United States
Environmental Protection
Agency
Office of Water
4304
Washington, D.C. 20460
EPA-822-B-00-024
December 2000
Estuarine and Coastal Marine
Waters: Bioassessment and
Biocriteria Technical Guidance
-------
-------
Estuarine and Coastal Marine Waters:
Bioassessment and Biocriteria Technical Guidance
George R. Gibson, Jr., Project Leader (4304)
USEPA
Office of Water
Office of Science & Technology
1200 Pennsylvania Avenue, NW
Washington, DC 20460
Principal Authors:
Michael L. Bowman
Principal Scientist
Tetra Tech, Inc.
10045 Red Run Boulevard, Suite 110
Owings Mills, MD 21117
George R. Gibson, Jr. (4304)
USEPA
Office of Water
Office of Science & Technology
1200 Pennsylvania Avenue, NW
Washington, DC 20460
Jeroen Gerritsen
Principal Scientist
Tetra Tech, Inc.
10045 Red Run Boulevard, Suite 110
Owings Mills, MD 21117
Blaine D. Snyder
Senior Scientist
Tetra Tech, Inc.
10045 Red Run Boulevard, Suite 110
Owings Mills, MD 21117
December 2000
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This document is dedicated to the memory of Dr. Douglas Farrell of the
Florida Department of Environmental Protection and Dr. Donald Lear, U.S.
Environmental Protection Agency (retired). It is fitting that this effort to which they
volunteered so much of their invaluable experience and expertise be so dedicated.
The benthic community index which Doug developed is also cited here as the
"Farrell Index" in further recognition of his unselfish contribution to the protection
and management of our coastal resources. Much of the methodology described in
the coastal survey portion of this guide was developed from Don Lear's pioneering
efforts.
The contributors to this manual sincerely hope that the good common sense,
attention to scientific veracity, and practical application of the information to
protect our marine resources - so ably personified by Don and Doug - is adequately
reflected in these pages.
Disclaimer
This manual provides technical guidance to States, Indian tribes and other authorized
jurisdictions to establish water quality criteria and standards under the Clean Water Act
(CWA), to protect aquatic life from the effects of pollution. Under the CWA, States and Indian
tribes are to establish water quality criteria to protect designated uses. State and Indian tribal
decision makers retain the discretion to adopt approaches on a case-by-case basis that differ
from this guidance when appropriate and scientifically defensible. While this manual
constitutes USEPA's scientific recommendations regarding biological criteria to help protect
resource quality and aquatic life, it does not substitute for the CWA or USEPA's regulations;
nor is it a regulation itself. Thus, it cannot impose legally binding requirements on USEPA,
States, Indian tribes or the regulated community, and might not apply to a particular situation
or circumstance. USEPA may change this guidance in the future.
This document has been approved for publication by the Office of Science and Technology,
Office of Water, U.S. Environmental Protection Agency. Mention of trade names, products, or
services does not convey and should not be interpreted as conveying, official USEPA approval,
endorsement or recommendation.
The suggested citation for this document is:
Gibson, G.R., M.L. Bowman, J. Gerritsen, and B.D. Snyder. 2000. Estuarine and Coastal Marine
Waters: Bioassessment and Biocriteria Technical Guidance. EPA 822-B-00-024. U.S.
Environmental Protection Agency, Office of Water, Washington, DC.
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Acknowledgments
The authors wish to express their sincere appreciation to the Estuarine and Coastal
Marine Biocriteria Workgroup and the peer reviewers (Arthur Newell - NYDEC,
Judith Weis - Rutgers University, John Gentile - University of Miami, Edward Long
NOAA, and Robert Diaz - Virginia Institute of Marine Science).
Estuarine and Coastal Marine Biocriteria Workgroup Attendees
1992 -1997
(Long Term Participation)
Suzanne Bolton
National Marine Fisheries Service
(ST2)
1315 East/West Hwy.
Silver Spring, MD 20910
301-713-2363
Michael L. Bowman
Tetra Tech, Inc.
10045 Red Run Blvd.
Suite 110
Owings Mills, MD 21117
Dan Campbell
c/oUSEPAERL/ORD
University of Rhode Island
27 Tarzwell Drive
Narragansett, RI 02882
Dan Dauer
Department of Biology
Old Dominion University
Norfolk, VA 23529
804-683-3595
Robert Diaz
VA Institute of Marine Science
Glouchester Point, VA 23062
804-642-7364
Cindy Driscoll
MD Department of Natural Resources
Oxford Laboratory
904 S. Morris St.
Oxford, MD 21654
410-226-0078
Charles Eaton
Bio-Marine Enterprises
2717 3rd Avenue North
Seattle, WA 98109
206-282-4945
Larry Eaton
NC Division of Water Quality
4401 Reedy Creek Road
Environmental Sciences Bldg.
Raleigh, NC 27607
919-733-6946
Douglas Farrell*
FL Department of Environmental
Protection
3804 Coconut Dr.
Tampa, FL 33619-8218
Brigette Farren
USEPA, Region III
1650 Arch Street
Philadelphia, PA 19103-2029
215-814-2767
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
-------
Chris Faulkner
USEPA, OWOW (4503F)
1200 Pennsylvania Ave.
Washington, DC 20460
202-260-6228
Jeroen Gerritsen
Tetra Tech, Inc.
10045 Red Run Blvd.
Suite 110
Owings Mills, MD 21117
George Gibson, Jr. (4304)
USEPA
Office of Water
Office of Science and Technology
1200 Pennsylvania Ave.
Washington, DC 20460
410-305-2618
Steve Glomb
U.S. Fish and Wildlife Service
4401 N Fairfax Dr.
Room 400
Arlington, VA 22203
703-358-2201
George Guillen
TX Water Commission
District 7
5144 East Sam Houston Parkway, N
Houston, TX 77015
713-457-5191
Susan Jackson
USEPA, OST/HECD (4304)
1200 Pennsylvania Avenue, NW
Washington, DC 20460
202-260-1800
Steve Jordan
MD Department of Natural Resources
904 South Morris Street
Oxford, MD 21654
410-226-0078
Don Kelso
George Mason University
3016 King Hall
4400 University Drive
Fairfax, VA 22030
Steve Kent
FL Department of Environmental
Protection
3319 Maguire Blvd.
Suite 232
Orlando, FL 32803
Don Lear*
Anne Arundel Community College
101 College Pkwy
Arnold, MD 21012
410-647-7100
Beth McGee
U.S. Fish and Wildlife Service
Chesapeake Bay Field Office
1777 Admiral Cochrane Drive
Annapolis, MD 21401
410-573-4524
Margaret McGinty
MD Department of Natural Resources
Tidewater Ecosystem Assessment
Annapolis, MD 21401
410-260-8637
Gil McRae
FL Marine Research Institute
100 Eighth Ave., SE
St. Petersburg, FL 33701
727-896-8626
727-823-0166 (fax)
IV
Acknowledgements
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William Muir
USEPA Region III
1650 Arch Street (3ES41)
Philadelphia, PA 19107
215-814-2541
Walt Nelson
USEPA
2111 SE Marine Science Dr.
Newport, OR 97365-5260
541-867-4041
Art Newell
NY Department of Environment
Division of Marine Resources
Building 40, SUNY
Stonybrook, NY 11790-235
516-444-0430
Dave Russell
USEPA Region III
Environmental Science Center
701 Mapes Road
Ft. Meade, MD 20755-5350
410-305-2656
Steve Wolfe
FL Department of Environmental
Protection
2600 Blair Stone Road
Tallahassee, FL 32399
* Deceased
Acknowledgment:
Additional scientific, technical, editorial, and production contributions were made
by William Swietlik (USEPA), Laura Gabanski (USEPA), Jim Latimer (USEPA),
David Scott (Dalhousie University), Gail Chmura (McGill University), Zorana
Spasojeviz (McGill University), Jerome Diamond (Tetra Tech, Inc.), Abby Markowitz
(Tetra Tech, Inc.), Kristen Pavlik (Tetra Tech, Inc.), Brenda Fowler (Tetra Tech, Inc.),
Erik Leppo (Tetra Tech, Inc.), and Regina Scheibner (Tetra Tech, Inc.). This
document was prepared by Tetra Tech, Inc.
For the Ocean City/Bethany Beach case study in Section 13.6, thanks are given to
David Russell, USEPA Region III provided taxonomic identifications, William Muir,
USEPA Region III assisted with data gathering, Eileen Watts, USEPA Region III
provided data analysis. Jeroen Gerritsen, Tetra Tech, Inc. offered constructive
comments, and Kristen Pavlik, Tetra Tech, Inc. made final editorial changes. Their
essential contributions to this report are greatly appreciated.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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Estuarine and Coastal Marine Waters:
Bioassessmentand Biocriteria Technical Guidance
CONTENTS
List of Figures xv
List of Tables xxi
Acronym List xxv
Executive Summary xxix
CHAPTER 1: Introduction: Bioassessment and Biocriteria 1-1
1.1 RATIONALE 1-1
1.1.1 Water Quality Monitoring 1-1
1.1.2 Advantages of Bioassessment and Biocriteria 1-1
1.2 LEGAL ORIGINS 1-2
1.2.1 Clean Water Act 1-2
1.2.2 305(b) Reporting 1-2
1.2.3 301(h) and 403(c) Programs 1-2
1.2.4 304(a) Criteria Methodology 1-2
1.2.5 Biocriteria 1-5
1.3 USES OF BIOCRITERIA 1-5
1.3.1 The Use of Bioassessment Data to Establish Biocriteria Appropriate
to Designated Beneficial Uses 1-6
1.3.2 Expansion and Improvement of Water Quality Standards 1-9
1.3.3 Detection of Problems Other Methods May Miss or Underestimate .. 1-9
1.3.4 Helping the Water Resource Managers Set Priorities 1-9
1.3.5 Use of Biosurveys and Biocriteria to Evaluate the Success or Failure
of Management Initiatives or Regulations 1-9
1.4 PROGRAM INTERDEPENDENCE 1-10
1.5 IMPLEMENTING BIOLOGICAL CRITERIA 1-10
1.6 CHARACTERISTICS OF EFFECTIVE BIOCRITERIA 1-11
1.7 CONCEPTUAL FRAMEWORK 1-11
1.7.1 Indicators of Biological Integrity and Survey Protocols 1-12
1.7.2 Comparison to a Reference 1-15
1.7.3 Assessment Tiers 1-16
vii Contents
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CONTENTS (CONTINUED)
CHAPTER 2: Biological Survey 2-1
2.1 INDICATORS OF BIOLOGICAL INTEGRITY 2-1
2.2 PRIMARY MEASURES OF COMMUNITY CONDITION AND CHANGE ... 2-1
2.2.1 Benthic Macroinvertebrates 2-1
2.2.2 Fish 2-2
2.2.3 Aquatic Macrophytes 2-3
2.2.4 Phytoplankton 2-4
2.3 MEASURES OF COMMUNITY CONDITION AND CHANGE BEING
DEVELOPED 2-5
2.3.1 Zooplankton 2-5
2.3.2 Epibenthos 2-6
2.3.3 Paleoenvironmental Reconstruction: preserved remains 2-7
2.4 THE USE OF INDEXES TO COMPILE AND EVALUATE
BIOLOGICAL DATA 2-7
2.5 INDICATOR TAXA 2-9
CHAPTER 3: Habitat Characterization 3-1
3.1 FLOW AND HYDROGRAPHY 3-2
3.1.1 Circulation and Tidal Regime 3-2
3.2 HABITAT TYPES 3-3
3.2.1 Open Water 3-4
3.2.2 Soft Bottom Substrates 3-4
3.2.3 Hard Bottom Substrates 3-5
3.2.4 Aquatic Macrophytes 3-5
3.2.5 Beaches 3-6
3.2.6 Sandflats 3-6
3.2.7 Mudflats 3-7
3.2.8 Emergent Marshes 3-7
3.2.9 Mangrove Forests 3-7
3.3 WATER COLUMN CHARACTERISTICS 3-7
3.3.1 Salinity 3-9
3.3.2 Temperature 3-10
3.3.3 Dissolved Oxygen 3-10
3.3.4 pH 3-12
3.3.5 Turbidity 3-12
3.3.6 Nutrients 3-13
3.3.7 Contaminants 3-14
3.3.8 Depth 3-15
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance viii
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CONTENTS (CONTINUED)
3.4 BOTTOM CHARACTERISTICS 3-15
3.4.1 Sediment Grain Size 3-16
3.4.2 Total Organic Carbon, Total Volatile Solids, and Acid Volatile
Sulfides 3-16
3.4.3 Sediment Oxidation-Reduction Potential 3-17
3.4.4 Sediment Contamination 3-18
3.5 PROPOSED HABITAT PARAMETERS 3-18
3.5.1 Tier 0 3-20
3.5.2 Tier 1 3-20
3.5.3 Tier 2 3-21
3.5.4 Tier 3 3-22
CHAPTER 4: Physical Classification and the Biological Reference Condition 4-1
4.1 CLASSIFICATION APPROACH 4-1
4.2 PHYSICAL CLASSIFICATION 4-4
4.2.1 Geographic Region 4-4
4.2.2 Estuarine Categories 4-5
4.2.3 Watershed Characteristics 4-6
4.2.4 Waterbody Characteristics 4-6
4.3 ESTABLISHING BIOLOGICAL REFERENCE CONDITIONS 4-7
4.3.1 Historical Data 4-7
4.3.2 Reference Sites 4-8
4.3.3 Models 4-9
4.3.4 Expert Opinion/Consensus 4-10
4.4 USE OF REFERENCE SITES TO CHARACTERIZE
REFERENCE CONDITION 4-11
4.4.1 Selected Reference Sites 4-12
4.4.2 Reference Condition Derived From Population Distribution 4-16
4.4.3 Site Specific Reference Sites 4-17
CHAPTER 5: Sampling Program Issues, Biological Assemblages, and Design 5-1
5.1 ASSEMBLAGES 5-1
5.1.1 Benthic Macroinvertebrates (Infauna) 5-2
5.1.2 Fish 5-14
5.1.3 Aquatic Macrophytes 5-15
5.1.4 Phytoplankton 5-16
5.1.5 Zooplankton (Developmental) 5-18
ix Contents
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CONTENTS (CONTINUED)
5.1.6 Epibenthos (Developmental) 5-19
5.1.7 Paleoenvironmental Systems (Developmental) 5-20
5.2 SAMPLING DESIGN ISSUES 5-21
5.2.1 Statement of the Problem 5-23
5.2.2 Definition of the Assessment Unit 5-24
5.2.3 Specifying the Population and Sample Unit 5-24
5.2.4 Sources of Variability 5-25
5.2.5 Alternative Sampling Designs 5-27
5.2.6 Optimizing Sampling 5-30
CHAPTER 6: Water Column & Bottom Characteristics 6-1
6.1 SALINITY, TEMPERATURE, DISSOLVED OXYGEN & pH 6-1
6.2 SECCHI DEPTH 6-1
6.3 DEPTH 6-1
6.4 SEDIMENT GRAIN SIZE 6-1
6.4.1 Estimation of "percent fines" (Tier 1) 6-1
6.4.2 Sediment Grain Size (Tiers 2 and 3) 6-4
6.5 RPD Layer Depth 6-5
6.6 TOTAL VOLATILE SOLIDS 6-5
6.7 SEDIMENT CONTAMINANT TOXICITY 6-5
6.7.1 10-day Static Sediment Toxicity Tests with Marine and Estuarine
Amphipods 6-5
6.7.2 10-day Static Sediment Toxicity Tests with Marine and Estuarine
Polychaetous Annelids 6-6
6.7.3 Static Accute Toxicity Tests with Echinoid Embryos 6-6
6.7.4 Toxicity Tests Using Marine Bivalves 6-7
6.8 NUTRIENTS (Tiers 2&3) 6-7
6.9 TOTAL ORGANIC CARBON (Tiers 2&3) 6-7
6.10 WATER COLUMN CONTAMINANTS (Tier 3) 6-8
6.11 ACID VOLATILE SULFIDES (Tier 3) 6-8
6.12 SEDIMENT CONTAMINANTS 6-9
CHAPTER 7: Tier 0: Desktop Screening 7-1
7.1 AREA AND GEOMORPHOMETRIC CLASSIFICATION 7-1
7.2 HABITAT TYPE 7-2
7.3 WATERSHED LAND USE 7-2
7.4 POPULATION DENSITY 7-2
7.5 NPDES DISCHARGES 7-2
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance x
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CONTENTS (CONTINUED)
7.6 BIOLOGICAL ASSEMBLAGES 7-2
7.7 WATER COLUMN AND BOTTOM CHARACTERISTICS 7-3
CHAPTER 8: Tier 1 8-1
8.1 BENTHOS 8-1
8.1.1 Sampling Procedure 8-3
8.1.2 Index Period 8-3
8.1.3 Analysis 8-3
8.2 FISH 8-3
8.2.1 Sampling Procedure 8-3
8.2.2 Sample Processing 8-4
8.3 MACROPHYTES 8-4
8.4 PHYTOPLANKTON 8-5
CHAPTER 9: Tier 2 9-1
9.1 BENTHOS 9-1
9.1.1 Sampling Procedure 9-2
9.1.2 Index Period 9-3
9.1.3 Analysis 9-3
9.2 FISH 9-3
9.2.1 Sampling Procedure 9-3
9.2.2 Sample Processing 9-3
9.2.3 Analysis 9-3
9.3 MACROPHYTES 9-3
9.3.1 Sampling Procedure 9-3
9.3.2 Index Period 9-4
9.3.3 Analysis 9-4
9.4 PHYTOPLANKTON 9-4
9.4.1 Sampling Procedure 9-4
9.4.2 Index Period 9-4
9.4.3 Analysis 9-5
9.5 EPIBENTHOS (Developmental) 9-5
9.5.1 Sampling Procedure 9-5
9.5.2 Index Period 9-5
9.5.3 Analysis 9-5
CHAPTER 10: Tier 3 10-1
10.1 BENTHOS 10-1
xi Contents
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CONTENTS (CONTINUED)
10.1.1 Sampling Procedure 10-3
10.1.2 Index Period 10-3
10.1.3 Analysis 10-3
10.2 FISH 10-3
10.2.1 Sampling Procedure 10-3
10.2.2 Sample Processing 10-3
10.2.3 Analysis 10-3
10.3 MACROPHYTES 10-3
10.3.1 Sampling Procedure 10-4
10.3.2 Index Period 10-4
10.3.3 Analysis 10-4
10.4 PHYTOPLANKTON 10-4
10.4.1 Sampling Procedure 10-4
10.4.2 Index Period 10-4
10.4.3 Analysis 10-4
10.5 EPIBENTHOS (Developmental) 10-4
10.5.1 Sampling Procedure 10-4
10.5.2 Index Period 10-4
10.5.3 Analysis 10-4
10.6 ZOOPLANKTON (Developmental) 10-4
10.6.1 Sampling Procedure 10-5
10.6.2 Index Period 10-5
10.6.3 Analysis 10-5
10.7 PALEOENVIRONMENTAL SYSTEMS (Developmental) 10-5
10.7.1 Sampling Procedure 10-5
10.7.2 Sample Processing 10-6
10.7.3 Analysis 10-6
CHAPTER 11: Index Development 11-1
11.1 OVERVIEW 11-1
11.2 CLASSIFICATION AND CHARACTERIZATION OF REFERENCE
CONDITION 11-2
11.2.1 Existing Classifications 11-3
11.2.2 Assessing a priori Classifications 11-6
11.3 INDEX DEVELOPMENT 11-6
11.3.1 Multimetric Index 11-7
11.3.2 Discriminant Model Index 11-13
11.3.3 Index Derived from Multivariate Ordination 11-14
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xii
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CONTENTS (CONTINUED)
CHAPTER 12: Quality Assurance: Design, Precision, and Management 12-1
12.1 PROGRAM DESIGN 12-1
12.1.1 Formulation of a Study Design 12-2
12.1.2 Establishment of Uncertainty Limits 12-2
12.1.3 Optimizing the Study Design: Evaluation of Statistical Power 12-3
12.2 MANAGEMENT 12-7
12.2.1 Personnel 12-7
12.2.2 Resources 12-7
12.3 OPERATIONAL QUALITY CONTROL 12-7
12.3.1 Field Operations 12-8
12.3.2 Laboratory Operations 12-9
12.3.3 Data Analysis 12-9
12.3.4 Reporting 12-9
CHAPTER 13: Case Studies 13-1
13.1 PUGET SOUND - DEVELOPMENT OF TRAWL-BASED TOOLS FOR
THE ASSESSMENT OF DEMERSAL FAUNA (MACROINVERTEBRATES
AND FISHES): A PUGET SOUND PILOT STUDY 13-1
13.1.1 Study Objectives 13-1
13.1.2 Study Methods 13-2
13.1.3 Study Results 13-3
13.2 GALVESTON BAY - DEVELOPMENT OF A RAPID BIO ASSESSMENT
METHOD AND INDEX OF BIOTIC INTEGRITY FOR COASTAL
ENVIRONMENTS: NORTHWESTERN GULF OF MEXICO PILOT
STUDIES 13-9
13.2.1 Study Objectives 13-9
13.2.2 Study Methods 13-9
13.2.3 Study Results 13-10
13.3 TAMPA BAY - DEVELOPMENT OF A COMMUNITY-BASED METRIC
FOR MARINE BENTHOS: A TAMPA BAY PILOT STUDY 13-21
13.3.1 Study Objectives 13-21
13.3.2 Study Methods 13-21
13.3.3 Study Results 13-23
13.4 NORTH CAROLINA - COMPARISON OF BIOLOGICAL METRICS
DERIVED FROM PONAR, EPIBENTHIC TRAWL, AND SWEEP NET
SAMPLES: A NORTH CAROLINA PILOT STUDY 13-25
13.4.1 Study Objectives 13-25
13.4.2 Study Location 13-25
xiii Contents
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CONTENTS (CONTINUED)
13.4.3 Study Methods 13-25
13.4.4 Results 13-27
13.4.5 Summary 13-30
13.5 INDIAN RIVER, FLORIDA - FIELD VERIFICATION OF MARINE
METRICS DEVELOPED FOR BENTHIC HABITATS: INDIAN RIVER
LAGOON, FLORIDA PILOT STUDIES 13-33
13.5.1 Study Objectives 13-33
13.5.2 Study Methods 13-33
13.5.3 Study Results 13-33
13.6 OCEAN CITY, MD - BETHANY BEACH, DE - A PRELIMINARY STUDY
OF THE USE OF MARINE BIOCRITERIA SURVEY TECHNIQUES
TO EVALUATE THE EFFECTS OF OCEAN SEWAGE OUTFALLS
IN THE MID-ATLANTIC BIGHT 13-39
13.6.1 Study Objectives 13-39
13.6.2 Study Methods 13-39
13.6.3 Study Results 13-42
13.6.4 Discussion and Conclusions 13-43
13.6.5 Use of the Bethany Beach-Ocean City Data to Illustrate
Biocriteria Development 13-50
13.7 ENVIRONMENTAL QUALITY OF ESTUARIES OF THE CAROLINIAN
PROVINCE: 1995 13-55
13.7.1 Background/Objectives 13-55
13.7.2 Methods 13-55
13.7.3 Benthic Infaunal Index 13-59
13.7.4 Results 13-61
13.8 ASSESSMENT OF THE ECOLOGICAL CONDITION OF THE
DELAWARE AND MARYLAND COASTAL BAYS 13-65
13.8.1 Background 13-65
13.8.2 Methods 13-65
13.8.3 Results/Conclusions 13-69
Glossary G-l
Literature Cited L-l
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xiv
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LIST OF FIGURES
Figure
1-1 Biocriteria for given classifications of estuaries and coastal marine areas ... 1-8
1-2 Program interdependence 1-10
1-3 The process for progressing from the classification of an estuary to
assessing the health of the estuary. Adapted from Paulsen et al. 1991 1-13
1-4 General comparison of Tiered Approach 1-18
3-1 Chemicals measured in sediments by the EMAP-Estuaries program 3-19
4-1 Graphical representation of bioassessment 4-3
4-2 Classification and assessment 4-4
4-3 Biogeographical provinces. Adapted from Holland 1990 4-6
4-4 Estuarine and coastal marine biocriteria survey method useful for
stratified random (population distribution) reference site selection. Wet
season/high flow salinity pattern showing mainstem sampling sites for
four salinity and three substrate classifications 4-8
4-5 Estuarine and coastal marine biocriteria survey method useful for
a priori reference site selection. Wet season/high flow salinity
pattern showing tributary reference sites and mainstem transects
for four salinity and three substrate classifications 4-14
4-6 Estuarine and coastal marine biocriteria survey method useful
for a prori reference site selection. Dry season/low flow salinity pattern
showing tributary reference sites and mainstem transects for four
salinity and three substrate classifications 4-15
xv Contents
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LIST OF FIGURES (CONTINUED)
Figure
4-7 Hypothetical cumulative frequency distribution of metric values for all
sites in a given estuarine or coastal marine class. The dotted line
shows the metric value corresponding to the 95th percentile 4-17
4-8 Estuarine and coastal marine biocriteria survey method useful for
stratified random (population distribution) reference site selection. Dry
season/low flow salinity pattern showing mainstem sampling sites
for four salinity and three substrate classifications 4-18
4-9 Estuarine and coastal marine survey method for navigation channel
assessment 4-20
4-10 Estuarine and coastal marine biocriteria survey method useful for
marine site selection 4-20
5-1 Cross-section of sediment in clamshell bucket illustrating acceptable
and unacceptable grabs 5-9
5-2 Description of various sampling methods 5-28
11-1 The process for progressing from the classification of an estuary to
assessing the health of the estuary. Adapted from Paulsen et al. 1991 11-3
11-2 Mean number of species and salinity at EMAP-Estuaries sampling
stations in the Virginian Province (from Weisberg et al. 1993) 11-4
11-3 Hypothetical box plot illustrating how a successful metric discriminates
between reference and stressed sites 11-9
11-4 Basis of metric scores using the 95th percentile as a standard 11-11
11-5 Steps 1-3. Establishing site scores on a contamination gradient 11-16
11-6 Step 5. Abundance of species A and contamination scores 11-17
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xvi
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LIST OF FIGURES (CONTINUED)
Figure
12-1 Effect of increasing sample size from na to n2 on power 12-4
12-2 Example sample size calculations for comparing proportions and
population means 12-8
12-3 Six qualitative and quantitative data characteristics usually employed to
describe data quality 12-9
13-1 General location of the case studies 13-2
13-2a Bony fish abundance and total fish abundance for reference and
contaminated sites 13-4
13-2b Bony fish biomass and total fish biomass for reference and
contaminated sites 13-4
13-2c Mean individual weights of fish species from contaminated and reference
stations 13-5
13-3 Ponar samples: biotic index vs. salinity 13-28
13-4 BI, total taxa and amphipod, and caridean taxa by salinity 13-29
13-5 Development of biocriteria 13-31
13-6 Bethany Beach - Ocean City study area 13-40
13-7 Bethany Beach - Ocean City sampling locations 13-41
13-8a Total number of macroinvertebrate individuals at Bethany Beach sites;
summer data, n=9 13-44
xvii Contents
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LIST OF FIGURES (CONTINUED)
Figure
13-8b Total number of macroinvertebrate individuals at Ocean City sites;
summer data, n=9 13-44
13-9a Total number of macroinvertebrate taxa at Bethany Beach sites;
summer data, n=9 13-45
13-9b Total number of macroinvertebrate taxa at Ocean City sites; summer
data, n=9 13-45
13-10a Simpson's dominance index for macroinvertebrates at Bethany Beach
sites; summer data, n=9 13-46
13-1 Ob Simpson's dominance index for macroinvertebrates at Ocean City sites;
summer data, n=9 13-46
13-lla Shannon-Wiener diversity index for macroinvertebrates at Bethany
Beach sites; summer data, n=9 13-47
13-llb Shannon-Wiener diversity index for macroinvertebrates at Ocean City
sites; summer data, n=9 13-47
13-12a Richness index for macroinvertebrates at Bethany Beach sites;
summer data, n=9 13-48
13-12b Richness index for macroinvertebrates at Ocean City sites; summer
data, n=9 13-48
13-13 Proposed diagnostic nearfield station array 13-51
13-14 1995 Carolinian Province sampling stations 13-56
13-15 Frequency distribution of index scores for undegraded vs. degraded
stations in 1993/1995 "development" data set 13-62
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xviii
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LIST OF FIGURES (CONTINUED)
Figure
13-16 Comparison of the percent of expected bioeffects detected with the
benthic index vs. (A) four sediment bioassays and (B) three individual
infaunal attributes 13-63
13-17 Percent area (and 95% C.I.) of CP estuaries with higher > 1.5 to < 3),
and low (< 1.5) benthic index values 13-64
13-18 Comparison of benthic index values by estuarine class and subregion ... 13-64
xix Contents
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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xx
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LIST OF TABLES
Table
1-1 Applications of estuarine biological monitoring protocols and biocriteria ... 1-3
1-2 Impacts on the marine environment of the Southern California Bight.
Modified from Bernstein et al. 1991 1-7
3-1 Habitat measurements for estuaries and coastal marine waters 3-23
4-1 Comparison of elements for characterizing reference conditions (adapted
from Gerritsen et al. 1995) 4-9
5-1 Potential benthic macroinvertebrate metrics 5-3
5-2 Metrics from which the EMAP Virginian and Louisianian benthic indexes
were developed 5-4
5-3 Sampling summary for infaunal benthic macroinvertebrates 5-5
5-4 Summary of bottom sampling equipment (adapted from USEPA 1992,
Klemm et al. 1992, and ASTM 1991) 5-7
5-5 Mesh sizes used in estuary benthic monitoring programs 5-14
5-6 Sampling summary for fish 5-15
5-7 Potential aquatic macrophyte metrics 5-17
5-8 Sampling summary for aquatic macrophytes 5-17
5-9 Sampling summary for phytoplankton 5-17
5-10 Sampling summary for epibenthos 5-20
5-11 Potential paleoecological indicators 5-22
5-12 Sampling summary for paleoenvironmental systems 5-22
xxi Contents
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LIST OF TABLES (CONTINUED)
Table
6-1 Water Column & Bottom Characteristics. "Addition" refers to added
detail or intensities for a parameters initiated in an earlier tier 6-2
7-1 Tier 0 Desktop screening for estuaries and coastal marine waters 7-1
8-1 Tier 1 Assessment. Requires single field visit in spring or summer
index period 8-2
9-1 Tier 2 Assessment. Requires two or more field visits, one of which
should occur within chosen index period. In addition to requirements
from Tier 0 & 1 9-2
10-1 Tier 3 Assessment. Requires four or more field visits, one of which
should occur within the chosen index period. In addition to requirements
from Tiers 0-2 10-2
11-1 Potential metrics for macrophytes, benthic macroinvertebrates, and fish
that could be considered for estuaries. Redundancy can be evaluated
during the calibration phase to eliminate overlapping metrics 11-8
11-2 Estuarine fish IBI metrics proposed by Thompson and Fitzhugh (1986) ... 11-13
11-3 Maryland estuarine fish IBI metrics 11-14
12-1 Errors in hypothesis testing 12-4
12-2 Common values of (ZK + Z2(3)2 for estimating sample size for use with
equations 1 and 2 (Snedecor and Cochran 1980) 12-6
12-3 Example QC elements for field and laboratory activities 12-10
13-1 A preliminary list of tolerant and sensitive fish and invertebrate species
from the Tacoma Waterways and Quartermaster Harbor 13-6
13-2 Candidate attributes of demersal fauna showing significant differences
in the present study 13-7
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xxii
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LIST OF TABLES (CONTINUED)
Table
13-3 Rationale for the inclusin of proposed nekton community metrics 13-12
13-4 Proposed seine metrics for use in an estuarine IBI along Texas coast 13-15
13-5 Proposed trawl metrics for use in an estuarine IBI along Texas coast 13-16
13-6 Proposed gillnet metrics for use in estuarine IBI along Texas coast 13-17
13-7 Proposed fish health index and condition factors for use in estuarine
rapid bioassessments of Texas Gulf coast tidal tributaries 13-18
13-8 Advantages and disadvantages to using the epibenthic Renfro beam
trawl for the sampling of benthos 13-22
13-9 Farrell epifaunal index results for the Fort Desoto Park - Tampa Bay
Pilot Study 13-24
13-10 Advantages and disadvantages noted for the three benthic assemblage
collection methods 13-26
13-11 Functional metrics for the three benthic assemblage collection methods ... 13-28
13-12 Comparison between winter and summer samples of the ability of the
various metrics tested to discriminate between impaired and low
impairment sites 13-37
13-13 Establishment of reference condition using the mean of the interquartile
range of scores for three reference sites 13-52
13-14 Comparison of the reference condition derived biocriteria to the
interquartile range of scores at the Bethany Beach and Ocean City
outfalls 13-53
13-15 Estuarine resources of the Carolinian Province 13-57
13-16 Core environmental indicators for the Carolinian Province 13-58
xxiii Contents
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LIST OF TABLES (CONTINUED)
Table
13-17 Exposure indicators under development in the Carolinian Province 13-59
13-18 Environmental parameters for the Mary land/Delaware Coastal Bays .... 13-68
13-19 Chesapeake Bay submerged aquatic vegetation habitat requirements
for a polyhaline environment (Dennison et al. 1993) 13-68
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance xxiv
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Acronym List
APHA
AVS
BMP
CCA
CDF
CSREES
CTD
CV
CWA
DFA
DGPS
DMRs
DNR
DO
EMAP
EPA
ER-L
ER-M
FEI
FTE
CIS
GPS
IBI
ITI
American Public Health Association
Acid Volatile Sulfides
Best Management Practices
Canonical Correspondence Analysis
Cumulative Distribution Function
Cooperative State Research, Education, & Extension Service
Conductivity - Temperature - Depth Meter
Coefficient of Variation
Clean Water Act
Discriminant Function Analysis
Differential Global Positioning System
Discharge Monitoring Reports
Department of Natural Resources
Dissolved Oxygen
Environmental Monitoring & Assessment Program
Environmental Protection Agency
Effects Range-Low
Effects Range-Median
Farrell Epifaunal Index
Full Time Equivalent
Geographic Information System
Global Positioning System
Chesapeake Bay Estuarine Index of Biotic Integrity
Infaunal Trophic Index
xxv
Acronym List
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MDS
NMDS
NMFS
NOAA
NODC
NPDES
NS&T
PAHs
PCA
PCBs
PCE
PCS
POTW
QA
QC
RBP
RPD
SAV
SEM
SOP
SPM
SQG
SQT
STORET
TDN
TDP
Multidimensional Scaling
Non-metric Multidimensional Scaling
National Marine Fisheries Service
National Oceanic and Atmospheric Administration
National Oceanographic Data Center
National Pollutant Discharge Elimination System
National Status & Trends
Polyaromatic Hydrocarbons
Principle Components Analysis
Polychlorinated Biphenyls
Power Cost Efficiency
Permit Compliance System
Publically Owned Treatment Works
Quality Assurance
Quality Control
Rapid Bioassessment Protocol
Redox Potential Discontinuity
Submerged Aquatic Vegetation
Simultaniously Extracted Metals
Standard Operating Procedure
Suspended Particulate Matter
Sediment Quality Guidelines
Sediment Quality Triad
STOrage & RETrieval
Total Dissolved Nitrogen
Total Dissolved Phosphorus
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
XXVI
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TMDL
TOC
TPC
TPN
TPP
TSS
TVS
TWINSPAN
UPMGA
USDA CSREES
USGS
Total Maximum Daily Loads
Total Organic Carbon
Total Particulate Carbon
Total Particulate Nitrogen
Total Particulate Phosphorus
Total Suspended Solids
Total Volatile Sulfides
Two-Way INdicator SPecies ANalysis
Unweighted Pair Group Mean Averages
United States Department of Agriculture Cooperative State
Research Education Extension Service
United States Geological Survey
XXVII
Acronym List
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Executive Summary
This technical guidance document is
based on the concept that bioassessment
and biocriteria programs for estuaries
and near coastal waters are interrelated
and critical components of
comprehensive water resource
protection and management.
Understanding how estuarine
ecosystems function and respond to
human activity requires a holistic
approach to protection and management
that integrates biological assessments
into the more traditional chemical and
physical evaluations. Section 101 of the
Clean Water Act requires federal and
state agencies to "restore and maintain
the chemical, physical, and biological
integrity of the nation's waters."
Relatively undisturbed aquatic
ecosystems have high biological integrity,
defined as
the condition of an aquatic
community inhabiting unimpaired
waterbodies of a specified habitat as
measured by an evaluation of
multiple attributes of the aquatic
biota. Three critical components of
biological integrity are that the biota
is (1) the product of the evolutionary
process for that locality, or site, (2)
inclusive of a broad range of
biological and ecological
characteristics such as taxonomic
richness and composition, and
trophic structure, and (3) is found
in the study bio geographic region
(USEPA19963)1
In water resource monitoring and
protection, biological criteria are an
important addition to the traditional
physical and chemical criteria used by
EPA. The relative biological integrity, or
quality, of the resource can be assessed
by comparing the health and diversity of
its biological communities to the health
and diversity of biological communities
in waters with the same physical
characteristics but which are relatively
unimpacted by human development.
There are basically four elements that
comprise biocriteria:
1. Reference waters (relatively
undisturbed areas that can be
compared to study areas) serve
as "benchmarks" of water
resource quality decision
making.
2. The historical record of the
biological quality, diversity and
productivity.
3. Model projection of the
historical and reference
condition data (if necessary).
4. The objective assessment of this
information by a regional panel
of specialists such as state,
1 Biological criteria: Technical guidance for streams and small rivers. EPA 822-B-
96-001. U.S. Environmental Protection Agency, Office of Water, Washington, DC.
XXIX
Executive Summary
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academic, and federal estuarine
ecologists, chemists, fisheries
biologists, oceanographers, and
resource managers.
The summation of these four factors is
the biological criterion for a given
estuary or class of coastal water in a
geographic region. Examples of the
parameters included in a biocriterion are
community measures or indexes drawn
from dynamic assessments of resident
fish, benthic invertebrate, macrophyte,
and planktonic assemblages making up
the biological community.
Many natural resource agencies
throughout the United States have
begun the process of developing and
implementing bioassessments and
criteria programs primarily for rivers
and streams. This document is part of
the effort to advance the use of these
strategies with regard to estuaries and
near coastal waters, thereby fostering
the development of credible and
practical bioassessment programs. This
document is intended to provide
managers and field biologists with
functional methods and approaches for
bioassessment and biocriteria
development.
In developing biological information, it
is imperative that the physical and
chemical habitat be carefully measured
and documented. Information such as
salinity, depth, sediment grain size, and
water quality (including pH,
temperature, DO, nutrients, and
toxicants) is essential to proper
classification of the waters for
comparison and to the potential
subsequent investigation of possible
causes of degradation so that
responsible management can be
initiated.
This guidance provides detailed
descriptions of the appropriate habitat
measurements to make the subsequent
physical classification to be achieved.
The document then describes four levels
of investigative intensity or sampling
tiers. These tiers are suggested as one
possible approach to organizing the data
gathering efforts and investigation
needed to be able to establish biocriteria
in a scientifically defensible manner.
Other approaches using variations of
these tiers may be appropriate
depending on program objectives.
> Tier 0 is a preliminary review of
existing literature and data available
for the estuary or coastal water of
concern. It provides candidate
reference sites for the development
of a reference condition;
> Tier I is a one-time site visit with
preliminary data gathering to refine
the information in Tier 0 and
establish candidate biocriteria;
> Tier II repeats and builds on
measurements initiated in Tier I and
establishes the reference condition
data which is combined with the
historical record, possible models or
other extrapolations, and a
consensus of regional expert opinion
to establish and employ the
biocriteria for management decision
making;
*• Tier III is the diagnostic
investigation requiring the most
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
xxx
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sampling events and most extensive
parameters to help establish
management efforts for those waters
which do not meet the biocriteria.
Biocriteria development is not a one size
fits all proposition. Biocriteria can be
developed on biogeographical province
basis or on a smaller local basis to
account for the geographic, climatologic,
and biologic variation in the country.
Reference conditions and biocriteria
must be specific to each part of the
country in order to be responsive and
useful for decision making. It is
important to remember that such
circumstances vary and that this
document cannot address every
situation or experience. It is oriented
toward practical decision making rather
than research. Its primary audience is
intended to be state and tribal resource
managers. It is also intended to provide
managers and biologists with functional
methods and approaches to facilitate the
implementation of viable bioassessment
and biocriteria programs that meet their
individual needs and resources.
Biocriteria can be used to help support
and protect designated uses of water
resources; expand and improve water
quality standards; detect problems other
water quality measurements may miss
or underestimate; help water resource
managers set priorities for management
planning and, assess the relative success
or failure of management projects.
Biocriteria do not supersede or replace
physical or chemical criteria for water
resource decision making and
management. In fact biocriteria
augment these established measures so
USEPA and the States and Tribes are
better informed about the quality of our
nations extensive and coastal water
resources. The bioassessment/
biocriteria process is a particularly cost
effective screening tool to evaluate over
all water quality and determine water
resource status and trends. The
following table shows the progression of
the biocriteria process.
XXXI
Executive Summary
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Sequential progression of the biocriteria process. Adapted from
Paulsen etal. 1991.
Step 1
Preliminary Classification to Determine Reference Conditions and
Regional Ecological Expectations
• Resource classification
• Determination of best representative sites (reference sites representative
of class categories)
Step 2
Survey of Reference Sites and Selected Impaired Sites
• Collection of data on biota and physical habitat
• Compilation of raw data (taxonomic lists, abundance levels, and other
direct measures and observations)
Step 3
Final Classification
• Test preliminary classification
• Revise if necessary
Step 4
Metric Evaluation and Index Development
• Data analysis (data summaries)
• Testing and validation of metrics by resource class
• Evaluation of metrics for effectiveness in detecting impairment
• Selection of biological endpoints
• Aggregation of metrics into index.
• Test the index for validity on another data set.
Step 5
Biocriteria Development
• Adjustment by physical and chemical covariates
• Adjustment by designated aquatic life use
Step 6
Implementation of Monitoring and Assessment Program
• Determination of temporal variability of reference sites
• Identification of problems
Step 7
Protective or Remedial Management Action
• Initiate programs to preserve exceptional waters
• Implement management practices to restore the biota of degraded
waters and to identify and address the causes of this degradation
Step 8
Continual Monitoring and Periodic Review of References and Criteria
• Biological surveys continue to assess efficiency of management efforts
• Evaluate potential changes in reference condition and adjust biocriteria
as management is accomplished
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
XXXII
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Chapter 1
Introduction: Bioassessment
and Biocriteria
1.1 Rationale
1.1.1 Water Quality Monitoring
The recognition that chemical water
quality analyses do not adequately
predict or reflect the condition of all
aquatic resources has led to the
development of measures of biological
integrity expressed by biological criteria.
Biological surveys, criteria, and
assessments complement physical and
chemical assessments of water quality by
reflecting the cumulative effects of
human activities, and natural
disturbances on a water body, including
the possible causes of these effects. The
biological approach is best used for
detecting generalized and non-specific
impairments to biological integrity, and
for assessing the severity of those
impairments. Then, chemical and
toxicity tests, and more refined habitat
assessments, can be used to identify
probable causes and their sources, and to
suggest corrective measures.
For the purposes of bioassessment and
biocriteria development described here,
an estuary is a semi-enclosed water body
that has a free connection with the open
sea and an inflow of freshwater that
mixes with the seawater; including
fjords, bays, inlets, lagoons, and tidal
rivers. Coastal marine waters are those
marine waters adjacent to and receiving
estuarine discharges and extending
seaward over the continental shelf
and/or the edge of the U.S. territorial
sea.
1.1.2 Advantages of Bioassessment
and Biocriteria
Bioassessment is intended to detect
biological responses to pollution and
perturbation. Routine water quality
monitoring for example, detects effects
of nutrient enrichment and chronic
acidification, but normally is not
designed to detect trace levels of
toxicants or contaminants, ephemeral
pollution events (e.g., acidic episodes,
spills, short-lived toxicants and
pesticides, short-term sediment loading),
or combined or synergistic impacts.
Bioassessment, by monitoring organisms
that integrate the effects of
environmental changes, may in time
detect these effects.
Bioassessment, coupled with habitat
assessment; i.e., physical and chemical
measurements, helps identify probable
causes of impairment not detected by
physical and chemical water quality
analyses alone, such as nonpoint source
pollution and contamination, erosion, or
poor land use practices. The detection
of water resource impairment,
accomplished by comparing biological
assessment results to the biological
criteria, leads to more definitive
chemical testing and investigations
which should reveal the cause of the
degradation. This, in turn, should
prompt regulatory and other
management action to alleviate the
problem. Continued biological
monitoring, with the data collected
compared to the criteria, will determine
the relative success of the management
efforts.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-1
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1.2 Legal Origins
1.2.3 301 (h) and 403(c) Programs
1.2.1 Clean Water Act
The CWA, Section 101, requires federal
and state governments to "restore and
maintain the chemical, physical, and
biological integrity of the nation's
waters." Thus, the Act mandates the
restoration and maintenance of
biological integrity in the Nation's
waters. The combination of performing
biological assessments and comparing
the results with established biological
criteria is an efficient approach for
evaluating the biological integrity of
aquatic ecosystems. Other pertinent
sections of the CWA are Sections 305(b),
301(h), and 403(c). Table 1-1 outlines
suggestions for the application of
biological monitoring and biocriteria for
estuaries through existing state programs
and regulations.
1.2.2 305(b) Reporting
States and the USEPA report on the
status and progress of water pollution
control efforts in §305(b) reports
submitted every two years. Inclusion of
biological assessment results in these
reports will improve the public
understanding of the biological health
and integrity of water bodies. Many of
the better known and widely reported
recoveries from pollution have involved
the renewal or reappearance of valued
species to systems from which they had
nearly disappeared, or the recovery of a
viable fishery from contaminants.
Examples of such recoveries are the
restoration of the lower Potomac River
and of shellfish beds in Maine.
Incorporation of biological integrity in
§305(b) reports will ensure the inclusion
of a bioassessment endpoint, and will
make the reports more accessible and
meaningful to many segments of the
public.
Two other programs within USEPA that
specifically rely on biological
monitoring data in coastal marine areas
are the §301(h) Waiver Program and the
§403 (c) Ocean Discharger Program. The
§301 (h) program allows estuarine and
marine dischargers who meet specific
criteria set forth by USEPA to defer
secondary treatment if they can show
that their discharge does not produce
adverse effects on resident biological
communities. As part of the modified
NPDES permit received through this
waiver program, the dischargers are
required to conduct extensive biological
monitoring programs designed to detect
detrimental effects to those biological
communities.
The §403(c) Ocean Discharge Program
requires that all dischargers to marine
waters provide an assessment of
discharge impact on the biological
community in the area of the discharge
and on the surrounding biological
communities. This program requires
extensive biological monitoring for some
dischargers. Community bioassessment
methods are valuable in this program
for trend assessment and, in some cases,
refinement into more rigorous and
definitive assessments.
1.2.4 304(a) Criteria Methodology
This technical guidance was developed
under the §304(a) requirement that,
"criteria for water quality accurately
reflecting the latest scientific knowledge
of the kind and extent of all identifiable
effects on health and welfare including,
but not limited to, plankton, fish,
shellfish, wildlife, plant life, shorelines,
beaches, aesthetics, and recreation
which may be expected from the
presence of pollutants in any body of
1-2
Introduction - Bioassessment & Biocriteria
-------
water . . ." be published and updated as
needed.
Under this section, a guidance document
must include information on restoration
and maintenance of chemical, physical,
and biological integrity of navigable and
ground waters, waters of the contiguous
zone, and the ocean. This also covers
information identifying conventional
pollutants, such as those classified as
biological oxygen demanding,
Table 1-1. Applications of estuarine biological monitoring protocols and biocriteria.
Program
Biological Monitoring and
Assessment
Biological Criteria
Section 305(b)/
Reporting
Improving data for beneficial use
assessment.
Improving water quality reporting.
Identifying waters that are
not achieving their aquatic
life use support.
Defining an understandable
endpoint in terms of
"biological health" or
"biological integrity" of
waterbodies."
National Estuary
Program (NEP)
Assessing status of biological
components of estuarine systems.
Develop monitoring objectives and
performance criteria.
Establish testable hypothesis and
select statistical methods.
Assessing estuarine trophic status
and trends, and assessing
biological trends.
Select analytical methods &
alternative sampling designs.
Evaluate expected monitoring study
performance.
Implement monitoring study & data
analysis. [Monitoring and sampling
needs vary for each estuary]
Identifying estuaries that are
not attaining designated use
(including aquatic life use)
support.
Defining estuarine biological
integrity based on a
reference condition.
Identifying impairments due
to toxic substances,
eutrophication, and habitat
modification.
Section
319/Nonpoint
Source Program
Evaluating nonpoint source impacts
and sources.
Measuring site-specific ecosystem
response to remediation or
mitigation activities.
Assessing biological resource
trends within watersheds.
Determining effectiveness of
nonpoint source controls.
Watershed
Protection
Approach
Assessing biological resource
trends within watersheds.
Setting goals for watershed
and regional planning.
TMDLs
Identifying biological assemblage
and habitat impairments that
indicate nonattainment of water
quality standards.
Priority ranking waterbodies.
Documenting ecological/water
quality response as a result of
TMDL implementation.
Identifying water
quality-limited waters that
require TMDLs.
Establishing endpoints for
TMDL development, i.e.,
measuring success.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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Table 1-1 (cont'd). Applications of estuarine biological monitoring protocols and biocriteria.
Program
Biological Monitoring and
Assessment
Biological Criteria
NPDES Permitting
Measuring improvement or lack of
improvement of mitigation efforts.
Developing protocols that
demonstrate the relationship of
biological metrics to effluent
characteristics.
Performing aquatic life use
compliance monitoring.
Helping to verify that
NPDES permit limits are
resulting in achievement of
state water quality standard.
State Monitoring
Programs
Improving water quality reporting.
Documenting improvement or lack
of improvement of mitigation efforts
including estuary clean-up efforts,
TMDL application, NPDES efforts,
nonpoint source pollution controls,
etc.
Problem identification and trend
assessment.
Prioritizing waterbodies.
Providing a benchmark for
measuring effectiveness of
controls and performing
watershed/regional
planning.
Risk Assessment
Providing data needed to estimate
ecological risk to assessment
endpoints.
Providing an assessment or
measurement endpoint.
Water Quality
Criteria and
Standards
Developing data bases for estuarine
phytoplankton, macro invertebrates,
fish, plants, and other
assemblages.
Developing indices that assess
estuarine biota compared to a
reference.
Providing data for aquatic life use
classifications.
Providing benchmark for
identifying waterbodies that
are not attaining aquatic life
use classification.
Developing site-specific
standards.
Section 301(h)/
Waiver Program
Allows marine discharges who meet
USEPA criteria to defer secondary
treatment if discharge does not
produce adverse effects on resident
biological communities.
Providing threshold against
which to measure
detrimental effects on
biological communities.
Section
403(c)/Ocean
Discharge Program
Requires marine dischargers to
provide an assessment of
discharge impact on biological
community in discharge area as
well as surrounding communities.
Providing threshold against
which to measure
discharger impacts on
biological communities.
Section 304(a)/
Criteria
Methodology
Provides information on restoration
and maintenance of chemical,
physical, and biological integrity of
waters.
Identifies conventional pollutants,
their concentrations and effects on
surrounding communities.
Providing the benchmark for
measuring the effects of
pollutants on the biological
community.
1-4
Introduction - Bioassessment & Biocriteria
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suspended solids, fecal coliform, and pH.
Section 304(a)(8) authorizes USEPA to
develop and publish methods for
establishing and measuring water
quality criteria for toxic pollution, on
other bases than a pollutant by pollutant
approach. This includes biological
monitoring and assessment methods.
Specific states have the authority to
enforce more stringent regulations as
necessary.
1.2.5 Biocriteria
A major purpose of developing
biological assessment methods is to
establish biological criteria for surface
waters. Biological criteria are guidelines
or benchmarks adopted by states to
evaluate the relative biological integrity
of surface waters. The criteria are
defined as "narrative expressions or
numerical values that describe the
biological integrity of aquatic
communities inhabiting waters of a
given designated aquatic life use"
(USEPA 1990). Biological criteria are, in
effect, a practical approach to
establishing management goals designed
to protect or restore biological integrity.
Biocriteria can be adopted by a State into
their water quality standards, along with
chemical, physical and toxicity criteria to
better protect aquatic life uses of
waterbodies.
Biocriteria can be developed from
reasonable expectations for the locality
based on: historical data; reference
conditions; empirical models; and the
consensus judgment of regional experts
(Section 1.4.2). The reference condition
component of biocriteria requires
minimally impaired reference sites
against which the study area may be
compared. Minimally impaired sites are
not necessarily pristine; they must,
however, exhibit minimal influence by
human activities relative to the overall
region of study (USEPA 1996a). In some
instances, "minimally impaired" sites
are not available because the entire area
has been degraded. Biocriteria are then
based on historical data, empirical
models if appropriate, and expert
judgement to set a condition better than
present sites. Restoration of the
degraded area must therefore be
accomplished before any such reference
sites can be established.
Biological criteria typically include the
condition of aquatic communities at
designated reference sites as an
important component. The conditions
of aquatic life found at these sites are
used to help detect both the causes and
levels of risk to biological integrity at
other sites of that type in a region. In
keeping with the policy of not
degrading the resource, the reference
conditions — like the criteria they help
define — are expected to be upgraded
with each improvement to the water
resource. It is important that biological
criteria not be based on data derived
from degraded reference sites. In fact, a
concerted effort should be made by
States and other jurisdictions to preserve
the quality of designated reference sites
by setting those areas aside in preserves
or parks or by inclusion in use
protection programs so that continuity
of the biocriteria data base can be
maintained. Biocriteria supported by
bioassessment surveys serve several
purposes in surface water programs,
discussed in the following section.
1.3 Uses of Biocriteria
The biocriteria-bioassessment process
helps resource managers identify
impairment of designated beneficial
uses. It expands and improves
designated beneficial use classifications
and their associated water quality
standards. It detects problems other
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-5
-------
survey methods may miss or
underestimate. It is a process which
helps the resource manager set program
priorities. It can also be used to evaluate
management and regulatory efforts. For
example, the information summarized in
Table 1-2 indicates that wastewater
outfalls are a controlling factor of soft
bottom benthic communities and that
there is a moderate scientific
understanding of the effects of these
outfalls specifically in the Southern
California Bight (USEPA 1992).
1.3.1 The Use of Bioassessment Data
to Establish Biocriteria
Appropriate to Designated
Beneficial Uses
The hypothetical information presented
in Figure 1-1 represents data collected for
a given class of similar estuarine or
coastal reaches (e.g., similar sediments,
depths, and salinities) within the same
geographic region. For these areas some
high level of resource quality can be
conceived which represents a pristine
condition, essentially the optimum
potential or integrity of those waters. A
completely unimpaired (no negative
human impacts upon the organisms of
the natural system) estuary or coastal
marine area is referred to as having
biological integrity. The approximation
of this ideal quality at the top of a
continuum can be expressed by a variety
of environmental measures of the biota
indicated on the vertical axis of the
graph. The determined ideal level of
biological measurements at the
maximum score is shown by the upper
horizontal line (equivalent to biological
integrity). A second horizontal line
somewhat below this is the level set as
the reference condition, the attainable
level of integrity derived from actual
measurements from among the highest
quality areas in the class. All
information on this axis is expected to be
objectively derived through the scientific
process and usually is presented in a
comprehensive index of many biological
characteristics such as an IBI or the
EMAP benthic index (Chapter 11).
The horizontal axis represents a
progression of socially determined use
designations; i.e., those predominant
uses the State has concluded are
appropriate for a particular estuary,
region or area within the class. These
hypothetical designated uses are
arranged on the graph from those
usually associated with relatively low
water resource quality on the left, to
those associated with very high,
relatively natural, resource quality on
the far right.
The potentially optimal array of
biological criteria for this class of
waters, then, are scores between the
reference condition and the level of
biological integrity; i.e., between that
which is achievable and that which is
ideal. The narrower this area, the higher
the quality of the waters throughout the
class, and the less restoration
management is required. The objective,
then, is to protect these resources.
On the same horizontal axis, a class of
high quality regional uses are further
described by a subset of aquatic life
uses. These are the designated uses for
which management goals are also
described by desirable characteristics of
the aquatic biota to be especially
protected, such as "protection of the
health and diversity, undiminished, of
all indigenous species of fish and
invertebrates" for those designated as
exceptional natural waters. Resource
managers need to apply their first,
concerted efforts to those uses because it
is usually more cost-effective and
resource-conservative to protect existing
high quality areas than it is to restore
degraded ones.
1-6
Introduction - Bioassessment & Biocriteria
-------
Table 1-2. Impacts on the marine environment of the Southern California Bight. Modified from
Bernstein et al. 1991.
Valued Ecosystem Components
Sources of
Perturbation
Storms
El Ninos
California Current
Upwelling
Blooms/Invasions
Ecol. Interactions
Power Plants
Wastewater Outfalls
Dredging
Rivers/Storm Runoff
Commercial Fishing
Sport Fishing
Habitat Loss/Mod.
OilSoills
All
ertidal
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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-7
-------
Figure 1-1
Biocriteria for
given
classifications of
estuaries and
coastal marine
areas. Shaded
boxes represent
the appropriate
biocriterion range
for selected
classes.
Unshaded boxes
represent the
range of
measurement
results for test
sites in given
classes. The
vertical arrows
above the boxes
for the
"significantly
altered estuaries
and coastal marine
areas" class
indicate the goal of
raising the
biocriterion for
these waters over
time in response to
restoration efforts.
HIGH
LOW
Range of Biological Criteria
• Reference Condition
A A
Altered Estuaries
and Coastal
Marine Areas
Harbor Shipping Channel
(Meets or Exceeds)
Protected for
Particular
Fisheries
Exceptional
Natural
Estuaries
OTHER DESIGNATED USES AQUATIC LIFE USES HIGH
DESIGNATED USES (SOCIAL)
Selected biocriteria with an acceptable
range of variation, perhaps one standard
deviation, are shown as cross hatched
boxes appropriately located for each
designated use. Test results for a given
area in any use classification Cbox and
whisker"plots showin g the full range of
measurements including variation for
that area) can then be compared
graphically to the biocriterion for that
designated use. Three interpretations of
an estuarine or coastal marine area meets
its criterion, meets or perhaps even
exceeds its criterion, and fails to meet the
criterion are illustrated.
A fourth possible result is the marginal
condition of significantly altered systems
such as urban harbors or shipping
channels. The original condition of these
areas may very well have been within
the optimal range of biotic health and
diversity for the region, but intense
development has significantly altered
them so that as a group they no longer
meet the minimum reference condition
for similar areas of the region. An
interim biocriterion for these areas may
be set with the intention of progressively
raising the criterion when sequential
restoration efforts are accomplished
through a long range management
effort.
The "other desi gnated uses"to the left
of the bifurcation line may still be
surveyed to assist management decision
makers; however, they fail to meet the
criteria, and there are no designated
aquatic life uses which apply.
The designated uses, aquatic life uses
and biocriteria are all hypothetical in
this illustration, but the
interrelationships of societal and
scientific elements of decision making
should be evident. They are
independent processes linked by an
environmental ethic and the USEPA
policy of antidegradation of water
resource quality (the reference condition
'bottom line"so to speak). A rational
decision can be made which balances
that which is ideal with that which is
1-8
Introduction - Bioassessment & Biocriteria
-------
achievable measured by the objective
processes of science.
1.3.2 Expansion and Improvement of
Water Quality Standards
When a State adopts biological criteria in
their water quality standards to protect
aquatic life uses, the criteria become
benchmarks for decision making, and
may form the basis for requirements in
NPDES permits and other regulatory
programs.
1.3.3 Detection of Problems Other
Methods May Miss or
Underestimate
In the process of establishing biocriteria,
more data and information is inevitably
developed than was previously
available. The review of this new
information often reveals problems not
evident before or provides expanded
insight into existing concerns and issues.
Armed with this information, a water
resources manager is better able to
examine issues and make decisions.
1.3.4 Helping the Water Resource
Manager Set Priorities
In light of the new information described
above, the schedule of activities,
allocation of funds, and uses of
personnel and equipment may be more
appropriately prioritized according to
the urgency or magnitude of the
problems identified.
With the expanded available biological
information augmenting chemical and
physical information, managers can
apply a triage approach to water
resource projects based on the actual
condition of the biota affected. This is
much like a physician evaluating
multiple emergency medical patients.
Essentially, areas that are critically
impaired, those that are moderately
impaired, and those in good condition
for which protection rather than
remediation is required, can all be
identified. Rational decisions can then
be made about how to apply limited
resources for the best results in
accordance with the needs and priorities
of the state.
1.3.5 Use of Biosurveys and
Biocriteria to Evaluate the
Success or Failure of
Management Initiatives or
Regulations
The manager may design a biosurvey to
collect data before and after a permit,
regulation or other management effort
has been implemented, perhaps
augmented by spatially distributed
nearfield/farfield sampling as well.
With this information and the biocriteria
decision making benchmark, it is
possible to clearly evaluate the
environmental response of the system to
the methods applied. This is useful in
the NPDES permit review process as a
way to help determine the effectiveness
of permit controls. Typically, biocriteria
are not used directly in NPDES permits
as effluent limitations. Biomonitoring
above and below a permit site when
compared to the established biocriteria
will reveal the adequacy of the permit to
achieve its intended purpose.
If the biota are unimpaired or
recovering, it may be wise to leave the
permit, management practice or
regulation as is. If the biota are
impaired or declining, the review
recommendation may be to change the
permit, management technique or
regulation accordingly. With NPDES
permits, the five year review cycle
allows sufficient time for extensive
biological information to be developed
so this determination can be made with
reasonable confidence.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-9
-------
1.4 Program Interdependence
It should be readily evident from the
applications described above that
physical, chemical, and biological
surveys and monitoring (repetitive
surveys of the same area) and biological
criteria are interrelated in the water
resource management process. Figure 1-2
illustrates this interrelationship, often
referred to as "adaptive management."
In this continually cycling process,
monitoring provides the information
necessary to identify problems and to
establish biocriteria for the decision
making, management planning, and
implementation necessary to respond
appropriately. Continued monitoring
then reveals the relative success of the
effort by comparing the new results to
those criteria again. At this point the
criteria or the management plan may be
adjusted as needed and the cycle repeats.
Ideally, the estuarine or coastal
waters improve with each cycle.
Figure 1-2
Program
Interdependence
1.5 Implementing Biological
Criteria
Implementing biocriteria requires an
established and standardized
methodology for biological assessment
adjusted to regional or state conditions.
Hence, guidance for state and regional
development of biocriteria has two
elements which are described in the
biological criteria technical guidance
documents such as this one:
*• Bioassessment Protocols are
methods used to assess the status
and trends of water bodies.
Guidance documents for
bioassessment contain suggested
methods and protocols for
establishing monitoring programs
that use biological assessment.
*• Biocriteria Guidance assists states
in establishing biological criteria for
water bodies. Biocriteria are a series
of ambient water resource quality
values or statements of condition
that relate to the desired biological
integrity for that class of waters.
When established they can be used
to evaluate similar water bodies in
that region. Implementation of
biocriteria requires use of
bioassessment protocols and a state
or regional biomonitoring database.
The National Program Guidance for
biocriteria describes issues related to
development and implementation
(USEPA1990). The first biocriteria
technical guidance issued was for
streams and small rivers (USEPA
1996a). It incorporated both
biosurvey techniques and biocriteria
development methods. It was
followed by the Lakes and Reservoir
Bioassessment and Biocriteria
Guidance (USEPA 1998). Each of
these documents incorporated
biosurvey techniques and the same
approach is being followed in
similar documents for rivers,
wetlands, and coral reefs in addition
to this present technical guidance
for estuaries and coastal marine
waters.
1-10
Introduction - Bioassessment & Biocriteria
-------
1.6 Characteristics of
Effective Biocriteria
Generally, effective biocriteria share
several common characteristics:
> Provide for scientifically sound, cost-
effective evaluations;
*• Protect sensitive biological values;
*• Protect healthy, natural aquatic
communities;
*• Support and strive for protection of
chemical, physical, and biological
integrity;
*• May include specific characteristics
required for attainment of
designated use;
*• Are clearly written and easily
understood;
*• Adhere to the philosophy and policy
of nondegradation of water resource
quality;
*• Are defensible in a court of law.
In addition, effective biocriteria are set at
levels sensitive to anthropogenic
impacts; they are not set so high that
sites that have reached their full
potential are considered as failing to
meet the criterion, nor so low that
unacceptably impaired sites are rated as
meeting them, which defeats the purpose
of the CWA. The establishment of
formal biocriteria warrants careful
consideration of planning, management,
and regulatory goals and the best
attainable condition at a site. Balanced
biocriteria will allow multiple uses to be
considered so that any conflicting uses
are evaluated at the outset. The best
balance is achieved by developing
biocriteria that closely represent the
natural biota, protect against further
degradation, and stimulate restoration
of degraded sites.
Developing and implementing
biological criteria occurs in three steps
(USEPA1996a):
1. Planning the biocriteria
development program, including:
• definition of program objectives;
• establishment of interagency
cooperation;
• identifying acceptable levels of
uncertainty for decisions made
on the basis of biocriteria;
• establishing data quality
objectives.
2. Characterizing reference conditions
for biocriteria and identifying
candidate reference sites, which may
require a biological survey.
3. Establishing biocriteria based, in
part, on characterized reference
conditions and designated use
classes of the state.
1.7 Conceptual Framework
The central principle of biological
assessment is comparison of the
biological resources of a water body to a
biological criterion based, in part, on a
reference condition. Impairment of the
water body is judged by its departure
from the biocriteria. This approach
presumes that the purpose of
management is to prevent and repair
anthropogenic; i.e., human-induced,
damage to natural resources. Biological
assessment of water bodies is predicated
on our ability to define, measure, and
compare biological integrity between
similar systems. This requires an
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-11
-------
operational definition of biological
integrity as follows:
"...the condition of the aquatic
community inhabiting
unimpaired water bodies of a
specified habitat as measured by
community structure and
function (USEPA1990)."
