United States

Environmental Protection

Agency

EPA-822-B-00-024

December 2000

Office of Water

4304

Washington, D.C. 20460

	



	

	

		



	
	
	

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
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. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance iii

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/o USEPA ERL/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
iv Acknowledgements

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)
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance v

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.

vii Contents

Estuarine and Coastal Marine Waters:

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

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
ix Contents

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

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
xi Contents

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

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
xiii Contents

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 BIOASSESSMENT

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

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-1

Literature Cited ........................................................... . L-1
xv Contents

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

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
xvii Contents

LIST OF FIGURES (CONTINUED)

Figure

12-1 Effect of increasing sample size from n1 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xviii

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

13-10b Simpson’s dominance index for macroinvertebrates at Ocean City sites;

summer data, n=9 ................................................ 13-46

13-11a Shannon-Wiener diversity index for macroinvertebrates at Bethany 

Beach sites; summer data, n=9 ...................................... 13-47

13-11b 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
xix Contents

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

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

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 (Z" + Z2$)

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
xxiii Contents

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

LIST OF TABLES (CONTINUED)

Table 

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

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

13-19 Chesapeake Bay submerged aquatic vegetation habitat requirements

for a polyhaline environment (Dennison et al. 1993) .................... 13-68
xxv Acronym List

Acronym List

APHA American Public Health Association

AVS Acid Volatile Sulfides

BMP Best Management Practices

CCA Canonical Correspondence Analysis

CDF Cumulative Distribution Function

CSREES Cooperative State Research, Education, & Extension Service

CTD Conductivity - Temperature - Depth Meter

CV Coefficient of Variation

CWA Clean Water Act

DFA Discriminant Function Analysis

DGPS Differential Global Positioning System

DMRs Discharge Monitoring Reports

DNR Department of Natural Resources

DO Dissolved Oxygen

EMAP Environmental Monitoring & Assessment Program

EPA Environmental Protection Agency

ER-L Effects Range-Low

ER-M Effects Range-Median

FEI Farrell Epifaunal Index

FTE Full Time Equivalent

GIS Geographic Information System

GPS Global Positioning System

IBI Chesapeake Bay Estuarine Index of Biotic Integrity

ITI Infaunal Trophic Index
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xxvi

MDS Multidimensional Scaling

NMDS Non-metric Multidimensional Scaling

NMFS National Marine Fisheries Service

NOAA National Oceanic and Atmospheric Administration

NODC National Oceanographic Data Center

NPDES National Pollutant Discharge Elimination System

NS&T National Status & Trends

PAHs Polyaromatic Hydrocarbons

PCA Principle Components Analysis

PCBs Polychlorinated Biphenyls

PCE Power Cost Efficiency

PCS Permit Compliance System

POTW Publically Owned Treatment Works

QA Quality Assurance

QC Quality Control

RBP Rapid Bioassessment Protocol

RPD Redox Potential Discontinuity

SAV Submerged Aquatic Vegetation

SEM Simultaniously Extracted Metals

SOP Standard Operating Procedure

SPM Suspended Particulate Matter

SQG Sediment Quality Guidelines

SQT Sediment Quality Triad

STORET STOrage & RETrieval

TDN Total Dissolved Nitrogen

TDP Total Dissolved Phosphorus
xxvii Acronym List

TMDL Total Maximum Daily Loads

TOC Total Organic Carbon

TPC Total Particulate Carbon

TPN Total Particulate Nitrogen

TPP Total Particulate Phosphorus

TSS Total Suspended Solids

TVS Total Volatile Sulfides

TWINSPAN Two-Way INdicator SPecies ANalysis

UPMGA Unweighted Pair Group Mean Averages

USDA CSREES United States Department of Agriculture Cooperative State

Research Education Extension Service

USGS United States Geological Survey

xxix Executive Summary

Executive Summary

_________________

1 Biological criteria: Technical guidance for streams and small rivers. EPA 822-B96-001. U.S. Environmental Protection Agency, Office of Water, Washington, DC.

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 biogeographic region

(USEPA 1996a)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,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xxx

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
xxxi Executive Summary

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xxxii

Sequential progression of the biocriteria process. Adapted from 

Paulsen et al. 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 summ aries)

• 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 program s to preserve exceptional waters

• Implement managem ent 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 managem ent is accomplished
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-1

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.
1-2 Introduction - Bioassessment & Biocriteria

1.2 Legal Origins

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.

1.2.3 301(h) and 403(c) Programs

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 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-3

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.

W atershed

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.

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

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, 
1-4 Introduction - Bioassessment & Biocriteria

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, macroinvertebrates,

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)/

W aiver Program

C Allows marine discharges who meet

USEPA criteria to defer secondary

treatment if discharge does not

produce adverse effects on resident

biological comm unities.

C Providing threshold against

which to measure

detrimental effects on

biological comm unities.

Section

403(c)/Ocean

Discharge Program

C Requires marine dischargers to

provide an assessment of

discharge impact on biological

comm unity in discharge area as

well as surrounding comm unities.

C Providing threshold against

which to measure

discharger impacts on

biological comm unities.

Section 304(a)/

Criteria

Methodology

C Provides information on restoration

and maintenance of chemical,

physical, and biological integrity of

waters.

C Identifies conventional pollutants,

their concentrations and effects on

surrounding comm unities.

C Providing the benchmark for

measuring the effects of

pollutants on the biological

community.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-5

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
1-6 Introduction - Bioassessment & Biocriteria

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-7

Valued Ecosystem Components

Intertidal

Phytoplankton

Zooplankton

Soft Bottom Benthos

Hard Bottom Benthos

Kelp Beds

Commercial Shellfish

Pelagic Fish

Demersal Fish

Fish Eggs & LarvaeMarine MammalsMarine BirdsHuman Health

All

Sources of

Perturbation

Wetlands & Estuaries

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.

Oil Spills

All

Net effect of each source on all components

Net effect of each source on all components

KEY

Potential Importance Understanding

Controlling

Major

Moderate

Some

High

Moderate

Low

Table 1-2. Impacts on the marine environment of the Southern California Bight. Modified from

Bernstein et al. 1991.
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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.

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 (“box 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-9

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.
1-10 Introduction - Bioassessment & Biocriteria

Figure 1-2

Program 

Interdependence

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.

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

(USEPA 1990). 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-11

1.6 Characteristics of

Effective Biocriteria

Generally, effective biocriteria share

several common characteristics:

< Provide for scientifically sound, costeffective 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

(USEPA 1996a):

1. Planning the biocriteria

development program, including:

C definition of program objectives;

C establishment of interagency

cooperation;

C identifying acceptable levels of

uncertainty for decisions made

on the basis of biocriteria;

C 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 
1-12 Introduction - Bioassessment & Biocriteria

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 (USEPA 1990).”

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-13

Estuarine Class

Designation

Tier 0

Historical Data

Review

Tier 2

Sampling

Tier 1

Sampling

Tier 3

Sampling

Evaluation and

Calibration of Metrics

and other Indicators

Biocriteria

Relative to

Estuary Class

Aggregation

Assessment

of Sites

Figure 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.

Virginian and Gulf provinces (Paul

et al. 1999, Engle et al. 1999).

 Multivariate ordination 

approaches — Several approaches

have been developed using

multivariate 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.
1-14 Introduction - Bioassessment & Biocriteria

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-15

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 costeffective. 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 sitespecific 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
1-16 Introduction - Bioassessment & Biocriteria

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-17

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
1-18 Introduction - Bioassessment & Biocriteria

Tier 0

-No field observations

-Desktop screening

-Literature search

-Questionnaires to local experts

-Support planning for monitoring and more detailed

 assessments

Tier 1

-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

Tier 3

-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

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.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-19

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. 

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 2-1

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 (USEPA 1990).”

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
2-2 Biological Survey

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 inhouse 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; 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 2-3

< Fish are important in the linkage

between benthic and pelagic food

webs;

< They are long-lived and are

therefore good indicators of longterm 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 marshdwelling 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. 
2-4 Biological Survey

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:
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 2-5

< 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 0o to

40oC.

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. 
2-6 Biological Survey

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 2-7

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 shortterm 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 wellestablished and consistent way to

evaluate and compare many discrete

units as a continuum of performance or

condition. Also similar to student
2-8 Biological Survey

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 2-9

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"
2-10 Biological Survey

or highly sensitive organisms are less

likely to be found in both polluted and

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,

including pollution sensitive ones and

some that are pollution tolerant.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-1

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 physicalchemical 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
3-2 Habitat Characterization

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

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
3-4 Habitat Characterization

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. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-5

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

Kimball 1984).

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-gm-2 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
3-6 Habitat Characterization

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-:M, mean DIP <0.35-:M;

mean SPM (suspended particulate

matter) <20-mgL-1; mean chlorophyll a

(in water column) <15-: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 et al. 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 macroand 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

faunal 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-7

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-tovolume 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 McIvor

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 proproots 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
3-8 Habitat Characterization

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-9

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. 
3-10 Habitat Characterization

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). CTDmeasured salinity is also incorporated in

other estuarine monitoring programs;

for example, the Chesapeake Bay

(Holland et al. 1988, 1989), San Francisco

Bay (ABAG 1991), and Puget Sound

(PSWQA 1988, 1990, 1991). Monitoring

guidance for the National Estuary

Program (USEPA 1992) 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-11

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.
3-12 Habitat Characterization

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 particleadsorbed 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-13

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 colimiting 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 colimiting. Smith and Hitchcock (1994)

concluded that phosphorus (and silica)

potentially limits phytoplankton growth

in the Louisiana Bight during winterspring, 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
3-14 Habitat Characterization

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

 to . Dissolved nitrogen

species that could be incorporated into

chemical analyses of this nutrient

include total dissolved N (TDN), and

dissolved inorganic nitrogen (DIN =

 + + ) (LaPointe and

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 effortbased 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-15

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 infaunal 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-
3-16 Habitat Characterization

reduction potential discontinuity layer

provides information on aerobic vs.

anaerobic respiration in sediments. 

