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                             NOAA STATUS AND TRENDS
                                        Mussel Watch Project
                                                 Technical Report
                                                          Year VIII


                                                                                                            ..... ...... ................. ... ....


                                                    The Geochemical and
                                                    Environmental Research Group
                                                    Texas A&M Research Foundation






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                      OAA NATIONAL
                 STATUS AND TRENDS

                 Mussel Watch Project

                 Year 8 Technical Report



                 Prepared by

                 The Geochemical and Environmental Research
                 Group (GERG)
                 Texas A&M University
                 833 Graham Road
                 College Station, Texas 77845

                 Submitted to                            Property of CSC Library

                 U.S. Department of Commerce
                 National Oceanic & Atmospheric Administration
                 1305 East-West Hwy.
          38     Silver Spring, MD 209 10

                                                         U . S . DEPARTMENT OF COMMERCE NOA A
                                                         COASTAL SERVICES CENTER
                                                         2234 SOUTH HOBSON AVENUE
                 September 1994                          CHARLESTON , SC 29405-24 11'@

     X-


















                                                                  TABLE OF CONTENTS



                           Introduction         ...........................................................................................             1

                           Reprint 1: Sources of Local Variation in Polynuclear Aromatic
                                Hydrocarbon and Pesticide Body Burden in Oysters
                                LCtassostrea. virgin               from Galveston Bay, Texas                   ...............................       10

                           Reprint 2: Sediment Contaminants in Casco Bay, Maine:
                                Inventories, Sources, and Potentialfor Biological Impact                                ......................       21

                           Reprint 3: Polynuclear Aromatic Hydrocarbon Contaminants
                                in Oysters from the Gulf of Mexico (1986-1990)                           ....................................        37

                           Reprint 4: Modeling Oyster Populations I[. Adult Size and
                                Reproductive Effort            .............................................................................         46

                           Reprint 5: Correlation Between Bioassay-Derived P4501AI
                                Induction Activity and Chemical Analysis of Clam
                                (Laternula. elliptica) Extracts from McMurdo Sound,
                                Antarctica       ..........................................................................................          65








                  NOAX S NATIONAL STATUS AND TRENDS (NS&T) MUSSEL WATCH
                                      PROGRAM - GULF OF M]EXIC0


                       The purpose of the NOAA National Status and Trends (NS&T)
                 Mussel Watch Project is to determine the long-term temporal and spatial
                 trends of selected environmental contaminant concentrations in bays
                 and estuaries. The key questions in this regard are:

                       (1) What is the current condition of the nation's coastal zone?
                       (2) Are these conditions getting better or worse?

                       This report represents the Year 8 Technical Report from this multi-
                 year project. These questions have been addressed in detail as evidenced
                 by the scientific papers and reports that have resulted from the
                 Geochemical and Environmental Research Group's (GERG)
                 interpretations of the Gulf Coast data (Table 1). Publications not
                 included in GERG's previous Technical Reports are contained in this
                 technical report.

                       This report is an update on the current condition of the Gulf of
                 Mexico coastal zone, based on results from Years 1 through 8 of the
                 NOAA NS&T Mussel Watch Project. Following is a brief sampling survey
                 of these years:

                         Year 1 - 49 sites (147 stations) of the original 51 sites were
                                   successfully sampled. Sediments and oysters were
                                   analyzed at triplicate stations from all sites.
                         Year 2 -  48 sites (144 stations) of the original 51 sites were
                                   successfully sampled. Sediments and oysters were
                                   analyzed at triplicate stations from all sites.
                         Year 3 -  Twenty (20) sites were added to the original list of 51
                                   sites for a total of 71 sites. Sixty-four (64) sites (192
                                   stations) of the 71 sites were sampled (only 19 of the
                                   new sites were sampled). Oysters were analyzed at
                                   triplicate stations from all sites. Sediments were
                                   analyzed at only the new sites (three stations analyzed
                                   per site).
                         Year 4 -  Seven (7) new sites were added (only six of the new sites
                                   were successfully sampled). Sixty-seven (67) sites (201
                                   stations) of the 78 total sites were sampled. Oysters
                                   were analyzed at triplicate stations from all sites.
                                   Sediments were analyzed at only the new sites (three
                                   stations analyzed per site).
                         Year 5 -  Three (3) new sites were added to the sampling project
                                   (only two of these sites were successfully sampled;
                                   79:MBDR and 80:PBSP). Sixty-eight (68) sites (204
                                   stations) of the 80 total sites were sampled. Oysters
                                   were analyzed at triplicate stations from all sites.








                                   Sediments were analyzed at only the new sites (three
                                   stations analyzed per site).
                         Year 6 -  Two (2) new sites were added to the sampling project
                                   (81:BHKF in Bahia Honda Key, FL and 63:LPGO in
                                   Lake Pontchartrain, LA). Sixty-four (64) sites (192
                                   stations) were sampled. Oysters were analyzed at
                                   triplicate stations from all sites. Sediments were
                                   analyzed at only the new sites (three stations analyzed
                                   per site) -
                         Year 7 - Five new sites were established including three new
                                   sites in Puerto Rico (Sites 86 to 88) and two new sites
                                   in Choctawhatchee Bay (Sites 84 and 85). Sixty-seven
                                   (67) sites were analyzed. Only one oyster analysis was
                                   conducted at each of the old sites on a composite from
                                   the three stations. Sediments were analyzed at the five
                                   new sites and one site in Florida (PBPH) (three stations
                                   analyzed per site).
                         Year 8 -  Sixty-eight (68) existing sites were sampled. Only one
                                   oyster analysis was conducted at each of the existing
                                   sites on a composite from the three stations.
                                   Sediments were not collected at any sites.

                 Details of the sample collection and location of field sampling sites are
                 contained in a separate report titled "Field Sampling and Logistics in
                 Year 8".

                       The oyster and sediment samples were analyzed for contaminant
                 concentrations [trace metals, polynuclear aromatic hydrocarbons (PAH),
                 pesticides and polychlorinated biphenyls (PCBs)], and other parameters
                 that aid in the interpretation of contaminant distributions (grain size,
                 oyster size, hpid content, etc.). The analytical procedures used and the
                 QA/QC Project Plan are detailed in a separate report titled "Analytical
                 Methods". The data that were produced from the sample analyses for
                 Year 8 are found in a separate report titled "Analytical Data".

                       A complete and comprehensive interpretation of the data from the
                 National Status and Trends Project for oyster data coupled with the
                 sediment data is an on-going process. We have begun and are
                 continuing that process as evidenced by this report and the scientific
                 manuscripts that we have published or submitted for publication (Table
                 1). As part of the data interpretation and dissemination, over 40
                 presentations of the NOAA NS&T Gulf Coast Mussel Watch Project were
                 given at national and international meetings. With eight years of data,
                 the question of temporal trends of contaminant concentrations has been
                 addressed. A general conclusion found for most contaminants measured
                 is that the concentrations have remained relatively constant over the
                 eight-year sampling period. This general trend, however, is not observed
                 at all sites. Some sites show significant changes (both increases and
                 decreases) among the years. Continued sampling is addressing the
                 frequency and rates of these changes.


                                                       2








                      Exceptions to this general trend are found for DDTs and TBT.
                When historical data for DDT in bivalves is compared to current NS&T
                data, a decrease in concentration is apparent. Also based on TBT data
                collected as part of the NOAA NS&T Mussel Watch Project, a decline in
                TBT concentration in oysters is apparent. Both declines may be in
                response to regulatory actions.

                      During Year 3 of this project, 20 new sites were added. These sites
                were chosen to be closer to urban areas, and therefore, to the sources of
                contaminant inputs. These new sites were not, however, located near
                any known point sources of contaminant input. These sites were added
                to better represent the current status of contaminant concentrations in
                the Gulf of Mexico. Over the subsequent years of the project (Years 4
                through 7) additional sites have been added to increase the
                representative coverage of the Gulf of Mexico and U.S. Caribbean
                territories.

                      While sampling sites for this project were specifically chosen to
                avoid known point sources of contamination, the detection of coprostanol
                in sediment from all sites indicates that the products of man's activities
                have reached all of the sites sampled. However, when compared to
                known point sources of contamination, all of the contaminant
                concentrations reported are, in most cases, many orders of magnitude
                lower than obviously contaminated areas. The lower concentrations in
                Gulf of Mexico samples most likely reflect the fact that the sites are
                further removed from point sources of inputs, a condition which is
                harder to achieve in East and West Coast estuaries. In fact, new sites
                added in Years 3 through 7 are closer to urban areas and generally had
                higher contaminant concentrations. An important conclusion derived
                from the extensive NS&T data set is that contamination levels in Gulf
                Coast near shore areas remain the same or are getting better, and most
                areas removed from point sources are not severely contaminated.

                      This document represents one of three report products as part of
                Year 8 of the NS&T Gulf of Mexico projects. The other two reports are
                entitled:

                         Analytical Data, Year 8
                         Field Sampling and Logistics, Year 8












                                                    3









                   Table 1. GERG/NOAA NS&T PUBLICATIONS                                       Included in
                                                                                             Year Report

                   Wade, T.L., B. Garcia-Romero and J.M. Brooks (1988)
                           Tributyltin contamination of bivalves from U.S. coastal
                           estuaries. Environmental Science and Technology, 22:
                           1488-1493.                                                               IV

                   Wade, T.L., E.L. Atlas, J.M. Brooks, M.C. Kennicutt H, R.G. Fox,
                           J. Sericano, B. Garcia-Romero and D. DeFreitas (1988)
                           NOAA Gulf of Mexico Status and Trends Program:
                           Trace organic contaminant distribution in sediments
                           and oysters. Estuaries, 11: 171-179.                                     IV

                   Wade, T.L., B. Garcia-Romero and J.M. Brooks (1988)
                           Tributyltin analyses in association with NOAA's
                           National Status and Trends Mussel Watch Program. In:
                           OCEANS '88 Conference Proceedings, Baltimore, MD, 31
                           Oct. - 2 Nov. 1988, pp. 1198-1201.                                       IV

                   Wade, T.L., M.C. Kennicutt, 11 and J.M. Brooks (1989) Gulf of
                           Mexico hydrocarbon seep communities: III: Aromatic
                           hydrocarbon burdens of organisms from oil seep
                           ecosystems. Marine Environmental Research, 27: 19-30.                    IV

                   Wade, T.L. and J.L. Sericano (1989) Trends in organic
                           contaminant distributions in oysters from the Gulf of
                           Mexico. In: Proceedings, Oceans '89 Conference, Seattle,
                           WA, pp. 585-589.                                                         IV

                   Wade, T.L. and B. Garcia-Romero (1989) Status and trends of
                           tributyltin contamination of oysters and sediments from
                           the Gulf of Mexico. In: Proceedings, Oceans '89
                           Conference, Seattle, WA, pp. 550-553.                                    IV

                   Wade, T.L. and C.S. Giam (1989) Organic contaminants in the
                           Gulf of Mexico. In: Proceedings, 22nd Waterfor Texas
                           Conference, Oct. 19-21, 1988, South Shore Harbour Resort
                           and Conference Center, League City, TX (R. Jensen and C.
                           Dunagan, Eds.), pp. 25-30.                                                V

                   Craig,  A., E.N. Powell, R.R. Fay and J.M. Brooks (1989)
                           Distribution of Perkinsus marinus in Gulf coast oyster
                           populations. Estuaries, 12: 82-91.                                       IV

                   Presley, B.J., R.J. Taylor and P.N. Boothe (1990) Trace metals
                           in Gulf of Mexico oysters. The Science of the Total
                           Environment, 97/98: 551-553.                                             IV








                                                              4










                   Sericano, J.L., E.L. Atlas, T.L. Wade and J.M. Brooks (1990)
                          NOAA's Status and Trends Mussel Watch Program:
                          Chlorinated pesticides and PCB's in oysters
                          (Crassostrea virginica) and sediments from the Gulf of
                          Mexico, 1986-1987. Marine Environmental Research, 29:
                          161-203.                                                                  IV

                   Wade, T.L., B. Garcia-Romero and J.M. Brooks (1990) Butyltins
                          in sediments and bivalves from U.S. coastal areas.
                          Chemosphere, 20: 647-662.                                                 IV

                   Brooks, J.M., M.C. Kennicutt H, T.L. Wade, A.D. Hart, G.J.
                          Denoux and T.J. McDonald (1990) Hydrocarbon
                          distributions around a shallow water multiwell
                          platform. Environmental Science and Technology, 24:
                          1079-1085.                                                                IV

                   Sericano, J.L., T.L. Wade, E.L. Atlas and J.M. Brooks (1990)
                          Historical perspective on the environmental
                          bioavailability of DDT and its derivatives to Gulf of
                          Mexico oysters. Environmental Science and Technology,
                          24: 1541-1548.                                                            IV

                   Wade, T.L., J.L. Sericano, B. Garcia-Romero, J.M. Brooks and
                          B.J. Presley (1990) Gulf coast NOAA National Status &
                          Trends Mussel Watch: the first four years. In: MTS'90
                          Conference Proceedings, Washington, D.C., 26-28
                          September 1990, pp. 274-280.                                           IV, V

                   Brooks, J.M., T.L. Wade, B.J. Presley, J.L. Sericano, T.J.
                          McDonald, T.J. Jackson, D.L. Wilkinson and T.F. Davis
                          (1991) Toxic contamination of aquatic organisms in
                          Galveston Bay. In: Proceedings Galveston Bay
                          Characterization Workshop, February 21-23, pp. 65-67.                     V1

                   Wade, T.L. I.M. Brooks, J.L. Sericano, T.J. McDonald, B. Garcia-
                          Romero, R.R. Fay, and D.L. Wilkinson (1991) Trace
                          organic contamination in Galveston Bay: Results from
                          the NOAA National Status and Trends Mussel Watch
                          Program In: Proceedings Galveston Bay Characterization
                          Workshop, February 21-23, pp. 68-70.                                      VI

                   Presley, B.J., R.J. Taylor and P.N. Boothe (1991) Trace metals
                          in Galveston Bay oysters. In: Proceedings Galveston Bay
                          Characterization Workshop, February 21-23, pp. 71-73.                     VI

                   Sericano, I.L., T.L. Wade and J.M. Brooks (1991) Transplanted
                          oysters as sentinel organisms in monitoring studies. In:
                          Proceedings Galveston Bay Characterization Workshop,
                          February 21-23, pp. 74-75.                                                VI





                                                             5









                   McDonald, S.J., J.M. Brooks, D. Wilkinson, T.L. Wade and T.J.
                          McDonald (1991) The effects of the Apex Barge oil spill
                          on the fish of Galveston Bay. In: Proceedings Galveston
                          Bay Characterization Workshop, February 21-23, pp. 85-
                          86.                                                                          VI

                   Wade, T.L., J.M. Brooks, M.C. Kennicutt 11, T.J. McDonald, G.J.
                          Denoux and T.J. Jackson (1991) Oysters as biomonitors
                          of oil in the ocean. In: Proceedings 23rd Annual Offshore
                          Technology Conference, No. 6529, Houston, TX, May 6-
                          9,, pp. 275-280.                                                              V

                   Brooks, J.M., M.A. Champ, T.L. Wade, and S.J. McDonald
                          (1991) GEARS:          Response strategy for oil and
                          hazardous spills. SeaTechnology, April 1991,pp.25-32.                         V

                   Sericano, J.L., T. L. Wade and J.M. Brooks (1991) Chlorinated
                          hydrocarbons in Gulf of Mexico oysters: Overview of
                          the first four years of the NOAA's National Status and
                          Trends Mussel Watch Program (1986-1989). In: Water
                          Pollution: Modelling, Measuring and Prediction. Wrobel,
                          L.C. and Brebbia, C.A. (Eds.), Computational Mechanics
                          Publications, Southampton, and Elsevier Applied Science,
                          London, pp. 665-681.                                                     V, VI

                   Wade, T.L., B. Garcia-Romero and J.M. Brooks (1991)
                          Bioavailability of butyltins. In- Organic Geochemistry -
                          Advances and Applications in the Natural Environment.
                          Manning, D.A.C. (Ed.), Manchester University Press,
                          Manchester, pp. 571-573.                                                      V

                   Wilson, E.A., E.N. Powell, M.A. Craig, T.L. Wade and J.M.
                          Brooks (199 1) The distribution of Perkinsus marinus in
                          Gulf coast oysters: its relationship with temperature,
                          reproduction and pollutant body burden. Int. Reuve der
                          Gesantan Hydrobioligie, 75: 533-550.                                         IV

                   Sericano, J.L., A.M. El-Husseini and T.L. Wade (1991) Isolation
                          of planar polychlorinated biphenyls by carbon column
                          chromatography. Chemosphere, 23(7): 915-924.                             V, VI

                   Wade, T.L., B. Garcia-Romero and J.M. Brooks (1991) Oysters
                          as biomonitors of butyltins in the Gulf of Mexico.
                          Marine Environmental Research, 32: 233-241.                             IV, V

                   Wilson, E.A., E.N. Powell, T.L. Wade, R.J. Taylor, B.I. Presley
                          and J.M. Brooks (1991) Spatial and temporal
                          distributions of contaminant body burden and disease
                          in Gulf of Mexico oyster populations: The role of local
                          and large-scale climatic controls. Helgolander
                          Meeresunters, 46: 201-235.                                              V, VI





                                                               6








                   Powell, W.N., J.D. Gauthier, E.A. Wilson, A. Nelson, R.R. Fay
                          and J.M. Brooks (1992) Oyster disease and climate
                          change. Are yearly changes in Perkinsus Marinus
                          parasitism in oysters (Crassostrea virginica) controlled
                          by climatic cycles in the Gulf of Mexico? PSZNI: Marine
                          Ecology, 13: 243-270.                                                      IV

                   Hofmann, E.E., E.N. Powell, J.M. Klinck E.A. Wilson (1992)
                          Modeling oyster populations 111. critical feeding
                          periods, growth and reproduction. J.              Shellfish
                          Research, 2: 399-416.                                                        V

                   Sericano, J.L., T.L. Wade, A.M. El-Husseini and J.M. Brooks
                          (1992) Environmental significance of the uptake and
                          depuration of planar PCB congeners by the American
                          oyster (Crassostrea virginica). Marine Pollution Bulletin,
                          24: 537-543.                                                               VI

                   Wade, T.L., E.N. Powell, T.J. Jackson and J.M. Brooks (1992)
                          Processes controlling temporal trends in Gulf of Mexico
                          Oyster health and contaminant concentrations. In:
                          Proceedings MTS '92, Marine Technology Society, Oct. 19 -
                          21, Washington, D.C. pp. 223-229.                                          VI

                   Tripp, B.W., I.W. Farrington, E.D. Goldberg and J.L. Sericano
                          (1992) International mussel watch: the initial
                          implementation phase. Marine Pollution Bulletin, 24:
                          371-373.                                                                   V1

                   Sericano, J.L., T.L. Wade and J.M.- Brooks (1993) The
                          usefulness of transplanted oysters in biomonitoring
                          studies. In: Proceedings of The Coastal Society Twetfth
                          International Conference, Oct. 21-24, 1990, San Antonio,
                          TX, pp. 417-429.                                                       V, VII

                   Wade, T.L., J.L. Sericano, LM. Brooks and B.J. Presley (1993)
                          Overview of the first four years of the NOAA National
                          Status and Trends Mussel Watch Program.                  In:
                          Proceedings of The Coastal Society Twelfth International
                          Conference, Oct. 21-24, 1990, San Antonio, TX, pp. 323-
                          334.                                                                   V, V111

                   Sericano, J.L., T.L. Wade, E.N. Powell and J.M. Brooks (1993)
                          Concurrent chemical and histological analyses: Are
                          they compatible? Chemistry and Ecology, 8: 41-47.                      V, VI

                   Sericano, J.L., T.L. Wade, J.M. Brooks, E.L. Atlas, R.R. Fay and
                          D.L. Wilkinson (1993) National Status and Trends
                          Mussel Watch Program: chlordane-related compounds
                          in Gulf of Mexico oysters: 1986-1990. Environmental
                          Pollution, 82: 23-32.                                                  V, VI





                                                              7









                    Wade, T.L., T.J. Jackson, J.M. Brooks, J.L. Sericano, B. Garcia-
                            Romero and D.L. Wilkinson (1993) Trace organic
                            contamination in Galveston Bay oysters: results from
                            the NOAA National Status and Trends Mussel Watch
                            Program. In: Proceedings, The Second State of the Bay
                            Symposium, Galveston, TX, February 4-6, pp. 109-111.                       V11

                    Presley, B.J. and K.T. Jiann (1993) Indicators of trace metal
                            pollution in Galveston Bay. In: Proceedings, The Second
                            State of the Bay Symposium, Galveston, TX, February 4-6,
                            pp. 127-13 1.                                                              VII

                    Wade, T.L., T.J. Jackson, T.J. McDonald, D.L. Wilkinson, and
                            J.M. Brooks (1993) Oysters as biomonitors of the APEX
                            barge oil spill. In: Proceedings, 1993 International Oil
                            Spill Conference, Tampa, FL, March 29-April 1, pp. 127-
                            131.                                                                       V11

                    Palmer, S.J., B.J. Presley, R.J. Taylor and E.N. Powell (1993)
                            Field studies using the oyster Crassostrea virginica to
                            determine mercury accumulation and depuration rates.
                            Bulletin Environmental Contamination Toxicology, 51:
                            464-470.                                                                   VII

                    Morse, J.W., B.J. Presley and R.J. Taylor (1993) Trace metal
                            chen-dstry of Galveston Bay: water, sediment and biota.
                            Marine Environmental Research, 36: 1-37.                                   VII

                    Sericano, J.L. (1993) The American oyster (Crassostrea
                            v&ginica) as a bioindicator of trace organic
                            contamination.     Ph.D. Dissertation, Department of
                            Oceanography, Texas A&M University, 242 p.                                 V111

                    Palmer, S.J. and B.J. Presley (1993) Mercury bioaccumulation
                            by shrimp (Penaeus aztecus) transplanted to Lavaca
                            Bay, Texas. Marine Pollution Bulletin, 26(10): 564-566.                    VII

                    Garcia-Romero, B., T.L. Wade, G.G. Salata, and J.M. Brooks
                            (1993) Butyltin concentrations in oysters from the Gulf
                            of Mexico during 1989-1991. Environmental Pollution,
                            81: 103-111.                                                           V1, V111

                    Ellis, M.S., K.-S. Choi, T.L. Wade, E.N. Powell, T.J. Jackson and
                            D.H. Lewis (1993) Sources of local variation in
                            polynuclear aromatic hydrocarbon and pesticide body
                            burden in oysters (Crassostrea virginica) from Galveston
                            Bay, Texas. Comparative Biochemistry and Physiology,
                            106C: 689-698.                                                        V1, VHI

                    Kennicutt, M.C. 11, T.L. Wade, B.J. Presley, A.G. Requejo, J.M.
                            Brooks and G.J. Denoux (1993) Sediment contaminants
                            in Casco Bay, Maine: inventories, sources and potential
                            for biological effects. Environmental Science and
                            Technology, 28(l): 1-15.                                                  VIII









                   Jackson, T.J., T.L. Wade, T.J. McDonald, D.L. Wilkinson and J.M.
                          Brooks (1994) Polynuclear aromatic hydrocarbon
                          contaminants in oysters from the Gulf of Mexico (1986 -
                          1990). Environmental Pollution, 83: 291-298.                    V1, VU, VM

                   Sericano, J.L., T.L. Wade, B. Garcia-Romero and J.M. Brooks
                          (1994) Environmental accumulation and depuration of
                          tributyltin by the American Oyster, Crassostrea
                          virginica. Marine Environmental Research (in press).                      IV

                   Hofmann, E.E., J.M. Klinck, E.N. Powell, S. Boyles, M. Ellis
                          (1994) Modeling oyster populations U. Adult size and
                          reproductive effort. Journal of Shel4flsh Research, 13(l):
                          165-182.                                                             V, Vin

                   McDonald, S.J., M.C. Kennicutt H, J.L. Sericano, T.L. Wade, H.
                          Liu, and S.H. Safe (1994) Correlation between bioassay-
                          derived P450 1A I -Induction activity and chemical
                          analysis of clam (Laternula efliptica) extracts from
                          McMurdo Sound, Antarctica. Chemosphere, 28(12):
                          2237-2248.                                                               Vin

                   Sericano, J.L., T.L. Wade and J.M. Brooks (1994) Accumulation
                          and depuration of organic compounds by the American
                          oyster (Cassostrea virginica). Science of the Total
                          Environment (in press).                                                   IX

                   Sericano, J.L., S.H. Safe, T.L. Wade, and J.M. Brooks (1994)
                          Toxicological significance of non-, mono-, and di-ortho
                          substituted polychlorinated biphenyls in oysters from
                          Galveston and Tampa Bays. Environmental Toxicology
                          and Chemistry, 13(11): x-xx (in press).                                   Ix

                   Velinsky, D.J., T.L. Wade, C.E. Schlekat, B.L. McGee, and B.J.
                          Presley (1994) Tidal river sediments in the Washington,
                          D.C. area. 1. Distribution and sources of trace metals.
                          Estuaries, 17: 305-320.                                                   Ix

                   Wade, T.L., D.J. Velinsky, E. Reinharz, and C.E. Schlekat (1994)
                          Tidal river sediments in the Washington, D.C. area. U.
                          Distribution and sources of organic contaminants.
                          Estuaries, 17: 321-333.                                                   ix














                                                              9














                           Reprint 1


          Sources of Local Variation in Polynuclear
           Aromatic Hydrocarbon Pesticide Body
          Burden in Oysters (Crassostrea virginica)
                 from Galveston Bay, Texas

           Matthew S. Ellis, Kwang-Sik Choi, Terry L.
         Wade, Eric N. Powell, Thomas J. Jackson, and
                        Donald H. Lewis














                               10










                                   Comp. Biochern. Physiol. Vol. I D6C, No. 3. pp. 689-698, 1993                                         Perpmon Press Ltd
                                   Printed in Great BriWn





                                                SOURCES OF LOCAL VARIATION IN POLYNUCLEAR
                                                AROMATIC HYDROCARBON AND PESTICIDE BODY
                                                  BURDEN IN OYSTERS (CRASSOSTREA VIRGINICA)
                                                                  FROM GALVESTON BAY, TEXAS

                                                    MATTIIEW S. ELLIS,* KWANG-SIK CHoi,* TERRY L. WADEJ ERic N. POWELL,*
                                                                      THomAs J. JAcKsoNt and DONALD H. LEWIS:
                                                   *Department of Oceanography; tGeochemical and Environmental Research Group; and
                                            tDepartment of Veterinary Pathobiology, Texas A&M University, College Station, TX 77843, U.S.A.

                                                               (Received 28 June 1993; acceptedfor publication 6 August 1"3)

                                            Abstract-1. Eggs and sperm contain significantly more PAH (polynuclear aromatic hydrocarbon) than
                                            somatic tissues in oysters (Crassostrea virginica) taken from Galveston Bay.
                                              2. The quantity of gonadal material was the most important correlate of PAH body burden.
                                              3. Eggs, but not sperm, were enriched in chlorinated compounds (e.g. DDD, chlordane), while both
                                            eggs and sperm were enriched in total PCBs relative to somatic tissue.
                                              4. Oysters may lose up to 50% of their total body burden of certain PAHs and pesticides in a single
                                            spawn.




                                                        INTRODUMON                               correlated with latitude in the Gulf of Mexico. Con-
                                   Bivalve molluscs have frequently been used as indi-           taminant body burdens average higher at higher
                                   cator organisms in studies monitoring levels of con-          latitudes. Wilson el al. (1990) suggested that the
                                   taminants in the environment. These organisms are             latitudinal temperature gradient in the Gulf produced
                                   utilized because of their ability to accumulate and           variation in reproductive effort and that this variation
                                                                                                 in reproductive effort affected PAH body burden
                                   concentrate both metal and organic contaminants               sufficiently to override the effect of local variation in
                                   enabling them to serve as long-term integrators of            contaminant loading. Wilson et al. (1992), in a more
                                   their environment (Phillips, 1977). One such program          thorough analysis, showed that PAH body burden
                                   is the NOAA Status and Trends (NS&T) Program                  responds to climate change and that biological
                                   ("Mussel Watch") designed to monitor changes in               factors are the likely intermediaries between the
                                   environmental quality along the Atlantic, Pacific and         climate's effect on temperature and freshwater inflow
                                   Gulf'coasts of the United States by measuring levels          and the final body burden of PAHs.
                                   of chemical contaminants in fish, bivalves, and sedi-           Two likely intermediaries are spawning and dis-
                                   ments and identifying biological responses to those           ease. Spawning has frequently been forwarded as an
                                   contaminants (e.g. Wilson el al., 1992, 1990, Scricano        important route of depuration (Marcus and Stokes,
                                   el aL, 1990; Presley et aL, 1990).                            1985; Jovanovich and Marion, 1987; Cossa. 1989)
                                      Unfortunately, many biological and environmental           because lipid loss peaks at this time (Chu ei al., 1990).
                                   factors affect the rate and extent of bioaccumulation         Parasites and pathogens are less frequently impli-
                                   besides contaminant availability. Biological factors          cated (Khan, 1987), but parasites and pathogens
                                   include differential growth rate (Cunningham and              should have an effect; if for no other reason, they
                                   Tripp, 1975; Boyden, 1977), reproductive stage (Cun-          frequently reduce spawning frequency or the number
                                   ningham and Tripp, 1975; Frazier, 1975; Martinici&            of gametes per spawn (Ak berali and Truema n, 1985;
                                   et al., 1984), stress and disease (Shuster and Pringle,       Ford and Figueras, 1988; Barber et al., 1988). In
                                   1969; Sindermann, 1983; Moore et al., 1989). These            oysters, both spawning frequency and disease are
                                   biological factors make spatial and temporal com-             significantly affected by temperature and salinity
                                   parisons designed to evaluate the status and trends of        (Hofmann et al., 1992, Soniat and Gauthier, 1989)
                                   contaminant loading more difficult. The NOAA                  and thus could serve as important intermediaries by
                                   Status and Trends Program has proven to be no                 which variation in climate might affect contaminant
                                   exception.                                                    body burden.
                                      In the Gulf of Mexico, the mollusc used for                  Climate exerts its influence over large geographic
                                   monitoring by NOAA is the oyster Crassostrea vir-             scales. Biological parameters capable of responding
                                   ginica. Analysis of the first 4 yr of NS&T data has           to climate change and, thus, affecting contaminant
                                   shown that the body burden of polynuclear aromatic            body burden on a large geographic scale, should
                                   hydrocarbons (PAHs) and pesticides in oysters is          689 certainly do so as well on a local scale. Accordingly,









                                             690                                                         M. S. ELLis et al.


                                                                           Table 1. The scale used for the analysis of gonadal stage (after GERG, 1990)
                                                                                                    Assigned
                                                                                                    numerical
                                                                       Developmental stage            value                       Description
                                                                       Sexually undifferentiated         I     Uttle or no gonadal tissue visible
                                                                       Early development                 2     Follicles beginning to expand
                                                                       Mid-development                   3     FoIlicks expanded and beginning to coaksce; no
                                                                                                               mature gametes present
                                                                       late development                  4     Folficles greatly expanded, coalesced, but
                                                                                                               considerable connective tissue remaining; some
                                                                                                               mature gametes present
                                                                       Fully developed                   5     Most gametes mature; little connective tissue
                                                                                                               remaining
                                                                       Spawning                          6     Gametes visible in gonoducts
                                                                       Spawned                           7     Reduced number of gametes; some mature
                                                                                                               gametes still remaining, evidence of renewed
                                                                                                               reproductive activity
                                                                       Spawned                           8     Few or no gametes visible, gonadal tissue
                                                                                                               atrophying



                                             spawning frequency and disease should be important                       son to the Gulf-wide mean (Sericano et al., 1990;
                                             sources of local (within population) variability in                      Wade et al., 1988). September is near the end of the
                                             contaminant body burden. Monitoring programs                             spawning season; most individuals should have
                                             typically sample infrequently (NS&T samples once                         spawned at least twice over the 4 previous months.
                                             per year) so that the basis for within-sample variabil-                  The oysters were placed on ice and returned to the
                                             ity is an important consideration. Accordingly, the                      laboratory. Maximum length and wet weight were
                                             primary purpose of this study was to examine sources                     determined. The condition of each meat was rated on
                                             of local variability in PAH body burden at any                           a serniquantitative scale from I (very good) to 9 (very
                                             sampling period. Some analyses of chlorinated pesti-                     poor), according to Quick and Mackin (1971). A
                                             cides and PCBs were also conducted.                                      small section of gonadal tissue was taken and fixed in
                                                Unfortunately, the variables likely of most import-                   Davidson's fixative (Fig. 28 in NOAA, 1983). A small
                                             ance in determining local variability in body bur-                       section of mantle tissue was removed for determi-
                                             den, spawning frequency and the time since the last                      nation of P. marinus infection following Ray (1966).
                                             spawn, are variables that cannot be readily measured                     The remaining tissue was placed in a precombusted
                                             even in a temporally-intensive sampling program                          mason jar with a teflon-lined screw cap and frozen for
                                             because continuous (or dribble) spawning is a fre-                       PAH analyses.
                                             quent condition at latitudes south of Chesapeake                            Perkinsus marinus infection intensity was rated
                                             Bay, including the entire Gulf of Mexico (Hofmann                        on the 0 (uninfected) to 5 (highly infected) point
                                             et al., 1992). Consequently, more readily measured                       scale of Mackin (1962) as modified by Craig et al.
                                             variables must be. used as surrogates for the more                       (1989). Tissue samples were embedded in paraffin,
                                             desirable variables. Thus, we examined a series of                       sectioned at 6,um and stained in Harris' hematoxylin
                                             indices related to reproductive state, including stage                   and picro/Navy eosin (Preece, 1972). Reproductive
                                             of reproduction and the quantity of gonadal material                     stage was rated on a scale of I (sexually undifferenti-
                                             present, and a series of indices related to health,                      ated) to 8 (spawned out) slightly expanded from
                                             namely digestive gland atrophy, condition and                            Ford and Figueras (1988) by GERG (1990)
                                             Joerkbuw marinus infection intensity. PerkbLw mari-                      (Table 1). Digestive gland atrophy was rated semi-
                                             nus, an endoparasitic protozoan, is responsible for                      quantitatively from 0 (no atrophy) to 4 (extreme
                                             high mortality (typically > 50%) in market-sized                         atrophy) as described by Gauthier et al. (1990)
                                             oysters in the Gulf each year (Hofstetter, 1977;                         (Table 2).
                                             Osburn et al., 1985; Ray, 1987) and is known to delay                       The analytical procedures used for PAHs and
                                             reproduction (White et al., 1988; Wilson et al., 1988).                  pesticides were based on NOAA's NS&T techniques
                                             Digestive gland atrophy is a putatively pathogenic                       for organic compounds (MacLeod et al., 1985) with
                                             condition (e.g. Marig6mez et al., 1990; Moore et al.,                    some modification by Wade c- al. (1988). These
                                             1989) common in Gulf coast oysters (Gauthier et al.,                     methods have been detailed elsewhere (Wade el al.,
                                             1990).                                                                   1988; Wade and Sericano, 1989; Sericano et al., 1990;


