United States
Environmental Protection
Agency
Office of Water
4304
Washington, D.C. 20460
EPA-822-B-00-024
December 2000
Estuarine and Coastal Marine
Waters: Bioassessment and
Biocriteria Technical Guidance

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Estuarine and Coastal Marine Waters:
Bioassessment and Biocriteria Technical Guidance
George R. Gibson, Jr., Project Leader (4304)
USEPA
Office of Water
Office of Science & Technology
1200 Pennsylvania Avenue, NW
Washington, DC 20460
Principal Authors:

Michael L. Bowman
Principal Scientist
Tetra Tech, Inc.
10045 Red Run Boulevard, Suite 110
Owings Mills, MD 21117

George R. Gibson, Jr. (4304)
USEPA
Office of Water
Office of Science & Technology
1200 Pennsylvania Avenue, NW
Washington, DC 20460
Jeroen Gerritsen
Principal Scientist
Tetra Tech, Inc.
10045 Red Run Boulevard, Suite 110
Owings Mills, MD 21117

Blaine D. Snyder
Senior Scientist
Tetra Tech, Inc.
10045 Red Run Boulevard, Suite 110
Owings Mills, MD 21117
December 2000

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        This document is dedicated to the memory of Dr. Douglas Farrell of the
  Florida Department of Environmental Protection and Dr. Donald Lear, U.S.
  Environmental Protection Agency (retired).  It is fitting that this effort to which they
  volunteered so much of their invaluable experience and expertise be so dedicated.
  The benthic community index which Doug developed is also cited here  as the
  "Farrell Index" in further recognition of his unselfish contribution to the protection
  and management of our coastal resources. Much of the methodology described in
  the coastal survey portion of this guide was developed from Don Lear's pioneering
  efforts.

        The contributors to this manual sincerely hope that the good common sense,
  attention to scientific  veracity, and practical application  of the information to
  protect our marine resources - so ably personified by Don and Doug - is adequately
  reflected in these pages.
                                     Disclaimer

This manual provides technical guidance to States, Indian tribes and other authorized
jurisdictions to establish water quality criteria and standards under the Clean Water Act
(CWA), to protect aquatic life from the effects of pollution. Under the CWA, States and Indian
tribes are to establish water quality criteria to protect designated uses.  State and Indian tribal
decision makers retain the discretion to adopt approaches on a case-by-case basis that differ
from this guidance when appropriate and scientifically defensible.  While this manual
constitutes USEPA's scientific recommendations regarding biological criteria to help protect
resource quality and aquatic life, it does not substitute for the CWA or USEPA's regulations;
nor is it a regulation itself. Thus, it cannot impose legally binding requirements on USEPA,
States, Indian tribes or the regulated community, and might not apply  to a particular situation
or circumstance.  USEPA may change this guidance in the future.

This document has been approved for publication by the Office of Science and Technology,
Office of Water, U.S. Environmental Protection Agency. Mention of trade names, products, or
services does not convey and should not be interpreted as conveying, official USEPA approval,
endorsement or recommendation.

The suggested citation for this document is:

Gibson, G.R., M.L. Bowman, J. Gerritsen, and B.D. Snyder. 2000. Estuarine and Coastal Marine
Waters: Bioassessment and Biocriteria Technical Guidance. EPA 822-B-00-024.  U.S.
Environmental Protection Agency, Office of Water, Washington, DC.

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  Acknowledgments
   The authors wish to express their sincere appreciation to the Estuarine and Coastal
   Marine Biocriteria Workgroup and the peer reviewers (Arthur Newell - NYDEC,
   Judith Weis - Rutgers University, John Gentile - University of Miami, Edward Long
   NOAA, and Robert Diaz - Virginia Institute of Marine Science).

            Estuarine and Coastal Marine Biocriteria Workgroup Attendees
                                    1992 -1997
                             (Long Term Participation)
   Suzanne Bolton
   National Marine Fisheries Service
   (ST2)
   1315 East/West Hwy.
   Silver Spring, MD 20910
   301-713-2363

   Michael L. Bowman
   Tetra Tech, Inc.
   10045 Red Run Blvd.
   Suite 110
   Owings Mills, MD 21117

   Dan Campbell
   c/oUSEPAERL/ORD
   University of Rhode Island
   27 Tarzwell Drive
   Narragansett, RI 02882

   Dan Dauer
   Department of Biology
   Old Dominion University
   Norfolk, VA 23529
   804-683-3595

   Robert Diaz
   VA Institute of Marine Science
   Glouchester Point, VA 23062
   804-642-7364
Cindy Driscoll
MD Department of Natural Resources
Oxford Laboratory
904 S. Morris St.
Oxford, MD 21654
410-226-0078

Charles Eaton
Bio-Marine Enterprises
2717 3rd Avenue North
Seattle, WA 98109
206-282-4945

Larry Eaton
NC Division of Water Quality
4401 Reedy Creek Road
Environmental Sciences Bldg.
Raleigh, NC 27607
919-733-6946

Douglas Farrell*
FL Department of Environmental
Protection
3804 Coconut Dr.
Tampa, FL 33619-8218

Brigette Farren
USEPA, Region III
1650 Arch Street
Philadelphia, PA 19103-2029
215-814-2767
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance

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   Chris Faulkner
   USEPA, OWOW (4503F)
   1200 Pennsylvania Ave.
   Washington, DC 20460
   202-260-6228

   Jeroen Gerritsen
   Tetra Tech, Inc.
   10045 Red Run Blvd.
   Suite 110
   Owings Mills, MD 21117

   George Gibson, Jr. (4304)
   USEPA
   Office of Water
   Office of Science and Technology
   1200 Pennsylvania Ave.
   Washington, DC 20460
   410-305-2618

   Steve Glomb
   U.S. Fish and Wildlife Service
   4401 N Fairfax Dr.
   Room 400
   Arlington, VA 22203
   703-358-2201

   George Guillen
   TX Water Commission
   District 7
   5144 East Sam Houston Parkway, N
   Houston, TX 77015
   713-457-5191

   Susan Jackson
   USEPA, OST/HECD (4304)
   1200 Pennsylvania Avenue, NW
   Washington, DC 20460
   202-260-1800
Steve Jordan
MD Department of Natural Resources
904 South Morris Street
Oxford, MD 21654
410-226-0078

Don Kelso
George Mason University
3016 King Hall
4400 University Drive
Fairfax, VA 22030

Steve Kent
FL Department of Environmental
Protection
3319 Maguire Blvd.
Suite 232
Orlando, FL 32803

Don Lear*
Anne Arundel Community College
101 College Pkwy
Arnold, MD 21012
410-647-7100

Beth McGee
U.S. Fish and Wildlife Service
Chesapeake Bay Field Office
1777 Admiral Cochrane Drive
Annapolis, MD 21401
410-573-4524

Margaret McGinty
MD Department of Natural Resources
Tidewater Ecosystem Assessment
Annapolis, MD 21401
410-260-8637

Gil McRae
FL Marine Research Institute
100 Eighth Ave., SE
St. Petersburg, FL 33701
727-896-8626
727-823-0166 (fax)
IV
                         Acknowledgements

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   William Muir
   USEPA Region III
   1650 Arch Street (3ES41)
   Philadelphia, PA 19107
   215-814-2541

   Walt Nelson
   USEPA
   2111 SE Marine Science Dr.
   Newport, OR 97365-5260
   541-867-4041

   Art Newell
   NY Department of Environment
   Division of Marine Resources
   Building 40, SUNY
   Stonybrook, NY 11790-235
   516-444-0430
Dave Russell
USEPA Region III
Environmental Science Center
701 Mapes Road
Ft. Meade, MD 20755-5350
410-305-2656

Steve Wolfe
FL Department of Environmental
Protection
2600 Blair Stone Road
Tallahassee, FL 32399
   *  Deceased

   Acknowledgment:

   Additional scientific, technical, editorial, and production contributions were made
   by William Swietlik (USEPA), Laura Gabanski (USEPA), Jim Latimer (USEPA),
   David Scott (Dalhousie University), Gail Chmura (McGill University), Zorana
   Spasojeviz (McGill University), Jerome Diamond (Tetra Tech, Inc.), Abby Markowitz
   (Tetra Tech, Inc.), Kristen Pavlik (Tetra Tech, Inc.), Brenda Fowler (Tetra Tech, Inc.),
   Erik Leppo (Tetra Tech, Inc.), and Regina Scheibner (Tetra Tech, Inc.). This
   document was prepared by Tetra Tech, Inc.

   For the Ocean City/Bethany Beach case study in Section 13.6, thanks are given to
   David Russell, USEPA Region III provided taxonomic identifications, William Muir,
   USEPA Region III assisted with data gathering, Eileen Watts, USEPA Region III
   provided data analysis. Jeroen Gerritsen, Tetra Tech, Inc. offered constructive
   comments, and Kristen Pavlik, Tetra Tech, Inc. made final editorial changes. Their
   essential contributions to this report are greatly appreciated.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance

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Estuarine and Coastal Marine Waters:
Bioassessmentand Biocriteria Technical Guidance
                                CONTENTS

List of Figures  	  xv
List of Tables  	xxi
Acronym List	  xxv
Executive Summary	xxix

CHAPTER 1: Introduction: Bioassessment and Biocriteria  	1-1
1.1    RATIONALE	1-1
      1.1.1    Water Quality Monitoring 	1-1
      1.1.2    Advantages of Bioassessment and Biocriteria	1-1
1.2    LEGAL ORIGINS  	1-2
      1.2.1    Clean Water Act	1-2
      1.2.2    305(b) Reporting	1-2
      1.2.3    301(h) and 403(c) Programs 	1-2
      1.2.4    304(a) Criteria Methodology 	1-2
      1.2.5    Biocriteria  	1-5
1.3    USES OF BIOCRITERIA	1-5
      1.3.1    The Use of Bioassessment Data to Establish Biocriteria Appropriate
             to Designated Beneficial Uses 	1-6
      1.3.2    Expansion and Improvement of Water Quality Standards	1-9
      1.3.3    Detection of Problems Other Methods May Miss or Underestimate .. 1-9
      1.3.4    Helping the Water Resource Managers Set Priorities  	1-9
      1.3.5    Use of Biosurveys and Biocriteria to Evaluate the Success or Failure
             of Management Initiatives or Regulations	1-9
1.4    PROGRAM INTERDEPENDENCE	1-10
1.5    IMPLEMENTING BIOLOGICAL CRITERIA	1-10
1.6    CHARACTERISTICS OF EFFECTIVE BIOCRITERIA 	1-11
1.7    CONCEPTUAL FRAMEWORK	1-11
      1.7.1    Indicators of Biological Integrity and Survey Protocols  	1-12
      1.7.2    Comparison to a Reference	1-15
      1.7.3    Assessment Tiers	1-16
vii                                                                     Contents

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                        CONTENTS (CONTINUED)

CHAPTER 2:  Biological Survey	2-1
2.1    INDICATORS OF BIOLOGICAL INTEGRITY	2-1
2.2    PRIMARY MEASURES OF COMMUNITY CONDITION AND CHANGE ... 2-1
      2.2.1   Benthic Macroinvertebrates	2-1
      2.2.2   Fish	2-2
      2.2.3   Aquatic Macrophytes  	2-3
      2.2.4   Phytoplankton 	2-4
2.3    MEASURES OF COMMUNITY CONDITION AND CHANGE BEING
      DEVELOPED	2-5
      2.3.1   Zooplankton	2-5
      2.3.2   Epibenthos	2-6
      2.3.3   Paleoenvironmental Reconstruction: preserved remains  	2-7
2.4    THE USE OF INDEXES TO COMPILE AND EVALUATE
      BIOLOGICAL DATA	2-7
2.5    INDICATOR TAXA	2-9

CHAPTER 3:  Habitat Characterization  	3-1
3.1    FLOW AND HYDROGRAPHY 	3-2
      3.1.1   Circulation and Tidal Regime 	3-2
3.2    HABITAT TYPES 	3-3
      3.2.1   Open Water	3-4
      3.2.2   Soft Bottom Substrates 	3-4
      3.2.3   Hard Bottom Substrates 	3-5
      3.2.4   Aquatic Macrophytes  	3-5
      3.2.5   Beaches 	3-6
      3.2.6   Sandflats 	3-6
      3.2.7   Mudflats 	3-7
      3.2.8   Emergent Marshes	3-7
      3.2.9   Mangrove Forests	3-7
3.3    WATER COLUMN CHARACTERISTICS	3-7
      3.3.1   Salinity	3-9
      3.3.2   Temperature	3-10
      3.3.3   Dissolved Oxygen 	3-10
      3.3.4   pH	3-12
      3.3.5   Turbidity	3-12
      3.3.6   Nutrients	3-13
      3.3.7   Contaminants	3-14
      3.3.8   Depth	3-15

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                viii

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                        CONTENTS (CONTINUED)

3.4    BOTTOM CHARACTERISTICS	3-15
      3.4.1    Sediment Grain Size	3-16
      3.4.2    Total Organic Carbon, Total Volatile Solids, and Acid Volatile
              Sulfides 	3-16
      3.4.3    Sediment Oxidation-Reduction Potential	3-17
      3.4.4    Sediment Contamination 	3-18
3.5    PROPOSED HABITAT PARAMETERS	3-18
      3.5.1    Tier 0 	3-20
      3.5.2    Tier 1 	3-20
      3.5.3    Tier 2 	3-21
      3.5.4    Tier 3 	3-22

CHAPTER 4: Physical Classification and the Biological Reference Condition	4-1
4.1    CLASSIFICATION APPROACH	4-1
4.2    PHYSICAL CLASSIFICATION	4-4
      4.2.1    Geographic Region 	4-4
      4.2.2    Estuarine Categories	4-5
      4.2.3    Watershed Characteristics  	4-6
      4.2.4    Waterbody Characteristics	4-6
4.3    ESTABLISHING BIOLOGICAL REFERENCE CONDITIONS 	4-7
      4.3.1    Historical Data	4-7
      4.3.2    Reference Sites 	4-8
      4.3.3    Models	4-9
      4.3.4    Expert Opinion/Consensus	4-10
4.4    USE OF REFERENCE SITES TO CHARACTERIZE
      REFERENCE CONDITION	4-11
      4.4.1    Selected Reference Sites  	4-12
      4.4.2    Reference Condition Derived From Population Distribution	4-16
      4.4.3    Site Specific Reference Sites 	4-17

CHAPTER 5:  Sampling Program Issues, Biological Assemblages, and Design	5-1
5.1    ASSEMBLAGES 	5-1
      5.1.1    Benthic Macroinvertebrates (Infauna) 	5-2
      5.1.2    Fish	5-14
      5.1.3    Aquatic Macrophytes 	5-15
      5.1.4    Phytoplankton 	5-16
      5.1.5    Zooplankton (Developmental)	5-18
ix                                                                       Contents

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                       CONTENTS (CONTINUED)

      5.1.6   Epibenthos (Developmental) 	5-19
      5.1.7   Paleoenvironmental Systems (Developmental)	5-20
5.2    SAMPLING DESIGN ISSUES	5-21
      5.2.1   Statement of the Problem	5-23
      5.2.2   Definition of the Assessment Unit	5-24
      5.2.3   Specifying the Population and Sample Unit 	5-24
      5.2.4   Sources of Variability  	5-25
      5.2.5   Alternative Sampling Designs	5-27
      5.2.6   Optimizing Sampling  	5-30

CHAPTER 6: Water Column & Bottom Characteristics  	6-1
6.1    SALINITY, TEMPERATURE, DISSOLVED OXYGEN & pH  	6-1
6.2    SECCHI DEPTH  	6-1
6.3    DEPTH	6-1
6.4    SEDIMENT GRAIN SIZE 	6-1
      6.4.1   Estimation of "percent fines" (Tier 1)	6-1
      6.4.2   Sediment Grain Size (Tiers 2 and 3) 	6-4
6.5    RPD Layer Depth 	6-5
6.6    TOTAL VOLATILE SOLIDS	6-5
6.7    SEDIMENT CONTAMINANT TOXICITY	6-5
      6.7.1   10-day Static Sediment Toxicity Tests with Marine and Estuarine
             Amphipods  	6-5
      6.7.2   10-day Static Sediment Toxicity Tests with Marine and Estuarine
             Polychaetous Annelids	6-6
      6.7.3   Static Accute Toxicity Tests with Echinoid Embryos	6-6
      6.7.4   Toxicity Tests Using Marine Bivalves	6-7
6.8    NUTRIENTS (Tiers 2&3) 	6-7
6.9    TOTAL ORGANIC CARBON (Tiers 2&3)  	6-7
6.10   WATER COLUMN CONTAMINANTS (Tier 3)  	6-8
6.11   ACID VOLATILE SULFIDES (Tier 3) 	6-8
6.12   SEDIMENT CONTAMINANTS	6-9

CHAPTER 7:  Tier 0: Desktop Screening  	7-1
7.1    AREA AND GEOMORPHOMETRIC CLASSIFICATION 	7-1
7.2    HABITAT TYPE  	7-2
7.3    WATERSHED LAND USE 	7-2
7.4    POPULATION DENSITY 	7-2
7.5    NPDES DISCHARGES	7-2

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria  Technical Guidance                 x

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                        CONTENTS (CONTINUED)

7.6    BIOLOGICAL ASSEMBLAGES 	7-2
7.7    WATER COLUMN AND BOTTOM CHARACTERISTICS	7-3

CHAPTER 8: Tier 1   	8-1
8.1    BENTHOS 	8-1
      8.1.1    Sampling Procedure 	8-3
      8.1.2    Index Period	8-3
      8.1.3    Analysis	8-3
8.2    FISH	8-3
      8.2.1    Sampling Procedure 	8-3
      8.2.2    Sample Processing	8-4
8.3    MACROPHYTES  	8-4
8.4    PHYTOPLANKTON 	8-5

CHAPTER 9: Tier 2   	9-1
9.1    BENTHOS 	9-1
      9.1.1    Sampling Procedure 	9-2
      9.1.2    Index Period	9-3
      9.1.3    Analysis	9-3
9.2    FISH	9-3
      9.2.1    Sampling Procedure 	9-3
      9.2.2    Sample Processing  	9-3
      9.2.3    Analysis  	9-3
9.3    MACROPHYTES	9-3
      9.3.1    Sampling Procedure 	9-3
      9.3.2   Index Period	9-4
      9.3.3    Analysis	9-4
9.4    PHYTOPLANKTON 	9-4
      9.4.1    Sampling Procedure 	9-4
      9.4.2   Index Period	9-4
      9.4.3   Analysis	9-5
9.5    EPIBENTHOS (Developmental)	9-5
      9.5.1    Sampling Procedure 	9-5
      9.5.2   Index Period	9-5
      9.5.3   Analysis	9-5

CHAPTER 10: Tier 3	10-1
10.1  BENTHOS  	10-1

xi                                                                     Contents

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                        CONTENTS (CONTINUED)

      10.1.1   Sampling Procedure 	10-3
      10.1.2   Index Period	10-3
      10.1.3   Analysis	10-3
10.2   FISH	10-3
      10.2.1   Sampling Procedure 	10-3
      10.2.2   Sample Processing  	10-3
      10.2.3   Analysis  	10-3
10.3   MACROPHYTES	10-3
      10.3.1   Sampling Procedure 	10-4
      10.3.2   Index Period	10-4
      10.3.3   Analysis	10-4
10.4   PHYTOPLANKTON 	10-4
      10.4.1   Sampling Procedure 	10-4
      10.4.2   Index Period	10-4
      10.4.3   Analysis	10-4
10.5   EPIBENTHOS (Developmental)	10-4
      10.5.1   Sampling Procedure 	10-4
      10.5.2   Index Period	10-4
      10.5.3   Analysis	10-4
10.6   ZOOPLANKTON (Developmental)	10-4
      10.6.1   Sampling Procedure 	10-5
      10.6.2   Index Period	10-5
      10.6.3   Analysis	10-5
10.7   PALEOENVIRONMENTAL SYSTEMS (Developmental) 	10-5
      10.7.1   Sampling Procedure 	10-5
      10.7.2   Sample Processing	10-6
      10.7.3   Analysis	10-6

CHAPTER 11: Index Development 	11-1
11.1   OVERVIEW	11-1
11.2   CLASSIFICATION AND CHARACTERIZATION OF REFERENCE
      CONDITION	  11-2
      11.2.1   Existing Classifications	11-3
      11.2.2   Assessing a priori Classifications	11-6
11.3   INDEX DEVELOPMENT	11-6
      11.3.1   Multimetric Index 	11-7
      11.3.2   Discriminant Model Index	11-13
      11.3.3   Index Derived from Multivariate Ordination	11-14

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                 xii

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                       CONTENTS (CONTINUED)

CHAPTER 12: Quality Assurance: Design, Precision, and Management	12-1
12.1   PROGRAM DESIGN 	12-1
      12.1.1  Formulation of a Study Design 	12-2
      12.1.2  Establishment of Uncertainty Limits	12-2
      12.1.3  Optimizing the Study Design: Evaluation of Statistical Power 	12-3
12.2   MANAGEMENT	12-7
      12.2.1  Personnel	12-7
      12.2.2  Resources	12-7
12.3   OPERATIONAL QUALITY CONTROL	12-7
      12.3.1  Field Operations	12-8
      12.3.2  Laboratory Operations 	12-9
      12.3.3  Data Analysis	12-9
      12.3.4  Reporting	12-9

CHAPTER 13: Case Studies	13-1
13.1   PUGET SOUND - DEVELOPMENT OF TRAWL-BASED TOOLS FOR
      THE ASSESSMENT OF DEMERSAL FAUNA (MACROINVERTEBRATES
      AND FISHES): A PUGET SOUND PILOT STUDY	13-1
      13.1.1  Study Objectives	13-1
      13.1.2  Study Methods	13-2
      13.1.3  Study Results 	13-3
13.2   GALVESTON BAY - DEVELOPMENT OF A RAPID BIO ASSESSMENT
      METHOD AND INDEX OF BIOTIC INTEGRITY FOR COASTAL
      ENVIRONMENTS: NORTHWESTERN GULF OF MEXICO PILOT
      STUDIES	13-9
      13.2.1  Study Objectives	13-9
      13.2.2  Study Methods	13-9
      13.2.3  Study Results 	13-10
13.3   TAMPA BAY - DEVELOPMENT OF A COMMUNITY-BASED METRIC
      FOR MARINE BENTHOS: A TAMPA BAY PILOT STUDY 	13-21
      13.3.1  Study Objectives	13-21
      13.3.2  Study Methods	13-21
      13.3.3  Study Results 	13-23
13.4   NORTH CAROLINA - COMPARISON OF BIOLOGICAL METRICS
      DERIVED FROM PONAR, EPIBENTHIC TRAWL, AND SWEEP NET
      SAMPLES: A NORTH CAROLINA PILOT STUDY  	13-25
      13.4.1  Study Objectives	13-25
      13.4.2  Study Location	13-25

xiii                                                                 Contents

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                       CONTENTS (CONTINUED)

      13.4.3   Study Methods	13-25
      13.4.4   Results	13-27
      13.4.5   Summary	13-30
13.5   INDIAN RIVER, FLORIDA - FIELD VERIFICATION OF MARINE
      METRICS DEVELOPED FOR BENTHIC HABITATS: INDIAN RIVER
      LAGOON, FLORIDA PILOT STUDIES	13-33
      13.5.1   Study Objectives	13-33
      13.5.2   Study Methods	13-33
      13.5.3   Study Results  	13-33
13.6   OCEAN CITY, MD - BETHANY BEACH, DE - A PRELIMINARY STUDY
      OF THE USE OF MARINE BIOCRITERIA SURVEY TECHNIQUES
      TO EVALUATE THE EFFECTS OF OCEAN SEWAGE OUTFALLS
      IN THE MID-ATLANTIC BIGHT 	13-39
      13.6.1   Study Objectives	13-39
      13.6.2   Study Methods	13-39
      13.6.3   Study Results  	13-42
      13.6.4   Discussion and Conclusions	13-43
      13.6.5   Use of the Bethany Beach-Ocean City Data to Illustrate
             Biocriteria Development	13-50
13.7   ENVIRONMENTAL QUALITY OF ESTUARIES OF THE CAROLINIAN
      PROVINCE: 1995  	13-55
      13.7.1   Background/Objectives 	13-55
      13.7.2   Methods	13-55
      13.7.3   Benthic Infaunal Index 	13-59
      13.7.4   Results	13-61
13.8   ASSESSMENT OF THE ECOLOGICAL CONDITION OF THE
      DELAWARE AND MARYLAND COASTAL BAYS	13-65
      13.8.1   Background	13-65
      13.8.2   Methods	13-65
      13.8.3   Results/Conclusions	13-69

Glossary	 G-l
Literature Cited	L-l
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance               xiv

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                              LIST OF FIGURES

Figure

1-1     Biocriteria for given classifications of estuaries and coastal marine areas  ... 1-8

1-2     Program interdependence  	1-10

1-3     The process for progressing from the classification of an estuary to
        assessing the health of the estuary. Adapted from Paulsen et al. 1991	1-13

1-4     General comparison of Tiered Approach	1-18

3-1     Chemicals measured in sediments by the EMAP-Estuaries program	3-19

4-1     Graphical representation of bioassessment	4-3

4-2     Classification and assessment 	4-4

4-3     Biogeographical provinces. Adapted from Holland 1990	4-6

4-4     Estuarine and coastal marine biocriteria survey method useful for
        stratified random (population distribution) reference site selection.  Wet
        season/high  flow salinity pattern showing mainstem sampling sites for
        four salinity and three substrate classifications	4-8

4-5     Estuarine and coastal marine biocriteria survey method useful for
        a priori reference site selection. Wet season/high flow salinity
        pattern showing tributary reference sites and mainstem transects
        for four salinity and three substrate classifications	4-14

4-6     Estuarine and coastal marine biocriteria survey method useful
        for a prori reference site selection. Dry season/low flow salinity pattern
        showing tributary reference sites and mainstem transects for four
        salinity and three substrate classifications	4-15
xv                                                                          Contents

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                      LIST OF FIGURES (CONTINUED)

Figure

4-7     Hypothetical cumulative frequency distribution of metric values for all
        sites in a given estuarine or coastal marine class. The dotted line
        shows the metric value corresponding to the 95th percentile  	4-17

4-8     Estuarine and  coastal marine biocriteria survey method useful for
        stratified random (population distribution) reference site selection. Dry
        season/low flow salinity pattern showing mainstem sampling sites
        for four salinity and three substrate classifications	4-18

4-9     Estuarine and  coastal marine survey method for navigation channel
        assessment	4-20

4-10    Estuarine and  coastal marine biocriteria survey method useful for
        marine site selection 	4-20

5-1     Cross-section of sediment in clamshell bucket illustrating acceptable
        and unacceptable grabs	5-9

5-2     Description of various sampling methods	5-28

11-1    The process for progressing from the classification of an estuary to
        assessing the health of the estuary. Adapted from Paulsen et al. 1991	11-3

11-2    Mean number  of species and salinity at EMAP-Estuaries sampling
        stations in the  Virginian Province (from Weisberg et al. 1993)	11-4

11-3    Hypothetical box plot illustrating how a successful metric discriminates
        between reference and  stressed sites	11-9

11-4    Basis of metric scores using the 95th percentile as a standard	11-11

11-5    Steps 1-3.  Establishing site scores on a contamination gradient  	11-16

11-6    Step 5. Abundance of species A and contamination scores	11-17
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                 xvi

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                     LIST OF FIGURES (CONTINUED)

Figure

12-1    Effect of increasing sample size from na to n2 on power  	12-4

12-2    Example sample size calculations for comparing proportions and
        population means	12-8

12-3    Six qualitative and quantitative data characteristics usually employed to
        describe data quality	12-9

13-1    General location of the case studies 	13-2

13-2a   Bony fish abundance and total fish abundance for reference and
        contaminated sites	13-4

13-2b   Bony fish biomass and total fish biomass for reference and
        contaminated sites	13-4

13-2c   Mean individual weights of fish species from contaminated and reference
        stations	13-5

13-3    Ponar samples: biotic index vs. salinity  	13-28

13-4    BI, total taxa and amphipod, and caridean taxa by salinity  	13-29

13-5    Development of biocriteria	13-31

13-6    Bethany Beach - Ocean City study area  	13-40

13-7    Bethany Beach - Ocean City sampling locations	13-41

13-8a   Total number of macroinvertebrate individuals at Bethany Beach sites;
        summer data, n=9 	13-44
xvii                                                                       Contents

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                     LIST OF FIGURES (CONTINUED)

Figure

13-8b   Total number of macroinvertebrate individuals at Ocean City sites;
        summer data, n=9  	13-44

13-9a   Total number of macroinvertebrate taxa at Bethany Beach sites;
        summer data, n=9  	13-45

13-9b   Total number of macroinvertebrate taxa at Ocean City sites; summer
        data, n=9  	13-45

13-10a  Simpson's dominance index for macroinvertebrates at Bethany Beach
        sites; summer data, n=9	13-46

13-1 Ob  Simpson's dominance index for macroinvertebrates at Ocean City sites;
        summer data, n=9  	13-46

13-lla  Shannon-Wiener diversity index for macroinvertebrates at Bethany
        Beach sites; summer data, n=9	13-47

13-llb  Shannon-Wiener diversity index for macroinvertebrates at Ocean City
        sites; summer data, n=9	13-47

13-12a  Richness index for macroinvertebrates at Bethany Beach sites;
        summer data, n=9  	13-48

13-12b  Richness index for macroinvertebrates at Ocean City sites; summer
        data, n=9  	13-48

13-13   Proposed diagnostic nearfield station array 	13-51

13-14   1995 Carolinian Province sampling stations 	13-56

13-15   Frequency distribution of index scores for undegraded vs. degraded
        stations in 1993/1995 "development" data set 	13-62
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                xviii

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                     LIST OF FIGURES (CONTINUED)

Figure

13-16   Comparison of the percent of expected bioeffects detected with the
        benthic index vs. (A) four sediment bioassays and (B) three individual
        infaunal attributes	13-63

13-17   Percent area (and 95% C.I.) of CP estuaries with higher > 1.5 to < 3),
        and low (< 1.5) benthic index values	13-64

13-18   Comparison of benthic index values by estuarine class and subregion  ... 13-64
xix                                                                      Contents

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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                      xx

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                              LIST OF TABLES

Table

1-1    Applications of estuarine biological monitoring protocols and biocriteria ... 1-3

1-2    Impacts on the marine environment of the Southern California Bight.
       Modified from Bernstein et al. 1991  	  1-7

3-1    Habitat measurements for estuaries and coastal marine waters	3-23

4-1    Comparison of elements for characterizing reference conditions (adapted
       from Gerritsen et al. 1995)  	4-9

5-1    Potential benthic macroinvertebrate metrics	5-3

5-2    Metrics from which the EMAP Virginian and Louisianian benthic indexes
       were developed	5-4

5-3    Sampling summary for infaunal benthic macroinvertebrates 	5-5

5-4    Summary of bottom sampling equipment (adapted from USEPA 1992,
       Klemm et al. 1992, and ASTM 1991)	5-7

5-5    Mesh sizes used in estuary benthic monitoring programs	5-14

5-6    Sampling summary for fish	5-15

5-7    Potential aquatic macrophyte metrics  	5-17

5-8    Sampling summary for aquatic macrophytes	5-17

5-9    Sampling summary for phytoplankton	5-17

5-10   Sampling summary for epibenthos	5-20

5-11   Potential paleoecological indicators	5-22

5-12   Sampling summary for paleoenvironmental systems	5-22


xxi                                                                       Contents

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                      LIST OF TABLES (CONTINUED)

Table

6-1     Water Column & Bottom Characteristics. "Addition" refers to added
       detail or intensities for a parameters initiated in an earlier tier	6-2

7-1     Tier 0 Desktop screening for estuaries and coastal marine waters 	7-1

8-1     Tier 1 Assessment. Requires single field visit in spring or summer
       index period	8-2

9-1     Tier 2 Assessment. Requires two or more field visits, one of which
       should occur within chosen index period. In addition to requirements
       from Tier 0 & 1	9-2

10-1   Tier 3 Assessment. Requires four or more field visits, one of which
       should occur within the chosen index period. In addition to requirements
       from Tiers 0-2	10-2

11-1   Potential metrics for macrophytes, benthic macroinvertebrates, and fish
       that could be considered for estuaries. Redundancy can be evaluated
       during the calibration phase to eliminate overlapping metrics	11-8

11-2   Estuarine fish IBI metrics proposed by Thompson and Fitzhugh (1986) ...  11-13

11-3   Maryland estuarine fish IBI metrics	11-14

12-1   Errors in hypothesis testing	12-4

12-2   Common values of (ZK + Z2(3)2 for estimating sample size for use with
       equations 1 and 2 (Snedecor and Cochran 1980)  	12-6

12-3   Example QC elements for field and laboratory activities	12-10

13-1   A preliminary list of tolerant and sensitive fish and invertebrate species
       from the Tacoma Waterways and Quartermaster Harbor  	13-6

13-2   Candidate attributes of demersal fauna showing significant differences
       in the present study	13-7

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                xxii

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                      LIST OF TABLES (CONTINUED)

Table

13-3   Rationale for the inclusin of proposed nekton community metrics	13-12

13-4   Proposed seine metrics for use in an estuarine IBI along Texas coast	13-15

13-5   Proposed trawl metrics for use in an estuarine IBI along Texas coast  	13-16

13-6   Proposed gillnet metrics for use in estuarine IBI along Texas coast  	13-17

13-7   Proposed fish health index and condition factors for use in estuarine
       rapid bioassessments of Texas Gulf coast tidal tributaries	13-18

13-8   Advantages and disadvantages to using the epibenthic Renfro beam
       trawl for the sampling of benthos	13-22

13-9   Farrell epifaunal index results for the Fort Desoto Park - Tampa Bay
       Pilot Study 	13-24

13-10  Advantages and disadvantages noted for the three benthic assemblage
       collection methods	13-26

13-11  Functional metrics for the three benthic assemblage collection methods ... 13-28

13-12  Comparison between winter and summer samples of the ability of the
       various metrics tested to discriminate between impaired and low
       impairment sites  	13-37

13-13  Establishment of reference condition using the mean of the interquartile
       range of scores for three reference sites	13-52

13-14  Comparison of the reference condition derived biocriteria to the
       interquartile range of scores at the Bethany Beach and Ocean City
       outfalls	13-53

13-15  Estuarine resources of the Carolinian Province 	13-57

13-16  Core environmental indicators for the Carolinian Province	13-58

xxiii                                                                        Contents

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                     LIST OF TABLES (CONTINUED)

Table

13-17  Exposure indicators under development in the Carolinian Province	13-59

13-18  Environmental parameters for the Mary land/Delaware Coastal Bays  .... 13-68

13-19  Chesapeake Bay submerged aquatic vegetation habitat requirements
       for a polyhaline environment (Dennison et al. 1993)	13-68
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance               xxiv

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  Acronym  List
    APHA



    AVS



    BMP



    CCA



    CDF



    CSREES



    CTD



    CV



    CWA



    DFA



    DGPS



    DMRs



    DNR



    DO



    EMAP



    EPA



    ER-L



    ER-M



    FEI



    FTE



    CIS



    GPS



    IBI



    ITI
American Public Health Association



Acid Volatile Sulfides



Best Management Practices



Canonical Correspondence Analysis



Cumulative Distribution Function



Cooperative State Research, Education, & Extension Service



Conductivity - Temperature - Depth Meter



Coefficient of Variation



Clean Water Act



Discriminant Function Analysis



Differential Global Positioning System



Discharge Monitoring Reports



Department of Natural Resources



Dissolved Oxygen



Environmental Monitoring & Assessment Program



Environmental Protection Agency



Effects Range-Low



Effects Range-Median



Farrell Epifaunal Index



Full Time Equivalent



Geographic Information System



Global Positioning System



Chesapeake Bay Estuarine Index of Biotic Integrity



Infaunal Trophic Index
xxv
                                             Acronym List

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    MDS



    NMDS



    NMFS



    NOAA



    NODC



    NPDES



    NS&T



    PAHs



    PCA



    PCBs



    PCE



    PCS



    POTW



    QA



    QC



    RBP



    RPD



    SAV



    SEM



    SOP



    SPM



    SQG



    SQT



    STORET



    TDN



    TDP
Multidimensional Scaling



Non-metric Multidimensional Scaling



National Marine Fisheries Service



National Oceanic and Atmospheric Administration



National Oceanographic Data Center



National Pollutant Discharge Elimination System



National Status & Trends



Polyaromatic Hydrocarbons



Principle Components Analysis



Polychlorinated Biphenyls



Power Cost Efficiency



Permit Compliance System



Publically Owned Treatment Works



Quality Assurance



Quality Control



Rapid Bioassessment Protocol



Redox Potential Discontinuity



Submerged Aquatic Vegetation



Simultaniously Extracted Metals



Standard Operating Procedure



Suspended Particulate Matter



Sediment Quality Guidelines



Sediment Quality Triad



STOrage & RETrieval



Total Dissolved Nitrogen



Total Dissolved Phosphorus
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                              XXVI

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    TMDL

    TOC

    TPC

    TPN

    TPP

    TSS

    TVS

    TWINSPAN

    UPMGA

    USDA CSREES


    USGS
Total Maximum Daily Loads

Total Organic Carbon

Total Particulate Carbon

Total Particulate Nitrogen

Total Particulate Phosphorus

Total Suspended Solids

Total Volatile Sulfides

Two-Way INdicator SPecies ANalysis

Unweighted Pair Group Mean Averages

United States Department of Agriculture Cooperative State
Research Education Extension Service

United States Geological Survey
XXVII
                                              Acronym List

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  Executive Summary
   This technical guidance document is
   based on the concept that bioassessment
   and biocriteria programs for estuaries
   and near coastal waters are interrelated
   and critical components of
   comprehensive water resource
   protection and management.
   Understanding how estuarine
   ecosystems function and respond to
   human activity requires a holistic
   approach to protection and management
   that integrates biological assessments
   into the more traditional chemical and
   physical evaluations. Section 101 of the
   Clean Water Act requires federal and
   state  agencies to "restore and maintain
   the chemical, physical, and biological
   integrity of the nation's waters."
   Relatively undisturbed aquatic
   ecosystems have high biological integrity,
   defined as

       the condition of an aquatic
       community inhabiting unimpaired
       waterbodies of a specified habitat as
       measured by an evaluation of
       multiple attributes of the aquatic
       biota. Three critical components of
       biological integrity are that the biota
       is (1) the product of the evolutionary
       process for that locality, or site, (2)
       inclusive of a broad range of
       biological and ecological
       characteristics such as taxonomic
       richness and composition, and
       trophic structure,  and (3) is found
   in the study bio geographic region
   (USEPA19963)1

In water resource monitoring and
protection, biological criteria are an
important addition to the traditional
physical and chemical criteria used by
EPA. The relative biological integrity, or
quality, of the resource can be assessed
by comparing the health and diversity of
its biological communities to the health
and diversity of biological communities
in waters with the  same physical
characteristics but which are relatively
unimpacted by human development.
There are basically four elements that
comprise biocriteria:

   1.  Reference waters (relatively
       undisturbed areas that can be
       compared to study areas) serve
       as "benchmarks" of water
       resource quality decision
       making.

   2.  The historical record of the
       biological quality, diversity and
       productivity.

   3.  Model projection of the
       historical and reference
       condition data (if necessary).

   4.  The objective assessment of this
       information by a regional panel
       of specialists such as state,
    1 Biological criteria: Technical guidance for streams and small rivers. EPA 822-B-
    96-001.  U.S. Environmental Protection Agency, Office of Water, Washington, DC.
XXIX
                          Executive Summary

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           academic, and federal estuarine
           ecologists, chemists, fisheries
           biologists, oceanographers, and
           resource managers.

   The summation of these four factors is
   the biological criterion for a given
   estuary or class of coastal water in a
   geographic region.  Examples of the
   parameters included in a biocriterion are
   community measures or indexes drawn
   from dynamic assessments of resident
   fish, benthic invertebrate, macrophyte,
   and planktonic assemblages making up
   the biological community.

   Many natural resource agencies
   throughout the United States have
   begun the process of developing and
   implementing bioassessments and
   criteria programs primarily for rivers
   and streams. This document is part of
   the effort to advance the use of these
   strategies with regard to estuaries and
   near coastal waters, thereby fostering
   the development of credible and
   practical bioassessment programs. This
   document is intended to provide
   managers and field biologists with
   functional methods and approaches for
   bioassessment  and biocriteria
   development.

   In developing biological information, it
   is imperative that the physical and
   chemical habitat be carefully measured
   and documented. Information such as
   salinity, depth, sediment grain size, and
   water quality (including pH,
   temperature, DO, nutrients, and
   toxicants) is essential to proper
   classification of the waters for
   comparison and to the potential
   subsequent investigation of possible
causes of degradation so that
responsible management can be
initiated.

This guidance provides detailed
descriptions of the appropriate habitat
measurements to make the subsequent
physical classification to be achieved.
The document then describes four levels
of investigative intensity or sampling
tiers. These tiers are suggested as one
possible approach to organizing the data
gathering efforts and investigation
needed to be able to establish biocriteria
in a scientifically defensible manner.
Other approaches using variations of
these tiers may be appropriate
depending on program objectives.

>  Tier 0 is a preliminary  review of
   existing literature and  data available
   for the estuary or coastal water of
   concern. It provides candidate
   reference sites for the development
   of a reference condition;

>  Tier I is a one-time site visit with
   preliminary data gathering to refine
   the information in Tier 0 and
   establish candidate biocriteria;

>  Tier II repeats and builds on
   measurements initiated in Tier I and
   establishes the reference condition
   data which is combined with the
   historical record, possible models or
   other extrapolations, and a
   consensus of regional expert opinion
   to establish and employ the
   biocriteria for management decision
   making;

*•  Tier III is the diagnostic
   investigation requiring the most
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                                  xxx

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       sampling events and most extensive
       parameters to help establish
       management efforts for those waters
       which do not meet the biocriteria.

   Biocriteria development is not a one size
   fits all proposition.  Biocriteria can be
   developed on biogeographical province
   basis or on a smaller local basis to
   account for the geographic, climatologic,
   and biologic variation in the country.
   Reference conditions and biocriteria
   must be specific to each part of the
   country in order to be responsive and
   useful for decision making. It is
   important to remember that such
   circumstances vary and that this
   document cannot address every
   situation or experience.  It is oriented
   toward practical decision making rather
   than research. Its primary audience is
   intended to be state and tribal resource
   managers.  It is also intended to provide
   managers and biologists with functional
   methods and approaches to facilitate the
   implementation of viable bioassessment
   and biocriteria programs that meet their
   individual needs and resources.

   Biocriteria can be used to help support
   and protect designated uses of water
   resources; expand and improve water
   quality standards; detect problems other
   water quality measurements may miss
   or underestimate; help water resource
   managers set priorities for management
   planning and, assess the relative success
   or failure of management projects.

   Biocriteria do not supersede or replace
   physical or chemical criteria for water
   resource decision making and
   management. In fact biocriteria
   augment these established measures so
USEPA and the States and Tribes are
better informed about the quality of our
nations extensive and coastal water
resources. The bioassessment/
biocriteria process is a particularly cost
effective screening tool to evaluate over
all water quality and determine water
resource status and trends.  The
following table shows the progression of
the biocriteria process.
XXXI
                          Executive Summary

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    Sequential progression of the biocriteria process.  Adapted from
    Paulsen etal. 1991.
      Step 1
Preliminary Classification to Determine Reference Conditions and
Regional Ecological Expectations
•  Resource classification
•  Determination of best representative sites (reference sites representative
  of class categories)	
      Step 2
Survey of Reference Sites and Selected Impaired Sites
•  Collection of data on biota and physical habitat
•  Compilation of raw data (taxonomic lists, abundance levels, and other
  direct measures  and observations)	
      Step 3
Final Classification
•  Test preliminary classification
•  Revise if necessary	
      Step 4
Metric Evaluation and Index Development
•  Data analysis (data summaries)
•  Testing and validation of metrics by resource class
•  Evaluation  of metrics for effectiveness in detecting impairment
•  Selection of biological endpoints
•  Aggregation of metrics into index.
•  Test the index for validity on another data set.	
      Step 5
Biocriteria Development
•  Adjustment by physical and chemical covariates
•  Adjustment by designated aquatic life use	
      Step 6
Implementation of Monitoring and Assessment Program
•  Determination of temporal variability of reference sites
•  Identification of problems	
      Step 7
Protective or Remedial Management Action
•  Initiate programs to preserve exceptional waters
•  Implement management practices to restore the biota of degraded
  waters and to identify and address the causes of this degradation
      Step 8
Continual Monitoring and Periodic Review of References and Criteria
•  Biological surveys continue to assess efficiency of management efforts
•  Evaluate potential changes in reference condition and adjust biocriteria
  as management is accomplished
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                                        XXXII

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    Chapter 1
     Introduction: Bioassessment
     and Biocriteria
   1.1    Rationale

   1.1.1   Water Quality Monitoring

   The recognition that chemical water
   quality analyses do not adequately
   predict or reflect the condition of all
   aquatic resources has led to the
   development of measures of biological
   integrity expressed by biological criteria.
   Biological surveys, criteria, and
   assessments complement physical and
   chemical assessments of water quality by
   reflecting the cumulative effects of
   human activities, and natural
   disturbances on a water body, including
   the possible causes of these effects. The
   biological approach is best used for
   detecting generalized and non-specific
   impairments to biological integrity, and
   for assessing the severity of those
   impairments. Then, chemical and
   toxicity tests, and more refined habitat
   assessments, can be used to identify
   probable causes and their sources, and to
   suggest corrective measures.

   For the purposes of bioassessment and
   biocriteria development described here,
   an estuary is a semi-enclosed water body
   that has a free connection with the open
   sea and an inflow of freshwater that
   mixes with the seawater; including
   fjords, bays, inlets, lagoons, and tidal
   rivers. Coastal marine waters are those
   marine waters adjacent to and receiving
   estuarine discharges and extending
   seaward over the continental shelf
   and/or the edge of the U.S. territorial
   sea.
1.1.2  Advantages of Bioassessment
       and Biocriteria

Bioassessment is intended to detect
biological responses to pollution and
perturbation. Routine water quality
monitoring for example, detects effects
of nutrient enrichment and chronic
acidification, but normally is not
designed to detect trace levels of
toxicants or contaminants, ephemeral
pollution events (e.g., acidic episodes,
spills, short-lived toxicants and
pesticides, short-term sediment loading),
or combined or synergistic impacts.
Bioassessment, by monitoring organisms
that integrate the effects of
environmental changes, may in time
detect these effects.

Bioassessment, coupled with habitat
assessment; i.e., physical and chemical
measurements, helps identify probable
causes of impairment not detected by
physical and chemical water quality
analyses alone, such as nonpoint source
pollution and contamination, erosion, or
poor land use practices.  The detection
of water resource impairment,
accomplished by comparing biological
assessment results to the biological
criteria, leads to more  definitive
chemical testing and investigations
which should reveal the cause of the
degradation. This, in turn, should
prompt regulatory and other
management action to alleviate the
problem. Continued biological
monitoring, with the data collected
compared to the criteria, will determine
the relative success of  the management
efforts.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      1-1

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   1.2    Legal Origins
1.2.3  301 (h) and 403(c) Programs
   1.2.1   Clean Water Act

   The CWA, Section 101, requires federal
   and state governments to "restore and
   maintain the chemical, physical, and
   biological integrity of the nation's
   waters." Thus, the Act mandates the
   restoration and maintenance of
   biological integrity in the Nation's
   waters. The combination of performing
   biological assessments and comparing
   the results with established biological
   criteria is an efficient approach for
   evaluating the biological integrity of
   aquatic ecosystems.  Other pertinent
   sections of the CWA are Sections 305(b),
   301(h), and 403(c). Table 1-1 outlines
   suggestions for the application of
   biological monitoring and biocriteria for
   estuaries through existing state programs
   and regulations.

   1.2.2  305(b) Reporting

   States and the USEPA report on the
   status and progress of water pollution
   control efforts in §305(b) reports
   submitted every two years. Inclusion of
   biological assessment results in these
   reports will improve the public
   understanding of the biological health
   and integrity of water bodies.  Many of
   the better known and widely reported
   recoveries from pollution have involved
   the renewal or reappearance of valued
   species to systems from which they had
   nearly disappeared, or the recovery of a
   viable  fishery from contaminants.
   Examples of such recoveries are the
   restoration of the lower Potomac River
   and of shellfish beds in Maine.
   Incorporation of biological integrity in
   §305(b) reports will ensure the inclusion
   of a bioassessment endpoint, and will
   make the reports more accessible and
   meaningful to many segments of the
   public.
Two other programs within USEPA that
specifically rely on biological
monitoring data in coastal marine areas
are the §301(h) Waiver Program and the
§403 (c) Ocean Discharger Program. The
§301 (h) program allows estuarine and
marine dischargers who meet specific
criteria set forth by USEPA to defer
secondary treatment if they can show
that their discharge does not produce
adverse effects on resident biological
communities. As part of the modified
NPDES permit received through this
waiver program, the dischargers are
required to conduct extensive biological
monitoring programs designed to detect
detrimental effects to those biological
communities.

The §403(c) Ocean Discharge Program
requires that all dischargers to marine
waters provide an  assessment of
discharge impact on the biological
community in the area of the discharge
and on the surrounding biological
communities. This program requires
extensive biological monitoring for some
dischargers. Community bioassessment
methods are valuable in this program
for trend assessment and, in some cases,
refinement into more rigorous and
definitive assessments.

1.2.4 304(a) Criteria Methodology

This technical guidance was developed
under the §304(a) requirement that,
"criteria for water quality accurately
reflecting the latest scientific knowledge
of the kind and extent of all identifiable
effects on health and welfare including,
but not limited to,  plankton, fish,
shellfish, wildlife, plant life, shorelines,
beaches, aesthetics, and recreation
which may be expected from  the
presence of pollutants in any body of
1-2
         Introduction - Bioassessment & Biocriteria

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    water . .  ." be published and updated as
    needed.

    Under this section, a guidance document
    must include information on restoration
    and maintenance of chemical, physical,
                     and biological integrity of navigable and
                     ground waters, waters of the contiguous
                     zone, and the ocean.  This also covers
                     information identifying conventional
                     pollutants, such as those classified as
                     biological oxygen demanding,
    Table 1-1.  Applications of estuarine biological monitoring protocols and biocriteria.
          Program
   Biological Monitoring and
         Assessment
   Biological Criteria
     Section 305(b)/
     Reporting
Improving data for beneficial use
assessment.
Improving water quality reporting.
 Identifying waters that are
 not achieving their aquatic
 life use support.
 Defining an understandable
 endpoint in terms of
 "biological health" or
 "biological integrity"  of
 waterbodies."
     National Estuary
     Program (NEP)
Assessing status of biological
components of estuarine systems.
Develop monitoring objectives and
performance criteria.
Establish testable hypothesis and
select statistical methods.
Assessing estuarine trophic status
and trends, and assessing
biological trends.
Select analytical methods &
alternative sampling designs.
Evaluate expected monitoring study
performance.
Implement monitoring study & data
analysis. [Monitoring and sampling
needs vary for each estuary]
Identifying estuaries that are
not attaining designated use
(including aquatic life  use)
support.
Defining estuarine biological
integrity based on a
reference condition.
Identifying impairments due
to toxic substances,
eutrophication, and habitat
modification.
     Section
     319/Nonpoint
     Source Program
Evaluating nonpoint source impacts
and sources.
Measuring site-specific ecosystem
response to  remediation or
mitigation activities.
Assessing biological resource
trends within watersheds.
Determining effectiveness of
nonpoint source controls.
     Watershed
     Protection
     Approach
Assessing biological resource
trends within watersheds.
Setting goals for watershed
and regional planning.
     TMDLs
 Identifying biological assemblage
 and habitat impairments that
 indicate nonattainment of water
 quality standards.
 Priority ranking waterbodies.
 Documenting ecological/water
 quality response as a result of
 TMDL implementation.
Identifying water
quality-limited waters that
require TMDLs.
Establishing endpoints for
TMDL development, i.e.,
measuring success.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                               1-3

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    Table 1-1 (cont'd). Applications of estuarine biological monitoring protocols and biocriteria.
         Program
   Biological Monitoring and
         Assessment
   Biological Criteria
    NPDES Permitting
Measuring improvement or lack of
improvement of mitigation  efforts.
Developing protocols that
demonstrate the relationship of
biological metrics to effluent
characteristics.
Performing aquatic life use
compliance monitoring.
Helping to verify that
NPDES permit limits are
resulting in achievement of
state water quality standard.
    State Monitoring
    Programs
Improving water quality reporting.
Documenting improvement or lack
of improvement of mitigation  efforts
including estuary clean-up efforts,
TMDL application, NPDES efforts,
nonpoint source pollution controls,
etc.
Problem identification and trend
assessment.
Prioritizing waterbodies.
Providing a benchmark for
measuring effectiveness of
controls and performing
watershed/regional
planning.
    Risk Assessment
Providing data needed to estimate
ecological risk to assessment
endpoints.
Providing an assessment or
measurement endpoint.
    Water Quality
    Criteria  and
    Standards
Developing data bases for estuarine
phytoplankton, macro invertebrates,
fish, plants, and other
assemblages.
Developing indices that assess
estuarine biota compared to a
reference.
Providing data for aquatic life use
classifications.
Providing benchmark for
identifying waterbodies that
are not attaining aquatic life
use classification.
Developing site-specific
standards.
    Section 301(h)/
    Waiver Program
Allows marine discharges who meet
USEPA criteria to defer secondary
treatment if discharge does not
produce adverse effects on resident
biological communities.
Providing threshold against
which to measure
detrimental effects on
biological communities.
    Section
    403(c)/Ocean
    Discharge Program
Requires marine dischargers to
provide an assessment of
discharge impact on biological
community in discharge area as
well as surrounding communities.
Providing threshold against
which to measure
discharger impacts on
biological communities.
     Section 304(a)/
     Criteria
     Methodology
Provides information on restoration
and maintenance of chemical,
physical, and biological integrity of
waters.
Identifies conventional pollutants,
their concentrations and effects on
surrounding communities.
Providing the benchmark for
measuring the effects of
pollutants on the biological
community.
1-4
                                Introduction - Bioassessment & Biocriteria

-------
   suspended solids, fecal coliform, and pH.
   Section 304(a)(8) authorizes USEPA to
   develop and publish methods for
   establishing and measuring water
   quality criteria for toxic pollution, on
   other bases than a pollutant by pollutant
   approach. This includes biological
   monitoring and assessment methods.
   Specific states have the authority to
   enforce more stringent regulations as
   necessary.

   1.2.5  Biocriteria

   A major purpose of developing
   biological assessment methods is to
   establish biological criteria for surface
   waters. Biological criteria are guidelines
   or benchmarks adopted by states to
   evaluate the relative biological integrity
   of surface waters.  The criteria are
   defined as "narrative expressions or
   numerical values that describe the
   biological integrity of aquatic
   communities inhabiting waters of a
   given designated aquatic life use"
   (USEPA 1990).  Biological criteria  are, in
   effect, a practical approach to
   establishing management goals designed
   to protect or restore biological integrity.
   Biocriteria can be adopted by a State into
   their water quality standards, along with
   chemical, physical and toxicity criteria to
   better protect aquatic life uses of
   waterbodies.

   Biocriteria can be developed from
   reasonable expectations for the locality
   based on: historical data; reference
   conditions; empirical models; and the
   consensus judgment of regional experts
   (Section 1.4.2). The reference condition
   component of biocriteria requires
   minimally impaired reference sites
   against which the study area may be
   compared.  Minimally impaired sites are
   not necessarily pristine; they must,
   however, exhibit minimal influence by
   human activities relative  to the overall
   region of study (USEPA 1996a). In some
instances, "minimally impaired" sites
are not available because the entire area
has been degraded. Biocriteria are then
based on historical data, empirical
models if appropriate, and expert
judgement to set a condition better than
present sites. Restoration of the
degraded area must therefore be
accomplished before any such reference
sites can be established.

Biological criteria typically include the
condition of aquatic communities at
designated reference sites as an
important component. The conditions
of aquatic life found at these sites are
used to help detect both the causes and
levels of risk to biological integrity at
other sites of that type in a region. In
keeping with the policy of not
degrading the resource, the reference
conditions — like the criteria they help
define — are expected to be upgraded
with each improvement to the water
resource.  It is important that biological
criteria not be based on data derived
from degraded reference sites. In fact, a
concerted effort should be made by
States and other jurisdictions to preserve
the quality of designated reference sites
by setting those areas aside in preserves
or parks or by inclusion in use
protection programs so that continuity
of the biocriteria data base can be
maintained. Biocriteria supported by
bioassessment surveys serve several
purposes in surface water programs,
discussed in the following section.

1.3   Uses of Biocriteria

The biocriteria-bioassessment process
helps resource managers identify
impairment of designated beneficial
uses. It expands and improves
designated beneficial use classifications
and their associated water quality
standards. It detects problems other
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       1-5

-------
   survey methods may miss or
   underestimate. It is a process which
   helps the resource manager set program
   priorities. It can also be used to evaluate
   management and regulatory efforts.  For
   example, the information summarized in
   Table 1-2 indicates that wastewater
   outfalls are a controlling factor of soft
   bottom benthic communities and that
   there is a moderate scientific
   understanding of the effects of these
   outfalls specifically in the Southern
   California Bight (USEPA 1992).

   1.3.1  The Use of Bioassessment Data
          to Establish Biocriteria
          Appropriate to Designated
          Beneficial Uses

   The hypothetical information presented
   in Figure 1-1 represents data collected for
   a given class of similar estuarine or
   coastal reaches (e.g., similar sediments,
   depths, and salinities) within the same
   geographic region. For these areas some
   high level of resource quality can be
   conceived which represents a pristine
   condition, essentially the optimum
   potential or integrity of those waters. A
   completely unimpaired (no negative
   human impacts upon the organisms of
   the natural system) estuary or  coastal
   marine area is referred to as having
   biological integrity.  The approximation
   of this ideal quality at the top of a
   continuum can be expressed by a variety
   of environmental measures of the biota
   indicated on the vertical axis of the
   graph. The determined ideal level of
   biological measurements at the
   maximum score is shown by the upper
   horizontal line (equivalent to biological
   integrity). A second horizontal line
   somewhat below this is the level set as
   the reference condition, the attainable
   level of integrity derived from actual
   measurements from among the highest
   quality areas in the class. All
   information on this axis is expected to be
   objectively derived through the scientific
process and usually is presented in a
comprehensive index of many biological
characteristics such as an IBI or the
EMAP benthic index (Chapter 11).

The horizontal axis represents a
progression of socially determined use
designations; i.e., those predominant
uses the State has concluded are
appropriate for a particular estuary,
region or area within the class. These
hypothetical designated uses are
arranged on the graph from those
usually associated with relatively low
water resource quality on the left, to
those associated with very high,
relatively natural, resource quality on
the far right.

The potentially optimal  array of
biological criteria for this class of
waters, then, are scores between the
reference condition and the level of
biological integrity; i.e.,  between that
which is achievable and that which is
ideal. The narrower  this area, the higher
the quality of the waters throughout the
class, and the less restoration
management is required. The objective,
then, is to protect these resources.

On the same horizontal  axis, a class of
high quality regional uses are further
described by a subset of aquatic life
uses. These are the designated uses for
which management goals are also
described by desirable characteristics of
the aquatic biota to be especially
protected, such as "protection of the
health and diversity, undiminished, of
all indigenous species of fish and
invertebrates" for those designated as
exceptional natural waters. Resource
managers need to apply their first,
concerted efforts to those uses because it
is usually more cost-effective and
resource-conservative to protect existing
high quality areas than it is to restore
degraded ones.
1-6
         Introduction - Bioassessment & Biocriteria

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    Table 1-2.  Impacts on the marine environment of the Southern California Bight.  Modified from
    Bernstein et al. 1991.
Valued Ecosystem Components



Sources of
Perturbation
Storms
El Ninos
California Current
Upwelling
Blooms/Invasions

Ecol. Interactions


Power Plants

Wastewater Outfalls

Dredging

Rivers/Storm Runoff
Commercial Fishing

Sport Fishing
Habitat Loss/Mod.
OilSoills
All



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KEY
Potential Importance
>>rControlling O Moderate
A Major O Some
Understanding
^H High
1 1 Moderate
1 1 Low
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-7

-------
 Figure 1-1	
 Biocriteria for
 given
 classifications of
 estuaries and
 coastal marine
 areas. Shaded
 boxes represent
 the appropriate
 biocriterion range
 for selected
 classes.
 Unshaded boxes
 represent the
 range of
 measurement
 results for test
 sites in given
 classes.  The
 vertical arrows
 above the boxes
 for the
 "significantly
 altered estuaries
 and coastal marine
 areas" class
 indicate the goal of
 raising the
 biocriterion for
 these waters over
 time in response to
 restoration efforts.
HIGH
LOW
         Range of Biological Criteria
        • Reference Condition
                       A  A
                       Altered Estuaries
                        and Coastal
                        Marine Areas
      Harbor   Shipping Channel
                                                   (Meets or Exceeds)
Protected for
 Particular
 Fisheries
Exceptional
 Natural
Estuaries
     OTHER DESIGNATED USES                   AQUATIC LIFE USES    HIGH
                      DESIGNATED USES (SOCIAL)
    Selected biocriteria with an acceptable
    range of variation, perhaps one standard
    deviation, are shown as cross hatched
    boxes appropriately located for each
    designated use. Test results for a given
    area in any use classification Cbox and
    whisker"plots showin g the full range of
    measurements including variation for
    that area) can then be compared
    graphically to the biocriterion for that
    designated use. Three interpretations of
    an estuarine or coastal marine area meets
    its criterion, meets or perhaps even
    exceeds its criterion, and fails to meet the
    criterion are illustrated.

    A fourth possible result is the marginal
    condition of significantly altered systems
    such as urban harbors or shipping
    channels.  The original condition of these
    areas may very well have been within
    the  optimal range of biotic health and
    diversity for the region, but intense
    development has significantly altered
    them so that as a group they no longer
    meet the minimum reference condition
                        for similar areas of the region.  An
                        interim biocriterion for these areas may
                        be set with the intention of progressively
                        raising the criterion when sequential
                        restoration efforts are accomplished
                        through a long range management
                        effort.

                        The "other desi gnated uses"to the left
                        of the bifurcation line may still be
                        surveyed to assist management decision
                        makers; however, they fail to meet the
                        criteria, and there are no designated
                        aquatic life uses which apply.

                        The designated uses, aquatic life uses
                        and biocriteria are all hypothetical in
                        this illustration, but the
                        interrelationships of societal and
                        scientific elements of decision making
                        should be evident. They are
                        independent processes linked by an
                        environmental ethic and the USEPA
                        policy of antidegradation of water
                        resource quality (the reference condition
                        'bottom line"so to speak).  A rational
                        decision can be made which balances
                        that which is ideal with that which is
1-8
                                  Introduction - Bioassessment & Biocriteria

-------
   achievable measured by the objective
   processes of science.

   1.3.2 Expansion and Improvement of
         Water Quality Standards

   When a State adopts biological criteria in
   their water quality standards to protect
   aquatic life uses, the criteria become
   benchmarks for decision making, and
   may form the basis for requirements in
   NPDES permits and other regulatory
   programs.

   1.3.3 Detection of Problems Other
         Methods  May Miss or
         Underestimate

   In the process of establishing biocriteria,
   more data and information is inevitably
   developed than was previously
   available. The review of this new
   information often reveals problems not
   evident before or provides expanded
   insight into existing concerns and issues.
   Armed with this information, a water
   resources manager is better able to
   examine issues and make decisions.

   1.3.4 Helping the Water Resource
         Manager Set Priorities

   In light of the new information described
   above, the schedule of activities,
   allocation of funds, and uses of
   personnel and equipment may be more
   appropriately prioritized according to
   the urgency or magnitude of the
   problems identified.

   With the expanded available biological
   information augmenting chemical and
   physical information, managers can
   apply a triage approach to water
   resource projects based on the actual
   condition of the biota affected. This is
   much like a physician evaluating
   multiple emergency medical patients.
   Essentially, areas that are critically
   impaired, those that are moderately
impaired, and those in good condition
for which protection rather than
remediation is required, can all be
identified. Rational decisions can then
be made about how to apply limited
resources for the best results in
accordance with the needs and priorities
of the state.

1.3.5  Use of Biosurveys and
      Biocriteria to Evaluate the
      Success or Failure of
      Management Initiatives or
      Regulations

The manager may design a biosurvey to
collect data before and after a permit,
regulation or other management effort
has been implemented, perhaps
augmented by spatially distributed
nearfield/farfield sampling as well.
With this information and the biocriteria
decision making benchmark, it is
possible to clearly evaluate the
environmental response of the system to
the methods applied. This is useful in
the NPDES permit review process as a
way to help determine the effectiveness
of permit controls.  Typically, biocriteria
are not used directly in NPDES permits
as effluent limitations. Biomonitoring
above and below a permit site when
compared to the established biocriteria
will reveal the adequacy of the permit to
achieve its intended purpose.

If the biota are unimpaired or
recovering, it may be wise to leave the
permit, management practice or
regulation as is. If the biota are
impaired or declining, the review
recommendation may be to change the
permit, management technique or
regulation accordingly. With NPDES
permits, the  five year review cycle
allows sufficient time for extensive
biological information to be developed
so this determination can be made with
reasonable confidence.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      1-9

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             1.4   Program Interdependence

             It should be readily evident from the
             applications described above that
             physical, chemical, and biological
             surveys and monitoring (repetitive
             surveys of the same area) and biological
             criteria are interrelated in the water
             resource management process. Figure 1-2
             illustrates this interrelationship, often
             referred to as "adaptive management."
             In this continually cycling process,
             monitoring provides the information
             necessary to identify problems and to
             establish biocriteria for the decision
             making, management planning, and
             implementation necessary to respond
             appropriately.  Continued monitoring
             then reveals the relative success of the
             effort by comparing the new results to
             those criteria again. At this point the
             criteria or the management plan may be
             adjusted as needed and the cycle repeats.
             Ideally, the estuarine  or coastal
             waters improve with  each cycle.
Figure 1-2
Program
Interdependence


             1.5   Implementing Biological
                   Criteria

             Implementing biocriteria requires an
             established and standardized
             methodology for biological assessment
             adjusted to regional or state conditions.
             Hence, guidance for state and regional
             development of biocriteria has two
elements which are described in the
biological criteria technical guidance
documents such as this one:

*•   Bioassessment Protocols are
    methods used to assess the status
    and trends of water bodies.
    Guidance documents for
    bioassessment contain suggested
    methods and protocols for
    establishing monitoring programs
    that use biological assessment.

*•   Biocriteria Guidance assists states
    in establishing biological criteria for
    water bodies. Biocriteria are a series
    of ambient water resource quality
    values or statements of condition
    that relate to the desired biological
    integrity for that class of waters.
    When established they can be used
    to evaluate similar water bodies in
    that region. Implementation of
    biocriteria requires use of
    bioassessment protocols and a state
    or regional biomonitoring database.
    The National Program Guidance for
    biocriteria describes issues related to
    development and implementation
    (USEPA1990). The first biocriteria
    technical guidance issued was for
    streams and small rivers (USEPA
    1996a). It incorporated both
    biosurvey techniques and biocriteria
    development methods.  It was
    followed by the Lakes and Reservoir
    Bioassessment and Biocriteria
    Guidance (USEPA 1998). Each of
    these documents incorporated
    biosurvey techniques and the same
    approach is being followed in
    similar documents for rivers,
    wetlands, and  coral reefs in addition
    to this present technical guidance
    for estuaries and coastal marine
    waters.
          1-10
         Introduction - Bioassessment & Biocriteria

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   1.6    Characteristics of
           Effective Biocriteria

   Generally, effective biocriteria share
   several common characteristics:

   >   Provide for scientifically sound, cost-
       effective evaluations;

   *•   Protect sensitive biological values;

   *•   Protect healthy, natural aquatic
       communities;

   *•   Support and strive for protection of
       chemical, physical, and biological
       integrity;

   *•   May include specific characteristics
       required for attainment of
       designated use;

   *•   Are clearly written and easily
       understood;

   *•   Adhere to the philosophy and policy
       of nondegradation of water resource
       quality;

   *•   Are defensible in a court of law.

   In addition, effective biocriteria are set at
   levels sensitive to anthropogenic
   impacts; they are not set so high that
   sites that have reached their full
   potential are considered as failing to
   meet the criterion, nor so low that
   unacceptably impaired sites are rated as
   meeting them, which defeats the purpose
   of the CWA. The establishment of
   formal biocriteria warrants careful
   consideration of planning, management,
   and regulatory goals and the best
   attainable condition at a site. Balanced
   biocriteria will allow multiple uses to be
   considered so that any conflicting uses
   are evaluated at the outset. The best
   balance is achieved by developing
   biocriteria that closely represent the
   natural biota, protect against further
degradation, and stimulate restoration
of degraded sites.

Developing and implementing
biological criteria occurs in three steps
(USEPA1996a):

1.   Planning the biocriteria
    development program, including:

    •   definition of program objectives;
    •   establishment of interagency
       cooperation;
    •   identifying acceptable levels of
       uncertainty for decisions made
       on the basis of biocriteria;
    •   establishing data quality
       objectives.

2.   Characterizing reference conditions
    for biocriteria and identifying
    candidate reference sites, which may
    require a biological survey.

3.   Establishing biocriteria based, in
    part, on characterized reference
    conditions and designated use
    classes of the state.

1.7    Conceptual Framework

The central principle of biological
assessment is comparison of the
biological resources of a water body to a
biological criterion based, in part, on a
reference condition.  Impairment of the
water body is judged by its departure
from the biocriteria.  This  approach
presumes that the purpose of
management is to prevent and repair
anthropogenic; i.e., human-induced,
damage to natural resources. Biological
assessment of water bodies is predicated
on our ability to define, measure, and
compare biological integrity between
similar systems. This requires an
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      1-11

-------
   operational definition of biological
   integrity as follows:

       "...the condition of the aquatic
       community inhabiting
       unimpaired water bodies of a
       specified habitat as measured by
       community structure and
       function (USEPA1990)."

   The functional definition also requires
   definitions of "unimpaired" and
   "community structure and function", and
   the habitat must be specified.
   Community structure and function is
   operationally defined by the biological
   measures chosen for bioassessment,
   consisting primarily of measures of
   species richness, trophic diversity
   (relative numbers of herbivores and top
   carnivores), and indicator species.  In
   addition to biological community
   structure and function, chemical (DO,
   salinity, contaminants, dissolved TOC,
   inorganic nitrogen, etc.) and physical
   (sediment composition) attributes are
   measured to define an unimpaired site.
   The combined attributes form the basis
   for defining reference conditions for
   biological criteria.  When unimpaired
   water bodies do not exist within a
   region, an operational definition of
   unimpaired can be developed from a
   combination of minimally impaired
   estuaries and coastal waters, historical
   information, and professional judgment
   (Section 1.7.2).  Figure 1-3 shows a
   simplified framework for progressing
   from an estuarine classification to
   assessing the health of the estuary.

   1.7.1  Indicators of Biological
          Integrity and Survey Protocols

   Several analytical approaches have been
   developed to assess the biological
   condition of waterbodies within the
   framework of comparison to reference,
   ranging in complexity from simple
   comparison of indicator values, to
development of multivariate models:

*•   Comparison of indicator values —
    Indicator of metric values can be
    compared directly to the reference
    condition, without development of
    an index. This has been used most
    often for paleoecological
    comparison, where biological
    indicators are limited to certain
    indicator species, deposition rates,
    organic carbon loss, etc. (Turner and
    Rabalais 1994, Sen Gupta et al. 1996,
    Cooper and Brush 1991, Latimer et
    al. 1997).

*•   Multimetric index — The
    multimetric approach is to define an
    array of metrics or measures that
    individually provide limited
    information on biological status, but
    when integrated, function as an
    overall indicator of biological
    condition. Metrics incorporate
    information from individual,
    population, and community levels
    into a single, ecologically-based
    index of water resource quality
    (Gray 1989, Plafkin et al. 1989, Karr
    1991). The index is typically a sum
    or an average of  standardized scores
    of its component metrics (Barbour et
    al. 1999). Developed initially for
    streams, the multimetric approach
    has increasingly been applied to
    estuaries (Weisberg 1997, Hyland et
    al. 1998).

*•   Discriminant analysis to develop an
    index from metric values — In this
    approach, metrics (calculated as
    above) are used to develop a
    multivariate discriminant analysis
    model to distinguish reference sites
    from impaired sites. The calibrated
    model is then applied to assessment
    sites to determine whether they are
    impaired. This approach was used
    in EMAP-Near Coastal for the
1-12
         Introduction - Bioassessment & Biocriteria

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Estuarine Class
Designation
*
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\, v
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and other Indicators
<^ggregatior£>
,/ Biocriteria iS.
/ Relative to J>
N^Estuary Clasa/
Assessment
of Sites






•*>k
TierS
Sampling
^x"
s



Figure 1-3
The process
for progressing
from the
classification
of an estuary
to assessing
the health of
the estuary.
Adapted from
Pauisen et al.
1991.




       Virginian and Gulf provinces (Paul
       et al. 1999, Engle et al. 1999).

   *•   Multivariate ordination
       approaches — Several approaches
       have been developed using
       rnultivariate ordination to examine
       differences in species composition
       between reference and impaired
       sites.  The purpose of ordination
       analysis is to  reduce the complexity
       of many variables (for example,
       abundances of over 100 species from
       many estuarine sites), by re-ordering
       the information into fewer variables.
       These approaches have been used to
       show the effects of oil drilling in the
       North Sea (Warwick and Clarke
       1991), and to  develop an index of
       benthic quality in California (Smith
       et al. 2000).

   While all of these approaches are
   appropriate to biocriteria development
   when properly applied, the multimetric
approach is highlighted in this
guidance. This is because it is the best
developed and most extensively used
method to date.  Investigators should
carefully consider what is most
appropriate for their specific program.
Time and experience will ultimately
determine the best approach or
combination for each state to use.
Chapter 11 goes into further detail about
methods of classification and assessment
using all three approaches.

The multimetric concept came  to fruition
with the fish Index of Biotic Integrity
(IBI) first conceived by Karr (1981). The
IBI aggregates various elements and
surrogate measures of process  into a
single assessment of biological
condition. Karr (1981) and  Karr et al.
(1986) demonstrated that combinations
of these attributes or metrics provide
valuable synthetic  assessments of the
status of water resources.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      1-13

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   A metric is a calculated term or
   enumeration representing some aspect of
   biological assemblage structure,
   function, or other measurable
   characteristic.  Similarly, each of the
   assemblages (e.g., fish, benthic
   macroinvertebrates composing the
   aquatic community) measured would be
   expected to have a response range to
   perturbation events or degraded
   conditions.  Thus, biosurveys targeting
   multiple species and assemblages; i.e.,
   multimetric, will likely provide detection
   capability over a broad range of impacts,
   and the biocriteria derived from their
   results could provide protection to a
   large segment of the ecosystem.

   Metrics can be expressed numerically as
   integers or ratios.  Consistent routines in
   normalizing individual metric values
   provide a means of combining metric
   scores which initially consisted of
   dissimilar numerical expressions.
   However, final decisions on impact/no
   impact or management actions are not
   made on the single, aggregated value
   alone. Rather, if comparisons to
   established reference values indicate an
   impairment in biological condition,
   component parameters (or metrics) are
   examined for their individual effects on
   the aggregated value and for indications
   of potential causes.

   Assessment of biological integrity using
   this multimetric approach typically
   focuses on four broad classes of
   community properties. Ecological
   systems respond to anthropogenic
   impacts with changes in one or more of
   these classes of properties (e.g., Karr et
   al. 1986, Schindler 1988, Plafkin et al.
   1989, Schindler et al. 1989, Karr 1991,
   Barbour et al. 1992). The four properties
   are:
       Health of populations, typically
       expressed as number of individuals
       per m2 or as biomass, reflecting
    possible stress from anthropogenic
    sources;

*•   Community structure and
    composition, or the number and
    kinds of species in an assemblage.
    Exotic species are typically
    undesirable, and high diversity is
    usually desirable. Species structure
    metrics include diversity and
    evenness indexes as well as presence
    of indicator species, counts of
    tolerant or intolerant species, the
    percentage of individual taxa in
    comparison to the total number
    sampled, and abundance
    proportions of taxonomic groups
    (e.g. crustaceans, mollusks,
    polychaetes), or comparisons of
    infauna vs. epifauna;

*•   Trophic structure, or the relative
    proportion of different trophic levels
    and functional feeding groups (e.g.,
    Barbour et al. 1992). In estuaries,
    abundant, diverse, and relatively
    large top carnivores (e.g.,
    piscivorous fish) are typically
    desirable as representative of a
    broad, stable, and substantial
    trophic network;

*•   System function, or the
    productivity and material cycling of
    the system or its components
    (trophic levels, assemblages,
    species).  Measures of system
    function include primary
    production and standing stock
    biomass.

Since biological integrity is defined as an
indicator of undisturbed conditions, it
too must be measured relative to those
conditions. The requirement of the
biological criteria process for a reference
by which to measure biological integrity
makes it a practical tool (sensu Peters
1991) for managing society's impact on
the natural environment.
1-14
         Introduction - Bioassessment & Biocriteria

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   Monitoring and assessment programs
   typically do not have the resources to
   measure all ecological attributes of
   concern to the public and to managers,
   and assessment tools must be cost-
   effective.  Ideally, metrics selected for
   monitoring must be scientifically valid;
   should not require large amounts of
   expensive equipment; and  should be
   relatively rapid in the field. The selected
   variables must be:

   *•   Related to Biological Integrity In
       general, almost any biological
       measurement is related to biological
       integrity, but some are more clearly
       tied to the properties of biotic
       systems of concern to society (e.g.,
       native species, fish production,
       diverse trophic structure) (Suter
       1993);

   *•   Responsive to Environmental
       Stresses Biological measurements
       and the metrics developed from
       them must respond to environmental
       stress. Metrics that are not
       monotonic; i.e., they do not
       consistently exhibit low values in
       response to one end of a stressor
       continuum and high values in
       response to the opposite end, or that
       respond oppositely to different
       stresses, are difficult to interpret in
       practice;

   *•   Measurable with Low Error
       Variability and measurement error
       should be controllable  so that a
       reasonable sampling effort yields
       sufficient precision. Index period
       sampling; i.e., sampling during
       specific time periods in the annual
       cycle, is one way to reduce seasonal
       variability.  However, there are costs
       in terms of information derived
       which may be prohibitive (see later
       discussion on seasonality);
>   Cost-effective Cost of a metric
    should be proportional to the value
    of the information obtained.
    Usually, the simplest approach is
    most cost-effective and should be
    selected so long as results are
    sufficient to the agency's objectives;

>   Environmentally Benign to
    Measure Sampling methods that
    significantly disturb or alter habitats
    and biota should be avoided.

1.7.2  Comparison to a Reference

As noted earlier, establishing biocriteria
includes determining the reference
condition.  The reference condition
establishes the basis for making
comparisons and for detecting use
impairment. Because absolutely pristine
estuarine and coastal marine habitats
probably do not exist, resource
managers must decide on acceptable
levels of minimum impacts that exist or
that are achievable in a given region.
Acceptable reference conditions will
differ among geographic regions and
states because estuarine salinity
gradients, trophic state, bottom
sediment types, morphology and
biological communities differ between
regions.

