogenized by stirring. Aliquots with a wet weight of approximately 0.02 g were weighed into precombusted ampules with 1 mL of Milli-Q™ water. TIC was determined by sealing each ampule on the TOC analyzer (0.1. Corporation Model 700). Two mL of 5 percent phosphoric acid was injected into the ampules. The carbon dioxide generated was purged with nitrogen to an infrared detector. The resulting millivolt (mV) reading was converted to micrograms TIC. TOC was analyzed by removing the ampules from the analyzer and purging with oxygen. One mL of potassium persulfate solution (5 percent K2S20g) was added immediately before the ampules were sealed. Samples were digested by heating the ampules in an autoclave. Ampules were then attached to the TOC analyzer ampule-breaking assemblage. Carbon (as carbon dioxide) was purged from the ampule using nitrogen and detected as above. The resulting values were recorded as ug organic carbon. 15 Al Aluminum FAA Ag Silver GFAA As Arsenic GFAA Cd Cadmium GFAA Cr Chromium GFAA Cu Fe Copper Iron GFAA FAA Hg Mn Ni Mercury Manganese Nickel CVAA FAA GFAA Pb Lead GFAA Sb Se Antimony Selenium GFAA GFAA Si Silicon COLOR Sn Tin GFAA Ti Thallium GFAA Zn Zinc FAA Table 3. Analytical methods for trace and major elements in sediment samples and limits of detection. Symbol Element Analytical Method Method Detection Limits 560 0.01 2.9 0.08 1.2 0.77 16 0.008 5.0 0.42 0.28 6.2 6.9 600 5.0 16 2.3 GFAA = Graphite Furnace Atomic Absorption CVAA = Cold Vapor Atomic Absorption FAA = Flame Atomic Absorption COLOR = Colorimetric Benthic Community Analyses Sample collections. Benthic infaunal samples were collected at all three stations at each of the five sediment sampling sites that were sampled for the chemical and bioassay analyses. Five replicate samples were collected at each station. All collections were made in February 1987 by SAIC. Samples were collected using a modified 0.1 m^ Van Veen grab. The samples taken for benthos analyses were randomly interspersed among those taken for the chemical/bioassay analyses. They were treated separately and individually and not composited. The samples were sieved in the field using a 1-mm screen. The retained material was fixed in formalin for 48 hours and returned to SAIC, La Jolla, California. Samples were delivered to the laboratory at MEC for processing, identified only by site, station, and replicate designation. Laboratory processing. Laboratory processing of the samples has been performed thus far for samples from four of the five collection sites; the samples from the OA site were deferred for later analyses. Benthic samples received at MEC were logged onto an inventory data sheet. Container identifications on this sheet were used to track samples from receipt through laboratory processing to computer data input. Once in the laboratory, samples were transferred from formalin to 70 percent alcohol for preservation. The majority of the biogenic debris (worm tubes, etc.) in each sample was identified. Organisms were sorted into major and minor taxonomic groups (e.g., crustaceans, echinoderms, molluscs, polychaetes, nemerteans, sipunculids, etc.) using stereoscopic dissecting microscopes. A laboratory supervisor reviewed the procedures, including sample sorting, handling, and labeling that were followed by the experienced sorters. 16 A strict quality assurance/quality control protocol (QA/QC) was followed by SAIC and MEC to insure a degree of sorting thoroughness and efficiency that resulted in >95 percent effectiveness. A minimum 10 percent re-sort was conducted on every sample. A statistical procedure, which sets an upper limit to the number of organisms that can be round in a re-sort of a fraction of the sample, was used to determine whether a sample had passed the QA/QC check. The pass criterion was that, at the 95 percent probability level, 95 percent of the organisms in a sample were removed during the original sort. In the first fraction re- sort, 10 percent of the original sample was re-sorted and checked for missed organisms. A sample passed if the number of organisms found did not exceed a predetermined number (this predetermined number is part of a specially developed statistical program designed for this purpose). If the sample failed, a second 10 percent of the sample was re-sorted, and a third if needed. Failure of the third 10 percent necessitated complete re-sorting of the entire sample. The complexity of the present samples, which contained large quantities of byssal threads, amphipod tubes, polychaete tubes, and extensive shell hash, resulted in several complete sample re-sorts. Sample re-sorts were checked daily by the laboratory supervisor. Following satisfactory completion of QA/QC procedures, the specimens from each sample were distributed to taxonomists. Specialists in the taxonomy of each phyletic group enumerated and identified specimens to the lowest practical taxonomic level. To insure taxonomic consistency and provide QA, 10 percent of all species identifications were checked against reference collection organisms. In addition, 1 percent of the identified specimens were sent out, unlabeled, for taxonomic QA checks. Taxonomic data were entered directly onto computer keypunch sheets, thus precluding transcription errors. Unique National Oceanographic Data Center (NODC) codes were used to identify each taxon. Biomass was determined for each major taxonomic group. Specimens were placed on a 0.3-mm screen and aspirated for 10 seconds, then placed in tared containers and weighed to 0.01 g on an electronic Sartorius balance. Data were coded directly on keypunch data sheets for entry into the data base. Data base development. The quality of the data was checked during various stages of handling. Keypunch sheets were examined by laboratory supervisors prior to submission to insure that data sheets were completed and all fields correctly entered. After the data were entered into the computer data base, an error-checking program was used to validate the data entries. All data fields were checked for alphabetic, alphanumeric, or numeric characters, and for acceptable ranges and characteristics. In addition, 10 percent of all data entries were checked manually by data management personnel. Additional 10 percent increments were checked if errors were found, and this interactive process continued until no errors were found or until the entire data set was reviewed. After the QA checks, the data base was considered complete and ready for analysis. Data analyses. Data were organized for presentation at three different levels and reported in detail in a final contractor report available from NOAA (Barnett el ah, 1987). Level 1 data analyses included determinations of the name and number of individuals (abundance) for each species in each replicate grab, and the total number of organisms and total biomass in each replicate grab {i.e., per 0.1 nvO for the major taxonomic groups. Level 2, the station summary, included the means and standard deviations of the sample data from each of three stations at a site. Level 3, the site summary, included the means and standard deviations calculated for the three stations at each site. Levels 2 and 3 included the means and standard deviations for the following parameters: 1) abundance of each species, 2) biomass of each major taxonomic group, 3) total abundance and total biomass of all biota, and 4) numerical proportion of the most abundant species and taxonomic groups to the total abundance of all biota. Level 3 also included the following community descriptive parameters: 1) the Shannon-Weiner diversity index (H), 2) Pielou's measure of equitability (evenness, J), 3) dominance (D) measured as the complement of equitability (i.e., D=l-J), and 4) species richness (R). 17 Most station and site summaries, and all analyses, used only species that were considered part of the benthic infauna. Transient, water column, or terrestrial species were excluded. Data analyses included multivariate cluster analyses and univariate Analysis of Variance (ANOVA) techniques. The multivariate technique employed to examine community differences consisted of classificatory procedures (Clifford and Stephenson, 1975) based on multiple attributes (e.g., species composition). The primary assumption underlying this approach was that optimal areas (habitats) for a particular species within an environment were inhabited by greater abundances of that particular species. Areas with similar species composition (in terms of both types and abundance) were assumed to provide similar physical/chemical microenvironments. Conversely, areas that supported modified or different assemblages of species were assumed to provide altered or different microenvironments. Two classifications were performed in which entities were grouped by specific common attributes. The sampling stations (entities) were grouped by similarities in species composition (attributes). This is termed the "normal" analysis by Clifford and Stephenson (1975). The "inverse" analysis grouped the species (entities) with respect to their distribution among stations (attributes). Both analyses used only identifiable species that were considered to be important in the benthic infauna. Taxa not used in the analyses included species not part of the benthic infaunal community and rare taxa. A number of rare taxa were found in this study. They carried little classification information (Boesch, 1977), but they could mask much of the information carried by the more common species. To ensure that they did not do so, taxa that did not occur in at least two replicates and at a minimum of two stations were excluded from the analyses. The classification analyses involved three procedures. The first was a calculation of an inter-entity similarity (distance) matrix using the Bray-Curtis index (Clifford and Stephenson, 1975). In the normal analysis, abundance data were square root-transformed and standardized by species mean. Next, the step-across procedure (Bradfield and Kenkel, 1987; Williamson, 1978) was applied prior to application of the flexible sorting strategy (Lance and Williams, 1967; Clifford and Stephenson, 1975). The third procedure was sorting, by which the entities were clustered into a hierarchical dendrogram. Dendrograms from both the normal and inverse analyses were combined into a two-way coincidence table (Clifford and Stephenson, 1975). The values of relative abundance of each species were replaced by symbols (Smith, 1976) in the body of the two-way table as an aid to presenting the patterns of species distributions. ANOVA techniques were applied to dominant species, taxonomic groups, and community parameters to support statistically (e.g., with probability levels and confidence limits) the community differences that were found. Station and site differences were assessed using the Student-Newman-Keuls (S-N-K) test (Sokal and Rohlf, 1969). Differences between sites were tested by contrasts on site means. The site means were calculated by averaging the means of the station within each site. Since six contrasts were performed, the a error rate for each contrast was adjusted, using Bonferroni's equation, to (1=0.05/6=0.008. The ANOVA and S-N-K tests were applied to: 1) community parameters (including total abundance), number of species, diversity (H), evenness (J), and dominance (I-J); 2) abundance and biomass in five major taxonomic groups, and total biomass; and 3) abundance data for the five numerically dominant species at each station and site. Tests of abundance used log (x+1) transformed data. 18 Sediment Profiling Photography Contrary to the other biological tests, this method was applied at sites throughout the estuary. A sediment profiling camera was used to determine a variety of sedimentological and biological properties of surficial sediments at 69 sites. The objective of this analysis was not to evaluate the sensitivity of the test to a range in chemical contamination. Rather, it was to characterize sediment properties, mainly indicative of organic enrichment, throughout the San Francisco Bay estuary. However, 4 of the 69 sampling sites corresponded with those sampled for toxicity testing, chemical analyses, and benthos. Therefore, the data from these four sites are included in this report to facilitate a complete review of all the analyses performed in San Francisco Bay. Details of methods and results for all 69 sites are presented by Revelas et al. (1987). Data acquisition. Field operations were conducted by SAIC with the vessel PROPHECY from 3 through 9 February, 1987. The environments surveyed included shallow fine-grained areas, deep fine- and coarse-grained high energy channel habitats, active and inactive disposal sites, creeks and river mouths, and ports and inner harbors. Five replicate photographs were taken per site. Navigation and data logging,. Navigational control of the survey vessel during this project was provided by the SAIC Integrated Navigation and Data Acquisition System (INDAS). This particular system consisted of a Northstar 6000 LORAN-C receiver interfaced to a Hewlett-Packard Series 200 model 20 microcomputer. A calibration procedure was utilized during this project which resulted in a much more accurate LORAN-C positioning system than is usually possible. In order to calibrate LORAN-C, it was necessary to position the LORAN- C receiver at locations whose positions were known with a high degree of certainty. With the resulting calibration factors applied to the incoming LORAN-C coordinates, the ship's geodetic position was calculated to an accuracy of ± 20 meters. REMOTS™ images. REMOTS™ sediment-profile images were taken using a modified Benthos Model 3731 Sediment-Profile camera (Benthos Inc. North Falmouth, Massachusetts). The camera consisted of a wedge-shaped prism with a Plexiglas™ face plate; light was provided by an internal strobe. The back of the prism had a mirror mounted at a 45-degree angle to reflect the profile of the sediment-water interface up to the camera, which was mounted horizontally on the top of the prism. The prism was filled with distilled water, and because the object to be photographed was directly against the face plate, turbidity of the ambient seawater was never a limiting factor. The camera was mounted on a large tube frame and raised and lowered by winch. REMOTS™ image analyses. REMOTS™ measurements of all physical parameters and some biological parameters were measured directly from the film negatives using a video digitizer and computer image analysis system. Negatives were used for analysis instead of positive prints in order to avoid changes in image density that can accompany the printing of a positive image. Proprietary SAIC software allowed the measurement and storage of data on 22 different variables for each REMOTS™ image obtained. Apparent redox potential discontinuity depth. Oxic near-surface marine sediments have a higher reflectance value relative to underlying hypoxic or anoxic sediments. This discontinuity is readily apparent in REMOTS™ images and is due to the fact that oxidized surface sediment contains particles coated with ferric hydroxide (an olive color when associated with particles), while the sulphidic sediments below this oxygenated layer are gray to black. The boundary between the colored ferric hydroxide surface sediment and underlying gray to black sediment is called the apparent redox potential discontinuity (RPD) and its apparent depth was determined at each site. 19 The depth of the apparent RPD in the sediment column is an important time-integrator of dissolved oxygen conditions within sediment pore waters. In the absence of bioturbating organisms, this high reflectance layer (in muds) will typically be 1- to 3-mm thick (Rhoads, 1974). This depth is related to the rate of supply of molecular oxygen (by Fickian diffusion) into the bottom, and the consumption of that oxygen by the sediment and associated microflora. In sediments which have very high sediment-oxygen demand (SOD), the sediment may lack a high reflectance layer even when the overlying water column is aerobic. In the presence of bioturbating macrofauna, the high reflectance layer may be several centimeters thick. Infaunal successional stage. The mapping of successional stages was based on the theory that organism-sediment interactions follow a predictable sequence after a major seafloor perturbation (Rhoads and Germano, 1982; Rhoads and Boyer, 1982; Maurer et al., 1985; Pearson and Rosenberg, 1978). This theory states that primary succession results in "the predictable appearance of macrobenthic invertebrates belonging to specific functional types following a benthic disturbance." The term "disturbance" includes natural processes, such as seafloor erosion, changes in seafloor chemistry, foraging disturbances which cause major reorganization of the resident benthos, or anthropogenic impacts, such as dredged material or sewage sludge dumping, thermal effluents from power plants, pollution impacts from industrial discharge, etc. The designation of successional status in REMOTS™ images was based on the recognition of two end-member assemblages. Disturbed benthic environments are commonly associated with dense tube aggregations at or near the sediment surface. These appear as small hair-like tube projections at the sediment surface. They are usually spaced 10 or more per linear cm along the imaged sediment surface. These "enrichment" assemblages typically consist of spionid or capitellid polychaete populations and were mapped as Stage I seres. In the absence of further disturbance, these early successional assemblages are eventually replaced by infaunal deposit feeders; the start of this "infaunalization" process was designated arbitrarily as a Stage II sere. These seres were identified as shallow-dwelling bivalves or tubicolous amphipods, such as those belonging to the genus Ampelisca. These amphipods were also occasionally densely aggregated at the sediment surface. The other end-member infaunal assemblage (Stage III) was dominated by polychaetes which have larger body sizes, are less abundant, and feed head down several centimeters below the surface (conveyor-belt species). These species were usually not imaged per se, but rather the feeding pockets or voids that develop around their head ends could be seen in profile images. Active voids were lenticular in shape and the bottoms of these were typically filled with coarse particles. Inactive voids appeared as "collapsed" or relic structures which were recognizable only by their lenticular shape and coarser grain size. These infaunal stages were typically represented by maldanid or orbiniid polychaetes and mapped as Stage III seres. They were typically present on those parts of the seafloor which did not experience severe, frequent (i.e., several times a year) physical disturbance or organic enrichment. This trophic type is apparently adapted to sediments which are relatively "oligotrophic" (Rice and Rhoads, in press). The pattern described above for primary succession, or the pattern of changes in benthic community functional types after a radical disturbance or the opening of a new patch in the physical environment for colonization, has been repeatedly documented in REMOTS™ monitoring of severely disturbed areas such as dredged material disposal sites. However, it is also quite common when monitoring "ambient" seafloor areas to detect a combination of successional seres in the same image (e.g., a Stage I on Stage III, or Stage II on Stage III). This designation documents the process of secondary succession, which is usually the result of mild physical disturbances or biological interactions such as competition and predation. Secondary succession is the process of re-establishment of conditions similar to the original community after a temporary disturbance. 20 REMOTS™ Organism-Sediment Index. A multi-parameter REMOTS™ organism- sediment index (OSI), constructed to characterize habitat quality, was calculated for each site. The REMOTS™ OSI was determined by summing the appropriate subset indices shown in Table 4. The lowest OSI value (-10) was given to those bottoms which had low or no dissolved oxygen in the overlying bottom water, no apparent macrofaunal life, and methane gas present in the sediment. At the other end of the scale, an aerobic bottom with a deeply depressed RPD, evidence of a mature macrofaunal assemblage, and no apparent methane gas bubbles at depth had a REMOTS™ OSI value of +11. Past REMOTS™ surveys had shown the OSI to be an excellent parameter for mapping disturbance gradients in an area and documenting ecosystem recovery after disturbance (see Germano and Rhoads, 1984). Table 4. Calculation of the REMOTS™ OSI Value CHOOSE ONE VALUE: CHOOSE ONE VALUE: Mean RPD Depth Index Value 0.00 cm 0 >0 -0.75 cm 1 0.76 -1.50 cm 2 1.51 - 2.25 cm 3 2.26 - 3.00 cm 4 3.01 - 3.75 cm 5 > 3.75 cm 6 Successional Stage Index Value Azoic 4 Stage I Stage I -> II Stage II Stage II -> III Stage III Stage I on III Stage II on III 1 2 3 4 5 5 5 1 IF APPROPRIATE: Chemical Parameters Index Value Methane Present -2 No/ Low Dissolved Oxygen -4 REMOTS ORGANISM-SEDIMENT INDEX = Total of above subindices RANGE: -10 to +11 21 Fish Hepatic Aryl Hydrocarbon Hydroxylase Activity Slices <5 mm thick were removed from the posterior liver for the in-vitro assay of microsomal enzyme activity. These were immediately frozen on dry ice and transferred within an hour to a freezer maintained at -76°C. One or more liver slices were later used to prepare a microsomal pellet. These microsomes were assayed for AHH activity using the method of Nebert and Gelboin (1968) as described previously (Spies et al., 1982). A portion of the hepatic microsomes from each fish was re-assayed with 10"^ M 7,8-BF. This concentration was determined to cause maximal suppression of AHH activity. A more optimal assay temperature was determined to be 25°C rather than 18 or 37°C. At 25°C, reaction kinetics were linear for 10 min. An Aminco Bowman spectrofluorometer was used to quantify the 3- OH benzo(a)pyrene metabolite. The spectrofluorometer was calibrated with quinine sulfate standards. In addition, a standard of microsomes from 3-methylchoIanthrene-induced mice was assayed with each batch of microsomes as a control for assay conditions. Fluoresence values of assays were corrected according to the quinine sulfate standard. Based on duplicate and triplicate assays from seven fish, the mean coefficient of variation was 14.6 percent for AHH activity, and 2 percent for the mean percent change in AHH activity with the addition of the AHH inhibitor, 7,8-BF. Protein concentrations were determined by the method of Lowry et al. (1951) using bovine serum albumin (BSA) as the standard. Hepatic AHH specific activities, are reported as picomoles 3-OH-benzo(a)pyrene (B(a)p) milligrams (mg) protein"! min"* . Fish Reproductive Success For the November-December collections, a small section of the gonad of each female was removed during necropsy and preserved in Davidson's fixative. Appropriate subsections were taken from female gonads in these samples and made up into paraffin sections at 6 \im, mounted on microscope slides and stained with hematoxylin and eosin. These were later examined to evaluate the predominant egg stages present (Yamamoto, 1956) and for the occurrence of atretic oocytes. Fish captured in the January-February sampling period were taken live to the LLNL to be spawned. Spawning success of several stages in reproduction was determined. Fish handling. The spawning methods of Policansky and Sieswierda (1979), the only known procedure for spawning Platichthys stellatus, were adopted. After capture by trawl from San Francisco Bay in the winter months, 1 to 3 days were allowed for acclimation to the laboratory seawater system that is maintained at 11 to 13°C and at a salinity of 29 to 30 ppt. The holding aquaria measured 58 x 58 x 47 cm (158.1 L) and two to three females were placed in each aquarium. Males were generally maintained separately. Gonadally mature females were then started on a course of intramuscular injections of freeze-dried pituitaries from spawning carp (Crescent Biochemicals) reconstituted in physiological saline, 1 mg pituitary kg'^d"^. Over 90 percent of females, captured mainly in the months of January and February, responded by eventually spawning. The mean time to spawning in all fish (n=49) captured in previous research and so treated in 1983-1985, was 27 ± 13 days. Females generally spawned between two and five times. Females that had not spawned within 43 days were eliminated from analyses because of the positive relationship observed between numbers of days of injections and hepatic AHH activity after 47 d (Rice et al, in press). It was not always necessary to administer pituitary injections as males, unlike females, were often captured in San Francisco Bay in a condition in which sperm could be stripped from them and with a photoperiod of less than 8 h d'l males came into spawning condition in the laboratory. 22 Protocol for spawning. As females began to swell, they were observed daily and occasionally picked up to determine if there were signs of eggs in the lower portion of the oviduct. Fish were handled deliberately and gently to minimize stress. From the onset of rapid swelling, it was usually only several days until females had freely flowing eggs. Many females needed only to be removed from the water and tipped vertically for the weight of the fish to expel eggs from oviduct; other fish required only gently abdominal pressure to start the free flow of eggs. From each of several successive 30-mL aliquots, 10 mL of eggs were removed for the determination of percent floating eggs. A second 10-mL egg aliquot was placed in a damp 400-mL beaker, two drops of sperm stripped within 30 seconds from a male were added and rapidly swirled for 1 to 15 seconds. Approximately 400 mL of sea water were then added to the beaker. A pooled aliquot was made up of the remaining 10 mL in each of the fourth through final egg aliquots. When egg volumes were small, sometimes a portion of the third aliquot would be included in the pooled aliquot. Fertilized egg aliquots were washed free of sperm approximately 20 min after fertilization by a complete exchange of sea water. Usually only one male that met a simple sperm motility test was necessary for the spawning tests as males contribute very little to the variability of fertilization success. Measures of early reproductive success. Several measures of early reproductive success were determined to facilitate the detection of effects at specific developmental stages. Viable hatch is the proportion of spawned eggs that produce viable larvae. Hatching success is the proportion of spawned eggs that hatch. Fertilization success is the proportion of spawned eggs that are fertilized. In addition to these commonly used measures of survival, it is important to recognize that often large numbers of spawned eggs sink. Floating eggs contain the potentially viable gametes, since sinking eggs are usually not fertilized and do not develop normally. Thus, where N = total number of eggs spawned, V = the number of eggs that float (viable eggs), F = the number of fertilized eggs, H = the number of eggs that hatched, and L = the total number of normal larvae, the following measures of survival through early life history stages were determined: (1) percent floating eggs = (V/N) *100 (2) percent fertilization success = (F/V) *100 (3) percent embryological success = (H/F) *100 (4) percent normal larvae = (L/H) *100; in which the sources of variability for these measures in more than 100 spawnings have been assessed and a standard protocol adopted for spawning and evaluation of developmental success (Spies et al., 1985). Percent floating eggs was determined volumetrically in a calibrated centrifuge tube approximately 10 min after spawning. Fertilization success was measured at the 4-8 blastomere stage after eggs had been held at 11-12°C for 3 to 4 h following fertilization in the first incubation chamber, a 400-mL beaker. Eggs were scored in five categories: (1) fertilized eggs with even cleavages, (2) fertilized eggs with uneven cleavages, (3) unfertilized eggs with cortical reaction, (4) unfertilized eggs without a cortical reaction, and (5) ill-formed opaque eggs or highly disorganized zygotes. Fertilized eggs were considered to be those in categories 1 and 2. Eggs in category 2 never comprised more than 5 percent of the total. Embryological success and hatching success were determined 80 to 100 hours after fertilization based on the number of fertilized eggs that began incubation in a second 23 chamber, a 400-mL beaker provided with a screen-covered port that allowed sea water to flow through but retained the eggs. In most cases, between 150 and 200 eggs were used to determine embryological success. This second chamber was held at the same temperature as the first, but was provided with flow-through seawater at the rate of 2 to 3 mL per min. A major source of variability in egg survival is related to the sequence of eggs in spawning: eggs spawned (= stripped) first do not develop as well as those spawned last and a regular progression of egg quality in the early part of a spawning can be seen as aliquots are taken during the course of a stripping. This phenomenon is a function of egg position within the ovarian lumen after ovulation and may be related to the time between ovulation and stripping. Although we cannot precisely control this source of variability due to differences between females, we have incorporated two procedures into our protocol that minimize its effect. Firstly, the first two to three aliquots (39 mL each) of spawned eggs are not used in estimating reproductive success. Secondly, the second and subsequent spawnings of each female are done at 48-h intervals to standardize as much as possible the time between ovulation and stripping. Since the sources of between-spawn variability are unknown, there was no basis for evaluating or controlling its effect on the outcome of these experiments, we therefore simply averaged the reproductive success measures for all spawnings of each female. Males contribute less than 1 percent to the variability in fertilization success provided they have motile sperm, therefore the main effects of contaminants on egg survival could best be determined by evaluating the spawning females. With these features in the protocol between-female variance for the reproductive success measures from 123 spawnings of 43 females was as follows: 45.3 percent for floating eggs, 48.2 percent for fertilization success, 35.7 percent embryological success, and 16.1 percent for percent normal larvae (Spies and Rice, 1988). We therefore concluded that substantial differences in reproductive success measures could be detected between females with the following procedure: 1. Females that were noticeably hydra ted were watched closely and stripped once they had freely flowing eggs. Subsequent spawnings were carried out at 48-h intervals. 2. Eggs were collected in a series of 30-mL aliquots. The number of aliquots varied between two and eight, with five to six being the usual number. 3. From each aliquot two 10-mL portions of eggs were removed to evaluate reproductive success. The remainder of eggs (excluding those from aliquots 1 to 3, or 1 to 2) were combined and 10 mL of eggs taken to produce a pooled aliquot which was independently evaluated for the reproductive success measures. 4. To evaluate percent floating eggs in an aliquot, 10 mL of eggs were placed in a graduated, glass 40-mL centrifuge tube, 30 mL of seawater added, the contents stirred, and after standing for 15 to 30 min, the volume ratios of floating and sinking eggs (V:N) determined. 5. A male which had been determined to have sperm that remained motile for 2 min after stripping was used to fertilize the eggs. 6. To evaluate fertilization success in an aliquot, 10 mL of eggs were placed in a wetted glass 400-mL beaker, 2 drops of sperm added, the contents vigorously stirred, 300 mL of seawater added, and the beaker placed in a seawater table for 20 to 30 min. Floating eggs were then transferred to clean seawater in a second 400-mL beaker with a piece of nytex screen. Fertilization success (F:V) ratio was determined at the 4 to 8 blastomere stage after 3 to 4 hat 11 to 13°C. 7. To determine embryological success and percent normal larvae, 150 to 200 eggs that had been evaluated for fertilization success were transferred to a 500-mL glass beaker provided with a 2 to 3 mL/min flow of seawater and a screened outflow to retain the eggs. 24 Usually only the pooled aliquot from each spawning was evaluated. Dead eggs and embryos were removed daily and preserved in 10 percent neutral formalin. After 80 to 100 hours, the remaining sample was preserved and H:F and L:H ratios were later determined. 8. In nearly all cases, the pooled aliquot was used to provide a single determination per spawning of each reproductive success measure. The measures of percent floating eggs and percent fertilization success in the serial aliquots were used in the above-mentioned analysis of variance. 