                                                                         METHODS                                             Table 2. The scale used for digestive gland atrophy
                                                                                                                         Assigned numerical
                                             Within -population differences in body burden                                      value                          Description
                                                Oysters were collected in September, 1990, from                                   0                 Normal
                                                                                                                                                    Less than one-half atrophied
                                             Confederate Reef in the West Bay extension of                                        2                 About  one-half atrophied
                                             Galveston Bay. Confederate Reef oysters normally                                     3                 Greater than one-half atrophied
                                             have a relatively high PAH body burden in compari-                                   4                 Completely atrophied

                                                                                                                 12







                                                                       PAH and pesticide body burden in oysters                                   691

                                  GERG, 1990). Only a brief overview will be given           &dy burden of eggs and sperm
                                  here.                                                         In July 199 1, additional oysters were obtained from
                                    Samples were extracted with methylene chloride           Galveston Bay for examining the relative PAH, chlo-
                                  after drying with Na2SO, The samples were then             rinated pesticide, and PCB content of eggs, sperm
                                  purified by silica/alurnina column chromatography'         and the remaining body tissues. Most oysters were
                                  In order to mmove lipids, a higli-performance liquid       7-12 cm, long and exhibited fully-developed gonads.
                                  chromatography separation was performed. Purified          Oysters were shucked and their sex determined by
                                  extracts were then analyzed by gas chromatography          microscope slide smear.
                                  with a mass spectrometry detector, GC/MS/SIM for              The contaminant content of the gametes, which is
                                  PAHs and GC-ECD for chlorinated pesticides and             the only tissue component lost during spawning, may
                                  PCBs. All concentrations am reported as nanograms          be dissimilar from the remaining gonadal tissue.
                                  of analyte per gram dry weight of sample, or ppb.          Therefore, the eggs and sperm were isolated from the
                                  Concentrations in the procedural blanks were in all        mmaining gonadal and somatic mass. The body of
                                  cases, below reporting levels for each individual          each oyster was separated from other somatic tissues.
                                  analyte. The accuracy and precision of these methods       The remainder including gill, mantle, adductor
                                  have been established by several intercalibration exer-    muscle and labial palps was stored at - 20'C for
                                  cises overseen by the U.S. National Institute of           PAH, 'pesticide, and PCB analysis. Gonads contain-
                                  Standards and Technology.
                                                                                             ing eggs or sperm were excised from the visceral mass
                                    Oyster gonadal tissue surrounds much of the body         using scissors and forceps. Gonads were placed on a
                                  mass and, thus, is difficult to excise cleanly and weigh   petri dish and phosphate buffered saline (0. 15 M
                                  (Kennedy and Battle, 1964; Morales-Alamo and               NaCl, 0.003 M KC1, 0.01 M phosphate buffer,
                                  Mann, 1989). Thus, a quantitative gonadal index            pH 7.4) (PBS) was added. Eggs or sperm were ex-
                                  based on gonad weight, as is frequently used in            tracted by squeezing the gonads with a rubber-headed
                                  invertebrates and fish, is not available. Accordingly,     syringe piston. The egg extract was then filtered
                                  a polyclonal rabbit anti-oyster egg antibody was used
                                  to quantify the amount of egg protein present (Choi        through a 100jurn nylon mesh screen; the sperm
                                  et al., 1993). A single radial immunodiffusion     assay   extract was filtered through a 30,urn nylon mesh
                                  (Mancini et al., 1965; Garvey et al., 1977) was            screen.
                                  performed to quantitate egg protein using 1.5%                Oyster egg filtrates were washed 4 times by resus-
                                  agarose in barbitone bufrer (0.01 M sodium barbital,       pending the filtrates into 30 ml of PBS and centrifug-
                                  0.0022 M barbital, 0.01 % sodium azide as preserva-        ing at 700 g for 10 min. During each washing, tissue
                                  tive, pH 8.6). Two millilitres of the rabbit serum         debris and other impurities sedimented on the egg
                                  containing anti-oyster antibody was mixed in 18 ml of      pellets were removed by pasteur pipette. After the
                                  the agarose gel and cast on a 10 x 10 cm glass plate.      final washing, the egg pellets were resuspended into
                                  Four millilitre diameter wells were made on the plate      an equal volume of PHS. Five millilitres of the
                                  using a gel puncher and 20 p I of oyster egg standard      resuspension was transferred to a 15 ml centrifuge
                                  (0.05 mg ml- I to 3.2 ing ml - 1) or the sample were       tube, 7 ml PBS added to resuspend the eggs, and the
                                  placed in the wells and incubated in a humid chamber       suspension centrifuged at 5OOg for l5min. Any
                                  for 48 hr at room temperature. After incubation, the       remaining tissue debris layered on the egg pellet was
                                  plate was pressed, dried, stained with 0.5% (w/,)          removed using a pasteur pipette. Egg pellets from
                                  Coomassie Brilliant Blue, and destained with 50%           10-20 oysters were pooled in a 50 ml centrifuge tube
                                  EtOH and 10% acetic acid. Diameters of the precipi-        and sedirriented by centrifugation (700 g for 15 min).
                                  tation rings were measured to the nearest 0. 1 mm. A       Oyster egg pellets were then resuspended into an
                                  standard curve was constructed by plotting concen-         equal volume of PBS. A 60% Percoll solution (4:6
                                  tration of the egg standard against the diameter           PBS/100% Percoll) (100% Percoll is 9:1 Percoll
                                  squared of the precipitation rings, and the concen-        stock: 10X PBS) was prepared. Five millilitres of egg
                                  tration of each sample was read from the curve.            suspension was mixed with 35 ml 60% Percoll and
                                    Removal of the body section for histological analy-      centrifuged at 900 g for 20 min. Oyster eggs formed
                                  sis biases both the total PAH concentration and the        an aggregate at the top of the centrifuge tube after
                                  gonadal quantity as measured by us. Sericano et al.        centrifugation. Purified eggs were harvested from the
                                  (in press b) showed that the effect of this bias on PAH    tube and washed twice by centrifuging at 700g for
                                  content is an expected 10-20% reduction in measured        10 min.
                                  body burden. For gonadal quantity, the percent                Oyster sperm filtrates were washed 4 tinies with
                                  reduction can be expected to be considerably higher.       PBS by centrifuging at 700 g for 15 min. Tissue debris
                                  Readers are cautioned not to accept the reported           found at the top of the oyster sperm pellet was
                                  measures of gonadal quantity as true measures of           removed using a pasteur pipette during each washing
                                  completely intact oysters. However, as most oysters        step. After the final washing, the sperm extracts were
                                  wem similar in size, the bias introduced in both           msuspended into an equal volume of PBS. 70%
                                  measures would be equivalent over all samples and          Percoll was prepared and 35 ml 70% Percoll was
                                  thus not compromise the data analysis.                     mixed with 5 ml sperm suspension and centrifuged at

                                                                                          13









                                      692                                                M. S. F-- el al.


                                                                                                   900 g for 20 min. Oyster sperm were found at the
                                                                                                   bottom of the centrifuge tube and other impurities
                                                                                                   found at the top of the Percoll as a float. Purified
                                                                                                   oyster sperm were pooled from 20-30 oysters and
                                                                                                   washed twice with PBS by centrifuging at 8OOg for
                                                                                                   15 n-dn.
                                                                                                     Because an involved procedure of this sort could
                                                                                                   lead to significant contamination, each solution was
                                                              N                                    subjected to chemical analysis. No solutions were
                                                                    .'T   .2                       found to be significantly contaminated by PAHs,
                                                                  ;; r-:                           pesticides or PCBs.



                                                                                                                           RESULTS
                                                               Z  S                                Within -population differences in PAH body burden
                                                               06
                                                                             C4
                                                             Z                                       Forty oysters were     analyzed (30 females and 10
                                                                                                   males). We present the means and ranges of the
                                                                                                   variables measured in Table 3. The mean length for
                                                                                                   the group was 8.0 cm, wet weight 9.6 g, condition
                                                       r                                           code 4.3 (fair plus), Perkinsus marinus infection inten-
                                                                                                   sity 1.45 (light plus), and digestive gland atrophy 2.1
                                                                                                   (about half atrophied). The sample contained individ-
                                                                                                   uals covering nearly the entire range of condition
                                                               C6
                                                                  00      00 C4
                                                                                                   codes, two-thirds of the range of possible P. marinus
                                                                                                   infection intensities, six of eight possible gonadal
                                                                                                   states and all stages of digestive gland atrophy. The
                                                           C   El cc      a                        variability in this data set is typical of single collec-
                                                           H-.    Z Z     Z
                                                               00                                  tions of oysters in the Gulf of Mexico region (Wilson
                                                                                                   et al., 1990).
                                                                                                     By sex, the lengths of females and males were fairly
                                                                                                   close (7.9 cm vs. 8.1 cm); however, females were
                                                       8                                           heavier than males (9.9 g vs. 8.6 g). The weight differ-
                                                                                                   ence is considerable since females are actually 0.2 cm
                                                             ValL
                                                       0       a                                   shorter on average. Condition code for both sexes
                                                       L                                           was also fairly close (4.6 for males vs. 4.2 for females)
                                                                                                   as was digestive gland atrophy (1.8 for males and 2.2
                                                                                                   for females). Perkinsus marinus infection intensity
                                                                                                   differed substantially with males at 0.77 and females
                                                                                                   at 1.67. Most animals were nearly ready to spawn or
                                                                                                   spawning. Reproductive stage was similar: 5.3 and
                                                                                                   5.6 for males and females, respectively. When
                                                                                                   measured quantitatively, the 30 females averaged
                                                                                                   6.29 mg eggs per female (equivalent to about
                                                                          V  It                    4.8 x 10' fully-developed eggs per female). As a sec-
                                                                                                   tion of gonad was removed for histology, these values
                                                                                                   underestimate female fecundity.
                                                                                                     Although we explored the entire suite of PAHs per
                                                                                                   NOAA's Status and Trends protocol (GERG. 1990),
                                                                                                   we only report data for the five most important
                                                                      ro C0  C.                    PAHs: fluoranthene, phenanthrene, pyrene, naph-
                                                                                 Z                 thalene and chrysene. Males and females had similar
                                                                                                   body burdens except for fluoranthene where females
                                                                                                   had about one-third more. Means for both sexes
                                                                                                   ranged from 12.0 ng g dry wt-' for phenanthrcne to
                                                                                                   49.0 ng g dry wt -I for fluoranthene.
                                                                                                     A Spearman's rank analysis showed that many of
                                                                                                   the biological variables were correlated as might be
                                                                                                   expected. Accordingly, prior to considering their
                                                                                             14    relationship with the PAHs, the relationships among









                                                                                             PAH and pesticide body burden in oysters                                                              693

                                           Table 4. Best 3-variable model for each biological variable for all              Table 6. Best 3-variable model for each biological variable for male
                                           oysters combined (i.e. both sexes combined) and the amount of                    oysters and the amount of variation explained (R'). Significant
                                           variation explained (R). Significant partial correlations are shown              partial correlations are shown by asterisks, as defined in Table 4
                                           by asterisks: 00.05 < P < 0.01; **,0.025 < P < 0.05; 1*00.01 <                                                            Explanatory variable
                                                P < 0.025; 00**0.001 < P < 0.01; ****00.0001 < P < 0,001                    Variable                  R2                    (N = 10)
                                                                                      Explanatory variable
                                           Variable                   R2                    (N = 39)                        Gonadal stage             0.70   Length
                                           Perkbmw marbw            0.18      Condition code                                                                 Wet weight
                                           infiection intensity               Wet weight                                                                     Perkbuw marinus infwion
                                                                              F,,***                                                                         intensity***
                                           Digestive gland          0.14      Length                                        Condition code            0.20   Length
                                           atrophy                            Condition code                                                                 Wet weight
                                                                              Gonadal stage-                                                                 Perkbuw marinw infection intensity
                                           Sex                      0.21      Length                                        Perkinsus marinus         0.74   Length-
                                                                              Condition code                                infection intensity              Wet weight-
                                                                              P. marinus infection intensity***                                              Digestive gland atrophy""
                                           Gonadal stage            0.34      Condition code*                               Digestive gland           0.80   Perkinnis marinus
                                                                              Wet weight****                                atrophy                          infection intensity""
                                                                              Digestive gland atrophy*                                                       Length..
                                           Condition code           0.15      Gonadal stage*                                                                 Wet weight"
                                                                              Wet weight"
                                                                              Digestive gland    atrophy
                                                                                                                               Considering both sexes together, condition code
                                           the biological variables themselves must be under-                               and sex were the most important variables correlating
                                           stood. Because of the many significant correlations                              with the PAHs (Table 7). Among the females, go-
                                           among them, we chose to identify the best 3-variable                             nadal quantity had a significant effect in three of five
                                           model explaining variation for each of the important                             cases (Table 8): fluoranthene, pyrene and chrysene.
                                           biological variables, as detailed in Tables 4 to 6.                              Each of the contaminant's concentrations was higher
                                           Because gonadal quantity was measured in only 30 of                              in females having more eggs. Digestive gland atrophy
                                           the 40 individuals and only in females, we examined                              was also a significant correlate of chrysene. Female
                                           the data with and without this variable included. The                            oysters having a higher degree of atrophy had more
                                           variables examined were length, wet weight, Perkin-                              chrysene. If gonadal quantity was removed, few
                                           sus marinus infection intensity, digestive gland atro-                           significant correlations remained. Among the males,
                                           phy, sex, condition code, gonadal stage and gonadal                              digestive gland atrophy was significantly correlated in
                                           quantity.                                                                        three of five cases (Table 9). PAH concentration was
                                                                                                                            lower in male oysters characterized by a greater
                                              The important correlations were: (a) between                         sex      degree of digestive gland atrophy. Condition c,)de
                                           and P. marinus infection intensity, males had fighter                            was significant in two of five cases; higher condition
                                           infections; and (b) between gonadal stage, condition                             code (less healthy) occurred with higher PAH concen-
                                           code and digestive gland atrophy. Among the                                      tration.
                                           females, only the relationship between gonadal stage
                                           and condition code remained significant. Among the
                                           males, digestive gland atrophy was correlated with p.                            Body burden of eggs and sperm
                                           marinus infection intensity. Inasmuch as the two sexes                              Samples of pure eggs and sperm, collected from
                                           were distinctive in the relationships among biological                           oysters taken earlier in the spawning season than
                                           attributes, we will consider the sexes separately in                             those supporting the previous data, had significantly
                                           most of the remaining analyses.                                                  higher PAH levels than somatic tissue for all five


                                           Table 5. Best 3-variable model for each biological variable for female oysters and the amount of variation explained (R2). Analyses were
                                              conducted with and without gonadal quantity included. Significant             partial correlations are shown by asterisks, as defined in Table 4
                                                                                              With gonadal quantity (N = 23)                          Without gonadal quantity (N = 29)
                                           Variable                                      R2                Explanatory variable                    R2                Explanatory variable
                                           Gonadal stage                                0.54          Length                                     0.47           Condition code
                                                                                                      Condition code"                                           Wet weight'-**
                                                                                                      Wet weight-                                               Digestive gland    atrophy
                                           Condition code                               0.23          Length                                     0.11           Gonadal stage
                                                                                                      Gonadal stage"                                            Wet weight
                                                                                                      Wet weight***                                             Digestive gland atrophy
                                           Perkimus marinus infection                   0.22          Length                                     0.06           Condition code
                                           intensity                                                  Gonadal stage                                             Gonadal stage
                                                                                                      Digestive gland atrophy                                   Digestive gland    atrophy
                                           Digestive gland atrophy                      0.16          Perkkms marinus infection                  0.11           Condition code
                                                                                                      intensity                                                 Wet weight
                                                                                                      Length                                                    Gonadal stage
                                           Gonadal quantity                                           Wet weight                                 0.07           Perkinsus marinus infection
                                                                                                                                                                intensity
                                                                                                                                                                Wet weight
                                                                                                                                                                Digestive gland atrophy



                                                                                                                       15









                                                    694                                                           M. S. ELLis et al.

                                                    Table 7. Best 3-variable model for each PAH for ail oysters                Table 9. Best 3-variable model for each PAH for male oysters and
                                                    combined and the amount of variation explained (fil). Significant          the amount of variation explained (R'). Significant partial corm.
                                                    partial correlations am shown by asterisks, as defined in Table 4                  lations am shown by asterisks. as defined in Table 4
                                                    Variable               R2               Explanatory variable               Variable                     R2           Explanatory variable
                                                                                                                               Flueranthene              0.49         Length
                                                    Fluoranthene         0.20      Length                                                                             Gonadal stage
                                                                                   Perkkna maruna infection intensity                                                 Digestive gland atrophy*
                                                    Phmnthmne            0.11      F,,**                                       Phenanthrene              0.67         Condition code**
                                                                                   Condition code                                                                     Gonadal stage
                                                                                   Gonadal stage                                                                      Digestive gland atrophy
                                                    Naphthalene          0.20      Sex                                         Naphthalene               0.73         Condition code***
                                                                                   Condition oode*"                                                                   Gonadal stage*
                                                                                   Gonadal stage                                                                      Digestive gland atrophy
                                                    Pyrene               0.19      Sex                                         PyMne                     0.68         Length
                                                                                   Length                                                                             Gonadal stage
                                                                                   Perkkww marbw infection intensity                                                  Digestive gland atrophy***
                                                    Chrysene             0.14      Sex**                                       Chrysene                  0.59         Condition code
                                                                                   Perkinm marinus infection intensity                                                Gonadal stage
                                                                                   Wet weight                                                                         Digestive gland atrophy*
                                                                                   Sex



                                                    PAHs (Table 10). A factor of 5 difference was typical.                     spawning. Eggs and sperm had PAH concentrations
                                                    Total PCBs were concentrated in eggs and sperm by                          5 times higher than somatic tissue, 3-4 times higher
                                                    a factor of about 5 over the somatic tissue. The                           for pesticides, and the gonadal tissue can account for
                                                    chlorinated compounds like lindane, chlordane,                             25% of animal dry weight prior to spawning (Choi
                                                    dieldrin and DDT (plus breakdown products) were                            et al., 1993; Klinck et al., 1992).
                                                    concentrated in eggs by about 4 times, but tended to                          (2) The quantity of gonadal material was the most
                                                    be equivalent to or lower than the somatic tissue in                       important correlate of PAH body burden and much
                                                    sperm.                                                                     more important than, for example, gonadal stage.
                                                                                                                               Less gonadal material indicates recent spawning since
                                                                                MSMSSION                                       these oysters were collected well into the spawning
                                                    Spawning as a route of depuration                                          season; all had certainly spawned at least once prior
                                                                                                                               to collection.
                                                      Our data suggest that reproduction is an important                          (3) Sex was an important determinant of body
                                                    depuration route for oysters; the frequency of repro-                      burden. PAH and PCB concentrations differed be-
                                                    duction is the most important determinant of body                          tween sexes in some cases, chlorinated pesticide con-
                                                    burden, under equivalent exposure levels. Sex and                          centrations were dramatically lower in male gametes,
                                                    health arc important secondary determinants of body                        and the factors correlating with body burden differed.
                                                    burden because both affect reproductive state and the                      Health-related factors were much more important in
                                                    frequency of reproduction. The three following ob-                         males. Factors decreasing health probably also
                                                    servations support these two conclusions:                                  decrease spawning frequency. The most important
                                                      (1) Both eggs and sperm contain signilicantly more                       correlation occurred with digestive gland atrophy;
                                                    PAH and PCB than somatic tissue. Eggs also con-                            however in males, digestive gland atrophy was highly
                                                    tained more chlorinated pesticides. The concentration                      inversely correlated with Perkinsus marinus infection
                                                    factor is sufficient to conclude that over half of the                     intensity, so the two parameters behaved similarly in
                                                    PAH body burden, and somewhat Less of the pesti-                           explaining the variation in PAH body burden among
                                                    cide body burden, could be in gonadal tissue prior to                      oysters taken from the same site. PAHs were lower


                                                    Table 8. Best 3-variable model for each PAH for femake oysters and the amount of variation explained (R2). Analyses were conducted with
                                                              and without gonadal quantity included. Significant partial correlations am shown by asterisks, as defined in Table 4
                                                                                       With gonadal quantity                                          Without gonadal quantity
                                                    Variable                 R2                   Explanatory   variable                    A 2                   Explanatory variable
                                                    Fluoranthene             0.37        Condition code                                    0.18         Length
                                                                                         wet weight                                                     Condition code
                                                                                         Gonadal quantity***                                            Perkkw marinus infection intensity
                                                    Phenanthmne              0.18        Perkinsw marinw infection intensity               0.16         Condition code
                                                                                         Digestive gland atrophy                                        PerkAw marinus infection intensity
                                                                                         Gonadal quantity                                               Digestive gland atrophy
                                                    Naphthalene              0.21        Length                                            0.27         Length"O
                                                                                         Digestive gland atrophy                                        Perkkw marinta infection intensity
                                                                                         Gonadal quantity                                               Digestive gland atrophy*
                                                    Pymne                    0.31        Gonadal quantity**                                0.20         Length
                                                                                         Digestive gland atrophy                                        Condition code
                                                                                         Gonadal stage                                                  Perkimw marinus infection intensity
                                                    Chryscne                 0.51        Length**-                                         0.25         Perkkw marinus infection intensity*
                                                                                         Digestive gland atrophy"                                       Wet weight*
                                                                                         Gonadal quantity""*                                            Digestive gland atrophy


                                                                                                                    16







                                                                                               PAH and pesticide body burden in oysters                                                                  695

                                                  Table 10. PAH concentrations in pooled sarnples (groups) of purified oyster eggs, purified sperm and somatic tissue (in ppb)
                                                                            Group A                     Group 0                    Group C                     Group D                     Group E
                                                                        Eggs       Tissue           Eggs       I issue         Eggs       Tissue          Sperm          Tissue      Sperm         Tissue
                                           Naphthalene                  45.1          9.0           51.9         9.9           42.5          5.9          64.8           12.3        70.5           12.3
                                           Phenanthmme                  23.5          2.9           26.9         4.1           29.0          3.4          26. 1          5.6         29.9           5.6
                                           Fluoranthem                  16.1          2.9           15.8         3.0           17.7          3.2          11.6           3.3         17.6           3.3
                                           Pyrene                       20.7          3.7           18.4         3.7           18.2          3.8          13.1           4.0         18.1           4.0
                                           Chrysem                      11.5          2.4           12.5         2.0           10.9          2.2            7.2          2.4         16.6           2.4



                                           with lower         P. marinus infection intensity and P.                            that these are variables that can normally be easily
                                           fftarinus is known to slow reproduction in oysters                                  measured in oyster individuals, whereas spawning
                                           (Wilson et al., 1988; White et al., 1988).                                          time and frequency cannot. Nevertheless, under these
                                                                                                                               conditions, only the strongest relationships might be
                                           Reproduction, health and body burden                                                expected to generate a signal of sufficient intensity to
                                              The importance of reproduction in molluscs in                                    be observed as a significant correlation.
                                           controlling or affecting body burden is open to                                         Correlations were found, indicating the importance
                                           disagreement. Mix et al. (1982) and DiSalvo et al.                                  of reproductive state and health on body burden. The
                                           (1975) found PAHs no more concentrated in Mytilus                                   amount of variation explained among individuals in
                                           eduhs gonadal material than somatic tissue (purified                                their PAH body burdens was generally low; however,
                                           eggs were not measured), but noticed a significant                                  this probably emphasizes the previous point, that
                                           drop in body burden during the spawning season.                                     each of the measured variables are themselves rela-
                                           Sericano et al. (in press b) found that the central bo y                            tively poor indicators of how recently and how
                                           region including the gonad contained proportionately                                frequently each animal had spawned. Stegeman and
                                           more PAH in oysters. Lee el al. (1972), Fortner and                                 Teal (1973) emphasized the importance of the total
                                           Sick (1985) and Solbakken et al. (1982), as examples,                               ex  .posure history of any individual organism in deter-
                                           found the hepatopancreas to be an important depot                                   mining body burden. One aspect of this exposure
                                           for PAHs in bivalves; however, gonadal material, and                                history is the time since the last significant depuration
                                           in particular, gametes, were not separately measured.                               event due to spawning.
                                           In scallops where gonads can be separated from the                                      Hydrocarbons can be taken up by feeding as well
                                           somatic tissue by dissection, Friocourt et al. (1985)                               as in the dissolved phase (e.g. McElroy et al., 1989)
                                           found gonadal material enriched in PAHs over                                        and can affect filtration rate (Axiak et al., 1988;
                                           muscle but not digestive gland tissue. Rossi and                                    Barszcz et al., 1978). PAHs can also affect the
                                           Anderson (1977) observed spawning to be an import-                                  digestive gland (Nott and Moore, 1987). Theoreti-
                                           ant depuration route in a polychaete Neanthes are-                                  cally, digestive gland atrophy should be related to
                                           naceodentata.                                                                       nutritional state. Digestive gland atrophy was corre-
                                              If spawning.is an important route of depuration,                                 lated weakly with higher PAHs in females and more
                                           then factors affecting spawning frequency and how                                   strongly with lower PAHs in males. One possible
                                           r=ntly the last spawn occurred prior to collection                                  explanation for these divergent results is the strong
                                           will alrect body burden. The biological variables                                   correlation of digestive gland atrophy and Perkinsus
                                           measured as surrogates of spawning frequency are                                    marinus infection intensity in males. In any case, no
                                           gonadal quantity and gonadal stage, Perkin3w mari-                                  unambiguous effect of digestive gland atrophy could
                                           nus infection intensity, and some general indicators of                             be discerned.
                                           health. Few of these were correlated among them-                                        Our data clearly support the importance of repro-
                                           selves, so that most serve as separate, somewhat                                    duction, at least in oysters, during the summer and
                                           unique, indicators of the many factors that might                                   fall. We suggest that the weak evidence for the
                                           affect spawning frequency and how recently the last                                 importance of reproduction in most time series of
                                           spawn occurred prior to collection. Each has its own                                contaminant body burden generally stems from three
                                           history, in some cases not necessarily related to                                   factors: collection of animals out of spawning season
                                           spawning frequency, so that each is only a poor                                     when little gonadal material is present, failure to
                                           surrogate for the desired variable, but we emphasize                                analyze purified gametes which are the primary ve-


                                               Table 11. Pesticide concentrations in pooled samples (SToups) tof purified oyster eggs, purified sperm and somatic tissue (in ppb)
                                                                            Group A                     Group B                    Group C                     Group D                     Group E
                                                                        Eggs      Tissue            Eggs      Tissue           Eggs       Tissue          Sperm          Tissue      Sperm        Tissue
                                           LiDdane                      9.4           2.1           5.5          2.2           8.2           1.8          < 1.0          2.2         < 1.0          2.2
                                           Total BHCs                   14.7          5.0           9.5          5.2           14.0          3.9          < 1.0          5.2           2.4          5.2
                                           a-Chlordane                  6.5           3.8           5.0          3.9           5.1           2.4          < 1.0          4.5           3.6          4.5
                                           Dieldrin                     6.3           2.2           6.1          1.9           5.8           1.7          < 1.0          1.8           1.7          1.8
                                           4,4'DDE                      32.1          9.1           26.0         9.2           26.7          7.5            4.1          11.9          6.6          11.9
                                           4.4'DDD                      12.3          3.7           11.7         3.2           12.5          3.1          < 1.0          3.6           3.5          3.6
                                           Total PCBS                   132.6       36.5            147.8        33.5          113.0        29.6          114.2          53.8        )02.3          53.8




                                                                                                                       17









                                             696                                                   M. S. ELLIS et at.

                                             hicle of depuration during spawning, and the poor                substantial fraction of the body burden is lost in
                                             understanding of the dynamics of             uptake after        spawning.
                                             spawning. We suggest that the timing of the last                   Wilson et al. (1990) found the latitudinal gradient
                                             spawning event prior to sampling-animals recover                 in PAH body burden to be stronger than the latitudi-
                                             their body burden within a month or less after a                 nal gradient in pesticide body burden. We found
                                             deputation event (Sericano et al., in press)- and the            gonadal material concentrated much more highly in
                                             degree of gonadal development (e.g. Hofmann et al.,              PAHs than pesticides and some pesticides are not
                                             1992) are important variables affecting PAH body                 concentrated in male gonadal material at all. Our
                                             burden in oysters.                                               data would suggest that temperature, and therefore
                                                Lowe and Pipe (1987) and Moore et al. (1989)                  latitude, should have a much greater impact on PAHs
                                             observed gonadal      resorption at high PAH concen-             through reproduction than on pesticides, in agree-
                                             trations. We observed no such effect in our analyses;            ment with the findings of Wilson et al. (1990). Taken
                                             however, body burdens were lower.                                together, our data and those of Wilson et al. (1990,
                                             Variation between compounds                                      1992) suggest that interpretation of the results of
                                                                                                              monitoring studies such as the Status and Trends
                                                Fluoranthene, pyrene and chrysene were very simi-             program using bivalves requires that close attention
                                             lar in their response to the biological variables;               be paid to the reproductive state and health of the
                                             naphthalene and phenanthrene formed a second                     sampled populations.
                                             group quite different from the other three. Certainly,
                                             uptake, storage and deputation must be relatively                Acknowkdgements-This research was supported by a grant
                                             similar within these two groups but different between            from the Center for Energy and Minerals Resources, Texas
                                             them. Phenanthrene and naphthalene are lower mol-                A&M University (TAMU), an institutional grant NA89-
                                                                                                              AA-D-SG139 to TAMU by the National Sea Grant College
                                             ecular weight, more water soluble compounds and                  Program, National Oceanic and Atmospheric Adminis-
                                             equilibrate faster with the environment (Pruell et al.,          tration (NOAA), U.S. Department of Commerce, grant
                                             1986; Sericano et al., in press). They might lose the            50-DGNC-5-00262 from the U.S. Department of Com-
                                             signal imposed by spawning events faster than the                merce, NOAA, Ocean Assessments Division, and computer
                                                                                                              funds from the TAMU College of Geosciences and Mar-
                                             larger three PAHs exaIrtined. Phenanthrene and                   itime Studies Research Development Fund. We appreciate
                                             naphthalene supported fewer significant correlations,            this support.
                                             and none with reproduction, despite their enrichment
                                             in eggs and sperm, but were correlated with general
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                                                   of Mexico, %itb comments on the relationship of the                 disease in Gulf of Mexico oyster populations: the role of
                                                   oyster parasite to temperature and salinity. Tulane Stud.           local and large-scale climatic controls. Holgol. Meeresun-
                                                   Zool. Bot. 27, 21-27.                                               ters. 46, 201-235.









































                                                                                                            20














                           Reprint 2


            Sediment Contaminants in Casco Bay,
              Maine: Inventories, Sources, and
                Potential for Biological Impact

            M.C. Kennicutt H. T.L. Wade, B.J. Presley,,
           A.Q. Requejo, J.M. Brooks and G.J. Denoux














                                21












                          Sediment Contaminants In Casco Bay, Maine: Inventories, Sources, and
                          Potential for Biological Impact

                          U. C. Kordftuff 11, * T. L Wmle, 0. J. Pres1ey, A. G. Requelo, J. M. Brooks, mW Q. J. Denoux
                          Geocheffkal and Envhmmental Plesearch Group, Texas A&M UnNwsfty, 833 Graham Road, College Statlon, Texas 77845
                          An inventory-based approach to environmental assessment            term accumulator of contaminants, which are probably
                                                                                             the main avenue of chronic exposure of the associated
                          that determines concentrations of sedimentary contam-
                          inants, defines their origins, and assesses the potential for      ecosystem.
                          biological impact is illustrated in Casco Bay, ME. The             Site Description
                          Most widespread contaminants in Casco Bay are petroleum
                          and petroleum byproducta. The highest concentrations                 Casco Bay is situated along the Atlantic Coast of Maine
                          of contaminants are associated with Population centers,            and is bounded by Cape Small to the northeast and Cape
                          effluent outfalls, and spills. The majority of PAH in              Elizabeth to the southwest (Figure 1). The bay has a
                          sediments are the product of high-temperature combustion           wealth of natural resources and -srine habitats that
                          processes. PAH concentrations at sites in close proximity          support a rich and diverse ecosystem. The bay proper is
                          to Portland exceed values believed to produce toxic                a4OO-kM2 embayment of the Gulf of Maine which includes
                          responses in marine benthic organisms. Incontrast,PCB,             Portland Harbor, a major docking facility and the principal
                          DDTs, and chlordane concentrations in the sediments are            fishing port of Maine. More than 300 mi of coastline and
                          belo@w concentrations thought to produce toxic effects in          nearly 400 islands are encompassed by the bay (1).
                          marine organisms. Metal concentrations in sediments are
                          also below those that elicit biological responses. The             Methods
                          geographic distribution of contaminants is initially con-
                          trolled by the proximity to sources, and the regional                Sediment samples were analyzed for trace metals,
                          differences in concentrations are the result of sediment           aliphatic and polycyclic aromatic hydrocarbons, pesticides
                          accumulation patterns. Detrital (terrestrial), autochth-           and PCBs (Table 1). Matrix spikes, laboratory sample
                          onous manne, pyrogenic, and petroleum sources for PAH,             duplicates, and laboratory blanks were processed with each
                          alkanes, and trace metals are defined.                             batch of samples (10-20samples/batch). Duplicateswere
                                                                                             produced by subeampling in the laboratory. Standard
                          Introduction                                                       reference materials (National Institute of Standards and
                                                                                             Technology) were analyzed to audit the performance of
                            The systematic inventory of contaminants within mairtal          the analytical methods. The quality assurance standards
                          environments is often a first step in developing a logical         are those of the NOAA's National Status and Trend
                          and effective approach to preserving, protecting, and/or           Program, of the RPks Environmental Monitoring and
                          reclaiming resources impacted by human activities. While           Assessment Program-Near Coastal (EMAP-NC) and of
                          bulk inventories of chemicals alone cannot predict bio-            the U.S. Fish and Wildlife Service (FWS) for trace
                          logical impacts or "ecosystem health", this first-order            contaminant analyses (2). These methods have undergone
                          evaluation ofthe presence and magnitude ofcontamination            extensive intercalibration with EPA, NOAA, NIST and
                          can indicate which processes are most influential in               FWS. Detailed methods are provided elsewhere (3).
                          controlling ecosystem exposure. Cause and effect must                Sample Collection. Sediment samples were collected
                          be linked by careful consideration of contaminant input,           in August 1991 (Figure 1). Station locations were chosen
                          transport, ultimate fate, and biological impact. High-             to provide good areal coverage, sediments of different ages
                          quality analyses, intensive sampling, and an evaluation of         (including erosional features), and representative coverage
                          a broad spectrum of contaminants can contribute to                 of benthic communities. Bathymetry and sediment tex-
                          defining those processes or activities most closely linked         bm also guided site selection. The sampling sites are
                          to detrimental or unwanted impacts. Innate in this type            designated as CS, EB, IB, OB, SW, and WB (i.e., Cape
                          of approach is the generation of large, complex multi-             Small, Fast Bay, Inner Bay, Outer Bay, Shallow Water,
                          component data sets that must be fully integrated and              and West Bay, respectively). A number identifies the
                          rigorously evaluated, An approach utilizin comprehen-              location within the bay. Samples were taken with either
                          grve chemical inventories and a detailed statistical analysis      a Smith-McIntyre grab sampler, a ponar grab sampler, or
                          of the data is'reported for a study of Casm Bay, ME,               by hand. All samples were carefully inspected to ensure
                          sediments. Surficial sediments were evaluated as a long-           that undisturbed sediments were collected.
                          901343ex/%/09284001$04.60/0    0 IM Anwtan Chm" 900MY         22                         EnvWn. Sd. Tedwid., Vol. 28, No. 1. 1994 1





























                                                      Cueo Say

                                                                                                                                                                                                                                              0.
                                                                                           abe"  a a                      70010,                                                 70000'                             . ..... . .....    egos
                                                                                                                                                                                                      .......               ...
                                                                                                                                                                                                    . ....    .... .
                                                                                                  X:
                                                                                                                                                             X.   . ... ..
                                                                                                                                                                                           M.