The functional definition also requires
definitions of "unimpaired" and
"community structure and function", and
the habitat must be specified.
Community structure and function is
operationally defined by the biological
measures chosen for bioassessment,
consisting primarily of measures of
species richness, trophic diversity
(relative numbers of herbivores and top
carnivores), and indicator species. In
addition to biological community
structure and function, chemical (DO,
salinity, contaminants, dissolved TOC,
inorganic nitrogen, etc.) and physical
(sediment composition) attributes are
measured to define an unimpaired site.
The combined attributes form the basis
for defining reference conditions for
biological criteria. When unimpaired
water bodies do not exist within a
region, an operational definition of
unimpaired can be developed from a
combination of minimally impaired
estuaries and coastal waters, historical
information, and professional judgment
(Section 1.7.2). Figure 1-3 shows a
simplified framework for progressing
from an estuarine classification to
assessing the health of the estuary.
1.7.1 Indicators of Biological
Integrity and Survey Protocols
Several analytical approaches have been
developed to assess the biological
condition of waterbodies within the
framework of comparison to reference,
ranging in complexity from simple
comparison of indicator values, to
development of multivariate models:
*• Comparison of indicator values —
Indicator of metric values can be
compared directly to the reference
condition, without development of
an index. This has been used most
often for paleoecological
comparison, where biological
indicators are limited to certain
indicator species, deposition rates,
organic carbon loss, etc. (Turner and
Rabalais 1994, Sen Gupta et al. 1996,
Cooper and Brush 1991, Latimer et
al. 1997).
*• Multimetric index — The
multimetric approach is to define an
array of metrics or measures that
individually provide limited
information on biological status, but
when integrated, function as an
overall indicator of biological
condition. Metrics incorporate
information from individual,
population, and community levels
into a single, ecologically-based
index of water resource quality
(Gray 1989, Plafkin et al. 1989, Karr
1991). The index is typically a sum
or an average of standardized scores
of its component metrics (Barbour et
al. 1999). Developed initially for
streams, the multimetric approach
has increasingly been applied to
estuaries (Weisberg 1997, Hyland et
al. 1998).
*• Discriminant analysis to develop an
index from metric values — In this
approach, metrics (calculated as
above) are used to develop a
multivariate discriminant analysis
model to distinguish reference sites
from impaired sites. The calibrated
model is then applied to assessment
sites to determine whether they are
impaired. This approach was used
in EMAP-Near Coastal for the
1-12
Introduction - Bioassessment & Biocriteria
-------
Estuarine Class
Designation
*
TierO
Historical Data
Review
*f*^ ^ ""*
Tier 1 Tier 2
Sampling Sampling
\, v
^S,^ Evaluation and
Calibration of Metrics
and other Indicators
<^ggregatior£>
,/ Biocriteria iS.
/ Relative to J>
N^Estuary Clasa/
Assessment
of Sites
•*>k
TierS
Sampling
^x"
s
Figure 1-3
The process
for progressing
from the
classification
of an estuary
to assessing
the health of
the estuary.
Adapted from
Pauisen et al.
1991.
Virginian and Gulf provinces (Paul
et al. 1999, Engle et al. 1999).
*• Multivariate ordination
approaches — Several approaches
have been developed using
rnultivariate ordination to examine
differences in species composition
between reference and impaired
sites. The purpose of ordination
analysis is to reduce the complexity
of many variables (for example,
abundances of over 100 species from
many estuarine sites), by re-ordering
the information into fewer variables.
These approaches have been used to
show the effects of oil drilling in the
North Sea (Warwick and Clarke
1991), and to develop an index of
benthic quality in California (Smith
et al. 2000).
While all of these approaches are
appropriate to biocriteria development
when properly applied, the multimetric
approach is highlighted in this
guidance. This is because it is the best
developed and most extensively used
method to date. Investigators should
carefully consider what is most
appropriate for their specific program.
Time and experience will ultimately
determine the best approach or
combination for each state to use.
Chapter 11 goes into further detail about
methods of classification and assessment
using all three approaches.
The multimetric concept came to fruition
with the fish Index of Biotic Integrity
(IBI) first conceived by Karr (1981). The
IBI aggregates various elements and
surrogate measures of process into a
single assessment of biological
condition. Karr (1981) and Karr et al.
(1986) demonstrated that combinations
of these attributes or metrics provide
valuable synthetic assessments of the
status of water resources.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-13
-------
A metric is a calculated term or
enumeration representing some aspect of
biological assemblage structure,
function, or other measurable
characteristic. Similarly, each of the
assemblages (e.g., fish, benthic
macroinvertebrates composing the
aquatic community) measured would be
expected to have a response range to
perturbation events or degraded
conditions. Thus, biosurveys targeting
multiple species and assemblages; i.e.,
multimetric, will likely provide detection
capability over a broad range of impacts,
and the biocriteria derived from their
results could provide protection to a
large segment of the ecosystem.
Metrics can be expressed numerically as
integers or ratios. Consistent routines in
normalizing individual metric values
provide a means of combining metric
scores which initially consisted of
dissimilar numerical expressions.
However, final decisions on impact/no
impact or management actions are not
made on the single, aggregated value
alone. Rather, if comparisons to
established reference values indicate an
impairment in biological condition,
component parameters (or metrics) are
examined for their individual effects on
the aggregated value and for indications
of potential causes.
Assessment of biological integrity using
this multimetric approach typically
focuses on four broad classes of
community properties. Ecological
systems respond to anthropogenic
impacts with changes in one or more of
these classes of properties (e.g., Karr et
al. 1986, Schindler 1988, Plafkin et al.
1989, Schindler et al. 1989, Karr 1991,
Barbour et al. 1992). The four properties
are:
Health of populations, typically
expressed as number of individuals
per m2 or as biomass, reflecting
possible stress from anthropogenic
sources;
*• Community structure and
composition, or the number and
kinds of species in an assemblage.
Exotic species are typically
undesirable, and high diversity is
usually desirable. Species structure
metrics include diversity and
evenness indexes as well as presence
of indicator species, counts of
tolerant or intolerant species, the
percentage of individual taxa in
comparison to the total number
sampled, and abundance
proportions of taxonomic groups
(e.g. crustaceans, mollusks,
polychaetes), or comparisons of
infauna vs. epifauna;
*• Trophic structure, or the relative
proportion of different trophic levels
and functional feeding groups (e.g.,
Barbour et al. 1992). In estuaries,
abundant, diverse, and relatively
large top carnivores (e.g.,
piscivorous fish) are typically
desirable as representative of a
broad, stable, and substantial
trophic network;
*• System function, or the
productivity and material cycling of
the system or its components
(trophic levels, assemblages,
species). Measures of system
function include primary
production and standing stock
biomass.
Since biological integrity is defined as an
indicator of undisturbed conditions, it
too must be measured relative to those
conditions. The requirement of the
biological criteria process for a reference
by which to measure biological integrity
makes it a practical tool (sensu Peters
1991) for managing society's impact on
the natural environment.
1-14
Introduction - Bioassessment & Biocriteria
-------
Monitoring and assessment programs
typically do not have the resources to
measure all ecological attributes of
concern to the public and to managers,
and assessment tools must be cost-
effective. Ideally, metrics selected for
monitoring must be scientifically valid;
should not require large amounts of
expensive equipment; and should be
relatively rapid in the field. The selected
variables must be:
*• Related to Biological Integrity In
general, almost any biological
measurement is related to biological
integrity, but some are more clearly
tied to the properties of biotic
systems of concern to society (e.g.,
native species, fish production,
diverse trophic structure) (Suter
1993);
*• Responsive to Environmental
Stresses Biological measurements
and the metrics developed from
them must respond to environmental
stress. Metrics that are not
monotonic; i.e., they do not
consistently exhibit low values in
response to one end of a stressor
continuum and high values in
response to the opposite end, or that
respond oppositely to different
stresses, are difficult to interpret in
practice;
*• Measurable with Low Error
Variability and measurement error
should be controllable so that a
reasonable sampling effort yields
sufficient precision. Index period
sampling; i.e., sampling during
specific time periods in the annual
cycle, is one way to reduce seasonal
variability. However, there are costs
in terms of information derived
which may be prohibitive (see later
discussion on seasonality);
> Cost-effective Cost of a metric
should be proportional to the value
of the information obtained.
Usually, the simplest approach is
most cost-effective and should be
selected so long as results are
sufficient to the agency's objectives;
> Environmentally Benign to
Measure Sampling methods that
significantly disturb or alter habitats
and biota should be avoided.
1.7.2 Comparison to a Reference
As noted earlier, establishing biocriteria
includes determining the reference
condition. The reference condition
establishes the basis for making
comparisons and for detecting use
impairment. Because absolutely pristine
estuarine and coastal marine habitats
probably do not exist, resource
managers must decide on acceptable
levels of minimum impacts that exist or
that are achievable in a given region.
Acceptable reference conditions will
differ among geographic regions and
states because estuarine salinity
gradients, trophic state, bottom
sediment types, morphology and
biological communities differ between
regions.
Reference conditions can be established
in a variety of ways. It is important to
recognize that the reference condition is
best developed from a population of
sites, not from a single site. However, in
some instances, particularly coastal
environments and sites influenced by
controversial land uses, the use of site-
specific nearfield/farfield stations may
be necessary and appropriate to
augment the reference condition. They
should include information derived
from:
*• Historical Data are usually available
that describe biological conditions in
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
1-15
-------
the estuary or coastal marine region
over some period of time in the past.
Careful review and evaluation of
these data provide insight about the
communities that once existed
and/or those that may be
reestablished. Review of the
literature and existing data is an
important initial phase in the
biocriteria development process.
However, if data have not been
collected for this specific purpose,
they need to be carefully reviewed
before being applied;
*• Reference Sites are minimally
impaired locations in the same or
similar water bodies and habitat
types at which data are collected for
comparison with test sites.
Reference sites could include sites
that are away from point sources or
concentrated nonpoint loadings; sites
in sub-estuaries; sites occurring
along impact gradients
(nearfield/farfield); and regional
reference sites that may be applied to
a variety of test sites in a given area;
*• Models include mathematical
models (logical constructs following
from first principles and
assumptions), statistical models
(built from observed relationships
between variables), or a combination
of the two. Paleobiological
reconstructions of historic or
prehistoric conditions are typically
statistical or empirical models
(Latimer et al. 1997, Alve 1991, Dixit
et al. 1992). The degree of
complexity of mathematical models
to predict reference conditions is
potentially unlimited with attendant
increased costs and loss of predictive
ability as complexity increases
(Peters 1991). Mathematical models
that predict biological reference
conditions should only be used with
great caution, because they are
complex and often untestable
hypotheses (Oreskes et al. 1994,
Peters 1991);
*• Expert Opinion/Consensus A
consensus of qualified experts is
always needed for assessing all of
the above information; establishing
the reference condition; and helping
develop the biocriteria. This is
especially the case in impaired
locales where no candidate reference
sites are acceptable and models are
deemed unreliable. In these cases,
expert consensus is a workable
alternative used to establish
reference "expectations". Under
such circumstances, the reference
condition may be defined using a
consensus of expert opinion based
on sound ecological principles
applicable to a region of interest.
The procedures for these
determinations and decisions
should be well documented for the
record.
1.7.3 Assessment Tiers
Biological surveys of estuaries and
coastal marine waters can be
implemented in several tiers, ranging
from a simple and inexpensive screening
to detailed field sampling, analysis, and
assessment. The tiered approach gives
agencies one suggested approach for
planning, organizing, and implementing
biological surveys. Other approaches
may also be available. Agencies should
consider the approach that would work
best to meet their program objectives.
The tiers are intended to be
implemented cumulatively, that is, each
tier should incorporate the elements in
the preceding tier as appropriate for the
waters in which they are applied. Each
integrated tier includes both biological
and habitat components. Higher tiers
require successively more effort and
yield more detailed information on
1-16
Introduction - Bioassessment & Biocriteria
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specific biotic assemblages and potential
stresses on the system. Higher tiers
reflect higher quality information and
reduced uncertainty in the final
assessment (Costanza et al. 1992). A
desktop screening and three field survey
tiers are described in this document.
Figure 1-4 provides a summary of the
requirements for each tier.
Tier 0 is a desktop screening assessment
that consists of compiling documented
information for the estuary or coastal
marine areas of concern through a
literature search and sending survey
questionnaires to local experts. No field
observations are made at this assessment
level. Desktop screening should precede
any of the three subsequent tiers. Its
purpose is to support the planning for
monitoring and more detailed
assessments. Information to be compiled
in Tier 0 includes: area and
geomorphometric classification, habitat
type, watershed land use, population
density, NPDES discharges, water
quality data (salinity, temperature, DO,
pH, turbidity), biological assemblage
data, and water column and bottom
characteristics.
Tier 1 is the least complex of the survey
approaches. It consists of a one-time
visit to sites during a suitable,
predetermined index period to collect
biological and habitat data using
standardized methods. The focus of this
tier is on developing screening or survey
information. These variables include a
rudimentary identification of organisms
(benthos, fish, macrophytes, or
phytoplankon), water column
characteristics (salinity, temperature,
DO, pH, Secchi depth, water depth), and
bottom characteristics (grain size, RPD
layer depth, total volatile solids, and
sediment toxicity). States may choose
some variation of this list depending on
regional characteristics and resources.
Evaluation of the data collected, as well
as historical data for the area, leads to an
initial classification of sites and
identification of candidate reference
sites.
Tier 2 is somewhat more complex. A
higher level of detail is incorporated into
the standardized biological methods and
multiple visits to the site are made to
address temporal variability and/or
seasonality. Another assemblage
(epibenthos) could be selected in
addition to those listed above. Water
column nutrient measurements are
added to the Tier 1 water column
characteristics. A tactile categorization
of grain size, plus total organic carbon,
are added to the bottom characteristics.
The data collected in this tier will allow
the development of preliminary
biological criteria.
Tier 3 is the most rigorous survey tier.
Three or more assemblages are sampled
here, through multiple site visits to
account for seasonal variations in the
selected estuarine and coastal marine
biological assemblages and should
incorporate supplemental studies which
might be necessary for diagnostic
assessment of the potential causes of
observed impairments. This tier adds
water column pesticides and metals
measurements, plus full grain size
characterization (sieving to determine
percent grain size composition), acid
volatile sulfides, and sediment
contaminants. This tier also allows the
resource agency to develop a database
sufficient to support resource
management activities to reduce the
identified impairments and to develop
and refine biocriteria.
Biological Assessment
The procedure of biological assessment
is to sample two or more biological
assemblages and record data such as
abundance, condition, biomass, and
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Figure 1-4
General
comparison of
Tiered
Approach.
Tiers are
intended to be
implemented
cumulatively.
Each tier
should
incorporate the
elements in
the preceding
tier as
appropriate for
the waters in
which they are
applied, as
necessary for
specific
programs.
Tier 0
-No field observations
-Desktop screening
-Literature search
-Questionnaires to local experts
-Support planning for monitoring and more detailed
assessments
Tierl
-One time visit to sites during suitable, predetermined index period
-Least complex survey approach
-Develop screening/survey information
-States choose variation of variables (assemblages + water column &
bottom characteristics) according to regional characteristics & resources
-Leads to initial classification & ID of candidate reference sites
Tier 2
-2 or more visits to site
-More complex
-Possible to add another assemblage
-Add to water column & bottom characteristics samples
-Allows for development of preliminary biological criteria
Tier3
-4 or more visits to sites
-Most rigorous
-3 or more assemblages
-Incorporate supplemental studies
-Additions to water column & bottom characteristics
-Develop database to support resource management activities to reduce impairments
& define/refine biocriteria
other characteristics of each species.
These data are then used to calculate
metrics, such as taxa richness, percent
dominance, number of intolerant species,
and percent abundance of tolerant
species. Each metric is compared to its
expected value under reference
conditions, and rated good (similar to
reference), fair (different from reference),
or poor (substantially different from
reference). Numeric scores are assigned
to the ratings, and the scores of all
metrics of an assemblage are summed for
a total score for the assemblage. The
total score is again compared to the
expected total score under reference
conditions, and the assemblage as a
whole is assigned an ordinal rating of
good, fair, or poor. This second
comparison to reference conditions is
necessary because not all metrics are
expected to score "good" at all times
even in pristine conditions; the final
assemblage score thus takes into account
natural variability in metric values.
Once these values are satisfactorily
established they can be incorporated in
the development of a biocriterion for a
particular estuarine or coastal marine
1-18
Introduction - Bioassessment & Biocriteria
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class. "Biological assessment" at this
point becomes a comparison of
monitoring scores to the biocriteria for
management decision making. The
following several chapters describe the
processes necessary to the development
of suitable metrics and finally their
incorporation in biological criteria for
water resource management decision
making.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 1-19
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Chapter 2
Biological Survey
2.1 Indicators of Biological
Integrity
A key concept underlying the approach
to biological surveys presented in this
document is that of biological integrity.
Biological integrity, discussed in greater
detail in Section 1.7, may be
operationally defined as
"...the condition of the aquatic
community inhabiting unimpaired
waterbodies of a specified habitat as
measured by community structure
and function (USEPA1990)."
Biological integrity is an ideal condition;
estuarine and coastal marine
communities can approach a condition
of biological integrity when they are
minimally impaired by human activities.
In order to determine the degree to
which these communities approach
biological integrity, it is necessary to
measure attributes (or indicators) of
community structure and function and
to be able to distinguish between natural
variations and anthropogenic impacts.
Various techniques can be used at any
level to document the effects of
anthropogenic perturbations on
biological communities. Discussion of
these techniques falls into three general
areas, the first two of which are
measurement processes and the third is
a data processing technique. They are:
*• Measures of community condition
and change;
*• The presence or absence of indicator
taxa;
*• The use of indexes to compile and
evaluate large amounts of biological
data for evaluation.
The suitability of many of the
approaches in each of these categories
has long been the subject of debate
among biologists and natural resource
managers. The following discussion
examines both the utility and
uncertainty surrounding these
community assessment tools.
2.2 Primary Measures of
Community Condition
and Change
Whenever possible, the investigator
should try to examine two or more
assemblages because different organism
groups react differently to perturbation.
The more diverse the measures used, the
more robust the investigative technique
is and the more confidence the manager
can place in the results. However, this
idea must be reconciled with the
limitations of the costs of multiple and
diverse surveys and the relative
availability of reliable scientific methods
to measure some assemblages. The
prevalent approaches today are
measures of benthic macroinvertebrate
infauna, fish, and aquatic vegetation.
2.2.1 Benthic Macroinvertebrates
The benthic infauna have long been
used for water quality assessments
because of their tendency to be more
sedentary and thus more reliable site
indicators over time compared to fish
and plankton. Consequently, a larger
body of data has been accumulated for
this assemblage. Examination of benthic
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2-1
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community structure and function is a
valuable tool for evaluating the
condition of benthic habitats, for
monitoring rates of recovery after
environmental perturbations and
potentially to provide an early warning
of developing impacts to the system.
Bilyard (1987) and USEPA (1991) cite the
following specific advantages of
monitoring benthic infauna to determine
overall aquatic community health:
*• Benthic infauna are typically
sedentary and therefore are most
likely to respond to local
environmental impacts, thus
narrowing the list of possible causes
of impairment;
*• Benthic infauna are sensitive to
disturbances of habitat such that the
communities respond fairly quickly
with changes in species composition
and abundance;
*• Benthic infauna are important
components of the food chain and
often act to transport not only
nutrients, but also toxicants, to the
rest of the system;
*• Monitoring benthic infauna provides
an in situ measure of relative biotic
integrity and habitat quality;
*• Of the biota typically measured, this
assemblage has the strongest
supporting database. Thus, it has
extensive historical and geographic
application.
Some limitations of benthic infauna
sampling include:
*• Relatively few state and federal
programs have the necessary in-
house taxonomic expertise to
support extensive monitoring
activities;
*• Current methods can distinguish
severely impaired sites from those
that are minimally impaired.
However, it can be difficult to
discriminate between slightly or
moderately impaired areas,
particularly in estuaries (due to their
natural spatial and temporal
variability);
*• The condition of benthic habitats can
vary over relatively small scales.
Therefore, if too few samples are
collected from a specified area, the
ambient heterogeneity to be
expected may be missed, potentially
leading to incorrect conclusions
regarding the biological and water
quality conditions in the area;
*• The cost and effort to sort, count,
and identify benthic invertebrate
samples can be significant, requiring
tradeoffs between expenses and the
desired level of confidence in
decisions based upon the collected
data.
2.2.2 Fish
Fish are an important component of
estuarine and marine communities
because of their economic, recreational,
aesthetic and ecological roles. The
abundance and health of the fish
community is also the primary indicator
used by the public to discern the health
of a water body. Fish are good
indicators of ecological health because:
*• They are relatively sensitive to most
habitat disturbances;
*• Being mobile, sensitive fish species
may avoid stressful environments,
leading to measurable population
patterns reflecting that stress;
2-2
Biological Survey
-------
> Fish are important in the linkage
between benthic and pelagic food
webs;
*• They are long-lived and are
therefore good indicators of long-
term effects;
*• They may exhibit physiological,
morphological, or behavioral
responses to stresses;
*• Fish may exhibit obvious external
anatomical pathology due to
chemical pollutants;
*• Fish databases originally compiled
to support state and federal fisheries
management programs may be
available. These databases may
require integration with other data
(e.g., water quality) to be useful for
bioassessment and biocriteria
purposes.
The limitations on the use of fish in
community bioassessments include:
> Fish represent a relatively high
trophic level, and lower level
organisms may provide an earlier
indication of water quality problems;
*• Some fish are resident species with
relatively limited lifetime spatial
ranges. Others have relatively large
ranges, making it difficult to isolate
probable causes of degradation that
could occur anywhere within their
range. Thus, the spatial scale of
sampling is an issue and because of
seasonal, open water migrations,
temporal adjustments may also be
necessary;
*• Mobile organisms such as fish may
avoid stressful environments,
reducing their exposure to toxic or
other harmful conditions;
*• Fish surveys may be biased because
of recreational and commercial
fishing pressures on the same or
related fish assemblages;
*• Some fish are very habitat selective
and their habitats may not be easily
sampled (e.g., reef- or marsh-
dwelling species);
*• Since they are mobile, spatial
variability is very high, requiring a
large sampling effort to adequately
characterize the fish assemblage.
2.2.3 Aquatic Macrophytes
Aquatic macrophytes in estuarine and
coastal marine waters may include
vascular plants (e.g., seagrasses) and
algae (e.g., sessile and drift). Vascular
aquatic macrophytes are a vital resource
because of their value as extensive
primary producers in estuaries. They
are a food source for waterfowl, a
habitat and nursery area for
commercially and recreationally
important fish species, a protection
against shoreline erosion, and a
buffering mechanism for excessive
nutrient loadings. The primary
productivity that has been observed for
submerged aquatic vegetation (SAV)
communities in estuaries is among the
highest for any aquatic system (USEPA
1992). Excessive nutrient loadings lead
to prolific phytoplankton and epiphytic
macroalgal growth on seagrass which
out-compete the seagrass through
shading, as evidenced by the 1970s and
1980s decline of eelgrass in the
Chesapeake Bay along with the current
decline in Waquoit Bay. Because of the
combined high productivity and habitat
function of this plant community, any or
all of the other estuarine or coastal
marine biota can be affected by the
presence or absence of macrophytes.
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2-3
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Some of the advantages of using aquatic
macrophytes in biological surveys are:
*• Vascular plants are a sessile
community. There is essentially no
mobility to rooted vascular or
holdfast-established algal plant
communities, so expansion or
contraction of seagrass beds can be
readily measured as an
environmental indicator;
*• Measurement of macrophyte
community extent and relative
density can be fairly easily
accomplished by remote means,
such as aerial photography, if the
water is clear or shallow;
*• Sampling frequency is reduced
because of the relatively low
community turnover compared to
other biota such as benthic
invertebrates or fish;
*• Taxonomic identification in a given
area is generally consistent and
straight-forward.
Some of the disadvantages of
macrophyte surveys are:
*• Relatively slow response by the
plant community to perturbation
makes this a delayed indicator of
water quality impacts. This could be
critical if prompt management
responses are needed;
*• Successional blooms of some
macrophytes means seasonal cycles
need to be identified and
accommodated by the survey
schedule to avoid misinterpretation
of data and false assumptions of
water quality impacts;
> Changes in abundance and extent of
submerged macrophytes are not
necessarily related to changes in
water quality;
*• Aquatic macrophytes do not stand
alone as an indicator of ecosystem
condition; additional parameters
(e.g., water column nutrient
concentrations, light penetration) are
required to interpret macrophyte
data.
2.2.4 Phytoplankton
Many estuaries and marine waters can
be considered "plankton-dominated"
systems, which implies that this
assemblage should provide valuable
information in an assessment of
ecosystem condition. Advantages of
using plankton include:
> Plankton provide the most notable
indication of eutrophication in
estuarine environments. Changes in
nutrient concentrations can result in
long-term changes in estuarine
community structure and function
and planktonic primary producers
are one of the earliest communities
to respond;
> Changes in plankton primary
production will in turn affect higher
trophic levels of macroinvertebrates
and fish;
> Many states routinely monitor
chlorophyll a as part of water quality
monitoring due to the ease and
relatively low cost of analysis;
> Plankton have generally short life
cycles and rapid reproduction rates
making them valuable indicators of
short-term impact.
As with all other assemblages, there are
disadvantages associated with using
phytoplankton in a biosurvey:
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Biological Survey
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> The fact that phytoplankton are
subject to rapid distribution with the
winds, tides, and currents means
they may not remain in place long
enough to be source identifiers of
short-term impacts. This problem is
compounded by the ability of some
phytoplankton to synthesize
atmospheric sources of nitrogen,
thus confounding the identification
of runoff sources of nutrients in
estuaries and the resultant changes
in the aquatic biota;
*• Taxonomic identification of
phytoplankton can be difficult and
time-consuming;
*• Competition by aquatic
macrophytes, higher respiration
rates, and increased grazing by
zooplankton may counteract
increased phytoplankton biomass
resulting from nutrient enrichment.
These reasons argue for
investigating phytoplankton and
zooplankton together as biological
indicators;
*• Phytoplankton can undergo blooms,
the causes of which might be
indeterminate, at varying
frequencies.
2.3 Measures of Community
Condition and Change
Being Developed
Two assemblages (zooplankton,
epibenthos) have considerable potential
for expanding the biological information
available for biocriteria development
and bioassessments. These assemblages,
however, are considered
"developmental" at this time. As survey
methods become more refined and
routine, databases for these assemblages
will expand and the techniques are
expected to become sufficiently robust to
be incorporated in biocriteria
development and environmental
management decision making.
Paleoenvironmental reconstruction is an
additional technique being developed.
This technique allows investigators to
infer past conditions from the remains of
several groups of organisms found in
sediment cores, and to compare those
past conditions to current ones.
2.3.1 Zooplankton
Zooplankton consist of two basic
categories: holoplankton which spend
their entire life cycle as plankton, and
meroplankton which are only plankton
while in the larval life stage.
Holoplankton are characterized by rapid
growth rates, broad physiological
tolerance ranges, and behavioral
patterns which promote their survival in
estuarine and marine waters. The
calanoid copepods are the numerically
dominant group of the holoplankton,
and the genus Acartia (A. tonsa and A.
clausi) is the most abundant and
widespread in estuaries. Acartia is able
to withstand fresh to hypersaline waters
and temperatures ranging from 0° to
40°C.
The meroplankton are much more
diverse than the holoplankton and
consist of the larvae of polychaetes,
barnacles, mollusks, bryozoans,
echinoderms, and tunicates as well as
the eggs, larvae, and young of
crustaceans and fish.
Zooplankton populations are subject to
extensive seasonal fluctuations reflecting
hydrologic processes, recruitment, food
sources, temperature, and predation.
They are of considerable importance as
the link between planktonic primary
producers and higher carnivores. As
such, they are also early indicators of
trophic shifts in the aquatic system.
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Advantages of zooplankton sampling
are similar to phytoplankton:
> The rapid turnover of the
community provides a quick
response indicator to water quality
perturbation;
*• Sampling equipment is inexpensive
and easily used;
*• Compared to phytoplankton, sorting
and identification is fairly easy.
Some limitations of using zooplankton
in biosurveys are:
*• The lack of a substantial data base
for most regions;
*• The high mobility and turnover rate
of zooplankton in the water column.
While this permits a quick response
by zooplankton to environmental
changes on the one hand, it also
increases the difficulty of evaluating
cause and effect relationships for this
assemblage.
2.3.2 Epibenthos
The sampling of those animals living on
the sediments or on structures may
prove to be the link between relatively
low cost but highly variable fish
community information, and the more
consistent but expensive benthic
macroinvertebrate surveys. The process
has been tested with considerable
success in Washington, North Carolina,
and Florida (Chapter 13).
Advantages of using this assemblage
are:
The relatively sedentary life style of
some epibenthic fauna can result in
an in-place accumulation of
indicative pathogens and toxicants
in individuals while the community
composition reflects the average
salinity, temperature and dissolved
oxygen of that locale over an
extended period of time (Day et al.
1989);
*• Ease of data collection by use of
small otter trawls or beam trawls;
*• Relative ease of identification
because taxonomic lists of local
crustaceans, mollusks, and
echinoderms can be fairly easily
compiled;
*• Sampling is as inexpensive as fish
surveys, and can often be done with
the same or similar equipment
during the same survey;
*• Decapod Crustacea are usually very
important prey for fish and are
important components in benthic
food webs. Some (e.g., shrimp and
crabs) are harvested for human
consumption.
Possible difficulties involve:
*• Potential equipment snags and
difficulties in macrophyte beds;
*• Benthic infauna would likely be
included in the trawl sample due to
disturbance of surface sediments;
*• As when using otter trawls for fish,
benthic habitat may be destroyed;
*• There is greater potential for
avoidance by organisms than when
sampling for benthic
macroinvertebrates, though not as
great as with fish surveys;
*• Because of relatively low taxa
numbers in some environments,
especially coastal marine waters,
impact response may not be as
sensitive as desired; this could be
2-6
Biological Survey
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addressed by the use of indicator
species instead of a multimetric
approach;
*• Epibenthos are very sensitive to
substrate type;
*• Relative sensitivity remains to be
determined in many areas.
2.3.3 Paleoenvironmental
Reconstruction: preserved
remains
Several groups of organisms in estuaries
leave remains in the bottom sediments.
Some of the remains are resistant to
decay and become a permanent
biological record of the life in that
waterbody. Comparisons of present-day
biota to that of the past allow past
environmental conditions to be inferred.
Several groups of organisms have been
used for this type of study in estuaries
including diatoms, dinoflagellates, and
foraminifera (Latimer et al. 1997).
The approach is to elucidate
relationships between environmental
conditions (for example, temperature,
dissolved oxygen, nutrient
concentrations) and the relative
abundance of target species. These
known relationships are then used to
infer past conditions from the observed
remains in the sediment. Advantages of
studying paleoenvironmental systems
include:
*• diatoms, dinoflagellate cysts, and
foraminifera found in sediments
integrate conditions over broad
spatial scales and over time periods
of one year or more, so that short-
term variability does not confound
assessment;
*• there is no need to adhere to an
index period for sampling;
*• paleoenvironmental reconstruction
can provide a site-specific reference
by showing conditions in the past.
Disadvantages of studying
paleoenvironmental systems include:
*• it requires a relatively stable
depositional environment; it is not
suitable for shallow estuaries subject
to frequent resuspension;
*• it requires conditions for
preservation of target assemblages in
the sediment;
*• temporal resolution is limited by the
rate of accumulation (between 1-10
years); it cannot be used to assess
short-term response to stressors or to
restoration efforts;
*• at the time of this writing, technical
expertise for estuarine paleoecology
is specialized, with only a small
handful of research institutions
active in North America.
2.4 The Use of Indexes to
Compile And Evaluate
Biological Data
It is evident that biological surveys can
generate tremendous amounts of raw
data. The usual approach to sorting this
wealth of observations is to summarize a
series of diverse community
measurements into one or more
dimensionless indexes, much as the
cumulative performance of a student's
work for a year can be reduced to
annual grades.
As with student grades, the use of
dimensionless indexes is a well-
established and consistent way to
evaluate and compare many discrete
units as a continuum of performance or
condition. Also similar to student
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grading, detailed insight is lost when the
complex interplay of so many discrete
variables is reduced to a single score.
The reasons for high or low scores are
not always evident and the accuracy of
the scoring process itself is always
subject to debate. Indexing is the only
way to rank order information for
decision making. However, valuable
insight is lost at every level of data
reduction. There is no alternative to the
process short of relying entirely on the
professional judgment and wide
variation of skill of individual biologists.
The strengths of index development and
use are:
*• It is a rational, consistent way to
reduce large amounts of data to
unitless, meaningful interpretations;
*• It is a quantitative treatment of the
observations which permits
statistical assessments;
> Interpretive bias is reduced in the
treatment of the data.
Conversely, indexing:
> Removes the decision-making from
detailed evaluation of the data and
information to just reporting of
simplified indexes;
*• May be viewed as irrefutable,
despite evidence to the contrary;
*• May obscure important and
confounding interrelationships in
the aquatic environment
contributing to the index score(s);
*• Obscures more information as each
level of data reduction is performed
leading to an index value, so that
some indexes are not sufficiently
sensitive to reflect biotic change;
*• Provides no indications of causes of
the relative condition of the system.
The best way to guard against the
problems of indexing, while using it to
expedite decision-making, is to always
retain the raw data. These files can be
used to translate historical data sets into
present indexes for temporal continuity,
and even more important, they can be
evaluated to provide an interpretation
and potential diagnosis for management
action when a particular site is being
evaluated.
Indexes are most often used to measure
community composition such as species
abundance, diversity, evenness,
richness, and dominance or conditions
such as incidence of disease,
malformation, and distributions of year
classes. These can be used to assess the
changes in community structure that
occur as a result of anthropogenic
perturbations (Boyle et al. 1990).
Community function can also be
described through indexes such as the
Infaunal Trophic Index (Word 1978,
1980, USEPA 1987).
Although indexes have long been used
in applied and theoretical ecology, it is
recognized that some of them, when
applied individually, are insensitive to
stress-induced changes in naturally
occurring biological communities (Boyle
et al. 1990). Because of varying
sensitivities of the community indexes,
several of them should be used
concurrently for evaluating impacts.
This approach provides greater certainty
of the data interpretation than reliance
on any single index. Conversely, while
Ludwig and Reynolds (1988) indicate
that the most reliable community
measures in evenly matched surveys are
number of individuals and number of
taxa as direct measures; it has been
2-8
Biological Survey
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observed in the coastal marine studies
associated with this guidance manual
that, at least in two mid-Atlantic Bight
outfall studies, the diversity index and
the richness index both appear to be
more responsive than number of
individuals or number of taxa to sewage
impacts (Gibson, Chapter 13). For a
more detailed discussion of the different
indexes and their particular applications
see Chapter 11 (Index Development)
and Chapter 13 (Case Studies).
2.5 Indicator Taxa
Indicator taxa or species are those
organisms whose presence (or absence)
at a site indicates specific environmental
conditions. If an organism known to be
intolerant of pollution is found to be
abundant at a site, high water quality
conditions can be inferred. On the other
hand, dominance by pollution tolerant
organisms implies a degraded condition.
When available, indicator taxa are an
important, cost-effective preliminary
survey tool for site assessments.
However, the investigator should
always ascertain that absence of an
indicator organism is a fact and not
merely a reflection of insufficient
sampling.
Swartz et al. (1985,1986,1994) have
demonstrated the sensitivity of the
amphipod Rhepoxynius abronius to the
complex contaminant mixture that often
characterizes coastal marine benthic
pollution. Their studies were performed
along pollution gradients from the Los
Angeles County Sanitation Districts'
sewage outfalls to control conditions in
Santa Monica Bay. The results showed
that there were significant increases in
the concentration of most sediment
contaminants and significant decreases
in benthic taxa richness and abundance
at stations where sediment was acutely
toxic to R. abronius (Swartz et al. 1985).
More studies performed by Swartz et al.
(1994) at a designated Superfund site in
San Francisco Bay also showed that
acute sediment toxicity lab tests of R.
abronius correlated with biologically
adverse sediment contamination in the
field. Other EMAP studies (Summers et
al. 1992) included a 10-day acute test
using the tube-dwelling amphipod,
Ampelisca abdita. The majority of
sediments proving significantly toxic to
A. abdita were found in Louisiana and
Alabama estuarine waters.
A well-known indicator for degraded
systems is the polychaete Capitella
capitata. C. capitata and its related
species are collectively known as the C.
capitata complex. In general, the
presence of this indicator species
corresponds to a dominance of deposit
feeders that colonize an area as organic
pollution increases. Swartz et al. (1985)
observed dominance of Capitella near
sewage outfalls. A recent study in the
Mid-Atlantic Bight by the U.S. Army
Corps of Engineers (1996) suggests that
the polychaete Amastigos caperatus may
have indicator potential similar to the
Capitella complex.
A problem with using pollution tolerant
indicator organisms is that some of these
organisms may be ubiquitous and found
in naturally occurring organically
enriched habitats as well as in minimally
impaired waters. To be useful as an
indicator, they must have displaced
other, less robust taxa and have
achieved numeric dominance. Tolerant
and ubiquitous organisms can be found
in sediments far away from sources of
sewage pollution and long after plumes
have dispersed.
The use of the concept of "clean"
indicator species is less subject to this
form of misinterpretation. These "clean"
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2-9
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or highly sensitive organisms are less including pollution sensitive ones and
likely to be found in both polluted and some that are pollution tolerant.
high quality habitats.
The best option may be the paired use of
both pollution tolerant and intolerant
indicator species. If both indicators
change concurrently in opposite
directions, more confidence can be
placed in the interpretation.
As part of the biological survey process,
individual indicator species are useful in
reducing analytical costs. They are not
only a valuable preliminary assessment
tool, they are a cost-effective way to
define the magnitude, spatial, and
temporal extent of an impact (USEPA
1992). Selected indicators should
possess the following characteristics
(Green 1984):
*• Provide sufficiently precise and
accurate appraisals of:
— species of concern
— magnitude of anthropogenic
disturbance;
*• Be cost-effective and statistically
reliable as an alternative to
monitoring all critical community
measures;
*• Appropriate to the spatial and
temporal scale demanded by the
study objectives.
When indicator species are employed in
tandem for impact investigations, a
gradient of species distribution can often
be identified. Such a gradient might
progress from the most degraded
waters, having low diversity
communities dominated by pollution
tolerant opportunistic species, to
unimpaired or minimally impaired
waters having diverse communities that
are comprised of a wide range of taxa,
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Chapter 3
Habitat Characterization
Biological assessment in estuaries and
coastal marine waters is built around
assessing two separate ecosystem
components: the habitat and the biota.
The biota are the resident plant and
animal assemblages in the water body.
The condition of the biota depends in
part on the quality of the physical-
chemical environment of estuaries and
coastal marine waters; i.e., habitat.
Habitat is in turn influenced by natural
and catastrophic events, climate, and
human activities. These include:
+ Seasonal variations in precipitation,
temperature shifts, and wind or
wave patterns;
+ Introduced or extirpated species able
to influence the habitat (such as
burrowing organisms, plants, or
diseases/parasites;
* Shifts in sedimentation or scouring
patterns;
*• Dredging and filling;
*• Shoreline or basin construction;
+ Bulkheading and jetty construction;
+ A variety of land use and
navigational practices.
This conceptual model is based on an
understanding of the causal mechanisms
of natural and anthropogenic stress
effects in estuarine and coastal marine
ecosystems.
Estuaries integrate processes because
they receive and retain matter and
energy released in the watershed. Many
human activities directly affect aquatic
habitat including discharges,
agriculture, and urban land use which
contribute materials (sediment,
nutrients, contaminants) to the water
body. Biological communities are
directly affected by their physical
habitat and water quality conditions,
and also by direct human activities such
as stocking or harvesting.
Components of biota are the biological
assemblages, such as algae, aquatic
macrophytes, benthos, epibenthos,
plankton, and fish. Habitat components
for the biological assessment of these
assemblages are hierarchical, and
include the watershed, the nearshore
zone, the water column, and the
sediment. An integrated assessment
evaluates the condition of estuaries and
coastal marine waters by aggregating
data on components of both habitat and
biota. The habitat component may be
damaged by physical stress or chemical
degradation from pollution. Thus,
habitat studies may help identify causes
of biological decline as well as being the
important determinant of the types of
biotic communities to be expected. This
classification function is crucial to
proper biocriteria development.
Habitat characterization is essential to
the proper classification of sites.
Although estuaries are by definition
transitional zones between fresh water
and the sea, and both estuaries and
coastal marine waters incorporate many
environmental gradients (e.g., salinity,
sediment grain size, depth), individual
locations and conditions are often
defined categorically. Thus, a site may
be characterized as oligohaline or
mesohaline with respect to salinity, or
sand or mud with respect to sediment
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3-1
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grain size. The composition of
biological assemblages can vary
dramatically along these habitat
gradients, and valid comparisons of
estuarine and coastal marine biological
assemblages require that their habitats
be correctly classified.
3.1 Flow and Hydrography
The type of estuarine ecosystem in a
specific area is primarily controlled by
the physical environment; i.e.,
geomorphology, climate, salinity, and
the availability of fresh water. The
absolute values of the abiotic factors are
not as important as the degree of
fluctuation of factors such as the
microclimate, water movement,
chemical cycling, and physical structure
(Day et al. 1989). In addition, the
residence time of water in an estuary can
influence overall water column
pollutant concentrations.
The abiotic features thought to be
important in determining the specific
nature of estuaries as proposed by Day
et al. (1989) are:
+ The degree of protection and
buffering from direct oceanic forces;
* The quantity of freshwater input and
associated dissolved and suspended
materials;
* The water circulation patterns that
are determined by riverine and tidal
currents, geomorphology and wind.
Tides play a critical role in
influencing circulation, and
biochemical and biological
processes. In many coastal regimes,
the wind-driven currents are more
predominant than tidal and
geomorphologically-induced
currents;
*• Depth—stronger interactions
between the water column and the
bottom occur in shallow estuaries,
thereby expediting the release of
sediment nutrients for use by the
phytoplankton;
* Variability of salinity and the
sharpness and pattern of the salinity
gradient from the mouth to the
headwaters. Water circulation
influences the salinity gradient and
the distribution of biological
assemblages;
+ The rate of geomorphological change
generated by various physical forces
that control sediment transport
within the estuary.
These controlling abiotic features are
discussed in more detail in the following
sections.
3.1.1 Circulation and Tidal Regime
Circulation is the physical process that
influences or controls many of the
ecological processes occurring in an
estuary, including the degree to which
an estuary is dominated or modified by
hydrodynamics. The three major
driving forces behind the circulation
patterns in estuaries are: (1)
gravitational circulation; (2) tidal
circulation; and (3) wind-driven
circulation. Geostrophic forcing; i.e., the
Coriolis effect, can significantly alter
estuarine circulation patterns as does
bathymetry. A notable example is the
Chesapeake Bay, where lower salinities
extend further south along the Bay's
western shore in comparison to its
eastern shore.
Gravitational circulation is induced by
water masses of differing densities and
the layering of fresh water inflow on top
of more saline waters. These density
differences cause the lighter fresh water
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Habitat Characterization
-------
to flow over top of the saltwater to form
what is commonly termed the "salt
wedge". In what is termed the
"classical" estuarine gravitational
circulation, the pressure surfaces of the
fresh water are tilted seaward and the
pressure surfaces of the saltwater are
tilted toward the head of the estuary.
The shear stress forces that occur at the
interface of these two water masses
cause vertical mixing and an eventual
equalizing of the pressure surfaces
somewhere near mid-depth. The fresh
water surface layer has a net seaward
movement, the saltwater layer on the
bottom has a net movement upward into
the estuary and the interface is a zone of
no net movement.
Typically, density differences and the
resulting circulation are determined by
salinity and the circulation as is
described above. However, in arctic or
subarctic estuaries, the fresh water
inflow may be substantially colder than
the saltwater causing the fresh water
inflow to sink below the saltwater,
reversing the expected circulation
pattern. In shallow lagoons that receive
little or no fresh water input such as
Florida Bay or Laguna Madre, the
evaporation rate can cause the salinity of
the water within the lagoon to rise
higher than the ocean waters. When this
happens, the ocean water flows into the
estuary on the surface and the estuarine
water flows out on the bottom, resulting
in reverse circulation. Most often,
though, shallow lagoons are well-mixed
by the wind and reverse circulation is
only observed at the mouth of the
lagoon.
Tidal circulation occurs when the ebb
and flow of the tides becomes the
driving force behind circulation. This is
known to occur in estuaries with steep
constrictions or with shallow depths and
large tidal ranges (e.g., Puget Sound),
and in the absence of density gradients
or wind stress. In many estuarine
systems, gravitational and tidal effects
coexist.
Wind circulation is common in estuaries
with open water, shallow water depths,
a small tidal range, and low fresh water
input. Although the effects of wind may
be overshadowed by gravitational or
tidal forces, periods of sustained wind
can have dramatic ecological effects. In
the Ten Thousand Islands region of the
Florida Everglades, sustained northern
winds virtually drain the water out of
large portions of the estuary for
extended periods of time, exposing large
areas of mudflats. Winds that blow into
an estuary can create a net flood flow
and result in the inundation of marshes
and grass lands. In lagoons as well,
water can pile up on one side of the
lagoon creating a seiche or a sloshing of
the water back and forth within the
lagoon.
Attention to these diverse, often
variable, and always significant
circulation patterns is essential to
understanding the biotic distribution of
coastal and estuarine environments.
This must always be addressed before
attempting to attribute such distribution
to anthropogenic influences.
3.2 Habitat Types
Use of a single habitat to characterize
biological assemblage condition would
minimize the requirements for
expenditure of time and resources.
However, estuaries and coastal marine
waters are inherently heterogeneous
systems. By definition, a salinity
gradient is present in any estuary.
Greater numbers of species are typically
observed at the marine end of the
salinity gradient, with the fewest
numbers observed in about 3-7-ppt
(Weisberg et al. 1993). This may be due
to the unpredictable nature with which
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3-3
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the brackish water zone varies along the
length of the estuary; driven by the
strength and intervals of freshwater
inflow.
In addition to a salinity gradient,
estuarine habitats vary in bottom
substrates, and in the predominance of
erosional versus depositional
environments. The variations in these
characteristics will lead to differences in
the way pollutants and other stressors
will effect the biota. For example,
depositional environments occur where
large amounts of terrigenous sediments
are transported by rivers to embayments
and where the water is sufficiently
quiescent that fine-grained sediments
settle out. Metals, synthetic organic
pollutants, and other contaminants
adsorb to fine-grained sediments
(Holland 1990) and low-density organic
detritus. Thus, the prevalence of
depositional areas may reduce the
likelihood of water column exposure of
estuarine organisms to toxic materials,
but may increase the exposure to
burrowing organisms. Conversely, the
water column of erosional zones is often
highly enriched as resuspended
phosphorus is episodically mobilized.
Habitats in estuaries and coastal marine
waters can be classified into nine major
categories. These habitats are
summarized below in a progression
from open, deep waters to decreasing
depths near the shoreline. The choice to
sample one or more of these nine
habitats will be dictated by their areal
extent and the nature of the problems
being addressed.
3.2.1 Open Water
Sampling in open water may
demonstrate phytoplankton blooms
which might be symptomatic of
eutrophication from anthropogenic
inputs of phosphorus or nitrogen. It
should be noted that not all
phytoplankton blooms (e.g., red tides)
result from anthropogenic stresses.
Increases in the standing stocks of
bacteria associated with fecal material
can be used to identify the presence of
sewage effluent. Open water (plankton
and nekton) studies also allow
assessment of pelagic food webs.
Sampling of pelagic finfish also occurs
in open estuarine and marine waters.
Limitations of sampling in open water
include a high degree of patchiness in
the plankton and finfish assemblages,
which necessitates the sampling of large
volumes and areas of water before
results can be described with acceptable
precision. Because of the transitory
residence time of water parcels moving
through estuaries and the short life
cycles of planktonic flora and fauna, a
relatively high sampling frequency is
necessary to distinguish signals from
noise in this area.
3.2.2 Soft Bottom Substrates
A "soft bottom" deposit may be
dominated by mud or fine- to relatively
coarse-grained, hard-packed sand. All
of these sediments can be sampled with
appropriate grabs. Soft bottom
substrates provide habitat for
economically valuable clams, shrimp,
and juvenile flatfishes. Muds have a
high surface area-to-volume ratio,
providing a large surface area for the
adsorption of metals and organic
pollutants. Also, fine-grained deposits
are often rich in biogenic adhesives
(mucopolysaccharide secreted by
microbes and meio- and macrofauna), to
which organic pollutants may adhere.
Under anoxic conditions, these deposits
are often called 'black ma yonnaise."
Conversely, sands have a lower surface
area-to-volume ratio. Thus, there is less
surface area available in the deposit to
which pollutants may adsorb.
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Habitat Characterization
-------
A limitation of sampling in soft
substrates is that the samples must be
sieved before individuals can be counted
and identified. With medium or coarse
sands this also means large volumes of
sediment are retained on the sieves for
subsequent processing. Thus,
measurements cannot be readily made
in the field. This is especially true for
samples in which an abundance of
organic debris (wood chips, seagrass
leaves) masks the presence of small,
cryptic organisms.
3.2.3 Hard Bottom Substrates
Hard bottom substrates can include
offshore rocky outcrops; oyster, relic
shell, and worm tube reefs; and relic
limestone and coral outcrops. Oyster
and mussel beds are major habitats
supporting a complex community of
various species essential to the biological
diversity of estuaries such as
Chesapeake, Florida, and Tampa Bays.
In fjords the predominant subtidal
habitat may be the rocky walls
extending below the water line. An
advantage of sampling these areas is
that the macroalgae growing along these
walls may be relatively sensitive to
stress and can be used in bioassays or
tested for bioaccumulation (Levin and
Kimballl984).
Hard bottom substrates frequently occur
in high-energy environments common
in portions of Alaska, Washington,
Oregon, and northern California, as well
as New England. For example,
gravel/cobble beaches are typically
subject to high incident wave energy.
Accumulations of fine-grained
sediments or organic detritus are not
expected on hard substrates either
because there is no riverine source or
because the energy of the environment
prevents their accumulation. In
addition, subtidal rocky bottoms are
difficult to sample remotely. A grab
sampler cannot be used, for example, as
it can in soft-bottom habitats. Typically,
divers conduct transect observations
and take photos.
Another limitation of sampling hard
substrate is that the larvae and spores of
rocky substrate organisms are typically
planktonic; therefore, recruitment may
be strongly influenced by factors outside
the estuary. Sampling and analysis
methods must be appropriate both to the
specific type of hard substrate as well as
regional characteristics due to the fact
that hard bottom substrates can exist
from rocky, high energy regions in
California to carbonate sediment, low
energy regions in Florida.
3.2.4 Aquatic Macrophytes
Macrophyte beds are among the most
important estuarine habitats, both
ecologically and economically.
Seagrasses (in this text, used to describe
macrophytes existing from tidal fresh to
marine conditions) create an
environment with a high degree of
structural complexity. Ecological niches
exist within the sediment, between the
rhizomes, along the surfaces of the
leaves, and in the protected portion of
the water column within the bed. Thus,
a seagrass bed is capable of supporting a
highly diverse fauna. Seagrass beds are
among the most productive aquatic
habitats. In western Florida, Thalassia
testudinum beds produce 8,100-gm2 dry
weight of leaves at maximum standing
crop (Hillman et al. 1989). Seagrass beds
provide "nursery areas" for juvenile
fishes and decapod crustaceans,
including many of economic
importance. Seagrass leaves are known
to bioaccumulate and possibly to
bioconcentrate metals (Ward 1989).
The right mix of nutrients and water
clarity are key in seagrass growth and
survival in estuarine systems. A study
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3-5
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by Stevenson et al. (1993) demonstrated
regrowth of SAV in the Choptank River
of the Chesapeake Bay (mesohaline
salinity regime) was associated with
mean DIN <10-|iM, mean DIP <0.35-|J,M;
mean SPM (suspended particulate
matter) <20-mgL"1; mean chlorophyll a
(in water column) <15-|J,gL"1; and mean
light attenuation coefficient (Kd)<2-m"1.
In addition to serving as habitat for
invertebrates and fish, macrophytes are
also a biological assemblage in their own
right and appear to be relatively
sensitive to stress. These beds can be
monitored from historical photos and
other records (Shepard etal. 1989).
Areal reductions are often attributed to
shading, which may result from a
variety of anthropogenic factors
including turbidity (from ship traffic,
dredging, or harbor construction which
may stir fine-grained material up into
the water column) and eutrophication
(where inputs of nutrients stimulate
increases in the density of
phytoplankton and of epiphytic macro-
and microscopic algae on leaf surfaces).
A limitation of sampling in seagrass
habitats is that because of their
ecological complexity, multiple
sampling strategies are required to
survey the various components of the
fauna (Howard et al. 1989), increasing
the expenditure of time and resources by
investigating agencies.
3.2.5 Beaches
Beaches are accumulations of
unconsolidated sediment (e.g., sand,
cobble) extending shoreward from the
near low-tide line to some demarcation
such as a sea cliff or dune field, or to the
point where permanent vegetation is
established (Komar 1976). High energy
beaches typically consist of shingle or
cobble due to the removal of finer
sediments by high incident wave
energy. These beaches may be
commonly found on the Atlantic coast
north of Cape Cod and along the Pacific
coast. High energy beaches of
southeastern Florida are composed of
sand and are protected by sabellariid
reefs offshore. Low energy beaches
consist of sand and finer sediments and
are widely located on the Atlantic coast
south of Cape Cod, the Gulf of Mexico,
and along the southern Pacific coast,
and along the shorelines of most
estuaries and their tidal tributaries.
Distinct zones occur across the beach
profile, proceeding from the subtidal
offshore and inshore zones, through the
foreshore that lies between the upper
current of wave swash at high tide and
the low water mark of the backrush of
the wave swash at low tide, to the
subaerial backshore (Komar 1976).
These zones contain a gradation of
f aunal communities in response to
varying conditions of wave energy,
sediment size, and inundation by water.
Sampling across the beach profile can be
problematic, particularly on high energy
beaches, due to the rapidly-varying
wave conditions and distribution
patterns of beach infauna and epifauna.
If attempted, core samplers can be used
on low energy beaches but quadrat
surface sampling may be required on
high energy beaches.
3.2.6 Sandflats
Deposits described as "fine sand"
contain some silts and clays and harbor
rich communities of both deposit- and
suspension-feeding invertebrates.
"Coarse sands," found in higher energy
environments, are expected to be
dominated by suspension-feeding
invertebrates. If a sufficient erosional
force is applied to a sandy bed by the
overlying flow, sand waves form. Sand
waves indicate a physically stressful
habitat, typified by a relatively
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Habitat Characterization
-------
depauperate fauna. It should be noted
that coarse sands generally contain
relatively low faunal densities and
biomass. However, when coarse sands
are colonized by surf clams and
echinoderms (sand dollars), densities
and biomass can be very high.
Compared to mudflats, relatively little
organic material and few associated
pollutants are expected to accumulate in
coarse sands. Calcareous deposits in
Puerto Rico and Hawaii may provide an
exception to this in that they have high
organic matter content and many
pollutants (Dossis and Warren 1981).
3.2.7 Mudflats
Mudflats provide habitat for
commercially important clams and other
invertebrates and feeding habitat for
fishes and shorebirds. Fine-grained
sediments (i.e., clay) and organic
detritus accumulate on mudflats. These
materials provide a large surface-to-
volume ratio adsorb metals and organic
pollutants. This same expanse of
usually nutrient and oxygen rich habitat
also supports diverse primary
producers, bacteria, plankton, and fish
and invertebrate species in a complex
community.
3.2.8 Emergent Marshes
Where present, emergent marshes may
be extremely important components of
estuaries and coastal marine
embayments and lagoons because they
filter storm water runoff from cities,
forests, and agricultural areas.
Emergent marshes may also provide
flood protection by attenuating peaks in
storm water flow and reducing the
erosive energy of wave action.
Traditionally, the ecological health of a
marsh has been characterized by
measuring changes in its areal extent
and the abundance and diversity of its
fish and wildlife populations. Although
"microelements" of the marsh
community (e.g., terrestrial insect
assemblages) may be more sensitive to
perturbations, these studies may be
more expensive and time-consuming to
carry out. For example, insect
populations are difficult to sample
quantitatively because of their mobility
and cyclic abundance.
3.2.9 Mangrove Forests
Low-lying tropical coasts are often
bordered by dense mangrove forests.
Temperature, particularly the frequency
of freezes, and rainfall gradients restrict
mangrove distribution. In the Gulf of
Mexico, mangrove forests occur along
the coasts south of Cedar Keys, Florida
and generally south of Port Isabel,
Texas. Isolated stands of black
mangrove (Avicennia germinans) occur in
the Mississippi deltaic plain (Day et al.
1989), but mangroves are otherwise
absent from the northern Gulf coast,
which is dominated by salt marshes.
Significant mangrove stands also occur
south of Cape Canaveral on the east
coast of Florida (Odum and Mclvor
1990). Mangrove forests and their
associated waters provide valuable
habitat for a range of invertebrates,
fishes, amphibians, reptiles, birds, and
mammals. Mangroves are also valuable
as stabilizers of intertidal sediments, and
the structural complexity of the prop-
roots provides habitat for many
commercially and recreationally
important fishes.
3.3 Water Column
Characteristics
Many chemical and biological processes
in the environment are affected —
directly or indirectly—by the physical
characteristics of that environment
(Thomann and Mueller 1987).
Therefore, collection of physicochemical
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data such as salinity, temperature,
dissolved oxygen, pH, turbidity,
nutrients, contaminants, and depth
provides information necessary to
evaluate biological data.
Although organisms living in estuaries
are adapted for life in a physically
dynamic system, many are living near
the limit of their physiological tolerance
range and any long-term alteration of
physicochemical environmental
conditions could force their permanent
exclusion from the estuary. Even in
minimally-impaired estuaries, causes of
mass mortalities have been attributed to
depletions of dissolved oxygen and
changes in temperature, salinity, and
excessive turbidity (Odum 1970). In
areas subjected to anthropogenic stress,
changes in physical and chemical
parameters may occur too frequently, be
increased in magnitude, or be sustained
for periods of time that only the
extremely tolerant organisms can
endure.
The community composition of marine
and estuarine fish assemblages is
determined by the various species
tolerances and preferences for
environmental variables such as
substrate, salinity, and temperature
(Weinstein et al. 1980). These
environmental variables are controlled
by the quantity and direction of the flow
of water; i.e., fresh water inflow, tidal
cycles, circulation patterns, etc. The
spatial and temporal distribution and
abundance of fishes would typically be
determined by these variables.
Anthropogenic stress adds to the
complexity by interfering with some
aspects of the physiology of the fishes.
In the Chesapeake Bay, salinity is the
major factor affecting the regional
distribution of macrobenthos, while
sediment characteristics have the most
influence over local distributions
(Carriker 1967). In the upper
Chesapeake Bay, sedimentation,
stratification, circulation, nutrient levels,
and dissolved oxygen concentrations are
all determined by the strength and
variation of the fresh water inflow from
the Susquehanna River.
Basic water quality parameters should
always be monitored to provide a record
of environmental conditions at the time
of sampling and to provide information
used in assessing the condition of
biological assemblages. These
parameters should be measured at the
same time and location as the biological
sampling. Such episodic data will only
serve to provide a snapshot of the
conditions at the time of sampling and
will not characterize the habitat
conditions in such dynamic ecosystems.
To properly characterize many water
quality conditions, long-term data sets
are required, including data collected at
short intervals over complete tidal cycles
for each season.
Monitoring schemes for
physicochemical water quality
characteristics of the habitat usually
involve in situ methods. Data on the
water column's characteristics can be
collected relatively inexpensively; the
expense of different methods is
generally governed by the level of
automation. Nonetheless, it is essential
to standardize the monitoring design in
order to ensure the comparability of
monitoring data throughout the
program.
Measurements of temperature, salinity,
and turbidity should be taken at a
minimum of four depths in the vertical
profile: (1) 1-m below the surface, (2) 1-
m above the bottom, (3) 1-m above the
pycnocline, and (4) 1-m below the
pycnocline. If the waters are too
shallow or no stratification occurs, it
would be appropriate to take samples
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Habitat Characterization
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just below the surface, at mid-depth, and
just above the bottom. However,
features of water masses recorded in the
historical data; i.e., historical profiles of
salinity, temperature, and turbidity, and
the collection of other data types (e.g.,
plankton community structure and
water chemistry) should be considered
when establishing sample depths (Pond
and Pickard 1983).
When using in situ methods (e.g., a
conductivity-temperature-depth meter
[CTD], temperature, salinity and pH
measurements should be taken at 1-m
intervals with a maximum interval of
<5-m in deeper coastal waters. The
measurements should be made over the
entire depth profile (to within 1-m of the
surface and bottom). Little additional
cost is incurred for this detailed
characterization of the water column
once the CTD is deployed. In areas of
high stratification, a smaller interval
would be appropriate. With some of the
newer, more expensive probes, a
continuous readout is possible and
discussion of depth intervals is
immaterial.
3.3.1 Salinity
Estuaries are transitional zones in which
the chemical composition varies from
that of freshwater to marine. Salinity is
a key determinant in the distribution of
estuarine flora and fauna, especially for
benthic invertebrate communities (e.g.,
Engle et al. 1994, Holland et al. 1987,
Summers et al. 1993, Weisberg et al.
1993). Taxa richness is most strongly
affected by salinity, with relatively low
richness in brackish waters compared to
freshwater and seawater. Taxa richness
metrics can be expressed as a "percent of
expected" for a given salinity (Engle et
al. 1994, Summers et al. 1993, Weisberg
et al. 1993).
The best-known estuarine zonation
system (the Venice system) is based on
salinity and establishes five estuarine
salinity zones:
> Limnetic (0-0.5-ppt)
*• Oligohaline (0.5-5-ppt)
*• Mesohaline (5-18-ppt)
•• Polyhaline (18-30-ppt)
»• Euhaline (>30-ppt).
Bulger et al. (1993) conducted a Principal
Components Analysis (PCA) to derive
estuarine salinity zones based on field
data on the salinity ranges of 316 species
or life stages in the mid-Atlantic region
(primarily species found in the
Chesapeake and Delaware Bays). The
PCA showed that the data structure
underlying the salinity distributions of
the biota could be explained by five
principal components corresponding to
five overlapping salinity zones: 0-4 ppt;
2-14-ppt; 11-18-ppt; 16-27-ppt; and >24-
ppt. This zonation scheme is similar to
the Venice system, but is objectively
derived from the salinity distribution of
estuarine organisms. Measurement of
the ionic strength of estuarine and
marine waters is typically made using
salinity. Salinity may be defined as the
total solids in water after all carbonates
have been converted to oxides, all
bromide and iodide have been replaced
by chloride, and all organic matter has
been oxidized (APHA 1981), and is
usually reported as grams per kilogram
or parts per thousand. Salinity is most
commonly measured electronically
using a salinometer probe as part of a
CTD unit.
A related measure of the ionic strength
of water samples is the conductivity,
which is the ability of an aqueous
solution to carry an electric current.
This ability depends on the presence of
ions, their total concentration, mobility,
valence, relative concentrations, and on
the temperature of measurement.
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Conductivity is a more useful measure
in the tidal fresh water portion of
estuaries than is salinity (or chlorinity).
Conductivity is most frequently
measured using a CTD meter.
The EMAP-Estuaries program collects
point-in-time salinity measurements
concurrently with the collection of
biological and sediment samples using a
CTD probe (Holland 1990). CTD-
measured salinity is also incorporated in
other estuarine monitoring programs;
for example, the Chesapeake Bay
(Holland et al. 1988,1989), San Francisco
Bay (ABAC 1991), and Puget Sound
(PSWQA 1988,1990,1991). Monitoring
guidance for the National Estuary
Program (USEPA1992) and procedural
and monitoring guidance for the CWA
§403 program (USEPA 1994a) both
recommend CTD probes as the preferred
method for collecting salinity data.
3.3.2 Temperature
Temperature is an important
determinant of the rate of chemical
reactions and biological processes. DO
saturation is a function of water
temperature. Temperature influences
the spatial and seasonal distribution of
benthic infauna (Kendall 1983 cited in
Dardeau et al. 1992), microbial process
rates (Christian 1989), and temporal and
spatial distributions of fishes (e.g.,
Houde and Zastrow 1991). Estuarine
water temperature in temperate regions
is primarily a function of the
temperatures of influent streams, rivers,
the ocean, and tidal stage (Reid and
Wood 1976). In the sub-tropical
estuaries of Florida and Texas, estuarine
temperature may be more closely related
to incident sunlight and air temperature.
Because most estuaries are shallow,
there can be considerable diurnal and
seasonal temperature variation.
Estuarine temperature also varies with
air temperature and depth, leading to
vertical temperature gradients.
In addition to the potential influence of
natural temperature variations on
aquatic biota and chemical reactions,
anthropogenic thermal inputs can lead
to significant modifications of estuarine
and coastal marine biological
communities. A prime example is
thermal loading via discharge of cooling
water from power plants and other
industrial facilities. The important
influence of thermal discharges is
recognized in §316 of the CWA, which
allows USEPA or states to impose
effluent limitations on thermal loading
at point sources to ensure that balanced,
indigenous populations of shellfish, fish,
and wildlife in and on a water body will
be maintained. Temperature should be
measured at each sampling site with a
CTD probe at 1-m intervals from the
surface to within 1-m of the bottom
concomitantly with the collection of
salinity and DO data. Diel temperature
measurements may also be needed.
3.3.3 Dissolved Oxygen
Dissolved oxygen (DO) is a basic
physiological requirement for nearly all
aquatic biota and for the maintenance of
balanced populations (exceptions being
anaerobic systems). Most estuarine
populations can tolerate short exposures
to reduced DO concentrations without
adverse effects. Extended exposures to
DO concentrations less than 60% oxygen
saturation may result in modified
behavior, reduced abundance and
productivity, adverse reproductive
effects, and mortality (Holland et al.