9. Females had between two and five spawnings, with most females sacrificed after three spawnings. As mentioned above, the mean values of each measure for all spawnings was used to derive one series of reproductive success values for each female. Fish Plasma Hormone Analyses Plasma samples collected in the field from live fish were frozen at -76°C and shipped to Dr. Peter Thomas at the University of Texas for hormone analyses. Estradiol-17B and testosterone were analyzed by radioimmunoassay (RIA) techniques in P. stellatus. The estradiol-17B antiserum generated against estradiol-17B -3-carboxymethyl-ether BSA (Radioassay Systems Laboratories) cross-reacted 22.3 percent with 16-ketoestradiol, 2.46 percent with estriol, and 1.32 percent with estrone. The assay could detect 2.5 picograms (pg) estradiol-17B per assay tube. The testosterone antiserum prepared against testosterone- 3-BSA (Cambridge Medical Diagnostics) was relatively specific and cross-reacted 28.2 percent with dihydrotestosterone, 17.2 percent with 11-ketotestosterone, and 1.46 percent with androstenedione. The assay could detect 1.25 pg testosterone per assay tube. Radioimmunoassay for testosterone and estradiol-17B were performed on the same plasma extract. One hundred microliters of plasma were extracted with 2 mL hexane/ethyl acetate (70:30) in 12 X 75 mm borosilicate tubes. Prior to extraction, tritiated testosterone (1,800 counts per min (cpm)) was added to each sample for determination of extraction efficiency. The extract was dried under a stream of nitrogen and reconstituted in 250 mL of gelatin assay buffer (21.2 micromole (mM) phosphate buffer, pH 7.6). Two aliquots (50 mL and 25 mL) of the reconstituted sample were measured in each RIA to test for parallelism. In the estradiol-17B assay, 50 mL of tritiated steroid tracer (approximately 4,000 cpm, Radioassay Systems Laboratories) and 75 mL of antiserum (1 in 23,200 dilution) were added to the samples and the standards. In the testosterone assay, 25 mL of tritiated steroid tracer (approximately 4,000 cpm, Research Products International) and 25 mL of antiserum (1, in 9,000 dilution) were added to the samples and standards. Assay mixtures were incubated overnight at 4°C and bound steroid was separated from free steroid with dextran-coated charcoal. The intra-assay coefficients of variation (CV) of replicate determinations of estradiol- 17B and testosterone in a plasma control pool were 16.8 and 8.3 percent, respectively (estradiol-17B mean 1.14 ng/mL, s.e.m 0.15, N=3; testosterone 2.12 ng/mL, s.e.m 0.04, N=3). Recovery of steroid standards (40-250 pg/tube) added to the control plasma ranged from 94.5 to 119 percent. Fish Erythrocyte Micronuclei Analyses The number of micronuclei in peripheral erythrocytes of the fish was determined by the SCCWRP and Occidental College. A total of 158 fish were examined from the two sampling periods. The micronucleus technique was applied to circulating peripheral erythrocytes in approximately 1 cc of blood removed in a heparinized syringe from the caudal vein. For each fish, three blood smears were prepared immediately with one drop of blood each, 25 allowed to air dry, and fixed in methanol for 15 min. The blood smears were kept cold (on ice in the field or in a refrigerator in the lab) until they were processed. The smears were stained with May-Grunwald-Giemsa procedure (Preece, 1972) and examined on coded slides under a microscope at high power (1,000 x). One of the three slides was examined for each fish; one of the other two was used if the first was not usable. Two replicate counts of the number of micronucleated erythrocytes per 1,000 cells were made on each smear, and the results reported as the average of the two counts. Two types of micronuclei were reported: detached and attached. The degree of nuclear pleomorphism (loss of the usual elliptical shape of the nucleus) was determined for each slide and coded: 1 (<5% of erythrocytes), 2 (5-50%), or 3 (>50%). Severely pleomorphic nuclei had indentations and/or projections. If projection was greater than about one-fourth the nuclear diameter and terminated in a chromatin mass, it was counted as an attached micronucleus. Fish Hepatic Cytochrome P-450 Analyses Analyses of cytochrome P-450 enzyme activity were performed on liver microsome samples of individual fish by WHOI. Hepatic microsomes were prepared from pieces of liver that had been frozen on dry ice at the time of collection. Methods for microsome preparation were those in use at the LLNL. In addition, microsomes were prepared from gonad from a selected number of individuals. Samples of microsomes were shipped at various times from the LLNL to WHOI following preparation at Livermore by both LLNL and WHOI staff. Cytochromes P-450 and b$. Cytochrome P-450 (extinction coefficient (e) = 91 mM'^cm"^) was measured by sodium dithionite difference spectra of CO-treated samples and cytochrome b5 content (e = 185 mM^cm'^) was determined from NADH difference spectra as previously described (Stegeman et al, 1979). Each cuvette contained approximately 1 mg microsomal protein per mL. Assays for cytochrome b5 were usually carried out prior to cytochrome P-450 analysis using dilutions or concentrations like those above. After obtaining an NADH difference spectrum, NADH was balanced in the cuvettes by combining material in sample and reference cuvettes, and adding more NADH. The mix was then treated with CO, re-divided, and the sample reduced by Na2S204 to determine the cytochrome P-450 content. This procedure not only permitted quantitation of cytochrome b5, but effectively eliminated interference by b5 or hemoglobin in the analysis, thereby permitting quantitation of cytochrome P-420. NADH and CO were balanced in all analyses to permit measurement of putative cytochrome P-420, whether or not cytochrome b$ was analyzed. The degradation or denaturation product of cytochrome P-450, if present, could limit some interpretations. Ethoxyresorufin O-deethylase. EROD activity was measured by the spectrophotometric method described by Klotz et al. (1984). This method directly measures product formation, like the fluorometric analysis described by Burke et al. (1985), except that the resorufin is detected by absorbance. The reaction mixture contained 0.1 M Tris-Cl, pH 8.0 with 0.1 M NaCl, 2 uM 7-ethoxyresorufin added in methanol, and approximately 100 ug of microsomal protein in a final volume of 0.5 mL. The reaction was initiated by the addition of 0.5 mM NADPH and run at 26°C. The formation of resorufin (e = 73 mM^cm"1) was followed at 572 nm on a Shimadzu UV-260 or a Cary 118C recording spectrophotometer. Estradiol 2-Hydroxylase. Estradiol 2-hydroxylase activity was routinely assayed by 3H20 release from (2-3H)E2 (Kupfer et al, 1981). Our modified assay (Snowberger and Stegeman, 1987) consisted of microsomes (0.1-0.3 mg/mL), 25u.M (2-3H)E2 (16 uCi/uxnol), 1 mM EDTA, and 0.3 mM NADPH in 100 mM sodium phosphate buffer, pH 7.4 in a final volume of 200 uL. 26 The reaction was initiated with NADPH, progressed at 25o for 30 min, and was terminated with 200 uL ice-cold 16 mM CaC12 to aggregate the microsomes. Samples were transferred to test tubes containing dextran-coated charcoal (pellets from 200 uL of 1 percent activated charcoal and 0.5 percent dextran in 10 mM Tris, pH 8.0), vortexed, shaken at 0-5oC for 15 min, and centrifuged at 5,000 G. Aliquots (200-uL) of the supernatant were counted in a Packard Tri-Carb scintillation counter. Cytochrome P-450E homologue. Immunoblot ( "Western" blot) analyses were accomplished with monoclonal antibody (MAb) 1-12-3 against P-450E, the major PAH-induced form isolated from the marine fish scup (Klotz et «/., 1983). The characterization of this antibody and its specificity in immunoblotting has been described (Park et ah, 1986; Kloepper-Sams et ah, 1987). Microsomal samples were incubated in a steaming water bath for 10 min, in 20 mM Tris-HCl, pH 6.8, 1 percent SDS, 13.3 percent glycerol, and 1.7 percent B-mercaptoethanol and bromophenol blue. Proteins were electrophoretically resolved and were transferred onto 0.2 urn nitrocellulose paper essentially as described by Towbin et al. (1979). The blots were incubated in 5 percent dry milk in phosphate buffered saline (PBS) for 1 hour at 42°C, and MAb 1-12-3 diluted in PBS for 2 hours at room temperature. They were washed 10 min each in: PBS; 0.5 percent Tween, PBS; and PBS again, and then incubated for 1 hour in PBS with 5 ul-mL"l g0at anti-mouse peroxidase-linked IgG. They were washed again as above, and developed in PPB with HRP Color Developer (BioRad) containing 4-chloro-l-naphthol added in cold methanol and 0.02 percent hydrogen peroxide for 20 to 30 min. Stain deposition was measured by densitometric analysis with a soft laser densitometer (Helena Labs., Inc.). All enzyme analyses were done at least in duplicate; some were done up to 10 replicates. Enzyme assays as well as spectral and immunoblot analyses of P-450 were repeated for samples giving unusual results or results near the limits of detection. Some samples were analyzed three or more times. Repeated analyses showed less than 15 percent variation in the results for any given sample. Positive control samples. Selected individual P. stellatus captured at the BK and SP sites were treated with a known inducer, B-naphthoflavone (BNF). The treatment with BNF was done by R. Spies, and liver microsomes were prepared by WHOI personnel, at the LLNL. Microsomes were prepared from fresh liver, according to methods employed at WHOI. These microsomes were prepared to serve as a positive control, to validate the test methods, and to provide a measure of the degree of response which might be possible in P. stellatus. Fish Chemical Analyses Residues of chlorinated hydrocarbons in liver were determined at the LLNL using methods similar to those of Ozretich and Schroeder (1986). Briefly, tissues were macerated in pre-cleaned beakers, water was removed by addition of pre-combusted (600°C) anhydrous Na2SC>4, acetonitrile (UV grade) and an internal standard of 4,4'-dibromoocto- fluorobiphenyl was added, and the mixture was homogenized by a high-speed tissue macerator (Polytron) to produce the first extract. The first extract was decanted after settling and the mixture was extracted twice more, with the final extract clarified by centrifugation. The extracts were combined, and made up to 100 mL and cooled overnight at 4°C. A 50 mL subsample was removed to gravimetrically determine extracted lipids. A second subsample was removed for isolation, identification, and quantification of aromatic compounds of interest (PCB, DDT, and pesticides). Interfering saturated compounds (e.g., alkanes), remaining lipids, and fatty acids were removed by passing the extract through disposable reverse-phase chromatography columns (Baker) with C|g and NH2 solid-phase absorbents. The concentrated extract was analyzed by GC (Hewlett-Packard, 5880) using a 6^Ni ECD and a 0.25 mm inside diameter, 30-m fused-silica capillary column internally coated with cross-linked methyl silicone. Chlorinated hydrocarbons of interest were analyzed based on retention times and response factors of authentic external standards 27 (National Bureau of Standards/NOAA standards). Values of analytical blanks were subtracted and final concentrations were corrected for recovery of internal standards. Analyte identifications were confirmed using a Hewlett Packard Mass Selective Detector (MSD), model 5979, operating in the scan mode. The MSD was interfaced with a Hewlett Packard gas chromatograph, model 5880, equipped with a DB-1 fused-silica capillary column. Instrumental conditions included an ionization voltage of 2800 eV and scan conditions of m/z 45-450 at one scan per second. Selected ion searches were used to obtain ion chromatograms for compounds with known retention indexes that were suspected to be present in the samples. If necessary, the mass spectrum and retention time of an identified peak was retrieved and compared with an authentic standard or to a mass spectrum library to aid identification The PCBs were identified on the basis of International Union of Pure and Applied Chemists (IUPAC) congener numbers (Ballschmitter and Zell, 1980; Mullin et al, 1984). Since there are many more PCB congeners in contaminated marine environments than we could quantify in this study, 19 major congeners were chosen for analysis. These congeners represent the different degrees of chlorination encountered in aroclor mixtures, are indicative of specific aroclors, or are known to be biologically active. Congeners 18, 87, and 180 were used to estimate the concentrations of Aroclor 1242, 1254, and 1260, respectively (Capel et al, 1985). For example, congener 18 represents 9.38 percent of the total congeners in Aroclor 1242. In order to estimate the concentration of Aroclor 1242, the measured concentration of congener 18 is multiplied by (100/9.38). Congener 87 represents 3.32 percent of the congeners in Aroclor 1254. Congener 180 represents 6.5 percent of the congeners in Aroclor 1260. Congener numbers 66, 87, 118, 128, 153, 180, 195, and 206 are included since they are possible inducers of MFO activity in animals (Clark, 1986). Further, congener numbers 66, 118, 128, 180, 195, and 206 have chlorine atoms in positions 4 and 4' and are thought to be preferentially degraded in marine sediments (Brown et al, 1987). Congener numbers 87, 101, and 187 lack chlorines in the 4 and 4' positions and are included in order to compare 4,4' congeners and non-4,4' congeners. For example, in an unaltered Aroclor 1254, congener 118 is expected to be about 3.5 times more abundant than congener 87 (11.5%/3.3% = 3.5). For Aroclor 1260, the expected proportion of congener 180 to 187 is 2.6. In the past, use of these analytical methods results in 70 percent recoveries being within 50 to 90 percent. Analysis of split samples have produced values within 10 percent of the mean for 80 percent of the chlorinated compounds analyzed (Spies et al, 1988). Data Analysis Methods Sediment Toxicity Tests. Three attributes of the candidate toxicity tests were considered to be of primary importance and were evaluated: (1) sensitivity of each end-point to test sediments relative to respective controls, (2) within-sample analytical precision (i.e., low analytical variability among replicates), and (3) total range in biological response to the test samples relative to analytical precision (referred to hereafter as "discriminatory power"). Of less importance, the tests should demonstrate some concordance in response with a range in chemical contaminant concentrations. However, the evaluation of concordance between toxicity results and chemical data assumes that the etiological agents in the environmental sediments are among or co-vary with the chemical analytes that were quantified. This assumption may or may not be correct, since the most sensitive toxicity tests may identify some samples as "toxic" that otherwise would not be suspected as such based upon quantification of a limited number of chemical analytes. Other unquantified chemicals may occur in complex media such as sediments that are equally or more toxic than those that are quantified. Finally, if all tests with similar end-points (e.g., acute toxicity) are responding to related mechanisms of toxicity, toxicity data among the bioassays should demonstrate concordance. Outlier toxicity tests may be responding to only "nuisance" variables or may be insensitive . All sediment toxicity test data were tested for normality by either the Kolmogorov- Smirnov test (Zar, 1984) or an approximation of the Shapiro and Wilke test. Since all end- points were shown to be non-normally distributed (0.01 < p < 0.025), and could not be transformed to a normal distribution, non-parametric tests were used for further data 28 analyses. Tests of differences in toxicity results (i.e., "sensitivity") were performed two ways to satisfy two objectives. First, because these candidate tests were evaluated for future use in the NS&T Program in which the sampling protocol involves collection of samples at three unreplicated stations per site for chemical analyses, differences in mean results among sites for end-points measured at all stations were of interest. Results of each toxicity test for each site were analyzed by the non-parametric Kruskal-Wallis (K-W) test (oc=0.05) for differences between sites and respective controls and among sites. For those tests where significant differences were indicated, a non-parametric equivalent of the Student-Newman-Keuls (S-N-K) multiple comparison test was performed to determine which sites could be differentiated from each other, and a non-parametric equivalent to Dunnett's t-test was performed for differentiating sites from the respective control(s). The data from each of the three stations at each site were used as measures of within-site variance. Cumulative (pooled) results from the five laboratory replicates were used in these determinations of between-site differences. Second, to determine the relative sensitivities of each test to individual samples, each composited sediment sample from each station was regarded as an independent, individual sample and the differences between the samples and respective controls were determined and tallied. In this case, the five replicates tested in the laboratory per treatment were used as measures of within-treatment variability. In the latter statistical tests, no attempts were made to determine geographic patterns in toxicity response, but, rather, to determine sensitivity of each toxicity end-point to individual samples. Differences in results between individual samples and respective controls were tested with the K-W test and Dunnett's t-tests (Wilcoxon and Wilcox, 1964). In addition to the non-parametric tests, a few parametric tests were performed with the data in an exploratory phase to further characterize patterns in the results. Since these additional procedures used parametric methods, the results cannot be used in any inferential sense, but, rather, provide additional qualitative descriptions of the results. The standard deviations (SDs) and coefficients of variation (CVs) for the five replicates of each sample were calculated. Then, the averages of the CVs were determined for each of the toxicity end-points to evaluate relative analytical "precision." The difference between the maximum and minimum mean values observed in the samples was divided by the average SD to estimate the discriminatory power, an index that was not biased by the data from the controls. Correlations among toxicity end-points normalized to respective batch controls were determined by Spearman's rank correlation (Spearman, 1904). Spearman's rank correlations were also determined between toxicity and bulk sediment chemical data, in which the metals data were normalized to percent fines and the organics data were normalized to TOC content. Benthic Community Analyses. The data from the benthos taxonomic analyses and the sediment profiling survey were not completed for all five sediment sampling sites. Therefore, they were not subjected to the same statistical treatments applied to the sediment bioassay data. Methods described on pages 16 through 18 were used to classify sites with the data that were collected. Measures of Effects in Fish. The biological data from the fish analyses were summarized and listed as means and standard deviations for each site for each sampling episode. The chemical data from the fish were treated similarly. The biological data were evaluated with the Kolmogorov-Smirnov test to determine if they were normally distributed. Differences among sampling sites were tested with the K-W test followed by the non- parametric S-N-K test. Data from the analyses of nuclear pleomorphism in erythrocytes were tested with chi-square. Differences in chemical concentrations among sites were tested with one-way ANOVA. Correlations both among the biological measures and between biological measures and liver contaminant concentrations were determined with Spearman's rank correlation analysis. The range in response of each test among sites, the SD and the CV among the samples at each site, and the maximum range divided by the SD were calculated as indicators of methodological sensitivity. In addition to the non-parametric tests, a few parametric tests were performed with the data in an exploratory phase to further characterize patterns in the results. Since these 29 additional procedures used parametric methods, the results cannot be used in any inferential sense, but, rather, provide additional qualitative descriptions of the results. RESULTS Sediment Toxicity Test Results Solid Phase Bioassay with the Amphipod Rhepoxynius abronius. Results for three end- points in this bioassay are summarized in Table 5. In the control sediments from the amphipod collection site in Puget Sound, means of 19.6 ± 0.5 and 18.8 ± 1.3 survivors out of 20 (98 and 94 percent, respectively) were observed. Mean survival that was lower than the control means was seen in tests of all the samples. Among the most toxic, as judged by the fewest survivors, were samples 1, 2, 3, 7, 11, 13, and 15 in which 50 percent of the amphipods or fewer survived. Based upon previous experience with this bioassay, these results are indicative of highly toxic sediments. Usually, a result showing less than 75 percent survival is significant relative to controls (Swartz et ah, 1985; Mearns et ah, 1986), and a result showing fewer than 50 percent survivors is observed only in the most contaminated sites (Swartz et ah 1985). Mean survival in sample 1 sediments was roughly one-third that in sample 10 sediments. Means of 1.0 ± 2.2 and 1.4 ± 1.7 amphipods avoided (emerged from) the control sediments. Mean avoidance of the test sediments was relatively similar to that in controls in only three samples: numbers 3, 6, and 13. Mean avoidance of sediment samples 7, 8, and 9 was roughly 5 times higher than avoidance of controls. However, within-sample variability was relatively high for this end-point. Percent reburial of survivors at the end of the tests was similar in all samples and this end-point was not evaluated further. Solid Phase Toxicity Test with the Amphipod Ampclisca abdita. The toxicity data are presented in Table 6 as both counts and percents of survivors. Occasionally, more than 20 animals were inadvertently initially exposed to the sediments, despite the sieving step performed before the tests to remove native A. abdita. Means of 17.2 and 16.0 individuals (86 and 80 percent, respectively) survived the 10-d flow-through test in control sediments. The lowest mean percent survival occurred in samples 1, 2, and 3. Mean percent survival was highest in the SP and TB sediments. In some samples, i.e., those from SP, the amphipods showed higher mean survival than those exposed to the sediment from the amphipod collection site. Mean survival in sample 14 exceeded that for sample 1 by a factor of 1.4. Mean cumulative avoidance of the test sediments under flow-through conditions was highest in the OA sediments followed, in order, by avoidance of Control 1, VA, YB, TB, and SP sediments. Mean avoidance of OA sediments exceeded that of TB by a factor of about 3. These tests of all 15 samples were performed in flow-through conditions, whereas those with R. abronius were performed under static conditions. However, three samples also were tested with A. abdita under static conditions identical to those for R. abronius to provide a comparable basis for evaluation of the results. Mean survival was slightly lower in sample 1 and controls under static test conditions than in flow-through conditions, but was unchanged in samples 4 and 13. Elutriate Toxicity Test with Embryos of the Mussel Mytilus edulis. Data for the two end- points of this test are summarized in Table 7. Both end-points indicated that the three OA samples were the most toxic of all 15 stations tested. About 94 and 95 percent normal larvae were observed in sediment controls and seawater controls, respectively, compared to a site mean of 75 percent for OA. Relative to the controls, sediments from all stations caused lower percentages of normal development. Also, relative to controls, mean percent survival was lower in embryos exposed to samples from all stations. About 76 and 100 percent of the larvae survived in sediment controls and seawater controls, respectively. As few as 29.2 percent survived in OA samples. Mean percent normal development was roughly 1.3 times lower for sample 3 than for sample 8 and for the sediment control. Mean percent survival was about 2.5 times higher in sample 8 samples and the sediment control than in sample 3. 30 Table 5. Summary of amphipod Rhepoxynius abronius toxicity test results (mean values ± standard deviation3). Site Sample Number of Percent Avoidance0 Reburiald Percent Number Survivorsb Survival Reburiale OA 1 6.2 ± 2.8 31.0 ±13.9 3.2 ± 2.6 6.0 ± 2.3 97 2 7.8 ± 1.6 39.0 ± 8.2 1.6 ± 1.7 7.2 ± 2.0 92 3 8.8 ± 1.9 44.0 ± 9.6 1.4 ± 1.1 8.8 ± 1.9 100 Mean (n=3) 7.6 ± 1.3 38.0 ± 6.6 2.1 ± 1.0 7.3 ± 1.4 96 YB 4 14.8 ± 1.9 74.0 ± 9.6 1.8 ±1.1 14.0 ± 1.6 95 5 13.4 ± 2.4 67.0 ±12.0 1.6 ± 2.2 13.0 ±2.2 97 6 11.811.6 59.0 ±12.9 1.0 ± 0.7 11.2 ±2.3 95 Mean (n=3) 13.3 ±1.5 66.7 ± 7.5 1.5 ± 0.4 12.7 ±1.4 95 VA 7 6.2 ± 1.3 31.0 ±6.5 5.4 ± 4.2 6.2 ± 1.3 100 8 18.0 ±1.0 90.0 ± 5.0 7.2 ± 4.1 18.0 ±1.0 100 9 16.8 ± 3.5 84.0 ± 16.7 7.4 ± 6.4 16.8 ± 3.5 100 Mean (n=3) 13.7 ±4.8 68.3 ± 32.5 6.7 ±1.1 13.7 ± 6.5 100 SP 10 18.2 ±1.6 91.0 ±8.2 3.0 ± 2.0 18.0 ±1.4 99 11 9.2 ± 1.3 46.0 ± 6.5 2.6 ± 2.4 9.2 ± 1.3 100 12 16.6 ± 2.6 83.0 ±13.0 3.8 ± 3.0 16.6 ± 2.6 100 Mean (n=3) 14.7 ±4.8 73.5 ± 24.0 3.1 ± 0.6 14.6 ± 4.7 99 TB 13 5.6 ± 2.7 28.0 ± 13.5 1.4 ± 1.7 5.2 ± 3.0 93 14 11.0 ±1.9 55.0 ± 9.3 4.0 ± 2.9 10.6 ± 1.3 96 15 6.0 ± 1.9 30.0 ± 9.3 5.2 ± 3.4 5.8 ± 1.8 97 Mean (n=3) 7.5 ± 3.0 37.6 ±15.0 3.5 ±1.9 7.2 ± 3.0 96 Control 1 19.6 ± 0.5 98.0 ± 2.7 1.0 ± 2.2 19.6 ± 0.5 100 Control 2 18.8 ±1.3 94.0 ± 6.5 1.4 ± 1.7 18.4 ± 0.9 98 a n = 5 per station; all samples were tested with the Control 1 sample with the exception of VA 07 and VA 08 which were tested with the Control 2 sample. b 20.0 = 100% survival. c Cumulative number of amphipods on the surface per jar per day over the 10-d exposure period (out of a maximum of 20.0). d Number of surviving amphipods able to rebury after 1-hour exposure to control sediment and bioassay water. e Percent reburial = (mean reburial/mean survival) x 100 31 (9 c o > o> a +1 H t/1 01 1 « u ta •i* •— • %i a. 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S tn « « II o> C H n ^ o T3 ai 32 Table 7. Summary of Mytilus edulis mussel larvae toxicity test results (mean values ± standard deviation3). Site Sample Number of Percent Relative Percent Number Larvae*5 Survival0 Normal OA 1 2 3 Mean (n=3) 52 ±16 60 ±15 47 ±17 53 ± 7 32.3 ± 10.0 37.6 ± 9.1 29.1 ± 10.7 33.0 ± 4.3 73.1 ± 6.5 79.1 ± 1.9 72.7 ± 7.4 74.9 ± 3.6 YB 4 5 6 Mean (n=3) 77 ±14 82 ± 8 95 ±25 85 ± 9 48.2 ± 8.9 51.0 ± 5.2 58.8 ± 15.7 52.7 ± 5.5 84.1 ± 4.2 85.1 ± 3.5 88.1 ± 2.3 85.8 ± 2.1 VA 7 8 9 Mean (n=3) 78 ±11 117± 19 104 ± 17 100 ± 20 48.6 ± 6.5 73.0 ± 12.1 64.4 ± 10.8 62.0 ± 12.4 86.8 ± 1.6 93.4 ± 1.5 90.8 ± 1.3 90.3 ± 1.3 SP 10 11 12 Mean (n=3) 117 ±32 76 ±23 109 ± 29 101 ± 22 72.8 ± 19.4 47.2 ± 14.0 68.0 ± 18.3 62.7 ± 13.6 82.4 ± 1.3 85.6 ± 3.1 92.1 ± 1.2 86.7 ± 4.9 TB 13 13 15 Mean (n=3) 71 ±15 81 ±13 70 ±18 74 ± 6 44.2 ± 9.5 50.0 ± 8.0 43.5 ±11.0 45.9 ± 3.6 80.9 ± 4.7 84.2 ± 4.2 83.6 ± 2.8 82.9 ± 1.8 Sediment Control 01 122 ± 13 76.0 ± 7.9 93.7 ± 0.7 Seawater Control 01 161 ± 42 100.0 ± 25.9 94.8 ± 1.0 a r,= n=5 replicates per station. b Numbers of larvae enumerated at the end of the test, which are used to determine relative survival and percent abnormal larvae. c Survival is calculated relative to the numbers of survivors in the seawater control (=161), which is assigned a value of 100% survival. 33 Elutriate Toxicity Test with Embryos of the Urchin Strongylocentrotus purpuratus. Table 8 presents a summary of results for the various end-points of this test. A range of 84.4 to 87.5 percent of the larvae developed normally among the seawater and sediment controls. Consistently lower normal development was seen in samples from the TB and SP sites. Lowest mean percent normal development occurred in samples 13 and 14. Variability was very high in sample 13 due to the result from one replicate. The highest and lowest values differed by a factor of 1.4. The mean echinochrome pigment content was highest in tests of sample 14 and lowest in samples 1 and 2, differing by a factor of 1.3. Whereas the percent normal development end- point suggested highest toxicity in samples 13 and 14, the echinochrome pigment end-point suggested the lowest toxicity in those samples (Table 8). Fertilization success of eggs was tested in five samples. It was considerably lower in the batch 01 tests, which included samples 1, 4, and 7 than in the batch 02 tests, which included samples 11 and 13. Fertilization success also was low in batch 01 controls, due to a lower sperm density used in the first batch. Several end-points representing cytogenetic (mitotic) and cytologic abnormalities in the embryos were recorded for five samples (Table 8). All but one of the end-points indicated highest mean toxicity in sample 1. The lowest mean number of mitoses per larva was for those exposed to sample 1 sediments. Mean percent of the embryos with mitotic (anaphase) aberrations was highest (30 percent) in sample 1 and lowest (8 percent) in sample 13. Mean incidences of micronucleated cells were highest (5 in all the cells of 20 embryos) in sample 1 and lowest (0.6 in 20 embryos) in sample 13. Means of zero to 1.2 micronucleated cells out of those in 20 embryos were recorded in animals exposed to the controls. The mean number of embryos with at least one cytologic abnormality was highest in larvae exposed to sample 11 and lowest in those exposed to sample 13. The fertilized eggs of the white sea urchin (Lytechinus pictus) were exposed to elutriates of three samples (1, 4, and 13). A low yield of eggs was obtained from the laboratory population of urchins, forcing a reduction in the number of eggs added to the beakers. The mean percent normally developed embryos was similar among stations and controls, ranging from a minimum of 53.6 percent in a seawater control to a maximum of 70.1 percent in sample 1 (Appendix A). The exposures of green sea urchin embryos to the elutriate samples were not successful. Despite obtaining good yields of eggs and satisfactory fertilization percentages, normal embryo development was not obtained. None of the embryos in the control or elutriate samples developed beyond the early cleavage stages of development. Consequently, no usable data were obtained (Appendix A). Pore Water Toxicity Test with the Polychaete Dinophilus gyrociliatus. Mean survival was similar (86 to 100 percent) in all samples and controls (Table 9) and this end-point was not evaluated further. Mean survival of 100 percent occurred in tests of 11 of the 15 samples. Lowest mean egg production (2.9 eggs/female) was observed in polychaetes exposed to sediment pore water from sample 4, followed by that for sample 11. Means of 10.4 eggs per female were produced in seawater controls and 10.0 in pore water controls, similar to the results for tests of samples 13 and 15. Animals in the seawater control and sample 13 produced about 3.6 times more eggs than those exposed to sample 4. 34 0/ n •£ c 6 o s s 9 eft od H 8.2 1 ^2 is .a Xe EU t ID _ O .£eiu •a a; 1 8 1 F s| 2 = & w «=; cm **- ~> Os • "a! o u z ■n £ ^3 UJ o c/5 CO +1 CD +i •>3- CM CO +1 CD CO - o o o o o o +1 o 00 co CM +1 CVI 00 +1 CD 1^ CM CO +1 oo oS 00 r^ co d d° +1 +1 +1 O CT) p CO 00 00 co CM i- CM +1 +1 +1 CD CM t- d ih in in co oo d +1 oo d o +1 in CM co o i- t- co t- t- i- r-j O O O o CD CO W * O o o o O o o o •* CM CD ■* O O O O o o o o +1 +1 +1 +1 CM CM CO T 00 00 00 CO ooqo d d d d o in -^ cm ^t co co t- +l +1 +l +l 1^. CO 1^; O Tf d co 1 in oo co oo co il c i- CM CO £ CO CD +1 +1 +1 +1 i- CD CM O CD 00 CD CD O O O O d d d d p O CM rf CO CM in CM +1 +1 +1 +1 (O^Offl r^ i^ co in oo oo oo co co ii +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 m co ■* rf oo oo oo co o p p p d do d 00(0(0 iri co co T-" +i +i +i +i ■*(OSO co co oo oo OCMON CD O O CD °. *T T P d d d d in cm co ** sriio^ +i +l +i +i IflSOr; d c\i d cm oo oo co co CD r- Tf o o o o o o o O CD i- CD CD CO O CD ° P T P d d d d o +i P d CD CO p CM coi^ oS +1 +1 +1 cod* r^. oo r» T P d d +i +l ■^ m co co co co in d +i +i in •* d ^ co co r^ co cd cd CO co II il c c ■— ' Oi- W c t- T- r- S CO CO CD CD 2 5 co * in co ii c_ c TO CD t- t- CM CM o o o o c o 3 £ < o .o m >- -O O o < 0. CD > C0 H ? -^ 8 LU (/) UJ CO 03 ^ -^ — ' in (3 ■t ■& T3 ■5 o c/1 CU nj in CU T3 u 0) Cu -S $■ 0) ^£ « o >- U 01 u-i <=> C T3 ° CU 0 £ ■rt v as ffl O3 - 2 >« co » VH 1 £ 6 « e g _y •£ i n « id &"^ ^ "ft £ e II « 03 c cn cn CO -Q o 35 Table 9. Summary of sediment pore water toxicity test results with the polychaete Dinophilus gyrociliatus (mean values ± standard deviation3). Site Sample Number % Survival13 1 2 3 Mean (n=3) 100 100 100 4 5 6 Mean (n=3) 100 100 100 7 8 9 Mean (n=3) 100 96 100 10 11 12 Mean (n=3) 100 100 96 13 14 15 Mean (n=3) 100 86 95 Eggs/ female OA YB VA SP TB Seawater Control 1 Pore Water Control lc Pore Water Control 2d Pore Water Controls Combined (n=2) 100 95 95 95 8.6 ± 2.3 5.7 ± 1.0 6.3 ± 1.3 6.9 ± 1.5 2.9 ± 1.5 6.7 ± 4.2 6.7 ± 1.9 5.4 ± 2.2 9.0 ± 2.5 9.6 ± 1.9 6.8 ± 1.9 8.5 ± 1.5 9.5 ± 3.4 4.5 ± 3.5 6.9 ± 1.9 7.0 ± 2.5 10.3 ± 1.9 9.5 ± 2.2 10.1 ± 0.9 10.0 ± 0.4 10.4 ± 3.7 10.4 ± 2.7 9.5 ± 2.9 10.0 ± 2.7 a n=5 replicates per station. b Percent survival is based on the actual numbers of animals observed, as sometimes more than four animals/replicate were introduced at the start of a test. c Samples from TB and SP and Control 1 were tested as the first batch, d Samples from VA, YB, OA and Control 2 were tested as the second batch. 36 Physical/Chemical Properties of Sediments. Sedimentological properties of the samples are summarized in Table 10. Samples 1, 2, 3, 13, 14, and 15 had similar and relatively high clay and TOC content. Clay content was relatively low and sand content was relatively high in samples 7, 8, and 9. The percent gravel content was unusually high in samples 8 and 11. TIC was highest in samples 7 and 8. Trace Metals in Sediments Sample numbers 1, 2, and 3 had the highest concentrations of a variety of trace metals, notably, silver, cadmium, copper, mercury, lead, and zinc (Table 11). Many of the elements were nearly an order of magnitude higher in concentration in samples 1, 2, and 3 than in all the others. Relative to the differences in concentrations of these metals between samples 1, 2, and 3 together, and the other 12 samples, the differences in concentrations of metals among the other 12 samples were small. Sample number 8, which had a high gravel content, had relatively low concentrations of many metals, e. g., cadmium, chromium, copper, and mercury. Arsenic was most highly concentrated in samples 7 and 9. Samples 13 and 15 had among the lowest concentrations of silver, arsenic, copper, lead, and zinc, but had among the highest concentrations of chromium and nickel. Organic Compounds in Sediments Four classes of organic compounds were markedly more concentrated in samples 1, 2, and 3 than in all the others (Table 12). The concentration of total measured polynuclear aromatic hydrocarbons (ZPAH) in sample 1 was elevated by a factor of 20 over the concentration observed in sample number 15; EDDT was elevated by a factor of 50, total pesticides by a factor of about 40, and £PCB by a factor of about 73. All four classes of organic compounds were least concentrated in samples 13, 14, and 15 compared to the others. Relative to samples 1, 2, and 3 and samples 13, 14, and 15; the concentrations of the organic classes were intermediate in samples 4 through 12. The relative concentrations of some organic compounds varied among samples. For example, the ratio of 2PAH concentrations to EDDT concentrations was lower in samples 13, 14, and 15 than in the other samples. Coprostanol concentrations were similar in most of the 15 samples (Appendix B). Chemical Ratios to Reference The individual trace metal and organic chemical data were merged to form a cumulative index of overall contamination by the mixtures of quantified chemicals in each sample. Ratios-To-Reference (RTR) values (Chapman et al, 1987) were calculated by dividing the concentrations observed for the various metals and organics in each of the samples by the respective mean values calculated for the three samples (13, 14, and 15) from the rural area, Tomales Bay. Then, averages of these RTR values for each of the samples were calculated. These average ratios indicated that samples 1, 2, and 3 were most contaminated relative to the others; samples 13, 14, and 15 were least contaminated; and samples 4 through 12 were intermediate in contamination. 