                                                                                                                                                                                                                 ............
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                                                                        430
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                                                                        45                                                                                                                               3
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                                                                                                                                                              Ck.
                                                                                                                                                                                                                 40
                                                                                                                  7                                                                          61         2&
                                                                                                                             te
                                                                                                                    Inner
                                                                                                                     Bay
                                                                                                                 4
                                                                                                                        A
                                                                                                                                                                  10                                15*                 2 9       C4oPe
                                                                                                                                        7        0
                                                                                                                  '05o'                           6      48wel 1.
                                                                                                                    ..... .E                                                                                              40      SMSII
                                                                                                            2                                                                     Outer                                                       430
                                                                                                           0       3                                       *8 .0                  Say
                                                                                                               0.    4-..                                                                                                                     40
                                                                                                                               %r        4
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                                                                                                                ...........



                                                                                ...... ... ..                 .....
                                                                                 .............
                                                                                                                                                                                                                                              35


                                                                                                                 X.,


                                                                                                                                                                                                                    0 Sheflow WOW
                                                                                                                          7A1 0'                                                 7M'                                                   69050'
                                   PWm 1. Location map for the Casco Bay dudy.

                                       Hydrocarbons, Pesticides, and PCBs. The extrac-                                                           100 mash) chromatography. The extracts were sequen-
                                   tion method is that of Wade et aL (2). A total of 10 g of                                                     tially eluted from the column with 50 mL of pentane
                                   freeze-dried sediment was Soxhlet-extracted with meth-                                                        (aliphatic fraction) and 200 mL of 1:1 pentane--dichlo-
                                   y1ene chloride and concentrated in Kuderna-Danish U@bw                                                        romethane (aromatic/PCB/posticide fraction) and con-
                                   The extracts were fractionated by aluminwailica gel (80--                                          23         centrated for instrumental analysis.
                                   2 Envkon. Sol. Technol., VOL 28, No. 1, 1904




______________________________________________________________________________________________
Table 1.  Analytes Measured in Casco Bay Estuary Program




							Total Metals

	cadmium					chromimum							mercury
	copper					silver							arsenic
	lead						xinc								selenium
	nickel					iron

							Hydrocarbons

naphthalene					phenanthrene						benzo[k]fluoranthene
2-methylnaphthalene			anthracene							benzo[a]pyrene
1-methylnaphthalene			2-methylphenanthrene					benzo[e]pyrene
biphenyl					fluoranthene						indeno[1,2,3,-cd]pyrene
acenaphthene				benz[a]anthracene						dibenz[a,h]anthracene
acenaphthene				chrysene							benzo[g,h,i]perylene
fluorene					benzo[b]fluoranthene					

							In Addtion

			extended PAHs (alkylated homologues useful in differentiating oil from combustion sources)
			aliphatic fraction quantitation including C12-C34 n-alkanes, pristane, phytane, and the
				unresolved complex mixture

										PCBs

				congener-specific analysis of 20 individual PCBs including quantitative estimates of the
					amount of arochlor mixtures

										Pesticides

				aldrin				endosulfan I					hexachlorobenzene
				a-BHC					endosulfan II					2,4'-DDE
				p-BHC					endosulfan sulfate				2,4'-DDD
				 -BHC					endrin						2,4'-DDT
				 -BHC					endrin aldehyde					4,4'-DDD
				a-chlordane				heptachlor						4,4'-DDE
				 -chlordane				heptachlor epoxide				4,4'-DDT
				dieldrin				toxaphene

										Aneillary Parameters
						(1) TOC was determined by combustion in a Leco carbon analyzer to CO2 and
						   subsequent quantitation by IR
						(2) grain size (sand, silt, and clay) was determined by the Folk settling method
						(3) organic nitrogen was determined by a Kjeldahl digestion
						(4) % solids (dry weight) are determined and reported for all samples

			*Note:  Organic analyte concentrations are reported on the basis of dry weight of sediment and are corrected for surrogate recoveries.
			_______________________________________________________________________________________________________________________________________

				Aliphatic hydrocarbons (n-C13-n-C34), pristane, and phytane were analyzed by gas chromatography (HP-5980) in the splitless mode with 
			flame ionization detection (FID).  A 30 m x 0.32 mm i.d. fused-silica column with DB-5 bonded phase (J&W Scientific, Inc.)provided component
			seperations.  The FID was calibrated at five concentrations, and deuterated n-alkanes were used as surrogates and internal standards.  Aromatic
			hydrocarbons were quantified by gas chromatography with mass spectrometric detection (HP-5890-GC and HP-5970-MSD).  The samples were injected
			in the splitless mode onto a 30 m x 0.25 mm (0.32 mm film thickness) DB-5 fused silica capillary column (J&W Scientific Inc.) at an initial
			temperature of 60 degree C and temperature programmed at 12 degree C/min to 300 degree C and held at the final temperature for 6 min.
			The mass spectral data were acquired, and the molecular ions for each of the PAH analytes were used for quantification.  The GC/MS was calibrated
			by the injection of standards at five concentrations.  Analyte identifications were based on the retaention time of the quantitation ion for each analyte
			and a series of confirmation ions.  Deurated aromatic compounds were used for surrogates and internal standards.
				Pesticides and PCBs were separated by gas chromatography in the splitless mode using an electron capture detector (ECD).A 30 m x 0.32 mm
			i.d. fused-silica column with DB-5 bonded phase (J&W Scientific, Inc.)  Provided component separations.  Four calibration solutions were used
			to generate a nonlinear calibration curve.  A sample containing only PCBs was used to confirm the identificaiton of each PCB congener.  The surrogates
			DBOFB (dibromooctafluorobiphenyl). PCB-103 and PCB 198 for pesticide and PCB analysis were added during the extraction.  The 
			internal standard, TCMX (tetrachlorom-xylene), was added prior to GC/ECD analysis.  The chromatographic conditions for the pesticide-PCB analysis were 
			100 degree C for 1 min, then 5 degree C/min until 140 degree C, hold for 1min, then 1.5 degree C/min to 250 degree C, hold for 1 min, and then 10 degree
			C/min to a final temperature of 300 degree C, which was held for 5 min.  Trace Metals.  The major analytical technique used for trace metal determinaiton
			was atomic absorption spectrophotometry (AAA) in the flame mode for those elements in high enough concentration.  Graphite furnace (GC/AAS) or cold vapor 
			techniques were used when necessary.  Samples were pressure-digested in 50-mL closed all-Teflon "bombs" (Savillex Co.; Brooks et al.,
			1988).  Sediment aliquota (ca. 200 mg) were digested at 130 degree C in a mixture of nitric, perchloric, and hydrofluoric acids.  A saturated
			boric acid solution was then added to

											24

													Environ. Sci. Technol,Vol.28,No.1 1994  S				







                    complete the dissolution. Various dilutions were made            and phytane, suggesting a phytoplankton input (8-10).
                    on the clear digest solutions to bring them within the           Total alkanes and unresolved complex mixture (UCM)
                    calibration of the AAS. Standard reference materials and         concentrations varied from 151 to 10 078 ppb dry wt and
                    blanks were digested and analyzed with every batch of            from 2 to U5 ppm dry wt, respectively. PAHs were also
                    samples.                                                         detected at all locations sampled. The predominant PAHs
                      Concentrations of Fe, Mn, and Zn were determined by            are highly condensed ring structures with few alkylations
                    flame AAS using a Perkin-Elmer Model 306 instrument,             indicating a pyrogenic or combustion source (Figure 3;
                    following the manufacturer's recommendations with only           refs 11-14). Four-ring and larger PAHs account for more
                    slight modifications. Calibration curves were constructed        than 60 % ofsedimentary PAHs in Casco Bay. Total PAH
                    hm commercial standards. Concentrations of Ag, As,               concentrations varied from 16 to 20 798 ppb dry wt.
                    Cd, Cr, Cu, Ni, Pb, and Se were determined with a Perkin-          The western part of CascoBay (Inner Bay) is most highly
                    Zhner Zeeman 3030 instrument equipped with an HGA-               contaminated with PAH. Sediments from the Fore River
                    SW furnace and AS-60 autosampler. Matrix modifiers               area and locations close to Portland contain the highest
                    and analytical conditions for the furnace and spectro-           concentrations of PAH. In general, contaminants decrease
                    photometer were based on the manufacturer's recom-               in concentration with distance from populated areas.
                    n"n          with modifications as appropriate to     * i        However, regionally elevated PAH concentrations are also
                    sensitivity and minimize interferences. Mercury was              present at a few sites in Fast Bay and Cape Small. One
                    determined by cold vapor AAS following a slightly modified       station in the Cape Small (CS-4) region was unusual
                    EPA Method 245.5 aqua-regia/permanganate digestion.              compared to other sites in the region. Most Cape Small
                    A headapace sampling procedure was used to remove Hg             stations contained <1.0% organic carbon and more than
                    from the digest in contrast to the more common stripping         65 % sand, whereas sediment from station CS-4 contained
                    procedure. A UV monitor (IAboratory Data Control Co.)            2.7 % organic carbon and only 29.9 % sand. Total alkanes,
                    with a 30-cm path length call was used for Hg detection          UCK and total PAH concentrations were elevated at this
                    and quantification.                                              location as well. Sediments at station EB-9 also had high
                      Organic Carbon and Grain Size. Organic carbon                  concentrations of total PAH. An organic carbon content
                    (OC) was determined by detection Of C02 by an infrared           of 4.6% at EB-9 is the highest for all of the sediments
                    spectrometer after combustion in an 02 stream (LECO              sampled.
                    WR-12 total carbon system). Samples were acidified using           PCBs and Pesticides. Total PCB concentrations for
                    dilute HCl in methanol and then dried. Method blanks             the study area range from 0.4 to 485 ppb dry wt with a
                    and duplicate samples were analyzed every 20 samples.            median concentration of 15 ppb. Total PCBs are highest
                    Data are reported as micrograms of carbon per gram of            in the Inner Bay in close proximity to Portland. Con-
                    dryweight. All glassware and utensils are preheated prior        centrations are lowest in Cape Small and West Bay with
                    to use.                                                          a few anomalous values in East Bay. The site from Cape
                      Sediment grain size was determined by the procedure            Small with a total PCB concentration of 40 ppb dry wt has
                    of Folk (4), utilizing sieving to separate gravel and send       a higher TOC content (2.8%) than other samples from
                    fractions from the clay and silt fractions. The latter           Cape Small.
                    fractions were subsequently separated by the pipet (set-           Total DDT concentrations for the study area range from
                    ding rate) method. Detailed descriptions of the methods          below the method detection limit (0.25 ppb) to 21 ppb dry
                    utilized in measuring OC and grain size are reported in          weight. The DDTs were dominated by the pp'-isomers.
                    Brooks et at. (5).                                               This is expected since technical-grade DDT is primarily
                      Principal Components Analysis (PCA). The organic               the pp'- isomer (75-M%). In the environment, DDT is
                    and inorganic data were analyzed using PCA (6). The              metabolized to DDD and DDE. In some samples, DDD
                    results of PCA are highly dependent on the pretreatment          is the major metabolite while in other samples DDE
                    or scaling of the data matrix. The data for this study           predominates. Samples from the Inner Bay and associated
                    consist of a wide variety of analytes that range several         shallow water sites exhibit DDD > DDE while at most
                    orders of magnitude in their absolute values. Because            other locations DDE > DDD. There is a relatively high
                    PCA is a least-squares method, variables with large              percentage of undegraded DDT in Casco Bay sediments.
                    variance will have large loadings. To avoid this blas, the       Th! geographic distribution of total DDT concentrations
                    entire datamatrix was firstscaled bydividing each variable       IS similsk to that found for PCB9. The Inner Bay has the
                    by the standard deviation, This scaling assigns every            highest concentration in Qum Bay. East Bay and Outer
                    variable a variance of 1.0 so that each variable has the         Bay have intermediate concentrations, West Bay has lower
                    same influence in the PCA model. The technique of crow           concentrations, and the Cape Small region has the lowest
                    validation was used to establish the significance of each        concentrations.
                    principal component (7). PCA was performed on a                    The highest values of total chlordane are at Inner Bay
                    personal computer using the program SIRIUS (Pattern              sites. East Bay and Outer Bay sites are intermediate,
                    Recognition Systems A/S, Bergen, Norway).                        while West Bay and Cape S-1111 sites exhibit the lowest
                                                                                     concentrations. Total chlordane concentrations range
                    Results                                                          from below the method detection limit (0.25 ppb) to 4.9
                                                                                     ppb dry wt. Other organochlorine pesticides including
                      Hydrocarbons. Aliphatic hydrocarbons were detected             aldrin, BHC, dieldrin, endosulfan (1, 11, and sulfate),
                    at all stations sampled. The majority of resolved alkanes        endrin, endrin aldehyde, heptachlor, heptachlor epoxide,
                    had odd-carbori chain lengths with 23-33 carbons indic-          toxaphene, and hexad3lorobenzene were near or below
                    ative of plant biowaxes (Figure 2; refs 8-10). N-Cis,n-CM        the method detection limit (<0.25 ppb).
                    n-Cm n-C21, and pristane were often more abundant than             Trace Metals. Sediment trace metal data show con-
                    the co-occurring even carbon numbered normal alkanes             aderable geographic variation with generally higher values
                    4 BrAoi SaL TechnaL, Val. 26, No. 1, 1994                    25




















                                                                                                      7001 W                                      70000'                                       w





                                                                                                                                                                                                 i0c
                                                                                            ;:1 . ........                                                                     .......

                                                                                                                                                                                                 st



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                                                                    ..............                                                                                      5
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                  RW* 2- Av"09 nwml AM@ and bOPVnM mms"Oftm (Ppb dry weW, su"gato conwW and dWbtalon In sodknwft from Casw Say.














                                 4.59%


                29.94%/                   24.90%
                                                                             70010'                           70*OV


                                                                                                                                  00,
                                          3.

         p
                                               430
                             37.21%

                                                                                                                                         0


                                                                                                                                 ..........


                                                                                     Odwo      2

                                                                                                                   7
                                                                                                      Wed
                                                                                                     46 say
                                                                                                                12
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                                               43*                         8   9
                                                                                               'N3              8               Bay  I
                  24.67%,,'
                                               46:
                                                                                                                           3
                                                                                   10
                                                                                              t72                                     10
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                                                                    2
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                                                                       03
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                                                40                                               a  09        BOY

                                                                                      3

                                                                                               4.38%

                                                                               30.2296
                                                                                                        22.47%
                                                                        ..............


                                               430
                                                3                                                                   0 2 RING
                                                                                                          2.89%
                                                                                                                    0 3 RING
                                                                                                                       DST's
                                                                                                                       4 FMG
                                                                                                                                  0 ShIdlow Wale
                                                                                          40.05%                       S+ puma      sampl"

                                                                             7001 V                           70000'

                Fkp" 3. Average PAN compositions in mdMents by region w" Casco Say.



          = m = = m = m m m m = m m m =





                                                                                   0 to         0     m                                                                                Numbw of Swnples


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                  Figure 5.  Relationship between chromium, lead, nickel, and zinc concentrations (ppm dry weight) and iron content (% dry weight) in sediments
			from Casco Bay.      
           
	            Outer Bay, three East Bay, and one Cape Small sites. Eight               concentrations result in part from sediment accumulation
                  of the 10 most highly contaminated stations are located                  patterns. Thus, area of fine-grained sediment accumu-
                  in the Inner Bay region, including the six highest stations.             lation such as the Inner Bay have high scores for PC I and
                  The lowest levels of organic contaminants are in the Cape                exhibit high concentrations, while sediments in areas that
                  Small and West Bay regions. High levels of a variety of                  are characterized by a dynamic physical environment and
                  organic contaminants tend to occur at the same location.                 little sediment accumulation such as the Outer Bay have
                     For inorganic contamination, only those metals believed               low scores for PC I and exhibit lower concentrations. It
                  to be influenced by anthropogenic inputs were used to                    is also notable that both the organic and inorganic
                  rank the sample locations, i.e., Ag, Cd, Pb, Zn, and Hg.                 contaminants exhibit the same general trend. Shallow
                  Based on the formation of inorganic contaminant rank-                    water samples SW-I and SW-2 were identified as outliers
                  ings, 25 % of the locations with the highest levels were as              because their compositions were anomalous relative to the
                  follows: 12 Inner Bay, three East Bay, and one Outer Bay                 other sediments (extreme enrichment in PAH and PCB,
                  locations. Nine of the 10 highest locations are in the Inner             respectively). These samples were excluded from the PCA
                  Bay region, including the eight highest stations. Lowest                 analysis.
                  metal concentrations occur in the Cape Small region.                         PC 2 (12.3 % of the total variance) and PC 3 (6.1 % of
                  Eleven stations are ranked in the highest 25 % on both the               the total variance) are related to the composition of organic
                  inorganic and organic contaminat rankings (Figure 6).                   and inorganic contaminants in the sediments. Since
                  They are almost exclusively Inner Bay locations, i.e., 9 of              principal components are orthogonal, the processes gov-
                  11.                                                                      erning PC 2 and PC 3 are independent of PC 1. Hance,
                     Principal Components Analysis. A total of four                        the information contained in these principal components
                  significant principal components (PC) were extracted from                is more representative of contaminant sources in the
                  the Casco Bay data. PC 1 accounts for 48.9 % of the total                sediments and is not related to absolute concentration&
                  variance. The loadings for this PC show the sand content                     PC 2 is correlated positively with the Fe and saturated,
                  of the sediments inversely correlated with all other                     hydrocarbon content of the sediments (Figure 8). This
                  measured variables. PC 1 is inversely correlated with sand               most likely reflects a detrital component enriched in plant
                  content and positively correlated with the TOC content                   wax n-alkanes and inorganic clastics derived from con-
                  of the sediments (Figure 7). This principal component                    tinental erosion (8-10). A loadings cross-plot for PC 2
                  reflects differences in the concentration of the targeted                versus PC 3 (Figure 9) shows that, although all n-alkanes
                  analytes due to variations in sediment texture. This                     are positively loaded in PC 2, C23,C25,C27 adn C29 n-alkanes
                  finding is more significant than might appear at first                   have the highest loadings, consistent with this interpretation
                  consideration, as it implies that regional differences in                Figure 9 also shows that nearly all the aromatice


			8 Environ. Sci. Technol., Vol. 28, No. 1,1994
	
														29                                                           








































                  consideration, an it implies that regional differences in                tation. Figure 9 also shows that nearly all the aromatic
                                            29
 






                         Tale 2. Casoo Bay Ratuary Program Site Rankings Based on Organic Contaminant Data, I"I (Vpb dry wt surrogate


                                               tow           total           total            total           total         total         total         total           total
                                               PAHs         PAH           chlordane        chlordane          DDT9          DDT           PCBs          PCB           organic
                            station no.        (ppb)       ranking           (ppb)           ranking          (ppb)       ranking         (ppb)       ranking        ranking

                              CS-1                 93          2             0.01                 1            0.01           1             0.6            2                6
                              CS-7                 16          1             0.02                 3            0.02           2             0.4            1                7
                              CS-3              515            6             0.02                 2            0.10           4             2.0            5             17
                              WB-3              421            4             0.07                 4            0.18           6             2.6            6             19
                              SW-8              445            5             0.16               12             0.47           8             1.6            3             28
                              8W-10             595            8             0.11                 6            0.30           6             4.5            9             29
                              CS-2              362            3             0.24               19             0.04           3             1.7            4             29
                              CS-6              672            9             0.15               10             0.50           9             3.8            7             35
                              SW-12            1094           16             0.23               16             0.72          10             5.5          11              53
                              WB-6              774           11             0.23               15             0.94          14             6.0          13              53
                              SW-9              734           10             0.23               17             0.73          11             &1           17              55
                              WB-2              146           22             0.16               11             1.01          15             7.2          14              62
                              SW-5              oil           13             0.15                 9            1.63          26             7.3          16              64
                              WB-8             1112           is             0.11                 5            1.52          25             8.4          is              66
                              SW-7              807           12             0.25               20             1.70          29             5.2          10              71
                              SW-13             961           14             0.19               14             1.23          21             9.8          23              72
                              CS-6              546            7             1.32               53             0.33           7             3.9            8             75
                              WB-7             1329           20             0.12                 7            1.36          23            10.2          25              75
                              OB-1             1433           21             0.41               27             1.09          is             7.2          15              81
                              OB-11            1312           19             0.24               is             1.11          19            11.6          28              84
                              OB-7             1650           so             0.45               30             1.03          16             5.5          12              so
                              SW-14            1069           15             0.25               21             1.94          34             9.1          21              91
                              EB-1             2230           37             0.60               35             0.86          13             9.0          20             105
                              EB-2             2875           45             0.57               33             0.82          12             8.9          19             109
                              W'B-4            1496           24             0.56               31             1.83          31            11.5          27             113
                              SW-6             1526           26             0.30               23             2.29          41            10.0          24             114
                              WB-5             1102           17             0.57               32             1.91          33            14.1          34             116
                              EB-4             2791                          0.16               13             1.37          24            14.3          35             116
                              OB-4             1964           36             0.64               37             1.26          22             9.6          22             117
                              OB-6             1631           28             0.13                 8            2.33          43            18.8          42             121
                              OB-13            INS            29             0.85               42             1.69          28            11.5          26             125
                              OB-8             1865           33             0.39               25             1.72          30            17.4          39             127
                              EB-10            4545           65             0.43               28             1.12          20            13.5          31             134
                              WB-9             1901           34             0.33               24             2.28          40            16.3          as             136
                              WB-l             1490           23             0.91               43             2.42          45            11.8          29             140
                              OB-12            1696           31             0.74               39             2.00          35            14.4          36             141
                              SW-11            1501           25             0.98               46             3.10          49            13.9          32             152
                              OB-5             2964           48             0.60               34             1.65          27            18.9          43             152
                              IB-9             1946           35             0.78               41             3.56          50            13.4          30             156
                              EB-3             2939           46             1.06               47             2.26          39            14.0          33             165
                              IB-5             2545           40             0.96               45             2.40                        16.8          37             166
                              OB-9             2706           41             0.77               40             2.08          36            22.2          49             166
                              EB-8             3459           52             0.26               22             2.81          48            19.6          46             168
                              EB-5             2944           47             0.40               26             2.55          47            23.7          50             170
                              SW-15            7180           59             1.60               56             1.07          17            17.9          40             171
                              SW4              1530           27             1.12               48             3.93          54            19.1                         173
                              OB-2             1817           32             1.89               59             2.31          42            18.1          41             174
                              OB-10            2269           39             1.25               51             2.09          37            20.0          48             176
                              1"               3068           49             0.62               36             2.53          46            27.9          53             184
                              OB-15            4004           64             1.13               49             2.17          38            19.4          45             186
                              EB-8             2723           42             0.93               44             4."           57            19.9          47             190
                              CS-4             7454           61             0.71               38             1.89          32            40.0          59             190
                              OB-3             3727           63             0.43               29             4.12          55            30.7          64             191
                              M10              2737           43             1.13               60             3.69          51            27.9          52             196
                              EB-6             2233           38             1.72               57             3.86          52            35.7          57             204
                              E33-7            4872           W              1.30               52             3.86          53            23.9          51             212
                              M4               3273           51             1.39               54             7.63          59            31.8          65             219
                              M7               3109           50             1.84               58             C70           58            33.7          56             222
                              EB-9             7340           60             1.91               60             4.16          56            37.3          58             234
                              IB-2             6M             58             1.63               56             9.91          61            47.6          61             236
                              IB-3             5069           57             2.49               61             9.02          60            42.2          so             238
                              SW-1             20748          65             3.47               63            10.10          62            72.3          62             262
                              IB-1             9174           63             2.89               62            14.50          63            79.2          64             252
                              SW-3             7517           62             C91                65            20.42          65            77.1          63             255
                              9W-2             125M           64             3.98               64            16.81          64           48&0           66             257


                         hydrocarbons measured are loaded negatively in PC 2.                           in Casco Bay have different origins, which is generally
                         One exception is the alkylated chrysenes, which show a                         consistent with the known geochemistries of these cle
                         dight positive loading in PC 2. Thus, PC 2 can also be                         of compoun&
                         regarded a asaturate/aromatic hydrocarbon ratio. These                            PC 3 differentiates individual saturated and aromatic
                         reaft indicate that saturated and aromatic hydrocarbons                        hydrocarbons based on molecular weight (Figure 9). Most
                                                                                                  30                               Esw6oi.SaT*chrwL.VoL28,No.1.1W4 9





                      Table L Cameo Bay Estuary Program Site Rankin                  Based on Selected Metal Data. l"I Win dry wt)
                                                         Ag                     Cd                         Hg                     Pb                       Zn        total
                       station no. Ag (ug/g) ranking Cd (Ag/g) ranking Hg (Ag/g)                     rankin     Pb (Ag/g) ranking Zn GWg) ranking ranking
                          CS-7           0.05            1       0.069          5         <0.006           1        17.1          3           31           2          12
                          CS-3           0.06            1       0.053          3          0.008           1        17.6          4           35           4          13
                          CS-2           0.07            1       0.060          4          0.019           2        17.8          5           34           3          15
                          CS-1           0.05            1       0.071          6         <0.006           1        14.1          2           39           6          16
                          CS-5           0.09            3       0.036          1          0.031           3        20.0          6           38           5          is
                          CS-6           0.07            1       0.051          2          0.046           6        2D.8          9           46           9          27
                          Sw-8           0.09            3       0.150          14         0.019           2        20.5          7           34           3          29
                          SW-15          0.08            2       0.192          21         0.048           7        M6            1           28           1          32
                          SW-7           0.07            1       0.155          15         0.032           4        24.7          is          46           9          42
                          EB-4           0.10            4       0.076          7          0.058           10       23.3          11          59           11         43
                          EB-10          0.08            2       0.121          10         0.069           15       20.6          8           56           10         45
                          OB-11          0.10            4       0.168          17         0.049           8        25.5          14          43           a          51
                          EB-I           0.11            5       0.127          12         0.059           11       26.2          16          62           12         56
                          WB-3           0.11            5       0.258          28         0.031           3        20.5          7           69           14         57
                          EB-2           0.11            5       0.175          19         0.077           20       25.8          15          68           13         72
                          SW-5           0.12            6       0.245          27         0.062           13       27.5          20          40           7          73
                          OB-I           0.14            8       0.118          9          0.065           14       27.7          21          88           27         79
                          W]"            0.11            5       0.088          8          0.057           9        31.7          30          92           29         81
                          WB-8           0.13            7       0.293          30         0.077           20       26.8          17          68           13         87
                          SW-10          0.16            10      0.486          48         0.037           5        22.2          10          73           16         89
                          WB-7           0.11            5       0.312          32         0.071           17       27.1          18          80           20         92
                          SW-9           0.17            11      0.400          38         0.037           5        25.5          14          87           25         93
                          OB-15          0.16            10      0.155          15         0.102           28       29.3          24          75           17         94
                          SW-12          0.25            16      0.365          35         0.048           7        29.4          25          71           15         98
                          SW-4           0.19            12      0.213          24         0.097           27       32.0          32          35           4          99
                          SW-14          0.16            10      0.414          40         0.082           22       24.3          12          75           17         101
                          SW-13          0.15            9       0.125          11         0.073           18       31.5          28          101          36         102
                          OB-10          0.14            8       0.156          16         0.081           21       33.8          38          82           22         105
                          OB-2           0.12            6       0.133          13         0.058           10       37.7          49          92           29         107
                          OB-13          0.15            9       0.268          29         0.082           22       30.6          27          82           22         109
                          OB-8           0.14            8       0.176          20         0.087           24       35.7          43          76           18         113
                          SW-6           0.13            7       0.435          45         0.061           12       31.7          30          78           19         113
                          OB-5           0.15            9       0.200          .22        0.085           23       34.7          40          81           21         115
                          OB-4           0.17            11      0.226          25         0.104           29       33.1          36          75           17         118
                          WB-2           0.17            11      0.358          36         0.076           19       29.7          26          92           29         121
                          WB-1           0.15            9       0.430          42         0.087           24       28.4          22          93           30         127
                          OB-7           0.16            10      0.245          27         0.113           32       35.8          44          75           17         130
                          WB-4           0.17            11      0.444          46         0.082           22       28.6          23          94           31         133
                          WB-9           0.36            21      0.302          31         0.087           24       31.9          31          93           30         137
                          OB-9           0.17            11      0.174          is         0.113           32       38.3          51          91           28         140
                          CS-4           0.20            13      0.208          23         0.190           43       32.4          34          88           27         140
                          WB-5           0.15            9       0.529          52         0.069           16       27.4          19          140          45         141
                          sw-11          0.16            10      0.239          26         0.096           26       37.6          48          9.5          32         142
                          U315           0.20            13      0.325          33         0.094           25       38.1          50          84           23         144
                          EB-3           0.19            12      0.431          43         0.112           31       33.2          37          87           26         149
                          EB-9           0.19.           12      0.401          39         0.148           36       32.1          33          92           29         149
                          OB-12          0.19            12      0.434          44         0.118           33       35.1          41          92           29         159
                          OB-6           0.26            17      0.592          58         0.106           30       32.8          35          86           24         164
                          EB-7           0.20            13      0.608          59         0.153           37       31.6          29          100          36         173
                          OB-3           0.20            13      0.327          34         0.141           35       40.7          52          109          41         176
                          IB,10          0,23            14      0,501          50         0,170           39       36*0          41          98           34         1112
                          EB-8           0.23            14      0.720          so         0.181           42       U.1           39          97           33         188
                          UM             0.25            16      0.392          37         0.195           44       41.2          63          104          38         188
                          M8             0.24            15      0.573          56         0.168           38       35.3          42          104          38         189
                          EB-6           0.29            19      1.320          63         0.137           34       33.2          37          105          39         192
                          IB-9           0.23            14      0.557          63         0.173           40       36.2          46          106          40         193
                          EB-5           0.23            14      0.794          61         0.176           41       37.0          47          101          36         199
                          M-7            0.32            20      0.424          41         0.234           45       42.1          55          106          40         201
                          Sw-I           0.46            23      0.488          49         0.264           46       55.5          58          95           32         208
                          IB-4           0.27            111     0*171          55         0*274           49       41,5          54          102          37         213
                          M2             0.46            23      0.524          51         0.271           48       49.9          57          109          41         220
                          M-3            0.39            22      0.574          57         0.264           46       48.5          56          109          41
                          SW-2           0.67            24      0.478          47         0.392           50       70.3          60          117          43         224
                          IB-I           0.57            24      0.564          54         0.269           47       55.6          59          125                     228
                          SW-3           0.78            25      0.908          62         0.424           51       7&6           61          112          42         241


                       n-alkanes in the range Clo-C22 are positively loaded in PC                    carbons loaded negatively in PC 3 include most parent
                       3, as are the more highly alkylated (C2 and higher) two-                      two- and three-ring compowds, their methyl-substituted
                       and three-ring aromatics: naphthalenes, fluorenes, phenan-                    homologs, and most four- and five-ring aromatic com-
                       threnes, and dibenzothiophenes. Pristane, phytane, and                        pounds.
                       UCM hydrocarbons are also loaded positively in PC 3. In                             Together, the loadings for PC 2 and PC 3 discz@ate
                       contrast, n-allranes, in the range C2s-C34 along with Cm                      sources of organic and inorganic materials in the Casco
                       and C17 are loaded negatively in PC 3. Aromatic hydro-                        Bay sediments. Hydrocarbons loaded positively in PC 2

                       10 ErMw. SoL TechW., VoL 28, No. 1, IM                                  31





                                                             70*10'                                  70000'                                     69050'


                                                                                                                         .............

                                                                                                             -M.
                                                                                                               40
                                                                                                              A#                                        0
                      430
                                             -Nig
                      50
                                                                                                            05

                                                                                                                   ff
                                                                    .......... -x.
                                                            VA.
                                                .....................
                                    ....... ...........-
                                                                                   2       9
                                                                                                                                 04
                                                                       7
                                                                                                              7
                                                                                     West
                                                                                       Bay
                                                                                                                              East NP
                      43
                                                                                                                              Bay
                                                                                                                                                       59
                      45'                                                                                               3
                                                                         ............
                                                                                0                                                     10 Ir
                                                                                 72

                                                                                                                              4
                                                      7                                                         0
                                                                                                                 1     20         0
                                                        Inner                                                                           0
                                                         Bay     *5                        0
                                                                                                                     160            20     Cape
                               . . . . . . . . . .. . . . . . . . . . .                    10
                                                                                                                                      4M   Small
                                                       M
                                                                       f 0      V
                                                                               6
                                                 2                                                    Outer                    10                    430
                      430                                               0                                                      %
                                                                                                                                 00     5
                                                                        4             8    09          Bay
                                                                                5
                                                                                                                                           6 0
                                                                        3
                                                                                              2                                                  7
                                                                                                                                     01

                           ;j PCB--485

                                                          .........................