Sediment nutrients such as particulate

nitrogen and phosphorus can be remobilized 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 nonionic 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-17

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 noeffects 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
3-18 Habitat Characterization

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 (NRC 1989,

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, 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-19

Polyaromatic Hydrocarbons

(PAHs)

Acenaphthene

Anthracene

Benz(a)anthracene

Benzo(a)pyrene

Benzo(e)pyrene

Biphenyl

Chrysene

Dibenz(amh)anthracene

2,6-dimenhyulnaphthalene

Fluoranthene

Fluorene

2-methylnaphthalene

1-methylnaphthalene

1-methylphenanthrene

Naphthalene

Perylene

Phenanthrene

Pyrene

Benzo(b)fluoranthene

Acenaphthlyene

Benzo(k)fluoranthene

Benzo(g,h,i)perylene

Major 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

Hexachlorobenzene

Lindane (gamm a-BHC)

Mirex

18 PCB Congener

Congener Location

Number of CIs

8 2 4'

18 2 2' 5

28 2 4 4'

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'

105 2 3 3' 4 4'

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

195 2 2' 3 3' 4 4' 5 6

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 EMAPEstuaries

program. 

Refer also to

the NS&T

Program list of

chemicals

(O’Connor et

al. 1994).
3-20 Habitat Characterization

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 Tier 0

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-21

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
3-22 Habitat Characterization

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. siltclay, 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 groundtruthing. 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 Tier 3

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. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 3-23

Table 3-1. Habitat measurements for estuaries and coastal marine waters.

Habitat

Measurements

Assessment Tier Information Source Method(s) and

Equipment

0 1 2 3

Historical Information

Estuary area T T T T USGS quad maps Can be estimated from

maps or using GIS

Geomorphometric

classification

(classical coastal

plain estuary; salt

marsh estuary;

lagoon; fjord;

tectonically-caused

estuary)

T T T T USGS quad maps

Habitat type

(seagrass beds; hard

bottom; soft bottom;

water column;

emergent marsh;

mudflat; sandflat;

gravel/cobble; rocky)

T T T T NOAA bathymetry

charts; historic surveys

by federal, state

agencies and

universities

Watershed land use T T T T USGS land use maps;

state planning

agencies; local zoning

agencies

Can be estimated from

maps or using GIS

Population density T T T T US census data

NPDES discharges T T T T State water quality

agency

Vegetative cover T T T T Historic surveys by

federal, state agencies

and universities

Can be estimated from

maps or using GIS

Field-collected Information: Water Column Characteristics

Salinity, conductivity T* T T T Historic data from

federal, state agencies

and universities

Conductivity cells

(CTD meters)

DO T* T T T Historic data from

federal, state agencies

and universities

CTD meter equipped

with O2 probe,

recording DO meters

for Tier 3 may be

needed

Temperature T* T T T Historic data from

federal, state agencies

and universities

CTD meter, satellite

remote sensing.

pH T* T T T Historic data from

federal, state agencies

and universities.

CTD meter equipped

with pH probe
3-24 Habitat Characterization

Table 3-1 (Cont’d). Habitat measurements for estuaries and coastal marine waters.

Habitat

Measurements

Assessment Tier Information Source Method(s) and

Equipment 0123

Turbidity, Secchi

depth

7* 777 Historic data from

federal, state agencies

and universities

Secchi disk;

transmissometer,

nephelometer,

turbidimeter if desired

Nutrients (nitrogen

species,

phosphorus)

7* 7 7 Historic data from

federal, state agencies

and universities

Spectrophotometry

Organics, metals 7* 7 Historic data from

federal, state agencies

and universities

Standard methods for

selected suite of

contaminants

Field-collected Information: Bottom Characteristics

Depth 7* 777 Historic data from

federal, state agencies

and universities

Meter wheel,

fathometer,

hydrostatic pressure

sensor

Sediment grain size 7* 777 Historic data from

federal, state agencies

and universities

Sieving or separatory

column combined with

pipette analysis for

silt-clay fraction

Total volatile solids 7* 777 Historic data from

federal, state agencies

and universities

Standard methods 

Total organic carbon 7* 7 7 Historic data from

federal, state agencies

and universities

Standard methods

Acid volatile sulfides 7* 7 Historic data from

federal, state agencies

and universities

Standard methods

Sediment reductionoxidation potential

7* 777 Historic data from

federal, state agencies

and universities

Visual determination

of the depth of change

in sediment color in

core

Sediment

contamination

7* 7 Historic data from

federal, state agencies

and universities

Standard methods for

contaminants selected

* Historic data should be included in Tier 0; the tier does not include any field collection of

new data.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-1

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
4-2 Physical Classification and the Biological Reference Condition

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 humaninduced), 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 infaunal 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-3

0 1 2 3 4

0

1

2

3

4

Infaunal Index

"Biological Potential" Site a

Fish Index

Site b

2.0 - 2.7

1.7 - 3.3

Figure 4-1

Graphical

representation of

bioassessment. 

Assessment sites

a and b 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 welldocumented 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
4-4 Physical Classification and the Biological Reference Condition

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

-2

-1

0

1

2

Class I

Class II

Infaunal Index

Fish Index

Site a

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.

ensure that the final classification is 

meaningful and the reference conditions

are properly characterized. The

remaining sections of this chapter cover

physical classification, elements of

reference condition characterization, and

use of reference sites. The reference site

database should be periodically

reviewed as data accumulate to ensure

consistency of the reference

characterization and classification

scheme.

4.2 Physical Classification

This protocol is not intended to develop

a classification scheme applicable to the

entire United States. Classification

within the broad estuarine categories

described in Section 3.1 must be

regional, and regional expertise must be

used to determine those classification

variables which are useful in each

region.

A useful classification scheme is

hierarchical, beginning at the highest

(regional) level and stratifying only as

far down as necessary (Conquest et al.

1994). The procedure is to classify

estuaries and coastal marine waters by

geographic regions and then to increase

the stratification in the classification

hierarchy to a reasonable point for each

given region. Although several possible

classification levels are outlined below,

in practice, one to three relevant levels

would be entirely sufficient. 

Classification should avoid a

proliferation of classes that do not

contribute to assessment. The proposed

hierarchical scheme below applies to

both estuarine and coastal marine

waters.

4.2.1 Geographic Region

The geographic region, be it ecoregion,

physiographic province or other

delineation, determines landscape-level

features for classification such as:

climate, topography, regional geology

and soils, biogeography, and broad land

use patterns. Ecoregions are based on

geology, soils, geomorphology,

dominant land uses, and natural

vegetation (Hughes and Larsen 1988,

Omernik 1987) and have been shown to

account for the variability of water

quality and aquatic biota in several

freshwater areas of the United States. 

Seventy-six ecoregions were originally
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-5

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. 
4-6 Physical Classification and the Biological Reference Condition

Columbian

Californian

Acadian

Virginian

Carolinian

West Indian

Louisianian

Insular

Arctic

Bering

Aleutian Alaskan

Figure 4-3

Biogeographical

provinces adapted

from Holland

(1990). A form of

preliminary

regionalization

used by EMAPEstuaries.

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;
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-7

< 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 subdividing 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. 
4-8 Physical Classification and the Biological Reference Condition

Oligohaline

Marine

Mesohaline

Wet Season/High Flow

Key

coastal land area

transitional

sand

single comprehensive 

survey site

mud

Polyhaline

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.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-9

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

USEPA 1998b).

Historical Data Present-Day

Biology Predictive Models Expert Consensus

Strengths

Yields actual

historical

information on

status.

Inexpensive to

obtain.

Yields obtainable, 

best present status.

Any assemblages or

communities

deemed important

can be used.

When sufficient

data are not

available.

Work well for water

quality.

Relatively inexpensive.

Can be better applied

to biological

assemblages than

models.

Common sense and

experience can be

incorporated.

Weaknesses

Data might be

limited.

Studies likely

were designed

for different

purposes; data

might be

inappropriate.

Human impacts

present in

historical times

were

sometimes

severe.

Even best sites

subject to human

impacts.

Degraded sites might

lower subsequent

biocriteria.

Community and

ecosystem models

not always reliable.

Extrapolation

beyond known data

and relationships is

risky.

Can be expensive.

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
4-10 Physical Classification and the Biological Reference Condition

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-11

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
4-12 Physical Classification and the Biological Reference Condition

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-13

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 polyhalinesandy 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 EMAPEstuaries (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
4-14 Physical Classification and the Biological Reference Condition

Oligohaline

Polyhaline

Marine NPS loading

area too 

developed for a 

reference transect

A

tributary

survey

site Mesohaline

Wet Season/High Flow

Key

coastal land area

transitional

sand

urban areas

single comprehensive 

survey site

survey site transect 

across depth profile

mud

agricultural areas

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.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-15

Oligohaline

NPS loading

tributary

survey

site

A

Dry Season/Low Flow

area too 

developed for a 

reference transect

Marine

Mesohaline

Polyhaline

Key

coastal land area

transitional

sand

urban areas

single comprehensive 

survey site

survey site transect 

across depth profile

mud

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 ERM 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 EMAPidentified 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

USEPA national trend monitoring for

estuaries.
4-16 Physical Classification and the Biological Reference Condition

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-17

0HWULF 9DOXH

&XPXODWLYH )UHTXHQF\ SHUFHQW

0LQLPXP 0D[LPXP























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 upstream-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 
4-18 Physical Classification and the Biological Reference Condition

Oligohaline

Marine

Mesohaline

Dry Season/Low Flow

Key

coastal land area

transitional

sand

single comprehensive 

survey site

mud

Polyhaline

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.

may be subject to other stressors that

have not been considered. 

The second problem with the sitespecific 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 4-19

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: Nearshore 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). 
4-20 Physical Classification and the Biological Reference Condition

Impact 

Zone

"Up" channe l

s tations

"Down" channe l

s tations

H a rbor N e t

C u rre n t

D irection

Key

Test sites

R e ference sites

Figure 4-9

Estuarine and

coastal marine

survey method for

navigation channel

assessment. 

discharge

A

B

C

D

E

F

G

D 1

D 2

D 3

D 4

D 5

net longshore current

Figure 4-10

Estuarine and

coastal marine

biocriteria survey

method useful for

marine site

selection. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-1

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) (USEPA 1992) 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
5-2 Sampling Program Issues

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 "offthe-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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-3

Table 5-1. Potential benthic macroinvertebrate metrics.

