EPA 620/R-04/200

February 2005

Condition of Estuaries of the Western United

States for 1999: A Statistical Summary

Office of Research and Development

U.S. Environmental Protection Agency

Washington, DC 20460
ii

List of Authors

Walter G. Nelson1, Henry Lee II1, Janet O. Lamberson1, Virginia Engle2, Linda Harwell2,

Lisa M. Smith2

List of Author Affiliations

1

 Western Ecology Division, National Health and Environmental Effects Research

Laboratory, U.S. Environmental Protection Agency, Newport OR 97365

2

 Gulf Ecology Division, National Health and Environmental Effects Research 

Laboratory, U.S. Environmental Protection Agency, Gulf Breeze FL 32561
iii

Preface

This document is the statistical summary for the western states, coastal component of

the nationwide Environmental Monitoring and Assessment Program (EMAP). The focus

of the study during 1999 was the small estuaries of Washington, Oregon, and California

(excluding Puget Sound, the main channel of the Columbia River, and San Francisco

Bay). EMAP-West is a partnership of the States of California, Oregon and Washington,

the National Oceanic and Atmospheric Administration (NOAA), and the U.S.

Environmental Protection Agency (EPA). The program is administered through the EPA

and implemented through partnerships with a combination of federal and state

agencies, universities and the private sector.

The appropriate citation for this report is:

Nelson, Walter G., Lee II, Henry, Lamberson, Janet O., Engle, Virginia, Harwell,

Linda, Smith, Lisa M. 2004. Condition of Estuaries of Western United States for

1999: A Statistical Summary. Office of Research and Development, National

Health and Environmental Effects Research Laboratory, EPA/620/R-04/200. 

Disclaimer

The information in this document has been funded wholly or in part by the U.S.

Environmental Protection Agency under Cooperative Agreements with the states of

Washington (CR 827869 ) , Oregon (CR 87840 ), and California (CR 827870 ) and an

Inter Agency Agreement with the National Marine Fisheries Service (DW 13938780). It

has been subjected to review by the National Health and Environmental Effects

Research Laboratory and approved for publication. Approval does not signify that he

contents reflect the views of the agency, nor does mention of trade names or

commercial products constitute endorsement or recommendation for use. 
iv

Acknowledgments

Western Coastal EMAP involves the cooperation of a significant number of federal,

state, and local agencies. The project has been principally funded by the U.S.

Environmental Protection Agency Office of Research and Development. The following

organizations provided a wide range of field sampling, analytical and interpretive

support in their respective states through individual cooperative agreements with EPA:

Washington Department of Ecology, Oregon Department of Environmental Quality,

Southern California Coastal Water Research Project (SCCWRP). The Northwest

Fisheries Science Center, National Marine Fisheries Service, National Oceanic and

Atmospheric Administration provided field support and analysis of fish pathologies

through a cooperative agreement with EPA. Other research organizations provided

additional scientific support through subcontracts with these lead organizations. Moss

Landing Marine Laboratory provided the field crews for collection of samples in

California under contract to SCCWRP. 

The U.S. Geological Survey, Columbia Environmental Research Center, through the

Biomonitoring Environmental Status and Trends (BEST) Program, provided analyses for

H4IIE bioassay-derived 2,3,7,8-tetrachlorodibenzo - p -dioxin equivalents (TCDD-EQ)

for exposure of fish to planar halogenated hydrocarbons. Through their Marine

Ecotoxicology Research Station, BEST also provided two bioassays on sediment

porewater toxicity, the sea urchin Arbacia punctulata fertilization toxicity and embryo

development toxicity tests.

Project wide information management support was provided by SCCWRP as part of

their cooperative agreement. 

Many individuals within EPA made important contributions to Western Coastal EMAP.

Critical guidance and vision in establishing this program was provided by Kevin

Summers of Gulf Ecology Division. Tony Olsen of Western Ecology Division (WED) has

made numerous comments which have helped to improve the quality of this document. 

Lorraine Edmond of the Region 10 Office of EPA and Terrence Fleming of the Region 9

Office of EPA have ably served as the regional liaisons with the state participants in

their regions. Robert Ozretich of WED performed a detailed review of the database

contents used for this analysis, and we additionally thank him for his extensive quality

assurance review of this document.

We thank Jeff Hyland of NOAA and Joan Cabreza of the Region 10 Office of EPA for

their technical reviews of this report.

The success of the Western Coastal pilot has depended on the contributions and

dedication of many individuals. Special recognition for their efforts is due the following

participants:
v

Washington Department of Ecology

Casey Cliche

Margaret Dutch

Ken Dzinbal

Christina Ricci

Kathy Welch

Oregon Department of Environmental Quality

Mark Bautista

Greg Coffeen

Curtis Cude

Paula D’Alfonso

RaeAnn Haynes

Dan Hickman

Bob McCoy

Greg McMurray

Greg Pettit

Chris Redmond

Crystal Sigmon

Daniel Sigmon

Scott Sloane

Southern California Coastal Water Research Project (SCCWRP)

Larry Cooper

Steve Weisberg

Moss Landing Marine Laboratory

Russell Fairey

Cassandra Roberts

San Francisco Estuary Institute

Bruce Thompson

University of California Davis

Brian Anderson

National Oceanic and Atmospheric Administration

National Marine Fisheries Service, Northwest Fisheries Science Center

Bernie Anulacion

Tracy Collier

Dan Lomax

Mark Myers

Paul Olson
vi

U.S. Geological Survey

Biomonitoring of Environmental Status and Trends Program (BEST)