37 s 11 09 01 01 O »- s J3 u Ph t»5 65> e >-. oi fl u U o Ph c CO 53 P- c ii Oi 2 ° 01 01 BJJ O O O tv COOOvvO ■flfOOCOr- SO CO SO LO O O o ° CN (N L^ t-i minoo O 00 On sO 00S vOK O r~, O CO 3 §s O rH 8 O O SO in <-■ in ro *5mm rsi J-i 3 ?N t^ On 00 00 O i— i (N i— NJqOO rs! rs| rsi rsi ON On 00 ON §8S3 8888 O O O tN o o o so 0CH»N CT\ I-H CO r-< snON in so irj in Tf IH 00 00 in oo r^ co co rsi co co rH CO 00 rt; "i csi tt o in in in 5 OOrnqO t^ rj On CO rf Tf CO rf On O rsi ^< rs| r- CO CN in On tv . •»* bs' rsi rO rH CO r-< Tt CO ** cn rsi sq oo co oo so ^ T^ ^f ^f CO | O 00 ts. oo rsi so in ^ ^ ^ ^ 00 "* Csj 00 00 00 CO SO so so sO sO O r- p N; On On 00 00 rsi rsj rsi rsi rs. p in -^ in co O sd T^ ^* ^ T— * \6 * H T)i On r>. ^ CO ON 00 CO K cm in est co co in p co co rf in ■>* On i-h 00 On r-i rsi rH i-I rioqnts <-< in i-J rsi tsiNsqio <-h i-< Tf nj 1-J co ^ CO co oo O rs! rsi ro t^ 00 ON 01 O CO o ■** O O O CO o i-i rsi <3 t— I 1-H 1-H 0) ro ^ O so o o t< rsi c o u •2 00 co ^ in S i-* t— i rH 01 O •s to en CO H II u 38 c N s C CD 6S cn # £ £ bp Ph a u 3 en 3 -3 -3 (J\ 1— I * I— I cn i-h o co CO CO CO CO CO CM CN _, Tf Tf ^f 1 d o d ~> v v v c CN IN CN t-H 1-H 1H V V V co tn co tN in sd oo so CN CN CN CM CN i- 1 «-" sO so SO odd V V V IN 00 CO SO CN ON OS O CN i-i i— CN 00*05 CO CO CO CO 31 — ^ _ O H s0 rf in* * CO 00 CN i-h CO * t-< CO 00 i-h CN CN in os cn os H 8\N Is in * ■<* * CN tN OS 1— ' 00 so in cn OS O CN tN 00 OS 00 00 00 SO OS Tf tN O i-1 CO tN 0 00 CN rN so s OS sO co r* os in LO in in in in m CN T— < cn CO rO 1— T-* T— 1 1—1 CN CO < O CO sO CN CO 0O so CO 00 CO CN so CN CO CO CN CO 3 in CO i-h CN CO -T CM CN CO CO CO to CO « CO CO CO CN -r co <* IS c O O V V 0 V « C 0 V 0 V O V c 0 V 0 V O V ro ~N c O V O V 0 V tN CN CN tN tN tN « CN IN tN Cn CN tN « I-c H V V 1 — 1 V N C I-H V i-h V V c 1— 1 V V V « N^ c l-H V r— V r— V c * OS so O so t— OS OS tN CO os in * tN CO 00 tN IN CN CN in CN CN CN sO CN IN CN CO CN in CN so CN sO in CN sO CN CO CN CN CO CN CN CN CN CO so SO so odd V V V OS Os O odd v v v 00 CN SO CN CN CO CO CO t— 1 r* OS O O 1— I 1—* r— 1 <*Or V V v c OS OS OS (rt So'o'l odd v v v i-h tN * * tN so cn in O -j tN o - 00 i° 2 CN CN SO CO * CN CO CO d d d d * 00 o * 00 t-H 00 OS rf * in rr ■g in in cn co co * 00 * in cn - * co 00 i-h CN r- sO N (s| h. H. m co * * o o d d CN CN OS * os in os 06 CN SO SO CO CN i-h r* SO in co in * tN CN tN so sO CN ^h CO dodo c ro o £ Cn 00 OS $ CN CN CN so so so ro d d d "> v v v c Os Os OS SSsS^ d d d c V V V 00 tN OS 00 CN CN CN CN in rf Os so 00 CO CO I-" so ^h cn in i-h CN CO CN OS CO so SO CN CN CN CN d d d d 00 * Os o 00 Os 00 Os * * * * os os in 00 in in m in CN 00 00 Os 00 tN CN tN 00 O 00 Os CN CO CN CN d d d d o * co so SO Cn sD so i-h 00 so CN CO CN O CN sd so sd sd Os CO i-h i-h in Cn in so dodo 22 CN l-H l-H SO sO SO odd V V V c Os OS 00 d d d c v v v O O O tN CN -* (nj fsj CN i-h CO Os tN O tN * O Cn CN SO SO i-h O CN in tN so so 00 ^H * * co in iJ1 * d d d d 00 O Cn 00 00 cn so in in in in in CO sO O so CO so * "* rt" tN IN sO co * CO O CN i-h CN CN CO Cn O CO * * * * d d d d os ^h sp in co 06 * in CN CN CO Os 00 •-; * tN in sd in in O CO OS i-h cn in i-h co d d d d 102 cn e "ro > C o o B cu T3 G co II V 39 Table 12. Summary of sediment organics data (ppb dw). Site Sample Number ZPAHa ZDDT13 ZPEST1C1DEC ZPCBd OA 1 6206 69.5 42.0 304.9 2 5304 149.3 45.0 358.4 3 4312 71.7 49.6 420.9 mean 5274 120.0 45.5 361.4 YB 4 1062 25.8 5.8 73.5 5 1046 20.0 6.2 52.8 6 1023 17.9 4.5 43.6 mean 1044 21.2 5.5 56.6 VA 7 535 23.3 9.2 50.8 8 421 18.2 11.9 53.4 9 666 29.2 5.8 20.3 mean 541 23.6 9.0 41.5 SP 10 1320 8.3 4.2 20.6 11 1449 11.5 4.5 27.0 12 1432 8.5 4.3 25.6 mean 1400 9.4 4.3 24.4 TB 13 480 2.1 2.7 10.4 14 486 0.0 1.2 6.4 15 349 0.0 0.0 4.2 mean 438 0.7 1.3 7.0 a ZPAH is a summation of the concentrations of 19 polynuclear aromatic hydrocarbons. b Z DDT is a summation of the concentrations of six isomers of DDT/DDD/DDE. c ZPESTICIDE is a summation of the concentrations of nine pesticides other than DDT. d ZPCB is a summation of the concentrations of nine chlorination levels of polychlorinated biphenyls. 40 Relative Sensitivity. Precision, and Discriminatory Power of Sediment Toxicity Tests To determine the relative sensitivity of each toxicity end-point, the non-parametric K-W test followed by non-parametric Dunnett's t-test was performed to determine significant differences between test samples and respective controls. The numbers and proportions of samples in which toxicity was significantly higher than in the respective controls are tallied in Table 13. The end-points of R. abronius survival, M. edulis abnormal development, and M. edulis percent survival indicated toxicity in the most samples (> 87%). The end- points of A. abdita survival (flow-through conditions), A. abdita avoidance, R. abronius avoidance, and S. purpuratus echinochrome content indicated the least sensitivity (0 to 7% of the samples were indicated as "toxic" relative to controls). Relative to these end-points, those of D. gyrociliatus egg production and S. purpuratus abnormal development were intermediate in sensitivity. The end-points of mitoses per embryo, mitotic aberrations, and cytologic abnormalities in S. purpuratus were recorded in tests of only five samples and indicated sensitivity to a majority of those samples relative to controls. To determine the relative abilities of the toxicity tests to discriminate among sites as sampled with the NS&T Program protocols, the non-parametric K-W test was performed with the mean data from each site for each of nine end-points. Significant differences in toxicity between the sites and respective controls were indicated for only four toxicity end- points (Table 14). Percent survival among R. abronius was low in the sediments from the TB and OA sites, but the non-parametric K-W test did not indicate any significant differences (p = 0.11) between the sampling sites and the Puget Sound Control (Table 25). Also, there were no differences in toxicity among the five sites (p=0.12). Avoidance of the sediments from VA by R. abronius was significantly higher than that for Control sediments. Differences among the five sites were indicated (p=0.057), however, site-specific differences could not be identified by non-parametric S-N-K. No differences between sites and controls were indicated with A. abdita survival or avoidance, however, significantly lower survival was indicated in SP sediments than in the others. M. edulis indicated significantly lower normal development and survival in OA sediments than in the controls and in the other four sites. Percent normal development of S. purpuratus indicated TB sediments were significantly more toxic than the controls and the other sites, whereas echinochrome content indicated that TB was least toxic of the five sites. Egg production in D. gyrociliatus did not indicate any significant differences. Results of an ANOVA power analysis of minimum detectable differences are summarized in Table 15. The minimum detectable differences between sites for n=2, n=3, n=4, and n=5 stations sampled per site, based upon the data collected in this evaluation, are compared. For the n=3 scenario, which is the standard NS&T Program protocol, the end-points of S. purpuratus echinochrome, A. abdita survival, and M. edulis survival would be expected to detect the smallest differences between sites. The largest of the minimum detectable distances would be for the end-points of R. abronius survival and S. purpuratus abnormal development. 41 Table 13. Results of non-parametric Kruskal-Wallis tests of differences in toxicity between sediment samples and respective controls with np Dunnett's t-test Toxicity end-point P Value3 No. of batches Noofb comparisons "Toxic" Samples c Number Percent R. abronius percent survival avoidance A. abdita .41 & .0001 .21 & .12 percent survival (flow-thru) avoidance percent survival (static) M. edulis larvae percent abnormal percent relative survival S. purpuratus larvae percent abnormal percent abnormal and retarded echinochrome content percent fertilization no. of mitoses per embryo percent mitotic aberrations micronuclei incidence cytologic abnormality D. gyrociliatus egg production .22 & .03 .24 & .27 .0099 .0001 .001 .02 & .89 .38 & .12 .11 & .09 .02 & .05 .04 & .40 .11 & .01 .33 & .01 .008 & .04 .04 & .006 2 2 2 2 2 2 2 2 2 2 15 15 15 15 4 15 15 15 15 15 5 5 5 5 5 15 0 + 13 87 0 + 0 0 0 + 1 7 0 + 0 0 1 25 14 93 13 87 2 + 0 13 0 + 0 0 0 + 1 7 0+1 20 3 + 0 60 3 + 0 60 0 + 1 20 3 + 1 80 2 + 3 33 a P value at which differences were indicated by non-parametric K-W test for each batch of tests. b Indicates total number of comparisons, relative to respective controls, from both batches. c Tested by one-way, np Dunnett's t-test (a = 0.05); with "toxic" defined as different (e.g., lower survival) from appropriate control. 42 •a u cv Cu. en CD -m en 60 .S o, in cu > 5C e © Ja n> -w ns ■u ** in 0) ■w £ c • *« X o ■w c u CD B 0) * >— K « ^"^ W CD u C # CD CO a CD CO T3 cd > VH • *M O MH en en at cd ■4H O en ■s 3E a> & « 0 £ p n ■*-» Sg id T3 u • p-t 4m» u BO CD CD •w s .& a |u o, "3 l c O o c 60 C MH o O s <3 CO 2 cu « •a § rH 01 o 2 s A3 H o CO 3 co > &H CD C l-> CD 0) h "O a ., w C | 9 2 3 k " o S? § "8 6 oif- icat fro hth 5ing 111 to CD C C CD Hh C Jr! cH-o 9 x: (A B ^ Ph CO CO CD 3 «3 > &H CO > v> < > >v. < o en ^2 (8 o ■«ei 2 1 o (8 P U .S C C'fl •« 1) u . C CD CO < o < O olo CQ H < o CQ < O CO H < > < > CO H CQ H < > < O £ S §2 PQ CD < O £ < > < o CO cn §2 cn > §2 to P- > < > < > CO [3 oo in CN 00 d d in O VO i-i o d d O !- i— IN < > I I as CN Tf o o d d << OO ■a > 15 9 cn CD 00 i-i O CN d d m d w CO CO rH d d CO d CQ H Cfl ** -2^ c c trt CD CD ^2 U ' 3 cu u CD CD CS C >- CD 3 CJ 3 Oh 5i. CO c CD C o cj 1 s x: <_> o c S cj w c o 3 S"8 c Q- ;w 43 4.33 3.53 3.06 2.74 0.87 0.71 0.62 0.55 0.23 0.19 0.16 0.14 1.46 1.20 1.04 0.93 2.00 1.63 1.41 1.26 0.49 0.40 0.35 0.31 2.43 1.99 1.72 1.54 0.19 0.15 0.13 0.12 Table 15. Minimum detectable distance between sites, assuming n=2, n=3, n=4, and n=5 stations per site, based upon ANOVA power analysis, where a = 0.05 and power = 90%. n = 2 n = 3 n = 4 n = 5 R. abronius survival avoidance A. abdita survival avoidance M. edulis percent abnormal percent survival S. purpuratus percent abnormal echinochrome D. gyrociliatus egg production 0.76 0.62 0.53 0.48 A variety of calculations were performed to compare the relative analytical precision and discriminatory power of 15 of the toxicity end-points (Tables 16 and 17). For some end- points {e.g., R. abronius avoidance) the degree of within-sample variance differed greatly between samples taken at some sites (e.g., YB samples) (Table 16). For other end-points there was relatively high homogeneity (e.g., M. edulis percent normal development in VA sediments). The averages of the SDs and CVs for each toxicity test are compared in Table 10, the latter as an index of precision. Given that the SDs were largely influenced by the units in which the end-points were reported, the CVs are a better basis for comparison. Among all of the end-points, that of percent normal development in M. edulis had the lowest average CV (3.9%). Among the other end-points measured in all 15 samples, those of A. abdita survival and S. purpuratus percent normal development and echinochrome content also had relatively low average CVs. The CVs for the avoidance end-points of R. abronius and A. abdita were the highest. Among the end-points in the tests with S. purpuratus measured in five samples, the incidence of micronuclei was highly variable, and the number of mitoses per embryo and egg fertilization success were the least variable. The quotients obtained by dividing the total range in mean values by the average SD for each end-point are compared in Table 10. This quotient, the discriminatory power of the test, is intended to identify those end-points with the widest range in response and the lowest analytical variability independent of the use of controls. The discriminatory power was highest with the M. edulis percent normal development end-point and the R. abronius percent survival end-point. They had 6.5 and 6.1 SDs within the range in response, respectively. Among the other end-points measured in all 15 samples, those of avoidance of sediments by R. abronius and A. abdita had the lowest discriminatory power and those of M. edulis survival, S. purpuratus percent normal development and echinochrome content, and D. gyrociliatus egg production were intermediate. Among the S. purpuratus end-points measured in five samples, that of cytological abnormalities had a relatively high discriminatory power, while the others had relatively low values. 44 _0> Q_ a. co a> i CD Q. i3 (A o o o Q CO 1 c ?> o e 8 o .2 o ro < u Eg CD TO O N 0 E o £ cd o g o m 1 ffi e 2 I o 1 a> 3 0_ CO to CO O b CO co CD cb CM co Is- o CM 1- CM o •>* co CO CM co cd cd o ^ ^ d CM CM in B^N in CM to CD co CD oo co i-~ o> o CM CO cb d CM CM co CM CM CO CO to t- CO CO r* CM CO ■>- CM CO m co cm COO) co cb in s n co r- cm °P "*. T cb co - CO O CD qoiit as CD 3 a co ^ CM CM CO N r-' t- r- CM cd a T- CM CO t in co CO < O £ *-; co ". CO CO co to CM cd co CO CO l~~ 0> co CO co CM d cb »— T" CM *~ co co CD CO T- CM 10 r- O CD CD CD snoi co cd in •*>■* ID CM CO co en r-~ i*-^ cb cb f»- m co r; cm in CO CD »- t <~ CO O- CO < > ^ •* co lO «- CM ^ CO o CM P CD CO CO CD ■« J CM CM in CD CM y- O t-^ cb™^ in i h-i ■* N »"* ■ O «- CO co co co co CO •fl; co o co CD CO CM ° w" ■» <\i ^ coV *- *- *- iri to cb CO m o co CO ^ cb in CM r- CM CM CM 45 Table 17. Within-sample precision, range in results, and discriminatory power of 15 toxicity end-points measured in 3, 5, or 15 sediment samples. Toxicity Sample Average Average Sample means Discriminatory End-Point Size of SDs ofCVs Maximum Minimum Power3 (%) R. abronius Percent survival 15 10.3 21.4 91.0 28.0 6.1 Avoidance 15 2.6 83.5 7.4 1.0 2.5 A. abdita Percent survival 15 6.9 8.2 95.2 66.0 4.2 Avoidance 15 2.1 63.6 6.8 0.8 2.9 Percent survival (static) 3 13.6 19.9 86.0 51.0 2.6 M. edulis Percent normal 15 3.2 3.9 93.4 72.7 6.5 Percent survival 15 11.3 22.6 73.0 29.1 3.9 D. gyrociliatus Egg production 15 2.2 31.6 10.3 2.9 3.4 S. purpuratus Percent normal 15 5.6 7.1 88.4 63.9 4.4 Echinochrome 15 0.007 7.4 0.109 0.082 3.9 Percent eggs fertilized'5 (Batch 1) 3 7.8 13.8 66.4 50.0 2.1 (Batch 2) 2 2.9 3.4 89.8 81.2 3.0 Mitoses per embryo 5 1.0 16.8 8.0 5.6 2.4 Percent mitotic aberrations 5 7.1 36.2 30.1 8.0 3.1 Number of micronuclei 5 2.2 73.9 5.0 0.6 2.0 Cytologic abnormalities 5 4.6 29.2 32.0 6.4 5.6 a The result of dividing the difference between the maximum and minimum mean values by the average of the SDs. " Controls indicated that batches 1 and 2 behaved differently. 46 Correlations Among Sediment Toxicity End-Points All except two of the end-points (R. abronius and A. abdita avoidance) are presented in Table 18 such that a high value indicates non-toxicity (e.g., percent survival, percent normal). Therefore, the results of these correlation analyses should be interpreted carefully with regard to the sign (positive or inverse correlations) for these end-points. Three patterns in toxicity responses among the end-points were apparent, based upon the Spearman rank correlation analysis. First, results for the three end-points of M. edulis survival and normal development and R. abronius survival were relatively highly correlated with each other and not very highly correlated with any others. Second, results for the three end-points of A. abdita survival and avoidance and S. purpuratus echinochrome content were relatively highly correlated with each other. The pattern of response with the S. purpuratus percent normal development end-point contradicted that of A. abdita survival and S. purpuratus echinochrome content. Third, the results for the end-points of D. gyrociliatus egg production and R. abronius avoidance were weakly correlated with each other, indicating patterns that contradicted each other. Neither was highly correlated with the results of any of the other end-points. The correlations were strongest among the end-points in the first group and progressively weaker in the second and third groups. Although the toxicity data were not normally distributed, a parametric Principal Components Analysis among the bioassay end-points was performed in an exploratory mode to determine if there were any patterns in correspondence among the tests. Three factors were identified that explained 44.8 percent, 36.3 percent, and 18.9 percent of the total variability, respectively. The first factor suggested that the M. edulis percent normal and percent survival end-points and the R. abronius survival end-point had very similar patterns in toxic responses among the 15 samples. The second factor indicated that A. abdita survival and avoidance and S. purpuratus percent normal and echinochrome content had similar patterns in response. The third factor accounted for little of the total variability and contained the D. gyrociliatus reproduction data. Correlations Between Toxicity and Chemical Results Results of a Spearman rank analysis of correlations between toxicity test end-points and selected sedimentological variables, chemicals, or chemical classes are listed in Table 19. Trace metal data were normalized to percent fines and organic chemical data were normalized to TOC content. With a total of 190 correlations, the experimental level of significance became 0.05/190 = 0.0003 by the Bonferroni method. None of the correlations were significant at a = 0.0003. Therefore, the results for each toxicity end-point are treated qualitatively. Most of the end-points in Table 19 are presented such that a high value indicates non-toxicity (e.g., % normal, % survival), however, high values for the end-points of avoidance, micronuclei, cytological abnormalities and anaphase aberrations denote toxicity. Therefore, the correlations must be interpreted cautiously with regard to the sign (i.e., positive or negative correlations) for these latter end-points. Some of the end-points that were relatively highly correlated with each other (Table 18) also indicated similar patterns in their correlations with some of the same physical/chemical parameters. First, the toxicity end-points of percent normal development and percent survival of M. edulis, percent survival of R. abronius, and percent normal development of S. purpuratus indicated a similar pattern: they were most strongly inversely correlated with sedimentological factor(s) such as percent silt, percent clay, percent fines, and/or TOC content. The M. edulis end-points also were inversely correlated relatively highly with mercury concentration, whereas the R. abronius survival data were not very highly correlated with any of the chemical variables. Percent normal S. purpuratus data were also relatively highly positively correlated with the concentrations of DDE, other pesticides, zinc, and PCBs. Second, low percent survival and high incidences of avoidance of sediments by A. abdita and low echinochrome content of S. purpuratus also indicated a similar pattern: they were relatively highly correlated with increasing concentrations of DDE, other pesticides, and PCBs. The correlations between A. abdita survival and these chemicals were particularly high. Third, egg production in D. gyrociliatus was most inversely correlated with PAHs, 47 nickel, and percent silt and most positively correlated with Fossil Fuel Relative Index (FFRI). Among the S. purpuratus end-points measured in only five samples, the end-points of micronuclei incidence, anaphase aberrations, mitoses per embryo, and fertilization success were relatively highly correlated with one or more classes of organic compounds. In addition, anaphase aberrations were relatively highly correlated with several trace metals. Since the sample sizes for these end-points were relatively small, the apparent correlations between the concentrations of PAHs and the incidences of anaphase aberrations and micronuclei are illustrated graphically in Figures 2 and 3. 48 01 s s t/5 Ol 01 in rH ■a .s o> 1/5 m s o a. i ■a c 1-1 o 3 m « > -cs b a 3 ^6? « 5^ «3 > 00 i— i in in so (N so o m O 00 o t-^ ■"*■ in OM> \0 * rtoooos (S rt Tf M CO so i-1 in r* i-H r+ O CM CN CN CM O O OS in irjtoin s rots i— i oo sO r- 1 ts O t*» N WN >* N M rn in so r-< i— i so in so OS CM CO 00 ■<* CO CN 5; Q &j ttj ^ ^ c/i vi 49 1 ■o § a. 3 3 •3 3 S J c I f as 5. ft — 'a\r-inr^vor^^CT\vo(No\r-OM^mHnr:r*:^ Ttm>nooi/ioeiO}«nr-;Niflin0NN(S| «-« en eo r- •-« p- *© II Z ?S5 > "Q H 3 00-- J3 Q „ „ „ O aouffizeuSlePtfePf- 8 50 in C o •J3 u < < 6S 50" 40" 30" 20" 10- 0 -100 Stal3 Sta7 Sta11 sia4 Stal 100 200 Benz(a)anthracene, ppb dw 300 — I 400 50 i 2 40- < § m 30 i 20 io -i o I Sta 7 „ * Stall Sta 4 Sta 13 0 1000 2000 3000 4000 Total PAH, ppb dw 5000 Stal 6000 7000 Figure 2. Correspondence between incidence of anaphase aberrations (mean ± standard deviation) in Strongylocentrotus purpuratus embryos and concentrations of benzo(a)pyrene, benz(a)anthracene, and tPAH in sediments. 51 12-1 ■a 10- 0 o * S 6 o 2 -100 Sta7 Stal3 Stal Stall Sta4 100 200 300 400 500 Benzo(a)pyrene, ppb dw — i — 600 700 l 800 12 -| =5 io u T3 g v x> 1 S s° .3 a t! 2-1 8- 6- 4- -100 Stal3 Stall Sta7 Sta4 Stal 1 1 1 1 1 — 100 200 300 Benz(a)anthracene, ppb dw 400 12 -i us =3 io u &> o R ' a b 6 o o §h 4 'S « * Stall Sta7 Sta4 SStal3-L Stal — i ■ 1 ' 1 ' 1 ' 1 — 1000 2000 3000 4000 5000 Total PAH, ppb dw 6000 7000 Figure 3. Correspondence between incidence of micronuclei (mean + standard deviation) in Strongylocentrotus purpuratus embryos and concentrations of benzo(a)pyrene, benz(a)anthracene, and tPAH in sediments. 52 Benthic Community Composition Results A detailed description of the benthos data is available in the contractor's report to NO A A (Barnett et al., 1987). A summary of selected benthos parameters is listed in Table 20. No data are thus far available for the Oakland site. Among the four sites for which data exist, total abundance was highest at SP and lowest at YB. Species richness was high at TB and lower at all the San Francisco Bay sites: YB, SP, and VA. Dominance was highest at SP, reflecting the abundance of the crustacean Ampelisca abdita. Dominance was lowest at station 4 where the abundance of this amphipod was relatively low. Crustaceans dominated the community in abundance at YB and SP, whereas molluscs were dominant at VA and polychaetes were dominant at TB. Mean total biomass was distinctly high at VA and TB, where molluscs and polychaetes were dominants, respectively, and was low at YB and SP where crustaceans predominated. The amphipod A. abdita was the single most abundant organism found at the four sites, occurring in a mean concentration of 3,061 individuals per O.lm^ at SP. At the SP site, the dense population of tubes of A. abdita probably influenced the nature of the substrate. This species was also the dominant at YB, but in concentrations roughly an order of magnitude lower than those at SP. The tubes of the abundant polychaete Asychis elongatus likely influenced the character of the sediments at YB. Among the four sites, variability in species composition was highest at YB. Molluscs, especially Mya arenaria, were dominant in both abundance and biomass at VA, where a significant amount of shell hash was encountered in the sediments. Many polychaetes, especially Exogone lourei and the mud-dwelling mussel Musculista senhousia were among the most abundant biota at TB where crustaceans were relatively rare. The byssal threads of M. senhousia may have provided a haven for some infaunal species at TB. The dendrogram in Figure 4 produced by Barnett et al., (1987) summarizes the results of a community classification test based upon analyses of community similarity among stations and sites. The community similarity analyses performed on the data for each station produced both normal (by station) and inverse (by species) dendrograms, which were arranged on a single plot on a two-way coincidence diagram. The normal (vertical) dendrogram contains clusters of stations based upon similarity of faunal composition. The (horizontal) inverse dendrogram contains clusters of species that had similar distribution and abundance patterns among stations. The relative abundance of each species is identified by four symbols. The normal classification analysis identified four major cluster groups of stations, labelled as "site groups" 1, 2, 3, and 4. Site TB (site group 4) was determined to be the most dissimilar among the sites. Next, the dendrogram separated site VA from sites SP and YB. The latter two sites were most similar. Each site group consisted of stations from only one site indicating that faunal similarity was very high at stations within a site compared to similarity among sites. The inverse classification analysis identified five species groups with similar distribution and abundance patterns among stations. The fauna at site TB was composed almost exclusively of group A species, mainly polychaetes either unique to that site or rarely found at the other sites. Site TB also had some species from groups B and D. The fauna at YB included mainly species from species groups C and D along with species from groups B and E. Species group D was dominant at site SP and group E species were most abundant at site VA. The inverse analysis confirmed the pattern observed with the normal analysis: sites TB and VA were the most dissimilar in faunal composition. 53 CN « 6 -s o x 6 S3 3P in ^ & o Is (8 C 1 1 6 § 1/5 z C/5 DDD zzz c (8 HI <<<< oooo poop CO On Os t^ onn n i-h CN SO CO i— i in i— i sq r- CN Tj< Csj 6* 6*5*6* oq in cn in CO CN i— i rH i£j£6?6* oq os -* tt -* SO CN rn CN i-i Tf co so rH >* SO 00 sO sO CN CO ^ co m t^ in dodo tj< so sq cn rH OS Os O (S|lHl-l(S| poop IT Id rH in OnlSTj Os SO OS in co ri co co Hin cn p p p p CO I 00 H H CN t-^ 00 SO CN SO CN O CO CN CO CO in co os in ■* in •>* in ii c in in in II II II c c c c 3 Tf in so 2 pa ca to pa 6*6*6*6* COsO't ts. CN 00 Os 00 6*6*6*6* O rH O CO CN CO CN CN 6*6* 6* ?£ CN rr O Os 1— I T-H I-H f^ oo rN oo tN 6*6* 6*6* os sq so p iri n »« 6*6*6*i£ ■^ tj< sq in SO i-h CN CO 65 6*6*6* tv. Tt ■>* CN ri in if) ^i 00 00 00 00 o o Os so so m in in £fcgfc oooo oooo CN O CN i-h t% ri sO 00 i-h CN i— i i— i •*T O O ri i-h CO Os i— 1 CN CN i-h CN Tf ocsi in d i-S d d m I-H II c ^ .—. f-^ •*_* in in in - II II II £ sss s >> >> in T-H II ^ *~. *~- £ in in in • - CO in co cm co o in Tf CN Tf CO 6*6*6*6* t-. t-h in cn CO r^ 00 CN OS Os 00 Os 6*6*6*E* 0\N ts. r< Ifi^dts 6*6*6*6* co oo co in d d d d co o oo o so so in so d d d d oo so sq p t^! in ^ so CN CN CN CN Os cn oo in in OS CO Tf SO CO 00 t>« CO SO O T-H f^ CO 00 Os O Tt i— i-i CN *OTfN fs> cn i-h sq T-H f> SO 00 OnobN "* CO CO CO NOfs! rt CN •<*! [N "* I-H l-H rH I-H m in in 10 (n=! 11 (n=! 12 (n=l Mean i 13 (n=; 14 (n=! 15 (n=, Mean i c- eu Ch Ph cn cn cn cn pa pa pa pa 54 I DECREASING SIMILARITY SYMBOLS: BLANK - 0 .<> 0.6 - <• 1.0 ♦ <- 2.0 • > 2.0 -t:::::::;;;i;r ^_ Oplnodrniniis pugctlcns __^ Myscl la sp. 0 |L Anaemia occ ulcni il is f I lo.-re. ^^_ Mcdigmastlis %f>. Ni-pfiiys comma rn ^^^„ Ampe i i sc-t at><) i ta fe MliSCtil '5ta senlionsia corophium acherus [cm pl'S. J BpC .' rapleiiLos pugpiteiv ^-|__ PseudOpOlydora ho, ' Meteronnstus r ■ i i _^_ Loucon sp. h n_j— '■""""""-" j« ^^ StreblOSpIO bened _|— ""'" sp ' |l—— My.-, srcnnrin | Corophlun sp a I I Syiiiilotca laiicatu Xi + . + + - + + + + • • • + + • - - + • • • + - + - + + + + + + + + + - + + + + + + — + + + + + - - + + • • • • • • • • • + + + + — - + + - . + - + nm (1 I! Q Ii ri 0 + - + + - + - + + - + + + + + + - + . - + - + - + - + - + + + + + + + + + - + - + + . - + + • + + • + + + + + - 2 3 SITE GROUP a. o o LU 0. m Figure 4. Community classification analysis dendrograms and resultant two-way table. Distances axes are the Bray-Curtis distance values. Symbols in the two-way table represent the abundance values (square root transformed and standardized by the taxon mean); blank = 0, '.'< = 1.5, '..'< 1.0, '+'< = 2.0, '»'> 2.0. 55 A summary of tests of site differences with ANOVA and S-N-K performed by Barnett et al. (1987) is listed in Table 21. The site means were calculated as the averages of the means for the five replicates of the three stations at each site. Significant between-site differences were observed with all the selected parameters. Total counts, crustacean abundance and dominance were significantly higher at the SP site than at the others, and, accordingly, evenness and diversity were significantly lower there. Species richness, total biomass, and abundance of polychaetes/oligochaetes were significantly higher at TB than at the other sites. Mollusc abundance was significantly higher at VA and SP than at TB and YB. Table 21. Summary of site differences in selected benthic community parameters based upon ANOVA with a S-N-K test on mean or log (x + 1) transformed mean data from the YB, SP, VA, and TB sites. Means connected by the same underline are not significantly different (a >0.008) Total count site log mean Species richness site mean Crustacean abundance site log mean Mollusc abundance site log mean Polychaete/Oligochaete abundance site log mean Total biomass site mean Shannon-Wiener diversity index site mean Pielou evenness measure site mean Dominance index site mean SP TB VA YB 3.53 3.07 2.58 2.62 IB SP 21.13 YB VA 26.00 20.20 18.1 SP YB VA TB 3.45 2.41 1.93 0.76 VA SP TB YB 2.64 2.59 1.88 1.50 TB YB SP VA 3.03 1.92 1.91 1.77 TB VA SP YB 35.31 23.48 4.95 2.60 YB TB VA SP 1.39 1.29 1.26 0.70 YB VA TB SP 0.46 0.44 0.40 0.23 SP TB VA YB 0.77 0.60 0.56 0.53 Sediment Profiling Photography Results A variety of measures of the characteristics of sediments was recorded through use of sediment profiling photography and other means at four of the sites (Table 22). No data were produced for the TB site. The overall intent of these measurements was to determine the degree, if any, of organic enrichment of sediments as indicated by the variety of sedimentological and biological measures. The sediments were mainly fine-grained (> 4 phi; >95% fines) at three of the four sites; they were more coarse at VA. The indices of biological conditions at the sites (Organism- Sediment Index (OSI) and Infaunal Successional Stage) did not indicate the infauna were stressed or recently disturbed at most of the stations within the sites. Some of the stations at the OA site, however, indicated that recent disturbance or organic enrichment may have 56 occurred there. The OSI was lower and the apparent RPD was smaller there. The depth of the apparent RPD was most shallow at SP and OA, indicative of sediment organic enrichment and deepest at YB. However, contrary to expectation, the TOC and total organic nitrogen (TON) concentrations were the lowest, or among the lowest, at YB. Both TOC and TON were highest at OA. The density of Clostridium perfringens spores was over an order of magnitude higher at OA than elsewhere. Biological Characteristics of Fish Samples: Results All of the individual data from the fish that were evaluated are listed in Appendix C. They include data on the gender, size, weight, and measures of biological effects. Fish were located and captured at the BK, OK, VJ, SP, and RR sites in November- December; and at the BK, OK, VJ, and SC sites in January-February. About 15 fish were caught and used for evaluation at each of the five sampling sites in the first sampling (November-December). Females predominated at all sites, except SP where a nearly equal number of males was obtained in November-December (Table 23). Mature fish were most commonly examined at three of the sites; however, roughly equivalent numbers of immatures were found at the VJ and SP sites. The lengths of the fish were similar at all sites, although SP fish were slightly smaller and those at the RR were slightly larger than those at the other three sites. The relatively high proportion of immature fish at SP was reflected in the small mean length of the fish. The liver/body weight ratios and condition factors were similar among all sites and there was relatively low variability in the data from within the sites. The gonad/body weight ratios, however, showed greater differences among the sites, and were highly variable within sites. Relative to the other sites, the gonads in SP fish, where the most immatures were captured, were smaller. The RR fish which were the largest also had the highest gonad/body weight ratios. 57 60 C o a, 3 X s, o O ■g. 60 .5 2 d •a a) is ■5 I .5 2 a, ■a 3 -a ■a v I T3 V (A ■a c 5'S + z R i r II D I* al-S 6<* [2 o o w i-gs S 6 H 2 | -til so s «§* e yl a if) ass." B a- b a a 3 3 3 000. "^ "O "O 3 3 3 5S5 !*S3$S) 0\ 00 t-"1 0\ Sq L?^ t^; ^ co r-i oS uS 5.i^i MOCN + + + K uS in ir> C\ 0\ C\ IT) ffl; 0>83> c ! S 60 O | •s T3 a IV 3 > 3 3 58 SO 00 Os .©. & V u n i a s > o z .s 01 0) s o a MM S3 -a 13 3 O X! Ml •c 01 u ■a u 00 o o a I* i*s II co * o o t! o (0 I-" U< x C co O J c ? o — u >s,=i T3 O X P3 *- & .£P > CJ >s £ CO — x; «g to O 01 ■o S •a x 5 ti I 01 2 S 01 u5 6§ IN CM CO 6§ T— < 00 o O d d d +1 +1 +1 +i +1 SO CO CO o 00 CO 00 1-^ ts cn c4 Csj cm 00 Os CN &S £ CO l>N CO CN CO *-* d CN +1 +1 +1 +i +1 SO ID SO OS CO o OS 00 Os cm CN 1-1 d CN # S o in CN 00 o CN d d d d d +1 +i +i +1 +1 so CM CN CO 00 CO so CO 1 00 CM in sO in OS o CM +1 +1 +1 +1 +1 SO CO CM 00 Os 00 00 CO 3 in SO ■3" T— 1 CO CO o o ,_< 00 sO t< T-H ■* ■^ +1 +1 +1 +1 +1 CO CO CM in r-< r— i CO csi CO d CO SO CM IN CO t in vo oo f ^ ^ -v. ■*> v- 2 2 oo so 2 CO Os t—* OS in cm in oo in >^ T3 o> c o "3 2 !iy 01 (0 is CO O > Ol > o 2 £> c <9 40 cm), but had no vitellogenic oocytes. Two large females from the VJ site had very little gonadal material and were very thin. Based upon previous experience with this species in San Francisco Bay (Spies, personal communication); these four fish should have had vitellogenic oocytes during this sampling season. However, based upon their apparent condition they likely would not have spawned. 