                                                                                                                                                     430
                      43
                                                                                                                                                     35'




                                                                                                                                 0 Shallow Water
                                                                                                                                   Sarroes (SM

                                                             70010'                                   70000'                                     69050'

                      Pip" IL Localion of the 25 % high orgark (0) and kwgaric (12) mventrad" In w*nerft "M caw Bay.

                                                                               5              22M
                                                                              .-4




                                      loco
                                         %                                                    SM                                   00


                                                                                                                                 0
                                         13                                                   2=                              go

                                             cc
                          4-                 a
                          40        .0        0          10         20       30                 @D       -is     _;0                                 ;0

                                         fthwipid C-wo-" I MCI)                                                 P"nfAPM CD*4--" 2 (PC2)
                      rip" 7. RsbtbiM     betwom PC 1. TOC (%), and wid corderd            FW9 S.   PAftdons* betwom PC 2. Fe coderi! (% L and ssbNated
                      for Qksoo Say so&. w. .                                              all0hatle hydrocarbons (Ppb) for Casco Bay sefto.
                      and negatively in PC 3 (lower right quadrant, Figure 9)              include Fe, NL Se, As, Cr, and percentage sflt and clay
                      include compounds of algal (Cis and C17) and higher plant            (Figure 9). These distributions represent terrigenous
                      (CV-C@j) origin (8-10). Other similarly loaded variables             detrital and autochthonous marine input& TOC is sim-

                                                                                       32                       EmIrm ScL Tedvwl.. VOL 28, No. 1. 1104 11







                                       025
                                                 Weathered                                                    Fresh Diesel (?)
                                                                                             C11
                                                 Petroleum
                                       0.2"D

                                                                                                CIO
                                                                             C]FLU                   R12
                                                                                    UCUr ja       F'S
                                       0.10                                                    me
                                                              UNAP     Mim                                     CIO
                                       0.05.
                                                                                            NO    CIO          CU
                                   C*                    COW                 TCHLOR                                C22  ON
                                       .0.00. ...-M  ---------- caw  ...... 04W .. ........     Ga .................. --------------------
                                   IL                                                                                    PM CM
                                       -0.06                                                                       US
                                                                      BW                                  CV
                                                       RAJO                                                          CM
                                                         ;rl'Hci                 PERYL  :
                                       -0.10                                                 C34
                                                                    AGEY
                                       -0.15.

                                       -0.20-    Pyrogenic                              FAMM         Terrigenous Detrital &
                                                                                        P"
                                               Hydrocarbons                                          Autochthonous Marine
                                       -0.25 i         I          I          I                               I          1          1
                                           -0.20      -0.15     -0.10     -0-05       0.00        0.05       0.10      0.15


                                                                                      PC2
                     F*" 9. Pabft*No betwom PC2 and PC3 for PCA of Casco Bay conftn*aM data.
                     ilarly loaded, suggesting that biogenic materials are an           itive scores for PC 2, negative scores for PC 3) are found
                     important contributor to the organic richness of the               in the upper Fast Bay (EB-3, -5, -6, -7, and -8), and also
                     sediments (17). Hydrocarbons loaded negatively in both             at Outer Bay sites OB-1 and OB-12 and Inner Bay site
                     PC 2 and PC 3 (lower left quadrant, Figure 9) consist              IB-9. In contrast, the lower East Bay (EB-1, -2,4,-9, and
                     primarily of four- and rive-ring aromatics that are gen-           -10), as well as Outer Bay site OB-15 and shallow water
                     erated from both natural and anthropogenic combustion              site SW-15, contains a greater component originating from
                     processes. A combustion origin for these hydrocarbons is           pyrogertic sources (negative scores for PC 2 and PC 3).
                     also supported by the covariance of the parent two- and            Site CS-4 in Cape Small exhibits a composition simila to
                     three-ring aromatics which are structurally stable at high         the lower East Bay sites. These distributions are aignif-
                     temperatures (11-14). The departure of the alkylated               icant in that the sites that are simila in composition are
                     chrysenes from this trend suggests either a biogenic source        geographicaRy clustered. This suggests subtle differences
                     for these compounds or possibly some interference in their         in the principal sources of hydrocarbons in the upper and
                     analysis from biogenic material. Hydrocarbons loaded               lower East Bay.
                     negatively in PC 2 and positively in PC 3 (upper left                Sites characterized by inputs of weathered petroleum
                     quadrant, Figure 9) include two- and three-ring aromatics          (negative scores for PC 2, positive scores for PC 3) include
                     contsinin a C2 or greater alkylation. These compounds              the Inner Bay and shallow water sites nearest the city of
                     are the most abundant aromatic hydrocarbons in petro-              Portland (IB-1 and -2 and SWA 4, and -5). This is
                     leum and petroleum byproducts. Pristane and UCM are                probably the result of chronic inputs from runoffand point
                     similarly loaded, suggesting a weathered petroleum origin          sources associated with urban activities. Surprisingly,
                     (18,19). The source represented by the hydrocarbons that           however, the sandy sediments from Cape Small (CS-1, -2,
                     are loaded positively in both PC 2 and PC 3 (upper right           -3, -5, -7, and, to a lesser extent CS-6) have contaminant
                     quadrant, Figure 9) is equivocal. These consist primarily          compositions that are nearly identical to site E13-1. This
                     of n-alkanes in the range CIO-C22, which might represent           is illustrated in the scores cros&plot in Figure 10, where
                     a relatively unweathered petroleum product, i.e., diesel           the majority of Cape Small sites plot intermediate between
                     fuel. Alternatively, the covariance of these hydrocarbons          the lower East Bay and shallow water sites SW-3 and SW-4
                     with the metals Pb, Ag, and Hg and total DDTs and BHC              from the Inner Bay. This likely reflects aromatic hydro-
                     concentrations (Figure 9) suggest possible inputs from             carbon inputs from both pyrogenic and petroleum sources
                     runoff associated with either agricultural or industrial           at these locations and suggests that, despite significantly
                     activities. Principal component 4 (5.4 % of the total              lower concentrations, the assemblage of contaminants in
                     variance) is characterized by high positive loadings for           Cape Small sediments is simila to those at some con-
                     most of the chlorinated hydrocarbons analyzed and is lea           taminated Inner Bay sitea. Sites showing a relative
                     straightforward to interpret. It should be noted that the          enrichment in CIO-C= n-alkanes (positive scores for PC
                     organochlorine compounds are generally low and near the            2 and PC 3) include nearly all the West Bay sites and
                     method detection limit, thus indicating a relatively"noiW          shallow water sites SW-9, -10, -11, and -13 within the Went
                     data set                                                           Bay. Several nearby sites also exhibit a odmilsk compo-
                      Based on these interpretations, the distribution of               sition. These include Outer Bay site OB-13 and Inner
                     samples in a scores cross-plot of PC 2 versus PC 3 (Figure         Bay sites EB-6 and IB-10. Thus, although the origin of
                        can be used to assess the regional influence of a variety       this compositional feature is uncertain, it appears to
                     ofsources. Sediments exhibiting a predominantly biogenic           manifest itself over a limited portion of Casco Bay,
                     10

                     influence from detrital and autochthonous sources (pos-            suggestinga localized source. Several Outer Bayadm (OB-
                     12 BrAw " T*OvwL. VOL 26, No. 1. IN4                           33







                                                                    Weathered                                                                    Fresh Diesel (?)
                                                                    Petroleum



                                                 10

                                                   5                                                                                          
                                                                                                                                                 


                                                   
                                                        0    - ------------------------------ -------------- ----------      ------       ... ..........................
                                                  -5 

                                                                                                                   
                                                  -10                         


                                                                                                                                    Terrigenous Detrital &
                                                                    Pyrogenic                                                       Autochthonous Marine
                                                                  Hydrocarbons                                                                                      
                                                         -20	-15		-10		-5	0	5		10
                                                                                                                                                                    


                                                                                                   Principal Component 2
                              Figure 10. Suggested model for determining the source of hydrocarbons  and trace Metals In Casco Bay sediments.

                              Table 4. Comparison of ER-L, ER-M, Apparent Effects Thresholds, and Washington State Sediment Quality Criteria
                              Concentrations for Selected Chemicals in Sediments and Values Measured In Casco Bay (after Long and Morgan, 1990,
                              Washington State Dept. of Ecology Sediment Management Standards, Chapter 173-204 WAC)
                                                                                                                                    Casco Bay regional
                              chemical                                 deg of                       Inner Bay          West Bay            East Bay          Cape Small         Outer Bay
                              analyte    ER-L*     ER-M*       AET* confidence*	 WSSQC# 	min        max      min       max       min       max       min      max     min       max
                                                                                            Trace Elements (ppm dry wt)
                              arsenic       33        85        50  L/M                5.7      1.62      16.00    4.76      19.60     3.20      19.60     5.03   13.70      5.03      20.50
                              cadmium       5         9         5   H/H                5.1      0.213     0.908    0.088     0.529     0.076     1.320     0.036    0.208    0.036     0.592
                              chromium      80     145          NA4,M/M              26.0       31.00     91.00    35.00     100.00  29.00     105.00    37.00    93.00      43.00     93.00
                              copper        70     390          300 H/H              390        7.92      48.40    6.98      26.20     5.59      27.90     2.52   21.60      6.94      26.20
                              lead          35     110          300 M/H              450        27.50     75.60    20.50     37.60   13.60       37.00   14.10    32.40      25.50     40.70
                              mercury       0.15      1.3       1   M/H                0.41     0.061     0.424    0.019     0.096     0.048     0.181   <0.010     0.190    0.049     0.141
                              nickel        30        50        NSD M/M             NA         7.81      37.80    9.67      38.60       8.36        38.40   12.90    30.60      14.50     39.80
                              silver         1         2.2       1.7 M/M               6.1      0.12      0.78     0.07      0.36      0.08      0.29      <0.07     0.20     0.10      0.26
                              zinc        120      270          160 H/H              410        36.00   125.00     34.00     140.00  28.00     105.00    31.00    KOO        43.00   109.00
                               a ER-L, effects range-low. b ER-M, effects range-median. c AET, apparent effects threshold. d L,low; M, medium; H, high. e WSSQC,
                              Washington State Sediment Quality Criteria, calculated ppb dry wt based on 2% TOC. / ppm dry weight. f NSD, not sufficient data h NA,
                              not available.


                              3, -5, -8, -9, and -11) exhibit a composition intermediate                        low to high. A 10th and 50th percentile were then
                              between the Inner Bay sites characterized by weathered                            determined. Those were designated "effects range low"
                              petroleum and the West Bay sites enriched in lower                                and "effects range median* (ER-L and ER-M). The
                              molecular weight n-alkanes.                                                       Washington State Sediment Quality Criteria, the summary
                               Potential for Biological Effects. Biological effects                             of data from Long and Morgan (16), and the Casco Bay
                              or sediment quality were not directly measured in this                            results are compared in Tables 4-6.
                              study. However, the concentrations of most organic                                   The total PAH concentrations present in Inner Bay
                              contaminants detected are below the concentration levels                          sediments are above the PAH concentratiorm thought to
                              that are believed to evoke toxic responses in marine benthic                      produce toxic responses in marine benthic organisms, i.e.,
                              organisms (Tables 4-6). Long and Morgan (9) conducted                             total PAH >35 000 ppb (Table 4). Bioavailability and
                              an extensive review of articles that provide both concen-                         not necessarily absolute concentration are compared and
                              trations of contaminants in sediments and observed                                also a factor in determining whether a contaminant evokes
                              biological effects. Six different approaches used in these                        a biological response. For example, the mode of occurrence
                              studies were briefly described and reviewed. It was                               of PAH has been shown to vary widely depending on the
                              concluded that each approach had strengths and weak-                              original source (19). Coal or soot-associated combustion-
                              nesses, i.e., there is no perfect method for determining                           derived PAHs are often tightly bound or occur in the
                              specific threshold concentrations for contaminants in                             interiors of particles. This mode of occurrence renders
                              sediment. They therefore derive consensus values by                               these PAHs largely inert as far as biological effects. In
                              considering data from all of the studies reviewed. Sed-                            contrast, liquid hydrocarbons such as oil or creosote contain
                              iment concentrations shown by the studies to cause                                PAHs that are readily available to organisms and would
                              biological effects, and judged to be valid, were ranked from                       be expected to induce toxicological effects. A majority of
                                                                                                          34                               Environ. Sci. TechnoL., Vol. 28, No. 1, 1994 13







                         Table 5. Comparison of ER-L, ER-M, Apparent Effects Thresholds, and Washington State Sediment Quality Criteria
                         Concentrations for Selected Chemicals In Sediments and Values Measured in Casco Bay (after Long and Morgan 1990;
                         Washington State Dept of Ecology Sediment Management Standards, Chapter 173-204 WAC)
                                                                                                                           Casco Bay Regions
                           chemical                                   deg of                  Inner Bay       West Bay         East Bay        Cape Small        Outer Bay
                           analyte      ER-La  ER-Mb     AETc    confidenced    WSSQC         min  max        min     max        min   max     min       max      min    max
                                                                                 Polychlorinated Biphenyle (ppb)
                         total PCBs     50     400       370     M/M               240        7.31 484.97     1.58   16.32     8.89   37.30    0.44     40.02    5.50   30.67
                                                                                      DDT and Metabolites (ppb)
                         DDT            1      7         6       L/L                          0.49   4.28 <0.20        0.96     0.40    2.01    <0.20    0.86       0.47   1.52
                         DDD            2      20        NSD     M/L                          0.67 15.09      0.08    1.49     0.31    1.98   <0.07    0.62     0.34   2.04
                         DDE            2      15        NSD     L/L                            0.18   3.84   <0.06     1.14     0.07    0.48   <0.06    0.40     0.06   0.63
                         total DDT      3      350       NA      M/M                          1.63   20.42  <0.20     3.10     0.82    4.16    <0.20    1.89      1.03   4.12
                                                                                      Other Pesticides (ppb)
                         lindane        NA     NA        NSD     NA                        <0.07     0.48   <0.07     0.22  <0.07      0.35   <0.07    0.11     <0.07  0.34
                         chlordane      0.5    6         2       L/L                        0.15   4.91     0.07    0.98     0.16    1.91   <0.07    1.32     0.13   1.89
                         heptachlor     NA     NA        NSD     NA                         0.08   0.13   <0.04     0.05  <0.04      0.13   <0.04    <0.04    <0.04  0.04
                         dieldrin       0.02   8         NA      L/L                       <0.16     0.94   <0.16    <0.16  <0.16      0.43   <0.16    2.46     <0.16  1.40
                         aldrin         NA     NA        NSD     NA                        <0.28     <0.28  <0.28    <0.28  <0.28    <0.28    <0.28    <0.28    <0.28  <0.28
                         andrin         0.02   45        NSD     L/L                       <0.06     0.84   <0.06     0.21  <0.06      0.17   <0.06    <0.06    <0.06  0.65
				 mirex          NA     NA        NSD     NA                        <0.04     0.29   <0.04     0.08  <0.04      0.49   <0.04    0.66     <0.04  0.16
                             ER-L, effects range-low.      ER-M, effects range-median. c AET, apparent effects threshold. L, low, M, medium; H, high.  WSSQC,
                         Washington State Sediment Quality Criteria calculated ppb dry wt based on 2% TOC. / ppm dry weight  NSD, not sufficient data.  NA,
                         not available.


                         Table 6. Comparison of ER-L, ER-M, Apparent Effects Thresholds, and Washington State Sediment Quality Criteria
                         Concentrations for Selected Chemicals in Sediments and Values Measured in Casco Bay (after Long and Morgan. 1990;
                         Washington State Dept. of Ecology Sediment Management Standards, Chapter 173-204 WAC)
                                                                                                                                   Casco Bay regions
                                   chemical                                           deg of                Inner Bay 		West Bay 	East Bay            Cape Small   Outer Bay
                                    analyte            ER-Le ER-Mb 	AETc 		confidenced WSSQC 	min 	max	  min     max	min	max		 min	  max     min  max
                                                            Polynuclear Aromatic Hydrocarbons (ppb dry wt surrogated corrected)
                         acenaphthene                  150     650      150      L/L              320        2     81      <1      3       2    19   		 <1      13       2    6
                         anthracene                    85      960      300      L/M             4400        6    255       3     15       8   107           <1      99	     14   50
                         benz(a)anthracene             230     1600     550      L/M             2200       30    655      12     56       34  481      	  1     360      48  173
                         benzo[a]pyrene                400     2500     700      M/M             1980       43    741      17    100       50  498            1     433      62  209
                         benzo[e]pyrene                NA      NA       NSD      NA                         37    514      14     74       37  276            1     271      48  140
                         biphenyl                      NA      NA       NSD      NA                          3     29      <2      7       4   12            <2      10       4   12
                         chrysene                      400     2800     900      M/M             2200       44    766      19     74       47  530            1     398      53  192
                         dibenz[a,h]anthracene          80      280     100      M/M              240        3    105       3     41       7   58            <0      64      11   73
                         2,6-dimethyinaphthylene       NA      NA       NSD      NA                          4    130       1      9       3   28            <1      17       5   14
                         fluoranthene                  600     3600     1000     H/H             3200       90   1444      34    144       82  639            2     522     118  304
                         fluorene                      35      640      350      L/L              460        4    201       1      7       4   96            <1      27       6   16
                         1-methylnaphthalene           NA      NA       NSD      NA                          3     81       1      7       3   31            <1      20       5   11
                         2-methylphenanthrene          65      670      300      L/M              760        5     95       2     11       5   37            <1      34       8   17
                         1-methylphenanthrene          NA      NA       NSD      NA                         10    311       5     14       0   68            <1      49       8   33
                         naphthalene                   340     2100     500      M/H             7400        8    135       2     14       7   46            <2      41      12   26
                         Perylene                      NA      NA       NSD      NA                         17    216       9     56       31  110           <4      94      21   77
                         Phenanthrene                  225     1390     260      M/M             2000       42   1036      17     71       41  550            1     269      57  160
                         Pyrene                        350     2200     1000     M/M            20000       82   1552      31    137       78  500            2     562    1127  302
                         2,3,5-trimethylnaphthalene    NA      NA       NSD      NA                          3    187       1      4       2   34            <1       9       3    6
                         totel PAH                     4000    35000    22000    L/L                       911  20748     421   1901     1059  734O          16    7454    1312  4004
                           a ER-L, effects range-low. b ER-M, effects range-median.  cAET, apparent effects threshold. d L, low, M, medium; H, high. e WSSQC,
                         Washington State Sediment Quality Criteria. calculated ppb dry wt based on 2% TOC. f ppm dry weight. g NSD, not sufficient data. h NA.
                         not available.

                         the PAHs in this study are combustion related and thus                      biological response have been used, resulting in a large
                         may be in a sequestered form that significantly reduces                     and confusing literature. Thomas (20) briefly describes
                         their toxicity.                                                             eight different approaches to setting toxicity criteria for
                           Long and Morgan (16) estimated that median concen-                        sediments, but no actual data are presented. Pavlov (21)
                         trations of total PCB above 400 ppb dry wt elicits a toxic                  compared results from one of these approaches, the
                         response in most benthic organisms. For this study, only                    equilibrium partitioning approach, to results from other
                         one site (SW-2) is above this threshold. The DDT                            commonly used methods. He shows that the concentration
                         concentrations are low compared to concentrations known                     of a given metal needed to elicit a biological response, as
                         to cause a toxic response in most benthic organisms (16).                    determined by equilibrium partitioning and other meth-
                         Chlordane concentrations are "low" based on the definition                ods, does not vary widely (except for Hg). The threshold
                         Of O'Connor (15) and should pose little or no threat of                     concentrations for toxicity are much higher than those
                         toxic biological effects (16).                                              found in Casco Bay sediment.
                           A number of different approaches to determining the                         None of the metal concentrations in the Casco Bay
                         trace metal concentrations in sediments which lead to a                     sediments are as high as Long and Morgan's (16) ER-M,
                         
				14 Environ. SoL TechnoL. Vol. 28, No. 1. 1994                                 35





                          and only a few are as high as the ER-Le. For example,                         (2) Wade, T. L.; Atlas, E. L.; Brooks, J. M.; Kennicutt, M. C.,
                          Casco Bay chromium concentrations are as high as 105                              11; Fox, R. G; Sericano, J.; Garcia-Romero, B.; DeFreitas,
                          ppm, whereas the ER-L is 80 ppm. Many uncontaminated                              D. Estuaries 1998, 11, 171-179.
                          sediments from other parts of the world, however, contain                     (3) Kennicutt, M. C., 11; Wade, T. L.; Presley, B. J. Assessment
                                                                                                            of Sediment Contamination in Casco Bay-, Interpretive
                          chrorniurn concentrations higher than 105 ppm, and it is                          Report prepared for Casco Bay Estuary Project; GERG
                          unlikelythat chromium in Casco Bay sediment would cause                           Technical Report92-157; US. EPA. Washington, DC, 1992;
                          a biological effect. The same can be said for nickel and                          113 pp.
                          zinc, where Casco Bay concentrations are as high as 40                        (4) Folk, R. L Petrology of sedimentary rocks; Hemphill
                          and 140 ppm compared to ER-Ls of 30 and 120 ppm,                                  Publishing Co.: Austin, TX, 1974; 184 pp.
                          respectively. A few mercury concentrations in Casco Bay                       (5) Brooks, J. M.; Wade, T. L; Atlas, K L; Kennicutt, M. C.,
                          are also higher than the ER-L but are much lower than                             H, Presley, B. J.; Fay,& FL;Powell, K N.; Wolff, G. Analyses
                          those of highly contaminated sediments from Hudson-                               of bivalves and sediments for organic chemicals and trace
                          Raritan, Long Island Sound, Boston Harbor and elsewhere                           elements from Gulf of Mexico estuaries; Second annual
                                                                                                            report for NOAA's National Status and Trends Program;
                          (15). It is unlikely that mercury in Casco Bay sediment                           Contract 50-DGNC-5-00262.
                          is causing an effect on marine organisms. As with PAH,                        (6) Wold, S. Technometric8 1978, 20, 397-406.
                          bioavailability is an issue in determining trace metal                        (7) Joliffe, J. Principal Components Analysis; Springer-Ver-
                          toxicity.                                                                         1W. Berlin, 1986.
                                                                                                        (8) Brassell, S. C.; Eglinton, G.; Maxwell, J. &; Philp, R. P. In
                          Conclusions                                                                       Aquatic Pollutants, Transformations and Biological Ef-
                                                                                                            fects; Huntzinger, 0., van Lelyveld, L. H., Zoetman, B. C.
                             Detailed,    high-quality assured analysis of a broad                          J., Eds.; Pergamon Press: Oxford, 1978; pp 69-N.
                          spectrum of contaminants can be utilized to understand                        (9) Clark, R., Jr.; Blumer, M. Limnol. Oceanogr. 1967,12,79--
                          the dynamics of pollutants in coastal environments. The                           87.
                          potential processes implicated in releasing these contam-                    (10) Philp, F_ P. Fossil Fuel Biomarkers: Application and
                          inants to the marine environment can be identified and                            Spectra. Methods in Geochemi8try and Geophysics;
                          their relative importance can be estimated. Statistical                           Elsevier. New York, 1985; Vol. 23.
                          analysis of contaminant concentrations can be used to                        (11) ffites, K A.; La Flamme, & E.; Windsor, J. G., Jr.;
                          identify geographically consistent contaminant profiles                           Farrington, J. W.; Deuser, W. G. Geochim. Co8mochim. Acta
                                                                                                            1980,44,873-878.
                          and suggest the source ofthese pollutants. Thisapproach                      (12) Wakeham, S. G.; Schaffner, C.; Giger, W. Geochim. C08-
                          was applied to Casco Bay, ME.                                                     mochim. Acta 1980, 44, 403-413.
                             Anthropogenic contaminants are widespread throughout                      (13) Wakeham, S. G.; Schaffner, C.; Giger, W. Geochim. Coo-
                          Casco Bay, but in most cases occur at exceedingly low                             mochim. Acta 1980b, 44, 415-429.
                          concentrations. The focus ofcontamination is in the Inner                    (14) La Flamme, & E.; Mtes, K A. Geochim. Cosmochim. Acta
                          Bay region directly associated with the densest population                        1978, 42, 2&9-303.
                          centers and industrialization. Multiple processes add                        (15) O'Connor, T. P. Coastal Environmental Quality in the
                          contaminants to Casco Bay, and these chemicals have                               United States, 1990. Chemical Contamination in Sediment
                                                                                                            and Tissues; A Special NOAA 20th Anniversary Report-
                          accumulated in bay sediments. Localized accumulations                             Coastal and Estuarine Assessment Branch, Ocean Assess-
                          of various chemicals do occur, but even these areas are                           ments Division, Office of Oceanography and Marine As-
                          mostly below levels suspected of evoking toxic biological                         sessment, National Ocean Service, National Oceanic and
                          responses. In order to more specifically assign the sources                       Atmospheric Administration: Rockville, MD, 1990; 34 pp.
                          of the observed contaminants, intense localized sampling                     (16) Long, E. &; Morgan, L. G. The potential for biological
                          and analysis of effluents and runoff patterns would be                            effects of sediment-sorbed contaminants tested in the
                          needed. To determine sediment quality, bioassays of                               National Status and Trends Program; NOAA Technical
                                                                                                            Memorandum NOS OMA 52; NOAA Office of Oceanog-
                          sediments at suspect sites should be conducted to directly                        raphy and Marine Assessment, Ocean Assessments Divi-
                          assess the potential for biological impacts.                                      sion: Seattle, WA, 1990; 173 pp and appendices.
                                                                                                       (17) Boehm, P. D.; Requejo, AL G. Estuarine, Coastal ShelfSci.
                          Acknowledgments                                                                   1986, 23, 29-58.
                                                                                                       (18) Jones, D. M.; Douglas, A. G.; Parkes, F_ J.; Taylor, J.; Giger,
                             This project has been funded wholly or in part by the                          W.; Schaffner, C. The recognition ofbiodegraded petroleum-
                          United States Environmental Protection Agency as part                             derived aromatic hydrocarbons in recent sediments. Mar.
                          of the Casco Bay Estuary Project underAassistance                                 Pollut. Bull. 1983,14,103-108.
                          Agreement CE-001553-01 to the New England Interstate                         (19) McFlroy,A. E.; Farrington, J. W.;TeaLJ. M. InMetabolism
                          Water Pollution Control Commission. The contents of                               of Polycyclic Aromatic Hydrocarbons; VaranasL U., Ed.;
                          this document do not necessarily reflect the views and                            CRC Press. Boca Raton, FL, 1989; pp 1-39.
                          policiesofthe Environmental Protection Agency, nor does                      (20) Thomas, N. In Water Quality Standards for the 218t
                                                                                                            Century, Proceedings of a National Conference, Dallas,
                          mention oftrade narnes or commercial products constitute                          TX, March 1-3,1989, US. EPA Office of Water. Wash-
                          endorsement or recommendation for use. We would also                              ington, DC, 1989.
                          like to thank the National Oceanic and Atmospheric                           (21) Pavlov, S. P. In Fate and Effects of Sediment-Bound
                          Administration (Contract 50-DGNC-5-00262), National                               Chemicals in Aquatic Systems, Dickson, K. L, Mak, A. W.,
                          Status and Trends Program, for providing baseline data                            Brungs, W. A., Eds.; Pergamon Press:- New York, 1987; pp
                          for comparison.                                                                   388-342.

                          Literature Cited                                                             Received for review November 16, 1992. Revised manuscript
                                                                                                       received June 29, 1993. Accepted October 4, 1993.e
                           (1) Larsen, P. F.; Gadbois, D. F.; Johnson, A. C.; Doggett, L
                                F. Doggett. Bull. Environ. Contamin. Toxicol. 1993,30,530-               0 Abfftmct published in Advance ACS Abstracts, November 15,
                                5M.                                                                    199&
                                                                                                 36                            Emiw. ScL TedvioL, Vol. 28. No. 1. 1994 If














                          Reprint 3


            Polynuclear Aromatic Hydrocarbon
         Contaminants in Oysters from the Gulf of
                     Mexico (1986-1990)

          Thomas J. Jackson, Terry L. Wade,, Thomas
         J. McDonald, Dan L. Wilkinson, and James M.
                           Brooks
















                              37





                Environmental Pollution 93 (1994) 291-298




                                 POLYNUCLEAR AROMATIC HYDROCARBON
                                    CONTAMINANTS IN OYSTERS FROM THE
                                                 GULF OF MEXICO (1986--1990)


                            Thomas J. Jackson, Terry L. Wade, Thomas J. McDonald, Dan L. Wilkinson
                                                                  & James M. Brooks
                                 Geochemical and Environmental Research Group, College of Geosciences and Maritime Studies,
                                                  Texas A & M University, College Station, Texas 77845, USA

                                                      (Received I July 1992; accepted 25 September 1992)

                Abstract                                                          equilibrium concentration for trace organic contami-
                Polynuclear aromatic hydrocarbon (PAH) contaminant                nants such as PAHs within approximately one month
                concentrations in 870 composite oyster samples ftorn              (Sericano & Wade, unpublished data).
                coastal and estuarine areas of the Gulf of Mexico ana-               To assess the spatial and temporal variation of con-
                lyzed as part of National Oceanographic and Atmo-                 taminant levels of coastal and estuarine environments,
                spheric Administration's (NOAA's) National Status and             the National Oceanic and Atmospheric Administration
                Trends (NS&T) Mussel Watch Program exhibit a log-                 (NOAA) instituted the National Status and Trends
                normal distribution. There are two major populations in           (NS&T) Mussel Watch Program under its Program for
                the data. The cumulative ftequency function was used to           Marine Environmental Quality (O'Connor, 1990). The
                deconvolute the data distribution into two probability            sample sites were selected to characterize the overall
                density functions and calculate summary statistics for            concentration of contaminants in coastal and estuarine
                each population. The first population consists of sites           ecosystems away from known point-sources of contam-
                with lower PAH concentration probably due to back-                ination.
                ground contamination (ie. stormwater runoff, atmo-                   The focus of this paper is to examine the distribution
                spheric deposition). The second population are sites with         of the PAH contaminant concentrations in oysters
                higher concentrations of PAHs associated with local               collected from the Gulf of Mexico as part of NOAA's
                point sources of PAH input (ie. small oil spills, etc.).          NS&T Mussel Watch Program, and determine the
                The temporal pattern for the mean concentration of the            environmental factors controlling the concentration of
                populations from the Gulf of Mexico is consistent with            PAHs.
                large-scale climatic factors such as the El Nifto cycles
                which affect the precipitation regime.                            METHODS
                INTRODUCTION                                                      Sample   Collection
                                                                                  Oysters (Crassostrea virginica) were collected from
                Oysters and other bivalve molluscs have been used for             three stations at each site during the winter of each
                monitoring contaminants in the environment (Farring-              year (1986-1990). The number of sites per year varied
                ton et al., 1983). Oysters are sentinel organisms which           from 48 to 68. In some years not all sites had three
                concentrate contaminants from the marine environ-                 stations due to the low abundance of oysters at a specific
                ment, yet do not readily metabolize contaminants such             site (Table 1). Sample sites give coverage of the Gulf of
                as polynuclear aromatic hydrocarbons (PAHs) (Far-                 Mexico coastal and estuarine areas from southem-most
                rington & Quinn, 1973). PAHs enter the near-coastal               Texas to southern-most Florida (Fig. 1). Individual
                environment through a number of mechanisms (e.g.                  stations at each site are generally from 100 to 1000 m
                runoff, discharge of industrial waste or sewage, natural          apart. An analysis at each station represents a com-
                or industrial combustion processes, natural oil seep-             posite of twenty individual oysters. Each year, the field
                ages, and spills of petroleum or petroleum products).             sampling returned to as many sites as possible. In some
                 The contaminants found in oysters reflect the current            instances it was necessary to relocate or abandon an
                contaminant burden of an ecosystem. The concentra-                Table 1. National Status and Trends Oysters Gulf of Mexico
                tion of a contaminant in an oyster is the difference                       Sampling Propmu-Summary of sampling
                between uptake and excretion of that contaminant.
                Galveston Bay oysters transplanted from a 'high' level                                     1986    1987   1988    1989   1990
                site to a 'low' level site, and vice versa, come to a new
                                                                                  Year                       I                     IV      V
                                                                                  Number of sites            49     48      65     62      68
                F.nviron. Pollui. 0269-7491194/$06.00 C 1993 Elsevier Science     Number of samples         142    144     195    186     203
                Publishers Ltd, England. Printed in Great Britain             38




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                                                                                          21    22
                                                                                                       N
                                                                                                      23                                                                         4'1

                                                                                                                                   0-64
                                                                Galveston
                      290                         3C.                                                    24     2m$  7  29   65
                                                           57
                                                     14

                      280                 C46
                                         54
                                       3


                      270

                                       52                                                         GJFoF AIDW
                      26*

                               NEX



                      250


                      240                                                                                                                                                                       0 Mile

                                                                                                                                                                                               0 KII,


                                       970        960        950         940         930        920        910         900        890         880        870         860        850         840
                                                                                                                                                                                                    4f

























                                                                       Fig. 1. Location of NS&T Mussel Watch Sites in the Gulf of Mexico (Sericano et al., 1990).