Christine Bunck

Columbia Environmental Research Center

Don Tillet

Marine Ecotoxicology Research Station

Scott Carr

Gulf Breeze Project Office

Tom Heitmuller

Steve Robb

Pete Bourgeois

U.S. Environmental Protection Agency

Office of Research and Development

Tony Olsen

Steve Hale

John Macauley

Region 9

Terrence Fleming

Janet Hashimoto

Region 10

Lorraine Edmond

Gretchen Hayslip

Indus Corporation

Patrick Clinton
vii

Table of Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Disclaimer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvi

1.0 Introduction ...................................................... 1

1.1 Program Background ........................................ 1

1.2 The Western United States Context for

 a Coastal Condition Assessment ............................. 2

1.3 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.0 Methods ........................................................ 5

2.1 Sampling Design and Statistical Analysis Methods .................. 5

2.1.1 Background ......................................... 5

2.1.2 Sampling Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.2.1 1999 West Coast Design ........................ 6

2.1.2.2 2000 West Coast Design ........................ 8

2.2 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.3 Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

2.3.1 Water Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2.3.1.1 Hydrographic Profile . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2.3.1.2 Water Quality Indicators . . . . . . . . . . . . . . . . . . . . . . . . 28
viii

2.3.2 Sediment Toxicity Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.3.2.1 Sediment Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.3.2.2 Laboratory Test Methods . . . . . . . . . . . . . . . . . . . . . . . 30

2.3.2.2.1 Amphipod Toxicity Tests . . . . . . . . . . . . . . . . 30

2.3.2.2.2 Sea Urchin Toxicity Tests . . . . . . . . . . . . . . . 31

2.3.3 Biotic Condition Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.3.3.1 Benthic Community Structure . . . . . . . . . . . . . . . . . . . . 32

2.3.3.2 Fish Trawls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

2.3.3.3 Fish Community Structure . . . . . . . . . . . . . . . . . . . . . . 34

2.3.3.4 Fish Contaminant Sampling . . . . . . . . . . . . . . . . . . . . . 34

2.3.3.5 Fish Contaminant Chemistry Analyses . . . . . . . . . . . . . 35

2.3.3.6 Fish Gross Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . 36

2.3.4 Sediment Chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

2.4 General QA/QC Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

2.4.1 QA of Chemical Analyses . . . . . . . . . . . . . . . . . . . . . . . . . 42

2.4.2 QA of Taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

2.5 Data Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

2.6 Unsamplable Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

3.0 Indicator Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.1 Habitat Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.1.1 Salinity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.1.2 Water Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.1.3 pH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
ix

3.1.4 Sediment Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

3.1.5 Water Quality Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

3.1.6 Water Column Stratification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

3.2 Exposure Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3.2.1 Dissolved Oxygen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3.2.2 Sediment Contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3.2.2.1 Sediment Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3.2.2.2 Sediment Organics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

3.2.3 Sediment Toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

3.2.3.1 Ampelisca abdita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

3.2.3.2 Arbacia punctulata ............................ 99

3.2.4 Tissue Contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

3.3 Biotic Condition Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

3.3.1 Infaunal Species Richness and Diversity . . . . . . . . . . . . . . . . . 115

3.3.2 Infaunal Abundance and Taxonomic Composition . . . . . . . . . . 116

3.3.3 Demersal Species Richness and Abundance . . . . . . . . . . . . . . 124

4.0 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
x

List of Figures

Figure 2-1. Location of Washington EMAP survey sites. . . . . . . . . . . . . . . . . . . . . . 10

Figure 2-2. Location of EMAP survey sites along the northern portion 

of the Oregon coast, including survey sites for the intensification study of

Tillamook Bay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Figure 2-3. Location of EMAP survey sites along the southern portion

 of the Oregon coast. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure 2-4. Location of EMAP survey sites for the intensification study

 of Tillamook Bay, Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Figure 2-5. Location of California EMAP survey sites in Northern California

 from the Oregon Border to the Garcia River. . . . . . . . . . . . . . . . . . . . . . . . . 14

Figure 2-6. Location of California EMAP survey sites in Northern and

Central California from the Russian River to the Santa Ynez River. . . . . . . . 15

Figure 2-7. Location of California EMAP survey sites in Central and

Southern California from Santa Barbara to the Mexican border. . . . . . . . . . . 16

Figure 3.1-1. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. salinity of bottom waters. . . . . . . . . . . . . . . . . . . . . . . 58

Figure 3.1-2. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. temperature of bottom waters. . . . . . . . . . . . . . . . . . . 59

Figure 3.1-3. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. pH in bottom waters. . . . . . . . . . . . . . . . . . . . . . . . . . 60

Figure 3.1-4. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. percent silt-clay of sediments. . . . . . . . . . . . . . . . . . . 61

Figure 3.1-5. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. percent total organic carbon of sediments. . . . . . . . . . 62

Figure 3.1-6. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. water column mean concentration of chlorophyll a. . . 63

Figure 3.1-7. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. water column mean nitrate + nitrite concentration. . . . 64
xi

Figure 3.1-8. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. water column mean ammonium concentration. . . . . . 65

Figure 3.1-9. Percent area (and 95% C.I.) of small estuaries of the

West Coast states vs. water column mean total nitrogen

 (nitrate + nitrite + ammonium) concentration. . . . . . . . . . . . . . . . . . . . . . . . . 66

Figure 3.1-10. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. water column mean orthophosphate concentration. . . 67

Figure 3.1-11. Percent area (and 95% C.I.) of small estuaries of the

West Coast states vs. water column mean ratio of total nitrogen

 (nitrate + nitrite + ammonium) concentration to total orthophosphate

concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Figure 3.1-12. Percent area (and 95% C.I.) of small estuaries of the

West Coast states vs. water column total suspended solids concentration. . 69

Figure 3.1-13. Percent area (and 95% C.I.) of small estuaries of the

West Coast states vs. percent light transmission estimated

 at a reference depth of 1 m in the water column. . . . . . . . . . . . . . . . . . . . . . 70