60 Table 25. Summary of results of analyses of (a) microsomal enzyme activity and (b) plasma steroid hormone analyses in starry flounder (Platichthys stellatus) collected in November-December 1986; means ± standard deviation. _A. Site microsomal enzyme activity AHH (all) AHH w7,8BF (all) AAH (M,l) AMH w7,8BF (M,I) AHH (MF) AHH w7,8BF (MF) Berkeley 78.6 ± 37.8 (14) 24.8 ± 15.2 (14) 86 ±44 (8) Oakland 287.1 ± 227.5 (15) 51.1 ± 34.8 (14) 363 ± 94 (8) Vallejo 250.4 ± 248.2 (14) 54.6 ± 37.8 (14) 279 ± 271 (11) San Pablo Bay 134.2 ± 93.1 (13) 34.2 + 18.5 (8) 138 ± 96 (12) Russian River 64.7 ± 62.4 (15) 25.0 ± 12.3 (15) 75 ± 45 (5) 29 ± 17 (8) 68 ± 28 (6) 19 ± 9 (6) 54 ±34 (7) 200 ± 145 (7) 48 ±37 (7) 59 ±41 (11) 147 ± 105 (3) 37 ± 18 (3) 33 ± 19 (7) 86(1) 45(1) 30 ± 15 (5) 60 ± 71 (10) 22 ± 11 (10) Site Plasma steroids (ug/mL) Testosterone Estradiol MM MF I MM MF I Berkeley 1.2 ±0.41 (4) 0.14 ± .06 (6) 0.15 ±0.19(3) 0.35 ± 0.06 (4) 8.3 ± 5.3 (6) 1.6 ± 1.7 (3) Oakland 1.6(1) 038 + 0.35 (5) 0.26 ± 0.26 (5) 0.81 (1) 10.9 ± 10.7 (5) 0.78 ±0.52 (5) Vallejo 2.2 ± 1.2 (3) 0.48 ± 0.49 (2) 0.68 ± 0.96 (7) 0.36 ± 0.30 (3) 1.9 ± 1.7 (2) 0.50 ± 0.23 (7) San Pablo Bay 1.7 ±1.3 (5) 0.14(1) 0.75 ±0.88 (10) 0.27 ± 0.18 (5) 8.7(1) 0.44 ± 0.23 (10) Russian River 0.5 ± 0.32 (5) 0.2 ± 0.07 (6) 0.12 ± 0.05 (5) 0.34 ±0.16 (5) 7.7 ± 4.7 (6) 0.38 ±0.13 (5) MF - mature female, MM = mature male; I = immature AHH = aryl hydrocarbon hydoxylase activity, pmol 3-OH B(a)P/mg protein/min AHH W7, 8BF = AHH activity with 10-4 M 7,8-benzoflavone added 61 Liver Microsomal Enzyme Activity/Plasma Steroid Hormones/Reproductive Success (January-February). Differences among sites were difficult to detect with the fish from the second collection, since relatively few fish were caught at each site. AHH activity was similar among fish from the three sites (Table 26). Mean testosterone concentrations in BK fish were about one-third those in SC fish. Estradiol concentrations were similar among sites. There was a consistent pattern of lower measures of reproductive success in fish from BK compared to those from SC. The difference between site means was about three fold for percent embryological success, but within-site variability was high. Blood Erythrocyte Micronuclei. The mean number of micronucleated erythrocytes in all fish (both sampling periods) was lowest in fish from the coastal sites (SC and RR) compared to those from the four sites in San Francisco Bay (Table 27). The counts were highest in fish from the VJ and BK sites. OK and SP fish had similar mean values. Variability within each site was high, especially in the fish from BK and OK, where the standard deviations exceeded the means. The proportion of fish with zero micronucleated cells was highest in the fish from the SC and RR sites and lowest at the VJ, SP, and BK sites. In the November-December collection, the mean incidence of micronuclei was distinctly lower in the fish from RR (Table 27). No detached micronuclei were found and 77 percent of the cells had no micronuclei in the RR fish. The highest mean incidences of total and detached micronuclei were in BK, VJ, and SP fish; whereas, the highest mean incidences of attached micronuclei were in OK and BK fish. The incidence of nuclear pleomorphism (loss of the usual elliptical shape of the nucleus) was also recorded in each fish. The percent of the fish with this condition was highest in fish from BK and OK, lower in fish from SP, and lowest in fish from VJ, SC, and RR (Table 28) 62 c 3 O .5 m 01 in m in 01 u v a m 01 > •43 u S T3 O M a « SI s m oi — ' g c 5 * O •>- J3 ► !S *° 'S -o j§ +i ft, m > 6 n) oo 2$ It la a S 51 a£ u 3 -5 o c* (8 « I £ 9 o &3 Xi in E 01 Q4> t£ 00 O tJ< oo tv On CO NO CO +1 w+| rx 00 t^ ^-s NO W NO N /^H +1 w+| ON O NO ID t>> NO Ttf NO fN| O i— ^(N +1 ~+\ NO NO *— I lO LO NO >nT3 C ii CU 63 Table 27 Summary of results of mean counts of micronucleated erythrocytes (per 1000) in blood of Platichthys stellatus collected during two seasons (November-December 1986 and January- February 1987) and collected only in November-December 1986 (means ± standard deviation). Total Detached Attached Proportion of fish Site N Micronuclei Micronuclei Micronuclei with zero micronuclei All Fish Berkeley 42 1.9 ± 2.3 0.7 ± 0.7 1.2 ± 2.2 0.12 Oakland 23 1.5 ±2.1 0.5 ± 0.8 1.0 ±1.7 0.35 Vallejo 22 2.2 ± 1.5 0.9 ± 1.2 0.5 ± 0.5 0.09 San Pablo Bay 29 1.3 ± 1.2 0.7 ± 0.7 0.6 ± 0.8 0.17 Russian River 29 0.4 ± 0.7 0.1 ± 0.4 0.3 ± 0.4 0.66 Santa Cruz 13 0.6 ± 0.8 0.3 ± 0.3 0.4 ± 0.6 0.46 Nov-Dec Berkeley 14 2.4 ± 2.0 1.5 ± 0.8 1.2 ±1.6 0 Oakland 15 1.6 ±2.4 0.4 ± 0.3 1.3 ± 2.0 0.40 Vallejo 13 1.8 ±1.8 1.2 ± 1.5 0.6 ± 0.5 0 San Pablo Bay 12 1.8 ±1.1 1.2 ± 0.8 0.7 ± 0.4 0 Russian River 15 0.1 ± 0.3 0±0 0.1 ± 0.3 0.77 55 29 17 42 65 22 13 23 66 31 3 29 64 36 0 22 77 23 0 13 97 3 0 29 Table 28. Percent of P. stellatus with pleomorphic nuclei (NP). Each fish was rated: 1 if <5% of erythrocytes were pleomorphic; 2 if 5-50% of erythrocytes were pleomorphic; or 3 if >50% of erythrocytes were pleomorphic. N= sample size. Percent with NP rating STATION 1 2 3 Berkeley Oakland San Pablo Bay Vallejo Santa Cruz Russian River Liver Cytochrome P-450 Activity. Data were produced for a variety of end-points involving the cytochrome P-450 system. Values for many of the end-points were recorded for selected fish from one site (BK) injected with B-naphthoflavone (BNF), a known P-450 inducer, and untreated fish from each of the five collection sites. Total cytochrome P-450 content in nanomoles (nmol) per mg microsomal protein represents the native, active enzyme activity. Mean total P-450 content was about three fold higher in treated fish than in equivalent untreated samples (Table 29). Among the five collection sites, the highest mean values were found in fish at the OK site and the lowest were at the SP and RR sites. The differences in site means were less than twofold. 64 EROD activity, expressed as both nmol/min/mg microsomal protein and nmol/min/nmol of total P-450, is catalyzed by the P-450 system. About an 11-fold difference in mean EROD activity was observed between BNF-treated and untreated fish, indicating a very high potential for induction in P. stellatus (Table 29). Mean EROD activity, as nmol/min/mg protein, was highest among fish from the OK site; about 6 times higher than in RR fish and 4 times higher than in SP fish. When expressed as nmol/min/nmol P-450, the activity in BNF-treated fish was roughly fivefold higher than in untreated fish and the mean activity in OK fish was again highest, exceeding that in the RR fish by 4.5 times. Content of the apparent homologue of the BNF-, PCB-, PAH-inducible teleost cytochrome P-450E was determined and expressed as picomoles (pM)/mg microsomal protein (Table 29). Mean P-450E content in BNF-treated fish exceeded that in untreated fish by over 15 fold. Mean P-450E content was highest in field collections in the fish from OK and BK and lowest in fish from SP and RR. The mean value for the OK site exceeded that for SP and the RR site by nearly 14 times. Table 29. Summary of results for total hepatic cytochrome P-450 content, EROD activity, and "P-450E" content in field-sampled Platichthys stellatus collected in November- December (means ± SD) Treatment Total ERODb EROD0 P450Ed or site N P-450a Experimental Control 3 0.135±0.013 0.18610.097 1.43+0.83 11.11 8.3 BNFe 4 0.326±0.046 2.17010.787 6.80+2.68 171.4147.9 Environmental Berkeley 14 0.20010.076 0.12110.090 0.6810.51 16.0126.0 Oakland 15 0.26710.169 0.25910.208 1.4711.02 26.5123.0 Vallejo 14 0.20910.101 0.16110.034 0.62+0.32 3.5 + 6.7 San Pablo 14 0.16810.057 0.06210.030 0.6010.33 1.91 1.8 Russian River 15 0.191+0.070 0.04410.026 0.3210.17 1.91 2.1 a nM/mg protein D nM/min/mg protein c nM/min/nmol total P-450 " pM/mg protein e fish injected with p-naphthoflavone All of these analyses indicate that the fish at the OK site were exposed to the highest concentrations of P-450 enzyme inducers, including hydrocarbons such as PCBs and PAHs. The BK site ranked second by these measures, followed by VA, SP, and the RR sites. However, the values for BNF-treated fish exceeded those for the OK fish by 1.7 to 8.5 times for the measured end-points, indicating the fish from OK were not exposed to exceptionally high or maximally effective contaminant concentrations. 65 The mean levels of cytochrome b5 measured in fish from BK, OK, and RR and in fish injected with BNF were similar (Table 30). This measure likely represents the denatured, inactive form of cytochrome P-450. The origin of this degradation is not certain, but could have resulted from the procedures involved in freezing the liver tissue on dry ice. The levels of cytochrome P-420 also were fairly similar among sites. A major pathway of estradiol metabolism in fish is apparently through 2-hydroxylation. Mean measures of estradiol 2-hydroxylase in BK control and BNF-injected fish were essentially identical when expressed as nmol/min/mg protein, but considerably lower in BNF-injected fish when expressed as a function of total native P-450 content (Table 30). Expressed as nmol/min/nmol native P-450, the mean estradiol 2-hydroxylase activity was lowest in the BK and OK fish. The fish used in the experimental evaluation were immature females. Also, all of the SP fish that were analyzed were immature females. The comparable mean values for immature females from the BK, OK, VJ, SP, and RR sites were: 0.126 ± 0.037, 0.213 + 0.122, 0.246 ± 0.080, 0.299 ± 0.066, and 0.344 ± 0.148 nmol/min/nmol native P-450, respectively. Therefore, these mean values indicated that estradiol hydroxylation was lower in the fish from the two sites (OK and BK) where mean cytochrome P-450 induction was highest. They were highest in the sites (SP and RR) where induction was lowest. Results of analyses of the few fish caught in the January-February collections are summarized in Table 31. No conclusions can be drawn from the data because of the small sample size. Total cytochrome P-450 activity was very high in SC fish, but a large proportion of that activity was represented by cytochrome P-420, the putative inactive form. 66 i •a 8 a X ° (9 in UJ a in V 2 •a 6 fl o in u 21 •M X "8 ■£ o § > CS u "5 ■5 ~ "O c/> B 5 UJ « 2 a, • * -u 2 .. "> -v B B re .n bS o to o w T W N (X -8 f B ai 6° 2 B o "a S B 6S •S n o O >_ 2 fr-g " B «J 01 B > «j 41 O o bZ 3 8.5 a. in x> -a a> £ V o B ^ S a u O -£• *- vi fr£ »S 2 V > IT> im j; X> o *» -c O) 6 o 5 5 3 0, 41 w o B h N 4, >, U s*« "O o B rJ 2 h 3 fl ts . s o ■" ">* 41 •-" •a > D. X w s-i r^ t^ 00 o o noOvooo O r- O O i-c o o o o o o o -H -H -H +1 +1 +1 +1 en i-j r|i-;N(NN o o o o o o o en ^t CO ^ QQ 22 QQ 22 os en O i-i p p o o +1 -H 1 o I \o o o 5 en "* C 73 Si O 01 B u t; 01 6 B o "3 -T u •£ ^ ai 2 CQ CO u CCNiflUlo r-i 00 T— ' I— 1 o o OO\N00r- i— < r-< t—i O r-< o o o o o o o o © o o o -H -H -H +4 -H -H +1 CM ^h in in o o ih(|)NP1N O O O O O o o o o o oo \fi oo r-3 cn eN en en en ■^ in ■* •* in ■^ en o ^h o o +1 -H es -^" oo tN o t-- & •& m \o cn en o o o o o o -H -H -H •^ r— £ B 0 2 b 0) A! 03 3 ^CJ '53 0) e3 a o> 3 01 s 01 J5 01 J3 rx a. ™ o in t ■§ 2 I "S l. o CX 4, 6 2 -i- 01 g K B S B CX o m CU 01 Si 5 2 « rxo bo e £ b "^ > B .5 1 B ^ ^» b E nj ja o TJ 67 3 0.188 ± .077 0.071 ±0.011 0.680 ± 0.226 1 0.278 0.108 0.103 2 0.358 ± 0.138 0.082 ± 0.026 0.915 ± .559 Table 31. Summary of results for total cytochrome P-450 content and EROD activity in Platichthys stellatus sampled in January-February 1987. Treatment Total ERODb ERODc or site N P-450a Berkeley Oakland Santa Cruz a nmol/mg protein b nmol/min/mg protein c nmol/min/nmol total P-450 Relative Sensitivity of Bioeffects Measures in Fish Very few fish were caught in the January-February collections. The measures of spawning success, therefore, are difficult to interpret. A pattern of decreased success in fish from BK relative to those from outer coastal site at SC is suggested by the data, but the small sample sizes preclude drawing many conclusions. In many years of previous research with this species in San Francisco, significant differences in fertilization success and larval hatching success have been recorded among sites. Fish from the BK and OK sites have generally indicated impaired reproductive success compared to those from SP, SC, and other sites (Spies et ah, 1985; Spies and Rice, 1988). The measures of AHH and cytochrome P-450 activities in fish caught in January-February are equally difficult to interpret because of the small sample sizes. The measures of micronuclei in the January-February fish were pooled with those made on November-December fish. Therefore, the discussion of the biological measures in fish will be confined to those performed with fish caught in November and December. The data from the biological measures of the health of the fish caught in November and December were not normally distributed (Kolmogorov-Smirnov test). Following various transformations of the data, they remained not normally distributed. Therefore, non- parametric statistical tests generally were performed with the fish data. Based upon the non-parametric K-W test, there were no significant differences among sites in length (p = 0.106), weight (p = 0.113), GSI (p = 0.122), HSI (p = 0.708), and liver weight (p = 0.248) among females. Among the males, there were differences among sites in these measures: length (p = 0.014), weight (p = 0.010), GSI (p = 0.029), HSI ( p = 0.200), and liver weight (0.0495). However, non-parametric S-N-K tests could not identify which sites were different. Generally, the fish from the RR site were larger and those from the OK site were smaller than the others. Both EROD and cytochrome P-450E measurements indicated a similar pattern of relatively high induction of the cytochrome P-450 system in fish, especially immatures, from the BK and OK sites and low induction in fish from the SP, VJ, and RR sites. EROD activity, expressed as either units per mg protein or units per nmol P-450, indicated differences between sites (p = 0.0004 and p = 0.003, respectively): higher in immature fish from OK than in mature fish from SP, RR, and BK and immatures from RR (Table 32). Mean EROD activities in mature OK fish and immature BK fish were also relatively high, but not significantly different from those at other sites. Cytochrome P-450E activity per mg protein was significantly higher in immature OK fish than in mature fish from RR and SP 68 (p = 0.0011). When expressed in proportion to total P-450 content, the P-450E content was greater in immature OK fish than in mature SP, VJ and RR fish. Mean total P-450 content and P-420 content were highest in fish from OK, but there were no significant differences (p = .183 and 0.786, respectively) among sites (Table 32). Also, there were no significant differences (p = 0.385) among sites in percent denatured P-450 content. Cytochrome bs content did not differ between RR and OK fish (Mann-Whitney, p = 0.756). Two-way ANOVA (performed despite the fact that the data were not normally distributed) indicated there were no differences (p = 0.09 to 0.98) in any of the P-450 measurements between sites that were attributable to sex. However, both EROD activity and P-450E content/mg protein in immature fish exceeded those measures in mature fish. Estradiol 2-hydroxylase activity/mg protein did not differ significantly (p = 0.94) among sites. However, estradiol 2-hydroxylase/nmol P-450 content did differ significantly (p < 0.01) among sites (Table 32). The average values were lowest in mature BK fish where cytochrome P-450 induction was among the highest and highest in immature fish from SP. Consistent with this pattern was the observation (Table 30) that estradiol 2-hydroxylase activity in fish injected with BNF was about one-half that in untreated fish. This measure was significantly (p = 0.007) lower in mature females than in immature females. AHH activity was generally higher in immature fish than in mature fish. Significant between-site differences in AHH activity were indicated at p = 0.001, but non-parametric S-N-K could not distinguish which sites were different. The mean AHH values in fish in which the samples had been exposed to 7,8 benzflavone were generally one-third to one- fifth those of fish not exposed to this P-450 isozyme inhibitor. Estradiol concentration in plasma was not significantly different among sites (p = 0.94) (Table 32). The overall mean value in VJ fish, which were mostly immature, was about one- fifth that in fish from OK which included more matures. Since estradiol suppresses the induction of P-450E, an inverse relationship between estradiol content and P-450E content and EROD activity would be expected. But, this relationship was not obvious with the present data. As would be expected, mature females had higher plasma estradiol concentrations than immatures. Testosterone concentrations also did not differ significantly among sites (p = 0.40) (Table 32). Among the fish caught in November and December, the incidence of total counts of micronuclei in blood erythrocytes was significantly different among sites (non-parametric K-W, p = 0.0001). Non-parametric S-N-K indicated that counts were lower in RR than in SP, VJ and BK fish (Table 32). Incidences among the four sites in San Francisco Bay did not differ. Counts of both attached and detached micronuclei were recorded. The incidences of attached micronuclei in all fish did not differ significantly among sites (p = 0.061). However, the incidence of detached micronuclei did differ between sites (p = 0.001) with the same pattern as observed with total counts. The incidence of both forms did not differ among sites in males. However, total incidence and incidence of detached micronuclei were significantly lower in females from RR than in females from three other sites. The highest nuclear pleomorphism rating was observed in fish from the Berkeley and Oakland sites (Table 28). There was a significant difference in the incidence of this end- point among fish collected in November-December and January-February from the six sites (X^ = 11.07, p < 0.001). Because of the high frequency of zeros for class 3, classes 2 and 3 were combined. Fish from the RR site had the lowest incidence (Table 28). With these fish removed, the incidence was not significantly different at the remaining sites ( X^ = 2.42, df = 4, p > 0.50). 69 Table 32. Results of non-parametric Kruskal-Wallis tests of differences3 in biological measures in Platichthys stellatus collected at five sites in November and December 1986. Underlines indicate sites that were not different from each other (upper case for mature fish, lower case for immatures). Biological Measure (Increasing Toxicity) » EROD/mg protein EROD/nmol P-450 P-450E/mg protein P-450E/nmol P-450 Total P-450/mg protein P-420/mg protein Denatured P-450 (%) Cytochrome bs/mg protein0 Estradiol 2-OH/mg (females) Estradiol 2-OH/nmol P-450 (temales) AHH AHH with 7,8-BF Estradiol (mature females) Testosterone (males) Total Micronuclei Detached micronuclei Attached micronuclei rr SP RR BK sp VJ vj OK bk ok rr RR SP BK VJ sp vj OK bk ok SP RR VJ vi rr BK sd OK bk ok SP VJ RR vj BK rr sp bk OK ok SE. RR _VJ BK OK §£_ RR BK VJ QK SH yi. RR OK BK RR OK SP. SSL RR VJ BK BK OK RR VJ SP RR SP BK rr bk vj sp OK VJ ok BK RR bk. rr SP vj OK sp ok VJ RR OK BK VJ SP BJS m RR OK SP VJ BK RR OK SP VJ BK RR OK VJ BK SP a p< 0.05 D Mann-Whitney test 70 Fish Contaminant Concentrations: Results Data were produced for individual chlorinated organic compounds in the livers of the fish (normalized to wet weight in Appendix D, normalized to lipid weight in Appendix E). Mean values for sums of the six DDT/DDD/DDE isomers, many pesticides (hexachlorobenzene, lindane, heptachlor, aldrin, heptachlor epoxide, chlordane, transnonachlor, dieldrin, mirex), and tPCBs (based upon sums of the estimated concentrations of Aroclors 1242, 1254, and 1260) are listed in Table 33. The estimates of Aroclor concentrations are based upon the concentrations of only one IUPAC congener each, and, therefore, may not be very accurate estimates. Lipid content of the SC fish was about one- half that of fish from the other sites. Normalized to lipid content, the mean tDDT concentration was highest in fish from the OK, SC, VJ, and BK sites. Total pesticide concentrations, especially dieldrin in two fish, were highest in SC fish and considerably lower and relatively similar among fish from the other sites. Total PCB concentrations were highest in BK and OK fish. PCB concentrations were lowest in SP, RR, and VJ fish. Of the 74 fish analyzed, 13 had total PCB concentrations that exceeded 10 M-g/g lipid weight; all but one were from the BK and OK site (Appendix E). One of those fish from OK also had the highest concentrations of chlordane, transnonachlor, mirex, p,p-DDE, and tDDT of all the fish. One fish from RR had the highest dieldrin concentration (1.53 |ig/g lipid weight) of all the fish. One fish each from the BK and OK sites had about 30 |ig/g lipid weight tPCB concentrations, roughly three times higher than the site means. Table 33. Summary of contaminant data for Platichthys stellatus liver tissue from six sites (mean ± SD). Site ug/g lipid weight g lipid/g liver Total DDT Total Pesticides3 Total PCBsb Berkeley (n = 14) 0.17 ± 0.08 1.28 ± 0.8 0.45 ± 0.2 9.68 ± 7.7 Oakland (n = 15) 0.14 ± 0.07 1.68 ± 1.7 0.69 ± 0.5 12.48 ± 8.8 Russian River (n = 14) 0.13 ± 0.06 0.92 ± 0.9 0.44 ± 0.5 3.50 ± 2.9 Santa Cruz (n = 4) 0.07 ± 0.03 1.63 ±0.9 1.77 ±1.6 6.09±3.0 San Pablo Bay (n = 14) 0.18 ± 0.04 0.92 ± 0.4 0.39 ± 0.2 1.68 ± 1.5 Vallejo (n = 14) 0.14 ± 0.05 1.37 ±1.2 0.36 ±0.1 3.45 ± 3.6 a Sum of concentrations of lindane, heptachlor, aldrin, heptachlor epoxide, chlordane, transnonachlor, dieldrin, and mirex. b Sum of estimated concentrations of Aroclors 1242, 1254, and 1260. Table 34 summarizes the results of an analysis of variance of the chemical data from five sampling sites. Although o,p-DDT concentrations were higher at OK than at all other sites and p,p-DDD concentrations were higher in BK, OK and SP fish than in RR fish, there were no significant differences between sites in p,p-DDT, p,p-DDE or in the sum of resolved forms of DDT-type compounds (Table 34). No single DDT isomer accounted for the majority of the variation in the DDT concentration, according to Principal Components Analysis. Fish from either OK or BK generally had the highest concentrations of many of the pesticides that were quantified (Table 34). Although the lowest concentrations of lindane were in fish from RR, the highest concentrations of heptachlor epoxide were found in those fish. No significant site differences were found in heptachlor or dieldrin concentrations. Aldrin, tDDT, transnonachlor and mirex accounted for 50 percent of the variation among pesticides. 71 Significantly higher concentrations of Aroclor 1254, Aroclor 1260, and a sum of three aroclors were found in the OK and BK fish. Aroclor 1242, in contrast, was higher in RR fish than in BK fish. About one-third of the PCB congeners (IUPAC 8, 44, 66, 153, 101, 206) accounted for 58 percent of the variance among the PCBs. Lipid-normalized concentrations of contaminants in liver were generally not related to length or weight of the fish. Also, no significant correlations were apparent between gonad weight, liver weight, GSI and HSI and the concentrations of contaminants. These observations pertained to both the complete collection of November-December fish and to fish collected at individual sites. No consistent pattern in contamination was apparent for all the quantified chemicals among the sites. Fish from one site with the highest concentrations of one group of compounds did not necessarily have the highest concentrations of the others. For example, fish from the BK and OK sites had the highest tPCB concentrations, but among the lowest concentrations of heptachlor epoxide. Fish from the VJ site had relatively high DDE concentrations, but concentrations of other pesticides in those fish were relatively low. Fish from the RR site were surprisingly contaminated with PCBs relative to those from VJ and SP. However, the RR fish were larger than those from the other sites. The relative similarity in mean contaminant levels between BK and OK reflected the proximity of these two sites to each other. Overall, the fish from the SP, RR, and SC sites were generally the least contaminated, and those from the BK and OK sites were generally the most highly contaminated. Within-site variability was relatively high, as indicated by high standard deviations relative to the means. Some degree of variability in contaminant levels is to be expected in a population of feral fish because of their mobility. However, it is possible that these fish were exposed to and were affected by readily metabolized and nonquantified compounds, such as aromatic hydrocarbons, that may have been partially or wholly responsible for the induction of the biological measures. If the latter case pertained, then a strong correspondence between the biological data and the quantified chemical data would not be expected. 72 Table 34. Summary of results of 1-way ANOVA for chemical data in Platichthys stellatus collected at five sites in November and December 1986. Underlines connect sites that were not different. DECREASING CONCENTRATIONS > o,p - DDT p,p - DDT p,p - DDD p,p - DDE I DDT Lindane Heptachlor Heptachlor epoxide Transnonachlor Dieldrin Mi rex Aroclor 1242 Aroclor 1254 Aroclor 1260 ZPCB OK BK SP VI RR BK OK RR SP VI OK BK VI SP VJ RR RR OK BK SP OK BK RR VI SP BK SP VI OK RR BK OK RR VI SP RR VI SP OK BK OK BK RR VI SP OK RR BK SP VI OK RR VJ SP BK RR SP VI OK BK OK BK OK BK OK BK RR VJ_ RR YJ_ RR VJ_ SP SP SP Correlations Among Biological Measures in Fish. Table 35 summarizes the results of a qualitative Spearman rank correlation analysis between measures of length and weight of the fish and the measures of effects. Very few of the correlations were particularly high. Cytochrome P-450E was relatively highly inversely correlated with HSI. Estradiol 2-hydroxylase was relatively highly positively correlated with length, weight, and GSI. 73 Table 35. Spearman rank correlations between measures of bioeffects in fish and measures of length, weight, GSI, and HSI. Standard Length Weight GSI HSI AHH -.248 -.238 -.329 -.157 Mean total micronuclei -.064 -.093 -.032 .140 Cytochrome P-450E -.272 -.245 -.293 -.574 EROD/mg protein -.281* -.302 -.276 -.206 EROD/P-450 -.381 -.357 -.331 -.274 Cytochrome P-450 .015 .022 -.069 -.085 Cytochrome P-420 -.004 .022 -.014 .139 Percent denaturated P-450 -.037 -.005 -.012 .101 Total P-450E/total P-450 -.245 -.204 -.248 -.557 Testosterone -.131 -.148 .112 .335 Estradiol 2-hydroxylase .415 .478 .507 .264 Total P-450 .076 .074 -.001 .078 Spearman rank correlation analysis among the various measures of effects also did not show many high correlations (Table 36). AHH activity was most highly correlated with EROD activity, as would be expected. Many of the suite of cytochrome P-450 measures (i.e., total P-450, EROD, P-450E) were most highly correlated with each other. The counts of total micronuclei were not very highly correlated with the other measures. Measures of testosterone and estradiol 2-hydroxylase content were not highly correlated with the other measures. Correlations Among Bioeffects Measures and Contaminant Concentrations in Fish. None of the biological measures was particularly highly correlated with any of the chemical contaminants in the livers of the fish (Table 37). Total counts of micronuclei were most highly correlated (negatively) with mirex and aldrin concentrations. Cytochrome P- 450 and P-450E content and EROD activities were weakly positively correlated with tPCB concentrations. Estradiol 2-hydroxylase activity was relatively highly correlated with dieldrin concentrations. No single chemical or chemical class stood out as consistently being correlated with the biological measures. Within-Site Variability in Bioeffects Measures in Fish. Analytical variability, as evaluated with the sediment bioassays, could not be evaluated with the bioeffects measures in fish, since replicate analyses of individual fish were not performed on all the fish with all of the measures. However, within-site variability and between-site discriminatory power can be compared among measures, since all of the measures were performed on the same fish. Within-site variability among fish can be viewed two (opposing) ways. First, if one assumes that individual fish sampled within one area (site) had different histories of exposure to contaminants, then a bioeffects measure that has high within-site variability may simply reflect that variability if the measure is especially sensitive. If, on the other hand, one assumes that the fish sampled in one area (site) are from a relatively homogeneous population and, therefore, all the individuals have had a similar history of contaminant exposure, then a bioeffects measure with high within-site variability may indicate relatively low analytical precision. Unfortunately, Platichthys stellatus migrate in and out of San Francisco Bay annually and little is known of the fidelity of the returning adults to specific areas of the estuary. Although Spies et al. (1985, 1988) have demonstrated differences in measures of contaminants 74 in tissues and measures of bioeffects between sites in the bay, they also observed sufficient within-site variability to suggest that all the fisli from any one site were not from a distinct population with identical histories of contaminant exposure. An assortment of natural environmental factors and biological variables can influence within-site variability in the fish bioeffects measures. They could include genotype, gender, degree of maturation, stress preceding capture, stress during capture, and feeding success. Any combination of these and other factors may have contributed to the variability among fish within the sampling sites. Coefficients of variation in the biological measures performed on fish caught at each site in November and December differed among the measures (Table 38). The measures of total and attached micronuclei had high within-site variation. The analysis for cytochrome P-450E/mg protein also indicated relatively high variation. The coefficients of variation for testosterone, estradiol-2-hydroxylase/mg protein, total cytochrome P-450/mg protein, EROD/mg protein, and AHH with 7,8-BF were relatively small at most sites. Based upon data in Table 31, the chemical data from the BK and SP sites were the least variable. However, there was no apparent pattern of lower within-site variation in the biological measures in the fish from those two sites. The maximum and minimum site means, the total range in mean values, the average of the SDs, the average of the CVs, and the quotient of dividing the range by the average SD are listed in Table 39. The average CVs were highest for the end-points of attached and total micronuclei and cytochrome P-450E and lowest for total cytochrome P-450 and estradiol- 2-hydroxylase/mg protein. The quotients of total range over the average SDs were highest for EROD/mg protein and EROD/nmol P-450. By comparison, these values were relatively low for total P-450, attached micronuclei, and AHH following exposure to 7,8-benzflavone. 75 a u at MH MH u o C ai 01 in C o •*H ti o u 1 C/5 NO CO ■a o y a c 2 O in s w c Ph e s in 9 b 61 * AGO U uPh S"2 | o 7 tn Pt, at 3 (A (S O 01 4~l si .2 | O ID o ON t^ CM O oo ro O "* ift O •>* i-i \C 00 r— CO Tt1 On ts ^o NO CO co ^ Tj< o\ t^ *t ^J1 tv CM Cx CO 00 rt< 00 oo(sno4'C If) OmC N N N >C Oi nOOiOONNClHHIf) OOr-iO'-'OOOOcO 00 On IT) i— i— i On CM t*» On >C H N NIT) t^^i— i^-o rt I- l(*)Tf r- iOnKOOOi— I 01 (0 ■£, X o UJ o c 7 r 5,° •""in £ o b SOO >^« u w w o o o IT) CM IT) 7 7 7 Ch Ph Ph o o 3 u u £ p II o [ft 7 01 c CM ■v. s en "5 o O ffl in 7 en fUHW 76 X s g o u O 33 M Xi ai m > H •—I pa y w H Q D x >- 5 o m c nj t. O — U A 0> 3 4= u 0) ■a 8SiHr)«ooff>omMmo\ i— ii— 'CMCNOOOr-iOCNO l— ifSOOOi- O i— (N O O ^r i— i tonooinNn ■* r000600O^0>»>0rHT- O i— i ■ OON N(N rn in n oo vo * o\ SrHNnovooininooroo (SNOOOOi-iMDtN o\ t^ <-h O CN CO i-i i-H CM fS cn\0 0\0\NNM» i— ioc)Hoon>oo\ OHNNOOOH IT) "* O i-i O ^ PU oi m 3 c o b Ph £ o 3 it « soo < H U w w c Is Ph P- l-^H o 01 OJ £ £ o o -8 i- 2 ra c "0 LT, T 01 c £ ytochr ytochr UJ o in -r O hi UU^fch o> « o cm t .2 + ■oo « m en ri 77 .c o O. C 3 O ■a o E o r « a n a 3 » a a> E O) o o £ ■a « *- u o o (A i- 0 "^ 03 CO ai o T- o ^ H X J3 E ""* 41 1 X O **» 01 a Q w 73 C CO c 0 o *- £> .2 CD E o > > o «^ z 0 c (A — C 0) o 01 u u5 £ a m o > o •^ ^* CO oo* co ■o CD o u o J3 ~ a o K o *^ X O o in CM ^t D. o T3 o ra E Tn c LU -^ I O a CM £ o O a T3 a a E v> LU Ol E c LU • o o in * a a. o E o c IT) Q f O a. cc LU CD f c Q 2 O o CC Q. LU O ra in o -* 1- 0. t> o c» O SZ 3 u c ra o < o 2 \ CJ x: rs § c 2 3 o 2 2 o s D C o O t- o 2 o "5T T3 co ra ra E s o LU Q) C o Crt 2 0) ui ra o ^ U) CD 1- u. CO X CO X f- < JZ i X X < 0) c7> v co m in co S2 to r-! is! ^ J; cm gj r^ in oo _ co oo CO O - r^ cnJ ° • <° n co cm in o CO CO Ol 7 r" CO 0) 00 CO cm in in o * z * 09 •*' co in is. oa CO •- CM «- CM r CO Cfl t co co co in CO en 0) 05 CO en ■>t Is. o> CO 01 Is. rfi > Ill nr m CO T3 o ra •o°- c ID co § LU > CO ra C0 § CO 3 < m U > en CC 78 Table 39. Maximum and minimum site means, total ranges among site means, averages of the site SDs and CVs, and the quotient of dividing the range by the average SD for selected bioeffects measures in Platichthys stellatus. Maximum Minimum Total Average Average Range/ Site Mean Site Mean Range SD CV Average SD AHH (all fish) 287.1 64.7 222.4 133.8 78.4 1.7 AHH with 7,8-BF (all) 54.6 24.8 29.8 23.7 60.4 1.3 Testosterone (males) 2.2 0.5 1.7 0.8 57.3 2.1 Estradiol (females) 10.9 1.9 9.0 5.6 78.1 1.6 Total micronuclei* 2.4 0.1 2.3 1.5 140.5 1.5 Detached micronuclei* 1.5 0 1.5 0.7 82.3 2.1 Attached micronuclei* 1.3 0.1 1.2 1.0 149.1 1.2 Total P-450 0.267 0.168 0.099 0.095 44.0 1.0 EROD/mg protein 0.259 0.044 0.215 0.078 56.7 2.8 EROD/nmol P^50 1.47 0.32 1.15 0.47 60.8 2.4 P-450E 26.5 1.9 24.6 11.9 129.2 2.1 Estradiol 2-OH'ase/mg prote in 0.038 0.016 0.022 0.012 50.8 1.8 Estradiol 2-OH'ase/nmol P-450 0.299 0.101 0.198 0.091 62.4 2.2 * November - December fish DISCUSSION AND CONCLUSIONS Sediment Toxicity Tests Mytilus edulis. The bivalve larvae bioassay was initially developed for use in testing the toxicity of water and effluents, particularly pulp mill wastes in Puget Sound. Its initial use in sediment tests was reported by Chapman and Morgan, 1983. The embryos of oysters were initially used in the tests. The test has been used as a relatively quick and inexpensive indicator of sediment toxicity. Embryos generally can be acquired throughout most of the year, although with more difficulty during the winter. However, since the embryos of both oysters and mussels do not seek and colonize soft-bottom sediments, the test may be most appropriately viewed as an indicator test with less ecological relevance than, say, a solid phase test with an infaunal or epibenthic species. Protocols have been developed for the performance of the test. These protocols (Chapman and Becker, 1986), specify that at least 70 percent of the larvae must survive in seawater controls and that at least 90 percent of the larvae develop normally. These protocols recommended that either oyster larvae or mussel larvae could be used in the tests. Out of 60 stations sampled in the industrial waterways of Commencement Bay, normal development of oyster larvae was 70 percent or less in samples from 18 (30%) of the stations (Williams et a\., 1986). No normal larvae were observed in a test of one of the stations, less than 40 percent were normal in tests of five of the stations. In four samples from a rural reference area, Carr Inlet, mean percent normal development was 87 percent. About 96 percent of the larvae developed normally in seawater controls. In other research conducted in Puget Sound, less than 80 percent normal development was observed in 3 of 10 (30%) stations sampled in Bellingham Bay, 3 of 6 (50%) stations sampled in Everett Inner Harbor, 4 of 4 (100%) stations sampled in the Duwamish Waterway near Seattle, and 6 of 9 (67%) stations sampled in the Commencement Bay waterways (Long, 1985). Mean normal development was less than 40 percent in samples from Islais Waterway, off Port of San Francisco piers 94/96, off Hunters Point, and off Treasure Island tested with oyster or mussel larvae by various investigators (Long et al., 1988). By comparison, mean normal development 79 of mussel larvae in the present study exceeded 90 percent in both seawater and sediment controls and was less than 75 percent in the OA site sediments. Therefore, in comparison with some samples from highly contaminated waterways elsewhere in San Francisco Bay and in parts of Puget Sound, the samples tested in the present study were not as toxic to mussel larvae. Mean survival of oyster larvae was less than 50 percent in 8 of 10 (80%) samples from Bellingham Bay, 6 of 6 (100%) samples from Everett Inner Harbor, 4 of 4 (100%) samples from the Duwamish Waterway, and 8 of 9 (89%) samples from the Commencement Bay waterways (Long, 1985). Mean survival of mussel larvae was less than 15 percent in samples from the Islais Waterway, 24 to 50 percent in samples collected off the Alameda Naval Air Station and 50 to 83 percent in samples from the SP site tested in 1985 (Chapman et al, 1987). By comparison, 76 percent of the mussel larvae survived exposure to sediment controls in the present experiment. As few as 29 percent survived in tests of sediments from the OA site. Again, the survival end-point of this test indicated a degree of response that was somewhat less than that observed in other studies of very highly contaminated sediments. The adult mussels can be induced to spawn year-round as exemplified in this study. The tests were performed in February. However, several investigators have experienced problems, especially with oysters, in attempting to induce bivalves to spawn in the winter (Joe Cummins, US EPA; Paul Dinnel, University of Washington; Peter Chapman, E.V.S. Consultants, personal communications). The high sensitivity of the M. edulis larvae test observed in this evaluation was also reported by Chapman et al. (1987) in a previous study in San Francisco Bay in which six toxicity end-points were measured. In that study, the end-points of percent abnormal development and percent survival of M. edulis indicated that the most samples, 5 of 9 and 8 of 9, respectively, were "toxic" relative to controls. However, Williams et al. (1986) reported that a similar test performed with oyster larvae (Crassostrea gigas) was the least sensitive of three that were evaluated. It indicated 35 percent of the samples from Commencement Bay waterways were "toxic" relative to controls, compared to 39 percent for R. abronius and 63 percent for a Microtox™ test. In the data reported by Chapman et al. (1987), the analytical precision was somewhat lower (average CVs were 25% and 32.5%, respectively, for percent abnormal and percent survival) than in the present evaluation (average CVs of 3.9 and 22.6%, respectively). The positive correlations between the results of this test and the texture and TOC content of the sediments have not been quantified through empirical experimentation. However, similar to the results observed here, Chapman et al. (1987) often observed highest toxicity in samples that had the highest percent fines and TOC content, as well as the highest concentrations of toxicants. In this evaluation, fine-grained, organically enriched samples that were apparently not contaminated with the quantified analytes were also toxic to this organism. In conclusion, although the end-point of abnormal development of this test was the most sensitive and had the highest precision and discriminatory power of the five evaluated, it also may be sensitive to "nuisance variables" (Bayne et al., 1988) such as sedimentological properties and/or it may be a sensitive indicator of the toxicity of sediments contaminated with chemicals that are not routinely quantified in chemical analyses. Similar to the results reported here, the data from the M. edulis test and the R. abronius test previously have indicated very high concordance with each other (Williams et al., 1986; Chapman et al., 1987). Rhepoxynius abronius. This test has been developed and evaluated through extensive research (e.g., Swartz et al., 1985). The life history and sensitivity of the animal to many toxicants and sediment types has been described (e.g., Swartz et al., 1985). The species normally burrows in surface sediments and, therefore, is appropriate for use in solid phase tests. Populations in Yaquina Bay, Oregon and off Whidbey Island, Washington have been sampled year-round for use in toxicity tests. The analytical precision of the test has been quantified and compared among five laboratories (Mearns et ah, 1986). 