Reference conditions can be established
in a variety of ways.  It is important to
recognize that the reference condition is
best developed from a population of
sites, not from a single site. However, in
some instances, particularly coastal
environments and sites influenced by
controversial land uses, the use of site-
specific nearfield/farfield stations may
be necessary and appropriate to
augment the reference condition. They
should include information derived
from:

*•   Historical Data are usually available
    that describe biological conditions in
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      1-15

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       the estuary or coastal marine region
       over some period of time in the past.
       Careful review and evaluation of
       these data provide insight about the
       communities that once existed
       and/or those that may be
       reestablished. Review of the
       literature and existing data is an
       important initial phase in the
       biocriteria development process.
       However, if data have not been
       collected for this specific purpose,
       they need to be carefully reviewed
       before being applied;

   *•   Reference Sites are minimally
       impaired locations in the same or
       similar water bodies  and habitat
       types at which data are collected for
       comparison with test sites.
       Reference sites could include sites
       that  are away from point sources or
       concentrated nonpoint loadings; sites
       in sub-estuaries; sites occurring
       along impact gradients
       (nearfield/farfield); and regional
       reference sites that may be applied to
       a variety of test sites  in a given area;

   *•   Models include mathematical
       models (logical constructs following
       from first principles and
       assumptions), statistical models
       (built from observed relationships
       between variables), or a combination
       of the two. Paleobiological
       reconstructions of historic or
       prehistoric conditions are typically
       statistical or empirical models
       (Latimer et al. 1997,  Alve 1991, Dixit
       et al. 1992).  The degree of
       complexity of mathematical models
       to predict reference conditions is
       potentially unlimited with attendant
       increased costs and loss of predictive
       ability as complexity increases
       (Peters 1991). Mathematical models
       that  predict biological reference
       conditions should only be used with
       great caution, because they are
    complex and often untestable
    hypotheses (Oreskes et al. 1994,
    Peters 1991);

*•   Expert Opinion/Consensus A
    consensus of qualified experts is
    always needed for assessing all of
    the above information; establishing
    the reference condition; and helping
    develop the biocriteria. This is
    especially the case in impaired
    locales where no candidate reference
    sites are acceptable and models are
    deemed unreliable.  In these cases,
    expert consensus is a workable
    alternative used to establish
    reference "expectations". Under
    such circumstances, the reference
    condition may be defined using a
    consensus of expert opinion based
    on sound ecological principles
    applicable to a region of interest.
    The procedures for these
    determinations and decisions
    should be well documented for the
    record.

1.7.3  Assessment Tiers

Biological surveys of estuaries and
coastal marine waters can be
implemented in several tiers, ranging
from a simple and inexpensive screening
to detailed field sampling, analysis, and
assessment.  The tiered approach gives
agencies one suggested approach for
planning, organizing, and implementing
biological surveys. Other approaches
may also be available. Agencies should
consider the approach that would work
best to meet their program objectives.
The tiers are intended to be
implemented cumulatively, that is, each
tier should incorporate the elements in
the preceding tier as appropriate for the
waters in which they are applied. Each
integrated tier includes both biological
and habitat components. Higher tiers
require successively more effort and
yield more detailed information on
1-16
         Introduction - Bioassessment & Biocriteria

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   specific biotic assemblages and potential
   stresses on the system. Higher tiers
   reflect higher quality information and
   reduced uncertainty in the final
   assessment (Costanza et al. 1992). A
   desktop screening and three field survey
   tiers are described in this document.
   Figure 1-4 provides a summary of the
   requirements for each tier.

   Tier 0 is a desktop screening assessment
   that consists of compiling documented
   information for the estuary or coastal
   marine areas of concern through a
   literature search and sending survey
   questionnaires to local experts. No field
   observations are made at this assessment
   level. Desktop screening should precede
   any of the three subsequent tiers. Its
   purpose is to support the planning for
   monitoring and more detailed
   assessments. Information to be compiled
   in Tier 0 includes: area and
   geomorphometric classification, habitat
   type, watershed land use, population
   density, NPDES discharges, water
   quality data  (salinity, temperature, DO,
   pH, turbidity), biological assemblage
   data, and water column and bottom
   characteristics.

   Tier 1 is the least complex of the survey
   approaches.  It consists of a one-time
   visit to sites during a suitable,
   predetermined index period to collect
   biological and habitat data using
   standardized methods.  The focus of this
   tier is on developing screening or survey
   information. These variables include a
   rudimentary identification of organisms
   (benthos, fish, macrophytes, or
   phytoplankon), water column
   characteristics (salinity, temperature,
   DO, pH, Secchi depth, water depth), and
   bottom characteristics (grain size, RPD
   layer depth,  total volatile solids, and
   sediment toxicity). States may choose
   some variation of this list depending on
   regional characteristics and resources.
   Evaluation of the data collected, as well
as historical data for the area, leads to an
initial classification of sites and
identification of candidate reference
sites.

Tier 2 is somewhat more complex. A
higher level of detail is incorporated into
the standardized biological methods and
multiple visits to the site are made to
address temporal variability and/or
seasonality. Another assemblage
(epibenthos) could be selected in
addition to those listed above. Water
column nutrient measurements are
added to the Tier 1 water column
characteristics.  A tactile categorization
of grain size, plus total organic carbon,
are added to the bottom characteristics.
The data collected in this tier will allow
the development of preliminary
biological criteria.

Tier 3 is the most rigorous survey tier.
Three or more assemblages are sampled
here, through multiple site visits to
account for seasonal variations in the
selected estuarine and coastal marine
biological assemblages and should
incorporate supplemental studies which
might be necessary for diagnostic
assessment of the potential causes of
observed impairments. This tier adds
water column pesticides and metals
measurements, plus full grain size
characterization (sieving to determine
percent grain size composition), acid
volatile sulfides, and sediment
contaminants. This tier also allows the
resource agency to develop a database
sufficient to support resource
management activities to reduce the
identified impairments and to develop
and refine biocriteria.

         Biological Assessment

The procedure of biological assessment
is to sample two or more biological
assemblages and record data such as
abundance, condition, biomass, and
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                                      1-17

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   Figure 1-4
   General
   comparison of
   Tiered
   Approach.
   Tiers are
   intended to be
   implemented
   cumulatively.
   Each tier
   should
   incorporate the
   elements in
   the preceding
   tier as
   appropriate for
   the waters in
   which they are
   applied, as
   necessary for
   specific
   programs.
                              Tier 0
      -No field observations
      -Desktop screening
      -Literature search
      -Questionnaires to  local experts
      -Support planning for monitoring and more detailed
       assessments
                              Tierl
-One time visit to sites during suitable, predetermined index period
-Least complex survey approach
-Develop screening/survey information
-States choose variation of variables (assemblages + water column &
 bottom characteristics) according to regional characteristics & resources
-Leads to initial classification & ID of candidate reference sites
                                                        Tier 2
                       -2 or more visits to site
                       -More  complex
                       -Possible to add another assemblage
                       -Add to water column & bottom characteristics samples
                       -Allows for development of preliminary biological criteria
                                                        Tier3
                     -4 or more visits to sites
                     -Most rigorous
                     -3 or more assemblages
                     -Incorporate supplemental studies
                     -Additions to water column & bottom characteristics
                     -Develop database to support resource management activities to reduce impairments
                      & define/refine biocriteria
   other characteristics of each species.
   These data are then used to calculate
   metrics, such as taxa richness, percent
   dominance, number of intolerant species,
   and percent abundance of tolerant
   species. Each metric is compared to its
   expected value under reference
   conditions, and rated good (similar to
   reference), fair  (different from reference),
   or poor (substantially different from
   reference). Numeric scores are assigned
   to the ratings, and the scores of all
   metrics of an assemblage are summed for
   a total score for the assemblage.  The
   total score is again compared to the
                    expected total score under reference
                    conditions, and the assemblage as a
                    whole is assigned an ordinal rating of
                    good, fair, or poor.  This second
                    comparison to reference conditions is
                    necessary because not all metrics are
                    expected to score "good" at all times
                    even in pristine conditions; the final
                    assemblage score thus takes into account
                    natural variability in metric values.

                    Once these values are satisfactorily
                    established they can be incorporated in
                    the development of a biocriterion for a
                    particular estuarine or coastal marine
1-18
                              Introduction - Bioassessment & Biocriteria

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   class. "Biological assessment" at this
   point becomes a comparison of
   monitoring scores to the biocriteria for
   management decision making.  The
   following several chapters describe the
   processes necessary to the development
   of suitable metrics and finally their
   incorporation in biological criteria for
   water resource management decision
   making.
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 Chapter 2
 Biological Survey
   2.1    Indicators of Biological
          Integrity

   A key concept underlying the approach
   to biological surveys presented in this
   document is that of biological integrity.
   Biological integrity,  discussed in greater
   detail in Section 1.7, may be
   operationally defined as

      "...the condition of the aquatic
      community inhabiting unimpaired
      waterbodies of a specified habitat as
      measured by community structure
      and function (USEPA1990)."

   Biological integrity is an ideal condition;
   estuarine and coastal marine
   communities can approach a condition
   of biological integrity when they are
   minimally impaired by human activities.
   In order to determine the degree to
   which these communities approach
   biological integrity,  it is necessary to
   measure attributes (or indicators) of
   community structure and function and
   to be able to distinguish between natural
   variations and anthropogenic impacts.

   Various techniques can be used at any
   level to document the effects of
   anthropogenic perturbations on
   biological communities. Discussion of
   these techniques falls into three general
   areas, the first two of which are
   measurement processes and the third is
   a data processing technique. They are:

   *•  Measures of community condition
      and change;

   *•  The presence or  absence of  indicator
      taxa;
*•  The use of indexes to compile and
   evaluate large amounts of biological
   data for evaluation.

The suitability of many of the
approaches in each of these categories
has long been the subject of debate
among biologists and natural resource
managers. The following discussion
examines both the utility and
uncertainty surrounding these
community assessment tools.

2.2    Primary Measures of
       Community Condition
       and Change

Whenever possible, the investigator
should try to examine two or more
assemblages because different organism
groups react differently to perturbation.
The more diverse the measures used, the
more robust the investigative technique
is and the more confidence the manager
can place in the results.  However, this
idea  must be reconciled with the
limitations of the costs of multiple and
diverse surveys and the relative
availability of reliable scientific methods
to measure some assemblages. The
prevalent approaches today are
measures of benthic macroinvertebrate
infauna, fish, and aquatic vegetation.

2.2.1  Benthic Macroinvertebrates

The benthic infauna have long been
used for water quality assessments
because of their tendency to be more
sedentary and thus more reliable site
indicators over time compared to fish
and plankton. Consequently, a larger
body of data has been accumulated for
this assemblage. Examination of benthic
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                                     2-1

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   community structure and function is a
   valuable tool for evaluating the
   condition of benthic habitats, for
   monitoring rates of recovery after
   environmental perturbations and
   potentially to provide an early warning
   of developing impacts to the system.
   Bilyard (1987) and USEPA (1991) cite the
   following specific advantages of
   monitoring benthic infauna to determine
   overall aquatic community health:

   *•   Benthic infauna are typically
       sedentary and therefore are most
       likely to respond to local
       environmental impacts, thus
       narrowing the list of possible causes
       of impairment;

   *•   Benthic infauna are sensitive to
       disturbances of habitat such that the
       communities respond fairly quickly
       with changes in species composition
       and abundance;

   *•   Benthic infauna are important
       components of the food chain and
       often act to transport not only
       nutrients, but also toxicants, to the
       rest of the system;

   *•   Monitoring benthic infauna provides
       an in situ measure of relative biotic
       integrity and habitat quality;

   *•   Of the biota typically measured, this
       assemblage has the strongest
       supporting database. Thus, it has
       extensive historical and geographic
       application.

   Some limitations of benthic infauna
   sampling include:

   *•   Relatively few state and federal
       programs have the necessary in-
       house taxonomic expertise to
       support extensive monitoring
       activities;
*•  Current methods can distinguish
   severely impaired sites from those
   that are minimally impaired.
   However, it can be difficult to
   discriminate between slightly or
   moderately impaired areas,
   particularly in estuaries (due to their
   natural spatial and temporal
   variability);

*•  The condition of benthic habitats can
   vary over relatively small scales.
   Therefore, if too few samples are
   collected from a specified area, the
   ambient heterogeneity to be
   expected may be missed, potentially
   leading to incorrect conclusions
   regarding the biological and water
   quality conditions in the area;

*•  The cost and effort to sort, count,
   and identify benthic invertebrate
   samples can be significant, requiring
   tradeoffs between expenses and the
   desired level of confidence in
   decisions based upon the collected
   data.

2.2.2  Fish

Fish are an important component of
estuarine and marine communities
because of their economic, recreational,
aesthetic and ecological roles. The
abundance and health of the fish
community is also the primary indicator
used by the public to discern the health
of a water body. Fish are good
indicators of ecological health because:

*•  They are relatively sensitive to most
   habitat disturbances;

*•  Being mobile, sensitive fish species
   may avoid stressful environments,
   leading to measurable population
   patterns reflecting that stress;
2-2
                            Biological Survey

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   >   Fish are important in the linkage
       between benthic and pelagic food
       webs;

   *•   They are long-lived and are
       therefore good indicators of long-
       term effects;

   *•   They may exhibit physiological,
       morphological, or behavioral
       responses to stresses;

   *•   Fish may exhibit obvious external
       anatomical pathology due to
       chemical pollutants;

   *•   Fish databases originally compiled
       to support state and federal fisheries
       management programs may be
       available.  These databases may
       require integration with other data
       (e.g., water quality) to be useful for
       bioassessment and biocriteria
       purposes.

   The limitations on the use of fish in
   community bioassessments include:

   >   Fish represent a relatively high
       trophic level, and lower level
       organisms may provide an earlier
       indication of water quality problems;

   *•   Some fish are resident species with
       relatively limited lifetime spatial
       ranges. Others have relatively large
       ranges, making it difficult to isolate
       probable causes of degradation that
       could occur anywhere within their
       range.  Thus, the spatial scale of
       sampling is an issue and because of
       seasonal, open water migrations,
       temporal adjustments may also be
       necessary;

   *•   Mobile organisms such as fish may
       avoid stressful environments,
       reducing their exposure to toxic or
       other harmful conditions;
*•  Fish surveys may be biased because
   of recreational and commercial
   fishing pressures on the same or
   related fish assemblages;

*•  Some fish are very habitat selective
   and their habitats may not be easily
   sampled (e.g., reef- or marsh-
   dwelling species);

*•  Since they are mobile, spatial
   variability is very high, requiring a
   large sampling effort to adequately
   characterize the fish assemblage.

2.2.3  Aquatic Macrophytes

Aquatic macrophytes in estuarine and
coastal marine waters may include
vascular plants (e.g., seagrasses) and
algae (e.g., sessile and drift). Vascular
aquatic macrophytes are a vital resource
because of their value as extensive
primary producers in estuaries.  They
are a food source for waterfowl, a
habitat and nursery area for
commercially and recreationally
important fish species, a protection
against shoreline erosion, and a
buffering mechanism for excessive
nutrient loadings. The primary
productivity that has been observed for
submerged aquatic vegetation (SAV)
communities in estuaries is among the
highest for any aquatic system (USEPA
1992).  Excessive nutrient loadings lead
to prolific phytoplankton and epiphytic
macroalgal growth on seagrass which
out-compete the seagrass through
shading, as evidenced by the 1970s and
1980s decline of eelgrass in the
Chesapeake Bay along with the current
decline in Waquoit Bay. Because of the
combined high productivity and habitat
function of this plant community, any or
all of the other estuarine or coastal
marine biota can be affected by the
presence or  absence of macrophytes.
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   Some of the advantages of using aquatic
   macrophytes in biological surveys are:

   *•   Vascular plants are a sessile
       community.  There is essentially no
       mobility to rooted vascular or
       holdfast-established algal plant
       communities, so expansion or
       contraction of seagrass beds can be
       readily measured as an
       environmental indicator;

   *•   Measurement of macrophyte
       community extent and relative
       density can be fairly easily
       accomplished by remote means,
       such as aerial photography, if the
       water is clear or shallow;

   *•   Sampling frequency is reduced
       because of the  relatively low
       community turnover compared to
       other biota such as benthic
       invertebrates or fish;

   *•   Taxonomic identification in a given
       area is generally consistent and
       straight-forward.

   Some of the disadvantages  of
   macrophyte surveys are:

   *•   Relatively slow response by the
       plant community to perturbation
       makes this a delayed indicator of
       water quality impacts. This could be
       critical if prompt management
       responses are needed;

   *•   Successional blooms of  some
       macrophytes means seasonal cycles
       need to be identified and
       accommodated by the survey
       schedule to avoid misinterpretation
       of data and false assumptions of
       water quality impacts;

   >   Changes in abundance and extent of
       submerged macrophytes are not
   necessarily related to changes in
   water quality;

*•  Aquatic macrophytes do not stand
   alone as an indicator of ecosystem
   condition; additional parameters
   (e.g., water column nutrient
   concentrations, light penetration) are
   required to interpret macrophyte
   data.

2.2.4  Phytoplankton

Many estuaries and marine waters can
be considered "plankton-dominated"
systems, which implies that this
assemblage should provide valuable
information in an assessment of
ecosystem condition. Advantages of
using plankton include:

>  Plankton provide the most notable
   indication of eutrophication in
   estuarine environments. Changes in
   nutrient concentrations can result in
   long-term changes in estuarine
   community structure and function
   and planktonic primary producers
   are one of the earliest communities
   to respond;

>  Changes in plankton primary
   production will in turn affect higher
   trophic levels of macroinvertebrates
   and fish;

>  Many states routinely monitor
   chlorophyll a as part of water quality
   monitoring due to the ease and
   relatively low cost of analysis;

>  Plankton have generally short life
   cycles and rapid reproduction rates
   making them valuable indicators of
   short-term impact.

As with all other assemblages, there are
disadvantages associated with using
phytoplankton in a biosurvey:
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   >   The fact that phytoplankton are
       subject to rapid distribution with the
       winds, tides, and currents means
       they may not remain in place long
       enough to be source identifiers of
       short-term impacts. This problem is
       compounded by the ability of some
       phytoplankton to synthesize
       atmospheric sources of nitrogen,
       thus confounding the identification
       of runoff sources of nutrients in
       estuaries and the resultant changes
       in the aquatic biota;

   *•   Taxonomic identification of
       phytoplankton can be difficult and
       time-consuming;

   *•   Competition by aquatic
       macrophytes, higher respiration
       rates, and increased grazing by
       zooplankton may counteract
       increased phytoplankton biomass
       resulting from nutrient enrichment.
       These reasons argue for
       investigating phytoplankton and
       zooplankton together as biological
       indicators;

   *•   Phytoplankton can undergo blooms,
       the causes of which might be
       indeterminate, at varying
       frequencies.

   2.3   Measures of Community
          Condition and Change
          Being Developed

   Two assemblages (zooplankton,
   epibenthos) have considerable potential
   for expanding the biological information
   available for biocriteria development
   and bioassessments. These assemblages,
   however, are considered
   "developmental" at this time. As survey
   methods become more refined and
   routine, databases for these  assemblages
   will expand and the techniques are
   expected to become sufficiently robust to
be incorporated in biocriteria
development and environmental
management decision making.
Paleoenvironmental reconstruction is an
additional technique being developed.
This technique allows investigators to
infer past conditions from the remains of
several groups of organisms found in
sediment cores, and to compare those
past conditions to current ones.

2.3.1  Zooplankton

Zooplankton consist of two basic
categories:  holoplankton which spend
their entire life cycle as plankton, and
meroplankton which are only plankton
while in the larval life stage.

Holoplankton are characterized by rapid
growth rates, broad physiological
tolerance ranges, and behavioral
patterns which promote their survival in
estuarine and marine waters. The
calanoid  copepods  are the numerically
dominant group of the holoplankton,
and the genus Acartia (A. tonsa and A.
clausi) is  the most abundant and
widespread in estuaries. Acartia is able
to withstand fresh to hypersaline waters
and temperatures ranging from 0° to
40°C.

The meroplankton  are much more
diverse than the holoplankton and
consist of the larvae of polychaetes,
barnacles, mollusks, bryozoans,
echinoderms, and tunicates as well as
the eggs, larvae, and young of
crustaceans and fish.

Zooplankton populations are subject to
extensive seasonal  fluctuations reflecting
hydrologic processes, recruitment, food
sources, temperature, and predation.
They are of considerable importance as
the link between planktonic primary
producers and higher carnivores.  As
such, they are also  early indicators of
trophic shifts in the aquatic system.
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   Advantages of zooplankton sampling
   are similar to phytoplankton:

   >   The rapid turnover of the
       community provides a quick
       response indicator to water quality
       perturbation;

   *•   Sampling equipment is inexpensive
       and easily used;

   *•   Compared to phytoplankton, sorting
       and identification is fairly easy.

   Some limitations of using zooplankton
   in biosurveys are:

   *•   The lack of a substantial data base
       for most regions;

   *•   The high mobility and turnover rate
       of zooplankton in the water column.
       While this permits a quick response
       by zooplankton to environmental
       changes on the one hand, it also
       increases the difficulty of evaluating
       cause and effect relationships for this
       assemblage.

   2.3.2  Epibenthos

   The sampling of those animals living on
   the sediments or on structures may
   prove to be the link between relatively
   low cost but highly variable fish
   community information, and the more
   consistent but expensive benthic
   macroinvertebrate surveys. The process
   has been tested with considerable
   success in Washington, North Carolina,
   and Florida (Chapter 13).

   Advantages of using this assemblage
   are:
       The relatively sedentary life style of
       some epibenthic fauna can result in
       an in-place accumulation of
       indicative pathogens and toxicants
       in individuals while the community
   composition reflects the average
   salinity, temperature and dissolved
   oxygen of that locale over an
   extended period of time (Day et al.
   1989);

*•  Ease of data collection by use of
   small otter trawls or beam trawls;

*•  Relative ease of identification
   because taxonomic lists of local
   crustaceans, mollusks, and
   echinoderms can be fairly easily
   compiled;

*•  Sampling is as inexpensive as fish
   surveys, and can often be done with
   the same or similar equipment
   during the same survey;

*•  Decapod Crustacea are usually very
   important prey for fish and are
   important components in benthic
   food webs. Some (e.g., shrimp and
   crabs) are harvested for human
   consumption.

Possible difficulties involve:

*•  Potential equipment snags and
   difficulties in macrophyte beds;

*•  Benthic infauna would likely be
   included in the trawl sample due to
   disturbance of surface sediments;

*•  As when using otter trawls for fish,
   benthic habitat may be destroyed;

*•  There is greater potential for
   avoidance by organisms than when
   sampling for benthic
   macroinvertebrates, though not as
   great as with fish surveys;

*•  Because of relatively low taxa
   numbers in some environments,
   especially coastal marine waters,
   impact response may not be as
   sensitive as desired; this could be
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       addressed by the use of indicator
       species instead of a multimetric
       approach;

   *•   Epibenthos are very sensitive to
       substrate type;

   *•   Relative sensitivity remains to be
       determined in many areas.

   2.3.3  Paleoenvironmental
          Reconstruction: preserved
          remains

   Several groups of organisms in estuaries
   leave remains in the bottom sediments.
   Some of the remains are resistant to
   decay and become a permanent
   biological record of the life in that
   waterbody. Comparisons of present-day
   biota to that of the past allow past
   environmental conditions to be inferred.
   Several groups of organisms have been
   used for this type of study in estuaries
   including diatoms, dinoflagellates, and
   foraminifera (Latimer et al. 1997).

   The approach is to elucidate
   relationships between environmental
   conditions  (for example, temperature,
   dissolved oxygen,  nutrient
   concentrations) and the relative
   abundance of target species. These
   known relationships are then used to
   infer past conditions from  the observed
   remains in the sediment. Advantages of
   studying paleoenvironmental systems
   include:

   *•   diatoms, dinoflagellate cysts, and
       foraminifera  found in sediments
       integrate conditions over broad
       spatial scales and over  time periods
       of one year or more, so that short-
       term variability does not confound
       assessment;

   *•   there is no need to adhere to an
       index period for sampling;
*•  paleoenvironmental reconstruction
   can provide a site-specific reference
   by showing conditions in the past.

Disadvantages of studying
paleoenvironmental systems include:

*•  it requires a relatively stable
   depositional environment; it is not
   suitable for shallow estuaries subject
   to frequent resuspension;

*•  it requires conditions for
   preservation of target assemblages in
   the sediment;

*•  temporal resolution is limited by the
   rate of accumulation (between 1-10
   years); it cannot be used to assess
   short-term response to stressors or to
   restoration efforts;

*•  at the time of this writing, technical
   expertise for estuarine paleoecology
   is specialized, with only a small
   handful of research institutions
   active in North America.

2.4    The Use of Indexes to
       Compile And   Evaluate
       Biological Data

It is evident that biological surveys can
generate tremendous amounts of  raw
data. The usual approach to sorting this
wealth of observations is to  summarize a
series of diverse community
measurements into one or more
dimensionless indexes, much as the
cumulative performance of a student's
work for a year can be reduced to
annual grades.

As with student grades, the use of
dimensionless indexes is a well-
established and consistent way to
evaluate and compare many discrete
units as a continuum of performance or
condition. Also similar to student
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   grading, detailed insight is lost when the
   complex interplay of so many discrete
   variables is reduced to a single score.
   The reasons for high or low scores are
   not always evident and the accuracy of
   the scoring process itself is always
   subject to debate. Indexing is the only
   way to rank order information for
   decision making. However, valuable
   insight is lost at every level of data
   reduction. There is no alternative to the
   process short of relying entirely on the
   professional judgment and wide
   variation of skill of individual biologists.
   The strengths of index development and
   use are:

   *•   It is a rational, consistent way to
       reduce large amounts of data to
       unitless, meaningful interpretations;

   *•   It is a quantitative treatment of the
       observations which permits
       statistical assessments;

   >   Interpretive bias is reduced in the
       treatment of the data.

   Conversely, indexing:

   >   Removes the decision-making from
       detailed evaluation of the data and
       information to just reporting of
       simplified indexes;

   *•   May be viewed as irrefutable,
       despite evidence to the contrary;

   *•   May obscure important and
       confounding interrelationships in
       the aquatic environment
       contributing to the index score(s);
   *•   Obscures more information as each
       level of data reduction is performed
       leading to an index value, so that
       some indexes are not sufficiently
       sensitive to reflect biotic change;
*•  Provides no indications of causes of
   the relative condition of the system.

The best way to guard against the
problems of indexing, while using it to
expedite decision-making, is to always
retain the raw data. These files can be
used to translate historical data sets into
present indexes for temporal continuity,
and even more important, they can be
evaluated to provide an interpretation
and potential diagnosis for management
action when a particular site is being
evaluated.

Indexes are most often used to  measure
community composition such as species
abundance, diversity, evenness,
richness, and dominance or conditions
such as incidence of disease,
malformation, and distributions of year
classes. These can be used to assess the
changes in community structure that
occur as a result of anthropogenic
perturbations (Boyle et al. 1990).
Community function can also be
described through indexes such as the
Infaunal Trophic Index (Word  1978,
1980, USEPA 1987).

Although indexes have long been used
in applied and theoretical ecology, it is
recognized that some of them,  when
applied individually, are insensitive to
stress-induced changes in naturally
occurring biological communities (Boyle
et al. 1990). Because of varying
sensitivities of the community  indexes,
several of them should be used
concurrently for evaluating impacts.
This approach provides greater certainty
of the data interpretation than  reliance
on any single index. Conversely, while
Ludwig and Reynolds (1988) indicate
that the most reliable community
measures in evenly matched surveys are
number of individuals and number of
taxa as direct measures; it has been
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   observed in the coastal marine studies
   associated with this guidance manual
   that, at least in two mid-Atlantic Bight
   outfall studies, the diversity index and
   the richness index both appear to be
   more responsive than number of
   individuals or number of taxa to sewage
   impacts (Gibson, Chapter 13).  For a
   more detailed discussion of the different
   indexes and their particular applications
   see Chapter 11 (Index Development)
   and Chapter 13 (Case Studies).

   2.5   Indicator Taxa

   Indicator taxa or species are those
   organisms whose presence (or absence)
   at a site indicates specific environmental
   conditions.  If an organism known to be
   intolerant of pollution is found to be
   abundant at a site, high water quality
   conditions can be inferred. On the other
   hand, dominance by pollution tolerant
   organisms implies a degraded condition.
   When available, indicator  taxa are an
   important, cost-effective preliminary
   survey tool for site assessments.
   However, the investigator should
   always ascertain that absence of an
   indicator organism is a fact and not
   merely a reflection of insufficient
   sampling.

   Swartz et al. (1985,1986,1994) have
   demonstrated the sensitivity of the
   amphipod Rhepoxynius abronius to the
   complex contaminant mixture that often
   characterizes coastal marine benthic
   pollution. Their studies were performed
   along pollution gradients from the Los
   Angeles County Sanitation Districts'
   sewage outfalls to control  conditions in
   Santa Monica Bay. The results showed
   that there were significant increases in
   the concentration of most sediment
   contaminants and significant decreases
   in benthic taxa richness and abundance
   at stations where sediment was acutely
toxic to R. abronius (Swartz et al. 1985).
More studies performed by Swartz et al.
(1994) at a designated Superfund site in
San Francisco Bay also showed that
acute sediment toxicity lab tests of R.
abronius correlated with biologically
adverse sediment contamination in the
field.  Other EMAP studies (Summers et
al. 1992) included a 10-day acute test
using the tube-dwelling amphipod,
Ampelisca abdita.  The majority of
sediments proving significantly toxic to
A. abdita were found in Louisiana and
Alabama estuarine waters.

A well-known indicator for degraded
systems is the polychaete Capitella
capitata. C. capitata and its related
species are collectively known as the C.
capitata complex.  In general, the
presence of this indicator species
corresponds to a dominance  of deposit
feeders that colonize an area as organic
pollution increases.  Swartz et al. (1985)
observed dominance of Capitella near
sewage outfalls.  A recent study in the
Mid-Atlantic Bight by the U.S. Army
Corps of Engineers (1996) suggests that
the polychaete Amastigos caperatus may
have indicator potential similar to the
Capitella complex.

A problem with using pollution tolerant
indicator organisms is that some of these
organisms may be ubiquitous and found
in naturally occurring organically
enriched habitats as well as in minimally
impaired waters.  To be useful as an
indicator, they must have displaced
other, less robust taxa and have
achieved numeric dominance.  Tolerant
and ubiquitous organisms can be found
in sediments far away from sources of
sewage pollution and long after plumes
have dispersed.

The use of the concept of "clean"
indicator species is less subject to this
form of misinterpretation. These "clean"
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   or highly sensitive organisms are less      including pollution sensitive ones and
   likely to be found in both polluted and     some that are pollution tolerant.
   high quality habitats.

   The best option may be the paired use of
   both pollution tolerant and intolerant
   indicator species.  If both indicators
   change concurrently in opposite
   directions, more confidence can be
   placed in the interpretation.

   As part of the biological survey process,
   individual indicator species are useful in
   reducing analytical costs. They are not
   only a valuable preliminary assessment
   tool, they are a cost-effective way to
   define the magnitude, spatial, and
   temporal extent of an impact (USEPA
   1992). Selected indicators should
   possess the following characteristics
   (Green 1984):

   *•   Provide sufficiently precise and
       accurate appraisals of:

           —  species of concern
           —  magnitude of anthropogenic
              disturbance;

   *•   Be cost-effective and statistically
       reliable as an alternative to
       monitoring all critical community
       measures;

   *•   Appropriate to the spatial and
       temporal scale demanded by the
       study objectives.

   When indicator species are employed in
   tandem for impact investigations, a
   gradient of species distribution can often
   be identified.  Such a gradient might
   progress from the most degraded
   waters, having low diversity
   communities dominated by pollution
   tolerant opportunistic species, to
   unimpaired or minimally impaired
   waters having diverse communities that
   are comprised of a wide range of taxa,

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 Chapter 3
 Habitat Characterization
   Biological assessment in estuaries and
   coastal marine waters is built around
   assessing two separate ecosystem
   components: the habitat and the biota.
   The biota are the resident plant and
   animal assemblages in the water body.
   The condition of the biota depends in
   part on the quality of the physical-
   chemical environment of estuaries and
   coastal marine waters; i.e., habitat.
   Habitat is in turn influenced by natural
   and catastrophic events, climate, and
   human activities. These include:

   +   Seasonal variations in precipitation,
       temperature shifts, and wind or
       wave patterns;

   +   Introduced or extirpated species able
       to influence the habitat (such as
       burrowing organisms, plants, or
       diseases/parasites;

   *   Shifts in sedimentation or scouring
       patterns;

   *•   Dredging and filling;

   *•   Shoreline or basin construction;

   +   Bulkheading and jetty construction;

   +   A variety of land use and
       navigational practices.

   This conceptual model is based on an
   understanding of the causal mechanisms
   of natural and anthropogenic stress
   effects in estuarine and coastal marine
   ecosystems.

   Estuaries integrate processes because
   they receive and retain matter and
   energy released in the watershed. Many
   human activities directly affect aquatic
habitat including discharges,
agriculture, and urban land use which
contribute materials (sediment,
nutrients, contaminants) to the water
body. Biological communities are
directly affected by their physical
habitat and water quality conditions,
and also by direct human activities such
as stocking or harvesting.

Components of biota are the biological
assemblages, such as algae, aquatic
macrophytes, benthos, epibenthos,
plankton, and fish. Habitat components
for the biological assessment of these
assemblages are hierarchical, and
include the watershed, the nearshore
zone, the water column, and the
sediment. An integrated assessment
evaluates the condition of estuaries and
coastal marine waters by aggregating
data on components of both habitat and
biota. The habitat component may be
damaged by physical stress or chemical
degradation from pollution. Thus,
habitat studies may help identify causes
of biological decline as well as being the
important determinant of the types of
biotic communities to be expected. This
classification function is crucial to
proper biocriteria development.

Habitat characterization is essential to
the proper classification of sites.
Although estuaries are by definition
transitional zones between fresh water
and the sea, and both estuaries and
coastal marine waters incorporate many
environmental gradients (e.g., salinity,
sediment grain size, depth), individual
locations and conditions are often
defined categorically. Thus, a site may
be characterized as oligohaline or
mesohaline with respect to salinity, or
sand or mud with respect to sediment
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   grain size. The composition of
   biological assemblages can vary
   dramatically along these habitat
   gradients, and valid comparisons of
   estuarine and coastal marine biological
   assemblages require that their habitats
   be correctly classified.

   3.1    Flow and Hydrography

   The type of estuarine ecosystem in a
   specific area is primarily controlled by
   the physical environment; i.e.,
   geomorphology, climate, salinity, and
   the availability of fresh water. The
   absolute values of the abiotic factors are
   not as important as the degree of
   fluctuation of factors such as the
   microclimate, water movement,
   chemical cycling, and physical structure
   (Day et al. 1989). In addition, the
   residence time of water in an estuary can
   influence overall water column
   pollutant concentrations.

   The abiotic features thought to be
   important in determining the specific
   nature of estuaries as proposed by Day
   et al. (1989) are:

   +   The degree of protection and
       buffering from direct oceanic forces;

   *   The quantity of freshwater input and
       associated dissolved and suspended
       materials;

   *   The water circulation patterns that
       are determined by riverine and tidal
       currents, geomorphology and wind.
       Tides play a critical role in
       influencing circulation, and
       biochemical and biological
       processes.  In many coastal regimes,
       the wind-driven currents are more
       predominant than tidal and
       geomorphologically-induced
       currents;
*•  Depth—stronger interactions
   between the water column and the
   bottom occur in shallow estuaries,
   thereby expediting the release of
   sediment nutrients for use by the
   phytoplankton;

*  Variability of salinity and the
   sharpness and pattern of the salinity
   gradient from the mouth to the
   headwaters. Water circulation
   influences the salinity gradient and
   the distribution of biological
   assemblages;

+  The rate of geomorphological change
   generated by various physical forces
   that control sediment transport
   within the estuary.

These controlling abiotic features are
discussed in more detail in the following
sections.

3.1.1   Circulation and Tidal Regime

Circulation is the physical process that
influences or controls many of the
ecological processes occurring in an
estuary, including the degree to which
an estuary is dominated or modified by
hydrodynamics. The three major
driving forces behind the circulation
patterns in estuaries are: (1)
gravitational circulation; (2) tidal
circulation; and (3) wind-driven
circulation. Geostrophic forcing; i.e., the
Coriolis effect, can significantly alter
estuarine circulation patterns as does
bathymetry. A notable example is the
Chesapeake Bay, where lower salinities
extend further south along the Bay's
western shore in comparison to its
eastern shore.

Gravitational circulation is induced by
water masses of differing densities and
the layering of fresh water inflow on top
of more saline waters. These density
differences cause the lighter fresh water
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                       Habitat Characterization

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   to flow over top of the saltwater to form
   what is commonly termed the "salt
   wedge".  In what is termed the
   "classical" estuarine gravitational
   circulation, the pressure surfaces of the
   fresh water are tilted seaward and the
   pressure surfaces of the saltwater are
   tilted toward the head of the estuary.
   The shear stress forces that occur at the
   interface of these two water masses
   cause vertical mixing and an eventual
   equalizing of the pressure surfaces
   somewhere near mid-depth. The fresh
   water surface layer has a net seaward
   movement, the saltwater layer on the
   bottom has a net movement upward into
   the estuary and the interface is a zone of
   no net  movement.

   Typically, density differences and the
   resulting circulation are determined by
   salinity and the circulation as is
   described above. However, in arctic or
   subarctic estuaries, the fresh water
   inflow may be substantially colder than
   the saltwater causing the fresh water
   inflow to sink below the saltwater,
   reversing the expected circulation
   pattern. In shallow lagoons that receive
   little or no fresh water input such as
   Florida Bay or Laguna Madre, the
   evaporation rate can cause the salinity of
   the water within the lagoon to rise
   higher than the ocean waters. When this
   happens, the ocean water flows into the
   estuary on the surface and the estuarine
   water flows out on the bottom, resulting
   in reverse circulation. Most often,
   though, shallow lagoons are well-mixed
   by the  wind and reverse circulation is
   only observed at the mouth of the
   lagoon.

   Tidal circulation occurs when the ebb
   and flow of the tides becomes the
   driving force behind circulation. This is
   known to occur in  estuaries with steep
   constrictions or with shallow depths and
   large tidal ranges (e.g., Puget Sound),
   and in the absence of density gradients
or wind stress. In many estuarine
systems, gravitational and tidal effects
coexist.

Wind circulation is common in estuaries
with open water, shallow water depths,
a small tidal range, and low fresh water
input.  Although the effects of wind may
be overshadowed by gravitational or
tidal forces, periods of sustained wind
can have dramatic ecological effects. In
the Ten Thousand Islands region of the
Florida Everglades, sustained northern
winds virtually drain the water out of
large portions of the estuary for
extended periods of time, exposing large
areas of mudflats. Winds that blow into
an estuary can create a net flood flow
and result in the inundation of marshes
and grass lands.  In lagoons as well,
water can pile up on one side of the
lagoon creating a seiche or a sloshing of
the water back and forth within the
lagoon.

Attention to these diverse, often
variable, and always significant
circulation patterns is  essential to
understanding the biotic distribution of
coastal and estuarine environments.
This must always be addressed before
attempting to attribute such distribution
to anthropogenic influences.

3.2   Habitat Types

Use of a single habitat to characterize
biological assemblage condition would
minimize the requirements for
expenditure of time and resources.
However, estuaries and coastal marine
waters are inherently heterogeneous
systems. By definition, a salinity
gradient is present in any estuary.
Greater numbers of species are typically
observed at the marine end of the
salinity gradient, with the fewest
numbers observed in about 3-7-ppt
(Weisberg et al. 1993). This may be due
to the unpredictable nature with which
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   the brackish water zone varies along the
   length of the estuary; driven by the
   strength and intervals of freshwater
   inflow.

   In addition to a salinity gradient,
   estuarine habitats vary in bottom
   substrates, and in the predominance of
   erosional versus depositional
   environments. The variations in these
   characteristics will lead to differences in
   the way pollutants and other stressors
   will effect the biota. For example,
   depositional environments occur where
   large amounts of terrigenous sediments
   are transported by rivers to embayments
   and where the water is sufficiently
   quiescent that fine-grained sediments
   settle out. Metals, synthetic organic
   pollutants, and other contaminants
   adsorb to fine-grained sediments
   (Holland 1990) and low-density organic
   detritus. Thus, the prevalence of
   depositional areas may reduce the
   likelihood of water column exposure of
   estuarine organisms to toxic materials,
   but may increase the exposure to
   burrowing organisms.  Conversely, the
   water column of erosional zones is often
   highly enriched as resuspended
   phosphorus is episodically mobilized.

   Habitats in estuaries and coastal marine
   waters can be classified into nine major
   categories. These habitats are
   summarized below in a progression
   from open, deep waters to decreasing
   depths near the shoreline.  The choice to
   sample one or more of these nine
   habitats will be dictated by their areal
   extent  and the nature of the problems
   being addressed.

   3.2.1   Open Water

   Sampling in open water may
   demonstrate phytoplankton blooms
   which  might be symptomatic of
   eutrophication from anthropogenic
   inputs of phosphorus or nitrogen. It
should be noted that not all
phytoplankton blooms (e.g., red tides)
result from anthropogenic stresses.
Increases in the standing stocks of
bacteria associated with fecal material
can be used to identify the presence of
sewage effluent. Open water (plankton
and nekton) studies also allow
assessment of pelagic food webs.
Sampling of pelagic finfish also occurs
in open estuarine and marine waters.
Limitations of sampling in open water
include a high degree of patchiness in
the plankton and finfish assemblages,
which necessitates the sampling of large
volumes and  areas of water before
results can be described with acceptable
precision. Because of the transitory
residence time of water parcels moving
through estuaries and the short life
cycles of planktonic flora and fauna, a
relatively high sampling frequency is
necessary to distinguish signals from
noise in this area.

3.2.2  Soft Bottom Substrates

A "soft bottom" deposit may be
dominated by mud or fine- to relatively
coarse-grained, hard-packed sand. All
of these sediments can be sampled with
appropriate grabs.  Soft bottom
substrates provide habitat for
economically valuable clams, shrimp,
and juvenile flatfishes.  Muds have a
high surface area-to-volume ratio,
providing a large surface area for the
adsorption of metals and organic
pollutants.  Also, fine-grained deposits
are often rich in biogenic adhesives
(mucopolysaccharide secreted by
microbes and meio- and macrofauna), to
which organic pollutants may adhere.
Under anoxic conditions, these deposits
are often called 'black ma yonnaise."
Conversely, sands have a lower surface
area-to-volume ratio. Thus, there is less
surface area available in the deposit to
which pollutants may adsorb.
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                       Habitat Characterization

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   A limitation of sampling in soft
   substrates is that the samples must be
   sieved before individuals can be counted
   and identified. With medium or coarse
   sands this also means large volumes of
   sediment are retained on the sieves for
   subsequent processing.  Thus,
   measurements cannot be readily made
   in the field. This is especially true for
   samples in which an abundance of
   organic debris (wood chips, seagrass
   leaves) masks the presence of small,
   cryptic organisms.

   3.2.3  Hard Bottom Substrates

   Hard bottom substrates can include
   offshore rocky outcrops; oyster, relic
   shell, and worm tube reefs; and relic
   limestone and coral outcrops. Oyster
   and mussel beds are major habitats
   supporting a complex community of
   various species essential to the biological
   diversity of estuaries such as
   Chesapeake, Florida, and Tampa Bays.
   In fjords the predominant subtidal
   habitat may be the rocky walls
   extending below the water line. An
   advantage of sampling these areas is
   that the macroalgae growing along these
   walls may be relatively sensitive to
   stress and can be used in bioassays or
   tested  for bioaccumulation (Levin and
   Kimballl984).

   Hard bottom substrates frequently occur
   in high-energy environments common
   in portions of  Alaska, Washington,
   Oregon, and northern California, as well
   as New England.  For example,
   gravel/cobble beaches are typically
   subject to high incident wave energy.
   Accumulations of fine-grained
   sediments or organic detritus are not
   expected on hard substrates either
   because there is no riverine source or
   because the energy of the environment
   prevents their accumulation. In
   addition, subtidal  rocky bottoms are
   difficult to sample remotely. A grab
sampler cannot be used, for example, as
it can in soft-bottom habitats.  Typically,
divers conduct transect observations
and take photos.

Another limitation of sampling hard
substrate is that the larvae and spores of
rocky substrate organisms are typically
planktonic; therefore, recruitment may
be strongly influenced by factors outside
the estuary. Sampling and analysis
methods must be appropriate both to the
specific type of  hard substrate as well as
regional characteristics due to the fact
that hard bottom substrates can exist
from rocky, high energy regions in
California to carbonate sediment, low
energy regions in Florida.

3.2.4   Aquatic Macrophytes

Macrophyte beds are among the most
important estuarine habitats, both
ecologically and economically.
Seagrasses (in this text, used to describe
macrophytes existing from tidal fresh to
marine conditions) create an
environment with a high degree of
structural complexity. Ecological niches
exist within the sediment,  between the
rhizomes, along the surfaces of the
leaves, and in the protected portion of
the water column within the bed. Thus,
a seagrass bed is capable of supporting a
highly diverse fauna. Seagrass beds are
among the most productive aquatic
habitats. In western Florida, Thalassia
testudinum beds produce 8,100-gm2 dry
weight of leaves at maximum standing
crop (Hillman et al. 1989).  Seagrass beds
provide "nursery areas" for juvenile
fishes and decapod crustaceans,
including many of economic
importance. Seagrass leaves are known
to bioaccumulate and possibly to
bioconcentrate metals (Ward 1989).

The right mix of nutrients  and water
clarity are key in seagrass  growth and
survival in estuarine systems. A study
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   by Stevenson et al. (1993) demonstrated
   regrowth of SAV in the Choptank River
   of the Chesapeake Bay (mesohaline
   salinity regime) was associated with
   mean DIN <10-|iM, mean DIP <0.35-|J,M;
   mean SPM (suspended particulate
   matter) <20-mgL"1; mean chlorophyll a
   (in water column) <15-|J,gL"1; and mean
   light attenuation coefficient (Kd)<2-m"1.

   In addition to serving as habitat for
   invertebrates and fish, macrophytes are
   also a biological assemblage in their own
   right and appear to be relatively
   sensitive to stress.  These beds can be
   monitored from historical photos and
   other records (Shepard etal. 1989).
   Areal reductions are often attributed to
   shading, which may result from a
   variety of anthropogenic factors
   including turbidity (from ship traffic,
   dredging, or harbor construction which
   may stir fine-grained material up into
   the water column) and eutrophication
   (where inputs of nutrients stimulate
   increases in the density of
   phytoplankton and of epiphytic macro-
   and microscopic algae on leaf surfaces).

   A limitation of sampling in seagrass
   habitats is that because of their
   ecological complexity, multiple
   sampling strategies are required to
   survey the various components of the
   fauna (Howard et al. 1989), increasing
   the expenditure of time and resources by
   investigating agencies.

   3.2.5  Beaches

   Beaches are accumulations of
   unconsolidated sediment (e.g., sand,
   cobble) extending shoreward from the
   near low-tide line to some demarcation
   such as a sea cliff or dune field, or to the
   point where permanent vegetation is
   established  (Komar 1976).  High energy
   beaches typically consist of shingle or
   cobble due to the removal of finer
   sediments by high incident wave
energy. These beaches may be
commonly found on the Atlantic coast
north of Cape Cod and along the Pacific
coast. High energy beaches of
southeastern Florida are composed of
sand and are protected by sabellariid
reefs offshore.  Low energy beaches
consist of sand and finer sediments and
are widely located on the Atlantic coast
south of Cape Cod, the Gulf of Mexico,
and along the southern Pacific coast,
and along the shorelines of most
estuaries and their tidal tributaries.

Distinct zones occur across the beach
profile, proceeding from the subtidal
offshore and inshore zones, through the
foreshore that lies between the upper
current of wave swash at high tide and
the low water mark of the backrush of
the wave swash at low tide, to the
subaerial backshore (Komar 1976).
These zones contain a gradation of
f aunal communities in response to
varying conditions of wave energy,
sediment size, and inundation by water.
Sampling across the beach profile can be
problematic, particularly  on high energy
beaches, due to the rapidly-varying
wave conditions and distribution
patterns of beach infauna and epifauna.
If attempted, core samplers can be used
on low energy beaches but quadrat
surface sampling may be  required on
high energy beaches.

3.2.6  Sandflats

Deposits described as "fine sand"
contain some silts and clays and harbor
rich communities of both deposit- and
suspension-feeding invertebrates.
"Coarse sands," found in higher energy
environments, are expected to be
dominated by suspension-feeding
invertebrates. If a sufficient erosional
force is applied to a sandy bed by the
overlying flow, sand waves form.  Sand
waves indicate a physically stressful
habitat, typified by a relatively
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                      Habitat Characterization

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   depauperate fauna. It should be noted
   that coarse sands generally contain
   relatively low faunal densities and
   biomass. However, when coarse sands
   are colonized by surf clams and
   echinoderms (sand dollars), densities
   and biomass can be very high.
   Compared to mudflats, relatively little
   organic material and few associated
   pollutants are expected to accumulate in
   coarse sands. Calcareous deposits in
   Puerto Rico and Hawaii may provide an
   exception to this in that they have high
   organic matter content and many
   pollutants (Dossis and Warren 1981).

   3.2.7  Mudflats

   Mudflats provide habitat for
   commercially important clams and other
   invertebrates and feeding habitat for
   fishes and shorebirds. Fine-grained
   sediments (i.e., clay) and organic
   detritus accumulate on mudflats.  These
   materials provide a large surface-to-
   volume ratio adsorb metals and organic
   pollutants.  This same expanse of
   usually nutrient and oxygen rich habitat
   also supports diverse primary
   producers, bacteria, plankton, and fish
   and invertebrate species in a complex
   community.

   3.2.8  Emergent Marshes

   Where present, emergent marshes may
   be extremely important components of
   estuaries and coastal marine
   embayments and lagoons because they
   filter storm water runoff from cities,
   forests, and agricultural areas.
   Emergent marshes may  also provide
   flood protection by attenuating peaks in
   storm water flow and reducing the
   erosive energy of wave action.

   Traditionally, the ecological health of a
   marsh has been characterized by
   measuring changes in its areal extent
   and the abundance and diversity of its
fish and wildlife populations. Although
"microelements" of the marsh
community (e.g., terrestrial insect
assemblages) may be more sensitive to
perturbations, these studies may be
more expensive and time-consuming to
carry out. For example, insect
populations are difficult to sample
quantitatively because of their mobility
and cyclic abundance.

3.2.9 Mangrove Forests

Low-lying tropical coasts are often
bordered by dense mangrove forests.
Temperature, particularly the frequency
of freezes, and rainfall gradients restrict
mangrove distribution. In the Gulf of
Mexico, mangrove forests occur along
the coasts south of Cedar Keys, Florida
and generally south of Port Isabel,
Texas.  Isolated stands of black
mangrove (Avicennia germinans) occur in
the Mississippi deltaic plain (Day et al.
1989), but mangroves are otherwise
absent from the northern Gulf coast,
which is dominated by salt marshes.
Significant mangrove stands also occur
south of Cape Canaveral on the east
coast of Florida (Odum and Mclvor
1990).  Mangrove forests and their
associated waters provide  valuable
habitat for a range of invertebrates,
fishes, amphibians, reptiles, birds, and
mammals. Mangroves are also valuable
as stabilizers of intertidal sediments, and
the structural complexity of the prop-
roots provides habitat for many
commercially and recreationally
important fishes.

3.3    Water  Column
       Characteristics

Many chemical and biological processes
in the environment are affected —
directly or indirectly—by the physical
characteristics of that environment
(Thomann and Mueller 1987).
Therefore, collection of physicochemical
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   data such as salinity, temperature,
   dissolved oxygen, pH, turbidity,
   nutrients, contaminants, and depth
   provides information necessary to
   evaluate biological data.

   Although organisms living in estuaries
   are adapted for life in a physically
   dynamic system, many are living near
   the limit of their physiological tolerance
   range and any long-term alteration of
   physicochemical environmental
   conditions could force their permanent
   exclusion from the estuary. Even in
   minimally-impaired estuaries, causes of
   mass mortalities have been attributed to
   depletions of dissolved oxygen and
   changes in temperature, salinity, and
   excessive  turbidity (Odum 1970).  In
   areas subjected to anthropogenic stress,
   changes in physical and chemical
   parameters may occur too frequently, be
   increased in magnitude, or be sustained
   for periods of time that only the
   extremely tolerant organisms can
   endure.

   The community composition of marine
   and estuarine fish assemblages is
   determined by the various species
   tolerances and preferences for
   environmental variables such as
   substrate, salinity, and temperature
   (Weinstein et al. 1980). These
   environmental variables are controlled
   by the quantity and direction of the flow
   of water; i.e., fresh water inflow, tidal
   cycles, circulation patterns, etc. The
   spatial and temporal distribution and
   abundance of fishes would typically be
   determined by these variables.
   Anthropogenic stress adds to the
   complexity by interfering with some
   aspects of the physiology of the fishes.

   In the Chesapeake Bay, salinity is the
   major factor affecting the regional
   distribution of macrobenthos, while
   sediment characteristics have the most
   influence over local distributions
(Carriker 1967). In the upper
Chesapeake Bay, sedimentation,
stratification, circulation, nutrient levels,
and dissolved oxygen concentrations are
all determined by the strength and
variation of the fresh water inflow from
the Susquehanna River.

Basic water quality parameters should
always be monitored to provide a record
of environmental conditions at the time
of sampling and to provide information
used in assessing the condition of
biological assemblages.  These
parameters should be measured at the
same time and location as the biological
sampling.  Such episodic data will only
serve to provide a snapshot of the
conditions at the time of sampling and
will not characterize the habitat
conditions in such dynamic ecosystems.
To properly characterize many water
quality conditions, long-term data sets
are required, including data collected at
short intervals over complete tidal cycles
for each season.

Monitoring schemes for
physicochemical water quality
characteristics of the habitat usually
involve in situ methods. Data on the
water column's characteristics can be
collected relatively inexpensively; the
expense of different methods is
generally governed by the level of
automation.  Nonetheless, it is essential
to standardize the monitoring design in
order to ensure the comparability of
monitoring data throughout the
program.

Measurements  of temperature, salinity,
and turbidity should be taken at a
minimum of four depths in the vertical
profile:  (1) 1-m below the surface, (2) 1-
m above the bottom, (3) 1-m above the
pycnocline, and (4)  1-m below the
pycnocline. If the waters are too
shallow or no stratification occurs, it
would be appropriate to take samples
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                       Habitat Characterization

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   just below the surface, at mid-depth, and
   just above the bottom. However,
   features of water masses recorded in the
   historical data; i.e., historical profiles of
   salinity, temperature, and turbidity, and
   the collection of other data types (e.g.,
   plankton community structure and
   water chemistry) should be considered
   when establishing sample depths (Pond
   and Pickard 1983).

   When using in situ methods (e.g., a
   conductivity-temperature-depth meter
   [CTD], temperature, salinity and pH
   measurements should be taken at 1-m
   intervals with a maximum interval of
   <5-m in deeper coastal waters. The
   measurements should be made over the
   entire depth profile (to within 1-m of the
   surface and bottom).  Little additional
   cost is incurred for this detailed
   characterization of the water column
   once the CTD is deployed. In  areas of
   high stratification, a smaller interval
   would be appropriate. With some of the
   newer, more expensive probes, a
   continuous readout is possible and
   discussion of depth intervals is
   immaterial.

   3.3.1   Salinity

   Estuaries are transitional zones in which
   the chemical composition varies from
   that of freshwater to marine. Salinity is
   a key determinant in the distribution of
   estuarine flora and fauna, especially for
   benthic invertebrate communities (e.g.,
   Engle et al. 1994, Holland et al. 1987,
   Summers et al. 1993, Weisberg et al.
   1993). Taxa richness is most strongly
   affected by salinity, with relatively low
   richness in brackish waters compared to
   freshwater and seawater. Taxa richness
   metrics can be expressed as a "percent of
   expected" for a given salinity (Engle et
   al. 1994, Summers et al. 1993, Weisberg
   et al. 1993).
The best-known estuarine zonation
system (the Venice system) is based on
salinity and establishes five estuarine
salinity zones:

>  Limnetic (0-0.5-ppt)
*•  Oligohaline (0.5-5-ppt)
*•  Mesohaline (5-18-ppt)
••  Polyhaline (18-30-ppt)
»•  Euhaline (>30-ppt).

Bulger et al. (1993) conducted a Principal
Components Analysis (PCA) to derive
estuarine salinity zones based on field
data on the salinity ranges of 316 species
or life stages in the mid-Atlantic  region
(primarily species found in the
Chesapeake and Delaware Bays). The
PCA showed that the data structure
underlying the salinity distributions of
the biota could be explained by five
principal components corresponding to
five overlapping salinity zones: 0-4 ppt;
2-14-ppt; 11-18-ppt; 16-27-ppt; and >24-
ppt.  This zonation scheme is similar to
the Venice  system, but is objectively
derived from the salinity distribution of
estuarine organisms. Measurement of
the ionic strength of estuarine and
marine waters is typically made using
salinity. Salinity may be defined as the
total solids in water after all carbonates
have been converted to oxides, all
bromide and iodide have been replaced
by chloride, and all organic matter has
been oxidized (APHA 1981), and is
usually reported as grams per kilogram
or parts per thousand. Salinity is most
commonly measured electronically
using a salinometer probe as part of a
CTD unit.

A related measure of the ionic strength
of water samples is the conductivity,
which is the ability of an aqueous
solution to carry an electric current.
This ability depends on the presence of
ions, their total concentration, mobility,
valence, relative concentrations,  and on
the temperature of measurement.
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   Conductivity is a more useful measure
   in the tidal fresh water portion of
   estuaries than is salinity (or chlorinity).
   Conductivity is most frequently
   measured using a CTD meter.

   The EMAP-Estuaries program collects
   point-in-time salinity measurements
   concurrently with the collection of
   biological and sediment samples using a
   CTD probe (Holland 1990). CTD-
   measured salinity is also incorporated in
   other estuarine monitoring programs;
   for example, the Chesapeake Bay
   (Holland et al. 1988,1989), San Francisco
   Bay (ABAC 1991), and Puget Sound
   (PSWQA 1988,1990,1991). Monitoring
   guidance for the National Estuary
   Program (USEPA1992) and procedural
   and monitoring guidance for the CWA
   §403 program (USEPA 1994a) both
   recommend CTD probes as the preferred
   method for collecting salinity data.

   3.3.2  Temperature

   Temperature is an important
   determinant of the rate of chemical
   reactions and biological processes.  DO
   saturation is a function of water
   temperature. Temperature influences
   the spatial and seasonal distribution of
   benthic infauna (Kendall 1983 cited in
   Dardeau et al. 1992), microbial process
   rates (Christian 1989), and temporal and
   spatial distributions of fishes (e.g.,
   Houde and Zastrow 1991). Estuarine
   water temperature in temperate regions
   is primarily a function of the
   temperatures of influent streams, rivers,
   the ocean, and tidal stage (Reid and
   Wood 1976). In the sub-tropical
   estuaries of Florida and Texas, estuarine
   temperature may be more closely related
   to incident sunlight and air temperature.
   Because most estuaries are shallow,
   there can be considerable diurnal and
   seasonal temperature variation.
   Estuarine temperature also varies with
air temperature and depth, leading to
vertical temperature gradients.

In addition to the potential influence of
natural temperature variations on
aquatic biota and chemical reactions,
anthropogenic thermal inputs can lead
to significant modifications of estuarine
and coastal marine biological
communities. A prime example is
thermal loading via discharge of cooling
water from power plants and other
industrial facilities.  The important
influence of thermal discharges is
recognized in §316 of the CWA, which
allows USEPA or states to impose
effluent limitations on thermal loading
at point sources to ensure that balanced,
indigenous populations  of shellfish, fish,
and wildlife in and on a water body will
be maintained.  Temperature should be
measured at each sampling site with a
CTD probe at 1-m intervals from the
surface to within 1-m of the bottom
concomitantly with the collection of
salinity and DO data. Diel temperature
measurements may also be needed.

3.3.3  Dissolved Oxygen

Dissolved oxygen (DO) is a basic
physiological requirement for nearly all
aquatic biota and for the maintenance of
balanced populations (exceptions being
anaerobic systems). Most estuarine
populations can tolerate short exposures
to reduced DO concentrations without
adverse effects. Extended exposures to
DO concentrations less than  60% oxygen
saturation may result in modified
behavior, reduced abundance and
productivity, adverse reproductive
effects, and mortality (Holland et al.
1989, Reish and Barnard 1960, Vernberg
1972).  Low DO conditions can also
increase the vulnerability of benthos to
predation as they extend above the
sediment surface to obtain more oxygen.
Exposure to less than 30% saturation
(~2-mgL~1) for 1 to 4 days causes
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                      Habitat Characterization

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   mortality to most species, especially
   during summer when metabolic rates
   are high. Some benthic
   macroinvertebrate species tolerate low
   DO conditions, and prolonged low DO
   concentrations frequently lead to
   changes in the composition of benthic
   macroinvertebrate assemblages in
   certain areas (Holland et al. 1989).
   Aquatic biota  exposed to low DO may
   be more susceptible to adverse effects of
   other stressors (e.g., disease, toxic
   chemicals,  habitat modification)
   (Holland 1990).

   Because DO concentration throughout
   the water column can vary widely with
   tide, time of day, wind patterns, and
   biological activity, the EMAP-Estuaries
   program conducted extensive
   comparisons of point-in-time and
   continuous collections of DO data.  In
   deeper areas of Chesapeake Bay, within
   EMAP's Virginian Province, bottom DO
   has a strong tidal signal; high tide
   corresponds to lower DO near the
   bottom. Significant serial
   autocorrelation of dissolved oxygen
   concentration persists for 6 to 8 days,
   indicating  that consecutive
   measurements taken less than 8 days
   apart may  not be independent (Holland
   1990). In some EMAP Louisianian
   Province estuaries a strong diurnal cycle
   with lower DO occurs at night (Stickney
   1984, Turner et al. 1987). Low DO in
   these shallow, often well-mixed
   estuaries may be highly variable both
   spatially and temporally (Sanford et al.
   1990, Schroeder 1979, Rabalais et al.
   1985). These conditions can lead to
   misclassification of the ecological
   condition of estuaries with respect  to
   hypoxia.

   Goals of the EMAP analyses comparing
   DO measurement approaches were to
   determine  the best measure for
   representing DO exposure, to evaluate
   the stability of DO over the sampling
(i.e., index) period, and to determine if
the characteristics of exposure to
extreme low DO can be predicted from
short-term continuous DO records
(Holland 1990). Analyses of the data for
the Virginian Province showed that
three instantaneous DO profile
measurements best characterized the
DO status of a site. In contrast, in the
Louisianian Province the minimum DO
measured over a 24-hour period was
most successful in characterizing both
low and high frequency hypoxia sites.
These differences have logistical
implications for bioassessment of
estuarine and coastal marine waters in
that instantaneous DO measurements
can be made with CTD meters equipped
with a DO probe; the 24-hour minimum
DO measurements require the use of a
continuous recording DO meter that
must be deployed and subsequently
retrieved. Consequently, dissolved
oxygen is an important habitat
parameter, but the manager must
exercise care in both sampling design
and data interpretation when attributing
biotic responses to potential hypoxia.

Collection of DO in Tier 1 of these
procedures should include an
instantaneous measurement at the same
stations and times as biological samples
are collected. Tier 2 should include
measurement of DO in the early
morning at each station as a minimum.
Tier 3 should include DO collected along
a depth profile from surface to within 1-
m of the bottom at 1-m intervals. For
more detailed characterization of DO
conditions, particularly at sites which
may undergo hypoxia, recording DO
meters may need be deployed in Tier 3.
In any case, as the EMAP experiences
indicate, careful DO profiles should be
established for each region surveyed
before any presumptions about
community response are made.
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   3.3.4 pH

   Another important indicator of the
   chemical condition of estuarine and
   coastal marine waters is pH. In
   estuaries, pH will usually be controlled
   by the mixing of seawater solutes with
   those in the fresh water inflow. A major
   factor influencing the pH of estuarine
   waters is the carbon dioxide solubility,
   which is a function primarily of salinity
   and secondarily of temperature.
   Seawater is a very stable buffering
   system containing excess bases, notably
   boric acid and borate salts, carbonic acid
   and carbonate. Surface seawater pH
   usually ranges between pH 8.1 and 8.3.
   River waters usually contain a lower
   concentration of excess bases than
   seawater; this shifts the carbonate
   buffering system toward a higher
   concentration of free carbon dioxide and
   lower pH in the upper reaches of rivers.
   Because fresh water inflow to estuaries
   is typically much less buffered than
   seawater, greater variation in pH is
   observed in the less saline portions of
   estuaries than near their  mouths.  The
   range of pH values observed in the
   upper reaches of estuaries can be 7.5 -
   9.0.

   Measurement of pH in estuaries and
   coastal marine waters can provide an
   indication of possible pollutant input
   (e.g., releases of acids or  caustic
   materials) or high concentrations  of
   phytoplankton (due to photosynthesis
   and respiration, pH varies inversely
   with the free carbon dioxide
   concentration and directly with DO).

   3.3.5  Turbidity

   The major component of turbidity in
   estuaries is silt. The volume of silt
   discharged into estuaries by streams and
   rivers varies seasonally, with the
   maximum discharge occurring during
   the wettest months.  Silt  may also be
resuspended from sediments within
estuaries.  Turbidity has two primary
effects in estuaries. First, light
penetration is reduced, which directly
affects primary production and
abundance of aquatic macrophytes in
the estuary. Second, settling of the
particulate matter can result in
deposition zones of mud, silt, other
sediments, and detritus. This deposited
material can cause changes in the
composition of benthic invertebrate
assemblages. For example, deposition of
mud and silt can result in the clogging
of gills of oysters and other filter-feeding
species and a loss of a hard substrate
required by these species. In coastal
areas, the deposition of silt in pockets of
uneven sandy bottom contributes to the
"patchy" distribution of benthic
invertebrate species, especially annelids,
amphipods, and isopods.  Deposited
material can also contain particle-
adsorbed contaminants; this can result
in contaminated sediment "hot spots".
In contrast to these negative effects on
the benthic invertebrate assemblage,
turbidity can have positive effects on the
fish assemblage by increasing protection
from predators by reduced visibility.

Turbidity can be easily assessed (as light
penetration) using a Secchi disk, which
is probably the most widely used
method for estimating light penetration
(USEPA 1992). Secchi disks are easy to
use, the results are easy to interpret, and
they are suitable for estimating light
attenuation coefficients through the
water column.  Secchi disk
measurements may vary somewhat
because of interpersonal differences in
visual acuity of observers, and,
therefore, caution must be exercised
when comparing Secchi disk readings
taken by different investigators.

If measurement of turbidity per se is
deemed necessary by a state, it may be
accomplished  in situ by using a
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                       Habitat Characterization

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   transmissometer or turbidimeter as part
   of a CTD system. Nephelometry is the
   preferred method for measuring
   turbidity because it is more sensitive,
   effective over a wider range of
   turbidities, and less sensitive to particle
   size variations than other methods
   (USEPA 1992).

   3.3.6  Nutrients

   Nutrient fluxes are central in controlling
   the primary and secondary production
   of estuaries.  Estuarine autotrophs (i.e.,
   algae, diatoms, vascular plants) require
   numerous macro- and micronutrients
   and vitamins, including C, N, P, Si, S, K,
   Mg, Na, Ca, Fe, Mn, Zn, Cu, B, Mo, Co,
   V, thiamin, cyanocobalamin, and biotin
   (Hutchinson 1967 cited in Day et al.
   1989).  Higher trophic levels are
   influenced indirectly by nutrients
   through their dependence on a
   phytoplankton food base. Nitrogen,
   phosphorus, carbon, and silicon (used
   by diatoms) are the most studied of the
   nutrients in estuaries and coastal marine
   waters (Bricker and Stevenson 1996).
   This guidance document focuses
   particularly on nitrogen and phosphorus
   as the two key, potentially limiting and
   more manageable nutrients for the
   autotrophic assemblages; i.e.,
   macrophytes, phytoplankton, to be
   incorporated in bioassessment
   procedures. The measurement of water
   column nutrient concentrations in Tiers
   2 and 3 will aid in identifying possible
   sources of biological impairment.
   NOAA maintains a nationwide database
   on eutrophication and toxic algae
   blooms that can be cited to provide
   water column information.

   It is a basic tenet of botany that multiple
   nutrients are necessary for plant growth,
   and that a shortage of any single
   nutrient will limit further growth. Thus,
   estuaries are sometimes referred to as
   "nutrient-limited." This concept is
based on the finding that, under good
growth conditions, algae have a
relatively stable N:P atomic ratio of
about 15-16:1.  This ratio is frequently
known as the Redfield ratio (Redfield
1958, Correll 1987, Malone et al. 1996).
The Redfield ratio is an approximation
and can vary depending on the stage of
algal cell division, changes in light
intensity or quality, or temperature
(Correll 1987). Even considering these
factors, measurement of nitrogen and
phosphorus concentrations in estuarine
and coastal marine waters provides a
useful benchmark for evaluating the
possible effects of increased loadings of
these nutrients. Nutrient limitations in
estuarine and coastal marine waters may
change seasonally in response to
temporal variations in nutrient loadings
in the watershed and in hydrologic
patterns. In the Chesapeake Bay,
phytoplankton appear to be P-limited
during spring when biomass reaches its
annual maximum and N-limited during
summer when phytoplankton growth
rates are highest (Malone et al. 1996). In
North Carolina estuaries, N-limitation
occurs across a trophic gradient of
highly productive (Pamlico), moderately
productive (Neuse), and less productive
systems (Beaufort, Morehead City area)
(Mallin 1994).  Phosphorus may be co-
limiting in some of these areas during
portions of the year (Mallin 1994). In the
Florida Keys and  adjacent Florida Bay,
LaPointe and Clark (1992) determined
that phosphorus is the primary limiting
nutrient, with nitrogen being co-
limiting. Smith and Hitchcock (1994)
concluded that phosphorus (and silica)
potentially limits  phytoplankton growth
in the Louisiana Bight during winter-
spring, particularly at low salinities. In
late summer nitrogen may be limiting in
higher salinity waters of the Louisiana
Bight.

Nitrogen and phosphorus occur in
estuarine and coastal marine waters in
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     3-13

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   many forms which can be variously
   described in terms of oxidation state,
   phase (solid-liquid-gas), chemical
   structure, or analytical method.
   Nitrogen forms are the most diverse,
   with nitrogen compounds ranging from
   NO3 to NH4 . Dissolved nitrogen
   species that could be incorporated into
   chemical analyses of this nutrient
   include total dissolved N (TDN), and
   dissolved inorganic nitrogen (DIN =
   NH* + NO3  + NO2)(LaPointeand
   Clark 1992).  Nitrate concentrations are
   typically controlled largely by external
   inputs to estuarine and coastal marine
   waters via land runoff. In some areas
   (e.g., Chesapeake Bay) atmospheric
   deposition may account  for an
   important fraction of the nitrogen load
   to the water body (Dickerson 1995,
   Boynton et al. 1995). Ammonia
   concentrations are highest in waters
   receiving large inputs of sewage (Day et
   al. 1989). Dissolved organic nitrogen
   (DON) can be calculated as TDN minus
   DIN (LaPointe and Clark 1992).

   Measurements of total dissolved P
   (TDP) and soluble reactive phosphorus
   (SRP) can be used to estimate dissolved
   organic phosphorus (DOP = TDP - SRP)
   (LaPointe and Clark 1992).

   3.3.7  Contaminants

   Measuring organic compounds and
   metals is particularly important because
   of the adverse effects they can have on
   aquatic life and on human health and
   recreation if these contaminants enter
   the food chain. Sources of organic and
   inorganic chemical contaminants
   include direct release to the water body,
   urban runoff, atmospheric deposition,
   industrial and municipal discharges,
   and upstream runoff (Velinsky et al.
   1994, Wade et al. 1994). Organic and
   metals contaminants in the water
   column will usually be adsorbed onto
   sediment particles, settle to the bottom,
and become a source of toxicity to
organisms and bioaccumulation to the
food chain. Contaminant analyses
should be tailored to the types of
substances known or suspected as
chemicals of potential concern at a site.
Chemical concentrations should be
compared to applicable sediment quality
guidance documents to aid in
interpretation and to provide an effort-
based assessment method. Results of
any toxicity tests conducted should be
compared against results from controls
and against statistical standards to
provide relative rankings. Chemical
analyses, toxicity tests, and benthic
analyses constitute the sediment quality
triad, originally proposed by Long and
Chapman (1985).

The Sediment Quality Triad approach,
(SQT) (Long and Chapman 1985,
Chapman et al. 1987, Long 1989,
Chapman 1996) can be used to assess
pollution-induced estuarine and coastal
marine system degradation (Schlekat et
al. 1994). In an analysis of sediment
metals concentrations from 497 sites in
Gulf of Mexico estuaries, Summers et al.
(1996) normalized metals concentrations
for extant concentrations of aluminum
to identify the concentrations expected
from natural sources versus
anthropogenic sources. Krumgalz
(1993) applied a "fingerprints" approach
to estuarine and  coastal marine
pollutant source identification.  This
approach assumes that if anthropogenic
pollutants in a particular area had
originated from the same source, then
pairwise relationships between the
concentrations of these pollutants in
sediments from various sampling sites
in the contaminated area would be
linear.  The correlations between
pollutants will depend on the origin  of
the contaminants and on the patterns of
mixing contaminated sediments and
contaminants with "pure" sediment.
Thus, the "fingerprints" can be used  to
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                      Habitat Characterization

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   trace the distribution of contaminants
   from a source, or conversely, to identify
   potential sources.

   3.3.8  Depth

   Depth characterization is important for
   evaluating DO, temperature and salinity
   profiles, tidal regime consistency, and
   the percent of the water column that is
   photic. This may be especially
   significant in coastal areas where
   bathymetry changes can be great and
   other potentially related distinctions
   such as grain size are not as evident.

   3.4   Bottom Characteristics

   The SQT approach is generally the most
   comprehensive assessment of relative
   sediment quality. In this approach data
   are collected to determine
   concentrations of potentially toxic
   chemicals in sediments, to measure the
   relative bioavailability and toxicity of
   sediment-associated toxicants with
   laboratory bioassays, and to identify
   degradation of resident infauna possibly
   attributable to the contaminants.

   Chemical data can be generated through
   analyses of the bulk sediments and
   compared to applicable sediment quality
   guidelines (SQGs), proposed or
   promulgated criteria or standards
   wherever they exist, and  relevant
   sedimentological factors such as grain
   size, total organic carbon, or aluminum.
   Data analyses can be conducted to
   identify both sites and chemicals of
   potential concern. Chemicals of highest
   potential concern are those in which
   SQG or other applicable values were
   exceeded most frequently and by the
   largest amount.  These chemicals also
   would be expected to show strong
   associations with measures of toxicity.
   Moreover, chemicals of highest concern
   may be those determined to be
   bioavailable and bioaccumulative in
laboratory exposures (Chapman et al.
1988). If possible, historical data should
be used to focus the chemical analyses.

Toxicity data can be generated through a
battery of short-term tests performed
under the controlled environment of the
laboratory. Amphipod survival tests,
which are most frequently used in North
America, are done with exposures to
solid-phase sediments and percent
survival is measured after 10-days.
These acute tests often are accompanied
by tests of other sediment phases (e.g.,
pore waters and solvent extracts) with
sublethal endpoints (Long et al. 1996).
Data from the tests provide information
for ranking and prioritizing sampling
sites according to their  potential for
causing adverse effects among resident
infauna. Confirmation of adverse effects
among the infauna must be done with
analyses of samples collected from the
same locations tested for chemical
concentrations and toxicity.  Measures of
species richness, total abundance,
relative abundance of crustaceans
(particularly inf aunal amphipods)
and/or  other relatively sensitive taxa
provide information on the degree to
which resident biota have been
adversely affected. Chapman (1996)
provided  useful guidance on the
interpretation of the SQT data.

Measurements of bottom characteristics
of estuaries and coastal marine waters
provide important data for interpreting
the condition of targeted biological
assemblages. Sediment grain size
influences the spatial distribution of
benthic macroinvertebrates and fishes.
Fine-grained sediments can adsorb
contaminants, creating a source of
potential impairment to bottom
communities. Organic carbon found in
these sediments can mediate the
concentrations of DO, organic
contaminants, and metals. Measuring
the depth of the sediment oxidation-
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     3-15

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   reduction potential discontinuity layer
   provides information on aerobic vs.
   anaerobic respiration in sediments.
   Sediment nutrients such as particulate
   nitrogen and phosphorus can be re-
   mobilized by physical disturbance or
   changes in the water column chemistry
   to become an additional nutrient source
   leading to potential eutrophication,
   phytoplankton blooms, and hypoxia of
   estuarine and coastal marine waters.
   Finally, sediment contaminant
   measurements can provide insights on
   factors that might limit biological
   assemblages and lead to potential
   human health effects.

   3.4.1  Sediment Grain Size

   The objective of measuring sediment
   grain size is to detect and describe
   spatial and temporal changes of the
   benthic habitat.  The availability of
   sediment contaminants is often
   correlated with sediment grain size
   because more sediment contaminants
   are adsorbed onto small grained
   sediments due to their greater surface
   area. Likewise, grain size information
   may explain the temporal and spatial
   variability in biological assemblages
   related to an organism's ability to build
   tubes, capture food, and escape
   predation. Grain size data may be used
   to determine the extent of or recovery
   from environmental  perturbations, to
   evaluate the condition of benthic
   habitats, and to assist in providing early
   warnings of potential impacts to the
   estuarine ecosystem  (USEPA 1992).
   The most common measurements and
   classifications of sediment grain size are
   as follows:

   >•   clay       < 0.004-mm
   *   silt        0.004 - 0.064-mm
   >   sand      0.064 - 1.0-mm
   *•   gravel    > 1.0-mm
3.4.2  Total Organic Carbon, Total
       Volatile Solids, and Acid
       Volatile Sulfides

Total organic carbon (TOC) and acid
volatile sulfides (AVS) are considered by
some to be the most important sediment
properties determining the
bioavailability and toxicity of certain
organic compounds and trace metals in
sediments (DiToro et al. 1990, DiToro et
al. 1991). The importance of these
factors is based on an equilibrium
partitioning approach.  This approach
assumes  that the bioavailable fraction of
chemicals in sediment is correlated to
that fraction in the porewater rather
than whole sediment concentrations.
Therefore, factors that influence the
partitioning of compounds between
sediment and porewater will govern
bioavailability. In addition, it is
assumed that equilibrium exists among
the phases (hence, the name
"equilibrium partitioning").  For non-
ionic hydrophobic organic chemicals,
the primary factor influencing
partitioning is TOC; for certain divalent
cationic metals; i.e., cadmium, copper,
nickel, lead, zinc, an important binding
phase is the acid volatile sulfide fraction.
The development of sediment quality
criteria by USEPA is based on these
assumptions and a comparison of
predicted porewater concentrations to
existing water quality criteria (DiToro et
al. 1991, Ankley et al. 1996).

Normalization of non-ionic organic
compounds is accomplished by
calculating chemical concentrations per
gram of sediment organic carbon rather
than per gram of dry sediment. This
approach allows comparisons of the
potential bioavailability of non-ionic
organic compounds across different
sediment types and can be used to
screen for chemicals of concern. For an
explanation for how to apply this
approach to calculate sediment quality
3-16
                      Habitat Characterization

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   criteria the reader is referred to DiToro
   et al. (1991).

   Although SQGs (Sediment Quality
   Guidelines) derived for organic
   compounds and trace metals reported
   on a dry weight (bulk) basis have been
   shown to be reliable and predictive of
   both non-toxic and toxic conditions
   (Ingersoll et al.  1996, MacDonald et al.
   1996, Long et al. 1998a); these values do
   not account for the relative
   bioavailability of sediment-associated
   chemicals. In areas in which high trace
   metal concentrations are known or
   suspected, or in which SQGs are
   exceeded, further evaluations of
   chemical contamination may be aided in
   subsequent analyses by use of the
   simultaneously extracted metals/acid
   volatile sulfides (SEM/AVS) tool to
   provide estimates of bioavailability.

   The AVS normalization approach
   assumes that select trace metals bind to
   sediment sulfide, specifically the sulfide
   fraction soluble in cold acid, known as
   AVS (Allen et al. 1993). The
   bioavailability of trace metals capable of
   forming insoluble metal sulfides will be
   determined by the proportion of these
   metal ions not bound to sulfide. Hence,
   on a molar basis, if the concentration of
   SEM is less than the molar concentration
   of AVS, all of the metals should
   precipitate as metal sulfides and not be
   bioavailable. Conversely, if SEM
   exceeds AVS then free metal ions may
   exist in the porewater. This approach
   appears to work best in situations when
   the ratio of [SEM]/[AVS] is less than 1.0
   or the  difference between SEM and AVS
   concentrations is less than 0.0 (Hansen
   et al. 1996). That is, the SEV/AVS tool is
   primarily intended for use as a no-
   effects tool and caution is advised in
   using it as a predictor of toxicity or other
   effects. Long et al. (1998b) reported that
   the SEM/AVS tool and SQGs based
   upon bulk sediment chemistry for trace
metals performed equally well in
correctly predicting samples as either
toxic or non-toxic.  For an excellent
discussion of the applicability,
advantages and disadvantages of this
approach, the reader is referred to
several review papers in Environmental
Toxicology and Chemistry, Volume 15,
#12.