1989, Reish and Barnard 1960, Vernberg
1972). Low DO conditions can also
increase the vulnerability of benthos to
predation as they extend above the
sediment surface to obtain more oxygen.
Exposure to less than 30% saturation
(~2-mgL~1) for 1 to 4 days causes
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Habitat Characterization
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mortality to most species, especially
during summer when metabolic rates
are high. Some benthic
macroinvertebrate species tolerate low
DO conditions, and prolonged low DO
concentrations frequently lead to
changes in the composition of benthic
macroinvertebrate assemblages in
certain areas (Holland et al. 1989).
Aquatic biota exposed to low DO may
be more susceptible to adverse effects of
other stressors (e.g., disease, toxic
chemicals, habitat modification)
(Holland 1990).
Because DO concentration throughout
the water column can vary widely with
tide, time of day, wind patterns, and
biological activity, the EMAP-Estuaries
program conducted extensive
comparisons of point-in-time and
continuous collections of DO data. In
deeper areas of Chesapeake Bay, within
EMAP's Virginian Province, bottom DO
has a strong tidal signal; high tide
corresponds to lower DO near the
bottom. Significant serial
autocorrelation of dissolved oxygen
concentration persists for 6 to 8 days,
indicating that consecutive
measurements taken less than 8 days
apart may not be independent (Holland
1990). In some EMAP Louisianian
Province estuaries a strong diurnal cycle
with lower DO occurs at night (Stickney
1984, Turner et al. 1987). Low DO in
these shallow, often well-mixed
estuaries may be highly variable both
spatially and temporally (Sanford et al.
1990, Schroeder 1979, Rabalais et al.
1985). These conditions can lead to
misclassification of the ecological
condition of estuaries with respect to
hypoxia.
Goals of the EMAP analyses comparing
DO measurement approaches were to
determine the best measure for
representing DO exposure, to evaluate
the stability of DO over the sampling
(i.e., index) period, and to determine if
the characteristics of exposure to
extreme low DO can be predicted from
short-term continuous DO records
(Holland 1990). Analyses of the data for
the Virginian Province showed that
three instantaneous DO profile
measurements best characterized the
DO status of a site. In contrast, in the
Louisianian Province the minimum DO
measured over a 24-hour period was
most successful in characterizing both
low and high frequency hypoxia sites.
These differences have logistical
implications for bioassessment of
estuarine and coastal marine waters in
that instantaneous DO measurements
can be made with CTD meters equipped
with a DO probe; the 24-hour minimum
DO measurements require the use of a
continuous recording DO meter that
must be deployed and subsequently
retrieved. Consequently, dissolved
oxygen is an important habitat
parameter, but the manager must
exercise care in both sampling design
and data interpretation when attributing
biotic responses to potential hypoxia.
Collection of DO in Tier 1 of these
procedures should include an
instantaneous measurement at the same
stations and times as biological samples
are collected. Tier 2 should include
measurement of DO in the early
morning at each station as a minimum.
Tier 3 should include DO collected along
a depth profile from surface to within 1-
m of the bottom at 1-m intervals. For
more detailed characterization of DO
conditions, particularly at sites which
may undergo hypoxia, recording DO
meters may need be deployed in Tier 3.
In any case, as the EMAP experiences
indicate, careful DO profiles should be
established for each region surveyed
before any presumptions about
community response are made.
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3.3.4 pH
Another important indicator of the
chemical condition of estuarine and
coastal marine waters is pH. In
estuaries, pH will usually be controlled
by the mixing of seawater solutes with
those in the fresh water inflow. A major
factor influencing the pH of estuarine
waters is the carbon dioxide solubility,
which is a function primarily of salinity
and secondarily of temperature.
Seawater is a very stable buffering
system containing excess bases, notably
boric acid and borate salts, carbonic acid
and carbonate. Surface seawater pH
usually ranges between pH 8.1 and 8.3.
River waters usually contain a lower
concentration of excess bases than
seawater; this shifts the carbonate
buffering system toward a higher
concentration of free carbon dioxide and
lower pH in the upper reaches of rivers.
Because fresh water inflow to estuaries
is typically much less buffered than
seawater, greater variation in pH is
observed in the less saline portions of
estuaries than near their mouths. The
range of pH values observed in the
upper reaches of estuaries can be 7.5 -
9.0.
Measurement of pH in estuaries and
coastal marine waters can provide an
indication of possible pollutant input
(e.g., releases of acids or caustic
materials) or high concentrations of
phytoplankton (due to photosynthesis
and respiration, pH varies inversely
with the free carbon dioxide
concentration and directly with DO).
3.3.5 Turbidity
The major component of turbidity in
estuaries is silt. The volume of silt
discharged into estuaries by streams and
rivers varies seasonally, with the
maximum discharge occurring during
the wettest months. Silt may also be
resuspended from sediments within
estuaries. Turbidity has two primary
effects in estuaries. First, light
penetration is reduced, which directly
affects primary production and
abundance of aquatic macrophytes in
the estuary. Second, settling of the
particulate matter can result in
deposition zones of mud, silt, other
sediments, and detritus. This deposited
material can cause changes in the
composition of benthic invertebrate
assemblages. For example, deposition of
mud and silt can result in the clogging
of gills of oysters and other filter-feeding
species and a loss of a hard substrate
required by these species. In coastal
areas, the deposition of silt in pockets of
uneven sandy bottom contributes to the
"patchy" distribution of benthic
invertebrate species, especially annelids,
amphipods, and isopods. Deposited
material can also contain particle-
adsorbed contaminants; this can result
in contaminated sediment "hot spots".
In contrast to these negative effects on
the benthic invertebrate assemblage,
turbidity can have positive effects on the
fish assemblage by increasing protection
from predators by reduced visibility.
Turbidity can be easily assessed (as light
penetration) using a Secchi disk, which
is probably the most widely used
method for estimating light penetration
(USEPA 1992). Secchi disks are easy to
use, the results are easy to interpret, and
they are suitable for estimating light
attenuation coefficients through the
water column. Secchi disk
measurements may vary somewhat
because of interpersonal differences in
visual acuity of observers, and,
therefore, caution must be exercised
when comparing Secchi disk readings
taken by different investigators.
If measurement of turbidity per se is
deemed necessary by a state, it may be
accomplished in situ by using a
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Habitat Characterization
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transmissometer or turbidimeter as part
of a CTD system. Nephelometry is the
preferred method for measuring
turbidity because it is more sensitive,
effective over a wider range of
turbidities, and less sensitive to particle
size variations than other methods
(USEPA 1992).
3.3.6 Nutrients
Nutrient fluxes are central in controlling
the primary and secondary production
of estuaries. Estuarine autotrophs (i.e.,
algae, diatoms, vascular plants) require
numerous macro- and micronutrients
and vitamins, including C, N, P, Si, S, K,
Mg, Na, Ca, Fe, Mn, Zn, Cu, B, Mo, Co,
V, thiamin, cyanocobalamin, and biotin
(Hutchinson 1967 cited in Day et al.
1989). Higher trophic levels are
influenced indirectly by nutrients
through their dependence on a
phytoplankton food base. Nitrogen,
phosphorus, carbon, and silicon (used
by diatoms) are the most studied of the
nutrients in estuaries and coastal marine
waters (Bricker and Stevenson 1996).
This guidance document focuses
particularly on nitrogen and phosphorus
as the two key, potentially limiting and
more manageable nutrients for the
autotrophic assemblages; i.e.,
macrophytes, phytoplankton, to be
incorporated in bioassessment
procedures. The measurement of water
column nutrient concentrations in Tiers
2 and 3 will aid in identifying possible
sources of biological impairment.
NOAA maintains a nationwide database
on eutrophication and toxic algae
blooms that can be cited to provide
water column information.
It is a basic tenet of botany that multiple
nutrients are necessary for plant growth,
and that a shortage of any single
nutrient will limit further growth. Thus,
estuaries are sometimes referred to as
"nutrient-limited." This concept is
based on the finding that, under good
growth conditions, algae have a
relatively stable N:P atomic ratio of
about 15-16:1. This ratio is frequently
known as the Redfield ratio (Redfield
1958, Correll 1987, Malone et al. 1996).
The Redfield ratio is an approximation
and can vary depending on the stage of
algal cell division, changes in light
intensity or quality, or temperature
(Correll 1987). Even considering these
factors, measurement of nitrogen and
phosphorus concentrations in estuarine
and coastal marine waters provides a
useful benchmark for evaluating the
possible effects of increased loadings of
these nutrients. Nutrient limitations in
estuarine and coastal marine waters may
change seasonally in response to
temporal variations in nutrient loadings
in the watershed and in hydrologic
patterns. In the Chesapeake Bay,
phytoplankton appear to be P-limited
during spring when biomass reaches its
annual maximum and N-limited during
summer when phytoplankton growth
rates are highest (Malone et al. 1996). In
North Carolina estuaries, N-limitation
occurs across a trophic gradient of
highly productive (Pamlico), moderately
productive (Neuse), and less productive
systems (Beaufort, Morehead City area)
(Mallin 1994). Phosphorus may be co-
limiting in some of these areas during
portions of the year (Mallin 1994). In the
Florida Keys and adjacent Florida Bay,
LaPointe and Clark (1992) determined
that phosphorus is the primary limiting
nutrient, with nitrogen being co-
limiting. Smith and Hitchcock (1994)
concluded that phosphorus (and silica)
potentially limits phytoplankton growth
in the Louisiana Bight during winter-
spring, particularly at low salinities. In
late summer nitrogen may be limiting in
higher salinity waters of the Louisiana
Bight.
Nitrogen and phosphorus occur in
estuarine and coastal marine waters in
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-13
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many forms which can be variously
described in terms of oxidation state,
phase (solid-liquid-gas), chemical
structure, or analytical method.
Nitrogen forms are the most diverse,
with nitrogen compounds ranging from
NO3 to NH4 . Dissolved nitrogen
species that could be incorporated into
chemical analyses of this nutrient
include total dissolved N (TDN), and
dissolved inorganic nitrogen (DIN =
NH* + NO3 + NO2)(LaPointeand
Clark 1992). Nitrate concentrations are
typically controlled largely by external
inputs to estuarine and coastal marine
waters via land runoff. In some areas
(e.g., Chesapeake Bay) atmospheric
deposition may account for an
important fraction of the nitrogen load
to the water body (Dickerson 1995,
Boynton et al. 1995). Ammonia
concentrations are highest in waters
receiving large inputs of sewage (Day et
al. 1989). Dissolved organic nitrogen
(DON) can be calculated as TDN minus
DIN (LaPointe and Clark 1992).
Measurements of total dissolved P
(TDP) and soluble reactive phosphorus
(SRP) can be used to estimate dissolved
organic phosphorus (DOP = TDP - SRP)
(LaPointe and Clark 1992).
3.3.7 Contaminants
Measuring organic compounds and
metals is particularly important because
of the adverse effects they can have on
aquatic life and on human health and
recreation if these contaminants enter
the food chain. Sources of organic and
inorganic chemical contaminants
include direct release to the water body,
urban runoff, atmospheric deposition,
industrial and municipal discharges,
and upstream runoff (Velinsky et al.
1994, Wade et al. 1994). Organic and
metals contaminants in the water
column will usually be adsorbed onto
sediment particles, settle to the bottom,
and become a source of toxicity to
organisms and bioaccumulation to the
food chain. Contaminant analyses
should be tailored to the types of
substances known or suspected as
chemicals of potential concern at a site.
Chemical concentrations should be
compared to applicable sediment quality
guidance documents to aid in
interpretation and to provide an effort-
based assessment method. Results of
any toxicity tests conducted should be
compared against results from controls
and against statistical standards to
provide relative rankings. Chemical
analyses, toxicity tests, and benthic
analyses constitute the sediment quality
triad, originally proposed by Long and
Chapman (1985).
The Sediment Quality Triad approach,
(SQT) (Long and Chapman 1985,
Chapman et al. 1987, Long 1989,
Chapman 1996) can be used to assess
pollution-induced estuarine and coastal
marine system degradation (Schlekat et
al. 1994). In an analysis of sediment
metals concentrations from 497 sites in
Gulf of Mexico estuaries, Summers et al.
(1996) normalized metals concentrations
for extant concentrations of aluminum
to identify the concentrations expected
from natural sources versus
anthropogenic sources. Krumgalz
(1993) applied a "fingerprints" approach
to estuarine and coastal marine
pollutant source identification. This
approach assumes that if anthropogenic
pollutants in a particular area had
originated from the same source, then
pairwise relationships between the
concentrations of these pollutants in
sediments from various sampling sites
in the contaminated area would be
linear. The correlations between
pollutants will depend on the origin of
the contaminants and on the patterns of
mixing contaminated sediments and
contaminants with "pure" sediment.
Thus, the "fingerprints" can be used to
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Habitat Characterization
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trace the distribution of contaminants
from a source, or conversely, to identify
potential sources.
3.3.8 Depth
Depth characterization is important for
evaluating DO, temperature and salinity
profiles, tidal regime consistency, and
the percent of the water column that is
photic. This may be especially
significant in coastal areas where
bathymetry changes can be great and
other potentially related distinctions
such as grain size are not as evident.
3.4 Bottom Characteristics
The SQT approach is generally the most
comprehensive assessment of relative
sediment quality. In this approach data
are collected to determine
concentrations of potentially toxic
chemicals in sediments, to measure the
relative bioavailability and toxicity of
sediment-associated toxicants with
laboratory bioassays, and to identify
degradation of resident infauna possibly
attributable to the contaminants.
Chemical data can be generated through
analyses of the bulk sediments and
compared to applicable sediment quality
guidelines (SQGs), proposed or
promulgated criteria or standards
wherever they exist, and relevant
sedimentological factors such as grain
size, total organic carbon, or aluminum.
Data analyses can be conducted to
identify both sites and chemicals of
potential concern. Chemicals of highest
potential concern are those in which
SQG or other applicable values were
exceeded most frequently and by the
largest amount. These chemicals also
would be expected to show strong
associations with measures of toxicity.
Moreover, chemicals of highest concern
may be those determined to be
bioavailable and bioaccumulative in
laboratory exposures (Chapman et al.
1988). If possible, historical data should
be used to focus the chemical analyses.
Toxicity data can be generated through a
battery of short-term tests performed
under the controlled environment of the
laboratory. Amphipod survival tests,
which are most frequently used in North
America, are done with exposures to
solid-phase sediments and percent
survival is measured after 10-days.
These acute tests often are accompanied
by tests of other sediment phases (e.g.,
pore waters and solvent extracts) with
sublethal endpoints (Long et al. 1996).
Data from the tests provide information
for ranking and prioritizing sampling
sites according to their potential for
causing adverse effects among resident
infauna. Confirmation of adverse effects
among the infauna must be done with
analyses of samples collected from the
same locations tested for chemical
concentrations and toxicity. Measures of
species richness, total abundance,
relative abundance of crustaceans
(particularly inf aunal amphipods)
and/or other relatively sensitive taxa
provide information on the degree to
which resident biota have been
adversely affected. Chapman (1996)
provided useful guidance on the
interpretation of the SQT data.
Measurements of bottom characteristics
of estuaries and coastal marine waters
provide important data for interpreting
the condition of targeted biological
assemblages. Sediment grain size
influences the spatial distribution of
benthic macroinvertebrates and fishes.
Fine-grained sediments can adsorb
contaminants, creating a source of
potential impairment to bottom
communities. Organic carbon found in
these sediments can mediate the
concentrations of DO, organic
contaminants, and metals. Measuring
the depth of the sediment oxidation-
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-15
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reduction potential discontinuity layer
provides information on aerobic vs.
anaerobic respiration in sediments.
Sediment nutrients such as particulate
nitrogen and phosphorus can be re-
mobilized by physical disturbance or
changes in the water column chemistry
to become an additional nutrient source
leading to potential eutrophication,
phytoplankton blooms, and hypoxia of
estuarine and coastal marine waters.
Finally, sediment contaminant
measurements can provide insights on
factors that might limit biological
assemblages and lead to potential
human health effects.
3.4.1 Sediment Grain Size
The objective of measuring sediment
grain size is to detect and describe
spatial and temporal changes of the
benthic habitat. The availability of
sediment contaminants is often
correlated with sediment grain size
because more sediment contaminants
are adsorbed onto small grained
sediments due to their greater surface
area. Likewise, grain size information
may explain the temporal and spatial
variability in biological assemblages
related to an organism's ability to build
tubes, capture food, and escape
predation. Grain size data may be used
to determine the extent of or recovery
from environmental perturbations, to
evaluate the condition of benthic
habitats, and to assist in providing early
warnings of potential impacts to the
estuarine ecosystem (USEPA 1992).
The most common measurements and
classifications of sediment grain size are
as follows:
>• clay < 0.004-mm
* silt 0.004 - 0.064-mm
> sand 0.064 - 1.0-mm
*• gravel > 1.0-mm
3.4.2 Total Organic Carbon, Total
Volatile Solids, and Acid
Volatile Sulfides
Total organic carbon (TOC) and acid
volatile sulfides (AVS) are considered by
some to be the most important sediment
properties determining the
bioavailability and toxicity of certain
organic compounds and trace metals in
sediments (DiToro et al. 1990, DiToro et
al. 1991). The importance of these
factors is based on an equilibrium
partitioning approach. This approach
assumes that the bioavailable fraction of
chemicals in sediment is correlated to
that fraction in the porewater rather
than whole sediment concentrations.
Therefore, factors that influence the
partitioning of compounds between
sediment and porewater will govern
bioavailability. In addition, it is
assumed that equilibrium exists among
the phases (hence, the name
"equilibrium partitioning"). For non-
ionic hydrophobic organic chemicals,
the primary factor influencing
partitioning is TOC; for certain divalent
cationic metals; i.e., cadmium, copper,
nickel, lead, zinc, an important binding
phase is the acid volatile sulfide fraction.
The development of sediment quality
criteria by USEPA is based on these
assumptions and a comparison of
predicted porewater concentrations to
existing water quality criteria (DiToro et
al. 1991, Ankley et al. 1996).
Normalization of non-ionic organic
compounds is accomplished by
calculating chemical concentrations per
gram of sediment organic carbon rather
than per gram of dry sediment. This
approach allows comparisons of the
potential bioavailability of non-ionic
organic compounds across different
sediment types and can be used to
screen for chemicals of concern. For an
explanation for how to apply this
approach to calculate sediment quality
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Habitat Characterization
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criteria the reader is referred to DiToro
et al. (1991).
Although SQGs (Sediment Quality
Guidelines) derived for organic
compounds and trace metals reported
on a dry weight (bulk) basis have been
shown to be reliable and predictive of
both non-toxic and toxic conditions
(Ingersoll et al. 1996, MacDonald et al.
1996, Long et al. 1998a); these values do
not account for the relative
bioavailability of sediment-associated
chemicals. In areas in which high trace
metal concentrations are known or
suspected, or in which SQGs are
exceeded, further evaluations of
chemical contamination may be aided in
subsequent analyses by use of the
simultaneously extracted metals/acid
volatile sulfides (SEM/AVS) tool to
provide estimates of bioavailability.
The AVS normalization approach
assumes that select trace metals bind to
sediment sulfide, specifically the sulfide
fraction soluble in cold acid, known as
AVS (Allen et al. 1993). The
bioavailability of trace metals capable of
forming insoluble metal sulfides will be
determined by the proportion of these
metal ions not bound to sulfide. Hence,
on a molar basis, if the concentration of
SEM is less than the molar concentration
of AVS, all of the metals should
precipitate as metal sulfides and not be
bioavailable. Conversely, if SEM
exceeds AVS then free metal ions may
exist in the porewater. This approach
appears to work best in situations when
the ratio of [SEM]/[AVS] is less than 1.0
or the difference between SEM and AVS
concentrations is less than 0.0 (Hansen
et al. 1996). That is, the SEV/AVS tool is
primarily intended for use as a no-
effects tool and caution is advised in
using it as a predictor of toxicity or other
effects. Long et al. (1998b) reported that
the SEM/AVS tool and SQGs based
upon bulk sediment chemistry for trace
metals performed equally well in
correctly predicting samples as either
toxic or non-toxic. For an excellent
discussion of the applicability,
advantages and disadvantages of this
approach, the reader is referred to
several review papers in Environmental
Toxicology and Chemistry, Volume 15,
#12.
3.4.3 Sediment Oxidation-Reduction
Potential
There are four oxidation-reduction
(redox) processes related to biological
respiration that occur in benthic
sediments. These chemical reactions,
which depend on the availability of
electron acceptors; i.e., oxygen, nitrate,
sulfate, and carbonate, stratify the
sediments into four zones. Oxygen is
the electron acceptor used for aerobic
respiration and is the most important
oxidizing agent at the surface of the
sediments. Nitrate reduction occurs
between 0- and 4-cm and produces
elemental nitrogen. This is followed by
sulfate reduction which produces
hydrogen sulfide. Carbonate reduction
occurs between 10- and 50-cm and
results in the production of methane.
Aerobic respiration will be the dominant
reaction as long as oxygen is available.
The depth at which oxygen is fully
depleted and the redox potential goes to
zero has been termed the redox potential
discontinuity (RPD) layer (Day et al.
1989). Burrowing organisms oxidize the
sediments and hence will increase the
zone of habitability as reflected in the
depth of the RPD layer. Color changes
in the substrate occur as a result of the
oxidation and reduction of metals, such
as iron, in the sediments. The upper few
centimeters may appear brown from the
formation of iron oxides and
hydroxides, whereas the zone of
reduction turns gray and eventually
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-17
-------
black in the deeper sediments from the
formation of ferrous sulfide and pyrite.
When examining a cross-section of a
sediment core sample, the RPD layer is
visibly noticeable by this change in
color. The depth of this color change
should be recorded because, as noted
above, it indicates the zone of
habitability for benthic infauna. The
closer to the sediment surface this color
change appears, the less available
dissolved oxygen exists in the sediment
porewater.
3.4.4 Sediment Contamination
Sampling the surface sediments for the
presence of contaminants can provide
insight on factors limiting the benthic
community, as well as the potential for
impacts to human health; i.e., by
biomagnification or bioaccumulation in
the food chain or by the contamination
of shellfish. Metals and organic
chemicals entering estuaries from fresh
water inflows, point sources of
pollution, and various nonpoint sources,
including atmospheric deposition,
generally are retained within estuaries
and accumulate within the sediments
(Forstner and Wittman 1981, Hinga
1988, Nixon et al. 1986, Schubel and
Carter 1984, Turekian 1977) because of
the affinity of most contaminants for
particle adsorption (Hinga 1988;
Honeyman and Santschi 1988).
Chemical and microbial contaminants
generally adsorb to fine-grained
materials in the water and are deposited
on the bottom, accumulating at
deposition sites, including regions of
upper tidal fresh water, low current
velocity, deep basins, and the zone of
maximum turbidity in the upper reaches
of estuaries within which suspended
sediment concentrations are greater than
those either farther upstream or farther
seaward (Schubel and Carter 1984). The
concentration of contaminants in
sediments is dependent upon
interactions between natural (e.g.,
chemical and physical sediment
characteristics) and anthropogenic
factors (e.g., type and volume of
contaminant loadings) (Sharpe et al.
1984).
Bottom sediments in some estuaries
(e.g., harbors near urban areas and
industrial centers) are so contaminated
that they represent a threat to both
human and ecological health (NRC1989,
OTA 1987, Weaver 1984), but
contaminated sediments are not limited
to these areas. Pollutant runoff from
agricultural areas also is an important
source of contaminant input to estuaries
(Boynton et al. 1988, Pait et al. 1989).
The EMAP program uses the NOAA
National Status and Trends (NS&T)
suite of contaminants as the basis for
measurements in homogenized
subsamples of collected sediments
(Figure 3-1). A useful citation for the
NS&T Program list of chemicals is
O'Connor et al. 1994. The NOAA suite
includes chlorinated pesticides,
polychlorinated biphenyls (PCBs),
polyaromatic hydrocarbons (PAHs),
major elements, and trace metals.
3.5 Proposed Habitat
Parameters
Table 3-1 summarizes the proposed
habitat measurements by survey tier and
provides possible sources of
information, methods, and equipment,
as appropriate. Agency-specific
objectives will determine the overall
design of any sampling program. The
following tier distribution is just one
approach possible for gathering and
organizing data. Habitat measurements
are intended to be cumulative across
tiers; that is, the desktop screening of
Tier 0 should be incorporated into Tier 1,
Tiers 0 and 1 parameters should be
incorporated into Tier 2, and Tiers 0,1,
3-18
Habitat Characterization
-------
Polyaromatic Hydrocarbons
(PAHs)
Acenaphthene
Anthracene
Benz(ajanthracene
Benzo(ajpyrene
Benzo(e_)pyrene
Biphenyl
Chrysene
Dibenz(a_mh_)a nth race ne
2, 6-di me nhyul naphthalene
Fluoranthene
Fluorene
2- methyl naphthalene
1 -methylnaphthalene
1 -methylphenanthrene
Naphthalene
Perylene
Phenanthrene
Pyrene
Benzo(b)fluoranthene
Acenaphthlyene
Benzo(k)fluoranthene
Benzo(g,h,i)perylene
Maior Elements
Aluminum
Iron
Manganese
Silicon
Trace Elements
Antimony
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Selenium
Silver
Tin
Zinc
DDT and its metabolites
o,p'-DDD
p,p'-DDD
o,p'-DDE
p,p'-DDE
o,p'-DDT
p,p'-DDT
Chlorinated pesticides other than DDT
Aldrin
Alpha-Chlordane
Trans-Nonachlor
Dieldrin
Heptachlor
Heptachlor epoxide
Hexachloro benzene
Lindane (gamma-BHC)
Mi rex
18 PCB Congener
Congener Location
Number ofCIs
8 24'
18 2 2' 5
28 244'
52 2 2' 5 5'
44 2 2' 3 5'
66 2 3' 4 4'
74 2 4 4' 5
99 2 2' 4 4' 5
101 2 2' 4 5 5'
118 2 3' 4 4' 5
153 2 2' 4 4' 5 5'
106 ? 3 3' 4 4'
I \J\J £- \J \J *T T^
138 2 2' 3 4 4' 5'
187 2 2' 3 4' 5 5' 6
128 2 2' 3 3' 4 4'
180 2 2' 3 4 4' 5 5'
170 2 2' 3 3' 4 4' 5
1QC; 1 1' ^ V A A' ^ R
1 c/CJ ^L^lOOHHUO
206 2 2' 3 3' 4 4' 5 5' 6
209 2 2' 3 3' 4 4' 5 5' 6 6'
Other measurements
Tributyltin
Acid volatile sulfides
Total organic carbon
Figure 3-1
Chemicals
measured in
sediments by
the EMAP-
Estuaries
program.
Refer also to
the NS&T
Program list of
chemicals
(O'Connor et
al. 1994).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-19
-------
and 2 parameters should be
incorporated into Tier 3. The habitat
tiers described here should be used with
the corresponding biological survey tier.
3.5.1 TierO
The purpose of a Tier 0 assessment is to
support the planning for monitoring and
more detailed assessments. Tier 0 is a
desktop screening assessment in which
documented information for the estuary
or coastal marine areas of concern is
compiled from sources including
databases, peer-reviewed and gray
literature, state and federal agencies,
universities, and local experts. A Tier 0
assessment should always precede any
of the three subsequent tiers.
Examination of long-term data records
(e.g., salinity, DO, climate) is
particularly important for identifying
the variability which must be accounted
for in the design of subsequent field
monitoring. Habitat parameters to
examine in Tier 0 include:
Area and Geomorphometric
Classification
The size and classification of an estuary
indicates its potential to respond to
various impacts. Estuary types include
coastal plain, lagoon, fjord, and
tectonically-caused. Circulation type
(e.g., gravitational, tidal, wind-induced)
influences current patterns, salinity
regimes, and thermal and dissolved
oxygen patterns.
Habitat Type
Identifying and delineating the various
habitat types (Section 3.3) that occur in
the estuary or coastal marine waters will
be necessary for partitioning the natural
variability in the system. The extent of
such a delineation will depend on the
size of the area of concern and the
nature of the environmental gradients
present. Initial partitioning will
probably be based on salinity, sediment
type, and depth.
Watershed Land Use and Population
Land use and population data for the
watershed will help to identify classes of
contaminants and other stresses that
may affect the water body. For example,
agricultural areas located near an
estuary might be expected to be sources
of nonpoint loading of nutrients,
pesticides, herbicides, and sediment.
Urban areas may contribute toxic
compounds via stormwater runoff. The
pattern and magnitude of population
density in the watershed can potentially
provide clues regarding the potential for
human-induced impacts to the water
body.
Water Column and Bottom
Characteristics
Historic data on water column and
bottom characteristics is central for
identifying system variability and to
support the design of subsequent
monitoring. This data can also be used
by states to identify types and locations
of potential impairment, for example,
areas with high concentrations of water
column nutrients, suspended sediment,
or sediment contaminants.
3.5.2 Tier 1
Tier 1 is a basic field assessment that is
used for screening purposes to identify
potential reference and impaired sites.
For biocriteria development purposes, it
is adequate for only rudimentary habitat
classifications and evaluations. It
identifies the general physical
characteristics of the estuary or coastal
region, the habitats, and the potential
sources of anthropogenic stress. Tier 1
relies heavily on existing information
identified in Tier 0 and supplemented
3-20
Habitat Characterization
-------
by one-time easily-measured field
parameters, which are measured
concomitantly with the collection of
biological data. Much of the habitat
information needed in this tier can be
acquired from state or federal agency
records. Depending on the needs of the
state, Tier 1 habitat characterizations
may include the following elements:
Estuary Characteristics
Information on estuary characteristics is
essential for the development of
appropriate sampling strategies. Data to
be compiled in this category includes
estuary area, geomorphometric
classification (e.g., classical coastal plain
estuary, lagoon), and habitat types
present (e.g., hard bottom, soft bottom).
These data can be obtained from USGS
maps, NOAA charts, and reports and
data archives at federal and state
agencies and universities.
Watershed Characteristics
Knowledge of watershed characteristics
can provide important information for
determining appropriate sampling
station locations and for evaluating
possible sources and causes of biological
and habitat impairment. Data to be
compiled for this category include
watershed land use, human population
density, NPDES discharge locations, and
vegetative cover. These data are likely
to exist at federal, state, and local
agencies and universities.
Water Column Characteristics
The characteristics in a water column
play a key role in determining the biota
present at a given location and their
broader distribution patterns.
Parameters to be measured in Tier 1 in
the field include salinity and
conductivity, DO, temperature, pH,
turbidity and Secchi depth. Records of
tidal stage and current velocity at the
time of sampling at each station should
be acquired from NOAA.
Bottom Characteristics
Characteristics of bottom sediments also
are key determinants of aquatic biota
present in estuaries and coastal marine
waters. Parameters to be measured in
Tier 1 include depth, dominant sediment
type, total volatile solids, and sediment
RPD layer depth.
3.5.3 Tier 2
Tier 2 provides the information
necessary to develop a quantitative
ranking of the sites that can be used to
prioritize resources and sampling
efforts. Habitat information collected in
Tier 2 will be used in the development
of biocriteria. In addition to Tier 1
habitat characterization, Tier 2 includes:
Water Column Nutrients
Nutrients in the water column
determine the nutrient state of the area
and may indicate possible sources of
impairment, particularly nonpoint
source runoff.
Sediment Characterization
The organisms closely associated with
the bottom are strongly influenced by
such sediment characteristics as the
average grain size and the percent
composition of silt, sand, and clay (Day
et al. 1989). These characteristics
determine the structure of the benthic
community based on the preferences of
the major groups of organisms. For
example, suspension feeders are found
more often in firmer, sandier substrates
than are deposit feeders; interstitial
meiofauna are predominant in sandy
areas, whereas burrowing meiofauna
prefer silty mud. Although a high
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-21
-------
organic content in the sediments can
increase the rate of oxygen depletion,
there are many organisms that require
high concentrations of organic matter.
Sediment characteristics to be measured
in Tier 2 include percent sand vs. silt-
clay, mean grain size, total volatile
solids, and total organic carbon.
Shorezone Vegetative Cover
Characterization
Shorezone vegetation provides stability
for beaches, wetlands, banks, and cliffs,
serving to reduce erosion and nonpoint
source runoff to the water body. As
such, evaluation of shorezone vegetative
cover is important for identifying
possible sources of impairment and
remedial approaches. Terrestrial
riparian vegetated areas to consider are
uplands and the floodplain. Areas of
emergent, intertidal, and submerged
vegetation should also be characterized.
Shorezone vegetative cover is important
for reducing nutrient and sediment
loading to estuaries from nonpoint
source runoff, attenuating incident wave
energy and reducing shore erosion, and
providing important nursery and
feeding habitat for migratory species.
Salt marshes and aquatic macrophytes
have high gross primary productivity
and provide a source of autochthonous
organic matter for detrital feeders in
adjacent waters. An assessment of the
coverage and types of shorezone
vegetation can contribute to the overall
assessment of the condition of estuarine
and coastal marine habitat. Evaluation
of vegetative cover is most easily
accomplished by aerial photography
and mapping coupled with ground-
truthing. Detailed procedures used for
photography and mapping aquatic
macrophytes are provided by Orth et al.
(1993) (Chesapeake Bay), Ferguson and
Wood (1994) (North Carolina estuaries),
and USEPA (1992) (National Estuary
Program) and can be adapted for use in
other areas.
3.5.4 Tier3
Tier 3 provides a detailed assessment
with a high level of certainty of the
biological or habitat condition of the
estuarine and coastal marine
environment. It is the definitive
assessment level to distinguish habitat
variation from anthropogenic impacts
when the biocriteria have been
exceeded. Tier 3 focuses on biological
community level investigations and
thoroughly integrates the physical,
chemical and biological data to yield a
detailed impact assessment. In addition
to the habitat parameters compiled in
Tier 0 and measured in Tiers 1 and 2,
sediment oxidation-reduction potential,
sand/silt/clay proportions, sediment
contaminants, and water column
pesticides, herbicides, and metals,
nutrient speciation, and AVS/SEM as
needed may be measured in this tier.
Tier 3 provides the detailed diagnostic
information necessary for: (1)
identifying specific problem sources in
the drainage area; (2) delineating
mitigation options for the identified
problems; and (3) preparing written
management plans for the estuary or
coastal marine area of interest.
Although the data collected in Tier 3
cannot prove cause-and-effect
relationships between identified
stressors and ecosystem responses, they
can provide a strong correlation and a
definitive assessment, with a high
degree of certainty, of the biological
integrity of the target waters and their
habitats.
3-22
Habitat Characterization
-------
Table 3-1.
Habitat measurements for estuaries and coastal marine waters.
Habitat
Measurements
Assessment Tier
0
1
2
3
Information Source
Method(s) and
Equipment
Historical Information
Estuary area
Geomorphometric
classification
(classical coastal
plain estuary; salt
marsh estuary;
lagoon; fjord;
tectonically-caused
estuary)
Habitat type
(seagrass beds; hard
bottom; soft bottom;
water column;
emergent marsh;
mudflat; sandflat;
gravel/cobble; rocky)
Watershed land use
Population density
NPDES discharges
Vegetative cover
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
USGS quad maps
USGS quad maps
NOAA bathymetry
charts; historic surveys
by federal, state
agencies and
universities
USGS land use maps;
state planning
agencies; local zoning
agencies
US census data
State water quality
agency
Historic surveys by
federal, state agencies
and universities
Can be estimated from
maps or using CIS
Can be estimated from
maps or using GIS
Can be estimated from
maps or using GIS
Field-collected Information: Water Column Characteristics
Salinity, conductivity
DO
Temperature
PH
/*
/*
/*
/*
/
/
/
/
/
/
/
/
/
/
/
/
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities.
Conductivity cells
(CTD meters)
CTD meter equipped
with O2 probe,
recording DO meters
for Tier 3 may be
needed
CTD meter, satellite
remote sensing.
CTD meter equipped
with pH probe
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
3-23
-------
Table 3-1 (Cont'd). Habitat measurements for estuaries and coastal marine waters.
Habitat
Measurements
Turbidity, Secchi
depth
Nutrients (nitrogen
species,
phosphorus)
Organics, metals
Assessment Tier
0
/*
/*
/*
1
/
2
/
/
3
/
/
/
Information Source
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Method(s) and
Equipment
Secchi disk;
transmissometer,
nephelometer,
turbidimeter if desired
Spectrophotometry
Standard methods for
selected suite of
contaminants
Field-collected Information: Bottom Characteristics
Depth
Sediment grain size
Total volatile solids
Total organic carbon
Acid volatile sulfides
Sediment reduction-
oxidation potential
Sediment
contamination
/*
/*
/*
/*
/*
/*
/*
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Historic data from
federal, state agencies
and universities
Meter wheel,
fathometer,
hydrostatic pressure
sensor
Sieving or separatory
column combined with
pipette analysis for
silt-clay fraction
Standard methods
Standard methods
Standard methods
Visual determination
of the depth of change
in sediment color in
core
Standard methods for
contaminants selected
Historic data should be included in Tier 0; the tier does not include any field collection of
new data.
3-24
Habitat Characterization
-------
Chapter 4
Physical Classification and
the Biological Reference
Condition
Estuaries and coastal marine waters
span a range of spatial scales from small
subestuaries, embayments, and coastal
lagoons to large estuaries (e.g.,
Chesapeake Bay, Puget Sound) and
open coastal waters. The procedures
described in this document rely on a
spatial hierarchy to accommodate the
potentially large range of water bodies
that states may assess. The top level in
the hierarchy is a geographic region
containing comparable landform and
climate. The provinces used by the
EMAP-Estuaries program (e.g.,
Carolinian, Columbian) are examples of
this hierarchical level. The next level
consists of individual watershed
characteristics. Key attributes to
consider at this level include land cover,
the watershed-to-basin area ratio, and
the geology and soils of the watershed.
Examples of the use of this hierarchical
level in estuarine assessment are the
Chesapeake Bay watershed, New Jersey
coastal bays, or California saline
lagoons. The lowest level in the
hierarchy considers habitat
characteristics. As discussed in Chapter
3, the three primary variables used to
partition spatial heterogeneity at this
level are sediment grain size, salinity,
and water depth. Description of
sampling sites as "low mesohaline,
mud" or "10-m depth, gravel" would be
examples of this level of the hierarchy.
Reference conditions are expectations of
the status of biological communities in
the absence of anthropogenic
disturbances and pollution, and are
usually based on the status of multiple
reference sites. Ideally, reference sites
are minimally impaired by human
pollution and disturbance. The care that
states use in selecting reference sites and
developing reference condition
parameters, together with their use of
standardized survey techniques, will
directly influence the quality of the
resulting water body assessment. At a
minimum, reference conditions should
be identified for each of the estuary and
coastal marine classification categories
developed by a state.
Reference conditions reflect the biotic
potential for estuaries and coastal
marine waters if they are not impaired
by human activity or pollution.
Attainment of an aquatic life designated
use is evaluated against the reference
condition as a key element in the
biocriteria for that aquatic life use.
Biocriteria may be set higher than the
best conditions observed in the data
available for an area that is highly
impaired. In this instance, interim,
incremental criteria may be established
as the regional authority works on
environmental recovery.
4.1 Classification Approach
The biological reference condition must
be determined separately for each
estuarine or coastal marine physical
class. Assessing biological condition
requires reference conditions for
comparison and for development of
models and indexes to help establish
biocriteria and detect impairment.
There is no single "best" classification
nor are resources available to determine
all possible differences between all
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-1
-------
estuarine and coastal marine sites in a
region. The key to classification is
practicality within the region or state in
which it will be applied; i.e., local
conditions determine the classes.
Classification will depend on regional
experts familiar with the range of
estuarine conditions in a region as well
as the biological similarities and
differences among the assessment units.
Ultimately, physical classification may
be used to develop a predictive model of
those estuarine and coastal marine
characteristics that affect the values of
the biological metrics and indexes at
reference sites.
The regional differences in estuarine and
coastal marine biological communities
across the United States must be
accounted for in the development of a
biological criteria program. These
differences can be identified by
comparing the biology of water bodies
of interest to a reference condition. As
biological conditions change across the
country, the reference conditions will
also change. To account for the regional
geographic differences that create
structural differences in biological
habitat (either natural or human-
induced), states should classify estuaries
and coastal marine waters or segments
thereof into groups. A reference
condition should be established for each
of these classification groups. Biotic
index comparisons can then be made
within each classification group and
inappropriate biological comparisons
between different classes will be
precluded. Moreover, the aquatic life
expectations of water bodies are
tempered by realistic expectations. With
biological systems, it is not possible to
set uniform, nationwide numeric
biological criteria.
Estuaries vary widely in size, shape, and
ecological and physical characteristics,
and a single reference condition that
applies to all estuaries (or coastal marine
waters) would be inappropriate. The
purpose of classification is to group
similar estuarine or coastal marine sites
together; i.e., to prevent the comparison
of apples and oranges. Classifying the
variability of biological measures within
groups inevitably requires professional
judgment to arrive at a workable system
that separates clearly different systems,
does not consider each estuary or
subestuary a special case, and does not
lead to the proliferation of classification
groups. The intent of classification is to
identify the smallest number of groups
of estuarine or coastal marine categories
that under ideal conditions would have
comparable biological communities for
that region. As much as possible,
classification should be restricted to
those characteristics of estuaries and
coastal marine waters that are intrinsic,
natural, reasonably stable over time, and
not the result of human activities.
The approach to reference condition
characterization and classification is
illustrated in Figure 4-1. An idealized
biological potential for estuarine sites is
expressed, for instance, by a fish index
and an inf aunal index, each within a
certain range of values (Figure 4-1). A
test site is compared to the expected
ranges of values, and if its indexes are
outside those ranges, it is judged as not
meeting expectations to some degree.
Test sites are usually not compared to a
theoretical ideal, but to biological
criteria derived from a population of
reference sites. Test sites are judged as
not meeting the criterion if they are
beyond some predetermined limit of the
distribution of reference values.
4-2
Physical Classification and the Biological Reference Condition
-------
4 -,
3 -
2 -
1 -
2.0- 2.7
S/fe a
"Biological Potential"
S/fe
1.7- 3.3
Infaunal Index
Figure 4-1
Graphical
representation of
bioassessment.
Assessment sites
a and £> are
compared to an
ideal biological
potential. Site a is
near its potential.
Site b deviates
from it.
A population of reference sites might
consist of sites which overlap different
classes of estuarine or coastal marine
waters (Figure 4-2). A useful
classification system in this instance
separates these reference sites into
classes with different biological
expectations. The classification itself
must be based on abiotic information
that is minimally affected by human
activities (e.g., ecoregion, estuary and
coastal marine physical characteristics,
basin characteristics), such that test sites
can be assigned to one of the classes
before any biological information is
obtained. Furthermore, the
classification must explain biological
variability in the reference sites (Figure
4-2). Separation into classes then lowers
inherent variation and allows greater
precision in assessing test sites. If test
site "a" in Figure 4-2 is a member of class
II, it would be judged as not meeting
reference expectations. If, however, the
physical classification were not done,
site "a" would be judged to meet
reference expectations because it is
within the limits of all reference sites.
Sequence of Classification and
Characterization
The general sequence of reference
condition characterization is to first
make a preliminary physical
classification of estuaries and coastal
marine areas within a region (Conquest
et al. 1994). Because of natural variation
among and within estuaries and coastal
marine waters, reference conditions will
likely differ with geographic regions,
major salinity zones, depth profiles, and
bottom sediment types. Following
classification, reference conditions are
characterized using some combination
of reference sites, historical data, expert
opinion, and empirical models. A key
element is the use of reference sites
because they represent realistic,
achievable goals and can be regularly
monitored. Historical data and well-
documented expert opinion should be
used to evaluate the information
developed from the reference site data
and possibly from empirical models.
The preliminary classification is
reconciled with the biological data to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-3
-------
Figure 4-2
Classification and
assessment. If
reference sites are
not classified, Site
a is at or near its
potential. If
reference sites are
classified and Site
a is in Class II, it
does not meet its
potential and
might be judged
impaired.
-------
identified in the conterminous United
States (Omernik 1987); but recent
refinements have yielded a greater
resolution for some areas.
It should be noted that many of the
characteristics that can be used as
classification variables are often
subsumed by the geographic region. For
example, watersheds are often similar
within major geographic regions, having
resulted from the regional
geomorphology. Within such regions, it
might be sufficient to classify using only
morphology such as depth, area, or
bathymetry. Examples are the coastal
bays of the Delmarva peninsula or the
sounds behind North Carolina's Outer
Banks.
The EMAP-Estuaries program uses
biogeograpical provinces, defined by:
major climatic zones and prevailing
ocean currents. EMAP coastal areas in
the continental United States are
encompassed within seven provinces
described as Acadian, Virginian,
Carolinian; West Indian; Louisianian;
Californian; and Columbian (Figure 4-3)
(Holland 1990). These roughly
approximate the traditional descriptors
of New England, Mid-Atlantic Bight,
Southeast Coastal, Caribbean, Gulf
Coastal, Southwest, and Northwest
Pacific Coast. For strictly coastal waters,
this may be a sufficient level of
classification.
4.2.2 Estuarine Categories
Estuaries can be categorized into four
major classes based on their
geomorphology: (1) coastal plain
estuaries (Chesapeake Bay; Cape
Canaveral, FL), (2) lagoons (Pamlico
Sound, NC), (3) fjords (Puget Sound),
and (4) tectonically-caused estuaries
(San Francisco Bay) (Day et al. 1989).
While these classifications appear to be
large scale in nature, they can be used to
make initial divisions of estuaries on a
regional scale.
There are two types of coastal plain
estuaries: classical and salt marsh. The
classical coastal plain estuary is
sometimes referred to as a "drowned
river valley." These estuaries were
formed during the last eustatic rise in
sea level and they exhibit
geomorphological features similar to
river channels and floodplains. The salt
marsh estuary lacks a major river source
and is characterized by a well-defined
tidal drainage network, dendritically
intersecting the extensive coastal salt
marshes (Day et al. 1989). Exchange
with the ocean occurs through narrow
tidal inlets which are in a constant state
of flux. Consequently, salt marsh
estuarine circulation is dominated by
fresh water inflow and the tides.
Lagoons are characterized by narrow
tidal inlets and uniformly shallow; i.e.,
less than 2-m deep, open water areas.
The inlets are created by the erosion of
the narrow Pleistocene ridge that
formed along the coast some 80,000
years ago during the interglacial stage
(Day et al. 1989). Lagoons are primarily
wind-dominated and they have a
subaqueous drainage channel network
that is not as well-drained as the salt
marsh estuary.
Classical fjords, formed during the last
ice age, are river valleys that were
carved out by the leading ice edge of
advancing continental glaciers. When
the glacier receded, large rock deposits
were left behind where the leading edge
had stopped. Others are also a result of
glacial scouring of the coast; however,
these estuaries were formed in regions
with less spectacular continental relief
and more extensive continental shelves,
therefore they are much shallower than
typical fjords.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-5
-------
Figure 4-3
Biogeographical
provinces adapted
from Holland
(1990). A form of
preliminary
regionalization
used by EMAP-
Estuaries.
Tectonically-caused estuaries are created
by faulting, graben formation, landslide,
or volcanic eruption. They are highly
variable and they may resemble coastal
plain estuaries, lagoons, or fjords.
4.2.3 Watershed Characteristics
Watershed characteristics affect estuary
and coastal marine hydrodynamics,
sediment and nutrient loads, chemical
and metals contaminant loads, and
dissolved solids. Watershed
characteristics that may be used as
classification variables include:
* Land cover - extent of natural
vegetation;
* Watershed-to-estuary area ratio;
* Soils, geology (erosiveness of soils),
and topography.
4.2.4 Waterbody Characteristics
The third level of the classification
hierarchy focuses on waterbody
characteristics. Attributes that are
considered at this level include
waterbody morphology,
hydrodynamics, and water quality.
Each of these factors has a direct
influence on the biota present in the
waterbody.
Morphological Characteristics
Morphological characteristics of the
estuary or coastal marine waters
influence hydrodynamics and system
responses to pollution. Morphological
characteristics include:
* Depth (mean, maximum);
* Bathymetry - three-dimensional
bottom profile;
* Surface area;
4-6
Physical Classification and the Biological Reference Condition
-------
*• Bottom type and sediments -
substrate and grain size.
Hydrodynamics
Hydrodynamics forms a basis for water
quality. Mixing and circulation patterns
influence nutrient retention and the
development of hypoxia.
Hydrodynamic factors include:
*• Retention time;
*• Stratification and mixing;
*• Currents - speed and direction;
*• Tidal range;
*• Altered inflow to the waterbody,
such as increased or decreased
freshwater inflow from runoff or
diversions.
Water Quality
As noted above, many water quality
characteristics are relatively uniform
within a region because they are the
result of common regional, watershed,
and hydrodynamic characteristics.
Although water quality variables might
be redundant for a classification scheme
if regions are the primary classification
variable, it is frequently convenient to
subclassify according to water quality.
An example is the practice of sub-
dividing estuaries along their gradient
into oligohaline, mesohaline, and
polyhaline regions (see Figure 4-4 for an
example of such a delineation). Water
quality variables useful for classification
are:
*• Salinity and conductivity;
*• Turbidity (Secchi depth);
*• Dissolved oxygen (DO);
> pH.
Human actions (e.g., discharges, land
use, freshwater flow diversions) alter
water quality, especially sediment and
nutrient concentrations, but they can
also affect salinity, conductivity,
turbidity, DO, and pH. Therefore, care
must be taken that classification
according to characteristic water quality
reflects natural conditions and not
anthropogenic impacts. For example, if
estuarine sites are highly turbid due to
poor land management practices in the
watershed, they should not be classified
as highly turbid. Instead, they should
be classified according to the turbidity
class they would have had in the
absence of poor land use.
4.3 Establishing Biological
Reference Conditions
Estuarine and coastal marine reference
conditions should be established using
some combination of four elements: (1)
evaluation of historical data; (2)
sampling of reference sites; (3)
prediction of expected conditions using
models; and (4) expert consensus. Each
element has its inherent strengths and
weaknesses (Table 4-1) that states must
consider relative to their program needs,
available data, and staff expertise.
4.3.1 Historical Data
In many cases, historical data are
available that describe past biological
conditions in the region. For the
purpose of this document, historical
data are datasets collected by programs
that are no longer active; in many cases
using methods now superseded by other
methods. Careful evaluation of these
data provides insight about past and
potential community composition of
estuarine and coastal marine waters and
is an important initial phase in the
biocriteria development process.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-7
-------
Figure 4-4
Estuarine and
coastal marine
biocriteria survey
method useful for
stratified random
(population
distribution)
reference site
selection. Wet
season/high flow
salinity pattern
showing mainstem
sampling sites for
four salinity and
three substrate
classifications.
Wet Season/High Flow
Key
Q mud
[~] transitional
g sand
Q coastal land area
• single comprehensive
survey site
Marine
Review of historical data collected in
these waters is helpful for establishing
potential sample sizes based on the
variability in the record. These records
are usually available in the published
literature, natural history museums,
college and university departments, and
federal and state agencies. Caution
should be exercised in using this
information because some biological
surveys occurred at impaired sites, may
have used incompatible sampling
methods, inappropriate or inadequate
QA/QC procedures, were insufficiently
documented, or had objectives markedly
different from biocriteria determination.
While important for establishing
perspective with respect to current
reference site data, historical
information alone should not be used to
establish precise reference conditions.
4.3.2 Reference Sites
Reference sites refer to locations within
a classification category at which data
are collected to represent the most
natural ambient conditions present. The
biocriteria approach generally uses this
population of reference sites to establish
the collective reference condition that
will in turn be used for comparisons of
metrics and test sites. Reference sites in
estuaries and coastal marine waters
include either sites that are distant from
point and nonpoint sources and may be
applied to a variety of test sites in a
given area, or sites that occur along
4-8
Physical Classification and the Biological Reference Condition
-------
Table 4-1. Comparison of elements for characterizing reference conditions (adapted from
USEPA1998b).
to
.c
"S)
c
£
w
to
o
to
to
tu
c
.*:
CO
0)
§
Historical Data
Yields actual
historical
information on
status.
Inexpensive to
obtain.
Data might be
limited.
Studies likely
were designed
for different
purposes; data
might be
inappropriate.
Human impacts
present in
historical times
were
sometimes
severe.
Present-Day
Biology
Yields obtainable,
best present status.
Any assemblages or
communities
deemed important
can be used.
Even best sites
subject to human
impacts.
Degraded sites might
lower subsequent
biocriteria.
Predictive Models
When sufficient
data are not
available.
Work well for water
quality.
Community and
ecosystem models
not always reliable.
Extrapolation
beyond known data
and relationships is
risky.
Can be expensive.
Expert Consensus
Relatively inexpensive.
Can be better applied
to biological
assemblages than
models.
Common sense and
experience can be
incorporated.
May be qualitative
descriptions of "ideal"
communities.
Experts might be
biased.
gradients of impact; i.e., nearfield/
farfield.
All monitoring sites, whether reference
or test, can vary spatially and
temporally due to natural causes. A
central measure from several reference
sites is used so that natural variability
and uncertainty can be accommodated.
Statistically, this means that the status of
particular estuarine or coastal marine
"test" sites are judged by comparing
them to a population of reference sites
for the particular classification category.
There are 3 approaches for using
reference sites; these are discussed in
Section 4.4.
4.3.3 Models
Mathematical models may be
characterized as descriptive or
mechanistic. Descriptive models (also
known as correlative or statistical
models) describe observed relationships
among measured attributes of a system.
This approach models data without
attention to causal factors. Prediction,
including forecasting and managing, is
the primary goal of a descriptive model,
and the model is considered successful if
it fits the data well. The utility of
descriptive models is often affected by
the quantity and quality of data
available, and in many cases, insufficient
data exists to construct a useful model.
Mechanistic models seek to explain
observed relationships as the result of
underlying processes - they are also
called process models. They typically
consist of a set of state variables, which
describe how the system is "now", and a
set of dynamic equations that describe
how the state variables change over time
(exogenous variables, or "forcing
functions" may also be included). In a
sense, mechanistic models are a set of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-9
-------
descriptive models for each component
of a system. The objective of
mechanistic models is to describe the
system itself and not simply the data
obtained by taking measurements; i.e.,
"fitting the data" is not the prime
objective. Mechanistic models have
many more constraints and are more
time-consuming to construct than
descriptive models due to the need to
match system structure. Despite the fact
that these models are not designed for
prediction, they are often built and used
to forecast and manage ecological
resources for the following reasons: 1)
in some cases, one does not want to
perform an experiment without a
reasonable idea of what will happen
(e.g. work involving endangered
species); 2) some experiments are not
feasible - the amount of data needed for
a multivariate statistical model grows
very rapidly with the number of
variables, and obtaining the data
required for a descriptive model is
prohibitively expensive.
There are two main types of mechanistic
models commonly used in biology and
ecology. Simulation (also known as
management) models are practically
oriented and focus on prediction and
management. In these models,
numerical accuracy is what matters
most, the model need not match the
system processes and structure.
Management models are system specific,
resulting in numerical predictions for
one particular system. Theoretical (also
known as analytical) models focus on
scientific understanding of the system.
These models are highly analytical,
typically involving systems of
differential equations, and emphasize
principles rather than numerical
accuracy. These models have to be
simple enough to allow understanding
of system behavior and what the model
is predicting. This trade-off often
requires that the investigator omit or
estimate many quantitative or unknown
details, and often assumptions about the
interaction of system components
represent hypotheses rather than
empirically-derived relationships.
Theoretical models can apply to many
qualitatively similar systems; they are
useful whenever the phenomenon of
interest occurs across multiple systems.
The degree of complexity of mechanistic
models to predict reference conditions is
potentially unlimited with attendant
increased costs and loss of predictive
ability as complexity increases (Peters
1991). However, these models can
provide much insight into the
interactions which determine ecological
condition. Management-oriented
mechanistic models sacrifice numerical
accuracy in order to capture system
dynamics. These models are
mathematically complex and require
more time and effort to develop than
descriptive models. The primary value
of mechanistic models may be for
understanding ecosystem processes and
evaluating likely system responses when
mitigation projects are implemented.
4.3.4 Expert Opinion/Consensus
In any data evaluation, it is important to
establish a qualified team of regional
specialists so the error inherent in
professional judgment can be reduced.
This team should evaluate the historical
data, the candidate reference sites,
subsequent data collected, and any
models used in the process. This expert
team function is even more important
when no candidate reference sites are
acceptable. Expert consensus then
becomes a workable alternative in
establishing reference expectations.
Under such circumstances, the reference
condition may be defined using a
consensus of expert opinion based on
sound ecological principles applicable to
the region of interest.
4-10
Physical Classification and the Biological Reference Condition
-------
Three or four biologists are convened for
each assemblage to be used in the
assessment, and each expert should be
familiar with the estuaries or coastal
marine waters and assemblages of the
region. The experts are asked to develop
a description of the assemblage in
relatively unimpaired estuaries and
coastal marine waters, based on their
collective experience. The description
developed by consensus will necessarily
be more qualitative than quantitative,
but metrics and metric scoring can be
developed.
It is important that the process used to
review the available information and to
develop a consensus be thoroughly
documented so that it can be repeated in
the future if necessary and to provide
quality control on its results. This same
panel of biologists and natural resource
managers may also be consulted in the
development of the overall reference
condition and subsequent biocriteria. In
establishing the team of experts, it
should be recognized that bias toward
specific assemblages may exist and the
team should be appropriately balanced.
4.4 Use of Reference Sites to
Characterize Reference
Condition
The determination of the biological
reference condition from reference sites
is based on the premise that estuaries
and coastal marine waters least affected
by human activity will exhibit biological
conditions most natural and attainable
for those waters in the region.
Anthropogenic effects include all
possible human influences, for example,
watershed disturbances, habitat
alteration (channel dredging and
dredged material disposal, shoreline
bulkheading), nonpoint source inputs,
point source discharges, atmospheric
deposition, and fishing pressure.
Human activities can be either
detrimental, such as pollutant inputs, or
positive, such as responsible resource
protection or restoration. In either case,
the manager developing a biocriteria
program must evaluate the effect of such
activities on biological resources and
habitat. In practice, most reference sites
will have some of these impacts,
however, the selection of reference sites
is always made from those with the least
anthropogenic influences.
Reference sites must be carefully
selected because they are used as a key
part of the biocriteria benchmark against
which test sites are compared. The
conditions at reference sites should
represent the best range of minimally
impaired conditions that can be
achieved within a classification category
for the region. Two primary
considerations guide the selection of
reference sites within each site class:
minimal impairment and
representativeness.
Minimal Impairment - Sites that are
relatively undisturbed by human
activities are ideal reference sites.
However, land use practices and the
presence of major urban areas in the
basins of many of the nation's estuaries
or adjacent to its coastal marine waters
have altered the landscape and quality
of water resources to such a degree that
truly undisturbed sites are rarely
available. In fact, it can be argued that
no unimpaired sites exist. Therefore, a
criterion of "minimally impaired" must
be used to determine the selection of
reference sites. In regions where
minimally impaired sites are still
significantly degraded, the search for
suitable sites should be extended over a
wider area, and multistate cooperation
may be essential. It is advisable that the
state make every effort, once reference
sites are selected, to protect these areas
from degradation. This may involve:
purchase of land or easements; where
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-11
-------
appropriate, location within public
reserves; use restrictions or permit
constraints on fishing, discharge, or
dredging/disposal to protect the quality
of the reference area waters.
Representativeness - Reference sites must
be representative of the best quality of
the estuaries and coastal marine waters
under investigation; that is, they must
exhibit conditions similar to what would
be expected to be found in the region.
They should not represent degraded
conditions, even if such conditions are
the most common. Sites containing
locally unusual environmental
characteristics can result in
uncharacteristic biological conditions
and should be avoided.
Once the physical estuarine or coastal
marine classification is completed, the
biological reference condition should be
defined for each class. This can be
accomplished with three basic
approaches: (1) selected reference sites;
(2) determination from population
distributions; and (3) site-specific
reference sites. The second approach,
determination from population
distributions, is a relaxation of the
requirement for minimal impairment;
and the third approach, site-specific
reference sites, is a relaxation of the
representativeness requirement.
4.4.1 Selected Reference Sites
In this approach, reference conditions
are characterized based on the best
available sites for a given physical class
of estuarine or coastal marine waters,
and indexes or models are developed by
comparing the best sites (the reference
sites) to a second set of sites that may be
impaired. The approach assumes that
within the population of sites some are
minimally disturbed and therefore
comprise a minimally impaired
biological condition. Selection of
reference sites must be physical or
chemical; for example, minimal
instances of hypoxia, substantially free
of contaminants, a large proportion of
natural vegetation in the watershed,
little or no industrial point sources, little
or no urban runoff, or little or no
agricultural nonpoint source pollution.
Impaired ("test") sites for testing
response of metrics and model building
are selected for the presence of one or
more such anthropogenic disturbances.
Prior definition and selection of
reference sites has been used
successfully in streams for fish and
invertebrate indexes and models (e.g.,
Barbour et al. 1995, Ohio EPA 1987,
Reynoldson and Zarull 1993, USEPA
1987, Wright et al. 1984), and in estuaries
for benthic invertebrate indexes (Engle
et al. 1994, Summers et al. 1993,
Weisberg et al. 1993).
Reference Site Criteria - The overall goal
in establishing the reference condition
from carefully selected reference sites is
to describe the optimal biota that
investigators may expect to find at the
test sites of interest in the absence of
stresses. These "test" or "assessment"
sites can then be compared to the
reference sites to determine whether
impairment exists. The characteristics of
appropriate reference sites vary among
regions of the country and for different
water body and habitat types. In
general, the following characteristics
(modified from Hughes et al. 1986) are
typical of ideal reference sites:
*• Sediments and water column
substantially free of contaminants;
*• Natural bathymetry, typical of the
region;
*• Natural currents and tidal regime;
*• Shorelines representative of
undisturbed estuaries and coastal
4-12
Physical Classification and the Biological Reference Condition
-------
marine areas in the region (generally
covered by vegetation with little
evidence of shoreline erosion);
*• Natural color and odor of the water.
In this approach, a single minimally
impaired site does not represent any one
region or population of sites, and a
frequent difficulty is matching habitats
for valid comparison, particularly given
that the influence of nonpoint source
runoff or specific point source
discharges may extend over wide areas
due to transport of pollutant loads by
currents and tides. Reference conditions
based on multiple sites are more
representative and are important to
establishing quantitative-based or
numeric biocriteria.
Representative reference sites should be
selected within each of the identified
classes. A sufficient number of sites are
then sampled to adequately characterize
the range of existing conditions and to
reduce the variability in the
measurements for each class. It is
desirable to sample a minimum of 10
sites per class, and 30 sites per class is
usually optimal for cost effectiveness. In
regions where all sites are impacted, the
selected number of "best" sites of each
class (e.g., mesohaline mud habitat) are
sampled, where "best" is determined by
least anthropogenic disturbance or
impacts, but not by most desirable biota.
In regions where the population of
minimally impaired reference sites is
large, a stratified random sampling
scheme (using those sites) will yield an
unbiased estimation of reference
conditions (Gilbert 1987).
Stressed Sites - Effective metrics respond
to environmental degradation and allow
discrimination of impaired sites from
the reference expectations. Metrics that
do not respond are not useful in
bioassessment. Response is determined
by sampling a set of stressed sites in the
same way as the reference sites. Sites
with known problems, such as nutrient
loading, thermal pollution, toxic
sediments, or those influenced by urban
land use, are good candidates. There
should be several in each class for
adequate tests of metric responses.
Since impaired sites are frequently
locations of monitoring by water quality
agencies, data might already exist to test
the biological metrics. However, the
sampling methods for reference and
impaired sites should be comparable.
For a lengthy sampling season, it is
important to account for seasonal shifts
of the salinity zone boundaries. Stations
proximal to these transition zones may
need to be either located far enough
away from the boundary to have
consistent year-round application or else
their classification should be shifted
with the seasons. For example, some
areas in Figure 4-5 may be polyhaline-
sandy bottom in the spring, but in the
winter they would be classified as
marine-sandy bottom (Figure 4-6).
Thus, such stations have a change of
classification with the shifting of the
halocline. An alternative is to avoid
placing stations near the transition zone
so that, except in extreme climatic
conditions, these stations have
consistent habitat characteristics. The
biotic data collected at all sites is then
subclassified by sediment type (e.g.,
sand, sandy-mud, mud) and depth for
this salinity region. This information
becomes the reference condition and
part of the biocriteria for any test sites in
the region.
Example: EMAP Estuary - The EMAP-
Estuaries (EMAP-E) program collected
samples in the Virginian and
Louisianian provinces. One of the goals
of the EMAP-E effort is to develop a
statistical benthic index of estuarine
condition based on extensive
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-13
-------
Figure 4-5
Estuarine and
coastal marine
biocriteria survey
method useful for
a priori reference
site selection.
Wet season/high
flow salinity
pattern showing
tributary reference
sites and
mainstem
transects for four
salinity and three
substrate
classifications.
Wet Season/High Flow
Kev
Q
mud
transitional
sand
coastal land area
single comprehensive
survey site
survey site transect
across depth profile
urban areas
agricultural areas
information about benthic community
structure. A test data set of reference
stations has been compiled for the
purpose of formulating the index.
Habitat characteristics used by EMAP to
define reference stations from the 1990
and 1991 Virginian province (refer to
Figure 4-3) collections in Chesapeake
Bay were:
* Stations where no contaminant
exceeded the effects range-median
(ER-M) value (which equals the
concentration at which 50% of
collected data demonstrated adverse
biological effects [Long et al. 1995]);
* No sediment toxicity was observed;
i.e., percent survival greater than
75% and not significantly different
from controls;
* Bottom DO was never less than 1-
mgL'1, 90% of the continuous DO
measurements were greater than 3-
mgL'1 and 75% of the DO
measurements were greater than 4-
mgL'1 (Schimmel et al. 1994).
The list of stations generated using these
characteristics was reviewed to
eliminate any reference sites located in
areas potentially subject to physical
disturbance, such as dredged shipping
channels. Fifty-three sites from the
4-14
Physical Classification and the Biological Reference Condition
-------
Dry Season/Low Flow
Kev
n
mud
transitional
sand
coastal land area
single comprehensive
survey site
survey site transect
across depth profile
urban areas
| agricultural areas
Figure 4-6
Estuarine and
coastal marine
biocriteria survey
method useful for
a priori reference
site selection.