Metric Response to Impairment

No. of taxa reduced

Mean no. of individuals per taxon substantially lower or higher

% contribution of dominant taxon elevated

Shannon-W iener diversity reduced

Total biomass substantially lower or higher

% biomass of opportunistic species elevated 

% abundance of opportunistic species elevated

Equilibrium species biomass reduced

Equilibrium species abundance reduced

% taxa below 5-cm reduced

% biomass below 5-cm reduced

% carnivores and omnivores elevated

No. of amphipod species reduced

% individuals as amphipods reduced

% individuals as polychaetes/oligochaetes elevated

No. of bivalve species reduced

% individuals as molluscs reduced

% individuals as deposit feeders elevated

Mean size of organism in habitat reduced

Proportion of expected no. of species in sample reduced

Proportion of expected no. of species at site reduced

Mean weight per individual polychaete reduced

No. of suspension feeders reduced

% individuals as suspension feeders reduced

No. of gastropod species reduced

No. of Capitellid polychaete species 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, 
5-4 Sampling Program Issues

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

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

Abundance

Measures

Total benthic abundance per event # Mean benthic abundance per sample # Total benthic

biomass per event # Mean benthic biomass per sample

Individual Health Biomass/abundance ratio # Mean weight per individual polychaete # Mean weight per

individual mollusc

Functional

Groups

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

Taxonomic

Composition

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

Shannon-Wiener Diversity Index # Pielou’s Evenness Index # Mean number of species #

Mean number of polychaete species

Abundance

Measures

Mean benthic abundance per site

Individual Health n.a.

Taxonomic

Composition

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-5

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

Habitat Preferred: soft sediments (mud-sand).

Sampling

Gear

Regionally most appropriate for substrate (Table 5-4).

Index

Period

Regionally most appropriate

Preferred:

Summer - East & Gulf Coast

Spring - Pacific Northwest

Alternative:

All four seasons, or winter and summer

Sampling 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.

Analysis 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 
5-6 Sampling Program Issues

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-7

Table 5-4. Summary of bottom sampling equipment (Adapted from USEPA 1992, Klemm et al.

1992, and ASTM 1998b).

.

DEVICE USE ADVANTAGES DISADVANTAGES KB Corer

Soft sediments

only.

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.

Samples limited surface area. 

Requires boat and winch.

 Ballcheck Single and 

 Multiple Tube

Soft sediment

only.

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.

Heavy; requires boat and winch. 

Does not retain sand unless

bronze core retainers are used.

 Fluorocarbon plastic  or Glass Tube

Shallow wadeable

waters or deep

waters if SCUBA

available. Soft or

semi-consolidated

deposits

Preserves layering and permits

historical study of sediment

deposition. Rapid-samples

immediately ready for laboratory

shipment. Minimal risk of

contamination.

Small sample size requires

repetitive sampling. Impractical

in water > 1-m depth if SCUBA

not available.

 Hand Corer with 

 removable Fluorocarbon 

 plastic or glass liners.

Same as above

except more

consolidated

sediments can be

obtained.

Handles provide for greater ease of

substrate penetration. Above

advantages.

Careful handling necessary to

prevent spillage. Requires

removal of liners before

repetitive sampling. Slight risk

of metal contamination from

barrel and core cutter.

 Box

 Corer

Same as above. Collection of large undisturbed

sample allowing for subsampling.

Hard to handle.

 Phleger (Gravity) Corer

Semi-consolidated

sediments.

Low risk of sample contamination. 

Maintains sediment integrity relatively

well.

Careful handling necessary to

avoid sediment spillage. Small

sample, requires repetitive

operation and removal of liners. 

Time consuming.

 Young Grab 

Lakes, estuarine

and marine areas.

Eliminates metal contamination if

grab is plastic or kynar lined. 

Reduced pressure wave. Can

subsample. Better penetration in

sand than the modified Van Veen.

Expensive, heavy, requires boat

and winch.

 Ekman or Box  Dredge

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.

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.

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.
5-8 Sampling Program Issues

Table 5-4 (Cont’d). Summary of bottom sampling equipment (Adapted from USEPA 1992,

Klemm et al. 1992, and ASTM 1998b).

DEVICE USE ADVANTAGES DISADVANTAGES Ponar Grab Sampler

Useful on sand,

silt, or clay.

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.

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.

 BMH-53 Piston  Cover

Waters of 1-2-m

deep when used

with extension rod. 

Soft to semiconsolidated

deposits.

Piston provides for greater sample

retention.

Cores must be extruded on site

to other containers - metal

barrels introduce risk of metal

contamination.

Modified Van Veen

Useful on sand,

silt, or clay. 

Adequate on most substrates. Large

sample obtained intact.

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.

BMH-60

Sampling moving

waters from a fixed

platform.

Streamlined configuration allows

sampling where other devices could

not achieve proper orientation.

Possible contamination from

metal construction. 

Subsampling difficult. Not

effective for sampling fine

sediments.

 Smith-McIntyre

 Grab

Useful on most

substrates.

Reduced pressure wave. Designed

for sampling hard substrates. Can

subsample and make vertical crosssections. 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.

Loss of fines. Heavy; requires

boat and winch. Possible metal

contamination unless grab is

lined.

 Scoops, Drag  Buckets

Useful on most

substrates. 

Various

environments

depending on

depth and

substrate.

Inexpensive, easy to handle. 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 EMAPEstuaries 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-9

Acceptable if Minimum

Penetration Requirement Met

and Overlying Water is Present

Unacceptable (Canted with

Partial Sample)

Unacceptable

(Washed)

Unacceptable

(Washed, Rock Caught in Jaws)

Figure 5-1

Cross-section of

sediment in

clamshell bucket

illustrating

acceptable and

unacceptable

grabs.

Program selected a Young grab

(sometimes referred to as a Youngmodified 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
5-10 Sampling Program Issues

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 macroinvertebrates in estuaries. Because of its weight

a winch is necessary for retrieving the

sample from a stationary boat.

The Ekman grab sampler is a boxshaped device with two scoop-like jaws

that must penetrate the intended

substrate without disturbing the watersediment 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-McIntyre Grab:

The Smith-McIntyre 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-McIntyre 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-McIntyre 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-11

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-McIntyre.

Young Grab:

The Young grab sampler is similar in

operation to the Van Veen and the

Smith-McIntyre, but the sample can be

accessed undisturbed from the top of the

grab through hinged doors like a SmithMcIntyre. 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-McIntyre. 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-McIntyre 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 SmithMcIntyre designs are effective off-shore

grabs for the biocriteria development

purposes of this guidance, the SmithMcIntyre 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 crosssectioned and examined intact, although

this is easier with the Smith-McIntyre

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-
5-12 Sampling Program Issues

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-13

retention of total macrofaunal organisms

by 130 to 180%; however, costs for

processing the samples may increase as

much as 200% (USEPA 1986-1991).

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 infauna 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
5-14 Sampling Program Issues

Table 5-5. Mesh sizes used in estuary benthic monitoring programs.

Monitoring Program Mesh Size (mm) Reference

Chesapeake Bay 0.5 Dauer 1993, Holland et al.

1987, 1988, 1989, 

Ranasinghe et al. 1992

Tar/Pamlico 0.5 Eaton 1992a-d

EMAP-Near Coastal 0.5 USEPA 1992, W eisberg et

al. 1993, Holland 1990

Naples Bay, Florida 0.595 Simpson et al. 1979

Puget Sound Ambient

Monitoring Program

1.0 PSW QA 1988, 1990, 1991

Puget Sound Estuary

Program

1.0 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-15

Table 5-6. Sampling summary for fish. 

Habitat Sublittoral.

Sampling Gear Seines and any gear that effectively captures bottom-feeding and pelagic

fish, usually otter trawls.

Index Period Any season can be selected depending upon migration and recruitment

patterns in the region. Seasonal sampling might be needed to assess

particular problems.

Sampling Bottom-feeding and pelagic fish. Sufficient sets of gear to obtain

representative species counts (usually 4 or more).

Analysis Collected species are weighed, measured, and examined for external

abnormalities (lesions, growths, deformities). Histopathology may be

performed.

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
5-16 Sampling Program Issues

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 phytoplanktondominated 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-17

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 5-9. Sampling summary for phytoplankton.

Habitat Each sampling site preferred.

Sampling Gear Fluorometer attached to CTD (USEPA 1994e) for in situ measurements;

or spectrophotometrically on water samples collected with a water

sampler.

Index Period Tiers 1 and 2: June - September

Tiers 2 (optional) and 3: growing season average; 6-10 samples; March -

October (longer in subtropical regions).

Sampling Preferred: single sample, 0.5-m depth. 

Alternate: at same depths as nutrient samples.

Analysis Tier 1: Chlorophyll a mg/L (Tiers 1-3). Tier 2: ID dominant taxa. Tier 3: 

full comm unity species characterization.

Table 5-8. Sampling summary for aquatic macrophytes.

Habitat Euphotic zone.

Sampling Gear Aerial photography; quadrats

Index Period During growing season

Sampling Tier 1: Estimate of area covered by macrophytes.

Tiers 2-3: Quadrat samples for biomass collected by diver; 3-5 randomly

placed transects perpendicular to shore; samples are taken at 0.5-m

depth intervals from edge of emergent zone to the sublittoral.

Analysis Tier 1: Dominant taxa identified, % cover estimated from aerial

photography.

Tiers 2-3: All species identified, relative abundance of each estimated

from wet weight.
5-18 Sampling Program Issues

< 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-:m

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 midsummer 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-19

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;
5-20 Sampling Program Issues

Table 5-10. Sampling summary for epibenthos.

Habitat Soft sediments (sleds and trawls); shallow, vegetated (dip net)

Sampling Gear Renfro Beam Trawl (Farrell 1993a,b), sm all otter trawl; epibenthic sled; dip

net

Index Period Preferred: mid-summ er

Alternative: growing season, average of 10 samples.

Sampling Ca. 4-m tow length in estuaries; 0.1 - 0.5 nm tow lengths (DGPS) in

coastal waters and Puget Sound.

Analysis Taxonomic ID preferably to species.

< 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

cost-effectiveness;

< 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.

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;

< 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.