3.4.3   Sediment Oxidation-Reduction
       Potential

There are four oxidation-reduction
(redox) processes related to biological
respiration that occur in benthic
sediments. These chemical reactions,
which depend on the availability of
electron acceptors; i.e., oxygen, nitrate,
sulfate, and carbonate, stratify the
sediments into four zones. Oxygen is
the electron acceptor used for aerobic
respiration and is the most important
oxidizing agent at the surface of the
sediments. Nitrate reduction occurs
between 0- and 4-cm and produces
elemental nitrogen. This is followed by
sulfate reduction which produces
hydrogen sulfide. Carbonate reduction
occurs between 10- and 50-cm and
results in the production of methane.

Aerobic respiration will be the dominant
reaction as long as oxygen is available.
The depth at which oxygen is fully
depleted and the redox potential goes to
zero has been termed the redox potential
discontinuity (RPD) layer (Day et al.
1989).  Burrowing organisms oxidize the
sediments and hence will increase the
zone of habitability as reflected in the
depth of the RPD layer.  Color changes
in the substrate occur as a result of the
oxidation and reduction of metals, such
as iron, in the sediments. The upper few
centimeters may appear brown from the
formation of iron oxides and
hydroxides, whereas the zone of
reduction turns gray and eventually
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     3-17

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   black in the deeper sediments from the
   formation of ferrous sulfide and pyrite.
   When examining a cross-section of a
   sediment core sample, the RPD layer is
   visibly noticeable by this change in
   color. The depth of this color change
   should be recorded because, as noted
   above, it indicates the zone of
   habitability for benthic infauna. The
   closer to the sediment surface this color
   change appears, the less available
   dissolved oxygen exists in the sediment
   porewater.

   3.4.4  Sediment Contamination

   Sampling the surface sediments for the
   presence of contaminants can provide
   insight on factors limiting the benthic
   community, as well as the potential for
   impacts to human health; i.e., by
   biomagnification or bioaccumulation in
   the food chain or by the contamination
   of shellfish. Metals and organic
   chemicals entering estuaries from fresh
   water inflows, point sources of
   pollution, and various nonpoint sources,
   including atmospheric  deposition,
   generally are retained within estuaries
   and accumulate within the sediments
   (Forstner and Wittman 1981, Hinga
   1988, Nixon et al. 1986, Schubel and
   Carter 1984, Turekian 1977) because of
   the affinity of most contaminants for
   particle adsorption (Hinga 1988;
   Honeyman and Santschi 1988).
   Chemical and microbial contaminants
   generally adsorb to fine-grained
   materials in the water and are deposited
   on the bottom, accumulating at
   deposition sites, including regions of
   upper tidal fresh water, low current
   velocity, deep basins, and the zone of
   maximum turbidity in the upper reaches
   of estuaries within which suspended
   sediment concentrations are greater than
   those either farther upstream or farther
   seaward (Schubel and Carter 1984). The
   concentration of contaminants in
   sediments is dependent upon
interactions between natural (e.g.,
chemical and physical sediment
characteristics) and anthropogenic
factors (e.g., type and volume of
contaminant loadings) (Sharpe et al.
1984).

Bottom sediments in some estuaries
(e.g., harbors near urban areas and
industrial centers) are so contaminated
that they represent a threat to both
human and ecological health (NRC1989,
OTA 1987, Weaver 1984), but
contaminated sediments are not limited
to these areas.  Pollutant runoff from
agricultural areas also is an important
source of contaminant input to estuaries
(Boynton et al. 1988, Pait et al. 1989).

The EMAP program uses the NOAA
National Status and Trends (NS&T)
suite of contaminants as the basis for
measurements in homogenized
subsamples of collected sediments
(Figure 3-1). A useful citation for the
NS&T Program list of chemicals is
O'Connor et al. 1994. The NOAA suite
includes chlorinated pesticides,
polychlorinated biphenyls (PCBs),
polyaromatic hydrocarbons (PAHs),
major elements, and trace metals.

3.5   Proposed  Habitat
       Parameters

Table 3-1 summarizes the proposed
habitat measurements by survey tier and
provides possible sources of
information, methods, and equipment,
as appropriate. Agency-specific
objectives will determine the overall
design of any sampling program. The
following tier distribution is just one
approach possible for gathering and
organizing data.  Habitat measurements
are intended to be cumulative across
tiers; that is, the desktop screening of
Tier 0 should be incorporated into Tier 1,
Tiers 0 and 1 parameters should be
incorporated into Tier 2, and Tiers 0,1,
3-18
                      Habitat Characterization

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Polyaromatic Hydrocarbons
(PAHs)

Acenaphthene
Anthracene
Benz(ajanthracene
Benzo(ajpyrene
Benzo(e_)pyrene
Biphenyl
Chrysene
Dibenz(a_mh_)a nth race ne
2, 6-di me nhyul naphthalene
Fluoranthene
Fluorene
2- methyl naphthalene
1 -methylnaphthalene
1 -methylphenanthrene
Naphthalene
Perylene
Phenanthrene
Pyrene
Benzo(b)fluoranthene
Acenaphthlyene
Benzo(k)fluoranthene
Benzo(g,h,i)perylene

Maior Elements
Aluminum
Iron
Manganese
Silicon

Trace Elements
Antimony
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Selenium
Silver
Tin
Zinc
DDT and its metabolites
o,p'-DDD
p,p'-DDD
o,p'-DDE
p,p'-DDE
o,p'-DDT
p,p'-DDT
Chlorinated pesticides other than DDT
Aldrin
Alpha-Chlordane
Trans-Nonachlor
Dieldrin
Heptachlor
Heptachlor epoxide
Hexachloro benzene
Lindane (gamma-BHC)
Mi rex

18 PCB Congener

Congener Location
Number ofCIs
8 24'
18 2 2' 5
28 244'
52 2 2' 5 5'
44 2 2' 3 5'
66 2 3' 4 4'
74 2 4 4' 5
99 2 2' 4 4' 5
101 2 2' 4 5 5'
118 2 3' 4 4' 5
153 2 2' 4 4' 5 5'
106 ? 3 3' 4 4'
I \J\J £- \J \J *T T^
138 2 2' 3 4 4' 5'
187 2 2' 3 4' 5 5' 6
128 2 2' 3 3' 4 4'
180 2 2' 3 4 4' 5 5'
170 2 2' 3 3' 4 4' 5
1QC; 1 1' ^ V A A' ^ R
1 c/CJ ^L^lOOHHUO
206 2 2' 3 3' 4 4' 5 5' 6
209 2 2' 3 3' 4 4' 5 5' 6 6'


Other measurements
Tributyltin
Acid volatile sulfides
Total organic carbon











                                                                        Figure 3-1
                                                                        Chemicals
                                                                        measured in
                                                                        sediments by
                                                                        the EMAP-
                                                                        Estuaries
                                                                        program.
                                                                        Refer also to
                                                                        the NS&T
                                                                        Program list of
                                                                        chemicals
                                                                        (O'Connor et
                                                                        al. 1994).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-19

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   and 2 parameters should be
   incorporated into Tier 3.  The habitat
   tiers described here should be used with
   the corresponding biological survey tier.

   3.5.1   TierO

   The purpose of a Tier 0 assessment is to
   support the planning for monitoring and
   more detailed assessments. Tier 0 is a
   desktop screening assessment in which
   documented information for the estuary
   or coastal marine areas of concern is
   compiled from sources including
   databases, peer-reviewed and gray
   literature, state and federal agencies,
   universities, and local experts. A Tier 0
   assessment  should always precede any
   of the three subsequent tiers.
   Examination of long-term data records
   (e.g., salinity, DO, climate)  is
   particularly important for identifying
   the variability which must be accounted
   for in the design of subsequent field
   monitoring.  Habitat parameters to
   examine in Tier 0 include:

   Area and Geomorphometric
   Classification

   The size and classification of an estuary
   indicates  its potential to respond to
   various impacts. Estuary types include
   coastal plain, lagoon, fjord, and
   tectonically-caused.  Circulation type
   (e.g., gravitational, tidal, wind-induced)
   influences current patterns, salinity
   regimes, and thermal and dissolved
   oxygen patterns.

   Habitat Type

   Identifying  and delineating the various
   habitat types (Section 3.3) that occur in
   the estuary  or coastal marine  waters will
   be necessary for partitioning the natural
   variability in the system. The extent of
   such a delineation will depend on the
   size of the area of concern and the
   nature of the environmental gradients
present. Initial partitioning will
probably be based on salinity, sediment
type, and depth.

Watershed Land Use and Population

Land use and population data for the
watershed will help to identify classes of
contaminants and other stresses that
may affect the water body.  For example,
agricultural areas located near an
estuary might be expected to be sources
of nonpoint loading of nutrients,
pesticides, herbicides, and sediment.
Urban areas may contribute toxic
compounds via stormwater runoff. The
pattern and magnitude of population
density in the watershed can potentially
provide clues regarding the potential for
human-induced impacts to the water
body.

Water Column and Bottom
Characteristics

Historic data on water column and
bottom characteristics is central for
identifying system variability and to
support the design of subsequent
monitoring. This data can also be used
by states to identify types and locations
of potential impairment, for example,
areas with high concentrations of water
column nutrients, suspended sediment,
or sediment contaminants.

3.5.2  Tier 1

Tier 1 is a basic field assessment that is
used for screening purposes to identify
potential reference and impaired sites.
For biocriteria development purposes, it
is adequate for only rudimentary habitat
classifications and evaluations.  It
identifies the general physical
characteristics of the estuary or coastal
region, the habitats, and the potential
sources of anthropogenic stress.  Tier 1
relies heavily on existing information
identified in Tier 0 and supplemented
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                       Habitat Characterization

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   by one-time easily-measured field
   parameters, which are measured
   concomitantly with the collection of
   biological data. Much of the habitat
   information needed in this tier can be
   acquired from state or federal agency
   records. Depending on the needs of the
   state, Tier 1 habitat characterizations
   may include the following elements:

   Estuary Characteristics

   Information on estuary characteristics is
   essential for the development of
   appropriate sampling strategies. Data to
   be compiled in this category includes
   estuary area, geomorphometric
   classification (e.g., classical coastal plain
   estuary, lagoon), and habitat types
   present (e.g., hard bottom, soft bottom).
   These data can be obtained from USGS
   maps, NOAA charts, and reports and
   data archives at federal and state
   agencies and universities.

   Watershed Characteristics

   Knowledge of watershed characteristics
   can provide important information for
   determining appropriate sampling
   station locations and for evaluating
   possible sources and causes of biological
   and habitat impairment.  Data to be
   compiled for this category include
   watershed land use, human population
   density, NPDES discharge locations, and
   vegetative cover. These data are likely
   to exist at federal, state, and local
   agencies and universities.

   Water Column Characteristics

   The characteristics in a water column
   play a key role in determining the biota
   present at a given location and their
   broader distribution patterns.
   Parameters to be measured in Tier 1 in
   the field include salinity  and
   conductivity, DO, temperature, pH,
   turbidity and Secchi depth.  Records of
tidal stage and current velocity at the
time of sampling at each station should
be acquired from NOAA.

Bottom Characteristics

Characteristics of bottom sediments also
are key determinants of aquatic biota
present in estuaries and coastal marine
waters.  Parameters to be measured in
Tier 1 include depth, dominant sediment
type, total volatile solids, and sediment
RPD layer depth.

3.5.3  Tier 2

Tier 2 provides the information
necessary to develop a quantitative
ranking of the sites that can be used to
prioritize resources and sampling
efforts.  Habitat information collected in
Tier 2 will be used in the development
of biocriteria. In addition to Tier 1
habitat characterization, Tier 2 includes:

Water Column Nutrients

Nutrients in the water column
determine the nutrient state  of the area
and may indicate possible sources of
impairment, particularly nonpoint
source runoff.

Sediment Characterization

The organisms closely associated with
the bottom are strongly influenced  by
such sediment characteristics as the
average grain size and the percent
composition of silt, sand, and clay (Day
et al. 1989). These characteristics
determine the structure of the benthic
community based on the preferences of
the major groups of organisms. For
example, suspension feeders are found
more often in firmer, sandier substrates
than are deposit feeders; interstitial
meiofauna are predominant in sandy
areas, whereas burrowing meiofauna
prefer silty mud. Although  a high
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      3-21

-------
   organic content in the sediments can
   increase the rate of oxygen depletion,
   there are many organisms that require
   high concentrations of organic matter.
   Sediment characteristics to be measured
   in Tier 2 include percent sand vs. silt-
   clay, mean grain size, total volatile
   solids, and total  organic carbon.

   Shorezone Vegetative Cover
   Characterization

   Shorezone vegetation provides stability
   for beaches, wetlands, banks, and cliffs,
   serving to reduce erosion and nonpoint
   source runoff to  the water body.  As
   such, evaluation of shorezone vegetative
   cover is important for identifying
   possible sources of impairment and
   remedial approaches. Terrestrial
   riparian vegetated areas to consider are
   uplands and the floodplain.  Areas of
   emergent, intertidal, and submerged
   vegetation should also be characterized.

   Shorezone vegetative cover is important
   for reducing nutrient and sediment
   loading to estuaries from nonpoint
   source runoff, attenuating incident wave
   energy and reducing shore erosion, and
   providing important nursery and
   feeding habitat for migratory species.
   Salt marshes and aquatic macrophytes
   have high gross  primary productivity
   and provide a source of autochthonous
   organic matter for detrital feeders in
   adjacent waters. An assessment of the
   coverage and types of shorezone
   vegetation can contribute to the overall
   assessment of the condition of estuarine
   and coastal marine habitat. Evaluation
   of vegetative cover is most easily
   accomplished by aerial photography
   and mapping coupled with ground-
   truthing. Detailed procedures used for
   photography and mapping aquatic
   macrophytes are provided by Orth et al.
   (1993) (Chesapeake Bay), Ferguson and
   Wood (1994) (North Carolina estuaries),
   and USEPA (1992) (National Estuary
Program) and can be adapted for use in
other areas.

3.5.4  Tier3

Tier 3 provides a detailed assessment
with a high level of certainty of the
biological or habitat condition of the
estuarine and coastal marine
environment. It is the definitive
assessment level to distinguish habitat
variation from anthropogenic impacts
when the biocriteria have been
exceeded. Tier 3 focuses on biological
community level investigations and
thoroughly integrates the physical,
chemical and biological data to yield a
detailed impact assessment.  In addition
to the habitat parameters compiled in
Tier 0 and measured in Tiers 1 and 2,
sediment oxidation-reduction potential,
sand/silt/clay proportions, sediment
contaminants, and water column
pesticides, herbicides, and metals,
nutrient speciation, and AVS/SEM as
needed may be measured in this tier.

Tier 3 provides the detailed diagnostic
information necessary for: (1)
identifying specific problem sources in
the drainage area; (2) delineating
mitigation options for the identified
problems; and (3) preparing written
management plans for the estuary or
coastal marine area of interest.
Although the data collected in Tier 3
cannot prove cause-and-effect
relationships between identified
stressors and ecosystem responses, they
can provide a strong correlation and a
definitive assessment, with a high
degree of certainty, of the biological
integrity of the target waters and their
habitats.
3-22
                      Habitat Characterization

-------
    Table 3-1.
Habitat measurements for estuaries and coastal marine waters.
Habitat
Measurements
Assessment Tier
0
1
2
3
Information Source
Method(s) and
Equipment
Historical Information
Estuary area
Geomorphometric
classification
(classical coastal
plain estuary; salt
marsh estuary;
lagoon; fjord;
tectonically-caused
estuary)
Habitat type
(seagrass beds; hard
bottom; soft bottom;
water column;
emergent marsh;
mudflat; sandflat;
gravel/cobble; rocky)
Watershed land use
Population density
NPDES discharges
Vegetative cover
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
USGS quad maps
USGS quad maps
NOAA bathymetry
charts; historic surveys
by federal, state
agencies and
universities
USGS land use maps;
state planning
agencies; local zoning
agencies
US census data
State water quality
agency
Historic surveys by
federal, state agencies
and universities
Can be estimated from
maps or using CIS


Can be estimated from
maps or using GIS


Can be estimated from
maps or using GIS
Field-collected Information: Water Column Characteristics
Salinity, conductivity
DO
Temperature
PH
/*
/*
/*
/*
/
/
/
/
/
/
/
/
/
/
/
/
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities.
Conductivity cells
(CTD meters)
CTD meter equipped
with O2 probe,
recording DO meters
for Tier 3 may be
needed
CTD meter, satellite
remote sensing.
CTD meter equipped
with pH probe
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                            3-23

-------
      Table 3-1 (Cont'd).  Habitat measurements for estuaries and coastal marine waters.
Habitat
Measurements
Turbidity, Secchi
depth
Nutrients (nitrogen
species,
phosphorus)
Organics, metals
Assessment Tier
0
/*
/*
/*
1
/


2
/
/

3
/
/
/
Information Source
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Method(s) and
Equipment
Secchi disk;
transmissometer,
nephelometer,
turbidimeter if desired
Spectrophotometry
Standard methods for
selected suite of
contaminants
Field-collected Information: Bottom Characteristics
Depth
Sediment grain size
Total volatile solids
Total organic carbon
Acid volatile sulfides
Sediment reduction-
oxidation potential
Sediment
contamination
/*
/*
/*
/*
/*
/*
/*
/
/
/


/

/
/
/
/

/

/
/
/
/
/
/
/
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Meter wheel,
fathometer,
hydrostatic pressure
sensor
Sieving or separatory
column combined with
pipette analysis for
silt-clay fraction
Standard methods
Standard methods
Standard methods
Visual determination
of the depth of change
in sediment color in
core
Standard methods for
contaminants selected
        Historic data should be included in Tier 0; the tier does not include any field collection of
        new data.
3-24
Habitat Characterization

-------
 Chapter 4
 Physical Classification and
 the  Biological Reference
 Condition
   Estuaries and coastal marine waters
   span a range of spatial scales from small
   subestuaries, embayments, and coastal
   lagoons to large estuaries (e.g.,
   Chesapeake Bay, Puget Sound) and
   open coastal waters.  The procedures
   described in this document rely on a
   spatial hierarchy to accommodate the
   potentially large range of water bodies
   that states may assess. The top level in
   the hierarchy is a geographic region
   containing comparable landform and
   climate. The provinces used by the
   EMAP-Estuaries program (e.g.,
   Carolinian, Columbian) are examples of
   this hierarchical level. The next level
   consists of  individual watershed
   characteristics. Key attributes to
   consider at this level include land cover,
   the watershed-to-basin area ratio, and
   the geology and soils of the watershed.
   Examples of the use of this hierarchical
   level in estuarine assessment are the
   Chesapeake Bay watershed, New Jersey
   coastal bays, or California saline
   lagoons. The lowest level in the
   hierarchy considers habitat
   characteristics. As discussed in Chapter
   3, the three primary variables used to
   partition spatial heterogeneity at this
   level are sediment grain size, salinity,
   and water depth. Description of
   sampling sites as "low mesohaline,
   mud" or "10-m depth, gravel" would be
   examples of this level of the hierarchy.

   Reference conditions are expectations of
   the status of biological communities  in
   the absence of anthropogenic
   disturbances and pollution, and are
   usually based on the status of multiple
   reference sites. Ideally, reference sites
are minimally impaired by human
pollution and disturbance. The care that
states use in selecting reference sites and
developing reference condition
parameters, together with their use of
standardized survey techniques, will
directly influence the quality of the
resulting water body assessment. At a
minimum, reference conditions should
be identified for each of the estuary and
coastal marine classification categories
developed by a state.

Reference conditions reflect the biotic
potential for estuaries and coastal
marine waters if they are not impaired
by human activity or pollution.
Attainment of an aquatic life designated
use is evaluated against the reference
condition as a key element in the
biocriteria for that aquatic life use.
Biocriteria may be set higher than the
best conditions observed in the data
available for an area that is highly
impaired.  In this instance, interim,
incremental criteria may be established
as the regional authority works on
environmental recovery.

4.1    Classification Approach

The biological reference condition must
be determined separately for each
estuarine or coastal marine physical
class. Assessing biological condition
requires reference conditions for
comparison and for development of
models and indexes to help establish
biocriteria and detect impairment.
There is no single "best" classification
nor are resources available to determine
all possible differences between all
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      4-1

-------
   estuarine and coastal marine sites in a
   region. The key to classification is
   practicality within the region or state in
   which it will be applied; i.e., local
   conditions determine the classes.
   Classification will depend on regional
   experts familiar with the range of
   estuarine conditions in a region as well
   as the biological similarities and
   differences among the assessment units.
   Ultimately, physical classification may
   be used to develop a predictive  model of
   those estuarine and coastal marine
   characteristics that affect the values of
   the biological metrics and indexes at
   reference sites.

   The regional differences in estuarine and
   coastal marine biological communities
   across the United States  must be
   accounted for in the development of a
   biological criteria program. These
   differences can be identified by
   comparing the biology of water bodies
   of interest to a reference condition. As
   biological conditions change across the
   country, the reference conditions will
   also change. To account for the regional
   geographic differences that create
   structural differences in biological
   habitat (either natural or human-
   induced), states should classify  estuaries
   and coastal marine waters or segments
   thereof into groups. A reference
   condition should be established for each
   of these classification groups. Biotic
   index comparisons can then be made
   within each classification group and
   inappropriate biological comparisons
   between different classes will be
   precluded. Moreover, the aquatic life
   expectations of water bodies are
   tempered by realistic expectations. With
   biological systems, it is not possible to
   set uniform, nationwide numeric
   biological criteria.

   Estuaries vary widely in size, shape, and
   ecological and physical characteristics,
   and a single reference condition that
      applies to all estuaries (or coastal marine
      waters) would be inappropriate.  The
      purpose of classification is to group
      similar estuarine or coastal marine sites
      together; i.e., to prevent the comparison
      of apples and oranges.  Classifying the
      variability of biological measures within
      groups inevitably requires professional
      judgment to arrive at a workable system
      that separates clearly different systems,
      does not consider each estuary or
      subestuary a special case, and does not
      lead to the proliferation of classification
      groups. The intent of classification is to
      identify the smallest number of groups
      of estuarine or coastal marine categories
      that under ideal conditions would have
      comparable biological communities for
      that region. As much as possible,
      classification should be restricted to
      those characteristics of estuaries and
      coastal marine waters that are intrinsic,
      natural, reasonably stable over time, and
      not the result of human activities.

      The approach to reference condition
      characterization and classification is
      illustrated in Figure 4-1. An idealized
      biological potential for estuarine sites is
      expressed, for instance, by a fish index
      and an inf aunal index, each within a
      certain range of values (Figure 4-1). A
      test site is compared to the expected
      ranges of values, and if its indexes are
      outside those ranges, it is judged as not
      meeting expectations to some degree.
      Test sites are usually not compared to a
      theoretical ideal, but to biological
      criteria derived from a population of
      reference sites. Test sites  are judged as
      not meeting the criterion if they are
      beyond some predetermined limit of  the
      distribution of reference values.
4-2
Physical Classification and the Biological Reference Condition

-------
               4 -,
               3 -
               2 -
               1 -
                     2.0- 2.7
                          S/fe a
                                   "Biological Potential"
                           S/fe
                                         1.7- 3.3
                                 Infaunal Index
                      Figure 4-1
                      Graphical
                      representation of
                      bioassessment.
                      Assessment sites
                      a and £> are
                      compared to an
                      ideal biological
                      potential.  Site a is
                      near its potential.
                      Site b deviates
                      from it.
    A population of reference sites might
    consist of sites which overlap different
    classes of estuarine or coastal marine
    waters (Figure 4-2). A useful
    classification system in this instance
    separates these reference sites into
    classes with different biological
    expectations. The classification itself
    must be based on abiotic information
    that is minimally affected by human
    activities (e.g., ecoregion, estuary and
    coastal marine physical characteristics,
    basin characteristics), such that test sites
    can be assigned to one of the classes
    before any biological information is
    obtained. Furthermore, the
    classification must explain biological
    variability in the reference sites (Figure
    4-2).  Separation into classes then lowers
    inherent variation and allows greater
    precision in assessing test sites. If test
    site "a" in Figure 4-2 is a member of class
    II, it would be judged as not meeting
    reference expectations.  If, however, the
    physical classification were not done,
    site "a" would be judged to meet
    reference expectations because it is
    within the limits of all reference sites.
     Sequence of Classification and
            Characterization

The general sequence of reference
condition characterization is to first
make a preliminary physical
classification of estuaries and coastal
marine areas within a region (Conquest
et al. 1994). Because of natural variation
among and within estuaries and coastal
marine waters, reference conditions will
likely differ with geographic regions,
major salinity zones, depth profiles, and
bottom sediment types. Following
classification, reference conditions are
characterized using some combination
of reference sites, historical data, expert
opinion, and empirical models. A key
element is the use of reference sites
because they represent realistic,
achievable goals and can be regularly
monitored. Historical data and well-
documented expert opinion should be
used to evaluate the information
developed from the reference site data
and possibly from empirical models.
The preliminary classification is
reconciled with the biological data to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                         4-3

-------
    Figure 4-2	
    Classification and
    assessment.  If
    reference sites are
    not classified, Site
    a is at or near its
    potential.  If
    reference sites are
    classified  and Site
    a is in Class II, it
    does not meet its
    potential and
    might be judged
    impaired.

-------
   identified in the conterminous United
   States (Omernik 1987); but recent
   refinements have yielded a greater
   resolution for some areas.

   It should be noted that many of the
   characteristics that can be used as
   classification variables are often
   subsumed by the geographic region. For
   example, watersheds are often similar
   within major geographic regions, having
   resulted from the regional
   geomorphology.  Within such regions, it
   might be sufficient to classify using only
   morphology such as depth, area, or
   bathymetry. Examples are the coastal
   bays of the Delmarva peninsula or the
   sounds behind North Carolina's Outer
   Banks.

   The EMAP-Estuaries program uses
   biogeograpical provinces, defined by:
   major climatic zones and prevailing
   ocean currents. EMAP coastal areas in
   the continental United States are
   encompassed within seven provinces
   described as Acadian, Virginian,
   Carolinian; West Indian; Louisianian;
   Californian; and Columbian (Figure 4-3)
   (Holland 1990). These roughly
   approximate the traditional descriptors
   of New England, Mid-Atlantic Bight,
   Southeast Coastal, Caribbean, Gulf
   Coastal, Southwest, and Northwest
   Pacific Coast. For strictly coastal waters,
   this may be a sufficient level of
   classification.

   4.2.2   Estuarine Categories

   Estuaries can be categorized into four
   major classes based on their
   geomorphology:  (1) coastal plain
   estuaries (Chesapeake Bay; Cape
   Canaveral, FL), (2) lagoons (Pamlico
   Sound, NC), (3) fjords (Puget Sound),
   and (4) tectonically-caused estuaries
   (San Francisco Bay) (Day et al. 1989).
   While these classifications appear to be
   large scale in nature, they can be used to
make initial divisions of estuaries on a
regional scale.

There are two types of coastal plain
estuaries: classical and salt marsh.  The
classical coastal plain estuary is
sometimes referred to as a "drowned
river valley." These estuaries were
formed during the last eustatic rise in
sea level and they exhibit
geomorphological features similar to
river channels and floodplains.  The salt
marsh estuary lacks a major river source
and is characterized by a well-defined
tidal drainage network, dendritically
intersecting the extensive coastal salt
marshes  (Day et al. 1989).  Exchange
with the ocean occurs through narrow
tidal inlets which are in a constant state
of flux. Consequently,  salt marsh
estuarine circulation is  dominated by
fresh water inflow and the tides.

Lagoons are characterized by narrow
tidal inlets and uniformly  shallow; i.e.,
less than 2-m deep, open water areas.
The inlets are created by the erosion of
the narrow Pleistocene ridge that
formed along the coast some 80,000
years ago during the interglacial stage
(Day et al. 1989). Lagoons are primarily
wind-dominated and they have a
subaqueous drainage channel network
that is not as well-drained as the salt
marsh estuary.

Classical fjords, formed during the last
ice age, are river valleys that were
carved out by the leading  ice edge of
advancing continental glaciers.  When
the glacier receded, large rock deposits
were left behind where the leading edge
had stopped. Others are also a result of
glacial scouring of the coast; however,
these estuaries were formed in regions
with less spectacular continental relief
and more extensive continental shelves,
therefore they are much shallower than
typical fjords.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      4-5

-------
Figure 4-3
Biogeographical
provinces adapted
from Holland
(1990).  A form of
preliminary
regionalization
used by EMAP-
Estuaries.
          Tectonically-caused estuaries are created
          by faulting, graben formation, landslide,
          or volcanic eruption. They are highly
          variable and they may resemble coastal
          plain estuaries, lagoons, or fjords.

          4.2.3  Watershed Characteristics

          Watershed characteristics affect estuary
          and coastal marine hydrodynamics,
          sediment and nutrient loads, chemical
          and metals contaminant loads, and
          dissolved solids. Watershed
          characteristics that may be used as
          classification variables include:

          *   Land cover - extent of natural
              vegetation;

          *   Watershed-to-estuary area ratio;

          *   Soils, geology (erosiveness of soils),
              and topography.
      4.2.4  Waterbody Characteristics

      The third level of the classification
      hierarchy focuses on waterbody
      characteristics. Attributes that are
      considered at this level include
      waterbody morphology,
      hydrodynamics, and water quality.
      Each of these factors has a direct
      influence on the biota present in the
      waterbody.

           Morphological Characteristics

      Morphological characteristics of the
      estuary or coastal marine waters
      influence hydrodynamics and system
      responses to pollution.  Morphological
      characteristics include:

      *   Depth (mean, maximum);

      *   Bathymetry - three-dimensional
          bottom profile;

      *   Surface area;
       4-6
Physical Classification and the Biological Reference Condition

-------
   *•   Bottom type and sediments -
       substrate and grain size.

               Hydrodynamics

   Hydrodynamics forms a basis for water
   quality. Mixing and circulation patterns
   influence nutrient retention and the
   development of hypoxia.

   Hydrodynamic factors include:

   *•   Retention time;

   *•   Stratification and mixing;

   *•   Currents - speed and direction;

   *•   Tidal range;

   *•   Altered inflow to the waterbody,
       such as increased or decreased
       freshwater inflow from runoff or
       diversions.

                Water Quality

   As noted above, many water quality
   characteristics are relatively uniform
   within a region because they are the
   result of common regional, watershed,
   and hydrodynamic characteristics.
   Although water quality variables might
   be redundant for a classification scheme
   if regions are the primary classification
   variable, it is frequently convenient to
   subclassify according to water quality.
   An example is the practice  of sub-
   dividing estuaries along their gradient
   into oligohaline, mesohaline, and
   polyhaline regions (see Figure 4-4 for an
   example of such a delineation). Water
   quality variables useful for classification
   are:

   *•   Salinity and conductivity;

   *•   Turbidity (Secchi depth);

   *•   Dissolved oxygen (DO);
>  pH.

Human actions (e.g., discharges, land
use, freshwater flow diversions) alter
water quality, especially sediment and
nutrient concentrations, but they can
also affect salinity, conductivity,
turbidity, DO, and pH. Therefore, care
must be taken that classification
according to characteristic water quality
reflects natural  conditions and not
anthropogenic impacts. For example, if
estuarine sites are highly turbid due to
poor land management practices in the
watershed, they should not be classified
as highly turbid. Instead, they should
be classified according to the turbidity
class they would have had in the
absence of poor land use.

4.3    Establishing Biological
       Reference Conditions

Estuarine and coastal marine reference
conditions should be established using
some combination of four elements: (1)
evaluation of historical data; (2)
sampling of reference sites; (3)
prediction of expected conditions using
models; and (4) expert consensus. Each
element has its  inherent strengths and
weaknesses (Table 4-1) that states must
consider relative to their program needs,
available data, and staff expertise.

4.3.1   Historical Data

In many cases, historical data are
available that describe past biological
conditions in the region.  For the
purpose of this  document, historical
data are datasets collected by programs
that are no longer active;  in many cases
using methods  now superseded by other
methods. Careful evaluation of these
data provides insight about past and
potential community composition of
estuarine and coastal marine waters and
is an important initial phase in the
biocriteria development process.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      4-7

-------
    Figure 4-4
    Estuarine and
    coastal marine
    biocriteria survey
    method useful for
    stratified random
    (population
    distribution)
    reference site
    selection. Wet
    season/high flow
    salinity pattern
    showing mainstem
    sampling sites for
    four salinity and
    three substrate
    classifications.
Wet Season/High Flow
                      Key
                       Q  mud
                       [~]  transitional
                       g  sand
                       Q  coastal land area
                        •  single comprehensive
                           survey site
                                              Marine
    Review of historical data collected in
    these waters is helpful for establishing
    potential sample sizes based on the
    variability in the record. These records
    are usually available in the published
    literature, natural history museums,
    college and university departments, and
    federal and state agencies. Caution
    should be exercised in using this
    information because some biological
    surveys occurred at impaired sites, may
    have used incompatible sampling
    methods, inappropriate or inadequate
    QA/QC procedures, were insufficiently
    documented, or had objectives markedly
    different from biocriteria determination.
    While important for establishing
    perspective with respect to current
    reference site data, historical
                        information alone should not be used to
                        establish precise reference conditions.

                        4.3.2  Reference Sites

                        Reference sites refer to locations within
                        a classification category at which data
                        are collected to represent the most
                        natural ambient conditions present. The
                        biocriteria approach generally uses this
                        population of reference sites to establish
                        the collective reference condition that
                        will in turn be used for comparisons of
                        metrics and test sites. Reference sites in
                        estuaries and coastal marine waters
                        include either sites that are distant from
                        point and nonpoint sources and may be
                        applied to a variety of test sites in a
                        given area, or sites that occur along
4-8
                  Physical Classification and the Biological Reference Condition

-------
 Table 4-1. Comparison of elements for characterizing reference conditions (adapted from
 USEPA1998b).



to
.c
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c
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o
to
to
tu
c
.*:
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Historical Data
Yields actual
historical
information on
status.

Inexpensive to
obtain.



Data might be
limited.

Studies likely
were designed
for different
purposes; data
might be
inappropriate.

Human impacts
present in
historical times
were
sometimes
severe.
Present-Day
Biology
Yields obtainable,
best present status.


Any assemblages or
communities
deemed important
can be used.


Even best sites
subject to human
impacts.

Degraded sites might
lower subsequent
biocriteria.









Predictive Models
When sufficient
data are not
available.


Work well for water
quality.



Community and
ecosystem models
not always reliable.

Extrapolation
beyond known data
and relationships is
risky.

Can be expensive.






Expert Consensus
Relatively inexpensive.

Can be better applied
to biological
assemblages than
models.

Common sense and
experience can be
incorporated.
May be qualitative
descriptions of "ideal"
communities.

Experts might be
biased.










    gradients of impact; i.e., nearfield/
    farfield.

    All monitoring sites, whether reference
    or test, can vary spatially and
    temporally due to natural causes. A
    central measure from several reference
    sites is used so that natural variability
    and uncertainty can be accommodated.
    Statistically, this means that the status of
    particular estuarine or coastal marine
    "test" sites are judged by comparing
    them to a population of reference sites
    for the particular classification category.
    There are 3 approaches for using
    reference sites; these are discussed in
    Section 4.4.

    4.3.3   Models

    Mathematical models may be
    characterized as descriptive or
    mechanistic. Descriptive models (also
    known as correlative or statistical
models) describe observed relationships
among measured attributes of a system.
This approach models data without
attention to causal factors. Prediction,
including forecasting and managing, is
the primary goal of a descriptive model,
and the model is considered successful if
it fits the data well. The utility of
descriptive models is often affected by
the quantity and quality of data
available, and in many cases, insufficient
data exists to construct a useful model.

Mechanistic models seek to explain
observed relationships as the result of
underlying processes - they are also
called process models. They typically
consist of a set of state variables, which
describe how the system is "now", and a
set of dynamic equations that describe
how the state variables change over time
(exogenous variables, or "forcing
functions" may also be included).  In a
sense, mechanistic models are a set of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       4-9

-------
   descriptive models for each component
   of a system. The objective of
   mechanistic models is to describe the
   system itself and not simply the data
   obtained by taking measurements; i.e.,
   "fitting the data" is not the prime
   objective. Mechanistic models have
   many more constraints and are more
   time-consuming to construct than
   descriptive models due to the need to
   match system structure. Despite the fact
   that these models are not designed for
   prediction, they are often built and used
   to forecast and manage ecological
   resources for the following reasons: 1)
   in some cases, one does not want to
   perform an experiment without a
   reasonable idea of what will happen
   (e.g. work involving endangered
   species); 2) some experiments are not
   feasible - the amount of data needed for
   a multivariate statistical model grows
   very rapidly with the number of
   variables, and obtaining the data
   required for a descriptive model is
   prohibitively expensive.

   There are two main types of mechanistic
   models commonly used in biology and
   ecology. Simulation (also known as
   management) models are practically
   oriented and focus on prediction and
   management. In these models,
   numerical accuracy is what matters
   most, the model need not match the
   system processes and structure.
   Management models are system specific,
   resulting in numerical predictions for
   one particular system. Theoretical (also
   known as analytical) models focus on
   scientific understanding of the system.
   These models are highly analytical,
   typically involving systems of
   differential equations, and emphasize
   principles rather than numerical
   accuracy. These models have to be
   simple enough to allow  understanding
   of system behavior and what the model
   is predicting. This trade-off often
   requires that the investigator omit or
      estimate many quantitative or unknown
      details, and often assumptions about the
      interaction of system components
      represent hypotheses rather than
      empirically-derived relationships.
      Theoretical models can apply to many
      qualitatively similar systems; they are
      useful whenever the phenomenon of
      interest occurs across multiple systems.

      The degree of complexity of mechanistic
      models to predict reference conditions is
      potentially unlimited with attendant
      increased costs and loss of predictive
      ability as complexity increases (Peters
      1991). However, these models can
      provide much insight into the
      interactions which determine ecological
      condition. Management-oriented
      mechanistic models sacrifice numerical
      accuracy in order to capture system
      dynamics. These models are
      mathematically complex and require
      more time and effort to develop than
      descriptive models.  The primary value
      of mechanistic models may be for
      understanding ecosystem processes and
      evaluating likely system responses when
      mitigation projects are implemented.

      4.3.4  Expert Opinion/Consensus

      In any data evaluation, it is important to
      establish a qualified team of regional
      specialists so the error inherent in
      professional judgment can be reduced.
      This team should evaluate the historical
      data, the candidate reference sites,
      subsequent data collected, and any
      models used in the process. This expert
      team function is even more important
      when no candidate reference sites are
      acceptable. Expert consensus then
      becomes a workable alternative in
      establishing reference expectations.
      Under such circumstances, the reference
      condition may be defined using a
      consensus of expert opinion based on
      sound ecological principles applicable to
      the region of interest.
4-10
Physical Classification and the Biological Reference Condition

-------
   Three or four biologists are convened for
   each assemblage to be used in the
   assessment, and each expert should be
   familiar with the estuaries or coastal
   marine waters and assemblages of the
   region. The experts are asked to develop
   a description of the assemblage in
   relatively unimpaired estuaries and
   coastal marine waters, based on their
   collective experience. The description
   developed by consensus will necessarily
   be more qualitative than quantitative,
   but metrics and metric scoring can be
   developed.

   It is important that the process used to
   review the available information and to
   develop a consensus be thoroughly
   documented so that it can be repeated in
   the future if necessary and to provide
   quality control on its results. This same
   panel of biologists and natural resource
   managers may also be consulted in the
   development of the overall reference
   condition and subsequent biocriteria. In
   establishing the team of experts, it
   should be recognized that bias toward
   specific assemblages may exist and the
   team should be appropriately balanced.

   4.4    Use of Reference Sites to
          Characterize Reference
          Condition

   The determination of the biological
   reference condition from reference sites
   is based on the premise that estuaries
   and coastal marine waters least affected
   by human activity will exhibit biological
   conditions most natural and attainable
   for those waters in the region.
   Anthropogenic effects include all
   possible human influences, for example,
   watershed disturbances, habitat
   alteration (channel dredging and
   dredged material disposal, shoreline
   bulkheading), nonpoint source inputs,
   point source discharges, atmospheric
   deposition, and fishing pressure.
   Human activities can be either
detrimental, such as pollutant inputs, or
positive, such as responsible resource
protection or restoration. In either case,
the manager developing a biocriteria
program must evaluate the effect of such
activities on biological resources and
habitat. In practice, most reference sites
will have some of these impacts,
however, the selection of reference sites
is always made from those with the least
anthropogenic influences.

Reference sites must be carefully
selected because they are used as a key
part of the biocriteria benchmark against
which test sites are compared.  The
conditions at reference sites should
represent the best range of minimally
impaired conditions that can be
achieved within a classification category
for the region. Two primary
considerations guide the selection of
reference sites within each site class:
minimal impairment and
representativeness.

Minimal Impairment - Sites that are
relatively undisturbed by human
activities are ideal reference sites.
However, land use practices and the
presence of major urban areas in the
basins of many of the nation's estuaries
or adjacent to its coastal marine waters
have altered the landscape and quality
of water resources to such a degree that
truly undisturbed sites are rarely
available.  In fact, it can  be argued that
no unimpaired sites exist.  Therefore, a
criterion of "minimally impaired" must
be used to determine the selection of
reference sites.  In regions where
minimally impaired sites are still
significantly degraded, the search for
suitable sites  should be extended over a
wider area, and multistate cooperation
may be essential. It is advisable that the
state make every effort,  once reference
sites are selected, to protect these areas
from degradation. This may involve:
purchase of land or easements; where
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     4-11

-------
   appropriate, location within public
   reserves; use restrictions or permit
   constraints on fishing, discharge, or
   dredging/disposal to protect the quality
   of the reference area waters.

   Representativeness - Reference sites must
   be representative of the best quality of
   the estuaries and coastal marine waters
   under investigation; that is, they must
   exhibit conditions similar to what would
   be expected to be found in the region.
   They should not represent degraded
   conditions, even if such conditions are
   the most common. Sites containing
   locally unusual environmental
   characteristics can result in
   uncharacteristic biological conditions
   and should be avoided.

   Once the physical estuarine or coastal
   marine classification is completed, the
   biological reference condition should be
   defined for each class. This can be
   accomplished with three basic
   approaches: (1) selected reference sites;
   (2) determination from population
   distributions; and (3) site-specific
   reference sites. The second approach,
   determination from population
   distributions, is a relaxation of the
   requirement for minimal impairment;
   and the third approach,  site-specific
   reference sites, is a relaxation of the
   representativeness requirement.

   4.4.1  Selected Reference Sites

   In this approach, reference conditions
   are characterized based on the best
   available sites for a given physical class
   of estuarine or coastal marine waters,
   and indexes or models are developed by
   comparing the best sites (the reference
   sites) to  a second set of sites that may be
   impaired.  The approach assumes that
   within the population of sites  some are
   minimally disturbed and therefore
   comprise a minimally impaired
   biological condition. Selection of
      reference sites must be physical or
      chemical; for example, minimal
      instances of hypoxia, substantially free
      of contaminants, a large proportion of
      natural vegetation in the watershed,
      little or no industrial point sources, little
      or no urban runoff, or little or no
      agricultural nonpoint source pollution.
      Impaired ("test") sites for testing
      response of metrics and model building
      are selected for the presence of one or
      more such anthropogenic disturbances.
      Prior definition and selection of
      reference sites has been used
      successfully in streams for fish and
      invertebrate indexes and models (e.g.,
      Barbour  et al. 1995, Ohio EPA 1987,
      Reynoldson and Zarull 1993, USEPA
      1987, Wright et al. 1984), and in estuaries
      for  benthic invertebrate indexes (Engle
      et al. 1994, Summers et al. 1993,
      Weisberg et al. 1993).

      Reference Site Criteria - The overall goal
      in establishing the reference condition
      from carefully selected reference sites is
      to describe the optimal biota that
      investigators may expect to find at the
      test sites of interest in the absence of
      stresses.  These "test" or "assessment"
      sites can then be compared to the
      reference sites to determine whether
      impairment exists. The characteristics of
      appropriate reference sites vary among
      regions of the country and for different
      water body and habitat types. In
      general,  the following characteristics
      (modified from Hughes et al. 1986) are
      typical of ideal reference sites:

      *•   Sediments and water column
          substantially free of contaminants;

      *•   Natural bathymetry, typical of the
          region;

      *•   Natural currents and tidal regime;

      *•   Shorelines representative of
          undisturbed estuaries and coastal
4-12
Physical Classification and the Biological Reference Condition

-------
       marine areas in the region (generally
       covered by vegetation with little
       evidence of shoreline erosion);

    *•   Natural color and odor of the water.

    In this approach, a single minimally
    impaired site does not represent any one
    region or population of sites, and a
    frequent difficulty is matching habitats
    for valid comparison, particularly given
    that the influence of nonpoint source
    runoff or specific point source
    discharges may extend over wide areas
    due to transport of pollutant loads by
    currents and tides.  Reference conditions
    based on multiple sites are more
    representative and are important to
    establishing quantitative-based or
    numeric biocriteria.

    Representative reference sites should be
    selected within each of the identified
    classes. A sufficient number of sites are
    then sampled to adequately characterize
    the range of existing conditions and to
    reduce the variability in the
    measurements for each class. It is
    desirable to sample a minimum of 10
    sites per class, and 30 sites per class is
    usually optimal for cost effectiveness. In
    regions where all sites are impacted, the
    selected number of "best" sites of each
    class (e.g., mesohaline mud habitat) are
    sampled, where "best" is determined by
    least anthropogenic disturbance or
    impacts, but not by most desirable biota.
    In regions where the population of
    minimally impaired reference sites is
    large, a stratified random sampling
    scheme (using those sites) will yield an
    unbiased estimation of reference
    conditions (Gilbert 1987).

    Stressed Sites - Effective metrics respond
    to environmental degradation and allow
    discrimination of impaired sites from
    the reference expectations. Metrics that
    do not respond  are not useful in
    bioassessment.  Response is determined
by sampling a set of stressed sites in the
same way as the reference sites. Sites
with known problems, such as nutrient
loading, thermal pollution, toxic
sediments, or those influenced by urban
land use, are good candidates. There
should be several in each class for
adequate tests of metric responses.
Since impaired sites are frequently
locations of monitoring by water quality
agencies, data might already exist to test
the biological metrics.  However, the
sampling methods for reference and
impaired sites should be comparable.

For a lengthy sampling season, it is
important to account for seasonal shifts
of the salinity zone boundaries. Stations
proximal to these transition zones may
need to be either located far enough
away from the boundary to have
consistent year-round application or else
their classification should be shifted
with the seasons. For example, some
areas in Figure 4-5 may be polyhaline-
sandy bottom in the spring, but in the
winter they would be classified as
marine-sandy bottom (Figure 4-6).
Thus, such stations have a change of
classification with the shifting of the
halocline. An alternative is to avoid
placing stations near the transition zone
so that, except in extreme climatic
conditions, these stations have
consistent habitat characteristics.  The
biotic data collected at  all sites is then
subclassified by sediment type (e.g.,
sand, sandy-mud, mud) and depth for
this salinity region. This information
becomes the reference condition and
part of the biocriteria for any test sites in
the region.

Example: EMAP Estuary - The EMAP-
Estuaries (EMAP-E) program collected
samples in the Virginian and
Louisianian provinces. One of the goals
of the EMAP-E effort is to develop a
statistical benthic index of estuarine
condition based on extensive
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      4-13

-------
       Figure 4-5
       Estuarine and
       coastal marine
       biocriteria survey
       method useful for
       a priori reference
       site selection.
       Wet season/high
       flow salinity
       pattern showing
       tributary reference
       sites and
       mainstem
       transects for four
       salinity and three
       substrate
       classifications.
Wet Season/High Flow
                          Kev

                           Q
     mud
     transitional
     sand
     coastal land area
     single comprehensive
     survey site
     survey site transect
     across depth profile
     urban areas
     agricultural areas
    information about benthic community
    structure. A test data set of reference
    stations has been compiled for the
    purpose of formulating the index.

    Habitat characteristics used by EMAP to
    define reference stations from the 1990
    and 1991 Virginian province (refer to
    Figure 4-3) collections in Chesapeake
    Bay were:

    *   Stations where no contaminant
       exceeded the effects range-median
       (ER-M) value (which equals the
       concentration at which 50% of
       collected data demonstrated adverse
       biological effects [Long et al. 1995]);
                    *   No sediment toxicity was observed;
                        i.e., percent survival greater than
                        75%  and not significantly different
                        from controls;

                    *   Bottom DO was never less than 1-
                        mgL'1, 90% of the continuous DO
                        measurements were greater than 3-
                        mgL'1 and 75%  of the DO
                        measurements were greater than 4-
                        mgL'1 (Schimmel et al. 1994).

                    The list of stations generated using these
                    characteristics was reviewed to
                    eliminate any reference sites located in
                    areas potentially subject to physical
                    disturbance, such as dredged shipping
                    channels. Fifty-three sites from the
4-14
              Physical Classification and the Biological Reference Condition

-------
     Dry Season/Low Flow
    Kev
     n
mud
transitional
sand
coastal land area
single comprehensive
survey site
survey site transect
across depth profile
 urban areas

| agricultural areas
                                                            Figure 4-6
                                                                     Estuarine and
                                                                     coastal marine
                                                                     biocriteria survey
                                                                     method useful for
                                                                     a priori reference
                                                                     site selection.
                                                                     Dry season/low
                                                                     flow salinity
                                                                     pattern showing
                                                                     tributary
                                                                     reference sites
                                                                     and mainstem
                                                                     transects for four
                                                                     salinity and three
                                                                     substrate
                                                                     classifications.
    combined 1990 and 1991 data sets were
    considered to be reference sites.


    A similar process has been used for data
    collected in 1991 in the Louisianian
    province (refer to Figure 4-3). Using the
    following criteria, eight sites were
    classified as reference sites:
       The minimum DO value over a 24-
       hour period was less than 3.0-mgL"1
       (Summers and Engle 1993);


       Sediment concentrations for any
       contaminant did not exceed the BR-
       IM value;
                                      *  The percent survival for Ampelisca
                                         abdita (10-day) or Mysidopsis bahia
                                         (96-hour) in acute sediment
                                         bioassays was indistinguishable
                                         from controls (Engle et al. 1994).


                                      As states develop their estuarine and
                                      coastal marine biocriteria, they may
                                      wish to consider incorporating EMAP-
                                      identified reference sites into their
                                      sampling programs.  To the degree that
                                      these stations meet state reference
                                      condition requirements, they can serve
                                      as regional reference sites within the
                                      appropriate state classification
                                      categories while also contributing to
                                      USE PA national trend monitoring for
                                      estuaries.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                              4-15

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   4.4.2  Reference Condition Derived
          from Population Distribution

   One problem in the use of the minimally
   impaired sites technique is what to do if
   an area is so extensively degraded that
   even the least impaired site indicates
   significant deterioration. Many systems
   are greatly altered through channel
   dredging and spoil disposal,
   urbanization, and construction and
   operation of marinas and other
   commercial or industrial enterprises.
   The condition of these systems is a result
   of societal decisions  that have to be
   taken into account. However, the
   existence of greatly altered systems
   should not compromise the objective of
   defining the natural state as a reference
   condition.  These disturbed systems
   should not be presumed to represent a
   reference condition of any sort.

   Although the biocriteria established for
   these altered systems serve as a baseline
   for judging impairment, the ultimate
   goal is to achieve the sites' recovery to
   the best attainable condition as
   represented by historical information
   and by conditions at "minimally
   impaired" sites. Consensus of expert
   opinion and historical data play an
   especially important role in
   characterizing the reference condition
   for these systems, as does the
   application of innovative management
   practices to obtain resource
   improvement.

   In defining the biocriteria, managers
   must strike a balance between the  ideal
   restoration of the water resource and the
   fact that human activity affects the
   environment. The most appropriate
   course of action will be to use
   minimally impaired sites as
   representing the maximum amount of
   degradation that will be tolerated,
   thereby ensuring adherence to the
   antidegradation policy of the CWA.
      Continual monitoring should provide
      the feedback necessary to make
      reference condition and interim criteria
      adjustments as warranted during the
      restoration process.

      In this approach, reference conditions
      are derived from the distribution of
      calculated metrics for the entire
      biological data set within a physical
      classification without preselecting any
      reference sites. The entire data set can
      be plotted as a cumulative frequency
      distribution to help determine "best"
      values of candidate metrics (Figure 4-7).
      This approach is applied in cases where
      prior definition of reference sites is not
      possible because all sites are considered
      impaired or because too few reference
      sites exist (e.g., one or two) for an
      unbiased characterization of regional
      reference conditions. This approach has
      been used successfully for fish and
      invertebrate indexes in streams (e.g.,
      Karr et al. 1986, Plafkin et al. 1989) and
      for fish (Jordan et al. 1992, Deegan et al.
      1997) in estuaries.

      The biological reference condition is
      defined from some upper fraction of the
      component indicator variables (metrics)
      and this reference condition is
      subsequently used to judge the
      biological status of other sites. There is
      no independent (nonbiological)
      definition of reference condition.
      Reference condition and biological
      responses are  confirmed by identifying
      severely impaired  sites and then
      comparing them with the derived
      reference condition to determine the
      response(s) of biological indicators to
      impacts, and by selecting metrics that
      are known to respond to perturbation
      from other studies.

      A representative sample is taken of the
      entire population of estuary or coastal
      marine sites (Figure 4-8).  Sites that are
      known to be severely impaired may be
4-16
Physical Classification and the Biological Reference Condition

-------
    CD
    3
    cr
    2
    j_

    I
    03
    3
    3
    o
        100 —
        90 —
80

70

60

50

40

30

20

10
               I
             Minimum
           I
        Maximum
                           Metric Value
                  Figure 4-7
                  Hypothetical
                  cumulative
                  frequency
                  distribution of
                  metric values for
                  all sites in a given
                  estuarine or
                  coastal marine
                  class. The dotted
                  line shows the
                  metric value
                  corresponding to
                  the 95th
                  percentile.
   excluded from the sample, if desired.
   The population distribution of each
   biological metric (Chapter 11) is
   determined, and the 95th percentile of
   each metric is taken as its reference
   value. The range from the minimum
   possible value to the reference value is
   trisected, and values in the top third of
   the trisected range are presumed to be
   similar to reference conditions. Scoring
   of metrics is explained more fully in
   Chapter 11.
   A central assumption of the population
   distribution approach is that at least
   some sites in the population of sites are
   in good condition, which will be
   reflected in the highest scores of the
   individual metrics. Because there is no
   independent definition of reference; i.e.,
   independent of biological status,
   reference conditions defined in this way
   must be taken as interim and subject to
   future reinterpretation. Again,
   antidegradation safeguards must be in
   place to prevent further deterioration of
   the reference condition and criteria.

   4.4.3   Site-specific Reference Sites

   The site-specific approach is analogous
   to up stream-downstream comparisons
in running water or control-impact
designs. It consists of selecting a
reference site paired with each site to be
assessed. There is no characterization of
reference conditions for a physical class
of estuarine or coastal marine waters;
each test site and each reference site is a
special case with each test site compared
to its reference site. Reference sites are
selected to be similar to their respective
test site, but unimpaired by the
perturbations  of interest at the test site.
This approach may be less costly at the
outset because the design and logistics
are simpler than the other approaches.
However, after several years of
sampling and monitoring, costs for this
approach are likely to be similar or
greater because each new test site
requires its own paired reference site.

The site-specific approach has two
problems stemming from the fact that
there is usually only a single reference
site or a single nearby reference area
from which reference sites are selected.
The first problem is representativeness:
Does the reference site represent
reference conditions? Although the
reference site may lack the specific
stressor that is present at the test site,
unless carefully evaluated and placed, it
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       4-17

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    Figure 4-8
    Estuarine and coastal marine
    biocriteria survey method useful
    for stratified random (population
    distribution) reference site
    selection. Dry season/low flow
    salinity pattern showing
    mainstem sampling sites for
    four salinity and three substrate
    classifications.
Dry Season/Low Flow
                                 Kev
                                  Q mud
                                  [~| transitional
                                  g sand
                                  FJ coastal land area
                                   • single comprehensive
                                     survey site
                                          Marine
    may be subject to other stressors that
    have not been considered.
    The second problem with the site-
    specific approach is the potential for
    trivial statistical comparison of two sites
    in that it  is almost always possible to
    demonstrate a statistically significant
    difference between two sites by
    pseudoreplication (Hurlbert 1984).
    Pseudoreplication is the repeated
    measurement of a single experimental
    unit or sampling unit, and treating the
    measurements as if they were
    independent replicates of the sampling
    unit. A single reference site does not
    yield sufficient information to
    meaningfully judge the biological
    relevance of a statistical difference at the
    test site.  The judgment that biotic
             differences between a single test site and
             its reference site may be due to
             differences in impacts can not depend
             on statistical tests, but requires a careful
             weight-of-evidence evaluation (e.g.,
             Hurlbert 1984, Schindler 1971).

             If the objective of a study is to test the
             response of a particular metric, and if
             there are several paired sites, then a
             paired approach can be very powerful,
             allowing paired statistical tests (e.g.,
             Frydenborg 1994). A paired
             experimental design is not
             pseudoreplication because each site pair
             is an independent replicate, and the
             sample size (n) is the number of pairs.
4-18
       Physical Classification and the Biological Reference Condition

-------
   Example 1: Navigation channels -

   Navigation channels can represent an
   important component of overall
   estuarine areas (e.g., Houston Ship
   Channel,  entrance to Chesapeake Bay
   and major harbors).  Resource agencies
   may need to determine the relative
   quality of navigation channels in
   relation to the entire estuarine system as
   part of the overall resource evaluation.

   Stations should be arrayed essentially in
   a nearfield-farfield pattern as shown in
   Figure 4-9, with farfield stations located
   "up" current and nearfield stations
   "down" current, outside the zone of
   suspected impact. Stations should be
   located such that depth, grain size, and
   salinity remain consistent.  These
   conditions may be difficult to locate in a
   tidally-influenced channel.
   Furthermore, if the navigation channel
   to be assessed is dredged to constant
   depth, changes in biota will primarily be
   a function of salinity, given uniform
   poor substrate and the periodic
   destruction of the benthic habitat by
   dredging.

   The reference condition for navigation
   channels would be determined from the
   central tendency (e.g., median) of the
   biological data collected at "upstream"
   stations, that is, those stations that are
   expected  to be out of the zone of
   influence of impact sources (e.g.,
   harbors, industrial areas). Sites from
   which the reference  condition is
   determined should be of comparable
   depth, grain size, and salinity to those in
   suspected impact zones and have the
   same dredging history.

   Example 2: Near shore marine -

   The station array in coastal marine
   waters is  essentially a variation of the
   nearfield-farfield approach because of
   the open water characteristics. Transects
should be laid parallel to shore along
equal depth contours, with sampling
stations placed approximately evenly
along the transect (Figure 4-10). For
habitat consistency, the survey team
should strive to maintain uniform depth,
bottom type, salinity, DO, and pH
characteristics at a minimum for all sites.

These parallel transects can evolve to an
open grid station array if sampling
stations are added around outfalls. In
Figure 4-10, the D1-D5 series of stations
is added to the transect to reveal effluent
distribution shifts around the discharge
site. This approach addresses two
aspects of effluent impact monitoring:
(1) the relative biological community
change near the discharge as compared
to the reference condition described by
observation of either end of the transect;
and (2) the potential shifting, seasonal
change, or expansion or contraction of
the zone of effluent influence from the
discharge. Both forms of information are
important to adequately assess the
biological effects of such effluents. This
design was used for bioassessment of
ocean outfalls from Delaware and
Maryland (see Chapter 13).

A complete grid, while more involved
and expensive, would allow a more
precise evaluation of the effects of these
discharge plumes as they shift in
position in response to changes in
nearshore currents and seasonal shifts in
wave regime (Figure 4-10).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      4-19

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    Figure 4-9	
    Estuarine and
    coastal marine
    survey method for
    navigation channel
    assessment.
                           Harbor
               / •/   "Up" channel
                      stations
                                                                             Net
                                                                             Cu rrent
                                                                             Direction
                                                                   "Down" channel
                                                                   stations
    Figure 4-10
    Estuarine and
    coastal marine
    biocriteria survey
    method useful for
    marine site
    selection.
              net longshore current

               • A
               'C.D3
               i D  • D4
               >E.D5

               » F
               i G
4-20
Physical Classification and the Biological Reference Condition

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 Chapter 5
 Sampling Program  Issues
 Biological Assemblages
 and Design
   This chapter presents sampling program
   issues that are common to each of the
   three assessment tiers that employ field
   sampling. These issues include the
   biological assemblages (Section 5.1) that
   might be sampled, sampling design
   strategies (Section 5.2 and 5.3), and
   logistical considerations (Section 5.4).
   Historically, benthic macroinvertebrates
   have been the most widely sampled
   assemblage, which is described in detail
   in this chapter.

   As described earlier in this document, a
   possible sampling methodology is a
   progressive tiered design, ranging from
   simple biological assessment to detailed,
   intensive studies. The tiers are intended
   to be implemented cumulatively, that is
   when possible, each tier should
   incorporate the elements in the
   preceding tier as appropriate for the
   estuaries or coastal marine water in
   which they are applied. In general, the
   methods are derived from those used
   along the coastal United States (Dauer
   1993, Farrell 1993a, b, Nelson et al. 1993,
   Word 1980,1978, Word et al. 1976); in
   Puget Sound (Eaton and Dinnel 1993); in
   the EMAP - Estuaries program (Holland
   1990), and in USEPA's National Estuary
   Program (NEP) (USEPA1992) and 403
   Monitoring Program (USEPA 1994a).

   Assessment tiers 1 through 3 require
   sampling biological assemblages and
   habitats in one or more field visits. Six
   biological assemblages, including two
   developmental/ experimental
   assemblages, are recommended for
   estuarine and coastal marine waters
bioassessment. Each tier is comprised of
a subset of assemblages, with the
number of assemblages increasing in the
higher tiers.  While these six
assemblages are described, specific
environmental circumstances and
budget constraints will determine what
subset each state uses.  For example, if
finances are extremely limited on the
East Coast the single most effective
assemblage to sample may be
macrophytes. On the West Coast
benthic macroinvertebrates or fish may
the assemblages of choice. The
bioassessment measurements are made
along transects extending from shore to
the deepest (channel) portion of the
estuary, in a systematic grid along
transects extending away from point
source discharges (nearfield/farfield), or
in a probablistic design. The number of
transects or grid points, the assemblages
sampled, and the intensity of sampling
effort are determined by the assessment
tier with overall effort increasing at each
higher tier.

5.1  Assemblages

The study of any group of organisms
will yield information on the status of
their environment.  The objectives in
selecting assemblages for estuarine and
coastal marine bioassessment were to
identify those that:  (1) are
unambiguously useful for biological
assessment; (2) can be sampled and
interpreted in a cost-effective way; and
(3) have easily calculated metrics that
can be used alone or in a multimetric
index of the assemblage. Assemblages
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     5-1

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   that meet these criteria are suggested for
   use in estuarine and coastal marine
   assessment; assemblages that do not
   presently meet the criteria are
   considered to be developmental.
   Suggested assemblages include infaunal
   benthic macroinvertebrates, fish, aquatic
   macrophytes, and phytoplankton
   (chlorophyll a}. The developmental
   assemblages include zooplankton,
   epibenthos, and paleoenvironmental
   systems. These developmental
   assemblages are promising, but they
   lack the same level of refinement
   documented for the suggested
   assemblages listed above and
   unresolved technical problems remain
   with respect to cost-effective assessment
   and interpretation. Background and
   rationale for these  suggested
   assemblages was presented in Chapter 2.

   Multimetric bioassessment is not a
   ready-made, one-size-fits-all instrument
   that will tell managers whether estuaries
   or coastal marine waters are healthy. It
   is an approach that is expected to be
   modified to specific regional conditions
   before it can be applied. For example,
   bioassessment of streams has been
   successful when modified and calibrated
   regionally (e.g., Barbour et al. 1996a,
   Ohio  EPA 1990, Miller et al. 1988), but it
   has been less successful when used "off-
   the-shelf."  Successful application
   requires region-specific selection and
   calibration of metrics, as well as regional
   characterization of reference conditions.
   For example, benthic infauna are rare in
   rocky, fjord-type estuaries and would be
   an inappropriate assemblage to sample
   in such a setting.

   5.1.1   Benthic Macroinvertebrates
          (Infauna)

   Benthic macroinvertebrates are an
   appropriate assemblage for all biological
   assessments of water bodies because
   they respond to water, sediment, and
habitat qualities (Holland 1990, Plafkin
et al. 1989), are not very mobile, and
consequently, integrate long-term
changes in these ecosystem components.
For those reasons, benthic
macroinvertebrates tend to dominate
this text.

Individual macroinvertebrate species
have sensitive life stages that respond to
stress and integrate effects of short-term
environmental variations, whereas
community composition depends on
long-term environmental conditions.  In
addition to taxonomic identification,
benthic macroinvertebrate metrics may
require knowledge of the feeding group
to which a species belongs, for example,
suspension feeders and deposit feeders.
Potential metrics for estuarine and
coastal marine benthos are listed in
Table 5-1. Metrics considered in the
EMAP Estuaries program are listed in
Table 5-2.

          Sampling Strategies

The sampling area should focus on the
most predominant substrate available
(in many estuaries and coastal marine
areas this will be soft sediments of mud
through sand grain sizes), and the
metrics should be developed
independent of microhabitat variation
(Table 5-3).  The type of sampling gear
will depend on the substrate being
sampled; each substrate has its own
optimal sampling gear (Section 5.1.1.4).
Standardized sampling techniques for
each gear type should be followed to
allow for the comparison of data.
Processing of samples should be
standardized by using a mesh size
appropriate to the region.  In the past,
monitoring programs conducted in east
coast waters have often used a 0.5-mm
mesh screen, while west coast programs
have used a 1.0-mm screen (Bowman et
al. 1993).  States should consider testing
various mesh size screens to determine
5-2
                     Sampling Program Issues

-------
  Table 5-1.
Potential benthic macroinvertebrate metrics.
Metric
No. of taxa
Mean no. of individuals pertaxon
% contribution of dominant taxon
Shannon-Wiener diversity
Total biomass
% biomass of opportunistic species
% abundance of opportunistic species
Equilibrium species biomass
Equilibrium species abundance
% taxa below 5-cm
% biomass below 5-cm
% carnivores and omnivores
No. of amphipod species
% individuals as amphipods
% individuals as polychaetes/oligochaetes
No. of bivalve species
% individuals as molluscs
% individuals as deposit feeders
Mean size of organism in habitat
Proportion of expected no. of species in sample
Proportion of expected no. of species at site
Mean weight per individual polychaete
No. of suspension feeders
% individuals as suspension feeders
No. of gastropod species
No. of Capitellid polychaete species
Response to Impairment
reduced
substantially lower or higher
elevated
reduced
substantially lower or higher
elevated
elevated
reduced
reduced
reduced
reduced
elevated
reduced
reduced
elevated
reduced
reduced
elevated
reduced
reduced
reduced
reduced
reduced
reduced
reduced
elevated
   the most appropriate size for their
   bioassessment activities. Ferraro et al.
   (1994) present a process to evaluate the
   optimum infaunal sampling protocol;
   i.e., sampling unit area, sieve mesh size,
   and sample size [n], discussed more
   fully in Section 5.2.6.
                                          Time and Costs

                              An informal survey of some states that
                              conduct routine monitoring of estuaries
                              and coastal marine waters indicates that
                              estuarine sampling requires a minimum
                              of two full-time equivalent (FTE) staff,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                      5-3

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     Table 5-2.        Metrics from which the EMAP Virginian and Louisianian benthic indexes were
                      developed. Louisianian Province has reduced number of metrics due to
                      knowledge gained from previous Virginian province studies (n.a. - not applicable).
Community
Measure of
Structure/
Function
Metrics
Virginian Province
Biodiversity/
Species
Richness
Abundance
Measures
Individual Health
Functional
Groups
Taxonomic
Composition
Proportion of expected number of species present in a sample • Proportion of expected
number of species present at a site • Shannon-Weiner Diversity Index • Pielou's evenness
index
Total benthic abundance per event • Mean benthic abundance per sample • Total benthic
biomass per event • Mean benthic biomass per sample
Biomass/abundance ratio • Mean weight per individual polychaete • Mean weight per
individual mollusc
Number of suspension feeding organisms per event • Biomass of suspension feeding
organisms per event • Percent of total benthic abundance as suspension feeders • Percent
of total benthic abundance as suspension feeding biomass • Number of deposit feeding
organisms per event • Biomass of deposit feeding organisms per event • Percent of total
benthic abundance as deposit feeding organisms • Number of benthic omnivores/predators
per event • Biomass of benthic omnivores/predators per event • Percent of total benthic
abundance as omnivores/predators • Percent of total benthic biomass as
omnivores/predators • Number of opportunistic species per event • Mean number of
opportunistic species per sample • Percent of total benthic abundance as opportunists •
Number of equilibrium species per event • Mean number of equilibrium species per sample •
Percent of total benthic abundance as equilibrium species • Percent of mean benthic
abundance as equilibrium species
Number of amphipods per event • Amphipod biomass per event • Percent of total benthic
abundance as amphipods • Percent of total benthic biomass as amphipods • Number of
bivalves per event • Bivalve biomass per event • Percent of total benthic abundance as
bivalves • Percent of total benthic biomass as bivalves • Number of gastropods per event •
Gastropod biomass per event • Percent of total benthic abundance as gastropods • Percent
of total benthic biomass as gastropods • Number of molluscs per event • Mollusc biomass
per event • Percent of total benthic abundance as molluscs • Percent of total benthic
biomass as molluscs • Number of polychaetes per event • Polychaete biomass per event •
Percent of total benthic abundance as polychaetes • Percent of total benthic biomass as
polychaetes • Number of Capitellid polychaetes per event • Percent of total benthic
abundance as Capitellid polychaetes • Number of Spionid polychaetes per event • Percent
of total benthic abundance as Spionid polychaetes • Percent of total polychaete abundance
as Spionid polychaetes • Number of Tubificid oligochaetes per event • Percent of total
benthic abundance as Tubificid oligochaetes
Louisianian Province
Biodiversity/
Species
Richness
Abundance
Measures
Individual Health
Taxonomic
Composition
Shannon-Wiener Diversity Index • Pielou's Evenness Index • Mean number of species •
Mean number of polychaete species
Mean benthic abundance per site
n.a.
Mean abundance of amphipods per site • Proportion of total benthic abundance as
amphipods • Mean abundance of decapods per site • Proportion of total benthic abundance
as decapods • Mean abundance of bivalves per site • Proportion of total benthic abundance
as bivalves • Mean abundance of gastropods per site • Proportion of total benthic
abundance as gastropods • Mean abundance of molluscs per site • Proportion of total
benthic abundance as molluscs • Mean abundance of polychaetes per site • Proportion of
total benthic abundance as polychaetes • Mean abundance of Capitellid polychaetes per site
• Proportion of total benthic abundance as Capitellid polychaetes • Mean abundance of
Spionid polychaetes per site • Proportion of total benthic abundance as Spionid polychaetes
• Proportion of total polychaete abundance as Spionid polychaetes • Mean abundance of
Tubificid oligochaetes per site • Proportion of total benthic abundance as Tubificid
oligochaetes
5-4
Sampling Program Issues

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   Table 5-3.
Sampling summary for infaunal benthic macroinvertebrates.
Habitat
Sampling
Gear
Index
Period
Sampling
Analysis
Preferred: soft sediments (mud-sand).
Regionally most appropriate for substrate (Table 5-4).
Regionally most appropriate
Preferred:
Summer- East & GulfCoast
Spring - Pacific Northwest
Alternative:
All four seasons, orwinter and summer
Preferred: samples from 3 grabs at each of at least 10 sites.
Alternative: keep sites as replicates if a within-class variance
estimate will be used in assessment.
Preferred: lowest practical taxonomic level
Alternative: identification to class and family.
   and has an associated per sample cost of
   $200 - $400.

   Coastal marine sampling requires a
   minimum of four FTEs, and has an
   associated cost of $400 - $800. Three
   months to a year are required from time
   of sampling to preparation of an
   interpretive report.

             Assessment Tiers

   The benthic infaunal assemblage is
   appropriate for all three field tiers
   outlined for the biological assessment of
   estuaries and coastal marine waters.
   Tier 1 determines the presence/absence
   of macroinvertebrates below 5-cm depth
   in the sediment and briefly describes the
   class  and family of observed benthos.
   Tier 2 determines the major taxa and
   indicator species present in each sample
   to the genus and species level. Tier 3
   applies a full benthic community
   assessment, recording the numbers of
   individuals in each grab to the genus
   and species level, and can include
   determination of biomass if deemed
   appropriate by the state.  Tier 3 uses the
   benthic community assessment with
   replication and additional diagnostic
                          stations and parameters as indicated by
                          the data.

                                        Gear Type

                          All sampling methods and gear types
                          have specific biases because they capture
                          a target assemblage. Because estuaries
                          and coastal marine waters are complex
                          environments with a potentially large
                          number of habitats, it is important to
                          choose sampling methods and gear
                          appropriate for a specific habitat type.
                          Sampling within a given habitat type
                          such as a salinity regime, bottom grain
                          size, and/or depth should be conducted
                          so that samples can be considered
                          representative of the community being
                          studied.

                          A large number of benthic sampling
                          methods and gear are available.  The
                          choice of appropriate methods and gear
                          will depend upon the goals of the
                          sampling and the habitat to be sampled.

                          *•   In subtidal areas, benthic infauna
                              can be collected using grabs, such as
                              Young, Ponar, or Van Veen; or cores
                              such as box, gravity, or hand-held
                              cores collected by divers.  Grab or
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                 5-5

-------
       core size and number of replicates
       should be sufficient to adequately
       sample the infaunal community,
       bearing in mind that distribution is
       usually spatially clumped rather
       than random or regular; and

   >   Intertidal areas may best be sampled
       at low tide with hand-held cores.
       For certain infauna it may also be
       feasible to estimate abundance by
       counting the number of surface
       structures within a given area. For
       example, some polychaete worms
       build identifiable tube or mound
       structures, or leave identifiable fecal
       coils in intertidal areas.  If the local
       infauna has been studied to the
       extent that identification of such
       topographic features can be
       correlated to the presence of a
       particular organism, crude
       abundance and presence/absence
       evaluations may be possible.

   Collection of sediments and benthic
   organisms should be done concurrently
   in order to reduce the costs of field
   sampling and to permit sound
   correlation and multivariate analyses.
   Therefore, the sampling equipment and
   procedure should also include sampling
   the sediment.

   Desirable attributes for sediment
   sampling gear include:

   *•   Creates a minimal pressure wave
       when descending;

   >   Forms a nearly leakproof seal when
       the sediment sample is taken;

   *•   Prevents winnowing and excessive
       sample disturbance when ascending;

   *•   Allows easy access to the sample
       surface so that undisturbed
       subsamples may be taken;
*•  Allows vertical sectioning of
   undisturbed samples for profile
   examination.

Penetration well below the desired
sampling depth is preferred to prevent
sample disturbance as the device closes.
It is best to use a sampler that has a
means of weight adjustment so that
penetration depths may be modified
with changing sediment type (USEPA
1992).

           Grab Samplers

Well designed and constructed grab
samplers are capable of consistently
sampling bottom habitats.  Depending
on the size of the device, areas of 0.02- to
0.5-m2 and depths ranging from 5- to 15-
cm may be sampled.  Limitations of grab
samplers include:

*•  Variability among samples in
   penetration depth depending on
   sediment  properties;

*•  Oblique angles of penetration which
   result in varying penetration depths
   within a sample; and

*•  The sample may be folded or
   otherwise distributed by some
   devices, such as the Shipek sampler,
   resulting in the loss of information
   concerning the vertical structure of
   benthic communities in the
   sediments.

However, careful use of these devices
will provide reliable quantitative data.
Grab samplers are the tools of choice for
a number of estuarine and marine
monitoring programs due to their ability
to provide quantitative data at a
relatively low cost (Fredette et al. 1989,
USEPA 1986-1991). Various grab
samplers which could be used for Tiers
1-3 are summarized in Table 5-4.
5-6
                     Sampling Program Issues

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    Table 5-4.   Summary of bottom sampling equipment (Adapted from USEPA1992, Klemm etal.
               1992, and ASTM 1998b).
DEVICE
S-H
OJ
a
c
-S
"ij jy
u ^
u
II
S m
§ u
tin O
'orer with
ble Fluorocarbon
3r glass liners.
-a o ••£
§ 8 j§
0)
X >H
1r
2
0)
IJ
2
O
be
fi
O
Ekman or Box
Dredge
USE
Soft sediments
only.
Soft sediment
only.

Shallow wadeable
waters or deep
waters if SCUBA
available. Soft or
semi-consolidated
deposits

Same as above
except more
consolidated
sediments can be
obtained.

Same as above.
Semi-consolidated
sediments.


Lakes, estuarine
and marine areas.

Soft to semi-soft
sediments. Can
be used from boat,
bridge, or pier in
waters of various
depths. Weights
can be added for
deeper penetration
in fine sand.
ADVANTAGES
Samples a variety of soft substrates
up to harder types. Sampling tube
can be modified up to 100-cm2
substrate surface; least disturbance
to water/bottom interface. Can be
used in shallow to medium-shallow
water up to 30.5-m or deeper.
Good penetration on soft sediment.
Small sample volume allows greater
number of replicates to be collected
in a short time period. Samples deep
burrowing organisms. Used in
shallow to deep water (3-m to 183-m).
Automatic check valves prevent
sample loss.

Preserves layering and permits
historical study otsediment
deposition. Rapid-samples
immediately ready for laboratory
shipment. Minimal risk of
contamination.

Handles provide for greater ease of
substrate penetration. Above
advantages.

Collection of large undisturbed
sample allowing for subsampling.
Low risk of sample contamination.
Maintains sediment integrity relatively
well.


Eliminates metal contamination if
grab is plastic or kynar lined.
Reduced pressure wave. Can
subsample. Better penetration in
sand than the modified Van Veen.

Obtains a larger sample than coring
tubes. Can be subsampled through
box lid. Hinged top doors reduce
washout, shock waves and substrate
disturbance. Range of sizes
available.
DISADVANTAGES
Samples limited surface area.
Requires boat and winch.
Heavy; requires boat and winch.
Does not retain sand unless
bronze core retainers are used.

Small sample size requires
repetitive sampling. Impractical
in water > 1-m depth if SCUBA
not available.

Careful handling necessary to
prevent spillage. Requires
removal of liners before
repetitive sampling. Slight risk
of metal contamination from
barrel and core cutter.

Hard to handle.
Careful handling necessary to
avoid sediment spillage. Small
sample, requires repetitive
operation and removal of liners.
Time consuming.


Expensive, heavy, requires boat
and winch.

Possible incomplete jaw closure
and sample loss. Possible
shock wave which may disturb
the fines. Metal construction
may introduce contaminants.
Possible loss of fines on
retrieval. Inefficient in deep
water or where even moderate
current exists.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-7

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     Table 5-4 (Cont'd). Summary of bottom sampling equipment (Adapted from USE PA 1992,
     Klemm et al. 1992, and ASTM 1998b).
DEVICE
Ponar Grab Sampler
1
E
CO
LTl
1 ;H
pa U
Modified Van Veen
o
£
S
pa
JH
i
'^ ^
lu
be
D
-. en
11
c/5 pa
USE
Useful on sand,
silt, or clay.
Waters of 1-2-m
deep when used
with extension rod.
Soft to semi-
consolidated
deposits.
Useful on sand,
silt, or clay.
Sampling moving
waters from a fixed
platform.
Useful on most
substrates.
Useful on most
substrates.
Various
environments
depending on
depth and
substrate.
ADVANTAGES
Most universal grab sampler.
Adequate on most substrates; very
efficient for hard sediments. Large
sample obtained intact permitting
subsampling. Better penetration than
other grabs: sideplates and screens
reduce washout, shock waves and
substrate disturbance.
Piston provides for greater sample
retention.
Adequate on most substrates. Large
sample obtained intact.
Streamlined configuration allows
sampling where other devices could
not achieve proper orientation.
Reduced pressure wave. Designed
for sampling hard substrates. Can
subsample and make vertical cross-
sections. Greater penetration in sand
and cobble than modified Van Veen,
but possibly not as deep as a Young
grab. Better closure in areas with
wood debris.
Inexpensive, easy to handle.
DISADVANTAGES
Shock wave from descent may
disturb fines. Possible
incomplete closure of jaws
results in sample loss. Possible
contamination from metal frame
construction. Sample must be
further prepared for analysis. A
very heavy grab requires use of
a boat with winch and cable.
Shell hash can hold jaws open
causing loss of sample. Must
use stainless-lined grab for
sediment metals samples.
Cores must be extruded on site
to other containers - metal
barrels introduce risk of metal
contamination.
Requires boat and winch.
Shock wave from descent may
disturb fines. Possible
incomplete closure of jaws
results in sample loss. Possible
contamination from metal frame
construction. Sample must be
further prepared for analysis.
Limited penetration in hard
sand. Possible overpenetration
in soft silt.
Possible contamination from
metal construction.
Subsampling difficult. Not
effective for sampling fine
sediments.
Loss of fines. Heavy; requires
boat and winch. Possible metal
contamination unless grab is
lined.
Loss of fines on retrieval
through water column. Layer
information not collected.
   The number and kinds of
   macroinvertebrates collected by a
   particular grab may be affected by the
   habitat sampled, substrate type
   sampled, depth of penetration, angle of
   closure, completeness of closure of the
   jaws and potential loss of sample
   material during retrieval, creation of a
   "shock" wave and "washout" of
   organisms at the surface of the substrate.
   The high-flow velocities often
   encountered in rivers and wave action in
   estuaries and coastal marine waters can
   also affect stability of the sampler
(Klemm et al. 1992). USEPA EMAP-
Estuaries protocols describe a simple
and consistent method for accepting or
rejecting a bottom grab (Figure 5-1).