Dry season/low
flow salinity
pattern showing
tributary
reference sites
and mainstem
transects for four
salinity and three
substrate
classifications.
combined 1990 and 1991 data sets were
considered to be reference sites.
A similar process has been used for data
collected in 1991 in the Louisianian
province (refer to Figure 4-3). Using the
following criteria, eight sites were
classified as reference sites:
The minimum DO value over a 24-
hour period was less than 3.0-mgL"1
(Summers and Engle 1993);
Sediment concentrations for any
contaminant did not exceed the BR-
IM value;
* The percent survival for Ampelisca
abdita (10-day) or Mysidopsis bahia
(96-hour) in acute sediment
bioassays was indistinguishable
from controls (Engle et al. 1994).
As states develop their estuarine and
coastal marine biocriteria, they may
wish to consider incorporating EMAP-
identified reference sites into their
sampling programs. To the degree that
these stations meet state reference
condition requirements, they can serve
as regional reference sites within the
appropriate state classification
categories while also contributing to
USE PA national trend monitoring for
estuaries.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-15
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4.4.2 Reference Condition Derived
from Population Distribution
One problem in the use of the minimally
impaired sites technique is what to do if
an area is so extensively degraded that
even the least impaired site indicates
significant deterioration. Many systems
are greatly altered through channel
dredging and spoil disposal,
urbanization, and construction and
operation of marinas and other
commercial or industrial enterprises.
The condition of these systems is a result
of societal decisions that have to be
taken into account. However, the
existence of greatly altered systems
should not compromise the objective of
defining the natural state as a reference
condition. These disturbed systems
should not be presumed to represent a
reference condition of any sort.
Although the biocriteria established for
these altered systems serve as a baseline
for judging impairment, the ultimate
goal is to achieve the sites' recovery to
the best attainable condition as
represented by historical information
and by conditions at "minimally
impaired" sites. Consensus of expert
opinion and historical data play an
especially important role in
characterizing the reference condition
for these systems, as does the
application of innovative management
practices to obtain resource
improvement.
In defining the biocriteria, managers
must strike a balance between the ideal
restoration of the water resource and the
fact that human activity affects the
environment. The most appropriate
course of action will be to use
minimally impaired sites as
representing the maximum amount of
degradation that will be tolerated,
thereby ensuring adherence to the
antidegradation policy of the CWA.
Continual monitoring should provide
the feedback necessary to make
reference condition and interim criteria
adjustments as warranted during the
restoration process.
In this approach, reference conditions
are derived from the distribution of
calculated metrics for the entire
biological data set within a physical
classification without preselecting any
reference sites. The entire data set can
be plotted as a cumulative frequency
distribution to help determine "best"
values of candidate metrics (Figure 4-7).
This approach is applied in cases where
prior definition of reference sites is not
possible because all sites are considered
impaired or because too few reference
sites exist (e.g., one or two) for an
unbiased characterization of regional
reference conditions. This approach has
been used successfully for fish and
invertebrate indexes in streams (e.g.,
Karr et al. 1986, Plafkin et al. 1989) and
for fish (Jordan et al. 1992, Deegan et al.
1997) in estuaries.
The biological reference condition is
defined from some upper fraction of the
component indicator variables (metrics)
and this reference condition is
subsequently used to judge the
biological status of other sites. There is
no independent (nonbiological)
definition of reference condition.
Reference condition and biological
responses are confirmed by identifying
severely impaired sites and then
comparing them with the derived
reference condition to determine the
response(s) of biological indicators to
impacts, and by selecting metrics that
are known to respond to perturbation
from other studies.
A representative sample is taken of the
entire population of estuary or coastal
marine sites (Figure 4-8). Sites that are
known to be severely impaired may be
4-16
Physical Classification and the Biological Reference Condition
-------
CD
3
cr
2
j_
I
03
3
3
o
100 —
90 —
80
70
60
50
40
30
20
10
I
Minimum
I
Maximum
Metric Value
Figure 4-7
Hypothetical
cumulative
frequency
distribution of
metric values for
all sites in a given
estuarine or
coastal marine
class. The dotted
line shows the
metric value
corresponding to
the 95th
percentile.
excluded from the sample, if desired.
The population distribution of each
biological metric (Chapter 11) is
determined, and the 95th percentile of
each metric is taken as its reference
value. The range from the minimum
possible value to the reference value is
trisected, and values in the top third of
the trisected range are presumed to be
similar to reference conditions. Scoring
of metrics is explained more fully in
Chapter 11.
A central assumption of the population
distribution approach is that at least
some sites in the population of sites are
in good condition, which will be
reflected in the highest scores of the
individual metrics. Because there is no
independent definition of reference; i.e.,
independent of biological status,
reference conditions defined in this way
must be taken as interim and subject to
future reinterpretation. Again,
antidegradation safeguards must be in
place to prevent further deterioration of
the reference condition and criteria.
4.4.3 Site-specific Reference Sites
The site-specific approach is analogous
to up stream-downstream comparisons
in running water or control-impact
designs. It consists of selecting a
reference site paired with each site to be
assessed. There is no characterization of
reference conditions for a physical class
of estuarine or coastal marine waters;
each test site and each reference site is a
special case with each test site compared
to its reference site. Reference sites are
selected to be similar to their respective
test site, but unimpaired by the
perturbations of interest at the test site.
This approach may be less costly at the
outset because the design and logistics
are simpler than the other approaches.
However, after several years of
sampling and monitoring, costs for this
approach are likely to be similar or
greater because each new test site
requires its own paired reference site.
The site-specific approach has two
problems stemming from the fact that
there is usually only a single reference
site or a single nearby reference area
from which reference sites are selected.
The first problem is representativeness:
Does the reference site represent
reference conditions? Although the
reference site may lack the specific
stressor that is present at the test site,
unless carefully evaluated and placed, it
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-17
-------
Figure 4-8
Estuarine and coastal marine
biocriteria survey method useful
for stratified random (population
distribution) reference site
selection. Dry season/low flow
salinity pattern showing
mainstem sampling sites for
four salinity and three substrate
classifications.
Dry Season/Low Flow
Kev
Q mud
[~| transitional
g sand
FJ coastal land area
• single comprehensive
survey site
Marine
may be subject to other stressors that
have not been considered.
The second problem with the site-
specific approach is the potential for
trivial statistical comparison of two sites
in that it is almost always possible to
demonstrate a statistically significant
difference between two sites by
pseudoreplication (Hurlbert 1984).
Pseudoreplication is the repeated
measurement of a single experimental
unit or sampling unit, and treating the
measurements as if they were
independent replicates of the sampling
unit. A single reference site does not
yield sufficient information to
meaningfully judge the biological
relevance of a statistical difference at the
test site. The judgment that biotic
differences between a single test site and
its reference site may be due to
differences in impacts can not depend
on statistical tests, but requires a careful
weight-of-evidence evaluation (e.g.,
Hurlbert 1984, Schindler 1971).
If the objective of a study is to test the
response of a particular metric, and if
there are several paired sites, then a
paired approach can be very powerful,
allowing paired statistical tests (e.g.,
Frydenborg 1994). A paired
experimental design is not
pseudoreplication because each site pair
is an independent replicate, and the
sample size (n) is the number of pairs.
4-18
Physical Classification and the Biological Reference Condition
-------
Example 1: Navigation channels -
Navigation channels can represent an
important component of overall
estuarine areas (e.g., Houston Ship
Channel, entrance to Chesapeake Bay
and major harbors). Resource agencies
may need to determine the relative
quality of navigation channels in
relation to the entire estuarine system as
part of the overall resource evaluation.
Stations should be arrayed essentially in
a nearfield-farfield pattern as shown in
Figure 4-9, with farfield stations located
"up" current and nearfield stations
"down" current, outside the zone of
suspected impact. Stations should be
located such that depth, grain size, and
salinity remain consistent. These
conditions may be difficult to locate in a
tidally-influenced channel.
Furthermore, if the navigation channel
to be assessed is dredged to constant
depth, changes in biota will primarily be
a function of salinity, given uniform
poor substrate and the periodic
destruction of the benthic habitat by
dredging.
The reference condition for navigation
channels would be determined from the
central tendency (e.g., median) of the
biological data collected at "upstream"
stations, that is, those stations that are
expected to be out of the zone of
influence of impact sources (e.g.,
harbors, industrial areas). Sites from
which the reference condition is
determined should be of comparable
depth, grain size, and salinity to those in
suspected impact zones and have the
same dredging history.
Example 2: Near shore marine -
The station array in coastal marine
waters is essentially a variation of the
nearfield-farfield approach because of
the open water characteristics. Transects
should be laid parallel to shore along
equal depth contours, with sampling
stations placed approximately evenly
along the transect (Figure 4-10). For
habitat consistency, the survey team
should strive to maintain uniform depth,
bottom type, salinity, DO, and pH
characteristics at a minimum for all sites.
These parallel transects can evolve to an
open grid station array if sampling
stations are added around outfalls. In
Figure 4-10, the D1-D5 series of stations
is added to the transect to reveal effluent
distribution shifts around the discharge
site. This approach addresses two
aspects of effluent impact monitoring:
(1) the relative biological community
change near the discharge as compared
to the reference condition described by
observation of either end of the transect;
and (2) the potential shifting, seasonal
change, or expansion or contraction of
the zone of effluent influence from the
discharge. Both forms of information are
important to adequately assess the
biological effects of such effluents. This
design was used for bioassessment of
ocean outfalls from Delaware and
Maryland (see Chapter 13).
A complete grid, while more involved
and expensive, would allow a more
precise evaluation of the effects of these
discharge plumes as they shift in
position in response to changes in
nearshore currents and seasonal shifts in
wave regime (Figure 4-10).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
4-19
-------
Figure 4-9
Estuarine and
coastal marine
survey method for
navigation channel
assessment.
Harbor
/ •/ "Up" channel
stations
Net
Cu rrent
Direction
"Down" channel
stations
Figure 4-10
Estuarine and
coastal marine
biocriteria survey
method useful for
marine site
selection.
net longshore current
• A
'C.D3
i D • D4
>E.D5
» F
i G
4-20
Physical Classification and the Biological Reference Condition
-------
Chapter 5
Sampling Program Issues
Biological Assemblages
and Design
This chapter presents sampling program
issues that are common to each of the
three assessment tiers that employ field
sampling. These issues include the
biological assemblages (Section 5.1) that
might be sampled, sampling design
strategies (Section 5.2 and 5.3), and
logistical considerations (Section 5.4).
Historically, benthic macroinvertebrates
have been the most widely sampled
assemblage, which is described in detail
in this chapter.
As described earlier in this document, a
possible sampling methodology is a
progressive tiered design, ranging from
simple biological assessment to detailed,
intensive studies. The tiers are intended
to be implemented cumulatively, that is
when possible, each tier should
incorporate the elements in the
preceding tier as appropriate for the
estuaries or coastal marine water in
which they are applied. In general, the
methods are derived from those used
along the coastal United States (Dauer
1993, Farrell 1993a, b, Nelson et al. 1993,
Word 1980,1978, Word et al. 1976); in
Puget Sound (Eaton and Dinnel 1993); in
the EMAP - Estuaries program (Holland
1990), and in USEPA's National Estuary
Program (NEP) (USEPA1992) and 403
Monitoring Program (USEPA 1994a).
Assessment tiers 1 through 3 require
sampling biological assemblages and
habitats in one or more field visits. Six
biological assemblages, including two
developmental/ experimental
assemblages, are recommended for
estuarine and coastal marine waters
bioassessment. Each tier is comprised of
a subset of assemblages, with the
number of assemblages increasing in the
higher tiers. While these six
assemblages are described, specific
environmental circumstances and
budget constraints will determine what
subset each state uses. For example, if
finances are extremely limited on the
East Coast the single most effective
assemblage to sample may be
macrophytes. On the West Coast
benthic macroinvertebrates or fish may
the assemblages of choice. The
bioassessment measurements are made
along transects extending from shore to
the deepest (channel) portion of the
estuary, in a systematic grid along
transects extending away from point
source discharges (nearfield/farfield), or
in a probablistic design. The number of
transects or grid points, the assemblages
sampled, and the intensity of sampling
effort are determined by the assessment
tier with overall effort increasing at each
higher tier.
5.1 Assemblages
The study of any group of organisms
will yield information on the status of
their environment. The objectives in
selecting assemblages for estuarine and
coastal marine bioassessment were to
identify those that: (1) are
unambiguously useful for biological
assessment; (2) can be sampled and
interpreted in a cost-effective way; and
(3) have easily calculated metrics that
can be used alone or in a multimetric
index of the assemblage. Assemblages
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-1
-------
that meet these criteria are suggested for
use in estuarine and coastal marine
assessment; assemblages that do not
presently meet the criteria are
considered to be developmental.
Suggested assemblages include infaunal
benthic macroinvertebrates, fish, aquatic
macrophytes, and phytoplankton
(chlorophyll a}. The developmental
assemblages include zooplankton,
epibenthos, and paleoenvironmental
systems. These developmental
assemblages are promising, but they
lack the same level of refinement
documented for the suggested
assemblages listed above and
unresolved technical problems remain
with respect to cost-effective assessment
and interpretation. Background and
rationale for these suggested
assemblages was presented in Chapter 2.
Multimetric bioassessment is not a
ready-made, one-size-fits-all instrument
that will tell managers whether estuaries
or coastal marine waters are healthy. It
is an approach that is expected to be
modified to specific regional conditions
before it can be applied. For example,
bioassessment of streams has been
successful when modified and calibrated
regionally (e.g., Barbour et al. 1996a,
Ohio EPA 1990, Miller et al. 1988), but it
has been less successful when used "off-
the-shelf." Successful application
requires region-specific selection and
calibration of metrics, as well as regional
characterization of reference conditions.
For example, benthic infauna are rare in
rocky, fjord-type estuaries and would be
an inappropriate assemblage to sample
in such a setting.
5.1.1 Benthic Macroinvertebrates
(Infauna)
Benthic macroinvertebrates are an
appropriate assemblage for all biological
assessments of water bodies because
they respond to water, sediment, and
habitat qualities (Holland 1990, Plafkin
et al. 1989), are not very mobile, and
consequently, integrate long-term
changes in these ecosystem components.
For those reasons, benthic
macroinvertebrates tend to dominate
this text.
Individual macroinvertebrate species
have sensitive life stages that respond to
stress and integrate effects of short-term
environmental variations, whereas
community composition depends on
long-term environmental conditions. In
addition to taxonomic identification,
benthic macroinvertebrate metrics may
require knowledge of the feeding group
to which a species belongs, for example,
suspension feeders and deposit feeders.
Potential metrics for estuarine and
coastal marine benthos are listed in
Table 5-1. Metrics considered in the
EMAP Estuaries program are listed in
Table 5-2.
Sampling Strategies
The sampling area should focus on the
most predominant substrate available
(in many estuaries and coastal marine
areas this will be soft sediments of mud
through sand grain sizes), and the
metrics should be developed
independent of microhabitat variation
(Table 5-3). The type of sampling gear
will depend on the substrate being
sampled; each substrate has its own
optimal sampling gear (Section 5.1.1.4).
Standardized sampling techniques for
each gear type should be followed to
allow for the comparison of data.
Processing of samples should be
standardized by using a mesh size
appropriate to the region. In the past,
monitoring programs conducted in east
coast waters have often used a 0.5-mm
mesh screen, while west coast programs
have used a 1.0-mm screen (Bowman et
al. 1993). States should consider testing
various mesh size screens to determine
5-2
Sampling Program Issues
-------
Table 5-1.
Potential benthic macroinvertebrate metrics.
Metric
No. of taxa
Mean no. of individuals pertaxon
% contribution of dominant taxon
Shannon-Wiener diversity
Total biomass
% biomass of opportunistic species
% abundance of opportunistic species
Equilibrium species biomass
Equilibrium species abundance
% taxa below 5-cm
% biomass below 5-cm
% carnivores and omnivores
No. of amphipod species
% individuals as amphipods
% individuals as polychaetes/oligochaetes
No. of bivalve species
% individuals as molluscs
% individuals as deposit feeders
Mean size of organism in habitat
Proportion of expected no. of species in sample
Proportion of expected no. of species at site
Mean weight per individual polychaete
No. of suspension feeders
% individuals as suspension feeders
No. of gastropod species
No. of Capitellid polychaete species
Response to Impairment
reduced
substantially lower or higher
elevated
reduced
substantially lower or higher
elevated
elevated
reduced
reduced
reduced
reduced
elevated
reduced
reduced
elevated
reduced
reduced
elevated
reduced
reduced
reduced
reduced
reduced
reduced
reduced
elevated
the most appropriate size for their
bioassessment activities. Ferraro et al.
(1994) present a process to evaluate the
optimum infaunal sampling protocol;
i.e., sampling unit area, sieve mesh size,
and sample size [n], discussed more
fully in Section 5.2.6.
Time and Costs
An informal survey of some states that
conduct routine monitoring of estuaries
and coastal marine waters indicates that
estuarine sampling requires a minimum
of two full-time equivalent (FTE) staff,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-3
-------
Table 5-2. Metrics from which the EMAP Virginian and Louisianian benthic indexes were
developed. Louisianian Province has reduced number of metrics due to
knowledge gained from previous Virginian province studies (n.a. - not applicable).
Community
Measure of
Structure/
Function
Metrics
Virginian Province
Biodiversity/
Species
Richness
Abundance
Measures
Individual Health
Functional
Groups
Taxonomic
Composition
Proportion of expected number of species present in a sample • Proportion of expected
number of species present at a site • Shannon-Weiner Diversity Index • Pielou's evenness
index
Total benthic abundance per event • Mean benthic abundance per sample • Total benthic
biomass per event • Mean benthic biomass per sample
Biomass/abundance ratio • Mean weight per individual polychaete • Mean weight per
individual mollusc
Number of suspension feeding organisms per event • Biomass of suspension feeding
organisms per event • Percent of total benthic abundance as suspension feeders • Percent
of total benthic abundance as suspension feeding biomass • Number of deposit feeding
organisms per event • Biomass of deposit feeding organisms per event • Percent of total
benthic abundance as deposit feeding organisms • Number of benthic omnivores/predators
per event • Biomass of benthic omnivores/predators per event • Percent of total benthic
abundance as omnivores/predators • Percent of total benthic biomass as
omnivores/predators • Number of opportunistic species per event • Mean number of
opportunistic species per sample • Percent of total benthic abundance as opportunists •
Number of equilibrium species per event • Mean number of equilibrium species per sample •
Percent of total benthic abundance as equilibrium species • Percent of mean benthic
abundance as equilibrium species
Number of amphipods per event • Amphipod biomass per event • Percent of total benthic
abundance as amphipods • Percent of total benthic biomass as amphipods • Number of
bivalves per event • Bivalve biomass per event • Percent of total benthic abundance as
bivalves • Percent of total benthic biomass as bivalves • Number of gastropods per event •
Gastropod biomass per event • Percent of total benthic abundance as gastropods • Percent
of total benthic biomass as gastropods • Number of molluscs per event • Mollusc biomass
per event • Percent of total benthic abundance as molluscs • Percent of total benthic
biomass as molluscs • Number of polychaetes per event • Polychaete biomass per event •
Percent of total benthic abundance as polychaetes • Percent of total benthic biomass as
polychaetes • Number of Capitellid polychaetes per event • Percent of total benthic
abundance as Capitellid polychaetes • Number of Spionid polychaetes per event • Percent
of total benthic abundance as Spionid polychaetes • Percent of total polychaete abundance
as Spionid polychaetes • Number of Tubificid oligochaetes per event • Percent of total
benthic abundance as Tubificid oligochaetes
Louisianian Province
Biodiversity/
Species
Richness
Abundance
Measures
Individual Health
Taxonomic
Composition
Shannon-Wiener Diversity Index • Pielou's Evenness Index • Mean number of species •
Mean number of polychaete species
Mean benthic abundance per site
n.a.
Mean abundance of amphipods per site • Proportion of total benthic abundance as
amphipods • Mean abundance of decapods per site • Proportion of total benthic abundance
as decapods • Mean abundance of bivalves per site • Proportion of total benthic abundance
as bivalves • Mean abundance of gastropods per site • Proportion of total benthic
abundance as gastropods • Mean abundance of molluscs per site • Proportion of total
benthic abundance as molluscs • Mean abundance of polychaetes per site • Proportion of
total benthic abundance as polychaetes • Mean abundance of Capitellid polychaetes per site
• Proportion of total benthic abundance as Capitellid polychaetes • Mean abundance of
Spionid polychaetes per site • Proportion of total benthic abundance as Spionid polychaetes
• Proportion of total polychaete abundance as Spionid polychaetes • Mean abundance of
Tubificid oligochaetes per site • Proportion of total benthic abundance as Tubificid
oligochaetes
5-4
Sampling Program Issues
-------
Table 5-3.
Sampling summary for infaunal benthic macroinvertebrates.
Habitat
Sampling
Gear
Index
Period
Sampling
Analysis
Preferred: soft sediments (mud-sand).
Regionally most appropriate for substrate (Table 5-4).
Regionally most appropriate
Preferred:
Summer- East & GulfCoast
Spring - Pacific Northwest
Alternative:
All four seasons, orwinter and summer
Preferred: samples from 3 grabs at each of at least 10 sites.
Alternative: keep sites as replicates if a within-class variance
estimate will be used in assessment.
Preferred: lowest practical taxonomic level
Alternative: identification to class and family.
and has an associated per sample cost of
$200 - $400.
Coastal marine sampling requires a
minimum of four FTEs, and has an
associated cost of $400 - $800. Three
months to a year are required from time
of sampling to preparation of an
interpretive report.
Assessment Tiers
The benthic infaunal assemblage is
appropriate for all three field tiers
outlined for the biological assessment of
estuaries and coastal marine waters.
Tier 1 determines the presence/absence
of macroinvertebrates below 5-cm depth
in the sediment and briefly describes the
class and family of observed benthos.
Tier 2 determines the major taxa and
indicator species present in each sample
to the genus and species level. Tier 3
applies a full benthic community
assessment, recording the numbers of
individuals in each grab to the genus
and species level, and can include
determination of biomass if deemed
appropriate by the state. Tier 3 uses the
benthic community assessment with
replication and additional diagnostic
stations and parameters as indicated by
the data.
Gear Type
All sampling methods and gear types
have specific biases because they capture
a target assemblage. Because estuaries
and coastal marine waters are complex
environments with a potentially large
number of habitats, it is important to
choose sampling methods and gear
appropriate for a specific habitat type.
Sampling within a given habitat type
such as a salinity regime, bottom grain
size, and/or depth should be conducted
so that samples can be considered
representative of the community being
studied.
A large number of benthic sampling
methods and gear are available. The
choice of appropriate methods and gear
will depend upon the goals of the
sampling and the habitat to be sampled.
*• In subtidal areas, benthic infauna
can be collected using grabs, such as
Young, Ponar, or Van Veen; or cores
such as box, gravity, or hand-held
cores collected by divers. Grab or
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-5
-------
core size and number of replicates
should be sufficient to adequately
sample the infaunal community,
bearing in mind that distribution is
usually spatially clumped rather
than random or regular; and
> Intertidal areas may best be sampled
at low tide with hand-held cores.
For certain infauna it may also be
feasible to estimate abundance by
counting the number of surface
structures within a given area. For
example, some polychaete worms
build identifiable tube or mound
structures, or leave identifiable fecal
coils in intertidal areas. If the local
infauna has been studied to the
extent that identification of such
topographic features can be
correlated to the presence of a
particular organism, crude
abundance and presence/absence
evaluations may be possible.
Collection of sediments and benthic
organisms should be done concurrently
in order to reduce the costs of field
sampling and to permit sound
correlation and multivariate analyses.
Therefore, the sampling equipment and
procedure should also include sampling
the sediment.
Desirable attributes for sediment
sampling gear include:
*• Creates a minimal pressure wave
when descending;
> Forms a nearly leakproof seal when
the sediment sample is taken;
*• Prevents winnowing and excessive
sample disturbance when ascending;
*• Allows easy access to the sample
surface so that undisturbed
subsamples may be taken;
*• Allows vertical sectioning of
undisturbed samples for profile
examination.
Penetration well below the desired
sampling depth is preferred to prevent
sample disturbance as the device closes.
It is best to use a sampler that has a
means of weight adjustment so that
penetration depths may be modified
with changing sediment type (USEPA
1992).
Grab Samplers
Well designed and constructed grab
samplers are capable of consistently
sampling bottom habitats. Depending
on the size of the device, areas of 0.02- to
0.5-m2 and depths ranging from 5- to 15-
cm may be sampled. Limitations of grab
samplers include:
*• Variability among samples in
penetration depth depending on
sediment properties;
*• Oblique angles of penetration which
result in varying penetration depths
within a sample; and
*• The sample may be folded or
otherwise distributed by some
devices, such as the Shipek sampler,
resulting in the loss of information
concerning the vertical structure of
benthic communities in the
sediments.
However, careful use of these devices
will provide reliable quantitative data.
Grab samplers are the tools of choice for
a number of estuarine and marine
monitoring programs due to their ability
to provide quantitative data at a
relatively low cost (Fredette et al. 1989,
USEPA 1986-1991). Various grab
samplers which could be used for Tiers
1-3 are summarized in Table 5-4.
5-6
Sampling Program Issues
-------
Table 5-4. Summary of bottom sampling equipment (Adapted from USEPA1992, Klemm etal.
1992, and ASTM 1998b).
DEVICE
S-H
OJ
a
c
-S
"ij jy
u ^
u
II
S m
§ u
tin O
'orer with
ble Fluorocarbon
3r glass liners.
-a o ••£
§ 8 j§
0)
X >H
1r
2
0)
IJ
2
O
be
fi
O
Ekman or Box
Dredge
USE
Soft sediments
only.
Soft sediment
only.
Shallow wadeable
waters or deep
waters if SCUBA
available. Soft or
semi-consolidated
deposits
Same as above
except more
consolidated
sediments can be
obtained.
Same as above.
Semi-consolidated
sediments.
Lakes, estuarine
and marine areas.
Soft to semi-soft
sediments. Can
be used from boat,
bridge, or pier in
waters of various
depths. Weights
can be added for
deeper penetration
in fine sand.
ADVANTAGES
Samples a variety of soft substrates
up to harder types. Sampling tube
can be modified up to 100-cm2
substrate surface; least disturbance
to water/bottom interface. Can be
used in shallow to medium-shallow
water up to 30.5-m or deeper.
Good penetration on soft sediment.
Small sample volume allows greater
number of replicates to be collected
in a short time period. Samples deep
burrowing organisms. Used in
shallow to deep water (3-m to 183-m).
Automatic check valves prevent
sample loss.
Preserves layering and permits
historical study otsediment
deposition. Rapid-samples
immediately ready for laboratory
shipment. Minimal risk of
contamination.
Handles provide for greater ease of
substrate penetration. Above
advantages.
Collection of large undisturbed
sample allowing for subsampling.
Low risk of sample contamination.
Maintains sediment integrity relatively
well.
Eliminates metal contamination if
grab is plastic or kynar lined.
Reduced pressure wave. Can
subsample. Better penetration in
sand than the modified Van Veen.
Obtains a larger sample than coring
tubes. Can be subsampled through
box lid. Hinged top doors reduce
washout, shock waves and substrate
disturbance. Range of sizes
available.
DISADVANTAGES
Samples limited surface area.
Requires boat and winch.
Heavy; requires boat and winch.
Does not retain sand unless
bronze core retainers are used.
Small sample size requires
repetitive sampling. Impractical
in water > 1-m depth if SCUBA
not available.
Careful handling necessary to
prevent spillage. Requires
removal of liners before
repetitive sampling. Slight risk
of metal contamination from
barrel and core cutter.
Hard to handle.
Careful handling necessary to
avoid sediment spillage. Small
sample, requires repetitive
operation and removal of liners.
Time consuming.
Expensive, heavy, requires boat
and winch.
Possible incomplete jaw closure
and sample loss. Possible
shock wave which may disturb
the fines. Metal construction
may introduce contaminants.
Possible loss of fines on
retrieval. Inefficient in deep
water or where even moderate
current exists.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-7
-------
Table 5-4 (Cont'd). Summary of bottom sampling equipment (Adapted from USE PA 1992,
Klemm et al. 1992, and ASTM 1998b).
DEVICE
Ponar Grab Sampler
1
E
CO
LTl
1 ;H
pa U
Modified Van Veen
o
£
S
pa
JH
i
'^ ^
lu
be
D
-. en
11
c/5 pa
USE
Useful on sand,
silt, or clay.
Waters of 1-2-m
deep when used
with extension rod.
Soft to semi-
consolidated
deposits.
Useful on sand,
silt, or clay.
Sampling moving
waters from a fixed
platform.
Useful on most
substrates.
Useful on most
substrates.
Various
environments
depending on
depth and
substrate.
ADVANTAGES
Most universal grab sampler.
Adequate on most substrates; very
efficient for hard sediments. Large
sample obtained intact permitting
subsampling. Better penetration than
other grabs: sideplates and screens
reduce washout, shock waves and
substrate disturbance.
Piston provides for greater sample
retention.
Adequate on most substrates. Large
sample obtained intact.
Streamlined configuration allows
sampling where other devices could
not achieve proper orientation.
Reduced pressure wave. Designed
for sampling hard substrates. Can
subsample and make vertical cross-
sections. Greater penetration in sand
and cobble than modified Van Veen,
but possibly not as deep as a Young
grab. Better closure in areas with
wood debris.
Inexpensive, easy to handle.
DISADVANTAGES
Shock wave from descent may
disturb fines. Possible
incomplete closure of jaws
results in sample loss. Possible
contamination from metal frame
construction. Sample must be
further prepared for analysis. A
very heavy grab requires use of
a boat with winch and cable.
Shell hash can hold jaws open
causing loss of sample. Must
use stainless-lined grab for
sediment metals samples.
Cores must be extruded on site
to other containers - metal
barrels introduce risk of metal
contamination.
Requires boat and winch.
Shock wave from descent may
disturb fines. Possible
incomplete closure of jaws
results in sample loss. Possible
contamination from metal frame
construction. Sample must be
further prepared for analysis.
Limited penetration in hard
sand. Possible overpenetration
in soft silt.
Possible contamination from
metal construction.
Subsampling difficult. Not
effective for sampling fine
sediments.
Loss of fines. Heavy; requires
boat and winch. Possible metal
contamination unless grab is
lined.
Loss of fines on retrieval
through water column. Layer
information not collected.
The number and kinds of
macroinvertebrates collected by a
particular grab may be affected by the
habitat sampled, substrate type
sampled, depth of penetration, angle of
closure, completeness of closure of the
jaws and potential loss of sample
material during retrieval, creation of a
"shock" wave and "washout" of
organisms at the surface of the substrate.
The high-flow velocities often
encountered in rivers and wave action in
estuaries and coastal marine waters can
also affect stability of the sampler
(Klemm et al. 1992). USEPA EMAP-
Estuaries protocols describe a simple
and consistent method for accepting or
rejecting a bottom grab (Figure 5-1).
The type and size of the grab samples
(or other device) selected for use will
depend on factors such as the size of
boat, available winch and hoisting gear,
the type of sediment to be sampled,
water depth, current velocity, and
whether sampling is conducted in
sheltered areas or open water (Klemm et
al. 1992). The EMAP-Near Coastal
5-8
Sampling Program Issues
-------
Figure 5-1
Cross-section of
sediment in
clamshell bucket
illustrating
acceptable and
unacceptable
grabs.
Acceptable if Minimum
Penetration Requirement Met
and Overlying Water is Present
Unacceptable
(Washed, Rock Caught in Jaws)
Unacceptable (Canted with
Partial Sample)
Unacceptable
(Washed)
Program selected a Young grab
(sometimes referred to as a Young-
modified Van Veen) that samples a
surface area of 440-cm2 (Weisberg et al.
1993). This Young grab was selected
because it deploys easily from small
boats (24-ft) and it samples sand and
mud habitats adequately. The
maximum penetration depth of the grab
was 10-cm.
PONAR Grab:
The PONAR has side plates and a screen
on the top of the sample compartment to
prevent loss of the sample during
closure. With one set of weights, this
heavy steel sampler can weigh 20-kg.
Word et al. (1976) report that the large
amount of surface disturbance
associated with Ponar grabs can be
greatly reduced by simply installing
hinges rather than fixed screen tops,
which will reduce the pressure wave
associated with the sampler's descent
into the sediment. The standard Ponar
takes a sample area of 523-cm2. A small
version, the petite Ponar grab, takes a
sample area of 232-cm2 and can be used
in habitats where there may be an
unusual abundance of
macroinvertebrates, thus eliminating the
need to subsample.
The weight of the standard Ponar grab
makes it necessary to use a winch and
cable or portable crane for retrieving the
sample, and ideally the samples should
be taken from a stationary boat. The
smaller version (petite Ponar grab) is
designed for hand-line operation, but it
may be used with a winch and cable.
Ekman Grab:
The Ekman grab sampler is used to
obtain samples of macroinvertebrates
from soft sediments, such as very fine
sand, mud, silt, and sludge where there
is little current. This grab is inefficient
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-9
-------
in deep waters, under adverse weather
conditions, and in waters with moderate
to strong currents or wave action. The
Wildco box corer is like a heavy duty
Ekman with a frame and weights and
can be used to collect macroinverte-
brates in estuaries. Because of its weight
a winch is necessary for retrieving the
sample from a stationary boat.
The Ekman grab sampler is a box-
shaped device with two scoop-like jaws
that must penetrate the intended
substrate without disturbing the water-
sediment boundary layer, close when
positioned properly on the bottom, and
retain a discrete sample of sediment
while it is brought to the surface for
processing. Hinged doors on the top of
the grab prevent washout during sample
retrieval. The grab is made of 12- to 20-
gauge brass or stainless steel and weighs
approximately 32-kg. The box-like part
holding the sample has spring-operated
jaws on the bottom that must be
manually set. The sampler is available
in several sizes; however, in very soft
substrates only a tall model should be
used, either a 23-cm or a 30.5-cm model.
The Ekman grab can be operated from a
boat with a winch and cable.
Smith-Mclntyre Grab:
The Smith-Mclntyre grab sampler is
designed to obtain samples of
macroinvertebrates from sediments in
rough weather and deep water in
estuaries and oceans. This device
samples a surface area of 0.1-m2 and is
useful for sampling macroinvertebrates
from a broad array of sand, gravel, mud,
clay, and similar substrates.
The Smith-Mclntyre grab sampler has
hinged top doors to prevent sample
washout and the pressure wave in
descent. Its paired jaws are forced into
the intended substrate by two "loaded"
strong coiled springs when the grab
touches the bottom. The jaws close
when positioned properly on the
bottom, and retain a discrete sample of
sediment to be brought to the surface for
processing. The device is heavy and can
weigh 45.4-kg or more. The chief
advantage of the sampler is its stability
and easier control in deep and rough
waters. The spring-loaded jaws of the
Smith-Mclntyre grab must be considered
a hazard and caution should be
exercised when using the device. Due to
the weight and size, this device must be
used from a vessel with boom and lifting
capabilities.
Modified Van Veen Grab:
The modified Van Veen grab sampler is
used to obtain samples of
macroinvertebrates from sediments in
estuaries and other marine habitats.
This device is useful for sampling sand,
gravel, mud, clay and similar substrates
and is available in three sizes: 0.06-m2,
0.1-m2, and 0.2-m2. Larger versions of
this grab are available, and their use is
dependent upon the type of bottom to be
sampled, and the type of vessel available
to deploy the sampler.
The modified Van Veen grab sampler
has paired jaws that penetrate the
intended substrate without disturbing
the water-sediment boundary layer.
They are closed by the pincher-like
action of two long arms. The long arms
give added leverage for penetrating
hard sediments.
The modified Van Veen is basically an
improved version of the Petersen grab in
that long arms have been attached to the
jaws to help stabilize the grab on the
bottom in the open sea just prior to or
during closure of the device. This grab
is used extensively in Puget Sound for
the ambient monitoring program and for
pollution-related surveys. Large hinged
screen doors with rubber flaps have
5-10
Sampling Program Issues
-------
been added to the top of the sampler for
access to the surface of the sample.
Additional weights can be applied to the
modified Van Veen jaws to effect greater
penetration in sediments, although
penetration is not as deep in hard sand
or cobble as with the Young grab or the
Smith-Mclntyre.
Young Grab:
The Young grab sampler is similar in
operation to the Van Veen and the
Smith-Mclntyre, but the sample can be
accessed undisturbed from the top of the
grab through hinged doors like a Smith-
Mclntyre. It is encircled by a ring-like
frame which enhances flat, stable
landings of the grab on the substrate.
Weights can be added to the frame to
aid penetration in hard sand or cobble.
A major advantage of the Young grab is
efficient performance without the risk of
injury associated with the spring-loaded
Smith-Mclntyre. This grab can be
provided in a 0.044-m2 and a 0.1-m2
version. The former is appropriate to
small boat operations while the latter
size is more effective for marine work
and obviously requires fewer lowerings
or "drops" to obtain the same volume of
material and community representation.
Recent comparisons of the Young and
Smith-Mclntyre grabs in rough Atlantic
waters revealed consistently greater
volumes of sediment collected by the
Young grab in six trials each in soft
sandy muds, sand, packed sand, and
sand and gravel sediments. While the
grabs were the same size (0.1-m2) and
had the same weight attached, the
significant factor in performance was the
design differences of the two grabs
(Gibson 1995, unpublished).
While either the 0.1-m2 Young or Smith-
Mclntyre designs are effective off-shore
grabs for the biocriteria development
purposes of this guidance, the Smith-
Mclntyre provides better access to the
sample while the Young grab is easier
and safer to operate, especially in rough
weather. An advantage of both designs
is that the retrieved sample can be cross-
sectioned and examined intact, although
this is easier with the Smith-Mclntyre
design.
Core Samplers
Core samplers use a surrounding frame
to ensure vertical entry; vertical
sectioning of the sample is possible
(USEPA 1986-1991). Coring devices can
be used at various depths in any
substrate that is sufficiently compacted
so that an undisturbed sample is
retained; however, they are best suited
for sampling the relatively homogenous
soft sediments, such as clay, silt, or sand
of the deeper portions of estuaries and
coastal marine waters. Because of the
small area sampled, data from coring
devices are likely to provide very
imprecise estimates of the standing crop
of macrobenthos.
KB, Ballcheck, and Phleger Corers:
KB type, Ballcheck, and Phleger corers
are examples of devices used in shallow
or deep water; they depend on gravity to
drive them into the sediment. The cores
are designed so that they retain the
sample as it is withdrawn from the
sediment and returned to the surface.
Hand corers designed for manual
operation are used in shallow water.
Sections of the core can be extruded and
preserved separately or the entire core
can be retained in the tube and
processed in the field or laboratory.
Intact cores can also be preserved by
freezing and processed later.
Additional replication with corers is
feasible because of the small amount of
material per sample that must be
handled in the laboratory. Multiple-
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-11
-------
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
5-12
Sampling Program Issues
-------
retention of total macrofaunal organisms
by 130 to 180%; however, costs for
processing the samples may increase as
much as 200% (USEPA1986-1991).
It is recommended that a standard mesh
size be selected for all monitoring
studies. A review of estuarine
monitoring programs from around the
country (Bowman et al. 1993) showed
that both 0.5- and 1.0-mm mesh sizes are
used, with a slight majority of the
programs reviewed using a 0.5-mm
mesh screen (Table 5-5). Dauer (1993)
evaluated biocriteria developed from
data collected as part of the Virginia
Benthic Biological Monitoring Program
using a 0.5-mm mesh screen.
Sieving can be done either aboard the
survey vessel or on shore after the
cruise. Sieving occurs prior to fixation
(sample preservation) aboard the vessel,
whereas waiting until after the cruise
requires fixation prior to sieving. If
inadequate concentrations of fixative are
added and deterioration or
decomposition of organisms occurs,
there may be significant sample
degradation. If large numbers of
samples are to be collected, field sieving
reduces sample storage requirements as
well as the modification/loss of data
(USEPA 1992,1994d).
After samples have been collected, the
samples must be processed so that data
can be collected and analyzed. Two
aspects of sample processing of
particular concern are the subsampling
and identification that may occur in the
field or laboratory. Sorting procedures
are described in Klemm et al. (1992).
*• Subsampling of benthic inf auna can
be accomplished by subcoring; i.e.,
removing smaller core samples from
within a grab or core sample, and
sorting all organisms found within
the subcore. The size and number of
subcores that should be taken will
depend upon the variability of the
infaunal community. Representative
subsampling can be difficult to
achieve if benthic species have
patchy or clumped distributions.
Subsampling can also damage
collected organisms (e.g., polychaete
worms), decreasing the number of
specimens that can be identified to
genus or species;
*• Several studies have examined the
effect of varying levels of taxonomic
analysis on the results of statistical
measures of the infaunal community
(e.g., Ferraro and Cole 1990,1992,
1995, Warwick 1988, Warwick et al.
1990). The studies indicate that in
some instances species-level
taxonomic identification does not
yield any more information than
family- or even phylum-level
identification. The degree of
taxonomic proficiency required to
adequately characterize the
community will depend upon the
diversity present in the community.
Species level identification is
necessary and cost-effective for fish
surveys. However, while this is
desired for macroinvertebrates, it is
often too costly and assessment
needs can usually be met at the
genus level.
Although species-level identifications
may not be necessary for classifying sites
as minimally impaired or impaired, this
degree of taxonomic identification may
be required to assess the sources of
impairment using data collected in Tier
3. Species-level identifications require
greater taxonomic expertise than do
higher taxonomic divisions; this species
level of expertise may not be as readily
available to state agencies. If this is the
case, then state resource managers must
determine whether the cost of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-13
-------
Table 5-5.
Mesh sizes used in estuary benthic monitoring programs.
Monitoring Program
Chesapeake Bay
Tar/Pamlico
EMAP-Near Coastal
Naples Bay, Florida
Puget Sound Ambient
Monitoring Program
Puget Sound Estuary
Program
Mesh Size (mm)
0.5
0.5
0.5
0.595
1.0
1.0
Reference
Dauer 1993, Holland et al.
1987, 1988, 1989,
Ranasinghe et al. 1992
Eaton 1992a-d
USEPA 1992, Weisberg et
al. 1993, Holland 1990
Simpson et al. 1979
PSWQA 1988, 1990, 1991
Simenstad et al. 1991
contracting these identifications is
justified based on the information
obtained and the assessment tier to
which it would be applied. One
approach to this problem of obtaining
sufficient taxonomic expertise is for the
states of a region to cooperate in a joint
venture to employ the taxonomic
expertise necessary to all. In this
manner the cost of a skilled taxonomist,
either contracted or on staff, can be
shared.
5.1.2 Fish
Fish communities include species in a
variety of trophic levels (omnivores,
herbivores, planktivores, piscivores).
Fish are long-lived, integrate long- and
short-term changes, and they also
integrate effects of lower trophic levels;
thus, fish community structure is a good
measure of integrated environmental
health. Estuarine and coastal marine
fish receive a large amount of public
attention because of sport and
commercial fishing and attendant
concerns regarding fish production and
safety for human consumption. On the
negative side, fish may be wide-ranging
or migratory and might not reflect local
conditions in estuaries and coastal
marine waters; some fish species may
also be influenced by management
(stocking), angling, and commercial
harvesting; and unbiased sampling is
difficult because each feasible gear type
is highly selective.
Sampling Gear
Fish communities may vary
considerably among the numerous
habitat types that may be present in a
target estuary or coastal marine area.
The choice of sampling method and gear
type will depend upon the habitat and
the fish species of interest. Shallow
areas may best be sampled using dip
nets or beach seines, while deeper
waters may be sampled using gill nets,
purse seines, or otter trawls. Net and
mesh size should be appropriate to
allow a representative sample of target
fish to be obtained. Fishing effort
should be comparable among stations
with constant tow distances, times,
speeds, and lengths of trawl warps.
Because there is no easy way of
estimating population size in any given
area of an estuary or coastal marine area,
consistency in effort is of the utmost
5-14
Sampling Program Issues
-------
importance to allow legitimate
comparisons among sites.
Maryland DNR's IBI sampling
techniques are designed to sample the
nearshore fish communities in the tidal
tributaries of the Chesapeake Bay. They
were modeled after the Maryland
Striped Bass Juvenile Seine Survey
which has been ongoing since 1954
(Goodyear 1985). Two beach seines are
pulled at each site allowing a half hour
interval between hauls for repopulation
of the seine area. Seines are pulled with
the tide employing a "quarter sweep"
method where one end of the seine is
held on shore while the other end is
fully extended perpendicular to shore,
and then pulled back into shore forming
a semi-circle. The seine used is a bagless
6.4-mm mesh seine 30.5-m in length and
1.2-m deep. Precautions are taken upon
approaching the site to avoid
disturbance of the sampling area.
Concurrent trawls are pulled with the
tide in the channel adjacent to shore. A
small otter trawl (3.1-m with 12.8-mm
stretch mesh, and 50.8-cm x 25.4-cm
doors) with tickler chains is used to
sample the bottom community local to
the seine sample area. Water quality
measurements (temperature, dissolved
oxygen, pH, conductivity, and salinity)
and Secchi depth are also taken in the
trawling area. Water quality is sampled
at surface, mid, and bottom depths.
These measurements have proven useful
in relating water quality parameters to
fish communities. A summary of fish
sampling is given in Table 5-6.
*• Subsampling of fish collected using
any of the sampling methods
mentioned above is problematic. It
is probably most efficient and
statistically valid to identify and
make external measurements and
observations of all fish caught
during a given tow or time period.
> The level of taxonomic identification
required to effectively characterize
the fish community will depend
upon the diversity of the community
being sampled and the metrics being
used to evaluate the data.
Identification to species is preferable
for most individuals taken in a given
area. Individuals that cannot be
field-identified should be preserved
and returned to the lab for
identification.
5.1.3 Aquatic Macrophytes
Macrophytes form an integral part of the
littoral zone of many estuaries and
Table 5-6.
Sampling summary for fish.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Sublittoral.
Seines and any gear that effectively captures bottom -feed ing and pelagic
fish, usually otter trawls.
Any season can be selected depending upon migration and recruitment
patterns in the region. Seasonal sampling might be needed to assess
particular problems.
Bottom-feeding and pelagic fish. Sufficient sets of gear to obtain
representative species counts (usually 4 or more).
Collected species are weighed, measured, and examined for external
abnormalities (lesions, growths, deformities). Histopathology may be
performed.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-15
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coastal marine waters, serving as habitat
for fish and invertebrates as well as
being a distinct biological assemblage.
For many estuaries, the areal extent and
distribution of SAV is used as an
indicator of estuarine quality (Batiuk et
al. 1992). Ecosystems whose primary
producer component is dominated by
aquatic macrophytes can be transformed
to macro algae or phytoplankton-
dominated systems through nutrient
enrichment. Increased nutrient input
stimulates macrophyte growth;
however, it also promotes growth of
periphyton and phytoplankton, which
shade the SAV. The shading reduces
macrophyte growth and survival
(Dennison et al. 1993, Batiuk et al. 1992).
Overall, macrophyte standing stock is an
excellent indicator of estuarine water
quality. The presence of confounding
factors, such as diseases, can be
determined from examination of
affected plants, or from historical
information. Potential macrophyte
metrics are listed in Table 5-7 and the
recommended sampling protocol for
macrophytes is summarized in Table 5-
8. Field sampling can be performed in a
single visit. Plants are identified and
weighed on-site, with voucher
specimens preserved as necessary.
There is no intensive laboratory analysis
required.
5.1.4 Phytoplankton
Phytoplankton are the base of most
estuarine food webs (Day et al. 1989),
and fish production is linked to
phytoplankton primary production (e.g.,
Day et al. 1989). Excessive nutrient and
organic inputs from human activities in
estuaries and their watersheds leads to
eutrophication characterized by:
reduction in seagrasses, increases in
phytoplankton biomass, macrophyte
biomass (macroalgal biomass), reduced
water clarity, and reduced oxygen
saturation in bottom waters. From a
human perspective, problems might
include loss of aesthetic appeal,
decreases in desirable commercial and
game fishes, and loss of recreational
access caused by increased macrophyte
production.
Phytoplankton standing stock is
measured by surface chlorophyll a
concentration, sampled at the 0.5-m
depth at each sampling site (Table 5-9).
Tiers 1 and 2 can use a single
measurement taken at each sampling
site with a fluorometer attached to a
conductivity-temperature-depth meter
(CTD) (USEPA 1994c) taken from June
through September. Alternatively,
chlorophyll a may be determined
spectrophotometrically on
phytoplankton samples returned to the
lab. Tier 2 can include identification of
dominant taxa, including nuisance taxa.
Tier 3 uses a seasonal or annual average
surface chlorophyll concentration from
all stations over all sampling events and
can include full characterization of the
phytoplankton community.
If phytoplankton communities are to be
sampled, several techniques may be
employed; these are described more
fully in APHA (1992).
*• Phytoplankton samples may be
obtained using water bottles
deployed on a wire at a given, or
preferably various, depths. The
water bottles used should be
constructed and cleaned in a manner
appropriate for the collection of
phytoplankton samples (e.g., Niskin
bottles washed and rinsed in order
to remove contaminants).
Chlorophyll concentration is
measured from the sampled water,
and phtyoplankton cells may be
filtered or settled for identification
and enumeration.
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Sampling Program Issues
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Table 5-7.
Potential aquatic macrophyte metrics.
Metric
Response to impairment
Tier 1:
% cover
dominant taxa
substantially more or less than reference
substantially more or less than reference
Tiers 2-3:
% cover
biomass
maximum depth of plant growth
density of new shoots
stem counts
reduced or enhanced
substantially more or less than reference
reduced under enrichment
reduced
reduced
Table 5-8.
Sampling summary for aquatic macrophytes.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Euphotic zone.
Aerial photography; quadrats
During growing season
Tier 1 : Estimate of area covered by macrophytes.
Tiers 2-3: Quadrat samples for biomass collected by diver; 3-5
placed transects perpendicular to shore; sam pies are taken at 0
depth intervals from edge of emergent zone to the sublittoral.
randomly
.5-m
Tier 1 : Dominant taxa identified, % cover estimated from aerial
photography.
Tiers 2-3: All species identified, relative abundance of each estimated
from wet weight.
Table 5-9.
Sampling summary for phytoplankton.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Each sampling site preferred.
Fluorometer attached to CTD (USEPA 1994e) for in situ measurements;
or spectrophotometrically on water samples collected with a water
sampler.
Tiers 1 and 2: June - September
Tiers 2 (optional) and 3: growing season average; 6-10 samples; March -
October (longer in subtropical regions).
Preferred: single sample, 0.5-m depth.
Alternate: at same depths as nutrient samples.
Tier!: Chlorophyll a mg/L (Tiers 1-3). Tier 2: ID dominant taxa. Tier 3:
full comm unity species characterization.
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*• Phytoplankton may also be
collected by net hauls using a
plankton net with an appropriate
mesh size.
Bottle collections are most useful
when analyzing a bulk community
measure such as chlorophyll a
concentration (assuming a
fluorometer coupled to a CTD is not
used), while net hauls are better for
studies designed to enumerate
species. Water samples for
chlorophyll a determination can also
be used for nutrient analysis.
*• The level of taxonomic
identification that should occur
will depend upon the diversity of
the community, the analyses that
are to be performed, and the cost
and availability of taxonomic
experience;
*• If phytoplankton are collected
using water bottles, the water may
be subsampled in the field or lab
prior to analysis. The size and
number of subsamples that should
be taken will depend upon the
variability present in the
community;
*• If subsamples are taken from net
hauls, it may be necessary to
resuspend the organisms found in
the cod end of the net in a larger
volume of water in order to
facilitate subsampling.
5.1.5 Zooplankton
(Developmental)
Zooplankton are most effectively
sampled using net hauls with 118-|_im
mesh sizes. Because zooplankton are
known to exhibit diel periodicity in
their locations in the water column,
sampling times should reflect this
temporal variability; i.e., sampling
should, in general, be conducted at
night. Also, consideration should be
given to the use of vertical or oblique
tows. In any instance, gear size, mesh
size, rate of retrieval on the haul back,
vertical or oblique tow, time of day or
night and tide cycle are factors which
must be kept constant if zooplankton
surveys are to be included in
biocriteria development.
Meaningful bulk community
measurements do not exist for
zooplankton; therefore, if zooplankton
are to be sampled, they should be
identified and enumerated. It may be
difficult to locate or develop the
taxonomic expertise necessary to
identify zooplankton to species,
especially given the large number of
planktonic larvae. Zooplankton are
considered to be in a developmental
status with respect to their use as an
estuarine and coastal marine
bioassessment assemblage.
Zooplankton populations experience
year-round seasonal fluctuations in
abundance as a result of variable
larval recruitment into the population,
variable food sources, and physical
processes which may move larvae and
adults into and out of the estuary (Day
et al. 1989). The pattern of seasonal
abundance differs with changes in
latitude. Zooplankton in higher
latitudes have one or more mid-
summer peaks and very low numbers
during the winter.
Abundances in temperate estuaries
are much more variable and may
experience spring peaks and minima
during the summer and winter
months. Tropical estuaries do not
experience the low in population
during the winter.
Some long-term monitoring projects
have identified community measures
that indicate changes in
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Sampling Program Issues
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environmental conditions over time
(e.g., nutrient loads or toxicants), as
well as particular zooplankton taxa
whose densities affect larval fish
survival (Buchanan 1991).
Zooplankton community
characteristics that are under
investigation for application as
bioindicators include:
> Diversity, measured through
standard indexes such as
Shannon-Wiener, to evaluate the
taxonomic complexity of the
assemblage;
*• Ratios of specific taxonomic
groups within the assemblage to
gauge community balance and
identify possible impairment;
*• Presence of Hypotrichs (a ciliate of
the order Hypotrichida);
*• Total biomass to assess
assemblage production;
*• Relative abundance of pollution
tolerant and sensitive species to
identify and evaluate impairments
to the assemblage;
> Unnatural variability in
abundance can be used to identify
the presence of short-term
pollution or climate events;
*• Size structure can be used to
evaluate the growth of cohorts in
the assemblage, which can
provide information on possible
short- and long-term system
perturbations.
5.1.6 Epibenthos (Developmental)
The epibenthos assemblage is also
considered to be in a developmental
stage for use in estuarine and coastal
marine bioassessment. Taxa within
the epibenthic community appear to
be persistent and sensitive to
environmental stress. They are
characterized by physiological
mechanisms that allow them to
tolerate the varying salinity, DO, and
temperature conditions encountered
in estuaries and coastal marine waters,
or reproductive cycles that allow them
to avoid high-stress periods. Some
epibenthos and facultative infauna
can relocate to avoid areas of
environmental stress.
Epibenthos can be sampled using a
Renfro beam trawl, otter trawl, or
epidbenthic sled. Camera tows or
remotely operated vehicles with
camera or video capabilities may also
allow enumeration of epibenthos,
although collection of organisms
would not be possible and
quantitative assessments difficult.
Subsampling might involve a process
similar to that suggested by Plafkin et
al. (1989); a box with a numbered grid
system into which collected
epibenthos are evenly distributed
could be used to randomly select an
appropriate number of organisms for
subsequent sorting.
Some of the advantages to using
epibenthos for estuarine and coastal
marine bioassessment are:
> This assemblage is very sensitive
to anthropogenic sources of stress,
and it can be used in both a
nearfield and farfield context with
equal facility;
Sampling can be conducted in shallow
waters using a dip net and in deep
waters with a trawl;
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*• The total number of common
species will be limited by the fact
that the deep water sampling gear
is restricted to fairly level bottoms;
*• Subsampling can be employed to
reduce labor costs and increase
co st-ef f ectiveness;
*• Field and lab work, and data
analyses can be done quickly with
trained personnel;
*• Samples can be sorted
qualitatively, and a nonparametric
analysis can be applied to provide
a quick screening method.
*• Seagrasses and macroalgae can
hinder or increase the time
necessary for field sorting;
*• The seasonality of epifauna needs
to be factored into the sampling
design.
The developmental method described
in Chapter 13 appears promising for
detecting impairment. If successfully
adapted to regions outside Florida,
North Carolina, and Puget Sound
where it is being tested, it may
become a standard estuarine
bioassessment method in the future.
A proposed sampling protocol is
summarized in Table 5-10.
Table 5-10.
Sampling summary for epibenthos.
Habitat
Sampling Gear
Index Period
Sampling
Analysis
Soft sediments (sleds and trawls); shallow,
Renfro Beam Trawl (Farrell 1993a,b), smal
net
vegetated (dip net)
otter trawl; epibenthic sled; dip
Preferred: mid-summer
Alternative: growing season, average of 10 samples.
Ca. 4-m tow length in estuaries; 0.1 - 0.5 nm tow lengths (DGPS) in
coastal waters and Puget Sound.
Taxonomic ID preferably to species.
The disadvantages of this assessment
methodology are:
*• The stress index is developed
solely for anoxia; it might not
allow assessment of other
stressors;
*• Stress values may not be available
for many species, or may be
difficult to determine;
*• Sleds and trawls are restricted to
level bottoms; and cannot be used
for sampling hard bottoms, or rock
rubble;
5.1.7 Paleoenvironmental Systems
(developmental)
Diatom and foraminifera species have
narrow optima and tolerances for
many environmental variables, which
make them useful in quantifying
environmental characteristics to a
high degree of certainty. They
immigrate and replicate rapidly,
which makes them quick to respond
to environmental change (Dixit et al.
1992). Changes in assemblages also
correspond closely to shifts in other
biotic communities sampled in
estuaries such as aquatic macrophytes,
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Sampling Program Issues
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zooplankton, and fish. They have also
been used alone as environmental
indicators of eutrophication, metal
contamination, salinification, thermal
effluents, and land use changes.
Furthermore, since diatoms and
foraminifera are abundant in almost
every marine ecosystem, a relatively
small sample is sufficient for analysis.
This allows for many samples to be
easily collected, analyzed, and
archived (Dixitet al. 1992).
The general lack of time-series data
has prompted attempts to
demonstrate marine eutrophication
from present-day observations using
the benthic community and chemical
criteria (Dale et al. 1999). Benthic
foraminifera have been proven useful
as indicators of oxygen concentration
in bottom sediments (Alve 1991).
Dinoflagellate cysts are also
increasingly useful as indicators of
short-term environmental change
caused by climate and human
pollution (Dale et al. 1999). The cysts
are recovered by pollen identification
techniques; they are acid-resistant and
therefore not subject to dissolution
problems sometimes affecting diatoms
and foraminifera (Dale et al. 1999).
Measurements of biogenic silica in
sediments are most often used as an
index of diatom production (Stoermer
et al. 1990, Conley et al. 1993, Cooper
1995). Isolation of BSi from Si in
mineral phase is based upon the fact
that the silica of diatoms is only
weakly crystalline and dissolves
readily in a weak base. Potential
indicators and a proposed sampling
summary are shown in Tables 5-11
and 5-12.
The total number of cores taken in a
particular estuary is dependent upon
the hydrological complexity of the
estuary. Generally, one to three cores,
but some times up to ten are required
from each estuary or tributary being
assessed. However, once a
paleoecological record is established,
there is no need to repeat the
sampling.
Although the number of cores is
small, each core requires substantial
effort to analyze: sectioning,
radioisotope dating, chemical
analysis, pollen analysis for further
dating, and diatom or foraminifera
analysis. Current estimates for
paleological analysis is about $100 per
section (not per core), depending on
the number and intensity of analysis
done on each section and the
experience of the lab performing the
analysis. The complexity of estuaries
requires some background
information about the area in which
sampling is occurring. This
information should assist in decision
making on the location and number of
cores to be retrieved.
The study of paleoenvironmental
systems requires a corer that will
retrieve an intact core, with minimal
edge disturbance (Table 5-4). K-B,
Phleger, and Piston corers have all
been used successfully for these
analyses (see Section 5.1.1). Small
surface area is not an issue; a single
core will suffice.
5.2 Sampling Design Issues
Consideration of sampling design is
critical in developing a new
monitoring program for estuarine
bioassessment and biocriteria.
Sampling design includes defining the
questions to be addressed by the data,
defining the units that will be
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Table 5-11. Potential paleoecological indicators
Indicator
Taxa richness (diatom,
foraminifera,
dinoflagellate cysts )
Biogenic silica
Total organic carbon,
Total N, Total S
Ammonia/Elphidium
ratio (foraminifera)
Centric/pennate ratio
(diatoms)
% Cyclotella
sedimentation rate
Dinoflagellate cysts
% Fursenkoina
% Trochammina
Response to Impairment
reduced
increase with nutrient
enrichment
increase with enrichment
increase with hypoxia
increase with nutrient
enrichment
increase with nutrient
enrichment
increase with watershed
erosion
increase with cultural
eutrophication
increases with hypoxia
increases with hypoxia
Reference
Cooper and Brush 1991
Turner and Rabalais 1994
Turner and Rabalais 1994
Sen Gupta etal. 1996
Cooper and Brush 1991
Cooper and Brush 1991
Brush 1989
Dale etal. 1999
Alve 1991
Patterson 1990
Table 5-12. Sampling summary for paleoenvironmental systems
Habitat
Sampling gear
Index period
Sampling
Analysis
Diatoms
Foraminifera
Dinoflagellate
Cysts
Age of sections
up to 150 years
Older than 150
years
Stable depositionalzone, biogeochemical conditions for preservation
Bottom corer
None
Tiers 1-2: none
Tier 3: background information specific to the estuary being sampled will
determine the number of cores necessary.
Cores sectioned at regular intervals depending on deposition rate and
resolution desired.
Species composition and enumeration of at least 300 organisms in each
section. Digestion/clarification methods depend on assemblage.
210Pb determination based on radioisotope assay with alpha
spectroscopy.
Palynological (pollen) analysis correlated with known historical changes
in terrestrial vegetation (land use), and 14C analysis (>1000 yr).
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Sampling Program Issues
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sampled, and developing a sampling
design that is cost-effective for
answering the defined questions.
5.2.1 Statement of the Problem
The first task in developing a
sampling and assessment program is
to determine, and be able to state in
simple fashion, the principal questions
that the sampling program will
answer. Questions may or may not be
framed as hypotheses to test,
depending on program objectives. For
example, suppose that a sampling
program objective is to establish
reference conditions for biological
criteria for estuaries in a given region.
Typically, the initial objectives of a
survey designed to develop criteria
are to identify and characterize classes
of reference sites in estuaries. Initial
questions may then include:
*• Should minimally disturbed sites
be divided into two or more
classes that differ in biological
characteristics and dynamics?;
*• What are the physical, chemical,
and relevant biotic characteristics
of each of the estuary site classes?
After the monitoring and assessment
program has developed biological
criteria, new questions need to be
developed that encompass
assessments of individual sites,
estuaries, or estuaries of an entire
region or state. Specific questions
may include:
*• Is site abc similar to reference sites
of its class (unimpaired), or is it
different from reference sites (is it
altered or impaired)?;
> Overall, what is the status of
estuarine waters in the region?
What percentage of estuarine
waters is similar to reference
conditions? What percentage is
impaired?;
*• Has estuary abc changed over a
certain period? Has it improved
or deteriorated?;
> Overall, have estuarine waters in
the region improved or
deteriorated over a certain period?
Have individual estuaries
improved? Are more waters
similar to reference conditions
now than some time ago?
Finally, resource managers often wish
to determine the relationships among
variables, that is, to develop
predictive, empirical (statistical)
models that can be used to design
management responses to perceived
problems. Examples of specific
questions include:
*• Can trophic state of an estuary be
predicted by areal nitrogen
loading rate?;
*• Can biota of an estuary be
predicted by watershed land use?
Monitoring and assessment data, and
derived models, may also be used to
help determine causal relationships
between stressors and responses of
systems. Inferring cause requires
manipulative experiments, or
inference from multiple lines of
evidence (Suter 1993). Since surveys
and monitoring programs preclude
experimental investigations, inference
of causal relations is beyond the scope
of this document. Often, there is
enough experimental evidence
available from other studies so that
additional causal experiments are not
necessary and would be superfluous
(e.g., current knowledge of nutrients
and trophic state generally makes it
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unnecessary to "prove"
experimentally which nutrients are
limiting). The development of
predictive models usually does not
require formal hypothesis testing.
It is also necessary to specify the units
for which results will be reported.
Usually, these units are the population
(e.g., all estuarine waters), but often
subpopulations (e.g., embayments or
tributaries of a given estuary) and
even individual locations (e.g., sites of
special interest) can be used. In order
to help develop the sampling plan, it
is useful to create hypothetical
statements of results in the way that
they will be reported, for example:
*• Status of a place: Baltimore harbor is
degraded;
*• Status of a region: 20% of the area
ofPuget Soundhas elevated trophic
state, above reference expectations; or
20% of estuaries in Oregon have
elevated trophic state;
> Trends at a place: Benthic species
richness in Baltimore harbor has
increased by 20% since 1980;
> Trends of a region: Average estuary
trophic state in New Jersey has
increased by 20% since 1980; or
Average benthic index values in 20%
of estuaries of the west coast have
increased by 15% or more since 1980;
*• Relationships among variables:
50% increase ofN loading above
natural background is associated with
decline in taxa richness of benthic
macroinvertebrates, below reference
expectations; or Estuaries receiving
runoff from large urban areas have
50% greater probability of elevated
trophic state above reference than
estuaries not receiving such runoff.
5.2.2 Definition of the Assessment
Unit
Defining the resource and assessment
unit of the resource begins the process
of developing biological criteria. An
"assessment unit" is a whole estuary
or part of an estuary, that will be
assessed as meeting criteria, being
impaired, etc. Clearly, a single square
meter where a grab sample is taken is
not large enough to be an assessment
unit. An assessment unit should
consist of a definable segment, basin,
or entire estuary. For example, a large
complex estuary such as Puget Sound
could be divided into its component
inlet bays, canals, and passes. Many
of the larger components could in turn
be divided into segments.
Segmentation could be determined by
some combination of mean salinity,
water residence time, dominant
substrate, or mean depth. For
example, since estuarine fauna are
determined by salinity, segmentation
often corresponds to salinity zone
(tidal fresh, oligohaline, mesohaline,
polyhaline, and marine). Small
estuaries, such as salt ponds in New
England, could be single assessment
units.