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,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-21

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 (Dixit et 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 
5-22 Sampling Program Issues

Table 5-11. Potential paleoecological indicators

Indicator Response to Impairment Reference

Taxa richness (diatom,

foraminifera,

dinoflagellate cysts )

reduced Cooper and Brush 1991

Biogenic silica increase with nutrient

enrichment

Turner and Rabalais 1994

Total organic carbon,

Total N, Total S

increase with enrichment Turner and Rabalais 1994

Ammonia/Elphidium

ratio (foraminifera)

increase with hypoxia Sen Gupta et al. 1996

Centric/pennate ratio

(diatoms)

increase with nutrient

enrichment

Cooper and Brush 1991

% Cyclotella increase with nutrient

enrichment

Cooper and Brush 1991

sedimentation rate increase with watershed

erosion

Brush 1989

Dinoflagellate cysts increase with cultural

eutrophication

Dale et al. 1999

% Fursenkoina increases with hypoxia Alve 1991

% Trochammina increases with hypoxia Patterson 1990

Table 5-12. Sampling summary for paleoenvironmental systems

Habitat Stable depositional zone, biogeochemical conditions for preservation

Sampling gear Bottom corer

Index period None

Sampling Tiers 1-2: none

Tier 3: background information specific to the estuary being sampled will

determine the number of cores necessary.

Analysis Cores sectioned at regular intervals depending on deposition rate and

resolution desired.

Diatoms

Foraminifera

Dinoflagellate

Cysts

Species composition and enumeration of at least 300 organisms in each

section. Digestion/clarification methods depend on assemblage.

Age of sections

up to 150 years

210Pb determination based on radioisotope assay with alpha

spectroscopy.

Older than 150

years

Palynological (pollen) analysis correlated with known historical changes

in terrestrial vegetation (land use), and 14C analysis (>1000 yr).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-23

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
5-24 Sampling Program Issues

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

of Puget Sound has 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 of N 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,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-25

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.
5-26 Sampling Program Issues

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 costeffective, 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-27

sampling program (e.g., Peterman

1990, Fairweather 1991). The power of

a test (1-β) 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 k

th

unit of the population from one or
5-28 Sampling Program Issues

Sampling Methods

Simple Random:

Systematic:

Stratified:

Multistage:

Samples are independently located

at random

Samples are located at regular

intervals

The study area is divided into

nonoverlapping strata and samples 

are obtained from each

Large primary units are selected

which are then subsampled

Figure 5-2

Description of

various sampling

methods. 

Adapted from

USEPA 1992.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-29

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") may be

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 withinseason 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.
5-30 Sampling Program Issues

In bioassessment strategies involving

infrequent sampling, the biologicallyoptimal 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 midwinter, 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 “powercost 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., " =

0.5, 1-$ = 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” (ci

), in time or

money, of each sampling scheme i

at each station. The cost can

include labor hours for sampling,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 5-31

sorting, taxonomic identification,

and recording results.

3. Conduct statistical power analysis

to determine the minimum

number of replicate samples (ni

)

needed to detect the ES with an

acceptable probability of Type I (")

and Type II ($) error (e.g., " = $ =

0.05).

4. Calculate the power-cost efficiency

(PCE) for each sampling scheme

by:

PCEi = (n x c)min/(ni x ci)

where (n x c)min = minimum value

of (n x c) among the i sampling

schemes. The reciprocal of PCEi is

the factor by which the optimal

sampling scheme is more efficient

than alternative scheme i. When

PCE is determined for multiple

metrics, the overall optimal

sampling protocol may be defined

as that which ranks highest in PCE

for most metrics in the test set.

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 6-1

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” 

(Tier 1)

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-

:m

< 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
6-2 Water Column & Bottom Characteristics

Table 6-1. Water Column & Bottom Characteristics. “Addition” refers to added detail or intensities

for a parameter initiated in an earlier tier.

Characteristic Tier Collection Method Indicates Salinity

1

2

3

-measure at each sampling station, CTD

meter

-continuous or 1-2-m intervals through

water column

-shallow/inshore

-top, middle, bottom thirds of depth

Distribution of flora and

fauna

Temperature

1

2

-measure at each station, CTD meter

-1-2-m intervals through water column

-shallow/inshore

-top, middle, bottom thirds of depth

Rate of chemical

reactions and biological

processes

3

addition

-some southern waters undergo significant

diel changes, it may be desirable to obtain

24-hour temperature profiles

Dissolved Oxygen

1 -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

Possible reason for

modified behavior,

reduced abundance &

productivity, adverse

reproductive effects,

and mortality

2

addition

-measure early in morning at each station

at minimum

3

addition

-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)

Resource agency may

determine need for

more detailed

information to diagnose

sources & causes of

impairment

pH

1

2

3

-CTD w/ pH probe

-1-2-m intervals

-top, middle, bottom thirds of depth

Chemical condition,

pollutant input, high

concentrations of

phytoplankton

 Secchi Depth  (Turbidity)

1

2

3

-deepest part of transect/grid

-if area classified by depth, measure at

each station

-See Section 6.2 for complete procedure

Reduction of light

penetration, deposition

of mud and silt,

possible contaminated

sediment “hot spots”

Depth

1

2

3

-each station w/ calibrated depth sounder

-read off meter block when sediment

sampling

-shallow/inshore waters: long stick or

weighted line calibrated in decimals

Depth at sampling

station, possible

dredging or sediment

loading

Nutrients

2

3

-collected w/ bottle samplers or pump

-see Section 6.8 for complete procedure

Nutrient loading

 Acid Volatile  Sulfides

3 -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)

Bottom characteristics,

detailed purposes in

Section 3.5.4

Water Column 

Contaminants

3 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)

Trace distribution of

contaminants from a

source or to ID

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

Table 6-1 (Cont’d). Water Column & Bottom Characteristics. “Addition” refers to added detail or

intensities for a parameter initiated in an earlier tier.

Characteristic Tier Collection Method Indicates Sediment Grain Size

1 -determine “percent fines” at each station,

see Section 6.4.1 for complete procedure

Spatial and temporal

changes of the benthic

habitat, evaluate

condition of benthic

habitats

2 -see Section 6.4.2 for complete procedure Determine extent or

recovery from

environmental

perturbations

3 Assist in providing early

warnings of potential

impacts to the

estuarine ecosystem

Total Organic Carbon

2 -see Section 6.9 for complete procedure Provide information

regarding sediment

organic content

(possibly influenced by

sewage outfalls)

3

addition

-measure additional sediment analytes Examine potential

influences of outfalls,

ID potential

contaminant “hot spots”

RPD Layer Depth

1 -vertical bisection, distance from sediment

surface to a noticeable change in color

from brownish (oxidizing conditions) to

gray (reducing conditions)

Note presence/absence

of benthos; learn about

life history, taxa

abundance, & major

taxa biomass

distribution; more large,

deep dwelling

species=”healthy”

system

 Total Volatile  Sulfides

1 -deepest section along transect/grid

-see Standard Methods (APHA 1992) for

sampling & analytical methods

Sediment and carbon

content

Sediment Contaminants

1 -conducted at outset of survey 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

2 *like TOC, if toxicity tests are initially

negative, no need to repeat annually

unless biological data from infauna

indicate otherwise

3 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
6-4 Water Column & Bottom Characteristics

< 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. Clean away

any sediment that might adhere to the

outside of the beaker. Carefully wash

this sediment through a 63-:m 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 finegrained 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 6-5

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 mesoand 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).
6-6 Water Column & Bottom Characteristics

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 Frickers 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 6-7

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
6-8 Water Column & Bottom Characteristics

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 EMAPEstuaries 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).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 6-9

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).

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 7-1

Chapter 7

Tier 0: Desktop Screening

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

Component Information Source Use

Estuary area USGS quad maps, GIS

-support planning

for monitoring

and more

detailed

assessments

-incorporates

time & cost

efficiencies

-allows evaluation

of a large number

of sites

Geomorphic

classification 

USGS quad maps, GIS

Habitat type NOAA bathymetry charts; historic surveys by federal,

state agencies, and universities

Biological

assemblages

Historic data from federal, state agencies, and

universities. NMFS for marine mammal data

Watershed

land use

USGS land use maps; state and county planning

agencies; local zoning agencies; USDA CSREES

Population

density

US census data

NPDES

discharges

State water quality agency and regional USEPA offices, 

PCS database

Water column

& bottom

characteristics

Historic data from federal, state agencies, and

universities; STORET, NODC databases

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;
7-2 Tier 0: Desktop Screening

< 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. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 7-3

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. 

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 8-1

Chapter 8

Tier 1

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
8-2 Tier 1

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

*3 replicate grabs

*x-section of Smith-McIntyre or

Young grab

*measure RPD depth

*brief description of classes &

families of benthos present in grab

*record faunal presence/absence

of benthos above and below the

RPD depth in sediment x- section

DO stress, toxicity,

low productivity,

nutrient

enrichment, habitat

impairment

-Identification of

nutrient state

based on

chlorophyll a

concentration &

identification of

point and nonpoint

probable causes (if

stations are

carefully selected

& spaced)

-Detection of

emergent wetland

& shorezone fish

habitat loss from

shorezone survey

and macrophyte

assessment

-Detection of loss

of submerged

aquatic

macrophytes

Fish

*3 trawls

*3 seines

*species counts

*measure standard lengths

*record external abnormalities

DO stress, toxicity,

habitat impairment

Macrophytes

*aerial photos (if possible - or

estimate from shorezone survey

*% cover estimate

*record dominant taxa

Nutrient

enrichment,

sediment loading

Phytoplankton

*chlorophyll a

*record blooms

*identify dominant species

Nutrient

enrichment

Water Column Characteristics

*salinity/conductivity

*temperature

*DO

*pH

*Secchi depth

*depth

*TSS for seagrass

DO stresses,

eutrophication,

stratification,

turbidity

-Detection of

potential

impairment of

benthic

macroinvertebrate

& fish

assemblages

Bottom Characteristics

*grain size estimate & description

*RPD layer depth

*TVS

*sediment toxicity

Habitat

modification, DO

stress, sediment

toxicants

-Detection of

oxygen stress

samples at each sampling site, taking a

vertical cross-section of the sample, and

measuring the RPD layer depth to

record the presence/absence of benthos 

above and below the RPD depth in the

sediment cross-section. In addition to

the actual presence of organisms,

evidence of their presence, such as

bivalve siphons, siphon impressions in

clay/mud, or polychaete burrows,

should also be noted. The investigator

may also wish to sort and identify the

organisms found above and below the

RPD depth for additional information

relative to Tier 2. The method presented

here is a simplification of the Benthic

Assessment Method developed by Diaz

and Nelson (1993). Functional attributes

of the benthic infaunal community that

can be evaluated using these procedures

include:
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 8-3

< 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-McIntyre 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 infauna 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

infauna) 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
8-4 Tier 1

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 preexisting 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 fieldidentified from vegetation samples

collected in shallow waters. Detailed
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 8-5

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.