                                                   PAH contaminants in oysters ftom the Gutf of Mexico                                          293

               established oyster site due to lack of suitable sized                 Gas chromatography-mass spectrometry (GC-MS)
               bivalves (Wilkinson et al., 1991). The locations and                  PAHs were separated and quantified by GC-MS
               designator for the oyster sites are found in Wilkinson et             (HP5980-GC interfaced to a HP5970-MSD). The sam-
               al. (199 1), Sericano et al. (1990) and Wade el al. (1990).           ples were injected in the splitless mode on to a 30 in
                                                                                     XO-25 min (0-32 jAm film thickness) DB-5 fused silica
               Tissue extraction                                                     capillary column (J&W Scientific Inc.) at an initial tem-
               The tissue extraction process used was adapted from a                 perature of 60'C and temperature programmed at
               method developed by MacLeod et al. (1985). Approxi-                   120C/min to 300'C and held at the final temperature
               mately 15 g of wet tissue were used for the PAH                       for 6 min. The mass spectral data were acquired using
               analysis. After the addition of internal standards (surro-            selected ions for each of the PAH analytes. The
               gates) and 50 g of anhydrous Na2SO., the tissue was                   GC-MS was calibrated and linearity determined by
               extracted three times with dichloromethane using a                    injection of a standard containing all analytes at five
               tissuernizer. A 20 ml sample was removed from the total               concentrations ranging from 0.01 nglAl to I ng/tLl.
               solvent volume and concentrated to one ml for lipid                   Sample component concentrations were calculated
               percentage determination. The 280 ml of remaining                     from the average response factor for each analyte.
               solvent was concentrated to approximately 20 ml in a                  Analyte identifications were based on correct retention
               flat-bottomed flask equipped with a three-ball Synder                 time of the quantitation ion (molecular ion) for the
               column condenser. The tissue extract was then trans-                  specific analyte and confirmed by the ratio of quantita-
               ferred to a Kuderna-Danish tube heated in a water bath                tion ion to confirmation ion.
               (60'C) to concentrate the extract to a final volume of                  Calibration check samples were run with each set of
               2 ml. During concentration, the dichloromethane was                   samples (beginning, middle, and end), with no more
               exchanged for hexane.                                                 than 6 h between calibration checks. The calibration
                  The tissue extracts were fractionated by alumina: silica           check must maintain an average response factor within
               (80-100 mesh) open column chromatography. The                         101/6 for all analytes, with no one analyte greater than
               silica gel was activated at 170'C for 12 h and partially              ï¿½25% of the known concentration. A laboratory refer-
               deactivated with 3% distilled water (v/w). Twenty                     ence sample (oil spiked solution) was also analyzed
               grams of silica gel were slurry-packed in dichloro-                   with each set of samples to confirm GC-MS system
               methane over 10 g of alumina. Alumina was activated                   performance and calibration.
               at 400'C for 4 h and partially deactivated with 1%
               distilled water (v/w). The dichloromethane was replaced               RESULTS AND DISCUSSION
               with pentane by elution. The extract was then applied
               to the top of the column. The extract was sequentially                Oyster site variations
               eluted from the column with 50 n-d of pentane (aliphatic              During the first five years of this study a total of 870
               fraction) and 200 ml of I : I pentane: dichloromethane                composited oyster samples have been analyzed for
               (aromatic fraction). The aromatic fraction was further                PAHs. The tPAH (total NS&T PAHs) is the sum of the
               purified by HPLC to remove the lipids. The lipids were                eighteen aromatic hydrocarbon analytes, as measured in
               removed by size exclusion using dichloromethane as                    Year 1, with concentrations greater than 20 ng/g dry wt
               an isocratic mobile phase (7 ml/min) and two 22-5 x                   (Table 2); this was the reporting limit for Year I data
               250 min Phenogel 100 columns (Krahn et al., 1988).                    (Wade et al., 1988). The median PAH concentration at
               The purified aromatic fraction was collected from                     a site is used as a measure of the best indicator of the
               1.5 min    prior to the elution of 4,4'-dibromofluoro-                concentration. The median is a more stable (or resistant)
               biphenyl to 2 min after the elution of perylene. The
               retention  times of the two marker peaks were checked                 Table 2. National Status and Trends oysters polynuclear
               prior to  the beginning and at the end of a set of 10                                aromatic hydrocarbon analytes
               samples.   The purified aromatic fraction was concen-
               trated to I ml using a Kuderna-Danish tube heated in                                    Aromatic hydrocarbons
               a water bath at 60*C.                                                  Low molecular weight                 High molecular weight
                 Quality assurance for each set of ten samples in-
               cluded a procedural blank, matrix spike, duplicate, and               Biphenyl                              Fiuoranthene
               tissue standard reference material (NIST-SRM 1974)                    Naphthalene                           Pyrene
               which were carried through the entire analytical scheme.              1-methylnaphthalenc                   Benz(a)anthracene
               Internal standards (surrogates) were added to the sample              2-methylnaphthalene                   Chrysene
                                                                                     2,6-dimethylnaphthalene               Indeo[1,2,3-cd]pyrene'
               prior to extraction and were used for quantitation. The               1,6,7-trimethylnaphthalene'           Benzo(a)pyrene
               surrogates were dg-naphthalene, d,o-acenaphthene,                     Acenaphthene                          Benzo(e)pyrene
               d,o-phenanthrene, d12-chrysene, and d,2-perylene. Surro-              Acenaphthylene'                       Perylene
               gates were added al a concentration similar to that                   Fluorene                              Dibenz[a,h]anthracene
               expected for the analytes of interest. To monitor the                 Phenanthrene                          Benzo[g,hJ]perylene'
                                                                                     Anthraccne
               recovery of the surrogates, chromatography internal                   1-methylphenanthrene
               standards d,o-fluorene and d,2-benzo(a)pyrene were
               added just prior to GC-MS analysis.                             40    'Analytes not used in tPAH summation.





                            294                                                                 T J Jackson et al.


                                                                            Table 3. Total NS&T PAH concentration in oysters

                            No.     Sitc            Median concentration of tPAH              Bay group          No.     Site             Median concentration of tPAH             Bay group
                                  code                                                        median                     oDdc                                                         median
                                                 V        IV       III      II        I       (ng/g)                                  V       IV         111      11         1        (ng/g)
                                                 1990     1989   1988      1987     1986                                            1990      1989       1988    1987        1986
                                                 (ng/g) (ng/g)   (ng/g)  (ng/g) (ng/g)                                              (ng/g)    (ng/g)     (ng/g) (ng/g) (ng/g)

                            Texas                                                                                Louisiana-cont.
                              I   LMSB           22       20       30       20        25                          65     MRTP         212     310        1410     -          -    391 ï¿½ 582
                            52    LMPI           -        -      3380       -         -       30 ï¿½ 58             64     MRPL         403     330        695      -          -
                            78    LMAC           120      -        -        -         -                           31     BSSI         185       71       484      68         177  181 ï¿½ 134
                            53    CCBH           1530     -      1 600      -         -                           30     BSBG          45     202        213     118         265
                              2   CCNB           161      264      598     434        45      565 ï¿½ 725           32     LBMP          20       94        89      26         20    39 ï¿½ 59
                              3   CCIC           137      430      848      -       1 140                         62     LBNO          -        -         81      -          -
                            54    ABHI           -        -      1870       -         -
                                                                                                                 Mississippi
                              4   ABLR           20       20       20       21        20                          33     MSPC         103     300        175     319         99
                              5   CBCR           88       -        20       20        22      20 ï¿½ 1              34     MSBB       1 210'    893        1500   4310     1   600  322 ï¿½ 654
                              6   MBAR           20       20       20       20        21                          35     MSPB          59     306        776     300         246
                              7   SAPP           26       -        -        51        45                         Alabama
                              8   SAMP           -        -        -        49        93      25 ï¿½ 23             36     MBCP          20       90       288     137         31
                              9   ESSP           20       -        -        21        20                          66     MBHI         767     554        1110     -          -    295 ï¿½ 740
                            10    ESBD           21       70       21       -         -                           79     MBDR       1 520       -         -       -          -
                            12    MBGP           -        20       86       56        20                         Florida
                            11    MBLR           96       348      -        59        90      45 ï¿½ 48             67     PBPH         168     369        842      -          -
                            56    MBCB           20       -        56       -         -                           37     PBIB          -        21       204     250         406  197 ï¿½ 198
                            13    MBTP           20       20       56       20        20                          80     PBSP         130       -         -       -          -
                            55    MBDI           -        -        53       -         -
                            14    MBEM           201      200      23       22        78      138 ï¿½ 119           73     CBJB       1680      8590        -       -          -
                                                                                                                  39     CBSP         225     355        703     543         428  429 ï¿½ 1 140
                            72    BRCL           761      60       -        -         -                           38     CBSR          69       21       2540   2470         209
                            57    BRFS           955   1  670      682      -         -       792 ï¿½ 792           74     PCLO          98     229         -       -          -
                            18    GBCR           370   1  170      525     478      1 070                         68     PCMP       1 210     2690       4750     -          -  1800 ï¿½ 1 590
                            58    GBOB           315      593      543      -         -                           40     SAWB       1 150     2090       1990   1 970   11   800
                            16    GBTD           25       44       20      112        149     259 ï¿½ 606           41     APDB          20       24       2800     20         20    57 ï¿½ 530
                            15    GBYC           247.     132      207     568      1 030                         42     APCP         269     1110       740      20         109
                            59    GBSC           1290  1  350    3 100      -         -
                            17    GBHR           20       119      34       20        31                          75     AESP          33       74        -       -          -
                            Louisiana                                                                             69     SRWP          -        -        119      -          -
                            19    SLBB           108      154      169      26        247     154 ï¿½ 72            43     CKBP          20       74        24      68         22    46 ï¿½ 103
                            20    CLSJ           180      228      102      57        376     220 ï¿½ 218           76     TBNP         269     394         -       -          -
                            60    CLLC           404      726      20       -         -                           47     TBMK         101     170         20      49         372
                            21    JHJH           88       72       20       84        43      44 ï¿½ 50             44     TBPB          20     217        286      68         95
                                                                                                                  70     TBOT         112     357        212      -          -    126 ï¿½ 165
                            22    VBSP           189      31       20      118        79      79 ï¿½ 108            77     TBKA         252     834         -       -          -
                            24    ABOB           20       28       192     115        32      22 ï¿½ 42             45     TBHB          -        -        552    2150         460
                            25    CLCL           20       54       20       20        20                          46     TBCB          20       65        94      22         20
                            26    TBLB           20       49       306      37        20      40 ï¿½ 162            48     CBBI          20       83        31      43         20    51 ï¿½ 180
                            27    TBLF           101      50       83       20        25                          71     CBFM          69     546        272      -          -
                            61    BBTB           -        -        20       -         -                           49     NBNB          87     203        253     108         228   72 ï¿½ 129
                            28    BBSD           963   5480        44       25        57      963 ï¿½ 1 020         50     RBHC          20       77        67      20         47
                            29    BBMB           1010  1 310     1 460  1  111        822                         51     EVFU          47       68       257      20         112   68 ï¿½ 125




                            estimator of the typical value than the mean for data                                MBLR, MBCB, MBTP & MBDI) and Aransas bays
                            which may contain outliers (Hensel, 1990).                                           (ABLR, CBCR & MBAR) which exhibit low median
                              The data in Table 3 presents the spatial and temporal                              concentrations of tPAH and small variability in con-
                            variation for the median tPAH concentration in the                                   centration. The highest median tPAH concentration for
                            coastal and estuarine areas of the Gulf of Mexico. The                               a bay group in Texas is the Brazos River (BRCL &
                            sites are separated into Bay groups (Wilson el al., 1992)                            BRFS), which carries the runoff from agriculture and
                            for data comparison. The variability for each Bay                                    wastewater discharge from industrial point-sources
                            group is the standard deviation as computed from the                                 (NOAA, 1985). For the entire coastal and estuarine
                            interquartile range (IQR) for the. five years of data                                area of the Gulf of Mexico (Table 3), the highest
                            (Hensel, 1990). In Texas, Corpus Christi (CCBH,                                      median tPAH concentration for a bay group is near
                            CCNB, CCIC & ABHI) and Galveston bays (GBCR,                                         Panama City, Florida (PCLO, PCMP & SAWB),
                            GBOB, GBTD, GBYC, GBSC & GBHR) are near                                              which is close to a paper mill (NOAA, 1985; Wilkinson
                            industrial and population centers and exhibit high                                   et al., 1991).
                            median concentrations of tPAH and large variability in                                   There are ffteen sites (LMSB, ABLR, CBCR,
                            concentration compared to Matagorda (ESBD, MBGP,                                     MBAR, SAPP, ESSP, ESBD, MBGP, MBCB, MBTP,
                                                                                                             41





                                                                   PAH contaminants in oystersftom the Gu@'of Mexico                                                                    295

                                            NUT PAH Data - Years I to V                                                               NUT PAH Data - Years I to V
                          500-                                                                                      70.


                                                                                                                    60,
                          400-

                                                                                                                    50,


                          3W
                                                                                                              (a    40,


                          2DO-                                                                                E     30-
                                                                                                              n
                                                                                                              Z
                     Z
                                                                                                                    20

                          '00.
                                                                                                                    10-

                            0                                                                                       a @--                                             .= -                  I
                                         CLU-1              CLCL-2             CLCL-3                                       <20     30     100    300    1000    3000   10000 '30000
                                                       Me  and sww                                                                      Medta-n of Site - NS&T PAH (Ppb)
                     Fig. 2.   Total NS&T PAH concentration distribution during                              Fig.   4. Frequency distribution of the median total NS&T
                     the first five years for all three stations; Caillou Lake in                            PAH (tPAH) concentration in the Gulf of Mexico during the
                                        Louisiana (Site 25-CLCL).                                                                first five years of the program.


                     CLCL, LBMP, TBCB, CBBI & RBHQ with low                                                  Cumulative frequency model.
                     concentration of tPAH (< 100 ng/g) and little variation                                 Bar graphs (Wade et al., 1990) or crossplots (Wade &
                     in the observed values (Fig. 2). There are also six sites                               Sericano, 1989) of data comparing one year's data with
                     (GBSC, BBMB, MSBB, CBJB, PCMP & SAWB), of                                               another have been used to display the general trend for
                     the seventy-eight different sites, where high concentra-                                tPAH data (Wade & Sericano, 1989; Wade et al., 1990;
                     tions of tPAH (>1000 ng/g) are observed. Four sites                                     Wade et al., 1991). These data presentations easily
                     (CCIC, PBPH, PBIB & PCMP) exhibited a decrease in                                       visualize the variation in concentration for a particular
                     the tPAH each year during the first five years of this                                  site. In this report the cumulative frequency function is
                     study. Many sites exhibited a cyclic variation with time,                               used to examine the heterogeneous distribution of PAHs
                     At Choctawatchee Bay off Santa Rosa (CBSR, Fig. 3),                                     in Gulf of Mexico oysters (Mackay & Paterson, 1984).
                     the order of magnitude increase in concentration of                                     This approach has the advantage of examining the Gulf
                     tPAH in Years Il and III is probably due to relocation                                  of Mexico as a single environmental system, determining
                     of the collection site to an area containing wood pilings,                              the percentage of sites exposed to a particular threshold
                     which if treated with creosote, are a source of PAHs.                                   concentration, and providing information for environ-
                     The decrease in Years IV and V probably reflects relo-                                  mental evaluation.
                     cation of the collection stations to an oyster reef away                                   The distribution of the PAH data in Table 3 is best
                     from wood pilings. Due to prolonged freshwater condi-                                   described by a lognormal distribution i.e. the distribu-
                     tions in San Antonio Bay during 1988 and 1989 (Years                                    tion of data is skewed to low concentrations and has a
                     III IV), the oyster reefs experienced a die-off resulting in                            fraction which extends to high concentrations (Fig. 4).
                     no oysters being taken from SAPP, SAMP and ESSP.                                        O'Connor (1990) used the lognormal distribution,
                                                                                                             typical of environmental data, to define high concentra-
                                           NS&T PAH Data - Years I to V                                      tions as those whose logarithmic value is more than the
                          45W                                                                                mean plus one standard deviation of the logarithms for
                                                                                                  V          all concentrations. The tPAH data in Fig. 4 is further
                          4M-
                                                                                                             skewed in that analytes with concentrations less than
                          35W-                                                                               20 ng/g are not included in the sum of eighteen 2-5
                          3=-                                                                                ring aromatic hydrocarbon analytes in Table 2, i.e. the
                     CL                                                                                      data has been censored. For Years 1-111, only censored
                     .9
                          2M-                                                                                data was available, whereas for Years IV and V both
                          2=-                                                                                censored and uncensored data was available. A regres-
                                                                                                             sion analysis of the censored (tPAH) data versus
                     Z
                          15W-                                                                               uncensored data for the sum of all analytes (T-PAH) in
                          1000                                                                               Table 2 from Years IV and V yields the best fit line as
                          WD                                                                                 y = 153.0 + 0.9834 x (r2 = 0-9989); where y = uncen-
                                                                                                                          I I I I I I





                                                                                                             sored data, and x = censored data. Using the best fit
                                                                                                             fine from the Year IV and V data, the censored data
                                         cBsR_1             CBSR-2             CBSR-3
                                                       Sks and Stafim                                        for the cumulative frequency data was corrected to be
                     Fig. 3. Total NS&T PAH concentration distribution during                                the same as the uncensored cumulative frequency data.
                     the first five years for all three stations; Choctawatchee Bay                             Distribution functions are useful measures of environ-
                                      off Santa Rosa (Site 38-CBSR).                                     42   rkental quality data in that changes with time can be





                               296                                                                   T J. Jackson et al.


                                                Year V         lognormal MODEL                                                 Year V - lognormal MODEL-2                OpUlat*l  ons
                                                       Mean    2 50 STD    2 18                                                           Mean 1     214 mean 2      1 2P5

                                    1                                                         1                             1-                                                        0.9
                                0.9-                                                          -0.9       M0CW            0.9-                                                         0.8
                                                                                                         AIWW                                                                                    Aa-I
                                0.8-                                                          -0.8   41             C    0.8.                                                         0.7
                                0.7-                                                          -0.7   0
                                                                                                                    -9   0.7-
                                                                                                                    ts                                                                0.6
                                0.6-                                                          -0.6                       0.6-
                                                                                                                                                                                          c
                                                                                                                                                                                      0.5 M
                                0,5                                                           0.5                        0.5                                                              .0
                                                                                                     05                                                                               0.4 M
                                0.4-                                                          -0.4                       0.4-
                               E                                                                                    E                                                                 -0.3 16
                                0.3-                                                          0.3    02)            :3   0.3-                                                             z
                                0.2.                                                          0.2    cc             0    0.2-                                                         .2  cc

                                0.1-                                                          0.1                        0.1

                                    0-                                                                                      a
                                    10               100               i 0                10000                             fo               100
                                                   Total NS&T PAHs (ppb)                                                                   Total NS&T PAHs (ppb)
                               Fig. 5. Plot of the cumulative frequency distribution                 for Year       Fig. 6. Plot of the cumulative frequency distribution for Year
                               V total NS&T PAH (tPAH) concentration. compared to the                               V NS&T PAH (tPAH) concentration, compared to the
                               Gaussian curve and its cumulative frequency distribution gen-                        Gaussian curves and their cumulative frequency distributions
                               erated from a lognormal model with a mean of 250 ppb and                             generated from a two population lognormal model with a
                                                   standard deviation of 218.                                       mean of 214 ppb for Population I and a mean of 1205 ppb
                                                                                                                                                for Population 2.
                               ascertained without being influenced by outliers. For
                               the cumulative distribution plot, the data is sorted from                            computed, but did not compare as well with the actual
                               the lowest value to the highest, similar to rank trans-                              data for Year V.
                               formation (Conover & Iman, 1981). Each observation                                        The implication of the two populations in the data is
                               is I In fraction of the data set, where n is the number of                           that there are two primary mechanisms accounting for
                               samples in the data set. The sum of the fraction of the                              the distribution of T-PAH concentration in the Year V
                               samples less than the concentration is plotted against                               data. The sites with lower concentration PAHs are prob-
                               the concentration. From this plot the median can be                                  ably due to low level background inputs from storm-
                               determined, since it is defined as the 50th percentile.                              water runoff, atmospheric deposition and sewage
                               The interquartile range (IQR) is used a measure of                                   effluents, etc. (NOAA, 1985). The sites with higher con-
                               variability. The IQR is the 75th percentile minus the                                centration PAHs are probably due to local point-sources
                               25th percentile and equals 1-35 times the standard                                   of PAH contamination (i.e. small spills). From the log-
                               deviation for a normal distribution (Hensel, 1990).                                  normal cumulative frequency function two probability
                                To begin the examination of the distribution of the                                 density functions were derived, the relative proportion of
                               PAH concentration data, the logarithm of the sum of                                  the two populations were estimated to be 0.9 for popula-
                               all PAH analytes (T-PAH) for Year V data was plotted                                 tion one and 0.25 for population two. Comparison of
                               as a cumulative frequency distribution. The 50th                                     the cumulative frequency distribution derived from the
                               percentile was 250 ppb and the standard deviation as                                 sum of the two probability density functions, in the
                               determined from the IRQ was 218. The log of the data                                 above proportions, with the actual data for the cumula-
                               versus fraction of the samples was plotted and com-                                  tive frequency disffibution (Fig. 7) indicates a good
                               pared with a lognormal distribution (Fig. 5). The shape                              correlation.
                               of the cumulative frequency curve (i.e. the positive
                               deviation from the lognormal model) for the T-PAH                                                 Year V-lognormal MODEL                 2
                               data suggests two overlapping lognormal distributions.                                          I             Mean       2 14 Mean 2     i 2P50P'jIC4;"S
                               Making the assumption that there is a 2-5% overlap for                                       0.9-
                                                                                                                                                                                             MCM
                               the two distributions, the mean and standard deviation                                       0.8-
                               were computed for each data set, or population (Table                                     r_
                                                                                                                         0  0.7-
                               4). The cumulative frequency distribution from the two                                    r)
                               population model data compare well with the actual                                           0.6-
                               T-PAH data (Fig. 6). Other increments of overlap were                                        0.5-
                                                                                                                            0.4-
                                                                                                                         E
                                                                                                                            0.3-                                         Popi 0 n. PW2
                                                                                                                            0.2-
                               Table 4. Two population lognormal distribution model. Year                                   0.1-
                                                V-T-PAH data (2-5% overlap)
                                                                                                                               010             ... @60               1000               10000
                               Set            Percentille             STD= Log-mean                  STD of                                     Total NS&T PAHs (ppb)
                                       25%        500/6     75% IRQ/1,3        5                     log-data
                                                                                                                                                                                      0
                                                                                                                                                                                      0
                                                                                                                                                                                      0
                                                                                                                                       Z000@10000






                                                                                                     -              Ft. 7. Comparison of the cumulative frequency distributions
                               1        135         214      320        137         2.3308           0.278 3        for the actual Year V total NS&T PAH (WAH) concentra-
                               2        801      1 210     1 530        544        3-081 0           0.2093         tion data and the cumulative frequency distribution generated
                                                                                                                43                      from the two population model.





                                                           PAH contaminants in oystersftom the Gulf of Mexico                                                     297

                                        Table 5. Two population lognormal distribution model. Corrected tPAH data--Wg dry weight

                  Year                  Median                                 Population I                                           Population 2
                                          total
                                          data                   Mean (log)                   STD (log)                  Mean (log)                   STD (log)

                    1                     229                   197 (2-294 5)               108 (0129 8)                1075 (3-031 4)                714 (0-277 2)
                    11                    208                   186 (2-269 5)                87(0.196 7)                1 150 (3-059 9)             1 100 (0,381 1)
                    111                   345                   259 (2-413 3)               216 (0-343 5)               1910 (3-280 8)              1 190 (&261 8)
                    IV                    352                   269 (2-429 8)               174 (0-250 0)               1350 (3-131 6)              1 190 (0-303 9)
                    V                     270                   212 (2-326 3)               131 (0-263 9)               1170 (3-068 9)                637 (&243 5)



                     Since historical NS&T data (Table 3) is censored                           tration, while Year III had 80%, Year                 IV had 83%
                  data (Wade et al., 1988; Wade & Sericano, 1989; Wade                          and Year V had 87%. Alternatively, the cumulative
                  et al., 1990), the cumulative frequency distribution of                       frequency data can be used to calculate the percentage
                  this censored (tPAH) data was corrected using the best-                       of sites exposed to a concentration in excess of a partic-
                  fit-line from the data for Years IV and V. Data below                         ular threshold.
                  the reporting limit were extrapolated (Hensel, 1990,                             The cumulative frequency distribution was used in
                  Mackay & Paterson, 1984). The summary statistics for                          this study as an environmental evaluation too) to
                  the corrected data using the two population model for                         examine the heterogeneous distribution of total PAH
                  Years I-V data (Table 5) were calculated using the data                       contaminants in Gulf of Mexico oysters from coastal
                  from 0-80 for the original cumulative frequency distri-                       and estuarine areas collected during the winters of
                  bution for population I and from 77-5-100% for the                            1986-1990. The PAH concentrations exhibits a log-
                  original cumulative frequency distribution for popula-                        normal distribution with two major populations in the
                  tion 2 (Table 6).                                                             data for each year. The two populations were decon-
                     The summary statistics for the first five years of                         voluted into probability density functions and sum-
                  measuring PAH contaminants in the Gulf of Mexico                              mary statistics for each population were calculated.
                  for NOAA's NS&T Mussel Watch Program (Table 5)                                The lower PAH concentrations are probably related to
                  show variation in the means for both populations, indi-                       chronic inputs. Many of these low PAH concentration
                  cating temporal change in the total Gulf of Mexico                            sites show little variability from year to year, support-
                  data and with the highest values found in Years III and                       ing the contention that the PAH contamination is on a
                  IV. The higher mean concentrations of PAHs in Years                           continual basis. The higher concentration PAHs are
                  III and IV and the lower abundance in Years 1, 1] and                         probably associated with local point-sources of PAH
                  V is a pattern which is probably related to large-scale                       contamination or spills. Most of the high concentration
                  climatic factors such as the El Niho cycles (Philander,                       sites (>1000 ng/g dry tissue) show large variability
                  1989) which affects the precipitation regime (Wilson et                       from year to year, supporting the contention tbat PAH
                  al., 1992). Examination of the PAH data for individual                        contamination for these sites is on an episodic basis. In
                  sites, as discussed above, does not show this pattern.                        addition, 20% of Gulf of Mexico sites in Year III were
                     The cumulative frequency data for Years I-V gives                          exposed to a PAH threshold concentration of greater
                  the percentage of sites whose PAH concentration is less                       than 1000 ng/g of dry oyster tissue. Whereas. in Years I
                  than a particular concentration (Table 6). As an exam-                        and 11 only 11% of the Gulf of Mexico sites had
                  ple, using 1000 ppb as an arbitrary concentration, 89%                        concentrations greater than 1000 ng/g of total NS&T
                  of the sites for Years I and Il are less than this concen-                    PAHs. The changes in the mean concentration of the
                                                                                                two populations between years display a cyclic patter
                  Table 6. NS&T concentration distribution data (cumulative                     which is probably due to large-scale climatic factors
                        frequency). Corrected tPAH data--Wg dry weight                          such as the El Niho cycles which affects the precipita-
                                                                                                tion regime (Wilson el al., 1992). The cyclic pattern
                              1990        1989          1988        1987       1986             was obtained by examining the Gulf of Mexico as a
                             Year V Year IV Year III Year II                   Year I           single heterogenous system, since the PAH concentra-
                  100/0       110          171          110         110          110            tion data for individual sites does not clearly show this
                  20%         140          200          153         140          140            pattern.
                  3011/o      164          226          206         162          169
                  40%         212          269          259         186          197            ACKNOWLEDGEMENTS
                  W/o         270          352          345         208          229
                  60%         318          435          445         258          286            Funding for this research was supported by the
                  70%         191          119          112         110          371
                  80%         597          869        1030          480          557            National Oceanic and Atmospheric Administration,
                  9fto       1290         1440        2090         1300        1180             contract number 50-DGNC-5-00262 (National Status
                  95%        1670         2840        3020         2300        1750             and Trends Mussel Watch Program), through the Texas
                  91%        1920         1611        4510         3740        2450       44    A & M Research Foundation, Texas A & M University.






                     298                                                      T J Jackson et al.


                     REFERENCES                                                                ment and Tissues. A Special NOAA 20th Anniversary
                                                                                               Report. 34 pp.
                     Conover, W. J. & Iman, R. L. (1981). Rank transformations              Philander, G. (1989). El Niho and La Nifta. Amer. Scientist,
                       as a bridge between parametric and nonparametric statis-                77,451-9.
                       tics. The Amer. Statistician, 35, 124-9.                             Sericano, J. L., Wade, T. L., Atlas, E. L. & Brooks, J. M.
                     Farrington, J. W. & Quinn, J. G. (1973). Petroleum hydro-                 (1990). Historical perspective on the environmental
                       carbons in Narragansett Bay. 1. Survey of hydrocarbons in               bioavailability of DDT and its derivatives to Gulf of
                       sediments and clams (Mercenaria mercenaria). Estuar. and                Mexico oysters. Environ. Sci. Technol., 77, 1541-8.
                       Coast. Mar. Sci., 1, 71-9.                                           Wade, T. L., Atlas, E. L., Brooks, J. M., Kennicutt 11, M. C.,
                     Farrington, J. W., Goldberg, E. D., Risebrough, R. W.,                    Fox, R. G., Sericano, J. L., Garcia-Romero, B. & Defreitas,
                       Martin, J. H. & Bowen, V. T. (1983). US Mussel Watch                    D. A. (1988). NOAA Gulf of Mexico Status and Trends
                       1976-1978: An overview of the trace metal, DDE, PCB,.                   Program: Trace organic contaminant distribution in sedi-
                       hydrocarbon and artificial radionuclide data. Environ. Sci.             ments and oysters. Estuaries, 11, 171-9.
                       Technol., 17, 490-6.                                                 Wade, T. L. & Sericano, J. L. (1989). Trends in organic
                     Hensel, D. R. (1990). Less than obvious. Statistical treatment            contaminant distribution in oysters from the Gulf of
                       of the data below the detection limit. Environ. Sci. Tech-              Mexico. Oceans '89 Proceedings, Marine Technology
                       nol., 24, 1766-74.                                                      Society, IEEE Publication Number 89CH2780-5, pp. 585--9.
                     Krahn, M, M., Moore, L. V, Bogar, R. G., Wigren, C. A.,                Wade, T. L., Sericano, J. L., Garcia-Romero, B., Brooks,
                       Chan, S-L. & Brown, D. W. (1988). High-performance                      J. M. & Presley, B. J. (1990). Gulf Coast NOAA National
                       liquid chromatography method for isolating organic con-                 Status & Trends Mussel Watch: The first four years. Proc.
                       taminants from tissue and sediment extracts. J. Chromaiogr.,            Mar. Tech. Soc., 1990,274-80.
                       437,161-75.                                                          Wade, T. L., Brooks, 1. M., Kennicutt 11, M. C., Denoux,
                     Mackay, D. & Paterson, S. (1984). Spatial concentration                   G. J. & Jackson, T. J. (1991). Oysters as biomonitors of
                       distributions. Environ. Sci. Technol., 18, 207A-14A.                    oil in the ocean. Proceedings of the 23rd Annual Offshore
                     MacLeod, W. D., Brown, D. W., Friedman, A. J., Burrows,                   Technology Conference, OTC 6529, pp. 275-90.
                       D, G,, Maynes, 0,, Pearce, R. W., Wigren, C, A, & Bo,ar,             Wilkinson, D. L,, Brooks, 1. M* & Fay, R. R,,1991). NOAA
                       R. W. (1985). Standard analytical procedures of the NOAA                Status and Trends: Mussel Watch Program-Field
                       National Analytical Facility 1985-1986. Extractable Toxic               Sampling and Logistics Report-Year VI. GERG Technical
                       Organic Compounds, 2nd Ed. US Department of Commerce,                   Report 91-046, US Department of Commerce, National
                       NOAA/NMFS, NOAA Tech. Memo NMFS F/NWC,11,                               Oceanic & Atmospheric Administration, Ocean Assessment
                     NOAA (1985). Gulf of Mexico Coastal and Ocean Zones                       Division.
                       Strategic Assessment: Data Atlas, United States Depart-              Wilson, E. A., Powell, E. N., Wade, T. L., Taylor, R. J.,
                       ment of Commerce, National Oceanic and Atmospheric                      Presley, B. J. & Brooks, J. M. (1992). Spatial and temporal
                       Administration. pp. 4.0-5.32.                                           distributions of body burden and disease in the Gulf of
                     O'Connor, T. P. (1990). Coastal Environmental Quality in                  Mexico oyster populations: The role of local and large-
                       the United States, 1990. Chemical Contamination in Sedi-                scale climatic controls. Helgol. Meeresunters. (in press).


































                                                                                       45













                           Reprint 4


          Modeling Oyster Populations. 11. Adult
                Size and Reproductive Effort

           Eileen E. Hofmann, John M. Klinck, Eric N.
          Powell, Stephanie Boyles, and Matthew Ellis















                               46









                        J.1 of SM#ish R,,,.,,,h, Vol, 11, No* 1, 165-111,1114*


                               MODELING OYSTER POPULATIONS H. ADULT SIZE AND REPRODUCTIVE EFFORT


                                                                                                                                                                                  2
                                                                                   EILEEN E. HOFMANN,' JOHN M. KLINCK,' ERIC N. POWELL,
                                                                                   STEPHANIE BOYLES,              2  AND MATTHEW ELLIS2
                                                                                   'Centerfor Coastal Physical Oceanography
                                                                                   Crittenton Hall
                                                                                   Old Dominion University
                                                                                   Norfolk, Virginia 23529 USA
                                                                                   2Department of Oceanography
                                                                                   Texas A&M University
                                                                                   College Station, Texas 77843 USA


                                 ABSTRACT A time-dependent model of energy flow in post-settlement oyster populations is used to examine the factors that
                                 influence adult size and reproductive effort in a particular habitat, Galveston Bay, Texas, and in habitats that extend from Laguna
                                 Madre, Texas to Chesapeake Bay. The simulated populations show that adult size and reproductive effort are determined by the
                                 allocation of net production to somatic or reproductive tissue development and the rate of food acquisition, both of which are
                                 temperature dependent. For similar food conditions, increased temperature reduces the aocation of net production to somatic tissue
                                 and increases the rate of food acquisition. This temperature effect, however, is mediated by changes in food supply. Within the Gulf
                                 of Mexico, oyster size declines from north to south because increased temperature decreases the allocation of net production to somatic
                                 growth. An increase in food supply generally results in increased size as more energy is used in somatic growth; however, at low
                                 Mvides, as food supply increases, adult size decreases because the allocation of more net production to reproduction outweighs the
                                 effect of inicreased rates of food acquisition. Variations in temperature and food supply affect reproductive effort more than adult size
                                 because the rate of energy flow through the oyster is higher in warmer months when most net production is aflocated to reproduction
                                 and smaff changes in temperature substantially change the spawning season. The wide range of reproductive effort expected from small
                                 changes in temperature and food supply suggest that comparisons of adult size and reproductive effort between oyster populations can
                                 only be made within the context of a complete environmental analysis of food supply and associated physical parameters and an energy
                                 flow model.