An assessment unit is the smallest
spatial subdivision of an estuary that
will be assessed; i.e., given a rating of
good or poor. An assessment may be
based on one or more sample units
within an assessment unit. A sample
unit (or sample site) is a site where an
observation is made.
5.2.3 Specifying the Population
and Sample Unit
Sampling is statistically expressed as a
sample from a population of objects.
Thompson (1992) suggested in some
cases, the population is finite,
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Sampling Program Issues
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countable, and easy to specify, (e.g.,
all persons in a city, where each
person is a single member of the
population). In estuaries, the
population is often more difficult to
specify and may be infinite, (e.g., the
sediment of San Francisco Bay, where
any location in the Bay defines a
potential member of the population).
Sampling units may be natural units
(entire estuaries, cobbles on a beach),
or they may be arbitrary (plot,
quadrat, sampling gear area or
volume) (Pielou 1977). Finite
populations may be sampled with
corresponding natural sample units,
but often the sample unit (say, an
estuary) is too large to measure in its
entirety, and it must be characterized
with one or more second stage
samples of the sampling gear (bottles,
benthic grabs, quadrats, etc.).
The objective of sampling is to best
characterize individual sample units
in order to estimate some attributes
(e.g., nutrient concentrations, DO) and
their statistical parameters (e.g., mean,
median, variance, percentiles) of a
population of sample units. The
objective of the analysis is to be able to
say something (estimate) about the
population. Examples of sample units
include:
*• A point in an estuary (may be
characterized by single or multiple
sample device deployments). The
population would then be all
points in the estuary, an infinite
population. This is the most
common sample unit applied to
estuarine assessments;
*• A constant area, (e.g., square
meter, hectare). The population
would be an artificial one
consisting of all square meters of
estuarine surface area in an
estuary, a state or a region;
> An estuary or a definable portion
of the estuary as a single sample
unit. Whole estuaries as sample
units would only be used in very
broad-scale regional assessments,
as was done by EMAP-NC, for
example, for small estuaries as a
population (e.g., Strobel et al.
1995).
5.2.4 Sources of Variability
Variability of measurements has many
possible sources, and the intent of
many sampling designs is to minimize
the variability due to uncontrolled or
random effects, and conversely to be
able to characterize the variability
caused by experimental or class
effects. For example, we may stratify
estuarine waters by salinity and
bottom substrate type (rocky, sandy,
muddy). Typically, we stratify so that
observations (sample units) from the
same stratum will be more similar to
each other than to sample units in
other strata.
Environmental measures vary across
different scales of space and time, and
sampling design must consider the
scales of variation. When sampling
estuaries, measurements (say, benthic
assemblages) are taken at single
points in space and time (1 point
along a transect in mid-summer). If
the same measurement is made at a
different place (littoral zone),
embayment, or time (winter), the
measured values will likely be
different. A third component of
variability is the ability to accurately
measure the quantity interested in,
which can be affected by sampling
gear, instrumentation, errors in proper
adherence to field and laboratory
protocols, and the choice of methods
used in making determinations.
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The basic rule of efficient sampling
and measurement is to sample so as to
minimize measurement errors; to
maximize the components of
variability that have influence on the
central questions and reporting units;
and to control other sources of
variability that are not of interest, that
is, to minimize their effects on the
observations. Many locations are
sampled in order to examine and
characterize the variability due to
different locations (the sampling unit).
Each site is sampled in the same way,
in the same place, and in the same
time frame to minimize confounding
variability.
In statistical terminology, there is a
distinction between sampling error
and measurement error that has little
to do with actual errors in
measurement. Sampling error is the
error attributable to selecting a certain
sample unit (e.g., an estuary or a
location within an estuary) that may
not be representative of the
population of sample units. Statistical
measurement error is the ability of the
investigator to accurately characterize
the sampling unit. Thus,
measurement error includes
components of natural spatial and
temporal variability within the sample
unit as well as actual errors of
omission or commission by the
investigator. Measurement error is
minimized with methodological
standardization: selection of cost-
effective, low variability sampling
methods, proper training of
personnel, and quality assurance
procedures to minimize
methodological errors. In analytical
laboratory procedures, measurement
error is estimated by duplicate
determinations on some subset of
samples (but not necessarily all).
Similarly, in field investigations, some
subset of sample units should be
measured more than once to estimate
measurement error.
If the variance of individual
measurements (measurement error) is
unacceptably large; i.e., as large or
larger than variance expected among
sample units, then it is often necessary
to alter the sampling protocol, usually
by increasing sampling effort in some
way, to further reduce the
measurement error. Measurement
error can be reduced by multiple
observations at each sample unit, (e.g.,
multiple dredge casts at each
sampling event, multiple observations
in time during a growing season or
index period, depth-integrated
samples, or spatially integrated
samples.
A less costly alternative to multiple
measures in space is to make spatially
composite determinations. In nutrient
or chlorophyll determinations, a water
column pumped sample, where the
pump hose is lowered through the
water column, is an example of a
spatially composite determination.
Spatial integration of an observation
and compositing the material into a
single sample is almost always more
cost-effective than retaining separate,
multiple observations. This is
especially so for relatively costly
laboratory analyses such as organic
contaminants and benthic
macroinvertebrates. Many estuarine
programs have adopted sampling
protocols consisting of multiple grabs
at a site that are then composited into
a single bucket for laboratory
determinations (e.g., EMAP Near
Coastal: 3 composited Van Veen grabs
at each site; Holland 1990).
Statistical power is the ability of a
given hypothesis test to detect an
effect that actually exists, and must be
considered when designing a
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Sampling Program Issues
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sampling program (e.g., Peterman
1990, Fairweather 1991). The power of
a test (1-P) is defined as the
probability of correctly rejecting the
null hypothesis (H0) when H0 is false;
i.e. the probability of correctly finding
a difference [impairment] when one
exists. For a fixed confidence level
(e.g., 90%), power can be increased by
increasing the sample size or the
number of replicates. To evaluate
power and determine sampling effort,
an ecologically meaningful amount of
change in a variable must be set. See
Chapter 12 for a discussion of
statistical power, and examples.
Optimizing sampling design requires
consideration of tradeoffs among the
measures used, the effect size that is
considered meaningful, desired
power, desired confidence, and
resources available for the sampling
program. Every study requires some
level of repeated measurement of
sampling units to estimate precision
and measurement error. Repeated
measurement at 10% or more of sites
is common among many monitoring
programs.
5.2.5 Alternative Sampling
Designs
Sampling design is the selection of a
part of a population to observe the
attributes of interest, in order to
estimate the values of those attributes
for the whole population. Classical
sampling design makes assumptions
about the variables of interest, in
particular, it assumes that the values
are fixed (but unknown) for each
member of the population, until that
member is observed (Thompson 1992).
This assumption is perfectly
reasonable for some variables, say,
length, weight, and sex of members of
an animal population, but it seems
less reasonable for more dynamic
variables such as nutrient
concentrations, loadings, or
chlorophyll concentrations of
estuaries. Designs that assume that
the observed variables are themselves
random variables are model-based
designs, where prior knowledge or
assumptions (a model) are used to
select sample units.
Probability-based designs (random
sampling)
The most basic probability-based
design is simple random sampling,
where all possible sample units in the
population have the same probability
of being selected, that is, all possible
combinations of n sample units have
equal probability of selection from
among the N units in the population.
If the population N is finite and not
excessively large, a list can be made of
the N units, and a sample of n units is
randomly selected from the list. This
is termed list frame sampling. If the
population is very large or infinite
(such as locations in an estuary), one
can select a set of n random (x,y)
coordinates for the sample.
All sample combinations are equally
likely in simple random sampling,
thus there is no assurance that the
sample actually selected will be
representative of the population.
Other unbiased sampling designs that
attempt to acquire a more
representative sample include
stratified, systematic, multistage, and
adaptive designs (Figure 5-2). In
stratified sampling, the population is
subdivided or partitioned into strata,
and each stratum is sampled
separately. Partitioning is typically
done so as to make each stratum more
homogeneous than the overall
population. Systematic sampling is
the systematic selection of every kth
unit of the population from one or
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-27
-------
Sampling Methods
Simple Random: Samples are independently located
at random
Systematic: Samples are located at regular
intervals
Stratified: The study area is divided into
nonoverlapping strata and samples
are obtained from each
Multistage: Large primary units are selected
which are then subsampled
Figure 5-2
Description of
various sampling
methods.
Adapted from
USEPA1992.
more randomly selected starting units,
and ensures that samples are not
clumped in one region of the sample
space. Multistage sampling requires
selection of a sample of large primary
units, such as fields, hydrologic units,
rectangles, or hexagons, and then
selection of secondary sample units
such as plots or estuaries within each
primary unit in the first stage sample.
Estimation of statistical parameters
requires weighting of the data with
inclusion probabilities (the probability
that a given unit of the population
will be in the sample) specified in the
sampling design. In simple random
sampling, inclusion probabilities are
by definition equal, and no corrections
are necessary. Stratified sampling
requires weighting by the inclusion
probabilities of each stratum.
Unbiased estimators have been
developed for specific sampling
designs, and can be found in sampling
textbooks, such as Thompson (1992).
Model-based designs
Use of probability-based sampling
designs may miss relationships
among variables (models), especially
if there is a regression-type
relationship between an explanatory
and a response variable. As an
example, estimation of benthic
response to discharge or outfalls
requires a range of sites from those
directly adjacent to the outfalls to
those distant from, and presumably
unaffected by, the outfalls (e.g.
Warwick and Clarke 1991). A simple
random sample of estuarine sites is
not likely to capture the entire range,
because there would be a large cluster
of far sites, with few at high ends of
the gradient. A simple random
sample may therefore be highly
inefficient with respect to models or
specific hypotheses.
In model-based designs, sites are
selected based on prior knowledge of
auxiliary variables, such as estimated
loading, depth, salinity, substrate
5-28
Sampling Program Issues
-------
type, etc. These designs preclude an
unbiased estimate of the state of the
estuaries, unless the model can be
demonstrated to be robust and
predictive, in which case the
population value is predicted from the
model and from prior knowledge of
the auxiliary (predictive) variables.
Selection of unimpacted reference
sites is an example of a model-based
design which cannot later be used for
unbiased estimation of the biological
status of estuaries. Ideally, it may be
possible to specify a design that
allows unbiased estimation of both
population and model, with an
appropriately stratified design.
Statisticians should be consulted in
developing the sample design for a
biological criteria and monitoring
program.
Selecting a Design
The selection of a station array for
bioassessment will depend on the
nature of the study and/or the desire
to delineate the areal extent of
impairment. A randomized station
selection is most appropriate for
environmental status and trends
surveys such as conducted by EMAP.
However, for specific management
decision-making, pre-selected stations
placed on a gradient such as distance
from of a discharge (sometimes
termed "nearfield/farfield") maybe
more appropriate. This method is a
form of model-based design, and
more accurately identifies suspected
sources of impairment, assesses
impacts and monitors recovery.
The number of stations to be
incorporated in a study design is most
heavily influenced by the available
resources. A minimum of three
control or reference sites is desired to
provide some indication of
background variability. The number
of test sites may vary from one to
several depending on the purpose of
the study. The distance between
stations could be decreased; i.e.,
number of stations increased to
partially account for the inefficiency of
some sampling gear or, conversely,
the distance increased; i.e., number of
stations decreased once the data have
been evaluated.
Index Period
Most monitoring programs do not
have the resources to characterize
variability or to assess for all seasons.
Sampling can be restricted to an index
period when metrics are expected to
show the greatest response to
pollution stress and when within-
season variability is small (Holland
1990). A decision must be made
between selecting a sampling period
that is representative of the biological
community, or one that reflects the
worst-case conditions for pollution
stress. From the traditional
perspective of evaluating pollution
impacts in fresh water streams,
summer-time low flow conditions are
often chosen to assess effects from
point source discharges. These flow
conditions represent minimal effluent
dilution in combination with the
natural stressors of low water velocity
and high temperature in those
constrained environments. In
contrast, the effects of nonpoint source
pollution on the benthic community
are often evaluated following periods
of high flow since nonpoint source
effects on aquatic communities are
largely driven by runoff in the
watershed. Estuaries and coastal
waters accumulate materials from
both nonpoint and point sources in a
much more dynamic way and thereby
confound the assessment so useful for
streams.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
5-29
-------
In bioassessment strategies involving
infrequent sampling, the biologically-
optimal period for sampling becomes
a major consideration. Periods of
instability in community structure,
including recruitment of young,
natural harsh environmental
conditions, changes in food source,
and migration of certain target
populations are all considerations in
conducting these biosurveys. The
biologically-optimal period, usually
mid-summer and sometimes mid-
winter, avoids all of these elements
and focuses on the time when
communities are most stable. The
resource manager or biologist will
have to choose between these
conditions, or select to cover both,
depending on the needs of the study.
5.2.6 Optimizing Sampling
Ferraro et al. (1994,1989) present a
method for quantitatively evaluating
the optimum macrobenthic sampling
protocol, accounting for sampling unit
area, sieve mesh size, and number of
replicates (n). Their approach allows
managers responsible for designing
and implementing estuarine and
coastal marine bioassessment
programs to answer fundamental
questions:
*• How large should the sampling
unit be?;
*• What sieve mesh size should be
used?;
> How many replicate samples
should be taken?
The procedure calculates the "power-
cost efficiency" (PCE), which
incorporates both the number of
samples (n), the cost (field collection
effort and lab effort combined) and
the expected statistical power for each
alternative sampling scheme. See
Chapter 12 for a more detailed
discussion of statistical power. The
various sampling schemes consist of
different combinations of sampling
gear, gear area, sieve mesh size, and
number of replicates. The method
allows determining the optimum
among a set of sampling schemes for
detecting differences in reference vs.
impaired stations when the statistical
model is a t-distribution for
comparing two means. The optimum
scheme can be defined as the least
costly one capable of reliably (e.g., a =
0.5,1-P = 0.95) detecting a desired
difference in the means of a metric
between two stations. The approach
can be applied to each metric in a test
set of metrics and the results
aggregated to determine the optimum
protocol.
There are four primary steps in
assessing the PCE of a suite of
alternative sampling schemes:
1. For each scheme, collect replicate
samples at paired reference and
impaired stations. The observed
difference in metric values
between the stations is
operationally assumed to be the
magnitude of the difference
desired to be detected.
Alternatively, a percentage of the
median (e.g., 20%) for a given
metric calculated across reference
stations could be set as the
magnitude of the difference to be
detected. In either case, this
difference, divided by the
standard deviation, is the "effect
size" (ES) of interest.
2. Assess the "cost" (q), in time or
money, of each sampling scheme i
at each station. The cost can
include labor hours for sampling,
5-30
Sampling Program Issues
-------
sorting, taxonomic identification,
and recording results.
3. Conduct statistical power analysis
to determine the minimum
number of replicate samples (r\)
needed to detect the ES with an
acceptable probability of Type I (
-------
-------
Chapter 6
Water Column & Bottom
Characteristics
Tiers 1-3 contain active survey and site
sampling. Procedures for attaining
water column and bottom characteristics
are generally the same for each tier. The
sampling however, occurs more often
over the year. Differences are noted
where applicable. Table 6-1 compares
the level of effort for each tier.
However, agencies will decide which
components of each tier will be
incorporated into their specific
programs, then they will select the level
of effort appropriate for their program.
6.1 Salinity, Temperature,
Dissolved Oxygen, & pH
Salinity, conductivity, temperature,
dissolved oxygen, and pH should be
measured at each sampling station using
a CTD meter equipped with DO and pH
probes. Measurements should be made
at 1-m intervals through the water
column. In shallow, inshore waters,
measurements should be taken at the
top, middle, and bottom thirds of the
depth. For Tier 3, in some southern
waters that undergo significant diel
temperature changes, it may be
desirable to obtain 24-hour temperature
profiles using recording equipment.
6.2 Secchi Depth
Secchi depth is usually measured at the
deepest part of the transect or grid.
Where the area is classified by depth,
Secchi measurements should be made at
each station. Readings are obtained
with a 40-cm plastic or metal Secchi disk
that is either white or is divided into
black and white quadrants on a
nonstretchable line that is calibrated in
decimeters. The disk is lowered into the
water until it disappears from view and
the depth is recorded. The disk is then
slowly raised to the point where it
reappears, with the depth being
recorded again. The mean of these two
measurement is the Secchi depth.
Observations are made from the shady
side of the boat, without sunglasses, and
as close as possible to the water to
reduce glare.
6.3 Depth
Depth should be measured at each
station using a calibrated depth sounder.
Depth can be read off a meter block
when sediment sampling by zeroing the
block when the sampler is at the water
surface. In shallow, inshore waters, a
long stick or weighted line calibrated in
decimeters may be used.
6.4 Sediment Grain Size
6.4.1 Estimation of "percent fines"
(Tierl)
Analysis of sediment grain size for Tier
1 assessments can be limited to
determining the "percent fines" at each
station. A rapid wet sieving technique
used in Puget Sound (Eaton 1997) can
serve as the basis for this
characterization. Materials needed for
the procedure include:
*• standard testing sieve No. 230, 63-
50-ml plastic beaker (filled to the
brim with sediments is about 79-ml)
100-ml plastic graduated cylinder
water bottle(s) with small outlets
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
6-1
-------
Table 6-1. Wate
for a
Characteristic
-&•
:a
•a
GO
Temperature
Dissolved Oxygen
I
Q.
£
& >;
°3
^
o 3
£b
jz
&
Q
t/3
1
1
_u
J5
O f/3
>3
3 S
< GO
Water Column
Contaminants
- Column & Bottom Characteristics. "Addition" refers to added detail or intensities
parameter initiated in an earlier tier.
Tier
1
2
3
1
2
3
addition
1
2
addition
3
addition
1
2
3
1
2
3
1
2
3
2
3
3
3
Collection Method
-measure at each sampling station, CTD
meter
-continuous or 1-2-m intervals through
water column
-shallow/inshore
-top, middle, bottom thirds of depth
-measure at each station, CTD meter
-1-2-m intervals through water column
-shallow/inshore
-top, middle, bottom thirds of depth
-some southern waters undergo significant
diel changes, it may be desirable to obtain
24-hour temperature profiles
-measure at each station, CTD meter w/
DO probe
-continuous or 1-2-m intervals through
water column
-shallow/inshore
-top, middle, bottom thirds of depth
-measure early in morning at each station
at minimum
-collect along a depth profile from surface
to within 1-m of bottom at 1-2-m intervals
-in cases of hypoxic site: recording DO
meters may be deployed (EMAP -
Louisianian Province, Engle et al 1994)
-CTD w/ pH probe
-1-2-m intervals
-top, middle, bottom thirds of depth
-deepest part of transect/grid
-if area classified by depth, measure at
each station
-See Section 6.2 for complete procedure
-each station w/ calibrated depth sounder
-read off meter block when sediment
sampling
-shallow/inshore waters: long stick or
weighted line calibrated in decimals
-collected w/ bottle samplers or pump
-see Section 6.8 for complete procedure
-each station during index period, and any
other sampling visits through year
-once accurate AVS exists for each
station, analytes only performed once per
year (during index period)
Choose One:
-USEPA's list of Priority Pollutants,
Hazardous Substance, or Target
Compound/Analytes
-same compounds targeted in EMAP-E
(Table 3-1)
-develop own list (see Section 6.10 for
more detail)
Indicates
Distribution of flora and
fauna
Rate of chemical
reactions and biological
processes
Possible reason for
modified behavior,
reduced abundance &
productivity, adverse
reproductive effects,
and mortality
Resource agency may
determine need for
more detailed
information to diagnose
sources & causes of
impairment
Chemical condition,
pollutant input, high
concentrations of
phytoplankton
Reduction of light
penetration, deposition
of mud and silt,
possible contaminated
sediment "hot spots"
Depth at sampling
station, possible
dredging or sediment
loading
Nutrient loading
Bottom characteristics,
detailed purposes in
Section 3.5.4
Trace distribution of
contaminants from a
source or to ID
potential sources
6-2
Water Column & Bottom Characteristics
-------
Table 6-1 (Cont'd). Water Column & Bottom Characteristics. "Addition" refers to added detail or
intensities for a parameter initiated in an earliertier.
Characteristic
Sediment Grain Size
o
'2
^
ss
$ -g
O ra
H 0
RPD Layer Depth
JH
^
ll
II
H GO
Sediment Contaminants
Tier
1
2
3
2
3
addition
1
1
1
2
3
Collection Method
-determine "percent fines" at each station,
see Section 6.4.1 for complete procedure
-see Section 6.4.2 for complete procedure
-see Section 6.9 for complete procedure
-measure additional sediment analytes
-vertical bisection, distance from sediment
surface to a noticeable change in color
from brownish (oxidizing conditions) to
gray (reducing conditions)
-deepest section along transect/grid
-see Standard Methods (APHA 1992) for
sampling & analytical methods
-conducted at outset of survey
*like TOC, if toxicity tests are initially
negative, no need to repeat annually
unless biological data from infauna
indicate otherwise
Choose from three approaches:
-based on EPA's contaminant lists
-NOAA NS&T suite of contaminants (used
by EMAP)
-targeted list
*see Section 6.12 for complete procedure
and rationale
Indicates
Spatial and temporal
changes of the benthic
habitat, evaluate
condition of benthic
habitats
Determine extent or
recovery from
environmental
perturbations
Assist in providing early
warnings of potential
impacts to the
estuarine ecosystem
Provide information
regarding sediment
organic content
(possibly influenced by
sewage outfalls)
Examine potential
influences of outfalls,
ID potential
contaminant "hot spots"
Note presence/absence
of benthos; learn about
life history, taxa
abundance, & major
taxa biomass
distribution; more large,
deep dwelling
species="healthy"
system
Sediment and carbon
content
Positive=severe
impacts influence
spatial sampling
design, causal
investigations
Negative=subsequently
collected biological info.
essential to ID other,
possibly more subtle
stresses
Provide insight on
limiting factors in
benthic community
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
6-3
-------
> small stainless or plastic spatula
*• stainless butter knife
> hose with nozzle (if running water is
available).
Detailed directions for performing this
wet-sieving technique are as follows:
Fill a 50-ml plastic beaker to the brim
with the sediment to be analyzed. The
capacity of the completely filled beaker
can be measured using water and the
100-ml graduated cylinder, dean away
any sediment that might adhere to the
outside of the beaker. Carefully wash
this sediment through a 63-|_im standard
sieve (USA standard testing sieve No.
230) with stainless steel mesh. The sieve
itself is about 9" in diameter with a 2"
stainless lip. Be careful not to overflow
the sieve with rinsing water. It may be
easier to wash half of the sediment
through at a time. If running water is
available, use a small brass nozzle on the
end of the hose with very low water
pressure when washing the sediment,
otherwise the sediment will need to be
washed using the water bottle. If there
are occasional large worm tubes or
shells, these are discarded and replaced
with an approximately equal volume of
sediment. The sediment remaining on
the sieve is the coarse-grained fraction.
This is washed to one side of the sieve,
and then carefully placed into the plastic
100-ml graduated cylinder with a
stainless steel butter knife, and finally
with the small stainless spatula. The
water bottle is then used to wash any
remaining sediment directly into the
graduated cylinder, and to wash down
the sides of the cylinder. Let the
sediment-water mixture settle in the
100-ml graduated cylinder for
approximately 5 minutes until the
supernatant water is clear. This may
take longer for very fine-grained
sediments. Note the volume of the
coarse-grained fraction which remains
after sieving. This can be divided by the
original volume to obtain the percentage
of the coarse fraction. The standard
usage, however, is for percent fine-
grained fraction or "percent fines".
This is calculated by subtracting the
volume of sediment remaining in the
cylinder (ml of coarse-grained fraction)
from the original volume, and dividing
this number (ml of fine-grained) by the
original volume to obtain the percent
fines.
6.4.2 Sediment Grain Size (Tiers 2
and 3)
Additional grain size data for Tier 2 and
Tier 3 assessments should include
determination of the size distribution
using a standard graded sieve series.
This analysis should be performed for a
sediment sample collected at each
sampling station. In the early years of
the assessment program, this analysis
should be performed for each sampling
period. When an accurate sediment
characterization exists for the area of
each station, sediment grain size
analysis could be performed only
annually or biennially (on samples
collected in the index period), unless the
agency believed that sediment
conditions at a site may have changed.
This could occur, for example, following
a major storm. Buller and McManus
(1979) provide a review of the
methodological and statistical analysis
of sediment samples. If seasonal
variations in grain size are exhibited, it
is recommended that direct comparisons
between samples collected during
different seasons be avoided. Studies
investigating interannual variation in
the percent composition of grain sizes
should be conducted during the same
season (preferably the same month) each
year. Furthermore, it is recommended
that grain size be sampled when
contaminant concentrations are expected
to be at their highest level to evaluate
worst-case scenarios.
6-4
Water Column & Bottom Characteristics
-------
6.5 RPD Layer Depth
The concept behind using the depth
distribution of benthic
macroinvertebrates is based on the
premise that "healthy" benthic
communities in fine sediments in meso-
and polyhaline waters consist of
relatively large, deep dwelling species;
while impaired areas will have fewer of
these organisms. The depth distribution
of benthic infauna in sediments
integrates functional parameters such as
life history, taxa abundance, and major
taxa biomass distribution.
6.6 Total Volatile Solids
Total volatile solids (TVS) is the Tier 1
indicator for sediment carbon content.
TVS should be determined for the
deepest station along each transect or
grid, based on the assumption that
deeper stations will represent sinks for
organic carbon in the sediments.
Sampling and analytical methods are
discussed in Standard Methods (APHA
1992).
6.7 Sediment Contaminant
Toxicity
Sediment toxicity testing is a diagnostic
indicator for Tier 3. When results are
positive for a station, severe impacts at a
known locality will influence spatial
sampling design and causal
investigations. Where toxicity test
results are negative throughout the set
of stations sampled, subsequently
collected biological information is
essential to identify other, possibly more
subtle stresses on the system.
6.7.1 10-day Static Sediment
Toxicity Test with Marine and
Estuarine Amphipods
ASTM (1998a) and USEPA (1994b)
developed procedures that measure
short term adverse effects of potentially
contaminated sediment, or of a test
material experimentally added to
sediment, on marine or estuarine
infaunal amphipods during static 10-day
exposures for the following species:
Rhepoxynius abronius, Eohaustorius
estuaris, Ampelisca abdita, Grandidierella
japonica, and Leptocheirus plumulosus.
The amphipod Corophium insidiosum has
also been used in standard testing (Reish
and Lemay 1988). Solid phase tests use
overlying water in aerated 1-L glass test
chambers. Mortality and sublethal
effects such as growth, emergence of
adults, and inability to bury in clean
sediment are determined after exposure
of a specific number of amphipods
(usually 20) to the test sediment.
Response of the amphipods to the test
sediment is compared with the response
observed in control or reference
sediment. The negative control
sediment is used to provide a measure
of the acceptability of the test by
providing evidence of the health and
relative quality of the test organisms, the
suitability of the overlying water, and
test conditions and handling procedures
(ASTM 1998b, USEPA 1994b). The
reference sediment, which is similar in
physical characteristics to the test
sediments and typically collected from a
similar location, is used as the basis for
interpreting data obtained from the test
sediments (ASTM 1998b).
The toxicity of field-collected sediments
may be assessed by either (a) testing the
whole sediment and testing for
significant differences in responses
between reference or control and test
sediment exposed animals or (b) testing
dilutions of a test sediment with clean
sediment to obtain an LC50 or other
effect concentration, for survival,
reburial success, or growth (ASTM
1998b, Nelson et al. 1993, Swartz et al.
1995).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
6-5
-------
6.7.2 10-day Static Sediment
Toxicity Test with Marine and
Estuarine Polychaetous
Annelids
Marine or estuarine infaunal
polychaetes are used in whole sediment
tests during 10-day or 20- to 28-day
exposures to determine adverse effects
of potentially contaminated sediment, or
of a test material added experimentally
to sediment. Polychaete species include
Neanthes virens for the 10-day and
Neanthes arenaceodentata for the 10-day
and 20- to 28-day tests (ASTM 1998c).
Other polychaete species that have been
used in similar sediment testing include
Capitella capitata, Ophrotrocha diadema,
and Ctenodrilus serratus (Reish and
Lemay 1988). The 10-day test measures
effects of contaminated sediment on
polychaete survival. The 20- to 28-day
test determines effects of contaminated
sediment on polychaete survival and
growth. If smaller species are used, such
as N. arenaceodentata, five worms are
placed in a 1-L glass test chamber with a
minimum sediment depth of 2- to 3-cm
and the overlying water is aerated.
Either young adults or recently emerged
juvenile (2- to 3-weeks post-emergence)
worms are used in the 10-day test; only
recently emerged (2- to 3-weeks)
juveniles are used in the 20- to 28-day
test. Survival of worms exposed to the
test sediment is compared with the
survival in a negative control or
reference sediment in either test. If
larger species are used, such as N. virens,
ten worms are placed in a glass aquaria
(4- to 37-L) with a minimum sediment
depth of 10-cm and the overlying water
is aerated.
The percent survival of polychaetes
exposed to field-collected sediment is
compared to those exposed to a negative
control or reference sediment in 10-day
tests. Survival and body weight of
surviving animals is compared to those
exposed to negative control or reference
sediment in 20- to 28-day tests. The
toxicity of field sediments may also be
assessed by testing dilutions of highly
toxic test sediments with clean
sediments to obtain either an LC50 or
other effect concentration of the
material.
6.7.3 Static Acute Toxicity Tests
with Echinoid Embryos
Echinoderm embryos and larval form
sea urchins (Strongylocentrotus
purpuratus and Strongylocentrotus
droebachiensis) and sand dollars (Arbacia
punctulata, Lytechinus pictus, and
Dendraster excentricus) have been used in
marine sediment interstitial (pore) water
tests (ASTM 1998a). Interstitial water
from marine sediments is isolated using
either in-situ peepers (Sarda and Burton
1995, Brumbaugh et al. 1994, Bufflap and
Allen 1995), suction in the field (Watson
and Prickers 1990), laboratory
centrifugation (Ankley et al. 1991,
Burgess et al. 1993, Kemble et al. 1994,
ASTM 1998b), or sediment squeezing
(Long et al. 1990). Embryos are obtained
by inducing adults to spawn, using
either physical (e.g., electric stimuli) or
chemical (injection of potassium
chloride) means, and then combining
gametes.
Embryos are exposed to the test pore
water and controls (culture water) for
48- to 96-hours, depending on the
species and test temperature. The test
measures the proportion of embryos or
larvae that develop into normal pluteus
larvae. Pore waters can be tested
"whole"; i.e., undiluted, and organism
responses expressed in terms of a
significant difference between controls
and test waters. Alternatively, pore
water samples can be diluted with
known, clean culture water and the
results expressed as an LC50 or other
6-6
Water Column & Bottom Characteristics
-------
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
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
6-7
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assessed in Tier 3 with the measurement
of additional sediment analytes.
Standard methods for TOC analysis are
presented in APHA (1992). In the early
years of the assessment program, TOC
analysis should be performed for each
station in each sampling period. Once
the resource agency is confident that an
accurate characterization of sediment
TOC exists for each station, the analysis
could be performed only once every two
or more years (on samples collected in
the index period), unless stations that
appear to be influenced by organic input
(e.g., sewage outfalls) are identified. In
this case, TOC analysis should continue
to be performed for each sampling
period for these stations.
6.10 Water Column
Contaminants (Tier 3)
Water column contaminants such as
organic compounds (e.g., herbicides,
pesticides, hydrocarbons) and metals
may be important indicators of sources
and causes of impairment to biological
assemblages in estuaries and coastal
marine waters. Decisions on which
chemicals to include in Tier 3
assessments can be difficult. Three
approaches to selecting contaminants
might be useful. One approach would
be to analyze for all chemicals listed on
USEPA's Priority Pollutant, Hazardous
Substance, or Target Compound/
Analyte Lists. A second approach
would be to analyze for the same
compounds targeted in the EMAP-
Estuaries program (refer to Table 3-1). A
third approach would be to develop a
targeted list. In this latter approach, the
historical information from Tier 0 and
subsequent follow-up inquiries of land
use in the suspect area could point to
common pesticides, herbicides, or
industrial products or byproducts that
could form the basis of a select list of
contaminants to analyze. Sources for
this information also include NPDES
permit records and discharger toxicity
test results. In any case, three replicate
water samples should be collected at
each sampling station within an
appropriate index period and on at least
three other visits during the year to
capture temporal variations in
contaminant concentrations. Historic
water contaminant data, plus data
collected in this tier, can be used by the
state to determine a more limited list of
analytes for subsequent years of the
assessment and biocriteria program.
The same type of sampling bottle used
to collect water samples for nutrient
analysis may be used for contaminant
samples. USEPA (1992) and APHA
(1992) contain detailed information on
analytical methods.
6.11 Acid Volatile Sulfides
(Tier 3)
Details of the purposes for measuring
acid volatile sulfides (AVS) present in
bottom sediments are provided in
Section 3.5.4. Given the diagnostic
intent of a Tier 3 assessment, it is
important to include this analyte in
determinations of bottom characteristics
only if metals are suspected as a cause of
biological degradation. Allen et al.
(1993) discuss analytical methods for
this parameter. AVS measurements
should be made on sediment samples
collected at each station during an
appropriate index period and any other
sampling visits made throughout the
year. Once the resource agency is
confident that an accurate
characterization of sediment AVS exists
for each station, the analytes should be
performed only once per year (on
samples collected in the index period).
6-8
Water Column & Bottom Characteristics
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6.12 Sediment Contaminants
As with water column contaminants,
three approaches to selecting analytes
could be used: (1) a full scan based on
USEPA's contaminant lists; (2) the
NOAA National Status and Trends suite
of contaminants used by the EMAP
program (refer to Table 3-1); or (3) a
targeted list.
In this latter approach, the historical
information from Tier 0 and subsequent
follow-up inquiries of land use in the
suspect area could point to common
pesticides, herbicides, or industrial
products and byproducts that could
form the basis of a select list of
contaminants to analyze. In addition to
sampling organisms for contaminants,
sediment samples should be collected
from the device used for sampling
benthic infauna. The surface sediment
(top 2-cm) should be removed from
replicate grab samples and composited.
During collection, care should be taken
to avoid collecting material from the
edge of grabs and to use only samples
that have undisturbed sediment
surfaces. The composite sample should
be homogenized, and a subsample taken
for measurement of contaminant
concentrations. Analytical methods are
discussed in APHA (1992) and USEPA
(1992).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 6-9
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Chapter 7
Tier 0: Desktop Screening
The breakdown of screening and
sampling in the following chapters that
focus on the Tiered Approach are just
one way of designing a state-wide
monitoring program. Agency analysis
of resources and program objectives
should direct the custom development
of any monitoring program.
The desktop screening assessment (or
Tier 0) consists of compiling
documented information for the estuary
or coastal marine areas of concern
through a literature search and sending
survey questionnaires to local experts.
No field observations are made at this
assessment level. Desktop screening
should precede any of the three
subsequent tiers. Its fundamental
purpose is to support the planning for
monitoring and more detailed
assessments. It incorporates time and
cost efficiencies, allowing evaluation of a
large number of sites, and identifying
potentially affected areas for further
investigation in higher tiers. Table 7-1
gives an overview of the components,
sources, and uses of a desktop screening
assessment.
7.1 Area and
Geomorphometric
Classification
The size and classification of the estuary
indicates the potential for the
environment to respond to various types
of impacts. In addition, the
classification refers to the type of
circulation (e.g., gravitational, tidal,
wind-induced) that dominates the
estuary. Well-recognized estuary types
include:
*• Coastal plain estuary;
*• Lagoon;
Table 7-1. Tier 0 Desktop screening for estuaries and coastal marine waters.
Component
Estuary area
Geomorphic
classification
Habitat type
Biological
assemblages
Watershed
land use
Population
density
NPDES
discharges
Water column
& bottom
characteristics
Information Source
USGS quad maps, CIS
USGS quad maps, CIS
NOAA bathymetry charts; historic surveys by federal,
state agencies, and universities
Historic data from federal, state agencies, and
universities. NMFS for marine mammal data
USGS land use maps; state and county planning
agencies; local zoning agencies; USDA CSREES
US census data
State water quality agency and regional USEPA offices,
PCS database
Historic data from federal, state agencies, and
universities; STORET, NODC databases
Use
-support planning
for monitoring
and more
detailed
assessments
-incorporates
time & cost
efficiencies
-allows evaluation
of a large number
of sites
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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*• Fjord;
*• Tectonically-caused estuary.
7.2 Habitat Type
Partitioning of the resource by habitat
type (open water, soft bottom substrates,
hard bottom substrates, aquatic
macrophytes, high/low energy beaches,
sandflat, mudflat, emergent marsh) will
usually be required and the extent of the
partitioning will depend on the size of
the system and environmental gradients.
Initial subdivisions should be based on
salinity gradients, water depth, and
sediment type, particularly in coastal
marine areas.
7.3 Watershed Land Use
The pollutant and sediment load of fresh
water inflow into the estuary will
inevitably have some form of impact on
habitat and biota and this land use
information may subsequently help
identify causes of impairment.
Nonpoint source pollution has been
shown to be a major contributor to the
degradation of our aquatic resources.
Land use information will help
determine the type of contaminants that
are being flushed into the estuary. For
example, storm water runoff from
urbanized and industrial areas may
contain various types of toxins. Runoff
from agricultural areas could be
expected to contain fertilizers,
pesticides, and sediment. Fertilizers
have the potential to accelerate
eutrophication by excessive nutrient
enrichment, while pesticides may have
at least short-term toxic effects.
7.4 Population Density
This indicates the potential for the
whole array of impacts to the estuary
and coastal marine waters from
concentrated human activity. The more
populated the area surrounding the
estuary or coastal region, the higher the
potential for human-induced impacts.
7.5 NPDES Discharges
Industrial and municipal point source
dischargers must file monthly discharge
monitoring reports (DMRs) that provide
the effluent concentrations for the
contaminants in the effluent which they
are required to monitor. This data is
accessible via USEPA's PCS. Knowing
the number, type and location of point
source dischargers could provide the
background information necessary for
characterizing the contaminants
entering the estuary and the regions
within the estuary or coastline that
would be most affected by the
discharge.
7.6 Biological Assemblages
Existing information on any of the target
biological assemblages (benthos, fish,
macrophytes, photoplankton,
zooplankton, epibenthos,
paleoenvironmental systems) can be
valuable for:
*• Identifying potential reference sites,
and potentially impaired areas;
*• Determining presence/absence of
major taxonomic groups and
indicator organisms;
*• Evaluating spatial and temporal
variability of the biological
assemblages.
This information can be used to help
determine target assemblages for
higher-level tiers and the sampling
design and methods that might be
appropriate.
7-2
Tier 0: Desktop Screening
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7.7 Water Column and
Bottom Characteristics
Existing data on water column and
bottom characteristics will be crucial to
support the identification of appropriate
sampling strata based on salinity, grain
size, or depth. Further, this information
can help states identify potentially
impaired areas; i.e., areas receiving high
nutrient loadings or containing
contaminated sediments.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 7-3
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Chapter 8
Tierl
The Tier 1 assessment is just one way of
completing a minimal biological
assessment or simple field screening.
Specific agency needs will ultimately
decide the components of any state
monitoring program. The time period of
sampling should be selected to allow
states to answer the question: "What
information do we want to obtain from a
single site visit?" For example, it could
be conducted from a single field visit
during late summer when low dissolved
oxygen concentration, due to
stratification and eutrophication, is most
likely to occur or during some other
chosen index period, depending on the
monitoring purpose. It builds on the
information compiled in the desktop
screening assessment and consists of
sampling one or more biological
assemblages and collecting data on
water column and bottom characteristics
(Chapters 5 and 6). Tier 1 might roughly
identify whether an estuary or coastal
marine waters are nutrient enriched and
can distinguish among broad probable
causes if the nutrient state is different
from expectations (reference conditions).
This assessment tier enables:
*• coarse identification of nutrient state
based on chlorophyll a
concentration, and identification of
point and nonpoint probable cause if
stations are carefully selected and
spaced;
*• detection of emergent wetlands and
shore zone fish habitat loss from
shore zone survey and macrophyte
assessment;
*• detection of loss of submerged
aquatic macrophytes;
*• detection of potential impairment of
benthic macroinvertebrate and fish
assemblages;
*• detection of oxygen stress.
The Tier 1 assessment will not allow
separation of multiple probable causes.
It can establish the initial habitat
classification scheme and identify
several possible causes of impairment,
including point sources, nearfield
nonpoint sources (in the immediate
shore zone of the coast or estuary), and
farfield nonpoint sources (from land use
in the drainage). It cannot, however,
identify the most probable from among
several possible causes. It should also
help establish the most likely sites to use
in developing the reference condition
and test their candidacy for this
preliminary phase of biocriteria
development. Table 8-1 gives an
overview of the components, data
collection methods, and indicators for
Tier 1.
8.1 Benthos
Sampling and analysis of benthic
infaunal macroinvertebrates in Tier 1 is
intended to provide a rapidly obtained
snapshot of the condition of the benthic
assemblage. It is recognized that this
assemblage, and the methods presented,
will be most appropriate for sites with
soft sediments (e.g., mud, silt, sand).
For sites with hard bottom substrates,
other biological assemblages (e.g., fish,
macrophytes, phytoplankton) could be
selected to provide information on the
biological condition of the target waters.
The sampling strategy presented here
consists of collecting replicate grab
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8-1
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Table 8-1. Tier 1 Assessment. Requires single field visit in spring or summer index period.
Component
Data Collection
Indicator of
Uses
Biological Assemblages
Benthic Infauna
-C
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*• Species Life Histories The presence of
relatively large and long-lived
species, especially those found
deeper in the sediments, indicate
higher quality habitat than does the
presence of small and short-lived
taxa;
*• Major Taxa Abundance High
abundance of only a few taxa,
usually pollution tolerant ones,
indicates a degraded environment;
*• Major Taxa Biomass Distribution
Larger organisms, hence a higher
biomass per individual, are more
prevalent in better quality habitats;
*• Vertical Distribution of Biomass
Organisms living below 5-cm in soft
substrates indicate a relatively high
quality habitat.
8.1.1 Sampling Procedure
The primary objective of benthic
infaunal macroinvertebrate sampling in
Tier 1 is to determine whether there are
any large organisms below the RPD
depth. The recommended sediment
sampling procedure involves collecting
three replicate grab samples at each
station using a Smith-Mclntyre or Young
grab. The selection of sampling gear
should be made to maximize
compatibility with historic data. For
example, the state of Texas uses an
Ekman grab, and has an approximately
25-year data record using this gear type.
The sediment sample is vertically
bisected using a sheet metal partition.
The RPD layer depth is noted and
measured, if present, as the distance
from the sediment surface to a
noticeable change in color from
brownish (oxidizing conditions) to gray
(reducing conditions). The sediment
above the RPD depth is removed and
wet-sieved separately; the remaining
portion of the sample is also wet-sieved.
A sieve with mesh size appropriate for
the region should be used. The presence
or absence of benthic inf auna in either
subsample is noted. If present, the
classes and families should be noted and
recorded.
8.1.2 Index Period
Benthic infaunal macroinvertebrates are
sampled once during an appropriate
index period, the timing of which is
driven by the goals of the Tier 1
assessment and regional considerations.
8.1.3 Analysis
Note the presence/ absence of an RPD
layer and any infauna (or evidence of
inf auna) below 5-cm depth in the
sample. If present, identify benthic
infauna to class and family and record
abundance.
8.2 Fish
A Tier 1 assessment of the fish
assemblage is intended to provide a
rapid evaluation of its presence and
overall composition. Fish sampling in
Tier 1 can include shallow-water,
pelagic, and demersal fish communities
(Carmichael et al. 1992, Eaton and
Dinnel 1994, Guillen 1995a).
8.2.1 Sampling Procedure
Various nets can be used to sample
littoral and sublittoral areas. It is
recommended that trap nets (gill or fyke
nets) be set and fished twice a day for 2-
to 5-days. Due to the risk of boating
mishaps and vandalism, it is
recommended that investigators stay
with the nets while they are being
fished. Fish sampling methods are
detailed in Klemm et al. (1992).
*• Gillnets are set in littoral areas at
right angles to the shore or to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
8-3
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longshore fish movement. Gillnets
usually extend into sublittoral areas.
Smaller mesh size (0.5") is used in
shallow areas and up to 2 to 2.5"
mesh is used further away from
shore. To reduce size selectivity, an
experimental gillnet consisting of
panels of five different mesh sizes is
commonly used;
> Trawl nets and sonar can be used to
sample pelagic and demersal areas.
The length of the towline (warp)
should be at least six times the depth
of water and a trawl speed of about
2-knots over a 0.5-nautical mile
distance is appropriate for coastal
marine waters. These values of
warp length and trawling distance
can be reduced in estuaries. A 20-ft
trawl (16-ft effective trawl mouth) is
appropriate in marine waters, but an
8- or 10-ft trawl is easier to tow in
restricted waters.
8.2.2 Sample Processing
Sampling duration and area or distance
sampled (from DGPS) are recorded in
order to determine sampling effort.
Species are identified and enumerated.
Fish should be carefully removed from
the net to avoid undue handling and
damage. The catch should be sorted by
species, and length measurements made
of each individual. This measurement is
usually total length, but fork length or
standard length can also be used. At the
time of measurement, any deformities,
ulcerations, bleeding, fin rot, bulging
eyes or other disease indicators should
be noted and those fish saved for
histopathology. It is important to
distinguish net damage from pre-
existing conditions, if possible. Wet
weights can be taken by species by
weighing the fish either individually
using a platform scale or collectively
from tared hanging scales, depending
on the number of fish caught. As a
small matter of convenience, both scales
should weigh in metric units. Those
animals not saved for further
examination should be promptly
returned to the water.
The investigator should consult with
State and University fish pathologists of
the region for those most appropriate
sample preparation and preservation
techniques. Usually iced or frozen
specimens are inappropriate and in
some cases formaldehyde or other tissue
preservatives must be carefully used if
meaningful samples are to be presented.
Generally, small fish can be tagged and
placed whole in 10% formalin. Larger
fish will require dissection in the field
and the tissue samples tagged and
preserved in the same manner.
Protocols for preservation and dissection
should be obtained from the
laboratory/fish pathologist that will
receive the samples.
When collected, reference specimens of
each species from each site are
preserved in 10% formalin in a labeled
jar and retained by the state
ichthyological museum or other
designated repository to constitute a
biological record. This is especially
important for uncommon species, for
species requiring laboratory
identification, and for documenting new
distribution records. Later, all
specimens should be transferred from
formalin to 70% alcohol for long-term
storage.
8.3 Macrophytes
Areal coverage and distribution of
submerged aquatic macrophytes is
estimated from aerial photographs, if
available, and ground-truthed at the site.
The dominant taxa may be field-
identified from vegetation samples
collected in shallow waters. Detailed
8-4
Tier 1
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macrophyte monitoring and assessment
procedures are included in USEPA
(1992), Ferguson and Wood (1994), and
Orth et al. (1993).
8.4 Phytoplankton
Phytoplankton standing stock is
estimated by chlorophyll a
measurements. A sample is collected at
each station at one-half the Secchi depth
using a Kemmerer or Van Dorn sampler.
Chlorophyll a is determined using a
fluorometer or spectrophotometer as
discussed in APHA (1992). The
presence of any phytoplankton blooms
observed during the cruise should be
noted. Dominant phytoplankton species
should be identified.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 8-5
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Chapter 9
Tier 2
Tier 2 assessment is considered a routine
biological survey that incorporates two
or more field visits per year to capture
variations due to seasonal differences.
Tier 2 comprises increased sampling
effort and additional assemblages
compared to Tier 1. It includes two or
more biological assemblages (benthos,
fish, macrophytes, phytoplankton, or
epibenthos), in 2 or more visits per year,
in addition to more detailed
characterization of the water column
and bottom (Chapter 5). State agencies
can modify this schedule to
accommodate their program objectives.
This level is sufficient for identification
of appropriate habitat classes and
determination of the reference condition
for development of biological criteria.
Data collected in Tier 2, which
incorporates both Tier 1 and Tier 0,
should permit the state to confidently
develop biocriteria and apply them to
identify problem areas. This assessment
level enables:
*• Establishment of the biocriteria
"benchmarks" for decision-making
about impaired areas; including
identification of priorities;
*• Identification of trophic state based
on chlorophyll a and water column
nutrient measurements;
*• Detection of impairment of benthic
macroinvertebrate, fish, or
epibenthos assemblages, and
evaluation of potential causes of the
impairment;
*• Measurement of extent of
macrophyte coverage;
*• Identification of phytoplankton taxa
responsible for blooms.
A Tier 2 assessment should allow
identification of multiple probable
causes of impairment, given an adequate
number and placement of sampling
stations. This includes point sources,
and nearfield and farfield nonpoint
sources. Preliminary management plans
in response to the biocriteria
information can be developed. Table 9-1
gives an overview of the components,
data collection, methods, and indicators
for Tier 2.
9.1 Benthos
Sampling and analysis of benthic
inf auna in Tier 2 is intended to provide a
level of assessment consistent with
routine benthic macroinvertebrate
surveys presently conducted by states in
estuaries and coastal marine waters. As
with Tier 1, this assemblage, and the
methods presented, will be most
appropriate for soft sediments. For sites
with hard bottom substrates, other
biological assemblages (e.g., fish,
macrophytes, phytoplankton) could be
selected to provide information on the
biological condition of the target waters.
The sampling strategy for Tier 2 entails a
minimum of two field collection visits,
one of which should occur within the
chosen index period. Organisms are
identified to genus and species to
determine major taxa and the presence
of indicator organisms. Water column
and bottom characteristics are also
measured to evaluate the status of
physicochemical conditions.
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Table 9-1. Tier 2 Assessment. Requires two or more field visits, one of which should occur within
chosen index period. In addition to requirements from Tiers 0 & 1.
Component
Data Collection
Indicator of
Uses
Biological Assemblages
Benthic
Infauna
-C
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or black (reducing conditions). The
sample should be wet sieved through a
sieve mesh size determined to be
appropriate for the region (Section 6.3.2).
For cost and effort savings, an
appropriate diameter subcore (2.5- or 5-
cm) can be taken from each of the four
quadrants of the intact core. These
subcores should be compared to
organism counts taken from full cores to
establish the baseline relationship
between the two. Organisms and
sediment fractions should be placed in
tagged and labeled sample jars with a
10% solution of magnesium chloride or
magnesium sulfate to narcotize the
animals. After at least 30-minutes,
concentrated formaldehyde with rose
bengal dye can be added to the jars to
make a 10% solution of formaldehyde
by volume. The sediment/organism
material should never exceed half the
container volume to ensure adequate
mixing and fixation of the sample. For
preservation, the samples should be
transferred to 70% ethanol (APHA
1992).
9.1.2 Index Period
Benthic infaunal macroinvertebrates are
sampled once during an appropriate
index period, the timing of which is
driven by the goals of the Tier 2
assessment and regional considerations.
At least one other sampling visit is made
outside the index period to capture basic
seasonal differences in the assemblages.
The timing of this visit(s) will depend on
the specific goals of the assessment.
9.1.3 Analysis
Organisms in each sample are identified
to genus and species. Metrics selected
by the state can then be calculated to
assess the condition of the assemblage.
Metric values can then be used to help
develop biocriteria against which the
condition of the macroinvertebrate
assemblage is evaluated.
9.2 Fish
Tier 2 assessment of the fish assemblage
is intended to provide data sufficient to
evaluate impairment and to develop
biocriteria. Fish sampling in Tier 2 can
include shallow water, pelagic, and
demersal fish communities (Carmichael
et al. 1992, Eaton and Dinnell 1994,
Guillen 1994).
9.2.1 Sampling Procedure
See Section 8.2.1 for full procedure on
sampling fish.
9.2.2 Sample Processing
See Section 8.2.2 for full procedure on
sample processing.
9.2.3 Analysis
Based on the enumerated species list,
metrics selected by the state can be
calculated to evaluate potential
impairment to the fish assemblage and
to develop biocriteria for this
assemblage.
9.3 Macrophytes
Tier 2 assessment of macrophytes is
intended to provide sufficient data to
assess impairment to the macrophyte
assemblage as a significant habitat
variable and potential element of
biocriteria. Because of its importance as
habitat for other assemblages,
procedures for Tier 2 assessment of
macrophytes are considerably more
involved than for Tier 1.
9.3.1 Sampling Procedure
The extent of coverage and distribution
of macrophytes should be determined
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
9-3
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from aerial photographs. Existing aerial
photographs are inexpensive; however,
they may not be sufficiently recent to
depict present macrophyte distribution
in the water body. If new aerial
photographs are determined to be
needed, states should recognize that
overflights can be expensive and
complicated; often requiring assistance
from firms specializing in aerial
photography. Factors to consider when
planning new overflights include: tidal
stage; weather conditions; time of day;
and water turbidity (USEPA 1992).
Ferguson and Wood (1994) and Orth et
al. (1993) describe details of planning
aerial overflights, obtaining imagery,
photointerpretation, and preparation of
macrophyte distribution maps.
A key aspect of interpreting aerial
photographs is the performance of
ground surveys that serve to confirm the
existence of macrophyte beds identified
in the photographs, as well as beds that
may not be visible in the photos (Orth et
al. 1993). Transects can be plotted across
macrophyte beds in the various salinity
zones within an estuary or within the
sampling strata used for marine waters.
At each station on the transect a 1-m2
quadrat can be used for the purpose of
measuring percent cover and collecting
macrophyte samples for taxonomic
identification and measurement of wet
weight (USEPA 1992). Depth at the
channel-ward or seaward edge of
macrophyte extent should be recorded.
9.3.2 Index Period
Aquatic macrophytes should be
sampled once during an appropriate
index period, preferably during the time
of year when they would be expected to
be most dense and extensive. Other
sampling periods should be selected
based on the specific goals of the Tier 2
assessment, perhaps to measure
seasonal periods of stress or
diminishment of important nursery or
food areas.
9.3.3 Analysis
Percent cover and area may be derived
from analysis of aerial photographs.
The maximum depth of occurrence is a
good indicator of water quality.
Taxonomic identification from the field
trips will allow development of a species
list.
9.4 Phytoplankton
9.4.1 Sampling Procedure
Phytoplankton standing stock is
estimated by chlorophyll a
measurements. One approach might be
three replicate samples collected at each
station at one-half the Secchi depth
using a Kemmerer or Van Dorn sampler.
Another approach would collect a
depth-integrated sample through the
entire photic portion of the water
column. Chlorophyll a is determined
using a fluorometer or
spectrophotometer as discussed in
APHA (1992). The presence of any
phytoplankton blooms should be noted.
In addition to chlorophyll a
measurements, samples from each
station should be preserved for
subsequent analysis to identify the
dominant taxa and those taxa that might
be responsible for observed blooms
(USEPA 1992).
9.4.2 Index Period
Phytoplankton populations can vary
rapidly over space in response to tides
and currents, and over time in response
to ambient temperature and nutrient
inputs. For Tier 2, phytoplankton
should be sampled at least once during
an index period (usually summer) and at
least once outside that index period.
9-4
Tier 2
-------
9.4.3 Analysis
Chlorophyll a measurements can be
used to estimate phytoplankton
standing stock. Assuming that
chlorophyll a is about 1.5% of the ash-
free dry weight of algae, algae biomass
can be estimated by multiplying the
chlorophyll a content by a factor of 67
(APHA1992). This information can be
used in concert with the identification of
dominant taxa and "nuisance" taxa to
assess the overall condition of the
phytoplankton assemblage.
9.5 Epibenthos
(Developmental)
Although its use as an indicator of
estuarine and coastal marine biological
condition is considered to be under
development, epibenthos could be
selected as one of the biological
assemblages for a Tier 2 assessment and
has potential as an element of biological
criteria consistent with fish and benthic
invertebrates.
9.5.1 Sampling Procedure
Farrell (1993a, b) describes the use of a
beam trawl to collect epibenthos. A
beam trawl is a conical-shaped net, open
at the large end, which is towed over the
substrate surface. The net is kept open
by attaching each end of it to a rigid pole
or beam. This beam replaces the doors
of an otter trawl and forward movement
of the boat is not required to keep the
net open. The net is constructed in two
parts. The body is nylon bolting cloth
(50 openings/cm2), tapering to a
plankton net fitted with a removable
container. An effective swath width of
1.25-m has been tested in Florida waters
(Farrell 1993a, b). In wadeable water, a
D-frame net could be used to collect
epibenthos, or the beam trawl could be
pulled by hand. A relatively short tow
length of the beam trawl (4-m,
effectively sampling 5-m2 of bottom) in
estuaries may be beneficial for reducing
the sample size and detrital bulk. If a D-
frame net is used, at least an equivalent
area should be sampled. In offshore
waters, it may be necessary to increase
the tow length due to reduced organism
densities. Small otter trawls or an
epibenthic sled sampler can also be
used.
9.5.2 Index Period
Epibenthos should be sampled once,
preferably during an appropriate index
period. For many temperate areas of the
country, this is probably mid-summer.
Other sampling periods should be
selected based on the specific goal of the
Tier 2 assessment.
9.5.3 Analysis
The samples should be identified to
genus and species. The Farrell Index
(described in Chapter 13 - Case Studies,
as modified to reflect tolerance values of
taxa in the area sampled) should be
calculated to provide an assessment of
the condition of the assemblage in
response to organic pollutants and
eutrophication. Other metrics could be
calculated based on the specific taxa
present.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
9-5
-------
-------
Chapter 10
TierS
Tier 3 is the most rigorous of the
assessment tiers. It includes more
detailed assessment procedures that
allow monitoring agencies to focus on
specific water and sediment quality
problems in estuarine or coastal marine
waters. Tier 3 is intended to provide
definitive information needed to act on
biocriteria and to measure potential
success or failure of the management
effort. It allows states to conduct a
detailed diagnosis of the sources and
causes of impairment to biological
assemblages and the physicochemical
environment and to monitor their
response to subsequent mitigation
actions. However, the Tier 3 approach
can be customized to accommodate
specific state program objectives. Table
10-1 gives an overview of the
components, data collection methods,
and indicators for Tier 3.
Tier 3 assessments include multiple
sampling visits per year (four or more)
that occur within each season including
the index period. Data collected in Tier
3, which includes information compiled
in Tier 0 desktop screening and
comprises the information collected in
Tiers 1 and 2, involves sampling and
measurement of three or more biological
assemblages (benthos, fish macrophytes,
phytoplankton, zooplankton, or
epibenthos), in addition to more detailed
characterization of the water column
and bottom. A Tier 3 assessment
enables:
*• Identification of nutrient state based
on chlorophyll a and water column
nutrient measurements;
*• Detection of impairment of benthos,
fish, macrophytes, phytoplankton,
zooplankton, epibenthos, or
paleoenvironmental systems;
*• Diagnosis of specific sources and
causes of impairment;
*• Measurement of extent of
macrophyte coverage;
*• Identification of phytoplankton taxa
responsible for blooms;
> Evaluation of seasonal dynamics of
biological assemblages;
*• Detailed monitoring of sites
requiring management initiatives to
meet the biocriteria;
*• Inferences of past conditions as a
site-specific reference.
10.1 Benthos
Sampling and analysis of benthic
infaunal macroinvertebrates in Tier 3 is
intended to provide a diagnostic level of
assessment. This assemblage, and the
methods presented, will be most
appropriate for soft sediment. For sites
with hard bottom substrates, other
biological assemblages (e.g., fish,
macrophytes, phytoplankton,
zooplankton) could be selected to
provide information on the biological
condition of the target waters.
The sampling strategy for Tier 3 entails a
minimum of four field collection visits
per year, one of which should occur
within the chosen index period. The
remaining visits should occur
throughout the year to allow evaluation
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
10-1
-------
Table 10-1. Tier 3 Assessment. Requires four or more field visits, one of which should occur within the
chosen index period. In addition to requirements from Tiers 0-2.
Component
Data Collection
Indicator of
Uses
Biological Assemblages
o ro
il
,
.c
Q.
O
O
ro
2
Phytoplankton
Paleoenvironmental
Systems (developmental)
Epibenthos
(developmental)
Zooplankton
(developmental)
*determine biomass
"calculate multiple
metrics
*5 or more replicates
*histopathology on
representative
subsample of catch
*stem counts
*biomass
*record pathology
*full community
characterization to
species
*2 or 3 cores from
basin (one-time
sample)
See Tier 2
"identify to species
Fishing
pressure,
disease
Toxicity, habitat
impairment,
disease
Past conditions
Water quality
impairment, DO
stress
-Identification of nutrient state
based on chlorophyll a & water
column nutrient measurements
-Detection of impairment of
benthos, fish, macrophytes,
phytoplankton, Zooplankton,
epibenthos, or paleoenvironmental
systems
-Diagnosis of specific sources &
causes of impairment
-Measurement of extent of
macrophyte coverage
-Identification of phytoplankton
taxa responsible for blooms
-Evaluation of seasonal dynamics
of biological assemblages
-Detailed monitoring of sites
requiring management initiatives
to meet the biocriteria
-Integrate conditions over broad
spatial scales
Water Column Characteristics
"pesticides, herbicides
*metals
pesticides/
herbicides,
metals
Bottom Characteristics
*AVS
*sediment
contaminants
(organics, metals)
10-2
Tier 3
-------
of seasonal differences in the benthic
macroinvertebrate assemblages.
Organisms are identified to genus and
species. Water column and bottom
characteristics are also measured to
evaluate the status of physicochemical
conditions.
10.1.1 Sampling Procedure
Primary objectives of Tier 3 benthic
infaunal sampling are to evaluate
potential impairment to this
assemblage, to develop and refine
biocriteria, to diagnose causes and
sources of observed impairment, and
to evaluate seasonal changes in the
benthic infauna. This tier includes
more frequent sampling (a minimum
of four times per year) than either
Tiers 1 or 2 to allow detailed
discrimination of seasonality of
benthic abundance. See Section 8.1.1
for full detail on sampling procedures.
10.1.2 Index Period
Benthic infaunal macroinvertebrates
are sampled once or twice during an
appropriate index period, the timing
of which is driven by the goals of the
Tier 3 assessment and regional
considerations. At least two or three
other sampling visits are made
throughout the remaining portion of
the year to capture more detailed
seasonal differences in benthos than
would be possible in a Tier 2
assessment. Data collected in a
previous Tier 2 assessment, or historic
benthic infaunal macroinvertebrate
data, can be used to determine the
timing and frequency of non-index
period sampling.
10.1.3 Analysis
Organisms in each sample are
identified to genus and species. If
desired, and resources are available,
ash-free dry weight, at least to the
family level, may be measured to
determine the viability of biomass-
based metrics to the overall
assessment. Other metrics should be
selected by the resource management
agency as appropriate based on
historic data, data collected and
metrics used in preceding tiers, and
regional considerations.
10.2 Fish
Tier 3 assessment of the fish
assemblage is intended to allow
evaluation of impairment, to develop
and refine biocriteria, to diagnose
causes and sources of impairment,
and to evaluate seasonal differences in
the assemblage. Fish sampling in this
tier can include shallow-water,
pelagic, and demersal fish
communities (Carmichael et al. 1992,
Eaton and Dinnell 1994, GuiUen 1994).
10.2.1 Sampling Procedure
See Section 8.2.1 for full description of
fish sampling procedures.
10.2.2 Sample Processing
See Section 8.2.2 for full description of
fish sample processing.
10.2.3 Analysis
Based on the enumerated species list,
metrics selected by the state can be
calculated to evaluate potential
impairment to the fish assemblage, to
develop or refine biocriteria, to
examine seasonal dynamics of the
assemblage, or to diagnose sources
and causes of impairment.
10.3 Macrophytes
Tier 3 assessment of macrophytes is
intended to provide sufficient data to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
10-3
-------
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.
10-4
Tier 3
-------
10.6.1 Sampling Procedure
Three replicate vertical tows using a
118-|_im mesh net, 30-cm in diameter
should be made at each sampling
location. The tow should be vertically
integrated; that is, starting from 0.5-m
from the bottom to the surface, with a
retrieval rate of 0.5- to 1-ms"1.
Collected organisms should be
anesthetized with carbonated water
and preserved in 4% formalin. For
long-term storage after fixing,
specimens should be transferred to
70% ethanol. APHA (1992) describes
procedures for concentrating the
samples and preparing them for
examination.
10.6.2 Index Period
Zooplankton should be sampled once
during an appropriate index period
and a minimum of three other times
during the year to capture seasonal
variation in taxonomic composition
and abundance.
10.6.3 Analysis
Samples should be identified to the
lowest practical taxonomic level,
preferably genus and species.
Subsampling may be required to
achieve reasonable numbers of
organisms for identification.
10.7 Paleoenvironmental
Systems
(Developmental)
Developmental assessment of
paleoenvironmental systems is
intended to provide site-specific
reference by showing past conditions.
Several groups of organisms leave
remains in the bottom sediments.
Some of the remains are resistant to
decay and become a permanent
biological record of life in the estuary.
By comparing past biota with present-
day biota, past environmental
conditions can be inferred. Several
groups of organisms have been used:
diatoms, foraminifera, and
dinoflagellate cysts. Of these, diatom
frustules and foraminifera have been
used most often, and most
successfully, to infer past conditions.
A sample of the top 1- to 2-cm of
sediment contains a representative
sample of diatoms from the most
recent 1- to 5-years. If the sediments
remain undisturbed, then remains
preserved in the sediments are
integrators of estuarine history
(Charles et al. 1994, Dixit et al. 1992).
Because of the developmental nature
of this indicator, states or agencies
wishing to use paleoenvironmental
reconstruction should contact one of
the laboratories engaged in this
research for further information. The
methods described here are intended
to give a brief overview of the field,
but should not be used to plan a
monitoring program.