The type and size of the grab samples
(or other device) selected for use will
depend on factors such as the size of
boat, available winch and hoisting gear,
the type of sediment to be sampled,
water depth, current velocity, and
whether sampling is conducted in
sheltered areas or open water (Klemm et
al. 1992). The EMAP-Near Coastal
5-8
                      Sampling Program Issues

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   Figure 5-1
   Cross-section of
   sediment in
   clamshell bucket
   illustrating
   acceptable and
   unacceptable
   grabs.
                          Acceptable if Minimum
                        Penetration Requirement Met
                       and Overlying Water is Present
                   Unacceptable
             (Washed, Rock Caught in Jaws)
                         Unacceptable (Canted with
                             Partial Sample)
                  Unacceptable
                   (Washed)
   Program selected a Young grab
   (sometimes referred to as a Young-
   modified Van Veen) that samples a
   surface area of 440-cm2 (Weisberg et al.
   1993).  This Young grab was selected
   because it deploys easily from small
   boats (24-ft) and it samples sand and
   mud habitats adequately.  The
   maximum penetration depth of the grab
   was 10-cm.

   PONAR Grab:

   The PONAR has side plates and a screen
   on the top of the sample compartment to
   prevent loss of the sample during
   closure. With one set of weights, this
   heavy steel sampler can weigh 20-kg.
   Word et al. (1976) report that the large
   amount of surface disturbance
   associated with Ponar grabs can be
   greatly reduced by simply installing
   hinges rather than fixed screen tops,
   which will reduce the pressure wave
   associated with the sampler's descent
into the sediment.  The standard Ponar
takes a sample area of 523-cm2.  A small
version, the petite Ponar grab, takes a
sample area of 232-cm2 and can be used
in habitats where there may be an
unusual abundance of
macroinvertebrates, thus eliminating the
need to subsample.

The weight of the standard Ponar grab
makes it necessary to use a winch and
cable or portable crane for retrieving the
sample, and ideally the samples should
be taken from a stationary boat. The
smaller version (petite Ponar grab) is
designed for hand-line operation, but it
may be used with a winch and cable.

Ekman Grab:

The Ekman grab sampler is used to
obtain samples of macroinvertebrates
from soft sediments, such as very  fine
sand, mud, silt, and sludge where there
is little current. This grab is inefficient
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   in deep waters, under adverse weather
   conditions, and in waters with moderate
   to strong currents or wave action. The
   Wildco box corer is like a heavy duty
   Ekman with a frame and weights and
   can be used to collect macroinverte-
   brates in estuaries. Because of its weight
   a winch is necessary for retrieving the
   sample from a stationary boat.

   The Ekman grab sampler is a box-
   shaped device with two scoop-like jaws
   that must penetrate the intended
   substrate without disturbing the water-
   sediment boundary layer, close when
   positioned properly on the bottom, and
   retain a discrete sample of sediment
   while it is brought to the surface for
   processing. Hinged doors on the top of
   the grab prevent washout during sample
   retrieval. The grab is made of 12- to  20-
   gauge brass or stainless steel and weighs
   approximately 32-kg. The box-like part
   holding the sample has spring-operated
   jaws on the bottom that must be
   manually set. The sampler is available
   in several sizes; however, in very soft
   substrates only a tall model should be
   used, either a 23-cm or a 30.5-cm model.
   The Ekman grab can be operated from a
   boat with a winch and cable.

   Smith-Mclntyre Grab:

   The Smith-Mclntyre grab sampler is
   designed to obtain samples of
   macroinvertebrates from sediments in
   rough weather and deep water in
   estuaries and oceans. This device
   samples a surface area of 0.1-m2 and  is
   useful for sampling macroinvertebrates
   from a broad array of sand, gravel, mud,
   clay, and similar substrates.

   The Smith-Mclntyre grab sampler has
   hinged top doors to prevent sample
   washout and the pressure wave in
   descent.  Its paired jaws  are forced into
   the intended substrate by two "loaded"
   strong coiled springs when the grab
touches the bottom. The jaws close
when positioned properly on the
bottom, and retain a discrete sample of
sediment to be brought to the surface for
processing. The device is heavy and can
weigh 45.4-kg or more. The chief
advantage of the sampler is its stability
and easier control in deep and rough
waters.  The spring-loaded jaws of the
Smith-Mclntyre grab must be considered
a hazard and caution should be
exercised when using the device. Due to
the weight and size, this device must be
used from a vessel with boom and lifting
capabilities.

Modified Van Veen Grab:

The modified Van Veen grab sampler is
used to obtain samples of
macroinvertebrates from sediments in
estuaries and other marine habitats.
This device is useful for sampling sand,
gravel, mud, clay and similar substrates
and is available in three sizes: 0.06-m2,
0.1-m2, and 0.2-m2. Larger versions of
this grab are available, and their use is
dependent upon the type of bottom to be
sampled, and the type of vessel available
to deploy the sampler.

The modified Van Veen grab sampler
has paired jaws that penetrate the
intended substrate without disturbing
the water-sediment boundary layer.
They are closed by the pincher-like
action of two long arms. The long arms
give added leverage for penetrating
hard sediments.

The modified Van Veen is basically an
improved version of the Petersen grab in
that long arms have been attached to the
jaws to help stabilize the grab on the
bottom in the open sea just prior to or
during closure of the device. This grab
is used extensively in Puget Sound for
the ambient monitoring program and for
pollution-related surveys.  Large hinged
screen doors with rubber flaps have
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                     Sampling Program Issues

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   been added to the top of the sampler for
   access to the surface of the sample.
   Additional weights can be applied to the
   modified Van Veen jaws to effect greater
   penetration in sediments, although
   penetration is not as deep in hard sand
   or cobble as with the Young grab or the
   Smith-Mclntyre.

   Young Grab:

   The Young grab sampler is similar in
   operation to the Van Veen and the
   Smith-Mclntyre, but the sample can be
   accessed undisturbed  from the top of the
   grab through hinged doors like a Smith-
   Mclntyre. It is encircled by a ring-like
   frame which enhances flat, stable
   landings of the grab on the substrate.
   Weights can be added to the frame to
   aid penetration in hard sand or cobble.
   A major advantage of the Young grab is
   efficient performance without the risk of
   injury associated with the spring-loaded
   Smith-Mclntyre. This grab can be
   provided in a 0.044-m2 and a 0.1-m2
   version. The former is appropriate to
   small boat operations while the latter
   size is more effective for marine work
   and obviously requires fewer lowerings
   or "drops" to obtain the same volume of
   material and community representation.

   Recent comparisons of the Young and
   Smith-Mclntyre grabs in rough Atlantic
   waters revealed consistently greater
   volumes of sediment collected by the
   Young grab in six trials each in soft
   sandy muds, sand, packed sand, and
   sand and gravel sediments. While the
   grabs were the same size (0.1-m2) and
   had the same weight attached, the
   significant factor in performance was the
   design differences of the two grabs
   (Gibson 1995, unpublished).

   While either the 0.1-m2 Young or Smith-
   Mclntyre designs are effective off-shore
   grabs for the biocriteria development
   purposes of this guidance, the Smith-
Mclntyre provides better access to the
sample while the Young grab is easier
and safer to operate, especially in rough
weather. An advantage of both designs
is that the retrieved sample can be cross-
sectioned and examined intact, although
this is easier with the Smith-Mclntyre
design.

            Core Samplers

Core samplers use a surrounding frame
to ensure vertical entry; vertical
sectioning of the sample is possible
(USEPA 1986-1991). Coring devices can
be used at various depths in any
substrate that is sufficiently compacted
so that an undisturbed sample is
retained; however, they are best suited
for sampling the relatively homogenous
soft sediments, such as  clay, silt, or sand
of the deeper portions of estuaries and
coastal marine waters.  Because of the
small area sampled, data from coring
devices are likely to provide very
imprecise estimates of the standing crop
of macrobenthos.

KB, Ballcheck, and Phleger Corers:

KB type, Ballcheck, and Phleger corers
are examples of devices used in shallow
or deep water; they depend on gravity to
drive them into the sediment. The cores
are designed so that they retain the
sample as it is withdrawn from the
sediment and returned  to the surface.
Hand corers designed for manual
operation are used in shallow water.
Sections of the core can be extruded and
preserved separately or the entire core
can be retained in the tube and
processed in the field or laboratory.
Intact cores can also be preserved by
freezing and processed later.

Additional replication with corers is
feasible because of the small amount of
material per sample that must be
handled in the laboratory. Multiple-
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   head corers have been used in an
   attempt to reduce the field sampling
   effort that must be expended to collect
   large series of core samples (Flannagan
   1970).

   The Dendy inverting sampler (Welch
   1948) is a highly efficient coring-type
   device used for sampling at depths to 2-
   or 3-m in nonvegetated substrates
   ranging from soft mud through coarse
   sand. Because of the small surface area
   sampled, data obtained by this sampler
   suffer from the same lack of precision
   (Kajak 1963) as the coring devices
   described above.  Since the per-sample
   processing time is reduced, as with the
   corers, large numbers of replicates can
   be collected.

   Stovepipe-type devices include the
   Wilding sampler (Wilding 1940, APHA
   1992) and any tubular material such  as
   60- to 75-cm sections of standard 17-cm
   diameter stovepipe (Kajak 1963) or 75-
   cm sections of 30-cm diameter
   aluminum irrigation pipe fitted with
   handles.  In use, the irrigation pipe or
   commercial stovepipe is manually
   forced into the substrate, after which the
   contained vegetation and coarse
   substrate materials are removed by
   hand.  The remaining materials are
   repeatedly stirred into suspension,
   removed with a long-handled dipper
   and poured through a wooden-framed
   floating sieve. Because of the laborious
   and repetitive process of stirring,
   dipping, and sieving large volumes of
   material, the collection of a sample often
   requires 20- to 30-minutes.

   The use of stovepipe samplers is limited
   to standing or slowly moving waters
   having a maximum depth  of less than
   60-cm. Since problems relating to depth
   of sediment penetration, changes in
   cross-sectional area with depth of
   penetration, and escape of organisms are
   circumvented by stovepipe samplers,
they are appropriate for quantitative
sampling in all shallow-water benthic
habitats and can be deployed from small
boats. They probably represent the only
quantitative device suitable for sampling
shallow-water habitats containing
stands of rooted vascular plants and
they will collect organisms inhabiting
the vegetative substrates as well as those
living in sediments.

In marine waters, benthic macrofauna
are generally collected using various box
cores deployed from ships or other
platforms, or diver operated cores. A
box coring device consisting of a
rectangular corer having a cutting arm
which can seal the sample prior to
retraction from the bottom should be
used. In order to sample a sufficient
number of individuals and species, and
to integrate the patchy distribution of
fauna, each sample should have a
surface area of no less than 100-cm2 and
a sediment depth of at least 20-cm. In
sediments having deep, burrowing
fauna, a box corer capable of sampling
deeper sediment may be needed.  In
sandier sediments, it may be necessary
to substitute a grab sampler for the box
corer in order to achieve adequate
sediment penetration.  Visual inspection
of each sample is necessary to insure
that  an undisturbed and adequate
amount of sample is collected.

           Sieve Mesh Size

The use of different sieve mesh sizes for
screening benthic samples limits the
comparability of results between marine
monitoring studies (Reish 1959; Rees
1984). The major advantage of using a
smaller mesh size is the retention of both
juvenile and adult organisms as well as
large-and small-bodied taxa. The major
disadvantage is the concomitant
increased cost of sample processing.  For
example, using a 0.5-mm mesh rather
than a 1.0-mm mesh could increase
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                     Sampling Program Issues

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   retention of total macrofaunal organisms
   by 130 to 180%; however, costs for
   processing the samples may increase as
   much as 200% (USEPA1986-1991).

   It is recommended that a standard mesh
   size be selected for all monitoring
   studies.  A review of estuarine
   monitoring programs from around the
   country (Bowman et al. 1993) showed
   that both 0.5- and 1.0-mm mesh sizes are
   used, with a slight majority of the
   programs reviewed using a 0.5-mm
   mesh screen (Table 5-5). Dauer (1993)
   evaluated biocriteria developed from
   data collected as part of the Virginia
   Benthic Biological Monitoring Program
   using a 0.5-mm mesh screen.

   Sieving can be done either aboard the
   survey vessel or on shore after the
   cruise. Sieving occurs prior to fixation
   (sample preservation) aboard the vessel,
   whereas waiting until after the cruise
   requires fixation prior to sieving. If
   inadequate concentrations of fixative are
   added and deterioration or
   decomposition of organisms occurs,
   there may be significant sample
   degradation. If large numbers of
   samples are to be collected, field sieving
   reduces sample storage requirements as
   well as the modification/loss of data
   (USEPA 1992,1994d).

   After samples have been collected, the
   samples must be processed so that data
   can be collected and analyzed.  Two
   aspects of sample processing of
   particular concern are the subsampling
   and identification that may occur in the
   field or laboratory. Sorting procedures
   are described in Klemm et al. (1992).

   *•   Subsampling of benthic inf auna can
       be accomplished by subcoring; i.e.,
       removing smaller core samples from
       within a grab or core sample, and
       sorting all organisms found within
       the subcore. The size and number of
   subcores that should be taken will
   depend upon the variability of the
   infaunal community.  Representative
   subsampling can be difficult to
   achieve if benthic species have
   patchy or clumped distributions.
   Subsampling can also damage
   collected organisms (e.g., polychaete
   worms), decreasing the number of
   specimens that can be identified to
   genus or species;

*•  Several studies have examined the
   effect of varying levels of taxonomic
   analysis on the results of statistical
   measures of the infaunal community
   (e.g., Ferraro and Cole 1990,1992,
   1995, Warwick 1988, Warwick et al.
   1990). The studies indicate that in
   some instances species-level
   taxonomic identification does not
   yield any more information than
   family- or even phylum-level
   identification. The degree of
   taxonomic proficiency required to
   adequately characterize the
   community will depend upon the
   diversity present in the community.
   Species level identification is
   necessary and cost-effective for fish
   surveys. However, while this is
   desired for macroinvertebrates, it is
   often too costly and assessment
   needs can usually be met at the
   genus level.

Although species-level identifications
may not be necessary for classifying sites
as minimally impaired or impaired, this
degree of taxonomic identification may
be required to assess the sources of
impairment using data collected in Tier
3. Species-level identifications require
greater taxonomic expertise than do
higher taxonomic divisions; this species
level of expertise may not be as readily
available to state agencies. If this is the
case, then state resource managers must
determine whether the cost of
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  Table 5-5.
Mesh sizes used in estuary benthic monitoring programs.
Monitoring Program
Chesapeake Bay
Tar/Pamlico
EMAP-Near Coastal
Naples Bay, Florida
Puget Sound Ambient
Monitoring Program
Puget Sound Estuary
Program
Mesh Size (mm)
0.5
0.5
0.5
0.595
1.0
1.0
Reference
Dauer 1993, Holland et al.
1987, 1988, 1989,
Ranasinghe et al. 1992
Eaton 1992a-d
USEPA 1992, Weisberg et
al. 1993, Holland 1990
Simpson et al. 1979
PSWQA 1988, 1990, 1991
Simenstad et al. 1991
   contracting these identifications is
   justified based on the information
   obtained and the assessment tier to
   which it would be applied. One
   approach to this problem of obtaining
   sufficient taxonomic expertise is for the
   states of a region to cooperate in a joint
   venture to employ the taxonomic
   expertise  necessary to all. In this
   manner the cost of a skilled taxonomist,
   either contracted or on staff, can be
   shared.

   5.1.2   Fish

   Fish communities include species in a
   variety of trophic levels (omnivores,
   herbivores, planktivores, piscivores).
   Fish are long-lived, integrate long- and
   short-term changes, and they also
   integrate  effects of lower trophic levels;
   thus, fish community structure is  a good
   measure of integrated environmental
   health. Estuarine and coastal marine
   fish receive a large amount of public
   attention  because of sport and
   commercial fishing and attendant
   concerns regarding fish production and
   safety for human consumption. On the
   negative side, fish may be wide-ranging
   or migratory and might not reflect local
                            conditions in estuaries and coastal
                            marine waters; some fish species may
                            also be influenced by management
                            (stocking), angling, and commercial
                            harvesting; and unbiased sampling is
                            difficult because each feasible gear type
                            is highly selective.

                                        Sampling Gear

                            Fish communities may vary
                            considerably among the numerous
                            habitat types that may be present in a
                            target estuary or coastal marine area.
                            The choice of sampling method and gear
                            type will depend upon the habitat and
                            the fish species of interest. Shallow
                            areas may best be sampled using dip
                            nets or beach seines, while deeper
                            waters may be sampled using gill nets,
                            purse seines, or otter trawls. Net and
                            mesh size should be appropriate to
                            allow a representative sample of target
                            fish to be obtained.  Fishing effort
                            should be comparable among stations
                            with constant tow distances, times,
                            speeds, and lengths of trawl warps.
                            Because there is no  easy way of
                            estimating population size in any given
                            area of an estuary or coastal marine area,
                            consistency in effort is of the utmost
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                                                  Sampling Program Issues

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   importance to allow legitimate
   comparisons among sites.

   Maryland DNR's IBI sampling
   techniques are designed to sample the
   nearshore fish communities in the tidal
   tributaries of the Chesapeake Bay. They
   were modeled after the Maryland
   Striped Bass Juvenile Seine Survey
   which has been ongoing since 1954
   (Goodyear 1985). Two beach seines are
   pulled at each site allowing a half hour
   interval between hauls for repopulation
   of the seine area.  Seines are pulled with
   the tide employing a "quarter sweep"
   method where one end of the seine is
   held on shore while the other end is
   fully extended perpendicular to shore,
   and then pulled back into shore forming
   a semi-circle. The seine used is a bagless
   6.4-mm mesh seine 30.5-m in length and
   1.2-m deep. Precautions are taken upon
   approaching the site to avoid
   disturbance of the sampling area.

   Concurrent trawls are pulled with the
   tide in the channel adjacent to shore. A
   small otter trawl (3.1-m with 12.8-mm
   stretch mesh, and 50.8-cm x 25.4-cm
   doors) with tickler chains is used to
   sample the bottom community local to
   the seine sample area. Water quality
   measurements (temperature, dissolved
   oxygen, pH, conductivity, and salinity)
                          and Secchi depth are also taken in the
                          trawling area. Water quality is sampled
                          at surface, mid, and bottom depths.
                          These measurements have proven useful
                          in relating water quality parameters to
                          fish communities. A summary of fish
                          sampling is given in Table 5-6.

                          *•   Subsampling of fish collected using
                             any of the sampling methods
                             mentioned above is problematic.  It
                             is probably most efficient and
                             statistically valid to identify and
                             make external measurements and
                             observations of all fish caught
                             during a given tow or time period.

                          >   The level of taxonomic identification
                             required to effectively characterize
                             the fish community will depend
                             upon the diversity of the community
                             being sampled and the metrics being
                             used to evaluate the data.
                             Identification to species is preferable
                             for most individuals taken in a given
                             area.  Individuals that cannot be
                             field-identified should be preserved
                             and returned to the lab  for
                             identification.

                          5.1.3  Aquatic Macrophytes

                          Macrophytes form an integral part of the
                          littoral zone of many estuaries and
    Table 5-6.
Sampling summary for fish.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Sublittoral.
Seines and any gear that effectively captures bottom -feed ing and pelagic
fish, usually otter trawls.
Any season can be selected depending upon migration and recruitment
patterns in the region. Seasonal sampling might be needed to assess
particular problems.
Bottom-feeding and pelagic fish. Sufficient sets of gear to obtain
representative species counts (usually 4 or more).
Collected species are weighed, measured, and examined for external
abnormalities (lesions, growths, deformities). Histopathology may be
performed.
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   coastal marine waters, serving as habitat
   for fish and invertebrates as well as
   being a distinct biological assemblage.
   For many estuaries, the areal extent and
   distribution of SAV is used as an
   indicator of estuarine quality (Batiuk et
   al. 1992). Ecosystems whose primary
   producer component is dominated by
   aquatic macrophytes can be transformed
   to macro algae or phytoplankton-
   dominated systems through nutrient
   enrichment. Increased nutrient input
   stimulates macrophyte growth;
   however, it also promotes growth of
   periphyton and phytoplankton, which
   shade the SAV. The shading reduces
   macrophyte growth and survival
   (Dennison et al. 1993, Batiuk et al. 1992).
   Overall, macrophyte standing stock is an
   excellent indicator of estuarine water
   quality. The presence of confounding
   factors, such as diseases, can be
   determined from examination of
   affected plants, or from historical
   information.  Potential macrophyte
   metrics are listed in Table 5-7 and the
   recommended sampling protocol for
   macrophytes is summarized in Table 5-
   8. Field sampling can be performed in a
   single visit. Plants are identified and
   weighed on-site, with voucher
   specimens preserved as  necessary.
   There is no intensive laboratory analysis
   required.

   5.1.4  Phytoplankton

   Phytoplankton are the base of most
   estuarine food webs  (Day et al. 1989),
   and fish production is linked to
   phytoplankton primary  production (e.g.,
   Day et al. 1989). Excessive nutrient and
   organic inputs from human activities in
   estuaries and their watersheds leads to
   eutrophication characterized by:
   reduction in seagrasses, increases in
   phytoplankton biomass, macrophyte
   biomass (macroalgal biomass), reduced
   water clarity, and reduced oxygen
   saturation in bottom waters. From a
human perspective, problems might
include loss of aesthetic appeal,
decreases in desirable commercial and
game fishes, and loss of recreational
access caused by increased macrophyte
production.

Phytoplankton standing stock is
measured by surface chlorophyll a
concentration, sampled at the 0.5-m
depth at each sampling site (Table 5-9).
Tiers 1 and 2 can use a single
measurement taken at each sampling
site with a fluorometer attached to a
conductivity-temperature-depth meter
(CTD) (USEPA 1994c) taken from June
through September. Alternatively,
chlorophyll a may be determined
spectrophotometrically on
phytoplankton samples returned to the
lab.  Tier 2 can include identification of
dominant taxa, including nuisance taxa.
Tier 3 uses a seasonal or annual average
surface chlorophyll concentration from
all stations  over all sampling events and
can include full characterization of the
phytoplankton community.

If phytoplankton communities are to be
sampled, several techniques may be
employed; these  are described more
fully in APHA (1992).

*•   Phytoplankton samples may be
    obtained using water bottles
    deployed on  a wire at a given, or
    preferably various, depths.  The
    water bottles used should be
    constructed and cleaned in a manner
    appropriate for the collection of
    phytoplankton samples (e.g., Niskin
    bottles washed and rinsed in order
    to remove contaminants).
    Chlorophyll concentration is
    measured from the sampled water,
    and phtyoplankton cells may be
    filtered or settled for identification
    and enumeration.
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     Table 5-7.
Potential aquatic macrophyte metrics.
                       Metric
                                                        Response to impairment
       Tier 1:
       % cover
       dominant taxa
                          substantially more or less than reference
                          substantially more or less than reference
       Tiers 2-3:
       % cover
       biomass
       maximum depth of plant growth
       density of new shoots
       stem counts
                          reduced or enhanced
                          substantially more or less than reference
                          reduced under enrichment
                          reduced
                          reduced
     Table 5-8.
Sampling summary for aquatic macrophytes.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Euphotic zone.
Aerial photography; quadrats
During growing season
Tier 1 : Estimate of area covered by macrophytes.
Tiers 2-3: Quadrat samples for biomass collected by diver; 3-5
placed transects perpendicular to shore; sam pies are taken at 0
depth intervals from edge of emergent zone to the sublittoral.
randomly
.5-m
Tier 1 : Dominant taxa identified, % cover estimated from aerial
photography.
Tiers 2-3: All species identified, relative abundance of each estimated
from wet weight.
     Table 5-9.
Sampling summary for phytoplankton.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Each sampling site preferred.
Fluorometer attached to CTD (USEPA 1994e) for in situ measurements;
or spectrophotometrically on water samples collected with a water
sampler.
Tiers 1 and 2: June - September
Tiers 2 (optional) and 3: growing season average; 6-10 samples; March -
October (longer in subtropical regions).
Preferred: single sample, 0.5-m depth.
Alternate: at same depths as nutrient samples.
Tier!: Chlorophyll a mg/L (Tiers 1-3). Tier 2: ID dominant taxa. Tier 3:
full comm unity species characterization.
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   *•   Phytoplankton may also be
       collected by net hauls using a
       plankton net with an appropriate
       mesh size.

   Bottle collections are most useful
   when analyzing a bulk community
   measure such as chlorophyll a
   concentration (assuming a
   fluorometer coupled to a CTD is not
   used), while net hauls are better for
   studies designed to enumerate
   species. Water samples for
   chlorophyll a determination can also
   be used for nutrient analysis.

   *•   The level of taxonomic
       identification that should occur
       will depend upon the diversity of
       the community, the analyses that
       are to be performed, and the cost
       and availability of taxonomic
       experience;

   *•   If phytoplankton are collected
       using water bottles, the water may
       be subsampled in the field or lab
       prior to analysis. The size and
       number of subsamples that should
       be taken will depend upon the
       variability present in the
       community;

   *•   If subsamples are taken from net
       hauls, it may be necessary to
       resuspend the organisms found in
       the cod end of the net in a larger
       volume of water in order to
       facilitate subsampling.

   5.1.5  Zooplankton
   (Developmental)

   Zooplankton are most effectively
   sampled using net hauls with 118-|_im
   mesh sizes.  Because zooplankton are
   known to exhibit diel periodicity in
   their locations in the water column,
   sampling times should reflect this
   temporal variability; i.e., sampling
should, in general, be conducted at
night.  Also, consideration should be
given to the use of vertical or oblique
tows. In any instance, gear size, mesh
size, rate of retrieval on the haul back,
vertical or oblique tow, time of day or
night and tide cycle are factors which
must be kept constant if zooplankton
surveys are to be included in
biocriteria development.

Meaningful bulk community
measurements do not exist for
zooplankton; therefore, if zooplankton
are to be sampled, they should be
identified and enumerated.  It may be
difficult to  locate or develop the
taxonomic expertise necessary to
identify zooplankton to species,
especially given the large number of
planktonic  larvae. Zooplankton are
considered to be in a developmental
status with respect to their use as an
estuarine and coastal marine
bioassessment assemblage.
Zooplankton populations experience
year-round seasonal fluctuations in
abundance as a result of variable
larval recruitment into the population,
variable food sources, and physical
processes which may move larvae and
adults  into and out of the estuary (Day
et al. 1989). The pattern of seasonal
abundance differs with changes in
latitude. Zooplankton in higher
latitudes have one or more mid-
summer peaks and very low numbers
during the winter.

Abundances in temperate estuaries
are much more variable and may
experience spring peaks and minima
during the summer and winter
months. Tropical estuaries do not
experience the low in population
during the winter.

Some long-term monitoring projects
have identified community measures
that indicate changes in
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   environmental conditions over time
   (e.g., nutrient loads or toxicants), as
   well as particular zooplankton taxa
   whose densities affect larval fish
   survival (Buchanan 1991).
   Zooplankton community
   characteristics that are under
   investigation for application as
   bioindicators include:

   >   Diversity, measured through
       standard indexes such as
       Shannon-Wiener, to evaluate the
       taxonomic complexity of the
       assemblage;

   *•   Ratios of specific taxonomic
       groups within the assemblage to
       gauge community balance and
       identify possible impairment;

   *•   Presence of Hypotrichs (a ciliate of
       the order Hypotrichida);

   *•   Total biomass to assess
       assemblage production;

   *•   Relative abundance of pollution
       tolerant and sensitive species to
       identify and evaluate impairments
       to the assemblage;

   >   Unnatural variability in
       abundance can be used to identify
       the presence of short-term
       pollution or climate events;

   *•   Size structure can be used to
       evaluate the growth of cohorts in
       the assemblage, which can
       provide information on possible
       short- and long-term system
       perturbations.

   5.1.6  Epibenthos (Developmental)

   The epibenthos assemblage is also
   considered to be in a developmental
   stage for use in estuarine and coastal
   marine bioassessment. Taxa within
the epibenthic community appear to
be persistent and sensitive to
environmental stress.  They are
characterized by physiological
mechanisms that allow them to
tolerate the varying salinity, DO, and
temperature conditions encountered
in estuaries and coastal marine waters,
or reproductive cycles that allow them
to avoid high-stress periods. Some
epibenthos and facultative infauna
can relocate to avoid areas of
environmental stress.

Epibenthos can be sampled using a
Renfro beam trawl, otter trawl, or
epidbenthic sled.  Camera tows or
remotely operated vehicles with
camera or video capabilities may also
allow enumeration of epibenthos,
although collection of organisms
would not be possible and
quantitative assessments difficult.
Subsampling might involve a process
similar to that suggested by Plafkin et
al. (1989); a box with a numbered grid
system into which collected
epibenthos are evenly distributed
could be used to randomly select an
appropriate number of organisms for
subsequent sorting.

Some of the advantages to using
epibenthos for estuarine and coastal
marine bioassessment are:

>  This assemblage is very sensitive
   to anthropogenic sources of stress,
   and it can be used in both a
   nearfield and farfield context with
   equal facility;

Sampling can be conducted in shallow
waters using a dip net and in deep
waters with a trawl;
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   *•   The total number of common
       species will be limited by the fact
       that the deep water sampling gear
       is restricted to fairly level bottoms;

   *•   Subsampling can be employed to
       reduce labor costs and increase
       co st-ef f ectiveness;

   *•   Field and lab work, and data
       analyses can be done quickly with
       trained personnel;

   *•   Samples can be sorted
       qualitatively, and a nonparametric
       analysis can be applied to provide
       a quick screening method.
                           *•   Seagrasses and macroalgae can
                               hinder or increase the time
                               necessary for field sorting;

                           *•   The seasonality of epifauna needs
                               to be factored into the sampling
                               design.

                           The developmental method described
                           in Chapter 13 appears promising for
                           detecting impairment. If successfully
                           adapted to regions outside Florida,
                           North Carolina, and Puget Sound
                           where it is being tested, it may
                           become a standard estuarine
                           bioassessment method in the future.
                           A proposed sampling protocol is
                           summarized in Table 5-10.
    Table 5-10.
Sampling summary for epibenthos.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Soft sediments (sleds and trawls); shallow,
Renfro Beam Trawl (Farrell 1993a,b), smal
net
vegetated (dip net)
otter trawl; epibenthic sled; dip
Preferred: mid-summer
Alternative: growing season, average of 10 samples.
Ca. 4-m tow length in estuaries; 0.1 - 0.5 nm tow lengths (DGPS) in
coastal waters and Puget Sound.
Taxonomic ID preferably to species.
   The disadvantages of this assessment
   methodology are:

   *•   The stress index is developed
       solely for anoxia; it might not
       allow assessment of other
       stressors;

   *•   Stress values may not be available
       for many species, or may be
       difficult to determine;

   *•   Sleds and trawls are restricted to
       level bottoms; and cannot be used
       for sampling hard bottoms, or rock
       rubble;
                           5.1.7  Paleoenvironmental Systems
                                  (developmental)

                           Diatom and foraminifera species have
                           narrow optima and tolerances for
                           many environmental variables, which
                           make them useful in quantifying
                           environmental characteristics to a
                           high degree of certainty. They
                           immigrate and replicate rapidly,
                           which makes them quick to respond
                           to environmental change (Dixit et al.
                           1992).  Changes in assemblages also
                           correspond closely to shifts in other
                           biotic communities sampled in
                           estuaries such as aquatic macrophytes,
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                                              Sampling Program Issues

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   zooplankton, and fish. They have also
   been used alone as environmental
   indicators of eutrophication, metal
   contamination, salinification, thermal
   effluents, and land use changes.
   Furthermore, since diatoms and
   foraminifera are abundant in almost
   every marine ecosystem, a relatively
   small sample is sufficient for analysis.
   This allows for many samples to be
   easily collected, analyzed, and
   archived (Dixitet al. 1992).

   The general lack of time-series data
   has prompted attempts to
   demonstrate marine eutrophication
   from present-day observations using
   the benthic community and chemical
   criteria (Dale et al. 1999). Benthic
   foraminifera have been proven useful
   as indicators of oxygen concentration
   in bottom sediments (Alve 1991).
   Dinoflagellate cysts are also
   increasingly useful as indicators of
   short-term environmental change
   caused by climate and human
   pollution (Dale et al. 1999). The cysts
   are recovered by pollen identification
   techniques; they are acid-resistant and
   therefore not subject to dissolution
   problems sometimes affecting diatoms
   and foraminifera (Dale et al. 1999).
   Measurements of biogenic silica in
   sediments  are most often used as an
   index of diatom production (Stoermer
   et al. 1990, Conley et al. 1993, Cooper
   1995).  Isolation of BSi from Si in
   mineral phase is based upon the fact
   that the silica of diatoms is only
   weakly crystalline and dissolves
   readily in a weak base. Potential
   indicators and a proposed sampling
   summary are shown in Tables 5-11
   and 5-12.

   The total number of cores taken in a
   particular estuary is dependent upon
   the hydrological complexity of the
   estuary.  Generally, one to three cores,
   but some times up to ten are required
from each estuary or tributary being
assessed.  However, once a
paleoecological record is established,
there is no need to repeat the
sampling.

Although the number of cores is
small, each core requires substantial
effort to analyze: sectioning,
radioisotope dating, chemical
analysis, pollen analysis for further
dating, and diatom or foraminifera
analysis. Current estimates for
paleological analysis is about $100 per
section (not per core), depending on
the number and intensity of analysis
done on each section and the
experience of the lab performing the
analysis. The complexity of estuaries
requires some background
information about the area in which
sampling is occurring.  This
information should assist in decision
making on the location and number of
cores to be retrieved.

The study of paleoenvironmental
systems requires a corer that will
retrieve an intact core, with minimal
edge disturbance (Table 5-4). K-B,
Phleger, and Piston corers have all
been used successfully  for these
analyses (see Section 5.1.1). Small
surface area is not an issue; a single
core will suffice.

5.2    Sampling Design Issues

Consideration of sampling design is
critical in developing a new
monitoring program for estuarine
bioassessment and biocriteria.
Sampling design includes defining the
questions to be addressed by the data,
defining the units that will be
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     Table 5-11.	Potential paleoecological indicators
Indicator
Taxa richness (diatom,
foraminifera,
dinoflagellate cysts )
Biogenic silica
Total organic carbon,
Total N, Total S
Ammonia/Elphidium
ratio (foraminifera)
Centric/pennate ratio
(diatoms)
% Cyclotella
sedimentation rate
Dinoflagellate cysts
% Fursenkoina
% Trochammina
Response to Impairment
reduced
increase with nutrient
enrichment
increase with enrichment
increase with hypoxia
increase with nutrient
enrichment
increase with nutrient
enrichment
increase with watershed
erosion
increase with cultural
eutrophication
increases with hypoxia
increases with hypoxia
Reference
Cooper and Brush 1991
Turner and Rabalais 1994
Turner and Rabalais 1994
Sen Gupta etal. 1996
Cooper and Brush 1991
Cooper and Brush 1991
Brush 1989
Dale etal. 1999
Alve 1991
Patterson 1990
     Table 5-12.	Sampling summary for paleoenvironmental systems
Habitat
Sampling gear
Index period
Sampling
Analysis
Diatoms
Foraminifera
Dinoflagellate
Cysts
Age of sections
up to 150 years
Older than 150
years
Stable depositionalzone, biogeochemical conditions for preservation
Bottom corer
None
Tiers 1-2: none
Tier 3: background information specific to the estuary being sampled will
determine the number of cores necessary.
Cores sectioned at regular intervals depending on deposition rate and
resolution desired.
Species composition and enumeration of at least 300 organisms in each
section. Digestion/clarification methods depend on assemblage.
210Pb determination based on radioisotope assay with alpha
spectroscopy.
Palynological (pollen) analysis correlated with known historical changes
in terrestrial vegetation (land use), and 14C analysis (>1000 yr).
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Sampling Program Issues

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   sampled, and developing a sampling
   design that is cost-effective for
   answering the defined questions.

   5.2.1  Statement of the Problem

   The first task in developing a
   sampling and assessment program is
   to determine, and be able to state in
   simple fashion, the principal questions
   that the sampling program will
   answer.  Questions may or may not be
   framed as hypotheses to  test,
   depending on program objectives. For
   example, suppose that a sampling
   program objective is to establish
   reference conditions for biological
   criteria for estuaries in a  given region.
   Typically, the initial  objectives of a
   survey designed to develop criteria
   are to identify and characterize classes
   of reference sites in estuaries. Initial
   questions may then include:

   *•   Should minimally disturbed sites
       be divided into two or more
       classes that differ in biological
       characteristics and dynamics?;

   *•   What are the physical, chemical,
       and relevant biotic characteristics
       of each of the estuary site classes?

   After the monitoring and assessment
   program has developed biological
   criteria, new questions need to be
   developed that encompass
   assessments of individual sites,
   estuaries, or estuaries of  an entire
   region or state. Specific questions
   may include:

   *•   Is site abc similar to reference sites
       of its class (unimpaired), or is it
       different from reference sites (is it
       altered or impaired)?;

   >   Overall, what is the status of
       estuarine waters in the region?
       What percentage of estuarine
   waters is similar to reference
   conditions? What percentage is
   impaired?;

*•  Has estuary abc changed over a
   certain period? Has it improved
   or deteriorated?;

>  Overall, have estuarine waters in
   the region improved or
   deteriorated over a certain period?
   Have individual estuaries
   improved? Are more waters
   similar to reference conditions
   now than some time ago?

Finally, resource managers often wish
to determine the relationships among
variables, that is, to develop
predictive, empirical (statistical)
models that can be used to design
management responses to perceived
problems. Examples of specific
questions include:

*•  Can trophic state of an estuary be
   predicted by areal nitrogen
   loading rate?;

*•  Can biota of an estuary be
   predicted by watershed land use?

Monitoring and assessment data, and
derived models, may also be used to
help determine causal relationships
between stressors and responses of
systems. Inferring cause requires
manipulative experiments, or
inference from multiple lines of
evidence (Suter 1993). Since surveys
and monitoring programs preclude
experimental investigations, inference
of causal relations  is beyond the scope
of this document. Often, there is
enough experimental evidence
available from other studies so that
additional causal experiments are not
necessary and would be superfluous
(e.g., current knowledge of nutrients
and trophic state generally makes it
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   unnecessary to "prove"
   experimentally which nutrients are
   limiting). The development of
   predictive models usually does not
   require formal hypothesis testing.

   It is also necessary to specify the units
   for which results will be reported.
   Usually, these units are the population
   (e.g., all estuarine waters), but often
   subpopulations (e.g., embayments or
   tributaries of a given estuary) and
   even individual locations (e.g., sites of
   special interest) can be used. In order
   to help develop the sampling plan, it
   is useful to create hypothetical
   statements of results in the way that
   they will be reported, for example:

   *•   Status of a place: Baltimore harbor is
       degraded;

   *•   Status of a region: 20% of the area
       ofPuget Soundhas elevated trophic
       state, above reference  expectations; or
       20% of estuaries in Oregon have
       elevated trophic state;

   >   Trends at a place: Benthic species
       richness in Baltimore harbor has
       increased by 20% since 1980;

   >   Trends of a region:  Average estuary
       trophic state in New Jersey has
       increased by 20% since 1980; or
       Average benthic index values in 20%
       of estuaries of the west coast have
       increased by 15% or more since 1980;

   *•   Relationships among variables:
       50% increase ofN loading above
       natural background is associated with
       decline in taxa richness of benthic
       macroinvertebrates, below reference
       expectations; or Estuaries receiving
       runoff from large urban areas have
       50% greater probability of elevated
       trophic state above reference than
       estuaries not receiving such runoff.
5.2.2  Definition of the Assessment
       Unit

Defining the resource and assessment
unit of the resource begins the process
of developing biological criteria. An
"assessment unit" is a whole estuary
or part of an estuary, that will be
assessed as meeting criteria, being
impaired, etc.  Clearly, a single square
meter where a grab sample is taken is
not large enough to be an assessment
unit. An assessment unit should
consist of a definable segment, basin,
or entire estuary. For example, a large
complex estuary such as Puget Sound
could be divided into its component
inlet bays, canals, and passes.  Many
of the larger components could in turn
be divided into segments.

Segmentation could be determined by
some combination of mean salinity,
water residence time, dominant
substrate, or mean depth. For
example, since estuarine fauna are
determined  by salinity, segmentation
often corresponds to salinity zone
(tidal fresh,  oligohaline, mesohaline,
polyhaline,  and marine). Small
estuaries, such as salt ponds in New
England, could be single assessment
units.

An assessment unit is the smallest
spatial subdivision of an estuary that
will be assessed; i.e., given a rating of
good or poor.  An assessment may be
based on one or more sample units
within an assessment unit. A sample
unit (or sample site) is a site where an
observation is made.

5.2.3  Specifying the  Population
       and  Sample Unit

Sampling is statistically expressed as a
sample from a population of objects.
Thompson (1992) suggested in some
cases, the population is finite,
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                    Sampling Program Issues

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   countable, and easy to specify, (e.g.,
   all persons in a city, where each
   person is a single member of the
   population). In estuaries, the
   population is often more difficult to
   specify and may be infinite, (e.g., the
   sediment of San Francisco Bay, where
   any location in the Bay defines a
   potential member of the population).
   Sampling units may be natural units
   (entire estuaries, cobbles on a beach),
   or they may be arbitrary (plot,
   quadrat, sampling gear area or
   volume) (Pielou 1977). Finite
   populations may be sampled with
   corresponding natural sample units,
   but often the sample unit (say, an
   estuary) is too large to measure in its
   entirety, and it must be characterized
   with one or more second stage
   samples of the sampling gear (bottles,
   benthic grabs, quadrats, etc.).

   The objective of sampling is to best
   characterize individual sample units
   in order to estimate some attributes
   (e.g., nutrient concentrations, DO)  and
   their statistical parameters (e.g., mean,
   median, variance, percentiles) of a
   population of sample units.  The
   objective of the analysis is to be able to
   say something (estimate) about the
   population. Examples of sample units
   include:

   *•   A point in an estuary (may be
       characterized by single or multiple
       sample device deployments). The
       population would then be all
       points in the estuary, an infinite
       population. This is the most
       common sample unit applied to
       estuarine assessments;

   *•   A constant area, (e.g., square
       meter, hectare). The population
       would be an artificial one
       consisting of all square meters of
       estuarine surface area in an
       estuary, a state or a region;
>  An estuary or a definable portion
   of the estuary as a single sample
   unit. Whole estuaries as sample
   units would only be used in very
   broad-scale regional assessments,
   as was done by EMAP-NC, for
   example, for small estuaries as a
   population (e.g., Strobel et al.
   1995).

5.2.4  Sources of Variability

Variability of measurements has many
possible sources, and the intent of
many sampling designs is to minimize
the variability due to uncontrolled or
random effects, and conversely to be
able to characterize the variability
caused by experimental or class
effects. For example, we may stratify
estuarine waters by salinity and
bottom substrate type (rocky, sandy,
muddy). Typically, we stratify so that
observations (sample units) from the
same stratum will be more similar to
each other than to sample units in
other strata.

Environmental measures vary across
different scales of space and time, and
sampling design must consider the
scales of variation. When sampling
estuaries, measurements (say, benthic
assemblages) are taken at single
points in space and time (1 point
along a transect in mid-summer).  If
the same measurement is made at a
different place (littoral zone),
embayment, or time (winter), the
measured values will likely be
different.  A third component of
variability is the ability to accurately
measure the quantity interested in,
which can be affected by sampling
gear, instrumentation, errors in proper
adherence to field and laboratory
protocols, and the choice of methods
used in making determinations.
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   The basic rule of efficient sampling
   and measurement is to sample so as to
   minimize measurement errors; to
   maximize the components of
   variability that have influence on the
   central questions and reporting units;
   and to control other sources of
   variability that are not of interest, that
   is, to minimize their effects on the
   observations.  Many locations are
   sampled in order to examine and
   characterize the variability due to
   different locations (the sampling unit).
   Each site is sampled in the same way,
   in the same place, and in the same
   time frame to minimize confounding
   variability.

   In statistical terminology, there is a
   distinction between sampling error
   and measurement error that has little
   to do with actual errors in
   measurement. Sampling error is the
   error attributable to selecting a certain
   sample unit (e.g., an estuary or a
   location within an estuary) that may
   not be representative of the
   population of sample units. Statistical
   measurement error is the ability of the
   investigator to accurately characterize
   the sampling unit.  Thus,
   measurement error includes
   components of natural spatial and
   temporal variability within the  sample
   unit as well as actual errors of
   omission or commission by the
   investigator. Measurement error is
   minimized with methodological
   standardization:  selection of cost-
   effective, low variability sampling
   methods, proper training of
   personnel, and quality assurance
   procedures to minimize
   methodological errors. In analytical
   laboratory procedures, measurement
   error is estimated by duplicate
   determinations on some subset of
   samples (but not necessarily all).
   Similarly, in field investigations, some
   subset of sample units should be
measured more than once to estimate
measurement error.

If the variance of individual
measurements (measurement error) is
unacceptably large; i.e., as large or
larger than variance expected among
sample units, then it is often necessary
to alter the sampling protocol, usually
by increasing sampling effort in some
way, to further reduce the
measurement error. Measurement
error can be reduced by multiple
observations at each sample unit, (e.g.,
multiple dredge casts at each
sampling event, multiple observations
in time during a growing season or
index period, depth-integrated
samples, or spatially integrated
samples.

A less costly alternative to multiple
measures in space is to make spatially
composite determinations.  In nutrient
or chlorophyll determinations, a water
column pumped sample, where the
pump hose is lowered through the
water column, is an example of a
spatially composite determination.
Spatial integration of an observation
and compositing the material into a
single sample is almost always more
cost-effective than retaining separate,
multiple observations.  This is
especially so for relatively costly
laboratory analyses such as organic
contaminants and benthic
macroinvertebrates. Many estuarine
programs have adopted sampling
protocols consisting of multiple grabs
at a site that are then composited into
a single bucket for laboratory
determinations (e.g., EMAP Near
Coastal: 3 composited Van Veen grabs
at each site; Holland 1990).

Statistical power is the ability of a
given hypothesis test to detect an
effect that actually exists, and must be
considered when designing a
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   sampling program (e.g., Peterman
   1990, Fairweather 1991). The power of
   a test (1-P) is defined as the
   probability of correctly rejecting the
   null hypothesis (H0) when H0 is false;
   i.e. the probability of correctly finding
   a difference [impairment] when one
   exists.  For a fixed confidence level
   (e.g., 90%), power can be increased by
   increasing the sample size or the
   number of replicates.  To evaluate
   power and determine sampling effort,
   an ecologically meaningful amount of
   change in a variable must be set.  See
   Chapter 12 for a discussion of
   statistical power, and examples.

   Optimizing sampling design requires
   consideration of tradeoffs among the
   measures used, the effect size that is
   considered meaningful, desired
   power, desired confidence, and
   resources available for the sampling
   program. Every study requires some
   level of repeated measurement of
   sampling units to estimate precision
   and measurement error. Repeated
   measurement at 10% or more of sites
   is common among many monitoring
   programs.

   5.2.5  Alternative Sampling
          Designs

   Sampling design is the selection of a
   part of a population to observe the
   attributes of interest, in order to
   estimate the values of those attributes
   for the whole population.  Classical
   sampling design makes assumptions
   about the variables of interest, in
   particular, it assumes that the values
   are fixed (but unknown) for each
   member of the population, until that
   member is observed (Thompson 1992).
   This assumption is perfectly
   reasonable for some variables, say,
   length, weight, and sex of members of
   an animal population, but it seems
   less reasonable for more dynamic
variables such as nutrient
concentrations, loadings, or
chlorophyll concentrations of
estuaries.  Designs that assume that
the observed variables are themselves
random variables are model-based
designs, where prior knowledge or
assumptions (a model)  are used to
select sample units.

  Probability-based designs (random
             sampling)

The most basic probability-based
design is simple random sampling,
where all possible sample units in the
population have the same probability
of being selected, that is, all possible
combinations of n sample units have
equal probability  of selection from
among the N units in the population.
If the population N is finite and not
excessively large, a list  can be made of
the N units, and a sample of n units is
randomly selected from the list. This
is termed list frame sampling.  If the
population is very large or infinite
(such as locations in an estuary), one
can select a set of n random (x,y)
coordinates for the sample.

All sample combinations are equally
likely in simple random sampling,
thus there is no assurance that the
sample actually selected will be
representative of the population.
Other unbiased sampling designs that
attempt to acquire a more
representative sample include
stratified, systematic, multistage, and
adaptive designs  (Figure 5-2). In
stratified sampling, the population is
subdivided or partitioned into strata,
and each stratum is sampled
separately. Partitioning is typically
done so as to make each stratum more
homogeneous than the  overall
population. Systematic sampling is
the systematic selection of every kth
unit of the population from one or
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                   5-27

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                         Sampling Methods

     Simple Random:  Samples are independently located
                     at random
     Systematic:      Samples are located at regular
                     intervals
     Stratified:        The study area is divided into
                     nonoverlapping strata and samples
                     are obtained from each
     Multistage:       Large primary units are selected
                     which are then subsampled
                      Figure 5-2	
                      Description of
                      various sampling
                      methods.
                      Adapted from
                      USEPA1992.
   more randomly selected starting units,
   and ensures that samples are not
   clumped in one region of the sample
   space. Multistage sampling requires
   selection of a sample of large primary
   units, such as fields, hydrologic units,
   rectangles, or hexagons, and then
   selection of secondary sample units
   such as plots or estuaries within each
   primary unit in the first stage sample.

   Estimation of statistical parameters
   requires weighting of the data with
   inclusion probabilities (the probability
   that a given unit of the population
   will be in the sample) specified in the
   sampling design.  In simple random
   sampling, inclusion probabilities are
   by definition equal, and no corrections
   are necessary.  Stratified sampling
   requires weighting by the inclusion
   probabilities of each stratum.
   Unbiased estimators have been
   developed for specific sampling
   designs, and can be found in sampling
   textbooks, such as Thompson (1992).
        Model-based designs

Use of probability-based sampling
designs may miss relationships
among variables (models), especially
if there is a regression-type
relationship between an explanatory
and a response variable. As an
example, estimation of benthic
response to discharge or outfalls
requires a range of sites from those
directly adjacent to the outfalls to
those distant from, and presumably
unaffected by, the outfalls (e.g.
Warwick and Clarke 1991). A simple
random sample of estuarine sites is
not likely to capture the entire range,
because there would be a large cluster
of far sites, with few at high ends of
the gradient. A simple random
sample may therefore be highly
inefficient with respect to models or
specific hypotheses.

In model-based designs, sites are
selected based on prior knowledge of
auxiliary variables, such as estimated
loading, depth, salinity, substrate
5-28
                    Sampling Program Issues

-------
   type, etc.  These designs preclude an
   unbiased  estimate of the state of the
   estuaries, unless the model can be
   demonstrated to be robust and
   predictive, in which case the
   population value is predicted from the
   model and from prior knowledge of
   the auxiliary (predictive) variables.
   Selection  of unimpacted reference
   sites is an example of a model-based
   design which cannot later be used for
   unbiased  estimation of the biological
   status of estuaries.  Ideally, it may be
   possible to specify a design that
   allows unbiased estimation of both
   population and model, with an
   appropriately stratified design.
   Statisticians should be consulted in
   developing the sample design for a
   biological criteria and monitoring
   program.

             Selecting a Design

   The selection of a station array for
   bioassessment will  depend on the
   nature of  the study and/or the desire
   to delineate the areal extent of
   impairment. A randomized station
   selection is most appropriate for
   environmental status and trends
   surveys such as conducted by EMAP.
   However, for specific management
   decision-making, pre-selected stations
   placed on a gradient such as distance
   from of a  discharge (sometimes
   termed "nearfield/farfield") maybe
   more appropriate.  This method is a
   form of model-based design, and
   more accurately identifies suspected
   sources of impairment, assesses
   impacts and monitors recovery.

   The number of stations to be
   incorporated in a study design is most
   heavily influenced by the available
   resources. A minimum of three
   control or reference sites is desired to
   provide some indication of
   background variability. The number
of test sites may vary from one to
several depending on the purpose of
the study. The distance between
stations could be decreased; i.e.,
number of stations increased to
partially account for the inefficiency of
some sampling gear or, conversely,
the distance increased; i.e., number of
stations decreased once the data have
been evaluated.

            Index Period

Most monitoring programs do not
have the resources to characterize
variability or to assess for all seasons.
Sampling can be restricted to an index
period when metrics are expected to
show the greatest response to
pollution stress and when within-
season variability is small (Holland
1990). A decision must be made
between selecting a sampling period
that is representative of the biological
community, or one that reflects the
worst-case conditions for pollution
stress. From the traditional
perspective of evaluating pollution
impacts in fresh water streams,
summer-time low flow conditions are
often chosen to assess effects from
point source discharges.  These flow
conditions represent minimal effluent
dilution in combination with the
natural stressors of low water velocity
and high temperature in those
constrained environments.  In
contrast, the effects of nonpoint source
pollution on the benthic community
are often evaluated following periods
of high flow since nonpoint source
effects on aquatic communities are
largely driven by runoff in the
watershed.  Estuaries and coastal
waters accumulate materials from
both nonpoint and point sources in a
much more dynamic way and thereby
confound the assessment so useful for
streams.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                   5-29

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   In bioassessment strategies involving
   infrequent sampling, the biologically-
   optimal period for sampling becomes
   a major consideration. Periods of
   instability in community structure,
   including recruitment of young,
   natural harsh environmental
   conditions, changes in food source,
   and migration of certain target
   populations are all considerations in
   conducting these biosurveys.  The
   biologically-optimal period, usually
   mid-summer and sometimes mid-
   winter, avoids all of these elements
   and focuses on the time  when
   communities are most stable.  The
   resource manager or biologist will
   have to choose between these
   conditions, or select to cover both,
   depending on the needs of the study.

   5.2.6  Optimizing Sampling

   Ferraro et al. (1994,1989) present a
   method for quantitatively evaluating
   the optimum macrobenthic sampling
   protocol, accounting for sampling unit
   area, sieve mesh size, and number of
   replicates (n).  Their approach allows
   managers responsible for designing
   and implementing estuarine and
   coastal marine bioassessment
   programs to answer fundamental
   questions:

   *•   How large should the sampling
       unit be?;

   *•   What sieve mesh size should be
       used?;

   >   How many replicate samples
       should be taken?

   The procedure calculates the "power-
   cost efficiency" (PCE), which
   incorporates both the number of
   samples (n), the  cost (field collection
   effort and lab effort combined) and
   the expected statistical power for each
alternative sampling scheme.  See
Chapter 12 for a more detailed
discussion of statistical power. The
various sampling schemes consist of
different combinations of sampling
gear, gear area, sieve mesh size, and
number of replicates. The method
allows determining the optimum
among a set of sampling schemes for
detecting differences in reference vs.
impaired stations when the statistical
model is a t-distribution for
comparing two means. The optimum
scheme can be defined as the least
costly one capable of reliably (e.g., a =
0.5,1-P = 0.95) detecting a desired
difference in the means of a metric
between two stations. The approach
can be applied to each metric in a test
set of metrics and the results
aggregated to determine the optimum
protocol.

There are four primary steps in
assessing the PCE of a suite of
alternative sampling schemes:

1.  For each scheme, collect replicate
    samples at paired reference and
    impaired stations. The observed
    difference in metric values
    between the stations is
    operationally assumed to be the
    magnitude of the difference
    desired to be detected.
    Alternatively, a percentage of the
    median (e.g., 20%) for a given
    metric calculated across reference
    stations could be set  as the
    magnitude of the difference to be
    detected. In either case, this
    difference, divided by the
    standard deviation, is the "effect
    size" (ES) of interest.

2.  Assess the "cost" (q), in time  or
    money, of each sampling scheme i
    at each station. The cost can
    include labor hours for sampling,
5-30
                   Sampling Program Issues

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       sorting, taxonomic identification,
       and recording results.

   3.  Conduct statistical power analysis
       to determine the minimum
       number of replicate samples (r\)
       needed to detect the ES with an
       acceptable probability of Type I (
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 Chapter 6
 Water Column & Bottom
 Characteristics
   Tiers 1-3 contain active survey and site
   sampling. Procedures for attaining
   water column and bottom characteristics
   are generally the same for each tier. The
   sampling however, occurs more often
   over the year. Differences are noted
   where applicable.  Table 6-1 compares
   the level of effort for each tier.
   However, agencies will decide which
   components of each tier will be
   incorporated into their specific
   programs, then they will select the level
   of effort appropriate for their program.

   6.1    Salinity,  Temperature,
          Dissolved Oxygen, & pH

   Salinity, conductivity, temperature,
   dissolved oxygen, and pH should be
   measured at each sampling station using
   a CTD meter equipped with DO and pH
   probes.  Measurements should be made
   at 1-m intervals through the water
   column. In shallow, inshore waters,
   measurements should be taken at the
   top, middle, and bottom thirds of the
   depth. For Tier 3, in some southern
   waters that undergo significant diel
   temperature changes, it may be
   desirable to obtain 24-hour temperature
   profiles using recording equipment.

   6.2   Secchi Depth

   Secchi depth is usually measured at the
   deepest part of the transect or grid.
   Where the area is classified by depth,
   Secchi measurements should be made at
   each station. Readings are obtained
   with a 40-cm plastic or metal Secchi disk
   that is either white or is divided into
   black and white quadrants on a
   nonstretchable line that is calibrated in
decimeters. The disk is lowered into the
water until it disappears from view and
the depth is recorded.  The disk is then
slowly raised to the point where it
reappears, with the depth being
recorded again. The mean of these two
measurement is the Secchi depth.
Observations are made from the shady
side of the boat, without sunglasses, and
as close as possible to the water to
reduce glare.

6.3   Depth

Depth should be measured at each
station using a calibrated depth sounder.
Depth can be read off a meter block
when sediment sampling by zeroing the
block when the sampler is at the water
surface.  In shallow, inshore waters, a
long stick or weighted  line calibrated in
decimeters may be used.

6.4   Sediment Grain Size

6.4.1  Estimation of "percent fines"
      (Tierl)

Analysis of sediment grain size for Tier
1 assessments can be limited to
determining the "percent fines" at each
station.  A rapid wet sieving technique
used in Puget Sound (Eaton 1997) can
serve as the basis for this
characterization. Materials needed for
the procedure include:

*•  standard testing sieve No. 230, 63-
   50-ml plastic beaker (filled to the
   brim with sediments is about 79-ml)
   100-ml plastic graduated cylinder
   water bottle(s) with small outlets
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     6-1

-------
Table 6-1. Wate
for a
Characteristic
-&•
:a
•a
GO
Temperature
Dissolved Oxygen
I
Q.
£
& >;
°3
^
o 3
£b
jz
&
Q
t/3
1
1
_u
J5
O f/3
>3
3 S
< GO
Water Column
Contaminants
- Column & Bottom Characteristics. "Addition" refers to added detail or intensities
parameter initiated in an earlier tier.
Tier
1
2
3
1
2
3
addition
1
2
addition
3
addition
1
2
3
1
2
3
1
2
3
2
3
3
3
Collection Method
-measure at each sampling station, CTD
meter
-continuous or 1-2-m intervals through
water column
-shallow/inshore
-top, middle, bottom thirds of depth
-measure at each station, CTD meter
-1-2-m intervals through water column
-shallow/inshore
-top, middle, bottom thirds of depth
-some southern waters undergo significant
diel changes, it may be desirable to obtain
24-hour temperature profiles
-measure at each station, CTD meter w/
DO probe
-continuous or 1-2-m intervals through
water column
-shallow/inshore
-top, middle, bottom thirds of depth
-measure early in morning at each station
at minimum
-collect along a depth profile from surface
to within 1-m of bottom at 1-2-m intervals
-in cases of hypoxic site: recording DO
meters may be deployed (EMAP -
Louisianian Province, Engle et al 1994)
-CTD w/ pH probe
-1-2-m intervals
-top, middle, bottom thirds of depth
-deepest part of transect/grid
-if area classified by depth, measure at
each station
-See Section 6.2 for complete procedure
-each station w/ calibrated depth sounder
-read off meter block when sediment
sampling
-shallow/inshore waters: long stick or
weighted line calibrated in decimals
-collected w/ bottle samplers or pump
-see Section 6.8 for complete procedure
-each station during index period, and any
other sampling visits through year
-once accurate AVS exists for each
station, analytes only performed once per
year (during index period)
Choose One:
-USEPA's list of Priority Pollutants,
Hazardous Substance, or Target
Compound/Analytes
-same compounds targeted in EMAP-E
(Table 3-1)
-develop own list (see Section 6.10 for
more detail)
Indicates
Distribution of flora and
fauna
Rate of chemical
reactions and biological
processes
Possible reason for
modified behavior,
reduced abundance &
productivity, adverse
reproductive effects,
and mortality
Resource agency may
determine need for
more detailed
information to diagnose
sources & causes of
impairment
Chemical condition,
pollutant input, high
concentrations of
phytoplankton
Reduction of light
penetration, deposition
of mud and silt,
possible contaminated
sediment "hot spots"
Depth at sampling
station, possible
dredging or sediment
loading
Nutrient loading
Bottom characteristics,
detailed purposes in
Section 3.5.4
Trace distribution of
contaminants from a
source or to ID
potential sources
6-2
Water Column & Bottom Characteristics

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     Table 6-1 (Cont'd). Water Column & Bottom Characteristics. "Addition" refers to added detail or
     intensities for a parameter initiated in an earliertier.
Characteristic
Sediment Grain Size
o
'2
^
ss
$ -g
O ra
H 0
RPD Layer Depth
JH
^
ll
II
H GO
Sediment Contaminants
Tier
1
2
3
2
3
addition
1
1
1
2
3
Collection Method
-determine "percent fines" at each station,
see Section 6.4.1 for complete procedure
-see Section 6.4.2 for complete procedure
-see Section 6.9 for complete procedure
-measure additional sediment analytes
-vertical bisection, distance from sediment
surface to a noticeable change in color
from brownish (oxidizing conditions) to
gray (reducing conditions)
-deepest section along transect/grid
-see Standard Methods (APHA 1992) for
sampling & analytical methods
-conducted at outset of survey
*like TOC, if toxicity tests are initially
negative, no need to repeat annually
unless biological data from infauna
indicate otherwise
Choose from three approaches:
-based on EPA's contaminant lists
-NOAA NS&T suite of contaminants (used
by EMAP)
-targeted list
*see Section 6.12 for complete procedure
and rationale
Indicates
Spatial and temporal
changes of the benthic
habitat, evaluate
condition of benthic
habitats
Determine extent or
recovery from
environmental
perturbations
Assist in providing early
warnings of potential
impacts to the
estuarine ecosystem
Provide information
regarding sediment
organic content
(possibly influenced by
sewage outfalls)
Examine potential
influences of outfalls,
ID potential
contaminant "hot spots"
Note presence/absence
of benthos; learn about
life history, taxa
abundance, & major
taxa biomass
distribution; more large,
deep dwelling
species="healthy"
system
Sediment and carbon
content
Positive=severe
impacts influence
spatial sampling
design, causal
investigations
Negative=subsequently
collected biological info.
essential to ID other,
possibly more subtle
stresses
Provide insight on
limiting factors in
benthic community

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
6-3

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    >   small stainless or plastic spatula
    *•   stainless butter knife
    >   hose with nozzle (if running water is
       available).

    Detailed directions for performing this
    wet-sieving technique are as follows:

    Fill a 50-ml plastic beaker to the brim
    with the sediment to be analyzed. The
    capacity of the completely filled beaker
    can be measured using water and the
    100-ml graduated cylinder,  dean away
    any sediment that might adhere to the
    outside of the beaker. Carefully wash
    this sediment through a 63-|_im standard
    sieve (USA standard testing sieve No.
    230) with stainless steel mesh.  The sieve
    itself is about 9" in diameter with a 2"
    stainless lip. Be careful not to overflow
    the sieve with rinsing water. It may be
    easier to wash half of the sediment
    through at a time.  If running water is
    available, use a small brass  nozzle on the
    end of the hose with very low water
    pressure when washing the sediment,
    otherwise the sediment will need to be
    washed using the water bottle. If there
    are occasional large worm tubes or
    shells, these are discarded and replaced
    with an approximately equal volume of
    sediment. The sediment remaining on
    the sieve is the coarse-grained fraction.
    This is washed to one side of the sieve,
    and then carefully placed into the plastic
    100-ml graduated cylinder with a
    stainless steel butter knife, and finally
    with the small stainless spatula. The
    water bottle is then used to  wash any
    remaining sediment directly into the
    graduated cylinder, and to wash down
    the sides of the cylinder.  Let the
    sediment-water mixture settle in the
    100-ml graduated cylinder for
    approximately 5 minutes until the
    supernatant water is clear.  This may
    take longer for very fine-grained
    sediments. Note the volume of the
    coarse-grained fraction which remains
    after sieving. This can be divided by the
original volume to obtain the percentage
of the coarse fraction. The standard
usage, however, is for percent fine-
grained fraction or "percent fines".
This is calculated by subtracting the
volume of sediment remaining in the
cylinder (ml of coarse-grained fraction)
from the original volume, and dividing
this number (ml of fine-grained) by the
original volume to obtain the percent
fines.

6.4.2  Sediment Grain Size (Tiers  2
       and 3)

Additional grain size data for Tier 2 and
Tier 3 assessments should include
determination of the size distribution
using a standard graded sieve series.
This analysis should be performed for a
sediment sample collected at each
sampling station.  In the early years of
the assessment program, this analysis
should be performed for each  sampling
period.  When an accurate sediment
characterization exists for the area of
each station, sediment grain size
analysis could be performed only
annually or biennially (on samples
collected in the index period), unless the
agency believed that sediment
conditions at a site may have changed.
This could occur, for example, following
a major storm. Buller and McManus
(1979) provide a review of the
methodological and statistical analysis
of sediment samples. If seasonal
variations in grain size are exhibited, it
is recommended that direct comparisons
between samples collected during
different seasons be avoided.  Studies
investigating interannual variation in
the percent composition of grain sizes
should be conducted during the same
season (preferably the same month) each
year. Furthermore, it is recommended
that grain size be sampled when
contaminant concentrations are expected
to be at their highest level to evaluate
worst-case scenarios.
6-4
           Water Column & Bottom Characteristics

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   6.5   RPD Layer Depth

   The concept behind using the depth
   distribution of benthic
   macroinvertebrates is based on the
   premise that "healthy" benthic
   communities in fine sediments in meso-
   and polyhaline waters consist of
   relatively large, deep dwelling species;
   while impaired areas will have fewer of
   these organisms. The depth distribution
   of benthic infauna in sediments
   integrates functional parameters such as
   life history, taxa abundance, and major
   taxa biomass distribution.

   6.6   Total Volatile Solids

   Total volatile solids (TVS) is the Tier 1
   indicator for sediment carbon content.
   TVS should be determined for the
   deepest station along each transect or
   grid, based on the assumption that
   deeper stations will represent sinks for
   organic carbon in the sediments.
   Sampling and analytical methods are
   discussed in Standard Methods  (APHA
   1992).

   6.7   Sediment Contaminant
          Toxicity

   Sediment toxicity testing is a diagnostic
   indicator for Tier 3. When results are
   positive for a station, severe impacts at a
   known locality will influence spatial
   sampling design and causal
   investigations. Where toxicity test
   results are negative throughout  the set
   of stations  sampled, subsequently
   collected biological information is
   essential to identify other, possibly more
   subtle stresses on the system.

   6.7.1  10-day Static Sediment
          Toxicity Test with Marine and
          Estuarine Amphipods

   ASTM (1998a) and USEPA (1994b)
   developed procedures that measure
short term adverse effects of potentially
contaminated sediment, or of a test
material experimentally added to
sediment, on marine or estuarine
infaunal amphipods during static 10-day
exposures for the following species:
Rhepoxynius abronius, Eohaustorius
estuaris, Ampelisca abdita, Grandidierella
japonica, and Leptocheirus plumulosus.
The amphipod Corophium insidiosum has
also been used in standard testing (Reish
and Lemay 1988). Solid phase tests use
overlying water in aerated 1-L glass test
chambers. Mortality and sublethal
effects such  as growth, emergence of
adults, and inability to bury in clean
sediment are determined after exposure
of a specific number of amphipods
(usually 20)  to the test sediment.
Response of the amphipods to the test
sediment is  compared with the response
observed in control or reference
sediment. The negative control
sediment is  used to provide a measure
of the acceptability of the test by
providing evidence of the health and
relative quality of the test organisms, the
suitability of the overlying water, and
test conditions and handling procedures
(ASTM 1998b, USEPA 1994b). The
reference sediment, which is similar in
physical characteristics to the test
sediments and typically collected from a
similar location, is used  as the basis for
interpreting data obtained from the test
sediments (ASTM 1998b).

The toxicity of field-collected sediments
may be assessed by either (a) testing the
whole sediment and testing for
significant differences in responses
between reference or control and test
sediment exposed animals or (b) testing
dilutions of  a test sediment with clean
sediment to obtain an LC50 or other
effect concentration, for survival,
reburial success, or  growth (ASTM
1998b, Nelson et al. 1993, Swartz et al.
1995).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      6-5

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   6.7.2  10-day Static Sediment
          Toxicity Test with Marine and
          Estuarine Polychaetous
          Annelids

   Marine or estuarine infaunal
   polychaetes are used in whole sediment
   tests during 10-day or 20- to 28-day
   exposures to determine adverse effects
   of potentially contaminated sediment, or
   of a test material added experimentally
   to sediment. Polychaete species include
   Neanthes virens for the 10-day and
   Neanthes arenaceodentata for the 10-day
   and 20- to 28-day tests  (ASTM 1998c).
   Other polychaete species that have been
   used in similar sediment  testing include
   Capitella  capitata, Ophrotrocha diadema,
   and Ctenodrilus serratus (Reish and
   Lemay 1988). The 10-day test measures
   effects of contaminated sediment on
   polychaete survival.  The 20- to 28-day
   test determines effects of contaminated
   sediment on polychaete survival and
   growth.  If smaller species are used, such
   as N.  arenaceodentata, five worms are
   placed in a 1-L glass test chamber with a
   minimum sediment depth of 2- to 3-cm
   and the overlying water is aerated.
   Either young adults or recently emerged
   juvenile  (2- to 3-weeks  post-emergence)
   worms are used in the 10-day test; only
   recently  emerged (2- to 3-weeks)
   juveniles are used in the 20- to 28-day
   test. Survival of worms exposed to the
   test sediment is compared with the
   survival in a negative control or
   reference sediment in either test. If
   larger species are used, such as N. virens,
   ten worms are placed in a glass aquaria
   (4- to 37-L) with a minimum sediment
   depth of 10-cm and the overlying water
   is aerated.

   The percent survival of polychaetes
   exposed to field-collected sediment is
   compared to those exposed to a negative
   control or reference sediment in 10-day
   tests. Survival and body weight of
   surviving animals is compared to those
exposed to negative control or reference
sediment in 20- to 28-day tests. The
toxicity of field sediments may also be
assessed by testing dilutions of highly
toxic test sediments with clean
sediments to obtain either an LC50 or
other effect concentration of the
material.

6.7.3  Static Acute Toxicity Tests
       with Echinoid Embryos

Echinoderm embryos and larval form
sea urchins (Strongylocentrotus
purpuratus and Strongylocentrotus
droebachiensis)  and sand dollars (Arbacia
punctulata, Lytechinus pictus, and
Dendraster excentricus) have been used in
marine sediment interstitial (pore) water
tests (ASTM 1998a). Interstitial water
from marine sediments is isolated using
either in-situ peepers (Sarda and Burton
1995, Brumbaugh et al. 1994, Bufflap and
Allen 1995), suction in the field (Watson
and Prickers 1990), laboratory
centrifugation (Ankley et al. 1991,
Burgess et al. 1993, Kemble et al. 1994,
ASTM 1998b), or sediment squeezing
(Long et al. 1990). Embryos are obtained
by inducing adults to spawn, using
either physical (e.g., electric stimuli)  or
chemical (injection of potassium
chloride) means, and then combining
gametes.

Embryos are exposed to the test pore
water and controls (culture water) for
48- to 96-hours, depending on the
species and test temperature. The test
measures the proportion of embryos or
larvae that develop into normal pluteus
larvae. Pore waters can be tested
"whole"; i.e., undiluted, and organism
responses expressed in terms of a
significant difference between controls
and test waters. Alternatively, pore
water samples can be diluted with
known, clean culture water and the
results expressed as an LC50 or other
6-6
           Water Column & Bottom Characteristics

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   effect concentration with confidence
   limits.

   6.7.4  Toxicity Tests Using Marine
          Bivalves

   Juveniles of the marine bivalve species,
   Mulinia lateralis, have been used in
   whole sediment tests (Burgess and
   Morrison 1994). Juveniles are exposed
   for 7-days to determine adverse effects
   of potentially contaminated sediment, or
   of a test material added to sediment.
   Bivalve responses measured include
   survival and growth, (total organism
   dry weight). Ten juvenile bivalves (four
   weeks old) are placed into six replicate
   chambers per sediment or treatment.
   The sediment exposure chambers are
   prepared by placing approximately 1.0-
   cm deep sediment into 150-ml dishes,
   followed by the addition of 100-ml
   filtered 30-gkg"1 seawater. Upon
   initiation of the test a subsample of
   organisms are set aside for
   determination of initial juvenile weights.
   Bivalve survival in test chambers is
   compared to survival of bivalves in the
   negative control or reference sediment.
   Dry weight of the surviving organisms
   in test chambers is compared with dry
   weight of surviving organisms in the
   reference sediment, and  to the dry
   weight of the subsample set aside at the
   initiation of the test to determine
   growth.

   Similar to echinoderm testing
   summarized in Section 6.7.3, bivalve
   larvae have also been used in sediment
   pore water and sediment elutriate
   toxicity tests. Species used include
   Crassostrea gigas and Mytilus edulis
   (PSEP 1995).  Bivalve larvae are obtained
   from laboratory-cultured adult brood
   stock, which are induced to spawn.
   Developing embryos are exposed to the
   pore water or elutriate at 20°C for 48-60-
   hours using static-test conditions.  At
   test termination, subsamples of the
larvae are examined and the percentages
of mortality and abnormal survivors are
determined and analyzed.

6.8    Nutrients (Tiers 2&3)

Water column samples for nutrient
analysis can be collected using bottle
samplers such as Kemmerer, Van Dorn,
Niskin, or Nansen samplers. A pump
may be used as an alternative  sampling
device. In shallow water less than 2-m
depth, a mid-depth sample at  each
station should be obtained for nutrient
analysis.  In waters greater than 2-m
depth, samples should be collected at
each station at 1-m below the surface, 1-
m above the bottom, 1-m above the
pycnocline, 1-m below the pycnocline,
or at mid-depth.  Analytical methods for
NH4-N, NO3-N, NO2-N, Kjeldahl
nitrogen, total N, and total and reactive
P; i.e., ortho-P, are presented in APHA
(1992) and USEPA (1994c). These
nutrient analyses will help identify
eutrophication factors affecting
biocriteria development, as well as
supplement the USEPA's nutrient
criteria initiatives so that multiple
objectives can be accomplished at once.

6.9    Total Organic Carbon
       (Tiers 2&3)

In Tier 2, the primary purpose of
measuring  total organic carbon (TOC) is
to provide information regarding
sediment organic content, which might
be influenced by sewage outfalls
containing  high organic levels. As noted
in Chapter  3,  TOC in the sediment is an
important analyte for the purpose of
evaluating  the bioavailability  of organic
pollutants and metals  adsorbed by
sediments or  contained in sediment
porewater.  Data on sediment TOC
collected in this tier can be used to
examine potential influences of outfalls
in addition to potential sediment
contaminant "hot spots" that can be
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   assessed in Tier 3 with the measurement
   of additional sediment analytes.

   Standard methods for TOC analysis are
   presented in APHA (1992). In the early
   years of the assessment program, TOC
   analysis should be performed for each
   station in each sampling period. Once
   the resource agency is confident that an
   accurate characterization of sediment
   TOC exists for each station, the analysis
   could be performed only once every two
   or more years (on samples collected in
   the index period), unless stations that
   appear to be influenced by organic input
   (e.g., sewage outfalls) are identified. In
   this case, TOC analysis should continue
   to be performed for each sampling
   period for these stations.

   6.10  Water Column
          Contaminants (Tier 3)

   Water column contaminants such as
   organic compounds (e.g., herbicides,
   pesticides, hydrocarbons) and metals
   may be important indicators of sources
   and causes of impairment to biological
   assemblages in estuaries and coastal
   marine waters. Decisions on which
   chemicals to include in Tier 3
   assessments can be difficult.  Three
   approaches to selecting contaminants
   might be useful. One approach would
   be to analyze for all chemicals listed on
   USEPA's Priority Pollutant, Hazardous
   Substance, or Target Compound/
   Analyte Lists. A second approach
   would be to analyze for  the same
   compounds targeted in the EMAP-
   Estuaries program (refer to Table 3-1).  A
   third approach would be to develop a
   targeted list. In this latter approach, the
   historical information from Tier 0 and
   subsequent follow-up inquiries of land
   use in the suspect area could point to
   common pesticides, herbicides, or
   industrial products or byproducts that
   could form the basis of a select list of
   contaminants to analyze. Sources for
this information also include NPDES
permit records and discharger toxicity
test results. In any case, three replicate
water samples should be collected at
each sampling station within an
appropriate index period and on at least
three other visits during the year to
capture temporal variations in
contaminant concentrations. Historic
water contaminant data, plus data
collected in this tier, can be used by the
state to determine a more limited  list of
analytes for subsequent years of the
assessment and biocriteria program.

The same type of sampling bottle used
to collect water samples for nutrient
analysis may be used for contaminant
samples. USEPA (1992) and APHA
(1992) contain detailed information  on
analytical methods.

6.11   Acid Volatile Sulfides
       (Tier 3)

Details of the purposes for measuring
acid volatile sulfides (AVS) present in
bottom sediments are provided in
Section 3.5.4. Given the diagnostic
intent of a Tier 3 assessment, it is
important to include this analyte in
determinations of bottom characteristics
only if metals are suspected as a cause of
biological degradation.  Allen et al.
(1993) discuss analytical methods for
this parameter. AVS measurements
should be made on sediment samples
collected at each station during an
appropriate index period and any other
sampling visits made throughout the
year.  Once the resource agency is
confident that an accurate
characterization of sediment AVS exists
for each station, the analytes should be
performed only once per year (on
samples collected in the index period).
6-8
           Water Column & Bottom Characteristics

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   6.12  Sediment Contaminants

   As with water column contaminants,
   three approaches to selecting analytes
   could be used: (1) a full scan based on
   USEPA's contaminant lists; (2) the
   NOAA National Status and Trends suite
   of contaminants used by the EMAP
   program (refer to Table 3-1); or (3) a
   targeted list.