                                                    ]INTRODUCTION                                       size with latitude and the year-to-year variability in mean adult
                                                                                                        size suggest that one or more climatic variables limit oyster size.
                           Populations of any species tend to have a characteristic mean                The correlation with latitude suggests temperature as a likely vari-
                        adult size, which is defined as the size reached by the average                 able. From a physiological perspective, temperature may affect
                        surviving adult individual in the dominant cohort. When the char-               adult size by regulating the division of net production into somatic
                        acteristic adult size is considerably below that characteristic of the          and reproductive tissue growth and by regulating the relative rates
                        population, the population is described as stunted (Hallam 1965).               of filtration and respiration. As temperature increases, more net
                        Stunting is generally considered to result from suboptimal condi-               production is allocated to reproduction. Filtration and respiration
                        tions such as extreme environments or low food resources.                       rates also increase, but the rate of incmase in filtration rate is
                           In the Gulf of Mexico, populations of the American oyster                    greater (Powell et al. 1992b). Therefore, a complex interaction of
                        @Crassostrea virginica) exhibit a latitudinal gradient in character-            temperature with oyster physiology may place an upper lin-dt on
                        istic adult size (Fig. 1, Table 1). Mean adult size decreases with              adult size.
                        decreasing latitude on the eastern and western roasts of the Gulf.                  Related to adult size is the concept of reproductive senility
                        At the extremes of this distribution, most oysters fail to reach the            (Peterson 1983) in which fecundity per unit biomass declines at
                        standard size limit of 7.6 cm that is required for commerical ex-               large size or old age. The existence of reproductive senility in oys-
                        ploitation (e.g. Hofstetter 1977, Berrigan 1990). The nearly com-               ters remains to be determined. However, respiration rate rises
                        plete restriction of the Gulf of Mexico oyster fishery to the north-            faster than filtration rate with increasing body size (Klinck et al.
                        ern Gulf is the practical result of this trend. Additionally, year-to-          1992, Powell et al. 1992b). The different scaling of respiration and
                        year variations in mean adult oyster size show similar variations               filtration with body size suggests that the scope for growth in
                        throughout the Gulf of Mexico (Wilson et al. 1992). That is, the                oysters must eventually be curtailed at large size which will result
                        characteristic adult oyster size increases or decreases uniformly               in declining fecundity per unit biomass (Powell et al. 1992b).
                        among the many populations in the Gulf, Variation in age cannot                 Consequently, populations of lower characteristic size may spawn
                        be completely excluded as a contributor to these trends; however,               more per unit biomass.
                        the annual mortality in oyster populations from predators and dis-                 'Me objectives of this study are to investigate processes that
                        caw exceeds 75% throughout the Gulf of Mexico (e.g. Butler                      contribute to variation in the characteristic adult size of oyster
                        1953a, Moore and Trent 197 1, Powell et al. 1992a) and fished and               populations within a particular habitat and over a latitudinal gra-
                        unfished populations were included in the analysis. Accordingly,                dient in temperature and to address the possible influence of re-
                        the oyster populations sampled in the Gulf of Mexico were com-                  productive senility in oyster populations. These objectives are ad-
                        posed primarily of individuals that were one to two years in age                dressed using an energy flow model (Fig. 2) developed for post-
                        (Wilson et al. 1992). Hence, size rather than age accounts for the              settlement oyster populations. A series of simulations are
                        trends seen in these populations.                                               presented for Galveston Bay, Texas that consider the effect of
                           The similar bends on both sides of the Gulf of Mexico in oyster              variations in temperature, food supply and salinity on adult oyster


                                                                                                     47








                          166                                                         HoFMANN ET AL.



                                          30-                                          q
                                                                                       q                                         i
                                                                                                  M                              i
                                          25-                                    f g              M     0
                                                                      C                           M    n            r k  y             2      U
                                                                                                  m                   k                                   v
                                        z 20-                                       9
                                                                                 f                     n              k
                                                                   b       d 6                         n0                                     U    t
                                        M is-               3         C    d 0                          0                                     U
                                        2      -                      C          f                                       y                         t W    v
                                        be 10-        a        2      C                                               k
                                        z             a                          f                                                                   W
                                               '  i         3  j   b
                                             5-   5         3      b                                                                          u      W    v
                                                        4      2                           P                                                         W
                                                        4   3      b                       P                                              x
                                                        4                                                                                 X               v

                                                 1      3      5      7      9      11    13      15    17 19        21     23     25     27      29   31

                                                                                    RANK FOR LATITUDE
                          Figure 1. Mean adult oyster size (length) versus latitude plotted as the rank-order of latitude versus the rank-order of size [see Wilson et a].
                          (1"2) for details]. The four values for each size and latitude, referenced by letter (a-z) or number (1-5), are those given in Table I for 1986
                          to 1989. Bays with the characteristically smaller sizes am the more southerly bays on either side of the Gulf of Mexico (on the left), the bays
                          in the Florida Panhandle (right), and Tiger Pass and the Mississippi Delta.


                                                                                           TABLE 1.

                           Oyster population mean length (cm) and fraction of the population in advanced reproductive state (spawning or ready to spawn) for
                          thirly,one bay systems arou" the Gulf of Mexico that were sampled from 1916 to 1"9 as part of the NOAA Status and Trends program.
                          Details of the sampling sites an given in Wilson et al. (1"2). Bays are listed beginning with the southern most bay In Texas and proceding
                          clockwise around the Gulf of Mexico. The high fraction ready to spawn In the northern Gulf of Mexico in 1996 (bays I to s) resulted from
                                 sampling late in the year.  Year and Julian Day were used in the statistical analysis of these data to control for this effect.


                                                                           Length                                     Fraction in Advanced Reproductive State

                           Bay Systems                 1986          1987           1988          1"9           1986             1987              1998             1989
                          aLaguna Madre                8.16          6.95           6.04          6.03          0.14             O@86              0.27             0.15
                          bCcnpus Christi Bay          7.41          5.67           5.52          7.04          0.13             0.00              0.14             0.23
                          cAransas Bay                 8.47          8.20           8.19          6.38          0.05             0,02              0.04             0.05
                          dSan Antonio Bay             8.68          8.36           -             -             0.09             O@70                -                -
                          eMatagorda Bay               9.38          8.30           6.92          7.07          0.20             0.05              0.05             0.21
                          f East Matagorda Bay         10-13         8.37           6.72          6.29          0.10             0.00              0.14             0.23
                          gBrazos River                 -             -             8.57          7.14           -                 -                 -              0.33
                          hGalveston Bay               9.03          8.56           8.55          8.33          0.14             0.09              0.04             0.10
                          iSabine Lake                 10.44         9.65           9.66          8.40          0.00             0.15              0.00             0.00
                          jLake Calcasieu              11.48         8.27           7.99          9.32          0.00             0.00                -              0.00
                          kJoseph Harbor               8.36          8.79           8.19          7.06          0.67             0.00                -              0.14
                          1Vermillion Bay              8.72          9.66           9.91          9.06          0.93             0.00              0.25             0.00
                          m Caillou Lake               9.73          10.36          8.18          8.20          0.83             0.14              0.00             0.13
                          nLake Barre/Felicity         8.96          9.22           7.17          7.49          0.97             0.04              0.00             0.21
                          oBarataria Bay               10.08         9.57           7.04          6.86          0.89             0.00              0.15             0.35
                          pTiger Pass                   -             -             5.80          5.72           -                 -                 -              0.27
                          qPass a Loutre                -             -             11.23         10.57          -                 -               0.00             0.00
                          rBreton Sound                9.66          8.50           7.71          8.47          0.93             0.07              0.04             0.04
                          sLake Borgne                 8.94          7.27           7.52          5.68          1.00             0.00              0.07             0.00
                          tMississippi Sound           8.40          7.15           7.10          7.20          0.00             0.00              0.00             0.13
                          uMobile Bay                  8.62          9.03           6.03          6.66          0.13             0.00              0.00             0.13
                          vPensacola Bay               9.09          4.55           6.02          6.46          0.08             0.00              0.05             0.09
                          wChoctawatchee Bay           7.74          4.95           6.67          5.97          0.09             0.00              0.00             0.03
                          x. St. Andrew Bay            6.01          4.81           6.53          6.35          0.64             0100              0.10             0.06
                          yApalachicola Bay            8.43          7.35           8.29          6.64          0.13             0.07                -              0.04
                          zApalachee Bay                -             -             -             7.29           -                 -                 -              0.00
                          ICedar Key                   7.44          5.16           6.71          5.39          0.07             0.00              0.08             0.00
                          2 Tampa Bay                  6.58          5.90           6.37          6.44          0.25             0A1               0.23             0.57
                          30mulotte Harbor             6*12          1,30           6,47          6*64          0,00             0,01              0,41             0*27
                          4Rookery Bay                 6.70          5.26           4.67          5.47          0.00             0.13              0.11             0.13
                          5Everglades                  9.06          6.56           6.56          5.94          0.08             0.20              0.10             0.00



                                                                                                   48








                                                                                   MODELING OYSTER POPULATIONS                                                                          167

                                                                                     Particulate Load                                        TABLE 2.
                              Salinity                       mpersture                                       Biomass and length dimensions of the oyster size classes used In the
                                                                                                             model. Biomass is converted to size using the relationship given in
                                                                                                             White et al. (1988), denoted by W1PR, and Paynter and DiMcbele
                                                                                                             (1990), denoted by PD. The market-size/submarket-size boundary is
                                                         Filtration Rate                                     about one size class smaller usling the conversion from Paynter and
                                                                                                             DiMicbele (1990). The upper size class length conversions obtained
                                                                                                                    from the Paynter and DiMkhele (1990) relationship are
                                                                                                             extrapolations and are, therefore, less accurate, as are the final two
                                                           Ingestion                                         conversions obtained from the White et al. (1988) relationship. The
                                                                                                             range of length to blomass relationships In Galveston Bay, Texas is
                                                          Assimilation                                                                   shown in Figure 3.
                                                           Efficiency                                        Model Size            Biomass             Length (WPR)           Length (PD)
                                                                                                               Class         (g ash free dry wt)             (mm)                (mm)

                                                                                                                    1         1.3 x 10-7-0-028              0.3-25             0.15-21.4
                                                          Assimill tion                                             2                 0.028-0.10             25-35             21.4-35.7
                                                                                                                    3                 0.10-0.39              35-50             35.7-61.7
                                                                                                                    4                 0.39-0.98              50-63             61.7-89.4
                                                                                                                    5                 0.98-1.94              63-76             89.4-117.6
                                                        Respiratory ate             Respiration                     6                 1.95-3.53              7&-88            117.6-149.5
                                                                                                                    7                 3.53-5-52              88-100           149.5-178.9
                                                                                                                    8                 5.52-7.95             100-110           178.9-207.1
                                                                                                                    9                 7.95-12-93            110-125
                                                         Net Production                                           10                  12.93-25.91           125-150



                                                           Division of                                       2.5  in, 3.0 in and 3.5 in, respectively. Adult oysters, those indi-
                                                               Net                                           viduals capable of spawning, are defined as individuals weighing
                                                           Production                                        more than 0.65 g ash-ftee dry weight, about 50 nun in length
                                                                                                             (Hayes and Menzel 1981), although gonadal development has
                                                   S
                                                   Somatic         Reproduction                              been observed at somewhat smaller sizes (Coe 1936, Burkenroad
                                                    o'
                                              F    Growth                                                    1931). Hence, size classes I to 3 are juveniles.
                                  Figure 2. Schematic of the oyster population model.                           The following conversions and scaling factors were used in the
                                                                                                             oyster model. For simplicity, these are not explicitly shown in the
                         size. Aside from reductions in oyster growth rate from diseases                     governing equations that are described in the following section.
                         (Ray and Chandler 1955, Matthiessen et al. 1990) and perhaps                        First, all calculations were done in terms of energy (cal in-').
                         genetic differences (Grady et al. 1989, Reeb and Avise 1990)                        Oyster caloric content was obtained by applying a caloric conver-
                         these are likely to be the most important factors controlling size in               sion of 6100 cal g dry wt-' (Cummins and Wuycheck 1971), and
                         oyster populations, The effect of latitudinal temperature effects is                the food available to the oysters was converted to caloric equiva-
                         investigated with simulations that use environmental conditions                     lents by using 5168 cal g dry wt-'. The model calculations use
                         appropriate for the Laguna Madre, Apalachicola Bay and Chesa-                       biomass exclusively (and calories) and so are independent of oys-
                         peake Bay, as well as Galveston Bay.                                                ter growth form and length-to-biomass relationships. To relate the
                                                                                                             biomass size classes, defined in Table 2, to lengths for comparison
                                                         THE MODEL                                           to the available measurements and the standard measures of fish-
                                                                                                             ery ma agernent, the length-to-biomass conversion given in White
                         Basic Characteristics                                                               et al. (1988) was used. This conversion is only an approximation,
                                                                                                             however, given the variation in growth forms found in oysters
                             The oyster population model (Fig. 2) is designed to simulate                    within bays and throughout their latitudinal range. The model
                         the dynamics of the post-settlement phase of the oyster's life from                 results are presented in terms of biomass, which can be converted
                         newly-settled juvenile through adult. Therefore, the oyster's size                  to any local specific lengths by using an alternative length-to-
                         spectrum was partitioned into 10 size classes ITable 21, that are not               biomass relation and the size class boundaries given in Table 2                ,
                         equally apportioned across biomass. The lower size limit repre-                     One example, from Paynter and DiMichele (1990) is shown in
                         sents the size at settlement (Dupuy et al. 1977); the upper size limit              Table 2 for comparison.
                         represents an oyster larger than those normally found in the Gulf                      Second, gains, losses or transfers of energy (or biomass) be-
                         of Mexico. In Galveston Bay, for example, the largest oysters                       tween oyster size classes were expressed as specific rates (day-')
                         routinely collected am 7 to 8 g dry wt (Fig. 3), which corresponds                  which were then applied to the caloric content in a size class. For
                                                          TO






                                                                     R           EE
                                                @Z


























                         to model size class 9. Thus, the largest size class, 10, is large                   example, ingestion (cal day - 1) divided by a caloric value in cal
                         enough to prevent boundary effects in the model solutions at the                    gives a specific rate (cal day - '/cal = day - '), which is then used
                         upper end of the size-frequency distribution. The boundaries be-                    to calculate incremental changes in a size class. Because the size
                         tween size classes 4 and 5, 5 and 6, and 6 and 7 represent size                     classes in the model are not of equal size, transfers between size
                         limits that have been used or considered for market-size oysters:                   classes were scaled by the ratio of the average weight of the

                                                                                                           49









                         161                                                           HOIFMANN ET AL.


                                       120-
                                                                                                                               I Tom Roof
                                                                                                                               2 Dow Roof
                                                                                                                  04           3 Gaspips Roof
                                                                                                                  C%           4 Big Beazley Roof
                                       100-                                                                       It
                                                                                                                  Ln           5 Red Bluff Rest
                                                                                                                  tD           6 Stephenson Reef
                                                                                                                               7 Gale's Roof
                                    E                            %                                                             8 Yacht Club Roof
                                    E   80-                                                                                    9 Trinity Roof

                                                                                                                        1y=34.146 + 56.164*log(x)     RA2=0.739
                                                                                                                        2y=29.408 + 49.922*log(x)     RA2=0.828
                                        60-                                                                                                            A
                                                                                                                        3Y=37.977 + 43.078*iog(x)     R 2=0.835
                                                                                                                        4y=39.262 + 40.094*log(x)     RA2=0.847
                                    U)       -                                                                          5y=34.567 + 41.273*log(x)     RA2=0.787
                                                                                                                        6y=31.624 + 41.740*log(x)     RA2=0.729
                                                                                                                        7y=34.005 + 38.670*iog(x)     R A2=0.733
                                        40-                                                                             0y=36.511 + 36.01 S*Iog(x)    RA2=0.871
                                                                                                                        9y=46.390 + 27.229*log(x)     RA 2=0.770


                                        20
                                             0                      10                   20                     30
                                                                      Wet Weight (g)


                                       120-
                                                                                                                  N            1 Four Bit Roof
                                                                                                                               2 South Redfish Rest (east)
                                                                                                                  V            3 Bull Shoals
                                       100-                                                                                    4 Buoy 73175
                                                                                                                               5 Bart's Pass Reef
                                                                                                                               6 Hanna Roof (north)
                                                                                                                               7 Scott Roof
                                                                                                                  CA           8 Hanna Reef (south)
                                    E                                                                                          9 Fisher Reef
                                        go-
                                    rM
                                                                                                                        Iy=31.8T7 + 60.170'log(x)     RA2=0.808
                                                                                                                        2Y=37.976 + 52.423*log(x)     RA 2=0.714
                                        60                                                                                                             A
                                                                                                                        3Y=40.450 + 46.152*iog(x)     R 2--0.807
                                                                                                                        4Y=39.977 + 44.369*log(x)     R 2=0.792
                                                                                                                        5y--40.315 + 40.184*log(x)    RA2=0.895
                                                                                                                        6Y=34.904 + 39.827*log(x)     RA2=0.605
                                        40-                                                                             7y--41.472 + 33.021*log(x)    RA2--0.860
                                                                                                                        8y=31.653 + 39.104*log(x)     RA2=0.841
                                                                                                                        9y=39.594 + 30.429*k>g(x)     RA2=0.689


                                        20
                                             0                      10                   20                     30
                                                                      Wet Weight (g)
                         Figure 3. Shell length versus wet weight for oysters collected at eighteen locations in Galveston Bay, Texas. The curves indicate the empirical
                         relationships obtained using the data from the different locations. The numbers on the curves correspond to those for the empirical relationships
                         ftVm each site*


                         current size class (in g dry wt or cal) to that of the size class from     Governing Equation
                         which energy was being gained or to which energy was being lost:
                                                      W                                                The change in oyster standing stock with time in each size class
                                                        L  or _W_j_                                 (0) is the result of changes in net production and the addition of
                                                     Wj- I    Wj- I                                 individuals from the previous size class or loss to the next largest
                         where W is the median value for biomass (in g dry wt) in size class        size class by growth. Excretion was Dot included since it is a minor
                         j. This ensured that the total number of individuals in the simulated      cmpo,,nt of the oyster's energy budget (Boucher and Boucher-
                         population was conserved in the absence of recruitment and mor-            Rodoni 1988). Following VVhite et al. (1988), net production in
                         tality. Finally, each specific rate for each transfer between size         any size class, NP,, is the sum of somatic (P,,) and reproductive
                         classes was scaled to the relative size of the respective classes:         tissue (Pj) production which is assumed to be the difference be-
                                      for transfers up:        WiMi , , - Wi)                       tween assimilation (A) and respiration (R):
                                      for transfers down:      W/(Wi - wi-O.                                            NPj = Pv + P, = A, - R,                          (1)
                                                                                              50









                                                                               MODELING OYSTER POPULATIONS                                                                      169

                        Therefore, a govern ing equation for each oyster size class can be                           S -_ 7.5 ppt           FRqj = FRj
                        written as                                                                               3.5 < S < 7.5 ppt          FRj = FR@S- 3.5)14.0
                        !!@ij = Pjd + Pj + (gain from j - 1) - (loss to j + 1)                  (2)                  S :@z_ 3.5 ppt         FRaj   = 0
                        dr                                                                              where S is the ambient salinity and FRj is the rate obtained from
                                                                                                        equation (4). [Note that the second salinity relationship was mis-
                        for j = 1, 10, with Pri = 0 for j = 1, 3.                                       printed in Powell et al. (1992b) and Hofmann et al. (1992).]
                           Resorption of either gonadal or somatic tissue results in loss Of                The reduction in feeding efficiency at high particulate loads,
                        biomass. When NP, < 0, oysters lose biomass and transfer into the               characterized by pseudofeces production, was included as a de-
                        next lower size class. This is an important difference between this             pression in filtration rate rather than as a separate function as used
                        size class model and a size class model based on linear dimen-                  by Soniat (1982). From data presented in Loosanoff and Tommers
                        sions: shell size does not change, however biomass does during                  (1948), total particulate content can be related to a reduction in
                        periods of negative scope for growth. Ibis is the basis for the use             filtration rate as
                        of condition index as a measure of health in oysters (e.g, Newell                                                     10-4)100.41lx
                        1985, Wright and Hetzel 1985). To allow for a negative scope for                                      T = (4.17 X                                        (7)
                        growth, equation (1) is modified as                                             where T is the total particulate content (inorganic + organic) in g
                                                                                                        I` and x is the percent reduction in filtration rate. Solving equa-
                                   Loj = Pgj + Pj + (gain from j - 1)                                   tion (7) for the percent reduction in filtration rate gives an expres-
                                   di     - (loss to j + 1) + (gain from j + 1)                         sion for filtration rate modified by total particulate content, FR.,,
                                                                                                        of the form:
                                          -  (loss to j - 1).                                   (3)
                        The last two terms on the right side of equation (3) represent the                           FRrj =   FRaj[ I _ .01 (loglo T + 3.3                       (8)
                        individuals losing biomass and thus, translating down to the next                                                            0.0-418
                        lower size class. Implementation of the model given by equation                 Equation (8), if applied to total particulate content (inorganic +
                        (3) requires that the processes that result in production and/or loss           organic), approximates the results of Haven and Morales-Alamo
                        of somatic and reproductive tissue be described in mathematical                 (1966) and limits ingestion rate to approximately the maximum
                        terms. ne functional relationships used in the model and the                    value found by Epifanio and Ewart (1977). Therefore, an addi-
                        rationale for particular choices are given in the following sections.           tional term to lower ingestion efficiency at high food concentra-
                        Filtration Rate, Ingestion and Assimilation                                     tions was not used. We assume all particles are removed by fil-
                                                                                                        tration, a slight overestimate (Palmer and Williams 1980), that
                           For this model, the filtration rate relationship given by Doering            oysters feed more or less continuously (Higgins 1980a), and that
                        and Ovian (1986) was adapted to oysters using Hilbert's (1977)                  filtration rate does not vary with food availability (Higgins 1980b,
                        biomass-length relationship to obtain filtration rate for each size             Valenti and Epifanio 1981).
                        class as a function of temperature (T) and biomass:                                 Filtration rate times the ambient food concentration gives oys-
                                                                                                        ter ingestion. To the extent that oysters can select nitrogen-rich
                                                            &,0-%T0.95
                                                            -j                                          particles from the filtered material for ingestion, equation (8)
                                                    FRj @      2.95                             (4)     yields an underestimate of ingestion (Newell and Jordan 1983).
                                                                                                        Assimilation is obtained from ingestion using an assimilation ef-
                        and                                                                             ficiency of 0.75, an average value obtained from Tenore and Dun-
                                                          WA.317100.w                                   stan (1973), Langefoss and Maurer (1975), and Valenti and Epi-
                                                   Kj                                           (5)
                                                                                                        fanio (198 1).
                        where filtration rate, FR,, is given as ml filtered ind        min      and
                        W. is the ash-free dry weight in g for each size class. Powell et al.           ResPb26on
                        (1992b) show that equations (4) and (5) yield results comparable to                 Oyster respiration, R,, as a function of temperature and oyster
                        a more general equation derived for all bivalves, including oysters,            weight in each size class was obtained from Dame (1972) as
                        over the size range appropriate for this model. In addition, equa-
                        tion (4) has the advantage of containing the temperature-                                            Rj = (69.7 + 12.67)Wjb-'                            (9)
                        dependency described in more detail by Loosanoff (1958), an
                        attribute not present in most other filtration rate equations (Doer-            where b has the value 0.26. Equation (9) conforms to the more
                        ing and Oviatt 1986). Measurements (Loosanoff 1958) suggest                     general relationship for all bivalves obtained by Powell and Stan-
                        that the rate of increase of filtration rate moderates at temperatures          ton (1985).
                        above 25*C, in accordance with a general trend for bivalves de-                     Salinity effects on oyster respimtion over a range of tempera-
                        scribed by Winter (1978), and declines above 32*C. However,                     tures were parameterized using data given in Shurnway and Koehn
                        equation (4) yields realistic values throughout the normal temper-              (1982) as follows:
                        ature range, so it is used in the model without modification for                               T < 200C          R,     0.007T + 2.099
                        lower filtration rates at even higher temperatures.
                           Equation (4) was modified to allow for salinity effects on fil-              and
                        tmtion rate as described by LDosanoff (1953). Filtration rate de-                             T a@ 200C        R,      0.0915T + 1.324;
                        creases as salinity drops below 7.5 ppt and ceases at 3.5 ppt. In
                        mathematical terms:                                                             where R, is the ratio of respiration at 10 ppt to respiration at 20 ppt:
                                                                                                    51










                        170                                                         HOFMANN ET AL.


                        R, = Rio pl,/R20 . Equations (9) and (10) were combined to               disappear and for the oyster population to reach an equilibrium in
                        obtain respiration over a range of salinities as:                        response to a given set of environmental conditions.
                              S @-_ 15 ppt          Rj = Rj,                                        Numerous simulations (not shown) were performed initially
                        10 ppt < S < 15 ppt         Rj = R@ I + [(R, -     1)/5((15 - S))])      using real and idealized time series for the environmental vari-
                             S IC 10 ppt            Rj @ RjR,                                    ables. These simulations, some of which are reported by Powell et
                                                                                                 al. (1992b) and Hofmann et al. (1992), were used to calibrate and
                        Shurnway and Koehn (1982) identified effects of salinity on res-         verify the transfers between size classes and the overall population
                        piration at 20 ppt; however, we used a 15 ppt cutoff to conform to       characteristics and to provide guidance as to model sensitivity to
                        Chanley's (1958) observations on growth.                                 various parameters. These simulations demonstrated that temper-
                        Reproduction                                                             ature and food concentration had more of an effect on the structure
                                                                                                 and character of the simulated oyster populations than variations
                           For adult oysters        4, 10), net production was apportioned       (i.e. ï¿½ 10%) in individual model parameters. It should be noted
                        into growth and reproduction by using a temperature-dependent            that all of the parameters in the model am specified from either
                        reproduction efficiency of the form                                      field or laboratory measurements; no free parameters need to be
                                                                                                 empirically determined. Therefore, the focus of this modeling
                                             RIWJI = 0-054T   - 0.729                     (12)   study is on the effect of variations in environmental conditions on
                            anuary to June and                                                   characteristic adult oyster size and fecundity.
                                                                                                    The simulations described in the following sections used ob-
                        for                  RCO = 0.047T - 0.809                         (13)   served monthly-averaged time series of temperature of two years
                        for July to December. Equations (12) and (13) were derived em-           length from Galveston Bay (Soniat and Ray 1985), the Laguna
                        pirically from the field observations of Soniat and Ray (14.     085).   Madre (Powell et al. 1992b) and Chesapeake Bay (Galtsoff et al.
                        Disagreement exists in the literature concerning the extent to           1947). The temperature values were linearly interpolated to obtain
                        which oyster reproduction is temperature acclimatized (Loosanoff         values at one day intervals to be consistent with the time step used
                        and Davis 1953, Stauber 1950, Loosanoff 1969). However, from             in the model. For a six year simulation, the two-year temperature
                        the studies of Butler (1955), Kaufman (1979) and Quick and               time series was repeated three times.
                        Mackin (197 1), acclimatization appears unimportant over the lat-           For most of the simulations described in the following section,
                        itudinal range of Chesapeake Bay to the southern Gulf of Mexico.         salinity values were held constant at 24 ppt to remove the effect of
                        Equations (12) and (13) may not hold north of Delaware Bay.              low salinity on oyster respiration and filtration rates and to em-
                           The portion of new production that goes to reproduction is            phasize temperature effects. For some Galveston Bay simulations,
                        given by                                                                 a low salinity (7 ppt) event was imposed and one Chesapeake Bay
                                                                                                 simulation used the salinity time series given in Galtsoff et al.
                                          Pri = R.W_
                                                     ,NPj, for j = 4, 10,                 (14)   (1947). Food and turbidity values were specified as described for
                        Somatic growth is the remaining fraction. In cases where NPj < 0,        each simulation. A summary of the environmental conditions used
                        we assume preferential resorption of gonadal tissue to cover the         for the simulations is given in Table 3.
                        debt, although some data suggest the contrary (Pipe 1985). Go-                                        RESULTS
                        nadal resorption is commonly observed in stressed oysters (e.g.
                        Gennette and Morey 197 1) and in the fall and winter when food is        Basic Simulation
                        reduced (Kennedy and Battle 1964). For juveniles and adults with            The time evolution of an oyster population that resulted from
                        no gonadal tissue, resorption of somatic tissue occurs. We assume        the settlement of a cohort of ten individuals in mid-May (day 140)
                        reduced reproduction at low salinity (Engle 1947, Butler 1949)           that were subsequently exposed to the monthly-averaged temper-
                        results from decreased filtration rate and increased respiratory rate    atures from Galveston Bay, a constant salinity (24 ppt) and a
                        and so include no specific relationship for this effect.                 constant food supply of 0. 5 mg I - I was simulated. No recruitment
                           Although a considerable literature exists on factors controlling      or mortality was allowed so that the same individuals were tracked
                        the initiation of spawning (e.g. Stauber 1950, Loosanoff 1965,           from settlement onwards, about 5.5 years. This simulation pro-
                        Dupuy et al. 1977), including empirical temperature-dependent            vided a basic case to which other simulations could be compared.
                        relationships (Loosanoff and Davis 1953, Kaufman 1979), little is        Following settlement, the oyster population increases in biomass
                        understood about factors controlling the frequency of spawning           during the first 1.5 years of the simulation (Fig. 4a) after which it
                        over the entire spawning season (e.g. Davis and Chanley 1956). In        reaches a steady population distribution that is in equilibrium with
                        our model, spawning occurs when the cumulative reproductive              the imposed environmental conditions. The majority of the popu-
                        biomass of a size class exceeds 20% of the standing stock; an            lation at the end of the simulation is in size classes 5 and 6 (63 to
                        estimate based on data presented in Gallager and Mann (1986) and         98 mm) . In the first two years of the simulation, gonadal tissue is
                        Cboi et al. (1993).
                                                                                                 present in size classes 4 to 6. However, as the population stabi-
                        Mo&I Implementation and Environmental Forcing                            lizes, gonadal tissue is confined to size classes five and larger.
                                                                                                 Gonadal tissue development occurs in the adult size classes
                           The model described by equation (3) was solved numerically            throughout the summer and into the fall, with the maximum de-
                        using an implicit (Crank-Nicolson) tridiagonal solution technique        velopment as a fraction of body weight occurring in late July of
                        with a one day time step. The external forcing for the model is          each year.
                        from time senes that specify ambient temperature, salinity, food            A fall larval set, exposed to the same environmental condi-
                        concentration and turbidity conditions. Each simulation was run          tions, results in a similar population distribution (Fig. 4b). The
                        for 6 years which is sufficient time for transient adjustments to        oyster population stabilizes with the same size-frequency distribu-
                                                                                              52









                                                                          MODELING OYSTER POPULATIONS                                                             171


                                                    TABLE 3.                                    Bay (Soniat et al. 1984) were tested. The pattern of development
                          Summary of the environmental conditions used for the oyster           for an oyster population exposed to a food supply double that used
                                population simulations. Inclusion of a time varying             in the basic simulation (Fig. 5a) is not substantially different. A
                          mouthly-averaged temperature, salinity, food concentration or         stable size-frequency distribution develops in about 1.5 years.
                        torbidity time series is indicated by V. For simulations that used      However, the details of the population do differ. The final size-
                        constant salinity or food conditions the values are given in ppt or     frequency distribution shows that most of the individuals are in
                        mg 1-1, respectively. Some simulations used an idealized (I) food       size classes 8 and 9, 100-125 mm. Gonadal tissue development
                       time wries that included increased concentrations in the spring and      occurs throughout the year, but reaches maximum development in
                        fall to shoulate blooms. Exclusion of an environmental variable Is      the larger animals in the fall. A further increase in food supply by
                                                  deDoted by N.                                 50% results in a simulated population that rapidly increases in size
                                                                                          -     (Fig. 5b) and has the majority of the individuals in size class 8 and
                            Area         Temperature Salinity Food        Turbidity    Figure   larger. Development of gonadal tissue occurs in the larger indi-
                       Galveston Bay           V              24       0.5    N        4a, b    viduals throughout the year. Overall, these simulations demon-
                       Galveston Bay           V              24       1.0    N        5a       strate that oyster size increases with increasing food concentration.
                       Galveston Bay           V              24       1.5    N        5b          Food supply does not remain constant throughout the year in
                       Galveston Bay           V              V        V      N        6a       Galveston Bay at the levels used in the previous simulations.
                       Galveston Bay           V              V        V      V        6b       Rather, in many years, food supply shows maximum values in the
                       Galveston Bay           V              7        0.5    N        7a       spring and fall that are associated with the spring and fall plankton
                       Galveston Bay           V              7        1.0    N        7b       blooms and reduced food values in the winter. Hence, a monthly-
                       Galveston Bay           V              7        1.5    N        7c       averaged food time series from Galveston Bay (Soniat et al. 1984)
                       Chesapeake Bay          V              V        V      N        9a       was used with the model. This simulation also used observed
                       Laguna Madre            V              24       V      N        9b       salinity values for Galveston Bay. The time varying food supply
                       Laguna Madre            V              24       0.5    N        10a
                       Apalachicola Bay        V              24       0.5    N        lob      results in the simulated oyster population shown in Figure 6a. The
                       Chesapealce Bay         V              24       0.5    N        10c      final adult size for this population is intermediate between that
                       Laguna Madre            V              24       1.0    N        Ila      obtained for the constant low and medium food simulations. The
                       Apalachicola Bay        V              24       1.0    N        Ilb      majority of the adults are found in size classes 7 and 8 (88-110
                       Chesapeake Bay          V              24       1.0    N        llc      mm). Maximum gonadal tissue production is also associated with
                       Laguna Madre            V              24       1      N        13a      these size classes and occurs in the late summer and fall. A con-
                       Galveston Bay           V              24       1      N        13b      stant salinity of 24 ppt results in a simulated population (not
                       Chesapeake Bay          V              24       1      N        13c      shown) that is almost identical to that shown in Figure 6a.
                       tion and gonadal tissue development     is nearly identical. Conse-      Turbidity
                       quently, a spring settlement is used to initialize the simulations          In estuarine systems, like Galveston Bay, total seston includes
                       described in the following sections.                                     inorganic particles that can interfer with filtration and reduce in-
                          Overall, the growth rates, gonadal tissue production and adult        gestion rates at high enough concentrations. Hence, the overall
                       size of the simulated oyster populations shown in Figure 4 are in        food supply is effectively reduced. When monthly-averaged tur-
                       agreement with measurements from Galveston Bay. Some oysters             bidity values (Soniat et al. 1984) from Galveston Bay are included
                       reach size class 5 (63 mm) in about 45 days and size class 6 (76         as part of the food supply, the effect is to reduce the overall size
                       mm) in about 72 days after settlement. These growth rates are            of the oyster population and gonadal tissue development (Fig, 6b).
                       similar to those found for oysters in Galveston Bay and around the       'Me final adult size is reduced to 63 to 88 mm (size classes 5 and
                       Gulf coast in general (Powell et al. 1992a, Ingle and Dawson             6) and is similar to that obtained at the low constant food supply
                       1952, Hayes and Menzel 1981). Gonadal tissue production and              of 0.5 mg I`. Gonadal tissue development is confined to a
                       spawning in oyster populations in the northern Gulf of Mexico is         smaller portion of the year.
                       normally restricted to the summer months (Wilson et al. 1990).
                       Consequently, reproductively-advanced oysters make up the ma-            Salinity
                       jority of the population only from April to October. This same              Estuarine systems are frequently characterized by extended pe-
                       pattern is seen in the simulated population. In Galveston Bay the        riods of low salinity. As many laboratory and field studies have
                       upper limit on oyster size is 80 to 100 nun and the mean oyster          shown, the filtration and respiration rates of oysters are adversely
                       length is about 85 nim (Table 1; Wilson et al. 1992). Adult oyster       affected at salinities below 7.5 ppt and 15 ppt, respectively. Con-
                       size at the end of the simulation approaches this value.                 sequently, episodes of low salinity could result in reduced size and
                       I    Con&ok on Aduh Size                                                 reduced gonadal tissue development. To test the effect of this
                                                                                                environmental variable, the development of oyster populations
                       Food Supply                                                              during extended periods of low salinity (7 ppt) over a range of food
                                                                                                concentrations was simulated (Fig. 7).
                          Food supply is an important factor governing the growth and              The effect of low salinity is to reduce the overall size of the
                       development of post-settlement oyster populations, Within any            adult population and to hinder the development of gonadal tissue
                       one bay, local conditions can result in large variations in the food     at a given food concentration. The effect of low salinity is most
                       concentrations experienced by these populations. To investigate          pronounced at low food concentration (Fig. 7a) where the scope
                       this effect on oyster adult size, constant food supplies that brack-     for growth is most reduced. The final adult size is reduced relative
                       eted the range of typical food variations measured in Galveston          to the equivalent high salinity case (cf. Fig. 4a) and gonadal tissue

                                                                                            53









                         172                                                                  HOFMANN ET AL.
                              0       . . .                                                          'A                                                                              'B

                              9.0
                              '0





                              8.0


                              7.0


                              6.0





                         0    4.0


                              3.0
                              2.0                                                        E3 3.0   3.5                                                                    ED 3.0 - 3.5
                                                                                         W 3-S - 4.0
                                                                                                                                                                         IM 3.5 - 4.0
                                                                                              4.0 4.5                                                                    =     4.0-4.6
                                                                                              4.5 - 5.0                                                                  = 4.5 - 6.0
                              1.0                                                             >5.0                                                                       111111 >5.0
                                                                  j I I I , I            . I @ I                                                                         . I . I
                                         400 600 800 1000 1200 1400 1600 1800 2000                                200 400 600 800 1000 1200 1400 1600 1800 2000
                                                             TIME (Days)                                                                     TIME (Days)
                         FUUM 4. Comparison of the time evolution of oyster populations and gone" tissue development produced by recruitment of a cohort of ten
                         individuals into size class I on A) Julian Wy 140 (mid-May) and B) Julian Day 240 (early August). Isolines represent the number of individuals
                         which an given in terms of the logarithm of the number of oysters (log,, N). Size class boundaries are defined in terms of biomass (ash free dry
                         weight) as shown in Table 2. Hence, the zero contour corresponds to one individual. Population values less than this are indicated by the dashed
                         lines; solid fines are population values greater than one individual. Shading for the amount or gonadal tissue development represents the
                         logarithm of calories (log,, cal) with the darkest shades corresponding to the highest values. Contour interval is 0.5 for the number of individuals
                         in-' and 1.0 for gonadal tissue production. Numbers of individuals or calories are plotted opposite the size elm designations, not halfway
                         between; hence, on day 140 all individuals are in size class I opposite the grid mark labeled 1. The caloric values can be expressed as Joules by
                         using a conversion of 4.18 Joules cal'.