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 9-1

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

infauna 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.
9-2 Tier 2

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

*3 replicate grabs (or as

determined by testing; see

Section 5.2.6

*identify major taxa and indicator

spp. of each grab to genus and

species

-Establishment of biocriteria

“benchmarks” for decisionmaking 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 impairment

-Measurement of extent of

macrophyte coverage

-Identification of

phytoplankton taxa

responsible for blooms

Fish

*3 or more replicates

*biomass by species

Macrophytes

*area

*maximum depth

*identify taxa and measure wet

weight of 2-3 samples per

transect

Habitat

impairment

Phytoplankton

*identify dominant species,

including “nuisance” taxa, on a

seasonal basis

Epibenthos 

(developmental)

*mid-summer or growing season

average at genus and species

level

*calculate sensitivity metric

Water Column Characteristics

*nutrients: NH4, NO3,NO2,

Kjeldahl N, total and reactive P

Bottom Characteristics

*grain size measurements

*TOC

Organic

enrichment

9.1.1 Sampling Procedure

Primary objectives of Tier 2 benthic

infaunal sampling are to evaluate

potential impairment to this assemblage

and to generate the data necessary to

develop biocriteria. This Tier, unlike

Tier 1, incorporates multiple sampling

visits to allow a basic discrimination of

seasonal differences in the benthic

infaunal macroinvertebrate assemblage. 

The recommended sediment sampling

procedure involves collecting three

replicate grab samples at each station

using a Smith-McIntyre or Young grab. 

Sampling gear should be selected to

maximize compatibility with historic

data. 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 9-3

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
9-4 Tier 2

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 9-5

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 ashfree dry weight of algae, algae biomass

can be estimated by multiplying the

chlorophyll a content by a factor of 67

(APHA 1992). 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 Dframe 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.

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 10-1

Chapter 10

Tier 3

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 
10-2 Tier 3

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

Benthic

Infauna

*determine biomass

*calculate multiple

metrics

-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

Fish

*5 or more replicates

*histopathology on

representative

subsample of catch

Fishing

pressure,

disease

Macrophytes

*stem counts

*biomass

*record pathology

Toxicity, habitat

impairment,

disease

Phytoplankton

*full community

characterization to

species

Paleoenvironmental 

Systems (developmental)

*2 or 3 cores from

basin (one-time

sample)

Past conditions

Epibenthos(developmental)

See Tier 2

Zooplankton(developmental)

*identify to species Water quality

impairment, DO

stress

Water Column Characteristics

*pesticides, herbicides

*metals

pesticides/

herbicides,

metals

Bottom Characteristics

*AVS

*sediment

contaminants

(organics, metals)
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 10-3

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 biomassbased 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, Guillen 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
10-4 Tier 3

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 10-5

10.6.1 Sampling Procedure

Three replicate vertical tows using a

118-:m 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 presentday 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 KB, 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
10-6 Tier 3

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)

and EMAP (USEPA 1994e). 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 HCl,

followed by warm HF (adapted from

Barss and Williams 1973). They are

processed on a 10 :m 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-1

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,
11-2 Index Development

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 welldeveloped 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 selfevident, it may be necessary to develop

an alternative classification from the

data using one or more of several
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-3

1. WaterbodyClassification —The 

physical and habitat data along with 

biological data are used to group 

reference sites into homogeneous 

classes

2. Metric Identification —Those 

metrics or attributes that are 

ecologically relevant to assemblage 

and zoogeography are identified

3. Metric Calibration — Core metrics 

are sensitive to pollution and are 

informative of the ecological 

relationships of the assemblage to 

specific stressors or cumulative 

impacts

4. Index Development — Core 

metrics, whose values vary in scale, 

are transformed to dimensionless 

numbers for aggregation

Class 1 Class 2 Class N

Evaluation and Calibration

Core Metric Core Metric Core Metric

Partitioning of Entire Water Resource

Metric 1 Value Metric 2 Value Metric N Value

Identification of Biological Attributes

Aggregation

Index

Score

Biocriteria

Relative to

Waterbody

Class

Index Score

5. Threshold Establishment —The 

threshold (biocriterion) for 

discriminating between impaired and 

unimpaired is determined to provide 

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 nearcoastal 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, 
11-4 Index Development

Figure 11-2

Mean number

of species and

salinity at

EMAPEstuaries

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

salinityadjusted

species

richness

measures. 

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 ‰) had

the highest mean Shannon-Wiener

diversities, at 4.0 and 3.55, respectively

(Weisberg et al. 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-5

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 (Llansó 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 (Llansó 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 siltclay, and total organic carbon content of

sediments. Many of the correlations

were statistically significant at p < 0.05,

however, only salinity accounted for

20% or more of the variation (Summers

et al. 1993).

Southern California Bight

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
11-6 Index Development

(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 may be 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-7

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
11-8 Index Development

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 metrics.

Richness Composition Tolerance Trophic/Habitat

Macrophytes

< Not applicable < Not applicable < TSS

< light

attenuation

< Chlorophyll a

< DIN

< DIP

< % cover

< density of new

shoots

< biomass

< stem counts

Benthic Macroinvertebrates

< dominant taxa

< taxa richness

< Shannon-Wiener

Diversity Index

< mean # of

species

< Pielou’s

Evenness Index

< # amphipods per

event

< amphipod biomass

< mean abundance of

bivalves/site

< # of gastropods per

event

< %

polychaetes

< polychaete

biomass

< % or biomass

epibenthic

< % or biomass

deposit feeders

< % or biomass

suspension

feeders

Fish

< dominant taxa

< taxa richness

< # of estuarine

spawners

< # anadronomous

spawners

< total fish

exclusive of

Atlantic

menhaden

< total # of species

< # species in bottom

trawl

< # species comprising

90% of individuals

< #, % or

biomass of

menhaden

< 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-9

Min-Max

25%-75%

Median value

Metric Value

2

6

10

14

18

22

26

30

Reference Stressed

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
11-10 Index Development

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 et al. 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 nonreference 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-11

Scoring Methods

All

Sites

Trisection Quadrisection Percentage 

of standard

5

3

1

100

3

2

1

4

95th percentile

maximum

 0

observed value

95th value X 100 ( )

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 sitespecific 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.
11-12 Index Development

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 et al. 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. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-13

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

Community

Structure/Function

Metric

Species composition 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 of fish community

Number of species needed to make up 90% of collection

Trophic composition

(for adults of species)

Proportion of individuals as generalized benthic feeders

Proportion of individuals as generalized plankton grazers

Proportion of individuals as top carnivores

Fish abundance and

condition

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 0-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 
11-14 Index Development

Table 11-3. Maryland estuarine fish IBI metrics.

Community

Structure/Function

Metric Response

to

Impairment

Species composition Total number of species

Number of species in bottom trawl

Number of species comprising 90 percent of

individuals

reduced

reduced

reduced

Trophic composition

(for adults of species)

Proportion of planktivores

Proportion of benthic feeders

Proportion of piscivores

increased

decreased

decreased

Fish abundance and

condition

Number of estuarine spawners

Number of anadromous spawners

Total fish exclusive of Atlantic menhaden

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 stepwise 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-15

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:

I

a p

a

s

si

f

i

i

n

i

n

si

f

 

 

¦

¦

1

1

Equation 11-1.

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 f is used to downweight

extreme abundances. If f 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 f) 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 pi

. 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 ERL 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
11-16 Index Development

100

p

p

p

p

p

p

r

r

r

r

r

rr

“contaminated” end

“reference” end

•

•

•

•

Ordination Axis 1

Ordination Axis 2

• x

50

0

Step 1: ordination

Step 2: gradient

Step 3: project site scores

100

p

p

p

p

p

p

r

r

r

r

r

rr

“contaminated” end

“reference” end

•

•

•

•

Ordination Axis 1

Ordination Axis 2

• x

50

0

Step 1: ordination

Step 2: gradient

Step 3: project site scores

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 (pi

) 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 pi

, 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 pi

 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 11-17

Site Scores

Abundance of Species A

0

100

0 100

•••

•

•

• •• • •• ••

•••• ••••

• • ••

••

•••

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•••

•

•

• •• • •• •• •

• ••

•

•

•

•

•••

•

•

•

•

•

•

•

••

••

•

•

•

• •

••

•

•

•

•

•

•

•

•

•

•

•

•

Site Scores

Abundance of Species A

0

100

0 100

•••

•

•

• •• • •• ••

•••• ••••

• • ••

••

•••

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•••

•

•

• •• • •• •• •

• ••

•

•

•

•

•••

•

•

•

•

•

•

•

••

••

•

•

•

• •

••

•

•

•

•

•

•

•

•

•

•

•

•

Site Scores

Abundance of Species A

0

100

0 100

•••

•

•

• •• • •• ••••

•

• •• • •• ••

•••• ••••

• • ••

••

•••

•

•

•

•

•

•

•

•

•••

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•

•••

•

•

• •• • •• ••••

•

• •• • •• •• •

• ••

•

•

•

•

•••

•

•

•

•

•

•

•

•

•••

•

•

•

•

•

•

•

••

••

•

•

•

• •

••

•

•

•

•

•

•

•

•

•

•

•

•

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

abundanceweighted 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.
11-18 Index Development
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-1

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
12-2 Quality Assurance: Design, Precision and Management

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-3

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 (Ho)

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 Ho

, traditionally being

statements of change, effect, or

difference. Upon rejecting Ho, 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 Ho

 is

rejected although Ho is really true. A

Type II error (i.e., false negative) occurs

when Ho is not rejected although Ho is

really false. The magnitude of a Type I

error is represented by " and the

magnitude of a Type II error is

represented by $. Decision errors are

the result of measurement and sampling

design errors that were described in

Section 12.1.1. A proper balance

between sampling and measurement

errors should be maintained because

accuracy limits effective sample size

and vice versa (Blalock 1979). 

Comparison of Significance Level 

and Power

Regardless of the statistical test chosen

for analyzing the data, the analyst must

select the significance level of the test. 

That is, the analyst must determine

what error level is acceptable. The

probability of making a Type I error is

equal to the significance level (") of the

test and is selected by the data analyst. 