Figure 3.1-14. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. water column stratification index. . . . . . . . . . . . . . . . . 71

Figure 3.1-15. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. )Ft

 stratification index.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

Figure 3.2-1. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. dissolved oxygen of bottom waters. . . . . . . . . . . . . . . 74

Figure 3.2-2. Percent area (and 95% C.I.) of small estuaries of the 

West Coast states vs. dissolved oxygen of surface waters. . . . . . . . . . . . . . . 75

Figure 3.2-3. Percent area (and 95% C.I.) of West Coast small estuaries

 vs. sediment concentration of arsenic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Figure 3.2-4. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of cadmium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Figure 3.2-5. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of chromium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
xii

Figure 3.2-6. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of copper. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Figure 3.2-7. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of lead. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Figure 3.2-8. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of mercury. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Figure 3.2-9. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of nickel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

Figure 3.2-10. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of selenium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Figure 3.2-11. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of silver. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

Figure 3.2-12. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of tin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Figure 3.2-13. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of zinc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Figure 3.2-14. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of total PAHs. . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Figure 3.2-15. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of high molecular weight PAHs. . . . . . . . . . . . . . . . . . . . . . . . . 95

Figure 3.2-16. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of low molecular weight PAHs. . . . . . . . . . . . . . . . . . . . . . . . . . 96

Figure 3.2-17. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of total PCBs. . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

Figure 3.2-18. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. sediment concentration of total DDT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

Figure 3.2-19. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. percent control corrected survivorship of Ampelisca abdita. . . . . . . . . . . 101
xiii

Figure 3.2-20. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

fertilization of Arbacia punctulata eggs for the 100% water quality adjusted

porewater concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Figure 3.2-21. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

fertilization of Arbacia punctulata eggs for the 50% water quality adjusted

porewater concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

Figure 3.2-22. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

fertilization of Arbacia punctulata eggs for the 25% water quality adjusted

porewater concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

Figure 3.2-23. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

successful embryonic development of Arbacia punctulata for the 100% water

quality adjusted porewater concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Figure 3.2-24. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

successful embryonic development of Arbacia punctulata for the 50% water

quality adjusted porewater concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Figure 3.2-25. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

successful embryonic development of Arbacia punctulata for the 25% water

quality adjusted porewater concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Figure 3.3-1. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. benthic infaunal species richness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

Figure 3.3-2. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. benthic infaunal Hr diversity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

Figure 3.3-3. Percent area (and 95% C.I.) of West Coast small estuaries 

vs. benthic infaunal total abundance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
xiv

List of Tables

Table 2-1. West Coast sampling sites with station coordinates of locations sampled. 17

Table 2-2. Core environmental indicators for the EMAP Western Coastal survey. . . 25

Table 2-3. Environmental indicators under development or conducted

 by collaborators during the EMAP Western Coastal survey. . . . . . . . . . . . . . 26

Table 2-4. Compounds analyzed in all three states in sediments and fish tissues. . . 37

Table 2-5. Summary of EMAP-Coastal chemistry sample collection,

 preservation, and holding time requirements for sediment and fish tissues. . 38

Table 2-6. Methods used to analyze for contaminants in sediments and tissues. . . 39

Table 2-7. Units, method detection limits (MDL), and reporting limits (RL)

 for sediment chemistry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Table 2-8. Units, method detection limits (MDL), and reporting limits (RL)

 for tissue chemistry for compounds measured in all three states. . . . . . . . . . 46

Table 2-9. Summary of reference and matrix spike recoveries, and relative percent

differences (RPD) of duplicates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Table 2-10. Listing of primary and QA/QC taxonomists by taxon and region

 for the 1999 Western Coastal EMAP study. . . . . . . . . . . . . . . . . . . . . . . . . . 51

Table 3.2-1. Summary statistics for sediment metal concentrations (μg/g)

 for 190 stations from West Coast estuaries. . . . . . . . . . . . . . . . . . . . . . . . . . 79

Table 3.2-2. Mean sediment concentrations (ng/g dry weight) and frequency of

detection of the PAHs, PCBs and pesticides measured in all three states. . 93

Table 3.2-3. Species composition and relative abundance of the three

 fish groups used in the tissue residue analysis. . . . . . . . . . . . . . . . . . . . . . 110

Table 3.2-4. Fish tissue residues of metals measured in all three states. . . . . . . . 111

Table 3.2-5. Fish tissue residues of total PCBs, total DDT and the 

additional pesticides measured in all three states. . . . . . . . . . . . . . . . . . . . . 113

Table 3.3-1. Summary statistics for benthic abundance, number of 

species per benthic sample, and Hr. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
xv

Table 3.3-2. Abundance, taxonomic grouping, and classification of the

 ten most abundant benthic species in the three states including the

intensification sites in Northern California and Tillamook, Oregon. . . . . . . . 122

Table 3.3-3. Abundance, taxonomic grouping, and classification of the

 ten most abundant benthic species in the three states excluding

the Northern California intensification stations. . . . . . . . . . . . . . . . . . . . . . . 123

Table 3.3-4. Trawl duration and speed averaged across California, Oregon,

and Washington and in each individual state. . . . . . . . . . . . . . . . . . . . . . . . 125

Table 3.3-5. Mean number of fish captured per trawl and mean number

of fish species per trawl averaged across California, Oregon, and

Washington and for each individual state. . . . . . . . . . . . . . . . . . . . . . . . . . . 126

Table 3.3-6. Ten numerically dominant fish species averaged across California,

Oregon, and Washington, including both the base and intensive stations. . 127

Table 3.3-7 Mean and standard deviation of the five most numerically abundant fish

species in California, Oregon, and Washington. . . . . . . . . . . . . . . . . . . . . . 128
xvi

Executive Summary

As a part of the National Coastal Assessment, the Environmental Monitoring and

Assessment Program (EMAP) initiated a five-year Western Coastal component in 1999. 