                         production is less. Similar trends arc observed for low salin-                    7) and high salinity conditions (Figs. 4 and 5) shows that the
                         ity conditions at the higher food concentrations (Fig. 7b, c).                    effect of reduced salinity is minor relative to that of reduced
                         However, higher food concentrations offset the deleterious                        food. Therefore, the detrimental effects of low salinity on oyster
                         effects of low salinity somewhat by providing more energy for                     populations can be reduced by high, but not unusually high food
                         growth. Comparison of the simulated populations at low (Fig.                      supplies.



                                       a      9 1 r I -i            -1 4 1 1 1 8 1 1 1 1                            1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
                                                                                                     A                                                                                B
                           10.0 -


                              9.0 -

                              8.0                                                                                                                                         0.


                              7.0
                                                                                                                                             0 It's
                              &0


                              5.0


                              4.0


                              3
                                                                                         M 3.0 - 3.5                                                                     E3 3.0 - 3.6
                              2.0                                                        W 3.5 - 4.0                                                                     103.5-4.0
                                                                                              4.0 - 4.5                                                                  = 4.0 - CS
                                                                                              4.5 - 5.0                                                                       4.6 - S.0
                                                                                                                                                                        2.























































                              1.0                                                        W >5.0                                                                               >5.0

                                 200 400 600 SW 1000 1200 140D 1600 18DO 2000                                     200 400 600 800 1000 1200 1400 1600 1800 2000
                                                             TIME (Days)                                                                     TIME (Days)
                         Figure 5. Simulated oyster population distribution and gonadal dasue development that results from Galveston Bay environmental conditions
                                                                                                           ther
                         Wid constant food concentrations or A) 1.0 mg I           and B) 1.5 ing 1-'. 0   54   wise same as Figure 4.










                                                                                MODELING OYSTER POPULATIONS                                                                       173



                                                                                                   A                                                                              B
                            10.0
                                                                              'Zo

                            9.0


                            &0
                                                                                                                                                                         0 -

                            7.0


                            &0                                                             0.


                            5.0                                                                                      0.5


                        0   4.0


                            3.0
                                                                                           3.0 - 3.6                                                                  M 3.0 - 3.S
                            2.0                                                             3.6 '4.0                                                                  IM 3.5 - 4.0
                                                                                            4.0 -4.6                                                                  = 4.0 - 4.5
                                                                                            4.5 -S.0                                                                  IN 4.5 - 5.0
                            1.0                                                        IN >6.0                                                                        101 >6.0
                                                                                          I . I                                 I      t      I                       . I . I
                                 200 400 600 800 1000 1200 1400 16W 1800 2000                                   200 400 600 800 1000 1200 1400 1600 1800 2000
                                                           TIME (Days)                                                                     TIME (Days)
                        Figure 6. Simulated oyster population distribution and gonadal tissue development that results from Galveston Bay environmental conditions
                        and food conditions A) without, and B) with turbidity. Otherwise same as Figure 4.


                        Latitudinal Controls on Adult Size                                               agree with those reported for Chesapeake Bay oyster populations
                                                                                                         by Butler (1953b) and Beaven (1952). Yearly fluctuations in bio-
                        Temperature                                                                      mass are higher in Chesapeake Bay because scope for growth is
                            The monthly temperature distributions that are characteristic of             negative for longer periods during the winter.
                        Laguna Madre, Texas (26*N), Galveston Bay, Texas (290N),                            Adult size in Chesapeake Bay (size class 8) is larger relative to
                        Apalachicola Bay, Florida (30*N) and Chesapeake Bay, Virginia                    that in the Laguna Madre (size class 7). This difference arises
                        (38'N) show that all three bays reach about the same temperature                 despite the shorter growing season in Chesapeake Bay (Butler
                        (28'C) in the summer (Dekshenieks et al. 1993). The primary                      1953b). The Chesapeake Bay simulation (Fig. 9a) allows more
                        difference over this latitudinal range is in the winter temperatures             time at intermediate temperatures where somatic, but not repro-
                        and duration of cold conditions. To test the effect of temperature               ductive, tissue is developed. The practical result is a larger adult
                        on oyster size and gonadal tissue development over such a latitu-                population. Thus, the temperature range as well as the length of
                        dinal range, a series of simulations that used idealized temperature             time exposed to a temperature are important determinants of adult
                        time series were done. All simulations used six months of warm                   size.
                        (280C) temperature. The remaining six months were set at 25*C,
                        20*C, 15*C and 10*C to rrpresent winter conditions in the four                   Food Supply
                        bays, respectively.
                            For all the temperature conditions, the mode of the oyster pop-                 A low (0. 5 ing I         constant supply of food alters the size
                        ulation, after 5.5 years of simulation, was found in size class 7,               distribution of adult oysters from Laguna Madre to Chesapeake
                        88-100 nun (Fig. 8). However, the population distribution about                  Bay (Fig. 10). The simulated adult size is essentially the same
                        this mode varied considerably from bay to bay. The small tem-                    throughout the Gulf of Mexico. Adult oysters in Laguna Madre
                        perature difference between winter and summer conditions in La-                  (Fig. 10al, Galveston Bay (Fig. 4a) and Apalachicola Bay (Fig.
                        guna Madre, resulted in the oyster population being dominated by                 10b) are found in size class 6. Gonadal tissue production is about
                        essentially a single size class. Adult size increased between La-                the same in the three bays, with that in Laguna Madre being
                        guna Madre and Galveston Bay, with about 40% of the population                   somewhat higher and extending over more of the year. Chesa-
                        found in size class 8. This model result agrees with observations of             peake Bay oysters (Fig. 10c) are slightly smaller (size class 5)
                        hicreased adult oyster size in Galveston Bay relative to Laguna                  which results from decreased filtration rate and hence reduced net
                        Madre. However, the simulated size distributions suggest that                    production in response to the colder winter temperatures in this
                        adult size decreases between Galveston Bay and Chesapeake Bay,                   bay, Winter temperatures in Laguna Madre allow a higher rate of
                        which is opposite of the trend seen in the measurements. This                    filtration which results in this bay having the largest oysters at the
                        difference in simulated and observed adult size arises from the                  low food levels.
                        similar time periods used for the warm and cool temperatures.                       Doubling the available food supply to 1.0 mg I ', results in the
                            As a check on the above results, realistic temperature distribu-             largest oysters being produced at the mid-latitude sites, Galveston
                        tions for Chesapeake Bay and Laguna Madre were used with the                     Bay (Fig. 5a) and Apalachicola Bay (Fig. I 1b). The smaller adult
                        model (Fig. 9). 'Me simulated population size-frequency distribu-                size occurs in Laguna Madre (Fig. I I a) because mom of the aval)-
                        tion for Chesapeake Bay shows that oysters of size classes 6 and                 able food supply is used to produce reproductive rather than so-
                        7 (70-100 nun) are produced by the summer of the second year.                    matic tissue. Adult size in Chesapeake Bay (Fig. I 1c) is also
                        'Me juvenile growth rates and adult size obtained from the model                 smaller than that in the mid-latitude bays. However, this arises
                                                                                                     55










                                     174                                                                                              HOFMANN ET AL.
                                             10.0 -                                                                                   IA                                                          Size at 19W Days

                                               9.0    .
                                               IKO    -                                                                                                        10-
                                               7.0                                                                                                                 $_                                                                    Winter: 25*C
                                                                                                                                                                   s-                                                                    Summer: 21r C
                                               6.0        uib%                                                     0
                                                                                                                                                                   4-
                                                                               0.5                         N,__, CA
                                                                                                                                                                   2
                                                                                                                                                       Z

                                                                                                 05
                                                                                                                                                                   0-



                                               3.0

                                                                                                                            31 - 4.0
                                               2.0                                                                                                             10-
                                                                                                                            4.0 - 4.5
                                                                                                                            4.6 - 5.0                                                                                                    Winter: 20'C
                                               1.0
                                                                                                                                                            1      6-                                                                    Summer: 2W C
                                                             400 600 Wo                                                                                .1 -0
                                                                                      TWE (Days)                                                       E Z         4-
                                                                                                                                                       = -1
                                                                                                                                      B                z -         2-
                                                                                                                                                                   0





                                                                                                                                                               10-

                                                                                                                                                                                                                                         Winter: 15'C

                                                                                                                                                                   6-                                                                    Summer: 281 C

                                                                                                             9
                                                                                                of #11                                                 H           4
                                                                                                                                                            V
                                                                                                                                                       Z@ -5       2-

                                                                                                                                                                   0


                                                                                                                            3.0-3A
                                                                                                                            3.6-4.0
                                                                                                                            4.0-4.9
                                                                                                                            4.6 - co                           10-
                                                                                                                            .6.0                                   8-                                                                    Winter: 1o'C
                                                                                                                            I .       I  .             -62
                                                     200 400          GN $00 1000 1200 14M 1600 1600 2000                                                   42     6-                                                                    Summer: 281 C
                                                                                      TIME (Days)                                                           :2
                                                                                                                                                            Z      4-
                                                                                                                                      C                z -E        2-

                                                                                                                                                                   0
                                                       of                                                                                                                   1 2 3 4 5 6 7 8 9                                    10
                                                                                                                                                                                                        Size Class
                                                                                                                                                       F%wv 8- Simulated size frequencY distribution from year i, for four
                                                                                                                                                       ideahz4ed temPerature time seiries. Other environmental conditions
                                                                                                                     Vri                               were constant salinitY (24 Plit), Galveston Bay food conditions and no
                                                                                                                                                       turbidity.


                                                            J.                                                                                         due to the colder temperatures which limit winter net production
                                                            1*01                                                                                       rather than the production Of reproductive tissue.
                                                                                                                            3.0 - &5                   Environmental Controls on Reproductive potential
                                                                                                                            3.6-4.0
                                                                                                                            4.0-4.6
                                                                                                                            4.5-6.0
                                                                                                                            @.Lo                            The simulations presented in Figures 4-11 show that gonadal
                                                                                                                            -                          tissue development changes for a given set of environmental con-
                                                                            2 OL 'ICLO '12LO'14'm ISM 1800 20M                                         ditions. This in turn determines the reproductive potential (spawn-
                                                                                     TWE (Days)                                                        ing) of an oyster population - "Me ability to check the accuracy of
                                     F%ure 7. Shnubted oyster popubdon distribution and gonadal tissue                                                 the reproductive portion of the population model is limited due to
                                     d
                                     de, ,
                                      el                 that results &= Galveston Bay temperatuires, low sa-                                          the paucity of observations that provide measurements of oyster
                                     Vmhy (7 plit) condidous and food concentrations of A) 0-5 mg 1-1, 8)                                              reproductive state, oyster size, and environmental conditions con-
                                     1.0 mg I-', and Q 1.5 mg 1-1. Otherwise same as Figure 4.                                                         currently. However, them arc some general trends that should
                                                                                                                                                 56    aripear in the simulated po                 pulations.









                                                                                       MODELING OYSTER POPULATIONS                                                                              175


                                                                                                                                                                                                B I
                             10.0

                                                                                                                                       -2-0



                                                                                                q0
                               'Lo





                               6.0


                               6.0


                               4.0                                                                  %1 Of


                                                                                                  0*
                               3.0

                                                                                                M 3.0 - 3.5                                                                        EM 3.0 - 3.5
                               2*0                                                              W 3.5 - 4.0                                                                        10, IS-4.0
                                                                                                "    4.0.4'5                                                                            40-4.5
                                                                                                Z 4.5-50                                                                           C 4:5 - 5.0
                               1.0                                                                                                                                                 = U.0
                                                                                                                                    2
                                   200 400 600 800 1000 1200 1400 1600 1800 2000                                      200 400 600 800 1000 1200 1400 1600 1800 2000
                                                                TIME (Days)                                                                         TIME (Days)
                           Figure 9. Simulated oyster population distribution and gonadal tissue development that results from temperature, salinity and food conditions
                           characteristic of A) Chesapeake Bay and B) Lagun Madre. Observations on food distributions are lacking for Laguna Madre. Hence, the
                           Galveston Bay food time series was used in this simulation. Otherwise same as Figure 4.

                               The spawning frequency and pattern associated with the sim-                        period, recorded for Delaware Bay oysters held in the laboratory
                           ulated populations from Laguna Madre, Galveston Bay and Ches-                          was 3 X 10" to 4 X 107 eggs per female (Davis and Chanley
                           apeake Bay is shown in Figure 12. In general spawning is asso-                         1955). This study did not report food levels. Egg number, esti-
                           ciated with the larger size classes and the spawning season tends to                   mated from the simulation results for Chesapeake Bay and
                           be longer at lower latitudes. Also, the most southerly bays tend to                    Galveston Bay, using the approach described in Klinck et al.
                           have continuous spawning; whereas, that in Chesapeake Bay tends                        (1992), is 1.7 X 10" and 3 X 10" eggs per female, respectively,
                           to be confined to discrete pulses. This same trend is observed in                      for a spawning period of about 100 days.
                           the observations from the NOAA Status and Trends program (Ta-                             The extent to which these differences and similarities in
                           ble 2). More oysters were found in late reproductive phase, ready                      spawning frequency and pattern result from variations in en-
                           to spawn or spawning at lower latitudes.                                               vironmental conditions is discussed in Hofmann et al. (1992).
                               Spawning season is usually defined by the period of time dur-                      For this study, the interest is in the extent to which these differ-
                           ing which mature eggs are present or by the period of actual                           ences and similarities result from variations in adult size. Oyster
                           spawning. The simulated spawning season, as defined by signif-                         populations in Laguna Madre (Fig. 13a), Galveston Bay (Fig.
                           icant spawning events, is about 100 days in Laguna Madre (Fig.                         13b) and Chesapeake Bay (Fig. 13c) show a restriction in the
                           12a), somewhat shorter in Galveston Bay (Fig. 12b) and even                            period of reproductive effort, as measured by spawn production,
                           shorter in Chesapeake Bay (Fig. 12c). A tendency towards a                             over the course of the six-year simulation. This is a conse-
                           spring and fall spawning peak occurs in Galveston Bay (last two                        quence of the increased size of the population rather than of in-
                           years of simulation) and an even stronger tendency towards this                        creased age. Smaller oysters are more likely to have a positive
                           occurs in Chesapeake Bay. Significant gonadal material is present                      energy balance and cat allocate a larger fraction of their total
                           for about 200 days (7 months) in Galveston Bay, 160 days (5                            assimilated energy to reproduction. As a result, they can spawn
                           months) in Chesapeake Bay, and nearly all year in Laguna Madre.                        more frequently. This trend is independent of the pattern or fre-
                           These features of the stimulated spawning season are within the                        quency of spawning and is observed for all ranges of environmen-
                           range of values reported for oyster populations and fit the trend                      tal conditions.
                           toward shorter spawning seasons at higher latitudes (e.g. Hopkins                          A summary of reproductive effort, derived from the simula-
                           1935, Stauber 1950, Ingle 1951, Heffeman et al. 1989, and pre-                         tions, as it relates to average adult size, food supply and latitude is
                           vious references). The development of reproductive material in the                     given in Table 4. These results show the strong relationship that
                           simulated oyster populations, from initiation to first spawning,                       exists between reproductive effort, temperature and food supply.
                           takes about 40 days in Galveston Bay and 60 days in Chesapeake                         Overall reproductive effort is more variable than adult size. For
                           Bay. This is somewhat slower than the 20 to 40 days suggested by                       example, in Galveston Bay a reduction in food supply, produced
                           Kaufman (1979) and Loosanoff and Davis (1953). However, these                          by increased turbidity, gives a 67% reduction in average adult
                           time intervals were based on results from constant temperature                         size, but an 85% decrease in reproductive effort (Fig. 6a vs. Fig.
                           incubations, which will result in shorter times. Hayes and Menzel                      6b). Similarly, the change in temperature that occurs between
                           (1981) recorded mature gametes in oysters that were 40 to 50 days                      Galveston Bay and Laguna Madre reduces adult size by 6%, but
                           old, which is similar to what is observed in the simulated popu-                       increases reproductive effort by 23%. Higher temperatures pro-
                           Mons from Galveston Bay. Egg production, over a two month                              duce higher filtration rates which give increased net production.

                                                                                                               57








                                116                                                                                   HOFMANN ET AL.



                                                 I                                                                                                       I - I - a - 9                  1 - I       -  I   -   I   I i            V
                                                                                                                         A.                                                                                                       A
                                                                                                                                                                                                                       1.0
                                                            4.0 - 4.S
                                                            4.5 - &0
                                                            2.&0                                                                                                                                . . . . . . . . .
                                           9.0                                                                                                   8.0


                                           7.0
                                                                                                                                                 7.0


                                           9.0
                                                                                                                                                                                                                             0 U or


                                           6.0                                                                                                   5.0
                                           4.0                                                                                                                 '*j
                                                                                                                                                 4.0


                                           &0
                                                                                                                                                                                                                       3.0-3.6
                                                                                                                                                                                                                       3,5-4.0
                                           10                                                                                                    zo                                                                    4.0-4.6
                                                                                                                                                                                                                       4.6 - LO
                                           1                                                                                                     1.0                                                                   @5.0

                                                200 400 600            WO 1000 1200 1400 1600 1800 2000                                                200 400        600     600 1000 1200 14W 16W IWO -2000
                                                                             'nME (Days)                                                                                             TIME (Days)
                                                                        i -     r                                      I
                                                            S.C.&S                                                       B
                                                            3.5-4.
                                                      M     4.0-4.05
                                                            4.6 - &0
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                                                                                                                                                        Ar



                                                                                                                                                                                                                     or.  0 a
                                                                                                                                                                                           Lo     j.

                                                                                                                 MS                                                V




                                                                x                                                                                                                                                      3.0-3.5
                                                                                                                                                                                                                       3.S-4.0
                                                                                                                                                                                                                       4,0.4.5
                                                                                                                                                                                                                       4.6-6.0
                                                                                                                                                                                                                       >5.0
                                                                                                                                                                                   j                                   I . 1
                                                200    400 600        800 1000 12W 1400 1600 1800 2000                                                 200 400 600 NO IWO 12W 1400 1600 1800 2000
                                                                             TIME (Days)                                                                                             TIME (Days)

                                                            3.0-3.6                                                     C.                                                                                                        C
                                                            3.5-4.0
                                                                -4.5
                                                            4.SO-6.0

                                                                                                                                                                                                                       O.S



                                                       -2.





                                                                                                                                                            0A
                                                                                                                                                                                                         V.0
                                                                                                                                                                                of
                                                       00                                                                                                                                                              &0-&S
                                                                                                                                                                                                                       3.6-4.0




                                                LA     -1   -LA _t__ I       I t a I a         I I     I a I           I a                                                                                j
                                                200 400       600 SOO 1000 1200 1400 1600 IWO 2000                                                     200 400 600 NO IWO 1200 1400 1600 1800 2000
                                                                             TIME (Days)                                                                                             TtME (Days)
                               F%m 10. Simulated oyster population distribution amd gonadal tis-                                       Figure 11. Simulated oyster population distribution and gonadal tis-
                               sue development that remits from constant low food (0.5 mg V')                                          sat development that results from medium food (1.0 mg 1-1) supply
                               supply and environmental conditions characteristic of A) Laguna                                         and environmental conditions characteristic of A) I agma Madre, B)
                               Madre, B) Apalachicola Bay and Q Chesapeake Bay. Otherwise tune                                         Apalachicola Bay and Q Chesapeake Bay. Otherwise same as
                               as Figure 4.                                                                                            Figure 4.


                                                                                                                                 58









                                                                               MODELING, OYSTER POPULATIONS                                                                  177


                               10.0 -                                                     A                                                                              A

                                9.0 -
                                                                                                               .0


                                                                                                             8.0

                                7.0
                                                                                                             7.0


                                                                                                             6.0
                                                                                                                                                                        Ilk

                                                                                                             5.0
                                4.0
                                                                                                         4t  4.0                        4,
                                3.0                                           E3 1-2
                                                                              W 2-3                          3.0
                                2A    -                                       W 3-4
                                                                                    4-5                      Lo                                                1W 2-3
                                1A    -                                             >6     -                                                                   W 3.4
                                                                                    2                        1.0                                                   4-5
                                                45        'I-OLO-0 t2ko '14'0-0 .1600 1800 2000'                                                                   >S
                                                          TIME (Days)                                             200 400 600      $00 1000 1200 1400 1600 18W 2000
                                                                                                                                        TIME (Days)
                                                                                          B








                                                                                                                          42                               0.6
                                                                                                                                                                        Ah





                                                                                    2
                                                                                    2-3
                                                                                    3-4                                   X%,
                                                                                    4'5
                                                                                    >6                                                                         NE. 2-3
                                                                                    I , I-1                                                                    W   3-4
                                      200 600 600 $00 1000 1200 1400 1600 1800 2000                                                                            C   4-5
                                                          TIME (Days)                                                                                          W A
                                                                                                                  200  400   6W         '14;'12'00'14;'d; 1k           2000
                                                                                          C                                             TIME (Days)


                                                                                                                                                                         C





                                                                                                                                           00







                                                                                    1-2
                                                                                    2-3                                            00
                                                                                    3-4
                                                                                    4-5
                                                                                    >5                                                                         E-n
                                                                                    I .                                                                        M 2-3
                                      2W 400 600 800 1000 1200 14oo 16W ISW 2DOO                                                                               M 3.4
                                                          TIME (Days)                                                                                              4-5
                                                                                                                                                                   >S
                       I%= 12.        Comparison Of Spawning intensity Versus oyster population
                       du In A) Lwma Madre, B) Galveston Buy and Q Chesapeake Bay.                               200 400 6W        Soo 1000 1200 1400 1600 1600 2000
                       Spawning intensity 6 shown as loglo calories spawned with a contour                                              TIME (Days)
                       hd"Val   of "  Spawning intensity for lasun, Madre and Chesapeake              RgUre 13. Simulated oyster population distribution and spawn pro-
                       Bay was obtained from the simulated oyster populations shown in                duction for A) I a0m, Madre, B) Galveston Bay and Q Chesapeake
                       Figures 9b and 9a, respectively. The Galveston Bay spawning Intensity          Say obtained using an idealized food time series. Spawning Intensity is
                       was obtained trom the constant salinity simulation that was essentially        dmnm as Iogjq calories spawned with a contour interval of 1. Other-
                       klentical to the simulation results shown In Figure                            wbe same as Figure 4.
                                                                                                  59










                          178                                                              HOFMANN ET AL.


                                                         TABLE 4.                                                          A                                          C

                            Reproductive effort, average adult size and the ratio of the two
                          Calculated from year six of the simulated populations shown in the
                            bidicated figures. One simulation used is not shown (NS). This                     10.0-
                          11111110111latim used 111001011bly-averaged temperature and food conditions
                           hm Galveston Bay, Texas, & constant salinity of 24 ppt and no
                                                                                                                                                                       L6
                          ftrbidity. The results of this simulation were similar to those shown
                                                                                                                9.0-                                                       u.
                          In Fligure 6a. Size and reproductive efforl are based on simulations                                                                                    U.
                          that used the environmental time series defined in Table 3. Lower
                             food supply, higher turbidity, or the inclusion of disease (e.g.
                            Perkinsus marinw) could be expeected to reduce thses values.                        8.0-
                                                                                                                             0
                                                                                                                              C


                                              Reproductive       Average         Ratio
                                                                                                                7.0-
                                                    Effort         Size      (kcal:g dry FIgure                                                 U)
                                                                                                         0                                      1                 u. U.
                             Location               (kcal)      (g dry wt)       wt-1)       Number      0                                                         j j
                                                                                                                6.0-                                           U.
                          Laguna Madre vs.          266.71         4.87          54.77            Ila                                           U.,            I-11
                                                                                                                                                j
                          Galveston Bay             260.92         5.12          50.%             NS
                          Laguna Madre vs.          218.79         4.62          47.36            13a
                          Galveston Bay             179.03         4.89          36.61            13b           5.0-
                          Galveston Bay vs.         129.77         4.73          27.44            13a    :0.                                    to;
                                                                                                         0                                      JJ
                          Chesapeake Bay            47.47          4.24          11.19            13c                                                      kn1 I
                          Galveston Bay vs.         156.49         5.18          30.21            6a            4.0-                                       Ed
                          Galveston Bay             24.21          1.81          13.36            6b

                                                                                                                3.0-
                          However, most of the net production is allocated to reproductive                                             B Legend           C Legend
                          rather that somatic tissue development.                                                                      E   Low Salinity        Chesapeake Bay
                                             DISCUSSION AND SUNUAARY                                            2.0                        High Salinity       Apalachicola Say
                                                                                                                                                               Laguna Madre
                          General Characteria*s                                                                 1.0                                            Galveston Say
                            Adult size and reproductive effort in oyster populations are                 Figure 14. Comparison of adult size from year six of the simulations
                          determined by the temperature- and season-dependent allocation                 from A) Galveston and Chesapeake Bays (Figs. 6a and 99), B)
                          of net production to somatic and reproductive tissue development               Galveston Bay for high and low salinity at a range of food concentra-
                          which in turn depends upon the temperature regulation of filtration            tions (Figs. 4a, 5 and 7) and C) four bays and a range of food con-
                          rate. Salinity and turbidity affect oyster physiology through a re-            centrations. High and low salinity values are 24 ppt and 7 ppt and are
                          duction in the rate of food acquisition and cannot be distinguished            designated by HS and LS, respectively. Designations for high (1.5 ing
                          from a simple reduction in food supply. Although respiration rate              1-1), medium (1.0 rag 1-1), and low (0.5 ing 1-1) food concentrations
                          varies non-linearly with body mass and is affected by salinity          ,the   are HF, MY and LF, respectively.
                          overall effect of environmental conditions on respiration rate is
                          small and can be ignored, in most situations.                                      Variations in local environmental conditions also affect adult
                            A summary of simulated adult oyster size that results from                   oyster biomass. Low salinity conditions in an environment such as
                          variations in local and latitudinal controls on growth is given in             Galveston Bay can result in reduced adult size (Fig. 14b). How-
                          Figure 14. These simulations considered only environmental con-                ever, the effect of low salinity can be compensated for by increases
                          trol on oyster biomass. Oyster growth form is extremely plastic,               in food supply. Low salinity conditions combined with high food
                          although Kent (1988) argues for some predictable influences of                 conditions can result in adult biomass that is similar to that ob-
                          local habitat. Nevertheless, the shell length achieved in the various          tained during high salinity conditions. The largest reduction in
                          simulated populations may vary over a wide range (Table 2).                    adult oyster size occurs when low salinity is combined with a
                          Unfortunately, much of the available oyster measurements are in                restricted food supply.
                          terms of shell length or condition index rather than biomass. In this              The importance of food in determining adult biomass over a
                          discussion, except where noted, oyster size is considered strictly in          latitudinal range is illustrated in Figure 14c. For all bays, low food
                          terms of biomass, and where needed, conversions to length are                  conditions produced adult oysters that were about the same size,
                          done as shown in Table 2.                                                      size classes 5 to 6. The only exception is Chesapeake Bay where
                            The simulations indicate that adult oysters in Chesapeake Bay                somewhat smaller, size class 4, adult oysters are produced by low
                          tend to be about the same size in terms of biomass as those in                 food conditions. Medium food conditions result in larger adult
                          Galveston Bay (Fig. l4a), when presented with equivalent food                  oysters for all bays with minimal overlap with the size produced by
                          supplies, salinities and levels of turbidity, despite the difference in        low food conditions. Galveston and Apalachicola Bays have sim-
                                                                                                                                                                           AU





















































                          temperature regimes. Water temperatures in Chesapeake Bay tend                 ilar sized adult oyster populations. Individuals in Laguna Madre
                          to be colder for longer periods thart. in Galveston Bay. Thus, the             tend to be a bit smaller. The warmer temperatures in Laguna
                          temperature-dependent control on the allocation of net production              Madre result in more of net production going to form reproductive
                          results in more going to somatic rather than reproductive tissue               tissue, thereby producing more spawn and smaller individuals.
                          development.                                                                   Chesapeake Bay populations show a wider range of adult size, but
                                                                                                       60