In many cases, managers or analysts

define 1-" to be in the range of 0.90 to

0.99 (e.g., a confidence level of 90 to

99%), although there have been

environmental applications where 1-"

has been set to 0.80. Selecting a 95%

confidence level implies that the analyst

will reject the Ho

 when Ho

 is really true,

i.e., a false positive, 5% of the time.

Type II error depends on the

significance level, sample size, number

of replicates, variability, and which

alternative hypothesis is true. The

power of a test (1-$) is defined as the

probability of correctly rejecting Ho

when Ho

 is false. In general, for a fixed

sample size, " and $ vary inversely. 

Power can be increased ($ can be

reduced) by increasing the sample size

or number of replicates. Figure 12-1

illustrates this relationship. Suppose

the interest is in testing whether there is

a significant difference between the

means from two independent random

samples. As the difference in the two

sample means increases (as indicated on
12-4 Quality Assurance: Design, Precision and Management

n2

n1

a. Reference 

sample

critical value for n2

critical value for n1

n2

n1

probability of Type 

II error for n2

probability of Type II 

error (false negative) 

for n1

b. Test sample

rejection region, α 1 1 , for n

rejection region, α 2 2 , for n

{

{

n2

n1

a. Reference 

sample

critical value for n2

critical value for n1

n2

n1

probability of Type 

II error for n2

probability of Type II 

error (false negative) 

for n1

b. Test sample

rejection region, α 1 1 , for n

rejection region, α 2 2 , for n

{

{

Figure 12-1

Effect of

increasing sample

size from n1 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 n1 and n2

where n2 > n1.

Table 12-1. Errors in hypothesis testing.

Decision

State of the population (truth)

Ho is True Ho is False

Accept Ho 1-

(Confidence level)



(Type II error)

Reject Ho 

(Significance level)

(Type I error)

1-

(Power)

the x-axis), the probability of rejecting

Ho, the power, increases. If the real

difference between the two sample

means is zero, the probability of

rejecting Ho is equal to the significance

level, . Figure 12-1a shows the general

relationship between  and if  is

changed. Figure 12-1b shows the

relationship between  and if the

sample size is increased. The tradition

of 95% confidence ( = 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 firststep sampling results to estimate the

needed factors, for best design, of 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-5

Equation 12-1.

Equation 12-2.

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-). Recall that power is

equal to the probability of rejecting Ho

when Ho is false. Given this

information, the analyst substitutes

these values into the following equation

(Snedecor and Cochran 1980):

where Z and Z2 correspond to the

normal deviate. Common values of (Z

+ Z2)

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 no

using Equation 12-1; (2) round no up to

the next highest integer, f; and (3)

multiply no by (f+3)/(f+1) to derive the

final estimate of n. 

To compare the mean from two random

samples to detect a change of ; i.e.,

x

_

2-x

_

1, the following equation is used:

Common values of (Z + Z2)

2

 are

summarized in Table 12-2. To account
12-6 Quality Assurance: Design, Precision and Management

Equation 12-3.

Table 12-2. Common values of (Z + Z2)

2

 for estimating sample size for use with Equations 12-1

and 12-2 (Snedecor and Cochran 1980).

Power,

1-

 for One-sided Test  for Two-sided Test

0.01 0.05 0.10 0.01 0.05 0.10

0.80 10.04 6.18 4.51 11.68 7.85 6.18

0.85 11.31 7.19 5.37 13.05 8.98 7.19

0.90 13.02 8.56 6.57 14.88 10.51 8.56

0.95 15.77 10.82 8.56 17.81 12.99 10.82

0.99 21.65 15.77 13.02 24.03 18.37 15.77

 Equation 12-4.

x x xx x 1 ≤≤ ≤≤ ≤ ≤≤ r ps n ... ... ... ...

for s1 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 no using Equation 12-2; (2)

round no up to the next highest integer,

f; and (3) multiply no by (f+3)/(f+1) 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 ;

i.e., C-x

_

1, where C is the biocriteria limit:

In Equation 12-3, Z is most often onetailed, 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 (t/2,n-1) is used

to compute symmetric confidence

intervals for the population mean, :

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-7

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.

r np Z np p a

*

/

. =+ − ( ( )) 2

0 5 1

s np Z np p a

*

/

. =+ − ( ( )) 2

0 5 1

where Z/2 is selected from a normal

distribution table.

3. Round r

*

 and s

*

 up to the next

highest integers r and s. The 1-

lower and upper confidence limits

for xp are xr 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 communication (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 costeffective 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 
12-8 Quality Assurance: Design, Precision and Management

Example 1—Sample size calculation for comparing proportions

To detect a difference in proportions of 0.20 with a two-sided test, " equal

to 0.05, 1-$ equal to 0.90, and an estimate of p1 and p2 equal to 0.4 and 0.6,

no is computed from Equation 12-1 as 

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 detect the

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; " was selected as 0.05; and 1-$ was selected as 0.90. 

Substituting these values into Equation 12-2 yields 

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-9

< Precision - The level of agreement among repeated 

measurements of the 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.

< Com parability - 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 of the analytical methodologies employed; often a

function of the sensitivity of instrumentation.

Figure 12-3

Six qualitative and

quantitative data

characteristics

usually employed

to describe data

quality.

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.
12-10 Quality Assurance: Design, Precision and Management

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

Project Activity QC Element Evaluation Mechanism

Field Sampling Replicated samples at 10% of

sites by same field crew.

Calculate relative percent difference

(RPD) of index value or individual metric

score

Replicated samples at one to

two of total sites by different

field crew using same methods.

Calculate RPDs as above; use to

evaluate consistency and bias.

Physical Habitat

Assessment

(Qualitative)

Ensure appropriate training and

experience of operators;

multiple observers.

Resume or other documentation of

experience; discuss and resolve

differences in interpretation.

Physical Habitat

Assessment

(Quantitative)

Replicated measurements at

10% of sites.

Calculate RPDs between replicate

measurements; compare to

preestablished precision objectives.

Laboratory: 

Sample Sorting

Sample residue checked for

missed specimens to estimate

sorting efficiency; check

completed by separate lab staff.

Calculate percent recovery; compare to

preestablished goals.

Laboratory: 

Sample

Tracking

Logbook with record of all

sample information.

Not applicable. 

Laboratory: 

Taxonomic

Identification

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.

Calculate percent error; compare to

preestablished goals.

Data

Management

Proofreading; accuracy of

transcription.

All transcribed data entries compared by

hand to previous form—handwritten raw

data, previously computer-generated

tables, or data reports.

Data Analysis Hand-check of reduced data. For computer-assisted data reduction,

approximately 10% of reduced data

recalculated by hand from raw data to

ensure integrity of computer algorithm.

Appropriate statistics; training. Review by statistician or personnel with

statistical training.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-11

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 summeronly sampling (Alden et al. 1997).

Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-1

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 Puget Sound -

Development of TrawlBased Tools For the

Assessment of Demersal

Fauna

(Macroinvertebrates 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

infaunal 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 
13-2 Case Studies

Puget 

Sound

Galveston Bay

Tampa Bay

Indian River

North 

Carolina

Delaware Bay 

- Ocean City

Figure 13-1

General

location of the

case studies.

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 grainsize 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 midQuartermaster Harbor stratum to

compare the variability in results

between two stations of close proximity

with similar depth and sediment grainsize. 

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-3

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 noncontaminated 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 nonparametric 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

eelgrass). Sensitive (intolerant) species,

on the other hand, were defined as those

species whose relative abundance is 
13-4 Case Studies

QMH

1.1

QMH

1.2

QMH

1.3

QMH

1.4

QMH

1.5

TF

1.1

TF

1.2

TF

1.3

TF

1.4

TF

1.5

0.0

5.0

10.0

15.0

20.0

25.0

Abundance per 100 m2

Station and Replication

Bony Fish Abundance and Total Fish Abundance for Reference 

(QMH) and Contaminated (TF) Sites

Bony Fish (Osteichthyes)

Abundance

Bony plus Cartilaginous

Fish Abundance

OTTER TRAWL

REFERENCE CONTAMINATED

P=0.0003

P=0.0003

Figure 13-2a

Bony fish

abundance

and total fish

abundance for

reference and

contaminated

sites.

QMH

1.1

QMH

1.2

QMH

1.3

QMH

1.4

QMH

1.5

TF

1.1

TF

1.2

TF

1.3

TF

1.4

TF

1.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Biomass per 100 m2

Station and Replication

Bony Fish Biomass and Total Fish Biomass for Reference (QMH) 

and Contaminated (TF) Sites

Bony Fish (Osteichtheys)

Biomass

Bony plus Cartilaginous Fish

Biomass

OTTER TRAWL

REFERENCE CONTAMINATED

P=0.0001

P=0.0001

Figure 13-2b

Bony fish

biomass and

total fish

biomass for

reference and

contaminated

sites.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-5 Shiner Perch Snake Prickleback Adult Tomcod Speckled Sanddab English Sole Rock Sole Starry Flounder Sand Sole Pacific Herring Staghorn Sculpin

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Average Weight (KG)

Mean Individual Weights of Fish Species from Contaminated (TF) and 

Reference (QMH) Stations

Contaminated Stations (TF)

Reference Stations (QMH)

NS

NS

Figure 13-2c

Mean

individual

weights of fish

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
13-6 Case Studies

Table 13-1. A preliminary list of tolerant and sensitive fish and invertebrate species from the Tacoma

Waterways and Quartermaster Harbor.

FISH

Tolerant Species Sensitive Species

English sole Spiny dogfish

Sand sole Spotted ratfish

Flathead sole Longnose skate

Pacific tomcod Rock sole

Shiner surfperch Starry flounder

Snake prickleback Speckled sanddab

Pacific staghorn sculpin Pile surfperch

Striped surfperch

Bay goby

Blackbelly eelpout

Bay pipefish

Plainfin midshipman

INVERTEBRATE

Pandalus danae: coonstripe shrimp Cucumaria miniata: sea cucumber

Crangon spp.: sand shrimp Cucumaria piperata: spotted sea

cucumber

Cancer gracilis: purple cancer crab Pentamera populifera: crescent sea

cucumber

Cancer productus: red rock crab Parastichopus californica: edible sea

cucumber

Cancer magister: Dungeness crab Solaster stimpsoni: sunstar

Lophopanopeus bellus: crab Pagurus spp.: hermit crabs

Evasterias troschelli: mottled seastar Nassarius mendicus: snail

Metridium senile: plume anem one

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-7

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

Candidate Metrics Preliminary

Expectation

from Present

Study:

IMPAIRED SITE

Range of Values (and

mean) from Present

Pilot Study: IMPAIRED

SITE: Thea Foss Wty.