The objectives of the program were: to assess the condition of estuarine resources of

Washington, Oregon and California based on a range of indicators of environmental

quality using an integrated survey design; to establish a baseline for evaluating how the

conditions of the estuarine resources of these states change with time; to develop and

validate improved methods for use in future coastal monitoring and assessment efforts

in the western coastal states; and to transfer the technical approaches and methods for

designing, conducting and analyzing data from probability based environmental

assessments to the states and tribes.

The focus of the study during 1999 was the small estuaries of Washington, Oregon, and

California, excluding Puget Sound, the main channel of the Columbia River, and San

Francisco Bay, which were sampled in 2000 during the second year of the program. 

The environmental condition indicators used in this study included measures of: 1)

general habitat condition (depth, salinity, temperature, pH, total suspended solids,

sediment characteristics), 2) water quality indicators (chlorophyll a, nutrients), 3)

pollutant exposure indicators (dissolved oxygen concentration, sediment contaminants,

fish tissue contaminants, sediment toxicity), and 4) benthic condition indicators (diversity

and abundance of benthic infaunal and demersal fish species, fish pathological

anomalies).

The study utilized a stratified random sampling design, with the base study consisting of

150 sites equally divided among the three states. Additionally, intensification studies

were conducted that consisted of 30 sites located in Tillamook Bay, Oregon, and 30

sites distributed among the mouths of river dominated estuaries in northern California. 

All sites were combined for statistical analysis. Cumulative distribution functions (CDFs)

were produced using appropriate sampling area weightings to represent the areal extent

associated with given values of an indicator variable for the small estuaries of the West

Coast. 

Reflecting the fact that the sampling effort spanned both the Columbian and Californian

Biogeographic Provinces, the indicators of general habitat condition showed wide

ranges of values, e.g., bottom water temperatures from 8.5 to 32.1 °C. Approximately 

54% of the area of the small West Coast estuaries would be classified as euhaline ($30

psu) based on the EMAP sampling. Approximately 65% of the estuarine area had

sandy sediments (<20% silt clay), 29% had intermediate muddy sands (20-80% silt

clay), and 6 % had mud sediments (>80% silt clay). The TOC content of sediments was

# 1% in approximately 84% of the area of the small West Coast estuaries.

The pH of bottom waters for the small estuaries of West Coast states had the

surprisingly wide range of from 5.1 to 10.2, with extreme values associated with low

salinity locations. There was no geographic pattern to high values of chlorophyll a. 
xvii

Most water quality indicators showed similar CDF patterns, with high values being

observed in a very small percentage of estuarine area, thus generating extensive right

hand tails to CDF distributions. For example, the average water column concentration of

nitrate/nitrite of small West Coast estuaries ranged from 0 to 3472 :g L-1, but only 2.7 %

of estuarine area had nitrate/nitrite values that exceeded concentrations of 300 :gL-1. 

Approximately 75% of estuarine area had molar ratios of average water column total

nitrogen to total phosphorus (N/P) values # 16, suggesting nitrogen limitation. While

total suspended solids (TSS) ranged from 0 to 276.2 mg L-1, approximately 95% of

estuarine area had TSS # 19.1 mg L-1. Only about 12 % of estuarine area showed an

indication of strong water column stratification as indicated by the difference in surface

and bottom salinities, suggesting the estuarine areas sampled are generally well mixed.

Among pollution exposure indicators, less than four percent of estuarine area had

dissolved oxygen concentrations in bottom waters below 5 mg/L. High values of

potentially toxic metals generally occurred in a very small percentage of the estuarine

area sampled, with maximum values of many of the metals being observed in the highly

urbanized Los Angeles Harbor (cadmium, copper, lead, selenium, silver, tin, zinc). DDT

and other pesticides were detected in a relatively small percentage of estuarine area. 

Seventy- three percent of estuarine area had non-detectable levels of total PCBs. 

Highest levels of organic contaminants (pesticides, PAHs) generally were associated

with urbanized estuaries of southern California. 

Sediment toxicity tests with the amphipod Ampelisca abdita had control-corrected

survivorship # 80 % in only about 9 % of estuarine area. Using sediment pore water

bioassays, the control corrected, percent fertilization of eggs of the sea urchin Arbacia

punctulata was # 91 % in only about 10.5 % of estuarine area for the 100% of the water

quality adjusted (WQA) porewater treatment. Survivorship was higher for both 50% and

25% WQA porewater treatments. For a similar test using percent successful

development of Arbacia punctulata embryos, the control-corrected normal development

of embryos was # 91 % in about 49 % of area of small West Coast estuaries for the

100% of the WQA porewater treatment. Normal embryo development was higher for

both 50% and 25% WQA porewater treatments.

There was a total of 144 successful trawls across the three states, but due to the

number of stations without successful trawls, the analysis of the fish trawl data is limited

to summary statistics and species composition, and no CDFs are presented. The

number of individuals per trawl averaged 33.7 fish per trawl, with a low of 13.9 in

Oregon and a high of 68.0 in California. Species richness averaged 3.53 fish species

per trawl, with a low of 2.63 in Oregon and a high of 5.46 in California. A report on the

frequency of fish pathologies will be produced separately by NOAA.

Obtaining the target organisms (flatfish) for tissue analysis of contaminants proved

difficult, and tissue analyses were conducted on only 53% of the total stations occupied.