   In this latter approach, the historical
   information from Tier 0 and subsequent
   follow-up inquiries of land use in the
   suspect area could  point to common
   pesticides, herbicides, or industrial
   products and byproducts that could
   form the basis of a  select list of
   contaminants to analyze. In addition to
   sampling organisms for contaminants,
   sediment samples should be collected
   from the device used for sampling
   benthic infauna. The surface sediment
   (top 2-cm) should be removed from
   replicate grab samples and composited.
   During collection, care should be taken
   to avoid collecting  material from the
   edge of grabs and to use only samples
   that have undisturbed sediment
   surfaces. The composite sample should
   be homogenized, and a subsample taken
   for measurement of contaminant
   concentrations. Analytical methods are
   discussed in APHA (1992)  and USEPA
   (1992).
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 Chapter 7
 Tier 0: Desktop Screening
   The breakdown of screening and
   sampling in the following chapters that
   focus on the Tiered Approach are just
   one way of designing a state-wide
   monitoring program. Agency analysis
   of resources and program objectives
   should direct the custom development
   of any monitoring program.

   The desktop screening assessment (or
   Tier 0) consists of compiling
   documented information for the estuary
   or coastal marine areas of concern
   through a literature search and sending
   survey questionnaires to local experts.
   No field observations are made at this
   assessment level.  Desktop screening
   should precede any of the three
   subsequent tiers.  Its fundamental
   purpose is to  support the planning for
   monitoring and more detailed
   assessments.  It incorporates time and
   cost efficiencies, allowing evaluation of a
  large number of sites, and identifying
potentially affected areas for further
investigation in higher tiers. Table 7-1
gives an overview of the components,
sources, and uses of a desktop screening
assessment.

7.1    Area and
       Geomorphometric
       Classification

The size and classification of the estuary
indicates the potential for the
environment to respond to various types
of impacts. In addition, the
classification refers to the type of
circulation (e.g., gravitational, tidal,
wind-induced) that dominates the
estuary. Well-recognized estuary types
include:

*•  Coastal plain estuary;
*•  Lagoon;
     Table 7-1. Tier 0 Desktop screening for estuaries and coastal marine waters.
Component
Estuary area
Geomorphic
classification
Habitat type
Biological
assemblages
Watershed
land use
Population
density
NPDES
discharges
Water column
& bottom
characteristics
Information Source
USGS quad maps, CIS
USGS quad maps, CIS
NOAA bathymetry charts; historic surveys by federal,
state agencies, and universities
Historic data from federal, state agencies, and
universities. NMFS for marine mammal data
USGS land use maps; state and county planning
agencies; local zoning agencies; USDA CSREES
US census data
State water quality agency and regional USEPA offices,
PCS database
Historic data from federal, state agencies, and
universities; STORET, NODC databases
Use
-support planning
for monitoring
and more
detailed
assessments
-incorporates
time & cost
efficiencies
-allows evaluation
of a large number
of sites
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   *•   Fjord;
   *•   Tectonically-caused estuary.

   7.2   Habitat Type

   Partitioning of the resource by habitat
   type (open water, soft bottom substrates,
   hard bottom substrates, aquatic
   macrophytes, high/low energy beaches,
   sandflat, mudflat, emergent marsh) will
   usually be required and the extent of the
   partitioning will depend on the size of
   the system and environmental gradients.
   Initial subdivisions should be based on
   salinity gradients, water depth, and
   sediment type, particularly in coastal
   marine areas.

   7.3   Watershed Land  Use

   The pollutant and sediment load of fresh
   water inflow into the estuary will
   inevitably have some form of impact on
   habitat and biota and this land use
   information may subsequently help
   identify causes of impairment.
   Nonpoint source pollution has been
   shown to be a major contributor to the
   degradation of our aquatic resources.
   Land use information will help
   determine the type of contaminants that
   are being flushed into the estuary. For
   example, storm water runoff from
   urbanized and industrial areas may
   contain various types of toxins. Runoff
   from agricultural areas could be
   expected to contain fertilizers,
   pesticides, and sediment. Fertilizers
   have the potential to accelerate
   eutrophication by excessive nutrient
   enrichment, while pesticides may have
   at least short-term toxic effects.

   7.4   Population Density

   This indicates the potential for the
   whole array of impacts to the estuary
   and coastal marine waters from
   concentrated human activity. The more
   populated the area surrounding the
estuary or coastal region, the higher the
potential for human-induced impacts.

7.5    NPDES Discharges

Industrial and municipal point source
dischargers must file monthly discharge
monitoring reports (DMRs) that provide
the effluent concentrations for the
contaminants in the effluent which they
are required to monitor. This data is
accessible via USEPA's PCS. Knowing
the number, type and location of point
source dischargers could provide the
background information necessary for
characterizing the contaminants
entering the estuary and the regions
within the estuary or coastline that
would be most affected by the
discharge.

7.6    Biological Assemblages

Existing information on any of the target
biological assemblages (benthos, fish,
macrophytes, photoplankton,
zooplankton, epibenthos,
paleoenvironmental systems) can be
valuable for:

*•  Identifying potential reference sites,
   and potentially impaired areas;

*•  Determining presence/absence of
   major taxonomic groups and
   indicator organisms;

*•  Evaluating spatial and temporal
   variability of the biological
   assemblages.

This information can be used to help
determine target assemblages for
higher-level tiers and the sampling
design and methods that might be
appropriate.
7-2
                     Tier 0: Desktop Screening

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   7.7   Water Column and
          Bottom Characteristics

   Existing data on water column and
   bottom characteristics will be crucial to
   support the identification of appropriate
   sampling strata based on salinity, grain
   size, or depth.  Further, this information
   can help states identify potentially
   impaired areas; i.e., areas receiving high
   nutrient loadings or containing
   contaminated sediments.
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 Chapter 8
 Tierl
   The Tier 1 assessment is just one way of
   completing a minimal biological
   assessment or simple field screening.
   Specific agency needs will ultimately
   decide the components of any state
   monitoring program.  The time period of
   sampling should be selected to allow
   states to answer the question: "What
   information do we want to obtain from a
   single site visit?" For example, it could
   be conducted from a single field visit
   during late summer when low dissolved
   oxygen concentration, due to
   stratification and eutrophication, is most
   likely to occur or during some other
   chosen index period, depending on the
   monitoring purpose. It builds on the
   information compiled in the desktop
   screening assessment  and consists of
   sampling one or more biological
   assemblages and collecting data on
   water column and bottom characteristics
   (Chapters 5 and 6).  Tier 1 might roughly
   identify whether an estuary or coastal
   marine waters are nutrient enriched and
   can distinguish among broad probable
   causes if the nutrient state is different
   from expectations (reference conditions).
   This assessment tier enables:

   *•   coarse identification of nutrient state
       based on chlorophyll a
       concentration, and identification of
       point and nonpoint probable cause if
       stations are carefully selected and
       spaced;

   *•   detection of emergent wetlands and
       shore zone fish habitat loss from
       shore zone survey and macrophyte
       assessment;

   *•   detection of loss of submerged
       aquatic macrophytes;
*•  detection of potential impairment of
   benthic macroinvertebrate and fish
   assemblages;

*•  detection of oxygen stress.

The Tier 1 assessment will not allow
separation of multiple probable causes.
It can establish the initial habitat
classification scheme and identify
several possible causes of impairment,
including point sources, nearfield
nonpoint sources (in the immediate
shore zone of the coast or estuary), and
farfield nonpoint sources (from land use
in the drainage). It cannot, however,
identify the most probable from among
several possible causes.  It should also
help establish the most likely sites to use
in developing the reference condition
and test their candidacy for this
preliminary phase of biocriteria
development. Table 8-1 gives an
overview  of the components, data
collection methods, and indicators for
Tier 1.

8.1    Benthos

Sampling and analysis of benthic
infaunal macroinvertebrates  in Tier 1 is
intended to provide a rapidly obtained
snapshot of the condition of the benthic
assemblage. It is recognized that this
assemblage, and the methods presented,
will be most appropriate for sites with
soft sediments (e.g., mud, silt, sand).
For sites with hard bottom substrates,
other biological assemblages (e.g., fish,
macrophytes, phytoplankton) could be
selected to provide information on the
biological condition of the target waters.

The sampling strategy presented  here
consists of collecting replicate grab
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 Table 8-1. Tier 1 Assessment. Requires single field visit in spring or summer index period.
Component
Data Collection
Indicator of
Uses
Biological Assemblages
Benthic Infauna
-C

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   *•   Species Life Histories The presence of
       relatively large and long-lived
       species, especially those found
       deeper in the sediments, indicate
       higher quality habitat than does the
       presence of small and short-lived
       taxa;

   *•   Major Taxa Abundance High
       abundance of only a few taxa,
       usually pollution tolerant ones,
       indicates a degraded environment;

   *•   Major Taxa Biomass Distribution
       Larger organisms, hence a higher
       biomass per individual, are more
       prevalent in better quality habitats;

   *•   Vertical Distribution of Biomass
       Organisms living below 5-cm in soft
       substrates indicate a relatively high
       quality habitat.

   8.1.1  Sampling Procedure

   The primary objective of benthic
   infaunal macroinvertebrate sampling in
   Tier 1 is to determine whether there are
   any large organisms below the RPD
   depth. The recommended sediment
   sampling procedure involves collecting
   three replicate grab samples at each
   station using a Smith-Mclntyre or Young
   grab. The selection of sampling gear
   should be made to maximize
   compatibility with historic data.  For
   example, the state of Texas uses an
   Ekman grab, and has an approximately
   25-year data record using this gear type.
   The sediment sample is vertically
   bisected using a sheet metal partition.
   The RPD layer depth is noted and
   measured, if present, as the distance
   from the sediment surface to a
   noticeable change in color from
   brownish (oxidizing conditions) to gray
   (reducing conditions). The sediment
   above the RPD depth is removed and
   wet-sieved separately; the remaining
   portion of the sample is also wet-sieved.
A sieve with mesh size appropriate for
the region should be used. The presence
or absence of benthic inf auna in either
subsample is noted. If present, the
classes and families should be noted and
recorded.

8.1.2   Index Period

Benthic infaunal macroinvertebrates are
sampled once during an appropriate
index period, the timing of which is
driven by the goals of the Tier 1
assessment and regional considerations.

8.1.3   Analysis

Note the presence/ absence of an RPD
layer and any infauna (or evidence of
inf auna) below 5-cm depth in the
sample. If present, identify benthic
infauna to class and family and record
abundance.

8.2    Fish

A Tier 1 assessment of the fish
assemblage is intended to provide a
rapid evaluation of its presence and
overall composition. Fish sampling in
Tier 1 can include shallow-water,
pelagic, and demersal fish communities
(Carmichael et al. 1992, Eaton and
Dinnel 1994, Guillen 1995a).

8.2.1   Sampling Procedure

Various nets can be used to sample
littoral and sublittoral areas.  It is
recommended that trap nets  (gill or fyke
nets) be set and fished twice  a day for 2-
to 5-days.  Due to the risk of  boating
mishaps and vandalism, it is
recommended that investigators stay
with the nets while they are being
fished. Fish sampling methods are
detailed in Klemm et al.  (1992).

*•  Gillnets are set in littoral  areas at
   right angles to the shore or to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      8-3

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       longshore fish movement. Gillnets
       usually extend into sublittoral areas.
       Smaller mesh size (0.5") is used in
       shallow areas and up to 2 to 2.5"
       mesh is used further away from
       shore. To reduce size selectivity, an
       experimental gillnet consisting of
       panels of five different mesh sizes is
       commonly used;

    >   Trawl nets and sonar can be used to
       sample pelagic and demersal areas.
       The length of the towline (warp)
       should be at least six times the depth
       of water and a trawl speed of about
       2-knots over a 0.5-nautical mile
       distance is appropriate for coastal
       marine waters. These values of
       warp length and trawling distance
       can be reduced in estuaries.  A 20-ft
       trawl (16-ft effective trawl mouth) is
       appropriate in marine waters, but an
       8- or 10-ft trawl is easier to tow in
       restricted waters.

    8.2.2  Sample Processing

    Sampling duration and area or distance
    sampled (from DGPS) are recorded in
    order to determine sampling effort.
    Species are identified and enumerated.
    Fish should be carefully removed from
    the net to avoid undue handling and
    damage. The catch should be sorted by
    species, and length measurements made
    of each individual. This measurement is
    usually total length, but fork length or
    standard length can also be used. At the
    time of measurement, any deformities,
    ulcerations, bleeding, fin rot, bulging
    eyes or other disease indicators  should
    be noted and those fish saved for
    histopathology. It is important to
    distinguish net damage from pre-
    existing conditions, if possible.  Wet
    weights can be taken by species by
    weighing the fish either individually
    using a platform scale or collectively
    from tared hanging scales, depending
    on the number of fish caught. As a
small matter of convenience, both scales
should weigh in metric units.  Those
animals not saved for further

examination should be promptly
returned to the water.

The investigator should consult with
State and University fish pathologists of
the region for those most appropriate
sample preparation and preservation
techniques. Usually iced or frozen
specimens are inappropriate and in
some cases formaldehyde or other tissue
preservatives must be carefully used if
meaningful samples are to be presented.
Generally, small fish can be tagged and
placed whole in 10% formalin. Larger
fish will require dissection in the field
and the tissue samples tagged and
preserved in the same manner.
Protocols for preservation and dissection
should be obtained from the
laboratory/fish pathologist that will
receive the samples.

When collected, reference specimens of
each species from each site are
preserved in 10% formalin in a labeled
jar and retained by the state
ichthyological museum or other
designated repository to constitute a
biological record.  This is especially
important for uncommon species, for
species requiring laboratory
identification, and for documenting new
distribution records. Later, all
specimens should be transferred from
formalin to 70% alcohol for long-term
storage.

8.3    Macrophytes

Areal coverage and distribution of
submerged aquatic macrophytes is
estimated from aerial photographs, if
available, and ground-truthed at the site.
The dominant taxa may be field-
identified from vegetation samples
collected in shallow waters. Detailed
8-4
                                    Tier 1

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   macrophyte monitoring and assessment
   procedures are included in USEPA
   (1992), Ferguson and Wood (1994), and
   Orth et al. (1993).

   8.4    Phytoplankton

   Phytoplankton standing stock is
   estimated by chlorophyll a
   measurements.  A sample is collected at
   each station at one-half the Secchi depth
   using a Kemmerer or Van Dorn sampler.
   Chlorophyll a is determined using a
   fluorometer or spectrophotometer as
   discussed in APHA (1992). The
   presence of any phytoplankton blooms
   observed during the cruise should be
   noted. Dominant phytoplankton species
   should be identified.
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 Chapter 9
 Tier 2
   Tier 2 assessment is considered a routine
   biological survey that incorporates two
   or more field visits per year to capture
   variations due to seasonal differences.
   Tier 2 comprises increased sampling
   effort and additional assemblages
   compared to Tier 1. It includes two or
   more biological assemblages (benthos,
   fish, macrophytes, phytoplankton, or
   epibenthos), in 2 or more visits per year,
   in addition to more detailed
   characterization of the water column
   and bottom (Chapter 5). State agencies
   can modify  this schedule to
   accommodate their program objectives.

   This level is sufficient for identification
   of appropriate habitat classes and
   determination of the reference condition
   for development of biological criteria.
   Data collected in Tier 2, which
   incorporates both Tier 1 and Tier 0,
   should permit the state to confidently
   develop biocriteria and apply them to
   identify problem areas.  This assessment
   level enables:

   *•   Establishment of the biocriteria
       "benchmarks" for decision-making
       about impaired areas; including
       identification of priorities;

   *•   Identification of trophic state based
       on chlorophyll a and water column
       nutrient measurements;

   *•   Detection of impairment of benthic
       macroinvertebrate, fish, or
       epibenthos assemblages, and
       evaluation of potential causes of the
       impairment;

   *•   Measurement of extent of
       macrophyte coverage;
*•  Identification of phytoplankton taxa
   responsible for blooms.

A Tier 2 assessment should allow
identification of multiple probable
causes of impairment, given an adequate
number and placement of sampling
stations.  This includes point sources,
and nearfield and farfield nonpoint
sources. Preliminary management  plans
in response to the biocriteria
information can be developed. Table 9-1
gives an overview of the components,
data collection, methods, and indicators
for Tier 2.

9.1    Benthos

Sampling and analysis of benthic
inf auna in Tier 2 is intended to provide a
level of assessment consistent with
routine benthic macroinvertebrate
surveys presently conducted by states in
estuaries and coastal marine waters. As
with Tier 1, this assemblage, and the
methods presented, will be most
appropriate for soft sediments. For sites
with hard bottom substrates, other
biological assemblages (e.g., fish,
macrophytes, phytoplankton) could be
selected to provide information on  the
biological condition of the target waters.

The sampling strategy for Tier 2 entails a
minimum of two field collection visits,
one of which should occur within the
chosen index period. Organisms are
identified to genus and species to
determine major taxa and the presence
of indicator organisms. Water column
and bottom characteristics are also
measured to evaluate the status of
physicochemical conditions.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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 Table 9-1. Tier 2 Assessment. Requires two or more field visits, one of which should occur within
 chosen index period. In addition to requirements from Tiers 0 & 1.
Component
Data Collection
Indicator of
Uses
Biological Assemblages
Benthic
Infauna
-C

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   or black (reducing conditions). The
   sample should be wet sieved through a
   sieve mesh size determined to be
   appropriate for the region (Section 6.3.2).
   For cost and effort savings, an
   appropriate diameter subcore (2.5- or 5-
   cm) can be taken from each of the four
   quadrants of the intact core.  These
   subcores should be compared to
   organism counts taken from full cores to
   establish the baseline relationship
   between the two. Organisms and
   sediment fractions should be placed in
   tagged and labeled sample jars with a
   10% solution of magnesium chloride or
   magnesium sulfate to narcotize the
   animals. After at least 30-minutes,
   concentrated formaldehyde with rose
   bengal dye can be added to the jars to
   make a 10% solution of formaldehyde
   by volume. The sediment/organism
   material should never exceed half the
   container volume to ensure adequate
   mixing and fixation of the sample. For
   preservation, the samples should be
   transferred to 70% ethanol (APHA
   1992).

   9.1.2  Index Period

   Benthic infaunal macroinvertebrates are
   sampled once during an appropriate
   index period, the timing of which is
   driven by the goals of the Tier 2
   assessment and regional considerations.
   At least one other sampling visit is made
   outside the index period to capture basic
   seasonal differences in the assemblages.
   The timing of this visit(s) will depend on
   the specific goals of the assessment.

   9.1.3  Analysis

   Organisms in each sample are identified
   to genus and species.  Metrics selected
   by the state can then be calculated to
   assess the condition of the assemblage.
   Metric values can then be used to help
   develop biocriteria against which the
condition of the macroinvertebrate
assemblage is evaluated.

9.2    Fish

Tier 2 assessment of the fish assemblage
is intended to provide data sufficient to
evaluate impairment and to develop
biocriteria.  Fish sampling in Tier 2 can
include shallow water, pelagic, and
demersal fish communities (Carmichael
et al. 1992, Eaton and Dinnell 1994,
Guillen 1994).

9.2.1   Sampling Procedure

See Section 8.2.1 for full procedure on
sampling fish.

9.2.2   Sample Processing

See Section 8.2.2 for full procedure on
sample processing.

9.2.3   Analysis

Based on the enumerated species list,
metrics selected by the state can be
calculated to evaluate potential
impairment to the fish assemblage and
to develop biocriteria for this
assemblage.

9.3    Macrophytes

Tier 2 assessment of macrophytes is
intended to provide sufficient data to
assess impairment to the macrophyte
assemblage as a significant habitat
variable and potential element of
biocriteria.  Because of its importance as
habitat for other assemblages,
procedures for Tier 2 assessment of
macrophytes are considerably more
involved than for Tier 1.

9.3.1   Sampling Procedure

The extent of coverage and distribution
of macrophytes should be determined
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   from aerial photographs.  Existing aerial
   photographs are inexpensive; however,
   they may not be sufficiently recent to
   depict present macrophyte distribution
   in the water body.  If new aerial
   photographs are determined to be
   needed, states should recognize that
   overflights can be expensive and
   complicated; often requiring assistance
   from firms specializing in aerial
   photography. Factors to consider when
   planning new overflights include: tidal
   stage; weather conditions; time of day;
   and water turbidity (USEPA 1992).
   Ferguson and Wood (1994) and Orth et
   al. (1993) describe details of planning
   aerial overflights, obtaining imagery,
   photointerpretation, and preparation of
   macrophyte distribution maps.

   A key aspect of interpreting aerial
   photographs is the performance of
   ground surveys that serve to confirm the
   existence of macrophyte beds identified
   in the photographs, as well as beds that
   may not be visible in the photos (Orth et
   al. 1993). Transects can be plotted across
   macrophyte beds in the various salinity
   zones within an estuary or within the
   sampling strata used for marine waters.
   At each station on the transect a 1-m2
   quadrat can be used for the purpose of
   measuring percent cover and collecting
   macrophyte samples for taxonomic
   identification and measurement of wet
   weight (USEPA 1992). Depth  at the
   channel-ward or seaward edge of
   macrophyte extent should be recorded.

   9.3.2  Index Period

   Aquatic macrophytes should be
   sampled once during an appropriate
   index period, preferably during the time
   of year when they would be expected to
   be most dense and extensive.  Other
   sampling periods should be selected
   based on the specific goals of the Tier 2
   assessment, perhaps to measure
   seasonal periods of stress or
diminishment of important nursery or
food areas.

9.3.3  Analysis

Percent cover and area may be derived
from analysis of aerial photographs.
The maximum depth of occurrence is a
good indicator of water quality.
Taxonomic identification from the field
trips will allow development of a species
list.

9.4    Phytoplankton

9.4.1  Sampling  Procedure

Phytoplankton standing stock is
estimated by chlorophyll a
measurements. One approach might be
three replicate samples collected at each
station at one-half the Secchi depth
using a Kemmerer or Van Dorn sampler.
Another approach would collect a
depth-integrated sample through the
entire photic portion of the water
column. Chlorophyll a is determined
using a fluorometer or
spectrophotometer as discussed in
APHA (1992). The presence of any
phytoplankton blooms should be noted.
In addition to chlorophyll a
measurements, samples from each
station should be preserved for
subsequent analysis to identify the
dominant taxa and those taxa that might
be responsible for observed blooms
(USEPA 1992).

9.4.2  Index Period

Phytoplankton populations can vary
rapidly over space in response to tides
and currents, and over time in response
to ambient temperature and nutrient
inputs. For Tier 2, phytoplankton
should be sampled at least once during
an index period (usually summer) and at
least once outside that index period.
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                                    Tier 2

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   9.4.3  Analysis

   Chlorophyll a measurements can be
   used to estimate phytoplankton
   standing stock. Assuming that
   chlorophyll a is about 1.5% of the ash-
   free dry weight of algae, algae biomass
   can be estimated by multiplying the
   chlorophyll a content by a factor of 67
   (APHA1992). This information can be
   used in concert with the identification of
   dominant taxa and "nuisance" taxa to
   assess the overall condition of the
   phytoplankton assemblage.

   9.5   Epibenthos
          (Developmental)

   Although its use as an indicator of
   estuarine and coastal marine biological
   condition is considered to be under
   development, epibenthos could be
   selected as one of the biological
   assemblages for a Tier 2 assessment and
   has potential as an element of biological
   criteria consistent with fish and benthic
   invertebrates.

   9.5.1  Sampling Procedure

   Farrell (1993a, b) describes the use of a
   beam trawl to collect epibenthos. A
   beam trawl is a conical-shaped net, open
   at the large end, which is towed over the
   substrate surface. The net is kept open
   by attaching each end of it to a rigid pole
   or beam. This beam replaces the doors
   of an otter trawl and forward movement
   of the boat is not required to  keep the
   net open. The net is constructed in two
   parts.  The body is nylon bolting cloth
   (50 openings/cm2), tapering to a
   plankton net fitted with a removable
   container.  An effective swath width of
   1.25-m has been tested in Florida waters
   (Farrell 1993a, b). In wadeable water, a
   D-frame net could be used to collect
   epibenthos, or the beam trawl could be
   pulled by hand. A relatively short tow
   length of the beam trawl (4-m,
effectively sampling 5-m2 of bottom) in
estuaries may be beneficial for reducing
the sample size and detrital bulk. If a D-
frame net is used, at least an equivalent
area should be sampled. In offshore
waters, it may be necessary to increase
the tow length due to reduced organism
densities. Small otter trawls or an
epibenthic sled sampler can also be
used.

9.5.2   Index Period

Epibenthos should be sampled once,
preferably during an appropriate index
period. For many temperate areas of the
country, this is probably mid-summer.
Other sampling periods should be
selected based on the specific goal of the
Tier 2 assessment.

9.5.3   Analysis

The samples should be identified to
genus and species. The Farrell Index
(described in Chapter 13 - Case Studies,
as modified to reflect tolerance values of
taxa in the area sampled) should be
calculated to provide an assessment of
the condition of the assemblage in
response to organic pollutants and
eutrophication. Other metrics could be
calculated based on the specific taxa
present.
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 Chapter 10
 TierS
   Tier 3 is the most rigorous of the
   assessment tiers. It includes more
   detailed assessment procedures that
   allow monitoring agencies to focus on
   specific water and sediment quality
   problems in estuarine or coastal marine
   waters. Tier 3 is intended to provide
   definitive information needed to act on
   biocriteria and to measure potential
   success or failure of the management
   effort.  It allows states to conduct a
   detailed diagnosis of the sources and
   causes of impairment to biological
   assemblages and the physicochemical
   environment and to monitor their
   response to subsequent mitigation
   actions. However, the Tier 3 approach
   can be customized to accommodate
   specific state program objectives. Table
   10-1 gives an overview of the
   components, data collection methods,
   and indicators for Tier 3.

   Tier 3 assessments include multiple
   sampling visits per year (four or more)
   that occur within each season including
   the index period. Data collected in Tier
   3, which includes information compiled
   in Tier 0  desktop screening and
   comprises the information collected  in
   Tiers 1 and 2, involves sampling and
   measurement of three or more biological
   assemblages (benthos, fish macrophytes,
   phytoplankton, zooplankton, or
   epibenthos), in addition to more detailed
   characterization of the water column
   and bottom. A Tier 3 assessment
   enables:

   *•   Identification of nutrient state based
       on chlorophyll a and water column
       nutrient measurements;
*•  Detection of impairment of benthos,
   fish, macrophytes, phytoplankton,
   zooplankton, epibenthos, or
   paleoenvironmental systems;

*•  Diagnosis of specific sources and
   causes of impairment;

*•  Measurement of extent of
   macrophyte coverage;

*•  Identification of phytoplankton taxa
   responsible for blooms;

>  Evaluation of seasonal dynamics of
   biological assemblages;

*•  Detailed monitoring of sites
   requiring management initiatives to
   meet the biocriteria;

*•  Inferences of past conditions as a
   site-specific reference.

10.1   Benthos

Sampling and analysis of benthic
infaunal macroinvertebrates in Tier 3 is
intended to provide a diagnostic level of
assessment. This assemblage, and the
methods presented, will be most
appropriate for soft sediment. For sites
with hard bottom substrates, other
biological assemblages (e.g., fish,
macrophytes, phytoplankton,
zooplankton) could be selected to
provide information on the biological
condition of the target waters.

The sampling strategy for Tier 3 entails a
minimum of four field collection visits
per year, one  of which should occur
within the chosen index period.  The
remaining visits should occur
throughout the year to allow evaluation
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     Table 10-1. Tier 3 Assessment.  Requires four or more field visits, one of which should occur within the
     chosen index period. In addition to requirements from Tiers 0-2.
Component
Data Collection
Indicator of
Uses
Biological Assemblages
o ro
il
,
.c
Q.
O
O
ro
2
Phytoplankton
Paleoenvironmental
Systems (developmental)
Epibenthos
(developmental)
Zooplankton
(developmental)
*determine biomass
"calculate multiple
metrics
*5 or more replicates
*histopathology on
representative
subsample of catch
*stem counts
*biomass
*record pathology
*full community
characterization to
species
*2 or 3 cores from
basin (one-time
sample)
See Tier 2
"identify to species

Fishing
pressure,
disease
Toxicity, habitat
impairment,
disease

Past conditions

Water quality
impairment, DO
stress
-Identification of nutrient state
based on chlorophyll a & water
column nutrient measurements
-Detection of impairment of
benthos, fish, macrophytes,
phytoplankton, Zooplankton,
epibenthos, or paleoenvironmental
systems
-Diagnosis of specific sources &
causes of impairment
-Measurement of extent of
macrophyte coverage
-Identification of phytoplankton
taxa responsible for blooms
-Evaluation of seasonal dynamics
of biological assemblages
-Detailed monitoring of sites
requiring management initiatives
to meet the biocriteria
-Integrate conditions over broad
spatial scales
Water Column Characteristics

"pesticides, herbicides
*metals
pesticides/
herbicides,
metals

Bottom Characteristics

*AVS
*sediment
contaminants
(organics, metals)


10-2
Tier 3

-------
   of seasonal differences in the benthic
   macroinvertebrate assemblages.
   Organisms are identified to genus and
   species. Water column and bottom
   characteristics are also measured to
   evaluate the status of physicochemical
   conditions.

   10.1.1 Sampling Procedure

   Primary objectives of Tier 3 benthic
   infaunal sampling are to evaluate
   potential impairment to this
   assemblage, to develop and refine
   biocriteria, to diagnose causes and
   sources of observed impairment, and
   to evaluate seasonal changes in the
   benthic infauna. This tier includes
   more frequent sampling (a minimum
   of four times per year) than either
   Tiers 1 or 2 to allow detailed
   discrimination of seasonality of
   benthic abundance. See Section 8.1.1
   for full detail on sampling procedures.

   10.1.2 Index Period

   Benthic infaunal macroinvertebrates
   are sampled once or twice during an
   appropriate index period, the timing
   of which is driven by the goals of the
   Tier 3 assessment and regional
   considerations. At least two or three
   other sampling visits are made
   throughout the remaining portion of
   the year to capture more detailed
   seasonal differences in benthos than
   would be possible  in a Tier 2
   assessment. Data collected in a
   previous Tier 2 assessment, or historic
   benthic infaunal macroinvertebrate
   data, can be used to determine the
   timing and frequency of non-index
   period sampling.

   10.1.3 Analysis

   Organisms in each sample are
   identified to genus and species. If
   desired, and resources are available,
ash-free dry weight, at least to the
family level, may be measured to
determine the viability of biomass-
based metrics to the overall
assessment. Other metrics should be
selected by the resource management
agency as appropriate based on
historic data, data collected and
metrics used in preceding tiers, and
regional considerations.

10.2  Fish

Tier 3 assessment of the fish
assemblage is intended to allow
evaluation of impairment,  to develop
and refine biocriteria, to diagnose
causes and sources of impairment,
and to evaluate seasonal differences in
the assemblage. Fish sampling in this
tier can include shallow-water,
pelagic, and demersal fish
communities (Carmichael et al. 1992,
Eaton and Dinnell 1994, GuiUen 1994).

10.2.1  Sampling Procedure

See Section 8.2.1 for full description of
fish sampling procedures.

10.2.2 Sample Processing

See Section 8.2.2 for full description of
fish sample processing.

10.2.3 Analysis

Based on the enumerated species list,
metrics selected by the state can be
calculated to evaluate potential
impairment to the fish assemblage, to
develop or refine biocriteria, to
examine seasonal dynamics of the
assemblage, or to diagnose sources
and causes of impairment.

10.3  Macrophytes

Tier 3 assessment of macrophytes is
intended to provide sufficient data to
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                                   10-3

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   assess impairment to the macrophyte
   assemblage, to develop or refine
   biocriteria, or to diagnose  sources and
   causes of impairment.

   10.3.1 Sampling Procedure

   See Section 8.3.1 for full description of
   macrophyte sampling procedures.

   10.3.2 Index Period

   See Section 8.3.2 for full description of
   the macrophyte index period.

   10.3.3 Analysis

   Percent cover and area may be
   derived from analysis of aerial
   photographs. Taxonomic
   identification from the field trips will
   allow development of a species list.
   Stem counts made within  quadrats
   along each sampling transect in
   addition to biomass determination
   will provide more detailed
   information on assemblage condition.
   Detailed pathology observations
   should be made;  they can  be used to
   evaluate potential causes of
   impairment.

   10.4  Phytoplankton

   10.4.1 Sampling Procedure

   See Section 9.4.1 for a full  description
   of the phytoplankton sampling
   procedure.

   10.4.2 Index Period

   Phytoplankton should be  sampled at
   least once during an appropriate
   index period and a minimum of three
   other times per year to capture
   seasonal changes in the composition
   and abundance of the assemblage.
   Following review of data collected
   from historical data or through any of
the assessment tiers described here,
the resource management agency may
determine that a higher frequency of
sampling is needed to characterize the
phytoplankton assemblage based on
its potential for rapid spatial and
temporal variation.

10.4.3 Analysis

See Section 9.4.3 for a full description
of phytoplankton analysis.

10.5  Epibenthos
       (Developmental)

As in Tier 2, even though epibenthos
is currently under development as a
biological indicator, it can still be
useful in the Tier 3 assessment.

10.5.1  Sampling Procedure

See Section 9.5.1 for a full description
of the epibenthos sampling procedure.

10.5.2 Index Period

See Section 9.5.2 for a full description
of the epibenthos index period.

10.5.3 Analysis

See Section 9.5.3 for a full description
of epibenthos analysis.

10.6  Zooplankton
       (Developmental)

Zooplankton are an important link
between phytoplankton in estuaries
and coastal marine waters and higher
consumers. States might choose to
include this developmental
assemblage as part of a Tier 3
assessment.
10-4
                                 Tier 3

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   10.6.1 Sampling Procedure

   Three replicate vertical tows using a
   118-|_im mesh net, 30-cm in diameter
   should be made at each sampling
   location. The tow should be vertically
   integrated; that is, starting from 0.5-m
   from the bottom to the surface, with a
   retrieval rate of 0.5- to 1-ms"1.
   Collected  organisms should be
   anesthetized with carbonated water
   and preserved in 4% formalin.  For
   long-term storage after fixing,
   specimens should be transferred to
   70% ethanol. APHA (1992)  describes
   procedures for concentrating the
   samples and preparing them for
   examination.

   10.6.2 Index Period

   Zooplankton should be sampled once
   during an appropriate index period
   and a minimum of three other times
   during the year to capture seasonal
   variation in taxonomic composition
   and abundance.

   10.6.3 Analysis

   Samples should be identified to the
   lowest practical taxonomic level,
   preferably genus and species.
   Subsampling may be required to
   achieve reasonable numbers of
   organisms for identification.

   10.7  Paleoenvironmental
          Systems
          (Developmental)

   Developmental assessment of
   paleoenvironmental systems is
   intended to  provide site-specific
   reference by showing past conditions.
   Several groups of organisms leave
   remains in the bottom sediments.
   Some of the remains are resistant to
   decay and become a permanent
   biological record of life in the estuary.
By comparing past biota with present-
day biota, past environmental
conditions can be inferred. Several
groups of organisms have been used:
diatoms, foraminifera, and
dinoflagellate cysts.  Of these, diatom
frustules and foraminifera have been
used most often, and most
successfully, to infer past conditions.
A sample of the top 1- to 2-cm of
sediment contains a representative
sample of diatoms from the most
recent 1- to 5-years.  If the sediments
remain undisturbed, then remains
preserved in the sediments are
integrators of estuarine history
(Charles et al. 1994, Dixit et al. 1992).
Because of the developmental nature
of this indicator, states or agencies
wishing to use paleoenvironmental
reconstruction should contact one of
the laboratories engaged in this
research for further information. The
methods described here are intended
to give a brief overview of the field,
but should not be used to plan a
monitoring program.

10.7.1 Sampling Procedure

Cores are generally taken with
standard gravity corers, such as the K-
B, Phleger, or Piston. The chosen
corer should retrieve a core deep
enough to sample sediments from the
earliest desired time period, with
minimal edge disturbance. Core
length thus depends on time period
and sedimentation rate. Core samples
are extruded from the corer and
subsectioned immediately after
collection.  Sections 1-cm thick are
removed from the core at intervals
according to the time resolution
desired. These sections are removed
from the core using an apparatus
described by Glew (1988) then are
bagged, labeled and identified using a
permanent ink pen.  The bags
prepared from a single core sample
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   are placed in a sealed container for
   storage and transport. Samples are
   kept at 4°C until shipment.

   10.7.2 Sample Processing

   Once in the laboratory, the sections
   are dried and weighed. Foraminifera
   and diatoms  are processed so as to
   digest organic matter and preserve
   carbonate (foraminifera) or silica
   (diatoms), following the standard
   methods of Krom and Berner (1983)
   andEMAP(USEPA1994e). An
   aliquot of frustules or tests is mounted
   for optical and/or scanning electron
   microscopy for identification.
   Dinoflagellate cysts are subjected to a
   standard pollen analysis involving the
   digestion of minerals in cold HC1,
   followed by warm HF (adapted from
   Barss and Williams 1973). They are
   processed on a 10 |_im sieve. Samples
   for counting  and identification are not
   random, but  systematic.

   Transects are taken on microscope
   slides, counting and  identifying all
   target taxa encountered. A count of
   300 or more is necessary for
   meaningful analysis of percentage
   data, but lower counts are still valid if
   results are reported on a concentration
   basis. In some depositional systems it
   is not feasible to count 300
   dinoflagellate cysts, but the data is
   still informative.

   Charcoal is seen in pollen analysis and
   dinoflagellate cyst preparations. The
   larger sieve size used for foraminifera
   would exclude  most charcoal
   particles, thus make  this material
   unsuitable for charcoal studies.

   10.7.3 Analysis

   Standard dating methods use either
   carbon-14, pollen, 137Cs, or 210Pb (Dixit
   1992, Cooper and Brush 1991, Dale et
al. 1999, Alve 1991). Additional time
points can be established from traces
of known historic events (charcoal
from large-scale fires, radioisotopes
from atmospheric testing and the
Chernobyl accident). Known
responses of indicator taxa or
biogeochemical indicators (e.g.,
biogenic silica) are used to infer past
environmental conditions of an
estuary. This allows for the
assessment of current environmental
conditions based on those of the past.

Quantitative paleoenvironmental
reconstruction in estuaries requires
the development of a data set that
associates current conditions with
current surficial diatom,
dinoflagellate, or foraminifera
assemblages. Present-day associations
are used to infer past conditions based
on fossil assemblages in deeper
sediment layers. Quantitative
prediction is usually done in two
steps: development of predictive
models (calibration or transfer
functions), followed by use of the
models to infer environmental
variables from fossil assemblages
(Charles and Smol 1994). Quantitative
reconstruction has not yet been widely
developed for estuaries.
10-6
                                  Tier 3

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 Chapter 11
 Index Development
   11.1  Overview

   Many methods have been developed to
   assess the condition of water resources
   from biological data, beginning with the
   saprobien system in the early 20th
   century to present-day  development of
   biological markers.  This chapter will
   discuss three methods for analyzing and
   assessing water body condition from
   assemblage and community-level
   biological information:

   1.  Multimetric index.

   This is the basis of many indexes used in
   fresh waters: the Index of Biotic
   Integrity (IBI; Karr et al. 1986), the
   Invertebrate Community Index (ICI;
   Ohio EPA 1987); the Rapid
   Bioassessment Protocols for Use in
   Wadeable Streams and Rivers:
   Periphyton, Benthic Macroinvertebrates,
   and Fish, Second Edition (RBP; Barbour
   et al. 1999); and state indexes developed
   from these (e.g., Southerland and
   Stribling 1995). More recently,
   multimetric IBI - type indexes have been
   developed for estuarine assemblages
   (e.g. Cape Cod fish, Deegan et al. 1997;
   Chesapeake Bay macroinvertebrates,
   Weisberg et al. 1997; Carolinian
   Province macroinvertebrates, Hyland et
   al. 1998). The Chesapeake Bay
   development (Weisberg et al. 1997) will
   be used to illustrate the method.

   2.  Discriminant model index.

   This is the basis of stream bioassessment
   in Maine (Davies et al. 1993), and of the
   estuarine invertebrate indexes
   developed by the EMAP-NC program in
the Virginian and Louisianan provinces
(Weisberg et al. 1993; Schimmel et al.
1994; Strobel et al. 1994; Summers et al.
1993,1994; Engle et al. 1994). The
EMAP-NC, Louisianian and Virginian
Province examples will be used to
illustrate the method.

3.  Index derived from multivariate
   ordination.

Smith et al. (2000) and Allen and Smith
(2000) have developed a pollution
tolerance index for near-coastal sites of
Southern California, using species
composition of benthic
macroinvertebrates and demersal fish.
Other approaches using ordination have
demonstrated differences in
composition between reference and
stressed sites (e.g., Warwick and Clarke
1991). The approach of Smith et al. uses
ordination of species composition to
develop a numeric index on a scale of 0-
100, that can be used directly for
biocriteria. The Smith et al. example
will be used to illustrate the method.

Many other methods are possible, as
well as permutations of the three
methods above, all of which are beyond
the scope of this document.  These three
were selected because:

*•  They use community and
   assemblage data;

>  The methods are not restricted to
   any one assemblage. The examples
   all use benthic macroinvertebrates,
   but any other assemblage could also
   be used, such as fish,
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       phytoplankton, zooplankton or
       macrophytes;

   *•   The examples used to illustrate the
       methods have been carried out over
       wide geographic areas with many
       sites, demonstrating the generality of
       the methods;

   *•   The examples used to illustrate the
       methods are concise, the methods
       were fully documented, and have
       been carried to completion, that is,
       assessment of biological impairment
       and non-impairment.

   All three of the methods use the same
   general approach:  sites are assessed by
   comparing the assemblage of organisms
   found at a site to an expectation derived
   from observations of many relatively
   undisturbed reference sites. The
   expectations are modified by classifying
   the reference sites to account for natural
   variability, and each assessment site is
   classified using non-biological (physical,
   chemical, geographic) information.
   Finally, metrics (methods 1 and 2) or the
   species ordination (method 3) are tested
   for response to stressors by comparison
   of reference and known impaired sites.
   An example of the assessment process is
   summarized in Figure 11-1.

   This chapter will first discuss methods
   of classification, with emphasis  on those
   that have been successful in estuaries
   and coastal waters.  The remainder of
   the chapter then discusses the three
   assessment methods.  This chapter is not
   intended to be an instruction manual on
   using the different statistical methods; it
   is intended to show, with selected
   examples, techniques that have  been
   used to develop biological indexes.
   Details of applications and methodology
   can be found in the cited documents and
   articles and in statistical textbooks and
   manuals (e.g., Ludwig and Reynolds
   1988, Reckhow and Warren-Hicks 1996).
11.2  Classification and
       Characterization of
       Reference Condition

The objective of characterization is to
finalize the classification of reference
sites and to describe (characterize) each
of the reference classes in terms of
metrics, assemblage composition, and
physical-chemical variables.  As
outlined in Chapter 4, classification may
be a physical rule-based classification,
or an analytical data interpretation
where rules are derived from the data.
The analytical approach requires a
relatively large reference data set to
derive the classes and rules, with many
sites and both biological and
physical-chemical data from each site.

The basic assumption of classification is
that biogeography, physical habitat, and
water quality largely determine
attributes such as taxa richness,
abundance, and species dominance in
estuarine and coastal marine biological
communities. In other words, if
habitats are classified  adequately,
reference biological communities should
correspond to the habitat classification.

Several statistical tools can assist in site
classification, but there is no one set
procedure. If the rule-based
classification is based  on well-
developed prior knowledge and
professional judgment, graphical
analysis of metrics, followed by any
necessary modifications and tests of the
resultant classification, it is usually
sufficient. If necessary, the classification
is refined until an optimal classification
emerges that satisfactorily accounts for
variation in reference  site biological
data.

If a physical classification is not self-
evident, it may be necessary to develop
an alternative classification from the
data using one or more of several
11-2
                          Index Development

-------
   1. V\atertadyQasafication—The
   physical and habitat data along with
   bidogcal data are used ID gioup
   reference sites into homogeneous
   dasses
   2 MstacIdentification—Those
   metrics or attri butes that are
   ecologically relevant to asserrdage
   and zoogeography are identified
   3. Fvfetric Calibration—Gore metrics
   are sensitive to pollution and are
   informative of the ecological
   relationships of the asserrdage to
   specific stressors or cumJative
   irrpacts
   4. I noex Development—Core
   (retries, whose values vary in scale,
   are transforrred to drrensionless
   numbers for aggregation
   5. Threshold Establishment—The
   threshold (bocriterion) for
   dscnrri rating between impaired and
   urirrpaired isdeterrrined to pnovide
   a basis for assessment
                    Figure 11-1	
                    The process for
                    progressing from
                    the classification
                    of an estuary to
                    assessing the
                    health of the
                    estuary.  Adapted
                    from Paulsen et al.
                    1991.
    classification methods. These methods
    include cluster analysis and several
    ordination methods such as: principal
    components analysis, correspondence
    analysis, and multidimensional scaling.

    11.2.1 Existing Classifications

    With the growth of efforts to improve
    environmental monitoring and develop
    biocriteria, several successful
    classifications  of estuarine and near-
    coastal biological assemblages have been
    developed.  Here, we summarize several
    of these and integrate their findings on
    classification of North American
    estuarine assemblages.
       EMAP Virginian Province

Natural environmental factors affecting
species composition were examined in
the EMAP Virginian Province Project
(Paul et al. 1999, Strobel et al. 1995,
Weisberg et al. 1993). Salinity has been
known to control estuarine organisms
since the early days of marine biology.
Over 75% of the candidate measures
were related significantly to salinity
distributions (Figure 11-2). Correlation
analysis was used to examine
associations of habitat factors with
candidate biological metrics.  Of the
correlations between candidate
measures and habitat factors,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                          11-3

-------
      Figure 11-2
      Mean number
      of species and
      salinity at
      EMAP-
      Estuaries
      sampling
      stations in the
      Virginian
      Province (from
      Weisberg et al.
      1993). The
      regression line
      shown is the
      expected
      number of
      species based
      on the
      polynomial
      regression,
      and was used
      to estimate
      salinity-
      adjusted
      species
      richness
      measures.
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0 5 10 15 20 26 30 35
(ppt)
   species richness was most strongly
   correlated with salinity.

   In addition to salinity, the physical
   characteristics of estuarine sediments
   and depth also influence benthic
   infaunal distribution and the
   accumulation of contaminants in
   sediments (Rhoads 1974, Plumb 1981).
   EMAP collected sediment grain size,
   silt-clay content, latitude, and depth
   data to help interpret benthic response.
   Although silt-clay content and depth
   were statistically significant, only
   salinity was deemed to have a
   biologically significant influence on
   benthic macroinvertebrates (r2 >0.025;
   Weisberg et al. 1993). Estuary type was
   stratified in the project design, but
   community differences due to estuary
   type were not reported.

               Chesapeake Bay

   Weisberg et al. (1997) developed an
   estuarine benthic index of biotic
   integrity for the Chesapeake Bay.
Cluster analysis of benthic infauna
indicated seven distinct habitats defined
by substrate and salinity.  Polyhaline
sand and mud, (salinities  (>18 %o) had
the highest mean Shannon-Wiener
diversities, at 4.0 and 3.55, respectively
(Weisberg etal.  1997).

      EMAP Carolinian Province

From July - September 1995, a study
was conducted to assess the
environmental condition of estuaries in
the EMAP Carolinian Province (Hyland
et al. 1998, see Chapter 13). The
program sampled water depth, salinity,
and substrate classifications (% silt-clay)
as habitat indicators.

Species richness showed highly
significant correlations with latitude,
bottom salinity, and silt-clay/TOC
sediment content. The Shannon-Wiener
index, H' (a combination of species
richness  and evenness), also showed
highly significant correlations (p <
0.0030) with bottom salinity as well as
11-4
                           Index Development

-------
   with silt-clay fractions. As with
   diversity, infaunal abundance showed
   highly significant correlations (p <
   0.0016) with the silt-clay and TOC
   sediment content (Hyland et al. 1998).

               North Carolina

   The North Carolina study was designed
   to compare biological metrics derived
   from three sampling methods (Ponar,
   epibenthic trawl, and sweep net).
   Salinity was the only habitat
   characteristic that was significantly
   correlated with biological metrics. Total
   taxa showed a positive correlation with
   salinity (Eaton 1994a; see Chapter 13).

                Puget Sound

   The objective of the Puget Sound study
   was to characterize benthic
   macroinvertebrate communities into
   habitats classified as degraded and
   habitats that are relatively unimpaired,
   which can then be classified as reference
   sites for the Sound (Llanso 1999).

   The diverse assemblages sampled were
   mainly associated with sediment type
   and water depth, reinforcing results
   from previous studies (Lie 1974). The
   classes of sediments defined for the
   Puget Sound estuaries were:  sands,
   clays, and mixed. These three classes
   did not have exact boundaries, but
   instead overlapped at both ends of their
   spectrums (Llanso 1999). Stations with
   finer substrates had fewer species than
   those with coarser substrates. On
   average, sand substrates  supported
   more species and abundance  than did
   clay, with deep sites having the lowest
   abundance levels.  Overall, clay stations
   in the southern part of Puget Sound
   supported fewer species than many
   other shallow clay locations.  The
   majority of species were not restricted to
   only one substrate, instead they were
   widely distributed in different types  of
sediment showing the most abundance
in sand, mixed sediment, or muddy
bottoms.

     EMAP Louisianian Province

Prior studies in the Gulf of Mexico had
shown salinity and sediment type to be
among the most important factors that
determine benthic infaunal
relationships in Gulf of Mexico estuaries
(Flint and Kalke 1985, Gaston et al. 1988,
Rabalais 1990, Rakocinski et al. 1991).
Of the 182 total sites sampled, Pearson
correlations were performed between all
candidate measures and salinity,
longitude of sampling site (as a measure
of geographical gradient), percent silt-
clay, and total organic carbon content of
sediments. Many of the correlations
were statistically significant atp < 0.05,
however, only salinity accounted for
20% or more of the variation (Summers
et al. 1993).

       Southern  California Eight

The Southern California Coastal Water
Research Project sampled megabenthic
invertebrate assemblages, benthic
infaunal assemblages, and demersal fish
assemblages to determine their
relationship to depth, latitude, and
sediment types in the Southern
California Bight.  There was no salinity
gradient because the entire study area
was nearshore marine. Overall, depth
was found to be the defining factor in
the organization of each assemblage
(Allen et al. 1999, Bergen et al. 1999).

Sediment type was found to be a
secondary factor in the organization of
benthic infaunal assemblages. This
finding could be attributed to the large
study area. In fact, within a constrained
depth range, sediment type may be a
more important factor (Bergen et al.
1999). These findings are consistent
with those of Snelgrove and Butman
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     11-5

-------
   (1994) which suggested that the
   hydrodynamic environment and the
   amount of organic material in the
   sediment are more likely to be primary
   driving forces, with depth and sediment
   grain size as secondary correlates.

                 Conclusions

   Three habitat indicators have been
   demonstrated repeatedly to influence
   biological assemblages of estuaries and
   near coastal environments. In studies
   where there was a salinity gradient,
   salinity was found to be the most
   important habitat indicator. Depth and
   substrate are also important and usually
   correlated, especially if there is a large
   depth gradient at the sample site. The
   physical type of estuary (e.g., fjord,
   lagoon, tidal river) has not been
   demonstrated to be vital in wide
   geographic studies, such as those
   conducted by EMAP in the Virginian,
   Louisianian, and Carolinian provinces,
   but may not have been adequately
   tested. Therefore, the importance of
   measuring estuary type, subregion, or
   subprovinces is still questionable.

   Lessons learned from both EMAP and
   other independent studies conclude that
   the basic classification of an index
   should be by biogeograpical province,
   salinity, substrate (silt-clay content,
   sediment grain size), and depth. The
   effects of salinity, substrate, and depth
   should be tested within the study area to
   determine whether all are required as
   habitat indicators in  an individual area.
   Moreover, decisions  need to be made as
   to the use of discrete classes or
   continuous covariates in statistical
   analysis. If other classifications are
   suspected to be important indicators of
   the health of a system, they should also
   be tested (e.g., estuary type).
11.2.2 Assessing a priori
       Classifications

Although there is no serious doubt over
the influence of salinity, sediment, and
depth on estuarine biota, the effects
must be characterized or calibrated to
establish reference conditions. Several
approaches have been used, as outlined
in the examples in this chapter.  Often,
one of the first steps is a cluster analysis
of the species composition of the sites to
determine if sites can be broken down
into groups (e.g., Weisberg et al. 1997,
Smith et al. 2000). Sites maybe divided
into groups defined by the important
variables (e.g., salinity and sediment;
Weisberg et al. 1997, depth; Smith et al.
1999), or the groups may be separated
by discriminant function analysis (DFA)
if simple, single relationships are not
sufficient (e.g., Engle and Summers
1999).

Another approach is to examine
correlations between environmental
variables and biological metrics
calculated from the species data, so that
reference expectations can be calibrated
accordingly.  For example, species
richness in estuaries is strongly affected
by salinity (refer to Figure 11-2).
Weisberg et al. (1993) used the
relationships of Figure 11-2 to develop a
nonlinear regression of maximum
expected species richness on salinity.
Species richness was then adjusted by
the salinity-specific maximum in further
development of their model of
impairment.

11.3  Index Development

An index for assessing sites can be
developed after classification of sites of
the region is completed. Index
development using the three
approaches followed in this chapter is
discussed here.
11-6
                          Index Development

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    11.3.1 Multimetric Index

    Step 1. Identify Potential Measures For
    Each Assemblage.

    Metrics allow the investigator to use
    meaningful indicator attributes in
    assessing the status of assemblages and
    communities in response to
    perturbation.  The definition of a metric
    is a characteristic of the biota that
    changes in some predictable way with
    increased human influence (Barbour et
    al. 1995).  For a metric to be useful, it
    must have the following technical
    attributes: (1) ecological relevance to the
    biological assemblage or community
    under study and  to the specified
    program objectives, (2) sensitivity to
    stressors and provide a response that
    can be discriminated from natural
    variation.  The purpose of using
    multiple metrics to assess biological
    condition is to aggregate and convey the
    information available regarding the
    elements  and processes of aquatic
    communities.

    All metrics that have ecological
    relevance to the assemblage under study
    and that respond to the targeted
    stressors are potential metrics for
    testing. From this "universe" of metrics,
    some will be eliminated because of
    insufficient data or because the range of
    values is not sufficient for
    discrimination between natural
    variability and anthropogenic effects.
    This step  is taken to identify the
    candidate metrics that are most
    informative, and therefore, warrant
    further analysis.

    Representative metrics should be
    selected from each of four primary
    categories:  (1) richness measures for
    diversity  or variety of the assemblage;
    (2) composition measures for identity
    and dominance; (3) tolerance measures
    that represent sensitivity to
perturbation; and (4) trophic or habit
measures for information on feeding
strategies and guilds. Table 11-1 further
illustrates metrics for various
assemblages that have been useful in
estuaries. Components of Step 1
include:

>  Review of the value ranges of
   potential metrics, and elimination of
   those that have too many zero
   values in the population of reference
   sites to calculate the metric at a large
   enough proportion of sites;

*•  Descriptive statistics (central
   tendency, range, distribution,
   outliers) to characterize metric
   performance within the population
   of reference sites of each site class;

*•  Elimination of metrics that have too
   high variability in the reference site
   population such that they cannot
   discriminate among sites of different
   condition.

Step 2. Select Robust Measures.

Core metrics are those that will
discriminate between good and poor
quality ecological conditions.
Discriminatory ability of biological
metrics is evaluated by comparing the
distribution of each metric at a set of
reference sites with the distribution of
metrics from a set of "known" stressed
sites (defined by physical and  chemical
characteristics) within each site class.  If
there is minimal or no overlap between
the distributions, then the metric can be
considered to be a strong discriminator
between reference and impaired
conditions (Figure 11-3).

Criteria are established to identify a
population of "known" stressed sites
based on physical and chemical
measures of degradation. Criteria for
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      11-7

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Table 11-1. Potential metrics for macrophytes, benthic macroinvertebrates, and fish that
could be considered for estuaries. Redundancy can be evaluated during the
calibration phase to eliminate overlapping


 %
polychaetes
- polychaete
biomass




- #, % or
biomass of
menhaden







Trophic/Habitat
- % cover
- density of new
shoots
- biomass
- stem counts

- % or biomass
epibenthic
- % or biomass
deposit feeders
- % or biomass
suspension
feeders

- Proportion of
planktivores
- Proportion of
benthic feeders
- Proportion of
piscivores




   stressed sites can include (Weisberg et
   al. 1993):

   *•   Any sediment contaminant
       exceeding the Long et al. (1995)
       effects range-median (ER-M)
       concentration;

   *•   Survival in toxicity tests less than
       80% of controls;

   *•   Low dissolved oxygen;

   *•   Total sediment organic carbon > 3%.

   Following identification of reference and
   stressed sites, the biological metrics that
   best discriminate between them are
   determined.

   Those metrics having the strongest
   discriminatory power provide the most
   confidence in assessing biological
   condition of unknown sites. Metrics can
be easily compared by estimating their
discrimination efficiency (DE) or the
percentage of stressed sites below a
threshold representing the reference
sites.  For example, DE could be
measured as the percentage of stressed
sites below the 25th percentile of
reference sites, for a given metric.

Several studies have used tests of
statistical significance between
reference and  stressed sites to select
metrics (e.g., Weisberg et al. 1997,
Hyland et al. 1998). Significance tests
should only be used if the sample size
(number of reference and stressed sites)
is large enough that the test has
sufficient power to detect a meaningful
difference.
11-8
                          Index Development

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30
26

22
3 18
ro
•| 14
^>
10
6






[





Refe




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[



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| Min-Max
I I 25%-75%
n Median value
                                                                  Figure 11-3
                                                                  Hypothetical box
                                                                  plot illustrating how
                                                                  a successful metric
                                                                  discriminates
                                                                  between reference
                                                                  and stressed sites.
   Step 3. Determine the best aggregation of
   core measures for indicating status and
   change in condition.

   The purpose of an index is to provide a
   means of integrating information from
   the various measures of biological
   attributes (or metrics). Metrics vary in
   their scale—they are integers,
   percentages, or dimensionless numbers.
   Prior to developing an integrated index
   for assessing biological condition, it is
   necessary to standardize core metrics via
   transformation to unitless scores. The
   standardization assumes that each
   metric has the same value and
   importance; i.e., they are weighted the
   same, and that a 50% change in one
   metric is of equal value to assessment as
   a 50% change in another.

   Where possible, the scoring criterion for
   each metric is based on the distribution
   of values in the population sites, which
   include reference sites; for example, the
   95th percentile of the data distribution is
   commonly used to eliminate extreme
   outliers. From this upper percentile, the
   range of the metric values can be
   standardized as a percentage of the 95th
percentile value, or other (e.g., trisected
or quadrisected), to provide a range of
scores. Those values that are closest to
the 95th percentile receive higher scores,
and those having a greater deviation
from this percentile receive lower
scores. For those metrics whose values
increase in response to perturbation the
5th percentile is used to remove outliers
and to form a basis for scoring.

Alternative methods for scoring metrics
are currently in use in various parts of
the U.S. for multimetric indexes. A
"trisection"  of the scoring range has
been well documented (Karr et al.  1986,
Ohio EPA 1987, Weisberg et al. 1997,
Hyland et al. 1998). More recent studies
are finding that a standardization of all
metrics as percentages of the 95th
percentile value yields the most
sensitive index, because more
information of the component metrics is
retained (e.g., Hughes et al. 1998).

Aggregation of metric scores simplifies
management and decision making so
that a single index value is used to
determine whether action is needed.
Biological condition of waterbodies is
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      11-9

-------
   judged based on the summed index
   value (Karr et al. 1986). If the index
   value is above a criterion, then the
   stream is judged as "optimal" or
   "excellent" in condition. The exact
   nature of the action needed (e.g.,
   restoration, mitigation, pollution
   enforcement) is not determined by the
   index value, but by analyses of the
   component metrics in addition to the
   raw data, and integrated with other
   ecological information. Therefore, the
   index is not the sole determinant of
   impairment and diagnostics, but when
   used in concert with the component
   information, strengthens the assessment
   (Barbour etal. 1996b).  Components of
   Step 3 include:

   *•   Development of scoring criteria for
       each metric (within each site class)
       from the  appropriate percentile of
       the data distribution (Figure 11-4). If
       the metric is associated with a
       significant covariate such as estuary
       size,  depth, or salinity a scatterplot
       of the metric and covariate and a
       moving estimate of the appropriate
       percentile, are used to determine
       scoring criteria as a function of the
       covariate (e.g., Weisberg et al. 1993);

   *•   Testing the ability of the final index
       to discriminate between populations
       of reference and anthropogenically
       affected (stressed) sites.

   Step 4. Index thresholds for assessment and
   biocriteria.

   The multimetric index value for a site is
   a summation of the scores of the metrics
   and has a finite range within each site
   class and index period, depending on
   the maximum possible score of the
   metrics (Barbour et al.  1996a). This
   range can be subdivided into any
   number  of categories corresponding to
   various levels of impairment. Because
   the metrics are normalized to reference
conditions and expectations for the
classes, any decision on subdivision
should reflect the distribution of the
scores for the reference sites.

Rating categories are used to assess the
condition of both reference and non-
reference sites.  Most of the reference
sites should be rated as good or very good
in biological condition, which would be
as expected. However, a few reference
sites may be given the rating as poor
sporadically among the collection dates.
If a "reference" site consistently receives
a fair or poor rating, then the  site should
be re-evaluated as to its proper
assignment. Putative reference sites
may be rated "poor" for several reasons:

*•   Natural variability — owing to
    seasonal, spatial, and random
    biological events, any reference site
    may score below the reference
    population 10th percentile. If due to
    natural variability, a low score
    should occur 10% of the time or less;

*•   Impairment — stressors that were
    not detected in previous sampling or
    surveys may occur at a "reference"
    site; for example, episodic non-point
    source pollution  or historical
    contamination may be present at a
    site;

*•   Non-representative site — reference
    sites are intended to be
    representative of their class. If there
    are no anthropogenic stressors, yet a
    "reference" site consistently scores
    outside the range of the rest of the
    reference population, the  site may
    be a special or unique case,  or it may
    have been misclassified and actually
    belong to another class of sites.
11-10
                          Index Development

-------
maximum







- - -*
o
n 5 4
n

3
3 	 /observed value ^ ,„„ \
LJ 2 ^95th value X1°°j

i
i i
All Trisection Quadrisection Percentage
Sites of standard
Scoring Methods
                                                               Figure 11-4
                                                               Basis of metric
                                                               scores using the
                                                               95th percentile as a
                                                               standard.
   Components of Step 4 include:

   *•   Assessment categories are
       subdivided from the range of
       possible scores for each site class.
       Categories should be proportional to
       the interquartile range (or standard
       deviation) of total scores in the
       reference sites.  Thus, reference sites
       with a small interquartile range
       (small s.d.; small coefficient of
       variation) would yield more
       assessment categories than a more
       variable reference population;

   *•   The validity of biological condition
       categories is evaluated by comparing
       the index scores of the reference and
       known stressed sites to those
       categories.  If reference sites are not
       rated good or very good, then some
       adjustment in either the biological
       condition designations or the listing
       of reference sites may be necessary;

   *•   Confidence intervals are estimated
       for the multimetric index to help
       determine biological condition for
       sites that fall in close proximity to a
       threshold. Precision and sensitivity
       are determined from replicate
       samples, and are important for
       estimating the confidence of
       individual assessments.
Once the framework for bioassessment
is in place, conducting bioassessments
becomes relatively routine. Either a
targeted design that focuses on site-
specific problems or a probability-based
design, which is appropriate for 305(b),
area-wide, and watershed monitoring,
can be done efficiently.  Routine
monitoring of reference sites should be
based on a random selection procedure,
which will allow for cost efficiencies in
sampling while monitoring the status of
the reference condition. Potential
reference sites of each class would be
randomly selected for sampling, so that
an unbiased estimate of reference
condition can be developed. A
randomized subset of reference sites can
be resampled at some regular interval
(e.g., a 4-year cycle) to provide
information on trends in reference sites.

    Example 1: Chesapeake Bay Index
    Development

For the Chesapeake Bay, a separate
benthic index was developed for each of
seven habitats: tidal fresh, oligohaline,
low mesohaline, high mesohaline sand,
high mesohaline mud, polyhaline sand,
and polyhaline mud (Weisberg et al.
1997).  These habitats had been
identified as separate assemblages in
the classification step.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     11-11

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   Reference and stressed sites were
   identified by the following: from
   existing Chesapeake Bay data, no
   reference sites could be in highly
   developed (urban) watersheds or near
   known point-source discharges, no
   reference site could have organic carbon
   content > 2%, no reference site could
   have any sediment contaminants
   exceeding the Long et al. (1995) effects
   range-median (ER-M) concentration, no
   reference site could have low dissolved
   oxygen, and no reference site could
   exhibit any sediment toxicity. Stressed
   sites were defined as those with any
   contaminant exceeding the ER-M
   concentration and measured sediment
   toxicity, or total organic carbon
   exceeded 3%, or dissolved oxygen was
   low, < 2-mgL'1 (Weisberg etal. 1997).

   Index development proceeded through
   the steps:

   Step 1. 17 candidate metrics were
   identified based on the paradigms of
   Pearson and  Rosenberg (1978).

   Step 2. 15 of the 17 metrics could
   distinguish between reference sites and
   stressed sites in one or more of the seven
   habitats.

   Step 3. Four to seven of the metrics were
   used for an index specific to each habitat
   type. Scoring of metrics was on a 5-3-1
   scale, with metric values greater  than
   the reference site median scored  as 5;
   between the 5th and the median of the
   reference sites scored as 3; and below
   the 5th percentile scored as 1.

   Step 4. The index was able to correctly
   classify as reference or stressed 93% of
   an independent validation data set that
   had not been used to develop the index.
   Example 2: Louisiana and Maryland
   Fish Indexes

Several states are developing fish
indexes of biotic integrity (IBI) for
estuarine species. The multimetric
Index of Biotic Integrity (IBI) concept
was originally developed for fresh
water streams (Karr 1981), and has been
modified and applied to a Louisiana
estuary (Thompson and Fitzhugh 1986).
The strength of this index is that many
factors affecting biological integrity can
be measured in fish (e.g., community
composition, relative abundance, health,
etc.). This proposed estuarine IBI
maintains the same three main
categories as those of the fresh water
IBI: species composition, trophic
composition, and fish condition.
However, the metrics are modified to
reflect estuarine habitats and fish
assemblages. In addition, because
estuarine systems exhibit a high degree
of seasonality in their fish fauna, a
measure of seasonal variability was
incorporated. The metrics for estuaries
are based on life history and habitat
requirements similar to those of the
fresh water IBI. Proposed metrics from
Thompson and Fitzhugh (1986)  for
estuarine communities are listed in
Table 11-2. A similar fish Index of Biotic
Integrity is being adapted for
application in estuarine and coastal
marine habitats on the Gulf Coast of
Texas (Guillen 1995).

The state of Maryland has also
developed a fish Index of Biotic
Integrity that is more rapid and less
expensive to apply (Jordan et al. 1992).
This fish IBI is comprised of nine
metrics (Table 11-3) that can be
compared to measurements of the
physical environment such as dissolved
oxygen and land use.
11-12
                          Index Development

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     Table 11-2.
Estuarine fish IBI metrics proposed by Thompson and Fitzhugh (1986).
Community
Structure/Function
Species composition
Trophic composition
(for adults of species)
Fish abundance and
condition
Metric
Total number of fish species
Number and identity of resident estuarine species
Number and identity of marine species
Number and identity of sciaenids
Number and identity of freshwater species
Proportion of individuals as bay anchovy
Measure of seasonal overlap offish community
Number of species needed to make up 90% of collection
Proportion of individuals as generalized benthic feeders
Proportion of individuals as generalized plankton grazers
Proportion of individuals as top carnivores
Proportion of young of year in sample or number of individuals
in sample
Proportion of individuals with disease, tumors, fin damage, and
other anomalies
   The results of some preliminary analyses
   from areas in the Chesapeake Bay with
   salinities ranging from O-to-16 ppt
   indicate that the Maryland IBI can be
   used to identify large scale spatial and
   temporal trends in biological integrity
   and that the index responds to water
   quality (DO) and land use impacts.

   11.3.2  Discriminant Model Index

       Discriminant Model Approach

   The discriminant model approach was
   used by EMAP to develop benthic
   condition indexes for the Virginian
   Province (Mid-Atlantic) and for the
   Louisianian Province (Gulf Coast)
   (Engle et al. 1994, Summers et al. 1993,
   Weisberg et al. 1993, Paul et al.  1999)
   based on defined reference sites. Sets of
   minimally impaired sites; i.e.,
   "reference" and impaired sites were
   identified; impaired sites were affected
   by either hypoxia (DO <2 mgL"1); toxic
   sediments; or sediment contamination
   above the ER-M threshold. Minimally
   impaired sites were defined to have DO
   >5 mgL"1 and no detectable toxicity or
   contamination. The two site types
   represented the ends of a continuum,
                          with intermediate sites not used for
                          discriminant model building (Engle et
                          al. 1994, Weisberg et al. 1993).

                          The classification step for the EMAP
                          discriminant models consisted of
                          examining associations between benthic
                          macroinvertebrate metrics and physical
                          habitat measures of salinity, sediment
                          grain size, and depth.  Only salinity had
                          a strong relationship with the taxa
                          richness metric; taxa richness was
                          estimated as the  percent of taxa
                          expected, adjusted for salinity (refer to
                          Figure 11-2).

                               Discriminant Model Analysis

                          The discriminant model analysis is a
                          multivariate procedure that attempts to
                          build a model that will predict the
                          membership of a site into two or more
                          predetermined classes. In the example
                          used in EMAP, the classes were
                          reference and impaired sites (by low
                          DO, toxicity or metal contamination).
                          The model procedure attempts to find a
                          linear combination of input variables
                          (biological metrics) that best predicts
                          membership in the class. Alternative
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                              11-13

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    Table 11-3. Maryland estuarine fish IBI metrics.
Community
Structure/Function
Species composition
Trophic composition
(for adults of species)
Fish abundance and
condition
Metric
Total number of species
Number of species in bottom trawl
Number of species comprising 90 percent of
individuals
Proportion of planktivores
Proportion of benthic feeders
Proportion of piscivores
Number of estuarine spawners
Number of anadromous spawners
Total fish exclusive of Atlantic menhaden
Response
to
Impairment
reduced
reduced
reduced
increased
decreased
decreased
decreased
decreased
decreased
   models are tested by estimating the
   proportion of sites (from the
   model-building data set) that are
   misclassified. The best model usually
   has the lowest misclassification rate.  A
   test of a model requires an independent
   test data set that was not used to build
   the model.

   EMAP built discriminant models using
   benthic metrics in a step wise model
   building approach. The models used
   three to five metrics in the Louisianian
   and Virginian provinces respectively,
   and both models used taxa richness
   (Engle et al. 1994, Weisberg et al. 1993).
   The benthic indexes were then
   calculated as the discriminant score of a
   site and standardized on a scale of 1 to
   10.

   Performance of the discriminant models
   was good in distinguishing reference
   from  impaired sites in the calibration
   data:  100% for the Gulf of Mexico sites
   (Engle et al. 1994; n = 16 sites) and 86-
   93 % for the Virginian Province sites
   (Weisberg et al. 1993; n = 33 sites).
   When tested with validation data
   collected in subsequent years, however,
   both sets or models failed to predict
   adequately and had to be redeveloped
   (Engle and Summers 1999, Strobel et al.
1994,1995, Paul et al. 1999). Inclusion of
several years of monitoring data in both
provinces produced more robust and
reliable models.  In the Virginian
Province, the robust calibration data set
consisted of 60 sites (30 each).

An improved index was created to be
applicable across a variety of estuarine
environments in the Gulf of Mexico
(Engle and Summers 1999). The
statistical approach described in Engle
and Summers (1999) proved to be
applicable throughout the estuaries in
the northern Gulf of Mexico. This
benthic index was also validated
independently by Rakoncinski (1997),
who compared results of canonical
correspondence analysis (CCA) with
data from EMAP-E (1991-1992), using
the index developed in Engle et al. 1994
(Engle and Summers 1999).

11.3.3 Index Derived from
       Multivariate Ordination

An index for biocriteria was derived by
Smith et al. (2000) using multivariate
ordination to derive a pollution
gradient, which in turn was used to
develop an index. The approach was
developed with benthic
macroinvertebrates from the Southern
11-14
                          Index Development

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   California Bight (Smith et al. 2000; see
   also 11.2.1, p. 11-5), and is currently
   being applied to demersal fish from the
   same waters (Allen and Smith 2000).
   The approach is computationally
   intensive and rather complex. We will
   describe the result first (the index and its
   components), and then briefly describe
   how the components themselves are
   derived.

   The central assumption of this approach
   is that each species has a tolerance for
   pollution, and that if the pollution
   tolerance is known for sufficiently large
   set of species, it is possible to infer the
   degree of degradation from species
   composition and the tolerances. This is
   the basis of the familiar Hilsenhoff Biotic
   Index (HBI; Hilsenhoff 1987) of
   freshwater bioassessment, as well as of
   several metrics in the multimetric
   approach.  For example, capitellid
   polychaetes are known to be tolerant to
   organic pollution (BOD). The index
   used by Smith et al. is a weighted
   average tolerance value of all species
   found in a sample, weighted by
   abundance of the species:
   Equation 11-1.
I
                       afsl  Pi
                    I
   where Is is the index value for sample s,
   n is the number of species in sample s, asi
   is the abundance of species i in sample s,
   Pi is the tolerance value of species i, and
   the exponent/is used to downweight
   extreme abundances.  If/is zero, then
   the index is not weighted by abundance
   (Smith et al. 2000, Allen and Smith
   2000).

   The index of equation (11-1) is
   computationally almost identical (except
for the introduction of the
transformation exponent/) to the
Hilsenhoff Biotic Index.  Biocriteria can
be assigned to index values; for
example, if the index is defined in the
range from 0 (unpolluted) to 100
(severely polluted), then a criterion for
Class A estuarine waters might be
values < 25.

The steps below outline the derivation
of the tolerance values pt. A data set is
required with sites that span a range
from unpolluted to severely polluted.
In the Southern California Bight, these
were defined by sediment contaminant
levels above and below the effects range
median (ER-M) and effects range low
(ER-L) concentrations (Long et al. 1995).
Levels of a contaminant below the ER-L,
between the ER-L and ER-M, and above
the ER-M are rarely, occasionally, and
frequently, respectively, associated  with
adverse effects. Impacted sites had six
of eight selected contaminants  (Cu, Pb,
Ni, Zn, Cd, Cr, PCB, and DDT) above
the ER-M. Reference sites consisted of
stations lying outside of POTW
discharge areas and with no more than
one selected contaminant above the ER-
L for a contaminant.

The data must be divided into two sets:
a calibration subset and a test subset.

Step 1.  Ordination analysis of species
abundance (calibration data).

Ordination analysis produces a plot of
sites in ordination space (Figure 11-5).
Distances between pairs of points are
proportional to the dissimilarity of
species composition in the
corresponding samples:  samples with
very similar composition will be close
together in the ordination diagram. If
the species are associated with the
pollution gradient, the sites will define a
gradient, with polluted sites at one  end
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                            11-15

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      CM

      I
      1
             Step 1:  ordination
                                                   "contaminated" end
                                                   Step 2: gradient
                                     \
                                         Step 3: project site scores
                r \  r
                 "reference" end
                             Ordination Axis 1
                       Figure 11-5
                       Steps 1-3.
                       Establishing site
                       scores on a
                       contamination
                       gradient. The
                       gradient is
                       established between
                       reference ("r") and
                       contaminated ("p")
                       sites as plotted in
                       ordination space.
                       Dots are sites not
                       designated as either
                       reference or
                       contaminated.  The
                       projection of site "x"
                       on the gradient
                       (dotted line) yields
                       its site score.
                       Adapted from Smith
                       et al. 2000.
   and unpolluted sites at the other (Figure
   11-5).
    Step 2.  Find the pollution gradient.

    The two ends of the pollution gradient
    are defined as the average positions in
    ordination space of the unpolluted and
    polluted sites, respectively. These ends
    are connected by a line, which
    represents the pollution gradient as
    expressed by the observed species
    compositions.

    Step 3.  Project all calibration observations
    onto the pollution-effects gradient.

    The position of each site in the
    ordination space is projected onto the
    gradient.  This projection is the site score
    of the calibration sites (Figure 11-5).

    Step 4.  Rescale the projections.

    Site scores are scaled from 0 ("least
    polluted") to 100 ("most polluted").
Step 5. Compute tolerance values for each
species.

Each species has an "average" position
on the pollution gradient. These species
positions are the tolerance values (p;) of
Equation 11-1. Site scores calculated in
Step 4 give each site a position on the
pollution gradient. The abundance of a
species at each observation can be
plotted against the site scores (Figure
11-6). The species position on the
gradient, or the tolerance value pit is the
abundance-weighted average position
for the species over all sites.

Step 6. Compute the f parameter.

The f-parameter is iterated
simultaneously with the pt in an
optimization procedure (Smith et al.
2000).

The species tolerance scores were in
turn used to predict the Benthic
Response Index (BRI) according to
Equation 11-1. The BRI is the position
of a site on the contamination gradient,
or the predicted value of the site score
11-16
                            Index Development

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        100
              ••  ••  •    • •     •
             •*•   • «• «•   • w «•  ••
                        '•	• —  J»   *   •••*•••<
                                                            100
                                Ste Scores
                       Figure 11-6
                       Step 5.
                       Computing the
                       tolerance values.
                       Abundance of
                       Species A and
                       site scores (from
                       Figure 11-5) of all
                       sites where
                       Species A
                       occurs.  The
                       abundance-
                       weighted average
                       score over all
                       sites is Species
                       A's pollution
                       tolerance score
                       (arrow). This
                       example shows a
                       highly tolerant
                       species, which
                       occurs in greatest
                       abundances at
                       the most polluted
                       sites. Adapted
                       from Smith et al.
                       2000.
   calculated in Step 4. Actual site scores
   (Step 4) are calculated only for the
   calibration data; site score is predicted as
   BRI for all assessment sites.

   The BRI was developed separately for 3
   depth zones: 10-35-m, 25-130-m, and
   110-324-m. Earlier work had shown that
   benthic communities off Southern
   California could be classified by depth
   and sediment type (see Section 11.2.1, p.
   11-5). Sediment type was secondary,
   and was not deemed to have a strong
   enough effect to justify further
   categorization of the data set.

   The tolerance index developed by Smith
   et al. was then tested with the
   independent data (not used to develop
   the index). The independent test
   showed that the model was largely
   correct in predicting position along the
   contamination gradient. For further
   details of calculations and formulas, see
   Smith et al. (2000).  The approach is
   currently being extended to demersal
   fish from the same region (Allen and
   Smith 2000).
Smith et al. estimated tolerance values
for over 450 marine species from
southern California. The BRI
contamination score can be calculated
for any new site from species
abundance data at the site. The BRI has
a range from 0 (unpolluted) to 100
(severely polluted) and biocriteria can
be set at selected values for specific
aquatic life uses of coastal waters of
Southern California. Reference sites
had BRI values < 25, and all severely
contaminated sites had BRI > 36 (Smith
et al. 2000).  The reference values could
form the basis of biocriteria for the
region.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     11-17

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11-18                                                                       Index Development

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 Chapter  12
 Quality Assurance:
 Design, Precision and
 Management
   Quality assurance (QA) is an integrated
   program for ensuring the reliability of
   monitoring and measurement data and
   includes quality control.  Quality control
   (QC) refers to operational procedures for
   obtaining prescribed standards of
   performance in the monitoring and
   measurement process. Specific QC
   elements can be developed for most, if
   not all, project activities.  All project
   activities, from sampling (data
   collection) and laboratory analysis to
   statistical analysis and reporting, are
   potential error sources (Peters 1988).
   Because error is cumulative and can
   significantly affect the results of a
   project, all possible efforts must be made
   to control it. Therefore, quality
   assurance is a continuous process that
   should be implemented throughout the
   entire development and operation of a
   program.

   The purpose of  an overall quality
   assurance project plan (QAPP),
   containing specific QC elements and
   activities, is to minimize — and when
   possible eliminate—the potential for
   error. Additionally, there are objective
   mechanisms for evaluating activities
   relative to pre-established measurement
   quality objectives and other project
   goals.  The appropriateness of the
   investigator's methods and procedures
   and the quality of the data to be
   obtained must be ensured before the
   results can be accepted and used in
   decision making.
QA is accomplished through:

*•  Program design;

*•  Investigator training;

*•  Standardized data gathering and
   processing procedures;

*•  Verification of data reproducibility;

*•  Instrument calibration and
   maintenance.