Range of Values (and

mean) from Present

Pilot Study:

REFERENCE SITE:

QM Hbr.

Total Fish Abundance per

100 m2

, 4-6 m. Depth.

(10-15 m.—no difference).

Elevated or no

difference

TF 1: 20.6 to 22.7 

mean = 21.4

QMH 1: 

 8.3 to 14.2 

 mean = 11.9

Total Fish Biomass per 100

m2

Reduced 0.54 to 0.97 kg (mean =

0.73)

0.81 to 4.82 kg (mean =

2.64) 

Fish Species Richness 

 (Number of fish species)

Reduced per tow: 6-13

cumulative:10-14 

per tow: 11-18

cumulative:15-18

Fish Species Evenness 

(Number of Fish Species $

90% of Total Abundance) 

Reduced 3-6 (mean = 3.7) 4-7 (mean = 5.2)

Mean Individual Weight

and Size of all Species

(except Pacific Herring and

Staghorn Sculpin)

Reduced e.g. English Sole 45 to

114 g (mean = 75 g.)

e.g. English Sole 125 to

484 g. (mean=204 g.)

Tolerant Species

Abundance and Biomass

(English Sole, Pacific

Staghorn Sculpin, Pacific

Tomcod, Shiner Surfperch,

Snake Prickleback, Purple

Crab, Mottled Seastar, Plum

Anemone) 

Elevated or (in

some cases) no

difference

e.g. English Sole 

2.8-10.1 (5.3) per 100 m2

e.g. juv. Tomcod 

0.39 to 9.87 (7.3)

e.g. Purple Crab

4.7 to 56.0 (22.8) 

e.g. English Sole 0.2 to

6.1 (2.3) per 100 m2

e.g. juv. Tomcod 0 to

0.69 (0.4)

e.g. Purple Crab 0.0 to

6.3 (2.7) 

Sensitive Species

Abundance and Biomass

(Bay Goby, Starry Flounder,

Rock Sole, Cartilaginous

Fish, Sea Cucumbers)

Reduced e.g. Bay Goby 0.4 to 3.9

(1.7) per 100 m2

e.g. Cucumaria piperata 

 Zero 

e.g. Bay Goby 28.6-

41.9 (36.5) per 100 m2

e.g. Cucumaria piperata

 0.0 to 5.9 (2.5)

Sensitive Species Index

(proportion of sensitive to

sensitive + tolerant)

Reduced 0.016 to 0.098 mean =

0.049

0.075 to 0.787 mean =

0.357
13-8 Case Studies
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-9

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
13-10 Case Studies

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-11

"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 gillnet 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 salinityadjusted 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., 15-85th

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., ‹15th

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.
13-12 Case Studies

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 of fish, 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-13

Table 13-3 (Cont’d). Rationale for the 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,

ln 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.
13-14 Case Studies

Table 13-3 (Cont’d). Rationale for the 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 longterm 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 of fish 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-15

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 <200

200-450

>450

<50

50-400

>400

NA

900

>900

NA

700

>700

1

2

3

*(A) Log Catch <.5

4.5-6.0

6.0

<.9

3.9-5.8

5.8

<4.2

4.2-6.4

>6.4

<1.5

1.5-6.3

>6.3

1

2

3

*Prop. Pen. Shrimp <.01

0.01-0.3

>0.3

<25

.25-.56

>56

NA

NA

NA

NA

0.04

>0.04

1

2

3

Category B

(B) Prop. Shad >0.83

NA

0.83

>.60

.04-.60

0.04

>.59

NA

.59

>.78

NA

.78

1

2

3

*(B) Prop. B. Anchovy

If Bay A. = 0

then use 'Shad' metric

>0.8

NA

0.8

>.52

.04-.52

<.04

>.13

NA

.13

>.34

NA

.34

1

2

3

*Dominance Ratio >0.88

0.44-0.88

 <0.44

>.65

.40-.65

<.40

>.82

.26-.82

.26

>.78

.27-.78

<.27

1

2

3

Category C

*(C) Mean #Taxa <6

6-11

>11

<6

6-10

>10

<6

6-10

>10

<5

5-10

>10

1

2

3

(C) Cum. #Taxa <10

10-19

>19

<6

6-11

>11

<11

11-18

>18

<11

11-19

>19

1

2

3

(C) Mean #Fish Taxa <3

3-7

>7

<3

3-7

>7

<3.5

3.5-7

>7

<4

4-8

>8

1

2

3

Total IBI Score

Concern 5-7 5-7 4-5 7-9

Normal 8-12 8-12 6-10 10-12

Excellent 13-15 13-15 11-12 13-15

Total IBI Score (WHEN INVERTS NOT USED)

Concern 4-5 4-5 4-5 5-6

Normal 6-10 6-10 6-10 7-10

Excellent 11-12 11-12 11-12 11-12

* Recommended metric; if mean log total catch or total catch = 0, then score = high concern.
13-16 Case Studies

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

Metric Summer Value Fall Value Winter

Value

Spring

Value

Score

*Prop. Total Catch

as P. Shrimp

*

#0.45

>0.45

<0.42

.42- .83

>0.83

*

*

*

*

#0.08

>0.08

1

2

3

 *Prop Total Catch

as Shad

>0.06

*

#0.06

>0.08

*

#0.08

*

*

*

>0.03

NA

#0.03

1

2

3

Category A

*Mean # Nekton

Taxa

<1.8

1.8-9.3

>9.3

<4.3

4.3-9.9

>9.9

<4.4

4.4-8.8

>8.8

<4.1

4.1-7.7

>7.7

1

2

3

Mean # Fish Taxa <2.2

2.2-6.3

>6.3

<4.2

4.2-6.6

>6.6

<2.1

2.1-6.8

>6.8

<1.6

1.6-4.9

>4.9

1

2

3

Total IBI Score

Concern 4 3 1 4

Normal 5-8 4-8 2 5-8

Excellent 9 9 3 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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-17

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

Metric Assigned Metric Score

0 1 2 3

1) Total Nekton Catch 0 1<26 26<47 $47

2) Category 2 (Pick 1 of the 2 Metrics Listed)

 2a) Number of

Nekton Taxa

0 1<7 7<8 $8

 2b) H' * <1.25 1.25<1.85 $1.85

3) Category 3 (Pick 1 of the 2 metrics listed)

 3a) Evenness J * <.58 .58<.81 $.81

 3b) Number of Taxa

= 90% Total

Nekton Catch

* <4 4<6 $6

No. Crust. Spp. * Not Recom. Not

Recom.

Not Recom.

4) No. Pred. Taxa * 0 1 >1

No. "Minnow" Taxa * Not Recom. Not

Recom.

Not Recom.

5) No. Scaenids/B. Cat.

Taxa

* 0 1-2 >2

Total IBI Score (SUM OF

ALL 5 METRIC

CATEGORIES)

0 5-6 7-13 14-15

Total IBI Rank HIGH

CONCERN

CONCERN NORMAL 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.
13-18 Case Studies

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

Assigned FHI Rank

1 2 3

Blue Catfish FHI Score >70 40-70 <40

Atlantic Croaker FHI

Score

>50 30-50 <30

Sea Catfish "Hardhead"

(least recommend) score

>30 * #30

Spot FHI Score >61 32-61 <32

AVERAGE SPECIES FHI

RANK

1-1.4 1.5-2.5 $2.6

Total FHI Rank based on

average scores of single

species

CONCERN NORMAL EXCELLENT

CONDITION FACTOR

Species

Assigned Condition Factor (CF) Rank

1 2 3

Blue Catfish CF <.78 .78-.97 >.97

Atlantic Croaker CF <1.02 1.02-1.15 >1.15

See Catfish "Hardhead"

CF

<.82 .82-1.10 >1.10

Spot CF <1.25 1.25-1.44 >1.44

AVERAGE SPECIES CF

RANK

1-1.4 1.5-2.5 $2.6

Total CF Rank based on

average scores of single

species.

CONCERN NORMAL EXCELLENT
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-19

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
13-20 Case Studies
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-21

13.3 Tampa 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 ShannonWiener 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
13-22 Case Studies

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

comm on 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 costeffectiveness.

• 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-23

infauna) 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 mgL-1.

3 Slightly tolerant - slightly

sensitive. The identified

species can withstand brief

excursions to 2.5-3.0 mgL-1

.

4 Sensitive. The identified

species can withstand brief

periods below 4.0 mgL-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:

where: ni

 = number of individuals of

species i;

Ii = tolerance value for species i;
13-24 Case Studies

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

BEAM TRAWL SAMPLE RESULTS

Sources Controls

Stations

Number of Taxa

Index Total

Index

4

8

15

1.88

6

13

27

2.08

5

16

35

2.19

7

29

69

2.38

2

27

72

2.67

1

31

84

2.71

3

38

106

2.79

N = total individuals from all

species used in the calculation.

In a strictly qualitative approach, an

index value may be calculated using the

formula:

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@orl1.dep.state.fl.us
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-25

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 hardpacked 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 Dframe 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
13-26 Case Studies

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 5-10 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.

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 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-27

metrics included: Farrell Biotic Index

(modified for North Carolina), number

of amphipods and caridian shrimp, total

taxa, percent annelid abundance,

percent mollusc abundance, ShannonWiener 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.
13-28 Case Studies

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 —

Ponar Biotic Indices

0.5

1

1.5

2

2.5

3

0 10 20 30 40

Salinity

Biotic Index

BI Reference

BI Unknown

BI Impacted

Ponar Biotic Indices

0.5

1

1.5

2

2.5

3

0 10 20 30 40

Salinity

Biotic Index

BI Reference

BI Unknown

BI Impacted

Figure 13-3

Ponar samples:

biotic index vs. 

salinity
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-29

Biotic Index

1.5

2

2.5

3

3.5

4

0 10 20 30 40

Salinity

Biotic Index

BI Reference

BI Intermediate

BI Impacted

BI Unknown

Sweep Total Taxa

0

20

40

60

80

100

120

140

160

180

0 10 20 30 40

Salinity

Total Taxa

T T Reference

T T Intermediate

T T Impacted

T T Unknow n

Amphipod & Caridean Shrimp Taxa

0

5

10

15

20

25

30

35

0 10 20 30 40

Salinity

A&C Taxa

A&C Reference

A&C Intermediate

A&C Impacted

A&C Unknown

Figure 13-4

BI, total taxa and

amphipod and

caridean taxa by

salinity.
13-30 Case Studies

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-31

STEP 1: Assign points for each of three metrics from a sweep sample.