Thus cumulative distribution functions were not computed. There was no consistent

spatial pattern in location of maximum fish tissue metal concentrations, with highest
xviii

values of mercury being recorded in several California estuaries, highest arsenic and

lead values being recorded in several Washington estuaries, and highest copper values

being recorded in an Oregon estuary. Maximum fish tissue residues for total PCBs

were associated with urbanized estuaries in California, which were also associated with

highest sediment concentrations of these contaminants. Tissue residues of DDT and its

metabolites were considerably higher than other pesticides measured. 

A total of 187 samples of benthic infauna (>1 mm) were obtained using either grabs or a

combination of smaller corers to obtain equivalent surface area (0.1 m2

). Reflecting the

wide geographic distribution of sampling, a total of 841 non-colonial benthic taxa were

recorded. Species richness ranged from 1 to 157 taxa per sample. Lowest species

richness tended to be associated with low salinity sites, and highest species richness

was associated with salinities > 30 psu. About 50% of the area of small West Coast

estuaries had species richness # 17 species per sample. The northern California

intensive study sites tended to have lower species richness and Hr diversity values than

other stations.

Benthic infaunal abundance averaged 1378.9 individuals per sample, with lowest mean

abundance per sample in Washington estuaries and highest mean abundance values in

California estuaries, particularly the northern California intensive study sites. About

50% of the area of small West Coast estuaries had mean infaunal abundance # 151

individuals per sample. Two amphipod species (Americorophium spinicorne,

Americorophium salmonis), which had extremely high abundances in several northern

California locations, made up 54 % of total infaunal abundance in the study. Among the

10 most abundant taxa at all study sites, nonindigenous and cryptogenic (species of

uncertain geographic origin) species made up 6 % of total infaunal abundance. 

The 1999 Western Coastal EMAP study provides the first quantitative assessment of

the condition of the small estuaries of Washington, Oregon and California. When these

data are combined with the data collected in 2000 from the three largest estuarine

systems on the West Coast (Puget Sound, Columbia River, San Francisco Bay), there

will exist the first comprehensive data set for evaluating the overall condition of all

estuarine systems of the West Coast. 
1

1.0 Introduction

1.1 Program Background

Safeguarding the natural environment is fundamental to the mission of the US

Environmental Protection Agency (EPA). The legislative mandate to undertake this part

of the Agency’s mission is embodied, in part, in the Clean Water Act (CWA). Sections of

this Act require the states to report the condition of their aquatic resources and list those

not meeting their designated use (Sections 305b and 303d, respectively). Calls for

improvements in environmental monitoring date back to the late 1970’s, and have been

recently reiterated by the General Accounting Office (GAO, 2000). The GAO report

shows that problems with monitoring of aquatic resources continue to limit states’

abilities to carry out several key management and regulatory activities on water quality.

At the national level, there is a clear need for coordinated monitoring of the nation’s

ecological resources. As a response to these needs at state and national levels, the

EPA Office of Research and Development (ORD) has undertaken research to support

the Agency’s Regional Offices and the states in their efforts to meet the CWA reporting

requirements. The Environmental Monitoring and Assessment Program (EMAP) is one

of the key components of that research and EMAP-West is the newest regional

research effort in EMAP. From 1999 through 2005, EMAP-West will seek to develop

and demonstrate the tools needed to measure ecological condition of the aquatic

resources in the 14 western states in EPA’s Regions 8,9, and 10. 

The Coastal Component of EMAP-West is a partnership with the states of California,

Oregon and Washington, the National Oceanic and Atmospheric Administration, and the

Biomonitoring of Environmental Status and Trends Program (BEST) of the U.S.

Geological Survey, to measure the condition of the estuaries of these three states.

Sampling began during the summer of 1999 and the initial phase of estuarine sampling

was completed in 2000. Data from this program will be the basis for individual reports of

condition for each state, and will be used to provide data to the National Coastal

Assessment.

The US EPA’s National Coastal Assessment (NCA) is a five-year effort led by EPA’s

Office of Research and Development to evaluate the assessment methods it has

developed to advance the science of ecosystem condition monitoring. This program will

survey the condition of the Nation’s coastal resources (estuaries and offshore waters)

by creating an integrated, comprehensive coastal monitoring program among the

coastal states to assess coastal ecological condition. The NCA is accomplished

through strategic partnerships with all 24 U.S. coastal states. Using a compatible,

probabilistic design and a common set of survey indicators, each state conducts the

survey and assesses the condition of its coastal resources independently. Because of

the compatible design, these state estimates can be aggregated to assess conditions at

the EPA Regional, biogeographical, and national levels.
2

This report provides a statistical summary of the data from the first year of sampling

(1999) for the small estuarine systems of the states of Washington, Oregon, and

California (excluding Puget Sound, the main channel of the Columbia River, and San

Francisco Bay).

1.2 The Western United States Context for a Coastal Condition Assessment

Nationwide, growth of the human population is disproportionally concentrated in the

coastal zone (Culliton et al., 1990). Within the coastal region of the western U.S.,

greatest population expansion has been in the major urban areas of Seattle, Portland,

the San Francisco Bay area, and much of Southern California. These metro areas are

either directly located on coastal water bodies or, like Portland, are on major rivers and

thus influence the estuaries downstream. While development around the estuaries

between north Puget Sound and Point Reyes, CA, has been less intense, substantial

population growth is taking place across the region. Human population growth in the

coastal zone of the west is a principal driver for many ecological stressors such as

habitat loss, pollution, and nutrient enhancement which alter coastal ecosystems and

affect the sustainability of coastal ecological resources (Copping and Bryant, 1993). 

Increased globalization of the economy is a major driver influencing the introduction of

exotic species into ports and harbors. Major environmental policy decisions at local,

state and federal levels related to land use planning, growth management, habitat

restoration and resource utilization will determine the future trajectory for estuarine

conditions of the western U.S. 