10.7.1 Sampling Procedure
Cores are generally taken with
standard gravity corers, such as the K-
B, Phleger, or Piston. The chosen
corer should retrieve a core deep
enough to sample sediments from the
earliest desired time period, with
minimal edge disturbance. Core
length thus depends on time period
and sedimentation rate. Core samples
are extruded from the corer and
subsectioned immediately after
collection. Sections 1-cm thick are
removed from the core at intervals
according to the time resolution
desired. These sections are removed
from the core using an apparatus
described by Glew (1988) then are
bagged, labeled and identified using a
permanent ink pen. The bags
prepared from a single core sample
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
10-5
-------
are placed in a sealed container for
storage and transport. Samples are
kept at 4°C until shipment.
10.7.2 Sample Processing
Once in the laboratory, the sections
are dried and weighed. Foraminifera
and diatoms are processed so as to
digest organic matter and preserve
carbonate (foraminifera) or silica
(diatoms), following the standard
methods of Krom and Berner (1983)
andEMAP(USEPA1994e). An
aliquot of frustules or tests is mounted
for optical and/or scanning electron
microscopy for identification.
Dinoflagellate cysts are subjected to a
standard pollen analysis involving the
digestion of minerals in cold HC1,
followed by warm HF (adapted from
Barss and Williams 1973). They are
processed on a 10 |_im sieve. Samples
for counting and identification are not
random, but systematic.
Transects are taken on microscope
slides, counting and identifying all
target taxa encountered. A count of
300 or more is necessary for
meaningful analysis of percentage
data, but lower counts are still valid if
results are reported on a concentration
basis. In some depositional systems it
is not feasible to count 300
dinoflagellate cysts, but the data is
still informative.
Charcoal is seen in pollen analysis and
dinoflagellate cyst preparations. The
larger sieve size used for foraminifera
would exclude most charcoal
particles, thus make this material
unsuitable for charcoal studies.
10.7.3 Analysis
Standard dating methods use either
carbon-14, pollen, 137Cs, or 210Pb (Dixit
1992, Cooper and Brush 1991, Dale et
al. 1999, Alve 1991). Additional time
points can be established from traces
of known historic events (charcoal
from large-scale fires, radioisotopes
from atmospheric testing and the
Chernobyl accident). Known
responses of indicator taxa or
biogeochemical indicators (e.g.,
biogenic silica) are used to infer past
environmental conditions of an
estuary. This allows for the
assessment of current environmental
conditions based on those of the past.
Quantitative paleoenvironmental
reconstruction in estuaries requires
the development of a data set that
associates current conditions with
current surficial diatom,
dinoflagellate, or foraminifera
assemblages. Present-day associations
are used to infer past conditions based
on fossil assemblages in deeper
sediment layers. Quantitative
prediction is usually done in two
steps: development of predictive
models (calibration or transfer
functions), followed by use of the
models to infer environmental
variables from fossil assemblages
(Charles and Smol 1994). Quantitative
reconstruction has not yet been widely
developed for estuaries.
10-6
Tier 3
-------
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,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-1
-------
phytoplankton, zooplankton or
macrophytes;
*• The examples used to illustrate the
methods have been carried out over
wide geographic areas with many
sites, demonstrating the generality of
the methods;
*• The examples used to illustrate the
methods are concise, the methods
were fully documented, and have
been carried to completion, that is,
assessment of biological impairment
and non-impairment.
All three of the methods use the same
general approach: sites are assessed by
comparing the assemblage of organisms
found at a site to an expectation derived
from observations of many relatively
undisturbed reference sites. The
expectations are modified by classifying
the reference sites to account for natural
variability, and each assessment site is
classified using non-biological (physical,
chemical, geographic) information.
Finally, metrics (methods 1 and 2) or the
species ordination (method 3) are tested
for response to stressors by comparison
of reference and known impaired sites.
An example of the assessment process is
summarized in Figure 11-1.
This chapter will first discuss methods
of classification, with emphasis on those
that have been successful in estuaries
and coastal waters. The remainder of
the chapter then discusses the three
assessment methods. This chapter is not
intended to be an instruction manual on
using the different statistical methods; it
is intended to show, with selected
examples, techniques that have been
used to develop biological indexes.
Details of applications and methodology
can be found in the cited documents and
articles and in statistical textbooks and
manuals (e.g., Ludwig and Reynolds
1988, Reckhow and Warren-Hicks 1996).
11.2 Classification and
Characterization of
Reference Condition
The objective of characterization is to
finalize the classification of reference
sites and to describe (characterize) each
of the reference classes in terms of
metrics, assemblage composition, and
physical-chemical variables. As
outlined in Chapter 4, classification may
be a physical rule-based classification,
or an analytical data interpretation
where rules are derived from the data.
The analytical approach requires a
relatively large reference data set to
derive the classes and rules, with many
sites and both biological and
physical-chemical data from each site.
The basic assumption of classification is
that biogeography, physical habitat, and
water quality largely determine
attributes such as taxa richness,
abundance, and species dominance in
estuarine and coastal marine biological
communities. In other words, if
habitats are classified adequately,
reference biological communities should
correspond to the habitat classification.
Several statistical tools can assist in site
classification, but there is no one set
procedure. If the rule-based
classification is based on well-
developed prior knowledge and
professional judgment, graphical
analysis of metrics, followed by any
necessary modifications and tests of the
resultant classification, it is usually
sufficient. If necessary, the classification
is refined until an optimal classification
emerges that satisfactorily accounts for
variation in reference site biological
data.
If a physical classification is not self-
evident, it may be necessary to develop
an alternative classification from the
data using one or more of several
11-2
Index Development
-------
1. V\atertadyQasafication—The
physical and habitat data along with
bidogcal data are used ID gioup
reference sites into homogeneous
dasses
2 MstacIdentification—Those
metrics or attri butes that are
ecologically relevant to asserrdage
and zoogeography are identified
3. Fvfetric Calibration—Gore metrics
are sensitive to pollution and are
informative of the ecological
relationships of the asserrdage to
specific stressors or cumJative
irrpacts
4. I noex Development—Core
(retries, whose values vary in scale,
are transforrred to drrensionless
numbers for aggregation
5. Threshold Establishment—The
threshold (bocriterion) for
dscnrri rating between impaired and
urirrpaired isdeterrrined to pnovide
a basis for assessment
Figure 11-1
The process for
progressing from
the classification
of an estuary to
assessing the
health of the
estuary. Adapted
from Paulsen et al.
1991.
classification methods. These methods
include cluster analysis and several
ordination methods such as: principal
components analysis, correspondence
analysis, and multidimensional scaling.
11.2.1 Existing Classifications
With the growth of efforts to improve
environmental monitoring and develop
biocriteria, several successful
classifications of estuarine and near-
coastal biological assemblages have been
developed. Here, we summarize several
of these and integrate their findings on
classification of North American
estuarine assemblages.
EMAP Virginian Province
Natural environmental factors affecting
species composition were examined in
the EMAP Virginian Province Project
(Paul et al. 1999, Strobel et al. 1995,
Weisberg et al. 1993). Salinity has been
known to control estuarine organisms
since the early days of marine biology.
Over 75% of the candidate measures
were related significantly to salinity
distributions (Figure 11-2). Correlation
analysis was used to examine
associations of habitat factors with
candidate biological metrics. Of the
correlations between candidate
measures and habitat factors,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-3
-------
Figure 11-2
Mean number
of species and
salinity at
EMAP-
Estuaries
sampling
stations in the
Virginian
Province (from
Weisberg et al.
1993). The
regression line
shown is the
expected
number of
species based
on the
polynomial
regression,
and was used
to estimate
salinity-
adjusted
species
richness
measures.
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0 5 10 15 20 26 30 35
(ppt)
species richness was most strongly
correlated with salinity.
In addition to salinity, the physical
characteristics of estuarine sediments
and depth also influence benthic
infaunal distribution and the
accumulation of contaminants in
sediments (Rhoads 1974, Plumb 1981).
EMAP collected sediment grain size,
silt-clay content, latitude, and depth
data to help interpret benthic response.
Although silt-clay content and depth
were statistically significant, only
salinity was deemed to have a
biologically significant influence on
benthic macroinvertebrates (r2 >0.025;
Weisberg et al. 1993). Estuary type was
stratified in the project design, but
community differences due to estuary
type were not reported.
Chesapeake Bay
Weisberg et al. (1997) developed an
estuarine benthic index of biotic
integrity for the Chesapeake Bay.
Cluster analysis of benthic infauna
indicated seven distinct habitats defined
by substrate and salinity. Polyhaline
sand and mud, (salinities (>18 %o) had
the highest mean Shannon-Wiener
diversities, at 4.0 and 3.55, respectively
(Weisberg etal. 1997).
EMAP Carolinian Province
From July - September 1995, a study
was conducted to assess the
environmental condition of estuaries in
the EMAP Carolinian Province (Hyland
et al. 1998, see Chapter 13). The
program sampled water depth, salinity,
and substrate classifications (% silt-clay)
as habitat indicators.
Species richness showed highly
significant correlations with latitude,
bottom salinity, and silt-clay/TOC
sediment content. The Shannon-Wiener
index, H' (a combination of species
richness and evenness), also showed
highly significant correlations (p <
0.0030) with bottom salinity as well as
11-4
Index Development
-------
with silt-clay fractions. As with
diversity, infaunal abundance showed
highly significant correlations (p <
0.0016) with the silt-clay and TOC
sediment content (Hyland et al. 1998).
North Carolina
The North Carolina study was designed
to compare biological metrics derived
from three sampling methods (Ponar,
epibenthic trawl, and sweep net).
Salinity was the only habitat
characteristic that was significantly
correlated with biological metrics. Total
taxa showed a positive correlation with
salinity (Eaton 1994a; see Chapter 13).
Puget Sound
The objective of the Puget Sound study
was to characterize benthic
macroinvertebrate communities into
habitats classified as degraded and
habitats that are relatively unimpaired,
which can then be classified as reference
sites for the Sound (Llanso 1999).
The diverse assemblages sampled were
mainly associated with sediment type
and water depth, reinforcing results
from previous studies (Lie 1974). The
classes of sediments defined for the
Puget Sound estuaries were: sands,
clays, and mixed. These three classes
did not have exact boundaries, but
instead overlapped at both ends of their
spectrums (Llanso 1999). Stations with
finer substrates had fewer species than
those with coarser substrates. On
average, sand substrates supported
more species and abundance than did
clay, with deep sites having the lowest
abundance levels. Overall, clay stations
in the southern part of Puget Sound
supported fewer species than many
other shallow clay locations. The
majority of species were not restricted to
only one substrate, instead they were
widely distributed in different types of
sediment showing the most abundance
in sand, mixed sediment, or muddy
bottoms.
EMAP Louisianian Province
Prior studies in the Gulf of Mexico had
shown salinity and sediment type to be
among the most important factors that
determine benthic infaunal
relationships in Gulf of Mexico estuaries
(Flint and Kalke 1985, Gaston et al. 1988,
Rabalais 1990, Rakocinski et al. 1991).
Of the 182 total sites sampled, Pearson
correlations were performed between all
candidate measures and salinity,
longitude of sampling site (as a measure
of geographical gradient), percent silt-
clay, and total organic carbon content of
sediments. Many of the correlations
were statistically significant atp < 0.05,
however, only salinity accounted for
20% or more of the variation (Summers
et al. 1993).
Southern California Eight
The Southern California Coastal Water
Research Project sampled megabenthic
invertebrate assemblages, benthic
infaunal assemblages, and demersal fish
assemblages to determine their
relationship to depth, latitude, and
sediment types in the Southern
California Bight. There was no salinity
gradient because the entire study area
was nearshore marine. Overall, depth
was found to be the defining factor in
the organization of each assemblage
(Allen et al. 1999, Bergen et al. 1999).
Sediment type was found to be a
secondary factor in the organization of
benthic infaunal assemblages. This
finding could be attributed to the large
study area. In fact, within a constrained
depth range, sediment type may be a
more important factor (Bergen et al.
1999). These findings are consistent
with those of Snelgrove and Butman
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-5
-------
(1994) which suggested that the
hydrodynamic environment and the
amount of organic material in the
sediment are more likely to be primary
driving forces, with depth and sediment
grain size as secondary correlates.
Conclusions
Three habitat indicators have been
demonstrated repeatedly to influence
biological assemblages of estuaries and
near coastal environments. In studies
where there was a salinity gradient,
salinity was found to be the most
important habitat indicator. Depth and
substrate are also important and usually
correlated, especially if there is a large
depth gradient at the sample site. The
physical type of estuary (e.g., fjord,
lagoon, tidal river) has not been
demonstrated to be vital in wide
geographic studies, such as those
conducted by EMAP in the Virginian,
Louisianian, and Carolinian provinces,
but may not have been adequately
tested. Therefore, the importance of
measuring estuary type, subregion, or
subprovinces is still questionable.
Lessons learned from both EMAP and
other independent studies conclude that
the basic classification of an index
should be by biogeograpical province,
salinity, substrate (silt-clay content,
sediment grain size), and depth. The
effects of salinity, substrate, and depth
should be tested within the study area to
determine whether all are required as
habitat indicators in an individual area.
Moreover, decisions need to be made as
to the use of discrete classes or
continuous covariates in statistical
analysis. If other classifications are
suspected to be important indicators of
the health of a system, they should also
be tested (e.g., estuary type).
11.2.2 Assessing a priori
Classifications
Although there is no serious doubt over
the influence of salinity, sediment, and
depth on estuarine biota, the effects
must be characterized or calibrated to
establish reference conditions. Several
approaches have been used, as outlined
in the examples in this chapter. Often,
one of the first steps is a cluster analysis
of the species composition of the sites to
determine if sites can be broken down
into groups (e.g., Weisberg et al. 1997,
Smith et al. 2000). Sites maybe divided
into groups defined by the important
variables (e.g., salinity and sediment;
Weisberg et al. 1997, depth; Smith et al.
1999), or the groups may be separated
by discriminant function analysis (DFA)
if simple, single relationships are not
sufficient (e.g., Engle and Summers
1999).
Another approach is to examine
correlations between environmental
variables and biological metrics
calculated from the species data, so that
reference expectations can be calibrated
accordingly. For example, species
richness in estuaries is strongly affected
by salinity (refer to Figure 11-2).
Weisberg et al. (1993) used the
relationships of Figure 11-2 to develop a
nonlinear regression of maximum
expected species richness on salinity.
Species richness was then adjusted by
the salinity-specific maximum in further
development of their model of
impairment.
11.3 Index Development
An index for assessing sites can be
developed after classification of sites of
the region is completed. Index
development using the three
approaches followed in this chapter is
discussed here.
11-6
Index Development
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11.3.1 Multimetric Index
Step 1. Identify Potential Measures For
Each Assemblage.
Metrics allow the investigator to use
meaningful indicator attributes in
assessing the status of assemblages and
communities in response to
perturbation. The definition of a metric
is a characteristic of the biota that
changes in some predictable way with
increased human influence (Barbour et
al. 1995). For a metric to be useful, it
must have the following technical
attributes: (1) ecological relevance to the
biological assemblage or community
under study and to the specified
program objectives, (2) sensitivity to
stressors and provide a response that
can be discriminated from natural
variation. The purpose of using
multiple metrics to assess biological
condition is to aggregate and convey the
information available regarding the
elements and processes of aquatic
communities.
All metrics that have ecological
relevance to the assemblage under study
and that respond to the targeted
stressors are potential metrics for
testing. From this "universe" of metrics,
some will be eliminated because of
insufficient data or because the range of
values is not sufficient for
discrimination between natural
variability and anthropogenic effects.
This step is taken to identify the
candidate metrics that are most
informative, and therefore, warrant
further analysis.
Representative metrics should be
selected from each of four primary
categories: (1) richness measures for
diversity or variety of the assemblage;
(2) composition measures for identity
and dominance; (3) tolerance measures
that represent sensitivity to
perturbation; and (4) trophic or habit
measures for information on feeding
strategies and guilds. Table 11-1 further
illustrates metrics for various
assemblages that have been useful in
estuaries. Components of Step 1
include:
> Review of the value ranges of
potential metrics, and elimination of
those that have too many zero
values in the population of reference
sites to calculate the metric at a large
enough proportion of sites;
*• Descriptive statistics (central
tendency, range, distribution,
outliers) to characterize metric
performance within the population
of reference sites of each site class;
*• Elimination of metrics that have too
high variability in the reference site
population such that they cannot
discriminate among sites of different
condition.
Step 2. Select Robust Measures.
Core metrics are those that will
discriminate between good and poor
quality ecological conditions.
Discriminatory ability of biological
metrics is evaluated by comparing the
distribution of each metric at a set of
reference sites with the distribution of
metrics from a set of "known" stressed
sites (defined by physical and chemical
characteristics) within each site class. If
there is minimal or no overlap between
the distributions, then the metric can be
considered to be a strong discriminator
between reference and impaired
conditions (Figure 11-3).
Criteria are established to identify a
population of "known" stressed sites
based on physical and chemical
measures of degradation. Criteria for
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-7
-------
Table 11-1. Potential metrics for macrophytes, benthic macroinvertebrates, and fish that
could be considered for estuaries. Redundancy can be evaluated during the
calibration phase to eliminate overlapping
%
polychaetes
- polychaete
biomass
- #, % or
biomass of
menhaden
Trophic/Habitat
- % cover
- density of new
shoots
- biomass
- stem counts
- % or biomass
epibenthic
- % or biomass
deposit feeders
- % or biomass
suspension
feeders
- Proportion of
planktivores
- Proportion of
benthic feeders
- Proportion of
piscivores
stressed sites can include (Weisberg et
al. 1993):
*• Any sediment contaminant
exceeding the Long et al. (1995)
effects range-median (ER-M)
concentration;
*• Survival in toxicity tests less than
80% of controls;
*• Low dissolved oxygen;
*• Total sediment organic carbon > 3%.
Following identification of reference and
stressed sites, the biological metrics that
best discriminate between them are
determined.
Those metrics having the strongest
discriminatory power provide the most
confidence in assessing biological
condition of unknown sites. Metrics can
be easily compared by estimating their
discrimination efficiency (DE) or the
percentage of stressed sites below a
threshold representing the reference
sites. For example, DE could be
measured as the percentage of stressed
sites below the 25th percentile of
reference sites, for a given metric.
Several studies have used tests of
statistical significance between
reference and stressed sites to select
metrics (e.g., Weisberg et al. 1997,
Hyland et al. 1998). Significance tests
should only be used if the sample size
(number of reference and stressed sites)
is large enough that the test has
sufficient power to detect a meaningful
difference.
11-8
Index Development
-------
30
26
22
3 18
ro
•| 14
^>
10
6
[
Refe
]
[
;rence Stre
]
;ssed
| Min-Max
I I 25%-75%
n Median value
Figure 11-3
Hypothetical box
plot illustrating how
a successful metric
discriminates
between reference
and stressed sites.
Step 3. Determine the best aggregation of
core measures for indicating status and
change in condition.
The purpose of an index is to provide a
means of integrating information from
the various measures of biological
attributes (or metrics). Metrics vary in
their scale—they are integers,
percentages, or dimensionless numbers.
Prior to developing an integrated index
for assessing biological condition, it is
necessary to standardize core metrics via
transformation to unitless scores. The
standardization assumes that each
metric has the same value and
importance; i.e., they are weighted the
same, and that a 50% change in one
metric is of equal value to assessment as
a 50% change in another.
Where possible, the scoring criterion for
each metric is based on the distribution
of values in the population sites, which
include reference sites; for example, the
95th percentile of the data distribution is
commonly used to eliminate extreme
outliers. From this upper percentile, the
range of the metric values can be
standardized as a percentage of the 95th
percentile value, or other (e.g., trisected
or quadrisected), to provide a range of
scores. Those values that are closest to
the 95th percentile receive higher scores,
and those having a greater deviation
from this percentile receive lower
scores. For those metrics whose values
increase in response to perturbation the
5th percentile is used to remove outliers
and to form a basis for scoring.
Alternative methods for scoring metrics
are currently in use in various parts of
the U.S. for multimetric indexes. A
"trisection" of the scoring range has
been well documented (Karr et al. 1986,
Ohio EPA 1987, Weisberg et al. 1997,
Hyland et al. 1998). More recent studies
are finding that a standardization of all
metrics as percentages of the 95th
percentile value yields the most
sensitive index, because more
information of the component metrics is
retained (e.g., Hughes et al. 1998).
Aggregation of metric scores simplifies
management and decision making so
that a single index value is used to
determine whether action is needed.
Biological condition of waterbodies is
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-9
-------
judged based on the summed index
value (Karr et al. 1986). If the index
value is above a criterion, then the
stream is judged as "optimal" or
"excellent" in condition. The exact
nature of the action needed (e.g.,
restoration, mitigation, pollution
enforcement) is not determined by the
index value, but by analyses of the
component metrics in addition to the
raw data, and integrated with other
ecological information. Therefore, the
index is not the sole determinant of
impairment and diagnostics, but when
used in concert with the component
information, strengthens the assessment
(Barbour etal. 1996b). Components of
Step 3 include:
*• Development of scoring criteria for
each metric (within each site class)
from the appropriate percentile of
the data distribution (Figure 11-4). If
the metric is associated with a
significant covariate such as estuary
size, depth, or salinity a scatterplot
of the metric and covariate and a
moving estimate of the appropriate
percentile, are used to determine
scoring criteria as a function of the
covariate (e.g., Weisberg et al. 1993);
*• Testing the ability of the final index
to discriminate between populations
of reference and anthropogenically
affected (stressed) sites.
Step 4. Index thresholds for assessment and
biocriteria.
The multimetric index value for a site is
a summation of the scores of the metrics
and has a finite range within each site
class and index period, depending on
the maximum possible score of the
metrics (Barbour et al. 1996a). This
range can be subdivided into any
number of categories corresponding to
various levels of impairment. Because
the metrics are normalized to reference
conditions and expectations for the
classes, any decision on subdivision
should reflect the distribution of the
scores for the reference sites.
Rating categories are used to assess the
condition of both reference and non-
reference sites. Most of the reference
sites should be rated as good or very good
in biological condition, which would be
as expected. However, a few reference
sites may be given the rating as poor
sporadically among the collection dates.
If a "reference" site consistently receives
a fair or poor rating, then the site should
be re-evaluated as to its proper
assignment. Putative reference sites
may be rated "poor" for several reasons:
*• Natural variability — owing to
seasonal, spatial, and random
biological events, any reference site
may score below the reference
population 10th percentile. If due to
natural variability, a low score
should occur 10% of the time or less;
*• Impairment — stressors that were
not detected in previous sampling or
surveys may occur at a "reference"
site; for example, episodic non-point
source pollution or historical
contamination may be present at a
site;
*• Non-representative site — reference
sites are intended to be
representative of their class. If there
are no anthropogenic stressors, yet a
"reference" site consistently scores
outside the range of the rest of the
reference population, the site may
be a special or unique case, or it may
have been misclassified and actually
belong to another class of sites.
11-10
Index Development
-------
maximum
- - -*
o
n 5 4
n
3
3 /observed value ^ ,„„ \
LJ 2 ^95th value X1°°j
i
i i
All Trisection Quadrisection Percentage
Sites of standard
Scoring Methods
Figure 11-4
Basis of metric
scores using the
95th percentile as a
standard.
Components of Step 4 include:
*• Assessment categories are
subdivided from the range of
possible scores for each site class.
Categories should be proportional to
the interquartile range (or standard
deviation) of total scores in the
reference sites. Thus, reference sites
with a small interquartile range
(small s.d.; small coefficient of
variation) would yield more
assessment categories than a more
variable reference population;
*• The validity of biological condition
categories is evaluated by comparing
the index scores of the reference and
known stressed sites to those
categories. If reference sites are not
rated good or very good, then some
adjustment in either the biological
condition designations or the listing
of reference sites may be necessary;
*• Confidence intervals are estimated
for the multimetric index to help
determine biological condition for
sites that fall in close proximity to a
threshold. Precision and sensitivity
are determined from replicate
samples, and are important for
estimating the confidence of
individual assessments.
Once the framework for bioassessment
is in place, conducting bioassessments
becomes relatively routine. Either a
targeted design that focuses on site-
specific problems or a probability-based
design, which is appropriate for 305(b),
area-wide, and watershed monitoring,
can be done efficiently. Routine
monitoring of reference sites should be
based on a random selection procedure,
which will allow for cost efficiencies in
sampling while monitoring the status of
the reference condition. Potential
reference sites of each class would be
randomly selected for sampling, so that
an unbiased estimate of reference
condition can be developed. A
randomized subset of reference sites can
be resampled at some regular interval
(e.g., a 4-year cycle) to provide
information on trends in reference sites.
Example 1: Chesapeake Bay Index
Development
For the Chesapeake Bay, a separate
benthic index was developed for each of
seven habitats: tidal fresh, oligohaline,
low mesohaline, high mesohaline sand,
high mesohaline mud, polyhaline sand,
and polyhaline mud (Weisberg et al.
1997). These habitats had been
identified as separate assemblages in
the classification step.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-11
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Reference and stressed sites were
identified by the following: from
existing Chesapeake Bay data, no
reference sites could be in highly
developed (urban) watersheds or near
known point-source discharges, no
reference site could have organic carbon
content > 2%, no reference site could
have any sediment contaminants
exceeding the Long et al. (1995) effects
range-median (ER-M) concentration, no
reference site could have low dissolved
oxygen, and no reference site could
exhibit any sediment toxicity. Stressed
sites were defined as those with any
contaminant exceeding the ER-M
concentration and measured sediment
toxicity, or total organic carbon
exceeded 3%, or dissolved oxygen was
low, < 2-mgL'1 (Weisberg etal. 1997).
Index development proceeded through
the steps:
Step 1. 17 candidate metrics were
identified based on the paradigms of
Pearson and Rosenberg (1978).
Step 2. 15 of the 17 metrics could
distinguish between reference sites and
stressed sites in one or more of the seven
habitats.
Step 3. Four to seven of the metrics were
used for an index specific to each habitat
type. Scoring of metrics was on a 5-3-1
scale, with metric values greater than
the reference site median scored as 5;
between the 5th and the median of the
reference sites scored as 3; and below
the 5th percentile scored as 1.
Step 4. The index was able to correctly
classify as reference or stressed 93% of
an independent validation data set that
had not been used to develop the index.
Example 2: Louisiana and Maryland
Fish Indexes
Several states are developing fish
indexes of biotic integrity (IBI) for
estuarine species. The multimetric
Index of Biotic Integrity (IBI) concept
was originally developed for fresh
water streams (Karr 1981), and has been
modified and applied to a Louisiana
estuary (Thompson and Fitzhugh 1986).
The strength of this index is that many
factors affecting biological integrity can
be measured in fish (e.g., community
composition, relative abundance, health,
etc.). This proposed estuarine IBI
maintains the same three main
categories as those of the fresh water
IBI: species composition, trophic
composition, and fish condition.
However, the metrics are modified to
reflect estuarine habitats and fish
assemblages. In addition, because
estuarine systems exhibit a high degree
of seasonality in their fish fauna, a
measure of seasonal variability was
incorporated. The metrics for estuaries
are based on life history and habitat
requirements similar to those of the
fresh water IBI. Proposed metrics from
Thompson and Fitzhugh (1986) for
estuarine communities are listed in
Table 11-2. A similar fish Index of Biotic
Integrity is being adapted for
application in estuarine and coastal
marine habitats on the Gulf Coast of
Texas (Guillen 1995).
The state of Maryland has also
developed a fish Index of Biotic
Integrity that is more rapid and less
expensive to apply (Jordan et al. 1992).
This fish IBI is comprised of nine
metrics (Table 11-3) that can be
compared to measurements of the
physical environment such as dissolved
oxygen and land use.
11-12
Index Development
-------
Table 11-2.
Estuarine fish IBI metrics proposed by Thompson and Fitzhugh (1986).
Community
Structure/Function
Species composition
Trophic composition
(for adults of species)
Fish abundance and
condition
Metric
Total number of fish species
Number and identity of resident estuarine species
Number and identity of marine species
Number and identity of sciaenids
Number and identity of freshwater species
Proportion of individuals as bay anchovy
Measure of seasonal overlap offish community
Number of species needed to make up 90% of collection
Proportion of individuals as generalized benthic feeders
Proportion of individuals as generalized plankton grazers
Proportion of individuals as top carnivores
Proportion of young of year in sample or number of individuals
in sample
Proportion of individuals with disease, tumors, fin damage, and
other anomalies
The results of some preliminary analyses
from areas in the Chesapeake Bay with
salinities ranging from O-to-16 ppt
indicate that the Maryland IBI can be
used to identify large scale spatial and
temporal trends in biological integrity
and that the index responds to water
quality (DO) and land use impacts.
11.3.2 Discriminant Model Index
Discriminant Model Approach
The discriminant model approach was
used by EMAP to develop benthic
condition indexes for the Virginian
Province (Mid-Atlantic) and for the
Louisianian Province (Gulf Coast)
(Engle et al. 1994, Summers et al. 1993,
Weisberg et al. 1993, Paul et al. 1999)
based on defined reference sites. Sets of
minimally impaired sites; i.e.,
"reference" and impaired sites were
identified; impaired sites were affected
by either hypoxia (DO <2 mgL"1); toxic
sediments; or sediment contamination
above the ER-M threshold. Minimally
impaired sites were defined to have DO
>5 mgL"1 and no detectable toxicity or
contamination. The two site types
represented the ends of a continuum,
with intermediate sites not used for
discriminant model building (Engle et
al. 1994, Weisberg et al. 1993).
The classification step for the EMAP
discriminant models consisted of
examining associations between benthic
macroinvertebrate metrics and physical
habitat measures of salinity, sediment
grain size, and depth. Only salinity had
a strong relationship with the taxa
richness metric; taxa richness was
estimated as the percent of taxa
expected, adjusted for salinity (refer to
Figure 11-2).
Discriminant Model Analysis
The discriminant model analysis is a
multivariate procedure that attempts to
build a model that will predict the
membership of a site into two or more
predetermined classes. In the example
used in EMAP, the classes were
reference and impaired sites (by low
DO, toxicity or metal contamination).
The model procedure attempts to find a
linear combination of input variables
(biological metrics) that best predicts
membership in the class. Alternative
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-13
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Table 11-3. Maryland estuarine fish IBI metrics.
Community
Structure/Function
Species composition
Trophic composition
(for adults of species)
Fish abundance and
condition
Metric
Total number of species
Number of species in bottom trawl
Number of species comprising 90 percent of
individuals
Proportion of planktivores
Proportion of benthic feeders
Proportion of piscivores
Number of estuarine spawners
Number of anadromous spawners
Total fish exclusive of Atlantic menhaden
Response
to
Impairment
reduced
reduced
reduced
increased
decreased
decreased
decreased
decreased
decreased
models are tested by estimating the
proportion of sites (from the
model-building data set) that are
misclassified. The best model usually
has the lowest misclassification rate. A
test of a model requires an independent
test data set that was not used to build
the model.
EMAP built discriminant models using
benthic metrics in a step wise model
building approach. The models used
three to five metrics in the Louisianian
and Virginian provinces respectively,
and both models used taxa richness
(Engle et al. 1994, Weisberg et al. 1993).
The benthic indexes were then
calculated as the discriminant score of a
site and standardized on a scale of 1 to
10.
Performance of the discriminant models
was good in distinguishing reference
from impaired sites in the calibration
data: 100% for the Gulf of Mexico sites
(Engle et al. 1994; n = 16 sites) and 86-
93 % for the Virginian Province sites
(Weisberg et al. 1993; n = 33 sites).
When tested with validation data
collected in subsequent years, however,
both sets or models failed to predict
adequately and had to be redeveloped
(Engle and Summers 1999, Strobel et al.
1994,1995, Paul et al. 1999). Inclusion of
several years of monitoring data in both
provinces produced more robust and
reliable models. In the Virginian
Province, the robust calibration data set
consisted of 60 sites (30 each).
An improved index was created to be
applicable across a variety of estuarine
environments in the Gulf of Mexico
(Engle and Summers 1999). The
statistical approach described in Engle
and Summers (1999) proved to be
applicable throughout the estuaries in
the northern Gulf of Mexico. This
benthic index was also validated
independently by Rakoncinski (1997),
who compared results of canonical
correspondence analysis (CCA) with
data from EMAP-E (1991-1992), using
the index developed in Engle et al. 1994
(Engle and Summers 1999).
11.3.3 Index Derived from
Multivariate Ordination
An index for biocriteria was derived by
Smith et al. (2000) using multivariate
ordination to derive a pollution
gradient, which in turn was used to
develop an index. The approach was
developed with benthic
macroinvertebrates from the Southern
11-14
Index Development
-------
California Bight (Smith et al. 2000; see
also 11.2.1, p. 11-5), and is currently
being applied to demersal fish from the
same waters (Allen and Smith 2000).
The approach is computationally
intensive and rather complex. We will
describe the result first (the index and its
components), and then briefly describe
how the components themselves are
derived.
The central assumption of this approach
is that each species has a tolerance for
pollution, and that if the pollution
tolerance is known for sufficiently large
set of species, it is possible to infer the
degree of degradation from species
composition and the tolerances. This is
the basis of the familiar Hilsenhoff Biotic
Index (HBI; Hilsenhoff 1987) of
freshwater bioassessment, as well as of
several metrics in the multimetric
approach. For example, capitellid
polychaetes are known to be tolerant to
organic pollution (BOD). The index
used by Smith et al. is a weighted
average tolerance value of all species
found in a sample, weighted by
abundance of the species:
Equation 11-1.
I
afsl Pi
I
where Is is the index value for sample s,
n is the number of species in sample s, asi
is the abundance of species i in sample s,
Pi is the tolerance value of species i, and
the exponent/is used to downweight
extreme abundances. If/is zero, then
the index is not weighted by abundance
(Smith et al. 2000, Allen and Smith
2000).
The index of equation (11-1) is
computationally almost identical (except
for the introduction of the
transformation exponent/) to the
Hilsenhoff Biotic Index. Biocriteria can
be assigned to index values; for
example, if the index is defined in the
range from 0 (unpolluted) to 100
(severely polluted), then a criterion for
Class A estuarine waters might be
values < 25.
The steps below outline the derivation
of the tolerance values pt. A data set is
required with sites that span a range
from unpolluted to severely polluted.
In the Southern California Bight, these
were defined by sediment contaminant
levels above and below the effects range
median (ER-M) and effects range low
(ER-L) concentrations (Long et al. 1995).
Levels of a contaminant below the ER-L,
between the ER-L and ER-M, and above
the ER-M are rarely, occasionally, and
frequently, respectively, associated with
adverse effects. Impacted sites had six
of eight selected contaminants (Cu, Pb,
Ni, Zn, Cd, Cr, PCB, and DDT) above
the ER-M. Reference sites consisted of
stations lying outside of POTW
discharge areas and with no more than
one selected contaminant above the ER-
L for a contaminant.
The data must be divided into two sets:
a calibration subset and a test subset.
Step 1. Ordination analysis of species
abundance (calibration data).
Ordination analysis produces a plot of
sites in ordination space (Figure 11-5).
Distances between pairs of points are
proportional to the dissimilarity of
species composition in the
corresponding samples: samples with
very similar composition will be close
together in the ordination diagram. If
the species are associated with the
pollution gradient, the sites will define a
gradient, with polluted sites at one end
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-15
-------
CM
I
1
Step 1: ordination
"contaminated" end
Step 2: gradient
\
Step 3: project site scores
r \ r
"reference" end
Ordination Axis 1
Figure 11-5
Steps 1-3.
Establishing site
scores on a
contamination
gradient. The
gradient is
established between
reference ("r") and
contaminated ("p")
sites as plotted in
ordination space.
Dots are sites not
designated as either
reference or
contaminated. The
projection of site "x"
on the gradient
(dotted line) yields
its site score.
Adapted from Smith
et al. 2000.
and unpolluted sites at the other (Figure
11-5).
Step 2. Find the pollution gradient.
The two ends of the pollution gradient
are defined as the average positions in
ordination space of the unpolluted and
polluted sites, respectively. These ends
are connected by a line, which
represents the pollution gradient as
expressed by the observed species
compositions.
Step 3. Project all calibration observations
onto the pollution-effects gradient.
The position of each site in the
ordination space is projected onto the
gradient. This projection is the site score
of the calibration sites (Figure 11-5).
Step 4. Rescale the projections.
Site scores are scaled from 0 ("least
polluted") to 100 ("most polluted").
Step 5. Compute tolerance values for each
species.
Each species has an "average" position
on the pollution gradient. These species
positions are the tolerance values (p;) of
Equation 11-1. Site scores calculated in
Step 4 give each site a position on the
pollution gradient. The abundance of a
species at each observation can be
plotted against the site scores (Figure
11-6). The species position on the
gradient, or the tolerance value pit is the
abundance-weighted average position
for the species over all sites.
Step 6. Compute the f parameter.
The f-parameter is iterated
simultaneously with the pt in an
optimization procedure (Smith et al.
2000).
The species tolerance scores were in
turn used to predict the Benthic
Response Index (BRI) according to
Equation 11-1. The BRI is the position
of a site on the contamination gradient,
or the predicted value of the site score
11-16
Index Development
-------
100
•• •• • • • •
•*• • «• «• • w «• ••
'• • — J» * •••*•••<
100
Ste Scores
Figure 11-6
Step 5.
Computing the
tolerance values.
Abundance of
Species A and
site scores (from
Figure 11-5) of all
sites where
Species A
occurs. The
abundance-
weighted average
score over all
sites is Species
A's pollution
tolerance score
(arrow). This
example shows a
highly tolerant
species, which
occurs in greatest
abundances at
the most polluted
sites. Adapted
from Smith et al.
2000.
calculated in Step 4. Actual site scores
(Step 4) are calculated only for the
calibration data; site score is predicted as
BRI for all assessment sites.
The BRI was developed separately for 3
depth zones: 10-35-m, 25-130-m, and
110-324-m. Earlier work had shown that
benthic communities off Southern
California could be classified by depth
and sediment type (see Section 11.2.1, p.
11-5). Sediment type was secondary,
and was not deemed to have a strong
enough effect to justify further
categorization of the data set.
The tolerance index developed by Smith
et al. was then tested with the
independent data (not used to develop
the index). The independent test
showed that the model was largely
correct in predicting position along the
contamination gradient. For further
details of calculations and formulas, see
Smith et al. (2000). The approach is
currently being extended to demersal
fish from the same region (Allen and
Smith 2000).
Smith et al. estimated tolerance values
for over 450 marine species from
southern California. The BRI
contamination score can be calculated
for any new site from species
abundance data at the site. The BRI has
a range from 0 (unpolluted) to 100
(severely polluted) and biocriteria can
be set at selected values for specific
aquatic life uses of coastal waters of
Southern California. Reference sites
had BRI values < 25, and all severely
contaminated sites had BRI > 36 (Smith
et al. 2000). The reference values could
form the basis of biocriteria for the
region.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
11-17
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11-18 Index Development
-------
Chapter 12
Quality Assurance:
Design, Precision and
Management
Quality assurance (QA) is an integrated
program for ensuring the reliability of
monitoring and measurement data and
includes quality control. Quality control
(QC) refers to operational procedures for
obtaining prescribed standards of
performance in the monitoring and
measurement process. Specific QC
elements can be developed for most, if
not all, project activities. All project
activities, from sampling (data
collection) and laboratory analysis to
statistical analysis and reporting, are
potential error sources (Peters 1988).
Because error is cumulative and can
significantly affect the results of a
project, all possible efforts must be made
to control it. Therefore, quality
assurance is a continuous process that
should be implemented throughout the
entire development and operation of a
program.
The purpose of an overall quality
assurance project plan (QAPP),
containing specific QC elements and
activities, is to minimize — and when
possible eliminate—the potential for
error. Additionally, there are objective
mechanisms for evaluating activities
relative to pre-established measurement
quality objectives and other project
goals. The appropriateness of the
investigator's methods and procedures
and the quality of the data to be
obtained must be ensured before the
results can be accepted and used in
decision making.
QA is accomplished through:
*• Program design;
*• Investigator training;
*• Standardized data gathering and
processing procedures;
*• Verification of data reproducibility;
*• Instrument calibration and
maintenance.
As outlined below, QA requirements
apply to all activities in an ecological
study. More detailed guidance and
examples for QA activities should be
obtained from USEPA (1994c, and
1998a); more general guidance is
outlined by USEPA (1993b).
12.1 Program Design
A central component of QA is overall
study design which includes
formulation of questions and
hypotheses, experimental design, and
development of analysis approaches.
The classical approach by which
scientists plan research consists of the
following steps:
*• Statement of the problem to be
resolved;
> Formulation of alternative
hypotheses that will explain the
phenomena or, in the case of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
12-1
-------
problems that do not involve
elaboration of processes, formulation
of specific research questions;
*• Establishment of boundaries within
which to resolve the problem;
> Formulation of an experimental or
study design that will falsify one or
more hypotheses or answer the
specific research questions;
*• Establishment of uncertainty limits
including setting acceptable
probabilities of type I and type II
errors for statistical hypothesis
testing;
*• Optimization of the study design
including power analysis of the
statistical design.
Experimental advances in basic sciences
have not included the last two steps
because uncertainty limits were
inappropriate or unknown.
Examination of experimental advances
also reveals that a high degree of
creativity and insight is required to
formulate hypotheses and study
designs; no formal planning process or
"cookbook" can guarantee creativity and
insight. Nevertheless, documentation of
the planning process and a complete
explanation of the conceptual
framework help others evaluate the
validity of scientific and technical
achievements.
12.1.1 Formulation of a Study Design
A study design is developed to answer
the specific monitoring questions
developed in formulating the questions
and objectives. Sampling design
considerations were discussed in
Chapter 5.
For quality assurance, some effort will
always be required for repeated samples
so that measurement error can always
be estimated from a subset of sites.
Repeated measurement at 10% or more
of sites is common among many
monitoring programs.
12.1.2 Establishment of Uncertainty
Limits
The level of uncertainty associated with
environmental measurements (due to
natural variability, sampling error,
measurement error, or other sources of
uncertainty) propagates directly to the
uncertainty of inferences and
conclusions that can be made from the
data. Establishing the limits of
statistical uncertainty for conclusions
also sets limits for the data to be
collected (also known as Data Quality
Objectives [DQOs]; Chaloud and Peck
1994). As mentioned in Chapter 5, there
is a close association between sampling
intensity and uncertainty. Reducing
uncertainty usually results in greater
costs. Assessing uncertainty, and
optimizing the study design (below)
require at least pilot data in hand, if not
results from one year or more of
monitoring.
As an example of uncertainty limits,
USEPA's EMAP program established
the following (Chaloud and Peck 1994):
*• Estimate the status of a population
of resources with 95% confidence
intervals that are within 10% of the
estimate;
*• Determine average change in status
of 20% over 10 years with 95%
confidence and statistical power of
0.8.
EMAP selected 95% confidence
intervals, however, there is nothing
"scientific" about choosing 95%
intervals over, say, 90 % or 99%. The
second limit above, determining
12-2
Quality Assurance: Design, Precision and Management
-------
change, implies that EMAP managers
were only willing to conclude a false
change in status 1 time out of 20 (Type I
error; false positive), but were willing to
conclude a false lack of change 1 time
out of 5 (Type II error, false negative).
12.1.3 Optimizing the Study Design:
Evaluation of Statistical Power
A principal aspect of probability
sampling is determining how many
samples will be required to achieve the
monitoring goals and what is the
probability of making an incorrect
decision based on the monitoring
results. The primary tool for conducting
these analyses is statistical power
analysis. Evaluating statistical power is
key to developing data quality criteria
and performance specifications for
decision making (USEPA 1996b) as well
as evaluating the performance of
existing monitoring programs (USEPA
1992). Power analysis provides an
evaluation of the ability to detect
statistically significant differences in a
measured monitoring variable. The
importance of this analysis can be seen
by examining the possible outcomes of a
statistical test. The null hypothesis (H0)
is the root of hypothesis testing.
Traditionally, null hypotheses are
statements of no change, no effect, or no
difference. For example, the mean
abundance at a test site is equal to the
mean abundance of the reference sites.
The alternative hypothesis (Ha) is
counter to H0, traditionally being
statements of change, effect, or
difference. Upon rejecting H0, Ha would
be accepted.
The two types of decision errors that
could be made in hypothesis testing are
depicted in Table 12-1. A Type I error
(i.e., false positive) occurs when H0 is
rejected although H0 is really true. A
Type II error (i.e., false negative) occurs
when H0 is not rejected although H0 is
really false. The magnitude of a Type I
error is represented by
-------
Table 12-1. Errors in hypothesis testing.
Decision
Accept H0
Reject H0
State of the population (truth)
H0 is True
1-a
(Confidence level)
a
(Significance level)
(Type I error)
H0 is False
P
(Type II error)
1-P
(Power)
Figure 12-1
Effect of
increasing sample
size from n., to n2
on power. The
curves represent
the probability
distribution of the
sample means
from 2 samples,
reference and test,
and for 2 sample
sizes n., and n2
where n2 > nv
a. Reference
sample
critical value for rj
"critical value for q
rejection region,a,, for n,
b. Test sample
rejection region,Oj, for r^
probability of Type II \
error (false negative)!
for n.
the x-axis), the probability of rejecting
H0, the power, increases. If the real
difference between the two sample
means is zero, the probability of
rejecting H0 is equal to the significance
level, CL. Figure 12-la shows the general
relationship between CC and P if (X is
changed. Figure 12-lb shows the
relationship between CC and P if the
sample size is increased. The tradition
of 95% confidence (a = 0.05) is entirely
arbitrary; there is no scientific
requirement that confidence be set at
95%. Indeed, for environmental
protection, power is at least as
important—and possibly more
important—than confidence (Peterman
1990, Fairweather 1991).
Basic Assumptions
Usually, several assumptions regarding
data distribution and variability must
be made to determine the sample size.
Applying any of the equations
described in this chapter is difficult
when no historical data set exists to
quantify initial estimates of proportions,
standard deviations, means, or
coefficients of variation. To estimate
these parameters, Cochran (1963)
recommends four sources:
*• Existing information on the same
population or a similar population;
+ A two-step sample. Use the first-
step sampling results to estimate the
needed factors, for best design, of
12-4
Quality Assurance: Design, Precision and Management
-------
the second step. Use data from both
steps to estimate the final precision
of the characteristic(s) sampled;
+ A "pilot study" on a "convenient" or
"meaningful" subsample. Use the
results to estimate the needed
factors. Here the results of the pilot
study generally cannot be used in
the calculation of the final precision
because often the pilot sample is not
representative of the entire
population to be sampled;
+ Informed judgment, or an educated
guess.
For evaluating existing programs,
proportions, standard deviations,
means, etc. would be estimated from
actual data.
Some assumptions might result in
sample size estimates that are too high
or too low. Depending on the sampling
cost and cost for not sampling enough
data, it must be decided whether to
make conservative or "best-value"
assumptions. Because of the fixed
mobilization costs, it is probably cheaper
to collect a few extra samples the first
time than to realize later that additional
data are needed. In most cases, the
analyst should probably consider
evaluating a range of assumptions
regarding the impact of sample size and
overall program cost. USEPA
recommends that if the analyst lacks a
background in statistics, he/she should
consult with a trained statistician to be
certain that the approach, design, and
assumptions are appropriate to the task
at hand.
Simple Comparison of Proportions and
Means from Two Samples
The proportion (e.g., percent dominant
taxon) or mean (e.g., mean number of
EPT taxa) of two data sets data sets can
be compared with a number of
statistical tests including the parametric
two-sample t-test, the nonparametric
Mann-Whitney test, and two-sample
test for proportions (USEPA 1996b). In
this case, two independent random
samples are taken and a hypothesis test
is used to determine whether there has
been a significant change. To compute
sample sizes for comparing two
proportions, p1 and p2, it is necessary to
provide a best estimate for p1 and p2, as
well as specifying the significance level
and power (1-0). Recall that power is
equal to the probability of rejecting H0
when H0 is false. Given this
information, the analyst substitutes
these values into the following equation
(Snedecor and Cochran 1980):
Equation 12-1.
«„=
where Za and Z2p correspond to the
normal deviate. Common values of (Za
+ Z2p)2 are summarized in Table 12-2.
To account for p1 and p2 being
estimated, t could be substituted for Z.
In lieu of an iterative calculation,
Snedecor and Cochran (1980) propose
the following approach: (1) compute n0
using Equation 12-1; (2) round n0 up to
the next highest integer,/; and (3)
multiply n0 by (f+3)/(f+l) to derive the
final estimate of n.
To compare the mean from two random
samples to detect a change of <5; i.e.,
\2-~Xi, the following equation is used:
Equation 12-2.
Common values of (Za + Z2p)2 are
summarized in Table 12-2. To account
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
12-5
-------
Table 12-2. Common values of (Za + Z^)2 for estimating sample size for use with Equations 12-1
and 12-2 (Snedecorand Cochran 1980).
Power,
1-/7
0.80
0.85
0.90
0.95
0.99
crfor One-sided Test
0.01
10.04
11.31
13.02
15.77
21.65
0.05
6.18
7.19
8.56
10.82
15.77
0.10
4.51
5.37
6.57
8.56
13.02
crfor Two-sided Test
0.01
11.68
13.05
14.88
17.81
24.03
0.05
7.85
8.98
10.51
12.99
18.37
0.10
6.18
7.19
8.56
10.82
15.77
for Si and s2 being estimated, Z should
be replaced with t. In lieu of an iterative
calculation, Snedecor and Cochran
(1980) propose the following approach:
(1) compute n0 using Equation 12-2; (2)
round n0 up to the next highest integer,
/; and (3) multiply n0 by (f+3)/(f+l) to
derive the final estimate of n.
A special case of Equation 12-2 arises for
biocriteria, when we compare the mean
of a sample to determine if the value is
below some set limit, that is, if the site is
impaired or below a reference threshold.
The threshold is fixed by previous
investigations and decisions, and is not
a random variable. We ask now
whether we can detect a change of d;
i.e., G-XJ, where C is the biocriteria limit:
Equation 12-3.
«„=
82
In Equation 12-3, Za is most often one-
tailed, because the concern is only
whether the value is below the
threshold.
Sample Size Calculations for Means and
Proportions
For large sample sizes or samples that
are normally distributed, symmetric
confidence intervals for the mean are
appropriate. This is because the
distribution of the sample mean will
approach a normal distribution even if
the data from which the mean is
estimated are not normally distributed.
The Student's t statistic (ia/2/n i) is used
to compute symmetric confidence
intervals for the population mean, |_l:
Equation 12-4.
x-t_
•a/2,/1-1
This equation is appropriate if the
samples are normally distributed or the
sample size is greater than 30
(Wonnacott and Wonnacott 1969),
although Helsel and Hirsch (1992)
suggest that highly skewed data might
require more than 100 observations.
Although several approaches exist to
estimate confidence levels for any
percentile, many rely on assuming a
normal or lognormal distribution. The
approach presented here (Conover
1980) for more than 20 observations
does not rely on these assumptions.
Conover (1980) also provides a
procedure for smaller sample sizes. To
calculate the confidence interval
corresponding to the median, lower
quartile, or upper quartile, the following
procedure is used.
1. Order the data from smallest to
largest observation such that
12-6
Quality Assurance: Design, Precision and Management
-------
where xp corresponds to the median; i.e.,
p=0.5, lower quartile; i.e., p=0.25, or
upper quartile; i.e., p=0.75.
2. Compute the values of r and s as
Equation 12-5.
where Za/2 is selected from a normal
distribution table.
3. Round r and s* up to the next
highest integers r and s. The 1-CC
lower and upper confidence limits
for xp are xt and xs, respectively.
It can be seen from Equation 12-5 that
estimation of medians or quartiles from
small samples can result in large
confidence intervals for the estimate.
For example, the 90% confidence
interval for the lower quartile of a
sample of n=10 covers the first 5
observations. A sample of less than 10
observations would have a confidence
interval extending below the smallest
observation. This is the reasoning
behind a general 'rule of thumb"that
estimation of reference conditions
should be based on a sample of 10 or
more sites, if at all possible. Figure 12-2
gives example sample size calculations
for comparing proportions and
population means.
12.2 Management
12.2.1 Personnel
Trained and experienced biologists
should be available to provide thorough
evaluations, provide support for various
activities, and serve as QC checks. They
should have training and experience
commensurate with the needs of the
program. At least one staff member
should be familiar with establishing a
QA framework. QA programs should
document personnel responsibilities
and duties and clearly delineate project
organization and lines of communica-
tion (USEPA 1998a). A time line
illustrating completion dates for major
project milestones or other tasks can be
a tremendously useful tool to track
project organization and progress.
12.2.2 Resources
Laboratory facilities, adequate field
equipment, supplies, and services
should be in place and operationally
consistent with the designed purposes
of the program so that high-quality
environmental data can be generated
and processed in an efficient and cost-
effective manner (USEPA 1992).
Adequate taxonomic references and
scientific literature should be available
to support laboratory work, data
processing, and interpretation.
12.3 Operational Quality
Control
Protocols should be developed for
designing a data base and for screening,
archiving, and documenting data. Data
screening identifies questionable data
based on expected values and obvious
outliers. Screening is especially
important if data are gathered from a
variety of sources and the original
investigators and data sheets are no
longer available. Figure 12-3 defines the
qualitative and quantitative data
characteristics that are most often used
to describe data quality.
These measurement quality indicators
require a priori consideration and
definition before the data collection
begins. Taken collectively, they provide
a summary characterization of the data
quality needed for a particular
environmental decision. Duplication of
approximately 10% of the total
sampling effort is a common level for
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
12-7
-------
Example 1—Sample size calculation for comparing proportions
To detect a difference in proportions of 0.20 with a two-sided test, a equal
to 0.05, '/-p equal to 0.90, and an estimate of p1 and p2 equal to 0.4 and 0.6,
n0 is computed from Equation 12-1 as
"o =
[(0.4)(0.6) + (0.6)(0.4)] =
(0.6 - 0.4)2
Rounding 126.1 to the next highest integer, f is equal to 127, and n is
computed as 126.1 x 130/128 or 128.1. Therefore 129 samples in each
random sample, or 258 total samples, are needed to detect a difference in
proportions of 0.2. Since these are proportions, the result means that the
total count in the sample must be at least 129. For example, to detectthe
above difference in the proportion of dominant taxon (e.g., benthic
macroinvertebrates or fish) of two sites, at least 129 individuals must be
counted and identified in each estuary.
The example illustrates that a statistically significant difference can be easily
detected in proportions if sufficient individuals are sampled. However, it is
doubtful that a difference between 40% and 60% in dominant taxon is
biologically meaningful.
Example 2—Sample size calculation for comparing population mean
abundance
To detect a difference of 20 in mean abundance with a two-sided test. The
standard deviation, s, was estimated as 30 for both samples based on
previous studies; a was selected as 0.05; and 1-$ was selected as 0.90.
Substituting these values into Equation 12-2 yields
n0 = 10.51
(302 + 302)
= 47.3
202
Rounding 47.3 to the next highest integer, f is equal to 48,
and n is computed as 47.3 x 51/49 or 49.2. Therefore 50
samples in each random sample, or 100 total samples, are
needed to detect a difference of 20.
Figure 12-2
Example
sample size
calculations for
comparing
proportions
and population
means.
operational QC Replication of samples
at a randomly selected subset of field
sites (usually, 10 percent of the total
number is considered appropriate) is
used to estimate precision, and
representativeness of the samples and
the methods. Splitting samples into
subsamples can be used to check
precision of the methodology, and
reprocessing of finished samples is used
to check accuracy of laboratory
operations.
12.3.1 Field Operations
For the field operations aspect of an
ecological study, the major QC elements
are: instrument calibration and
maintenance, crew training and
evaluation, field equipment, sample
handling, and additional effort checks.
The potential errors in field operations
range from personnel deficiencies to
equipment problems. Field notes are
integral to the documentation of
12-8
Quality Assurance: Design, Precision and Management
-------
Figure 12-3
Six qualitative and
quantitative data
characteristics
usually employed
to describe data
quality.
Precision - The level of agreement among repeated
measurements ofthe same characteristic.
Accuracy - The level of agreement between the true and the
measured value, where the divergence between the two is
referred to as bias.
Representativeness - The degree to which the collected data
accurately reflect the true system or population.
Completeness - The amount of data collected compared to the
amount expected under ideal conditions.
Comparability - The degree to which data from one source can be
compared to other, similar sources.
Measurability- The degree to which measured data exceed the
detection limits ofthe analytical methodologies employed; often a
function ofthe sensitivity of instrumentation.
activities and can be a potential error
source if incorrect recording occurs.
Training is one of the most important
QC elements for field operations.
Establishment and maintenance of a
voucher specimen collection should be
considered for biological data.
Transcription errors during data entry
can be reduced with double data entry.
Table 12-3 gives examples of QC
elements for field and laboratory
activities.
12.3.2 Laboratory Operations
The QC elements in laboratory
operations include sorting and
verification, taxonomy, duplicate
processing, archival procedures,
training, and data handling. Potential
error sources associated with sample
processing are best controlled by staff
training. Controlling taxonomic error
requires well-trained staff with expertise
to verify identifications. Counting error
and sorting efficiency are usually the
most prominent error considerations;
they can be controlled by training and
by duplicate processing, sorting, and
verification procedures.
12.3.3 Data Analysis
Errors can occur if inappropriate
statistics are used to analyze the data.
Undetected errors in the data base or
programming can be disastrous to
interpretation. Problems in managing
the data base can occur if steps are not
taken to oversee the data handling,
analysis, and summarization. The use
of standardized computer software for
data base management and data
analysis can minimize errors associated
with tabulation and statistical analysis.
A final consideration is the possible
misinterpretation of the findings. These
potential errors are best controlled by
qualified staff and adequate training.
12.3.4 Reporting
QC in reporting includes training, peer
review, and the use of a technical editor
and standard formats. The use of
obscure language can often mislead the
reader. Peer review and review by a
technical editor are essential to the
development of a sound scientific
document.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
12-9
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Table 12-3 Example QC elements for field and laboratory activities
Project Activity
Field Sampling
Physical Habitat
Assessment
(Qualitative)
Physical Habitat
Assessment
(Quantitative)
Laboratory:
Sample Sorting
Laboratory:
Sample
Tracking
Laboratory:
Taxonomic
Identification
Data
Management
Data Analysis
QC Element
Replicated samples at 10% of
sites by same field crew.
Replicated samples at one to
two of total sites by different
field crew using same methods.
Ensure appropriate training and
experience of operators;
multiple observers.
Replicated measurements at
10% of sites.
Sample residue checked for
missed specimens to estimate
sorting efficiency; check
completed by separate lab staff.
Logbook with record of all
sample information.
Independent identification
and/or verification by specialist;
ensure appropriate and current
taxonomic literature available;
adequate training and
experience in invertebrate
identifications; reference
collection; exchange selected
samples/specimens between
taxonomists.
Proofreading; accuracy of
transcription.
Hand-check of reduced data.
Appropriate statistics; training.
Evaluation Mechanism
Calculate relative percent difference
(RPD) of index value or individual metric
score
Calculate RPDs as above; use to
evaluate consistency and bias.
Resume or other documentation of
experience; discuss and resolve
differences in interpretation.
Calculate RPDs between replicate
measurements; compare to
preestablished precision objectives.
Calculate percent recovery; compare to
preestablished goals.
Not applicable.
Calculate percent error; compare to
preestablished goals.
All transcribed data entries compared by
hand to previous form — handwritten raw
data, previously computer-generated
tables, or data reports.
For computer-assisted data reduction,
approximately 10% of reduced data
recalculated by hand from raw data to
ensure integrity of computer algorithm.
Review by statistician or personnel with
statistical training.
12-10
Quality Assurance: Design, Precision and Management
-------
Case Study: Optimization of Benthic Sampling Protocols: gear, mesh size,
replicates
Ferraro et al. (1994) studied the cost-effectiveness of several alternative marine
benthic sampling protocols, including sampling gear, mesh size (0.5-mm or 1.0-
mm), and number of replicates (1-10), in southern California waters. Alternative
sampling gear was:
• 0.1-m2 van Veen grab
• 0.06-m2 van Veen grab
• 0.1-m2 van Veen grab subsampled by 1-6 core samples, 50-300-cm2 total
area subsampled.
Laboratory processing time was recorded for each sampling alternative. Twelve
measures of community structure were examined. Results showed that the power
of detecting differences between sites did not increase greatly for more than 4
replicates. Optimum cost-effectiveness was achieved with 5 core subsamples
(250-cm2) of 0.1-m2 grabs, replicated 4 times at each site (Ferraro et al. 1994).
Case Study: Optimization of Benthic Sampling: Seasonal sampling, trend
detection
Alden et al. (1997) examined seasonal and annual trends in estuarine benthic
macroinvertebrates community measures (diversity, total abundance, biomass, %
opportunities). Samples were taken seasonally (4 x per year) from 16 Chesapeake
Bay sites for 9 years. Long-term trends were examined by season, and the power
of detecting trends was examined for alternative sampling frequencies of 1
season, 2 seasons, or 4 seasons per year. Finally, reference and impaired sites
were compared among seasons to determine if some seasons yield greater power
of detection of impairment than other seasons.
Trends in indicator values were apparent and detectable in all seasons. Although
4-season sampling yielded the greatest power of trend detection, it was only
marginally better than 2-season sampling and 1 season sampling. In general,
summer sampling was most sensitive and yielded the greatest power, allowing
detection of trends of 4%-7% change per year in abundance, diversity, and %
opportunist metrics over the 9 year period. Biomass was much more variable: the
minimum detectable trend was approximately 20% change per year for summer-
only sampling (Alden et al. 1997).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 12-11
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Chapter 13
Case Studies
In conjunction with the drafting of this
guidance manual, the USEPA Biocriteria
Program has also supported or assisted
in the support of projects around the
country to evaluate estuarine and
coastal marine survey methods and to
develop metrics appropriate for use in
different settings. These studies were
conducted prior to the creation of this
guidance document. Each case study
exemplifies a section within the
guidance. This chapter summarizes
studies conducted in the Pacific
Northwest, Gulf of Mexico, and along
the Middle and South Atlantic coasts.
Some of the material presented here also
appears in the body of this text and the
information which follows expands on
that discussion. Further, the principal
investigators or other contact in each
instance are listed with their addresses
and phone numbers should the reader
desire to comment or request more
information.
13.1 PugetSound -
Development of Trawl-
Based Tools For the
Assessment of Demersal
Fauna
(Macro!nvertebrates and
Fishes): A Puget Sound
Pilot Study
The relationship between pollution and
the health and status of marine benthos
are being studied in the Puget Sound
region of Washington state (Figure 13-1).
Detailed sediment data, including
information on chemistry, toxicity and
inf aunal populations, are being collected
for the Puget Sound Ambient
Monitoring Program (PSAMP) as well as
for various urban bay, dredge disposal,
and Superfund action programs. The
PSAMP has quantitatively defined
population patterns of demersal fishes,
but has not defined those patterns for
other demersal fauna such as
macroinvertebrates. Nor has any
program developed data to explain how
the fauna are responding to the
environmental stresses associated with a
contaminated substrate.
13.1.1 Study Objectives
The Puget Sound study (Eaton and
Dinnel 1993, Eaton 1994,1995) was
initiated in 1993 to document demersal
populations in their entirety, and to
attempt to relate the resulting biological
information to sediment chemistry,
toxicity, and infauna. The pilot study,
funded by USEPA, began by assessing
the utility of using two different trawls
to quantitatively define demersal
populations at a given point in time.
Using the resulting documented
population patterns and comparisons
between reference and contaminated
areas, the study objectives were
ultimately to:
*• Gain a greater understanding of how
demersal populations are being
affected by pollution and habitat
degradation;
*• Determine which patterns reflect
environmental stress;
*• Develop metrics (biological
measures) which would help to
build a biological index for the rapid
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-1
-------
Figure 13-1
General
location of the
case studies.
Delaware Bay
- Ocean City
North
Carolina
Indian River
and economical assessment of stress
in subtidal biotic marine
communities.
13.1.2 Study Methods
Beam and otter trawls were used to
sample Puget Sound demersal fauna in
1993 and 1994. A 3-m beam trawl (with
a tickler chain attached in front of the
net) towed at 1.5 knots proved to be
very effective for sampling most
demersal invertebrates and small or
juvenile fishes. A 7.6-m Southern
California Coastal Water Research
Project otter trawl, towed at 2.5 knots,
was best suited for sampling larger and
more mobile marine fishes and
invertebrates. All trawl catches were
held in tubs of running seawater
following capture, and fauna were
subsequently sorted, identified,
counted, measured and weighed. All
organisms were released on station.
In the first year of the pilot study (1993)
sampling focused on two of the Tacoma
Waterways, the contaminated Hylebos
Waterway (a Superfund site) and the
adjacent, less-impacted Blair Waterway.
Sampling in 1994 compared another
Tacoma Waterway and Superfund site,
Thea Foss (City) Waterway, with a
cleaner and more natural reference
condition (six miles to the north) in
Quartermaster Harbor on Vashon
Island. Bottom depth, sediment grain-
size analysis (either historical
information or wet-sieving technique for
percent fines), bottom temperature, and
salinity data were recorded for all
stations to insure meaningful pairing of
sites.
Spatial coverage of the study area was
determined using a stratified random
design. The Hylebos and Blair
Waterways were divided into four
strata, the Thea Foss into three strata,
and Quartermaster Harbor into two.
One station was located in each stratum,
except in mid-Quartermaster Harbor
with two stations one being an
historical sediment monitoring station.
A second station was placed in the mid-
Quartermaster Harbor stratum to
compare the variability in results
between two stations of close proximity
with similar depth and sediment grain-
size.
Evaluation of ten consecutive and seven
non-consecutive otter trawl replications
in 1993 led to the conclusion that four or
five otter trawl replications were needed
to quantitatively define the demersal
fish community at a given station, and
that the replications should not recur in
13-2
Case Studies
-------
less than four hours. The 1994 sampling
design incorporated these
recommendations, utilizing a sampling
effort of five otter trawl and three beam
trawl replications per station.
The extensive data set resulting from the
trawl surveys was entered into
computer spreadsheets as catch files,
and was sorted and statistically
analyzed for patterns and relationships.