80 In the development of the R. abrotiius test protocols, Swartz et al. (1985) observed that with 5 replicates per treatment and 20 amphipods per replicate the test is 75 percent certain of detecting statistical significance (p<0.05) if the difference in mean survival between control and test sediments is 2.8. With the mean control survival of 19.0 that they suggest, this difference corresponds with mean survival of 16.2 or less in test sediment, roughly a 15 percent reduction in survival. The relatively high sensitivity of R. abronius survival has been reported in previous inter-method comparisons (Swartz et al, 1979, 1985; Williams et al, 1986; Chapman et al, 1987). In an inter-laboratory comparison of the R. abronius toxicity test, Mearns et al. (1986) found that survival greater than 87 percent clearly indicated sediments were not toxic and survival less than 76 percent clearly classified sediments as toxic. An overall mean of 19.2 ±1.1 amphipods survived in control sediments. The minimum mean survival was 15.8 ± 2.4 in a sample from Sinclair Inlet near Bremerton, Washington and 3.8 ± 3.1 in a sample spiked with 12 mg/kg cadmium. Mean emergence in control sediments was 0.4 amphipods out of 20. In that comparison, all five laboratories agreed in the ranking of test samples according to survival, emergence, and reburial end-points. At least four of the five laboratories agreed on mean values for the samples for the three end- points. Based upon the results of these two evaluations of the methods, mean survival in test sediments of 15.0 or fewer amphipods may be used as a conservative criterion for classifying a sample as "toxic." Out of 129 sediment samples from the industrial waterways of Commencement Bay, Washington, 92 (71.3 percent) were "toxic," i.e. 15 or fewer survivors (Swartz et al, 1982). Using the same criterion, 6 of 8 samples (75%) were toxic in inner Everett Harbor, Washington; 10 of 17 samples (59%) were toxic in Sinclair Inlet, Washington; and 5 of 10 samples (50%) were toxic off a major combined sewer overflow near Seattle (Battelle, 1986). None of the 15 samples collected at sites on the Palos Verdes shelf and in Santa Monica Bay, California resulted in 15 or fewer survivors (Swartz et al, 1986). Percent survival in sediments collected in 1984 from the Commencement Bay waterways was 25 percent or less in 23 of 60 samples (38.3%) (Williams et al, 1986). There were no survivors in a sample taken near a defunct metal smelter. Low survival of amphipods has been observed in samples from parts of San Francisco Bay (Long et al, 1988). The lowest mean survival rate (34.5%) in two deep cores taken off Hunters Point exceeded the mean (47%) observed in 10 samples from Islais Waterway. A grand mean survival of 11.0 percent was observed in 26 samples from South Bay tested with R. abronius (Baumgartner, unpublished manuscript). By comparison with the results from other studies, mean survival in the present study exceeded 75 percent at only 3 of the 15 stations sampled; therefore, 12 of 15 were "toxic," using the criterion stated above. The average CV reported here (21.4%) was exactly the same as that for data from nine samples reported by Chapman et al. (1987) and very similar to that (22.4%) for data from seven samples reported by Mearns et al. (1986). Also, the high analytical variance (average CV of 83.5%) for the avoidance end-point observed in this evaluation has been observed elsewhere: 65.7 percent in nine samples (Chapman et al, 1987); and 111.2 percent in seven samples (Mearns et al, 1986). Despite the correlations observed by Swartz et al. (1985) between sediment avoidance by R. abronius and the cadmium concentrations and the relatively good agreement among five laboratories in this end-point (Mearns et al, 1986), the avoidance end-point in this evaluation performed relatively poorly. Within-sample variability was very high, between-sample discriminatory power was low, the data did not correlate very highly with chemical concentrations, nor did they correlate with the data from the other tests. Also, the reburial end-point was not responsive at all, corroborating the observation of Swartz et al (1985) that failure to rebury was very rare among survivors of the 10-d tests. The negative correlations between R. abronius survival and both percent clay and TOC content corroborates this relationship demonstrated quantitatively in empirical experiments conducted by DeWitt et al. (1988). R. abronius normally occurs in well-sorted, fine sands and usually not in muddier sediments. Therefore, some degree of mortality observed in toxicity tests is probably attributable to the presence of fine-grained sediments when such samples are tested DeWitt et al. (1988) examined the possible role of particle size on R. abronius 81 mortality and observed, on average, 15 percent lower survival in uncontaminated fine- grained sediments than in uncontaminated coarse-grained sediments. They concluded, however, that particle size is probably just a "super-variable" that is correlated with the actual cause of mortality. The 15 percent effect of grain size, alone, upon survival would not explain the magnitude of the response observed in apparently uncontaminated sediments tested in this evaluation. In conclusion, the test of R. abronius survival was among the most sensitive bioassays and had a relatively wide range in response, a relatively high discriminatory power and intermediate precision; however, survival may be influenced by sedimentological variables and the end-points of reburial and avoidance appear to be relatively insensitive and/or highly variable. Ampelisca abdita. As opposed to R. abronius, which is a burrowing species, A. abdita forms mud tubes on the surface of fine-grained sediments. This species is indigenous to the New England area, but also has been introduced to San Francisco Bay where it is very abundant (Hopkins, 1986). The development of the A. abdita toxicity test has not yet progressed as far as that with R. abronius. Initial work with the test animal has indicated that it is not sensitive to uncontaminated fine-grained sediments, that it may be sensitive to coarse- grained sediments, and that it is somewhat less sensitive to contaminated sediments than R. abronius. In an evaluation of dredged material from Black Rock Harbor (BRH), Connecticut, Rogerson et ah (1985) observed acute toxicity in only one of ten species that was tested: Ampelisca abdita. They calculated a 96-h LC 50 of about 28 percent BRH material. A maximum of 84.8 percent mortality was observed in 50 percent BRH treatments tested for 96 hours. The ability of the test animal to build tubes was also impaired by exposure to all BRH treatments. Variability in test results due to the location of the test animal collection site was observed. In accompanying tests, Scott and Redmond (in press) observed effects of BRH material upon growth rate, egg production, and population growth. They also recorded dose-responsive mortality in chronic 18-, 32-, and 58-day tests. For example, in the 18-day exposures mortality was 9 percent, 98 percent and 100 percent in treatments that were 0 percent BRH/100 percent reference material, 25 percent BRH, and 50 percent BRH, respectively. Recent unpublished tests of sediments from New Bedford Harbor, Connecticut also have shown high toxicity of some samples: Over 90 percent mortality in samples from two sites in the inner harbor in 10-day exposures. In comparison, a maximum of 34 percent mortality was observed among the 15 samples tested in the present study with no dilution. In the present evaluation, mortalities in the control sediments exceeded those in some of the test samples and probably resulted in the underestimation of the potential sensitivity of this test. As a result, the end-point of survival was relatively insensitive, indicating a significant difference from controls in only 1 of the 15 samples tested; a sample from the Oakland Inner Harbor that was among the most contaminated. The sensitivity of this test, as determined in the present evaluation, may have been greater if the survival of A. abdita in the controls had been higher. The concentrations of PCBs and many trace metals were generally more than an order of magnitude higher in Black Rock Harbor sediments (Rogerson et al., 1985) than in those from Oakland Inner Harbor. The toxicity test results with Black Rock Harbor samples varied with the sampling location of the source of test organisms. Dose-dependent responses of A. abdita to Black Rock Harbor sediments were corroborated with the positive correlations observed in the present evaluation between toxicity and the concentrations of several classes of organic toxicants. The organism did not indicate sensitivity to fine-grained sediments that apparently were not highly contaminated. In conclusion, the end-point of A. abdita survival was less sensitive and had lower discriminatory power than that with R. abronius, but had relatively higher analytical precision than that with R. abronius, was not highly correlated with sedimentological variables, and was relatively highly correlated with several toxicants. The end-point of avoidance was not sensitive and had low precision and discriminatory power. Strongylocentrotus purpuratus. Before the present study, the relative sensitivity of sea urchin sperm and embryos to sediments had not been evaluated. However, toxicity tests with urchin or sand dollar sperm and embryos have been evaluated in bioassays of water- borne chemicals and sewage (Dinnel et al, 1982; Dinnel and Stober, 1987; Nacci et ah, 1986). 82 Dinnel et al. (1982) found that EC 50 or LC 50 values for silver and endosulfan tested with sperm or embryos of urchins (Strongylocentrotus droebachiensis) or sand dollars (Dendraster excentricus) were comparable to or slightly higher than those for zooea of crab (Carcinus maenas), Daphnia magna, embryos of oysters (Crassostrea virginica), or rainbow trout (Salmo gairdneri). D. excentricus sperm were observed to be more sensitive to municipal sewage influents and effluents than C. gigas embryos (Dinnel and Stober, 1987). In most of the tests, they also found that the sensitivity of S. droebachiensis embryo abnormality to sewage exceeded that of fertilization success and mortality of the embryos of the same species and mortality of Cancer magister zooea. In aquatic bioassays of organic compounds and trace metals, Nacci et at. (1986), observed that the sperm cell test was frequently more sensitive than the embryo test with the urchin Arbacia punctulata. Both were generally comparable to the Microtox™ bacterial bioluminescence test in sensitivity; sometimes exceeding it in sensitivity, sometimes not. Both were also generally comparable in sensitivity to bioassays with Pimephales promelas (fathead minnow) and Daphnia magna. The utility of cytogenetic/cytologic end-points to augment tests of percent egg fertilization and normal embryo development in S. purpuratus) was suggested by Hose et al. (1983) and Hose (1985). Generally, as the dose of aqueous B(a)p was increased, the number of mitoses per embryo decreased, the percent of mitoses with cytogenetic abnormalities increased, the number of micronuclei per embryo increased, and cytologic abnormalities increased. Also, the fertilization success and normal embryo development decreased. In addition, Bay et al. (1983) proposed use of a test of echinochrome pigment in the urchin bioassay and recorded the sensitivity of this end-point to aqueous copper and lowered salinity. In a survey of runoff water and sediments near Newport, California, sediment leachates were generally found to be not toxic to S. purpuratus fertilization success and embryo development (MBC and SCCWRP, 1980). However, as few as 1.1 percent and 1.6 percent of the embryos developed normally in two of the samples. The end-point of normal embryo development appeared to be more sensitive to the same samples than fertilization success. In an evaluation of prospective dredge material from Los Angeles Harbor, MBL (1982) observed significant reductions in either normal development or fertilization success of S. purpuratus or Lytechinus pictus exposed to liquid phase samples. Whereas, fertilization success and normal development exceeded 90 percent in seawater controls, they were less than 33 percent in some samples, and significantly different from controls in samples from 9 of 20 stations. In comparison, percent normal development in the present study was below 80 percent in only 2 out of 15 samples. However, fertilization success was 70 percent or lower in three out of five samples and in three out of four controls. In the present evaluation, the end-points of abnormal development and echinochrome pigment content were not as sensitive as those of abnormal development of M. edulis and of R. abronius. The increased incidences of cytogenetic abnormalities, micronuclei and cytological abnormalities and the decreased number of mitoses per embryo had been demonstrated to be responsive to benzo(a)pyrene (Hose, 1985). In the present evaluation, most of these end-points were sensitive to many of the samples tested and were correlated with increasing concentrations of many contaminants, including hydrocarbons. However, these end-points were evaluated in only five samples and the analytical variability was relatively high. The pattern in response among the samples indicated by the abnormal development end-point contradicted that indicated by many of the other end-points in the same test and in the A. abdita test. This contradiction may be a result of different toxicity mechanisms among these end-points or of unintentional bias in the subjective scoring of embryos as morphologically abnormal versus normal. This contradiction in results has not been observed by the analysts at SCCWRP in previous experience with this test in assessments of complex effluents. In conclusion, it appears that most of the end-points of this test are intermediate in sensitivity, precision, and discriminatory power, but the test should be developed and evaluated further, particularly to refine the mutagenicity and cytological end-points. No test of marine sediment mutagenicity has been widely tested and accepted. 83 Some compounds in sediments may be mutagenic or promutagenic and their effects probably are undetectable with tests of acute mortality. Dinophilus gyrociliatus. This species had been used to test the toxicity of dissolved contaminants and effluents. Because of its short life cycle, the species can be used to quickly determine effects upon reproductive success (Carr et al., 1986) The survival of D. gyrociliatus was found to be relatively resistant to Endosulfan and pentachlorophenol, but egg production was observed to be sensitive to complex effluents and pentachlorophenol (Carr et al., 1986). In this evaluation, survival also was insensitive However, egg production was sensitive to about one-third of the samples tested. There are no other sediment toxicity data with which to compare the results of these tests. The end- point of egg production is a biologically meaningful indicator of reproductive success. As expected with a test of pore water, the results were not strongly correlated with those from the tests of the solid phase sediments or elutriates. However, they were relatively highly correlated with the concentrations of PAHs in bulk sediments. The medium that is tested, the pore water, is predicted by equilibrium-partitioning theory to be the controlling exposure medium in the toxicity of sediments to infaunal organisms (DiToro, in press). Laboratory toxicity test results are often more highly correlated with TOC-normalized pore water chemical concentrations than with non-TOC-normalized pore water or bulk sediment chemical data (DiToro, in press). However, since the borosilicate filter used in the pore water extraction method may have removed some of the potentially toxic polar compounds, including organic compounds, this test may have underestimated the pore water toxicity. In conclusion, further testing and evaluation of other pore water extraction methods are needed to increase the sensitivity of this promising test. Patterns in the Toxicity Data. Three patterns in toxicological response to the samples described above were suggested by the rank correlations among toxicity tests (Table 11) and by correlations with similar chemical or physical variables (Table 12). These patterns were not related to the medium tested (i.e., solid phase, elutriate, pore water), nor to the biological type of end-point. Whereas the toxicity test end-points within each affinity group indicated similar patterns in response, some indicated negative correlations with end- points in other affinity groups. For example, the data from the M. edulis percent normal development end-point and the A. abdita avoidance end-point were positively correlated and, therefore, contradicted each other. Two end-points of the S. purpuratus test, echinochrome content and percent normal development, also contradicted each other. Despite the suggestions derived from the correlations between toxicity and chemical data, the etiological agents for each test are unknown. It is possible that each end-point responded to different physical or chemical properties, including those that were not quantified, in the very complex sediments that were tested. Therefore, until the relationships between these toxicity end-points and specific chemicals are quantified in empirical experimentation, comprehensive assessments of sediment toxicity are best made with multiple end-points. Many of the toxicity end-points measured in all samples indicated that samples 1, 2, and 3 from Oakland Inner Harbor were among the most toxic samples. As expected, these samples were also the most contaminated since the Oakland Inner Harbor is surrounded by a highly industrialized and urbanized area. However, unexpectedly, several of the end- points (e.g., M. edulis and S. purpuratus abnormal development and R. abronius survival) indicated that samples 13, 14, and 15 collected in Tomales Bay were among the most toxic samples. These unexpected results are not easily explained. The chemical data collected with the toxicity results and chemical analyses of previously collected sediments from the Tomales Bay location suggest that it is not contaminated. Tomales Bay receives no major industrial or municipal wastes and is mostly surrounded by pastures and forests. However, benthos samples collected synoptically with the sediments tested in this evaluation were dominated by relatively hardy polychaetes and molluscs and were nearly devoid of relatively sensitive crustaceans, possibly corroborating the toxicity test results. The model developed by DeWitt et al. (1988) for interpreting the results of measuring R. abronius survival in uncontaminated fine-grained sediments does not account, alone, for the degree of toxicity observed or for the multiplicity of end-points that indicated that these sediments 84 were toxic. Collectively, these chemical, toxicity and benthic community data suggest that some unquantified factor(s) that co-occurred with these fine-grained, organically enriched sediments somehow induced or influenced the biological responses. The data from Tomales Bay corroborate the strength of using multiple indicators such as those included in the Sediment Quality Triad concept (Long and Chapman, 1985; Chapman et al., 1987) in environmental assessments, since the chemical data, if collected alone, would have not suggested that biological effects were likely. However, both the toxicity tests and benthic community data demonstrated that the sediments were relatively inhospitable due to some unknown factor(s). Benthic Community Composition. The benthic community composition differed significantly among the four sites for which data are available. All parameters measured or calculated indicated between-site differences. Similarity in composition among stations at each of the four sites was relatively high. However, the degree of chemical contamination at these four sites did not differ remarkably, whereas it was relatively high at the OA site as compared to these four. Because no benthic data are available thus far for the most contaminated site, it is not possible to attribute the observed faunal differences in the benthos among sites to chemical contamination. Nichols (1979) summarized some of the natural factors that may contribute to alterations among benthic communities along with or instead of toxic chemicals in San Francisco Bay. The between-site differences in benthos observed at the four sites may be attributable to "natural" factors as well as the small differences in chemical contamination. The observation of relatively low abundance of crustaceans at the apparently least contaminated site, along with the indication of toxicity of sediments from that site to amphipods, mussel larvae, and urchin larvae suggest that some unquantified factor or characteristic of the TB sediments was toxic to sensitive species. Taxonomic analyses of the benthos from the OA site—where toxicity and contamination were generally highest— will confirm (or refute) the speculation that the benthos there were most affected by pollutants. In conclusion, the composition of benthic communities differed significantly among sites. This type of analysis is a tool that has been used in many studies of water quality in San Francisco Bay and many other places. The analyses are ecologically relevant, since the organisms are residents, form a major component of the ecosystem, and constitute an in situ bioassay of sediment quality. However, the composition of benthic communities is influenced and controlled by many natural factors such as proximity to brood stock, bottom scouring, water temperature and salinity, predation, depth, and sediment texture. Many of these factors probably varied among the sampling sites. Therefore, the differences in composition among the four sites could not be attributed only to the presence of chemical contamination. Sediment Profiling Photography The survey of 69 sites with sediment profiling photography provided useful baseline information on sedimentological characteristics of the estuary. The data indicated that the majority of the estuary was not organically enriched. However, some indices of sediment quality developed in the survey of 69 sites indicated poor conditions in selected peripheral harbors and channels. Among the four sites that corresponded with those sampled for measures of toxicity/contamination/benthos, the sediment profiling photography indicated that the OA site was most modified by sewage and organic enrichment. However, these data indicated that the infauna at that site were only minimally stressed. This survey technique has been used in studies of many fjords and estuaries worldwide, especially regarding re- colonization of defaunated sediments or organic enrichment of sediments. In conclusion, sediment profiling photography has been shown in numerous studies, including this one, to provide useful information on sedimentological and biological properties of soft-bottom sediments very quickly. 85 Measures of Bioeffects in Fish Micronuclei. Micronuclei are likely formed as a consequence of chromosome breakage or spindle dysfunction during mitosis. Micronuclei occur at background levels in uncontaminated conditions, but at very low incidences. Chromosomal aberrations and micronuclei may have a role in evolutionary changes. However, elevated incidences of micronuclei above background rates have been attributed to x-rays and specific chemicals with mutagenic properties. Therefore, as applied in the context of monitoring marine pollution, this test can be assumed to be responsive to chemicals with specific types of effects, primarily genotoxicity. Although the degree of pollution-related elevation of micronuclei incidence observed in studies of fish and mussels performed thus far are small, the differences between contaminated and uncontaminated conditions are often significant and show a consistent pattern among species. The background frequencies and the degree of elevations in frequencies at sites that are contaminated does not appear to be species specific. Whereas the enzymatic indicators of effects may respond to toxicants in time scales of days, micronuclei formation may be indicative and integrative of longer term exposures. The lifetime of blood cells may be several months. In a mobile animal, such as P. stellatus the measures of micronuclei abundance may be most useful when distinct populations are sampled and compared. In this evaluation, mean total micronuclei incidence in peripheral erythrocytes in fish caught in November-December ranged from 0.1 per 1,000 at RR to 2.4 per 1,000 at BK. The highest incidences were among fish from the San Francisco Bay sites compared to fish from coastal reference sites. In 27 New England coastal areas, micronucleus frequencies in mature erythrocytes of winter flounder (Pseudopleuronectes atnericanus) ranged from 0.2 per 1,000 at a site at Georges Banks to 5.6 per 1,000 at a site in Long Island Sound. The ratio of the highest and lowest value indicated a 29-fold difference between sites (Table 40), similar to that (24-fold) observed in the present study with P. stellatus. Overall mean frequencies in the New York Bight Apex (2.33/1,000, n=39) and throughout Long Island Sound (3.94 per 1,000, n=35) were significantly higher than in offshore areas (e.g., 0.46 per 1,000, n=13 on the mid-Atlantic shelf) (Longwell et al., 1983). Mean micronuclei frequencies in the cells of the gills of Mytilus galloprovincialis ranged from 2.2 per 1,000 to 4.7 per 1,000 at six sites in the Venetian Lagoon, Italy (Brunetti et al., 1988). The highest frequencies were generally found in populations nearest sources of pollutants. Mean micronuclei incidences in peripheral erythrocytes of Umbra limi injected with ethyl methanesulphonate exceeded those in control fish (maximum of 3.71 per 1,000 vs. 0.14 per 1,000), however the test was not dose-responsive (Metcalfe, 1988), possibly due to toxic effects on mitosis (Majone et al., 1987). Repeated injections of benzo(a)pyrene in Ictalurus nebulosus resulted in a dose-responsive increase in peripheral erythrocyte micronuclei. White croaker (Genyonemus lineatus) caught in California coastal waters off Dana Point had lower frequencies of micronuclei in peripheral erythrocytes (mean of 0.8 per 1,000, n=28) than those caught in San Pedro Bay (mean of 3.5 per 1,000, n=28) (Hose et al, 1987). Similar studies of kelp bass (Paralabrax clathratus) showed that fish from Catalina Island had lower incidences (mean of 0.6 per 1,000, n=15) than fish caught off White Point near a major sewer discharge (mean of 6.8 per 1,000, n=15). The ratios of the maximum and minimum values observed in the studies of these two species was about 4.4- and 11.3-fold, respectively (Table 40), as compared to 24-fold for P. stellatus in the present study. Nuclear pleomorphism also was found in those fish with the highest micronuclei frequencies. Though differences in micronuclei frequencies between sites were significant for both species, micronuclei counts were only weakly correlated with concentrations of tDDT and tPCB in the fish livers. Highest frequencies, however, occurred in fish from areas known to have high concentrations of PAHs in sediments. 86 Relative to many of the other tests performed on the fish, the counts of total micronuclei had relatively high within-site variability (Tables 38 and 39) and a relatively low range/SD (Table 29). Despite the probability that species of fish collected in other studies were exposed to very different water quality and hydrographic conditions, have different biological characteristics, and different sensitivities to toxicants, estimates of within-site variability and range/SD were surprisingly similar (Table 41). Relatively high average CVs among fish caught at each site in the present study also had been observed in other species (Table 41). The ranges/SD were relatively low for this measure in three of the four species for which there are micronuclei data (Table 41). 87 ti .5 JB *.