Changes associated with human population growth in the western coastal region tend to

be most obvious in the larger, urban areas, but all coastal resources have been

subjected to significant alterations over the last 150 years. In one of the earliest

ecological alterations, sea otters, a known ecological keystone species (Simenstad et

al., 1978), were largely removed from western coastal ecosystems by 1810, and

populations have never recovered. The wave of western mining in the late 1800's had

limited effects on most coastal systems in terms of altering estuaries or causing

chemical pollution (Durning, 1996). Outside of the major ports, western estuaries are

believed to have generally low concentrations of toxic pollutants because of relatively

low population densities and low levels of heavy industry (Copping and Bryant, 1993),

but data for most estuaries are sparse.

Due to exploitative fishing in the Pacific Northwest, native oyster populations were

largely wiped out by the late 1800's, and salmon catch peaked by the early 1900's

(Durning, 1996). Resource exploitation for agriculture, logging and damming each

resulted in massive changes to land use practices throughout the region. In the

Chesapeake Bay region, deforestation associated with human settlement and

agricultural clearing was shown to have led to a 100% increase in sediment

accumulation rates (Cooper and Brush, 1991) during the 1800's. Sedimentation

problems associated with land use changes may be especially acute along the West

Coast north of San Francisco due to the combination of steep coastal watersheds, high
3

rainfall, and timber harvesting. Nutrient and sediment loadings from population centers

will augment the increased flux of these materials resulting from the larger scale

watershed alterations associated with logging of the coastal mountains (Howarth et al.,

1991). 

The increase in regional and international marine commerce along the West Coast has

resulted in the introduction of nonindigenous species. The effect of nonindigenous

species on estuarine habitats has only recently come under scrutiny (Carlton and

Geller, 1993), but the potential for ecological transformation is great. Some 367 marine

invertebrate taxa were recorded in the ballast water of ships arriving in Coos Bay,

Oregon, from Japan (Carlton and Geller, 1993). In Washington state, the introduction of

smooth cordgrass, Spartina alterniflora, has resulted in the conversion of hundreds of

hectares of mud flat to salt marsh habitat with consequences to the ecosystem that

have not yet been fully defined (Simenstad and Thom, 1995).

Benthic environments are areas where many types of impacts from the stressors

described above will tend to accumulate. Deposition of toxic materials, accumulation of

sediment organics, and oxygen deficiency of bottom waters typically have a greater

impact on benthic organisms than on planktonic and nektonic organisms because of

their more sedentary nature. Long-term studies of the macrobenthos (Reish, 1986;

Holland and Shaughnessey, 1986) demonstrate that macrobenthos are a sensitive

indicator of pollutant effects. Benthic assemblages are also closely linked to both lower

and higher trophic levels, as well as to processes influencing water and sediment

quality, and therefore appear to integrate responses of the entire estuarine system

(Leppäkoski, 1979; Holland and Shaughnessey, 1986).

Biologically, the EMAP Western Coastal study area is represented by two biogeographic

provinces, the Columbian Province, which extends from the Washington border with

Canada to Point Conception, California, and the Californian Province, which extends

from Point Conception to the Mexican border. Within the biogeographic provinces there

are also major transitions in the distribution of the human population. Major population

centers occur in the southern end of Puget Sound, around San Francisco Bay, and

generally surrounding most of the estuaries of southern California. In contrast, the

region of coastline from north of San Francisco Bay through northern Puget Sound has

a much lower population density. While it may be presumed that the magnitude of

anthropogenic impacts will tend to show a similar distribution, this hypothesis has not

yet been tested for West Coast estuaries. 

1.3 Objectives

The EMAP sampling program conducted in the small estuaries of the West Coast in

1999 was the first-year component of the larger EMAP Western Coastal Program, which

has the following objectives:
4

1. To assess the condition of estuarine resources of Washington, Oregon and California

based on a range of indicators of environmental quality using an integrated survey

design;

2. To establish a baseline for evaluating how the conditions of the estuarine resources

of these states change with time;

3. To develop and validate improved methods for use in future coastal monitoring and

assessment efforts in the western coastal states;

4. To transfer the technical approaches and methods for designing, conducting and

analyzing data from probability based environmental assessments to the states and

tribes.
5

2.0 Methods

2.1 Sampling Design and Statistical Analysis Methods

2.1.1 Background

The EMAP approach to evaluating the condition of ecological resources is described in

reports such as Diaz-Ramos et al. (1996), Stevens (1997), Stevens and Olsen (1999),

and is also presented in summaries provided on the internet at the URL:

http://www.epa.gov/nheerl/arm/index.htm

A brief summary from these documents follows. 

Given that it is generally impossible to completely census an extensive resource such

as the set of all estuaries on the West Coast, a more practical approach to evaluating

resource condition is to sample selected portions of the resource using probability

based sampling. Studies based on random samples of the resource rather than on a

complete census are termed sample surveys. Sample surveys offer the advantages of

being affordable, and of allowing extrapolations to be made of the overall condition of

the resource based on the random samples collected. Survey methods are widely used

in national programs such as forest inventories, agricultural statistics survey, national

resource inventory, consumer price index, labor surveys, and such activities as voter

opinion surveys.

A survey design provides the approach to selecting samples in such a way that they

provide valid estimates for the entire resource of interest. Designing and executing a

sample survey involves five steps: (1) creating a list of all units of the target population

from which to select the sample, (2) selecting a random sample of units from this list, (3)

collecting data from the selected units, (4) summarizing the data with statistical analysis

procedures appropriate for the survey design, and (5) communicating the results. The

list or map that identifies every unit within the population of interest is termed the

sampling frame. 