The null hypothesis for the pilot study
was that the contaminated and non-
contaminated sites were not
significantly different for the parameters
measured (i.e., fish abundance, biomass,
mean individual weights, diversity and
evenness). Data comparisons were
tested for statistical significance using
either a parametric test (i.e., Student's
two-tailed, two-sample t-test either
paired or independent) or a non-
parametric test (i.e., two-sample
Kolmogorov-Smirnov Test) depending
on the outcome of the test for normality
(i.e., one-sample Kolmogorov-Smirnov
normality test). Species diversity was
calculated using the Shannon-Wiener
Index (H') with the natural logarithm,
although simple species richness
measurements proved to be more
statistically significant. Species
evenness was measured with Pielou's
evenness index (J) and number of
species >90% of total abundance.
Dominance was measured using the
dominance ratio, Nmax / N, where Nmax =
number of individuals of the most
abundant species, and N is the total
catch.
13.1.3 Study Results
Pilot study results focused on a
comparison of the reference and
contaminated stations which showed
the best match of environmental
parameters. Reference station QMH1 in
upper Quartermaster Harbor and
contaminated station TF1 in the upper
end of the Thea Foss Waterway proved
to be very similar in depth, sediment
grain size, bottom temperature and
salinity. A comparison of catch data for
the two stations indicated that fish
abundance in the reference area was
actually lower compared to that found
at the contaminated Superfund site
(Figure 13-2a), whereas fish biomass was
significantly greater at the reference site
(Figure 13-2b). This finding indicated
that the individual fishes at the reference
site must be considerably larger than
those found at the contaminated site,
and/ or that sensitive fish species found
at the reference site but not at the
contaminated site tended to be much
larger than the other fish. Both factors
contributed to the differences. Eight of
the thirteen fish and invertebrate species
common to both sites showed
significantly greater mean individual
weights at the reference stations, and of
the remaining five, only one species was
consistently larger at the contaminated
sites (Figure 13-2c). Also the
cartilaginous fishes (i.e. spiny dogfish,
spotted ratfish, and the skates),
tentatively classified as sensitive species,
were only rarely encountered in the
contaminated waterways and were very
large compared to the bony fishes.
A preliminary list of tolerant and
sensitive fish and invertebrate species
was generated for the Tacoma
waterways and Quartermaster Harbor
fauna based on the pilot study results
(Table 13-1). Tolerant species were
defined as those whose relative
abundance at contaminated sites is
significantly greater than or
indistinguishable from those species
found at comparable reference sites (i.e.,
site of comparable depth, salinity,
dissolved oxygen, sediment grain-size,
slope, and density of structures such as
eel grass). Sensitive (intolerant) species,
on the other hand, were defined as those
species whose relative abundance is
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-3
-------
Figure 13-2a
Bony fish
abundance
and total fish
abundance for
reference and
contaminated
sites.
Bony Fish Abundance and Total Fish Abundance for Reference
(QMH) and Contaminated (TF) Sites
25.0
D Bony Fish (Osteichthyes)
Abundance
H Bony plus Cartilaginous
Fish Abundance
0.0
QMH QMH QMH QMH QMH
1.1 1.2 1.3 1.4 1.5
REFERENCE
Station and Replication
TF
1-3 1.4 1.5
CONTAMINATED
Figure 13-2b
Bony fish
biomass and
total fish
biomass for
reference and
contaminated
sites.
Bony Fish Biomass and Total Fish Biomass for Reference (QMH)
and Contaminated (TF) Sites
D Bony Fish (Osteichtheys)
Biomass
D Bony plus Cartilaginous Fish
Biomass
0.0
QMH QMH QMH QMH QMH
1-1 1.2 1.3 1.4 1.5
TF
1.1
REFERENCE
Station and Replication
TF TF TF
1-2 1.3 1.4
CONTAMINATED
13-4
Case Studies
-------
Mean Individual Weights of Fish Species from Contaminated (TF) and
Reference (QMH) Stations
0.40-
0.35-
^ 0.30-
£ 0.25-
D)
| 0.20-
§, 0.15-
5
SJ 0.10-
0.05-
0.00-
^--"
^-'
,^^"
^-'
_-^-
^-^
^"
.,...-£
^
rV
D Contaminated Stations (TF)
D Reference Stations (QMH)
3^
a_
=a-
1
hi
1
I
i
fli S O T3 ° O
a. •§ E TJ w w
ai ^ i_ TO w) o
c .y HI w =j o
5 aJ
-
pi
N3
L_
3
1 *
S f^
<{
ft
oi a* o) ' c '
? 5 I |
° c 1 "
£,<"—£
Figure 13-2c
Mean
individual
weights offish
species from
contaminated
and reference
stations.
significantly greater from a reference
area than from a comparable
contaminated site.
The sensitive species index, derived
from the proportion of sensitive species
abundance or biomass to the total of
sensitive plus tolerant species, was
applied to the pilot study catch data.
Index results showed significant
differences for all comparisons (i.e., fish
abundance and biomass, and fish plus
invertebrate abundance and biomass
between contaminated and reference
sites). The results suggested that such
an index, if tested independently for
annual and seasonal variation, could be
very useful in tracking recovery of an
area after cleanup or remediation, or to
help classify impacted sites relative to
the benchmarks established through the
biocriteria.
Pilot study results also indicated that
fish species richness and fish species
evenness were useful measurements in
the site discrimination process.
Although no difference was found in
species richness using the beam trawl
sampling method, otter trawl catches
indicated that fish species richness was
notably greater at the reference site (16
species) than at the contaminated station
(11 species). When statistically
examined on a trawl-by-trawl basis (i.e.,
using the mean number of fish species
per sample), fish species richness was
significantly greater at the reference
stations. Fish species evenness, as
measured by the number of fish species
>90% of total abundance, was also
significantly higher at the reference
stations, both when paired with the
Thea Foss stations, and when compared
as a whole. External abnormalities or
anomalies, such as fin erosion or skin
tumors, were extremely rare at all
stations during both study years,
thereby suggesting that it may not be a
useful indicator of environmental stress.
The results of the first year of sampling
indicated that raw or averaged
abundance data were not useful in
differentiating contaminated and
reference sites. This discovery led to an
increased effort in recording biomass
data during the second study year, and
to the inclusion of a more natural
reference condition. Results of the
second year of sampling emphasized the
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-5
-------
Table 13-1. A preliminary list of tolerant and sensitive fish and invertebrate species from the Tacoma
Waterways and Quartermaster Harbor.
FISH
Tolerant Species
English sole
Sand sole
Flathead sole
Pacific tomcod
Shiner surfperch
Snake prickleback
Pacific staghorn sculpin
Sensitive Species
Spiny dogfish
Spotted ratfish
Longnose skate
Rock sole
Starry flounder
Speckled sanddab
Pile surfperch
Striped surfperch
Bay goby
Blackbelly eelpout
Bay pipefish
Plainfin midshipman
INVERTEBRATE
Pandalus danae: coonstripe shrimp
Crangon spp.: sand shrimp
Cancer gracilis'. purple cancer crab
Cancer productus: red rock crab
Cancer magister. Dungeness crab
Lophopanopeus bellus'. crab
Evasterias troschelli'. mottled seastar
Metridium senile', plume anemone
Cucumaria miniata: sea cucumber
Cucumaria piperata: spotted sea
cucumber
Pentamera populifera'. crescent sea
cucumber
Parastichopus californica: edible sea
cucumber
So/aster stimpsoni'. sunstar
Pagurus spp.'. hermit crabs
Nassarius mendicus'. snail
ecologically important fact that the
reference sites, despite fewer or equal
numbers of fishes, supported more than
twice the fish biomass than the
contaminated site. Almost every fish
species common to both areas was
significantly larger, and fish species
richness and evenness were significantly
higher at the reference site.
The sensitive species index proved to be
useful in differentiating sites. The
identification of sensitive (intolerant)
and tolerant demersal marine species is
in its infancy, due in part to the paucity
of data on demersal marine
communities and the lack of
quantitative sampling methods. With
the development of these sampling
techniques, the pilot study
demonstrated that information on the
demersal fauna should be included in
any future ecologically-based indexes of
pollution. Candidate attributes of
demersal fauna which warrant further
study are listed in Table 13-2.
Primary Contact: Charles Eaton
Bio-Marine Sciences
2717 3rd Ave. N
Seattle, WA 98109
206-282-4945
13-6
Case Studies
-------
Table 13-2. Candidate attributes of demersal fauna showing significant differences in the present study.
Candidate Metrics
Total Fish Abundance per
100 m2, 4-6 m. Depth.
(10-15 m. — no difference).
Total Fish Biomass per 100
m2
Fish Species Richness
(Number of fish species)
Fish Species Evenness
(Number of Fish Species >
90% of Total Abundance)
Mean Individual Weight
and Size of all Species
(except Pacific Herring and
Staghorn Sculpin)
Tolerant Species
Abundance and Biomass
(English Sole, Pacific
Staghorn Sculpin, Pacific
Tomcod, Shiner Surfperch,
Snake Prickleback, Purple
Crab, Mottled Seastar, Plum
Anemone)
Sensitive Species
Abundance and Biomass
(Bay Goby, Starry Flounder,
Rock Sole, Cartilaginous
Fish, Sea Cucumbers)
Sensitive Species Index
(proportion of sensitive to
sensitive + tolerant)
Preliminary
Expectation
from Present
Study:
IMPAIRED SITE
Elevated or no
difference
Reduced
Reduced
Reduced
Reduced
Elevated or (in
some cases) no
difference
Reduced
Reduced
Range of Values (and
mean) from Present
Pilot Study: IMPAIRED
SITE: Thea Foss Wty.
TF 1: 20.6 to 22.7
mean = 21.4
0.54 to 0.97 kg (mean =
0.73)
per tow: 6-13
cumulative:10-14
3-6 (mean = 3.7)
e.g. English Sole 45 to
114 g (mean = 75 g.)
e.g. English Sole
2.8-10.1 (5.3) per 100m2
e.g. juv. Tomcod
0.39 to 9.87 (7.3)
e.g. Purple Crab
4.7 to 56.0 (22.8)
e.g. Bay Goby 0.4 to 3.9
(1.7) per 100m2
e.g. Cucumaria piperata
Zero
0.016 to 0.098 mean =
0.049
Range of Values (and
mean) from Present
Pilot Study:
REFERENCE SITE:
QM Hbr.
QMH 1:
8. 3 to 14.2
mean = 11.9
0.81 to 4.82 kg (mean =
2.64)
per tow: 11-18
cumulative: 15-1 8
4-7 (mean = 5.2)
e.g. English Sole 125 to
484 g. (mean=204 g.)
e.g. English Sole 0.2 to
6.1 (2.3) per 100m2
e.g. juv. Tomcod 0 to
0.69(0.4)
e.g. Purple Crab 0.0 to
6.3(2.7)
e.g. Bay Goby 28.6-
41. 9 (36.5) per 100m2
e.g. Cucumaria piperata
0.0to5.9(2.5)
0.075 to 0.787 mean =
0.357
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-7
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13-8 Case Studies
-------
13.2 Galveston Bay -
Development of a
Rapid Bioassessment
Method and Index of
Biotic Integrity For
Coastal Environments:
Northwestern Gulf of
Mexico Pilot Studies
13.2.1 Study Objectives
A study was conducted on selected
streams and bayous within Galveston
Bay, Texas (Figure 13-1) coastal
ecosystems, in order to characterize the
expected fish assemblages of various
types of waterbodies (with varying
water and habitat quality) (Guillen
1995a). A second study objective was to
develop a prototype rapid
bioassessment technique similar to the
Index of Biotic Integrity for the
northwestern Gulf of Mexico. In order
to meet the second objective, several
criteria for the development of the
method had to be met. First, the method
had to be ecologically relevant, that is
any metric or ranking system had to
directly relate to ecological function and
structure. Secondly, the method had to
be taxonomically simple or kept to the
broadest taxonomic/functional group of
organisms that provide the most
information. The methods also had to
be simple (in terms of equipment, labor,
and analysis) cost effective, easily
standardized, subject to easy replication,
and adaptable to a variety of
environments.
13.2.2 Study Methods
The sampling design consisted of five
bayous classified according to the
potential for anthropogenic impact; i.e.,
urban versus rural, impaired versus
unimpaired and salinity effects; i.e.,
lower portions of tributaries versus
upper portions. Oyster Bayou,
Dickinson Bayou, Texas City Hurricane
Canal, Highland Bayou Diversionary
Canal, and Cedar Lakes Creek were
selected to fulfill these criteria. Oyster
Bayou is a minimally impaired coastal
bayou located in the middle portion of
Galveston Bay and flowing south to East
Bay. Oyster Bayou stations were
characterized by a silty clay substrate.
The moderately impaired Dickinson
Bayou is located in the northeastern
portion of Galveston County. Dickinson
Bayou is characterized by sandy to silty
clay substrates and is impaired by both
point and nonpoint sources. The Texas
City Hurricane Canal is an industrial
canal that flows into the Texas City ship
channel, and receives industrial and
stormwater discharges. The majority of
the canal banks possess a steep slope,
and little bank vegetation, and the
southern shoreline is an artificial levee.
The Highland Bayou Diversionary
Canal is an artificial waterbody created
by the Army Corps of Engineers in 1983.
The canal was created by channelization
of the upper reach of Highland Bayou
proper and construction of an earthen
dam directly below the channelized
portion, in order to reroute water
through a dredged canal into Jones Bay.
The canal is tidally influenced and
receives effluent discharge from
municipal wastewater treatment plants
and runoff from surrounding
agricultural grazing and pasture lands.
Cedar Lake Creek is a minimally
impaired rural bayou which extends 24-
miles from its origin at the intersection
of Cedar Lakes to the Gulf Intracoastal
Canal. There are no active discharges in
the watershed, however, an oilfield is
present at its upper reaches.
Predominant land use in the area is
cattle grazing and the San Bernard
Wildlife Refuge.
To summarize, two minimally impaired
bayous (Oyster Bayou and Cedar Lakes
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-9
-------
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
13-10
Case Studies
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"shad"; i.e., clupeids and engraulids,
proportion of total catch as poeciliids;
proportion of total catch as Penaeid
shrimp; and proportion of total catch as
palaemonid shrimp; i.e., grass shrimp.
The rationale for each proposed metric is
provided in Table 13-3.
Trawl, seine, and gill net results were
utilized in a cluster analysis, and then
subjected to stepwise discriminant
analyses. Observed seasonal and spatial
patterns and/or temperature and
salinity related correlations were used to
determine whether seasonal or salinity-
adjusted metrics were needed. In
addition, the decision to include data
from "impaired" sites in the derivation
of metrics was also evaluated using
these analyses. If initial statistical
analyses failed to show differences
between the reference sites and
impaired sites, then all sites were pooled
for derivation of metrics.
Due to the strong seasonal and/or
spatial trends observed in various
metrics using the seine data, cumulative
percent distributions of each candidate
metric were calculated by season for
minimally impaired watersheds.
Results of the distributions are
presented in Table 13-4. Metrics were
adjusted where distributions indicated
truncated values using the following
approach. If the distribution line could
be extended to the 15th or 85th percentile
value without crossing the Y axis, then
that estimated value was used. If it
could not, the metric was not used
during that season and/or the metric
rating was adjusted to reflect only two
conditions (e.g., normal and excellent).
This same procedure was used to derive
a proposed metric system using trawl
data (Table 13-5). A proposed list of
prototype metrics using gillnet catch
data was developed (Table 13-6);
however, since gillnet design and
deployment is variable, it may be
difficult to compare metrics derived
from the pilot study with other studies.
Pilot study results indicated that it
seems feasible that a prototype estuarine
bioassessment system based on nekton
community collections can be used to
successfully document impacts from
pollution. Analysis of potential metrics
through discriminant analysis, graphical
evaluation of cumulative distribution,
frequencies and correlation analyses
yielded the proposed metrics listed in
Tables 13-4,13-5 and 13-6. The
categories utilized in the framework of
the proposed system were based on the
following protocol. Depending on the
metric, those values less than the 15th
percentile were categorized as "concern".
The interquartile values; i.e., 15-85'h
percentile were categorized as "normal",
and values exceeding the 85th percentile
were classified as "excellent". In some
cases where high metric values denoted
degraded conditions, the inverse of the
proposed scheme was used; i.e., <15'h
percentile = "excellent". The
classification system was based
primarily on statistical distributions of
the observed data. Where data was
insufficient, a "not recommended"
disclaimer was listed.
It was difficult to single out one water
quality variable as having the most
influence on community structure and
the proposed metrics. Therefore, a
conservative approach was taken by
grouping by season and utilizing all
data across various salinity levels.
The proposed Index of Biotic Integrity
(IBI) metrics derived from the pilot
study would be most confidently
applied to situations where salinities
range from 1-25-ppt. Continued
calibration of this system with
additional data sets is needed. The
proposed metrics need to be evaluated
against independent data sets including
those in high (>25-ppt) salinity regimes.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-11
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Table 13-3. Rationale for the inclusion of proposed nekton community metrics.
Metric
Rationale
Total Catch
Total abundance is a rough measure of the total community
population and as such gives no information on individual species
population levels. Low abundances can be caused by various
stressors. It should be noted that high abundances caused by
individual opportunistic species can also indicate a disturbed
community.
Log Total Catch
Due to the inherent variability of populations, the patchiness of fish
schools and previously observed distributions offish, many
ecologists feel that the log-normal distribution fits the distribution of
nekton populations better. Therefore log total catch may be a more
appropriate indicator of total population levels. In order to handle
zero catches, however, a log (catch + 1) transformation is needed.
Total Number of Nekton Taxa
The species richness of any community is extremely important.
Reductions in species number may indicate an overall reduction in
available habitat or the presence of environmental stressors. This
may be due to the avoidance or death of sensitive species in an
area. The number of taxa collected is a relatively economical
measure. On a relative scale it is the cheapest information
obtainable from catch data.
Cumulative Number of
Nekton Taxa
The cumulative number of taxa is somewhat different than the total
number of taxa in that it reflects the upper limit of the number of
taxa one would expect to collect within a single replicate sample.
Large discrepancies between mean and cumulative number of
species may indicate high variability in habitat or distribution of
species. Like the total number of taxa metric a low cumulative
number of taxa can reflect limited habitat and/or the presence of
environmental stressors.
Total Number of Fish Taxa
This metric is closely related to total nekton species numbers.
However, it was added to address situations where only fish data is
tabulated.
Nekton Species Diversity
The Shannon-Wiener diversity function was selected to evaluate
nekton communities. This commonly used function (H')was
developed to incorporate the two most important components of
diversity, namely richness and evenness. Species richness is
normally tabulated. However, species richness alone provides no
information on how evenly individuals are distributed among
species. The majority of communities studied by ecologists show a
log-normal pattern of species abundance in which a relatively few
species possess a rather large number of individuals and a rather
large number of species possess few numbers of individuals. A
diverse community is one in which species number and evenness
are maximized. One problem with the use of H' is the fact that
various combinations of species numbers and evenness can yield
the same answer. Therefore diversity indexes should only be
evaluated in the presence of species richness and evenness.
13-12
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Table 13-3 (Cont'd). Rationale forthe inclusion of proposed nekton community metrics.
METRIC
RATIONALE
Nekton Evenness
One factor that influences diversity directly is the evenness of the
distribution of organisms between species. Populations possessing
high numbers of taxa but with highly uneven distributions between
taxa (e.g. highly dominant taxa) may reflect underlying habitat
limitations, stressors or seasonal patterns. One of the most
popular indexes used by marine biologists is the Pielou's evenness
index (J). This index is defined as:
J = H'/ln(S),
where H' is the Shannon-Weiner index,
In is the log base (e)
and S is equal to number of taxa
This index expresses H' relative to the maximum value that H' can
obtain when all of the species in the sample are perfectly even with
one individual per species.
Number of Nekton Taxa =
90% Catch
This index is the number of taxa that together add up to at least or
exceed 90% of the total catch. This is another measure of
evenness. High values would indicate a community in which there
is no clear dominant taxa. This index is influenced by the same
factors which effect the evenness index.
Nekton Dominance Ratio
This has also been referred to as the Berger-Parker index. This is
the ratio Nmax/N, where Nmax = number of individuals present in the
most abundant taxa, and N is the total catch. This equation is
computationally simple and can be easily programmed into
spreadsheets. In addition, it is intuitively easy to understand. High
dominance reactions reflects dominance of the community by a few
individuals which relates to an uneven distribution of individuals
within taxa resulting in poor diversity. This may be related to
potential stressors and other factors cited under the discussion of
Pielou's evenness.
Number of Crustacean
Nekton Taxa
The number of crustacean taxa present in the nekton is largely a
function of 4 principle groups. The first group are crab species
including blue crab, Callinectes sapidus. The second group
includes seasonally dominant groups of Penaeid shrimp which
migrate into tidal creeks and bayous as postlarva and juveniles.
The third group includes resident species of grass shrimp, genus
Palaemonetes. The final group include freshwater prawns, genus
Macrobrachium, and crayfish genus Procambarus. The presence
of crustacean taxa indicates a healthy population of benthic
herbivores and omnivores which serve as the primary food source
for many estuarine fish. In addition, crustaceans are especially
sensitive to organic pesticides.
Number of Predatory Fish
Taxa
Predatory fish were defined as fish in the family Carangidae,
Scombridae, and the genera Paralichthys, Lepisosteus,
Micropterus, Cynoscion, Morone and the species Sciaenops
ocellatus, Synodus foetens and Elops saurus. These species
represent individuals at the top of the food chain. Impacts to other
species they depend on may reduce these predators indirectly. In
addition, through the process of biomagnification predators are
more likely to bioconcentrate high levels of pollutants found in the
lower portions of the food chain.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-13
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Table 13-3 (Cont'd). Rationale forthe inclusion of proposed nekton community metrics.
METRIC
RATIONALE
Number of "Minnow" Taxa
The number of "minnow" taxa include resident species of
Cyprinodontidae and Poeciliidae. These two groups of small fish
represent the majority of resident species inhabiting marsh and
shallow water environments. The majority of these species are not
normally found offshore or in deeper waters due to predation. A
high number of these taxa may reflect habitat suitability of a
particular location to resistant species. Since these species are
largely non-migratory, their presence or lack of may indicate long-
term environmental perturbation. In contrast, high populations of
these species may correlate the absence of larger predators and/or
the presence of marginal habitat unsuitable for other less tolerant
taxa.
Number of Goby Taxa
This is another group of resident taxa that are primarily carnivorous,
feeding on small invertebrates. In addition, gobies are extremely
territorial and tend to stay within a defined area. Most gobies are
benthic. Reduced numbers of gobies would indicate localized
impacts to habitat, water quality and secondary impacts on food
sources namely, epibenthic invertebrates.
Proportion of Nekton Catch
as Poeciliids
Poeciliids are a group offish that are generally extremely tolerant to
poor water quality. Notable examples include the mosquitofish
(Gambusia affinis) and molly (Poecilia latipinna). These two
species are often found in harsh habitats where few other species
live. In addition, they are typically found in areas (e.g., shallow
flats) which are difficult for predators to exploit. A predominance of
Poeciliids in shoreline communities can therefore indicate degraded
conditions and/or lack of predators.
Proportion of Nekton Catch
as Penaeid Shrimp
One of the most important species ecologically and commercially
are the Penaeid shrimp, including the estuarine white shrimp
Penaeus setiferus, the brown shrimp P. aztecus, and the less
abundant pink shrimp P. duorarum. Typically these species enter
the estuaries as postlarvae. With continued migration they reach
tidal creeks and bayous as juveniles and spend the early part of the
first year in these areas prior to migrating back to the ocean to
spawn.
The proportion of catch as Penaeid shrimp may be an excellent
ecological indicator. Penaeid shrimp can serve as a metric that
addresses the nursery functions of a waterbody. It is also a lower
food chain omnivore. Many species are dependent upon this
invertebrate for food. Therefore, reduced numbers of shrimp can
detrimentally effect the entire nekton community. In addition, since
it is an arthropod it may serve as an excellent indicator of
secondary impacts associated with pesticide use.
13-14
Case Studies
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Table 13-4. Proposed seine metrics for use in an estuarine IBI along Texas coast.
Metric
Summer
Value
Fall
Value
Winter
Value
Spring
Value
Score
Category A
(A) Total Catch
*(A) Log Catch
*Prop. Pen. Shrimp
<200
200-450
>450
<5
4.5-6.0
>6.0
<01
0.01-0.3
>0.3
<50
50-400
>400
<9
3.9-5.8
>5.8
<25
.25-.56
>56
NA
<900
>900
<4.2
4.2-6.4
>6.4
NA
NA
NA
NA
<700
>700
<1.5
1.5-6.3
>6.3
NA
<0.04
>0.04
1
2
3
1
2
3
1
2
3
Category B
(B) Prop. Shad
*(B) Prop. B. Anchovy
If Bay A. =0
then use 'Shad' metric
*Dominance Ratio
>0.83
NA
<0.83
>0.8
NA
<0.8
>0.88
0.44-0.88
<0.44
>.60
.04-.60
<0.04
>.52
.04-.52
<04
>.65
.40-.65
<.40
>59
NA
<.59
>.13
NA
<.13
>.82
.26-.82
<.26
>.78
NA
<.78
>.34
NA
<.34
>.78
.27-.78
<.27
1
2
3
1
2
3
1
2
3
Category C
*(C) Mean #Taxa
(C) Cum. #Taxa
(C) Mean #Fish Taxa
<6
6-11
>11
<10
10-19
>19
<3
3-7
>7
<6
6-10
>10
<6
6-11
>11
<3
3-7
>7
<6
6-10
>10
<11
11-18
>18
<3.5
3.5-7
>7
<5
5-10
>10
<11
11-19
>19
<4
4-8
>8
1
2
3
1
2
3
1
2
3
Total IBI Score
Concern
Normal
Excellent
5-7
8-12
13-15
5-7
8-12
13-15
4-5
6-10
11-12
7-9
10-12
13-15
Total IBI Score (WHEN INVERTS NOT USED)
Concern
Normal
Excellent
4-5
6-10
11-12
4-5
6-10
11-12
4-5
6-10
11-12
5-6
7-10
11-12
Recommended metric; if mean log total catch or total catch = 0, then score = high concern.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-15
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Table 13-5. Proposed trawl metrics for use in an estuarine IBI along Texas coast.
Metric
*Prop. Total Catch
as P. Shrimp
*Prop Total Catch
as Shad
Summer Value
*
<0.45
>0.45
>0.06
*
<0.06
Fall Value
<0.42
.42- .83
>0.83
>0.08
*
<0.08
Winter
Value
*
*
*
*
*
*
Spring
Value
*
<0.08
>0.08
>0.03
NA
<0.03
Score
1
2
3
1
2
3
Category A
*Mean # Nekton
Taxa
Mean # Fish Taxa
<1.8
1.8-9.3
>9.3
<2.2
2.2-6.3
>6.3
<4.3
4.3-9.9
>9.9
<4.2
4.2-6.6
>6.6
<4.4
4.4-8.8
>8.8
<2.1
2.1-6.8
>6.8
<4.1
4.1-7.7
>7.7
<1.6
1.6-4.9
>4.9
1
2
3
1
2
3
Total IBI Score
Concern
Normal
Excellent
4
5-8
9
3
4-8
9
1
2
3
4
5-8
9
NOTE: To avoid problems caused by division by zero use the following formulas: For shrimp and shad
proportions let metric value = taxa group catch/(total catch + 1). Alternately if any one replicate total
catch = 0, then an IBI score of 'concern' can be given.
NOTE: Avoidance of winter sampling is recommended due to lack of suitable metrics.
* Recommended metric; if mean log total catch or total catch = 0, then score = high
concern.
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Case Studies
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Table 13-6. Proposed gillnet metrics for use in estuarine IBI along Texas coast.
Metric
1) Total Nekton Catch
Assigned Metric Score
0
0
1
K26
2
26<47
3
>47
2) Category 2 (Pick 1 of the 2 Metrics Listed)
2a) Number of
Nekton Taxa
2b) H1
0
*
1<7
<1.25
7<8
1.25<1.85
>8
>1.85
3) Category 3 (Pick 1 of the 2 metrics listed)
3a) Evenness J
3b) Number of Taxa
= 90% Total
Nekton Catch
No. Crust. Spp.
4) No. Pred. Taxa
No. "Minnow" Taxa
5) No. Scaenids/B. Cat.
Taxa
Total IBI Score (SUM OF
ALLS METRIC
CATEGORIES)
Total IBI Rank
*
*
*
*
*
*
0
HIGH
CONCERN
<.58
<4
Not Recom.
0
Not Recom.
0
5-6
CONCERN
.58<.81
4<6
Not
Recom.
1
Not
Recom.
1-2
7-13
NORMAL
>.81
>6
Not Recom.
>1
Not Recom.
>2
14-15
EXCELLENT
Due to the lack of strong correlation
between the seine and trawl-derived
metrics, it is advisable that future
studies use both gear types. Since
gillnet derived metrics were least
sensitive to water quality fluctuation,
and gillnet use is labor intensive and
difficult to replicate, gillnetting is the
least favored approach for evaluating
nekton community health.
A fish health index (FHI) was tested
during the pilot study to evaluate its
utility in assessing impacts on
estuarine fish communities. The FHI
methods mirrored those used by the
Tennessee Valley Authority (Dycus
and Meinert 1993, Dycus 1995).
Further evaluation is needed to
determine the discriminatory power;
i.e., impaired versus unimpaired sites
of the index. Proposed FHI values for
Gulf Coast bioassessments are listed
in Table 13-7. The FHI proved to be
time and cost efficient, and yielded
information that was complementary
to the IBI.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-17
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Table 13-7. Proposed fish health index and condition factors for use in estuarine rapid
bioassessments of Texas Gulf coast tidal tributaries.
FISH HEALTH INDEX
Species
Blue Catfish FHI Score
Atlantic Croaker FHI
Score
Sea Catfish "Hardhead"
(least recommend) score
Spot FHI Score
AVERAGE SPECIES FHI
RANK
Total FHI Rank based on
average scores of single
species
Assigned FHI Rank
1
>70
>50
>30
>61
1-1.4
CONCERN
2
40-70
30-50
*
32-61
1.5-2.5
NORMAL
3
<40
<30
<30
<32
>2.6
EXCELLENT
CONDITION FACTOR
Species
Blue Catfish CF
Atlantic Croaker CF
See Catfish "Hardhead"
CF
SpotCF
AVERAGE SPECIES CF
RANK
Total CF Rank based on
average scores of single
species.
Assigned Condition Factor (CF) Rank
1
<.78
<1.02
<.82
<1.25
1-1.4
CONCERN
2
.78-.Q7
1.02-1.15
.82-1.10
1.25-1.44
1.5-2.5
NORMAL
3
>.97
>1.15
>1.10
>1.44
>2.6
EXCELLENT
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Case Studies
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The application of estuarine rapid
bioassessment techniques in studies of
Gulf of Mexico coastal environments
is warranted, based on results of the
pilot study. Several of the methods
tested in the study (including seine
and trawl based IBI and FHI) would
aid water quality and fisheries
scientists in their evaluation of water
and habitat quality impacts resulting
from human activity. The pilot
bioassessment methods meet the
requirements for inclusion in routine
monitoring programs including: low
cost, low effort, readily obtainable
equipment, relatively easy taxonomy,
and replication of effort which is
suitable for statistical analyses.
Primary Contact: George J. Guillen,
U.S. Fish & Wildlife Service
1655 Heindon Rd.
Arcata, CA 95521
707-825-5109
george_guillen@fws.gov
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance 13-19
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13-20 Case Studies
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13.3 Tarn pa Bay-
Development of a
Community-Based Metric
for Marine Benthos: A
Tampa Bay Pilot Study
13.3.1 Study Objectives
State biological criteria in Florida have
been set at a 25 % decrease in Shannon-
Wiener diversity of benthic communities
in test versus reference sites. Input data
have been the sum of three ponar grab
samples per site; however, evidence has
suggested that these methods and
criteria are not sensitive enough. Pilot
studies in the Tampa Bay area (Figure
13-1) have tested a process of classifying
organisms according to their sensitivity
or tolerance to pollution, and
developing an index (the Farrell
Epifaunal Index) value for test and
reference sites (Farrell 1993a). The pilot
study used biological data from areas
surrounding treatment plant outfalls in
the index calculations, in order to detect
differences between test and reference
sites that were not evident using the
state criterion of a 25 % decrease in
diversity.
13.3.2 Study Methods
Water quality and benthic data were
developed from a 1992 short-term study
of the effects of three small package
plants on the seagrass communities at
Fort Desoto Park in Tampa Bay, Florida.
Three control stations were located on
Joe Island on the southern shore of
Tampa Bay, and an additional station
was located on a small island adjacent to
Fort Desoto (that was presumably under
the potential influence of the farfield
effects). Two sampling sites were
located at each station, one on the
shoreline (end of pipe) and a second 50-
m offshore. Four petite ponar replicates
were collected at each site; however,
only three were analyzed for
macroinvertebrates. This process was
consistent with Florida's biological
integrity standard as defined in the
Florida Administrative Code. After the
ponar samples were collected,
macroinvertebrates were also sampled
at each location using a modified Renfro
Beam Trawl towed for a distance of 4-m.
The Renfro Beam Trawl is a conical net,
open at the large end, which is normally
towed over the surface of the substrate.
The net is maintained in an open
position by attaching it to a rigid pole or
beam. The body of the net is
constructed of nylon bolting cloth (50
openings/cm2, which tapers to a
plankton net fitted with a removable
bucket. The effective swath width of the
custom trawl used for the pilot study
was 1.25-m. By towing the net over a
uniform measured distance, the results
were comparative (semiqualitative) and
relative abundances of the various
species were maintained. The
standardized tow length of 4-m
effectively sampled approximately 5-m2
of bottom. Some advantages and
disadvantages of using the epibenthic
beam trawl are listed in Table 13-8.
In advocating the use of the beam trawl,
which predominantly samples the
epifaunal and facultative infaunal
communities, one basic assumption was
made. Provided that the recruitment
potential for the individual community
components existed, it was assumed that
within a given set of natural
environmental parameters an expected
community of organisms would inhabit
any predetermined environmental
segment. In estuaries and many other
marine environments, populations of
different species vary significantly over
the seasons and from year to year;
however, these variations follow
predictable patterns. In Florida,
numerical dominance may vary among
annual cycles; however, species
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-21
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Table 13-8. Advantages and disadvantages to using the epibenthic Renfro beam trawl for the
sampling of benthos.
ADVANTAGES
DISADVANTAGES
The epibenthic assemblage is very
sensitive to anthropogenic
stressors, and this method can be
used in both a nearfield and farfield
context with equal facility.
Since this method is limited to level
bottoms, the total number of
common species will be limited
(thereby greatly simplifying training).
[NOTE: Time required for analysis
of three ponar samples was
approximately 20-hours, whereas
the time required to analyze a pilot
study trawl sample was a little less
than 10-hours].
This method lends itself to
subsampling which will reduce
processing hours and increase cost-
effectiveness.
Once initial training is completed,
field efforts can be relatively rapid
and analytical time can be reduced.
Samples can be sorted qualitatively,
and a nonparametric analysis can
be applied to provide a method of
quick screening.
The method is restricted to level bottoms.
Hard substrates cobble, and emergent
vegetation tend to invalidate the method.
In areas of abundant seagrasses or
macroalgae beds, sample bulk can be a
hindrance and some rough field sorting
may be required.
The epifauna tend to be seasonally
abundant; therefore, this factor would
have to be calibrated into the method if
multi-seasonal sampling events are
utilized.
composition generally remains stable.
Benthic macroinvertebrates, in terms of
both density and diversity, reach their
peak in Florida during the late winter to
early spring (or earlier in the southern
part of the state). Population minima for
most species occur during the summer
months. While they are dramatic, these
seasonal cycles can be factored into
efforts to establish biocriteria. It is
important to consider seasonality
because the species which are most
sensitive to environmental stress are
those which tend to reach their
population peaks during periods when
water quality factors are both stable and
optimal.
The epifaunal and facultative infaunal
community was targeted for the pilot
study since components of the
community appear to be both persistent
and very sensitive to environmental
stress. Within estuaries and adjacent
near-shore areas, physiochemical
parameters (e.g., temperature, salinity,
dissolved oxygen) will vary significantly
over an annual cycle. Sessile and
relatively immobile organisms
(including most of the infaunal
components) have evolved either
mechanisms which allow them to
tolerate these varying conditions, or
breeding cycles which allow them to
avoid periods of high stress. The more
motile members of the community
(including the epifauna and facultative
13-22
Case Studies
-------
inf auna) have the option of avoidance.
During periods of stress, these
organisms can move to deeper water or
to other areas where stressors are
mollified, and then return when
conditions improve. When an area is
being affected by relatively low levels of
anthropogenic stress, only the most
sensitive members of the benthic
community will respond, and these are
found among the epifaunal and
facultative infaunal components. It is
apparent that a method which is truly
sensitive to low levels of pollution must
target these components of the benthic
community, thereby advocating their
use in the Tampa Bay pilot study.
13.3.3 Study Results
A bioassessment approach should be
able to not only detect low levels of
environmental stress, but it should also
be able to detect those stress factors at
the earliest possible stages. One
approach which has been used
successfully in freshwater environments
has involved the assignment of the
specific index values to various
community components; i.e., species,
and basing community assessment on
the mean index value derived from
sampling that community (Lenat 1993).
The Farrell Epifaunal Index proposed in
the Tampa Bay pilot study was
specifically developed for the west coast
of Florida, but it should be useful in
adjacent areas. The index values
represented a somewhat subjective
evaluation of the relative tolerance or
intolerance to environmental stress. The
values were taken from an ongoing
effort to assign tolerance values to all
marine and estuarine
macroinvertebrates identified from the
coast of Florida. Information sources
have included agency monitoring data,
published records, gray literature, and
anecdotal information. Wherever
possible, all potential stressors including
sensitivity to toxic substances was taken
into account; however, the dominant
factor for most of the species was the
relative sensitivity to dissolved oxygen
depression. As a result, the Farrell
Epifaunal Index was probably most
sensitive to organic pollution and
eutrophication with associated wide
swings in dissolved oxygen.
The tolerance criteria for the index in
terms of dissolved oxygen requirements
were as follows:
0 Insufficient data to make an
evaluation.
1 Very tolerant. The identified
species can withstand short
periods of anoxia.
2 Tolerant. The identified
species can withstand brief
excursions to 1.0-1.5 rngL"1.
3 Slightly tolerant - slightly
sensitive. The identified
species can withstand brief
excursions to 2.5-3.0 rngL"1.
4 Sensitive. The identified
species can withstand brief
periods below 4.0 rngL"1.
5 Very sensitive. The identified
species are basically intolerant
of concentrations below 5.0
mgL"1; however, some species
may tolerate brief excursions
below this provided no other
stress factors are involved.
When the components from a sample
had been identified, the predetermined
tolerance values were assigned to the
various species, and a sample Farrell
Epifaunal Index value was calculated
using the formula:
Farrell Epifaunal Index = v— —
E N
where: n; = number of individuals of
species i;
I; = tolerance value for species i;
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-23
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N = total individuals from all
species used in the calculation.
In a strictly qualitative approach, an
index value may be calculated using the
formula:
Farrell Epifaunal Index (Qualitative) =
where: Is = index value for component
species s;
Ns = number of species used in
the calculation.
Pilot study calculations of Farrell
Epifaunal Index values required that the
appropriate tolerance value (0-5) be
assigned to individual taxa in each
sample. The values were then added,
and the summation was divided by the
total number of taxa utilized from the
sample. Taxa with a value of zero were
omitted from calculations. Pilot study
results (Table 13-9) indicated that the
index had been successful at detecting
differences between test and reference
sites. The resulting Farrell Epifaunal
Index will not meet all needs, and is not
the only metric that could be applied to
beam trawl or similar samples; however,
pilot study results indicate that at a
minimum it should prove to be an
effective screening method.
Primary Contact: Steven Kent, FLDEP,
3319 Maguire Blvd.
Orlando, FL 32803
407-894-7555, ext. 2227
kent_sl@orll.dep.state.fl.us
Table 13-9. Farrell epifaunal index results for the Fort Desoto Park-Tampa Bay Pilot Study.
BEAM TRAWL SAMPLE RESULTS
Stations
Number of Taxa
Index Total
Index
Sources
4
8
15
1.88
6
13
27
2.08
5
16
35
2.19
Controls
7
29
69
2.38
2
27
72
2.67
1
31
84
2.71
3
38
106
2.79
13-24
Case Studies
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13.4 North Carolina -
Comparison of Biological
Metrics Derived From
Ponar, Epibenthic Trawl,
and Sweep Net Samples:
A North Carolina Pilot
Study
13.4.1 Study Objectives
A test was designed to compare
biological metrics derived from three
sampling methods, to determine which
methods and metrics best demonstrated
differences between sampling sites
(Eaton 1994).
Test data consisted of benthic
assemblage collection results for petite
ponar, epibenthic trawl and sweep net
samples taken in the vicinity of
Wilmington, North Carolina (Figure 13-
1). The data set included February and
May 1993 ponar samples, November
1993 trawl and sweep net samples, and
February 1994 samples using each of the
three collection methods.
13.4.2 Study Location
Three sampling sites were located in
polyhaline (>20-ppt) waters in the
Wilmington vicinity. Howe Creek, a
primary nursery area north of
Wilmington, was selected as a reference
site. Development in the Howe Creek
area was sparse residential on the north
side of the creek with a new
development on the south side. Samples
were collected on the north side of the
creek, which placed a large saltmarsh
between the collection site and the
development to reduce possible impacts.
The Howe Creek sampling location was
characterized by sand and shell
substrata, abundant sponge and oyster
populations, and seasonally abundant
macroalgae (Ectocarpus and Cladophora).
A second sampling station (Hewletts
Creek) was chosen as a test site for the
assessment of nonpoint impacts.
Hewletts Creek receives runoff from
central Wilmington. It has occasionally
received pump station overflows, and its
shoreline is heavily developed with
single family residences. The large
quantities of macroalgae (Enteromorpha,
Ectocarpus, and Porphyra) that have been
flushed out of the creek could indicate
potential excess nutrients. The Hewletts
Creek station was characterized by hard-
packed medium sand and shell
substrates, intertidal oyster bars and
saltmarsh.
A sampling station located in Bradley
Creek was selected as a representative
impaired area. Most of this watershed
has been heavily developed, and the
lower portion of the creek supports two
marinas. Sampling was conducted just
upstream from one large marina and
immediately downstream from the U.S.
Route 76 bridge. The Bradley Creek
station was characterized by mud and
muddy sand substrate, intertidal oyster
bars, and seasonally common
macroalgae (Ectocarpus).
13.4.3 Study Methods
Three types of gear were employed to
sample the benthic assemblages at each
station. A petite ponar was used to
collect three replicates of 1-3 grabs each
(depending on faunal density), thereby
sampling the infauna in a 0.04-0.13-m2
area at each station. An epibenthic trawl
(1.25-m net mouth) was pulled over 4-m
of unvegetated substrate to collect the
epifauna and obligate infauna in a 5-m2
area at each station. This method is
further described in Section 9.5. A D-
frame net was swept through all
available habitats for 10-minutes,
collecting the epifauna and shallow
infauna in a 20- to 60-m2 area.
Advantages and disadvantages noted
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-25
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for each collection method are listed in
Table 13-10.
All samples were preserved in the field
with 10% formalin with Rose Bengal dye
added as a tissue stain. Samples were
returned to the laboratory, where they
were sorted from the detritus, then
identified to the lowest practical
taxonomic level (usually species).
Biological metrics taken from a wide
variety of sources were tested for each
sampling method. It was expected that
different metrics would prove useful for
different sampling methods. Test
Table 13-10. Advantages and disadvantages noted for the three benthic assemblage collection
methods.
METHOD
ADVANTAGES
DISADVANTAGES
Petite Ponar
can be used in any depth water
on almost all substrates (except
hard bottoms).
most previous researchers used
dredges, therefore some
comparisons with historic data
can be made.
true replication allows for
statistical treatment of the data.
it samples a relatively small
area, therefore rare and/or
large taxa may not be
collected.
the infauna are the most
tolerant portion of the
benthic community,
therefore minor stresses
may be easily missed.
sorting through large
amounts of sediment and
counting hundreds of
individuals of one or two
taxa can become tedious.
Epibenthic
Trawl
epifauna are generally more
intolerant to stresses than
infauna, therefore more subtle
environmental changes can be
detected than with infaunal
sampling.
a larger area is sampled than
with dredges, therefore more
rare taxa should be collected.
when operated properly, a
relatively small amount of
sediment is collected, therefore
sorting is not tedious.
results are not comparable
with most historic
databases.
the trawl is fairly unwieldy
and takes training to use
properly.
it is impractical to use in
depths beyond 5-1 0 m or in
strong currents (>1.5-2
m/s).
Timed Sweep
a large number of taxa are
collected including rare, large
and intolerant taxa.
since metrics are more reliable
when calculated with increasing
observations (taxa), change in a
metric is a more reliable indicator
of environmental change.
being semi-quantitative, only an
estimate of abundance is
required rather than having to
count each individual.
all habitats are sampled,
therefore loss or degradation of
habitat is more readily
documented.
method is limited to
wadeable areas.
large amounts of sediment
are usually collected,
making sorting tedious.
a higher degree of
taxonomic expertise is
required than needed for
the other methods.
results are not comparable
with most historic
databases.
13-26
Case Studies
-------
metrics included: Farrell Biotic Index
(modified for North Carolina), number
of amphipods and caridian shrimp, total
taxa, percent annelid abundance,
percent mollusc abundance, Shannon-
Wiener diversity index, amphipod
abundance, polychaete abundance,
molluscan abundance, gastropod
abundance, bivalve abundance,
capitellid polychaete abundance,
spionid polychaete abundance,
Hurlbert's PIE, Keefe's TU, Simpson's D,
and oligochaete and pelecypod
abundance (Engle et al. 1994; Farrell,
1993b, Nelson 1990, Washington 1984,
Weisberg et al. 1993). All metrics were
tested using the data generated from
each of the three collecting methods. A
metric was deemed to work if it was
able to correctly rank the stations; i.e., as
reference, slightly impaired, or heavily
impaired. Those metrics that correctly
ranked the stations were further tested
on a larger database to determine if
metric ranking was a spurious
coincidence or was due to the
measurement of a consistent component
of the biological community.
13.4.4 Results
Metrics that correctly ranked the three
sites and their values, are listed in Table
13-11 by sampling method. The Biotic
Index was the only metric to correctly
rank the sites; i.e., as reference, slightly
impaired, or impaired for each of the
three collection methods. For samples
collected by petite ponar, the Biotic
Index correctly ranked the sites for the
two February samples, but failed to
correctly rank the sites in May. This
may be related to seasonal fluctuations
in recruitment (Holland 1985). The
Biotic Index as a function of salinity at
38 sites sampled via petite ponar is
presented in Figure 13-3. Diamonds
represent reference sites, triangles
represent impacted sites and squares
represent areas of intermediate or
unknown water quality. Lines in the
figure represent possible break points
for future criteria.
Two metrics, Biotic Index (BI) and %
Oligochaete and Pelecypod abundance
(% O&P), correctly ranked the three sites
sampled using an epibenthic trawl
(Table 13-11). In February, but not in
May, the %O&P was low because two
taxa made up 70% of the individuals at
this site. This heavy skewness in
abundance may be due to seasonal
recruitment. To date, these samples are
the only collections made using the
modified trawl. More samples are
required to adequately test the efficacy
of the trawl.
The sweep method had three metrics
that ranked the three sites correctly
(Table 13-11): Biotic Index (BI), Total
Taxa (TT), and Amphipod and Caridean
Shrimp Taxa (A&C). Graphs of BI, TT,
and A&C values for 63 timed sweep
samples over a range of salinities are
presented in Figure 13-4. Each metric
appeared, in varying degrees, to be
affected by salinity. At sites where
salinities were above 8-ppt, there was
sufficient separation between Reference
sites (diamonds) and Impacted
(triangles) sites to identify sites with
Intermediate impact (squares) as well.
This separation was smaller in
intermediate salinities (8-20-ppt) than
higher salinities (>20-ppt). Samples
collected below 8-ppt salinity showed a
limited range of metric values. Only BI
was able to separate Reference from
Impacted sites in these low salinities.
The Total Taxa metric may be related to
the habitat diversity of an area; a
diversity of habitats at a site would
include more niches, thus allowing the
survival of more taxa. This suggests that
the Total Taxa metric could serve as a
habitat quality measure as well as a
measure of water quality.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-27
-------
Table 13-11. Functional metrics for the three benthic assemblage collection methods.
Howe Creek
(Reference Station)
Hewletts Creek
(Nonpoint Source
Impact Station)
Bradley Creek (Urban
Impact Station)
Petite Ponar
Date
Biotic Index
2/93 5/93 2/94 5/94
2.7 2.1 2.1 1.9
2/93 5/93 2/94 5/94
2.0 1.6 2.2 1.9
2/93 5/93 5/94 5/94
1.6 1.9 1.8 1.4
Epibenthic Trawl
Date
Biotic Index
% Oligochaeta &
Pelecypoda
Abundance
— — 2/94
5/94
— — 2.5 2.8
— — 21 3
11/93 — 2/94 5/94
2.8 — 2.4 2.7
27 — 31 6
— 2/94 5/94 —
— 1.7 2.0 —
— 37 4 —
Timed Sweep
Date
Biotic Index
Total taxa
Amphipoda &
Caridean shrimp
— — 2/94 5/94
— — 2.4 2.5
— — 109 95
— — 17 22
11/93 — 2/94 5/94
2.2 — 2.2 2.0
94 — 91 105
9 — 9 15
11/93 2/94 5/94 —
1.8 1.8 1.9 —
45 60 68 —
7 7 9 —
Figure 13-3
Ponar samples:
biotic index vs.
salinity
3 n
1 <^
X 2'b
0)
1 2
« i *,
o 1'5
m 1 .
Oc
P
• • *
• IA •
onar Biotic I
* h'-t
"•• i •
•
•
ndices
> •
•
• Bl Reference
• Bl Unknown
A Bl Impacted
*
0 10 20 30 40
Salinity
13-28
Case Studies
-------
Biotic Index
4
x J-b '
HI
1 3 -
•- oc
3 2-5-
<" ,
1 5
i 1
XX IX
x VH xx
2 v t n
"•" xxx A
X A
•«*„ ,i i
[t^-T ¥
•" *: .
A ^ A
» Bl Reference
• Bl Intermediate
A Bl Impacted
x Bl Unknown
0 10 20 30 40
Salinity
Figure 13-4
Bl, total taxa and
amphipod and
caridean taxa by
salinity.
Sweep Total Taxa
X
re 100 -
° 60 -
40 -
20 -
* >*SXx%x
^
I
1 i i3
7 *
^ x "
*
! . *
. ,'. «• .
* — «-li if *
/ " • •
XA
A
A X
1 T T Reference
• TTIntermediate
ATT Impacted
XTT Unknown
0 10 20 30 40
Salinity
Amphpod & Caridean Shrimp Taxa
35
X
re 25
l_ 20
O 15 -
08 I0
< 10
5
0 -
i *****]
•
• .' •
• ,
. •"
A A * *
• A
» A&C Reference
• A&C Intermediate
A A&C Impacted
x A&C Unknown
0 10 20 30 40
Salinity
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-29
-------
Amphipods and caridean shrimp
make up 10-15% of the total taxa at a
site. This correlation explains why the
graphs of the TT and A&C metrics
look similar. Since the Crustacea
include many of the most intolerant
taxa in the estuary, the A&C metric
may prove to be more sensitive to
slight differences in water quality
than the other metrics tested. One
potential problem with the A&C
metric is that it, like TT, appears to be
affected by habitat quality, especially
the presence or absence of seagrass
and shells.
The next step, following method
selection and metric determination,
was biocriteria development. In this
exercise, sweep samples at sites above
8-ppt were used because multiple
metrics had been identified which
showed a range of water qualities.
For each metric, a value above the
Reference/Intermediate line (Figure
13-4) was scored five points whereas a
value below the Intermediate/
Impacted line was scored 1. To
increase sensitivity, the Intermediate
Impact area was subdivided: values
in the upper 20 % were scored 4 points,
values in the middle 60% were scored
3 points, and values in the lower 20%
were scored 2 points. Points for each
of the three metrics were summed,
giving each site a total score between
3 and 15 points. Water quality
bioclassifications were assigned based
on the number of points scored by a
site (Figure 13-5).
An attempt was made, in step three of
biocriteria assignment, to address
natural situations where Taxa
Richness was depressed at a site (little
habitat diversity, wide salinity
swings, or high wave action). If one
or more of these situations could be
identified for a site, an extra two
points were awarded to the total
score. While this appears to
adequately correct a previously
unaddressed problem in biocriteria
development, assessment of the
usefulness of this approach must
await a validation study, which is
beyond the scope of the exercise
described here.
13.4.5 Summary
Test results indicated that there was
no metric which consistently ranked
the test stations in a priori order of
impact based on petite ponar
collections, though this may have
been due to confounding by a spring
peak in recruitment. The Biotic Index
ranked sites correctly most often.
Epibenthic trawl results correctly
ranked the test sites using the Biotic
Index and percent abundance of
Oligochaeta and Pelecypoda metrics.
Further sampling with the epibenthic
trawl is required to determine
whether it or the ponar will give more
reliable results in non-wadable areas.
The sweep method appeared to be the
most versatile of the three test
methods, resulting in three metrics
that correctly ranked the test sites. All
metrics appeared to lose sensitivity at
salinities below 20-ppt. Possible
seasonal effects and differences in
substrate appeared to be confounding
the analyses as well; therefore, these
factors must be taken into account
during the biocriteria development
process. The Biotic Index appeared to
be the most versatile tool since it was
the only metric to correctly rank sites
for all methods and all salinities.
Initial efforts at biocriteria
development in North Carolina will
focus on the Biotic Index as well as on
further sampling to determine the
effects of seasonality, substrate,
salinity, and habitat variables.
13-30
Case Studies
-------
Figure 13-5
Development of
biocriteria.
STEP 1: Assign points for each of three metrics from a sweep sample.
Polyhaline (2 1 ppt to seawater)
Points 54321
BI > 2.6 2.59-2.5 2.49-2.01 2.0-1.91 < 1.9
Total Taxa > 95 94 - 86 85 - 69 68-60 < 60
Amphipods& > 21 20-18 17-13 12-10 9-0
Caridean Shrimp
Mesohaline (8 ppt to 20 ppt)
Points 54321
BI > 2.2 2.2-2.16 2.15-1.96 1.95-1.9 <1
Total Taxa > 38 37-32 31-24 23-18 17-
Amphipods & > 8 7 6-5 4 3 -
Caridean Shrimp
STEP 2: Sum points. This will yield a number between 3 and 15.
STEP 3 : Check for Bonus Point conditions. Add 2 points to score if one or more
of the following conditions occurred: 1) Homogeneous habitat, 2) consistently high
wave action, 3) very high (>26 ppt/yr) salinity fluctuations.
STEP 4: Assign Bioclassification.
Bioclassification Points
No Impact 13-15
Slight Impact 11-12
Moderate Impact 8-10
Elevated Impact 6-7
Severe Impact 3-5
9
0
0
Primary Contact: Larry Eaton,
NC Division of Water Quality,
4401 Reedy Creek Road
Raleigh, NC 27602
919-733-6946
lawrence@dem.ehnr.state.nc.us
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-31
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13-32 Case Studies
-------
13.5 Indian River, Florida -
Field Verification of
Marine Metrics Developed
For Benthic Habitats:
Indian River Lagoon,
Florida Pilot Studies
13.5.1 Study Objectives
A research program was developed for
Florida estuaries to promote the
identification of benthic marine
parameters indicative of relative water
resource quality (Nelson et al. 1993,
Nelson and Spoon 1994 a, b). The
development of these parameters or
metrics was ultimately intended to help
quantify the diverse attributes and
interrelationships of the community to:
enhance documentation of possible
resource impairment from point and
non-point sources; evaluate aquatic life
use attainment; and to be incorporated
in the biological criteria process.
13.5.2 Study Methods
The process of developing benthic biota
community parameters (or metrics)
indicative of Florida estuarine resource
quality was initiated in 1993 with Indian
River Lagoon pilot studies (Figure 13-1).
The initial study involved the collection
and analysis of samples taken from six
stations, including two within the main
Indian River Lagoon and four at the
mouth of tributaries. Benthic samples
were collected by a diver using 8.2-cm
diameter Lexan cores which were
sectioned into 0-5-cm and 5-15-cm depth
fractions. Study sites were selected with
the primary criterion of a presumed
difference in pollution impact, with
secondary emphasis on similarity of
sediment type and tertiary emphasis on
similarity in salinity. Three sites were
designated impaired and three were
designated low impairment sites. The
small scale or smaller number of stations
limited the bottom salinity types
sampled to mesohaline, polyhaline, and
euhaline locations.
The nature of pollution impacts in the
Indian River Lagoon presented a major
problem in sample selection. Maximum
impacts of pollution input (primarily
from urban runoff) are felt within the
small lagoonal tributaries as compared
to the lagoon proper. Non-impaired
tributary sites are generally not
available, which forces most reference
sites to be in the lagoon proper. This
sometimes resulted in a difference in
salinity between the impaired and non-
impaired sites. For example, during
winter sampling, mean salinity at
impaired sites was 13-ppt (mesohaline),
and was 25.3-ppt (euhaline) at non-
impaired sites. However, these spatial
salinity differences appeared to be
seasonal in the lagoon. Samples taken in
June had a mean bottom salinity of 25.3-
ppt (euhaline) at impaired sites
compared to 29.6-ppt (euhaline) at non-
impaired sites.
13.5.3 Study Results
The benthic data were summarized in
terms of: the mean percent of biomass
contained in the top five centimeters of
the sediment profile at each of the
stations; and the mean weight per
individual compared among sites and
between the 0-5-cm and 5-15-cm depth
segments. There was no clear difference
in mean percent biomass (contained in
the top 5-cm) between the two sets; i.e.,
impaired, non-impaired of sites. There
was also no clear difference in mean
weight per individual based on
presumed differences in pollution
impact either for the surface sediments
or for the deeper sediments. Biomass
differences with differing salinities also
showed no clear differences, in that
mean values of the percent total biomass
above 5-cm ranged from 68% to 89% in
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-33
-------
mesohaline areas, and 69% to 81% in
euhaline areas. The value in the single
polyhaline area was 94%.
Sediment types within the study area
were classified as sand (>70% sand),
mixed (30-70% sand), and mud (<30%
sand). Both the impaired and non-
impaired sites had all sediment types
represented. There were no apparent
trends in biomass data among the
sediment types. There was no
indication that sand sites had less
biomass in surface sediments than
mixed sediments, or that mean weight
per individual differed among sediment
types.
During the initial studies, benthic data
were also summarized in terms of total
individual and total species metrics.
The mean percentage of total
individuals present above 5-cm ranged
from 96 to 99.6% at the study sites. The
differences in this metric between sites
of different pollution impact was thus
very low; therefore, this metric did not
clearly distinguish Indian River Lagoon
sites. Mean percentage of species above
5-cm in the sediments was calculated
from the data by dividing the total
number of species in the 0-5-cm fraction
by the sum of this value plus the total
number of species recorded in the
5 -15-cm fraction for each site. There
was no clear separation between the
sites based on this metric.
The initial Indian River Lagoon pilot
study and previous studies of the area
have examined the following metrics:
*• Mean total number of individuals;
*• Mean total number of species;
*• Percentage of amphipods;
*• Percentage of spionids;
*• Spionidae/capitellidae ratio;
*• Apparent color RPD depth.
Of the seven metrics, separation
between impaired and low impairment
sites was good for mean number of
species, percentage of amphipods,
percentage of spionids, spionidae/
capitellidae ratio, and apparent color
RPD depth. The percentage amphipod,
percentage spionid, and
spionidae/capitellidae ratio metrics
require separation of individual
specimens which requires greater time
than simple counts of total individuals
or total biomass. However, these
metrics seemed to offer much greater
powers of resolution than measures of
total individuals or biomass.
Limitations on the generality of the
conclusions of the initial pilot study
were imposed by the limited number of
sampling sites (6) and by the fact that
samples were obtained at only one point
in time. Seasonal variation in benthic
systems can be substantial; therefore, it
was essential to verify the temporal
generality of initial conclusions.
Similarly, spatial variations in salinity
regime have been demonstrated to
influence metric values. Therefore,
more extensive spatial and temporal
sampling was warranted to verify the
utility of the proposed metrics. To
provide temporal verification of metrics,
the six sites originally sampled in
January 1993 were resampled, and two
new sites were added to the sampling
plan to represent additional spatial
coverage of the Indian River Lagoon.
The two additional sites were located
near Cocoa, Florida, with one presumed
to be an impaired; i.e., located near a
sewage outfall pipe, and the other a low
impairment site. Core samples were
collected by divers (as in the initial pilot
study) during June, July and August
1993. All organisms collected were
13-34
Case Studies
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subsequently identified to the lowest
feasible taxon, counted, oven dried, and
weighed in the laboratory. Surface
water temperatures and salinity, and
bottom salinity measurements were
made in the field, and sediment samples
were collected by skin diving. One of
the proposed metrics was to involve
visual determination of the apparent
color RPD depth. It was difficult to
measure a visual RPD with any degree
of confidence since the surface layers of
sediment were often flocculent and were
therefore disturbed by the coring
process. Attempts to measure the
apparent visual RPD were therefore
abandoned during the second phase of
pilot studies.
A total of 64 benthic cores and 128 core
fractions were collected and processed
during the second phase of pilot studies.
There was no clear distinction for the 0-
5-cm sediment fraction in mean number
of individuals per core recorded at low
impaired versus impaired stations.
Mean number of benthic taxa recorded
per core from the 0-5-cm fraction also
failed to show clear differences between
the two sets of stations. Clear
distinctions were observed, however,
between the impaired and low impaired
sites with respect to mean abundance
per core for benthic organisms in the 5-
15-cm fractions. Abundances in the 5-
15-cm fractions differed by a factor of at
least 4 between the two sets of stations;
i.e., mean equaled 0-1.3 at impact
stations and 5-10 at low impact stations.
Impaired and low impaired sites also
showed clear separation based on the
mean number of taxa per core in the 5 -
15-cm fraction.
The total species richness of amphipod
crustaceans was seven at both the
impaired and low impact sites, and the
species recorded were similar. The
metric based on the percentage
abundance of amphipod crustaceans;
i.e., percent of total, failed to clearly
distinguish the two types of sites.
Comparisons of amphipod total
abundance; i.e., amphipod total count,
also failed to clearly distinguish
impaired versus low impact sites,
ranging from 4-1789 at low impact sites
and 27-62 at impaired sites. The 1993
summer results contrast strongly with
the winter results for the amphipod
metrics. Winter data showed clear
separation of impact versus low impact
stations with respect to both percent
abundance and total number of
amphipods, whereas summer data did
not.
The ratio of spionid polychaete
abundance to capitellid polychaete
abundance showed only partial
separation between station types in the
summer samples. There was a
decreased degree of separation with this
metric in summer versus winter
samples. The differences in the ratio
were generated both by reduced
numbers of spionids and by increased
numbers of capitellid polychaetes at the
low impact sites for winter samples. In
contrast, differences in summer samples
for the low impact sites were mainly
caused by high values for capitellids.
Therefore, a total capitellid metric was
examined for both seasons. Clear
separation between impaired and low
impact sites was given for this metric for
both summer and winter data.
Examination of a total annelid
abundance metric also demonstrated
separation of impaired and low impact
sites (for summer data).
Total faunal biomass showed no
separation of stations for either the 0-5-
cm or 5-15-cm core fractions. Expression
of the biomass values above 5-cm were
modified by subtracting biomass for the
occurrence of a few large organisms
(e.g., large bivalves). The adjusted
surface biomass metric also failed to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-35
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clearly separate the impaired and low
impact sites.
Differences in the values of benthic
community parameters were apparent
in summer samples as compared to the
winter samples from the same study
sites. The seasonal changes in
abundance were anticipated given
previous knowledge of seasonal
abundance patterns of macrobenthos in
the Indian River Lagoon. Some
proposed metrics were consistent in
their performance in both winter and
summer samples (Table 13-12). Both
abundance and taxa richness in the deep
sediment fraction were metrics which
gave clear separation in the sets of
stations in both winter and summer.
Abundance of capitellids also
consistently separated the station types
during both seasons.
The performance of some of the metrics
which appeared promising in the winter
samples was somewhat altered in
summer. For example, taxa richness in
the 0-5-cm fraction, percent amphipod
abundance, total amphipod abundance,
and spionid/capitellid ratio metrics
discriminant stations in the winter, but
did not do so (or gave unclear results) in
the summer. Explanations for this
change in performance may be complex.
The biomass measurements used in the
pilot studies were made on specimens
separated into lowest identified
taxonomic units, which required
considerable time and effort. Had the
biomass measures provided clear
separation of station types, it would
have been warranted to suggest that all
specimens be pooled to obtain a single
biomass value. However, it did not
appear that biomass values for either
depth fraction were useful as a benthic
metric for the Indian River Lagoon.
The pilot study results clearly indicate
that the season during which sampling
takes place may influence the ability of a
given metric to distinguish among sites.
Overall, clearer separation was seen
among sets of stations for winter
sampling than for summer sampling.
This appeared to be related to the fact
that highest organism density in Indian
River Lagoon benthos is seen during late
winter, rather than in the summer as is
the case at other locales. This clearly
points out the need to evaluate
seasonality at specific geographic areas.
Relatively few of the proposed metrics
consistently separated sites in the Indian
River Lagoon. The mean abundance of
organisms and mean species richness in
the 5-15-cm depth fraction, and
capitellid abundance metrics all
provided consistent separation of station
types. The relatively small sample size
in terms of number of stations appeared
to result in ambiguous interpretation;
i.e., clear station separation ability in
winter and marginal in summer, for the
total amphipod abundance and
spionid/capitellid ratio metrics. The
natural temporal variability in the
benthos may be sufficiently extreme to
affect the performance of these metrics;
therefore, the best way to minimize the
influence of the variation may be to
sample as many stations as possible.
In the most recent phase of pilot studies,
two amphipod metrics - mean number
of amphipods per site and the ratio of
Corophiidae/(Ampeliscidae +
Phoxocephalidae) - were assessed at a
total of ten stations within the Indian
River Lagoon. The original eight pilot
sites were resampled and two additional
sites were sampled during May and
June 1994, using techniques as described
for the earlier pilot studies. A total of 80
benthic cores were collected and
processed.