& ■2-5 "3 >— * s I E * Si S 5 b:| r §~ § a-a i o> Jt -i ."S ft. .5 * « S3 a ii 3 » n S S.2 «S «> ■Q H W .M T3 *» <■> e 01 in i a 01 01 SJ _ 01 X R ° B-* o ^ « •rt S •— « « u hi "TT § Ol •a ~: iJ c « 2 2 « r* r2 ft H 53 CJ jj>00 Oh B CO IS 5 R, o t U 5 os o o so H 2 s .0 ■*-. j3 5 H -c >~ -1— 53 ,« cS "u 3 5 a> C t/S Q s >> <3 R S «d r u « >> -c -+-• ■o ,y Wl -*~i 3 a a ft, <=, «3 in SI ft. (3 ft, w rr> 00 ro so OS O ON so 8 OS CM in p ro r* © Os Os Os in ■^ p in oq in os CM ih 00 00 Os en ■s 1 T3 - W ■S IS ^3 T3 s3 « C O 9 "3, ft" C TJ vg b < 00 '" OS lj ^ o 00 SO sO 00 00 00 Os Os OS U \- 3 ~: ro T3 ■M OS -J 00 « Os S « « W m S C 03 s § 01 re Xl U T3 (JJ ■*« 00 Table 41. Average CV and range/average SD for total micronuclei counts in Platichthys stellatus from San Francisco Bay (present study), Pseudopleuronectes antericanus from New England (Longwell, 1983), Genyonemus lineatus from southern California (Hose et ah, 1987), and Paralabrax clathratus from southern California (Hose et al., 1987). Platichthys Pseudopleuronectes Genyonemus Paralabrax stellatus (5 sites, americanus (27 sites, lineatus (2 sites, clathratus (2 sites, n=12 to 15 fish at n = 2 to 20 fish at n = 28 fish at n = 15 fish at each site) each site) each site) each site) Average CV 140.5% 81.2% 108.4% 87.5% Range/average SD 1.4 4.94 0.96 2.17 Micronuclei incidence in fish from all the sites in San Francisco Bay Bay was higher than in fish from coastal reference areas, however, there were no significant differences among sites within San Francisco Bay. Differences among sites in San Francisco Bay could have been expected, since the concentrations of chlorinated organic compounds in the fish differed among sites there. However, the formation of micronuclei may not be responsive to the measured analytes. They may be responsive to compounds such as aromatic hydrocarbons {e.g., B(a)p), which were not quantified in the fish and which are probably readily metabolized to compounds that are not readily quantified. Also, because of its shallow geomorphology and strong water currents, chemical contaminants are readily dispersed throughout the estuary. The concentrations of chemicals rarely show large gradients among the basins of the estuary, but do indicate elevations of most chemicals only in the peripheral harbors and industrial waterways (Long et al., 1988). Therefore, the fish collected at the sites in the estuary may have been exposed to relatively similar concentrations of mutagenic compounds and these concentrations may have been higher than those in fish from outside the estuary. In conclusion, it appears that the incidence of micronuclei is a relatively sensitive measure, that it has been successfully used in several species of marine animals and the data correlated with the concentrations of some organic compounds, but the data are relatively variable among fish captured at the same site. Cytochrome P-450. The cytochrome P-450 proteins catalyze monooxygenase reactions. They are the enzymes primarily responsible for metabolism or biotransformation of organic pollutants. This metabolism of xenobiotics can result in their inactivation and detoxification or their activation to toxic derivatives. Inactivation can lead to enhanced elimination and tolerance; activation can lead to serious organ dysfunction or pathology. Cytochrome P-450 enzymes are also responsible for both synthesis and degradation of steroid hormones. Aromatic hydrocarbons and chlorinated hydrocarbons, such as PCBs, can induce cytochrome P-450 activity. Cytochrome P-450 exists in different isozymes each having differing functions. One isozyme that has been isolated from fish hepatic microsomes is cytochrome P- 450E (Klotz et al, 1983), which appears to be inducible by PAH/PCB-type chemicals. Cytochrome P-450E is likely an important isozyme in conducting EROD activity. The background or uninduced levels of cytochrome P-450 activity have been measured in a variety of fish and invertebrates. For example, Stegeman and Kloepper-Sams (1987) reported levels ranging from 0.10 to 0.91 nmol/mg protein in mussels, crustaceans, fish, and rats. Average cytochrome P-450 content in four species of untreated fish ranged from 0.11 to 0.50 nmol/mg protein (James and Bend, 1980). In the latter study, exposure to 3- methylcholanthrene or 1,2,3,4-dibenzanthracene resulted in minimal or no change in total cytochrome P-450 content. In the present study, the lowest mean level of total P-450 content 89 was 0.135 nmol/mg protein in the P. stellatus, very similar to results in other species and phyla. Induction of cytochrome P-450 content by injection of the fish in the present study with BNF indicated a large potential for response in the Platichthys stellatus. Relative to controls, BNF-injected fish showed a 2.4-fold increase in mean total P-450 content. In contrast, Pseudopleuronectes americanus injected with BNF showed an increase in mean total P-450 content of 1.3-fold over that of controls (Stegeman et al., 1987). Similarly, mean EROD activity (units/min/nmol total P-450) increased 4.8-fold in BNF-treated P. stellatus relative to controls, whereas EROD activity in BNF-treated P. americanus changed 1.6-fold relative to controls. EROD activity in the deep-sea fish Cory-phaenoid.es armatus averaged 1.175 ± 0.310 nmol/nmol P-450 in fish from the Hudson Canyon off New York and 0.178 ± 0.050 nmol/nmol P-450 in fish from the Carson Canyon off Newfoundland (Stegeman et ah, 1986). Mean liver microsomal cytochrome P-450 content ranged from 0.18 ± 0.05 to 0.53 ± 0.11 nmol/mg protein in Platichthys flesus sampled at four sites in Langesund fjord, Norway (Stegeman et al., 1988). This range corresponded to roughly a 3-fold difference among sites. A difference of about 14-fold (from 3.5 ± 1.6 to 47.9 ± 18.7 pmol/min/mg protein) in the activity of the P-450E isozyme between the fish from the reference and contaminated sites indicated that the fish were highly induced at the contaminated site. Mean EROD activity in the same fish increased roughly 14-fold (from 39 ± 19 to 547 ± 236 pmoles/min/mg protein) between the reference site and the most contaminated site. All three of the responses (total P-450, P-450E, and EROD) paralleled the gradient in contamination reported by Addison and Edwards, 1988. All three appeared to be responsive to high molecular weight hydrocarbons (PAHs and PCBs) measured at the sites. None of the three was particularly responsive to the low molecular weight hydrocarbons in mesocosm exposures tested concurrently with analyses of feral fish. The pattern of EROD response in the Norwegian flounder {Platichthys flesus) recorded by Stegeman et al. (1988) using spectrophotometric methods was confirmed in the same fish by Addison and Edwards (1988) using fluorometric methods. With the latter methods, a 13.2-fold difference in EROD activity (range = 91 ± 41 to 1,206 ± 462 pmol/min/mg protein) was observed. The difference in mean total P-450 content in feral fish between the sites with the highest and lowest mean values was 1.6-fold in P. stellatus (present study), 1.7-fold in P. americanus (Stegeman et al, 1987), and 2.9-fold in P. flesus (Stegeman et al, 1988) (Table 40). The difference in mean EROD activity (units/min/nmol total P-450) between the highest and lowest sites was 4.6-fold in P. stellatus, 3.05-fold in P. americanus and 14.0-fold in P. flesus. The difference in mean P-450E content among sites was 13.9-fold in P. stellatus and 13.7-fold in P. flesus. The averages of the CVs and the ranges per average SD for four end-points are compared among three species of feral flatfish in Table 42. These species of fish were likely exposed to different water quality conditions in different geographic areas and were collected in studies with different methods and research objectives. For all five end-points, the average CVs and ranges/SDs were fairly similar among the three species, despite the differences in species and geography. The average CV for cytochrome P-450E content in P. stellatus was particularly high. The range per average SD was very consistent for the measures of EROD/mg protein among the three species. The average CVs were also very similar among the three species for AHH activity. 90 Table 42. Average CV and range/average SD for biochemical measures in Platichthys stellatus (present study), Platichthys flesus (Stegeman et al., 1988; Addison and Edwards, 1988), and Pseudopleurotiectes americanus (Stegeman et al., 1987). Platichthys stellatus (5 sites, n =14 to 15 fish per site) Platichthys flesus (4 sites, n = 10 to 12 fish per site) Pseudopleurotiectes americanus (4 sites, n = 8 to 18 fish per site) Total P-450/mg protein Average CV Range/ average SD 44.0% 1.0 26.8% 4.0 11.8% 4.3 EROD/mg protein Average CV Range/average SD 56.7% 2.8 69.2% 2.4 21.0% 2.6 EROD/nmol P-450 Average CV Range/average SD 60.8% 2.4 71.7% 1.2 19.9% 1.6 P-450E/mg protein Average CV Range/average SD 129.2% 2.V 52.7% 3.0 NA AHH (pmoI/B(a)P/min, Average CV Range/ average SD /mg protein) 78.4% 1.7 63.4% 1.3 48.3%* 1.2 *units were reported as nmol/B(a)p/min/mg protein It is apparent that the P. stellatus cytochrome P-450 system is highly responsive to exposures to organic compounds. Total P-450, EROD, and P-450E activities were highest in fish from the BK and/or OK sites which were located nearest known sources of potentially P-450-inducing contaminants. These end-points indicated differences in response both among the sites in the estuary and between sites within and outside the estuary. Experience with the P. stellatus confirmed the patterns in response observed with P. americanus and scup in New England and flounder in Norway. It is also apparent that these end-points are excellent specific indicators of exposure to high molecular weight hydrocarbons in the environment. The markedly different values obtained from highly induced fish versus fish from reference areas facilitates determinations of site-to-site differences. In either laboratory exposures or in feral fish, the suite of total P-450/EROD/P-450E end- points appear to respond to contaminants similarly among the species tested thus far. While the P-450 suite of tests may indicate the successful response of fish to xenobiotics, and may not necessarily reflect an adverse effect upon the longevity or fecundity of the animal, the tests, nevertheless, are indicators of exposure to contaminants that may not be quantifiable otherwise and that may cause subtle adverse effects. In conclusion, the suite of total P-450/ EROD/P-450E measures appears to be very sensitive, correlated with some contaminant data, relatively low in variability among fish from the same site and over a similar range in response among species. 91 Aryl Hydrocarbon Hydroxylase. Mixed-function oxygenase (MFO) enzymes are important, primarily in the liver, in detoxifying xenobiotics and steroid hormones. Relatively insoluble componds are converted into water-soluble metabolites, which may be excreted or further conjugated and, then, excreted in the urine or bile. Potent inducers of the MFO enzymes include polycyclic aromatic hydrocarbons, PCBs, and petroleum. MFO enzymes include AHH enzymes which were assayed in the present evaluation using benzo(a)pyrene as a substrate. In previous studies of P. stellatus in the San Francisco Bay, relatively high AHH activities were observed in samples most highly contaminated with chlorinated hydrocarbons. Mean AHH activities in fish collected in 1983-1984 from the BK, OK, and SP sites sampled in the present evaluation were 95, 54, and 51 units (pmol 3-OH B(a)p/min/mg protein), respectively (Spies et al, 1985). AHH activities were not suppressed in BK fish during gametogenesis (presumably, in response to exposure to organic contaminants), whereas they were suppressed in SP fish. The effects of AHH-mediated perturbations in the regulation of steroid hormones during and after gametogenesis is unknown, but could be significant in fish reporduction. In San Francisco Bay, high hepatic xenobiotic concentrations and high hepatic AHH activity in P. stellatus were negatively correlated with several measures of spawning success suggesting a cause-effect relationship. Some individual fish from the BK and OK sites had AHH activities of over 300 units (Spies et al., 1985). The mean AHH activities (147 to 363 units) recorded in the present study in fish from OK and VJ and in males and immatures at SP were higher than expected, based upon experience from previous studies of the same species. The large difference {e.g., 363 vs. 86 units in males and immatures) in activities between OK and BK fish also was unexpected, since the sites are near each other and in previous research the differences in AHH activities between these sites had not been as large. Compared to P. stellatus, mean AHH activities in P. americanus from four sites in New England were relatively high (450 to 770 pmol B(a)p metabolites/min/mg protein) and uniform. There was a strong correlation between EROD and AHH activities in fish from the Buzzards Bay site (Stegeman et al., 1987). Hepatic AHH activity in English sole (Parophrys vetulus) ranged from 36 to 330 pmol/mg protein/min in fish from a rural area, Discovery Bay, known to be uncontaminated with aromatic hydrocarbons (Varanasi et al, 1986). Fish from another area in Puget Sound with higher aromatic hydrocarbon concentrations had hepatic AHH activities that ranged from 330 to 570 pmol/mg protein/min. A strong positive correlation was observed in hepatic AHH activity and concentration of specific isozymes of cytochrome P-450. In a subsequent study, Johnston et al. (1988) reported a range of 72 to 492 pmol/mg/min in mean AHH activity in P. vetulus from Puget Sound sites, corresponding to a 6.8-fold difference between sites. A range of 33.5 ± 21.2 to 90.2 ± 52.2 pmol B(a)p hydroxylase/min/mg protein was reported by Addison and Edwards (1988) for P. flesus sampled along a pollution gradient in Langesundfjord, Norway. This range corresponded to a 2.7-fold difference between the least and most induced fish. Nearly a 4-fold difference in response in the same species was recorded following exposure to a dilution series of oil and copper in mesocosm basins. Hepatic AHH activity in untreated sheepshead (Archosargus probatocephalus), flounder {Paralichthyes lethostigma), stingray (Dasyatis sabina) and skate (Raja erinacea) averaged 3100 ± 1800, 250 ± 90, 770 ± 390 and 180 ± 180 units (50 pmol 3-hydroxybenzo(a)pyrene/ min/mg protein), respectively (James and Bend, 1980). Hepatic AHH activity was inducible with exposure to 3-methylcholanthrene or 1,2,3,4-dibenzanthrene, resulting in an increase in activity of over an order of magnitude in the same species. AHH activity in liver microsomes of the deep-sea fish Coryphaenoides armatus averaged 408 ± 170 units (pmol/min/nmol P-450) in samples from the Hudson Canyon off New York and 0.045 ± 0.010 units in samples from the Carson Canyon off Newfoundland (Stegeman et al., 1986). PCB concentrations in the fish livers were roughly 8 times higher in the Hudson Canyon than in the Carson Canyon. Gender-specific and species-specific differences in AHH activities were observed in sanddabs collected in Southern California (Spies et al, 1982). Specific activities were usually higher in males and about an order of magnitude higher in Citharichthys sordidus than in C. stigmaeus. Fish collected during the winter had lower activities than those 92 collected in the summer. Body size and AHH activity were usually not significantly correlated. AHH activity and hepatic P-450 content were significantly correlated. Fish that were fed oil and /or PCB showed significant increases in AHH activity relative to controls. Fish caught in areas near sources of contaminants or near natural oil seeps always had higher AHH activities than those caught in Monterey Bay, a relatively uncontaminated embayment. In conclusion, it appears that AHH activity was less sensitive than some of the other measures, that within-site variability was relatively moderate, that the measure is responsive to exposure to hydrocarbons, and that it may be influenced by gender, species, stage of gametogenesis, and seasons. Fish exposed to hydrocarbons often demonstrate a distinct difference in activity relative to fish from uncontaminated areas. AHH measurements complement other measures of the cytochrome P-450 system and are often correlated with them. Reproductive Success. Since all steps in steroid synthesis and metabolism are regulated by MFO enzymes, the potential exists in any of these steps to interfere with the proper quantities or timing of synthesis or metabolism of steroid hormones. Interference may be expressed as measures of the concentrations of precursor hormones or the concentrations of the hormones themselves or of the percent of reproductive products that survive to various stages in development. In the present evaluation, the concentrations of two steroid hormones were measured and selected fish were spawned to determine fertilization, hatching and embryological success. The measures of steroid hormone content and fertilization/ hatching/embryological success are important indicators of reproductive condition and success. They have been used successfully in other studies. However, in this evaluation the steroid hormone measures were relatively insensitive and the sample size available for the fertilization/hatching/ embryological success tests was too small to provide useful data. Summary Comparative Evaluation. Each of the biological tests is compared in a subjective rating matrix in Table 43. The biological end-points are compared with five criteria for which data were collected in the present evaluation. These five criteria are a subset of the original eight that were initially used to select the biological measures for evaluation. Sediment profiling photography was omitted, since it was performed to determine geographic patterns in the San Francisco Bay estuary, not to compare its performance with the other tests. The sample sizes for the reproductive success end-points were too small to evaluate their performance and the benthos analyses are incomplete. The 'sensitive' criterion reflected the ability of the biological test to determine differences either between a test sample and respective controls (sediment tests) or between two sampling sites (fish tests). The sediment toxicity tests were rated a "yes" for sensitive if the end-point indicated that one or more of the samples was significantly more toxic than respective controls (Table 13). The measures of fish health were rated a "yes" for sensitive if one or more of the sites were indicated as significantly different than other sites (Table 32). Both the sediment and fish tests rated a "yes" for the "correlated with toxicants" criterion of the rank correlations with toxic chemicals were equal to or exceeded .500 in Tables 19 and 39, respectively. Similarly, both sediment and fish tests generally rated a "yes" for the "not correlated with nuisance variables" criterion if the ranked correlations were less than 500 in Tables 19 and 35, respectively. The sediment and fish tests rated "yes" for the "low analytical variability" criterion if the average CVs were <30 percent (Table 17) and <75 percent (Table 39), respectively. The sediment and fish tests rated a "yes" for the "high discriminatory power" criterion if the quotients of the range over the average SD were >3.0 (Table 17) and >2.0 (Table 39), respectively. All of these yes/no thresholds were arbitrarily selected and the ratings for many of the tests could change if different values had been selected. Among the sediment toxicity tests, all but the end-points of avoidance by the two amphipods were sensitive to at least one of the samples tested. R. abronius survival, and M. edulis abnormal development and survival were the most sensitive end-points. The 93 benthic communities indicated significant differences between all sites. Most of the cytochrome P-450 end-points and two of the micronuclei end-points indicated differences between sites, and, therefore, rated yes's for the "sensitive" criterion. Half of the sediment toxicity end-points rated a "yes" for the "correlated with toxicants" criterion, including those of A. abdita survival, D. gyrociliatus reproduction and S. purpuratus echinochrome content and cytogenetic/mitotic abnormalities. None of the fish tests were very highly correlated with the concentrations of chemicals in the fish livers. Since no benthos data are available for the most contaminated site, correlation analyses have not yet been performed. Again, half of the sediment toxicity end-points rated a "yes" for not being correlated with nuisance variables (grain size and TOO. The benthos data have not yet been tested for correlations with sedimentological factors. The AHH, micronuclei, steroid hormone, and most of the P-450 end-points were not correlated with length, weight, or organ weight of the fish. However, HSI was inversely correlated with P-450E content and P-450E/total P-450; while estradiol 2-hydroxylase was positively correlated with GSI. The two avoidance end-points in the amphipod tests had very high analytical variability and rated a "no" in Table 43 for the "low analytical variability" criterion. The average CVs of two of the S. purpuratus cytogenetic/ mitotic end-points were very high, while those of two others were relatively low. One or more of the AHH, P-450 and hormone end-points had relatively high variability among fish at the sites while the others had low variability. All of the micronuclei end-points had relatively high variability among fish at sampling sites. The avoidance end-points in the amphipod tests and some of the S. purpuratus cytogenetic/mitotic end-points had relatively low discriminatory power. R. abronius survival and M. edulis percent normal end-points had the highest values among the sediment toxicity tests. Discriminatory power of the AHH end-points was relatively low. The discriminatory power of most of the P-450 end-points exceeded a value of 2.0. The testosterone concentration end-point had a relatively high discriminatory power, while that of estradiol content did not. The discriminatory power of the detached micronuclei end-point exceeded 2.0, whereas those of total and attached micronuclei did not. 94 Table 43. Subjective rating of each biological test end-point with regard to five performance criteria (see accompanying text for an explanation of the criteria). Correlated Not correlated Low High Sensitive with toxicants with nuisance variables analytical variability discriminatory power Sediments R. abronius survival avoidance yes no no no no yes yes no yes no A. abdita survival avoidance yes no yes yes yes yes yes no yes no M. edulis abnormalities yes no no yes yes survival yes ID no yes yes S. purpuratus D. gyrociliatus abnormalities echinochrome cytogenetic/ mitotic reproduction yes yes yes yes no yes yes yes no yes no yes yes yes ? yes yes yes no yes Benthos yes rd nd nd rd Fish AHH activity no Cytochrome P-450 content/ EROD activity yes Steroid hormone content no Reproductive success nd Micronuclei yes no no no rd no yes yes yes rd yes ? 7 nd no no yes ? rd RECOMMENDATIONS All of the biological measures that were evaluated provided useful information and most should be viewed as candidates for future use. None should be considered as the best, or the worst, but each has distinct strengths and weaknesses. Because the contamination of marine areas near urban centers often results in complex mixtures of chemicals, biological responses to those mixtures would be expected to be equally (or more) complex. Some chemicals may be acutely lethal and a short-term bioassay of sediment could be a useful indicator of the bioavailability and toxicity of those chemicals. Other chemicals may induce subtle changes that are expressed or quantifiable over only long periods of time. Tests of mutagenicity and/or enzymatic response may be useful in evaluating exposure of biota to these chemicals. No single biological measure can be expected to suffice as the sole test of effects of complex mixtures of contaminants. The measures evaluated in the present study should be viewed as a menu of candidates from which a suite of complementary tests can be selected and tailored for use in satisfying specific programmatic and technical objectives. Each measure has certain strengths and weaknesses that should be evaluated in the selection of the specific suite of tests. 95 The Mytilus edulis larvae test appears to have relatively high sensitiivity, precision, and discriminatory power; it has been sufficiently developed to warrant its use in screening studies of sediment toxicity; but the influence of sediment texture and organic carbon content should be evaluated in controlled laboratory experiments. A quick procedure for accurately counting the number of M. edulis embryos inoculated into the test chambers at the initiation of the tests should be developed to help reduce the variance in the end-point of survival. Many of the whole-embryo Strongylocentrotus purpuratus test end-points appear to be less sensitive than those measured with M. edulis, but the cytogenetic/ mitotic end- points should be evaluated further as indicators of mutagenicity in environmental samples. The relatively highly tested and developed Rhepoxynius abronius test is very sensitive and the influence of fine-grained sediments upon the organism has been quantified in controlled laboratory expeiments; the test should be used further in assessments of sediment quality. The relatively new test with Ampelisca abdita appears to be less sensitive than some of the others including that with R. abronius, but appears to be particularly suitable for testing the toxicity of fine-grained sediments; it should be used in assessments of sediments known or suspected to be highly contaminated; and a source of non-toxic native sediments should be located for use as controls. In both the R. abronius and A. abdita tests, emphasis should be placed upon the survival end-point; the avoidance end-point has very high within-sample variance, resulting in relatively low sensitivity; and the reburial end-point with R. abronius is insensitive and should be discontinued. Better methods of extracting sediment pore water that reduce the amount of organic contaminants that are removed from the pore water should be developed to enhance the utility of pore water tests; other tests of reproductive success such as that measured with Dinophilus gyrociliatus should.be developed. More emphasis should be placed upon the development of sediment toxicity tests in which mutagenicity is determined and in which reproductive success is determined. The benthic community samples from the Oakland Inner Harbor site should be analyzed to determine if the composition data confirm the toxicity test data. The survey of sediment quality performed in San Francisco Bay with the profiling photography should be repeated at selected sites where it appeared that the sediments and benthic communities were in transition to determine temporal trends. The cytochrome P-450 measures and micronuclei counts, together, appear to provide a suite of sensitive indicators of both exposure to and effects of certain hydrocarbons, including those that may be readily metabolized and not detected in fish; the enzymes may reflect recent expsoures to toxicants, whereas the micronuclei may integrate the effects of exposures over periods of several months; they should be used in assessments of marine environmental quality where the presence of hydrocarbons is known or suspected. 96 Tests of reproductive success in feral fish should be conducted with additional species (preferably, those that are non-migratory and demersal) in areas suspected of being highly contaminated. Biochemical and other analyses that are indicative of reproductive impairment, but are quicker and less expensive than spawning studies, should be tested and evaluated. Other comparative evaluations should be conducted as new candidate tests become available. 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Marine Environmental Research 19: 225-249. 104 Williamson, M. H. 1978. The ordination of incidence data. Journal of Ecology 66: 911-920. Yamamoto, K. 1956. Studies on the formation of fish eggs. I. Annual cycle in the development of ovarian eggs in the flounder, Liopsetta obscure. Hokkaido University. Faculty of Science. Journal Series 6. 2001(12): 363-373. Zar, J. H. 1984. Biostatistical Analysis. Englewood Cliffs, NJ: Prentice-Hall, Inc. 718 pp. 105 106 APPENDIX A SEDIMENT TOXICITY TEST DATA Individual sediment toxicity test data from five types of tests performed on five replicates at 15 stations sampled in the San Francisco Bay area. Some columns appear twice where tests were performed in two batches of samples; control values should be compared with data from samples tested in respective batches. Mytilus edulis tests were performed in one batch. TB and SP samples were tested with Control 1 samples in the Dinophilus gyrociliatus test. VA 2 and VA 3 samples were tested with Control 2 samples in the Rhepoxynius abronius test. VA, OA, and YB samples were tested with Control 1 samples in the VA test with Ampelisca abdita. VA, OA, and YB samples were tested with Control 1 samples in the test with Strongylocentrotus purpuratus. 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E i i ■ s < e u * E £ a. -g £> o . -o s "5 • & * 00 ■3 o I «i o c « * eg n h 0)0.0 S = S £ E 2 o o vo en en •» o — rj> •"■ "-" & * tj- tj- ts r~ vO rn tj- -d- cs ce •— o ~^ •— ^. >o »n O en ov s n os g o r* *o ;- ^o rf Tf i/i oc oo oo co oo in co £ ° ■ 24 " E I2 w >C Ov ^ O* N ^ N > ^ -^ e 0 < pq U Q is I o a Z f> J2 e < 5 £ «•* o 55 CO « * « 00 • i : Z o 4* O .£ s f E • ° i z^ = 5 Si ♦ — t- o> o m >n - » ^ M M N N « i w — w/1 logi mali . o t a ** O Z ^ = I 0 o h S « « " * S2£ S* E = =W z o V M » V «* ee N N — V) TT - -a- r-i ~ ~ —, ** (M O CO m t- ■ en — ' 0\ o o ° - N N N N en >o vo q 00 ■a; BO CO C~ cs CO r^ m co ~« — i cs o — o — o < m u Q w B 2 < « B 2 < « % % 1—1 pj fi E § § u u S s M | 1 < « U D W B 0 < euQu o c o U 1 s a :-. o U c O u bj § T3 00 a A-18 APPENDIX B SEDIMENT PHYSICAL AND CHEMICAL DATA Individual chemical and physical /chemical data from sediments sampled at 15 stations in the San Francisco Bay area. Concentrations of organic compounds are expressed as ug/kg (ppb) dry weight, coprostanol as ug/g (ppm), trace metals as mg/kg (ppm) dry weight or percent for aluminum, iron, and silicon. s a ■a a o u o u OS rl o> o o o o o o o o o o eN a a d i— « d © d o d o d o o o d o o o d d o a O o o o o o 00 ■* o o o o o o a O a d o a d d o o d o o o o o o o o o o a a a r~ (N o f« h N lO en Tj- a co a eN r-~ no C h N in Tt no r- in en in *t en oo m r- oo oo r- oo r» on m « h en a f-H r~- ■"H NO ^H > >- o ON ■ — i en ~« tn OO >n ■* m ■* C\l i-i oo «* fN r~ m a i— i ■* ri "* ^t on d CN "-• oo en oo NO oo 00 en oo m no K-) m T»- >n in o in n in ■* tj- Tt in in in in m in r~ r- r^ 00 oo oo 00 oo 00 00 oo 00 00 oo oo pq pq PP PQ CO PQ ^ CQ % PQ CQ CQ CQ CQ CQ ■5 < o p ed Tt m no (u §9 c a c m a **H CN eO en Tj ^n ^ u ,_, fmmi u ,_, fH I— ( u S Oh V3 6 p S r-* oo ^ o CI 00 NO n r-^ ■*' ri NO >/-i ci M3 ts NO 00 NO tN — © © NO WN NO u~i a NO •*' *r> p~ © a. >o ""■ 1—1 a. o O •*!■ o "*. o 00 -' ~ © OO tr> tN (N NO © © © en © © © ~ Q O. O ^ © tN © © o u-> o NO On -* U"> © m ON V © tN On tN On © © o © © © © © © © o © a tr> m m © d d tN tN © d © © © © © "O 1-H t— 1 .— i o m © m © © in d »— i d © U S3 o © o © © © © © © © © © © © © W d d d © © © © © © d © © © © o a © © © © © d © © © © e o o o © © © © © © o © © © © © u. »» d d d d © © d © © © © © © © © © -o 2 '3 © © © © © es ° © © © © © - a » a O — i o © © © r~ On © © © © © © © I* o — © t d d © © © »-< © On © © © © © d © © fl © © © © © -< l_ © © © © © o © © o © © © © o © e d d d © © © © © © © d © © © © JS u 00 © © o © 09 © d d © © Q. V S3 a e a a a a c *•" CS (4 C3 © — (N CO t*-> ■* u-> CO w i-H tN CI a> ■«t T> NO t» t— oo ON V o ,_, ,_ ID es a B e a E CA < O * < > PL, CO P B-2 Qu es a (►, JS 0) — a .! !" 5 sc r* >> a V a. m o o o odd o o o odd o o o O m O o o o odd O O O Oi m -i CI CI d o d o d o d ■<*■ CI o o o o o o o o o o o o > a o o o odd © © o odd © © © Os O CT\ o o o (N TT "> O d o d CI © d a. es a >. * ■= a- o o o o o q o o o q O q H e o a. a. H a Q a. © o o o o o o o o o o o o in o vi n n N — i \o in CI O) C^l m 00 SO r-- m r» Os o o o o o o o o o o o o o o o r— < N O t-~ o o o o © o o o o o o o o o o o © •—1 en OO r» so a 03 u £ a 6 n ^ «i c 03 U E 0h C/3 B B-3 a ea a 41 a u a < a 4) a ea a a 01 © 3 a s £ M « * os en o o o o odd © o © d © © © © CM CO © © © do© © © o © in cm © © © © q q © © o © q q q q ooo Tf- d ■ef f« ON d t vo cm' cm vd tn odd vo U~> © ■* en (S 1— < i— i CM U < a e C a a a 0 •*■ ea ea CO © H CM ea en •>»• in ea ■w ^-t CM m 4> tt >n VO *-H »-H <_H CJ C9 s B E E E C*fS < o sa < > PL, 00 r9 B-4 4) a it >> h V ft, >» u 41 ► o u ft! ° a N i, a i- 4> pq a o o o © o O o o o O o q eN r^ o en "3- oo vo en —^ © o o vd o\ in en in _*' r— < •—i en o ■* ^ r- en m VO m o *o NO ^t oo en en (N i-H <— 1 . — i o .— H f— < r— 1 On en" d NO m 00 m © vo CN ■— < •— < © vo r~ en VO r^ eN o 00 eN en f» en en in ■*' »—) ^- VO en oo t-~ oo 'S-' vd On d en t en * en >n ■* r-- t— t t— ■ en o •— 1 t— < VO vd m en r- Ov 00 ■* O o o o o o o o o © o o o o o en vd r~- m m r^ 00 r^ t eN 00 en d o o 00 en NO o en en en t— 00 ■* oo r~ ON ON r- r- 00 no eN eN eN eN in o en ~* '" t— ^ r~ o VO en 00 d r- «n •— < 4> 4) s at tn >» u u a », ,-■. 4) 08 " o o o O O o O o O o o o o o o oo r- _; in >* n- ,_! oo •* o\ rj oo d o o t- r^ ■* © m in in en r- en VO r~ T- * ^ t en VO VO m . — i «— i T— 1 • r—' t— I f-H o eN ■n o en O q On o KM eN (N On oo d d o »— < en e'- en CO q d 41 a 4> L. ft. 4) a 4> a o o o o q o o q o o q q O t>; q q d >* NO q d d d d -* oo t~ CO en NO r- eN •3- NO NO m (N en r- * o o VO r- >n VO oo en •* t)- *' r- r^ On en en m vo ■ — i ■* o o ■* ^r in en o r* NO eN (N ts en »—* CO q d en in en o\ *-< CN en m a o on 41 CU cs 1> • a 03 E a n n o O es t» m o en n d u NO >< a o fN SO h vi N ■n no no 00 d «i * >n r~ •^: n n N — do ON NO ooo ooo — oo ooo ooo ddo ooo ooo ooo ooo o o o o o o o d d o O W ft. es « s « o a o a at CA o q q q o q q o o q q o >n r- NO NO ^r n .— * NO t~- d ON ,-i O On >n oo ON o o .— i TJ-" NO T eN en en (N NO d m t» ■* en d r- oo "* en eN en en P» o o o t n ■"■ 1— < O •—l ■<*• o o q q q q q O o q o o q o q NO ,_! ,-J d r» d d 00 d >n d NO © d o en o in * en en cn ~- q On >n en d o d c — fN en iu 8 < o a >n no a 1) E O — ' Oh V3 S en ^- in a u B B-6 OS < © u ft © U PS u PL, a <* ON en CO CM m r~ no NO t— 1 oo NO cnj es CO NO NO ^f ON 00 o OO O es rt. t en en CM o CS oo -; <* ON m m m in NO m ON m CO in vo NO NO NO es NO m NO no >n in f .