The sampling frame for the EMAP Western Coastal Program was developed from

USGS 1:100,000-scale digital line graphs and stored as a GIS data layer in the

ARC/INFO program. A series of programs and scripts (Bourgeois et al., 1998) was 

written to create a random sampling generator (RSG) that runs in ArcView. Site

selection consisted of using the RSG to first overlay a user-defined sampling grid of

hexagons over the spatial resource which consisted of all estuaries of the West Coast.

The area of the hexagons was controlled by adjusting the distance to hexagon centers,

and by defining how many sample stations were to be generated for each sampling

region. After the sampling grid was overlaid on the estuarine resource, the program

randomly selected hexagons and randomly located a sampling point within the hexagon. 

Only one sampling site was selected from any hexagon selected. The program
6

determined whether a sampling point fell in water or on land, and sites that fell on land

were not included. The RSG was run iteratively until a hexagon size was determined

which generated the desired number of sampling sites within the resource (Bourgeois et

al., 1998).

Hexagon size may be different for classes of estuarine systems of different areal extent. 

The final data analysis which provides the estimates of resource condition then weights

the samples based on the area of the estuarine class. Stevens (1997) terms this a

random tessellation stratified survey design applied to each estuarine resource class.

2.1.2 Sampling Design

2.1.2.1 1999 West Coast Design

The assessment of condition of small estuaries conducted in 1999 was the first phase of

a planned two-year comprehensive assessment of all estuaries of the states of

Washington, Oregon and California. The complete assessment will require the

integrated analysis of data collected from the smaller estuarine systems in 1999 and the

larger estuarine systems in 2000. The intent of the design is to be able to combine data

from all stations for analysis, using the inclusion probabilities, defined as the total

estuarine area in km2

 within a given design stratum (= estuarine size class), to weight

the representation of samples in the combined analysis.

The West Coast sampling frame was constructed as a GIS coverage that would include 

the total area of the estuarine resource of interest. Available GIS coverages were not

perfect representations of the estuarine resource, and so the coverages were defined to

ensure that they included the resource, but may have possibly included some nearby

land or inland water. The inland boundary of the sampling frame was defined as the

head of salt water influence, while the seaward boundary was defined by the confluence

with the ocean. Sample locations could fall within any water depth contained within the

estuarine resource which was bounded by the shoreline. In some cases, extremely

shallow sites were deemed inaccessible by field crews with the sampling gear specified

(Section 2.6). Emergent salt marsh areas were not included in the sampling frame

because the required indicators to deal with marsh habitats were not available. 

For the state of Washington, the 1999 design included only estuaries along the

coastline outside of the Puget Sound system, and consisted of a total of 50 sites (Table

2.1). Tributary estuaries of the Columbia River located within Washington state were

included in the 1999 sampling effort, while the main channel area was not sampled until

2000 (as part of the 2000 Oregon design). The sampling frame used three hexagonal

grid sizes to cover the size range of estuaries: 0.86, 7.79, 36.58 km2

. The hexagonal

grid sizes were used to locate random sample sites within a total of four strata

representing differing total areas of the estuarine resource in Washington (Table 2.1).

To insure some level of sampling across the entire range of estuarine sizes, sampling 

effort was partitioned as 10 stations within the smallest estuarine size class, 25 stations
7

within the two strata representing the medium sized estuaries, and 15 stations in the

largest size class. No alternate or oversample sites were included in the design.

The Oregon 1999 design included only small estuaries of the state and consisted of 50

sites. Tributary estuaries of the Columbia River located within Oregon were included in

the 1999 sampling effort, while the main channel area was not sampled until 2000. The

sampling frame for small estuaries utilized four hex sizes to cover the size range of

estuaries: 1.24, 3.46, 4.58, and 7.28 km2

. Approximately equal sampling effort was

placed in each of the four estuarine strata, which represented differing size classes of

estuaries, to insure some level of sampling across the entire range of estuarine sizes. 

An intensive sampling effort was also designed for Tillamook Bay, where a total of 30

sites were selected using a hex size of 1.04 km2

. No points from the base study design

were placed in Tillamook Bay. All sites from both the base study and intensive study

were combined for analysis. No alternate or oversample sites were included in the

design.

The 1999 California base study design included all estuaries of the state with the

exception of San Francisco Bay, and consisted of a total of 50 sites. The sampling

frame utilized three hexagonal grid sizes to cover the size range of estuaries in the

sampling frame: 0.86, 7.79, and 12.50 km2

. Approximately equal sampling effort was

placed in each of the three estuarine size classes (<5, 5-25 and >25 km2

) to ensure

some level of sampling across the entire range of estuarine sizes. No alternate or

oversample sites were selected during the design, and thus any sites which could not

be sampled were not replaced.

The estuarine systems on the northern California coast, with the exception of the Arcata

and Humboldt Bay systems, are relatively poorly studied. A number of the rivers which

discharge directly into the Pacific Ocean have been listed as failing to meet designated

uses and have been designated for development of Total Maximum Daily Loadings

(TMDL). At the request of the Region 9 Office of EPA, an intensive study was

conducted to sample the river mouth estuaries of both TMDL listed and non-TMDL

listed systems of Northern California. The purpose of this assessment was to determine

if there was any difference in the estimates of condition for the two categories of

estuarine resource. 

Using finer scale hexagonal grids, 30 sites were randomly selected at the mouths of the

river systems in Northern California. The design for this intensive study incorporated 6

differing hexagonal grid sizes: 0.0346, 0.0498, 0.0585, 0.0800, 0.0914, and 0.1060 km2

. 