As outlined below, QA requirements
apply to all activities in an ecological
study.  More detailed guidance and
examples for QA activities should be
obtained from USEPA (1994c, and
1998a); more general guidance is
outlined by USEPA (1993b).

12.1   Program Design

A central component of QA is overall
study design which includes
formulation of questions and
hypotheses, experimental design, and
development of analysis approaches.
The classical approach by which
scientists plan research consists of the
following steps:

*•  Statement of the problem to be
   resolved;

>  Formulation of alternative
   hypotheses that will explain the
   phenomena or, in the case of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    12-1

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       problems that do not involve
       elaboration of processes, formulation
       of specific research questions;

   *•   Establishment of boundaries within
       which to resolve the problem;

   >   Formulation of an experimental or
       study design that will falsify one or
       more hypotheses or answer the
       specific research questions;

   *•   Establishment of uncertainty limits
       including setting acceptable
       probabilities of type I and type II
       errors for statistical hypothesis
       testing;

   *•   Optimization of the study design
       including power analysis of the
       statistical design.

   Experimental advances in basic sciences
   have not included the last two steps
   because uncertainty limits were
   inappropriate or unknown.
   Examination of experimental advances
   also reveals that a high degree of
   creativity and insight is required to
   formulate hypotheses and study
   designs; no formal planning process or
   "cookbook" can guarantee creativity and
   insight. Nevertheless, documentation of
   the planning process and a complete
   explanation of the conceptual
   framework help others evaluate the
   validity of scientific and technical
   achievements.

   12.1.1 Formulation of a Study Design

   A study design is developed to answer
   the specific monitoring questions
   developed in formulating the questions
   and objectives.  Sampling design
   considerations were discussed in
   Chapter 5.

   For quality assurance, some effort will
   always be required for repeated samples
 so that measurement error can always
 be estimated from a subset of sites.
 Repeated measurement at 10% or more
 of sites is common among many
 monitoring programs.

 12.1.2 Establishment of Uncertainty
        Limits

 The level of uncertainty associated with
 environmental measurements (due to
 natural variability, sampling error,
 measurement error, or other sources of
 uncertainty) propagates directly to the
 uncertainty of inferences  and
 conclusions that can be made from the
 data.  Establishing the limits of
 statistical uncertainty for  conclusions
 also sets limits for the data to be
 collected (also known as Data Quality
 Objectives [DQOs]; Chaloud and Peck
 1994).  As mentioned in Chapter 5, there
 is a close association between sampling
 intensity and uncertainty. Reducing
 uncertainty usually results in greater
 costs. Assessing uncertainty, and
 optimizing the study design (below)
 require at least pilot data in hand, if not
 results from one year or more of
 monitoring.

 As an example of uncertainty limits,
 USEPA's EMAP program established
 the following (Chaloud and Peck 1994):

 *•   Estimate the status of a population
     of resources with 95% confidence
     intervals that are within 10% of the
     estimate;

 *•   Determine average change in status
     of 20% over 10 years with 95%
     confidence and statistical power  of
     0.8.

 EMAP selected 95% confidence
 intervals, however, there is nothing
 "scientific" about choosing 95%
 intervals over, say, 90 % or 99%.  The
 second limit above, determining
12-2
Quality Assurance: Design, Precision and Management

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   change, implies that EMAP managers
   were only willing to conclude a false
   change in status 1 time out of 20 (Type I
   error; false positive), but were willing to
   conclude a false lack of change 1 time
   out of 5 (Type II error, false negative).

   12.1.3 Optimizing the Study Design:
          Evaluation of Statistical Power

   A principal aspect of probability
   sampling is determining how many
   samples will be required to achieve the
   monitoring goals and what is the
   probability of making an incorrect
   decision based on the monitoring
   results. The primary tool for conducting
   these analyses is statistical power
   analysis. Evaluating statistical power is
   key to developing data quality criteria
   and performance specifications for
   decision making (USEPA 1996b) as well
   as evaluating the performance of
   existing monitoring programs (USEPA
   1992).  Power analysis provides an
   evaluation of the ability to detect
   statistically significant differences in a
   measured monitoring variable.  The
   importance of this analysis can be seen
   by examining the possible outcomes  of a
   statistical test. The null hypothesis (H0)
   is the root of hypothesis testing.
   Traditionally, null hypotheses are
   statements of no change, no effect, or no
   difference. For example, the mean
   abundance at a test site is equal to the
   mean abundance of the reference sites.
   The alternative hypothesis (Ha) is
   counter to H0, traditionally being
   statements of change, effect, or
   difference. Upon rejecting H0, Ha would
   be accepted.

   The two types of decision errors that
   could be made in hypothesis testing are
   depicted in Table 12-1. A Type I error
   (i.e., false positive) occurs when H0 is
   rejected although H0 is really true. A
   Type II error (i.e., false negative) occurs
   when H0 is not rejected although H0 is
really false.  The magnitude of a Type I
error is represented by 
-------
     Table 12-1. Errors in hypothesis testing.
Decision
Accept H0
Reject H0
State of the population (truth)
H0 is True
1-a
(Confidence level)
a
(Significance level)
(Type I error)
H0 is False
P
(Type II error)
1-P
(Power)
   Figure 12-1
   Effect of
   increasing sample
   size from n., to n2
   on power. The
   curves represent
   the probability
   distribution of the
   sample means
   from 2 samples,
   reference and test,
   and for 2 sample
   sizes n., and n2
   where n2 > nv
a. Reference
  sample
                              critical value for rj

                                 "critical value for q
                              rejection region,a,, for n,
                           b. Test sample
                              rejection region,Oj, for r^
                                       probability of Type II \
                                       error (false negative)!
                                            for n.
   the x-axis), the probability of rejecting
   H0, the power, increases. If the real
   difference between the two sample
   means is zero, the probability of
   rejecting H0 is equal to the significance
   level, CL. Figure 12-la shows the general
   relationship between CC and P if (X is
   changed.  Figure 12-lb shows the
   relationship between CC and P if the
   sample size is increased. The tradition
   of 95% confidence  (a = 0.05) is entirely
   arbitrary; there is no scientific
   requirement that confidence be set at
   95%. Indeed, for environmental
   protection, power is at least as
   important—and possibly more
   important—than confidence (Peterman
   1990, Fairweather 1991).
                               Basic Assumptions

                    Usually, several assumptions regarding
                    data distribution and variability must
                    be made to determine the sample size.
                    Applying any of the equations
                    described in this chapter is difficult
                    when no historical data set exists to
                    quantify initial estimates of proportions,
                    standard deviations, means, or
                    coefficients of variation.  To estimate
                    these parameters, Cochran (1963)
                    recommends four sources:

                    *•   Existing information on the same
                        population or a similar population;

                    +   A two-step sample.  Use the first-
                        step sampling results to estimate the
                        needed factors, for best design, of
12-4
                   Quality Assurance: Design, Precision and Management

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       the second step. Use data from both
       steps to estimate the final precision
       of the characteristic(s) sampled;

   +   A "pilot study" on a "convenient" or
       "meaningful" subsample. Use the
       results to estimate the needed
       factors. Here the results of the pilot
       study generally cannot be used in
       the calculation of the final precision
       because often the pilot sample is not
       representative of the entire
       population to be sampled;

   +   Informed judgment, or an educated
       guess.

   For evaluating existing programs,
   proportions, standard deviations,
   means, etc. would be estimated from
   actual data.

   Some assumptions might result in
   sample size estimates that are too high
   or too low. Depending on the sampling
   cost and cost for not sampling enough
   data, it must be decided whether to
   make conservative or "best-value"
   assumptions. Because of the fixed
   mobilization costs, it is probably cheaper
   to collect a few extra samples the first
   time than to realize later that additional
   data are needed. In most cases, the
   analyst should probably consider
   evaluating a range of assumptions
   regarding the impact of sample size and
   overall program cost. USEPA
   recommends that if the analyst lacks a
   background in statistics, he/she should
   consult with a trained statistician to be
   certain that the approach, design, and
   assumptions are appropriate to the task
   at hand.

    Simple Comparison of Proportions and
          Means from Two Samples

   The proportion (e.g., percent dominant
   taxon) or mean (e.g., mean number of
   EPT taxa) of two data sets data sets can
be compared with a number of
statistical tests including the parametric
two-sample t-test, the nonparametric
Mann-Whitney test, and two-sample
test for proportions (USEPA 1996b). In
this case, two independent random
samples are taken and a hypothesis test
is used to determine whether there has
been a significant change. To compute
sample sizes for comparing two
proportions, p1 and p2, it is necessary to
provide a best estimate for p1 and p2, as
well as specifying the significance level
and power (1-0). Recall that power is
equal to the probability of rejecting H0
when H0 is false. Given this
information, the analyst substitutes
these values into the following equation
(Snedecor and Cochran 1980):

      Equation 12-1.
       «„=
where Za and Z2p correspond to the
normal deviate. Common values of (Za
+ Z2p)2 are summarized in Table 12-2.
To account for p1 and p2 being
estimated, t could be substituted for Z.
In lieu of an iterative calculation,
Snedecor and Cochran (1980) propose
the following approach:  (1) compute n0
using Equation 12-1; (2) round n0 up to
the next highest integer,/; and (3)
multiply n0 by (f+3)/(f+l) to derive the
final estimate of n.

To compare the mean from two random
samples to detect a change of <5; i.e.,
\2-~Xi, the following equation is used:

      Equation 12-2.
Common values of (Za + Z2p)2 are
summarized in Table 12-2. To account
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     12-5

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    Table 12-2. Common values of (Za + Z^)2 for estimating sample size for use with Equations 12-1
    and 12-2 (Snedecorand Cochran 1980).
Power,
1-/7
0.80
0.85
0.90
0.95
0.99
crfor One-sided Test
0.01
10.04
11.31
13.02
15.77
21.65
0.05
6.18
7.19
8.56
10.82
15.77
0.10
4.51
5.37
6.57
8.56
13.02
crfor Two-sided Test
0.01
11.68
13.05
14.88
17.81
24.03
0.05
7.85
8.98
10.51
12.99
18.37
0.10
6.18
7.19
8.56
10.82
15.77
   for Si and s2 being estimated, Z should
   be replaced with t. In lieu of an iterative
   calculation, Snedecor and Cochran
   (1980) propose the following approach:
   (1) compute n0 using Equation 12-2; (2)
   round n0 up to the next highest integer,
   /; and (3) multiply n0 by (f+3)/(f+l) to
   derive the final estimate of n.

   A special case of Equation 12-2 arises for
   biocriteria, when we compare the mean
   of a sample to determine if the value is
   below some set limit, that is, if the site is
   impaired or below a reference threshold.
   The threshold is fixed by previous
   investigations and decisions, and is not
   a random variable.  We ask now
   whether we can detect a change of d;
   i.e., G-XJ, where C is the biocriteria limit:
        Equation 12-3.
        «„=
                       82
   In Equation 12-3, Za is most often one-
   tailed, because the concern is only
   whether the value is below the
   threshold.

   Sample Size Calculations for Means and
                Proportions

   For large sample sizes or samples that
   are normally distributed, symmetric
   confidence intervals for the mean are
   appropriate. This is because the
   distribution of the sample mean will
   approach a normal distribution even if
   the data from which the mean is
 estimated are not normally distributed.
 The Student's t statistic (ia/2/n i) is used
 to compute symmetric confidence
 intervals for the population mean, |_l:

                  Equation 12-4.
    x-t_
                        •a/2,/1-1
 This equation is appropriate if the
 samples are normally distributed or the
 sample size is greater than 30
 (Wonnacott and Wonnacott 1969),
 although Helsel and Hirsch (1992)
 suggest that highly skewed data might
 require more than 100 observations.

 Although several approaches exist to
 estimate confidence levels for any
 percentile, many rely on assuming a
 normal or lognormal distribution. The
 approach presented here (Conover
 1980) for more than 20 observations
 does not rely on these assumptions.
 Conover (1980) also provides a
 procedure for smaller sample sizes. To
 calculate the confidence interval
 corresponding to the median, lower
 quartile, or upper quartile, the following
 procedure is used.

 1.  Order the data from smallest to
    largest observation such that
12-6
Quality Assurance: Design, Precision and Management

-------
   where xp corresponds to the median; i.e.,
   p=0.5, lower quartile; i.e., p=0.25, or
   upper quartile; i.e., p=0.75.

   2.  Compute the values of r and s as

       Equation 12-5.
       where Za/2 is selected from a normal
       distribution table.

   3.  Round r and s* up to the next
       highest integers r and s. The 1-CC
       lower and upper confidence limits
       for xp are xt and xs, respectively.

   It can be seen from Equation 12-5 that
   estimation of medians or quartiles from
   small samples can result in large
   confidence intervals for the estimate.
   For example, the 90% confidence
   interval for the lower quartile of a
   sample of n=10 covers the first 5
   observations. A sample of less than 10
   observations would have a confidence
   interval extending below the smallest
   observation. This is the reasoning
   behind a general 'rule of thumb"that
   estimation of reference conditions
   should be based on a sample of 10 or
   more sites, if at all possible. Figure 12-2
   gives example sample size calculations
   for comparing proportions and
   population means.

   12.2  Management

   12.2.1 Personnel

   Trained and experienced biologists
   should be available to provide thorough
   evaluations, provide support for various
   activities, and serve as QC checks. They
   should have training and experience
   commensurate with the needs of the
   program.  At least one staff member
   should be familiar with establishing a
   QA framework. QA programs should
document personnel responsibilities
and duties and clearly delineate project
organization and lines of communica-
tion (USEPA 1998a). A time line
illustrating completion dates for major
project milestones or other tasks can be
a tremendously useful tool to track
project organization and progress.

12.2.2 Resources

Laboratory facilities, adequate field
equipment, supplies, and services
should be in place and operationally
consistent with the designed purposes
of the program so that high-quality
environmental data can be generated
and processed in an efficient and  cost-
effective manner (USEPA 1992).
Adequate taxonomic references and
scientific literature  should be available
to support laboratory work, data
processing, and interpretation.

12.3  Operational Quality
       Control

Protocols should be developed for
designing a data base and for screening,
archiving, and documenting data. Data
screening identifies questionable  data
based on expected values and obvious
outliers. Screening is especially
important if data are gathered from a
variety of sources and the original
investigators and data sheets are no
longer available. Figure 12-3 defines the
qualitative and quantitative data
characteristics that  are most often used
to describe data quality.

These measurement quality indicators
require a priori consideration and
definition before the data collection
begins.  Taken collectively, they provide
a summary characterization of the data
quality needed for a particular
environmental decision. Duplication of
approximately 10% of the total
sampling effort is a common level for
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     12-7

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    Example 1—Sample size calculation for comparing proportions

    To detect a difference in proportions of 0.20 with a two-sided test, a equal
    to 0.05, '/-p equal to 0.90, and an estimate of p1 and p2 equal to 0.4 and 0.6,
    n0 is computed from Equation 12-1 as
"o  =
                  [(0.4)(0.6) + (0.6)(0.4)]  =
                        (0.6 - 0.4)2
    Rounding 126.1 to the next highest integer, f is equal to 127, and n is
    computed as 126.1 x 130/128 or 128.1.  Therefore 129 samples in each
    random sample, or 258 total samples, are  needed to detect a difference in
    proportions of 0.2. Since these are proportions, the result means that the
    total count in the sample must be at least 129.  For example, to detectthe
    above difference in the proportion of dominant taxon (e.g., benthic
    macroinvertebrates or fish) of two sites,  at least 129 individuals must be
    counted and identified in each estuary.

    The example illustrates that a statistically significant difference can be easily
    detected in  proportions if sufficient individuals are sampled. However, it is
    doubtful that a difference between 40% and 60%  in dominant taxon is
    biologically  meaningful.

    Example 2—Sample size calculation for comparing population mean
    abundance

    To detect a difference of 20 in mean abundance with a two-sided test. The
    standard deviation, s, was estimated  as  30 for both samples based on
    previous studies; a was selected as 0.05; and 1-$ was selected as 0.90.
    Substituting these  values into Equation 12-2 yields
     n0 =  10.51
                  (302 + 302)
                            =  47.3
                      202
    Rounding 47.3 to the next highest integer, f is equal to 48,
    and n is computed as 47.3 x 51/49 or 49.2.  Therefore 50
    samples in each random  sample, or 100 total samples, are
    needed to detect a difference of 20.
                                                                      Figure 12-2
                                                                      Example
                                                                      sample size
                                                                      calculations for
                                                                      comparing
                                                                      proportions
                                                                      and population
                                                                      means.
   operational QC Replication of samples
   at a randomly selected subset of field
   sites (usually, 10 percent of the total
   number is considered appropriate) is
   used to estimate precision, and
   representativeness of the samples and
   the methods. Splitting samples into
   subsamples can be used to check
   precision of the methodology, and
   reprocessing of finished samples is used
   to check accuracy of laboratory
   operations.
                                          12.3.1 Field Operations

                                          For the field operations aspect of an
                                          ecological study, the major QC elements
                                          are: instrument calibration and
                                          maintenance, crew training and
                                          evaluation, field equipment, sample
                                          handling, and additional effort checks.
                                          The potential errors in field operations
                                          range from personnel deficiencies to
                                          equipment problems. Field notes are
                                          integral to the documentation of
12-8
                                         Quality Assurance: Design, Precision and Management

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    Figure 12-3
    Six qualitative and
    quantitative data
    characteristics
    usually employed
    to describe data
    quality.
Precision - The level of agreement among repeated
measurements ofthe same characteristic.

Accuracy - The level of agreement between the true and the
measured value, where the divergence between the two is
referred to as bias.

Representativeness - The degree to which the collected data
accurately reflect the true system or population.

Completeness - The amount of data collected compared to the
amount expected  under ideal conditions.

Comparability - The degree to which data from one source can be
compared to other, similar sources.

Measurability- The degree to which measured data exceed the
detection  limits  ofthe analytical methodologies employed; often a
function ofthe sensitivity of instrumentation.
   activities and can be a potential error
   source if incorrect recording occurs.
   Training is one of the most important
   QC elements for field operations.
   Establishment and maintenance of a
   voucher specimen collection should be
   considered for biological data.
   Transcription errors during data entry
   can be reduced with double data entry.
   Table 12-3 gives examples of QC
   elements for field and laboratory
   activities.

   12.3.2 Laboratory Operations

   The QC elements in laboratory
   operations include sorting and
   verification, taxonomy, duplicate
   processing, archival procedures,
   training, and data handling. Potential
   error sources associated with sample
   processing are best controlled by staff
   training. Controlling taxonomic error
   requires well-trained staff with expertise
   to verify identifications. Counting error
   and sorting efficiency are usually the
   most prominent error considerations;
   they can be controlled by training and
   by duplicate processing, sorting, and
   verification procedures.
                    12.3.3 Data Analysis

                    Errors can occur if inappropriate
                    statistics are used to analyze the data.
                    Undetected errors in the data base or
                    programming can be disastrous to
                    interpretation.  Problems in managing
                    the data base can occur if steps are not
                    taken to oversee the data handling,
                    analysis, and summarization.  The use
                    of standardized computer software for
                    data base management and data
                    analysis can minimize errors associated
                    with tabulation and statistical analysis.
                    A final consideration is the possible
                    misinterpretation of the findings. These
                    potential errors are best controlled by
                    qualified staff and adequate training.

                    12.3.4 Reporting

                    QC in reporting includes training, peer
                    review, and the use of a technical editor
                    and standard formats. The use of
                    obscure language can often mislead the
                    reader. Peer review and review by a
                    technical editor are essential to the
                    development of a sound scientific
                    document.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                          12-9

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   Table 12-3 Example QC elements for field and laboratory activities
Project Activity
Field Sampling
Physical Habitat
Assessment
(Qualitative)
Physical Habitat
Assessment
(Quantitative)
Laboratory:
Sample Sorting
Laboratory:
Sample
Tracking
Laboratory:
Taxonomic
Identification
Data
Management
Data Analysis
QC Element
Replicated samples at 10% of
sites by same field crew.
Replicated samples at one to
two of total sites by different
field crew using same methods.
Ensure appropriate training and
experience of operators;
multiple observers.
Replicated measurements at
10% of sites.
Sample residue checked for
missed specimens to estimate
sorting efficiency; check
completed by separate lab staff.
Logbook with record of all
sample information.
Independent identification
and/or verification by specialist;
ensure appropriate and current
taxonomic literature available;
adequate training and
experience in invertebrate
identifications; reference
collection; exchange selected
samples/specimens between
taxonomists.
Proofreading; accuracy of
transcription.
Hand-check of reduced data.
Appropriate statistics; training.
Evaluation Mechanism
Calculate relative percent difference
(RPD) of index value or individual metric
score
Calculate RPDs as above; use to
evaluate consistency and bias.
Resume or other documentation of
experience; discuss and resolve
differences in interpretation.
Calculate RPDs between replicate
measurements; compare to
preestablished precision objectives.
Calculate percent recovery; compare to
preestablished goals.
Not applicable.
Calculate percent error; compare to
preestablished goals.
All transcribed data entries compared by
hand to previous form — handwritten raw
data, previously computer-generated
tables, or data reports.
For computer-assisted data reduction,
approximately 10% of reduced data
recalculated by hand from raw data to
ensure integrity of computer algorithm.
Review by statistician or personnel with
statistical training.
12-10
Quality Assurance: Design, Precision and Management

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    Case Study: Optimization of Benthic Sampling Protocols: gear, mesh size,
    replicates

    Ferraro et al. (1994) studied the cost-effectiveness of several alternative marine
    benthic sampling protocols, including sampling gear, mesh size (0.5-mm or 1.0-
    mm), and number of replicates (1-10), in southern California waters.  Alternative
    sampling gear was:

    •      0.1-m2 van Veen grab
    •      0.06-m2 van Veen grab
    •      0.1-m2 van Veen grab subsampled by 1-6 core samples, 50-300-cm2 total
           area subsampled.

    Laboratory processing time was recorded for each sampling alternative. Twelve
    measures of community structure were examined.  Results showed that the power
    of detecting differences between sites did not increase greatly for more than 4
    replicates. Optimum cost-effectiveness was achieved with 5 core subsamples
    (250-cm2) of 0.1-m2 grabs, replicated 4 times at each site (Ferraro et al. 1994).

    Case Study: Optimization of Benthic Sampling: Seasonal sampling, trend
    detection

    Alden et al. (1997) examined  seasonal and annual trends in estuarine benthic
    macroinvertebrates community measures (diversity, total abundance, biomass, %
    opportunities).  Samples were taken seasonally (4 x per year) from 16 Chesapeake
    Bay sites for 9 years.  Long-term trends were examined by season, and the power
    of detecting trends was examined for alternative sampling frequencies of 1
    season, 2 seasons, or 4 seasons per year. Finally, reference and impaired sites
    were compared among seasons to determine if some seasons yield greater power
    of detection of impairment than other seasons.

    Trends in indicator values were apparent and detectable in all seasons. Although
    4-season sampling yielded the greatest power of trend detection, it was only
    marginally better than 2-season sampling and 1 season sampling. In general,
    summer sampling was most  sensitive and yielded the greatest power, allowing
    detection of trends of 4%-7%  change per year in abundance, diversity, and %
    opportunist metrics over the  9 year period. Biomass was much more variable: the
    minimum detectable trend was approximately 20% change per year for summer-
    only sampling (Alden et al. 1997).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance             12-11

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 Chapter 13
 Case Studies
   In conjunction with the drafting of this
   guidance manual, the USEPA Biocriteria
   Program has also supported or assisted
   in the support of projects around the
   country to evaluate estuarine and
   coastal marine survey methods and to
   develop metrics appropriate for use in
   different settings. These studies were
   conducted prior to the creation of this
   guidance document. Each case study
   exemplifies a section within the
   guidance. This chapter summarizes
   studies conducted in the Pacific
   Northwest, Gulf of Mexico, and along
   the Middle and South Atlantic coasts.

   Some of the material presented here also
   appears in the body of this text and the
   information which follows expands on
   that discussion.  Further, the principal
   investigators or  other contact in each
   instance are listed with their addresses
   and phone numbers should the reader
   desire to comment or request more
   information.

   13.1   PugetSound -
          Development of Trawl-
          Based  Tools For the
          Assessment of Demersal
          Fauna
          (Macro!nvertebrates and
          Fishes): A Puget Sound
          Pilot Study

   The relationship between pollution and
   the health and status of marine benthos
   are being studied in the Puget Sound
   region of Washington state (Figure 13-1).
   Detailed sediment data, including
   information on chemistry, toxicity and
   inf aunal populations, are being collected
   for the Puget Sound Ambient
Monitoring Program (PSAMP) as well as
for various urban bay, dredge disposal,
and Superfund action programs.  The
PSAMP has quantitatively defined
population patterns of demersal fishes,
but has not defined those patterns for
other demersal fauna such as
macroinvertebrates.  Nor  has any
program developed data to explain how
the fauna are responding to the
environmental stresses associated with a
contaminated substrate.

13.1.1 Study Objectives

The Puget Sound study (Eaton and
Dinnel 1993, Eaton 1994,1995) was
initiated in 1993 to document demersal
populations in their entirety, and to
attempt to relate the resulting biological
information to sediment chemistry,
toxicity, and infauna. The pilot study,
funded by USEPA, began by assessing
the utility of using two different trawls
to quantitatively define demersal
populations at a given point in time.
Using the resulting documented
population patterns and comparisons
between reference and  contaminated
areas, the study objectives were
ultimately to:

*•  Gain a greater understanding of how
   demersal populations are being
   affected by pollution and habitat
   degradation;

*•  Determine which patterns reflect
   environmental stress;

*•  Develop metrics (biological
   measures) which would help to
   build a biological index for the rapid
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-1

-------
      Figure 13-1
      General
      location of the
      case studies.
                                                                          Delaware Bay
                                                                          - Ocean City
                                                                        North
                                                                        Carolina
                                                                      Indian River
       and economical assessment of stress
       in subtidal biotic marine
       communities.

   13.1.2 Study Methods

   Beam and otter trawls were used to
   sample Puget Sound demersal fauna in
   1993 and 1994.  A 3-m beam trawl (with
   a  tickler  chain attached in front of the
   net) towed at 1.5 knots proved to be
   very effective for sampling most
   demersal invertebrates and small or
   juvenile fishes. A 7.6-m Southern
   California Coastal Water Research
   Project otter trawl, towed at 2.5 knots,
   was best suited for sampling larger and
   more mobile marine fishes and
   invertebrates. All trawl catches were
   held in tubs of running seawater
   following capture, and fauna were
   subsequently sorted, identified,
   counted, measured and weighed. All
   organisms were released on station.

   In the first year of the pilot study (1993)
   sampling focused on two of the Tacoma
   Waterways, the contaminated Hylebos
   Waterway (a Superfund site) and the
   adjacent, less-impacted Blair Waterway.
   Sampling in 1994 compared another
   Tacoma Waterway and Superfund site,
   Thea Foss (City) Waterway, with a
   cleaner and more natural reference
condition (six miles to the north) in
Quartermaster Harbor on Vashon
Island. Bottom depth, sediment grain-
size analysis (either historical
information or wet-sieving technique for
percent fines), bottom temperature, and
salinity data were recorded for all
stations to insure meaningful pairing of
sites.

Spatial coverage of the study area was
determined using a stratified random
design. The Hylebos and Blair
Waterways were divided into four
strata, the Thea Foss into three strata,
and Quartermaster Harbor into two.
One station was located in each stratum,
except in mid-Quartermaster Harbor
with two stations    one being an
historical sediment monitoring station.
A second station was placed in the mid-
Quartermaster Harbor stratum to
compare the variability in results
between two stations of close proximity
with similar depth and sediment grain-
size.

Evaluation of ten consecutive and seven
non-consecutive otter trawl replications
in 1993 led to the conclusion that four or
five otter trawl replications were needed
to quantitatively define the demersal
fish community at a given station, and
that the replications should not recur in
13-2
                               Case Studies

-------
   less than four hours. The 1994 sampling
   design incorporated these
   recommendations, utilizing a sampling
   effort of five otter trawl and three beam
   trawl replications per station.

   The extensive data set resulting from the
   trawl surveys was entered into
   computer spreadsheets as catch files,
   and was sorted and statistically
   analyzed for patterns and relationships.
   The null hypothesis for the pilot study
   was that the contaminated and non-
   contaminated sites were not
   significantly different for the parameters
   measured (i.e., fish abundance, biomass,
   mean individual weights, diversity and
   evenness). Data comparisons were
   tested for statistical significance using
   either a parametric test (i.e., Student's
   two-tailed, two-sample t-test either
   paired or independent) or a non-
   parametric test (i.e., two-sample
   Kolmogorov-Smirnov Test) depending
   on the outcome of the test for normality
   (i.e., one-sample Kolmogorov-Smirnov
   normality test). Species diversity was
   calculated using the Shannon-Wiener
   Index (H') with the natural logarithm,
   although simple species richness
   measurements proved  to be more
   statistically significant. Species
   evenness was measured with Pielou's
   evenness index (J) and number of
   species >90% of total abundance.
   Dominance was measured using the
   dominance ratio, Nmax / N, where Nmax =
   number of individuals  of the most
   abundant species, and  N is the total
   catch.

   13.1.3  Study Results

   Pilot study results focused on a
   comparison of the reference and
   contaminated stations which showed
   the best match of environmental
   parameters. Reference station QMH1 in
   upper Quartermaster Harbor and
   contaminated station TF1 in the upper
   end of the Thea Foss Waterway proved
to be very similar in depth, sediment
grain size, bottom temperature and
salinity. A comparison of catch data for
the two stations indicated that fish
abundance in the reference area was
actually lower compared to that found
at the contaminated Superfund site
(Figure 13-2a), whereas fish biomass was
significantly greater at the reference site
(Figure 13-2b).  This finding indicated
that the individual fishes at the reference
site must be considerably larger than
those found at the contaminated site,
and/ or that sensitive fish species found
at the reference site but not at the
contaminated site tended to be much
larger than the other fish. Both factors
contributed to the differences. Eight of
the thirteen fish and invertebrate species
common to both sites showed
significantly greater mean individual
weights at the reference stations, and of
the remaining five, only one species was
consistently larger at the contaminated
sites (Figure 13-2c).  Also the
cartilaginous fishes (i.e. spiny dogfish,
spotted ratfish, and the skates),
tentatively classified as sensitive species,
were only rarely encountered in the
contaminated waterways and were very
large compared to the bony fishes.

A preliminary list of tolerant and
sensitive fish and invertebrate species
was generated for the Tacoma
waterways and Quartermaster Harbor
fauna based on the pilot study results
(Table 13-1). Tolerant species were
defined as those whose relative
abundance at contaminated sites is
significantly greater than or
indistinguishable from those species
found at comparable reference sites (i.e.,
site of comparable depth, salinity,
dissolved oxygen, sediment grain-size,
slope, and density of structures such as
eel grass).  Sensitive (intolerant) species,
on the  other hand, were defined as those
species whose relative abundance is
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     13-3

-------
Figure 13-2a
Bony fish
abundance
and total fish
abundance for
reference and
contaminated
sites.
 Bony Fish Abundance and Total Fish Abundance for Reference
              (QMH) and Contaminated (TF) Sites
25.0
                                                                     D Bony Fish (Osteichthyes)
                                                                       Abundance
                                                                     H Bony plus Cartilaginous
                                                                       Fish Abundance
                          0.0
                              QMH QMH QMH QMH QMH
                               1.1   1.2   1.3   1.4   1.5
                                     REFERENCE
                                                 Station and Replication
                                              TF
                                              1-3   1.4   1.5
                                             CONTAMINATED
Figure 13-2b
Bony fish
biomass and
total fish
biomass for
reference and
contaminated
sites.
 Bony Fish Biomass and Total Fish Biomass for Reference (QMH)
                  and Contaminated (TF) Sites
                                                                  D Bony Fish (Osteichtheys)
                                                                    Biomass
                                                                  D Bony plus Cartilaginous Fish
                                                                    Biomass
                     0.0
                         QMH  QMH  QMH  QMH  QMH
                          1-1    1.2   1.3    1.4    1.5
                                   TF
                                   1.1
                                    REFERENCE
                                              Station and Replication
TF    TF    TF
1-2    1.3    1.4
   CONTAMINATED
   13-4
                                                            Case Studies

-------



Mean Individual Weights of Fish Species from Contaminated (TF) and
Reference (QMH) Stations
0.40-
0.35-
^ 0.30-
£ 0.25-
D)
| 0.20-
§, 0.15-
5
SJ 0.10-
0.05-
0.00-
^--"
^-'
,^^"
^-'
_-^-
^-^
^"
.,...-£
^








rV

D Contaminated Stations (TF)
D Reference Stations (QMH)



3^



a_


=a-
1
hi


1
I


i
fli S O T3 ° O
a. •§ E TJ w w
ai ^ i_ TO w) o
c .y HI w =j o
5 aJ
-
pi


N3
L_


3
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S f^
<{






ft
oi a* o) ' c '
? 5 I |
° c 1 "
£,<"—£
                                                                   Figure 13-2c
                                                                   Mean
                                                                   individual
                                                                   weights offish
                                                                   species from
                                                                   contaminated
                                                                   and reference
                                                                   stations.
   significantly greater from a reference
   area than from a comparable
   contaminated site.

   The sensitive species index, derived
   from the proportion of sensitive species
   abundance or biomass to the total of
   sensitive plus tolerant species, was
   applied to the pilot study catch data.
   Index results showed significant
   differences for all comparisons (i.e., fish
   abundance and biomass, and fish plus
   invertebrate abundance and biomass
   between contaminated and reference
   sites).  The results suggested that such
   an index, if tested independently for
   annual and seasonal variation, could be
   very useful in tracking recovery of an
   area after cleanup or remediation, or to
   help classify impacted sites relative to
   the benchmarks established through the
   biocriteria.

   Pilot study results also indicated that
   fish species richness and fish species
   evenness were useful measurements in
   the site discrimination process.

   Although no difference was found in
   species richness using the beam trawl
   sampling method, otter trawl catches
indicated that fish species richness was
notably greater at the reference site (16
species) than at the contaminated station
(11 species). When statistically
examined on a trawl-by-trawl basis (i.e.,
using the mean number of fish species
per sample), fish species richness was
significantly greater at the reference
stations.  Fish species evenness, as
measured by the number of fish species
>90% of total abundance, was also
significantly higher at the reference
stations, both when paired with the
Thea Foss stations, and when compared
as a whole. External abnormalities or
anomalies, such as fin erosion or skin
tumors, were extremely rare at all
stations during both study years,
thereby suggesting that it may not be a
useful indicator of environmental stress.

The results of the first year of sampling
indicated that raw or averaged
abundance data were not useful in
differentiating contaminated and
reference sites.  This discovery led to an
increased effort in recording biomass
data during the second study year, and
to the inclusion of a more natural
reference condition.  Results of the
second year of sampling emphasized the
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    Table 13-1. A preliminary list of tolerant and sensitive fish and invertebrate species from the Tacoma
    Waterways and Quartermaster Harbor.
FISH
Tolerant Species
English sole
Sand sole
Flathead sole
Pacific tomcod
Shiner surfperch
Snake prickleback
Pacific staghorn sculpin





Sensitive Species
Spiny dogfish
Spotted ratfish
Longnose skate
Rock sole
Starry flounder
Speckled sanddab
Pile surfperch
Striped surfperch
Bay goby
Blackbelly eelpout
Bay pipefish
Plainfin midshipman
INVERTEBRATE
Pandalus danae: coonstripe shrimp
Crangon spp.: sand shrimp

Cancer gracilis'. purple cancer crab

Cancer productus: red rock crab

Cancer magister. Dungeness crab
Lophopanopeus bellus'. crab
Evasterias troschelli'. mottled seastar
Metridium senile', plume anemone
Cucumaria miniata: sea cucumber
Cucumaria piperata: spotted sea
cucumber
Pentamera populifera'. crescent sea
cucumber
Parastichopus californica: edible sea
cucumber
So/aster stimpsoni'. sunstar
Pagurus spp.'. hermit crabs
Nassarius mendicus'. snail

   ecologically important fact that the
   reference sites, despite fewer or equal
   numbers of fishes, supported more than
   twice the fish biomass than the
   contaminated site. Almost every fish
   species common to both areas was
   significantly larger, and fish species
   richness and evenness were significantly
   higher at the reference site.

   The sensitive species index proved to be
   useful in differentiating sites. The
   identification of sensitive (intolerant)
   and tolerant demersal marine species is
   in its infancy, due in part to the paucity
   of data on demersal  marine
   communities and the lack of
   quantitative  sampling methods. With
   the development of these sampling
   techniques, the pilot study
   demonstrated that information on the
   demersal fauna should  be included in
any future ecologically-based indexes of
pollution. Candidate attributes of
demersal fauna which warrant further
study are listed in Table 13-2.

Primary Contact: Charles Eaton
Bio-Marine Sciences
2717 3rd Ave. N
Seattle, WA 98109
206-282-4945
13-6
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    Table 13-2.  Candidate attributes of demersal fauna showing significant differences in the present study.
Candidate Metrics
Total Fish Abundance per
100 m2, 4-6 m. Depth.
(10-15 m. — no difference).
Total Fish Biomass per 100
m2
Fish Species Richness
(Number of fish species)
Fish Species Evenness
(Number of Fish Species >
90% of Total Abundance)
Mean Individual Weight
and Size of all Species
(except Pacific Herring and
Staghorn Sculpin)
Tolerant Species
Abundance and Biomass
(English Sole, Pacific
Staghorn Sculpin, Pacific
Tomcod, Shiner Surfperch,
Snake Prickleback, Purple
Crab, Mottled Seastar, Plum
Anemone)
Sensitive Species
Abundance and Biomass
(Bay Goby, Starry Flounder,
Rock Sole, Cartilaginous
Fish, Sea Cucumbers)
Sensitive Species Index
(proportion of sensitive to
sensitive + tolerant)
Preliminary
Expectation
from Present
Study:
IMPAIRED SITE
Elevated or no
difference
Reduced
Reduced
Reduced
Reduced
Elevated or (in
some cases) no
difference
Reduced
Reduced
Range of Values (and
mean) from Present
Pilot Study: IMPAIRED
SITE: Thea Foss Wty.
TF 1: 20.6 to 22.7
mean = 21.4
0.54 to 0.97 kg (mean =
0.73)
per tow: 6-13
cumulative:10-14
3-6 (mean = 3.7)
e.g. English Sole 45 to
114 g (mean = 75 g.)
e.g. English Sole
2.8-10.1 (5.3) per 100m2
e.g. juv. Tomcod
0.39 to 9.87 (7.3)
e.g. Purple Crab
4.7 to 56.0 (22.8)
e.g. Bay Goby 0.4 to 3.9
(1.7) per 100m2
e.g. Cucumaria piperata
Zero
0.016 to 0.098 mean =
0.049
Range of Values (and
mean) from Present
Pilot Study:
REFERENCE SITE:
QM Hbr.
QMH 1:
8. 3 to 14.2
mean = 11.9
0.81 to 4.82 kg (mean =
2.64)
per tow: 11-18
cumulative: 15-1 8
4-7 (mean = 5.2)
e.g. English Sole 125 to
484 g. (mean=204 g.)
e.g. English Sole 0.2 to
6.1 (2.3) per 100m2
e.g. juv. Tomcod 0 to
0.69(0.4)
e.g. Purple Crab 0.0 to
6.3(2.7)
e.g. Bay Goby 28.6-
41. 9 (36.5) per 100m2
e.g. Cucumaria piperata
0.0to5.9(2.5)
0.075 to 0.787 mean =
0.357
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   13.2  Galveston Bay -
          Development of a
          Rapid Bioassessment
          Method and Index of
          Biotic Integrity For
          Coastal Environments:
          Northwestern Gulf of
          Mexico Pilot Studies

   13.2.1  Study Objectives

   A study was conducted on selected
   streams and bayous within Galveston
   Bay, Texas (Figure 13-1) coastal
   ecosystems, in order to characterize the
   expected fish assemblages of various
   types of waterbodies (with varying
   water and habitat quality) (Guillen
   1995a).  A second study objective was to
   develop a prototype rapid
   bioassessment technique similar to the
   Index of Biotic Integrity for the
   northwestern Gulf of Mexico.  In order
   to meet the second objective, several
   criteria for the development of the
   method had to be met. First, the method
   had to be ecologically relevant, that is
   any metric or ranking system had to
   directly relate to ecological function and
   structure. Secondly, the method had to
   be taxonomically simple or kept to the
   broadest taxonomic/functional group of
   organisms that provide the most
   information. The methods also had to
   be simple (in terms of equipment, labor,
   and analysis) cost effective, easily
   standardized, subject to easy replication,
   and adaptable to a variety of
   environments.

   13.2.2 Study Methods

   The sampling design consisted of five
   bayous classified according to  the
   potential for anthropogenic impact; i.e.,
   urban versus rural, impaired versus
   unimpaired and salinity effects; i.e.,
   lower portions of tributaries versus
upper portions.  Oyster Bayou,
Dickinson Bayou, Texas City Hurricane
Canal, Highland Bayou Diversionary
Canal, and Cedar Lakes Creek were
selected to fulfill these criteria. Oyster
Bayou is a minimally impaired coastal
bayou located in the middle portion of
Galveston Bay and flowing south to East
Bay. Oyster Bayou stations were
characterized by a silty clay substrate.
The moderately impaired Dickinson
Bayou is located in the northeastern
portion of Galveston County. Dickinson
Bayou is characterized by sandy to silty
clay substrates and is impaired by both
point and nonpoint sources. The Texas
City Hurricane Canal is an industrial
canal that flows into the Texas City ship
channel, and receives industrial and
stormwater discharges.  The majority of
the canal banks  possess a steep slope,
and little bank vegetation, and the
southern shoreline is an artificial levee.
The Highland Bayou Diversionary
Canal is an artificial  waterbody created
by the Army Corps of Engineers in 1983.
The canal was created by channelization
of the upper reach of Highland Bayou
proper and construction of an earthen
dam directly below the channelized
portion, in order to reroute water
through a dredged canal into Jones Bay.
The canal is tidally influenced and
receives effluent discharge from
municipal wastewater treatment plants
and runoff from surrounding
agricultural grazing  and pasture lands.
Cedar Lake Creek is a minimally
impaired rural bayou which extends 24-
miles from its origin at the intersection
of Cedar Lakes to the Gulf Intracoastal
Canal. There are no active discharges in
the watershed, however, an oilfield is
present at its upper reaches.
Predominant land use in the area is
cattle grazing and the San Bernard
Wildlife Refuge.

To summarize, two minimally impaired
bayous (Oyster Bayou and Cedar Lakes
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-9

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   Creek) and three impaired waterbodies
   (Highland Bayou Diversionary Canal,
   Texas City Hurricane Canal and
   Dickinson Bayou) were surveyed during
   the study period.  The impaired sites
   included two that were influenced by
   residential and municipal wastewater,
   and one effected by industrial effluent.
   Two of the waterbodies were highly
   channelized and/or man-made. Site
   investigations involved seasonal
   quarterly surveys made at all stations
   within each watershed. Sampling was
   conducted during summer, fall, and
   winter 1991; spring and summer 1992;
   and winter, spring, summer, and fall
   1993.

   In order to evaluate the relationship
   between water quality and fish
   communities, various hydrological,
   habitat, and biological data were
   collected concurrently. Qualitative
   habitat measurements including
   primary and secondary tributary depth,
   width, substrate type, and shoreline
   vegetation were noted at each station.  A
   rapid field method for the evaluation of
   percent sand in sediments was also used
   to evaluate effects of sediment size on
   nekton populations. Measurements of
   surface and bottom temperature,
   dissolved oxygen, conductivity, salinity
   and pH were made. Surface water
   samples were also collected for the
   determination of total organic carbon,
   fecal coliforms, total and
   orthophosphate, nitrates, total ammonia,
   total suspended solids, and chlorophyll
   a. Individual water chemistry and
   habitat values were plotted against
   seasons and stations to evaluate
   temporal and spatial patterns.

   In addition, Pearson's correlation
   coefficients and stepwise and direct
   discriminant analyses were used to
   determine the relationship between the
   variables and clustered groupings of
   stations.  The analyses provided another
tool for investigators to evaluate the
relative influence of physicochemical
variables on coastal nekton
communities. Survey results showed
that the majority of water quality
variables were within previously
documented tolerance limits of estuarine
fish.

Nekton (fish and macrocrustacea) were
collected using experimental gillnets,
trawls, and seines.  Gillnets were 200 x
8-ft experimental monofilament nets
with eight panels of varying mesh sizes
(0.5-4-in mesh). Seine collections (five
replicates of 25-ft hauls) were made
using a 15 x 4-ft common minnow seine
with 1/8-in square mesh nylon netting.
Trawls were made  at main channel
stations in each watershed, using a 10-ft
otter trawl with 1-in mesh in the wings
and 1/4-in mesh in the cod end. Four
replicate trawls (five minute tows, each)
were made at each  of the mainstream
stations.  Nekton collected via all
sampling methods  were identified to the
lowest possible taxon, enumerated, and
measured.

13.2.3 Study Results

Several biological metrics were
considered during  the pilot study based
on historical usage and recent
recommendations in the literature.
Community metrics generated from
pilot study data included:  total catch,
log-transformed total catch, number of
nekton taxa, Shannon-Wiener diversity
index, Pielou evenness index, total
number of taxa making up 90% of the
catch, dominance ratio (ratio of most
abundant species/total catch), number
of crustacean species; number of
"bottom taxa"; i.e., sciaenids, flatfish,
blue catfish; number of predatory
species; number of "minnow" taxa; i.e.,
Poeciliids and/or cyprinodonts; number
of goby taxa; proportion of total catch as
bay anchovy; proportion of total catch as
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                              Case Studies

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   "shad"; i.e., clupeids and engraulids,
   proportion of total catch as poeciliids;
   proportion of total catch as Penaeid
   shrimp; and proportion of total catch as
   palaemonid shrimp; i.e., grass shrimp.
   The rationale for each proposed metric is
   provided in Table 13-3.

   Trawl, seine, and gill net results were
   utilized in a cluster analysis, and then
   subjected to stepwise discriminant
   analyses. Observed seasonal and spatial
   patterns and/or temperature and
   salinity related correlations were used to
   determine whether seasonal or salinity-
   adjusted metrics were needed.  In
   addition, the decision to include data
   from "impaired" sites in the derivation
   of metrics was also evaluated using
   these analyses. If initial statistical
   analyses failed to show differences
   between the reference sites and
   impaired sites, then all sites were pooled
   for derivation of metrics.

   Due to the strong seasonal and/or
   spatial trends observed in various
   metrics using the seine data, cumulative
   percent distributions of each candidate
   metric were calculated by season for
   minimally impaired watersheds.
   Results of the distributions are
   presented in Table 13-4.  Metrics were
   adjusted where distributions indicated
   truncated values using the following
   approach. If the distribution line could
   be extended to the 15th or 85th percentile
   value without crossing the Y axis, then
   that estimated value was used. If it
   could not, the metric was not used
   during that season  and/or the metric
   rating was adjusted to reflect only two
   conditions (e.g., normal and excellent).
   This same procedure was used to derive
   a proposed metric system using trawl
   data (Table 13-5). A proposed list of
   prototype metrics using gillnet catch
   data was developed (Table 13-6);
   however, since gillnet design and
   deployment is variable, it may be
difficult to compare metrics derived
from the pilot study with other studies.
Pilot study results indicated that it
seems feasible that a prototype estuarine
bioassessment system based on nekton
community collections can be used to
successfully document impacts from
pollution. Analysis of potential metrics
through discriminant analysis, graphical
evaluation of cumulative distribution,
frequencies and correlation analyses
yielded the proposed metrics listed in
Tables 13-4,13-5 and 13-6. The
categories utilized in the framework of
the proposed system were based on the
following protocol.  Depending on the
metric, those values less than the 15th
percentile were categorized as "concern".
The interquartile values; i.e., 15-85'h
percentile were categorized as "normal",
and values exceeding the 85th percentile
were classified as "excellent". In some
cases where high metric values denoted
degraded conditions, the inverse of the
proposed scheme was used; i.e., <15'h
percentile = "excellent". The
classification system was based
primarily on statistical distributions of
the observed data. Where data was
insufficient, a "not recommended"
disclaimer was listed.

It was difficult to single out one water
quality variable as having the most
influence on community structure and
the proposed metrics. Therefore, a
conservative approach was taken by
grouping by season and utilizing all
data across various salinity levels.

The proposed Index of Biotic Integrity
(IBI) metrics derived from the  pilot
study would be most confidently
applied to situations where salinities
range from 1-25-ppt.  Continued
calibration of this system with
additional data sets is needed. The
proposed metrics need to be evaluated
against independent data sets  including
those in high (>25-ppt) salinity regimes.
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                                     13-11

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    Table 13-3. Rationale for the inclusion of proposed nekton community metrics.
               Metric
                          Rationale
     Total Catch
Total abundance is a rough measure of the total community
population and as such gives no information on individual species
population levels. Low abundances can be caused by various
stressors.  It should be noted that high abundances caused by
individual opportunistic species can also indicate a disturbed
community.
     Log Total Catch
Due to the inherent variability of populations, the patchiness of fish
schools  and previously observed distributions offish, many
ecologists feel that the log-normal distribution fits the distribution of
nekton populations better. Therefore log total catch may be a more
appropriate indicator of total population levels. In order to handle
zero catches, however, a log (catch + 1) transformation is needed.
     Total Number of Nekton Taxa
The species richness of any community is extremely important.
Reductions in species number may indicate an overall reduction in
available habitat or the presence of environmental stressors. This
may be due to the avoidance or death of sensitive species in an
area.  The number of taxa collected is a relatively economical
measure.  On a relative scale it is the cheapest information
obtainable from catch data.
     Cumulative Number of
     Nekton Taxa
The cumulative number of taxa is somewhat different than the total
number of taxa in that it reflects the upper limit of the number of
taxa one would expect to collect within a single replicate sample.
Large discrepancies between mean and cumulative number of
species may indicate high variability in habitat or distribution of
species. Like the total number of taxa metric a low cumulative
number of taxa can reflect limited habitat and/or the presence of
environmental stressors.
     Total Number of Fish Taxa
This metric is closely related to total nekton species numbers.
However, it was added to address situations where only fish data is
tabulated.
     Nekton Species Diversity
The Shannon-Wiener diversity function was selected to evaluate
nekton communities.  This commonly used function (H')was
developed to incorporate the two most important components of
diversity, namely richness and evenness. Species richness is
normally tabulated. However, species richness alone provides no
information on how evenly individuals are distributed  among
species.  The majority of communities studied by ecologists show a
log-normal  pattern of species abundance in which a relatively few
species possess a rather large number of individuals and a rather
large number of species possess few numbers of individuals.  A
diverse community is one in which species number and evenness
are maximized. One problem with the use of H' is the fact that
various combinations of species numbers and evenness can yield
the same answer. Therefore diversity indexes should only be
evaluated in the presence of species richness and  evenness.
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     Table 13-3 (Cont'd). Rationale forthe inclusion of proposed nekton community metrics.
               METRIC
                         RATIONALE
     Nekton Evenness
One factor that influences diversity directly is the evenness of the
distribution of organisms between species. Populations possessing
high numbers of taxa but with highly uneven distributions between
taxa (e.g. highly dominant taxa) may reflect underlying habitat
limitations, stressors or seasonal patterns. One of the most
popular indexes used by marine biologists is the Pielou's evenness
index (J).  This index is defined as:

J = H'/ln(S),
where H' is the Shannon-Weiner index,
In is the log base (e)
and S is equal to number of taxa

This index expresses H' relative to the maximum value that H' can
obtain when all of the species in the sample are perfectly even with
one individual per species.
     Number of Nekton Taxa =
     90% Catch
This index is the number of taxa that together add up to at least or
exceed 90% of the total catch. This is another measure of
evenness.  High values would indicate a community in which there
is no clear dominant taxa. This index is influenced by the same
factors which effect the evenness index.
      Nekton Dominance Ratio
This has also been referred to as the Berger-Parker index. This is
the ratio Nmax/N, where Nmax = number of individuals present in the
most abundant taxa, and N is the total catch. This equation is
computationally simple and can be easily programmed into
spreadsheets. In addition, it is intuitively easy to understand.  High
dominance reactions reflects dominance of the community by a few
individuals which relates to an uneven distribution of individuals
within taxa resulting in poor diversity. This may be related to
potential stressors and other factors cited under the discussion of
Pielou's evenness.
      Number of Crustacean
      Nekton Taxa
The number of crustacean taxa present in the nekton is largely a
function of 4 principle groups.  The first group are crab species
including blue crab, Callinectes sapidus. The second group
includes seasonally dominant groups of Penaeid shrimp which
migrate into tidal creeks and bayous as postlarva and juveniles.
The third group includes resident species of grass shrimp, genus
Palaemonetes.  The final group include freshwater prawns, genus
Macrobrachium, and crayfish genus Procambarus. The presence
of crustacean taxa indicates a  healthy population of benthic
herbivores and omnivores which serve as the primary food source
for many estuarine fish. In addition, crustaceans are especially
sensitive to organic pesticides.
      Number of Predatory Fish
      Taxa
Predatory fish were defined as fish in the family Carangidae,
Scombridae,  and the genera Paralichthys, Lepisosteus,
Micropterus, Cynoscion, Morone and the species Sciaenops
ocellatus, Synodus foetens and Elops saurus. These species
represent individuals at the top of the food chain. Impacts to other
species they  depend on may reduce these predators indirectly.  In
addition, through the process of biomagnification predators are
more likely to bioconcentrate high levels of pollutants found in the
lower portions of the food chain.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                             13-13

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     Table 13-3 (Cont'd). Rationale forthe inclusion of proposed nekton community metrics.
               METRIC
                         RATIONALE
     Number of "Minnow" Taxa
The number of "minnow" taxa include resident species of
Cyprinodontidae and Poeciliidae. These two groups of small fish
represent the majority of resident species inhabiting marsh and
shallow water environments.  The majority of these species are not
normally  found offshore or in deeper waters due to predation.  A
high number of these taxa may reflect habitat suitability of a
particular location to resistant species.  Since these species are
largely non-migratory, their presence or lack of may indicate long-
term environmental perturbation.  In contrast, high populations of
these  species may correlate the absence of larger predators and/or
the presence of marginal habitat unsuitable for other less tolerant
taxa.
     Number of Goby Taxa
This is another group of resident taxa that are primarily carnivorous,
feeding on small invertebrates. In addition, gobies are extremely
territorial and tend to stay within a defined area. Most gobies are
benthic.  Reduced numbers of gobies would indicate localized
impacts to habitat, water quality and secondary impacts on food
sources namely, epibenthic invertebrates.
     Proportion of Nekton Catch
     as Poeciliids
Poeciliids are a group offish that are generally extremely tolerant to
poor water quality.  Notable examples include the mosquitofish
(Gambusia affinis) and molly (Poecilia latipinna). These two
species are often found in harsh habitats where few other species
live.  In addition, they are typically found in areas (e.g., shallow
flats) which are difficult for predators to exploit. A predominance of
Poeciliids in shoreline communities  can therefore indicate degraded
conditions and/or lack of predators.
     Proportion of Nekton Catch
     as Penaeid Shrimp
One of the most important species ecologically and commercially
are the Penaeid shrimp, including the estuarine white shrimp
Penaeus setiferus, the brown shrimp P. aztecus, and the less
abundant pink shrimp P. duorarum. Typically these species enter
the estuaries as postlarvae. With continued migration they reach
tidal creeks and bayous as juveniles and spend the early part of the
first year in these areas prior to migrating back to the ocean to
spawn.

The proportion of catch as Penaeid shrimp may be an excellent
ecological indicator.  Penaeid shrimp can serve as a metric that
addresses the nursery functions of a waterbody.  It is also a lower
food chain omnivore. Many species are dependent upon this
invertebrate for food. Therefore, reduced numbers of shrimp can
detrimentally effect the entire nekton community.  In  addition,  since
it is an arthropod it may serve as an excellent indicator of
secondary impacts associated with pesticide use.
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     Table 13-4. Proposed seine metrics for use in an estuarine IBI along Texas coast.
Metric
Summer
Value
Fall
Value
Winter
Value
Spring
Value
Score
Category A
(A) Total Catch
*(A) Log Catch
*Prop. Pen. Shrimp
<200
200-450
>450
<5
4.5-6.0
>6.0
<01
0.01-0.3
>0.3
<50
50-400
>400
<9
3.9-5.8
>5.8
<25
.25-.56
>56
NA
<900
>900
<4.2
4.2-6.4
>6.4
NA
NA
NA
NA
<700
>700
<1.5
1.5-6.3
>6.3
NA
<0.04
>0.04
1
2
3
1
2
3
1
2
3
Category B
(B) Prop. Shad
*(B) Prop. B. Anchovy
If Bay A. =0
then use 'Shad' metric
*Dominance Ratio
>0.83
NA
<0.83
>0.8
NA
<0.8
>0.88
0.44-0.88
<0.44
>.60
.04-.60
<0.04
>.52
.04-.52
<04
>.65
.40-.65
<.40
>59
NA
<.59
>.13
NA
<.13
>.82
.26-.82
<.26
>.78
NA
<.78
>.34
NA
<.34
>.78
.27-.78
<.27
1
2
3
1
2
3
1
2
3
Category C
*(C) Mean #Taxa
(C) Cum. #Taxa
(C) Mean #Fish Taxa
<6
6-11
>11
<10
10-19
>19
<3
3-7
>7
<6
6-10
>10
<6
6-11
>11
<3
3-7
>7
<6
6-10
>10
<11
11-18
>18
<3.5
3.5-7
>7
<5
5-10
>10
<11
11-19
>19
<4
4-8
>8
1
2
3
1
2
3
1
2
3
Total IBI Score
Concern
Normal
Excellent
5-7
8-12
13-15
5-7
8-12
13-15
4-5
6-10
11-12
7-9
10-12
13-15



Total IBI Score (WHEN INVERTS NOT USED)
Concern
Normal
Excellent
4-5
6-10
11-12
4-5
6-10
11-12
4-5
6-10
11-12
5-6
7-10
11-12



     Recommended metric; if mean log total catch or total catch = 0, then score = high concern.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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    Table 13-5. Proposed trawl metrics for use in an estuarine IBI along Texas coast.
Metric
*Prop. Total Catch
as P. Shrimp
*Prop Total Catch
as Shad
Summer Value
*
<0.45
>0.45
>0.06
*
<0.06
Fall Value
<0.42
.42- .83
>0.83
>0.08
*
<0.08
Winter
Value
*
*
*
*
*
*
Spring
Value
*
<0.08
>0.08
>0.03
NA
<0.03
Score
1
2
3
1
2
3
Category A
*Mean # Nekton
Taxa
Mean # Fish Taxa
<1.8
1.8-9.3
>9.3
<2.2
2.2-6.3
>6.3
<4.3
4.3-9.9
>9.9
<4.2
4.2-6.6
>6.6
<4.4
4.4-8.8
>8.8
<2.1
2.1-6.8
>6.8
<4.1
4.1-7.7
>7.7
<1.6
1.6-4.9
>4.9
1
2
3
1
2
3
Total IBI Score
Concern
Normal
Excellent
4
5-8
9
3
4-8
9
1
2
3
4
5-8
9



    NOTE: To avoid problems caused by division by zero use the following formulas: For shrimp and shad
    proportions let metric value = taxa group catch/(total catch + 1). Alternately if any one replicate total
    catch = 0, then an IBI score of 'concern' can be given.

    NOTE: Avoidance of winter sampling is recommended due to lack of suitable metrics.

    * Recommended metric; if mean log total catch or total catch  = 0, then score = high
     concern.
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Case Studies

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   Table 13-6. Proposed gillnet metrics for use in estuarine IBI along Texas coast.
Metric

1) Total Nekton Catch
Assigned Metric Score
0
0
1
K26
2
26<47
3
>47
2) Category 2 (Pick 1 of the 2 Metrics Listed)
2a) Number of
Nekton Taxa
2b) H1
0
*
1<7
<1.25
7<8
1.25<1.85
>8
>1.85
3) Category 3 (Pick 1 of the 2 metrics listed)
3a) Evenness J
3b) Number of Taxa
= 90% Total
Nekton Catch
No. Crust. Spp.
4) No. Pred. Taxa
No. "Minnow" Taxa
5) No. Scaenids/B. Cat.
Taxa
Total IBI Score (SUM OF
ALLS METRIC
CATEGORIES)
Total IBI Rank
*
*
*
*
*
*
0
HIGH
CONCERN
<.58
<4
Not Recom.
0
Not Recom.
0
5-6
CONCERN
.58<.81
4<6
Not
Recom.
1
Not
Recom.
1-2
7-13
NORMAL
>.81
>6
Not Recom.
>1
Not Recom.
>2
14-15
EXCELLENT
   Due to the lack of strong correlation
   between the seine and trawl-derived
   metrics, it is advisable that future
   studies use both gear types. Since
   gillnet derived metrics were least
   sensitive to water quality fluctuation,
   and gillnet use is labor intensive and
   difficult to replicate, gillnetting is the
   least favored approach for evaluating
   nekton community health.

   A fish health index (FHI) was tested
   during the pilot study to evaluate its
   utility in assessing impacts on
   estuarine fish communities. The FHI
   methods mirrored those used by the
   Tennessee Valley Authority (Dycus
   and Meinert 1993, Dycus 1995).
   Further evaluation is needed to
   determine the discriminatory power;
   i.e., impaired versus unimpaired sites
of the index.  Proposed FHI values for
Gulf Coast bioassessments are listed
in Table 13-7.  The FHI proved to be
time and cost efficient, and yielded
information that was complementary
to the IBI.
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    Table 13-7. Proposed fish health index and condition factors for use in estuarine rapid
    bioassessments of Texas Gulf coast tidal tributaries.
                                      FISH HEALTH INDEX
Species
Blue Catfish FHI Score
Atlantic Croaker FHI
Score
Sea Catfish "Hardhead"
(least recommend) score
Spot FHI Score
AVERAGE SPECIES FHI
RANK
Total FHI Rank based on
average scores of single
species
Assigned FHI Rank
1
>70
>50
>30
>61
1-1.4
CONCERN
2
40-70
30-50
*
32-61
1.5-2.5
NORMAL
3
<40
<30
<30
<32
>2.6
EXCELLENT
                                      CONDITION FACTOR
Species
Blue Catfish CF
Atlantic Croaker CF
See Catfish "Hardhead"
CF
SpotCF
AVERAGE SPECIES CF
RANK
Total CF Rank based on
average scores of single
species.
Assigned Condition Factor (CF) Rank
1
<.78
<1.02
<.82
<1.25
1-1.4
CONCERN
2
.78-.Q7
1.02-1.15
.82-1.10
1.25-1.44
1.5-2.5
NORMAL
3
>.97
>1.15
>1.10
>1.44
>2.6
EXCELLENT
13-18
Case Studies

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   The application of estuarine rapid
   bioassessment techniques in studies of
   Gulf of Mexico coastal environments
   is warranted, based on results of the
   pilot study. Several of the methods
   tested in the study (including seine
   and trawl based IBI and FHI) would
   aid water quality and fisheries
   scientists in their evaluation of water
   and habitat quality impacts resulting
   from human activity. The pilot
   bioassessment methods meet the
   requirements for inclusion in routine
   monitoring programs including:  low
   cost, low effort, readily obtainable
   equipment, relatively easy taxonomy,
   and replication of effort which is
   suitable for statistical analyses.

   Primary Contact: George J. Guillen,
   U.S. Fish & Wildlife Service
   1655 Heindon Rd.
   Arcata, CA 95521
   707-825-5109
   george_guillen@fws.gov
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13-20                                                                                  Case Studies

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   13.3  Tarn pa Bay-
          Development of a
          Community-Based Metric
          for Marine Benthos: A
          Tampa Bay Pilot Study

   13.3.1 Study Objectives

   State biological criteria in Florida have
   been set at a 25 % decrease in Shannon-
   Wiener diversity of benthic communities
   in test versus reference sites.  Input data
   have been the sum of three ponar grab
   samples per site; however, evidence has
   suggested that these methods and
   criteria are not sensitive enough. Pilot
   studies in the Tampa Bay area (Figure
   13-1) have tested a process of classifying
   organisms according to their sensitivity
   or tolerance to pollution, and
   developing an index (the Farrell
   Epifaunal Index) value for test and
   reference sites (Farrell 1993a). The pilot
   study used biological data from areas
   surrounding treatment plant outfalls in
   the index calculations, in order to detect
   differences between test and reference
   sites that were not evident using the
   state criterion of a 25 % decrease in
   diversity.

   13.3.2 Study Methods

   Water quality and benthic data were
   developed from a 1992 short-term study
   of the effects of three small package
   plants on the seagrass communities at
   Fort Desoto Park in Tampa Bay, Florida.
   Three control stations were located on
   Joe Island on the southern shore of
   Tampa Bay, and an additional station
   was located on a small island adjacent to
   Fort Desoto (that was presumably under
   the potential influence of the farfield
   effects). Two sampling sites were
   located at each station, one on the
   shoreline (end of pipe) and a second 50-
   m offshore.  Four petite ponar replicates
   were collected at each site;  however,
   only three were analyzed for
macroinvertebrates. This process was
consistent with Florida's biological
integrity standard as defined in the
Florida Administrative Code. After the
ponar samples were collected,
macroinvertebrates were also sampled
at each location using a modified Renfro
Beam Trawl towed for a  distance of 4-m.

The Renfro Beam Trawl is a conical net,
open at the large end, which is normally
towed over the surface of the substrate.
The net is  maintained in an open
position by attaching it to a rigid pole or
beam. The body of the net is
constructed of nylon bolting cloth (50
openings/cm2, which tapers to a
plankton net fitted with a removable
bucket.  The effective swath width of the
custom trawl used for  the pilot study
was 1.25-m. By towing the net over a
uniform measured distance, the results
were comparative (semiqualitative) and
relative abundances of the various
species were maintained. The
standardized tow length of 4-m
effectively sampled approximately 5-m2
of bottom. Some advantages and
disadvantages of using the epibenthic
beam trawl are listed in Table 13-8.

In advocating the use of the beam trawl,
which predominantly  samples the
epifaunal  and facultative infaunal
communities, one basic assumption was
made.  Provided that the recruitment
potential for the individual community
components existed, it was assumed that
within a given set of natural
environmental parameters an expected
community of organisms would inhabit
any predetermined environmental
segment.  In estuaries  and many other
marine environments, populations of
different species vary significantly over
the seasons and from year to year;
however, these variations follow
predictable patterns. In Florida,
numerical dominance  may vary among
annual cycles; however, species
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-21

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   Table 13-8.  Advantages and disadvantages to using the epibenthic Renfro beam trawl for the
   sampling of benthos.	
               ADVANTAGES
        DISADVANTAGES
        The epibenthic assemblage is very
        sensitive to anthropogenic
        stressors, and this method  can be
        used in both a nearfield and farfield
        context with equal facility.

        Since this method is limited to level
        bottoms, the total number of
        common species will be limited
        (thereby greatly simplifying  training).
        [NOTE:  Time required for analysis
        of three ponar samples was
        approximately 20-hours, whereas
        the time required to analyze a pilot
        study trawl sample was a little less
        than  10-hours].

        This  method lends itself to
        subsampling which will  reduce
        processing hours and increase cost-
        effectiveness.

        Once initial training is completed,
        field efforts can be relatively rapid
        and analytical time can  be reduced.

        Samples can be sorted qualitatively,
        and a nonparametric analysis can
        be applied to provide a  method of
        quick screening.	
The method is restricted to level bottoms.
Hard substrates cobble, and emergent
vegetation tend to invalidate the method.

In areas of abundant seagrasses or
macroalgae beds, sample bulk can be a
hindrance and some rough field sorting
may be required.

The epifauna tend to be seasonally
abundant; therefore, this factor would
have to be calibrated into the method if
multi-seasonal sampling events are
utilized.
    composition generally remains stable.
    Benthic macroinvertebrates, in terms of
    both density and diversity, reach their
    peak in Florida during the late winter to
    early spring (or earlier in the southern
    part of the state). Population minima for
    most species occur during the summer
    months.  While they are dramatic, these
    seasonal  cycles can be factored into
    efforts to establish biocriteria. It is
    important to consider seasonality
    because the species which are most
    sensitive  to environmental stress are
    those which tend to reach their
    population peaks during periods when
    water quality factors are both stable and
    optimal.
 The epifaunal and facultative infaunal
 community was targeted for the pilot
 study since components of the
 community appear to be both persistent
 and very sensitive to environmental
 stress.  Within estuaries and adjacent
 near-shore areas, physiochemical
 parameters (e.g., temperature, salinity,
 dissolved oxygen) will vary significantly
 over an annual cycle. Sessile and
 relatively immobile organisms
 (including most of the infaunal
 components) have evolved  either
 mechanisms which allow them  to
 tolerate these varying conditions, or
 breeding cycles which allow them to
 avoid periods of high stress. The more
 motile members of the community
 (including the epifauna and facultative
13-22
                                 Case Studies

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   inf auna) have the option of avoidance.
   During periods of stress, these
   organisms can move to deeper water or
   to other areas where stressors are
   mollified, and then return when
   conditions improve. When an area is
   being affected by relatively low levels of
   anthropogenic stress, only the most
   sensitive members of the benthic
   community will respond, and these are
   found among the epifaunal and
   facultative infaunal components. It is
   apparent that a method which is truly
   sensitive to low levels of pollution must
   target these components  of the benthic
   community, thereby advocating their
   use in the Tampa Bay pilot study.

   13.3.3 Study Results

   A bioassessment approach should be
   able to not only detect low levels of
   environmental stress, but it should also
   be able to detect those stress factors at
   the earliest possible stages. One
   approach which has been used
   successfully in freshwater environments
   has involved the assignment of the
   specific index values to various
   community components; i.e., species,
   and basing community assessment on
   the mean index value derived from
   sampling that community (Lenat 1993).
   The Farrell Epifaunal Index proposed in
   the Tampa Bay pilot study was
   specifically developed for the west coast
   of Florida, but it should be useful in
   adjacent areas. The index values
   represented a somewhat subjective
   evaluation of the relative tolerance or
   intolerance to environmental stress.  The
   values were taken from an ongoing
   effort to assign tolerance values to all
   marine and estuarine
   macroinvertebrates identified from the
   coast of Florida. Information sources
   have included agency monitoring  data,
   published records, gray literature, and
   anecdotal information. Wherever
   possible, all potential stressors including
sensitivity to toxic substances was taken
into account; however, the dominant
factor for most of the species was the
relative sensitivity to dissolved oxygen
depression.  As a result, the Farrell
Epifaunal Index was probably most
sensitive to organic pollution and
eutrophication with associated wide
swings in dissolved oxygen.

The tolerance criteria for the index in
terms of dissolved oxygen requirements
were as follows:

    0    Insufficient data to make an
         evaluation.
    1    Very tolerant. The identified
         species can withstand short
         periods of anoxia.
    2    Tolerant. The identified
         species can withstand brief
         excursions to 1.0-1.5 rngL"1.
    3    Slightly tolerant - slightly
         sensitive. The identified
         species can withstand brief
         excursions to 2.5-3.0 rngL"1.
    4    Sensitive.  The identified
         species can withstand brief
         periods below 4.0 rngL"1.
    5    Very sensitive. The identified
         species are basically intolerant
         of concentrations below 5.0
         mgL"1; however, some species
         may tolerate brief excursions
         below this provided no other
         stress factors are involved.

When the components from a sample
had been identified, the predetermined
tolerance values were assigned to the
various species, and a sample Farrell
Epifaunal Index value was calculated
using the formula:
      Farrell Epifaunal Index = v— —
                          E N
where:  n; = number of individuals of
        species i;
        I; = tolerance value for species i;
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                                     13-23

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           N = total individuals from all
           species used in the calculation.

   In a strictly qualitative approach, an
   index value may be calculated using the
   formula:
    Farrell Epifaunal Index (Qualitative) =

   where: Is = index value for component
           species s;
           Ns = number of species used in
           the calculation.

   Pilot study calculations of Farrell
   Epifaunal Index values required that the
   appropriate tolerance value (0-5) be
   assigned to individual taxa in each
   sample.  The values were then added,
   and the summation was divided by the
   total number of taxa utilized from the
sample. Taxa with a value of zero were
omitted from calculations. Pilot study
results (Table 13-9) indicated that the
index had been successful at detecting
differences between test and reference
sites.  The resulting Farrell Epifaunal
Index will not meet all needs, and is not
the only metric that could be applied to
beam trawl or similar samples; however,
pilot study results indicate that at a
minimum it should prove to be an
effective screening method.

Primary Contact: Steven Kent, FLDEP,
3319 Maguire Blvd.
Orlando, FL  32803
407-894-7555, ext. 2227
kent_sl@orll.dep.state.fl.us
   Table 13-9. Farrell epifaunal index results for the Fort Desoto Park-Tampa Bay Pilot Study.
BEAM TRAWL SAMPLE RESULTS

Stations
Number of Taxa
Index Total
Index
Sources
4
8
15
1.88
6
13
27
2.08
5
16
35
2.19
Controls
7
29
69
2.38
2
27
72
2.67
1
31
84
2.71
3
38
106
2.79
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                               Case Studies

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   13.4  North Carolina -
          Comparison of Biological
          Metrics Derived From
          Ponar, Epibenthic Trawl,
          and Sweep Net Samples:
          A North Carolina  Pilot
          Study

   13.4.1  Study Objectives

   A test was designed to compare
   biological metrics derived from three
   sampling methods, to determine which
   methods and metrics best demonstrated
   differences between sampling sites
   (Eaton 1994).

   Test data consisted of benthic
   assemblage collection results  for petite
   ponar, epibenthic trawl and sweep net
   samples taken in the vicinity  of
   Wilmington, North Carolina (Figure 13-
   1).  The data set included February and
   May 1993 ponar samples, November
   1993 trawl and sweep net samples, and
   February 1994 samples using each of the
   three collection methods.

   13.4.2 Study Location

   Three sampling sites were located in
   polyhaline (>20-ppt) waters in the
   Wilmington vicinity.  Howe Creek, a
   primary nursery area north of
   Wilmington, was selected as a reference
   site. Development in the Howe Creek
   area was sparse residential on the north
   side of the creek with a new
   development on the south side. Samples
   were collected on the north side of the
   creek, which placed a large saltmarsh
   between the collection site and the
   development to reduce possible impacts.
   The Howe Creek sampling location was
   characterized by sand and shell
   substrata, abundant sponge and oyster
   populations, and seasonally abundant
   macroalgae (Ectocarpus and Cladophora).
A second sampling station (Hewletts
Creek) was chosen as a test site for the
assessment of nonpoint impacts.
Hewletts Creek receives runoff from
central Wilmington. It has occasionally
received pump station overflows, and its
shoreline is heavily developed with
single family residences.  The large
quantities of macroalgae (Enteromorpha,
Ectocarpus, and Porphyra) that have been
flushed out of the creek could indicate
potential excess nutrients. The Hewletts
Creek station was characterized by hard-
packed medium sand and shell
substrates, intertidal oyster bars and
saltmarsh.

A sampling station located in Bradley
Creek was selected as a representative
impaired area. Most of this watershed
has been heavily developed, and the
lower portion of the creek supports two
marinas.  Sampling was conducted just
upstream from one large marina and
immediately downstream from the U.S.
Route 76 bridge.  The Bradley Creek
station was characterized by mud and
muddy sand substrate, intertidal oyster
bars, and seasonally common
macroalgae (Ectocarpus).

13.4.3 Study Methods

Three types of gear were employed to
sample the benthic assemblages at each
station.  A petite ponar was used to
collect three replicates of 1-3 grabs each
(depending on faunal density), thereby
sampling the infauna in a 0.04-0.13-m2
area at each station. An epibenthic trawl
(1.25-m net mouth) was pulled over 4-m
of unvegetated substrate to collect the
epifauna and obligate infauna in a 5-m2
area at each station. This method is
further described in Section 9.5. A D-
frame net was swept through all
available habitats for 10-minutes,
collecting the epifauna and shallow
infauna in a 20- to 60-m2 area.
Advantages and  disadvantages noted
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                   13-25

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    for each collection method are listed in
    Table 13-10.

    All samples were preserved in the field
    with 10% formalin with Rose Bengal dye
    added as a tissue stain. Samples were
    returned to the laboratory, where they
    were sorted from the detritus, then
                        identified to the lowest practical
                        taxonomic level (usually species).

                        Biological metrics taken from a wide
                        variety of sources were tested for each
                        sampling method. It was expected that
                        different metrics would prove useful for
                        different sampling methods. Test
   Table 13-10. Advantages and disadvantages noted for the three benthic assemblage collection
   methods.
       METHOD
      ADVANTAGES
  DISADVANTAGES
     Petite Ponar
can be used in any depth water
on almost all substrates (except
hard bottoms).
most previous researchers used
dredges, therefore some
comparisons with historic data
can be made.
true replication allows for
statistical treatment of the data.
it samples a relatively small
area, therefore rare and/or
large taxa may not be
collected.
the infauna are the most
tolerant portion of the
benthic community,
therefore minor stresses
may be easily missed.
sorting through large
amounts of sediment and
counting hundreds of
individuals of one or two
taxa can become tedious.
     Epibenthic
     Trawl
epifauna are generally more
intolerant to stresses than
infauna, therefore more subtle
environmental changes can be
detected than with infaunal
sampling.
a larger area is sampled than
with dredges, therefore more
rare taxa should be collected.
when  operated properly, a
relatively small amount of
sediment is collected, therefore
sorting is not tedious.	
results are not comparable
with most historic
databases.
the trawl is fairly unwieldy
and takes  training to use
properly.
it is impractical to use in
depths beyond 5-1 0 m or in
strong currents (>1.5-2
m/s).
     Timed Sweep
a large number of taxa are
collected including rare, large
and intolerant taxa.
since metrics are  more reliable
when calculated with increasing
observations (taxa), change in a
metric is a more reliable indicator
of environmental change.
being semi-quantitative, only an
estimate of abundance is
required rather than having to
count each individual.
all habitats are sampled,
therefore loss or degradation of
habitat is more readily
documented.
method is limited to
wadeable areas.
large amounts of sediment
are usually collected,
making sorting tedious.
a higher degree of
taxonomic expertise is
required than needed for
the other methods.
results are not comparable
with most historic
databases.
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                                                         Case Studies

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   metrics included: Farrell Biotic Index
   (modified for North Carolina), number
   of amphipods and caridian shrimp, total
   taxa, percent annelid abundance,
   percent mollusc abundance, Shannon-
   Wiener diversity index, amphipod
   abundance, polychaete abundance,
   molluscan abundance, gastropod
   abundance, bivalve abundance,
   capitellid polychaete abundance,
   spionid polychaete abundance,
   Hurlbert's PIE, Keefe's TU, Simpson's D,
   and oligochaete and pelecypod
   abundance (Engle et al. 1994; Farrell,
   1993b, Nelson 1990, Washington 1984,
   Weisberg et al. 1993).  All metrics were
   tested using the data generated from
   each of the three collecting methods. A
   metric was deemed to work if it was
   able to correctly rank  the stations; i.e., as
   reference, slightly impaired, or heavily
   impaired. Those metrics that correctly
   ranked the stations were further tested
   on a larger database to determine if
   metric ranking was a spurious
   coincidence or was due to the
   measurement of a consistent component
   of the biological community.

   13.4.4  Results

   Metrics that correctly ranked the three
   sites and their values, are listed in Table
   13-11 by sampling method. The Biotic
   Index was the only metric to correctly
   rank the sites; i.e., as reference, slightly
   impaired, or impaired for each of the
   three collection methods.  For samples
   collected by petite ponar, the Biotic
   Index correctly ranked the sites for the
   two February samples, but failed to
   correctly rank the sites in May. This
   may be related to seasonal fluctuations
   in recruitment (Holland 1985). The
   Biotic Index as a function of salinity at
   38 sites sampled via petite ponar is
   presented in Figure 13-3. Diamonds
   represent reference sites, triangles
   represent impacted sites and squares
   represent areas of intermediate or
unknown water quality. Lines in the
figure represent possible break points
for future criteria.

Two metrics, Biotic Index (BI) and %
Oligochaete and Pelecypod abundance
(% O&P), correctly ranked the three sites
sampled using an epibenthic trawl
(Table 13-11). In February, but not in
May, the %O&P was low because two
taxa made up 70% of the individuals at
this site. This heavy skewness in
abundance may be due to seasonal
recruitment. To date, these samples are
the only collections made using the
modified trawl. More samples are
required to adequately test the efficacy
of the trawl.