Polyhaline (21 ppt to seawater)

Points 5 4 3 2 1

BI

Total Taxa

Amphipods & 

 Caridean Shrimp

$ 2.6

$ 95

$ 21

2.59 - 2.5

 94 - 86

 20 - 18

2.49 - 2.01

 85 - 69

 17 - 13

2.0 - 1.91

 68 - 60

 12 - 10

# 1.9

< 60

9 - 0

Mesohaline (8 ppt to 20 ppt)

Points 5 4 3 2 1

BI

Total Taxa

Amphipods & 

 Caridean Shrimp

$ 2.2

$ 38

$ 8

2.2 - 2.16

 37 - 32

 7

2.15 - 1.96

 31 - 24

 6 - 5

1.95 - 1.9

 23 - 18

 4

< 1.9

17 - 0

3 - 0

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

Figure 13-5

Development of

biocriteria.

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
13-32 Case Studies
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-33

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 nonimpaired sites. For example, during

winter sampling, mean salinity at

impaired sites was 13-ppt (mesohaline),

and was 25.3-ppt (euhaline) at nonimpaired 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 nonimpaired 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
13-34 Case Studies

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 nonimpaired 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-35

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
13-36 Case Studies

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-37

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 WINTER SUMMER

0-5 cm abundance NO NO

5-15 cm abundance YES YES

0-5 cm taxa richness YES NO

5-15 cm taxa richness YES YES

percentage amphipods YES NO

total amphipod abundance YES ?

spionid/capitellid ratio YES ?

capitellid abundance YES YES

total annelid abundance NO YES

total biomass NO NO

total biomass (excluding large

bivalves)

?

mean percent biomass above

5 cm

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
13-38 Case Studies
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-39

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 

0.61-m3

s

-1( 14-mgd) and Ocean City

about 1.4-m3s

-1 (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 midpoint of the tow. Trawl scope used is six

to one. Benthic macroinvertebrate

samples are collected with a 0.1-m2

Smith-McIntyre 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 subsampling 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,
13-40 Case Studies

Figure 13-6

Bethany

Beach - Ocean

City study

area.

a comparison of the Smith-McIntyre 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.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-41

Figure 13-7

Bethany

Beach - Ocean

City sampling

locations.

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.
13-42 Case Studies

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 11-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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-43

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-

11a, 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 
13-44 Case Studies

Max

Min

75%

25%

Median

Station

Total Number of Individuals

10

100

1000

10000

ABCDE

Figure 13-8a

Total number

of macroinvertebrate

individuals at

Bethany

Beach sites;

summer

data, n=9.

Max

Min

75%

25%

Median

Station

Total Number of Individuals

10

100

1000

10000

FGH I J

Figure 13-8b

Total number

of macroinvertebrate

individuals at

Ocean City

sites;

summer

data, n=9.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-45

Max

Min

75%

25%

Median

Station

Total Number of Taxa

0

10

20

30

40

50

60

70

80

90

EFGH I

Figure 13-9b

Total number of

macroinvertebrate taxa

at Ocean City

sites; summer

data, n=9.

Max

Min

75%

25%

Median

Station

Total Number of Taxa

0

10

20

30

40

50

60

70

80

90

ABCDE

Figure 13-9a

Total number

of macroinvertebrate

taxa at

Bethany

Beach sites;

summer

data, n=9.
13-46 Case Studies

Max

Min

75%

25%

Median

Station

Total Number of Taxa

0

10

20

30

40

50

60

70

80

90

ABCDE

Figure 13-10a

Simpson’s

dominance index

for macroinvertebrates at Bethany

Beach sites;

summer data,

n=9.

Max

Min

75%

25%

Median

Station

Total Number of Taxa

0

10

20

30

40

50

60

70

80

90

EFGH I

Figure 13-10b

Simpson’s

dominance index

for macroinvertebrates at Ocean

City sites;

summer data,

n=9.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-47

Max

Min

75%

25%

Median

Station

Shannon-Wiener Index Value

0.5

1.0

1.5

2.0

2.5

3.0

3.5

EFGH I

Figure 13-11b

Shannon-Wiener

diversity index for

macroinvertebrates at

Ocean City sites;

summer data,

n=9.

Max

Min

75%

25%

Median

Station

Shannon-Wiener Index Value

0.5

1.0

1.5

2.0

2.5

3.0

3.5

ABCDE

Figure 13-11a

Shannon-Wiener

diversity index for

macroinvertebrates at

Bethany Beach

sites; summer

data, n=9.
13-48 Case Studies

Max

Min

75%

25%

Median

Station

Richness Index Value

2

4

6

8

10

ABCDE

Figure 13-12a

Richness index

for macroinvertebrates at

Bethany Beach

sites; summer

data, n=9.

Max

Min

75%

25%

Median

Station

Richness Index Value

2

4

6

8

10

EFGH I

Figure 13-12b

Richness index

for macroinvertebrates at

Ocean City sites;

summer data,

n=9.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-49

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-McIntyre and Young grabs

were both entirely adequate, but the

Young was more efficient and safer to

work with, while the Smith-McIntyre

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 macroinvertebrate 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
13-50 Case Studies

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 “G” 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 BeachOcean 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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-51

discharge

A

B

C

D

E

F

G

D1

D2

D3

D4

D5

net longshore current

#

ABC

D

EFG

SERIES

STATIONS

Datacanbeusedtoplot not only

impact, but relative expansion or

contraction of the area of impact over 

time.

Figure 13-13 

Proposed

diagnostic

nearfield station

array.

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
13-52 Case Studies

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 Individuals Taxa Simpson’s

Index

ShannonWiener

Richness

A 427-3049 46-71 0.075-0.161 2.597-3.137 7.3-9.1

E 281-474 40-49 0.076-0.224 2.262-3.889 6.6-8.0

I 136-841 27-42 0.129-0.260 1.993-2.524 5.3-6.0

Mean Score 281-1455 38-54 0.093-0.215 2.284-3.183 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

“G” (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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-53

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 Biocriteria Bethany Beach

Outfall

Ocean City

Outfall

No. Indiv. 281-1455 260-1988 49-6,492

No. Taxa =/>38-54 28-43 13-49

Simps. Dom. =/<0.093-0.215 0.171-0.642 0.179-0.643

Shan.-Wien. DI =/>2.284-3.183 0.970-2.648 1.855-2.883

Richness =/>6.4-7.7 4.6-5.8 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 III 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 
13-54 Case Studies
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-55

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 probabilitybased 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 nonrandomly 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
13-56 Case Studies

Figure 13-14

1995 Carolinian

Province sampling

stations.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-57

Table 13-15. Estuarine resources of the Carolinian Province.

Province Large

Estuaries

Small

Estuaries

Large Tidal

Rivers

All Years

Number of

Estuaries

200 3 194 3

Area

Represented

(km2

)

11,622.1 5,581.1 4,907 1,134

In 1995

Number of

Stations

88 16 55a17b

Area

Represented

(km2)

6,991.8 4,480.0 1,377.8 1,134

aStation 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 watercolumn 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 provincewide 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
13-58 Case Studies

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

Contam inants 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

Table 13-16. Core environmental indicators for the Carolinian Province.

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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-59

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 amm onia and hydrogen sulfide concentrations

Table 13-17. Exposure indicators under development in the Carolinian Province.

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, siltclay, 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 log10-

transformed data with flexible sorting as

the clustering method and Bray-Curtis

similarity as a resemblance measure (see

Boesch 1977). 
13-60 Case Studies

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). Seventyfive 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 U-tests, and

Komogorov-Smirnov two-sample tests;

at " = 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 pollutionsensitive 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

10th-50th 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)
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-61

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,

NOAA/National Ocean Service

217 Fort Johnson Rd. (P.O. Box 12559),

Charleston, SC 29422-2559

843-762-5415

jhyland@rdc.noaa.gov
13-62 Case Studies

Figure 13-15

Frequency distribution

of index scores for

undegraded vs.

degraded stations in

1993/1995

“development” data

set.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-63

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. 

aPercent

expected

bioeffects - #

stations (1995

core &

supplemental)

where an effect

was detected / #

stations with $ 1

ER-M/PEL or $ 3

ER-L/TEL

exceedance.
13-64 Case Studies

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. 

Figure 13-18

Comparison of

benthic index

values by

estuarine class

and subregion.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-65

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 probabilitybased 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
13-66 Case Studies

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 midAtlantic 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. Finegrained 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. 
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-67

Sediment type was defined according to

silt-clay content (fraction less than 63-μ);

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

VanVeen grab. Four measures of
13-68 Case Studies

Physical Parameters

Depth

% Silt/Clay content

Salinity

Temperature

pH

Water Quality Parameters

Chlorophyll a

Phaeophytin

Benthic chlorophyll

DO (Dissolved Oxygen)

NO2 (Nitrite)

NO3

 (Nitrate)

Ammonium

TDN (Total Dissolved Nitrogen)

Orthophosphate

TDP (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 13-18. Environmental parameters for the Maryland/Delaware Coastal Bays.

Table 13-19. Chesapeake Bay submerged aquatic vegetation habitat requirements for a polyhaline

environment (Dennison et al. 1993).

Parameter Critical Value

Light attenuation coefficient (kd

; m-1) 1.5

Total suspended solids (mgL-1) 15

Chlorophyll a (μg/l) 15

Dissolved inorganic nitrogen (μM) 10

Dissolved inorganic phosphorus (μM) 0.67
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-69

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 μgL-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
13-70 Case Studies

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 III

Environmental Science Center

701 Mapes Rd.

 Fort Meade, MD 20755

410-305-2742

Kutz.Rick@epa.gov
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance G-1

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.
G-2 Glossary

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

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.
G-4 Glossary

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.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance G-5

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 L-1

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