— . NO CO f- r- (N oo O en ,_ o ^r ON in (N On Tt in es r~ ■*' ON ooo ooo ooo oo© odd odd odd odd © © o © odd© U ON s 4) NO Tf 00 NO NO — ooo O NO 00 OOO oo Tt in -* en es d ■* es' odd d <-< es' odd en NO es' o d in u so >. a o. es es es T CM NO en tj- in N it O0 ooo — in ■* NO NO NO d es' es ON tj- m en en in m odd m m d **' 00 © d u a o 03 at ■*■» e u E CO in no u < O S9 a 03 r^ oo on o < o — i PL, 00 a es ca s in tu E p B-7 s C/5 V V V V V V V V V V V V V V V ■* Os s© v© Os p" 00 Os Ui 4> C/3 Oh a s ec a 4> 9 t- •a m SO OO r- r~ r- m O so r^ en Os so so in in en r-- en oo CN cm CN SO cn CN CN (N cn CN r) es m CN (N rj so CN CN rj CM ■* r~ "* ■ CN oo o »— • m OO m t- 1 — 1 f— < SO *—• t»> ,_, SO ^H o *t m ■n r~ SO SO so Os SO ,-H ,-H --. rM ■* m SO so en 00 n CN cj r~- Os en vo 00 ^h «t en >* •-; _ «■ SO in m en en O -H 00 a CN C3 E a E e2 B-8 a ON — . <* CO VO oo 00 1/1 <* CO r~ t -3- r- ■tf P- r-< o cs m Tf co CM r—i CO CO CO ~H co i— i en co co co co CO CN CO CM cm co CM CM co CO •* CO CO CO CO CO CO CO cm CO -» "4; ■* •* ■<* ■* CO ■0- 1; ■t CO "fr ^r ■* CO Tt ^t •* CO V V V en V V V V V V V V V V V V a o a ■** 4> *-* a r-< cs CO u < o a B P r-- oo os < > a 6 a cs « - g PL, C/5 co -rj- ui c U E P B-9 APPENDIX C MEASURES OF EFFECTS DATA FOR P. STELLATUS Individual data from measures of effects in P. stellatus. Site Sample No. Date Sex Maturity Std. Length Condition factor (w/lxlxl) Liver wt. (q) Gonad wt. (q) Total wt. (q) Wt/Length Berkeley 5120 Nov M mat 26 2.51 4.7 1.4 442 17 Berkeley 5121 • • • • Berkeley 5122 • • • • Berkeley 5123 • * • • Berkeley 5124 • • • • Berkeley 5125 * • • • Berkeley 5126 Nov F mat 30.5 2.35 7.9 31.2 666 21.84 Berkeley 5127 Nov F immat 30 2.44 5.9 6.8 658 21.93 Berkeley 5128 • • • • * • • • • Berkeley 5129 • • • • • • • • • Berkeley 5130 Nov F immat 26.5 2.24 4.1 4.3 416 15.7 Berkeley 5131 • • • • • • • • • Berkeley 5132 • • • • • • • • • Berkeley 5133 Nov M mat 29 2.27 7.1 12.2 554 19.1 Berkeley 5134 • • • • • • • • • Berkeley 5135 Nov F mat 40.5 2.36 20 41.2 1566 38.67 Berkeley 5136 Nov F mat 38.4 2.47 27 92.6 1397 36.38 Berkeley 5137 Nov F immat 26.5 2.34 4.3 4.5 436 16.45 Berkeley 5138 • • • • • • • • • Berkeley 5139 Nov F mat 44 2.38 35.3 165 2027 46.07 Berkeley 5140 Nov M mat 32 2.42 12 14 792 24.75 Berkeley 5141 • • • • • • • • • Berkeley 5142 Nov M mat 28 2.28 5.7 1.8 500 17.86 Berkeley 5143 • • • • • • • • • Berkeley 5144 • • • • • • • • • Berkeley 5145 • • • • • • • • • Berkeley 5146 Nov M immat 23 2.26 2.9 0.5 275 11.96 Berkeley 5147 • • • • • • • • • Berkeley 5148 • • • • • • • • • Berkeley 5149 Nov F immat 26.5 2.11 3.5 2.3 393 14.83 Berkeley 5150 Nov F mat 37.4 2.68 24 73 1403 37.51 Vallejo 5151 Nov F immat 20.5 2.38 2.2 0.8 205 10 Vallejo 5152 Nov F immat 29.5 1.57 3.4 3.3 402 13.63 Vallejo 5153 Nov F immat 35.4 0.94 16.8 27.9 417 11.78 Vallejo 5154 Nov M immat 23 2.13 2.9 1.6 259 11.26 San Pablo Bay 5155 Nov F mat 35.4 2.26 16.8 27.9 1002 28.31 San Pablo Bay 5156 Nov M mat 24.6 2.39 5.1 2.6 356 14.47 San Pablo Bay 5157 Nov M mat 26 2.33 6.7 4 409 15.73 San Pablo Bay 5158 Nov M immat 27 2.26 6.6 4.4 444 16.44 San Pablo Bay 5159 Nov M immat 20.5 2.24 1.9 0.1 193 9.41 San Pablo Bay 5160 Nov F immat 25.5 2.44 4.8 2.3 405 15.88 San Pablo Bay 5161 Nov F immat 26 2.65 5.2 2.3 466 17.92 San Pablo Bay 5162 • • • • • • • • • San Pablo Bay 5163 Nov F immat 24 2.77 4 2.5 383 15.96 San Pablo Bay 5164 Nov M mat 24 2.59 7.9 7.1 358 14.92 San Pablo Bay 5165 Nov M immat 26.5 2.23 8 6.7 415 15.66 Oakland 5166 Nov F mat 41 2.07 17.8 17.5 1428 34.83 Oakland 5167 Nov F immat 25.7 2.39 3.9 2.4 406 15.8 Oakland 5168 Nov F immat 34.2 2.2 9.6 6.3 881 25.76 Oakland 5169 Nov M immat 25 2.17 2.9 1 339 13.56 Oakland 5170 • • • • • • • • • Oakland 5171 Nov F mat 38.5 2.72 39.9 112 1553 40.34 Oakland 5172 Nov F mat 35.2 2.39 13 28.7 1043 29.63 Oakland 5173 • • • • • • • • • Oakland 5174 • • • • • • • • • Oakland 5175 • • • • • • • • • Oakland 5176 Nov F immat 34.8 2.15 8.5 8.7 905 26.01 San Pablo Bay 5177 • • • • • • • • • San Pablo Bay 5178 • • • • • • • • • C-1 Site Sample No. Date Sex Maturity Std. Length Condition factor (w/lxlxl) Liver wt. (g) Gonad wt. (g) Total wt. (g) Wt/Length San Pablo Bay 5179 , a • • • • San Pablo Bay 5180 • • • • • • San Pablo Bay 5181 • • • • • • San Pablo Bay 5182 Nov F Immat 29 2.41 6.3 2.9 587 20.24 San Pablo Bay 5183 • • • • • • San Pablo Bay 5184 • • • • • • San Pablo Bay 5185 Nov F immat 28.5 2.42 5.3 3.8 560 19.65 San Pablo Bay 5186 • • • • • • San Pablo Bay 5187 • • • • • • San Pablo Bay 5188 • • • • • • San Pablo Bay 5189 • • • • • • San Pablo Bay 5190 • • • • • • San Pablo Bay 5191 Nov M immat 20.6 2.35 2 0.9 205 9.95 San Pablo Bay 5192 • • * • • • San Pablo Bay 5193 • • • • • • San Pablo Bay 5194 • • • • • • San Pablo Bay 5195 Nov M immat 33 2.04 12 0.6 733 22.21 San Pablo Bay 5196 • • • • • • Vallejo 5197 • • • • • • Vallejo 5198 Nov M mat 31.8 2 11.1 3.5 642 20.19 Vallejo 5199 • • • • • • • • • Vallejo 5200 Nov M mat 25.8 2.35 5.6 2.5 404 15.66 Vallejo 5201 Nov F mat 51 1.65 39.7 71.7 2192 42.98 Vallejo 5202 Nov F immat 53 1.78 13.9 35.9 2657 50.13 Vallejo 5203 Nov M mat 25.7 2.26 6.3 2.3 384 14.94 Vallejo 5204 Nov F immat 24.6 2.38 3.5 1.3 355 14.43 Vallejo 5205 Nov F mat 30.2 2.58 9.7 14.4 712 23.58 Vallejo 5206 • • • • • • • • • Vallejo 5207 Nov F immat 24.5 2.16 3.5 1.6 317 12.94 Vallejo 5208 Nov F immat 24.8 2.06 3.5 2 314 12.66 Vallejo 5209 Nov M mat 23.5 2 32 4.1 3.1 301 12.81 Vallejo 5210 • • • • • • • • Vallejo 5211 • • • • • * • • • Vallejo 5212 • • • • • * • • • Oakland 5213 Nov F mat 33.6 2.42 13.7 23.3 918 27.32 Oakland 5214 • • . • • • • • • • Oakland 5215 Nov F immat 22.3 1.95 2.6 1.1 216 9.69 Oakland 5216 Nov F mat 37.5 2.65 27 64 1397 37.25 Oakland 5217 Nov F immat 22 2.22 1.9 1.2 236 10.73 Oakland 5218 Nov F mat 42.4 1.88 14.7 20 1431 33.75 Oakland 5219 Nov F immat 28 2.2 3.5 2.5 482 17.21 Oakland 5220 Nov M mat 23.5 2.74 4.3 3.1 356 15.15 Oakland 5221 Nov F mat 41 2.52 31.5 212 1740 42.44 Russian River 5222 Nov F mat 44 2.4 40.8 173 2047 46.52 Russian River 5223 Nov F mat 42.3 2.27 35 113 1715 40.54 Russian River 5224 Nov F mat 38.5 2.01 16.6 32.8 1146 29.77 Russian River 5225 Nov F mat 36 2.31 17.2 40.8 1076 29.89 Russian River 5226 Nov F immat 33.5 2.24 11.3 7.3 842 25.13 Russian River 5227 Nov F immat 37.5 1.77 9.3 6.3 932 24.85 Russian River 5228 Nov F immat 28 2.03 4.6 3.2 445 15.89 Russian River 5229 Nov M mat 38.5 2.09 15.1 29.5 1191 30.94 Russian River 5230 Nov F immat 33.5 2.19 8.1 3.2 824 24.6 Russian River 5231 Nov F immat 31 2.1 7.3 4 627 20.23 Russian River 5232 Nov M mat 40.5 1.95 18.6 37 1293 31.93 Russian River 5233 Nov M mat 32.5 2.3 9.4 22.2 790 24.31 Russian River 5234 Nov M mat 37.5 2.4 7.4 35.2 1267 33.79 Russian River 5235 • • • • • • • • • Russian River 5236 Nov M mat 35 2.35 13.3 19.4 1007 28.77 Russian River 5237 • • • • • • • • • C-2 Site Sample No. Date Sex Maturity Std. Length Condition (actor Liver Gonad Total Wt/Length (w/lxlxl) wt. (q) wt. (g) wt. (g) Russian River 5238 Russian River 5239 Russian River 5240 Russian River 5241 Russian River 5242 Russian River 5243 Russian River 5244 F mat 46 Russian River 5245 F mat 40 Russian River 5246 Russian River 5247 Russian River 5248 Russian River 5249 Russian River 5250 Russian River 5251 Russian River 5252 Berkeley 5253 Jan. F mat 43 Berkeley 5254 Jan. F mat 31.5 Berkeley 5255 Jan. F mat 35.7 Berkeley 5256 Jan. • • • Berkeley 5257 Jan. F mat 43 Berkeley 5258 Jan. • • • Berkeley 5260 Jan. • • • Berkeley 5261 Jan. • • • Berkeley 5263 Jan. F mat 39 Vallejo 5264 Jan. F . mat 39.8 Vallejo 5265 Jan. • • • Vallejo 5266 Jan. • • • Oakland 5267 Jan. • • • Oakland 5268 Jan. F mat 43 Oakland 5269 Jan. • • • Santa Cruz 5275 Jan. F mat 49 Santa Cruz 5276 Jan. F mat 41.2 Santa Cruz 5278 Jan. F mat 42.5 Santa Cruz 5279 Jan. F mat 43.2 Santa Cruz 5280 Jan. F mat 41.3 Santa Cruz 5311 Jan. F mat 40 Santa Cruz 5312 Jan. F mat 40 Santa Cruz 5313 Jan. • • • Santa Cruz 5314 Jan. F mat 45.5 Santa Cruz 5315 Jan. F mat 43.5 Santa Cruz 5316 Jan. F mat 42.8 Santa Cruz 5317 Jan. F mat 48.5 Santa Cruz 5318 Jan. F mat 44 Berkeley 5319 Jan. F mat 43 Berkeley 5320 J< in. • • • 2.2 2.31 2.436 2.824 2.331 2. 99 2.202 65 3.022 2.86 2.376 43.5 93.8 80 2141 1477 1937 1285 1748 1540 1696 2369 2436 1889 46 36 45 35 1415 36 40 37 55 55 43 54 93 05 99 .65 38 42.4 .35 36 93 C-3 Site Sample No. Date Liver/Body Gonad/Body GSI gonad wt./ (total HSI liver wt./(total wl x 100 wt x 100 wt - gonad wt) x 1,000 wt - liver wt) x 1,000 Berkeley 5120 Berkeley 5121 Berkeley 5122 Berkeley 5123 Berkeley 5124 Berkeley 5125 Berkeley 5126 Berkeley 5127 Berkeley 5128 Berkeley 5129 Berkeley 5130 Berkeley 5131 Berkeley 5132 Berkeley 5133 Berkeley 5134 Berkeley 5135 Berkeley 5136 Berkeley 5137 Berkeley 5138 Berkeley 5139 Berkeley 5140 Berkeley 5141 Berkeley 5142 Berkeley 5143 Berkeley 5144 Berkeley 5145 Berkeley 5146 Berkeley 5147 Berkeley 5148 Berkeley 5149 Berkeley 5150 Vallejo 5151 Vallejo 5152 Vallejo 5153 Vallejo 5154 San Pablo Bay 5155 San Pablo Bay 5156 San Pablo Bay 5157 San Pablo Bay 5158 San Pablo Bay 5159 San Pablo Bay 5160 San Pablo Bay 5161 San Pablo Bay 5162 San Pablo Bay 5163 San Pablo Bay 5164 San Pablo Bay 5165 Oakland 5166 Oakland 5167 Oakland 5168 Oakland 5169 Oakland 5170 Oakland 5171 Oakland 5172 Oakland 5173 Oakland 5174 Oakland 5175 Oakland 5176 San Pablo Bay 5177 San Pablo Bay 5178 Nov 1.06 0.32 3.18 10.63 Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov 1.19 0.9 0.99 1.28 1.28 1.93 0.99 • 1.74 1.52 1.14 1.05 0.89 1.71 1.07 0.85 4.03 1.12 1.68 1.43 1.64 1.49 0.98 1.19 1.12 1.04 2.21 1.93 1.25 0.96 1.09 0.86 2.57 1.25 4.68 1.03 1.03 2.2 2.63 6.63 1.03 8.14 1.77 0.36 0.18 0.59 5.2 0.39 0.82 6.69 0.62 2.78 0.73 0.98 0.99 0.05 0.57 0.49 0.65 1.98 1.61 1.23 0.59 0.72 0.29 7.21 2.75 49.15 10.44 10.44 22.52 27.02 70.99 10.43 88.61 17.99 0.94 0.96 3.61 1.82 5.89 54.89 3.92 8.28 71.7 6.22 28.64 7.36 9.88 10.01 0.52 5.71 4.96 6.57 20.23 16.41 12.41 5.95 7.2 2.96 77.72 28.3 9.71 11.86 8.97 9.86 12.82 12.77 19.33 9.86 17.41 15.15 11.4 10.55 8.91 17.11 10.73 8.46 40.29 11.2 16.77 14.33 16.38 14.86 9.84 11.85 11.16 • 10.44 22.07 19.28 12.46 9.61 10.9 8.55 25.69 12.46 9.39 C-4 Sile Sample No. San Pablo Bay 5179 San Pablo Bay 5180 San Pablo Bay 5181 San Pablo Bay 5182 San Pablo Bay 5183 San Pablo Bay 5184 San Pablo Bay 5185 San Pablo Bay 5186 San Pablo Bay 5187 San Pablo Bay 5188 San Pablo Bay 5189 San Pablo Bay 5190 San Pablo Bay 5191 San Pablo Bay 5192 San Pablo Bay 5193 San Pablo Bay 5194 San Pablo Bay 5195 San Pablo Bay 5196 Vallejo 5197 Vallejo 5198 Vallejo 5199 Vallejo 5200 Vallejo 5201 Vallejo 5202 Vallejo 5203 Vallejo 5204 Vallejo 5205 Vallejo 5206 Vallejo 5207 Vallejo 5208 Vallejo 5209 Vallejo 5210 Vallejo 5211 Vallejo 5212 Oakland 5213 Oakland 5214 Oakland 5215 Oakland 5216 Oakland 5217 Oakland 5218 Oakland 5219 Oakland 5220 Oakland 5221 Russian River 5222 Russian River 5223 Russian River 5224 Russian River 5225 Russian River 5226 Russian River 5227 Russian River 5228 Russian River 5229 Russian River 5230 Russian River 5231 Russian River 5232 Russian River 5233 Russian River 5234 Russian River 5235 Russian River 5236 Russian River 5237 Dale Liver/Body Gonad/Body wl x 100 wl x 100 GSI gonad wl./ (total wl - gonad wt) x 1,000 HSI liver wt./(total wt - liver wt) x 1,000 Nov Nov Nov Nov Nov • Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov 1.07 0.95 0.98 1.64 1.73 • 1.39 1.81 0.52 1.64 0.99 1.36 1.1 1.11 1.36 1.49 0.49 0.68 0.44 0.08 0.55 0.62 3.27 1.35 0.6 0.37 2.02 0.5 0.64 1.03 2.54 1.2 0.51 1.93 4.58 0.81 0.51 1.03 1.4 0.72 0.52 1.21 0.87 1.81 12.18 1.99 8.45 2.04 6.59 1.45 2.86 1.6 3.79 1.34 0.87 1 0.68 1.03 0.72 1.27 2.48 0.98 0.39 1.16 0.64 1.44 2.86 1.19 2.81 0.58 2.78 4.96 6.83 1.32 1.93 4.41 0.82 5.48 • 6.23 33.82 13.7 6.03 3.68 20.64 • 5.07 6.41 10.41 26.04 • 5.12 48.01 5.11 14.17 5.21 8.78 138.74 92.32 70.54 29.46 39.41 8.75 6.81 7.24 25.4 3.9 6.42 29.46 28.91 28.58 • 19.64 10.73 9.46 9.76 16.37 17.29 • 13.86 18.11 5.23 16.41 9.86 13.62 11.04 11.15 13.62 14.92 12.04 19.33 8.05 10.27 7.16 12.08 18.1 19.93 20.41 14.49 15.99 13.42 9.98 10.34 12.68 9.83 11.64 14.39 11.9 5.84 • 13.21 C-5 Site Sample No. Date Liver/Body Gonad/Body GSI gonad wt./ (total HSI liver wt./(tolal wl x 100 wt x 100 wt - gonad wt) x 1,000 wt - liver wt) x 1,000 Russian River 5238 Russian River 5239 Russian River 5240 Russian River 5241 Russian River 5242 Russian River 5243 Russian River 5244 2.03 4.38 45.82 20.32 Russian River 5245 0 5.42 57.27 3 Russian River 5246 Russian River 5247 Russian River 5248 Russian River 5249 Russian River 5250 Russian River 5251 Russian River 5252 Berkley 5253 Jan. • Berkley 5254 Jan. • Berkley 5255 Jan. Berkley 5256 Jan. • Berkley 5257 Jan. • Berkley 5258 Jan. • Berkley 5260 Jan. Berkley 5261 Jan. • Berkley 5263 Jan. • Vallejo 5264 Jan. • Vallejo 5265 Jan. • Vallejo 5266 Jan. • Oakland 5267 Jan. Oakland 5268 Jan. Oakland 5269 Jan. Santa Cruz 5275 Jan. • Santa Cruz 5276 Jan. • Santa Cruz 5278 Jan. • Santa Cruz 5279 Jan. Santa Cruz 5280 Jan. • Santa Cruz 5311 Jan. Santa Cruz 5312 Jan. • Santa Cruz 5313 Jan. • Santa Cruz 5314 Jan. • Santa Cruz 5315 Jan. • Santa Cruz 5316 Jan. • Santa Cruz 5317 Jan. • Santa Cruz 5318 Jan. • Berkley 5319 Jan. Berkley 5320 Jan. • C-6 Site Sample No. Date AHH activity AHH with 7.8-BF Egg Stage Testosterone Vitellogenin Estradiol pmol/mg/min pmol/mg/min nq/ml uq/P/ml nq/ml Berkeley 5120 Nov 50 11 0 1.17 _ 0.3 Berkeley 5121 • • 0 • - • Berkeley 5122 • • 0 • - • Berkeley 5123 • • 0 • - • Berkeley 5124 • • 0 • - • Berkeley 5125 • • 0 • - • Berkeley 5126 Nov 41 13 4 0.14 19.43 6.81 Berkeley 5127 Nov 42 9 0 0.1 2.86 1.03 Berkeley 5128 • • • 0 • - • Berkeley 5129 • • • 0 • - • Berkeley 5130 Nov 111 43 0 0.1 2.67 3.36 Berkeley 5131 • • • 0 • - • Berkeley 5132 • • • 0 • - • Berkeley 5133 Nov 1 14 50 0 1.29 2.55 0.44 Berkeley 5134 • • • 0 • - • Berkeley 5135 Nov 103 35 4 0.14 10.9 7.98 Berkeley 5136 Nov 96 24 5 0.07 14.16 5.8 Berkeley 5137 Nov 39 13 0 0.09 2.98 1.28 Berkeley 5138 • • • 0 • - • Berkeley 5139 Nov 49 17 5 0.24 20.83 11.47 Berkeley 5140 Nov 37 13 0 1.63 4.07 0.34 Berkeley 5141 • • • 0 • - • Berkeley 5142 Nov 86 16 0 0.64 3.21 0.33 Berkeley 5143 • • • 0 • - • Berkeley 5144 • * • 0 • - • Berkeley 5145 • • • 0 • - • Berkeley 5146 Nov 165 50 0 0.26 4.46 0.08 Berkeley 5147 • • • 0 • - • Berkeley 5148 • • • 0 • - • Berkeley 5149 Nov 89 39 0 • - • Berkeley 5150 Nov 79 14 5 0.12 20.52 16.77 Vallejo 5151 Nov 97 39 0 0.11 3.68 0.72 Vallejo 5152 Nov 33 11 0 0.09 2.05 0.28 Vallejo 5153 Nov 56 18 0 2.58 2.98 0.32 Vallejo 5154 Nov 170 23 0 1.37 2.82 0.26 San Pablo Bay 5155 Nov 86 45 0 0.14 12.56 8.71 San Pablo Bay 5156 Nov 5 1.4 0 1.56 3.52 0.58 San Pablo Bay 5157 Nov 193 44 0 1.6 3.76 0.2 San Pablo Bay 5158 Nov • • 0 1.48 3.1 0.22 San Pablo Bay 5159 Nov 83 39 0 0.17 3.02 0.13 San Pablo Bay 5160 Nov 163 • 0 0.12 1.74 0.73 San Pablo Bay 5161 Nov 98 • 0 0.06 1.35 0.58 San Pablo Bay 5162 • • • 0 • - • San Pablo Bay 5163 Nov 126 • 0 0.65 1.58 0.67 San Pablo Bay 5164 Nov 49 • 0 3.67 1.51 0.2 San Pablo Bay 5165 Nov 80 • 0 2.82 4.34 0.49 Oakland 5166 Nov 356 31 1 • - • Oakland 5167 Nov 178 111 0 0.12 4.07 1.58 Oakland 5168 Nov 587 45 1 0.21 3.29 1.01 Oakland 5169 Nov 209 • 0 • - • Oakland 5170 • • • 0 • - • Oakland 5171 Nov 40 24 5 0.19 17.57 1.72 Oakland 5172 Nov 166 31 4 • - • Oakland 5173 • • • 0 • - • Oakland 5174 • • • 0 • - • Oakland 5175 • • • 0 • - • Oakland 5176 Nov 615 46 1 0.73 0.98 0.58 San Pablo Bay 5177 • • • 0 • - • San Pablo Bay 5178 • • • 0 • - • C-7 Site Sample No. Dale AHH activity AHH with 7,8-BF Egg Stage Testosterone Vitellogenin Estradiol pmol/mq/min pmol/mg/min ng/ml uq/P/ml ng/ml San Pablo Bay 5179 • • 0 • _ • San Pablo Bay 5180 • • 0 • - • San Pablo Bay 5181 • • 0 • - • San Pablo Bay 5182 Nov 266 60 0 0.12 1.66 0.63 San Pablo Bay 5183 • • 0 • - • San Pablo Bay 5184 • • 0 • - • San Pablo Bay 5185 Nov 193 23 0 0.13 1.96 0.53 San Pablo Bay 5186 • • 0 • - • San Pablo Bay 5187 • • 0 • - • San Pablo Bay 5188 • • 0 • - • San Pablo Bay 5189 • • 0 • - • San Pablo Bay 5190 • • 0 • - • San Pablo Bay 5191 Nov 337 42 0 1.22 - 0.23 San Pablo Bay 5192 • • 0 • - • San Pablo Bay 5193 • • 0 ■ - • San Pablo Bay 5194 • • 0 • - • San Pablo Bay 5195 Nov 66 2 0 0 0.74 1.81 0.15 San Pablo Bay 5196 • • 0 • - • Vallejo 5197 • • 0 • - • Vallejo 5198 Nov 449 134 0 • - • Vallejo 5199 • • • 0 • - • Vallejo 5200 Nov 74 41 0 2.27 1.88 0.27 Vallejo 5201 Nov 268 58 4 0.13 8.61 3.13 Vallejo 5202 Nov 94 27 1 0.82 - 0.69 Vallejo 5203 Nov 958 79 0 2.24 1.81 0.64 Vallejo 5204 Nov 381 112 0 0.07 1.81 0.8 Vallejo 5205 Nov 79 26 4 • - • Vallejo 5206 • • • 0 • - • Vallejo 5207 Nov 437 72 0 0.09 2.03 0.48 Vallejo 5208 Nov 157 33 0 0.47 - 0.67 Vallejo 5209 Nov 252 91 0 3.44 1.66 0.12 Vallejo 5210 • • • • • • Vallejo 5211 • ■ • 0 • - • Vallejo 5212 • • • 0 • - • Oakland 5213 Nov 443 102 4 0.18 13.4 8.57 Oakland 5214 • • • 0 • - • Oakland 5215 Nov 773 93 0 0.09 0.91 • Oakland 5216 Nov 148 28 5 0.97 12.13 19.59 Oakland 5217 Nov 380 27 0 0.18 0.68 0.37 Oakland 5218 Nov 160 103 1 0.14 1.13 0.26 Oakland 5219 Nov 88 40 0 0.08 1.28 0.37 Oakland 5220 Nov 75 16 0 1.62 1.58 0.81 Oakland 5221 Nov 89 19 6 0.41 18.49 24.16 Russian River 5222 Nov 234 28 7 0.3 13.62 10.24 Russian River 5223 Nov 31 16 7 0.21 16.09 9.12 Russian River 5224 Nov 31 12 5 0.1 3.38 1.08 Russian River 5225 Nov 17 12 5 0.27 15.12 2.74 Russian River 5226 Nov 107 46 0 0.04 2.89 0.5 Russian River 5227 Nov 57 22 0 0.11 3.3 0.33 Russian River 5228 Nov 130 41 0 0.14 3.46 0.33 Russian River 5229 Nov 137 46 0 0.35 3.87 0.18 Russian River 5230 Nov 15 9 0 0.15 2.8 0.22 Russian River 5231 Nov 65 31 0 0.14 3.13 0.53 Russian River 5232 Nov 33 28 0 0.42 3.54 0.29 Russian River 5233 Nov 7 12 0 0.37 3.05 0.21 Russian River 5234 Nov 56 30 0 1.07 2.8 0.57 Russian River 5235 • • • 0 • - • Russian River 5236 Nov 32 24 0 0.28 2.31 0.44 Russian River 5237 • • » 0 • - • C-8 Site Sample No. Dale AH H activity AHH with 7.8-BF Egg Stage Testosterone Vitellogenin Estradiol pmol/mg/min pmol/mg/min ng/ml ug/P/ml ng/ml Russian River 5238 Russian River 5239 Russian River 5240 Russian River 5241 Russian River 5242 Russian River 5243 Russian River 5244 1 Russian River 5245 Russian River 5246 Russian River 5247 Russian River 5248 Russian River 5249 Russian River 5250 Russian River 5251 Russian River 5252 Berkeley 5253 Jan. 2 Berkeley 5254 Jan. Berkeley 5255 Jan. 0 Berkeley 5256 Jan. Berkeley 5257 Jan. Berkeley 5258 Jan. Berkeley 5260 Jan. Berkeley 5261 Jan. Berkeley 5263 Jan. 5 Vallejo 5264 Jan. Vallejo 5265 Jan. Vallejo 5266 Jan. Oakland 5267 Jan. Oakland 5268 Jan. 1 Oakland 5269 Jan. Santa Cruz 5275 Jan. Santa Cruz 5276 Jan. 6 Santa Cruz 5278 Jan. Santa Cruz 5279 Jan. Santa Cruz 5280 Jan. Santa Cruz 5311 Jan. Santa Cruz 5312 Jan. Santa Cruz 5313 Jan. Santa Cruz 5314 Jan. Santa Cruz 5315 Jan. Santa Cruz 5316 Jan. Santa Cruz 5317 Jan. Santa Cruz 5318 Jan. Berkeley 5319 Jan. Berkeley 5320 J; an. 0.17 0.18 47 3 09 42 21 76 1.41 1.49 1.09 19.25 9.04 11. 12. 14 19 20 25 50 15 17 C-9 Site Sample No. Dale Micronuclei (cnls/1.000cells) Nuclear Pleomorphism Cytochrome Cytochrome b5 Detached Attached Rating • P450 nmol/mg nmol/mg Berkeley 5120 Nov 2 0 Berkeley 5121 0 0 Berkeley 5122 0 1 Berkeley 5123 0.5 0.5 Berkeley 5124 1.5 0.5 Berkeley 5125 0.5 0 Berkeley 5126 Nov 1.5 0 Berkeley 5127 Nov 2 0 Berkeley 5128 • 0.5 2 Berkeley 5129 • 0.5 1 Berkeley 5130 Nov 3 3.5 Berkeley 5131 • 0 0.5 Berkeley 5132 • 0.5 0 Berkeley 5133 Nov 1.5 5.5 Berkeley 5134 • 0 0 Berkeley 5135 Nov 1 1.5 Berkeley 5136 Nov 1 2.5 Berkeley 5137 Nov 0 0.5 Berkeley 5138 • 0.5 5 Berkeley 5139 Nov 1 0.5 Berkeley 5140 Nov 0.5 0 Berkeley 5141 • 1.5 0.5 Berkeley 5142 Nov 1.5 0.5 Berkeley 5143 • 0 0.5 Berkeley 5144 • 0 0 Berkeley 5145 • 0.5 0 Berkeley 5146 Nov 0 0.5 Berkeley 5147 • 1 0 Berkeley 5148 • 0 1.5 Berkeley 5149 Nov 0.5 1 Berkeley 5150 Nov 2 0.5 Vallejo 5151 Nov 0 1.5 Vallejo 5152 Nov 2 0.5 Vallejo 5153 Nov 1 1 Vallejo 5154 Nov 1 1.5 San Pablo Bay 5155 Nov 0.5 0.5 San Pablo Bay 5156 Nov 1.5 0.5 San Pablo Bay 5157 Nov 1 0 San Pablo Bay 5158 Nov 1 1 San Pablo Bay 5159 Nov 1.5 1 San Pablo Bay 5160 Nov 3 1.5 San Pablo Bay 5161 Nov - 26.9 San Pablo Bay 5162 • 0 0.5 San Pablo Bay 5163 Nov - 0 San Pablo Bay 5164 Nov 1.5 1 San Pablo Bay 5165 Nov 0.5 0.5 Oakland 5166 Nov 1 3.5 Oakland 5167 Nov 0 0 Oakland 5168 Nov 0.5 0.5 Oakland 5169 Nov 0.5 2.5 Oakland 5170 • 0.5 0 Oakland 5171 Nov 0 0.5 Oakland 5172 Nov 0 0 Oakland 5173 • 0.5 0 Oakland 5174 • 0.5 0 Oakland 5175 • 0 0 Oakland 5176 Nov 1 0 San Pablo Bay 5177 • 0.5 0 San Pablo Bay 5178 0 0 2 1 2 1 2 1 1 1 2 1 3 1 1 3 1 2 3 1 3 2 1 1 1 1 1 1 1 1 2 1 2 2 2 2 1 1 2 1 1 1 2 0.23 0.22 0.21 0.16 0.12 0.09 0.24 0.12 0.21 0.15 0.13 0.14 0.11 0.109 0.038 0.119 0.165 0.27 0.066 0.114 0.12 0.071 0.056 0.089 0.104 0.076 0.042 0.146 0.228 0.114 0.21 0.072 0.19 0.213 0.045 0.038 0.028 0.102 0.03 0.102 C-10 Site Sample No. Date Micronuclei (cnts/1,000cells) Nuclear Pleomorphism Cytochrome Cytochrome b5 Detached Attached Rating * P450 nmol/mg nmol/mg San Pablo Bay 5179 • 1.5 1.5 San Pablo Bay 5180 • 0 0 San Pablo Bay 5181 • 0.5 0 San Pablo Bay 5182 Nov 1 0.5 San Pablo Bay 5183 • 0.5 0 San Pablo Bay 5184 • 0.5 3.5 San Pablo Bay 5185 Nov 0 0.5 San Pablo Bay 5186 • 0 1 San Pablo Bay 5187 • 1 0.5 San Pablo Bay 5188 • 0 0 San Pablo Bay 5189 • 0 0.5 San Pablo Bay 5190 • 0.5 2 San Pablo Bay 5191 Nov 0.5 1 San Pablo Bay 5192 • 0 0 San Pablo Bay 5193 • 0 0 San Pablo Bay 5194 • 0 0.5 San Pablo Bay 5195 Nov 2 0 San Pablo Bay 5196 • 0.5 0.5 Vallejo 5197 • 0 0 Vallejo 5198 Nov 0.5 0 Vallejo 5199 • 0.5 0.5 Vallejo 5200 Nov 0 0.5 Vallejo 5201 Nov 0.5 0 Vallejo 5202 Nov 5.5 1.5 Vallejo 5203 Nov 1.5 0.5 Vallejo 5204 Nov 2 0.5 Vallejo 5205 Nov 0 0.5 Vallejo 5206 • 0 1.5 Vallejo 5207 Nov - - Vallejo 5208 Nov 0.5 0 Vallejo 5209 Nov 1.5 0.5 Vallejo 5210 0 0 Vallejo 5211 • 1.5 0 Vallejo 5212 • 0.5 0 Oakland 5213 Nov 1 3.5 Oakland 5214 • 0 1.5 Oakland 5215 Nov 0 1.5 Oakland 5216 Nov 1 7 Oakland 5217 Nov 0 0 Oakland 5218 Nov 0.5 0 Oakland 5219 Nov 0 0 Oakland 5220 Nov 0 0 Oakland 5221 Nov 0 0 Russian River 5222 Nov 0 0 Russian River 5223 Nov 0 0 Russian River 5224 Nov 0 0 Russian River 5225 Nov 0 0 Russian River 5226 Nov 0 0 Russian River 5227 Nov 0 0 Russian River 5228 Nov 0 1 Russian River 5229 Nov - - Russian River 5230 Nov 0 0 Russian River 5231 Nov 0 0 Russian River 5232 Nov 0 0.5 Russian River 5233 Nov 0 0.5 Russian River 5234 Nov 0 0 Russian River 5235 • 0 0 Russian River 5236 Nov 0 0 Russian River 5237 • 0 0.5 0.149 0.091 0.127 0.236 0.211 • 0.15 0.098 0.048 0.195 0.2 0.083 0.161 0.095 0.217 • 0.149 0.241 0.028 0.171 0.049 0.091 0.015 0.12 0.031 0.256 0.078 0.21 0.099 0.11 • 0.15 0.102 0.185 0.04 0.144 0.033 0.107 0.028 0.112 0.034 0.088 0.027 0.126 0.057 0.154 0.104 0.23 • 0.036 0.039 0.128 0.039 0.17 0.1 0.1 0.19 • C-11 Site Sample No. Dale Micronuclei Detached (cnts/1,000cells) Attached Nuclear Pleomorphism Rating • Cytochrome Cytochrome b5 P450 nmol/mg nmol/mg Russian River 5238 0 0 Russian River 5239 1 1 Russian River 5240 0 0.5 Russian River 5241 0.5 0 Russian River 5242 1 1.5 Russian River 5243 1.5 1 Russian River 5244 0 0 Russian River 5245 0 0 Russian River 5246 0 0 Russian River 5247 0 0 Russian River 5248 0 0.5 Russian River 5249 0 0.5 Russian River 5250 0 0 Russian River 5251 0 1 Russian River 5252 0 0 Berkley 5253 Jan. 0 0.5 Berkley 5254 Jan. 0 1 Berkley 5255 Jan. 0.5 11 Berkley 5256 Jan. 0.5 0 Berkley 5257 Jan. 0 1.5 Berkley 5258 Jan. 0 0 Berkley 5260 Jan. 0 0.5 Berkley 5261 Jan. 0.5 0 Berkley 5263 Jan. - - Vallejo 5264 Jan. 0 0.5 Vallejo 5265 Jan. 0.5 0 Vallejo 5266 Jan. 0 0.5 Oakland 5267 Jan. 0 0 Oakland 5268 Jan. 3.5 0.5 Oakland 5269 Jan. 1 1.5 Santa Cruz 5275 Jan. 0 0 Santa Cruz 5276 Jan. 0.5 0.5 Santa Cruz 5278 Jan. 0.5 1.5 Santa Cruz 5279 Jan. 0.5 1 Santa Cruz 5280 Jan. 1 0 Santa Cruz 5311 Jan. 0 0 Santa Cruz 5312 Jan. 0 0.5 Santa Cruz 5313 Jan. 0.5 0 Santa Cruz 5314 Jan. 0 0 Santa Cruz 5315 Jan. 0 0 Santa Cruz 5316 Jan. 0 0 Santa Cruz 5317 Jan. 0 0 Santa Cruz 5318 Jan. 0.5 1.5 Berkley 5319 Jan. 0.5 0.5 Berkley 5320 J; in. 1.5 0.5 0.075 0 06 059 0. 012 0.013 51 22 0.076 0.025 0.006 0.021 09 C-12 Site Sample No. Date Cytochrome %Denatured P450 Cytochrome P420 nmol/mg (T450/420) P-450E pmol/mg P450E/ ERX) P450 xlOO nmol/min/mg Berkeley 5120 Nov Berkeley 5121 Berkeley 5122 Berkeley 5123 Berkeley 5124 Berkeley 5125 Berkeley 5126 Nov Berkeley 5127 Nov Berkeley 5128 • Berkeley 5129 • Berkeley 5130 Nov Berkeley 5131 • Berkeley 5132 • Berkeley 5133 Nov Berkeley 5134 • Berkeley 5135 Nov Berkeley 5136 Nov Berkeley 5137 Nov Berkeley 5138 • Berkeley 5139 Nov Berkeley 5140 Nov Berkeley 5141 • Berkeley 5142 Nov Berkeley 5143 • Berkeley 5144 • Berkeley 5145 • Berkeley 5146 Nov Berkeley 5147 • Berkeley 5148 • Berkeley 5149 Nov Berkeley 5150 Nov Vallejo 5151 Nov Vallejo 5152 Nov Vallejo 5153 Nov Vallejo 5154 Nov San Pablo Bay 5155 Nov San Pablo Bay 5156 Nov San Pablo Bay 5157 Nov San Pablo Bay 5158 Nov San Pablo Bay 5159 Nov San Pablo Bay 5160 Nov San Pablo Bay 5161 Nov San Pablo Bay 5162 • San Pablo Bay 5163 Nov San Pablo Bay 5164 Nov San Pablo Bay 5165 Nov Oakland 5166 Nov Oakland 5167 Nov Oakland 5168 Nov Oakland 5169 Nov Oakland 5170 • Oakland 5171 Nov Oakland 5172 Nov Oakland 5173 • Oakland 5174 • Oakland 5175 • Oakland 5176 Nov San Pablo Bay 5177 • San Pablo Bay 5178 » 0.02 0.06 0.1 0.061 0.181 0.079 0.08 0.05 0.11 0.106 0.04 0.043 0.1 0.08 0.05 0.09 0.04 0.06 0.05 0.05 0.1 0.044 0.14 0.07 0.083 0.048 0.194 0.106 100 0 33 50 0 ■ 30 46 • 35 38 28 50 49 51 0 21 0 60 41 29 56 41 40 • 32 40 70 23 38 38 28 • 40 50 33 84.1 53.5 36.6 24.3 25.7 6.2 • 0.8 0.5 1.6 36.7 0.172 0.149 0.231 0.148 0.001 0.17 0.23 0.24 0.124 6.5 3.5 0.17 1.7 0.8 0.054 1.7 0.8 0.057 • • 0.014 0.2 0.2 0.06 2.6 1.2 0.127 • • 0.049 • • 0.062 • • 0.031 3.1 1.8 0.131 4.9 3 0.032 2.8 2.9 0.064 2.9 2 0.089 • • * 3.2 2.1 0.072 • • 0.027 • • 0.039 15 7.9 0.14 45 12.2 0.547 33 18 0.244 21 7.2 0.125 1.8 1.5 0.055 9 2.3 0.107 0.356 C-13 Site Sample No. Date Cytochrome "/(.Denatured P450 Cytochrome P450E/ EROD P420 nmol/mq (T450/420) P-450E pmol/mq P450 X100 "imol/min/mg San Pablo Bay 5179 • San Pablo Bay 5180 • San Pablo Bay 5181 • San Pablo Bay 5182 Nov 0.11 71 1.8 0.7 0.078 San Pablo Bay 5183 • San Pablo Bay 5184 • San Pablo Bay 5185 Nov 0 3.1 3.4 0.044 San Pablo Bay 5186 • San Pablo Bay 5187 • San Pablo Bay 5188 • San Pablo Bay 5189 ■ San Pablo Bay 5190 • San Pablo Bay 5191 Nov 0.06 32 4.8 2.6 0.096 San Pablo Bay 5192 • San Pablo Bay 5193 • San Pablo Bay 5194 • San Pablo Bay 5195 Nov 0.06 20 0.059 San Pablo Bay 5196 • Vallejo 5197 • Vallejo 5198 Nov 0.107 34 1.9 0.6 0.073 Vallejo 5199 • • • • 4 Vallejo 5200 Nov 0.084 36 2.2 0.9 0.04 Vallejo 5201 Nov 0.199 67 0.04 0.01 0.05 Vallejo 5202 Nov 0.055 56 • 0.014 Vallejo 5203 Nov • 0 • 0.141 Vallejo 5204 Nov • 0 8 4 0.245 Vallejo 5205 Nov 0.063 43 • 0.048 Vallejo 5206 • • • • 1 Vallejo 5207 Nov 0.144 70 25 12.2 0.145 Vallejo 5208 Nov 0.054 36 0.2 0.1 0.115 Vallejo 5209 Nov 0.251 54 6.3 1.4 0.109 Vallejo 5210 • • • • i Vallejo 5211 • 0.11 71 1.8 0.7 0.078 Vallejo 5212 • • • . • * Oakland 5213 Nov 0.54 69 34.6 4.4 0.248 Oakland 5214 • • • • • t Oakland 5215 Nov 0.082 32 • • 0.667 Oakland 5216 Nov 0.05 35 0.5 3.5 0.046 Oakland 5217 Nov • 0 26 21.7 0.232 Oakland 5218 Nov 0.087 25 52 15.2 0.349 Oakland 5219 Nov • 0 82 39 0.61 Oakland 5220 Nov 0.046 29 14 9 0.118 Oakland 5221 Nov • 0 0.3 1.8 0.035 Russian River 5222 Nov 0.093 33 4.2 1.5 0.099 Russian River 5223 Nov • 0 0.8 0.6 0.064 Russian River 5224 Nov 0.02 16 1.3 1 0.056 Russian River 5225 Nov 0.134 54 • • 0.06 Russian River 5226 Nov 0.054 38 5 3.5 0.043 Russian River 5227 Nov 0.111 47 0.3 0.1 0.055 Russian River 5228 Nov • 0 5.8 3.7 0.063 Russian River 5229 Nov 0.09 28 4 1.2 0.054 Russian River 5230 Nov 0.059 62 • • 0.002 Russian River 5231 Nov 0.085 40 • • 0.021 Russian River 5232 Nov 0.05 23 2.9 1.3 0.033 Russian River 5233 Nov 0.08 44 • • 0.018 Russian River 5234 Nov 0.04 28 • . 0.01 Russian River 5235 • • • • • « Russian River 5236 Nov 0.082 30 3 1.1 0.033 Russian River 5237 • • • • • « C-14 Site Sample No. Dale Cytochrome %Denalured P450 Cytochrome P450E/ EPOD P420 nmol/mg (T450/420) P-450E pmol/mg P450 x100 nmol/min/mg Russian River 5238 Russian River 5239 Russian River 5240 Russian River 5241 Russian River 5242 Russian River 5243 Russian River 5244 Russian River 5245 Russian River 5246 Russian River 5247 Russian River 5248 Russian River 5249 Russian River 5250 Russian River 5251 Russian River 5252 Berkley 5253 Jan. Berkley 5254 Jan. Berkley 5255 Jan. Berkley 5256 Jan. Berkley 5257 Jan. Berkley 5258 Jan. Berkley 5260 Jan. Berkley 5261 Jan. Berkley 5263 Jan. Vallejo 5264 Jan. Vallejo 5265 Jan. Vallejo 5266 Jan. Oakland 5267 Jan. Oakland 5268 Jan. Oakland 5269 Jan. Santa Cruz 5275 Jan. Santa Cruz 5276 Jan. Santa Cruz 5278 Jan. Santa Cruz 5279 Jan. Santa Cruz 5280 Jan. Santa Cruz 5311 Jan. Santa Cruz 5312 Jan. Santa Cruz 5313 Jan. Santa Cruz 5314 Jan. Santa Cruz 5315 Jan. Santa Cruz 5316 Jan. Santa Cruz 5317 Jan. Santa Cruz 5318 Jan. Berkley 5319 Jan. Berkley 5320 J: in. 0.033 35 44 01 66 I 00 0.094 78 38 39 38 64 53 84 0.063 0.079 0.103 0.063 0.1 C-15 Site Sample No. Dale EROD/p450 nmol/min/nmol P450 Estradiol 2-OHase nmol/min/mq Berkeley 5120 Nov 0.76 . Berkeley 5121 • • Berkeley 5122 • • Berkeley 5123 • • Berkeley 5124 • • Berkeley 5125 • • Berkeley 5126 Nov • 0.015 Berkeley 5127 Nov 0.68 - Berkeley 5128 • • • Berkeley 5129 • • • Berkeley 5130 Nov 0.91 0.035 Berkeley 5131 • • • Berkeley 5132 • • ■ Berkeley 5133 Nov 0.94 - Berkeley 5134 • • • Berkeley 5135 Nov 0.02 0.01 Berkeley 5136 Nov • 0.011 Berkeley 5137 Nov 0.71 0.025 Berkeley 5138 • • • Berkeley 5139 Nov • 0.008 Berkeley 5140 Nov 1.12 - Berkeley 5141 • • • Berkeley 5142 Nov 1.61 - Berkeley 5143 • • • Berkeley 5144 • • • Berkeley 5145 • • • Berkeley 5146 Nov 0.96 - Berkeley 5147 • • ■ Berkeley 5148 • • ■ Berkeley 5149 Nov 1.24 0.015 Berkeley 5150 Nov 0.47 0.007 Vallejo 5151 Nov 0.52 - Vallejo 5152 Nov 0.38 0.01 Vallejo 5153 Nov 0.5 0.016 Vallejo 5154 Nov 0.77 - San Pablo Bay 5155 Nov 0.14 - San Pablo Bay 5156 Nov 0.94 • San Pablo Bay 5157 Nov 0.28 • San Pablo Bay 5158 Nov 1.09 • San Pablo Bay 5159 Nov 0.45 • San Pablo Bay 5160 Nov 1.12 0.018 San Pablo Bay 5161 Nov 1 0.031 San Pablo Bay 5162 • • • San Pablo Bay 5163 Nov 0.69 0.038 San Pablo Bay 5164 Nov 0.35 - San Pablo Bay 5165 Nov 0.39 - Oakland 5166 Nov 0.96 0.012 Oakland 5167 Nov 2.39 0.041 Oakland 5168 Nov 2.14 0.015 Oakland 5169 Nov 0.6 - Oakland 5170 • • • Oakland 5171 Nov 0.75 - Oakland 5172 Nov 0.56 0.018 Oakland 5173 • • • Oakland 5174 • • • Oakland 5175 • • • Oakland 5176 Nov 1.67 0.036 San Pablo Bay 5177 • • • San Pablo Bay 5178 • • • C-16 Site Sample No. Dale EROD/p450 nmol/min/nmol P450 Estradiol 2-OHase nmol/rnin/mq San Pablo Bay 5179 , • San Pablo Bay 5180 • • San Pablo Bay 5181 • • San Pablo Bay 5182 Nov 0.53 0.032 San Pablo Bay 5183 • • San Pablo Bay 5184 • • San Pablo Bay 5185 Nov 0.48 0.022 San Pablo Bay 5186 • • San Pablo Bay 5187 • • San Pablo Bay 5188 • • San Pablo Bay 5189 • • San Pablo Bay 5190 • • San Pablo Bay 5191 Nov 0.76 San Pablo Bay 5192 • • San Pablo Bay 5193 • • San Pablo Bay 5194 • • San Pablo Bay 5195 Nov 0.25 San Pablo Bay 5196 • • Vallejo 5197 • • Vallejo 5198 Nov 0.35 - Vallejo 5199 • • • Vallejo 5200 Nov 0.17 - Vallejo 5201 Nov 0.52 0.026 Vallejo 5202 Nov 0.29 - Vallejo 5203 Nov 0.773 - Vallejo 5204 Nov 1.22 - Vallejo 5205 Nov 0.57 0.018 Vallejo 5206 • • • Vallejo 5207 Nov 0.9 0.044 Vallejo 5208 Nov 1.21 0.03 Vallejo 5209 Nov 0.5 - Vallejo 5210 • • Vallejo 5211 • 0.53 • Vallejo 5212 • • • Oakland 5213 Nov 1.03 0.017 Oakland 5214 • • • Oakland 5215 Nov 3.9 0.039 Oakland 5216 Nov 0.51 0.014 Oakland 5217 Nov 1.93 0.01 Oakland 5218 Nov 1.36 0.048 Oakland 5219 Nov 2.9 0.051 Oakland 5220 Nov 1.07 - Oakland 5221 Nov 0.25 0.069 Russian River 5222 Nov 0.53 0.032 Russian River 5223 Nov 0.44 0.013 Russian River 5224 Nov 0.52 0.011 Russian River 5225 Nov 0.53 0.014 Russian River 5226 Nov 0.49 0.034 Russian River 5227 Nov 0.43 0.031 Russian River 5228 Nov 0.41 0.046 Russian River 5229 Nov 0.33 - Russian River 5230 Nov 0.05 0.021 Russian River 5231 Nov 0.16 0.027 Russian River 5232 Nov 0.19 - Russian River 5233 Nov 0.18 - Russian River 5234 Nov 0.1 - Russian River 5235 • • • Russian River 5236 Nov 0.17 • Russian River 5237 • • C-17 Site Sample No. Date EROD/p450 Estradiol 2-OHase nmol/min/nmol P450 nmol/min/mq Russian River 5238 Russian River 5239 Russian River 5240 Russian River 5241 Russian River 5242 Russian River 5243 Russian River 5244 Russian River 5245 Russian River 5246 Russian River 5247 Russian River 5248 Russian River 5249 Russian River 5250 Russian River 5251 Russian River 5252 Berkley 5253 Jan. Berkley 5254 Jan. Berkley 5255 Jan. Berkley 5256 Jan. Berkley 5257 Jan. Berkley 5258 Jan. Berkley 5260 Jan. Berkley 5261 Jan. Berkley 5263 Jan. Vallejo 5264 Jan. Vallejo 5265 Jan. Vallejo 5266 Jan. Oakland 5267 Jan. Oakland 5268 Jan. Oakland 5269 Jan. Santa Cruz 5275 Jan. Santa Cruz 5276 Jan. Santa Cruz 5278 Jan. Santa Cruz 5279 Jan. Santa Cruz 5280 Jan. Santa Cruz 5311 Jan. Santa Cruz 5312 Jan. Santa Cruz 5313 Jan. Santa Cruz 5314 Jan. Santa Cruz 5315 Jan. Santa Cruz 5316 Jan. Santa Cruz 5317 Jan. Santa Cruz 5318 Jan. Berkley 5319 Jan. Berkley 5320 Ja n. 84 1. 06 52 03 52 31 C-18 APPENDIX D CHEMICAL DATA (ug/kg wet weight) FOR P. STELLATUS Individual chemical data for each P. stellatus sample collected from six sites in the San Francisco Bay area (ug/kg ww). Site MSB opDDE ppDDE opDDD ppDDD opDDT ppDDT tDDT HCB BERKELEY BK 5120 ND 45.14 * 10.98 ND ND 56.12 ND BK 5126 0.85 78.47 * 30.34 ND ND 109.65 ND BK 5127 ND 117.19 * ND 11.42 ND 128.60 ND BK 5130 ND 132.24 * ND ND 3.60 135.84 ND BK 5133 ND 389.65 * 189.67 ND 16.81 596.14 ND BK 5135 ND 137.26 * 35.21 ND ND 172.47 ND BK 5136 ND 330.45 * 148.57 ND 64.36 543.38 0.59 BK 5137 ND 124.83 * 57.44 ND 6.33 188.60 ND BK 5139 ND 153.70 * 108.03 ND 58.57 320.30 ND BK 5140 ND 135.74 * ND ND 3.65 139.39 ND BK 5142 2.33 160.87 * 125.15 ND ND 288.35 ND BK 5146 ND 113.76 * 43.12 ND ND 156.88 ND BK 5149 ND 184.61 * 75.33 ND 10.21 270.16 ND BK 5150 ND 199.26 * 143.00 ND ND 342.26 ND BK 5253 ND 120.35 * 21.71 ND ND 142.06 ND BK 5255 ND 43.13 * 11.82 ND ND 54.94 ND BK 5263 ND 98.56 * 27.49 ND ND 126.05 ND BK 5319 ND 4.67 * 41.78 ND 27.18 73.63 ND 142.77 71.31 11.42 23.84 249.34 AVERAGE= 1.59 142.77 71.31 11.42 23.84 213.60 0.59 STD DEV 1.04 93.53 57.19 24.55 155.16 0.00 OAKLAND OK 5166 ND 175.41 * 112.24 39.83 ND 327.48 ND OK 5167 ND 135.83 * 70.01 ND 5.28 211.12 ND OK 5168 ND 135.34 * 153.46 ND 22.37 311.17 ND OK 5169 8.36 126.11 * 133.91 105.70 ND 374.08 ND OK 5171 1.07 167.25 * 107.98 ND 58.28 334.57 ND OK 5172 ND 101.19 * 70.37 ND ND 171.56 ND OK 5176 1.12 18.94 * 6.27 ND ND 26.33 ND OK 5213 ND 114.43 * 97.27 3.50 14.95 230.15 ND OK 5215 ND 25.06 * 19.34 ND ND 44.39 ND OK 5216 ND 244.01 * 108.29 ND ND 352.30 ND OK 5217 ND 382.52 * 51.02 52.66 9.74 495.94 ND OK 5218 ND 40.37 * 14.87 ND ND 55.24 ND OK 5219 ND 69.21 * 26.27 ND ND 95.48 ND OK 5220 1.44 44.01 * 39.82 ND ND 85.28 ND OK 5221 2.42 13.40 * 97.31 ND 18.95 132.07 0.94 OK 5268 ND 81.46 * 39.73 ND ND 121.18 ND AVERAGE= 2.88 117.16 71.76 50.42 21.59 210.52 0.94 STD DEV 3.11 95.62 45.42 42.32 19.00 140.98 RUSSIAN R RR 5222 40.42 82.82 * ND ND ND 123.24 ND RR 5223 ND ND * 35.17 ND 9.27 44.44 ND RR 5224 ND 10.41 * 3.90 ND 2.60 16.92 ND RR 5225 ND 132.67 * 7.70 ND ND 140.37 ND RR 5227 ND 72.00 * 3.60 ND ND 75.60 ND RR 5228 ND 36.83 * ND ND ND 36.83 ND RR 5229 ND 58.88 * 10.01 ND ND 68.89 ND RR 5230 2.00 172.03 * 17.72 ND ND 191.76 ND RR 5231 ND ND * 7.63 ND 10.89 18.51 ND D-l Site MSB opDDE ppDDE opDDD ppDDD opDDT ppDDT tDDT HCB RR 5232 ND 162.67 * 3.44 ND ND 166.12 ND RR 5233 ND 36.74 * 2.63 ND ND 39.38 ND RR 5234 ND 157.60 * 1.02 ND ND 158.62 ND RR 5236 ND ND * ND ND 40.99 40.99 ND RR 5244 2.28 195.45 * 31.70 ND 6.63 236.07 ND AVERAGE= 14.90 178.91 14.93 ND 14.08 96.98 ND STD DEV 22.10 64.32 11.88 15.37 71.32 SANTA CRUZ 5276 ND 148.05 • 27.81 8.11 2.83 186.80 ND sc 5311 17.52 11.62 * 47.13 14.08 37.46 127.81 ND sc 5316 25.61 25.96 * 23.14 ND 45.83 120.54 ND sc 5318 ND 2.02 * 4.05 3.56 19.90 29.52 ND AVERAGE= 21.56 46.91 25.53 8.58 26.50 116.17 ND STD DEV 5.72 68.14 17.69 5.28 19.13 64.94 ND SAN PABLO SP 5155 2.21 74.68 * 45.30 ND 1.94 124.12 ND SP 5156 2.88 112.33 * 82.59 8.60 6.22 212.62 ND SP 5157 2.05 116.85 * 55.52 ND 4.76 179.19 ND SP 5158 1.71 76.40 * 55.51 ND ND 133.61 ND SP 5159 2.46 39.63 * 8.26 ND ND 50.35 ND SP 5160 4.42 83.48 * 85.93 ND ND 173.84 ND SP 5161 2.39 38.69 * 33.81 ND ND 74.90 ND SP 5163 ND 84.74 * 46.68 ND ND 131.42 ND SP 5164 ND 56.44 * ND ND 12.06 68.51 ND SP 5165 3.79 247.30 * 165.18 ND 5.63 421.91 ND SP 5182 2.67 22.08 * 123.21 ND 20.76 168.72 ND SP 5185 ND 119.29 * 106.99 ND 9.93 236.21 ND SP 5191 3.16 113.25 * 69.13 ND ND 185.53 ND SP 5195 ND 171.94 * 18.23 ND ND 190.16 ND AVERAGE= 2.77 96.94 68.95 8.60 8.76 167.94 ND STD DEV 0.83 58.70 43.81 6.26 91.54 ND VALLEJO VJ 5151 ND 105.96 * 48.14 ND ND 154.10 ND VJ 5152 4.71 419.75 * 94.37 ND 7.02 525.85 ND VJ 5153 ND 61.11 * 43.13 0.96 2.17 107.38 ND VJ 5154 ND 91.05 * 36.30 ND 2.79 130.15 ND VJ 5198 ND 102.28 * 44.10 ND ND 146.38 ND VJ 5200 6.25 111.72 * ND ND ND 117.97 ND VJ 5201 ND 39.96 * 9.06 0.61 ND 49.63 ND VJ 5202 ND 231.16 * 4.27 ND ND 235.43 ND VJ 5203 1.61 115.75 * 70.27 7.30 7.17 202.10 ND VJ 5204 ND 43.44 * 36.27 ND 7.48 87.19 ND VJ 5205 3.06 94.43 * 57.75 1.63 ND 156.87 ND VJ 5207 4.02 73.30 * 26.98 ND ND 104.29 ND VJ 5208 3.04 71.50 * 33.41 ND ND 107.94 ND VJ 5209 1.03 112.83 * 60.85 ND 1.27 175.99 ND AVERAGE= 3.39 .119.59 43.45 2.62 4.65 164.38 ND STD DEV 1.79 97.91 24.21 3.15 2.86 114.44 ND D-2 Site MSB lindane heptachlor aldrin heptepox chlordane transnonachlor BERKELEY BK 5120 4.72 ND ND 1.41 ND 6.76 BK 5126 7.26 0.66 ND 1.36 2.92 13.41 BK 5127 10.62 2.50 ND ND 15.10 30.77 BK 5130 ND 16.31 ND ND 8.65 30.60 BK 5133 6.12 ND 1.49 5.48 10.11 65.69 BK 5135 4.63 12.61 ND 3.52 2.18 17.21 BK 5136 8.77 40.33 ND 8.74 7.53 37.26 BK 5137 20.95 ND ND 2.25 13.39 26.36 BK 5139 ND 1.61 ND 4.75 4.37 19.89 BK 5140 ND ND 0.27 2.58 2.49 16.95 BK 5142 15.92 26.66 1.43 4.86 10.87 33.89 BK 5146 ND 16.70 ND 5.77 4.14 16.03 BK 5149 ND ND ND ND 10.07 25.96 BK 5150 8.64 28.09 ND 6.60 8.64 41.95 BK 5253 ND 47.41 2.55 12.60 ND ND BK 5255 ND 14.86 3.55 8.57 ND 4.61 BK 5263 ND ND 4.80 ND 0.30 8.31 BK 5319 ND ND ND 13.67 3.29 8.50 AVERAGE= 9.74 18.89 2.35 5.87 6.94 23.77 STD DEV 5.45 15.44 1.64 3.87 4.47 15.57 OAKLAND OK 5166 ND ND ND 7.32 8.71 40.01 OK 5167 11.20 ND ND 4.64 7.60 53.34 OK 5168 19.72 ND ND 5.95 8.86 36.33 OK 5169 ND ND