The sweep method had three metrics
that ranked the three sites correctly
(Table 13-11): Biotic Index (BI), Total
Taxa (TT), and Amphipod and Caridean
Shrimp Taxa (A&C). Graphs of BI, TT,
and A&C values for 63 timed sweep
samples over a range of salinities are
presented in Figure 13-4. Each metric
appeared, in varying degrees, to be
affected by salinity.  At sites where
salinities were above 8-ppt, there was
sufficient separation between Reference
sites (diamonds) and Impacted
(triangles) sites to identify sites with
Intermediate impact (squares) as well.
This separation was smaller in
intermediate salinities (8-20-ppt) than
higher salinities (>20-ppt).  Samples
collected below 8-ppt salinity showed  a
limited range of metric values. Only BI
was able to separate Reference from
Impacted sites in these low salinities.

The Total Taxa metric may be related to
the habitat diversity of an area; a
diversity of habitats at a site would
include more niches, thus allowing the
survival of more taxa. This suggests that
the Total Taxa metric could serve as a
habitat quality measure as well as a
measure of water quality.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-27

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    Table 13-11.  Functional metrics for the three benthic assemblage collection methods.

Howe Creek
(Reference Station)
Hewletts Creek
(Nonpoint Source
Impact Station)
Bradley Creek (Urban
Impact Station)
Petite Ponar
Date
Biotic Index
2/93 5/93 2/94 5/94
2.7 2.1 2.1 1.9
2/93 5/93 2/94 5/94
2.0 1.6 2.2 1.9
2/93 5/93 5/94 5/94
1.6 1.9 1.8 1.4
Epibenthic Trawl
Date

Biotic Index

% Oligochaeta &
Pelecypoda
Abundance
— — 2/94
5/94

— — 2.5 2.8
— — 21 3
11/93 — 2/94 5/94

2.8 — 2.4 2.7

27 — 31 6
— 2/94 5/94 —

— 1.7 2.0 —

— 37 4 —
Timed Sweep
Date
Biotic Index
Total taxa
Amphipoda &
Caridean shrimp
— — 2/94 5/94
— — 2.4 2.5
— — 109 95
— — 17 22
11/93 — 2/94 5/94
2.2 — 2.2 2.0
94 — 91 105
9 — 9 15
11/93 2/94 5/94 —
1.8 1.8 1.9 —
45 60 68 —
7 7 9 —
    Figure 13-3
    Ponar samples:
    biotic index vs.
    salinity
3 n
1 <^
X 2'b
0)
1 2
« i *,
o 1'5
m 1 .
Oc
P


• • *
• IA •

onar Biotic I
* h'-t
"•• i •
•
•

ndices
> •
•

• Bl Reference
• Bl Unknown
A Bl Impacted
*


0 10 20 30 40
Salinity
13-28
Case Studies

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Biotic Index
4

x J-b '
HI
1 3 -
•- oc
3 2-5-
<" ,
1 5

i 1
XX IX
x VH xx
2 v t n
"•" xxx A
X A


•«*„ ,i i
	 [t^-T 	 ₯ 	
•" *: .
A ^ A

» Bl Reference
• Bl Intermediate
A Bl Impacted
x Bl Unknown

0 10 20 30 40
Salinity
                                                                              Figure 13-4	
                                                                              Bl, total taxa and
                                                                              amphipod and
                                                                              caridean taxa by
                                                                              salinity.
Sweep Total Taxa



X
re 100 -

° 60 -
40 -
20 -







* >*SXx%x



^
I

1 i i3
7 *
^ x "

*
! . *
. ,'. «• .
* — «-li 	 if 	 * 	
/ " • •
XA
A
A X


1 T T Reference
• TTIntermediate
ATT Impacted
XTT Unknown

0 10 20 30 40
Salinity
Amphpod & Caridean Shrimp Taxa
35
X
re 25

l_ 20
O 15 -
08 I0
< 10
5
0 -





i *****]






•
• .' •

• ,
. •"
A A * *
• A

» A&C Reference
• A&C Intermediate
A A&C Impacted
x A&C Unknown

0 10 20 30 40
Salinity
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-29

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   Amphipods and caridean shrimp
   make up 10-15% of the total taxa at a
   site. This correlation explains why the
   graphs of the TT and A&C metrics
   look similar. Since the Crustacea
   include many of the most intolerant
   taxa in the estuary, the A&C metric
   may prove to be more sensitive to
   slight differences in water quality
   than the other metrics tested. One
   potential problem with the A&C
   metric is that it, like TT, appears to be
   affected by habitat quality, especially
   the presence or absence of seagrass
   and shells.

   The next step, following method
   selection and metric determination,
   was biocriteria development. In this
   exercise, sweep samples at sites above
   8-ppt were used because multiple
   metrics had been identified which
   showed a range of water qualities.
   For each metric, a value above the
   Reference/Intermediate line (Figure
   13-4) was scored five points whereas a
   value below the Intermediate/
   Impacted line was scored 1.  To
   increase sensitivity, the Intermediate
   Impact area was subdivided: values
   in the upper 20 % were scored 4 points,
   values in the middle 60% were scored
   3 points, and values in the lower 20%
   were scored 2 points.  Points for each
   of the three metrics were summed,
   giving each site a total score between
   3 and 15 points. Water quality
   bioclassifications were assigned based
   on the number of points scored by a
   site (Figure 13-5).

   An attempt was made, in step three of
   biocriteria assignment, to address
   natural situations where Taxa
   Richness was depressed at a site (little
   habitat diversity, wide salinity
   swings, or high wave action).  If one
   or more of these situations could be
   identified for a site, an extra two
   points were awarded to the total
score. While this appears to
adequately correct a previously
unaddressed problem in biocriteria
development, assessment of the
usefulness of this approach must
await a validation study, which is
beyond the scope of the exercise
described here.

13.4.5 Summary

Test results indicated that there was
no metric which consistently ranked
the test stations in a priori order of
impact based on petite ponar
collections, though this may have
been due to confounding by a spring
peak in recruitment.  The Biotic Index
ranked sites correctly most often.
Epibenthic trawl results correctly
ranked the test sites using the Biotic
Index and percent abundance of
Oligochaeta and Pelecypoda metrics.
Further sampling with the epibenthic
trawl is required to determine
whether it or the ponar will give more
reliable results in non-wadable areas.
The sweep method appeared to be the
most versatile of the three test
methods, resulting in three metrics
that correctly ranked the test sites. All
metrics appeared to lose sensitivity at
salinities below 20-ppt. Possible
seasonal effects and differences in
substrate appeared to be confounding
the analyses as well; therefore, these
factors must be taken into account
during the biocriteria development
process.  The Biotic Index appeared to
be the most versatile tool since it was
the only metric to correctly rank sites
for all methods and all salinities.
Initial efforts at biocriteria
development in North Carolina will
focus on the Biotic Index as well as on
further sampling to determine the
effects of seasonality, substrate,
salinity, and habitat variables.
13-30
                             Case Studies

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       Figure 13-5
       Development of
       biocriteria.
STEP 1: Assign points for each of three metrics from a sweep sample.
Polyhaline (2 1 ppt to seawater)
Points 54321
BI > 2.6 2.59-2.5 2.49-2.01 2.0-1.91 < 1.9
Total Taxa > 95 94 - 86 85 - 69 68-60 < 60
Amphipods& > 21 20-18 17-13 12-10 9-0
Caridean Shrimp
Mesohaline (8 ppt to 20 ppt)
Points 54321
BI > 2.2 2.2-2.16 2.15-1.96 1.95-1.9 <1
Total Taxa > 38 37-32 31-24 23-18 17-
Amphipods & > 8 7 6-5 4 3 -
Caridean Shrimp
STEP 2: Sum points. This will yield a number between 3 and 15.
STEP 3 : Check for Bonus Point conditions. Add 2 points to score if one or more
of the following conditions occurred: 1) Homogeneous habitat, 2) consistently high
wave action, 3) very high (>26 ppt/yr) salinity fluctuations.
STEP 4: Assign Bioclassification.
Bioclassification Points
No Impact 13-15
Slight Impact 11-12
Moderate Impact 8-10
Elevated Impact 6-7
Severe Impact 3-5
9
0
0
    Primary Contact: Larry Eaton,
    NC Division of Water Quality,
    4401 Reedy Creek Road
    Raleigh, NC 27602
    919-733-6946
    lawrence@dem.ehnr.state.nc.us
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-31

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13-32                                                                                  Case Studies

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   13.5  Indian River, Florida -
          Field Verification of
          Marine Metrics Developed
          For Benthic Habitats:
          Indian River Lagoon,
          Florida Pilot Studies

   13.5.1 Study Objectives

   A research program was developed for
   Florida estuaries to promote the
   identification of benthic marine
   parameters indicative of relative water
   resource quality (Nelson et al. 1993,
   Nelson and Spoon 1994 a, b). The
   development of these parameters or
   metrics was ultimately intended to help
   quantify the diverse attributes and
   interrelationships of the community to:
   enhance documentation of possible
   resource impairment from point and
   non-point sources; evaluate aquatic life
   use attainment; and to be incorporated
   in the biological criteria process.

   13.5.2 Study Methods

   The process of developing benthic biota
   community parameters (or metrics)
   indicative of Florida estuarine resource
   quality was initiated in 1993 with Indian
   River Lagoon pilot studies (Figure 13-1).
   The initial study involved the collection
   and analysis of samples taken from six
   stations, including two within the main
   Indian River Lagoon and four at the
   mouth of tributaries. Benthic samples
   were collected by a diver using 8.2-cm
   diameter Lexan cores which were
   sectioned into 0-5-cm and 5-15-cm depth
   fractions.  Study sites were selected with
   the primary criterion of a presumed
   difference in pollution impact, with
   secondary emphasis on similarity of
   sediment type and tertiary emphasis on
   similarity in salinity. Three sites were
   designated impaired and three were
   designated low impairment sites. The
   small scale or smaller number of stations
limited the bottom salinity types
sampled to mesohaline, polyhaline, and
euhaline locations.

The nature of pollution impacts in the
Indian River Lagoon presented a major
problem in sample selection. Maximum
impacts of pollution input (primarily
from urban runoff) are felt within the
small lagoonal tributaries as compared
to the lagoon proper. Non-impaired
tributary sites are generally  not
available, which forces most reference
sites to be in the lagoon proper. This
sometimes resulted in a difference in
salinity between the impaired and non-
impaired sites.  For example, during
winter sampling, mean salinity at
impaired sites was 13-ppt (mesohaline),
and was 25.3-ppt (euhaline) at non-
impaired sites.  However, these spatial
salinity differences appeared to be
seasonal in the lagoon. Samples taken in
June had a mean bottom salinity of 25.3-
ppt (euhaline) at impaired sites
compared to 29.6-ppt (euhaline) at non-
impaired sites.

13.5.3 Study Results

The benthic data were summarized in
terms of: the mean percent  of biomass
contained in the top five centimeters of
the sediment profile at each of the
stations; and the mean weight per
individual compared among sites and
between the 0-5-cm and 5-15-cm depth
segments. There was no clear difference
in mean percent biomass (contained in
the top 5-cm) between the two sets; i.e.,
impaired, non-impaired of sites. There
was also no clear difference in mean
weight per individual based on
presumed differences in pollution
impact either for the surface sediments
or for the deeper sediments. Biomass
differences with differing salinities also
showed no clear differences, in that
mean values of the percent total biomass
above 5-cm ranged from 68% to 89% in
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                                    13-33

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   mesohaline areas, and 69% to 81% in
   euhaline areas. The value in the single
   polyhaline area was 94%.

   Sediment types within the study area
   were classified as sand (>70% sand),
   mixed (30-70% sand), and mud (<30%
   sand). Both the impaired and non-
   impaired sites had all sediment types
   represented.  There were no apparent
   trends in biomass data among the
   sediment types.  There was no
   indication that sand sites had less
   biomass in surface sediments than
   mixed sediments, or that mean weight
   per individual differed among sediment
   types.

   During the initial studies, benthic data
   were also summarized in terms of total
   individual and total species metrics.
   The mean percentage of total
   individuals present above 5-cm ranged
   from 96 to 99.6% at the study sites.  The
   differences in this metric between sites
   of different pollution impact was thus
   very low; therefore, this metric did not
   clearly distinguish Indian River Lagoon
   sites. Mean percentage of species above
   5-cm in the sediments was calculated
   from the data by dividing the total
   number of species in the 0-5-cm fraction
   by the sum of this value plus the total
   number of species recorded in the
   5 -15-cm fraction for each site. There
   was no clear separation between the
   sites based on this metric.

   The initial Indian River Lagoon pilot
   study and previous studies of the area
   have examined the following metrics:

   *•    Mean total number of individuals;

   *•    Mean total number of species;

   *•    Percentage of amphipods;

   *•    Percentage of spionids;
*•   Spionidae/capitellidae ratio;

*•   Apparent color RPD depth.

Of the seven metrics, separation
between impaired and low impairment
sites was good for mean number of
species, percentage of amphipods,
percentage of spionids, spionidae/
capitellidae ratio, and apparent color
RPD depth. The percentage amphipod,
percentage spionid, and
spionidae/capitellidae ratio metrics
require separation of individual
specimens which requires greater time
than simple counts of total individuals
or total biomass. However, these
metrics seemed to offer much greater
powers of resolution than measures of
total individuals or biomass.

Limitations on the generality of the
conclusions of the initial pilot study
were imposed by the limited number of
sampling sites (6) and by the fact that
samples were obtained at only one point
in time. Seasonal variation in benthic
systems can be substantial; therefore, it
was essential to verify the temporal
generality of initial conclusions.
Similarly, spatial variations in salinity
regime have been demonstrated to
influence metric values. Therefore,
more extensive spatial and temporal
sampling was warranted to verify the
utility of the proposed metrics.  To
provide temporal verification of metrics,
the six sites originally sampled in
January 1993 were resampled, and two
new sites were added to the sampling
plan to represent additional spatial
coverage of the Indian River Lagoon.
The two additional sites were located
near Cocoa, Florida, with one presumed
to be an impaired; i.e., located near a
sewage outfall pipe, and the other a low
impairment site. Core samples were
collected by divers (as in the initial pilot
study) during June, July and August
1993. All organisms collected were
13-34
                              Case Studies

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   subsequently identified to the lowest
   feasible taxon, counted, oven dried, and
   weighed in the laboratory. Surface
   water temperatures and salinity, and
   bottom salinity measurements were
   made in the field, and sediment samples
   were collected by skin diving. One of
   the proposed metrics was to involve
   visual determination of the apparent
   color RPD depth. It was difficult to
   measure a visual RPD with any degree
   of confidence since the surface layers of
   sediment were often flocculent and were
   therefore disturbed by the coring
   process.  Attempts to measure the
   apparent visual RPD were therefore
   abandoned during the second phase of
   pilot studies.

   A total of 64 benthic cores and 128 core
   fractions were collected and  processed
   during the second phase of pilot studies.
   There was no clear distinction for the 0-
   5-cm sediment fraction in mean number
   of individuals per core recorded at low
   impaired versus impaired stations.
   Mean number of benthic taxa recorded
   per core from the 0-5-cm fraction also
   failed to show clear differences between
   the two sets of stations. Clear
   distinctions were observed, however,
   between the impaired and low impaired
   sites with respect to mean abundance
   per core for benthic organisms in the 5-
   15-cm fractions.  Abundances in the  5-
   15-cm fractions differed by a factor of at
   least 4 between the two sets of stations;
   i.e., mean equaled 0-1.3 at impact
   stations and 5-10 at low impact stations.
   Impaired and low impaired sites also
   showed clear separation based on the
   mean number of taxa per core in the 5 -
   15-cm fraction.

   The total species richness of  amphipod
   crustaceans was seven at both the
   impaired and low impact sites, and the
   species recorded were similar.  The
   metric based on the percentage
   abundance of amphipod crustaceans;
i.e., percent of total, failed to clearly
distinguish the two types of sites.
Comparisons of amphipod total
abundance; i.e., amphipod total count,
also failed to clearly distinguish
impaired versus low impact sites,
ranging from 4-1789 at low impact sites
and 27-62 at impaired sites. The 1993
summer results contrast strongly with
the winter results for the amphipod
metrics. Winter data showed clear
separation of impact versus low impact
stations with respect to both percent
abundance and total number of
amphipods, whereas summer data did
not.

The ratio of spionid polychaete
abundance to capitellid polychaete
abundance showed only partial
separation between station types in the
summer samples. There was a
decreased degree of separation with this
metric in summer versus winter
samples. The differences in the ratio
were generated both by reduced
numbers of spionids and by increased
numbers of capitellid polychaetes at the
low impact sites for winter samples. In
contrast, differences in summer samples
for the low impact  sites were mainly
caused by high values for capitellids.
Therefore, a total capitellid metric was
examined for both  seasons. Clear
separation between impaired and low
impact sites was given for this metric for
both summer and winter data.
Examination of a total annelid
abundance metric also demonstrated
separation of impaired and low impact
sites (for summer data).

Total faunal biomass showed no
separation of stations for either the 0-5-
cm or 5-15-cm core fractions. Expression
of the biomass values above 5-cm were
modified by subtracting biomass for the
occurrence of a few large organisms
(e.g., large bivalves). The adjusted
surface  biomass metric also failed to
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                                    13-35

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   clearly separate the impaired and low
   impact sites.

   Differences in the values of benthic
   community parameters were apparent
   in summer samples as compared to the
   winter samples from the same study
   sites.  The seasonal changes in
   abundance were anticipated given
   previous knowledge of seasonal
   abundance patterns of macrobenthos in
   the Indian River Lagoon.  Some
   proposed metrics were consistent in
   their performance in both winter and
   summer samples (Table 13-12). Both
   abundance and taxa richness in the deep
   sediment fraction were metrics which
   gave clear separation in the sets of
   stations in both winter and summer.
   Abundance of capitellids also
   consistently separated the station types
   during both seasons.

   The performance of some of the metrics
   which appeared promising in the winter
   samples was somewhat altered in
   summer.  For example, taxa richness in
   the 0-5-cm fraction, percent amphipod
   abundance, total amphipod abundance,
   and spionid/capitellid ratio metrics
   discriminant stations in the winter, but
   did not do so (or gave unclear results) in
   the summer. Explanations for this
   change in performance may be complex.

   The biomass measurements used in the
   pilot studies were made on specimens
   separated into lowest identified
   taxonomic units, which required
   considerable time and effort. Had the
   biomass measures provided clear
   separation of station types, it would
   have been warranted to suggest that all
   specimens be pooled to obtain a single
   biomass value.  However, it did not
   appear that biomass values for either
   depth fraction were useful as a benthic
   metric for the Indian River Lagoon.
The pilot study results clearly indicate
that the season during which sampling
takes place may influence the ability of a
given metric to distinguish among sites.
Overall, clearer separation was seen
among sets of stations for winter
sampling than for summer sampling.
This appeared to be related to the fact
that highest organism density in Indian
River Lagoon benthos is seen during late
winter, rather than in the summer as is
the case at other locales. This clearly
points out the need to evaluate
seasonality at specific geographic areas.

Relatively few of the proposed metrics
consistently separated sites in the Indian
River Lagoon. The mean abundance of
organisms and mean species richness  in
the 5-15-cm depth fraction, and
capitellid abundance metrics all
provided consistent separation of station
types. The relatively small sample size
in terms of number of stations appeared
to result in ambiguous interpretation;
i.e., clear station separation ability in
winter and marginal in summer, for the
total amphipod abundance and
spionid/capitellid ratio metrics. The
natural temporal variability in the
benthos may be sufficiently extreme to
affect the performance of these metrics;
therefore, the best way to minimize the
influence of the variation may be to
sample as many stations as possible.

In the most recent phase of pilot studies,
two amphipod metrics - mean number
of amphipods per site and the ratio of
Corophiidae/(Ampeliscidae +
Phoxocephalidae) - were assessed at a
total of ten stations within the Indian
River Lagoon. The original eight pilot
sites were resampled and two additional
sites were sampled during May and
June 1994, using techniques as  described
for the earlier pilot studies.  A total of 80
benthic cores were collected and
processed.
13-36
                              Case Studies

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   Table 13-12. Comparison between winter and summer samples of the ability of the various metrics
   tested to discriminate between impaired and low impairment sites.
METRIC
0-5 cm abundance
5-15 cm abundance
0-5 cm taxa richness
5-15 cm taxa richness
percentage amphipods
total amphipod abundance
spionid/capitellid ratio
capitellid abundance
total annelid abundance
total biomass
total biomass (excluding large
bivalves)
mean percent biomass above
5 cm
WINTER
NO
YES
YES
YES
YES
YES
YES
YES
NO
NO

NO
SUMMER
NO
YES
NO
YES
NO
?
?
YES
YES
NO
?
NO
    NOTE: ? indicates marginal utility of metric due to inconsistent discrimination of impaired
          and low impairment sites.
   Results of collection analyses showed
   that the simplest amphipod metric,
   mean total abundance, clearly separated
   impaired from low impact sites in the
   late winter samples taken in 1993.
   However, summer 1993 and 1994 results
   indicated that the response of this metric
   was not satisfactory.  Available water
   quality information suggests a  division
   of the set of 10 stations into three
   groups: high impact, moderate impact,
   and low impact. Use of the mean
   number of amphipod metric did not
   provide a similar separation of sites for
   summer 1994 sampling data. However,
   the outcome of the Corophiidae/
   Ampeliscidae metric calculations was
   most consistent with the high impact,
   moderate impact, low impact division of
   sites, and therefore appeared to
   reasonably reflect water quality
   conditions of the Indian River Lagoon.
Primary Contact: Dr. Walter G. Nelson,
National Health & Environmental
Effects, Research Laboratory/ORD
Western Ecology Division,
Hatfield Marine Science Center
2111 SE Marine Science Dr.
Newport, OR 97365-5260
541-867-4041
Nelson. Walter@epa. gov
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13-38                                                                                  Case Studies

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   13.6  Ocean City, MD —
          Bethany Beach,  DE — A
          Preliminary Study of the
          Use of Marine Biocriteria
          Survey Techniques to
          Evaluate the Effects of
          Ocean Sewage Outfalls in
          the Mid-Atlantic  Bight

   13.6.1 Study Objectives

   This project investigates the practical,
   low cost application of marine biological
   community measurements and the near
   field/far field survey technique for use
   by coastal States as a water resource
   quality management tool. The methods
   applied here are derived from work
   reported by Pearson and Rosenberg
   (1978) and Mearns and Word (1982)
   with modifications.

   13.6.2 Study Methods

   The study area is a 16-km coastal reach
   between Bethany Beach, Delaware and
   Ocean City, Maryland (Figure 13-1,13-
   6).  These are nearly adjacent resort
   communities on the Mid-Atlantic
   seaboard between Delaware Bay and
   Chesapeake Bay. Each has a secondary
   treatment municipal sewage discharge
   site about 2.8-km offshore. Discharge is
   in both cases  through a diffuser at a
   water depth of approximately 12-m.
   The Bethany Beach sewage treatment
   plant average discharges about
   O.ei-mY^ 14-mgd) and Ocean City
   about 1.4-mY1 (32-mgd).

   A series of nine north-south trending
   stations were installed parallel to the
   coast at intervals of about 2-km, each in
   about 12-m depth of water and over
   medium to fine sandy bottoms  to obtain
   a similarity of habitat as much as
   possible. The stations are labeled "A"
   through "I", with station "C" at the
   Bethany Beach outfall and station "G" at
the Ocean City outfall (Figure 13-7).
This structure provides a set of control
or reference stations for comparison to
the test stations at "C" and "G". Each
station is located with differential GPS
with an estimated precision for the
receiver of +/- 5-m.

The variables measured are benthic fish
and macroinvertebrate communities as
reflected in indexes and metrics
incorporating number of taxa and
number of individuals per taxa. Fish
surveys are made with a 6-m (5-m
effective opening), 2.5-cm mesh otter
trawl. Tows are made parallel to the
shoreline at 1-ms"1 over 0.9-km with the
station coordinates located at the mid-
point of the tow. Trawl scope used is six
to one. Benthic macroinvertebrate
samples are collected with a 0.1-m2
Smith-Mclntyre grab or with a 0.1-m2
Young grab, and three replicates are
taken for each sample at each station site
as indicated by DGPS coordinates.
Ferraro et al. (1994) reviewed their
extensive data base and concluded that
five replicates with a 0.02-m2 petite
ponar grab, each sub-sampled with four
8-cm diameter cores is optimal for
waters of the Southern California Bight.
We elected to use the 0.1-m2 grab with
three replicates, but to count the entire
grab.  This was judged to be a
reasonable compromise between more
replicates and the uncertainty of sub-
sampling a site for which there was
inadequate preliminary information.
From this data base we hope to make
further sampling refinements in the
future. Identifications of collected
organisms are to species whenever
possible. All survey work was
conducted from the USEPA Ocean
Survey Vessel Peter W. Anderson.  The
Anderson is a 50-m research ship, but all
equipment used and methods employed
are appropriate for deployment from a
15-m vessel typically used by most
coastal States.  Incidental to this project,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                   13-39

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        Figure 13-6
        Bethany
        Beach - Ocean
        City study
        area.
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                            '^i\M   \-ji^
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                              •^ l>EC2l-r-^'-Ss
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                         • - >•?*;. ^; i "^ «hsi41,-
 --'TIJM—fcfc-.-f'':- -/STCZSy* -f.
                      ,'_i
   a comparison of the Smith-Mclntyre and
   Young grabs was made. Six replicate
   drops with each grab were made at
   three sites characterized by: hard
   packed fine sand; medium grain sand;
   and coarse sand and gravel. Either gear
   was judged acceptable, but the Young
   grab was less inclined to wash.
                                             I
               Sampling surveys have been conducted
               twice a year in July-September and
               January-February since 1993 to
               determine if multiple season indexing is
               necessary or appropriate. While the
               Mid-Atlantic area is considered to have
               four discrete seasons, benthic
               communities are expected to be in flux
13-40
                                           Case Studies

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    Figure 13-7
    Bethany
    Beach - Ocean
    City sampling
    locations.
FJ^Tfeil  gl&lfMi'AJL'
                                                         BEACH)
                                          ,, «J

                                           X
                                                                 * *:-?«•> CMS?
   during Spring and Fall and to be most
   stable in Summer and Winter
   (Ranasinghe et al. 1994).

   Fish sample processing is conducted on
   board with all individuals identified to
   genus and usually to species. Length
   measurements (TL) are made and any
   gross anomalies recorded. The fish are
   returned to the water as soon as
   measurements are completed. Benthic
   invertebrate sediment samples are
           sieved on board using a 0.5-mm mesh
           screen after recording a physical
           description of the sample and taking a
           2.5-cm diameter subcore for grain size
           analysis.  The retained material is fixed
           in 10% buffered formaldehyde with
           Rose Bengal dye added.  Taxonomic
           identifications and counts are made later
           at laboratory facilities ashore with most
           identifications carried to the species
           level.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                13-41

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   To make comparisons between the
   sample sites, habitat control in the
   survey design was maintained as well as
   possible by attention to three major
   variables:

   1)     Grain size of bottom sediments.
          This also reflected a habitat
          impact of the discharges when
          fine sediments were deposited in
          bottom depressions near the
          outfalls.  At the beginning of the
          project, sediment samples were
          collected from all nine stations
          and analyzed for heavy metals
          and a for a standard array of
          toxicants. All results were
          insignificant, suggesting no other
          sources of biotoxicity or
          impairment indigenous to the
          immediate area.

    2)     Water depth. Water depth over
          stations "A" through "E" ranges
          from Tl-m to 14-m with the
          variation accounted for by a
          general ridge and swale
          bathymetry off Bethany Beach.
          From "E" through "I", the
          variation is from 14- to 16-m,
          accounted for by an east-west
          ledge with about a 3-m drop just
          south of the Ocean City outfall.
          Subsequent data analyses
          suggest that these variations in
          water depth do not restrict fish
          or invertebrate distributions over
          the area.

   3)     Water quality. At the outset of
          the study, and each time
          biosurveys are conducted,
          multiple  depth and standard
          water quality measurements are
          made using a Sea-Bird SBE-9
          "CTD" probe. Conductivity,
          temperature, depth, dissolved
          oxygen, pH, transmissivity, and
          chlorinity/salinity are measured
       and recorded throughout the
       water column.

To date, these variables have been
consistent over the length of the transect
for each cruise.

In keeping with the objective of low
cost, practical applications of biological
community measurements for resource
impact detection; standard, basic but
robust taxonomic indexes were applied
to the data. The underlying premise for
the indexes is that once the raw data for
species and numbers of individuals per
species are compiled, the investigator's
primary question is whether or not there
is a detectible impact. More refined
indexes and indicators can later be
applied or developed as needed.  In this
regard, the treatments selected for this
project were: total number of
individuals, total number of taxa
(species), evenness index, Simpson's
dominance index, Margalef's taxa
richness index, and Shannon-Wiener
index of general  diversity. The
appropriate equations were taken from
Odum(1971).

13.6.3 Study Results

           Fish Survey Data

Analysis of the fish data showed no
significant differences in trawl data
between the stations in either summer or
winter collections for either number of
taxa or numbers  of individuals. These
results are based on single tows at each
station twice a year (summer and
winter) for three years. Concern that
this response results from too little data
led to a trial in summer 1995, with three
replicate trawl surveys over the nine
stations, i.e., sequential tows of stations
"A"  through "I"  conducted three times
in one day. The results were still
insignificant.  Better results might be
possible by replicating each station
13-42
                              Case Studies

-------
   individually. Eaton (1994) reported that
   for West Coast fish surveys in a
   Washington estuary, four replicate tows
   per station are necessary to obtain
   meaningful data within a fairly confined
   waterway. Qualitatively, taxa and
   number of individuals overall shifted
   considerably between summer and
   winter surveys at the nine stations.
   Greater numbers of both species and
   individuals (excepting winter runs of
   striped anchovy, Anchoa hepsetus) occur
   in the summer surveys.

       Benthic Macroinvertebrate Data

   Benthic macroinvertebrate results have
   been much more promising, but the
   same seasonal trend observed for fish
   for number of taxa and number of
   individuals has prevailed. Summer
   measurements are much more indicative
   of the condition of the benthic
   macroinvertebrate assemblages (some of
   the winter data is incomplete). The data
   in this instance is for three replicates at
   each station twice a year for three years.
   Significant differences are evident
   between each of the outfall sites and the
   other stations in the summer data
   (Figure 13-8a,b). The graphic data for
   number of individuals is intriguing in
   that it suggests enhanced and or
   enriched conditions at station "A",
   perhaps from the Delaware Bay
   discharge, and at the Ocean City outfall
   site.

   When numbers of species are compared,
   a more negative trend in outfall impact
   is evident, especially for the Bethany
   Beach outfall station (Figure 13-9a). A
   similar pattern occurs at Ocean City, but
   is not as strong (Figure 13-9b). Ludwig
   and  Reynolds (1988) state that a simple
   count of the number of species present,
   for samples of equal size, avoids some of
   the problems of using indexes which
   combine and may confound a number of
variables that characterize community
structure.

However, in this instance, it appears
that at least some indexes enhance the
measurement of outfall perturbations.
Box plots of Simpson's dominance index
(Figure 13-10a, b), the Shannon-Wiener
index of general diversity  (Figure 13-
lla, b), and particularly Margalef's
richness index (Figure 13-12a, b) (Odum
1971), over the three years of summer
data provide strong indications of the
negative effect of both discharges on the
benthic macroinvertebrate community.

13.6.4 Discussion and Conclusions

The nearfield/farfield survey design for
biological surveys, together with basic
indexes of community structure, appears
to work equally well on the West coast
and in Mid-Atlantic coast open water
environments (Santangelo, pers. comm.
1996). If the investigator is careful to
control for habitat characteristics, the
ends of the transect can serve as a
reference condition, the outfall stations
as test sites, and the intermediate
stations provide an indication of the
gradation of impact(s). The nine station
design of this study made it possible to
treat the  data as a combination of two
impact sites on the ambient
environment, or as two individual
studies in tandem.

 Summer benthic macroinvertebrate data
from stations "A" and "C" were
significantly different in either case,
lending confidence to the conclusion
that the wastewater discharges were
having a measurable impact on the
coastal marine environment.  This is of
particular interest because routine water
quality and sediment investigations at
the sites failed to consistently detect
change between the outfalls and the
surrounding stations. The biocriteria
technique employed appears to be not
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-43

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10000

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Figure 13-8a
Total number
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Bethany
Beach sites;
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                        Figure 13-8b
                        Total number
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                        invertebrate
                        individuals at
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                        sites;
                        summer
                        data, n=9.
13-44
                                Case Studies

-------
               Figure 13-9a
              Total number
              of macro-
              invertebrate
              taxa at
              Bethany
              Beach sites;
              summer
              data, n=9.
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             Figure 13-9b
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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                              13-45

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                                                                                             Figure 13-10a
                                                                                             Simpson's
                                                                                             dominance index
                                                                                             for macroinverte-
                                                                                             brates at Bethany
                                                                                             Beach sites;
                                                                                             summer data,
                                                                                             n=9.
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                                                                                             Figure 13-10b
                                                                                             Simpson's
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                                                                                             for macroinverte-
                                                                                             brates at Ocean
                                                                                             City sites;
                                                                                             summer data,
                                                                                             n=9.
13-46
Case Studies

-------
       Figure 13-11a
       Shannon-Wiener
       diversity index for
       macro-
       invertebrates at
       Bethany Beach
       sites; summer
       data, n=9.
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       Figure 13-11 b
       Shannon-Wiener
       diversity index for
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       invertebrates at
       Ocean City sites;
       summer data,
       n=9.
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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                                                    13-47

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Figure 13-12a
Richness index
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sites; summer
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                                                                             Ocean City sites;
                                                                             summer data,
                                                                             n=9.
13-48
Case Studies

-------
   only practical, but sensitive as well,
   detecting impacts that might not
   always be observed with routine
   chemical testing.  Standard indexes
   such as Margalef's Richness  Index,
   Simpson's Dominance Index and
   Shannon-Wiener's Diversity Index are
   robust and were entirely appropriate
   for this survey.

   The Smith-Mclntyre and Young grabs
   were both entirely adequate, but the
   Young was more efficient and safer to
   work with, while the Smith-Mclntyre
   was more accessible through the top
   for sub-sampling. Three replicate
   grabs were sufficient to generate
   meaningful data, but it may  be
   possible to reduce the costs of the
   taxonomic operation by sub-sampling
   the grabs. An attempt was made to do
   this by mechanically splitting the
   intact samples in half with a sheet
   metal partition. It failed because the
   surficial organisms were unequally
   distributed as the sample drained and
   the ship rolled. Subcores of 5-cm
   diameter might be a better alternative
   requiring far less analytical effort.
   Similarly, sieving and counting only
   the top 5-cm  of the sample as a
   variation of the technique reported by
   Diaz in Gibson et al. (1993) might be a
   more cost-effective approach.
   Another alternative to reduce the
   number of organisms dealt with is to
   double the sieve size to 1.0-mm, as
   practiced by many investigators. Any
   of these options could be explored and
   adopted as a cost-effective way to
   accomplish the benthic macroinverte-
   brate counts as long as the
   investigator ascertains that they
   produce reliable results consistent
   with those derived from the larger
   grab samples.

   The 6-m otter trawl used in the fish
   surveys performed well and is
   believed to be appropriate for both
coastal and estuarine biosurveys.
However, the fish community does
not appear to be very responsive to
sewage discharge effects in this
coastal area. This is probably because
of the mobility of the fish in these
open coastal waters, their seasonal
migrations, and the potential sport
and commercial fishing pressure
confounding the survey effort; but the
sampling replication factor was not
adequately investigated in this study.

For biocriteria development and site
monitoring, it is important to account
for  seasonality.  For the Mid-Atlantic
Bight, late June  to early September
appears to be a time of relatively high,
stable community productivity and an
optimal index period if once a year
sampling is preferred. According to
the Delaware and Maryland chambers
of commerce, since Bethany Beach and
Ocean City are summer resort
communities, their populations
increase at least ten-fold in warm
weather (pers. comm. 1990).  Their
lower winter discharge rates, together
with a natural cyclic depletion of the
marine community, may account for
the failure of our data to reveal
sewage impacts in  this season. This
may not be the case with a year-round
municipality of fairly large size. In
any case, if the responsible agency can
afford to sample at least occasionally
in winter, that baseline biological data
may prove invaluable in the event of
oil spills or other marine accidents.

After the assessment of results from
an initial set of 1.6-km interval station
transects, the investigator may choose
to delete some of the intermediate
reference stations and replace them
with a more diagnostic set of near
discharge monitoring stations. It will
then be possible to assess the relative
expansion or contraction of the area of
impact over time and  in response to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                  13-49

-------
   plant operation declines or
   improvements. The initial and
   subsequent reference site data become
   part of the biocriteria which can be
   used as a benchmark to assess
   operational efficiencies, management
   initiatives, and the adequacy of
   NPDES permits.

    Additional investigations for which
            results are pending

   1.  Because vertical splitting of each
   grab sample was determined to be an
   unsatisfactory approach to reducing
   sample volume and cost, we are
   attempting to test a horizontal
   approach at approximately the 5-cm
   depth level because most of the
   organisms observed are
   predominantly surficial sediment
   dwellers. In September 1996, the
   stations were sampled with three
   replicate grabs as before, but
   approximately the top 5-cm of
   sediment was scraped off of each
   sample and sieved through a 0.5-mm
   mesh screen. The remainder of the
   sample was similarly processed. We
   will count both fractions, combine the
   results and evaluate as usual.

   This information will then be
   compared to a similar assessment
   using just the top 5-cm fraction. If the
   same impact information results, it
   may be possible to monitor the
   stations using just the surface
   fractions as long as these results are
   periodically calibrated against full
   grab counts.

   2.  On the January, 1997 survey, all of
   the stations sampled for benthic
   macroinvertebrates were sieved first
   through a 1.0-mm screen and then
   through the 0.5-mm screen. These
   separate fractions can be combined to
   produce a comprehensive result. The
   1.0-mm fraction can then be compared
to this control to assess the relative
efficacy of this technique as a cost
saving approach for these waters. The
process  was repeated during the
summer of 1997 and the results of
both trials will be evaluated when
taxonomic studies, which were
delayed (for this and the above study)
are completed.

3. Because of the promising results of
this project so far, three additional
stations have been added around each
outfall station, e.g., "C" at Bethany
Beach and "C" at Ocean City. The
pattern  creates a roughly equilateral
triangle with  approximately 0.46-km
legs and a station at each apex with
the original station in the middle of
the triangle. The intent here is to see if
it is possible to refine the spatial
assessment of the zone of impact for
each outfall analogous to the concept
illustrated in  Figure 13-13.

13.6.5  Use  of the Bethany Beach-
        Ocean City Data to
        Illustrate Biocriteria
        Development

An example of biocriteria
development using this pilot project is
as follows.

Classification and Reference Site
Selection: A review of the data as
presented in Figures 13-7 through 13-
12 suggests that stations A, E, and I
are appropriate reference sites being
at the center and extreme ends of the
transect and equidistant from the
defined locales of effluent discharges
being evaluated. General water
quality  conditions, including salinity
and depth, are consistent for all
stations. Grain size, although shifting
from sand and gravel in the north at
station A to sand at station I in the
south represents the general benthic
habitat condition of the area with an
13-50
                             Case Studies

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Figure 13-13
Proposed
diagnostic
nearfield station
array.
   net longshore current
                         discharge
    • A
    • B

D1»*C»D3
    • D «D4
D2« 9 E» D5

    • F
    • G
                                    #
                                        Data can be used to plot not only
                                        impact, but relative expansion or
                                        contraction of the area of impact over
                                        time.
                                       A   B   CL
                                                         D
                                                     SERIES
                                                   -STATIONS—^
                          E   F   G
    acceptable variation for the region.
    Thus, the stations (or sites) are
    considered to all be of comparable
    habitat characteristics, and because of
    the spatial arrangement, sites A, E,
    and I are selected as references.

    Reference Condition: The reference
    condition may be derived from the
    interquartile range of scores of the
    values of the biotic condition
    measured at the reference sites. Table
      13-13 presents the range of those
      values for the summer parameters
      measured at each of the three
      reference sites and the mean range of
      those scores. The range was selected
      over mean or median values to
      accommodate the variability of the
      biological data.  This mean range is
      the reference condition or minimally
      impacted (by human activities, e.g.
      sewage discharge, all other factors
      being considered equal) condition for
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                        13-51

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   Table 13-13. Establishment of reference condition using the mean of the interquartile range of scores for three
   reference sites.
Inter-quartile Range of Values
Station
A
E
I
Mean Score
Individuals
427-3049
281-474
136-841
281-1455
Taxa
46-71
40-49
27-42
38-54
Simpson's
Index
0.075-0.161
0.076-0.224
0.129-0.260
0.093-0.215
Shannon-
Wiener
2.597-3.137
2.262-3.889
1.993-2.524
2.284-3.183
Richness
7.3-9.1
6.6-8.0
5.3-6.0
6.4-7.7
   this Maryland-Delaware reach of the
   Mid-Atlantic Bight.

   Biocriteria: The elements of a
   biocriterion are: (1) historical
   information about the area; (2) present
   reference condition information; (3)
   empirical modeling of data if needed;
   and (4) an assessment of this
   preceding information by a locally
   familiar panel of specialists.

   (1) There is insufficient local historical
   information or data to establish a
   trend against which the reference
   condition data can be compared.

   (2) The present reference condition
   data is presented above.

   (3) The indexes used to compile the
   raw data constitute the only modeling
   element since this is a site specific
   assessment.

   (4) The authors of this manual are
   surrogates for a panel of local
   specialists which would likely consist
   of USEPA, US Fish and Wildlife
   Service, NOAA, and State biologists
   and water resource managers.

   Consequently, the reference site data
   and index scores presented here
   essentially comprise by default, the
   candidate biocriteria for the purposes
   of this study.  However, it is
important to note that the other
elements of development of a
biocriterion should not be casually
dismissed. While the reference
condition is essential, with a large
available historical database these
present values might well be adjusted
either up or down to accommodate
the historical trend for the area.

Assessment Comparing Biocriteria to
the Test Sites: The test sites at "C"
(Bethany Beach, DE outfall)  and at
"C" (Ocean City, MD outfall) are then
compared to the biocriteria as
illustrated in Table 13-14.

Neither outfall site completely meets
the range of criteria derived from the
reference condition for any of the
metrics applied, although the Bethany
Beach outfall approximates the
criterion for number of taxa present.
It should be noted that the outlier at
reference station "A" (perhaps caused
by Delaware Bay enrichment) raises
this criterion range at the expense of
the Bethany Beach outfall. The Ocean
City outfall nearly fits the diversity
index criterion.  However the outfall
far exceeds the number of individuals
category by more than three times the
criterion.  This reflects several
instances when the benthic grab was
overwhelmed by polychaete worms, a
condition usually indicative of sewage
pollution.
13-52
                             Case Studies

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   Table 13-14. Comparison of the reference condition derived biocriteria to the interquartile range of scores at the
   Bethany Beach and Ocean City outfalls.
Variable
No. Indiv.
No. Taxa
Simps. Dom.
Shan.-Wien. Dl
Richness
Biocriteria
281-1455
=/>38-54
=/<0. 093-0. 215
=/>2.284-3.183
=/>6.4-7.7
Bethany Beach
Outfall
260-1988
28-43
0.171-0.642
0.970-2.648
4.6-5.8
Ocean City
Outfall
49-6,492
13-49
0.179-0.643
1.855-2.883
3.1-5.7
   This instance of near exceedance of
   one of the criteria in each case
   illustrates the importance of using
   several biological metrics to establish
   a reference condition which best
   represents a diverse and healthy
   community, and which contributes to
   more robust and sensitive biocriteria.

   Conclusion: For a formal criteria
   development program, more data are
   required, but the indexes applied
   appear to ably translate the data into
   workable criteria.  Ironically, the
   number of individuals and number of
   taxa metrics individually do not
   reflect apparent conditions as well as
   the indexes which combine these
   primary variables.

   Recommendations: The stations
   should continue to be monitored by
   USEPA Region in biologists and the
   data set further developed. The long
   term areal impact of the discharges
   should be better assessed using the
   additional near-discharge stations
   described above.  Changes in sieve
   size and use of grab fractions, if
   justified, will help reduce the cost of
   the monitoring.

   Eventually, as a further cost reduction
   measure, it may be possible to
   monitor just stations "A", "C", "E",
   "G", and "I". However, periodically
   the outfall stations should be
intensively monitored to determine if
the zones of impact are expanding or
contracting. The combined
information of criteria comparisons
and impact zone measurements
should provide valuable information
for NPDES permit evaluations at
Bethany Beach and Ocean City.

This technique and evaluation
approach may prove particularly
helpful as Eastern Seaboard
development continues to increase
and more coastal  communities seek
ocean discharge permits for their
municipal effluents.

Primary Contact:  George Gibson, Jr.
(4304), USEPA, Office of Water, Office
of Science and Technology
1200 Pennsylvania Avenue, NW
Washington, DC 20460
410-305-2618
gibson.george@epa.gov
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   13.7  Environmental Quality
          of Estuaries of the
          Carolinian Province:
          1995

   13.7.1  Background/Objectives

   A study was conducted to assess the
   environmental condition of estuaries in
   the EMAP Carolinian Province (Cape
   Henry, VA - St. Lucie Inlet, FL; Figure
   13-14). The objectives of this study are
   being addressed using a probability-
   based sampling design, under which a
   large regionally extensive population of
   randomly selected sites is sampled from
   year to year, following earlier EMAP-E
   designs (Strobel et al. 1994, Summers et
   al. 1993). This design makes it possible
   to produce unbiased estimates of the
   percent area of degraded vs.
   undegraded estuaries, based on a series
   of indicators of environmental quality.
   Overall, the objectives of the program
   are to:

   *•   Assess the condition of estuarine
       resources of the Carolinian Province
       based on a variety of synoptically
       measured indicators of
       environmental quality;

   *•   Establish a baseline for evaluating
       how the condition of these resources
       are changing with time;

   *•   Develop and validate improved
       methods for use in future coastal
       monitoring and assessment efforts.

   A total of 87 randomly located stations
   were sampled from July 5 - September
   14,1995 in accordance with the
   probabilistic sampling design.
   Wherever possible, synoptic measures
   were made of: 1) general physical
   habitat condition, 2) pollution exposure,
   3) biotic conditions, and 4) aesthetic
   quality. Percentages of degraded vs.
undegraded estuarine area were
compared to results of a related EMAP
survey conducted in 1994 in this same
region as part of a multi-year
monitoring effort.

13.7.2  Methods

An overall goal of EMAP is to make
statistically unbiased estimates of
ecological condition with known
confidence.  To approach this goal, a
probabilistic sampling framework was
established among the overall
population of estuaries comprising the
Carolinian Province.  Under this design,
each sampling point is a statistically
valid probability-based sample.  Thus,
percentages of estuarine area with
values of selected indicators above or
below suggested environmental
guidelines can be estimated based on the
conditions observed at individual
sampling points. Statistical confidence
intervals around these estimates also can
be calculated.  Moreover, these estimates
can be combined with those for other
regions that were sampled in a
consistent manner to yield national
estimates of estuarine condition. This
section describes in brief how stations
were selected using the probabilistic
design (see also Rathbun 1994).
Supplemental sites, selected non-
rand omly in clean areas and in
suspected polluted areas, were included
in the survey and are discussed below.

Sampling sites in 1995 consisted of 87
base stations and 21 supplemental
stations. Base stations were randomly
selected sites that made up the
probability-based monitoring design.
Four replicate bottom grabs were
collected from each station with a 0.04-
m2 young grab sampler. Data collected
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-55

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        Figure 13-14
        1995 Carolinian
        Province sampling
        stations.
                                                           VA
              NC
                                                    SC
                                           GA
                                                       EMAP-E Carolinian Province
                                                            Sampling Stations

                                                               1995

                                                    \
                                                  FL
   from these sites were used to produce
   unbiased estimates of estuarine
   condition throughout the province
   based on the various synoptically
   measured indicators of environmental
   quality.  The province-wide distribution
   of base sites is shown in Figure 13-14.
   Supplemental stations were selected
   non-randomly in areas for which there
   was some prior knowledge of the
   ambient environmental conditions.
   These sites, which represented both
   pristine areas and places with histories
   of anthropogenic disturbance, were used
   to test the discriminatory power of
   various ecological indicators included in
   the program. Data from supplemental
   sites were not included in the
   probabilistic spatial estimates.

   As in other EMAP-E provinces (Strobel
   et al. 1994, Summers et al. 1993), the
   sampling design for the base sites in the
   Carolinian Province was stratified based
mainly on the physical dimensions of an
estuary.  Table 13-15 breaks down the
estuarine resources of the Carolinian
Province by their size designation.
Stratification of the overall sampling
area into classes of estuaries with similar
attributes was necessary in order to
minimize within-class sampling
variability. Also, it was not feasible to
sample all of the different types of
estuaries that exist within a broad
geographic region at the same spatial
scale. Stratification by physical
dimensions of an estuary was adopted
because: 1) such attributes usually show
minimal change over extended periods;
2) alternative classification variables
such as salinity, sediment type, depth,
and extent of pollutant loadings would
result in the definition of classes for
which areal extents could vary widely
from year to year; 3) data for  physically
based classes can be aggregated  into
geographic units that are meaningful
13-56
                               Case Studies

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   Table 13-15. Estuarine resources of the Carolinian Province.

All Years
Number of
Estuaries
Area
Represented
(km2)
In 1995
Number of
Stations
Area
Represented
(km2)
Province Large
Estuaries
200 3
11,622.1 5,581.1
88 16
6,991.8 4,480.0
Small
Estuaries
194
4,907
55a
1,377.8
Large Tidal
Rivers
3
1,134
17b
1,134
    Station count includes 6 replicate stations
   bStation count includes 3 replicate stations

   from a regulatory or general-interest
   perspective; and 4) estuarine boundaries
   can be delineated more readily and
   accurately from maps or charts of the
   physical dimensions of coastal areas
   than from maps of sediment or water-
   column characteristics.

   Selection of base-site sampling
   approaches varied on the physical
   characteristics of the particular estuary
   being sampled.  Base sites in all estuaries
   were selected using an approach similar
   to the one used in the EMAP
   Louisianian Province (Summers et al.
   1993). In large estuaries, sites were
   selected using a sampling grid
   approach. A triangular lattice was
   placed initially over the study region
   and the resulting grid shifted randomly.
   In large tidal rivers, base sites were
   selected randomly, using a "spine and
   rib" approach.  Finally, base sites in
   small estuaries were selected using a
   random list-frame approach, also similar
   to the approach used in the EMAP
   Louisianian Province (Summers et al.
   1993). Table 13-16 lists the core
   environmental indicators sampled at the
   various sites.
   A standard series of environmental
   parameters was measured at each of the
base stations to provide a consistent set
of synoptic data for making province-
wide estimates of estuarine condition.
These "core" environmental indicators
included measures of general habitat
conditions, pollutant exposure, biotic
integrity, and aesthetic quality (Table 13-
16).  Habitat indicators describe the
physical and chemical conditions of
sample sites, and provide basic
information about the overall
environmental setting. Exposure
indicators provide measures of the types
and amounts of pollutants, or  other
adverse conditions, that could be
harmful to resident biota or human
health.  Biotic condition indicators
provide measures of the status of
biological resources in response to the
surrounding environmental conditions.
Aesthetic indicators provide additional
measures of environmental quality from
a human perceptual perspective.  There
is a fair amount of overlap among these
various indicator categories. For
example, some aesthetic indicators
(presence of oil sheens, noxious
sediment odors, and highly turbid
waters) could also reflect adverse
exposure conditions.  Another example
is dissolved oxygen (DO), listed  as an
exposure indicator because of  the
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   Table 13-16.  Core environmental indicators for the Carolinian Province.
     Habitat Indicators
     Water depth
     Water temperature
     Salinity
     Density stratification of water column
     Dissolved oxygen concentrations
     PH
     Percent silt-clay content of sediments
     Percent TOC in sediments
     Sediment acid-volatile sulfides (Yr. 2 only')	
     Exposure Indicators
     Low dissolved oxygen conditions
     Sediment contaminants
     Contaminants in fishes and invertebrates (Yr. 2 only)
     Sediment toxicity	
     Biotic Condition Indicators
     Infaunal species composition
     Infaunal species richness and diversity
     Infaunal abundance
     Benthic Infaunal Index
     Demersal species composition (invertebrates and fish)
     Demersal species richness and  diversity
     Demersal species abundance
     Demersal species lengths
     External pathological abnormalities in demersal biota
     Aesthetic Indicators
     Water clarity
     Anthropogenic debris (sea surface and in trawls)
     Noxious sediment odors (sulfides, petroleum)
     Oil sheens (sea surface and bottom sediments)
     "Results not shown in this report
   potential adverse biological effects of
   low oxygen concentrations, but which
   also is clearly a measure of general
   habitat conditions. These various core
   environmental parameters included
   ones used in other EMAP-E provinces
   (Strobel et al. 1994, Summers et al. 1993)
   to support regional comparisons and to
   provide a means for producing
   combined nationwide estimates of
   estuarine condition.

   In addition to making the standard
   EMAP-E measurements,  an emphasis
   was placed on developing and
   validating other complementary
   methods to aid in evaluating the quality
   of southeastern estuaries. Such
indicators, some still in the development
stage, are listed in Table 13-17. They
include sediment bioassays with
alternative test species, such as the
amphipod Ampelisca verrilli as an
alternative to A. abdita in standard 10-
day solid-phase toxicity tests; assays
with additional sublethal biological
endpoints, such as effects on feeding,
growth and fertilization success in key
estuarine organisms; additional indices
of environmental quality for tidal
marshes and estuarine fish assemblages;
and the incorporation of additional
exposure indicators, such as porewater
ammonia and hydrogen sulfide
concentrations, to help in the
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                                Case Studies

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   Table 13-17.  Exposure indicators under development in the Carolinian Province.
     10-day acute-toxicity sediment bioassay with alternative amphipod species, Ampelisca
     verrilli

     1-week sublethal bioassay for testing effects of sediment exposure on growth of juvenile
     clams Mercenaria mercenaria

     96-hour sublethal bioassay for testing effects of sediment exposure on feeding rates of
     Ampelisca verrilli

     1-hour sublethal bioassay using gametes of oysters Crassostrea virginica and clams
     Mercenaria mercenaria for testing effects of sediment exposure on fertilization success

     Sediment porewater ammonia and hydrogen sulfide concentrations
   interpretation of sediment toxicity
   results.

   13.7.3  Benthic Infaunal Index

   The modified IBI approach of Weisberg
   et al. (1997) was used to develop a
   benthic index for southeastern estuaries.
   The goal was to develop an index that
   possessed the following features: (1)
   suitable for use throughout the region,
   (2) applicable to a broad range of
   habitats, (3) easy to understand and
   interpret, and (4) effective in
   discriminating between undisturbed
   and disturbed conditions associated
   with human influences.

   Results of the 1994 survey (Hyland et al.
   1996) indicated that several natural
   abiotic factors (salinity, latitude, silt-
   clay, and TOC) had strong influences on
   infaunal variables. In the IBI approach,
   an attempt is made to account for such
   variations by defining habitat-specific
   reference conditions at sites free of
   anthropogenic stress and then
   comparing  conditions in samples with
   the expected reference conditions for
   similar habitat types. The basic steps
   used to develop the index involved: (1)
   defining major habitat types based on
   classification analysis of benthic species
   composition and evaluation of the
   physical characteristics of the resulting
   site groups; (2) selecting a development
data set representative of degraded and
undegraded sites in each habitat (3)
comparing various benthic attributes
between reference sites and degraded
sites for each of the major habitat types;
(4) selecting the benthic attributes that
best discriminated between reference
and degraded sites for inclusion in the
index; (5) establishing scoring criteria
(thresholds) for the selected attributes
based on the distribution of values at
reference sites; (6) constructing a
combined index value for any given
sample by assigning an individual score
for each attribute, based on the scoring
criteria, and then averaging the
individual scores; and (7) validating the
index with an independent data set.

Data from undegraded sites sampled in
1993 and 1994 were first analyzed using
classification (cluster) analysis of benthic
species composition and evaluation of
the physical factors associated with the
resulting station clusters to define major
habitat types. Several types of cluster
analyses were performed.  The one that
produced the clearest results was a
normal (Q-mode) analysis run on loglO-
transformed data with flexible sorting as
the clustering method and Bray-Curtis
similarity as a resemblance measure (see
Boesch 1977).
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   Differences in abiotic factors (salinity,
   latitude, % silt-clay, TOC) among the
   resulting station clusters were examined
   by ANOVA and pair-wise multiple
   comparison tests (Duncan's test and
   Tukey's HSD) to help delineate the
   major habitat types. Four site groups
   resulted: oligohaline-mesohaline
   stations (<8%) from all latitudes,
   polyhaline-euhaline stations (>18%)
   from northern latitudes (>34.5° N),
   polyhaline-euhaline stations from
   middle latitudes (30-34.5° N) and
   polyhaline-euhaline stations from
   southern latitudes (<30° N). Seventy-
   five stations sampled during the 1994
   survey were selected for the
   development data set.  These stations
   provided data from both degraded and
   undegraded sites in each of the four
   habitats. Classification of stations  into
   degraded and undegraded categories
   was based on the combination of
   chemical and toxicological criteria,
   mainly DO, and toxicity of sediment
   bioassays.  Marginal sites (minor
   evidence of stress with toxicity in only
   one assay and no accompanying adverse
   contaminant or DO conditions) were not
   included in the development data  set.

   Forty different infaunal attributes were
   tested with the 1994 development data
   set to determine those that best
   discriminated between undegraded and
   degraded sites within each habitat. This
   initial list of attributes included various
   measures of diversity, abundance,
   dominance, and presence of indicator
   species (e.g., pollution-sensitive vs.
   pollution-tolerant species, surface vs.
   subsurface feeders).  A subset of six
   candidate metrics was identified for
   possible inclusion in the index. Key
   criteria considered in the selection  were
   whether differences were in the right
   direction and statistically significant
   (based on results of Student t-tests,
   Mann-Whitney LT-tests, and
   Komogorov-Smirnov two-sample tests;
at a = 0.1).  These six metrics were: mean
number of taxa, mean abundance (all
taxa), mean H' diversity, 100 - %
abundance of the two most numerically
dominant species, and two different
measures of % abundance of pollution-
sensitive taxa.

Scoring criteria for each of these metrics
were developed based on the
distribution of values at undegraded
sites: score of 1, if value of metric for
sample being evaluated was in the lower
10th percentile of corresponding
reference-site values; score of 3, if value
of metric for sample was  in the lower
10lh-50'h percentile of reference-site
values; or score of 5, if value of metric
for sample was in the upper 50th
percentile of reference-site values.
Scoring criteria were determined
separately for each metric and habitat
type. A combined index value was then
computed for a sample by assigning a
score for each component metric (based
on the individual scoring criteria for the
corresponding habitat type) and then
averaging the individual scores. A
combined score < 3 suggested the
presence of a degraded benthic
assemblage (some apparent level of
stress to very unhealthy)  given that its
condition, based on the averaged
metrics, deviated from conditions
typical of the "best" (upper 50th
percentile) reference sites.

Forty different combinations of the six
candidate benthic metrics were further
evaluated to determine which
represented the best combined index.
The metric combination that produced
the highest percentage of correct
classifications; i.e., agreement with
predictions of sediment bioeffects based
on the chemistry  and toxicity data, was
then selected to represent the final
index. The resulting final index was the
average score of four metrics: (1) mean
abundance, (2) mean number of taxa, (3)
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                               Case Studies

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   100 - % abundance of the top two
   numerical dominants, and (4) %
   abundance of pollution-sensitive taxa
   (i.e., percent of total faunal abundance
   represented by Ampeliscidae +
   Haustoriidae + Hesionidae + Tellinidae
   + Lucinidae + Cirratulidae + Cyathura
   polita + C. burbanki.  The final combined
   index correctly classified 93 % of the
   stations province-wide in the
   development data set and 75 % of the
   stations in the independent validation
   data set.

   13.7.4   Results

   The multimetric index of biotic integrity
   index — consisting of measures of
   abundance, number of species,
   dominance, and relative abundance of
   pollution-sensitive taxa — produced a
   high percentage of correct station
   classifications; i.e., agreement with
   predictions of sediment bioeffects based
   on chemistry and toxicity data, in
   comparison to other metric
   combinations that were tested. The
   index correctly classified stations
   province-wide 93 %  of the time in the
   1994 development data set and 75% of
   the time in the independent 1993/1995
   validation data set.

   Figure 13-15 illustrates that stations with
   index values below 3 (suggestive of
   some apparent stress to highly degraded
   conditions) usually coincided with sites
   considered to be degraded based on a
   combination of chemistry and toxicity
   data, and that stations with scores of 3
   or higher usually coincided with
   undegraded sites. Agreement is the
   highest at the two ends of the scale.
   Thus, the evaluation of sediment
   quality based on the benthic index
   appears to agree reasonably well with
   predictions of sediment bioeffects based
   on the combined exposure data.
   Additional comparisons revealed that
   the benthic index detected a higher
percentage of samples where bioeffects
were expected (based on sediment
quality guideline exceedances) than did
any of the four individual sediment
bioassays (Fig. 13-16a) or individual
infaunal attributes (Fig. 13-16b). Benthic
index values for base stations sampled
in 1995 covered the full scale from 1 to 5.
Values < 1.5 (clearest evidence of a
degraded benthos) occurred at 14 of the
86 base sites, which represented 21 % of
the province area (Fig.13-17).
Transitional values of 2 to 2.5
(suggestive of some possible stress)
occurred at an additional 14 sites,
representing another 15% of the
province. Values >3 (suggestive of an
undegraded benthos) occurred at the
remaining 58 base sites, representing
64% of the area of the province.

By estuarine class, the estimated
percentage of area with degraded
benthic assemblages was the highest for
large tidal rivers and the lowest for large
estuaries (Fig. 13-18). By subregion, this
percentage was the highest in Florida
estuaries and the lowest in South
Carolina/Georgia estuaries.

Extracted or summarized from the
EMAP Carolinian Province Report,
Annual Statistical Summary for the 1995
EMAP - Estuaries Demonstration Project
in the Carolinian Province (Hyland et al.
1998).

Primary Contact: Jeffrey L. Hyland,
Carolinian Province Office,
NO A A/National Ocean Service
217 Fort Johnson Rd. (P.O. Box 12559),
Charleston, SC 29422-2559
843-762-5415
jhyland@rdc.noaa.gov
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-61

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      Figure 13-15
      Frequency distribution
      of index scores for
      undegraded vs.
      degraded stations in
      1993/1995
      "development" data
      set.
   5fi
   40
           Frequency Distribution of Index Scores
o'-
er)
                              30
                           ro
                           ~j — i
                          CO
                           O>
                          Q_
                              20
                              10
Habitat
Undegraded
Degraded
                                                      Index Score
13-62
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                           A. Benthic Index vs. Bioassays
               100
                       Ampetisca Afrpelisca  Microtox    Seed    Benthic
                         atxtta     verrlli             Clarn    Index
                        B, Bmthlc taCknc vs. Blotlc Attributes
                1DQ
                 80
             IB
             •O
             «
             a.
             a
             65
                            H'      racnnes   Wundince  Banlhfc I nOai
Figure 13-16
Comparison of
the percent of
expected
bioeffects
detected with the
benthic index vs.
(A) four sediment
bioassays and
(B) three
individual
infaunal
attributes.
"Percent
expected
bioeffects - #
stations (1995
core &
supplemental)
where an effect
was detected / #
stations with > 1
ER-M/PEL or > 3
ER-L/TEL
exceedance.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
               13-63

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         Figure 13-17
         Percent area
         (and 95% C.I.) of
         CP estuaries with
         high(> 3),
         intermediate (>
         1.5 to < 3), and
         low(< 1.5)
         benthic index
         values.
 Benthic Index
Healthy (> 3)
So me stress (> 1.5 to < 3)
Very unhealthy (< 1.5)
         Figure 13-18
         Comparison of
         benthic index
         values by
         estuarine class
         and subregion.
      Benthic Index
100


 80
                            i   60
                                40


                                20


                                 0
                                        I
      ] Some stress (> 1j5to<£
      I Very unh ea tthy (£ 1.5)
                  I
                          t
                                       Province  Large  Small   Tidal  VA-NC SC-GA   FL
                                                  EstuaryClass
                       Subregion
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   13.8  Assessment of the
          Ecological Condition of
          the Delaware and
          Maryland Coastal Bays

   13.8.1 Background

   The coastal bays formed by the barrier
   islands of Maryland and Delaware are
   important ecological and economic
   resources whose physical characteristics
   and location make them particularly
   vulnerable to the effects of pollutants. A
   first step in developing management
   strategies for these systems is to
   characterize their present condition and
   how it has changed over time. This
   project was undertaken as a
   collaborative effort of the Coastal Bays
   Joint Assessment (CBJA), a group of
   state and federal agencies, to assess the
   ecological condition of this system and
   fill a data void identified in previous
   characterization studies.

   Two hundred sites were sampled in the
   summer of 1993 using a probability-
   based sampling design that was
   stratified to allow assessments of the
   coastal bays as a whole, each of four
   major subsystems within coastal bays
   (Rehoboth Bay, Indian River Bay,
   Assawoman Bay, and Chincoteague
   Bay) and four target areas of special
   interest to resource managers (upper
   Indian River, St. Martin River, Trappe
   Creek, and artificial lagoons). Measures
   of biological response, sediment
   contaminants, and eutrophication were
   collected at each site using the same
   sampling methodologies and quality
   assurance/quality control procedures
   used by EMAP. The consistency of the
   sampling design and methodologies
   between this study and EMAP allows
   unbiased comparison of conditions in
   the coastal bays with that in other major
   estuarine systems in USEPA Region III
   that are sampled by EMAP. As an
additional part of the study, trends in
fish communities structure were
assessed by collecting monthly beach
seine and trawl measurements during
the summer at about 70 sites where
historic measurements of fish
communities have been made.

13.8.2  Methods

Sampling sites were selected using a
stratified random sampling design in
which the coastal bays were stratified
into several subsystems for which
independent estimates of condition were
desired:

*•   Upper Indian River;

*•   Trappe Creek/Newport Bay;

*•   St.  Martin River;

>   Artificial lagoons throughout the
    coastal bays;

>   All remaining areas within
    Maryland's coastal bays; and

>   All remaining areas within
    Delaware's coastal bays.

The upper Indian River, Trappe Creek,
and St. Martin River were defined as
sampling strata because resource
managers expressed particular concern
about these areas. Water quality data
suggest that each of these tidal creeks is
subject to excessive nutrient enrichment,
algal blooms, and low concentrations of
DO. These creeks are also believed to
transmit large nutrient loads (from
agricultural runoff) downstream
contributing to eutrophication
throughout the coastal bays (Boynton et
al. 1993).

Artificial lagoons were defined as a
stratum because of their high potential
for impact based on their physical
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-65

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   characteristics and their proximity to a
   variety of contaminant sources (Brenum
   1976). These dredged canal systems can
   form the aquatic equivalent of streets in
   development parcels; they already
   encompass 105 linear miles and almost
   4% of the surface area of Delaware's
   inland bays. In general, these systems
   are constructed as dead-end systems
   with little or no freshwater inflows for
   flushing. They are often dredged to a
   depth greater than the surrounding
   waters, leaving a ledge that further
   inhibits exchange with nearby waters
   and leads to stagnant water in the
   canals. The placement of these systems
   in relatively high density residential
   areas increases the potential
   contaminant input. Much of the
   modified land-use in dredged canal
   systems extends to the edge of the
   bulkheaded waters, providing a ready
   source of unfiltered runoff of lawn-care
   and pesticides. In many cases, the
   bulkhead and dock systems in these
   canal systems are built from treated
   lumber containing chromium, copper,
   and arsenic, providing another source of
   contaminants.

   Four replicate bottom grabs were
   collected from each station with a 0.04-
   m2 Young grab sampler. Of the two
   hundred sites sampled, 25 were in each
   of the first four sampling strata and 50
   were in each of the last two. Sites were
   selected by simple random sampling in
   all strata except artificial lagoons. The
   randomly selected sites were chosen by
   enhancing the base EMAP grid (Overton
   et al. 1990). A different level of
   enhancement was applied to each
   stratum to obtain the required number
   of samples.  Sites in the artificial lagoons
   were selected by developing a list frame
   (of all existing lagoons), randomly
   selecting 25 lagoons from that list, and
   then randomly selecting a site within
   each selected lagoon.
All sampling was conducted between
July 12 and September 30,1993.
Sampling was limited to a single index
period because available resources were
insufficient to sample in all seasons.
Late summer is the time during which
environmental stress on estuarine
systems in the mid-Atlantic region is
expected to be greatest owing to high
temperatures and low dilution flows
(Holland 1990). The sampling period
coincided with the period during which
EMAP sampled estuaries of the mid-
Atlantic region; therefore, data collected
in the coastal bays annually for EMAP
can be incorporated into estimates of
ecological condition generated from
Coastal Bays Joint Assessment (CBJA)
data.  That data can then contribute to
continuing development and evaluation
of EMAP indicators.

Measurements of physical
characteristics provide basic information
about the natural environment.
Knowledge of the physical context in
which biological and chemical data are
collected is important for interpreting
results accurately because physical
characteristics of the environment
determine the distribution and species
composition of estuarine communities,
particularly assemblages of benthic
macroinvertebrates. Salinity, sediment
type, and depth are all important
influences on benthic assemblages
(Snelgrove and Butman 1994, Holland et
al. 1989). Sediment grain size also
affects the accumulation of
contaminants in sediments. Fine-
grained sediments generally are more
susceptible to contamination than sands
because of the greater surface area of
fine particles (Rhoads 1974, Plumb
1981).

Depth, silt-clay content of the sediment,
bottom salinity, temperature, and pH
were measured to describe the physical
conditions at sites in the coastal bays.
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   Sediment type was defined according to
   silt-clay content (fraction less than 63-n);
   classifications were the same as those
   used for EMAP. Biologically
   meaningful salinity classes were defined
   according to a modified Venice System
   (Symposium on the Classification of
   Brackish Waters 1958).

   Healthy aquatic ecosystems require clear
   water, acceptable concentrations of
   dissolved oxygen, limited
   concentrations of phytoplankton, and
   appropriate concentrations of nutrients.
   Clear water is a critical requirement for
   submerged aquatic vegetation (SAV),
   which provides habitat for many other
   aquatic organisms (Dennison et al.
   1993).  As large concentrations of
   suspended sediment or algal blooms
   reduce water clarity, the amount of
   sunlight reaching SAV is diminished
   and the plants fail to thrive;
   consequently, critical habitat for crabs,
   fish, and other aquatic organisms is lost
   (Dennison et al. 1993). Nutrient
   enrichment causes excessive algal
   growth in the water column and on the
   surfaces of plants. As bacteria
   metabolize the excess algae, they deplete
   dissolved oxygen in the water column
   and sediments causing hypoxia and, in
   extreme cases, anoxia.

   Water quality in the coastal bays of
   Delaware and Maryland was evaluated
   using classes of indicators: measures of
   algal productivity, dissolved oxygen
   (DO), water clarity, and nutrients.
   Measures of algal biomass included the
   concentrations of chlorophyll in the
   water column and sediment, and
   phaeophytin. Secchi depth, total
   suspended solids (TSS), and turbidity
   were measured to assess water clarity.
   Nutrient measures included dissolved
   inorganic nitrogen (DIN; nitrite, nitrate,
   and ammonium), dissolved inorganic
   phosphorus (DIP), total dissolved
   nitrogen (TDN), total dissolved
phosphorus (TDP), and particulate
nitrogen and phosphorus.  Table 13-18
lists the core environmental parameters
sampled at the various sites.

Estimating the percent of eutrophied
area in the coastal bays requires
identifying threshold levels for selected
indicators that define eutrophication.
While no such levels have been
established for the coastal bays, the
Chesapeake Bay Program has
established thresholds for five water
quality parameters to  define critical
habitat requirements for supporting
SAV in a polyhaline environment
(Dennison et al. 1993); these thresholds
were used for our assessment (Table 13-
19). All but one of the SAV restoration
goal attributes were measured directly.
The light attenuation coefficient was
calculated from Secchi depth
measurements.

Threshold values of sediment
contaminants developed by Long and
Morgan (1990) and updated by Long et
al. (1995) were used to interpret
concentrations of sediment
contaminants measured in the coastal
bays.  Two values were identified for
each contaminant: an  effects range-low
(ER-L) value corresponding to
contaminant concentrations above
which biological effects begin to appear,
and an effects-range median (ER-M)
concentration, above which biological
effects are probable. Only a subset of
the contaminant samples collected for
the CBJA were processed because of cost
constraints; consequently, comparisons
were limited to the artificial lagoons and
the coastal bays as a whole.

Sediment samples for  analysis of benthic
macroinvertebrates, silt-clay content,
benthic chlorophyll, and chemical
contaminants were collected using a
0.044-m2, stainless steel, Young-modified
Van Veen  grab. Four measures of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                    13-67

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              Table 13-18. Environmental parameters forthe Maryland/Delaware Coastal Bays.
                Physical Parameters

                Depth
                % Silt/Clay content
                Salinity
                Temperature
                RH	
                Water Quality Parameters

                Chlorophyll a
                Phaeophytin
                Benthic chlorophyll
                DO (Dissolved Oxygen)
                NO2 (Nitrite)
                NO3 (Nitrate)
                Ammonium
                TON  (Total Dissolved Nitrogen)
                Orthophosphate
                TOP  (Total Dissolved Phosphorus)
                TPN  (Total Particulate Nitrogen)
                TPP  (Total Particulate Phosphorus)
                TPC  (Total Particulate Carbon)
                Secchi Depth
                TSS  (Total Suspended Solids)
                Turbidity	

                Benthic Parameters

                Abundance
                Biomass
                Number of Species
                Shannon-Wiener Index
                EMAP Index
     Table 13-19. Chesapeake Bay submerged aquatic vegetation habitat requirements fora polyhaline
     environment (Dennison et al. 1993).
Parameter
Light attenuation coefficient (kd; m"1)
Total suspended solids (mgL"1)
Chlorophyll a (ug/l)
Dissolved inorganic nitrogen (uM)
Dissolved inorganic phosphorus (uM)
Critical Value
1.5
15
15
10
0.67
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   biological response were used to
   evaluate the condition of benthic
   assemblages in the coastal bays of
   Delaware and Maryland: abundance,
   biomass, diversity, and the EMAP
   benthic index. Abundance and
   biomass are measures of total
   biological activity at a location. The
   diversity of benthic organisms
   supported by the habitat at a location
   often is considered a measure of the
   relative "health" of the environment.
   Diversity was evaluated using the
   number of species; i.e.,  species
   richness, at a location and the
   Shannon-Wiener diversity index,
   which incorporates both species
   richness and evenness components.
   The EMAP benthic index integrates
   measures of species diversity,
   composition, biomass, and abundance
   into a single value that distinguishes
   between sites of good or poor
   ecological condition (Schimmel et al.
   1994). A value of 0 or less denotes a
   degraded site at which the structure of
   the benthic community is poor, and
   the number of species, abundance of
   selected indicator species, and mean
   biomass are small.

   13.8.3    Results/Conclusions

   Major portions of the coastal bays
   have  degraded environmental quality.
   EMAP's benthic index measured 28%
   of the area in the coastal bays had
   degraded benthic communities. At
   least one sediment contaminant
   exceeding the Long et al. (1995) ER-L
   concentration (threshold of initial
   biological concern) were found in 68%
   of the area in the coastal bays.  More
   than 75%  of the area in the coastal
   bays failed the Chesapeake Bay
   Program's Submerged Aquatic
   Vegetation (SAV) restoration goals,
   which are a combination of measures
   that integrate nutrient,  chlorophyll,
   and water clarity parameters.
The tributaries to the coastal bays are
in poorer condition than the
mainstems of the major subsystems.
Previous studies have suggested that
the major tributaries to the system:
upper Indian River, St. Martin River,
and Trappe Creek are in poorer
condition than the mainstem water
bodies.  This study confirmed that
finding. The percentage of area
containing degraded benthos was
generally two to three times greater in
the tributaries compared to the rest of
the coastal bays. The percent of area
with DO less than the state standard
of 5-ppm was three to seven times
greater in the tributaries.  More than
70 %  of the area in upper Indian River
and St. Martin River and in the
artificial lagoons had chlorophyll a
concentrations exceeding the SAV
restoration goals.

Among  these systems, Trappe Creek
contained the sites in the worst
condition. Two sites in the upper
portion  of Trappe Creek had
concentrations of chlorophyll a
exceeding 350 ugL"1; algal blooms
were evident at each site. In addition,
daytime DO levels exceeding 14-ppm
were measured at both sites.
Although, supersaturated DO often
occurs in hypereutrophic waterbodies
on warm, sunny days. However, it
appears that degraded conditions in
the Trappe Creek system are spatially
limited to Trappe Creek and have not
spread to Newport Bay.
Undoubtedly, this results from the
low freshwater flow from this
tributary compared to the other
tributaries.

Moreover, the coastal bays are in as
poor or  worse condition than either
the Chesapeake or Delaware Bays
with respect to sediment contaminant
levels, water quality, and benthic
macroinvertebrate community
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                  13-69

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   condition. Based on comparison to
   EMAP data collected between 1990-
   1993, the coastal bays were found to
   have 68% chemical contamination in
   the sediments, a higher prevalence
   than either Chesapeake Bay or
   Delaware Bay. The total area in the
   coastal bays that had at least one
   sediment contaminant exceeding the
   Long et al. (1995) ER-L concentration
   was 50 % higher than the spatial extent
   EMAP estimated for Chesapeake Bay
   using identical methods, and 40 %
   higher, though not statistically
   distinguishable, from what EMAP
   estimated for Delaware Bay.

   Twenty-eight percent of the area in
   the coastal bays had degraded benthic
   communities as measured by EMAP's
   benthic index. This was significantly
   greater than the 16% EMAP estimated
   for Delaware Bay using the same
   methods and same index, and
   statistically indistinguishable from the
   26% estimated for the Chesapeake
   Bay.

   Nutrients were not measured by
   EMAP and statistically unbiased
   estimates of average concentrations
   are unavailable for either Chesapeake
   or Delaware Bays.  The Chesapeake
   Bay Program though, recently
   estimated that about 75% of the area
   in Chesapeake Bay meets SAV
   Restoration Goals.  This is more than
   three times the percent of area
   meeting SAV Restoration Goals in the
   coastal bays. Even when the turbidity
   and TSS components of the SAV
   Restoration Goals (which are naturally
   high in shallow systems), are ignored,
   almost half of the area in the coastal
   bays still fails the SAV Restoration
   Goal estimates for nutrients and
   chlorophyll.

   The fish community structure in
   Maryland's coastal bays has remained
relatively unchanged during the past
twenty years while that of similar
systems in Delaware have changed
substantially. Fish communities of the
Maryland coastal bays are dominated
by Atlantic silversides, bay anchovy,
Atlantic menhaden, and spot.  This
community structure is similar to that
of the Delaware coastal bays 35 years
ago. The fish fauna in Delaware's
coastal bays has shifted toward
species of the Family Cyprinodontidae
(e.g., killifish and sheepshead
minnow) which are more tolerant to
low oxygen stress, and extremes of
salinity and temperature.

Primary Contact: Dr. Frederik W. Kutz
U.S. EPA, Region HI
Environmental Science Center
701 Mapes Rd.
FortMeade,MD 20755
410-305-2742
Kutz.Rick@epa.gov
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 Glossary
   A posteriori classification - a
   classification based on the results of
   experimentation.

   A priori classification - a classification
   made prior to experimentation.

   Aquatic community - an association of
   interacting populations of aquatic
   organisms in a given waterbody or
   habitat.

   Aquatic life uses - a subset of designated
   uses for high quality waters.  As such,
   they are in need of special protection so
   that characteristics of their resident biotic
   communities are identified and protected.

   Assemblage - an association of interacting
   populations of organisms in a given
   waterbody (e.g., fish assemblage or
   benthic macroinvertebrate assemblage).

   Attribute - physical and biological
   characteristics of habitats which can be
   measured  or described.

   Benthic macroinvertebrates - see benthos.