13-36
Case Studies
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Table 13-12. Comparison between winter and summer samples of the ability of the various metrics
tested to discriminate between impaired and low impairment sites.
METRIC
0-5 cm abundance
5-15 cm abundance
0-5 cm taxa richness
5-15 cm taxa richness
percentage amphipods
total amphipod abundance
spionid/capitellid ratio
capitellid abundance
total annelid abundance
total biomass
total biomass (excluding large
bivalves)
mean percent biomass above
5 cm
WINTER
NO
YES
YES
YES
YES
YES
YES
YES
NO
NO
NO
SUMMER
NO
YES
NO
YES
NO
?
?
YES
YES
NO
?
NO
NOTE: ? indicates marginal utility of metric due to inconsistent discrimination of impaired
and low impairment sites.
Results of collection analyses showed
that the simplest amphipod metric,
mean total abundance, clearly separated
impaired from low impact sites in the
late winter samples taken in 1993.
However, summer 1993 and 1994 results
indicated that the response of this metric
was not satisfactory. Available water
quality information suggests a division
of the set of 10 stations into three
groups: high impact, moderate impact,
and low impact. Use of the mean
number of amphipod metric did not
provide a similar separation of sites for
summer 1994 sampling data. However,
the outcome of the Corophiidae/
Ampeliscidae metric calculations was
most consistent with the high impact,
moderate impact, low impact division of
sites, and therefore appeared to
reasonably reflect water quality
conditions of the Indian River Lagoon.
Primary Contact: Dr. Walter G. Nelson,
National Health & Environmental
Effects, Research Laboratory/ORD
Western Ecology Division,
Hatfield Marine Science Center
2111 SE Marine Science Dr.
Newport, OR 97365-5260
541-867-4041
Nelson. Walter@epa. gov
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-37
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13-38 Case Studies
-------
13.6 Ocean City, MD —
Bethany Beach, DE — A
Preliminary Study of the
Use of Marine Biocriteria
Survey Techniques to
Evaluate the Effects of
Ocean Sewage Outfalls in
the Mid-Atlantic Bight
13.6.1 Study Objectives
This project investigates the practical,
low cost application of marine biological
community measurements and the near
field/far field survey technique for use
by coastal States as a water resource
quality management tool. The methods
applied here are derived from work
reported by Pearson and Rosenberg
(1978) and Mearns and Word (1982)
with modifications.
13.6.2 Study Methods
The study area is a 16-km coastal reach
between Bethany Beach, Delaware and
Ocean City, Maryland (Figure 13-1,13-
6). These are nearly adjacent resort
communities on the Mid-Atlantic
seaboard between Delaware Bay and
Chesapeake Bay. Each has a secondary
treatment municipal sewage discharge
site about 2.8-km offshore. Discharge is
in both cases through a diffuser at a
water depth of approximately 12-m.
The Bethany Beach sewage treatment
plant average discharges about
O.ei-mY^ 14-mgd) and Ocean City
about 1.4-mY1 (32-mgd).
A series of nine north-south trending
stations were installed parallel to the
coast at intervals of about 2-km, each in
about 12-m depth of water and over
medium to fine sandy bottoms to obtain
a similarity of habitat as much as
possible. The stations are labeled "A"
through "I", with station "C" at the
Bethany Beach outfall and station "G" at
the Ocean City outfall (Figure 13-7).
This structure provides a set of control
or reference stations for comparison to
the test stations at "C" and "G". Each
station is located with differential GPS
with an estimated precision for the
receiver of +/- 5-m.
The variables measured are benthic fish
and macroinvertebrate communities as
reflected in indexes and metrics
incorporating number of taxa and
number of individuals per taxa. Fish
surveys are made with a 6-m (5-m
effective opening), 2.5-cm mesh otter
trawl. Tows are made parallel to the
shoreline at 1-ms"1 over 0.9-km with the
station coordinates located at the mid-
point of the tow. Trawl scope used is six
to one. Benthic macroinvertebrate
samples are collected with a 0.1-m2
Smith-Mclntyre grab or with a 0.1-m2
Young grab, and three replicates are
taken for each sample at each station site
as indicated by DGPS coordinates.
Ferraro et al. (1994) reviewed their
extensive data base and concluded that
five replicates with a 0.02-m2 petite
ponar grab, each sub-sampled with four
8-cm diameter cores is optimal for
waters of the Southern California Bight.
We elected to use the 0.1-m2 grab with
three replicates, but to count the entire
grab. This was judged to be a
reasonable compromise between more
replicates and the uncertainty of sub-
sampling a site for which there was
inadequate preliminary information.
From this data base we hope to make
further sampling refinements in the
future. Identifications of collected
organisms are to species whenever
possible. All survey work was
conducted from the USEPA Ocean
Survey Vessel Peter W. Anderson. The
Anderson is a 50-m research ship, but all
equipment used and methods employed
are appropriate for deployment from a
15-m vessel typically used by most
coastal States. Incidental to this project,
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-39
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Figure 13-6
Bethany
Beach - Ocean
City study
area.
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a comparison of the Smith-Mclntyre and
Young grabs was made. Six replicate
drops with each grab were made at
three sites characterized by: hard
packed fine sand; medium grain sand;
and coarse sand and gravel. Either gear
was judged acceptable, but the Young
grab was less inclined to wash.
I
Sampling surveys have been conducted
twice a year in July-September and
January-February since 1993 to
determine if multiple season indexing is
necessary or appropriate. While the
Mid-Atlantic area is considered to have
four discrete seasons, benthic
communities are expected to be in flux
13-40
Case Studies
-------
Figure 13-7
Bethany
Beach - Ocean
City sampling
locations.
FJ^Tfeil gl&lfMi'AJL'
BEACH)
,, «J
X
* *:-?«•> CMS?
during Spring and Fall and to be most
stable in Summer and Winter
(Ranasinghe et al. 1994).
Fish sample processing is conducted on
board with all individuals identified to
genus and usually to species. Length
measurements (TL) are made and any
gross anomalies recorded. The fish are
returned to the water as soon as
measurements are completed. Benthic
invertebrate sediment samples are
sieved on board using a 0.5-mm mesh
screen after recording a physical
description of the sample and taking a
2.5-cm diameter subcore for grain size
analysis. The retained material is fixed
in 10% buffered formaldehyde with
Rose Bengal dye added. Taxonomic
identifications and counts are made later
at laboratory facilities ashore with most
identifications carried to the species
level.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-41
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To make comparisons between the
sample sites, habitat control in the
survey design was maintained as well as
possible by attention to three major
variables:
1) Grain size of bottom sediments.
This also reflected a habitat
impact of the discharges when
fine sediments were deposited in
bottom depressions near the
outfalls. At the beginning of the
project, sediment samples were
collected from all nine stations
and analyzed for heavy metals
and a for a standard array of
toxicants. All results were
insignificant, suggesting no other
sources of biotoxicity or
impairment indigenous to the
immediate area.
2) Water depth. Water depth over
stations "A" through "E" ranges
from Tl-m to 14-m with the
variation accounted for by a
general ridge and swale
bathymetry off Bethany Beach.
From "E" through "I", the
variation is from 14- to 16-m,
accounted for by an east-west
ledge with about a 3-m drop just
south of the Ocean City outfall.
Subsequent data analyses
suggest that these variations in
water depth do not restrict fish
or invertebrate distributions over
the area.
3) Water quality. At the outset of
the study, and each time
biosurveys are conducted,
multiple depth and standard
water quality measurements are
made using a Sea-Bird SBE-9
"CTD" probe. Conductivity,
temperature, depth, dissolved
oxygen, pH, transmissivity, and
chlorinity/salinity are measured
and recorded throughout the
water column.
To date, these variables have been
consistent over the length of the transect
for each cruise.
In keeping with the objective of low
cost, practical applications of biological
community measurements for resource
impact detection; standard, basic but
robust taxonomic indexes were applied
to the data. The underlying premise for
the indexes is that once the raw data for
species and numbers of individuals per
species are compiled, the investigator's
primary question is whether or not there
is a detectible impact. More refined
indexes and indicators can later be
applied or developed as needed. In this
regard, the treatments selected for this
project were: total number of
individuals, total number of taxa
(species), evenness index, Simpson's
dominance index, Margalef's taxa
richness index, and Shannon-Wiener
index of general diversity. The
appropriate equations were taken from
Odum(1971).
13.6.3 Study Results
Fish Survey Data
Analysis of the fish data showed no
significant differences in trawl data
between the stations in either summer or
winter collections for either number of
taxa or numbers of individuals. These
results are based on single tows at each
station twice a year (summer and
winter) for three years. Concern that
this response results from too little data
led to a trial in summer 1995, with three
replicate trawl surveys over the nine
stations, i.e., sequential tows of stations
"A" through "I" conducted three times
in one day. The results were still
insignificant. Better results might be
possible by replicating each station
13-42
Case Studies
-------
individually. Eaton (1994) reported that
for West Coast fish surveys in a
Washington estuary, four replicate tows
per station are necessary to obtain
meaningful data within a fairly confined
waterway. Qualitatively, taxa and
number of individuals overall shifted
considerably between summer and
winter surveys at the nine stations.
Greater numbers of both species and
individuals (excepting winter runs of
striped anchovy, Anchoa hepsetus) occur
in the summer surveys.
Benthic Macroinvertebrate Data
Benthic macroinvertebrate results have
been much more promising, but the
same seasonal trend observed for fish
for number of taxa and number of
individuals has prevailed. Summer
measurements are much more indicative
of the condition of the benthic
macroinvertebrate assemblages (some of
the winter data is incomplete). The data
in this instance is for three replicates at
each station twice a year for three years.
Significant differences are evident
between each of the outfall sites and the
other stations in the summer data
(Figure 13-8a,b). The graphic data for
number of individuals is intriguing in
that it suggests enhanced and or
enriched conditions at station "A",
perhaps from the Delaware Bay
discharge, and at the Ocean City outfall
site.
When numbers of species are compared,
a more negative trend in outfall impact
is evident, especially for the Bethany
Beach outfall station (Figure 13-9a). A
similar pattern occurs at Ocean City, but
is not as strong (Figure 13-9b). Ludwig
and Reynolds (1988) state that a simple
count of the number of species present,
for samples of equal size, avoids some of
the problems of using indexes which
combine and may confound a number of
variables that characterize community
structure.
However, in this instance, it appears
that at least some indexes enhance the
measurement of outfall perturbations.
Box plots of Simpson's dominance index
(Figure 13-10a, b), the Shannon-Wiener
index of general diversity (Figure 13-
lla, b), and particularly Margalef's
richness index (Figure 13-12a, b) (Odum
1971), over the three years of summer
data provide strong indications of the
negative effect of both discharges on the
benthic macroinvertebrate community.
13.6.4 Discussion and Conclusions
The nearfield/farfield survey design for
biological surveys, together with basic
indexes of community structure, appears
to work equally well on the West coast
and in Mid-Atlantic coast open water
environments (Santangelo, pers. comm.
1996). If the investigator is careful to
control for habitat characteristics, the
ends of the transect can serve as a
reference condition, the outfall stations
as test sites, and the intermediate
stations provide an indication of the
gradation of impact(s). The nine station
design of this study made it possible to
treat the data as a combination of two
impact sites on the ambient
environment, or as two individual
studies in tandem.
Summer benthic macroinvertebrate data
from stations "A" and "C" were
significantly different in either case,
lending confidence to the conclusion
that the wastewater discharges were
having a measurable impact on the
coastal marine environment. This is of
particular interest because routine water
quality and sediment investigations at
the sites failed to consistently detect
change between the outfalls and the
surrounding stations. The biocriteria
technique employed appears to be not
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-43
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Figure 13-8a
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Total number
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individuals at
Ocean City
sites;
summer
data, n=9.
13-44
Case Studies
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Figure 13-9a
Total number
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invertebrate
taxa at
Bethany
Beach sites;
summer
data, n=9.
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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-45
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on
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Figure 13-10a
Simpson's
dominance index
for macroinverte-
brates at Bethany
Beach sites;
summer data,
n=9.
90
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Figure 13-10b
Simpson's
dominance index
for macroinverte-
brates at Ocean
City sites;
summer data,
n=9.
13-46
Case Studies
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Figure 13-11a
Shannon-Wiener
diversity index for
macro-
invertebrates at
Bethany Beach
sites; summer
data, n=9.
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Figure 13-11 b
Shannon-Wiener
diversity index for
macro-
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Ocean City sites;
summer data,
n=9.
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Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-47
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Figure 13-12a
Richness index
for macro-
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Bethany Beach
sites; summer
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Figure 13-12b
Richness index
for macro-
invertebrates at
Ocean City sites;
summer data,
n=9.
13-48
Case Studies
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only practical, but sensitive as well,
detecting impacts that might not
always be observed with routine
chemical testing. Standard indexes
such as Margalef's Richness Index,
Simpson's Dominance Index and
Shannon-Wiener's Diversity Index are
robust and were entirely appropriate
for this survey.
The Smith-Mclntyre and Young grabs
were both entirely adequate, but the
Young was more efficient and safer to
work with, while the Smith-Mclntyre
was more accessible through the top
for sub-sampling. Three replicate
grabs were sufficient to generate
meaningful data, but it may be
possible to reduce the costs of the
taxonomic operation by sub-sampling
the grabs. An attempt was made to do
this by mechanically splitting the
intact samples in half with a sheet
metal partition. It failed because the
surficial organisms were unequally
distributed as the sample drained and
the ship rolled. Subcores of 5-cm
diameter might be a better alternative
requiring far less analytical effort.
Similarly, sieving and counting only
the top 5-cm of the sample as a
variation of the technique reported by
Diaz in Gibson et al. (1993) might be a
more cost-effective approach.
Another alternative to reduce the
number of organisms dealt with is to
double the sieve size to 1.0-mm, as
practiced by many investigators. Any
of these options could be explored and
adopted as a cost-effective way to
accomplish the benthic macroinverte-
brate counts as long as the
investigator ascertains that they
produce reliable results consistent
with those derived from the larger
grab samples.
The 6-m otter trawl used in the fish
surveys performed well and is
believed to be appropriate for both
coastal and estuarine biosurveys.
However, the fish community does
not appear to be very responsive to
sewage discharge effects in this
coastal area. This is probably because
of the mobility of the fish in these
open coastal waters, their seasonal
migrations, and the potential sport
and commercial fishing pressure
confounding the survey effort; but the
sampling replication factor was not
adequately investigated in this study.
For biocriteria development and site
monitoring, it is important to account
for seasonality. For the Mid-Atlantic
Bight, late June to early September
appears to be a time of relatively high,
stable community productivity and an
optimal index period if once a year
sampling is preferred. According to
the Delaware and Maryland chambers
of commerce, since Bethany Beach and
Ocean City are summer resort
communities, their populations
increase at least ten-fold in warm
weather (pers. comm. 1990). Their
lower winter discharge rates, together
with a natural cyclic depletion of the
marine community, may account for
the failure of our data to reveal
sewage impacts in this season. This
may not be the case with a year-round
municipality of fairly large size. In
any case, if the responsible agency can
afford to sample at least occasionally
in winter, that baseline biological data
may prove invaluable in the event of
oil spills or other marine accidents.
After the assessment of results from
an initial set of 1.6-km interval station
transects, the investigator may choose
to delete some of the intermediate
reference stations and replace them
with a more diagnostic set of near
discharge monitoring stations. It will
then be possible to assess the relative
expansion or contraction of the area of
impact over time and in response to
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-49
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plant operation declines or
improvements. The initial and
subsequent reference site data become
part of the biocriteria which can be
used as a benchmark to assess
operational efficiencies, management
initiatives, and the adequacy of
NPDES permits.
Additional investigations for which
results are pending
1. Because vertical splitting of each
grab sample was determined to be an
unsatisfactory approach to reducing
sample volume and cost, we are
attempting to test a horizontal
approach at approximately the 5-cm
depth level because most of the
organisms observed are
predominantly surficial sediment
dwellers. In September 1996, the
stations were sampled with three
replicate grabs as before, but
approximately the top 5-cm of
sediment was scraped off of each
sample and sieved through a 0.5-mm
mesh screen. The remainder of the
sample was similarly processed. We
will count both fractions, combine the
results and evaluate as usual.
This information will then be
compared to a similar assessment
using just the top 5-cm fraction. If the
same impact information results, it
may be possible to monitor the
stations using just the surface
fractions as long as these results are
periodically calibrated against full
grab counts.
2. On the January, 1997 survey, all of
the stations sampled for benthic
macroinvertebrates were sieved first
through a 1.0-mm screen and then
through the 0.5-mm screen. These
separate fractions can be combined to
produce a comprehensive result. The
1.0-mm fraction can then be compared
to this control to assess the relative
efficacy of this technique as a cost
saving approach for these waters. The
process was repeated during the
summer of 1997 and the results of
both trials will be evaluated when
taxonomic studies, which were
delayed (for this and the above study)
are completed.
3. Because of the promising results of
this project so far, three additional
stations have been added around each
outfall station, e.g., "C" at Bethany
Beach and "C" at Ocean City. The
pattern creates a roughly equilateral
triangle with approximately 0.46-km
legs and a station at each apex with
the original station in the middle of
the triangle. The intent here is to see if
it is possible to refine the spatial
assessment of the zone of impact for
each outfall analogous to the concept
illustrated in Figure 13-13.
13.6.5 Use of the Bethany Beach-
Ocean City Data to
Illustrate Biocriteria
Development
An example of biocriteria
development using this pilot project is
as follows.
Classification and Reference Site
Selection: A review of the data as
presented in Figures 13-7 through 13-
12 suggests that stations A, E, and I
are appropriate reference sites being
at the center and extreme ends of the
transect and equidistant from the
defined locales of effluent discharges
being evaluated. General water
quality conditions, including salinity
and depth, are consistent for all
stations. Grain size, although shifting
from sand and gravel in the north at
station A to sand at station I in the
south represents the general benthic
habitat condition of the area with an
13-50
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Figure 13-13
Proposed
diagnostic
nearfield station
array.
net longshore current
discharge
• A
• B
D1»*C»D3
• D «D4
D2« 9 E» D5
• F
• G
#
Data can be used to plot not only
impact, but relative expansion or
contraction of the area of impact over
time.
A B CL
D
SERIES
-STATIONS—^
E F G
acceptable variation for the region.
Thus, the stations (or sites) are
considered to all be of comparable
habitat characteristics, and because of
the spatial arrangement, sites A, E,
and I are selected as references.
Reference Condition: The reference
condition may be derived from the
interquartile range of scores of the
values of the biotic condition
measured at the reference sites. Table
13-13 presents the range of those
values for the summer parameters
measured at each of the three
reference sites and the mean range of
those scores. The range was selected
over mean or median values to
accommodate the variability of the
biological data. This mean range is
the reference condition or minimally
impacted (by human activities, e.g.
sewage discharge, all other factors
being considered equal) condition for
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Table 13-13. Establishment of reference condition using the mean of the interquartile range of scores for three
reference sites.
Inter-quartile Range of Values
Station
A
E
I
Mean Score
Individuals
427-3049
281-474
136-841
281-1455
Taxa
46-71
40-49
27-42
38-54
Simpson's
Index
0.075-0.161
0.076-0.224
0.129-0.260
0.093-0.215
Shannon-
Wiener
2.597-3.137
2.262-3.889
1.993-2.524
2.284-3.183
Richness
7.3-9.1
6.6-8.0
5.3-6.0
6.4-7.7
this Maryland-Delaware reach of the
Mid-Atlantic Bight.
Biocriteria: The elements of a
biocriterion are: (1) historical
information about the area; (2) present
reference condition information; (3)
empirical modeling of data if needed;
and (4) an assessment of this
preceding information by a locally
familiar panel of specialists.
(1) There is insufficient local historical
information or data to establish a
trend against which the reference
condition data can be compared.
(2) The present reference condition
data is presented above.
(3) The indexes used to compile the
raw data constitute the only modeling
element since this is a site specific
assessment.
(4) The authors of this manual are
surrogates for a panel of local
specialists which would likely consist
of USEPA, US Fish and Wildlife
Service, NOAA, and State biologists
and water resource managers.
Consequently, the reference site data
and index scores presented here
essentially comprise by default, the
candidate biocriteria for the purposes
of this study. However, it is
important to note that the other
elements of development of a
biocriterion should not be casually
dismissed. While the reference
condition is essential, with a large
available historical database these
present values might well be adjusted
either up or down to accommodate
the historical trend for the area.
Assessment Comparing Biocriteria to
the Test Sites: The test sites at "C"
(Bethany Beach, DE outfall) and at
"C" (Ocean City, MD outfall) are then
compared to the biocriteria as
illustrated in Table 13-14.
Neither outfall site completely meets
the range of criteria derived from the
reference condition for any of the
metrics applied, although the Bethany
Beach outfall approximates the
criterion for number of taxa present.
It should be noted that the outlier at
reference station "A" (perhaps caused
by Delaware Bay enrichment) raises
this criterion range at the expense of
the Bethany Beach outfall. The Ocean
City outfall nearly fits the diversity
index criterion. However the outfall
far exceeds the number of individuals
category by more than three times the
criterion. This reflects several
instances when the benthic grab was
overwhelmed by polychaete worms, a
condition usually indicative of sewage
pollution.
13-52
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Table 13-14. Comparison of the reference condition derived biocriteria to the interquartile range of scores at the
Bethany Beach and Ocean City outfalls.
Variable
No. Indiv.
No. Taxa
Simps. Dom.
Shan.-Wien. Dl
Richness
Biocriteria
281-1455
=/>38-54
=/<0. 093-0. 215
=/>2.284-3.183
=/>6.4-7.7
Bethany Beach
Outfall
260-1988
28-43
0.171-0.642
0.970-2.648
4.6-5.8
Ocean City
Outfall
49-6,492
13-49
0.179-0.643
1.855-2.883
3.1-5.7
This instance of near exceedance of
one of the criteria in each case
illustrates the importance of using
several biological metrics to establish
a reference condition which best
represents a diverse and healthy
community, and which contributes to
more robust and sensitive biocriteria.
Conclusion: For a formal criteria
development program, more data are
required, but the indexes applied
appear to ably translate the data into
workable criteria. Ironically, the
number of individuals and number of
taxa metrics individually do not
reflect apparent conditions as well as
the indexes which combine these
primary variables.
Recommendations: The stations
should continue to be monitored by
USEPA Region in biologists and the
data set further developed. The long
term areal impact of the discharges
should be better assessed using the
additional near-discharge stations
described above. Changes in sieve
size and use of grab fractions, if
justified, will help reduce the cost of
the monitoring.
Eventually, as a further cost reduction
measure, it may be possible to
monitor just stations "A", "C", "E",
"G", and "I". However, periodically
the outfall stations should be
intensively monitored to determine if
the zones of impact are expanding or
contracting. The combined
information of criteria comparisons
and impact zone measurements
should provide valuable information
for NPDES permit evaluations at
Bethany Beach and Ocean City.
This technique and evaluation
approach may prove particularly
helpful as Eastern Seaboard
development continues to increase
and more coastal communities seek
ocean discharge permits for their
municipal effluents.
Primary Contact: George Gibson, Jr.
(4304), USEPA, Office of Water, Office
of Science and Technology
1200 Pennsylvania Avenue, NW
Washington, DC 20460
410-305-2618
gibson.george@epa.gov
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13-53
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13-54 Case Studies
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13.7 Environmental Quality
of Estuaries of the
Carolinian Province:
1995
13.7.1 Background/Objectives
A study was conducted to assess the
environmental condition of estuaries in
the EMAP Carolinian Province (Cape
Henry, VA - St. Lucie Inlet, FL; Figure
13-14). The objectives of this study are
being addressed using a probability-
based sampling design, under which a
large regionally extensive population of
randomly selected sites is sampled from
year to year, following earlier EMAP-E
designs (Strobel et al. 1994, Summers et
al. 1993). This design makes it possible
to produce unbiased estimates of the
percent area of degraded vs.
undegraded estuaries, based on a series
of indicators of environmental quality.
Overall, the objectives of the program
are to:
*• Assess the condition of estuarine
resources of the Carolinian Province
based on a variety of synoptically
measured indicators of
environmental quality;
*• Establish a baseline for evaluating
how the condition of these resources
are changing with time;
*• Develop and validate improved
methods for use in future coastal
monitoring and assessment efforts.
A total of 87 randomly located stations
were sampled from July 5 - September
14,1995 in accordance with the
probabilistic sampling design.
Wherever possible, synoptic measures
were made of: 1) general physical
habitat condition, 2) pollution exposure,
3) biotic conditions, and 4) aesthetic
quality. Percentages of degraded vs.
undegraded estuarine area were
compared to results of a related EMAP
survey conducted in 1994 in this same
region as part of a multi-year
monitoring effort.
13.7.2 Methods
An overall goal of EMAP is to make
statistically unbiased estimates of
ecological condition with known
confidence. To approach this goal, a
probabilistic sampling framework was
established among the overall
population of estuaries comprising the
Carolinian Province. Under this design,
each sampling point is a statistically
valid probability-based sample. Thus,
percentages of estuarine area with
values of selected indicators above or
below suggested environmental
guidelines can be estimated based on the
conditions observed at individual
sampling points. Statistical confidence
intervals around these estimates also can
be calculated. Moreover, these estimates
can be combined with those for other
regions that were sampled in a
consistent manner to yield national
estimates of estuarine condition. This
section describes in brief how stations
were selected using the probabilistic
design (see also Rathbun 1994).
Supplemental sites, selected non-
rand omly in clean areas and in
suspected polluted areas, were included
in the survey and are discussed below.
Sampling sites in 1995 consisted of 87
base stations and 21 supplemental
stations. Base stations were randomly
selected sites that made up the
probability-based monitoring design.
Four replicate bottom grabs were
collected from each station with a 0.04-
m2 young grab sampler. Data collected
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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Figure 13-14
1995 Carolinian
Province sampling
stations.
VA
NC
SC
GA
EMAP-E Carolinian Province
Sampling Stations
1995
\
FL
from these sites were used to produce
unbiased estimates of estuarine
condition throughout the province
based on the various synoptically
measured indicators of environmental
quality. The province-wide distribution
of base sites is shown in Figure 13-14.
Supplemental stations were selected
non-randomly in areas for which there
was some prior knowledge of the
ambient environmental conditions.
These sites, which represented both
pristine areas and places with histories
of anthropogenic disturbance, were used
to test the discriminatory power of
various ecological indicators included in
the program. Data from supplemental
sites were not included in the
probabilistic spatial estimates.
As in other EMAP-E provinces (Strobel
et al. 1994, Summers et al. 1993), the
sampling design for the base sites in the
Carolinian Province was stratified based
mainly on the physical dimensions of an
estuary. Table 13-15 breaks down the
estuarine resources of the Carolinian
Province by their size designation.
Stratification of the overall sampling
area into classes of estuaries with similar
attributes was necessary in order to
minimize within-class sampling
variability. Also, it was not feasible to
sample all of the different types of
estuaries that exist within a broad
geographic region at the same spatial
scale. Stratification by physical
dimensions of an estuary was adopted
because: 1) such attributes usually show
minimal change over extended periods;
2) alternative classification variables
such as salinity, sediment type, depth,
and extent of pollutant loadings would
result in the definition of classes for
which areal extents could vary widely
from year to year; 3) data for physically
based classes can be aggregated into
geographic units that are meaningful
13-56
Case Studies
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Table 13-15. Estuarine resources of the Carolinian Province.
All Years
Number of
Estuaries
Area
Represented
(km2)
In 1995
Number of
Stations
Area
Represented
(km2)
Province Large
Estuaries
200 3
11,622.1 5,581.1
88 16
6,991.8 4,480.0
Small
Estuaries
194
4,907
55a
1,377.8
Large Tidal
Rivers
3
1,134
17b
1,134
Station count includes 6 replicate stations
bStation count includes 3 replicate stations
from a regulatory or general-interest
perspective; and 4) estuarine boundaries
can be delineated more readily and
accurately from maps or charts of the
physical dimensions of coastal areas
than from maps of sediment or water-
column characteristics.
Selection of base-site sampling
approaches varied on the physical
characteristics of the particular estuary
being sampled. Base sites in all estuaries
were selected using an approach similar
to the one used in the EMAP
Louisianian Province (Summers et al.
1993). In large estuaries, sites were
selected using a sampling grid
approach. A triangular lattice was
placed initially over the study region
and the resulting grid shifted randomly.
In large tidal rivers, base sites were
selected randomly, using a "spine and
rib" approach. Finally, base sites in
small estuaries were selected using a
random list-frame approach, also similar
to the approach used in the EMAP
Louisianian Province (Summers et al.
1993). Table 13-16 lists the core
environmental indicators sampled at the
various sites.
A standard series of environmental
parameters was measured at each of the
base stations to provide a consistent set
of synoptic data for making province-
wide estimates of estuarine condition.
These "core" environmental indicators
included measures of general habitat
conditions, pollutant exposure, biotic
integrity, and aesthetic quality (Table 13-
16). Habitat indicators describe the
physical and chemical conditions of
sample sites, and provide basic
information about the overall
environmental setting. Exposure
indicators provide measures of the types
and amounts of pollutants, or other
adverse conditions, that could be
harmful to resident biota or human
health. Biotic condition indicators
provide measures of the status of
biological resources in response to the
surrounding environmental conditions.
Aesthetic indicators provide additional
measures of environmental quality from
a human perceptual perspective. There
is a fair amount of overlap among these
various indicator categories. For
example, some aesthetic indicators
(presence of oil sheens, noxious
sediment odors, and highly turbid
waters) could also reflect adverse
exposure conditions. Another example
is dissolved oxygen (DO), listed as an
exposure indicator because of the
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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Table 13-16. Core environmental indicators for the Carolinian Province.
Habitat Indicators
Water depth
Water temperature
Salinity
Density stratification of water column
Dissolved oxygen concentrations
PH
Percent silt-clay content of sediments
Percent TOC in sediments
Sediment acid-volatile sulfides (Yr. 2 only')
Exposure Indicators
Low dissolved oxygen conditions
Sediment contaminants
Contaminants in fishes and invertebrates (Yr. 2 only)
Sediment toxicity
Biotic Condition Indicators
Infaunal species composition
Infaunal species richness and diversity
Infaunal abundance
Benthic Infaunal Index
Demersal species composition (invertebrates and fish)
Demersal species richness and diversity
Demersal species abundance
Demersal species lengths
External pathological abnormalities in demersal biota
Aesthetic Indicators
Water clarity
Anthropogenic debris (sea surface and in trawls)
Noxious sediment odors (sulfides, petroleum)
Oil sheens (sea surface and bottom sediments)
"Results not shown in this report
potential adverse biological effects of
low oxygen concentrations, but which
also is clearly a measure of general
habitat conditions. These various core
environmental parameters included
ones used in other EMAP-E provinces
(Strobel et al. 1994, Summers et al. 1993)
to support regional comparisons and to
provide a means for producing
combined nationwide estimates of
estuarine condition.
In addition to making the standard
EMAP-E measurements, an emphasis
was placed on developing and
validating other complementary
methods to aid in evaluating the quality
of southeastern estuaries. Such
indicators, some still in the development
stage, are listed in Table 13-17. They
include sediment bioassays with
alternative test species, such as the
amphipod Ampelisca verrilli as an
alternative to A. abdita in standard 10-
day solid-phase toxicity tests; assays
with additional sublethal biological
endpoints, such as effects on feeding,
growth and fertilization success in key
estuarine organisms; additional indices
of environmental quality for tidal
marshes and estuarine fish assemblages;
and the incorporation of additional
exposure indicators, such as porewater
ammonia and hydrogen sulfide
concentrations, to help in the
13-58
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Table 13-17. Exposure indicators under development in the Carolinian Province.
10-day acute-toxicity sediment bioassay with alternative amphipod species, Ampelisca
verrilli
1-week sublethal bioassay for testing effects of sediment exposure on growth of juvenile
clams Mercenaria mercenaria
96-hour sublethal bioassay for testing effects of sediment exposure on feeding rates of
Ampelisca verrilli
1-hour sublethal bioassay using gametes of oysters Crassostrea virginica and clams
Mercenaria mercenaria for testing effects of sediment exposure on fertilization success
Sediment porewater ammonia and hydrogen sulfide concentrations
interpretation of sediment toxicity
results.
13.7.3 Benthic Infaunal Index
The modified IBI approach of Weisberg
et al. (1997) was used to develop a
benthic index for southeastern estuaries.
The goal was to develop an index that
possessed the following features: (1)
suitable for use throughout the region,
(2) applicable to a broad range of
habitats, (3) easy to understand and
interpret, and (4) effective in
discriminating between undisturbed
and disturbed conditions associated
with human influences.
Results of the 1994 survey (Hyland et al.
1996) indicated that several natural
abiotic factors (salinity, latitude, silt-
clay, and TOC) had strong influences on
infaunal variables. In the IBI approach,
an attempt is made to account for such
variations by defining habitat-specific
reference conditions at sites free of
anthropogenic stress and then
comparing conditions in samples with
the expected reference conditions for
similar habitat types. The basic steps
used to develop the index involved: (1)
defining major habitat types based on
classification analysis of benthic species
composition and evaluation of the
physical characteristics of the resulting
site groups; (2) selecting a development
data set representative of degraded and
undegraded sites in each habitat (3)
comparing various benthic attributes
between reference sites and degraded
sites for each of the major habitat types;
(4) selecting the benthic attributes that
best discriminated between reference
and degraded sites for inclusion in the
index; (5) establishing scoring criteria
(thresholds) for the selected attributes
based on the distribution of values at
reference sites; (6) constructing a
combined index value for any given
sample by assigning an individual score
for each attribute, based on the scoring
criteria, and then averaging the
individual scores; and (7) validating the
index with an independent data set.
Data from undegraded sites sampled in
1993 and 1994 were first analyzed using
classification (cluster) analysis of benthic
species composition and evaluation of
the physical factors associated with the
resulting station clusters to define major
habitat types. Several types of cluster
analyses were performed. The one that
produced the clearest results was a
normal (Q-mode) analysis run on loglO-
transformed data with flexible sorting as
the clustering method and Bray-Curtis
similarity as a resemblance measure (see
Boesch 1977).
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
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Differences in abiotic factors (salinity,
latitude, % silt-clay, TOC) among the
resulting station clusters were examined
by ANOVA and pair-wise multiple
comparison tests (Duncan's test and
Tukey's HSD) to help delineate the
major habitat types. Four site groups
resulted: oligohaline-mesohaline
stations (<8%) from all latitudes,
polyhaline-euhaline stations (>18%)
from northern latitudes (>34.5° N),
polyhaline-euhaline stations from
middle latitudes (30-34.5° N) and
polyhaline-euhaline stations from
southern latitudes (<30° N). Seventy-
five stations sampled during the 1994
survey were selected for the
development data set. These stations
provided data from both degraded and
undegraded sites in each of the four
habitats. Classification of stations into
degraded and undegraded categories
was based on the combination of
chemical and toxicological criteria,
mainly DO, and toxicity of sediment
bioassays. Marginal sites (minor
evidence of stress with toxicity in only
one assay and no accompanying adverse
contaminant or DO conditions) were not
included in the development data set.
Forty different infaunal attributes were
tested with the 1994 development data
set to determine those that best
discriminated between undegraded and
degraded sites within each habitat. This
initial list of attributes included various
measures of diversity, abundance,
dominance, and presence of indicator
species (e.g., pollution-sensitive vs.
pollution-tolerant species, surface vs.
subsurface feeders). A subset of six
candidate metrics was identified for
possible inclusion in the index. Key
criteria considered in the selection were
whether differences were in the right
direction and statistically significant
(based on results of Student t-tests,
Mann-Whitney LT-tests, and
Komogorov-Smirnov two-sample tests;
at a = 0.1). These six metrics were: mean
number of taxa, mean abundance (all
taxa), mean H' diversity, 100 - %
abundance of the two most numerically
dominant species, and two different
measures of % abundance of pollution-
sensitive taxa.
Scoring criteria for each of these metrics
were developed based on the
distribution of values at undegraded
sites: score of 1, if value of metric for
sample being evaluated was in the lower
10th percentile of corresponding
reference-site values; score of 3, if value
of metric for sample was in the lower
10lh-50'h percentile of reference-site
values; or score of 5, if value of metric
for sample was in the upper 50th
percentile of reference-site values.
Scoring criteria were determined
separately for each metric and habitat
type. A combined index value was then
computed for a sample by assigning a
score for each component metric (based
on the individual scoring criteria for the
corresponding habitat type) and then
averaging the individual scores. A
combined score < 3 suggested the
presence of a degraded benthic
assemblage (some apparent level of
stress to very unhealthy) given that its
condition, based on the averaged
metrics, deviated from conditions
typical of the "best" (upper 50th
percentile) reference sites.
Forty different combinations of the six
candidate benthic metrics were further
evaluated to determine which
represented the best combined index.
The metric combination that produced
the highest percentage of correct
classifications; i.e., agreement with
predictions of sediment bioeffects based
on the chemistry and toxicity data, was
then selected to represent the final
index. The resulting final index was the
average score of four metrics: (1) mean
abundance, (2) mean number of taxa, (3)
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Case Studies
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100 - % abundance of the top two
numerical dominants, and (4) %
abundance of pollution-sensitive taxa
(i.e., percent of total faunal abundance
represented by Ampeliscidae +
Haustoriidae + Hesionidae + Tellinidae
+ Lucinidae + Cirratulidae + Cyathura
polita + C. burbanki. The final combined
index correctly classified 93 % of the
stations province-wide in the
development data set and 75 % of the
stations in the independent validation
data set.
13.7.4 Results
The multimetric index of biotic integrity
index — consisting of measures of
abundance, number of species,
dominance, and relative abundance of
pollution-sensitive taxa — produced a
high percentage of correct station
classifications; i.e., agreement with
predictions of sediment bioeffects based
on chemistry and toxicity data, in
comparison to other metric
combinations that were tested. The
index correctly classified stations
province-wide 93 % of the time in the
1994 development data set and 75% of
the time in the independent 1993/1995
validation data set.
Figure 13-15 illustrates that stations with
index values below 3 (suggestive of
some apparent stress to highly degraded
conditions) usually coincided with sites
considered to be degraded based on a
combination of chemistry and toxicity
data, and that stations with scores of 3
or higher usually coincided with
undegraded sites. Agreement is the
highest at the two ends of the scale.
Thus, the evaluation of sediment
quality based on the benthic index
appears to agree reasonably well with
predictions of sediment bioeffects based
on the combined exposure data.
Additional comparisons revealed that
the benthic index detected a higher
percentage of samples where bioeffects
were expected (based on sediment
quality guideline exceedances) than did
any of the four individual sediment
bioassays (Fig. 13-16a) or individual
infaunal attributes (Fig. 13-16b). Benthic
index values for base stations sampled
in 1995 covered the full scale from 1 to 5.
Values < 1.5 (clearest evidence of a
degraded benthos) occurred at 14 of the
86 base sites, which represented 21 % of
the province area (Fig.13-17).
Transitional values of 2 to 2.5
(suggestive of some possible stress)
occurred at an additional 14 sites,
representing another 15% of the
province. Values >3 (suggestive of an
undegraded benthos) occurred at the
remaining 58 base sites, representing
64% of the area of the province.
By estuarine class, the estimated
percentage of area with degraded
benthic assemblages was the highest for
large tidal rivers and the lowest for large
estuaries (Fig. 13-18). By subregion, this
percentage was the highest in Florida
estuaries and the lowest in South
Carolina/Georgia estuaries.
Extracted or summarized from the
EMAP Carolinian Province Report,
Annual Statistical Summary for the 1995
EMAP - Estuaries Demonstration Project
in the Carolinian Province (Hyland et al.
1998).
Primary Contact: Jeffrey L. Hyland,
Carolinian Province Office,
NO A A/National Ocean Service
217 Fort Johnson Rd. (P.O. Box 12559),
Charleston, SC 29422-2559
843-762-5415
jhyland@rdc.noaa.gov
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-61
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Figure 13-15
Frequency distribution
of index scores for
undegraded vs.
degraded stations in
1993/1995
"development" data
set.
5fi
40
Frequency Distribution of Index Scores
o'-
er)
30
ro
~j — i
CO
O>
Q_
20
10
Habitat
Undegraded
Degraded
Index Score
13-62
Case Studies
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A. Benthic Index vs. Bioassays
100
Ampetisca Afrpelisca Microtox Seed Benthic
atxtta verrlli Clarn Index
B, Bmthlc taCknc vs. Blotlc Attributes
1DQ
80
IB
•O
«
a.
a
65
H' racnnes Wundince Banlhfc I nOai
Figure 13-16
Comparison of
the percent of
expected
bioeffects
detected with the
benthic index vs.
(A) four sediment
bioassays and
(B) three
individual
infaunal
attributes.
"Percent
expected
bioeffects - #
stations (1995
core &
supplemental)
where an effect
was detected / #
stations with > 1
ER-M/PEL or > 3
ER-L/TEL
exceedance.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-63
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Figure 13-17
Percent area
(and 95% C.I.) of
CP estuaries with
high(> 3),
intermediate (>
1.5 to < 3), and
low(< 1.5)
benthic index
values.
Benthic Index
Healthy (> 3)
So me stress (> 1.5 to < 3)
Very unhealthy (< 1.5)
Figure 13-18
Comparison of
benthic index
values by
estuarine class
and subregion.
Benthic Index
100
80
i 60
40
20
0
I
] Some stress (> 1j5to<£
I Very unh ea tthy (£ 1.5)
I
t
Province Large Small Tidal VA-NC SC-GA FL
EstuaryClass
Subregion
13-64
Case Studies
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13.8 Assessment of the
Ecological Condition of
the Delaware and
Maryland Coastal Bays
13.8.1 Background
The coastal bays formed by the barrier
islands of Maryland and Delaware are
important ecological and economic
resources whose physical characteristics
and location make them particularly
vulnerable to the effects of pollutants. A
first step in developing management
strategies for these systems is to
characterize their present condition and
how it has changed over time. This
project was undertaken as a
collaborative effort of the Coastal Bays
Joint Assessment (CBJA), a group of
state and federal agencies, to assess the
ecological condition of this system and
fill a data void identified in previous
characterization studies.
Two hundred sites were sampled in the
summer of 1993 using a probability-
based sampling design that was
stratified to allow assessments of the
coastal bays as a whole, each of four
major subsystems within coastal bays
(Rehoboth Bay, Indian River Bay,
Assawoman Bay, and Chincoteague
Bay) and four target areas of special
interest to resource managers (upper
Indian River, St. Martin River, Trappe
Creek, and artificial lagoons). Measures
of biological response, sediment
contaminants, and eutrophication were
collected at each site using the same
sampling methodologies and quality
assurance/quality control procedures
used by EMAP. The consistency of the
sampling design and methodologies
between this study and EMAP allows
unbiased comparison of conditions in
the coastal bays with that in other major
estuarine systems in USEPA Region III
that are sampled by EMAP. As an
additional part of the study, trends in
fish communities structure were
assessed by collecting monthly beach
seine and trawl measurements during
the summer at about 70 sites where
historic measurements of fish
communities have been made.
13.8.2 Methods
Sampling sites were selected using a
stratified random sampling design in
which the coastal bays were stratified
into several subsystems for which
independent estimates of condition were
desired:
*• Upper Indian River;
*• Trappe Creek/Newport Bay;
*• St. Martin River;
> Artificial lagoons throughout the
coastal bays;
> All remaining areas within
Maryland's coastal bays; and
> All remaining areas within
Delaware's coastal bays.
The upper Indian River, Trappe Creek,
and St. Martin River were defined as
sampling strata because resource
managers expressed particular concern
about these areas. Water quality data
suggest that each of these tidal creeks is
subject to excessive nutrient enrichment,
algal blooms, and low concentrations of
DO. These creeks are also believed to
transmit large nutrient loads (from
agricultural runoff) downstream
contributing to eutrophication
throughout the coastal bays (Boynton et
al. 1993).
Artificial lagoons were defined as a
stratum because of their high potential
for impact based on their physical
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-65
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characteristics and their proximity to a
variety of contaminant sources (Brenum
1976). These dredged canal systems can
form the aquatic equivalent of streets in
development parcels; they already
encompass 105 linear miles and almost
4% of the surface area of Delaware's
inland bays. In general, these systems
are constructed as dead-end systems
with little or no freshwater inflows for
flushing. They are often dredged to a
depth greater than the surrounding
waters, leaving a ledge that further
inhibits exchange with nearby waters
and leads to stagnant water in the
canals. The placement of these systems
in relatively high density residential
areas increases the potential
contaminant input. Much of the
modified land-use in dredged canal
systems extends to the edge of the
bulkheaded waters, providing a ready
source of unfiltered runoff of lawn-care
and pesticides. In many cases, the
bulkhead and dock systems in these
canal systems are built from treated
lumber containing chromium, copper,
and arsenic, providing another source of
contaminants.
Four replicate bottom grabs were
collected from each station with a 0.04-
m2 Young grab sampler. Of the two
hundred sites sampled, 25 were in each
of the first four sampling strata and 50
were in each of the last two. Sites were
selected by simple random sampling in
all strata except artificial lagoons. The
randomly selected sites were chosen by
enhancing the base EMAP grid (Overton
et al. 1990). A different level of
enhancement was applied to each
stratum to obtain the required number
of samples. Sites in the artificial lagoons
were selected by developing a list frame
(of all existing lagoons), randomly
selecting 25 lagoons from that list, and
then randomly selecting a site within
each selected lagoon.
All sampling was conducted between
July 12 and September 30,1993.
Sampling was limited to a single index
period because available resources were
insufficient to sample in all seasons.
Late summer is the time during which
environmental stress on estuarine
systems in the mid-Atlantic region is
expected to be greatest owing to high
temperatures and low dilution flows
(Holland 1990). The sampling period
coincided with the period during which
EMAP sampled estuaries of the mid-
Atlantic region; therefore, data collected
in the coastal bays annually for EMAP
can be incorporated into estimates of
ecological condition generated from
Coastal Bays Joint Assessment (CBJA)
data. That data can then contribute to
continuing development and evaluation
of EMAP indicators.
Measurements of physical
characteristics provide basic information
about the natural environment.
Knowledge of the physical context in
which biological and chemical data are
collected is important for interpreting
results accurately because physical
characteristics of the environment
determine the distribution and species
composition of estuarine communities,
particularly assemblages of benthic
macroinvertebrates. Salinity, sediment
type, and depth are all important
influences on benthic assemblages
(Snelgrove and Butman 1994, Holland et
al. 1989). Sediment grain size also
affects the accumulation of
contaminants in sediments. Fine-
grained sediments generally are more
susceptible to contamination than sands
because of the greater surface area of
fine particles (Rhoads 1974, Plumb
1981).
Depth, silt-clay content of the sediment,
bottom salinity, temperature, and pH
were measured to describe the physical
conditions at sites in the coastal bays.
13-66
Case Studies
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Sediment type was defined according to
silt-clay content (fraction less than 63-n);
classifications were the same as those
used for EMAP. Biologically
meaningful salinity classes were defined
according to a modified Venice System
(Symposium on the Classification of
Brackish Waters 1958).
Healthy aquatic ecosystems require clear
water, acceptable concentrations of
dissolved oxygen, limited
concentrations of phytoplankton, and
appropriate concentrations of nutrients.
Clear water is a critical requirement for
submerged aquatic vegetation (SAV),
which provides habitat for many other
aquatic organisms (Dennison et al.
1993). As large concentrations of
suspended sediment or algal blooms
reduce water clarity, the amount of
sunlight reaching SAV is diminished
and the plants fail to thrive;
consequently, critical habitat for crabs,
fish, and other aquatic organisms is lost
(Dennison et al. 1993). Nutrient
enrichment causes excessive algal
growth in the water column and on the
surfaces of plants. As bacteria
metabolize the excess algae, they deplete
dissolved oxygen in the water column
and sediments causing hypoxia and, in
extreme cases, anoxia.
Water quality in the coastal bays of
Delaware and Maryland was evaluated
using classes of indicators: measures of
algal productivity, dissolved oxygen
(DO), water clarity, and nutrients.
Measures of algal biomass included the
concentrations of chlorophyll in the
water column and sediment, and
phaeophytin. Secchi depth, total
suspended solids (TSS), and turbidity
were measured to assess water clarity.
Nutrient measures included dissolved
inorganic nitrogen (DIN; nitrite, nitrate,
and ammonium), dissolved inorganic
phosphorus (DIP), total dissolved
nitrogen (TDN), total dissolved
phosphorus (TDP), and particulate
nitrogen and phosphorus. Table 13-18
lists the core environmental parameters
sampled at the various sites.
Estimating the percent of eutrophied
area in the coastal bays requires
identifying threshold levels for selected
indicators that define eutrophication.
While no such levels have been
established for the coastal bays, the
Chesapeake Bay Program has
established thresholds for five water
quality parameters to define critical
habitat requirements for supporting
SAV in a polyhaline environment
(Dennison et al. 1993); these thresholds
were used for our assessment (Table 13-
19). All but one of the SAV restoration
goal attributes were measured directly.
The light attenuation coefficient was
calculated from Secchi depth
measurements.
Threshold values of sediment
contaminants developed by Long and
Morgan (1990) and updated by Long et
al. (1995) were used to interpret
concentrations of sediment
contaminants measured in the coastal
bays. Two values were identified for
each contaminant: an effects range-low
(ER-L) value corresponding to
contaminant concentrations above
which biological effects begin to appear,
and an effects-range median (ER-M)
concentration, above which biological
effects are probable. Only a subset of
the contaminant samples collected for
the CBJA were processed because of cost
constraints; consequently, comparisons
were limited to the artificial lagoons and
the coastal bays as a whole.
Sediment samples for analysis of benthic
macroinvertebrates, silt-clay content,
benthic chlorophyll, and chemical
contaminants were collected using a
0.044-m2, stainless steel, Young-modified
Van Veen grab. Four measures of
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-67
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Table 13-18. Environmental parameters forthe Maryland/Delaware Coastal Bays.
Physical Parameters
Depth
% Silt/Clay content
Salinity
Temperature
RH
Water Quality Parameters
Chlorophyll a
Phaeophytin
Benthic chlorophyll
DO (Dissolved Oxygen)
NO2 (Nitrite)
NO3 (Nitrate)
Ammonium
TON (Total Dissolved Nitrogen)
Orthophosphate
TOP (Total Dissolved Phosphorus)
TPN (Total Particulate Nitrogen)
TPP (Total Particulate Phosphorus)
TPC (Total Particulate Carbon)
Secchi Depth
TSS (Total Suspended Solids)
Turbidity
Benthic Parameters
Abundance
Biomass
Number of Species
Shannon-Wiener Index
EMAP Index
Table 13-19. Chesapeake Bay submerged aquatic vegetation habitat requirements fora polyhaline
environment (Dennison et al. 1993).
Parameter
Light attenuation coefficient (kd; m"1)
Total suspended solids (mgL"1)
Chlorophyll a (ug/l)
Dissolved inorganic nitrogen (uM)
Dissolved inorganic phosphorus (uM)
Critical Value
1.5
15
15
10
0.67
13-68
Case Studies
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biological response were used to
evaluate the condition of benthic
assemblages in the coastal bays of
Delaware and Maryland: abundance,
biomass, diversity, and the EMAP
benthic index. Abundance and
biomass are measures of total
biological activity at a location. The
diversity of benthic organisms
supported by the habitat at a location
often is considered a measure of the
relative "health" of the environment.
Diversity was evaluated using the
number of species; i.e., species
richness, at a location and the
Shannon-Wiener diversity index,
which incorporates both species
richness and evenness components.
The EMAP benthic index integrates
measures of species diversity,
composition, biomass, and abundance
into a single value that distinguishes
between sites of good or poor
ecological condition (Schimmel et al.
1994). A value of 0 or less denotes a
degraded site at which the structure of
the benthic community is poor, and
the number of species, abundance of
selected indicator species, and mean
biomass are small.
13.8.3 Results/Conclusions
Major portions of the coastal bays
have degraded environmental quality.
EMAP's benthic index measured 28%
of the area in the coastal bays had
degraded benthic communities. At
least one sediment contaminant
exceeding the Long et al. (1995) ER-L
concentration (threshold of initial
biological concern) were found in 68%
of the area in the coastal bays. More
than 75% of the area in the coastal
bays failed the Chesapeake Bay
Program's Submerged Aquatic
Vegetation (SAV) restoration goals,
which are a combination of measures
that integrate nutrient, chlorophyll,
and water clarity parameters.
The tributaries to the coastal bays are
in poorer condition than the
mainstems of the major subsystems.
Previous studies have suggested that
the major tributaries to the system:
upper Indian River, St. Martin River,
and Trappe Creek are in poorer
condition than the mainstem water
bodies. This study confirmed that
finding. The percentage of area
containing degraded benthos was
generally two to three times greater in
the tributaries compared to the rest of
the coastal bays. The percent of area
with DO less than the state standard
of 5-ppm was three to seven times
greater in the tributaries. More than
70 % of the area in upper Indian River
and St. Martin River and in the
artificial lagoons had chlorophyll a
concentrations exceeding the SAV
restoration goals.
Among these systems, Trappe Creek
contained the sites in the worst
condition. Two sites in the upper
portion of Trappe Creek had
concentrations of chlorophyll a
exceeding 350 ugL"1; algal blooms
were evident at each site. In addition,
daytime DO levels exceeding 14-ppm
were measured at both sites.
Although, supersaturated DO often
occurs in hypereutrophic waterbodies
on warm, sunny days. However, it
appears that degraded conditions in
the Trappe Creek system are spatially
limited to Trappe Creek and have not
spread to Newport Bay.
Undoubtedly, this results from the
low freshwater flow from this
tributary compared to the other
tributaries.
Moreover, the coastal bays are in as
poor or worse condition than either
the Chesapeake or Delaware Bays
with respect to sediment contaminant
levels, water quality, and benthic
macroinvertebrate community
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
13-69
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condition. Based on comparison to
EMAP data collected between 1990-
1993, the coastal bays were found to
have 68% chemical contamination in
the sediments, a higher prevalence
than either Chesapeake Bay or
Delaware Bay. The total area in the
coastal bays that had at least one
sediment contaminant exceeding the
Long et al. (1995) ER-L concentration
was 50 % higher than the spatial extent
EMAP estimated for Chesapeake Bay
using identical methods, and 40 %
higher, though not statistically
distinguishable, from what EMAP
estimated for Delaware Bay.
Twenty-eight percent of the area in
the coastal bays had degraded benthic
communities as measured by EMAP's
benthic index. This was significantly
greater than the 16% EMAP estimated
for Delaware Bay using the same
methods and same index, and
statistically indistinguishable from the
26% estimated for the Chesapeake
Bay.
Nutrients were not measured by
EMAP and statistically unbiased
estimates of average concentrations
are unavailable for either Chesapeake
or Delaware Bays. The Chesapeake
Bay Program though, recently
estimated that about 75% of the area
in Chesapeake Bay meets SAV
Restoration Goals. This is more than
three times the percent of area
meeting SAV Restoration Goals in the
coastal bays. Even when the turbidity
and TSS components of the SAV
Restoration Goals (which are naturally
high in shallow systems), are ignored,
almost half of the area in the coastal
bays still fails the SAV Restoration
Goal estimates for nutrients and
chlorophyll.
The fish community structure in
Maryland's coastal bays has remained
relatively unchanged during the past
twenty years while that of similar
systems in Delaware have changed
substantially. Fish communities of the
Maryland coastal bays are dominated
by Atlantic silversides, bay anchovy,
Atlantic menhaden, and spot. This
community structure is similar to that
of the Delaware coastal bays 35 years
ago. The fish fauna in Delaware's
coastal bays has shifted toward
species of the Family Cyprinodontidae
(e.g., killifish and sheepshead
minnow) which are more tolerant to
low oxygen stress, and extremes of
salinity and temperature.
Primary Contact: Dr. Frederik W. Kutz
U.S. EPA, Region HI
Environmental Science Center
701 Mapes Rd.
FortMeade,MD 20755
410-305-2742
Kutz.Rick@epa.gov
13-70
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Glossary
A posteriori classification - a
classification based on the results of
experimentation.
A priori classification - a classification
made prior to experimentation.
Aquatic community - an association of
interacting populations of aquatic
organisms in a given waterbody or
habitat.
Aquatic life uses - a subset of designated
uses for high quality waters. As such,
they are in need of special protection so
that characteristics of their resident biotic
communities are identified and protected.
Assemblage - an association of interacting
populations of organisms in a given
waterbody (e.g., fish assemblage or
benthic macroinvertebrate assemblage).
Attribute - physical and biological
characteristics of habitats which can be
measured or described.
Benthic macroinvertebrates - see benthos.
Benthos - animals without backbones,
living in or on the sediments, of a size
large enough to be seen by the unaided
eye, and which can be retained by a U.S.
Standard No. 30 sieve (28 openings/in,
0.595-mm openings). Also referred to as
benthic macroinvertebrates, infauna, or
macrobenthos.
Bioaccumulation - a process by which
chemicals are taken up by aquatic
organisms directly from water as well as
through exposure via other routes, such as
consumption of food and sediment
containing the chemicals.
Bioconcentration - a process by which
there is a net accumulation of a chemical
directly from water into aquatic organisms
resulting from simultaneous uptake (e.g.,
via gill or epithelial tissue) and
elimination.
Biological assemblage - a group of
phylogenetically (e.g., fish) or ecologically
(e.g., benthic macroinvertebrates) related
organisms that are part of an aquatic
community.
Biological assessment or Bioassessment -
an evaluation of the condition of a
waterbody using biological surveys and
other direct measures of the resident biota
of the surface waters, in conjunction with
biological criteria.
Biological criteria or Biocriteria -
guidelines or benchmarks adopted by
States to evaluate the relative biological
integrity of surface waters. Biocriteria are
narrative expressions or numerical values
that describe biological integrity of aquatic
communities inhabiting waters of a given
classification or designated aquatic life
use.
Biological indicators - plant or animal
species or communities with a narrow
range of environmental tolerances that
may be selected for monitoring because
their absence or presence and relative
abundances serve as barometers of
environmental conditions.
Biological integrity - the condition of the
aquatic community inhabiting unimpaired
waterbodies of a specified habitat as
measured by community structure and
function.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
G-1
-------
Biological monitoring or Biomonitoring -
multiple, routine biological surveys over
time using consistent sampling and
analysis methods for detection of changes
in biological condition.
Biological survey or Biosurvey -
collecting, processing and analyzing
representative portions of an estuarine or
marine community to determine its
structure and function.
Biomagnification - the result of the
processes of bioconcentration and
bioaccumulation by which tissue
concentrations of bioaccumulated
chemicals increase as the chemical passes
up through two or more trophic levels in
the food chain.
Biota - plants, animals and other living
resources.
Brackish - water with salt content ranging
between that of sea water and fresh water;
commonly used to refer to oligohaline
waters.
Coastal waters - marine waters adjacent to
and receiving estuarine discharges and
extending seaward over the continental
shelf and/or the edge of the U.S.
territorial sea.
Community - any group of organisms
belonging to a number of different species
that co-occur in the same habitat or area;
an association of interacting assemblages
in a given waterbody.
Demersal - living on or near the bottom of
a body of water (e.g., mid-water and
bottom-dwelling fish and shellfish, as
opposed to surface fish).
Designated uses - descriptions of the
optimal use of each waterbody as defined
by States including natural fisheries,
recreation, transportation, or mixed uses.
Discriminant analysis - a type of
multivariate analysis used to distinguish
between two groups.
Ecological integrity - the condition of an
unimpaired ecosystem as measured by
combined chemical, physical (including
habitat), and biological attributes.
Ecoregion - geographic regions of
ecological similarity defined by similar
climate, landform, soil, natural vegetation,
hydrology or other ecologically relevant
variables.
Effects Range-Low - concentration of a
chemical in sediment below which toxic
effects were rarely observed among
sensitive species (10th percentile of all toxic
effects).
Effects Range-Median - concentration of a
chemical in sediment above which toxic
effects are frequently observed among
sensitive species (50th percentile of all toxic
effects).
Epibenthos - those animals (usually
excluding fishes) living on the top of the
sediment surface.
Epifauna - benthic animals living on the
sediment or on and among rocks and
other structures.
Estuarine or coastal marine classes -
classes that reflect basic biological
communities and that are based on
physical parameters such as salinity,
depth, sediment grain size, dissolved
oxygen and basin geomorphology.
Estuarine waters - semi-enclosed body of
water which has a free connection with
the open sea and within which seawater is
measurably diluted with fresh water
derived from land drainage.
Facultative - capable of adaptive response
to varying environments.
G-2
Glossary
-------
Habitat - a place where the physical and
biological elements of ecosystems provide
an environment and elements of the food,
cover and space resources needed for
plant and animal survival.
Halocline - a vertical gradient in salinity.
Holoplankton - an aggregate of passively
floating, drifting or somewhat motile
organisms throughout their entire life
cycle.
Hypoxia - the condition of low dissolved
oxygen in aquatic systems (typically with
a concentration < 2-mgL"1 but > 0.5-
mgL-1).
IBI or Index of Biotic Integrity - a fish
community assessment approach that
incorporates the zoogeographic,
ecosystem, community and population
aspects of fisheries biology into a single
ecologically-based index of the quality of a
water resource.
Impact - a change in the chemical,
physical or biological quality or condition
of a waterbody caused by external
sources.
Impairment - a detrimental effect on the
biological integrity of a water body caused
by an impact.
Indexes - a usually dimensionless numeric
combination of scores derived from
biological measures called metrics.
Index period - a sampling period, with
selection based on temporal behavior of
the indicator(s) and the practical
considerations for sampling.
Indicator - characteristics for the
environment, both abiotic and biotic, that
can provide quantitative information on
environmental conditions.
Indicator taxa or Indicator species - those
organisms whose presence (or absence) at
a site is indicative of specific
environmental conditions.
Infauna - see benthos.
In situ - measurements taken in the
natural environment.
Kurtosis - a measure of the departure of a
frequency distribution from a normal
distribution, in terms of its relative
peakedness or flatness.
Littoral zone - the intertidal zone of the
estuarine or seashore; i.e., the shore zone
between the highest and lowest tides.
Macrobenthos - see benthos.
Macrofauna - animals of a size large
enough to be seen by the unaided eye and
which can be retained by a U.S. Standard
No. 30 sieve (28 meshes/in, 0.595-mm
openings).
Macroinvertebrates - animals without
backbones of a size large enough to be
seen by the unaided eye and which can be
retained by a U.S. Standard No. 30 sieve
(28 meshes/in, 0.595-mm openings).
Macrophytes - large aquatic plants that
may be rooted, non-rooted, vascular or
algiform (such as kelp); including
submerged aquatic vegetation, emergent
aquatic vegetation, and floating aquatic
vegetation.
Meiofauna - small interstitial; i.e.,
occurring between sediment particles,
animals that pass through a 1-mm mesh
sieve but are retained by a 0.1-mm mesh.
Meroplankton - organisms that are
planktonic only during the larval stage of
their life history.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance
G-3
-------
Mesohaline - the estuarine salinity zone
with a salinity range of 5-18-ppt.
Metric - a calculated term or enumeration
which represents some aspect of biological
assemblage structure, function, or other
measurable characteristic of the biota that
changes in some predictable way in
response to impacts to the water body.
Multimetric approach - an analysis
technique that uses a combination of
several measurable characteristics of the
biological assemblage to provide an
assessment of the status of water
resources.
Multivariate community analysis -
statistical methods (e.g., ordination or
discriminant analysis) for analyzing
physical and biological community data
using multiple variables.
NPDES or National Pollutant Discharge
Elimination System - a permit program
under Section 402 of the Clean Water Act
that imposes discharge limitations on
point sources by basing them on the
effluent limitation capabilities of a control
technology or on local water quality
standards.
Oligohaline - the estuarine salinity zone
with a salinity range of 0.5-5-ppt.
Optimal - most favorable point, degree, or
amount of something for obtaining a
given result; in ecology most natural or
minimally disturbed sites.
Pelagic - pertaining to open waters or the
organisms which inhabit those waters.
Pelagic zone - the area of open water
beyond the littoral zone.
Percent fines - in analysis of sediment
grain size, the percent of fine (.062-mm)
grained fraction of sediment in a sample.
Photic zone - the region in a water body
extending from the surface to the depth of
light penetration.
Plankton - free-floating or drifting
organisms with movements determined
by the motion of the water.
Population - an aggregate of
interbreeding individuals of a biological
species within a specified location.
Pseudoreplication - the repeated
measurement of a single experimental unit
or sampling unit, with the treatment of the
measurements as if they were
independent replicates of the sampling
unit.
Pycnocline - a zone of marked density
gradient.
Reference condition - the chemical,
physical or biological quality or condition
exhibited at either a single site or an
aggregation of sites that represents the
least impaired condition of a classification
of waters to which the reference condition
applies.
Reference sites - minimally impaired
locations in similar water bodies and
habitat types at which data are collected
for comparison with test sites. A separate
set of reference sites are defined for each
estuarine or coastal marine class.
Replicate - taking more than one sample
or performing more than one analysis.
Saprobien system - an ecological
classification of a polluted aquatic system
that is undergoing self-purification.
Classification is based on relative levels of
pollution, oxygen concentration and types
of indicator microorganisms; i.e.,
saprophagic microorganisms - feeding on
dead or decaying organic matter.
G-4
Glossary
-------
Seiche - a wave that oscillates (for a
period of a few minutes to hours) in lakes,
bays, lagoons or gulfs as a result of
seismic or atmospheric disturbances (e.g.,
"wind tides").
Simulation models - mathematical
models (logical constructs following from
first principles and assumptions),
statistical models (built from observed
relationships between variables), or a
combination of the two.
Skewness - the degree of statistical
asymmetry (or departure from symmetry)
of a population. Positive or negative
skewness indicates the presence of a long,
thin tail on the right or left of a
distribution respectively.
Test sites - those sites being tested for
biological impairment.
Trophic level - a broad class of an
ecosystem (e.g., green plants, herbivores,
carnivores) in which all organisms
procure food in the same general manner.
Use designations - predominant uses each
State determines appropriate for a
particular estuary, region, or area within
the class.
Zooplankton - free-floating or drifting
animals with movements determined by
the motion of the water.
Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance G-5
-------
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