                                                                            MODELING OYSTER POPULATIONS                                                               179


                       many individuals reach adult size typical of the lower latitude sites      increase in food apportioned to somatic growth and size remains
                       despite the cooler temperatures and more restricted growing sea-           stable. Reproductive potential, however, declines in these popu-
                       son (e.g. Butler 1953b).                                                   lations.
                                                                                                      Reduced size at lower latitudes is common in bivalves (e.g.
                       A&* Size (Biomws)                                                          Bauer 1992). Such a gradient in animal size can result from vari-
                          The shape of the growth curve for bivalves--whether size con-           ations in temperature in one of two ways. First, an environment
                       tinuously increases at some declining rate or asymptotes to some           characterized by low food supplies and warm temperatures can
                       maximum size (e.g. Levinton and Bambach 1970)--is probably                 produce large adult oysters despite increased reproduction because
                       more a function of environment than genetics. It is significant that       the total gain in energy from higher winter filtration rates results in
                       the simulated oyster populations reached sizes characteristic of           a net accumulation of somatic tissue. The decline in size at low
                       populations throughout the latitudinal range from Laguna Madre to          latitudes in the Gulf of Mexico suggests that this is not the normal
                       Chesapeake Bay solely on the basis of physiology and environ-              condition. Alternatively, an environment characterized by moder-
                       ment. No upper limit for oyster growth or adult size was included          ate-to-high food supply and warm temperatures can produce
                          any of the formulations used to describe oyster physiology.             smaller adult oysters because the greater allocation of net produc-
                       Limitations on size in the simulated populations come from the             tion to reproduction balances the positive effect of temperature on
                       in

                       balance between winter and summer somatic production less the              the rate of food acquisition. This is the more usual case.
                       energy expended in reproduction:                                               Stunting, the presence of a relatively small adult size in a
                                          P.i_ - Ps,_ @ Aj - Pj.                           (15)   population, is generally considered to result from restricted food
                                                                                                  supply. The results of this modeling study suggest that, at least for
                       In adult oysters, net production is normally negative in the winter        oysters, temperature and reproductive effort are also important in
                       and for die most part is balanced by somatic growth in the spring          restricting animal size. Hence, stunted populations can occur at the
                       and fall. Cessation or slowing of growth in the summer (e.g.               edge of the species' range where physiology directly limits size as
                       Beaven 1950) in disease-free oyster populations is normally due to         well as in populations that fail to reach the size expected for their
                       reproduction and spawning which accounts for most of the net               position within the latitudinal range.
                       production in older animals. Hence, the relationship given above               The observed oyster sizes from around the Gulf of Mexico
                       should result in a stable, but seasonally-oscillating, variation in        (Fig. 1) show two exceptions to the general trend of decreasing
                       adult oyster size. In the simulated population distributions, the          size at lower latitudes. It should be noted that the data presented in
                       balance between winter loss in net production and spring-summer-           Figure I are in terms of length, rather than biomass, and so are
                       fall gain begins in the second or third year depending on the              subject to the aforementioned caveats concerning the plasticity of
                       ambient temperature and food supply. Exceptions to this occur              oyster growth form. First, the adult length observed at lower lat-
                       only when food supply is very high.                                        itudes on both sides of the Gulf of Mexico is about I to 2 cm less
                          Growth rate in the hard clam, Mercenaria mercenaria, has a              than the average length observed in the northern Gulf. Such a
                       concave parabolic relationship with temperature (Ansell 1968).             length decrease is not easily produced in the simulated populations
                       Growth rates are lowest at low and high seasonal temperatures and          with a simple reduction in temperature and one biomass-length
                       maximum at intermediate temperatures. Multiplying equations 4              relationship. A 0.5 to I cm reduction in length is typical of the
                       and 12, and assuming a food supply adequate to minimize the                simulated populations. A temperature-dependent change in growth
                       effect of respiration on the energy budget and ignoring the depen-         form modifying the size-to-biomass relationship may also be in-
                       dence of filtration rate on length, yields a parabolic dependence for      volved. Second, oysters from Moblie Bay through the Florida
                       oyster growth rate on temperature of the same form                         Panhandle area and in Tiger Pass on the Mississippi Delta are
                                                   G a bT - a7"a                           (16)   unusually small. This region characteristically has the coldest win-
                                                                                                  ter temperatures in the Gulf of Mexico (Collier 1954). However,
                       where a and b are the constants in equation 12 and T is tempera-           the possibility that the colder temperatures reduce the growing
                       ture. If equation (16) is applied over the latitudinal range from          season and thus limit adult size is not supported by the simulated
                       Laguna Madre to Chesapeake Bay, then oyster growth rate and                populations. Even colder temperatures in Chesapeake Bay fail to
                       hence size should decrease at the southern and northern ends of the        reduce adult biomass. Either food supply is unusually meager in
                       distribution. Maximum growth rate and largest adult size would be          these two areas or mortality rates are unusually high. Thus, stunt-
                       found near the center of this range, However, both the oyster and          ing may be of local (Tiger Pass) or regional (Florida Panhandle)
                       the hard clarn (Ansell 1968) deviate from this expected distribution       extent. The effect of a change in growth form can be discounted in
                       in that adult size remains constant over a wide latitudinal range          this case because the length-biomass relationship given in White et
                       that includes habitats from the northern Gulf of Mexico to north of        al. (1989) is adequate for at least some of these populations.
                       Delaware Bay.                                                                  Butler (1953b) showed that oysters in Chesapeake Bay and the
                          The observed rather than expected [as suggested by equation             northern Gulf of Mexico reached about the same size in terms of
                       (16)] latitudinal distribution in size is also reproduced in the sim-      length. The simulations summarized in Figure 14 generally show
                       ulated oyster population distributions. This relationship between          that Gulf of Mexico oysters slightly exceed Chesapeake Bay oys-
                       size and latitude arises through temperature effects on the alloca-        ters in length when biomass is converted using a single length-
                       tion of net production to somatic and reproductive tissue growth           biomass relationship. A latitudinal difference in growth form
                       and on filtration rate which determines the rate of food acquisition.      would explain this differential. Kent (1988) describes a wide range
                       The longer periods of low temperature in the spring and fall found         in growth forms from Chesapeake Bay, so that within-bay varia-
                       at higher latitudes result in more time in which food is plentiful         tions cannot be discounted. However, the relationship given in
                       occurring at temperatures that favor somatic growth. As a result,          Paynter and DiMichele (1990) for a Chesapeake Bay population
                       decreased filtration rates at lower temperatures are balanced by an        from Tolley Point Bar predicts oysters much longer for a given

                                                                                               61








                         180                                                              HOFMANN ET AL.


                         weight and this prediction agrees with a biomass-length relation-             growth and reproduction. However, small changes in either result
                         ship obtained by Newell (University of Maryland, pers. comm.)                 in more pronounced changes in reproductive effort than in adult
                         from the Choptank River subestuary of the Chesapeake Bay. Lunz                size. For example, the rate of food acquisition is higher in warmer
                         (1938) suggested that a primary influence of anthropogenic: activ-            months when most net production is allocated to reproduction.
                         ities on oyster growth form was to decrease width and length, but             Hence, small changes in available food are magnified during this
                         with more of an effect on width. If true, this would explain a                period. The effect of small variations in environmental conditions
                         perceived variation between oyster size reported by Butler (1953b)            on oyster reproduction and spawning is discussed in detail by
                         snd the more recent measurements reported by PaynteT and                      Hofmann et al. (1992).
                         DiMichele (1990) and Newell (University of Maryland, pers.                        The wide range of reproductive efforts produced from small
                         comm.). Unfortunately, the observations reported in Butler                    changes in temperature or food supply suggests that comparisons
                         (1953b) are not in terms of biomass. The same trend might explain             of reproductive effort between oyster populations can only be
                         the tendency in the simulated oyster populations from Chesapeake              made within the context of a complete environmental analysis of
                         Bay to be slightly lower in weight and, therefore, length, than the           food supply, environmental conditions and a total energy budget
                         northern Gulf of Mexico oysters (e.g. Fig - H). The weight ob-                for the animal. The wide range of reproductive efforts reported for
                         tained from the simulated populations would result in a longer                bivalves in general (see Powell and Stanton 1985 for a review)
                         oyster in Chesapeake Bay using the conversions of Paynter and                 probably results from these interactions. Thus, correlations be-
                         DiMichele (1990) and Newell (University of Maryland, pers.                    tween size and reproductive effort will be location and time spe-
                         comm.).                                                                       cific, and general conclusions based upon such correlations may
                             The simulated oyster populations suggest an explanation for the           not be valid. For example, the relationship between temperature
                         concordance in year-to-year oscillations in oyster size throughout            and reproduction given by Kaufman (1979) requires similar rates
                         the Gulf of Mexico (Wilson et al. 1992). Climatic cycles, such as             of food acquisition among populations to provide valid compari-
                         El Nifto, change the Gulf-wide temperature and rainfall regime                sons *
                         (Powell et al. 1992a). Size, through the direct effect of tempera-                The assumption that populations of larger individuals should
                         ture on the allocation of net production to somatic and reproduc-             reproduce more is not always correct. For many situations, pop-
                         tive tissue or indirectly through variations in food supply, could be         ulations of smaller individuals may have a greater reproductive
                         affected by climatic variations in temperature and rainfall. Fur-             effort per unit of biomass. The simulated population distributions
                         thermore, such climatic effects are likely introduced through vari-           suggest that decreases in reproductive effort are related to in-
                         ations in temperature during the colder part of the year. For ex-             creased size rather than to age. The apparent reproductive senility
                         ample, the difference between a warm and cold winter could be                 in these populations results from the differential scaling of filtra-
                         sufficient to significantly alter adult size.                                 tion and respiration rate with body size, which reduces scope for
                         Reproduction                                                                  growth at a given food supply in larger animals.
                             The reproductive processes included in the oyster population                                      ACKNOWLEDGMIENTS
                         model are based upon simple empirical relationships-, however, the
                         simulated population distributions show trends typical of oyster                  We thank Elizabeth Wilson for help in data acquisition and
                         populations throughout the east coast of the U.S. and the Gulf of             model formulation. The NS&T data were collected through the
                         Mexico. This suggests that reproductive effort in oysters is pri-             efforts of too many to name; we thank the entire NS&T team at
                         marily a function of a genetical ly-determined temperature-                   Texas A&M University (TAMU). This research was supporled by
                         dependent allocation of net production into somatic and reproduc-             institutional grant NA89-AA-D-SG]28 to Texas A&M University
                         dve tissue development and an environmentally determined scope                (TAMU) by the National Sea Grant College Program, National
                         for growth. This temperature dependency may be described by                   Oceanic and Atmospheric Administration (NOAA), U.S. Depart-
                         simple linear relationships such as those given by equations (12)             ment of Commerce, grants 50-DGNC-5-00262 and 46-DGNC-0-
                         and (13) which may reflect temperature-dependent reaction rates               00047 from the U.S. Department of Commerce, NOAA, Ocean
                         in protein synthesis or hormonal control. The mechanism under-                Assessments Division, a grant from the Center for Energy and
                         lying the temperature-dependent allocation of net production                  Minerals Resources, Texas A&M University, a grant from the
                         would appear to be an important unknown in the reproductive                   U.S. Army Corps of Engineers, Galveston District Office
                         physiology of oysters.                                                        DACW64-91-C-0040 to TAMU and Old Dominion University
                             Reproductive potential is the result of the same physiological            (ODU) and computer funds from the College of Geosciences Re-
                         and environmental conditions that govern adult size, i.e. the tem-            search Development Fund. Additional computer resources and fa-
                         perature- and season-dependent rate of food acquisition and the               cilities were provided by the Center for Coastal Physical Ocean-
                         temperature-dependent allocation of net production into somatic               ography at ODU. We appreciate this support.


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182                                               Hofmann ET AL.



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   Prof. Pap. Ser. 13:1-55.





                                                                                          64












                           Reprint 5


            Correlation Between Bioassay-Derived
          P4501AI Inductive Activity and Chemical
            Analysis of Clam (Laternula elliptica)
               Extracts from McMurdo Sound,
                           Antarctica

           Susanne J. McDonald, Mahlon C. Kennicutt
           11, Jose L. Sericano, Terry L. Wade, Long Liu,
                       and Stephen H. Safe











                                65













                                                                                                                  Chemosphere, Vol. 28. No. 12, pp 2237-2248, 1994
                                                                                                                               Copyright 1994 Elacvier Science Ltd
                                                                                                                     Printed in Great Britain. All rights reserved
                                                                                   0045-6535(94)00144-8                                    0045-6535/94 $7.00+0.00




                                                    CORRELATION BETWEEN BIOASSAY-DREIVED P4501A1 INDUCTION
                                                  ACTIVITY AND CHEMICAL ANALYSIS OF CLAM (Laternula ellitica)
                                                         EXTRACTS FROM McMURDO SOUND, ANTARCTICA




                                                              Susanne J. McDonald, Mahlon C. Kennicutt, II, Jose Sericano,
                                                                       Terry L. Wade, Hong Liu and Stephen H Safe


                                                   Geochemical and Environmental Research Group (S.J.M., M.C.K., J.S. and T.L.W.)
                                                                                   Texas A&M University

                                                                                      833 Graham Rd.

                                                                                College Station, TX 77845


                                                        Department of Veterinary Physiology and Pharmacology (H.L. and S.H.S)
                                                                                   Texas A&M University
                                                                             College Station, TX 77843-4466

                                                                       Tel: 409-845-5988        FAX: 409-862-4929

                                                                      (Received in Gummy 25 March 1994; accepted 18 April 1994)



                                                                                       ABSTRACT



                                            Variable levesl of halogenated aromatic hydrocarbos were measured in clams (Laternula elliptica) collected
                                    from McMurdo Sound, Antarctica. Clams collected in and near Winter Quarters Bay contained high levels of
                                    organochlorine compounds, particularly pholychlorinated bigphenyls (PCBs). A strong gradient has been documented
                                    in Winter Quarters Bay that been linked to human activities at McMurdo Station. The activity of clam extracts as
                                    inducers of P4501A1 -dependent ethoxyresorufin 0-deethylase (EROD) activity was determined using in vitro
                                    bioassays utilizing rat hepatoma H4IIE cells. The extracts which exhibited the highest induction activities were those
                                    derived from clams collected in contaminated area . Additionally, there was an excellent linear correlation between
                                    induced EROD activity versus total PCB levels (r2=0.96). The complimentary nature of both the analytical and
                                    bioanalytical data confirms the utility of the latter assay and provides a method for estimating the 2,3,7,8-
                                    tetrachlorodibenzo-p-dioxin (TCDD) toxic equivalents in extracts from marine biota.






                                                                                           2237
  

                                                                                            66













                                     2239


                                                                                          DiTRODUCTION



                                                Halogenated aromatic hydrocarbons (HAHs) are industrial compounds or combustion by-products which
                                        have been widely identified as environmental contaminants in almost every component of the global ecosystem
                                        (Tanabe, 1988; McFarland and Clarke, 1989; Safe, 1990, 1991, Rappe, 1993, Rappe el al., 1993). The HAHs
                                        include the polychlorinated biphenyls (PCBs), dibenzoT-dioxins (PCDDs) and dibenzofurans (PCDFs). These
                                        chmnicals exhibit a number of common properties including their structural similarities, chemical stability, lipophificity
                                        and toxicological effects. The problems associated with the environmental persistence and transport of HAHs and
                                        their preferential bioconcentration in the food chain is primarily due to their resistance to degradation and highly
                                        hpophilic properties.
                                                PCBs, PCDDs and PCDFs have been identified as complex mixtures in diverse environmental samples and
                                        high resolution analytical procedures can give quantitative congener specific analysis of HAH mixtures (Muffin et
                                        al., 1984; Tanabe, 1988; McFarland and Clarke, 1999; Schulz et al., 1989; Duarte-Davidson et al., 1991; Rappe,
                                        1993; Rappe et aL. 1993). Risk assessment and risk management of these complex mixtures can be carried out using
                                        a toxic equivalency factor (TEF) approach in which all the toxic HAHs have been assigned a fractional potency
                                        rdative to 2,3,7,8-tetr&cWorodibenzop4iox:in (TCDD) (NATO/CCMS, 1998; Ahlborg, 1989; Safe, 1990; Ahlborg
                                        et al.. 1992). The TCDD or toxic equivalents (TEQ) of a mixture can be readdy adculated from quantitative
                                        congener-specific analytical data (Safe, 1990).
                                                In vitro bioassays have also been developed to determine the TEQ values of extracts from various
                                        environmental and indumial samples which exhibit *TCDD-like' activity (Bradlaw and Casterline, 1979,- Trotter et
                                        al., 1982; Casterline el al., 1983; Zacharewski et al., 1989; Ankley et al., 1991, 1992, 1993 -1 Tillitt ei al., 199 1 a,
                                        199 1 b, 1992, 1993; Jones et al, 1993). Since these compounds elicit similar toxic and biochemical responses via
                                        the aryl hydrocarbon (Ah) receptor signal transduction pathway (Safe, 1990), various Ah receptor-mediated
                                        msponses including P4501AI induction, antiestrogenicity and keratinization have been utilized to determine bioassay-
                                        derived TEQ values for any mixture (Bradlaw and Casterline, 1979; Trotter el al., 1982,- Casterline et al., 1983;
                                        Gerthy a al., 1994, 1993 - Zacharewski et aL, 1989,- TiHitt et al., 199 1 a, 1991b, 1992, 1993; Ankley el al., 1991,
                                        1992, 1993; Krishnan el al.. 1992; Jones et al., 1993 - Krishnan and Safe, 1993). This approach is useful for
                                        biomonitoring extracts since it obviates the need for relatively expensive chemical analysis, detects aU bioactive
                                        components in a mixture and their possible interactions with coextracted non-TCDD-fike compounds. This approach
                                        is particularly useful for invertebrates because, although the presence of P450 IA-monooxygenase enzymes has been
                                        confirmed in a number of invertebrates (Lee, 1982; James, 1989.- Livingstone, 199 1), there is no conclusive evidence
                                        showing they are inducible after exposure to aromatic hydrocarbons. Additionally, recent work by Hahn and
                                        coworkers (1992) did not detect the presence of the Ah receptor in nine invertebrate species. This suggests that
                                        invertebrates lack a functional Ah receptor, which is consistent with the failure to obsem induced P4501A-
                                        dependent activity. McNIurdo Sound, Antarctica, was selected for study because high concentrations of PCBs and






                                                                                                   67














                                                                                                                                                        2239


                                       po4rnuclev aromatic hydrocarbons (PAILS) have been measured in sediments collected in Winters Quarter Bay and
                                       marrounding area aAiihan el at., 1990; Risebrough el al., 1990; Lenihan, 1992). This paper reports the results of
                                       a P45OIA14nduction bioassay using rat hepatorm H4HIE MRS exposed to extracts from clam (Laremula elliptica)
                                        I * P I from both highly contaminated and control sites in McMurdo Sound. Additionally, the bioamy results are
                                       compared to the results of chernical analyses of the same samples for organochlorine and aromatic hydrocarbon
                                       pollutants.



                                                                               MATERIALS AND METHODS



                                               Sampling. Clam samples, in pools of 9 to 15 individuals, were collected by divers from impacted and
                                       nonimpacted areas in McMurdo Sound, Antarctica. Contaminated clams were collected from two contaminated
                                       locafions in the vicinity of the U.S. McMurdo Station, in Winter Quarters Bay and at the sewage outfall (WQB, Fig.
                                       1). Clams collected from three sites located in remote areas of the McMurdo Sound were used as controls (Fig. 2).
                                               Emwwfion and Cleanup. Approximately 5 to 15 g of wet tissue were used for the analysis of PAHs, PCBs
                                       and chlorinated pesticides. Fifty grams of anhydrous Na2SO4 and the appropriate amount of surrogates were added
                                       to each sample before extraction. The aromatic surrogate contained d4-1,4-dichlorobenzene, dg-naphthalene, d10-
                                       acenaplithene, djo-phenanthrene, d,2-drysene, arW d12-perylene. The surrogate for PCBs and chlorinated pesticides
                                       contained 4,4'-dibromooctafluorobiphenyl, PCB 103 and PCB 198. The tissue samples were then extracted with
                                       methylene chloride (3 times x 100 frd) using a *Tissumizer' homogenizer. The combined extracts were concentrated
                                       to 10-15 ml in a flat-bottom flask equipped with a three ball Snyder condenser and transferred to Kuderna-Danish
                                       tubes. The tubes were heated in a water bath at 60'C to concentrate the extracts to a final volume of 1-2 ml in

                                       hexane.
                                               The tissue extracts were initially cleansed by alumina (20 & 5% deactivated with H20):silica (10 g, 1%
                                       deactivated with H20) column chromatography. The columns were eluted with 200 ml of 1:1 methylene
                                       chloride: pentane and the aluate was concentrated as described above. This fraction was further purified by high
                                       performance liquid chromatography to remove excess of lipid materials. The extracts were concentrated to a final
                                       volume of 0.5-a nil, hexane, for GC/MS and GC-ECD analyses. Extracts used in the bioassy were obtained as
                                       described above except that the surrogates were not added and the extracts were concentrated and dissolved in
                                       DMSO.
                                               btsoumental Analysis. PAHs were analyzed by electron impact (70 eV) GC/MS in the selected ion mode
                                       (ie. molecular ions) as previously described (Wade el al., 1988). The GC/MS was calibrated and linearity was
                                       determined by injection of standards at five concentrations. Peak identity was confirmed by molecular ion, the ratio
                                       of the primary (base) ion to the secondary ion, and retention time. Instrument calibration was checked daily by
                                       reinjection of the original calibration mixture. The calibration check was maintained to within * 10% on average for








                                                                                              68













                                  2240













                                     Figure 1. 1=-ation of Winter
                                     Quarters Bay and the svwa$e                     3C
                                     outfaU in McMurdo Sound,
                                     Antarctica.
                                                                                             "Imp-


                                                                                 ntor Luk"  Boy


                                                                                                                           im







                                                                      0  50 100    200















                                          Boy of "ts






                                                           McMurdo Sound

                                                                                                            Figure 2. 'out ons of control sites in
                                                                                                            McMurdo Sound, Antarctica.




                                                                                           TWO
                                                                              McMurdo      an&
                                                                               Station cw.
                                                                                       emu




                                                                    Ross ke Shelf
                                                                       NOW I
                                                                         VW
















                                                                                    69


                                                                                                                  2241


all analytes of interest. Quality assurance for each set of sample included a system bland and a matrix spike which

were carried through the entire analytical scheme in a manner indentical to the claim samples. 

    PCBs and chlorinated pesticides were analyzed by fused-silica capillary column GC-ECD (Ni63) in spitless

mode. Capillary columns, 30 meters long x 0.25 mm i.d. with 0.25 pm DB-5 film thickness, were temperature-

programmed from 100 to 140 C at 5 C/min, from 140 to 250 C at 1.5 C/min, and from 250 to 300 C at 10 C/min

with 1 min hold time at the beginning of the program and before each program rate change. A hold time of 5 min

was used at the final temperature. Total run time was 94.33 min. Injector and detector temperatures were set at 275

and 325 C, respectively. Helium was used as the carrier gas. Nitrogen or argon/methane (95:5) were used as make-

up gases. The volume injected was 2 pl. The instruments were calibrated using authentic standards ar four different

conceptions to compensate for the non-linear response of the electron capture detector. Tetrachloro-m-xylene

(TCMX) was used as the GC internal standard to calculate the recoveries of the surrogates.

    In Vitro Bioassay. H4IIE cells were grown as continous cell lines in -essential medium supplemented with
 
2.2 mg/ml tissure culture grade sodium bicarbonate, 5% fetal calf serum, and 10 ml/l antibiotic-antimycotic solution

(Sigma). Stock cultures were grown in 150-cm2 tissue culture flasks and incubated in a humidified mixture of 5%

CO2 and 95% air under atomspheric pressure. For enzyme assays, approximately 1 x 10^6 cells in 2 ml media/well

were passaged to 6-well plates. Solutions of the clam extracts dissolved in dimethyl sulfoxide (DMSO) were added

to the culture plates so that the final concentration of DMSO in the medium was < 0.25%. Cells were also treated

with DMSO (solvent control) and different concentrations of TCDD to determine maximal induction activity. Cells

were harvested by manual scraping from culture plates, centrifgued at 1000 g for 6 min at 4 C, and resuspended

in 100 pl of Tris-sucrose buffer (38 mM Tris-HCl, 0.2 M sucrose, pH 8.0) Alquots (50pl) of the cell suspension

were incubated with 1.15 ml cofactor solution (containing 1 mg bovine serum albumin, 0.1 mg NADH, 01. mg

NADPH, and 1.5 mg MgSO4 in 0.1 M HEPES buffer, pH 7.5) in a 37 C water bath for 2 min. The reaction was

started by adding 50 pl. ethoxyresofufin solution (1 mg/40 ml) for a 6-min incubation and stopped by adding 2.5 ml

methanol. Samples were centrifuged at 1000 g for 10 min. The supernatant was used for fluorescence measurement

at an excitation wavelength fo 550 nm, and an emission wavelength of 585 nm (Pohl and Fouts, 1980). Samples

were run in triplicate and the results are expressed a means SD.


                                              RESULTS AND DISCUSSION


    Studies have shown that a strong organic contaminant gradient exists within Winter Quarters Bay that has

been attributed to human activities associated with McMurdo Station (Risebrough et al. 1990; Lenihan et al., 1990;

Lenihan, 1992). Contamination has been linked to a dump site, active recent years; fuel storage tanks; shipping

and construction activites, and station runoff. Additionally, the only sewer outfall for McMurdo Station is located

at the mouth of Winter Quarters Bay where raw sewage is discharged. High concentrations of aromatic

hydrocarbons and organochlorines were measured in sediments near the back of Winter Quarters Bay and decreased





                                             70














                                        2242


                                           with distance towards the mouth of the bay and with distance from the bay. Within Winter Quarters Bay, total
                                           purgeable hydrocarbons ranged from non-detectable to 4500 pg/g and total estimated PCBs ranged from 110 to 1400
                                           ng/g (Risebrough et al., 1990; Lenihan et al., 1990). In contrast, at control locations, no purgeable hydrocarbons
                                           were detected and estimated total PCB levels varied from < 0.01 to 0.8 ng/g. The concentrations of aromatic
                                           hydrocarbons and PCBs measured in Writer Quarters Bay sediments are considered high with respect to values
                                           reported for contaminated temperate locations and significant charnges in the benthic community have been correlated
                                           with the contaminant gradient (Lenihan el al., 1990; Lenihan, 1992).
                                                   Tqhe results in Table I summarize the quantitative analyses of organochlorine pesticides, total PCBs and PAHs
                                           in clam extracts from McMurdo Sound, Antarctica. The range of total hexachlorocyclohexanes (HCHs), chlordanes
                                           and DDT and related compounds varied from nondetectable to 2.83, non-detectable to 2.27, and 1.97 to 9.61 ng/g,
                                           respectively. Tissue chlordane and DDT levels were significantly higher in clams collected at sites in and near Winter
                                           Quarters Bay than at control locations. The highest levels of PCBs were measured (x=409 = 21 ng/g) in extracts
                                           from clam samples 7, 8, 9 and 10 which were collected from Winter Quarters Bay and the sewage outfall (Fig. 1).
                                           The PCB levels were significantly lower in samples collected al control locations in McMurdo Sound (Fig. 2). Total
                                           PAH levels in the clam extracts were above detection limits only from locations 2 and 10 and were not significantly
                                           different for control and contaminated sites.
                                                   The results in Table 2 summarize the induction of EROD activity in rat hepatoma H4IIE cells by aliquots of
                                           the clam extracts. Initial induction studies utilized 2 ul aliquots (run #1q) for the induciion studies and the results
                                           showed induced EROD activity in samples 6 through 9. In run #2, 5 pl aliquots, were used and higher induced
                                           enzyme activities were observed in samples 6 through 9 whereas in samples I through 5 and 10, only low induction
                                           was detected. Dose-response induction by the extracts was not possible due to limited availability of the extracts.
                                           Sample 8A was a duplicate of 8 and there were no significant differences between the induced EROD activities in
                                           these samples (for run #2), thus confirming the reproducibility of the induction bioassay (Tillitt et al., 1991b).
                                           TCDD-induced EROD activity was used as a positive control and I nM TCDD (0.644 ng/plate) was utilized as a
                                           100% maximal induced response. Since the dose-response curve for induction of EROD activity by TCDD was
                                           nearly linear from 0 to 1 nM, the TCDD or toxic equivalents (TEQ) could be determine for the various extracts (see
                                           Table 2).
                                                   Previous studies have demonstrated that both > 4-ring PAHs and several PCB congeners induce EROD
                                           activity in rat hepatoma H4IIE cells (Bradlaw and Casterline, 1979, Trotter et al., 1982, Tillitt et al. 1991b; Sawyer
                                           and Safe, 1982; Sawyer et al, 1984; Piskorska-Phswzynska et al., 1986; Kamps and Safe, 1987); however,
                                           congener-specific chromatographic analysis of the "TCDD-like" coplanar and monoortho coplanar PCBs was not
                                           obtained in this study and TEQs could not be calculated. However, there was a linear correlation between total PCB
                                           levels and induction-derived TEQs (Fig. 3. r2 =  0.95). The other organochlorine compounds present in high
                                           concentration in the extracts (Table 1) are not inducers of EROD activity. Thus, the high linear correlation between









                                                                                                      71
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                                                         Table 1. Organochlorine and PAH concentrations (ngig dry we'                                in Ldlernuld ellipfica extracts fforn McMurdo Sound, Antarc-tica.4

                                                                                                                     - Cinder Cones                             Bernaccm Bay                             Winter Quarters Ha_                       Bay of Sails
                                                                                           Sarryle No.         1          -2              3                   4             5                   6           7            9            9                  10
                                                           allCH                                               ND            ND           ND                  ND            2.09 M              ND          2.19         1.96         2.25               ND
                                                           HCB                                                 0.40          0.27         0.41                0.34          0.31                0.43        0.34         4,75         9.43               0.32
                                                           aNCH                                                ND            ND           ND                  ND            ND                  ND          ND           ND           ND                 ND
                                                           UHCH                                                NO            ND           ND                  0.38          0.37                0.61        0.64         0.43         0.41               0.42
                                                           O-HCH                                               ND            ND           ND                  ND            ND                  ND          ND           ND           ND                 ND
                                                           Reptachlor                                          ND            ND           ND                  ND            0.10                ND          ND           ND           ND                 0.03
                                                           Hepte-epoxide                                       ND            ND           ND                  ND            ND                  ND          ND           ND           ND                 ND
                                                           Oxychlordane                                        ND            ND           ND                  ND            ND                  ND          ND           ND           ND                 ND
                                                           11-Chlordane                                        ND            ND           ND                  ND            ND                  ND          ND           ND           ND                 ND
                                                           DChlordane                                          ND            0.36         0.25                ND            ND                  ND          ND           0.39         ND                 ND
                                                           tram-Nonectilor                                     ND            0.24         0.20                0.19          0.31                ND          ND           ND           0.14               0.12
                                                           cis-Nonschlor                                       ND            ND           ND                  0.24          ND                  1.53        1.61         1.88         1.75               ND
                                                           Aldrin                                              2.74          2.15         2.66                1.83          1.91                ND          1.66         1.64         1.88               ND
                                                           Dieldrin                                            0.77          0.71         0.79                0.66          ND                  ND          ND           ND           ND              0.89 ND
                                                           Endrin                                              ND            1.03         1.07                ND            0.41                ND          ND           0.32         ND                 ND
                                                           Mitex                                               ND            ND           ND                  ND            ND                  ND          ND           ND           HD                 ND
                                                           2.4'-DDE (O,P'-DDE)                                 ND            ND           ND                  ND            ND                  ND          ND           ND           ND                 ND
                                                           4.4'-DDE (P,P'-DDE)                                 O.S7          1.11         0.94                0.61          1.62                1.63        1.72         1.69         1.67               0.17
                                                           2.2'-DDD (O.P.DDD)                                  ND            ND           0.19                ND            ND                  0.40        0.34         0.36         0.24               ND
                                                           4.4'-DDD (P.P'-DDD)                                 ND            ND           ND                  0.80          0.36                .1.75       1.99         1.83         1.78               ND
                                                           2.4'-DDT (O.P'-DDT)                                 0.65          0.42         0.85                1.59          2.11                3.19        3.03         3.65         3DO                1.09
                                                           4,4'-DDT (P.P'-DDT)                                 0.67          0.86         0.92                1.11          1.11                1.91        1.90         2.07         1.94               0.60

                                                           Total HCI-Is                                        ND            ND           ND                  0.38          2.46                0.01        2.83         2.39         2.66               0.42
                                                           Total c1dordanes                                    ND            0.59         0.45                0.43          0.41                1.53        1.61         2.27         1.98               0.15
                                                           Total DDrs                                          1.89          2.39         2.98                4.10          5.22                9.77        8.88         9.61         9.64               1.97
                                                           Total PCas                                          22.2          19.2         17.5                19.0          19.1                383         414          433          404                5.1

                                                           Total PAHs                                          74.61         155.9        69.2 J              32.6 J        56.2 J              145.3 J     148.3 J      159.51 177.0                    67.3 J
                                                           Total PAI-Is (it 4-rinp)                            16.7 J        8.9 1        12.0 J              5.0 j         6.6 J               1.63        21.2 J       31.7 J       77.3 J             7.1 J

                                                             Tin analysis ordarn extracts for organochlorinecompounds arA PAH9 was carried out as desc:ribed in the Materials and Mediods section; ND - non-detectable.
                                                         J Below method detection limit. Data reported as ng/g dry weight. Samples 1.2 and 3 were collected at Cinder Cone; samples 4 wA 5 were collected in Bernache Bay; samples 6 srW 7
                                                             were collected near sewage outfall-, samples 8 and 9 were collected in Winter Quarters Bay; and sample 10 was collected in Bay of Sails.
                                                                                                                                                                                                                                                                           t'j


















                                                     Table 2. Induction Of EROD actrvity in rat hepatorna H41M cells by Laternula elliplica 0dracts from McMurdo Sound, Antarctica.8


                                                                                                                                            Run #1                                                       Run #2

                                                                                                                        EROD Activity                     TEQ                            EROD Activity                  TEQ
                                                       Sample Number                          site                    (pmol/min/mgYe                   (ng)/g@                        (Pm0Vmin1mgY0                    (n9Y9

                                                                 I                       Cinder Cones                         NDc                         ND                                 ND                         ND

                                                                 2                       Cinder Cones                         ND                          ND                             69.2 * 39.9                0.06 * 0.04

                                                                 3                       Cin(ler Cones                        ND                          ND                             319.57*47.9                0.23:k 0.04

                                                                 4                       Bernache Bay                         ND                          ND                             266.0*45.4                 0.21.+0.04

                                                                 5                       Bernache Bay                         ND                          ND                             191.9*44.6                 0. 16A 0.04

                                                                 6                       Sewage outfall                 735.7:k 107.1                0-98+0.15                           1940.0 ï¿½ 109.6             1.47 * 0.09
                                                                 7                       Sewage outfall                 694.3*77.2                   033:E0.10                           1447.6137.7                1.16*0.03
                                                                 8                   Winter Quarters Bay                1329.1 + 60.6d               1.79 + 0.08d                        2079.0 + 167.7d            1.66:k 0. 13d

                                                                 9                   Winter Quarters Bay                741.6:1213.9                 0-99k 0.28                          1558.5:k 32.9              1.241:0.03
                                                                 10                      Bay of Sails                         ND                          ND                             201.4 ï¿½ 45.8               0.16*0.04

                                                                 I I                         Blank                            NDO                         ND                                 ND                         ND
                                                                 RA                  Winter Quarters Bay                960.6:k 186.2d               1.29 * 0.25d                        1755.6 ï¿½ 347.5d            1.40 + 0.29d


                                                         The dam C*wb were dissolved in 50ml DMSO and either 2 or 5 0 aliquots (nin I or 2) were used in the hxluction bioassay as described in the Materials wd Klethods.
                                                         The results expressed as means + SD for separate determinations for each .,le,
                                                     b   The results are eXpreSSed as the rate of ethoXyreSorUf,
                                                                                                                 in Mdabol,       (p I/      Mg)/g of
                                                         ND - non-&ftctable.                                                  zed mo mint              dry tract.
                                                     d   A replicate of sample 8; no signilicWt diffamee (p < 0.05) bdvvm the                for
                                                     0   A sample blank.                                                               results   the two separate determination in run #2,
                                                     r   TEQ (ng)/g = 0.644 ng x (ER0D..0AR0DLrCDD) x dilution factor/dry tissue weight (g).


													2245










		Figure 3. Correlation between induced EROD activity versus PCB ( ) levels
		in Laternula elliptica extracts. The induction bioassay and results are derived from
		data in Table 2 and the analytical data are summarized in Table 1.

PCB levels versus induced EROD activity or TEQs (Fig. 3) coupled with the high concentrations of PCBs rel
to the 2 4-ring PAHs (Table 1) indicate that the PCBs are the major P4501A1 inducers in the clam extracts.
	These data demonstrate the the EROD induction on clam extracts from the Antarctic can be utili
to detect uptake of PCBs from contaminated sediments in Winter Quarters Bay as evidenced by the correla
between total PCB levels versus TEQs (or induced activity). Ongoing studies in our laboratories are investiga
organochlorine pollutants and PAHs.

					ACKNOWLEDGEMENTS

	Samples were collected by John Oliver and coworkers. The financial assistance of the National Institut
Health (P42-ES04917), the Texas Agricultural Experiment Station, the National Science Foundation Polar Prog
(OPP-9022346) and the National Oceanographic and Atmospheric Status and Trends Contract (50-D6NC-5-00
is gratefully acknowledged. S. Safe is a Burroughs Wellcome Toxicology Scholar.

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	23, 730-735.




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