   Benthos - animals without backbones,
   living in or on the sediments, of a size
   large enough to be seen by the unaided
   eye, and which can be retained by a U.S.
   Standard No.  30 sieve (28 openings/in,
   0.595-mm  openings).  Also referred to as
   benthic macroinvertebrates, infauna, or
   macrobenthos.

   Bioaccumulation - a process by which
   chemicals  are taken up by aquatic
   organisms directly from water as well as
   through exposure via other routes, such as
   consumption  of food  and  sediment
   containing the chemicals.
Bioconcentration - a process by which
there is a net accumulation of a chemical
directly from water into aquatic organisms
resulting from simultaneous uptake (e.g.,
via gill or epithelial tissue) and
elimination.

Biological assemblage - a group of
phylogenetically (e.g., fish) or ecologically
(e.g., benthic macroinvertebrates) related
organisms that are part of an aquatic
community.

Biological assessment or Bioassessment -
an evaluation of the condition of a
waterbody using biological surveys and
other direct measures of the resident biota
of the surface waters, in conjunction with
biological criteria.

Biological criteria or Biocriteria -
guidelines or benchmarks adopted by
States to evaluate the relative biological
integrity of surface waters. Biocriteria are
narrative expressions or numerical values
that  describe biological integrity of aquatic
communities inhabiting waters of a given
classification or designated aquatic life
use.

Biological indicators - plant or animal
species or communities with a narrow
range of environmental tolerances that
may be selected for monitoring because
their absence or presence and relative
abundances serve as barometers of
environmental conditions.

Biological integrity - the condition of the
aquatic community inhabiting unimpaired
waterbodies of a specified habitat as
measured by community structure and
function.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                        G-1

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   Biological monitoring or Biomonitoring -
   multiple, routine biological surveys over
   time using consistent sampling and
   analysis methods for detection of changes
   in biological condition.

   Biological survey or Biosurvey -
   collecting, processing and analyzing
   representative portions of an estuarine or
   marine community to determine its
   structure and function.

   Biomagnification - the result of the
   processes of bioconcentration and
   bioaccumulation by which tissue
   concentrations of bioaccumulated
   chemicals increase as the chemical passes
   up through  two  or more trophic levels in
   the food chain.

   Biota - plants, animals  and other living
   resources.

   Brackish - water with salt content ranging
   between that of sea water and fresh water;
   commonly used to refer to oligohaline
   waters.

   Coastal waters - marine waters adjacent to
   and receiving estuarine discharges and
   extending seaward over the continental
   shelf and/or the edge of the U.S.
   territorial sea.

   Community - any group of organisms
   belonging to a number of different species
   that co-occur in the same habitat or area;
   an association of interacting assemblages
   in a given waterbody.

   Demersal -  living on or near the bottom of
   a body of water  (e.g., mid-water and
   bottom-dwelling fish and shellfish, as
   opposed to surface fish).

   Designated uses - descriptions of the
   optimal use of each waterbody as defined
   by States including natural fisheries,
   recreation, transportation, or mixed uses.
Discriminant analysis - a type of
multivariate analysis used to distinguish
between two groups.

Ecological integrity - the condition of an
unimpaired ecosystem as measured by
combined chemical, physical (including
habitat), and biological attributes.

Ecoregion - geographic regions of
ecological similarity defined by similar
climate, landform, soil, natural vegetation,
hydrology or other ecologically relevant
variables.

Effects Range-Low - concentration of a
chemical in sediment below which toxic
effects were rarely observed among
sensitive species (10th percentile of all toxic
effects).

Effects Range-Median - concentration of a
chemical in sediment above which toxic
effects are frequently observed among
sensitive species (50th percentile of all toxic
effects).

Epibenthos - those animals (usually
excluding fishes) living on the top of the
sediment surface.

Epifauna - benthic animals living on the
sediment or on and among rocks and
other structures.

Estuarine or coastal marine classes -
classes that reflect basic biological
communities and that are based on
physical parameters such as salinity,
depth, sediment grain size, dissolved
oxygen and basin geomorphology.

Estuarine waters - semi-enclosed body of
water which has a free connection with
the open sea and within which seawater is
measurably diluted with fresh water
derived from land drainage.

Facultative - capable of adaptive response
to varying environments.
G-2
                                    Glossary

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   Habitat - a place where the physical and
   biological elements of ecosystems provide
   an environment and elements of the food,
   cover and space resources needed for
   plant and animal survival.

   Halocline - a vertical gradient in salinity.

   Holoplankton - an aggregate of passively
   floating, drifting or somewhat motile
   organisms throughout their entire life
   cycle.

   Hypoxia - the condition of low dissolved
   oxygen in aquatic systems (typically with
   a concentration < 2-mgL"1 but > 0.5-
   mgL-1).

   IBI or Index of Biotic Integrity - a fish
   community assessment approach that
   incorporates the zoogeographic,
   ecosystem, community and population
   aspects of fisheries biology into a single
   ecologically-based index of the quality of a
   water resource.

   Impact - a change  in the chemical,
   physical or biological quality or condition
   of a waterbody caused by external
   sources.

   Impairment - a detrimental effect on the
   biological integrity of a water body caused
   by an impact.

   Indexes - a usually dimensionless numeric
   combination of scores derived from
   biological measures called metrics.

   Index period - a sampling period, with
   selection based on temporal behavior of
   the indicator(s) and the practical
   considerations for  sampling.

   Indicator - characteristics for the
   environment, both abiotic and biotic, that
   can provide quantitative information on
   environmental conditions.
Indicator taxa or Indicator species - those
organisms whose presence (or absence) at
a site is indicative of specific
environmental conditions.

Infauna - see benthos.

In situ - measurements taken in the
natural environment.

Kurtosis - a measure of the departure of a
frequency distribution from a normal
distribution, in terms of its relative
peakedness or flatness.

Littoral zone - the intertidal zone of the
estuarine or seashore; i.e., the shore zone
between the highest and lowest tides.

Macrobenthos - see benthos.

Macrofauna - animals of a size large
enough to be seen by the unaided eye and
which can be retained by a U.S. Standard
No. 30 sieve (28 meshes/in, 0.595-mm
openings).

Macroinvertebrates - animals without
backbones of a size large enough to be
seen by the unaided eye and which can be
retained  by a U.S. Standard No. 30 sieve
(28 meshes/in, 0.595-mm openings).

Macrophytes - large aquatic plants that
may be rooted, non-rooted, vascular or
algiform (such as kelp); including
submerged aquatic vegetation, emergent
aquatic vegetation, and floating aquatic
vegetation.

Meiofauna -  small interstitial; i.e.,
occurring between sediment particles,
animals that pass through a 1-mm mesh
sieve but are  retained by a 0.1-mm mesh.

Meroplankton - organisms that are
planktonic only during the larval stage of
their life history.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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   Mesohaline - the estuarine salinity zone
   with a salinity range of 5-18-ppt.

   Metric - a calculated term or enumeration
   which represents some aspect of biological
   assemblage structure, function, or other
   measurable characteristic of the biota that
   changes in some predictable way in
   response to impacts to the water body.

   Multimetric  approach - an analysis
   technique that uses a combination of
   several measurable characteristics of the
   biological assemblage to provide an
   assessment of the status of water
   resources.

   Multivariate community analysis -
   statistical methods (e.g., ordination or
   discriminant analysis) for analyzing
   physical and biological community data
   using multiple variables.

   NPDES or National Pollutant Discharge
   Elimination  System - a permit program
   under Section 402 of the Clean Water Act
   that imposes discharge limitations on
   point sources by basing them on the
   effluent limitation capabilities of a control
   technology or on local water quality
   standards.

   Oligohaline  - the estuarine salinity zone
   with a salinity range of 0.5-5-ppt.

   Optimal - most favorable point,  degree, or
   amount of something for obtaining a
   given result;  in ecology most natural or
   minimally disturbed sites.

   Pelagic - pertaining to open waters or the
   organisms which inhabit those waters.

   Pelagic zone - the area of open water
   beyond the littoral zone.

   Percent fines - in analysis of sediment
   grain size, the percent of fine (.062-mm)
   grained fraction of sediment in a sample.
Photic zone - the region in a water body
extending from the surface to the depth of
light penetration.

Plankton - free-floating or drifting
organisms with movements determined
by the motion of the water.

Population - an aggregate of
interbreeding individuals of a biological
species within a specified location.

Pseudoreplication - the repeated
measurement of a single experimental unit
or sampling unit, with the treatment of the
measurements as if they were
independent replicates of the sampling
unit.

Pycnocline - a zone of marked density
gradient.

Reference condition - the chemical,
physical or biological quality or condition
exhibited at either a single site or an
aggregation of sites that represents the
least impaired condition of a classification
of waters to  which the reference condition
applies.

Reference sites - minimally impaired
locations in  similar water bodies and
habitat types at which data are collected
for comparison with  test sites.  A separate
set of reference sites are defined for each
estuarine or coastal marine class.

Replicate - taking more than one sample
or performing more than one analysis.

Saprobien system - an ecological
classification of a polluted aquatic system
that is undergoing self-purification.
Classification is based on relative levels of
pollution, oxygen concentration and types
of indicator  microorganisms; i.e.,
saprophagic microorganisms - feeding on
dead or decaying organic matter.
G-4
                                    Glossary

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   Seiche - a wave that oscillates (for a
   period of a few minutes to hours) in lakes,
   bays, lagoons or gulfs as a result of
   seismic or atmospheric disturbances (e.g.,
   "wind tides").

   Simulation models - mathematical
   models (logical constructs following from
   first principles and assumptions),
   statistical models (built from observed
   relationships between variables), or a
   combination of the two.

   Skewness - the degree of statistical
   asymmetry (or departure from symmetry)
   of a population. Positive or negative
   skewness indicates the presence of a long,
   thin tail on the right or left of a
   distribution respectively.

   Test sites - those sites being tested for
   biological impairment.

   Trophic level - a broad class of an
   ecosystem (e.g., green plants, herbivores,
   carnivores)  in which all organisms
   procure food in the same general manner.

   Use designations - predominant uses each
   State determines appropriate for a
   particular estuary, region, or area within
   the class.

   Zooplankton - free-floating or drifting
   animals with movements determined by
   the motion of the water.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance                  G-5

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 Literature Cited
   Alden, R.W., S.B. Weisberg, J.A.
   Ranasinghe, and D.M. Dauer.  1997.
   Optimizing temporal sampling
   strategies for benthic environmental
   monitoring programs. Marine Pollution
   Bulletin 34(11) :913-922.

   Allen, M.J. and R.W. Smith. 2000.
   Development of demersal fish biointegrity
   indices for coastal Southern California.
   Southern California Coastal Water
   Research Project, Westminster, CA.

   Allen, M.J., D. Diener, J. Mubarak, S.B.
   Weisberg, and S.L. Moore.  1999.
   Megabenthic invertebrate assemblages
   of the mainland shelf of southern
   California in 1994. Pages 113-124 in
   Weisberg, S.B. and D. Hallock (editors).
   Southern California Coastal Water Research
   Project, Annual Report 1997-1998.
   Reynolds and Reynolds, Santa Ana, CA.

   Allen, H.E., G. Fu and B. Deng. 1993.
   Analysis of acid-volatile sulfide (AVS)
   and simultaneously extracted metals
   (SEM) for the estimation of potential
   toxicity in aquatic sediments.
   Environmental Toxicology and Chemistry
   12:1441-1453.

   Alve, E.  1991. Foraminifera, climatic
   change, and pollution: A study of late
   Holocene sediments in Drammensfjord,
   southeast Norway. The  Holocene
   1(3):243-261.

   American Public Health Association
   (APHA). 1992.  Standard methods for the
   examination of waters and wastewater.
   American Public Health Association,
   American Water Works Association, and
   Water Pollution Control Federation.
   18th edition, Washington, DC.
American Public Health Association
(APHA). 1981. Standard methods for the
examination of water and wastewater.
American Public Health Association,
American Water Works Association, and
Water Pollution Control Federation.
15th edition, Washington, DC.

American Society for Testing and
Materials (ASTM). 1998 a. Standard
guide for conducting 10-day static
sediment toxicity tests with marine and
estuarine amphipods. E1367-92.
Volume 11.05:732-757. Annual Book of
Standards: American Society of Testing and
Materials, Conshohocken, PA.

American Society for Testing and
Materials (ASTM). 1998b. Standard
guide for collection, storage,
characterization, and manipulation of
sediments for toxicological testing.
E1391-94. Volume 11.05:768-788. Annual
Book of Standards: American Society of
Testing and Materials, Conshohocken,
PA.

American Society for Testing and
Materials (ASTM). 1998c. Standard
guide for conducting sediment toxicity
tests with marine and estuarine
polychaetous annelids. E1611-94.
Volume 11.05:1009-1032.  Annual Book of
Standards: American Society of Testing and
Materials, Conshohocken, PA.

American Society for Testing and
Materials (ASTM). 1991. Standard
guide for collection, storage,
characterization, and manipulation of
sediments for toxicological testing.
ASTM Designation E1391-90. Annual
Book of Standards. American Society for
Testing and Materials, Philadelphia, PA.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       L-1

-------
   Ankley, G.T., D.M. DiToro, DJ. Hansen
   and W.J. Berry. 1996. Technical basis
   and proposal for deriving sediment
   quality criteria for metals. Environmental
   Toxicology and Chemistry 15(12):2056-
   2066.

   Ankley, G., M. Schubauer-Berigan, J.
   Dierkes. 1991.  Predicting the toxicity of
   bulk sediments to aquatic organisms
   with aqueous test fractions: pore water
   vs. elutriate.  Environmental  Toxicology
   and Chemistry 10:925-939.

   Association of Bay Area Governments
   (ABAC).  1991. Status and trends report
   on wetlands and related habitats in the San
   Francisco estuary.  San Francisco Estuary
   Project. Oakland, CA.

   Barbour, M.T., J. Gerritsen, B.D.  Snyder,
   J.B. Stribling. 1999. Rapid bioassessment
   protocols for use in streams and wadeable
   rivers: periphyton, benthic
   macroinvertebrates, and fish, 2nd ed. EPA
   841-B-99-002. U.S. Environmental
   Protection Agency, Office of Water,
   Washington, D.C.

   Barbour, M.T., J. Gerritsen, and J.S.
   White.  1996a. Development of the Stream
   Condition Index (SCI) for Florida.
   Prepared for FL DEP, Tallahassee, FL.

   Barbour, M.T., J.M. Diamond, C.O.
   Yoder.  1996b. Biological assessment
   strategies: Applications and limitations.
   Pages 245-270 in D.R. Grothe, K.L.
   Dickson, and D.K. Reed-Judkins
   (editors). Whole effluent toxicity testing:
   An evaluation of methods and prediction of
   receiving system impacts. SET AC Press,
   Pensacola, Florida.

   Barbour, M.T., J.B. Stribling, and J.R.
   Karr. 1995. The multimetric approach
   for establishing biocriteria and
   measuring biological condition. In W.
   Davis, T. Simon (editors). Biological
   Assessment and Criteria: Tools for Water
Resource Planning and Decision Making.
Lewis Publishers. Boca Raton, FL.

Barbour, M.T., J.L. Plafkin, B.P. Bradley,
C.G. Graves, and R.W. Wisseman. 1992.
Evaluation of EPA's rapid bioassessment
benthic metrics: Metric redundancy and
variability among reference stream sites.
Environmental Toxicology and Chemistry
11:437-449.

Barss, M.S. and G.L. Williams. 1973.
Palynology and nannofossil processing
techniques.  Geological Survey ofCanaca
Paper.  73-26,1-25.

Batiuk, R.A., R.J. Orth, K.A. Moore, W.C.
Dennison, J.C. Stevenson, L.W. Staver,
V. Carter, N.B. Rybicki, R.E. Hickman, S.
Kollar, S. Bieber, P. Heasly. 1992.
Chesapeake Bay Submerged Aquatic
Vegetation Habitat Requirements and
Restoration Targets: A Technical Synthesis.
Chesapeake Bay Program, 68-WO-0043.

Bergen, M., S.B. Weisberg, R.W. Smith,
D. Cadien, A. Dalkey, D. Montagne, J.K.
Stull, R.G. Velarde.  1999.  Relationship
between depth, latitude, and  sediment
and the structure of benthic inf aunal
assemblages on the mainland shelf of
southern California.  Pages 125-136 in
Weisberg, S.B. and D. Hallock (editors).
Southern California Coastal Water Research
Project, Annual Report 1997-1998.
Reynolds and Reynolds, Santa Ana, CA.

Bernstein, B.B., B.E Thompson, and R.W.
Smith.  1991. A combined science and
management framework for developing
regional monitoring objectives.  Presented
at the National Estuary Program Science
Symposium, Sarasota, FL. 25-27
February 1991.

Bilyard, G.R. 1987.  The value of benthic
inf auna in marine pollution monitoring
studies. Marine Pollution Bulletin  18:581-
585.
L-2
                              Literature Cited

-------
   Blalock, H.M., Sr. 1979. Social Statistics.
   Revised 2nd edition. McGraw-Hill Book
   Company, New York, NY.

   Boesch, D.F.  1977. Application of
   numerical classification in ecological
   investigations of water pollution. EPA
   Grant No. R803599-01-1, ROAP/TASK
   No. 21 BEI, U.S. EPA Corvallis
   Environmental Research Laboratory,
   Newport, OR. 115 p.

   Bowman, M.L., E. Dohner, and C.
   Dohner. 1993.  Summary ofestuarine
   monitoring program attributes for:
   Chesapeake Bay benthos; Chesapeake Bay
   plankton; Tar/Pamlico; EMAP-Estuaries
   Virginian Province demonstration project;
   Naples Bay, Florida; San Francisco estuary
   and wetlands; Puget Sound ambient
   monitoring program; and Puget Sound
   estuary program. Prepared for U.S.
   Environmental Protection Agency,
   Assessment and Watershed Protection
   Division, Oceans and Coastal Protection
   Division, and Health and Ecological
   Criteria Division, Washington, DC by
   Tetra Tech, Inc., Owings Mills, MD.

   Boyle, T.P., G.M. Smillie, J.C. Anderson,
   and D.R. Bieson.  1990. A sensitivity
   analysis of nine diversity and seven
   similarity indices. Research Journal of the
   Water Pollution Control Federation 62:749.
Boynton, W.R., W.M. Kemp, J. Garber,
J.M. Barnes, L.L. Robertson, and J.L.
Watts. 1988. Chesapeake Bay water quality
monitoring program ecosystems processes
component. Level 1 Report No. 5.
Prepared for Maryland Department of
Environment by University of Maryland
Center for Environmental and Estuarine
Studies.

Brenum, G.  1976. A comparative study of
benthic communities of dredged lagoons,
tidal creeks, and areas of open bays in Little
Assawoman,  Indian River, and Rehoboth
Bays, Delaware. M.S. thesis, College of
Marine Studies, University of Delaware,
Newark, DE.

Brumbaugh, W., C. Ingersoll, N.
Kemble, T. May, and J. Zajicek.  1994.
Chemical  characterization of sediments
and pore water from the Upper  Clark
Fork River and Milltown Reservoir,
Montana.  Environmental Toxicology and
Chemistry 13:1971-1973.

Brush, G.S.  1989. Rates and patterns of
estuarine sediment accumulation.
Limnology and Oceanography 34(7):1235-
1246.

Bufflap, W.  and H. Allen. 1995.
Sediment pore water collection methods:
A review. Water Research 29:165-177.
   Boynton, W.R., J.H. Garber, R. Summers,
   and W.M. Kemp. 1995. Inputs,
   transformations, and transport of
   nitrogen and phosphorus in Chesapeake
   Bay and selected tributaries.  Estuaries
   18(1B):285-314.

   Boynton, W.R., L. Murray, W.M. Kemp,
   J.D. Hagy, C. Stokes, F. Jacobs, J. Bowers,
   S. Souza, B.  Rinsky, and J. Seibel. 1993.
   Maryland's Coastal Bays: An assessment of
   aquatic ecosystems, pollutant loadings, and
   management options.  Prepared for
   Maryland Department of the
   Environment.
Bulger, A.J., B.P. Hayden, M.E. Monaco,
D.M. Nelson, and M.G. McCormick-Ray.
1993. Biologically-based estuarine
salinity zones derived from a
multivariate analysis. Estuaries
16(2):311-322.

Burgess, R., K. Schweitzer, R. McKinney,
D. Phelps.  1993. Contaminated marine
sediments: Water column and
interstitial toxic effects.  Environmental
Toxicology and Chemistry 12:127-138.

Carmichael, J.T., B.M. Richardson, M.
Roberts,  and S.J. Jordan. 1992. Fish
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       L-3

-------
   assemblages and dissolved oxygen trends in
   eight Chesapeake Bay tributaries during the
   summers of 1989-1991: a data report.
   Maryland Department of Natural
   Resources, Chesapeake Bay Research
   and Monitoring Division, Annapolis,
   MD.

   Carriker, M.R.  1967. Ecology of
   estuarine benthic invertebrates: A
   perspective. American Association for
   the Advancement of Science,
   Washington, DC. Estuaries 83:442-487.

   Chaloud, DJ.  and D.V. Peck, editors.
   1994. Environmental Monitoring and
   Assessment Program: Integrated Quality
   Assurance Project Plan for the Surface
   Waters Resource Group, 1994 Activities.
   EPA 600/X-91/080, Rev. 2.00. USEPA,
   Las Vegas, NV.

   Chapman, P.M. 1996.  Presentation and
   interpretation of sediment quality triad
   data. Ecotoxicology 5:327-339.

   Chapman, P.M. 1988.  Marine sediment
   toxicity tests. In J.J. Lichtenberg, F.A.
   Winter, C.I. Weber, and L. Fredkin
   (editors). Chemical and Biological
   Characterization of Sludges, Sediments,
   Dredge Spoils, and Drilling Muds.
   Philadelphia, PA: ASTM.

   Chapman, P.M., R.N. Dexter, and E.R.
   Long.  1987. Synoptic measures of
   sediment contamination, toxicity, and
   infaunal community structure (the
   Sediment Quality Triad). Marine Ecology
   Progress Series 37:75-96.

   Charles et al. 1994. Paleolimnological
   approaches to biological monitoring.
   Pages 233-293 in L.L. Loeb, and A.
   Spacie (editors). Biological monitoring of
   aquatic systems. CRC Press, Boca Raton,
   FL.

   Charles, D.F. and J.P. Smol. 1994. Long-
   term chemical changes in lakes:
Quantitative inferences using biotic
remains in the sediment record.
Advances in Chemistry 237:1-51.

Christian, R.R.  1989. Microbial ecology
and organic detritus in estuaries. In
J.W. Day, Jr., C.A.S. Hall, W.M. Kemp,
and A. Yanez-Arancibia (editors).
Estuarine Ecology. John Wiley & Sons,
New York, NY. pp.558.

Cochran, W.G.  1963. Sampling
Techniques. John Wiley and Sons, Inc.,
New York, NY.

Conley, D.J., C.L. Shelske and E.F.
Stoermer. 1993. Modification of the
biogeochemical cycle of silica with
eutrophication. Marine Ecological
Progress Series 101:179-192.

Conover,W.J. 1980. Practical
Nonparametric Statistics.  2nd edition. John
Wiley and Sons, Inc., New York, NY.

Conquest, L.L., S.C. Ralph, and R.J.
Naiman. 1994. Implementation of
large-scale stream monitoring efforts:
Sampling design and data analysis
issues. Pages 69-90 in L. Loeb and A.
Spacie (editors). Biological Monitoring of
Aquatic Systems. Lewis Publishers, Boca
Raton, FL.

Cooper, S.R. 1995.  Chesapeake Bay
watershed historical land use: Impact
on water quality and diatom
communities. Ecological Applications
5:703-723.

Cooper, S.R. and G.S. Brush. 1991.
Long-term history of Chesapeake Bay
anoxia. Science 254:992-996.

Correll, D.L. 1987.  Nutrients in
Chesapeake Bay.  Pages 298-320 in S.K.
Majumdar, L.W. Hall, Jr. and H.M.
Austin (editors). Contaminant Problems
and Management of Living Chesapeake Bay
L-4
                             Literature Cited

-------
   Resources. Pennsylvania Academy of
   Science.

   Costanza, R., S.O. Funtowicz, and J.R.
   Ravetz. 1992. Assessing and
   communicating data quality in policy-
   relevant research.  Environmental
   Management 16(1):121-131.

   Dale, B., T.A. Thorsen and A. Fjellsa.
   1999. Dinoflagellate cysts as indicators
   of cultural eutrophication in the
   Oslofjord, Norway. Estuarine, Coastal
   and Shelf Science 48:371-382.

   Dardeau, M.R., R.F. Madlin, W.W.
   Schroeder, and J.P. Stout. 1992.
   Estuaries:  Biodiversity of the southeastern
   United States.  C.T. Hackney, S.M.
   Adams, and W.H. Martin (editors). John
   Wiley & Sons, New York, NY. pp. 779.

   Dauer, D.M.  1993. Biological criteria,
   environmental health and estuarine
   macrobenthic community structure.
   Marine Pollution Bulletin 26:249-257.

   Davies, S.P., L.T. Somides, D.L.
   Courtemanch, and F. Drummond. 1993.
   Maine Biological Monitoring and Biocriteria
   Development Program. Maine
   Department of Environmental
   Protection, Bureau of Water Quality
   Control, Division of Environmental
   Evaluation and Lake Studies, Augusta,
   ME.

   Day, J.W., C.A.S. Hall, W.M. Kemp, and
   A. Yanez-Aranciba.  1989. Estuarine
   Ecology. John Wiley & Sons, New York,
   NY. 558pp.

   Deegan, L.A., J.T. Finn, S.G. Ayvazian,
   C.A. Ryder-Kieffer, and J. Buonaccorsi.
   1997. Development and Validation of an
   Estuarine Biotic Integrity Index.
   Estuaries 20:601-617.

   Delaware Chamber of Commerce,
   personal communication, 1990.
Dennison, W.C., R.J. Orth, K.A. Moore,
J.C. Stevenson, V. Carter, S. Kollar, P.
Bergstrom, and R.A. Batiuk. 1993.
Assessing water quality with submerged
aquatic vegetation.  Bioscience 43:86-94.

Diaz, R. and W. Nelson. 1993.  Middle
and southern Atlantic coast estuarine
benthic invertebrate metrics development.
A Proceedings: Estuarine and  Near
Coastal Bioassessment and Biocriteria
Workshop, (November 18-19,1992.)
Annapolis, Maryland. U.S.
Environmental Protection Agency,
Office of Science and Technology.
Washington, DC.

Dickerson, R.  1995. Atmospheric
nitrogen deposition to the Chesapeake
Bay. In P. Hill and S. Nelson (editors).
Toward a Sustainable Coastal Watershed:
The Chesapeake Experiment. Proceedings of
a Conference, 1-3 June 1994, Norfolk, VA.
Chesapeake Research Consortium,
Edgewater, MD. CRC Publication No.
149. p. 507.

DiToro, D.M., J.D. Mahony, D.J. Hansen,
K.J. Scott, M.B. Hinks, S.M. Mayr and
M.S. Redmond.  1990. Toxicity of
cadmium in sediments: The role of acid
volatile sulfides. Environmental
Toxicology and Chemistry 9:1487-1502.

DiToro, D.M., C. Zarba, D.J. Hansen,
R.C. Swartz, C.E. Cowan, H.E.  Allen,
N.A. Thomas, P.R. Paquin and W.J.
Berry.  1991. Technical basis for
establishing sediment quality criteria for
non-ionic organic chemicals using
equilibrium partitioning. Environmental
Toxicology and Chemistry 10:1299-1307.

Dixit, S.S., J.P. Smol, J.C. Kingston, D.F.
Charles.  1992. Diatoms: powerful
indicators of environmental change.
Environmental Science and Technology
26(l):23-32.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       L-5

-------
   Dossis, P. and L.J. Warren.  1981. Zinc
   and lead in background and
   contaminated sediments from Spencer
   Gulf, South Australia. Environmental
   Science and Technology 15:1451-6.

   Dycus, D.L. 1995.  Aquatic ecological
   health determinations for TV A reservoirs -
   1994. An informal summary of'1994 vital
   monitoring results and ecological health
   determination methods. Tennessee Valley
   Authority Water Management.

   Dycus, D.L. and D.L. Meinert. 1993.
   Monitoring and evaluation of aquatic
   resource health and use suitability in
   Tennessee Valley Authority reservoirs.
   Water Management. Draft.

   Eaton, C.M. 1997.  Sediment wet-sieving
   technique to determine "percentfines."
   C.M. Eaton, Bio-Marine Enterprises,
   Seattle, WA.  Fax transmission to M.
   Bowman, Tetra Tech, Inc., Owings Mills,
   MD. 4 February 1997.

   Eaton, C. M.  1995. Population patterns
   of demersal fauna and environmental
   stress: a preliminary, trawl-based
   assessment. Puget Sound Notes 36:1-6.

   Eaton, C.M. 1994.  Development of trawl-
   based tools for the quantitative assessment of
   demersal fauna (macroinvertebrates and
   fishes): A summary of phase I and II.  Final
   Report to USEPA, Washington, DC.
   Order No. 4642.
assessment of demersal fauna
(macroinvertebrates and fishes): Pilot Study
in Puget Sound, Washington. Final report
to USEPA, Washington, DC.

Eaton, L. 1994. Results of a test of three
Methods, February 7, 1994. North
Carolina Division of Environmental
Management Biological Assessment
Group.  Memorandum to Ken Eagleson,
May 10,1994.

Eaton, L. 1992a. Pamlico basin sampling:
More metal hotspots.  Memorandum
dated March 11,1992 to T. MacPherson,
North Carolina Department of
Environment, Health, and Natural
Resources, Division of Environmental
Management, Raleigh, NC.

Eaton, L. 1992b. Diaz method testing
results. Memorandum date March 30,
1992 to Ken Eagleson, North Carolina
Department of Environment, Health,
and Natural Resources, Division of
Environmental Management, Raleigh,
NC.

Eaton, L. 1992c. Biological results from
sediment toxicity survey, Neuse and
Pamlico estuaries, January 9-10,1992.
Memorandum dated April 14, 1992 to
Harold Quidley, North Carolina.
Department of Environment, Health,
and Natural Resources, Division of
Environmental Management, Raleigh,
NC.
   Eaton, C.M. and P.A. Dinnel. 1994.
   Development of trawl-based criteria for the
   assessment of demersal fauna
   (macroinvertebrates and fishes): Pilot study
   in Puget Sound, Washington.  Presented at
   Estuarine and Near Coastal Marine
   Bioassessment/ Biocriteria Workgroup
   Meeting.  USEPA, Baltimore, MD.
   January 6th.

   Eaton, C.M. and P.A. Dinnel. 1993.
   Development of trawl-based criteria for
Eaton, L. 1992d. Letter dated
September 9,1992 from L. Eaton, North
Carolina Department of Environment,
Health, and Natural Resources, Division
of Environmental Management, Raleigh,
NC, to M. Bowman, Tetra Tech, Inc.,
Owings Mills, MD.

Engle, V.D. and J.K. Summers. 1999.
Refinement, validation, and application
of a benthic condition index for northern
L-6
                             Literature Cited

-------
   Gulf of Mexico estuaries. Estuaries
   22:624-635.

   Engle, V.D., J.K. Summers, and G.R.
   Gaston.  1994. A benthic index of
   environmental condition of Gulf of
   Mexico estuaries. Estuaries 17(2):372-
   384.

   Fairweather, P.G. 1991. Statistical
   power and design requirements for
   environmental monitoring. Australian
   Journal of Marine Freshwater Research
   42:555-67.

   Farrell, D.H. 1993a. A community based
   metric for marine benthos (Draft). Florida
   Department of Environmental
   Protection, Tampa, FL.

   Farrell, D. H. 1993b. Bioassessment in
   Florida. Pages 17-26 in A Proceedings:
   Estuarine and Near Coastal
   Bioassessment and Biocriteria
   Workshop, Annapolis, MD.  USEPA,
   Office of Science and Technology,
   Washington, D.C.

   Ferguson, R.L.  and L.L. Wood.  1994.
   Rooted vascular aquatic beds in the
   Albemarle-Pamlico estuarine system.
   National Marine Fisheries Service,
   Beaufort, NC. Project No. 94-02.

   Ferraro,  S.P. and F.A. Cole. 1990.
   Taxonomic level and sample site
   sufficient for assessing pollution impacts
   on the southern California
   macrobenthos. Marine Ecology Progress
   Series  67:251-262.

   Ferraro,  S.P. and F.A. Cole. 1992.
   Taxonomic level sufficient for assessing
   a moderate impact on macrobenthic
   communities in Puget Sound,
   Washington, D.C. Canadian Journal of
   Fisheries  and Aquatic Sciences 49(b):1184-
   1188.
Ferraro, S.P. and F.A. Cole. 1995.
Taxonomic level sufficient for assessing
pollution impacts on the southern
California bight macrobenthos -
revisited.  Environmental Toxicology and
Chemistry 14(6):1031-1040.

Ferraro, S.P., F.A. Cole, W.A. DeBen,
and R.C. Swartz.  1989. Power-cost
efficiency of eight macrobenthic
sampling schemes in Puget Sound,
Washington, USA. Canadian Journal of
Fisheries and Aquatic Sciences 46(10):2157-
2165.

Ferraro, S.P., R.C. Swartz, F.A. Cole, and
W.A. DeBen. 1994.  Optimum
macrobenthic sampling protocol for
detecting pollution impacts in the
southern California Bight.
Environmental Monitoring and Assessment
(29):127-153.

Flannagan, J.F.  1970. Efficiencies of
various grabs and corers in sampling
freshwater benthos.  Journal of the
Fisheries Research Board of Canada
27:1631-1700.

Flint, R.W. and R.D. Kalke. 1985.
Benthos Structure and function in a
south Texas estuary. Contributions in
Marine Science 28:33-53.

Forstner, U. and G.T.W. Wittmann.
1981.  Metal pollution in the aquatic
environment. Second revised edition.
Springer-Verlag, New York, NY.

Fredette, T.J., D.A. Nelson, T. Miller-
Way, J.A. Adair, V.A. Sotler, J.E.
Clausner, E.B. Hands, and FJ. Anders.
1989.  Selected tools and techniques for
physical and biological monitoring of
aquatic dredged material disposal sites.
Final Report. U.S. Army Engineer
Waterways Experiment Station,
Vicksburg, MS.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       L-7

-------
   Frydenborg R.  1994. Lake bioassessments
   for the determination ofnonpoint source
   impairment in Florida. Draft. FL DEP,
   Biology Section, Division of
   Administrative and Technical Services,
   Tallahassee, FL. July.

   Gaston, G.R., D.L. Lee, and J.C. Nasci.
   1988. Estuarine macrobenthos in
   Calcasieu Lake, Louisiana: Community
   and trophic structure. Estuaries 11:192-
   200.

   Gibson, G.R. 1995. Near coastal marine
   waters pilot project (unpublished report).
   USEPA, Office of Science and
   Technology, Health and Ecological
   Criteria Division, Washington, DC.

   Gibson, G.R. et al. 1993. Proceedings
   Estuarine and Near Coastal Marine
   Bioassessment and Biocriteria Workshop,
   18-19. November, 1992.

   Gibson, G.R. 1992. Procedures for
   initiating narrative biological criteria.
   EPA-822-B-92-002. USEPA, Office of
   Science and Technology, Washington,
   DC.

   Gilbert, R.0.1987.  Statistical Methods for
   Environmental Pollution Monitoring. Van
   Nostrand Reinhold, New York. 320pp.

   Glew,J.R.  1988.  A portable extruding
   device for close interval sectioning of
   unconsolidated core samples. Journal of
   Paleolimnology  1:235-239.

   Goodyear, C.P.  1985. Relationship
   between reported commercial landings
   and abundance of striped bass in
   Chesapeake Bay, Maryland. Transactions
   of the American Fisheries Society 114(1) :92-
   96.

   Gray,J.S. 1989. Effects of
   environmental stress on species rich
   assemblages. Biological Journal of the
   Unman Society 37:19-32.
Green, R.H. 1984. Some guidelines for
the design of biological monitoring
programs in the marine environment.
Pages 233-245 in H.H. White (editor).
Concepts of Marine Pollution
Measurements. University of Maryland
Sea Grant, College Park, MD.

Guillen, G. 1995a. Development of a rapid
bioassessment method and index ofbiotic
integrity in southeast Texas. Presented at
Estuarine and Near Coastal Marine
Bioassessment/Biocriteria Workgroup
Meeting.  U.S. EPA, Baltimore, MD.
January 6th.

Guillen, G.J.  1995b. Development of a
Rapid Bioassessment method and index of
biotic integrity for coastal environments
located along the northwest Gulf of Mexico -
DRAFT. Texas National Resource
Conservation Commission,
Environmental Assessment Program,
Field Operations  Division.

Guillen, G. 1994. Development of a rapid
bioassessment method and index ofbiotic
integrity in southeast Texas. Presented at
Estuarine and Near Coastal Marine
Bioassessment/Biocriteria Workgroup
Meeting.  USEPA, Baltimore, MD.

Hansen, D.J., Berry, W.J., Mahony, J.D.,
Boothman, W.S.,  DiToro, D.M., Robson,
D.L., Ankley, G.T., Ma, D., Yan, Q.,
Pesch, C.E. 1996. Predicting the toxicity
of metal-contaminated field sediments
using interstitial concentration of metals
and acid-volatile sulfide normalizations.
Environmental Toxicology and Chemistry
15:(12) 2080-2094.

Helsel, D.R. and R.M. Hirsch.  1992.
Statistical methods in water resources.
Elsevier, Amsterdam, Netherlands.

Hillman, K., D.I. Walker, A.W.D.
Larkum, and A.J. McComb.  1989.
Productivity and nutrient limitation.
Pages 635-685 in A.W.D. Larkum, A.J.
L-8
                              Literature Cited

-------
   McComb, and S.A. Shepard (editors).
   Biology ofSeagrasses.  A treatise on the
   biology ofseagmsses with special reference
   to the Australian region. Elsevier, New
   York, NY.

   Hilsenhoff, W.L.  1987. An improved
   biotic index of organic stream pollution.
   Great Lakes Entomologist 20:31-39.

   Hinga, K.R. 1988. Seasonal predictions
   for pollutant scavenging in two coastal
   environments using a model calibration
   based upon thorium scavenging. Marine
   Environmental Research 26:97-112.

   Holland, A.F. (editor). 1990.  Near coastal
   program plan for 1990: Estuaries.
   EPA/600/4-90/033.  Office of Research
   and Development, USEPA,
   Narragansett, RI.

   Holland, A.F. 1985.  Long-term
   variation of macrobenthos in a
   mesohaline region of the Chesapeake
   Bay. Estuaries 8(2a):93-113.

   Holland, A.F., A.T. Shaughnessy, L.C.
   Scott, V.A. Dickens, J. Gerritsen, and J.A.
   Ranasinghe. 1989. Long-term benthic
   monitoring and assessment program for the
   Maryland portion of the Chesapeake Bay:
   Interpretive report.  CBRM-LTB/EST-2.
   Prepared for MDNR, Power Plant
   Research Program, Annapolis, Maryland
   by Versar, Inc., Columbia, MD.

   Holland, A.F., A.T. Shaughnessy, L.C.
   Scott, V.A. Dickens, J.A. Ranasinghe,
   and J.K. Summers. 1988. Progress report:
   Long-term benthic monitoring and
   assessment program of the Maryland
   portion of Chesapeake Bay (July 1986 -
   October 1987).  PPRP-LTB/EST-88-1.
   Prepared for MDNR, Power Plant
   Research Program, Annapolis, Maryland
   by Versar, Inc., Columbia, MD.

   Holland, A.F., A.T. Shaughnessy, and
   M.H. Hiegel. 1987. Long-term variation
in mesohaline Chesapeake Bay
macrobenthos: spatial and temporal
patterns. Estuaries 10(3):227-245.

Honeyman, B.D. and P.H. Santschi.
1988. Metals in aquatic systems:
Predicting their scavenging residence
times from laboratory data remains a
challenge.  Environmental Science and
Technology 22:862-871.

Houde, E.D, and Zastrow, C.E. 1991.
Bay Anchovy Anchoa mitchilli.  Pages 81-
86 in S.L. Funderbunk, J.A. Mihursky,
S.J. Jordan, and D. Riley (editors).
Habitat requirements for Chesapeake Bay
living resources. Prepared for the Living
Resources Subcommittee, Chesapeake
Bay Program.

Howard, R.K., G.J. Edgar, and  P.A.
Hutchings.  1989. Faunal assemblages of
seagrass beds. Pages 536-564 in A.W.D.
Larkum, A.J. McComb, and S.A.
Shepard (editors).  Biology of seagrasses.
A treatise on the biology of seagr asses with
special reference to the Australian region.
Elsevier, New York, NY.

Hughes, R.M. and D.P. Larsen. 1988.
Ecoregions: An approach to surface
water protection. Journal of the Water
Pollution Control Federation 60:486-493.

Hughes, R.M., P.R. Kaufmann, A.T.
Herlihy, T.M. Kincaid, L. Reynolds and
D.P. Larsen. 1998.  A process for
developing and evaluating indices of
fish assemblage integrity. Canadian
Journal of Fisheries and Aquatic Science
55:1618-1631.

Hughes, R.M., D.P. Larsen, and J.M.
Omernik. 1986. Regional reference
sites: A method for assessing stream
potentials. Environmental Management
10:629-635.

Hurlbert,  S.H. 1984.  Pseudoreplication
and the design of ecological field
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                       L-9

-------
   experiments. Ecological Monographs
   54(2).

   Hutchinson, G.E. 1967. A treatise on
   limnology. Wiley, New York, NY.

   Hyland, J.L., L. Balthis, C.T. Hackney, G.
   McRae, A.H. Ringwood, T.R. Snoots,
   R.F. Van Dolah, and T.L. Wade.  1998.
   Environmental quality of estuaries of the
   Carolinian Province: 1995.  NOAA
   Technical Memorandum NOS ORCA
   123. National Oceanic and Atmospheric
   Administration, Charleston, SC.

   Hyland, J.L., T.J. Herrlinger, T.R. Snoots,
   A.H. Ringwood, R.F. Van Dolah, C.T.
   Hackney, G.A. Nelson, J.S. Rosen, and
   S.A. Kokkinakis.  1996. Environmental
   quality of estuaries of the Carolinian
   Province:  1994. Annual Statistical
   Summary for the 1994 EMAP-Estuaries
   Demonstration Project in the Carolinian
   Province. NOAA Technical
   Memorandum NOS ORCA 97. National
   Oceanic and Atmospheric
   Administration/NOS, Office of Ocean
   Resources Conservation and
   Assessment, Silver Spring, MD.  102 p.

   Ingersoll, C.G., P.S. Haverland, E.L.
   Brunson, T.J. Canfield, F.J. Dwyer, C.E.
   Henke, N.E. Kemble.  1996. Calculation
   and evaluation of sediment effect
   concentrations for the amphipod
   Hyalella azteca and the midge Chironomus
   riparius. Journal of Great Lakes Research
   22(3): 602-623.

   Jordan, S., J. Carmichael, and B.
   Richardson. 1992. Habitat measurements
   and index ofbiotic integrity based on fish
   sampling in northern Chesapeake Bay.  A
   Proceedings: Estuarine and Near
   Coastal Bioassessment and Biocriteria
   Workshop,  Annapolis, Maryland.
   USEPA, Office of Science and
   Technology, Washington, DC.
Kajak, Z. 1963. Analysis of quantitative
benthic methods. Ekologia Polska (A)
11:1-56.

Karr, J.R. 1991. Biological integrity: A
long-neglected aspect of water resource
management.  Ecological Applications
1:66-84.

Karr, J.R. 1981. Assessment of biotic
integrity using fish communities.
Fisheries 6(6):21-27.

Karr, J.R., K.D. Fausch, P.L. Angermeier,
P.R. Yant, and I.J. Schlosser. 1986.
Assessing biological integrity in running
waters: A method and its rationale. Illinois
Natural History Survey, Spec. Publ. 5.

Kemble, N., W. Brumbaugh, E. Brenson,
F. Dwyer, C. Ingersoll, D. Monda, and
D. Woodward. 1994.  Toxicity of metal
contaminated sediments from the Upper
Clark Fork River Montana to aquatic
invertebrates in laboratory exposures.
Environmental Toxicology and Chemistry
13:1985-1997.

Kendall, D.K.  1983.  The role of'physical-
chemical factors in structuring subtidal
marine and estuarine benthos.  Tech. Rep.
EL-83-2. U.S. Army Waterways Exp.
Stn., Vicksburg, MS.

Klemm, D.J., G.J.  Strober, and J.M.
Lazorchak. 1992. Fish field and laboratory
methods for evaluating the biological
integrity of surface waters. EPA/600/R-
92-111.  USEPA, Cincinnati, OH.

Komar, P.D. 1976. Beach processes and
sedimentation.  Prentice-Hall, Inc.
Englewood Cliffs, NJ.  429 pp.

Krom, M.D. and R.A Berner.  1983.
Journal of Sedimentary Petrology 53, 660.

Krumgalz, B.S. 1993. "Fingerprints"
approach to the identification of
anthropogenic trace metal sources in the
L-10
                              Literature Cited

-------
   nearshore and estuarine environments.
   Estuaries 16(3A):488-495.

   LaPointe, B.E. and M.W. Clark. 1992.
   Nutrient inputs from the watershed and
   coastal eutrophication in the Florida
   keys. Estuaries 15(4):465-476.

   Latimer,}., W. Boothman, R. Tobin, D.
   Keith, J. Kiddon, D. Scott,  S. Jayaraman,
   R. McKinney, and G. Chmura. 1997.
   Historical reconstruction of contaminant
   levels and ecological effects in a highly
   contaminated estuary. 14th International
   Conference of the Estuarine Research
   Federation.  Providence, RI.

   Lenat,D.R.  1993.  A biotic index f or the
   southeastern United States: Derivation
   and list of tolerance values, with criteria
   for assigning water quality ratings.
   Journal of the North American
   Benthological Society 12(3):279-290.

   Lie, U. 1974. Distribution and structure
   of benthic assemblages in  Puget Sound,
   Washington, USA. Marine Biology
   26:203-223.

   Llanso, R.J.  1999.  The distribution and
   structure of soft-bottom macrobenthos
   in Puget Sound in relation to natural
   and anthropogenic factors. Puget Sound
   Research 1998. Puget Sound Ambient
   Monitoring Program, Olympia, WA:
   760-771.

   Long,E.R.  1989.  The use  of the
   sediment quality triad in classification of
   sediment contamination.  Marine Board,
   National Research Council
   Symposium/Workshop on Contaminated
   Marine Sediments.  National Research
   Council, Washington, D.C.

   Long, E.R., L.J. Field, and  D.D.
   MacDonald. 1998a.  Predicting toxicity
   in marine sediments with  numerical
   sediment quality guidelines.
Environmental Toxicology and Chemistry
17(4):714-727.

Long, E.R., D. D. MacDonald, J.C.
Cubbage, and C.G. Ingersoll. 1998b.
Predicting the toxicity of sediment-
associated trace metals with SEM:AVS
concentrations and dry weight-
normalized concentrations:  A critical
comparison.  Environmental Toxicology
and Chemistry 17(4):972-974.

Long, E.R., A. Robertson, D.A. Wolfe,
J.Hameedi, and G.M. Sloane. 1996.
Estimates of the spatial extent of
sediment toxicity in major U.S. estuaries.
Environmental Science & Technology
30(12):3585-3592.

Long, E.R., D.D. MacDonald, S.L. Smith,
F.D. Calder. 1995.  Incidence of adverse
biological effects within ranges of
chemical concentrations in marine and
estuarine sediments. Environmental
Management 19:81-97.

Long, E.R. and L.G. Morgan. 1990. The
potential for biological effects ofsediment-
sorbed contaminants tested in the National
Status and Trends Program. NOAA
Technical Memorandum NOSOMA52.
U.S. Department of Commerce, National
Oceanic and Atmospheric
Administration, National Ocean Service,
Rockville, MD.

Long, E., M. Buchman, S.  Bay, R.
Breteler, R. Carr, P. Chapman, J. Hose,
A. Lissner, J. Scott, and D. Wolfe. 1990.
Comparative evaluation of five toxicity
tests with sediments from San Francisco
Bay and Tomales Bay, CA.
Environmental Toxicology and Chemistry
9:1193-1214.

Long, E.R. and P.M. Chapman.  1985. A
sediment quality triad: Measures of
sediment contamination,  toxicity and
infaunal community composition in
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      L-11

-------
   Puget Sound.  Marine Pollution Bulletin
   16:405-415.

   Luckenback, M.W., R.J. Diaz, and L.C.
   Schaffner. 1988. Benthic assessment
   procedures.

   Ludwig, J.A. and J.F. Reynolds. 1988.
   Statistical ecology. A primer on methods
   and computing. 337 p. John Wiley and
   Sons, New York, NY.

   Mallin, M.A. 1994. Phytoplankton
   ecology of North Carolina estuaries.
   Estuaries 17(3):561-574.

   Malone, T.C., D.J. Conley, T.R. Fisher,
   P.M. Gilbert, L.W. Harding, and K.G.
   Sellner. 1996.  Scales of nutrient-limited
   phytoplankton productivity in
   Chesapeake Bay. Estuaries 19(2B):371-
   385.

   Maryland Chamber of Commerce,
   personal communication, 1990.

   MacDonald, D.D., R.S. Carr, F.D. Calder,
   E.R. Long, and C.G. Ingersoll. 1996.
   Development  and evaluation of
   sediment quality guidelines for Florida
   coastal waters. Ecotoxicology 5:253-278.

   Mearns, A.J. and J.Q. Word. 1982.
   Forecasting effects of sewage solids on
   marine benthic communities. In G. F.
   Mayer (editor).  Ecological stress and the
   New York Bight: Science and management.
   Estuarine Research Federation. 713 pp.

   Miller, D.L., P.M. Leonard, R.M.
   Hughes, J.R. Karr,P.B. Moyle, L.H.
   Schrader, B.A. Thompson, R.A. Daniels,
   K.D. Fausch, G.A.  Fitzhugh, J.R.
   Gammon, D.B. Halliwell, P.L.
   Angermeier, and D.J. Orth.  1988.
   Regional applications of an index of
   biotic integrity for use in water resource
   management.  Fisheries 13:12-20.
National Research Council (NRC). 1989.
Contaminated Marine Sediments —
Assessment and Remediation. National
Academy Press, Washington, DC.

Nelson, W.G.  1990. Prospects for
development of an index of biotic
integrity for evaluating habitat
degradation in coastal systems.
Chemistry and Ecology 23: 152-165.

Nelson, W.G., and F.D. Spoon. 1994a.
Field verification of marine metrics
developed for benthic habitats. Florida
Institute of Technology, Oceanography
Program, Division of Marine and
Environmental Systems. Final Report to
Tetra Tech, Inc., Owings Mills, MD.

Nelson, W.G., and F.D. Spoon. 1994b.
Field Verification of the Use  ofAmphipods
As Bioindicators in Marine Coastal
Ecosystems.  Florida Institute of
Technology, Oceanography Program,
Division of Marine and Environmental
Systems.  Final Report to Tetra Tech,
Inc., Owings Mills, MD.

Nelson, W.G., R.J. Diaz, and F.D. Spoon.
1993. Comparison of results of marine
benthic metric development between
Chesapeake Bay and the Indian River
Lagoon, Florida. Florida Institute of
Technology, Division of Marine and
Environmental Systems, Final Report to
Tetra Tech, Inc., Owings Mills, MD.

Nelson, M., P. Landrum, G. Burton, Jr., J.
Klaine, E. Crecelius, T. Byl, D. Gossiaux,
V. Tsymbal, L. Cleveland, C. Ingersoll,
and G. Sasson-Brickson. 1993. Toxicity
of contaminated sediments in dilution
series with control sediments.
Chemosphere 27:1789-1812.

Nixon, S.W., C.D. Hunt and B.L.
Nowicki.  1986. The retention of
nutrients  (C, N, P), heavy  metals (Mn,
Cd, Pb, Cu), and petroleum
hydrocarbons in Narragansett Bay.
L-12
                             Literature Cited

-------
   Pages 99-122 in P. Lasserre and J.M.
   Martin (editors).  Biogeochemical Processes
   at the Land-Sea Boundary. Elsevier, New
   York, NY.

   O'Connor, T.P, A.Y Cantillo, and G.G.
   Lauenstein. 1994. Monitoring of
   temporal trends in chemical
   contamination by the NOAA National
   Status and Trends Mussel Watch Project.
   Pages 29-50 in K.J.M. Kramer (editor).
   Biomonitoring of Coastal Waters and
   Estuaries. CRC Press, Inc., Boca Raton,
   FL.

   Odum, E.P. 1971. Fundamentals of
   ecology, 3rd Edition.  W.B. Saunders Co.
   Philadelphia, PA.

   Odum, W. E. 1970. Insidious alteration
   of the estuarine environment.
   Transactions of the American Fisheries
   Society 4:836-850.

   Odum, W.E. and  C.C. Mclvor.  1990.
   Mangroves.  Chapter 15 in Myers, R.L.
   and J.J. Ewel (editors). Ecosystems of
   Florida. University of Central Florida
   Press.

   Office of Technology Assessment (OTA).
   1987. Wastes in marine environments.
   OTA, Washington, DC.

   Ohio EPA. 1990. The use of biocriteria in
   the Ohio  EPA surface water monitoring and
   assessment program. Ecological
   Assessment Section, Division of Water
   Quality Planning and Assessments,
   Ohio EPA, Columbus, OH. August 22.

   Ohio EPA. 1987. Biological criteria for the
   protection of aquatic life. Vols. 1-3.
   Monitor. Assess.  Prog., Surface Water
   Sec., Div. Water Quality, Ohio EPA,
   Columbus, OH.

   Omernik, J.M. 1987. Ecoregions of the
   conterminous United States.  Annals of
the Association of American Geographers
77(1):118-125.

Oreskes, N., K. Schrader-Frechette, and
K. Belitz. 1994. Verification, validation,
and confirmation of numerical models
in the earth sciences. Science 263:641-
646.

Orth, R.J., J.F. Nowak, G.F. Anderson,
and J.R. Whiting. 1993.  Distribution of
submerged aquatic vegetation in the
Chesapeake Bay and its tributaries and
Chincoteague Bay -1992.  Prepared by
Virginia Institute of Marine Science,
Gloucester Point, VA for the USEPA,
Chesapeake Bay Program Office,
Annapolis, MD.

Overton, W.S., D. White, and D.L.
Stevens. 1990. Design report for EMAP:
Environmental Monitoring Assessment
Program. EPA/600/3-91/053.  U.S.
Environmental Protection Agency,
Office of Research and Development,
Washington, DC.

Pait, A.S., D.R.G.  Farrow, J.A. Lowe, and
P.A. Pacheis. 1989.  Agricultural pesticide
use in estuarine drainage areas: A
preliminary summary for selected pesticides.
Strategic Assessment Branch Office of
Oceanography and Marine Assessment,
NOAA, Rockville, MD.

Patterson, R.T.  1990. Intertidal benthic
foraminiferal biofaces on the Fraser river
delta - British Columbia - Modern
distribution and paleoecological
importance. Micropaleontology 36:229-
245.

Paul, J.F., J.H. Gentile, K.J. Scott, S.C.
Schimmel,  D.E. Campbell, and R.W.
Latimer. 1999.  EMAP-Virginian Province
Four-Year Assessment Report (1990-1993).
EPA 600/R-99/004.  U.S. Environmental
Protection Agency, Atlantic Ecology
Division, Narragansett, RI.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      L-13

-------
   Paulsen, S.B., D.P. Larsen, P.R.
   Kaufmann, T.R. Whittier, J.R. Baker,
   D.V. Peck, J. McGue, R.M. Hughes, D.
   McMullen, D.L. Stevens, J.L. Stoddard, J.
   Lazorchak, W. Kinney, A.R. Selle, and R.
   Hjort.  1991. The Environmental
   Monitoring and Assessment Program
   (EMAP) - Surface waters monitoring
   research plan, fiscal year 1991.
   EPA/600/3-91/022. USEPA, Corvallis,
   OR.

   Pearson, T.H. and R. Rosenberg. 1978.
   Macrobenthic succession in relation to
   organic enrichment and pollution of the
   marine environment. Oceanography and
   Marine Biology Annual Review 16:229-311.

   Peterman, R.M. 1990.  The importance
   of reporting statistical power:  The forest
   decline and acidic deposition example.
   Ecology 71(5):2024-2027.

   Peters, J.A.  1988. Quality control
   infusion into stationary source
   sampling. In L.H. Keith (editor).
   Principles of environmental sampling.
   American Chemical Society,
   Washington, DC.

   Peters, R.H. 1991. A critique for ecology.
   Cambridge University Press,
   Cambridge, MA.

   Pielou, E.C. 1977. Mathematical ecology.
   John Wiley & Sons, Inc., New York, NY.
   385 pp.

   Plafkin, J.L., M.T. Barbour, K.D. Porter,
   S.K. Gross, and R.M. Hughes.  1989.
   Rapid bioassessment protocols for use in
   streams and rivers: Benthic
   macroinvertebrates and fish. EPA/440/4-
   89-001. USEPA, Office of Water,
   Washington, DC.

   Plumb, R.H. 1981.  Procedure for handling
   and chemical analysis of sediment and water
   samples. Technical Report EPA/CE-81-1.
   Prepared for the U.S. Environmental
Protection Agency/Corps of Engineers
Technical Committee on Criteria for
Dredge and Fill Material.
Environmental Laboratory, U.S. Army
Waterways Experiment Station,
Vicksburg, MS.

Pond, S. and G.L. Pickard. 1983.
Introductory dynamic oceanography.  3rd
Edition. Pergamon Press, Inc., New
York, NY.

Puget Sound Estuary Program (PSEP).
1995. Recommended guidelines for
conducting laboratory bioassays on Puget
Sound sediments. Prepared for USEPA
Region 10, Office of Puget-Sound,
Seattle, WA and Puget Sound Water
Quality Authority, Olympia, WA.

Puget Sound Water Quality Authority
(PSWQA).  1991. Puget Sound update.
Second annual report of the Puget
Sound Ambient Monitoring Program.
PSWQA, Seattle, WA. 99 pp.

Puget Sound Water Quality Authority
(PSWQA).  1990. Puget Sound update.
First annual report of the Puget Sound
Ambient Monitoring Program.  PSWQA,
Seattle, WA. 89pp.

Puget Sound Water Quality Authority
(PSWQA).  1988. Puget Sound ambient
monitoring program, monitoring
management committee. Final Report.
PSWQA, Seattle, WA. 145 pp.

Rabalais, N.N 1990. Biological
communities of the south Texas
continental shelf. American Zoologist
30:77-87.

Rabalais, N.N, M.J. Dagg, and D.F.
Boesch. 1985.  Nationwide review of
oxygen depletion and eutrophication in
estuarine and coastal waters:  Gulf of
Mexico (Alabama, Mississippi, Louisiana,
and Texas). Final Report to U.S.
Department of Commerce, NOAA,
L-14
                             Literature Cited

-------
   Ocean Assessment Division, Rockville,
   MD.

   Rakoncinski, C.F., S.S. Brown, G.R.
   Gaston, R.W. Heard, W.W. Walker, and
   J.K. Summers. 1997. Macrobenthic
   responses to natural and contaminant-
   related gradients in northern Gulf of
   Mexico estuaries.  Ecological Applications
   7:1278-1298.

   Rakocinski, C., R.W. Heard, T. Simons,
   and D. Gledhill. 1991.
   Macroinvertebrate associations from
   beaches of selected barrier islands in the
   Northern Gulf of Mexico: Important
   environmental relationships. Bulletin of
   Marine Science 48:689-701.

   Ranasinghe, J.A., D.M. Dauer, L.C.
   Schaffnter, RJ. Diaz. 1994. Chesapeake
   Bay Benthic Community Restoration Goals.
   Chesapeake Bay Program Office, 68-D9-
   0166; Chesapeake Bay Research &
   Monitoring Division, CB92-006-004.

   Ranasinghe, J.A., L.C. Scott, and R.
   Newport. 1992. Chesapeake Bay water
   quality monitoring program: long-term
   benthic monitoring and assessment
   component. Vol. I. Draft.  Prepared by
   Versar, Inc., Columbia, Maryland, for
   the Maryland Department of
   Environment, Baltimore, MD.

   Reckhow, K.H. and W. Warren-Hicks.
   1996. Biological criteria:  Technical
   guidance for survey design and statistical
   evaluation ofbiosurvey data. Prepared by
   School of the Environment, Duke
   University, Durham, NC for USEPA,
   Office of Science and Technology,
   Health and Ecological Criteria Division,
   Washington, DC.

   Reid, G.K. and R.D. Wood. 1976.
   Ecology of inland waters and estuaries. D.
   Van Nostrand Company, New York,
   NY. 485pp.
Reish, D. J. and J. L. Bernard.  1960.
Field toxicity tests in marine water
utilizing the polychaetous annelid
Capitella capitata (Fabricius). Pacific
Naturalist 1:1-8.

Reishi D. and J. Lemay.  1988. Bioassay
manual for dredged materials. US Army
Corps of Engineers, Los Angeles
District, Los Angeles, CA, Technical
Report DACW-09-83R-005.

Reynoldson, T.B. and M.A. Zarull. 1993.
An approach to the development of
biological sediment guidelines.  Pages
177-200  in S. Woodley, J. Kay, and G.
Grancis (editors). Ecological Integrity and
the Management of Ecosystems.  St. Lucie
Press.

Rhoads, D.C. 1974. Organism-sediment
relations on the muddy  sea floor.
Oceanography and Marine Biology Annual
Review 12:263-300.

Sanford, L.P., K.G. Sellner, and D.L.
Breitburg. 1990. Covariability of
dissolved oxygen with physical
characteristics in the summertime
Chesapeake Bay. Journal of Marine
Research 48:567-590.

Santangelo, R. 1996. County Sanitation
Districts of Orange County, 10844 Ellis
Ave., Fountain Valley, CA 92728.

Sarda, N. and G. Burton, Jr. 1995.
Ammonia variation in sediments:
spatial, temporal, and method-related
effects.  Environmental Toxicology and
Chemistry 14:1499-1506.

Schimmel, S.C., B.D. Melzian, D.E.
Campbell, C.J. Stubel, SJ. Benyi, J.S.
Rosen, and H.W. Buffum.  1994.
Statistical Summary: EMAP-Estuaries
Virginian Province -1991. EPA/620/R-
94/005.  Office of Research and
Development, USEPA, Narragansett, RI.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      L-15

-------
   Schindler, D.W. 1988.  Effects of acid
   rain on freshwater ecosystems.  Science
   239:149-158.

   Schindler, D.W. 1971.  A hypothesis to
   explain differences and similarities
   among lakes in the Experimental Lakes
   Area, northwestern Ontario. Journal of
   the Fisheries Research Board of Canada
   28:295-301.

   Schindler, D.W., S.E.M. Kasian and R.H.
   Hesslein. 1989.  Biological
   impoverishment in lakes of the
   midwestern and northeastern United
   States from acid rain.  Environmental
   Science and Technology 23:573-580.

   Schlekat, C.E., B.L. McGee, D.M.
   Boward, E. Reinharz, D.J. Velinsky,  and
   T.L. Wade. 1994. Tidal river sediments
   in the Washington, DC area. III.
   Biological effects associated with
   sediment contamination. Estuaries
   17(2):334-344.

   Schroeder, W.W. 1979. The dissolved
   oxygen puzzle of the Mobile estuary. In
   Jr. and J.P. Smith (editors). H.A.
   Loyacano, Symposium on the Natural
   Resources of the Mobile Estuary, Alabama,
   May 1979.  Alabama Coastal Area Board,
   Mississippi-Alabama Sea Grant
   Consortium, U.S. Fish and Wildlife
   Service.

   Schubel, J.R. and H.H.  Carter. 1984. The
   estuary as a filter for fine-grained
   suspended sediment.  Pages 81-104 in
   V.S. Kennedy (editor).  The Estuary as a
   Filter. Academic Press, Orlando, FL.

   Sen Gupta, B.K., R.E. Turner and N.N.
   Rabalais. 1996.  Seasonal oxygen
   depletion in continental-shelf waters of
   Louisiana: Historical record of benthic
   foraminifers. Geology 24(3):227-230.

   Sharpe, J.H., J.R. Pennock, T.M. Church,
   T.M. Tramontane, and L.A. Cifuentes.
1984.  The estuarine interaction of
nutrients, organics, and metals: A case
study in the Delaware Estuary. Pages
241-258 in V.S. Kennedy (editor). The
estuary as a filter. Academic Press,
Orlando, FL.

Shepard, S.A., A.J. McComb, D.A.
Bulthis, V. Neverauskas, D.A.
Steffensen, and R. West. 1989. Decline
of seagrasses. Pages 346-393 in A.W.D.
Larkum, A.J. McComb, and S.A.
Shepard (editors).  Biology of seagrasses.
A treatise on the biology of seagrasses with
special reference  to the Australian region.
Elsevier, New York, NY.

Simenstad, C.A., C.D. Tanner, R.M.
Thorn, and L.L. Conquest. 1991.  Puget
Sound Estuary Program: Estuarine habitat
assessment protocol. EPA 910/9-91-037.
Prepared for USEPA, Region 10, Office
of Puget Sound, Seattle, WA.  201 pp.

Simpson, B.L., R. Aaron, J. Betz, D.
Hicks, J. van der Kreeke, and B. Yokel.
1979.  The Naples Bay Study. Prepared
for the Collier County Conservancy,
Naples, FL.

Smith, S.M.  and G.L. Hitchcock.  1994.
Nutrient enrichments and
phytoplankton growth in the surface
waters of the Louisiana Bight.  Estuaries
17(4):740-753.

Smith, R.W., M. Bergen, S.B. Weisberg,
D. Cadien, A. Dalkey, D. Montagne, J.K.
Stull, & R.G. Velarde.  2000. Benthic
response index for assessing infaunal
communities on the mainland shelf of
southern California. Ecological
Applications. In press.

Snedecor, G.W. and W.G. Cochran.
1980.  Statistical methods.  7th edition. The
Iowa State University Press, Ames, IA.

Snelgrove, P.V.R. and C.A. Butman.
1994.  Animal-sediment relationships
L-16
                             Literature Cited

-------
   revisited: Cause versus effect.
   Oceanography and Marine Biology Annual
   Review 32:111-177.

   Southerland, M.T. and J.B. Stribling.
   1995. Status of biological criteria
   development and implementation.
   Pages 81-96 in W.S. Davis and T.P.
   Simon (editors). Biological assessment and
   criteria: Tools for water resources planning
   and decision making. Lewis Publishers,
   Boca Raton, FL.

   Stevenson, J.C., L.W. Staver, & K.W.
   Staver.  1993. Water quality associated
   with survival of submersed aquatic
   vegetation along an estuarine gradient.
   Estuaries 16(2)346-360.

   Stickney, R.R. 1984. Estuarine ecology of
   the southeastern United States and Gulf of
   Mexico. Texas A & M University Press,
   College Station, TX.

   Stoermer, E.F., J.A. Wolin, C.L. Schelske,
   and DJ. Conley. 1990. Siliceous
   microfossil succession in Lake Michigan.
   Limnology and Oceanography 35:959-967.

   Strobel, C.J., H.W. Buffum, S.J. Benyi,
   E.A. Petrocelli, D.R. Reifsteck, and D.J.
   Keith. 1995. Statistical Summary: EMAP-
   Estuaries Virginian Province -1990 to
   1993. EPA/620/R-94/026. U.S.
   Environmental Protection Agency,
   National Health and Environmental
   Effects Research Laboratory, Atlantic
   Ecology Division, Narragansett, RI.

   Strobel, C.J., S.J. Benyi, D.J. Keith, H.W.
   Buffum, and E.A. Petrocelli. 1994.
   Statistical summary: EMAP-Estuaries
   Virginian Province -1992. EPA/620/R-
   94/019.  USEPA, Environmental
   Research Laboratory, Narragansett, RI.

   Summers J.K. 1994. (EMAP-Estuaries - A
   report on the condition of the estuaries of the
   United States in 1990-1993: A program in
   progress.) Gulf Breeze (FL): U.S.
Environmental Protection Agency,
Office of Research and Development,
Environmental Research Laboratory.
EPA/620/R-94/

Summers, J.K., T.L. Wade, V.D. Engle,
and Z.A. Malneb. 1996. Normalization
of metal concentrations in estuarine
sediments from the Gulf of Mexico.
Estuaries 19(3)581-594.

Summers, J.K., J.M. Macauley, P.T.
Heitmuller, V.D. Engle, A.M. Adams,
and G.T. Brooks.  1993. Statistical
summary: EMAP-Estuaries Louisianian
Province -1991. EPA/600/R-93/001.
USEPA, Office of Research and
Development, Gulf Breeze, FL.

Summers, J.K. and V.D. Engle. 1993.
Evaluation of sampling strategies to
characterize dissolved oxygen
conditions in northern Gulf of Mexico
estuaries. Environmental Monitoring and
Assessment 24:219-229.

Summers, J.K., J.M. Macauley, and P.T.
Heitmuller. 1992. Field activities report:
Louisianian Province USEPA, Office of
Research and Development,
Environmental Research Laboratory,
Gulf Breeze, FL.  ERL-Gulf Breeze
Contribution No. SR-118.

Suter, G.W., II. 1993.  Ecological risk
assessment. Lewis Publishers, Boca
Raton, FL.

Swartz, R., D. Schults, R. Ozretich, J.
Lamberson, F. Cole, T. DeWitt. 1995.
PAH: A model to predict the toxicity of
polynuclear aromatic hydrocarbon
mixtures in field collected sediments.
Environmental Toxicology and Chemistry
14:1972-1987.

Swartz, R.C., F.A. Cole, J.O. Lamberson,
S.P. Ferraro, D.W. Schults, W.A. DeBen,
H. Lee II, and  R.J. Ozretich.  1994.
Sediment toxicity, contaminations and
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                      L-17

-------
   amphipod abundance at a DDT-and
   dieldrin-contaminated site in San
   Francisco Bay.  Environmental Toxicology
   and Chemistry 13(6):949-962.

   Swartz, R.C., F.A. Cole, D.W. Schults,
   and W.A. DeBen. 1986. Ecological
   changes in the Southern California Bight
   near a large sewage outfall:  Benthic
   conditions in 1980 and 1983. Marine
   Ecology Progress Series 31:1-13.

   Swartz, R.C., D.W. Schults, G.R.
   Ditsworth, W.A. DeBen, and F.A. Cole.
   1985. Sediment toxicity, contamination,
   and macrobenthic communities near a
   large sewage outfall.  Pages 152-175 in
   T.P. Boyle (editor).  Validation and
   predictability of laboratory methods for
   assessing the fate and effects of
   contaminants in aquatic ecosystems, ASTM
   STP 865. American Society for Testing
   and Materials, Philadelphia.

   Symposium on the Classification of
   Brackish Waters.  1958.  The Venice
   System for the Classification of Marine
   Waters According to Salinity. Oikos
   9:311-312.

   ter Braak, C.J.F. 1986. Canonical
   correspondence analysis:  new
   eigenvector technique for multivariate
   direct gradient analysis. Ecology
   67:1167-1179.

   Thomann, R.V. and J.A. Mueller.  1987.
   Principles of surface water quality modeling
   and control.  Harper and Row Publishers,
   New  York, NY. 694pp.

   Thompson, B.A., and G.R. Fitzhugh.
   1986. A use attainability study: An
   evaluation offish and macroinvertebrate
   assemblages of the Lower Calcasieu River,
   Louisiana. LSU-CFI-85-29. Louisiana
   State University Center for Wetland
   Resources, Coastal Fisheries Institute,
   Baton Rouge, LA.
Thompson, S.K. 1992. Sampling. John
Wiley & Sons, Inc., New York, NY.  343
pp.

Turekian, K.K. 1977. The fate of metals
in the oceans.  Geochimica et
Cosmochimica Acta 41:1139-1144.

Turner, R.E. and N.N. Rabalais. 1994.
Coastal eutrophication near the
Mississippi River delta.  Nature 368:619-
621.

Turner, R.E., W.W. Schroder, and W.J.
Wiseman. 1987. The role of
stratification in the deoxygenation of
Mobile Bay and adjacent shelf bottom
waters. Estuaries 10:13-19.

U.S. Army Corps of Engineers. 1996. A
comparison of the benthic macrofaunal
resources within the Bethany Beach Sand
Borrow Area. Prepared for U.S. Army
Corps of Engineers, Philadelphia
District by Versar, Inc., Columbia, MD.

U.S. Environmental Protection Agency
(USEPA). 1998a. EPA requirements for
quality assurance project plans for
environmental data operations. EPA
QA/R-5.  U.S. Environmental Protection
Agency, Quality Assurance Division,
Washington, DC 20460.

U.S. Environmental Protection Agency
(USEPA). 1998b. Lake and reservoir
bioassessment and biocriteria technical
guidance document. U.S. Environmental
Protection Agency, Office of Water,
Washington, D.C. EPA-841-B-98-007.

U.S. Environmental Protection Agency
(USEPA). 1996a. Biological criteria:
Technical guidance for streams and small
rivers.  EPA822-B-96-001. U.S.
Environmental Protection Agency,
Office of Water, Washington, DC.

U.S. Environmental Protection Agency
(USEPA). 1996b. Recommended
L-18
                             Literature Cited

-------
   guidelines for sampling and analyses in the
   Chesapeake Bay monitoring program.
   CBP/TRS 148/96.  EPA 903-R-006.
   Chesapeake Bay Program, Annapolis,
   MD.

   U.S. Environmental Protection Agency
   (USEPA). 1995.  Bibliography of methods
   for marine and estuarine monitoring. EPA
   842-B-95-002. USEPA,  Office of Water,
   Office of Wetlands, Oceans, and
   Watersheds, Oceans and Coastal
   Protection Division, Washington, DC.

   U.S. Environmental Protection Agency
   (USEPA). 1994a. CWA Section 403:
   Procedural and monitoring guidance. EPA
   842-B-94-003. Office of Wetlands,
   Oceans, and Watersheds, Oceans and
   Coastal Protection Division, USEPA,
   Washington, DC.

   U.S. Environmental Protection Agency
   (USEPA). 1994b. Methods for measuring
   the toxicity of sediment associated
   contaminants with estuarine and marine
   amphipods. EPA-600/R-94/025,
   Narragansett, RI.

   U.S. Environmental Protection Agency
   (USEPA). 1994c (draft). Generic quality
   assurance project plan guidance for
   programs using community-level biological
   assessment in streams and rivers. Prepared
   by Tetra Tech, Inc. for Assessment and
   Watershed Protection,  USEPA,
   Washington, DC. August 1.

   U.S. Environmental Protection Agency
   (USEPA). 1994d. Guidance for the data
   quality objectives process. EPA 600/R-
   96/055.  U.S. Environmental Protection
   Agency, Office of Research and
   Development, Washington, DC.

   U.S. Environmental Protection Agency
   (USEPA). 1994e. Environmental
   Monitoring and Assessment Program:
   Integrated quality assurance project plan for
   the Surface Waters Resource Group, 1994
activities, Rev. 200. U.S. Environmental
Protection Agency, Las Vegas, NV. EPA
600-X-91-080.

U.S. Environmental Protection Agency
(USEPA). 1993a. Environmental
Monitoring and Assessment Program.
EMAP-Estuaries Louisianian Province.
1993 Quality Assurance Project Plan.
USEPA, Office of Research and
Development, Washington, DC.

U.S. Environmental Protection Agency
(USEPA). 1993b (draft final).  EPA
requirements for quality assurance project
plans for environmental data operations.
EPA QA/R-5. Quality Assurance
Management Staff, USEPA, Washington,
DC.

U.S. Environmental Protection Agency
(USEPA). 1992. Monitoring guidance for
the national estuary program. Final. EPA
842-B-92-004. Office of Water, Oceans,
and Coastal Protection Division,
USEPA, Washington, DC.

U.S. Environmental Protection Agency
(USEPA). 1990. Biological criteria:
National program guidance for surface
waters. EPA-440/5-90-004. USEPA,
Office of Water, Office of Regulations
and Standards, Criteria and Standards
Division, Washington, DC.

U.S. Environmental Protection Agency
(USEPA). 1987. Surface water
monitoring: A framework for change.
USEPA, Office of Water, Office of Policy,
Planning and Evaluation, Washington,
DC.

U.S. Environmental Protection Agency
(USEPA). 1986-1991. Recommended
protocols for measuring selected
environmental variables in Puget Sound.
Looseleaf. Region 10, Puget Sound
Estuary Program, USEPA, Seattle, WA.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
                                     L-19

-------
   Vernberg, F. S. 1972. Dissolved gases.
   Pages 1491-1526 In O. Kinne (editor).
   Marine Ecology, New York, Wiley-
   Interscience. Volume I, Part 3.

   Ward, T.J.  1989. The accumulation and
   effects of metals in seagrass habitats.
   Pages 797-820 In A.W.D. Larkum, A.J.
   McComb, and S.A. Shepard (editors).
   Biology of seagrasses.  A treatise on the
   biology of seagrasses with special reference
   to the Australian region.  Elsevier, New
   York, NY.

   Warwick, R.M. 1988. Analysis of
   community attributes of the
   macrobenthos of Fierfjord/
   Laugelundfjord at taxonomic levels
   higher than species.  Marine Ecology
   Progress  Series 46:167-170.

   Warwick, R.M. and K.R. Clarke. 1991.
   A comparison of some methods for
   analyzing changes in benthic
   community structure.  Journal of the
   Marine Biological Association of the
   United Kingdom 71:225-244.

   Warwick, R.M., H.M. Platt, K.R. Clarke,
   J. Agard, and J. Gobin.  1990. Analysis
   of macroinvertebrate and macrobenthic
   community structures in relation to
   pollution and disturbance in Hamilton
   Harbor,  Bermuda. Journal of
   Experimental Marine Biology and Ecology
   138:119-142.

   Washington, H.G. 1984. Diversity, biotic
   and similarity indices, a review with
   special relevance to aquatic ecosystems.
   Water Research 18:  653-694.

   Watson, P.G. and T.E. Prickers.  1990. A
   multilevel, in situ pore-water sampler
   for use in intertidal sediments and
   laboratory microcosms.  Limnology and
   Oceanography 35:1381-1389.
Weaver, G. 1984. PCB contamination in
and around New Bedford, MA.
Estuaries 18:22A-27A.

Weinstein, M.P., S.L. Weiss, and M.F.
Walters. 1980.  Multiple determinants of
community structure in shallow marsh
habitats, Cape Fear River Estuary, North
Carolina, USA. Marine Biology 48:227-
243.

Wiesberg, S.B., J.A. Ranasinghe, D.M.
Dauer, L.C. Schaffner, R.J. Diaz, and J.B.
Frithsen. 1997. An estuarine benthic
Index of Biotic Integrity (B-IBI)  for
Chesapeake Bay. Estuaries 20:149-158.

Weisberg, S.B., J.B. Frithsen, A.F.
Holland, J.F. Paul, K.J. Scott, J.K.
Summers, H.T. Wilson, R. Valente, D.G.
Heimbuch, J. Gerritsen, S.C. Schimmel,
and R.W. Latimer. 1993.  EMAP-
Estuaries Virginian Province 1990
Demonstration Project Report.
EPA/620/R-93/006. Environmental
Research Laboratory, USEPA,
Narragansett, RI.

Wilding, J.R. 1940. A new  square-foot
aquatic sampler. Limnological Society of
America Special Publication, No. 4:1-4.

Wonnacott, T.H. and R.J. Wonnacott.
1969. Introductory Statistics. 2nd edition.
John Wiley and Sons, Inc., New York,
NY.

Word, J. Q. 1980.  The infaunal trophic
index. The 1980 Annual Report,
Southern California Coastal Research
Project. Long Beach, CA. pp 19-39.

Word, J.Q. 1978. The infaunal trophic
index. 1978 Annual Report, Southern
California Coastal Water Research
Project, Annual Report. Pages 19-39.
L-20
                             Literature Cited

-------
   Word, J.Q., T.J. Kauwling, and A.J.
   Mearns. 1976. A comparative field study
   ofbenthic sampling devices used in
   Southern California benthic surveys.
   Southern California Coastal Water
   Research Project, 1500 East Imperial
   Highway, El Segundo, CA.

   Wright, J.F., D. Moss, P.D. Armitage,
   and M.T. Furse. 1984. A preliminary
   classification of running-water sites in
   Great Britain based on
   macroinvertebrate species and the
   prediction of community type using
   environmental data. Freshwater Biology
   14:221-256.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance              L-21

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