ND 11.88 12.48 24.48 OK 5171 ND ND 0.64 6.78 4.79 23.97 OK 5172 ND ND ND ND 7.37 15.85 OK 5176 ND 1.24 0.69 ND 0.62 2.54 OK 5213 4.90 ND ND 2.22 4.94 33.72 OK 5215 ND 10.47 3.66 2.16 1.09 6.39 OK 5216 2.80 ND ND 3.65 12.70 41.77 OK 5217 ND ND ND ND 21.63 71.82 OK 5218 ND 16.96 4.19 ND 0.93 10.31 OK 5219 ND ND ND ND 2.65 10.78 OK 5220 5.68 ND 4.90 1.30 3.97 13.66 OK 5221 ND ND ND 13.23 3.80 24.16 OK 5268 ND 8.19 ND 0.46 0.13 6.68 AVERAGE= 8.86 9.21 2.82 5.42 6.39 25.99 STD DEV 6.82 6.49 2.01 4.18 5.68 19.16 RUSSIAN R RR 5222 ND 9.98 12.14 24.22 2.81 7.79 RR 5223 ND 67.69 ND ND ND 5.30 RR 5224 6.91 ND ND ND 5.10 3.42 RR 5225 ND ND ND 8.81 0.70 ND RR 5227 ND ND 10.40 1.20 ND 3.20 RR 5228 ND ND 3.83 ND ND 5.51 RR 5229 ND 3.06 3.65 ND 0.66 1.73 RR 5230 ND ND 6.61 28.87 ND 11.54 RR 5231 ND ND ND ND 2.05 8.23 D-3 Site MSB lindane heptachlor aldrin heptepox chlordane transnonachlor RR 5232 ND 7.85 ND ND ND 2.68 RR 5233 ND ND ND 0.27 0.49 2.30 RR 5234 ND 1.50 ND 2.67 1.28 7.11 RR 5236 ND ND ND ND 2.43 8.16 RR 5244 ND ND ND 1.17 1.72 8.59 AVERAGE= 6.91 18.02 30.31 12.15 1.92 9.05 STD DEV 27.98 3.83 11.99 1.45 3.02 , SANTA CRUZ 5276 ND 5.84 5.60 0.30 2.23 3.84 SC 5311 ND ND ND 6.82 5.43 14.53 sc 5316 ND ND ND 25.39 3.59 3.44 SC 5318 ND ND ND ND ND 2.68 AVERAGE= ND 5.84 5.60 10.84 3.75 6.12 STD DEV ND 13.02 1.61 5.62 SAN PABLO SP 5155 0.72 ND ND 2.18 5.39 8.09 SP 5156 6.15 18.20 2.30 4.20 9.98 15.48 SP 5157 7.18 ND ND 6.24 5.78 15.96 SP 5158 6.98 ND ND 4.17 5.33 11.29 SP 5159 5.15 ' ND ND 6.20 1.54 3.78 SP 5160 5.28 ND ND 6.87 13.74 21.31 SP 5161 2.05 ND ND 4.84 4.74 9.61 SP 5163 ND ND ND ND 5.53 12.75 SP 5164 ND ND 1.84 2.61 20.84 20.69 SP 5165 17.64 ND ND 9.49 29.62 65.12 SP 5182 8.58 6.82 ND ND 11.67 16.11 SP 5185 ND ND ND ND 4.96 ND SP 5191 ND 2.85 2.41 3.57 5.60 18.51 SP 5195 1.31 1.57 1.01 1.40 1.96 13.78 AVERAGE= 6.11 7.36 1.89 4.71 9.05 17.88 STD DEV 4.84 7.56 0.64 2.36 7.83 15.04 VALLEJO VJ 5151 ND 4.36 ND 2.71 6.60 27.56 VJ 5152 ND ND 1.56 1.71 13.42 46.85 VJ 5153 1.84 1.35 3.04 2.12 7.06 17.02 VJ 5154 ND ND ND ND 8.89 16.84 VJ 5198 ND ND 1.54 2.09 5.92 16.21 VJ 5200 12.82 6.30 3.82 0.64 10.47 17.47 VJ 5201 ND ND ND 2.33 1.43 ND VJ 5202 1.52 13.44 ND ND ND 5.37 VJ 5203 ND ND ND 1.36 11.27 16.61 VJ 5204 14.07 0.89 ND 8.11 2.69 5.12 VJ 5205 15.88 ND ND 28.08 7.15 13.02 VJ 5207 ND ND ND 0.91 8.16 9.41 VJ 5208 ND ND ND 1.73 5.47 11.26 VJ 5209 ND 2.67 1.26 5.45 14.18 17.81 AVERAGE= 9.23 4.84 2.24 4.77 7.90 16.97 STD DEV 6.97 4.67 1.12 7.64 3.77 10.75 D-4 Site MSB dieldrin mirex Total Pesticide 8 18 28 52 44 BERKELEY BK 5120 10.06 ND 10262.95 ND ND ND 11.12 3.95 BK 5126 15.22 ND 10292.82 ND ND 3.97 8.80 ND BK 5127 29.06 ND 10342.06 ND ND ND 19.61 ND BK 5130 28.22 0.90 10344.67 ND ND ND 33.54 7.55 BK 5133 63.27 ND 10418.16 ND ND 15.48 47.36 3.19 BK 5135 20.01 ND 10330.17 ND ND ND 20.80 ND BK 5136 63.58 ND 10438.80 ND ND 13.68 44.35 2.13 BK 5137 22.99 1.62 10361.56 ND ND ND 18.32 ND BK 5139 30.75 ND 10339.37 ND ND 13.18 23.79 40.57 BK 5140 26.41 ND 10328.69 ND ND 3.89 14.26 ND BK 5142 47.00 ND 10424.62 ND ND ND 33.26 ND BK 5146 21.69 ND 10356.33 ND ND 7.65 16.15 8.64 BK 5149 40.88 2.30 10377.20 ND ND 6.75 33.29 20.66 BK 5150 57.42 15.76 10467.09 ND ND 18.92 47.03 3.39 BK 5253 9.37 18.96 10596.89 ND ND 14.93 48.51 2.20 BK 5255 9.17 ND 10550.77 ND 22.71 ND ND ND BK 5263 20.21 2.29 10561.91 6.93 3.58 13.35 18.79 8.33 BK 5319 115.29 ND 10778.74 ND ND 3.33 ND ND AVERAGE= 35.03 6.97 10420.71 6.93 13.15 10.47 27.44 10.06 STD DEV 26.59 8.13 129.39 13.53 5.48 13.68 12.06 OAKLAND OK 5166 45.89 ND 10433.93 ND ND ND ND ND OK 5167 27.35 9.96 10448.07 ND ND 6.41 38.90 9.42 OK 5168 41.69 ND 10448.54 ND ND ND 28.11 10.88 OK 5169 59.78 26.02 10472.64 ND ND ND 65.69 ND OK 5171 41.07 ND 10419.26 ND ND 13.25 33.89 10.12 OK 5172 23.71 39.76 10430.69 12.28 ND ND ND ND OK 5176 2.80 1.68 10361.56 4.20 ND ND 5.45 ND OK 5213 30.71 ND 10502.48 12.94 ND 6.15 22.29 ND OK 5215 12.11 38.57 10504.44 ND ND 2.48 11.49 2.85 OK 5216 44.68 ND 10537.60 ND ND 16.03 20.62 ND OK 5217 18.67 31.70 10577.81 ND ND ND 14.56 9.56 OK 5218 7.96 6.58 10482.94 ND ND 3.02 ND ND OK 5219 10.13 24.91 10486.47 ND ND ND 13.38 27.13 OK 5220 ND ND 10469.51 5.98 ND ND 14.68 ND OK 5221 141.35 ND 10625.48 ND 7.64 ND 24.73 ND OK 5268 33.46 ND 10584.92 ND ND 12.16 17.03 ND AVERAGE= 36.09 22.40 10486.65 8.85 7.64 8.50 23.91 11.66 STD DEV 33.36 14.66 68.29 4.41 5.30 15.62 8.11 RUSSIAN R RR 5222 ND ND 10500.94 24.20 ND ND ND ND RR 5223 115.45 ND 10634.43 ND 74.35 ND ND ND RR 5224 66.61 ND 10530.03 ND ND ND ND 20.88 RR 5225 ND ND 10459.50 ND ND 27.58 ND ND RR 5227 ND 2.00 16.80 6.00 ND ND ND 3.60 RR 5228 0.82 18.68 10484.85 23.61 2.49 ND 1.15 4.60 RR 5229 0.08 ND 10467.18 ND ND ND 5.65 ND RR 5230 ND ND 10507.02 19.89 ND ND 27.25 ND RR 5231 91.72 10.70 10574.70 ND ND ND ND ND D-5 Site MSB dieldrin mi rex Total Pesticide 8 18 28 52 44 RR 5232 5.33 4.61 10484.48 ND ND 15.37 26.56 ND RR 5233 ND ND 10469.05 ND 5.57 ND 18.78 ND RR 5234 ND 23.17 10503.74 ND 3.42 ND 19.66 ND RR 5236 76.00 ND 10558.60 ND ND ND 10.89 ND RR 5244 5.09 7.64 10512.21 ND ND ND ND ND AVERAGE= 45.14 18.23 9764.54 35.32 21.46 21.47 15.71 23.94 STD DEV 47.37 8.25 2806.00 8.72 30.60 7.17 15.88 18.89 SANTA CRUZ 5276 ND ND 10569.80 4.27 ND ND ND 5.29 SC 5311 311.30 ND 10960.07 ND ND ND ND 13.24 SC 5316 104.87 19.22 10788.51 ND ND ND ND ND SC 5318 20.15 7.54 10666.38 ND ND 9.14 ND ND AVERAGE= 145.44 13.38 10746.19 4.27 ND 9.14 ND 9.27 STD DEV 149.75 8.25 168.34 ND ND 5.62 SAN PABLO i SP 5155 20.01 ND 10346.39 ND ND ND 11.90 ND SP 5156 34.04 1.71 10404.06 ND ND ND 26.73 9.03 SP 5157 24.05 2.45 10375.67 ND 2.72 ND 20.06 ND SP 5158 19.38 ND 10363.15 ND ND ND 13.47 ND SP 5159 8.42 7.52 10350.61 ND ND ND ND 3.31 SP 5160 27.79 ND 10394.99 ND ND ND 10.57 ND SP 5161 28.79 ND 10372.03 ND 6.99 ND ND ND SP 5163 19.62 ND 10363.90 ND ND ND 9.49 ND SP 5164 21.69 ND 10395.68 ND ND ND ND ND SP 5165 55.93 ND 10507.80 ND ND ND 30.70 ND SP 5182 103.35 7.72 10518.25 ND 5.01 ND 44.58 ND SP 5185 42.54 ND 10417.50 ND ND 28.73 ND 21.25 SP 5191 18.48 ND 10433.43 ND 16.94 ND 29.84 ND SP 5195 7.97 ND 10418.99 4.04 ND ND 27.34 6.45 AVERAGE= 30.86 4.85 10404.46 4.04 7.91 28.73 22.47 10.01 STD DEV 24.39 3.21 53.00 6.26 11.36 7.85 VALLEJO VJ 5151 17.77 3.36 10364.37 ND ND 4.42 33.38 7.36 VJ 5152 26.13 ND 10393.67 4.43 5.11 4.21 36.36 8.13 VJ 5153 13.95 5.43 10357.81 ND 6.80 ND 6.49 ND VJ 5154 22.48 ND 10356.22 ND ND 36.66 28.49 ND VJ 5198 18.37 5.80 10445.93 2.08 2.04 ND 28.59 6.02 VJ 5200 28.49 ND 10480.01 ND 6.37 ND 45.30 7.56 VJ 5201 2.22 8.51 10416.50 ND ND ND ND ND VJ 5202 1.03 ND 10425.36 ND ND ND ND 33.15 VJ 5203 26.80 ND 10462.05 ND ND ND 32.65 ND VJ 5204 6.96 ND 10445.83 ND ND ND ND 1.30 VJ 5205 13.80 ND 10487.93 ND ND ND 49.90 ND VJ 5207 11.73 ND 10444.23 ND ND ND ND ND VJ 5208 8.84 ND 10443.30 ND ND 11.94 22.52 ND VJ 5209 15.16 ND 10474.53 ND 2.16 ND 37.77 1.30 AVERAGE= 15.27 5.78 10428.41 3.26 4.50 14.31 32.15 9.26 STD DEV 8.74 2.12 44.89 1.66 2.27 15.33 12.09 10.92 D-6 Site MSB 66 101 opDDD/77 118 105 153 138 126 187 BERKELEY BK 5120 ND 8.57 15.75 11.75 5.08 31.39 34.65 ND 11.54 BK 5126 ND 14.92 26.72 21.15 5.26 43.56 42.71 ND 16.47 BK 5127 0.21 22.37 21.39 41.67 14.18 71.25 76.02 ND 17.82 BK 5130 ND 26.35 32.06 40.30 18.71 97.90 92.24 ND 40.63 BK 5133 11.76 87.44 150.16 192.45 34.47 356.07 331.61 ND 136.69 BK 5135 2.69 36.07 23.89 54.39 8.80 115.27 105.55 ND 53.71 BK 5136 10.22 77.04 60.58 132.92 21.79 246.48 209.09 ND 118.06 BK 5137 ND 18.46 7.76 26.38 7.72 60.68 63.21 ND 32.00 BK 5139 39.22 35.84 27.39 85.22 16.36 121.95 119.05 ND 54.53 BK 5140 0.80 24.74 18.40 51.66 9.15 77.61 73.06 ND 32.29 BK 5142 52.19 65.17 66.45 124.32 24.15 235.03 227.59 ND 143.09 BK 5146 ND 15.49 16.84 22.69 11.70 64.95 57.52 ND 17.95 BK 5149 ND 26.95 25.24 50.22 18.69 87.32 99.16 ND 37.91 BK 5150 57.72 46.48 41.85 111.78 20.95 142.54 127.00 ND 62.40 BK 5253 5.19 56.55 17.13 83.89 14.92 80.47 46.70 ND 35.51 BK 5255 ND ND 20.02 ND 9.64 46.00 23.48 ND 31.83 BK 5263 8.18 34.09 28.69 57.32 11.89 93.12 76.51 ND 33.85 BK 5319 ND 34.93 ND 64.92 11.57 101.99 101.45 ND 60.94 AVERAGE= 18.82 37.15 35.31 69.00 14.72 115.20 105.92 ND 52.07 STD DEV 22.10 22.51 33.35 47.97 7.49 83.71 78.08 ND 40.13 OAKLAND OK 5166 ND 70.10 50.87 104.42 39.05 195.73 163.34 ND 77.69 OK 5167 ND 87.78 50.87 176.53 27.61 224.22 222.08 ND 81.89 OK 5168 ND 57.97 45.54 179.13 24.97 291.52 243.38 ND 155.54 OK 5169 ND 43.91 36.86 39.88 34.26 47.30 94.54 ND 19.85 OK 5171 5.27 ■ 49.58 39.36 99.67 19.37 146.71 132.73 1.80 64.78 OK 5172 ND 17.52 27.13 24.02 43.08 ND ND ND 52.18 OK 5176 2.03 6.57 7.09 11.37 1.66 19.96 16.96 ND 16.42 OK 5213 ND 79.19 30.53 ND 46.60 320.73 269.50 ND ND OK 5215 ND 12.90 26.38 22.30 7.06 55.61 59.03 ND 28.18 OK 5216 ND 28.18 19.80 71.16 22.40 141.58 135.72 ND 50.42 OK 5217 1.30 15.35 ND 59.64 6.45 147.16 112.30 ND 10.18 OK 5218 0.36 9.94 32.78 31.44 8.69 67.28 60.20 ND 39.12 OK 5219 ND 12.56 13.54 35.33 8.60 50.40 68.60 ND 27.73 OK 5220 3.70 15.70 33.03 ND 22.42 36.83 33.28 ND 11.48 OK 5221 20.21 63.00 ND 70.67 8.76 67.80 107.46 ND 67.40 OK 5268 ND 42.45 34.05 66.11 11.99 95.83 79.39 ND 53.96 AVERAGE= 5.48 38.29 31.99 70.83 20.81 127.24 119.90 1.80 50.45 STD DEV 7.43 27.07 12.85 53.25 14.20 94.39 76.00 37.47 RUSSIAN R RR 5222 1.32 10.34 108.00 5.61 6.46 13.46 6.42 ND 6.70 RR 5223 ND ND 11.79 16.62 32.74 16.61 34.89 ND 23.38 RR 5224 ND ND ND 14.76 22.83 19.17 18.67 ND 13.06 RR 5225 ND ND 5.80 8.60 ND 11.14 ND ND 19.33 RR 5227 0.40 0.80 ND 27.60 ND 27.60 17.60 ND 5.60 RR 5228 ND 9.47 4.48 4.53 4.02 8.57 14.46 ND ND RR 5229 ND 6.48 58.84 2.15 2.89 4.62 2.81 ND 10.97 RR 5230 ND 19.19 25.34 20.34 13.44 38.34 12.64 14.26 20.92 RR 5231 ND 5.51 8.10 14.95 3.57 27.85 23.34 ND 12.36 D-7 Site MSB 66 101 opDDD/77 118 105 153 138 126 187 5232 ND ND 18.78 ND 6.99 11.56 4.95 ND 7.25 5233 ND 9.45 62.05 22.26 9.98 23.44 13.19 ND 174.61 5234 ND 12.84 8.83 13.05 3.27 13.08 7.72 ND 4.21 RR RR 5236 ND ND ND 5244 0.36 18.66 12.12 6.96 118.11 27.49 9.70 ND 3.11 22.59 7.79 65.04 52.34 ND 60.94 AVERAGE= 10.20 19.32 33.42 20.18 19.34 44.28 32.41 14.26 32.67 STD DEV 32.66 29.23 33.02 28.86 39.06 36.97 34.96 61.75 SANTA CRUZ 5276 0.22 13.02 19.64 17.24 2.70 19.20 18.13 ND 9.00 SC 5311 ND 14.34 10.51 16.48 75.70 24.92 15.90 ND 8.52 SC 5316 ND 17.45 47.43 13.94 3.71 10.10 8.11 ND 12.16 SC 5318 ND 3.53 ND 3.40 17.09 2.91 3.85 ND ND AVERAGE= 0.22 12.09 25.86 12.77 24.80 14.28 11.50 ND 9.89 STD DEV 6.00 19.23 6.40 34.56 9.73 6.67 ND 1.98 SAN PABLO SP 5155 13.46 10.09 11.35 13.59 5.98 29.38 2.67 ND 12.81 SP 5156 11.11 17.65 25.19 48.71 12.18 41.73 ND ND 13.80 SP 5157 15.82 15.78 16.55 35.45 8.92 44.49 53.77 ND 15.67 SP 5158 ND 14.00 14.92 26.58 6.91 40.00 37.74 ND 14.77 SP 5159 ND 8.70 8.05 1.99 3.93 9.45 ND ND 20.26 SP 5160 ND 18.78 17.52 2.63 11.10 18.59 23.84 ND 10.17 SP 5161 ND 10.38 14.80 ND 21.88 31.59 17.49 ND 7.72 SP 5163 ND 12.90 20.04 8.90 10.97 23.12 ND ND 13.60 SP 5164 2.40 ND 13.07 1.45 10.29 15.99 28.10 ND 7.91 SP 5165 ND 25.53 33.79 57.07 15.94 52.94 58.31 ND 18.35 SP 5182 ND 5.96 ND 20.65 41.02 31.00 31.21 ND 21.59 SP 5185 ND 15.42 1.24 8.95 ND 9.73 24.64 ND 12.03 SP 5191 ND 17.76 16.41 30.13 13.24 22.61 41.41 ND 13.49 SP 5195 ND 13.19 10.91 15.51 0.95 40.53 23.46 ND 17.38 AVERAGE= 10.70 14.32 15.68 20.89 12.56 29.37 31.15 ND 14.25 STD DEV 5.85 5.08 7.95 17.91 10.07 13.43 16.00 ND 4.18 VALLEJO VJ 5151 ND 13.63 ND ND 11.32 27.45 33.07 ND 10.78 VJ 5152 ND 31.51 34.00 48.38 11.51 84.72 75.08 ND 29.37 VJ 5153 ND 9.90 15.13 10.77 2.07 18.60 19.91 ND 3.48 VJ 5154 ND 17.12 27.38 7.77 17.76 23.64 42.10 ND 7.68 VJ 5198 ND 16.20 20.58 22.26 6.56 32.80 31.11 ND 14.42 VJ 5200 ND 24.84 32.10 30.58 3.35 28.13 15.72 ND 8.46 VJ 5201 4.07 4.70 8.88 9.76 6.48 10.47 ND 5.11 29.94 VJ 5202 16.09 11.47 11.50 20.44 4.36 20.86 27.54 ND 17.29 VJ 5203 4.00 17.76 48.65 24.20 2.97 22.04 23.56 ND ND VJ 5204 0.52 13.00 35.50 16.08 1.78 18.14 15.15 ND 5.73 VJ 5205 ND 13.67 21.47 10.99 1.25 13.56 15.35 ND 4.85 VJ 5207 ND ND 20.17 13.75 4.35 17.56 6.49 ND 4.76 VJ 5208 ND 10.98 15.12 9.15 10.69 23.55 19.23 ND 5.55 VJ 5209 ND 14.77 ND 15.17 2.44 14.37 19.52 ND 3.99 AVERAGE= 6.17 15.35 24.21 18.41 6.21 25.42 26.45 5.11 11.25 STD DEV 6.82 6.77 11.64 11.27 4.88 18.12 17.30 9.15 D-8 Site MSB 128 180 170 195 206 209 tPCB g lipid/ g.liver BERKELEY BK 5120 2.93 20.11 ND ND 5.98 0.84 10403.66 0.08 BK 5126 6.27 40.31 ND 1.74 7.23 4.65 10495.77 0.17 BK 5127 8.12 49.50 ND 2.82 11.14 0.24 10610.34 0.11 BK 5130 7.63 47.76 ND 2.98 10.42 2.71 10720.77 0.13 BK 5133 44.21 236.82 60.30 ND 30.02 18.68 12022.72 0.16 BK 5135 ND 73.70 ND ND 8.48 ND 10773.35 0.25 BK 5136 ND 152.88 ND ND 2.18 ND 11363.40 0.34 BK 5137 6.85 41.27 ND ND 6.70 ND 10563.35 0.18 BK 5139 14.37 84.07 6.11 ND 4.80 ND 10964.46 0.26 BK 5140 11.44 52.06 ND ND ND ND 10649.37 0.29 BK 5142 ND 205.27 ND ND 59.55 ND 11520.07 0.23 BK 5146 1.61 26.14 ND ND ND ND 10559.32 0.13 BK 5149 8.90 52.00 ND 3.60 17.97 10.73 10797.39 0.14 BK 5150 11.14 88.73 22.79 8.19 18.89 19.61 11149.41 0.28 BK 5253 6.75 51.18 ND 2.06 ND 0.04 10972.01 0.10 BK 5255 ND 19.67 ND 0.83 4.05 ND 10688.23 0.14 BK 5263 5.36 38.84 ND 1.28 2.14 ND 10968.24 0.06 BK 5319 ND 99.57 ND 2.57 12.06 11.35 11142.69 0.06 AVERAGE= 10.43 76.66 29.74 2.90 13.44 7.65 10909.14 0.17 STD DEV 10.71 61.92 27.75 2.17 14.76 7.75 411.79 0.08 OAKLAND OK 5166 15.00 139.98 52.54 ND ND ND 11240.70 0.22 OK 5167 22.76 96.56 7.75 5.15 9.66 1.82 11403.40 0.16 OK 5168 9.82 234.56 ND ND ND 42.71 11660.11 0.18 OK 5169 17.59 27.21 ND ND ND ND 10765.09 0.09 OK 5171 13.59 113.63 ND ND ND ND 11085.76 0.31 OK 5172 29.73 ND ND ND ND ND 10549.93 0.14 OK 5176 3.35 10.87 ND ND 1.84 0.90 10460.67 0.05 OK 5213 ND 322.18 ND ND ND ND 21996.77 0.17 OK 5215 5.68 43.19 ND 3.45 ND 16.02 10726.62 0.09 OK 5216 16.77 106.56 ND ND ND ND 11061.24 0.18 OK 5217 0.49 55.27 ND 2.81 12.46 ND 10881.52 0.07 OK 5218 11.28 45.74 ND ND 1.76 19.55 10767.16 0.05 OK 5219 6.44 25.07 ND ND 5.81 11.80 10744.39 0.13 OK 5220 2.55 16.98 ND ND 6.86 ND 10643.51 0.12 OK 5221 11.43 122.16 11.26 6.69 5.79 13.24 11050.25 0.23 OK 5268 10.61 39.65 ND ND 5.90 3.87 11008.99 0.11 AVERAGE= 11.81 93.31 23.85 4.52 6.26 13.74 11627.88 0.14 STD DEV 7.88 87.30 24.91 1.75 3.60 13.56 2782.99 0.07 RUSSIAN R RR 5222 2.02 4.13 ND ND 6.34 ND 10639.01 0.14 RR 5223 ND 32.58 ND ND 0.60 ND 10689.58 0.23 RR 5224 8.77 2.76 ND ND 0.22 ND 10569.12 0.13 RR 5225 8.85 28.73 ND ND 16.37 4.17 10580.57 0.07 RR 5227 2.00 11.60 ND ND 3.20 ND 79.60 0.04 RR 5228 ND ND ND ND 1.19 ND 10534.56 0.11 RR 5229 2.97 ND ND ND 3.44 ND 10558.83 0.13 RR 5230 ND 16.92 ND 0.96 12.78 ND 10702.26 0.06 RR 5231 9.33 8.91 ND ND 1.87 0.98 10578.76 0.06 D-9 Silc MSB 128 180 170 195 206 209 tPCB g lipid/ g.liver RR 5232 3.80 0.64 4.23 ND 18.83 ND 10582.95 0.19 RR 5233 7.45 28.53 ND ND 1.66 ND 10842.97 0.11 RR 5234 2.22 1.56 0.98 ND 12.19 ND 10571.03 0.21 RR 5236 20.27 62.57 ND ND ND 6.32 10737.40 0.20 RR 5244 ND 15.77 ND ND 6.02 ND 10749.62 0.18 AVERAGE= 9.83 29.05 2.60 0.96 9.69 3.82 9886.88 0.13 STD DEV 36.94 48.14 96.66 53.67 102.61 2824.19 0.06 SANT^ L. CRUZ 5276 1.85 16.29 ND ND 1.36 ND 10680.23 0.08 SC 5311 34.11 57.05 ND ND 0.45 2.23 10895.45 0.11 SC 5316 ND ND ND ND ND ND 10744.89 0.05 SC 5318 ND 22.97 ND ND ND ND 10698.89 0.05 AVERAGE= 17.98 32.10 ND ND 0.91 2.23 10754.86 0.07 STD DEV 22.81 21.86 ND ND 0.64 97.58 0.03 SAN PABLO SP 5155 3.34 18.00 ND ND 4.79 8.77 10456.13 0.17 SP 5156 5.25 26.62 ND ND 7.97 ND 10557.98 0.17 SP 5157 4.48 16.07 ND 1.23 5.71 ND 10570.72 0.17 SP 5158 5.61 5.80 ND ND ND ND 10495.80 0.19 SP 5159 66.45 1.83 ND ND 7.09 ND 10449.06 0.09 SP 5160 6.71 ND ND ND ND ND 10439.91 0.15 SP 5161 ND ND ND ND ND ND 10432.86 0.16 SP 5163 10.71 ND ND ND ND ND 109.73 0.12 SP 5164 4.06 ND ND ND ND ND 21076.46 0.16 SP 5165 4.86 26.38 ND ND 11.31 ND 10665.19 0.23 SP 5182 ND 7.30 ND ND ND 3.51 10575.82 0.22 SP 5185 ND ND ND 2.25 ND ND 10494.25 0.23 SP 5191 ND 4.80 69.87 ND 5.65 ND 10664.14 0.22 SP 5195 4.60 13.57 1.09 ND 7.91 ND 10576.92 0.19 AVERAGE= 11.61 13.37 35.48 1.74 7.20 6.14 204.21 0.18 STD DEV 19.38 9.18 48.64 0.72 2.18 3.72 93.83 0.04 VALLEJO VJ 5151 5.18 6.24 ND ND ND 0.38 10455.19 0.13 V] 5152 15.32 72.73 ND 2.08 3.73 ND 10770.67 0.16 VJ 5153 1.48 6.90 ND ND 7.57 ND 10415.11 0.20 VJ 5154 4.33 ND ND ND 1.09 6.91 10528.93 0.20 VJ 5198 2.74 9.77 ND ND 1.74 ND 10592.89 0.15 VJ 5200 ND 14.59 ND 0.67 6.22 ND 10623.90 0.11 VJ 5201 3.84 ND ND ND ND ND 10485.25 0.11 VJ 5202 10.52 14.93 ND ND ND ND 10592.16 0.05 VJ 5203 8.12 ND ND ND 7.15 ND 10597.10 0.17 VJ 5204 ND ND ND ND 0.68 ND 10515.90 0.18 VJ 5205 ND 10.41 ND ND 0.79 ND 10552.23 0.15 VJ 5207 19.20 12.72 ND ND 11.52 1.31 10525.83 0.10 VJ 5208 12.36 44.11 0.83 ND 5.63 ND 10607.65 0.07 VJ 5209 ND 10.38 ND ND 2.59 ND 10542.47 0.18 AVERAGE= 8.31 20.28 0.83 1.38 4.43 2.86 10557.52 0.14 STD DEV 5.89 21.39 1.00 3.49 3.53 86.00 0.05 D-10 APPENDIX E CHEMICAL DATA (ug/kg lipid weight) FOR P. STELLATUS Individual chemical data for each P. stellatus sample collected from six sites in the San Francisco Bay area (ug/kg lipid weight). Site MSB opDDE ppDDE opDDD ppDDD opDDT ppDDT HCB lindane BK 5120 ND 0.56 * 0.14 ND ND ND 0.06 BK 5126 0.01 0.46 * 0.18 ND ND ND 0.04 BK 5127 ND 1.07 * ND 0.10 ND ND 0.10 BK 5130 ND 1.02 * ND ND 0.03 ND ND BK 5133 ND 2.44 » 1.19 ND 0.11 ND 0.04 BK 5135 ND 0.55 * 0.14 ND ND ND 0.02 BK 5136 ND 0.97 * 0.44 ND 0.19 0.00 0.03 BK 5137 ND 0.69 * 0.32 ND 0.04 ND 0.12 BK 5139 ND 0.59 * 0.42 ND 0.23 ND ND BK 5140 ND 0.47 * ND ND 0.01 ND ND BK 5142 0.01 0.70 * 0.54 ND ND ND 0.07 BK 5146 ND 0.88 * 0.33 ND ND ND ND BK 5149 ND 1.32 * 0.54 ND 0.07 ND ND BK 5150 ND 0.71 * 0.51 ND ND ND 0.03 BK 5253 ND 1.20 * 0.22 ND ND ND ND BK 5255 ND 0.31 * 0.08 ND ND ND ND BK 5263 ND 1.64 * 0.46 ND ND ND ND BK 5319 ND 0.08 * 0.70 ND 0.45 ND ND AVERAGE 0.01 0.83 If 0.41 0.07 0.14 0.00 0.06 OK 5166 ND 0.80 * 0.51 0.18 ND ND ND OK 5167 ND 0.85 * 0.44 ND 0.03 ND 0.07 OK 5168 ND 0.75 * 0.85 ND 0.12 ND 0.11 OK 5169 0.09 1.40 * 1.49 1.17 ND ND ND OK 5171 0.00 0.54 * 0.35 ND 0.19 ND ND OK 5172 ND 0.72 * 0.50 ND ND ND ND OK 5176 0.02 0.38 * 0.13 ND ND ND ND OK 5213 ND 0.67 * 0.57 0.02 0.09 ND 0.03 OK 5215 ND 0.28 * 0.21 ND ND ND ND OK 5216 ND 1.36 * 0.60 ND ND ND 0.02 OK 5217 ND 5.46 * 0.73 0.75 0.14 ND ND OK 5218 ND 0.81 * 0.30 ND ND ND ND OK 5219 ND 0.53 * 0.20 ND ND ND ND OK 5220 0.01 0.37 * 0.33 ND ND ND 0.05 OK 5221 0.01 0.06 * 0.42 ND 0.08 0.00 ND OK 5268 ND 0.74 * 0.36 ND ND ND ND AVERAGE 0.02 0.82 * 0.50 0.35 0.15 0.01 0.06 RR 5222 0.29 0.59 • ND ND ND ND ND RR 5223 ND ND * 0.15 ND 0.04 ND ND RR 5224 ND 0.08 * 0.03 ND 0.02 ND 0.05 RR 5225 ND 1.90 * 0.11 ND ND ND ND RR 5227 ND 1.80 * 0.09 ND ND ND ND RR 5228 ND 0.33 * ND ND ND ND ND RR 5229 ND 0.45 * 0.08 ND ND ND ND RR 5230 0.03 2.87 * 0.30 ND ND ND ND RR 5231 ND ND * 0.13 ND 0.18 ND ND RR 5232 ND 0.86 * 0.02 ND ND ND ND RR 5233 ND 0.33 * 0.02 ND ND ND ND E-l Site MSB opDDE ppDDE opDDD ppDDD opDDT ppDDT HCB lindane RR 5234 ND 0.75 * 0.00 ND ND ND ND RR 5236 ND ND * ND ND 0.20 ND ND RR 5244 0.01 1.09 * 0.18 ND 0.04 ND ND AVERAGE 0.11 1.35 + 0.11 ND 0.11 ND 0.05 SC 5276 ND 1.85 * 0.35 0.10 0.04 ND ND sc 5311 0.16 0.11 * 0.43 0.13 0.34 ND ND SC 5316 0.51 0.52 * 0.46 ND 0.92 ND ND sc 5318 ND 0.04 * 0.08 0.07 0.40 ND ND AVERAGE 0.30 0.65 * 0.35 0.12 0.37 ND ND SP 5155 0.01 0.44 * 0.27 ND 0.01 ND 0.00 SP 5156 0.02 0.66 * 0.49 0.05 0.04 ND 0.04 SP 5157 0.01 0.69 * 0.33 ND 0.03 ND 0.04 SP 5158 0.01 0.40 * 0.29 ND ND ND 0.04 SP 5159 0.03 0.44 » 0.09 ND ND ND 0.06 SP 5160 0.03 0.56 * 0.57 ND ND ND 0.04 SP 5161 0.01 0.24 * 0.21 ND ND ND 0.01 SP 5163 ND 0.71 * 0.39 ND ND ND ND SP 5164 ND 0.35 * ND ND 0.08 ND ND SP 5165 0.02 1.08 * 0.72 ND 0.02 ND 0.08 SP 5182 0.01 0.10 * 0.56 ND 0.09 ND 0.04 SP 5185 ND 0.52 * 0.47 ND 0.04 ND ND SP 5191 0.01 0.51 • 0.31 ND ND ND ND SP 5195 ND 0.90 * 0.10 ND ND ND 0.01 AVERAGE 0.02 0.55 • 0.39 0.05 0.05 ND 0.03 VJ 5151 ND 0.82 * 0.37 ND ND ND ND VJ 5152 0.03 2.62 * 0.59 ND 0.04 ND ND VJ 5153 ND 0.31 * 0.22 0.00 0.01 ND 0.01 VJ 5154 ND 0.46 * 0.18 ND 0.01 ND ND VJ 5198 ND 0.68 * 0.29 ND ND ND ND VJ 5200 0.06 1.02 * ND ND ND ND 0.12 VJ 5201 ND 0.36 * 0.08 0.01 ND ND ND VJ 5202 ND 4.62 * 0.09 ND ND ND 0.03 VJ 5203 0.01 0.68 * 0.41 0.04 0.04 ND ND VJ 5204 ND 0.24 * 0.20 ND 0.04 ND 0.08 VJ 5205 0.02 0.63 * 0.39 0.01 ND ND 0.11 VJ 5207 0.04 0.73 * 0.27 ND ND ND ND VJ 5208 0.04 1.02 * 0.48 ND ND ND ND VJ 5209 0.01 0.63 * 0.34 ND 0.01 ND ND AVERAGE 0.02 0.85 * 0.31 0.02 0.03 ND 0.07 E-2 Site MSB heptachlor aldrin heptepox chlordane transnonachlor dieldrin mirex BK 5120 ND ND 0.02 ND 0.08 0.13 ND BK 5126 0.00 ND 0.01 0.02 0.08 0.09 ND BK 5127 0.02 ND ND 0.14 0.28 0.26 ND BK 5130 0.13 ND ND 0.07 0.24 0.22 0.01 BK 5133 ND 0.01 0.03 0.06 0.41 0.40 ND BK 5135 0.05 ND 0.01 0.01 0.07 0.08 ND BK 5136 0.12 ND 0.03 0.02 0.11 0.19 ND BK 5137 ND ND 0.01 0.07 0.15 0.13 0.01 BK 5139 0.01 ND 0.02 0.02 0.08 0.12 ND BK 5140 ND 0.00 0.01 0.01 0.06 0.09 ND BK 5142 0.12 0.01 0.02 0.05 0.15 0.20 ND BK 5146 0.13 ND 0.04 0.03 0.12 0.17 ND BK 5149 ND ND ND 0.07 0.19 0.29 0.02 BK 5150 0.10 ND 0.02 0.03 0.15 0.21 0.06 BK 5253 0.47 0.03 0.13 ND ND 0.09 0.19 BK 5255 0.11 0.03 0.06 ND 0.03 0.07 ND BK 5263 ND 0.08 ND 0.00 0.14 0.34 0.04 BK 5319 ND ND 0.23 0.05 0.14 1.92 ND AVERAGE 0.11 0.01 0.03 0.04 0.14 0.20 0.04 OK 5166 ND ND 0.03 0.04 0.18 0.21 ND OK 5167 ND ND 0.03 0.05 0.33 0.17 0.06 OK 5168 ND ND 0.03 0.05 0.20 0.23 ND OK 5169 ND ND 0.13 0.14 0.27 0.66 0.29 OK 5171 ND 0.00 0.02 0.02 0.08 0.13 ND OK 5172 ND ND ND 0.05 0.11 0.17 0.28 OK 5176 0.02 0.01 ND 0.01 0.05 0.06 0.03 OK 5213 ND ND 0.01 0.03 0.20 0.18 ND OK 5215 0.12 0.04 0.02 0.01 0.07 0.13 0.43 OK 5216 ND ND 0.02 0.07 0.23 0.25 ND OK 5217 ND ND ND 0.31 1.03 0.27 0.45 OK 5218 0.34 0.08 ND 0.02 0.21 0.16 0.13 OK 5219 ND ND ND 0.02 0.08 0.08 0.19 OK 5220 ND 0.04 0.01 0.03 0.11 ND ND OK 5221 ND ND 0.06 0.02 0.11 0.61 ND OK 5268 0.07 ND 0.00 0.00 0.06 0.30 ND AVERAGE 0.06 0.02 0.04 0.04 0.18 0.25 0.16 RR 5222 0.07 0.09 0.17 0.02 0.06 ND ND RR 5223 0.29 ND ND ND 0.02 0.50 ND RR 5224 ND ND ND 0.04 0.03 0.51 ND RR 5225 ND ND 0.13 0.01 ND ND ND RR 5227 ND 0.26 0.03 ND 0.08 ND 0.05 RR 5228 ND 0.03 ND ND 0.05 0.01 0.17 RR 5229 0.02 0.03 ND 0.01 0.01 0.00 ND RR 5230 ND 0.11 0.48 ND 0.19 ND ND RR 5231 ND ND ND 0.03 0.14 1.53 0.18 RR 5232 0.04 ND ND ND 0.01 0.03 0.02 RR 5233 ND ND 0.00 0.00 0.02 ND ND E-3 Site MSB hept aldrin heptepox chlordane transnon dieldrin mirex RR 5234 0.01 ND 0.01 0.01 0.03 ND 0.11 RR 5236 ND ND ND 0.01 0.04 0.38 ND RR 5244 ND ND 0.01 0.01 0.05 0.03 0.04 AVERAGE 0.14 0.23 0.09 0.01 0.07 0.34 0.14 SC 5276 0.07 0.07 0.00 0.03 0.05 ND ND sc 5311 ND ND 0.06 0.05 0.13 2.83 ND SC 5316 ND ND 0.51 0.07 0.07 2.10 0.38 sc 5318 ND ND ND ND 0.05 0.40 0.15 AVERAGE 0.08 0.08 0.15 0.05 0.08 2.01 0.18 SP 5155 ND ND 0.01 0.03 0.05 0.12 ND SP 5156 0.11 0.01 0.02 0.06 0.09 0.20 0.01 SP 5157 ND ND 0.04 0.03 0.09 0.14 0.01 SP 5158 ND ND 0.02 0.03 0.06 0.10 ND SP 5159 ND ND 0.07 0.02 0.04 0.09 0.08 SP 5160 ND ND 0.05 0.09 0.14 0.19 ND SP 5161 ND ND 0.03 0.03 0.06 0.18 ND SP 5163 ND ND ND 0.05 0.11 0.16 ND SP 5164 ND 0.01 0.02 0.13 0.13 0.14 ND SP 5165 ND ND 0.04 0.13 0.28 0.24 ND SP 5182 0.03 ND ND 0.05 0.07 0.47 0.04 SP 5185 ND ND ND 0.02 ND 0.18 ND SP 5191 0.01 0.01 0.02 0.03 0.08 0.08 ND SP 5195 0.01 0.01 0.01 0.01 0.07 0.04 ND AVERAGE 0.04 0.01 0.03 0.05 0.10 0.17 0.03 VJ 5151 0.03 ND 0.02 0.05 0.21 0.14 0.03 VJ 5152 ND 0.01 0.01 0.08 0.29 0.16 ND V] 5153 0.01 0.02 0.01 0.04 0.09 0.07 0.03 VJ 5154 ND ND ND 0.04 0.08 0.11 ND VJ 5198 ND 0.01 0.01 0.04 0.11 0.12 0.04 VJ 5200 0.06 0.03 0.01 0.10 0.16 0.26 ND VJ 5201 ND ND 0.02 0.01 ND 0.02 0.08 VJ 5202 0.27 ND ND ND 0.11 0.02 ND VJ 5203 ND ND 0.01 0.07 0.10 0.16 ND VJ 5204 0.00 ND 0.05 0.01 0.03 0.04 ND VJ 5205 ND ND 0.19 0.05 0.09 0.09 ND VJ 5207 ND ND 0.01 0.08 0.09 0.12 ND VJ 5208 ND ND 0.02 0.08 0.16 0.13 ND VJ 5209 0.01 0.01 0.03 0.08 0.10 0.08 ND AVERAGE 0.03 0.02 0.03 0.06 0.12 0.11 0.04 EA Site MSB 8 18 28 52 44 66 101 opDDD/77 118 105 BK 5120 ND ND ND 0.14 0.05 ND 0.11 0.20 0.15 0.06 BK 5126 ND ND 0.02 0.05 ND ND 0.09 0.16 0.12 0.03 BK 5127 ND ND ND 0.18 ND 0.00 0.20 0.19 0.38 0.13 BK 5130 ND ND ND 0.26 0.06 ND 0.20 0.25 0.31 0.14 BK 5133 ND ND 0.10 0.30 0.02 0.07 0.55 0.94 1.20 0.22 BK 5135 ND ND ND 0.08 ND 0.01 0.14 0.10 0.22 0.04 BK 5136 ND ND 0.04 0.13 0.01 0.03 0.23 0.18 0.39 0.06 BK 5137 ND ND ND 0.10 ND ND 0.10 0.04 0.15 0.04 BK 5139 ND ND 0.05 0.09 0.16 0.15 0.14 0.11 0.33 0.06 BK 5140 ND ND ■ 0.01 0.05 ND 0.00 0.09 0.06 0.18 0.03 BK 5142 ND ND ND 0.14 ND 0.23 0.28 0.29 0.54 0.11 BK 5146 ND ND 0.06 0.12 0.07 ND 0.12 0.13 0.17 0.09 BK 5149 ND ND 0.05 0.24 0.15 ND 0.19 0.18 0.36 0.13 BK 5150 ND ND 0.07 0.17 0.01 0.21 0.17 0.15 0.40 0.07 BK 5253 ND ND 0.15 0.49 0.02 0.05 0.57 0.17 0.84 0.15 BK 5255 ND 0.16 ND ND ND ND ND 0.14 ND 0.07 BK 5263 0.12 0.06 0.22 0.31 0.14 0.14 0.57 0.48 0.96 0.20 BK 5319 ND ND 0.06 ND ND ND 0.58 ND 1.08 0.19 AVERAGE 0.04 0.08 0.06 0.16 0.06 0.11 0.21 0.20 0.40 0.09 OK 5166 ND ND ND ND ND ND 0.32 0.23 0.47 0.18 OK 5167 ND ND 0.04 0.24 0.06 ND 0.55 0.32 1.10 0.17 OK 5168 ND ND ND 0.16 0.06 ND 0.32 0.25 1.00 0.14 OK 5169 ND ND ND 0.73 ND ND 0.49 0.41 0.44 0.38 OK 5171 ND ND 0.04 0.11 0.03 0.02 0.16 0.13 0.32 0.06 OK 5172 0.09 ND ND ND ND ND 0.13 0.19 0.17 0.31 OK 5176 0.08 ND ND 0.11 ND 0.04 0.13 0.14 0.23 0.03 OK 5213 0.08 ND 0.04 0.13 ND ND 0.47 0.18 ND 0.27 OK 5215 ND ND 0.03 0.13 0.03 ND 0.14 0.29 0.25 0.08 OK 5216 ND ND 0.09 0.11 ND ND 0.16 0.11 0.40 0.12 OK 5217 ND ND ND 0.21 0.14 0.02 0.22 ND 0.85 0.09 OK 5218 ND ND 0.06 ND ND 0.01 0.20 0.66 0.63 0.17 OK 5219 ND ND ND 0.10 0.21 ND 0.10 0.10 0.27 0.07 OK 5220 0.05 ND ND 0.12 ND 0.03 0.13 0.28 ND 0.19 OK 5221 ND 0.03 ND 0.11 ND 0.09 0.27 ND 0.31 0.04 OK 5268 ND ND 0.11 0.15 ND ND 0.39 0.31 0.60 0.11 AVERAGE 0.06 0.05 0.06 0.17 0.08 0.04 0.27 0.22 0.49 0.14 RR 5222 0.17 ND ND ND ND 0.01 0.07 0.77 0.04 0.05 RR 5223 ND 0.32 ND ND ND ND ND 0.05 0.07 0.14 RR 5224 ND ND ND ND 0.16 ND ND ND 0.11 0.18 RR 5225 ND ND 0.39 ND ND ND ND 0.08 0.12 ND RR 5227 0.45 ND ND ND 0.09 0.01 0.02 ND 0.18 ND RR 5228 0.21 0.02 ND 0.01 0.04 ND 0.09 0.04 0.04 0.04 RR 5229 ND ND ND 0.04 ND ND 0.05 0.45 0.02 0.02 RR 5230 0.33 ND ND 0.45 ND ND 0.32 0.42 0.34 0.22 RR 5231 ND ND ND ND ND ND 0.09 0.13 0.25 0.06 RR 5232 ND ND 0.08 0.14 ND ND ND 0.10 ND 0.04 RR 5233 ND 0.05 ND 0.17 ND ND 0.09 0.56 0.20 0.09 E-5 Site MSB 8 18 28 52 44 66 101 opDDD/77 118 105 RR 5234 ND 0.02 ND 0.09 ND ND 0.06 0.04 0.06 0.02 RR 5236 ND ND ND 0.05 ND ND ND ND 0.03 0.59 RR 5244 ND ND ND ND ND 0.00 0.10 0.07 0.13 0.04 AVERAGE 0.27 0.16 0.16 0.12 0.18 0.08 0.15 0.25 0.15 0.15 sc 5276 0.05 ND ND ND 0.07 0.00 0.16 0.25 0.22 0.03 sc 5311 ND ND ND ND 0.12 ND 0.13 0.10 0.15 0.69 sc 5316 ND ND ND ND ND ND 0.35 0.95 0.28 0.07 sc 5318 ND ND 0.18 ND ND ND 0.07 ND 0.07 0.34 AVERAGE 0.06 ND 0.13 ND 0.13 0.00 0.17 0.36 0.18 0.34 SP 5155 ND ND ND 0.07 ND 0.08 0.06 0.07 0.08 0.04 SP 5156 ND ND ND 0.16 0.05 0.07 0.10 0.15 0.29 0.07 SP 5157 ND 0.02 ND 0.12 ND 0.09 0.09 0.10 0.21 0.05 SP 5158 ND ND ND 0.07 ND ND 0.07 0.08 0.14 0.04 SP 5159 ND ND ND ND 0.04 ND 0.10 0.09 0.02 0.04 SP 5160 ND ND ND 0.07 ND ND 0.13 0.12 0.02 0.07 SP 5161 ND 0.04 ND ND ND ND 0.06 0.09 ND 0.14 SP 5163 ND ND ND 0.08 ND ND 0.11 0.17 0.07 0.09 SP 5164 ND ND ND ND ND 0.02 ND 0.08 0.01 0.06 SP 5165 ND ND ND 0.13 ND ND 0.11 0.15 0.25 0.07 SP 5182 ND 0.02 ND 0.20 ND ND 0.03 ND 0.09 0.19 SP 5185 ND ND 0.12 ND 0.09 ND 0.07 0.01 0.04 ND SP 5191 ND 0.08 ND 0.14 ND ND 0.08 0.07 0.14 0.06 SP 5195 0.02 ND ND 0.14 0.03 ND 0.07 0.06 0.08 0.00 AVERAGE 0.02 0.04 0.16 0.13 0.06 0.06 0.08 0.09 0.12 0.07 VJ 5151 ND ND 0.03 0.26 0.06 ND 0.10 ND ND 0.09 VJ 5152 0.03 0.03 0.03 0.23 0.05 ND 0.20 0.21 0.30 0.07 VJ 5153 ND 0.03 ND 0.03 ND ND 0.05 0.08 0.05 0.01 VJ 5154 ND ND 0.18 0.14 ND ND 0.09 0.14 0.04 0.09 VJ 5198 0.01 0.01 ND 0.19 0.04 ND 0.11 0.14 0.15 0.04 VJ 5200 ND 0.06 ND 0.41 0.07 ND 0.23 0.29 0.28 0.03 VJ 5201 ND ND ND ND ND 0.04 0.04 0.08 0.09 0.06 VJ 5202 ND ND ND ND 0.66 0.32 0.23 0.23 0.41 0.09 VJ 5203 ND ND ND 0.19 ND 0.02 0.10 0.29 0.14 0.02 VJ 5204 ND ND ND ND 0.01 0.00 0.07 0.20 0.09 0.01 VJ 5205 ND ND ND 0.33 ND ND 0.09 0.14 0.07 0.01 VJ 5207 ND ND ND ND ND ND ND 0.20 0.14 0.04 VJ 5208 ND ND 0.17 0.32 ND ND 0.16 0.22 0.13 0.15 VJ 5209 ND 0.01 ND 0.21 0.01 ND 0.08 ND 0.08 0.01 AVERAGE 0.02 0.03 0.10 0.23 0.07 0.04 0.11 0.17 0.13 0.04 E-6 Site MSB 153 138 126 187 128 180 170 195 206 209 est 1242 BK 5120 0.39 0.43 ND 0.14 0.04 0.25 ND ND 0.07 0.01 ND BK 5126 0.26 0.25 ND 0.10 0.04 0.24 ND 0.01 0.04 0.03 ND BK 5127 0.65 0.69 ND 0.16 0.07 0.45 ND 0.03 0.10 0.00 ND BK 5130 0.75 0.71 ND 0.31 0.06 0.37 ND 0.02 0.08 0.02 ND BK 5133 2.23 2.07 ND 0.85 0.28 1.48 0.38 ND 0.19 0.12 ND BK 5135 0.46 0.42 ND 0.21 ND 0.29 ND ND 0.03 ND ND BK 5136 0.72 0.61 ND 0.35 ND 0.45 ND ND 0.01 ND ND BK 5137 0.34 0.35 ND 0.18 0.04 0.23 ND ND 0.04 ND ND BK 5139 0.47 0.46 ND 0.21 0.06 0.32 0.02 ND 0.02 ND ND BK 5140 0.27 0.25 ND 0.11 0.04 0.18 ND ND ND ND ND BK 5142 1.02 0.99 ND 0.62 ND 0.89 ND ND 0.26 ND ND BK 5146 0.50 0.44 ND 0.14 0.01 0.20 ND ND ND ND ND BK 5149 0.62 0.71 ND 0.27 0.06 0.37 ND 0.03 0.13 0.08 ND BK 5150 0.51 0.45 ND 0.22 0.04 0.32 0.08 0.03 0.07 0.07 ND BK 5253 0.80 0.47 ND 0.36 0.07 0.51 ND 0.02 ND 0.00 ND BK 5255 0.33 0.17 ND 0.23 ND 0.14 ND 0.01 0.03 ND 1.7295 BK 5263 1.55 1.28 ND 0.56 0.09 0.65 ND 0.02 0.04 ND .6362 BK 5319 1.70 1.69 ND 1.02 ND 1.66 ND 0.04 0.20 0.19 ND AVERAGE 0.67 0.61 ND 0.30 0.06 0.44 0.17 0.02 0.08 0.04 .8112 OK 5166 0.89 0.74 ND 0.35 0.07 0.64 0.24 ND ND ND ND OK 5167 1.40 1.39 ND 0.51 0.14 0.60 0.05 0.03 0.06 0.01 ND OK 5168 1.62 1.35 ND 0.86 0.05 1.30 ND ND ND 0.24 ND OK 5169 0.53 1.05 ND 0.22 0.20 0.30 ND ND ND ND ND OK 5171 0.47 0.43 0.01 0.21 0.04 0.37 ND ND ND ND ND OK 5172 ND ND ND 0.37 0.21 ND ND ND ND ND ND OK 5176 0.40 0.34 ND 0.33 0.07 0.22 ND ND 0.04 0.02 ND OK 5213 1.89 1.59 ND ND ND 1.90 ND ND ND ND ND OK 5215 0.62 0.66 ND 0.31 0.06 0.48 ND 0.04 ND 0.18 ND OK 5216 0.79 0.75 ND 0.28 0.09 0.59 ND ND ND ND ND OK 5217 2.10 1.60 ND 0.15 0.01 0.79 ND 0.04 0.18 ND ND OK 5218 1.35 1.20 ND 0.78 0.23 0.91 ND ND 0.04 0.39 ND OK 5219 0.39 0.53 ND 0.21 0.05 0.19 ND ND 0.04 0.09 ND OK 5220 0.31 0.28 ND 0.10 0.02 0.14 ND ND 0.06 ND ND OK 5221 0.29 0.47 ND 0.29 0.05 0.53 0.05 0.03 0.03 0.06 .3541 OK 5268 0.87 0.72 ND 0.49 0.10 0.36 ND ND 0.05 0.04 ND AVERAGE 0.89 0.83 0.01 0.35 0.08 0.65 0.17 0.03 0.04 0.10 .5666 RR 5222 0.10 0.05 ND 0.05 0.01 0.03 ND ND 0.05 ND ND RR 5223 0.07 0.15 ND 0.10 ND 0.14 ND ND 0.00 ND 3.4461 RR 5224 0.15 0.14 ND 0.10 0.07 0.02 ND ND 0.00 ND ND RR 5225 0.16 ND ND 0.28 0.13 0.41 ND ND 0.23 0.06 ND RR 5227 0.69 0.44 ND 0.14 0.05 0.29 ND ND 0.08 ND ND RR 5228 0.08 0.13 ND ND ND ND ND ND 0.01 ND .2408 RR 5229 0.04 0.02 ND 0.08 0.02 ND ND ND 0.03 ND ND RR 5230 0.64 0.21 0.24 0.35 ND 0.28 ND 0.02 0.21 ND ND RR 5231 0.46 0.39 ND 0.21 0.16 0.15 ND ND 0.03 0.02 ND RR 5232 0.06 0.03 ND 0.04 0.02 0.00 0.02 ND 0.10 ND ND RR 5233 0.21 0.12 ND 1.59 0.07 0.26 ND ND 0.02 ND .5394 E-7 Site MSB 153 138 126 187 128 180 170 195 206 209 est 1242 RR 5234 0.06 0.04 ND 0.02 0.01 0.01 0.00 ND 0.06 ND .1737 RR 5236 0.14 0.05 ND 0.02 0.10 0.31 ND ND ND 0.03 ND RR 5244 0.36 0.29 ND 0.34 ND 0.09 ND ND 0.03 ND ND AVERAGE 0.33 0.24 0.11 0.25 0.07 0.22 0.02 0.01 0.07 0.03 1.7216 SC 5276 0.24 0.23 ND 0.11 0.02 0.20 ND ND 0.02 ND ND sc 5311 0.23 0.14 ND 0.08 0.31 0.52 ND ND 0.00 0.02 ND SC 5316 0.20 0.16 ND 0.24 ND ND ND ND ND ND ND sc 5318 0.06 0.08 ND ND ND 0.46 ND ND ND ND ND AVERAGE 0.20 0.16 .ND 0.14 0.25 0.44 ND ND 0.01 0.03 ND SP 5155 0.17 0.02 ND 0.08 0.02 0.11 ND ND 0.03 0.05 ND SP 5156 0.25 ND ND 0.08 0.03 0.16 ND ND 0.05 ND ND SP 5157 0.26 0.32 ND 0.09 0.03 0.09 ND 0.01 0.03 ND .1704 SP 5158 0.21 0.20 ND 0.08 0.03 0.03 ND ND ND ND ND SP 5159 0.11 ND ND 0.23 0.74 0.02 ND ND 0.08 ND ND SP 5160 0.12 0.16 ND 0.07 0.04 ND ND ND ND ND ND SP 5161 0.20 0.11 ND 0.05 ND ND ND ND ND ND .4655 SP 5163 0.19 ND ND 0.11 0.09 ND ND ND ND ND ND SP 5164 0.10 0.18 ND 0.05 0.03 ND ND ND ND ND ND SP 5165 0.23 0.25 ND 0.08 0.02 0.11 ND ND 0.05 ND ND SP 5182 0.14 0.14 ND 0.10 ND 0.03 ND ND ND 0.02 .2428 SP 5185 0.04 0.11 ND 0.05 ND ND ND 0.01 ND ND ND SP 5191 0.10 0.19 ND 0.06 ND 0.02 0.32 ND 0.03 ND .8206 SP 5195 0.21 0.12 ND 0.09 0.02 0.07 0.01 ND 0.04 ND ND AVERAGE 0.17 0.18 ND 0.08 0.07 0.08 0.20 0.01 0.04 0.03 .4781 VJ 5151 0.21 0.25 ND 0.08 0.04 0.05 ND ND ND 0.00 ND VJ 5152 0.53 0.47 ND 0.18 0.10 0.45 ND 0.01 0.02 ND .3403 VJ 5153 0.09 0.10 ND 0.02 0.01 0.03 ND ND 0.04 ND .3625 VJ 5154 0.12 0.21 ND 0.04 0.02 ND ND ND 0.01 0.03 ND VJ 5198 0.22 0.21 ND 0.10 0.02 0.07 ND ND 0.01 ND .1451 VJ 5200 0.26 0.14 ND 0.08 ND 0.13 ND 0.01 0.06 ND .6173 VJ 5201 0.10 ND 0.05 0.27 0.03 ND ND ND ND ND ND VJ 5202 0.42 0.55 ND 0.35 0.21 0.30 ND ND ND ND ND VJ 5203 0.13 0.14 ND ND 0.05 ND ND ND 0.04 ND ND VJ 5204 0.10 0.08 ND 0.03 ND ND ND ND 0.00 ND ND VJ 5205 0.09 0.10 ND 0.03 ND 0.07 ND ND 0.01 ND ND VJ 5207 0.18 0.06 ND 0.05 0.19 0.13 ND ND 0.12 0.01 ND VJ 5208 0.34 0.27 ND 0.08 0.18 0.63 0.01 ND 0.08 ND ND VJ 5209 0.08 0.11 ND 0.02 ND 0.06 ND ND 0.01 ND .1281 AVERAGE 0.18 0.19 0.04 0.08 0.06 0.14 0.01 0.01 0.03 0.02 .3424 E-8 Site MSB est 1254 est 1260 tPCBs BK 5120 1.2778 3.8656 5.1434 BK 5126 1.0824 3.6473 4.7297 BK 5127 3.2956 6.9208 10.2164 BK 5130 2.697 5.6503 8.3473 BK 5133 10.4643 22.7639 33.2282 BK 5135 1.8928 4.5341 6.4269 BK 5136 3.4011 6.9155 10.3167 BK 5137 1.2751 3.5264 4.8014 BK 5139 2.8515 4.973 7.8246 BK 5140 1.5498 2.7612 4.3111 BK 5142 4.7024 13.7262 18.4286 BK 5146 1.5186 3.0921 4.6107 BK 5149 3.121 5.7123 8.8334 BK 5150 3.4731 4.874 8.3471 BK 5253 7.2985 7.8715 15.17 BK 5255 ND 2.1611 3.8906 BK 5263 8.3117 9.9557 18.9035 BK 5319 9.413 25.5243 34.9373 AVERAGE 3.978 7.6931 11.5815 OK 5166 4.1293 9.7855 13.9149 OK 5167 9.5986 9.2822 18.8808 OK 5168 8.6579 20.0422 28.7001 OK 5169 3.8553 4.6499 8.5051 OK 5171 2.7972 5.6376 8.4348 OK 5172 1.4924 ND 1.4924 OK 5176 1.9791 3.3426 5.3217 OK 5213 ND 29.1478 29.1478 OK 5215 2.1553 7.3808 9.5361 OK 5216 3.4395 9.1049 12.5444 OK 5217 7.4122 12.1435 19.5556 OK 5218 5.4704 14.0686 19.539 OK 5219 2.3644 2.9663 5.3307 OK 5220 ND 2.1767 2.1767 OK 5221 2.6731 8.1688 11.196 OK 5268 5.2283 5.5443 10.7726 AVERAGE 4.2869 9.9831 14.8366 RR 5222 .3488 .4532 .8021 RR 5223 .6289 2.1787 6.2537 RR 5224 .9877 .3264 1.3141 RR 5225 1.0695 6.3129 7.3823 RR 5227 1.6 4.5 6.1 RR 5228 .3582 ND .599 RR 5229 .144 ND .144 RR 5230 2.9493 4.3377 7.287 RR 5231 2.1675 2.2827 4.4502 RR 5232 ND .0517 .0517 RR 5233 1.7608 3.9893 6.2894 E-9 Site MSB est 1254 est 1260 total PCBs RR 5234 .5406 .1141 .8284 RR 5236 .3026 4.8113 5.1139 RR 5244 1.092 1.3472 2.4393 AVERAGE 1.3217 3.3627 6.406 SC 5276 1.8751 3.1312 5.0062 sc 5311 1.3035 7.9761 9.2797 SC 5316 2.4248 ND 2.4248 sc 5318 .5918 7.0644 7.6562 AVERAGE 1.5318 6.8096 8.3414 SP 5155 .6955 1.6288 2.3242 SP 5156 2.4929 2.4087 4.9016 SP 5157 1.8143 1.4541 3.4389 SP 5158 1.2172 .4693 1.6865 SP 5159 .1925 .3119 .5044 SP 5160 .1524 ND .1524 SP 5161 ND ND .4655 SP 5163 .6455 ND .6455 SP 5164 .0787 ND .0787 SP 5165 2.1588 1.7639 3.9227 SP 5182 .8166 .5105 1.5699 SP 5185 .3384 ND .3384 SP 5191 1.1914 .3356 2.3475 SP 5195 .7102 1.0983 1.8084 AVERAGE 1.0303 1.1659 2.6743 VJ 5151 ND .7387 .7387 VJ 5152 2.6304 6.991 9.9617 VJ 5153 .4685 .5309 1.3619 VJ 5154 .3379 ND .3379 VJ 5198 1.2909 1.0023 2.4383 VJ 5200 2.4187 2.0394 5.0753 VJ 5201 .7722 ND .7722 VJ 5202 3.5573 4.5924 8.1497 VJ 5203 1.2387 ND 1.2387 VJ 5204 .7773 ND .7773 VJ 5205 .6372 1.0673 1.7045 VJ 5207 1.1962 1.9565 3.1527 VJ 5208 1.1368 9.6916 10.8284 VJ 5209 .7333 .8866 1.7479 AVERAGE 1.1439 2.2277 3.714 E-10