The hexagonal grid sizes were used to locate random sample sites within a total of

seven strata representing differing total areas of the estuarine resource in these

Northern California river mouth systems (Table 2-1). Sample sites were divided equally

between streams with and without TMDL listings (Table 2-1). No alternate or

oversample sites were selected during the design, and thus any sites which could not

be sampled were not replaced.
8

While the intent of the California design was to be able to integrate all study sites

seamlessly into combined analyses, an inadvertent design change occurred which

somewhat complicates interpretation of results. In defining the target population for the

Northern California sites, a restriction of sampling to a distance of 0.25 km from the

estuarine mouth was imposed. This definition differs from that of the remainder of the

West Coast assessment which used a target population defined by the head of salt in

the estuary. In order to prevent duplicative sampling effort, the intensive study of

northern California small river systems had been excluded from the frame for the base

California study. Thus, a small area (approximately 10 km2

) representing the portion of

the Northern California river systems excluded from the intensive study was

inadvertently omitted from the California sampling frame.

2.1.2.2 2000 West Coast Design

While results of the 2000 sampling effort are not presented in this report, a description

of the sample design for 2000 is provided in order to demonstrate the overall plan for

the western coastal assessment effort. 

The Washington 2000 sampling design included only the large “estuary” of Puget

Sound and its tributaries. Site selection for this estuary used a combined approach in

order to allow collaboration with a survey previously conducted by NOAA under the

NOAA National Status and Trends Program. The overall design combined the existing

NOAA probability based, randomized monitoring design with the EMAP Western

Coastal study design. The EMAP hexagonal grid was extended to include Canadian

waters at the north end of Puget Sound, and then was overlaid on the existing NOAA

monitoring sites. If a NOAA site fell within a hexagon, the site was designated as the

EMAP sampling point. If not, a random site was selected based on the EMAP

protocols. The design incorporated three different hex sizes, two covering most of the

Puget Sound region (86.6, 250.28 km2

), and one used for intensifying in the region of

the San Juan Islands (21.65 km2

). There were 41 stations selected based on the NOAA

sampling stations, in addition to 30 new EMAP stations, of which 10 were associated

with the San Juan Islands. No alternate or oversampling sites were included in the

design frame.

The Oregon 2000 design included only the main channel area of Columbia River. The

Columbia River system was split into two subpopulations, the lower, saline portion and

the upper, freshwater portion, with hex sizes of 13.85 and 5.4 km2

 and total numbers of

stations of 20 and 30, respectively. No alternate or oversample sites were included in

the design.

The 2000 California design included only San Francisco Bay and its tributaries. Site

selection for this estuary used a combined approach in order to allow collaboration with

a survey being conducted by NOAA under the NOAA National Status and Trends

Program. An EMAP sampling design was developed specifically for NOAA to implement

a multiyear monitoring program to characterize condition of the small systems within the
9

San Francisco Bay. To insure complete coverage of the bay for the EMAP Western

Coastal study, the NOAA design was augmented with a sampling design which split the

Bay into two subpopulations (open bay and smaller surrounding systems). For the open

bay, a hex size of 36.58 km2

 was used and 31 sites were generated. For the smaller

systems, a different hexagon size (3.46 km2 ) was used to generate 19 sites for

sampling. This grid was overlaid on the newly designed NOAA small systems

monitoring project. If a NOAA site fell within a hexagon, the site was used as the

sampling point. If not, a random point was generated based on the standard

randomization routines used by Western Coastal EMAP as part of the National Coastal

Assessment. No alternate or oversample sites were selected.
10

Figure 2-1. Location of Washington EMAP survey sites.
11

Figure 2-2. Location of EMAP survey sites along the northern portion of the Oregon

coast, including survey sites for the intensification study of Tillamook Bay. 
12

Figure 2-3. Location of EMAP survey sites along the southern portion of the Oregon

coast.
13

Figure 2-4. Location of EMAP survey sites for the intensification study of Tillamook

Bay, Oregon.
14

Figure 2-5. Location of California EMAP survey sites in Northern California from the

Oregon border to the Garcia River. 
15

Figure 2-6. Location of California EMAP survey sites in Northern and Central California

from the Russian River to the Santa Ynez River.
16

Figure 2-7. Location of California EMAP survey sites in Central and Southern California

from Santa Barbara to the Mexican border.
17

Table 2-1. West Coast sampling sites with station coordinates of locations sampled. 

The northern California small estuary TMDL study sites are noted as either Y = TMDL

Site, N = Non-TMDL Site. Frame area represents the total estuarine area within a

stratum. An * in a station location indicates the site was abandoned prior to sampling.

EMAP Sta. No. Latitude Longitude Estuary Hex Frame Area Stratum TMDL

Size km2

WA99-0001 48.320 -124.680 Makah Bay 7.79 77.288 WA99-002 N/A

WA99-0002 48.314 -124.670 Makah Bay 7.79 77.288 WA99-002 N/A

WA99-0003 48.305 -124.671 Makah Bay 7.79 77.288 WA99-002 N/A

WA99-0004 48.288 -124.365 Hoko River 0.86 8.363 WA99-001 N/A

WA99-0005 48.181 -124.708 Ozette River 0.86 8.363 WA99-001 N/A

WA99-0006 48.149 -123.633 Freshwater Bay 7.79 77.288 WA99-002 N/A

WA99-0007 48.148 -123.601 Freshwater Bay 7.79 77.288 WA99-002 N/A

WA99-0008 48.143 -123.616 Freshwater Bay 7.79 77.288 WA99-002 N/A

WA99-0009 48.160 -123.148 Dungeness Bay 7.79 111.478 WA99-003 N/A

WA99-0010 48.079 -122.900 Discovery Bay 7.79 111.478 WA99-003 N/A

WA99-0011 48.058 -122.905 Discovery Bay 7.79 111.478 WA99-003 N/A

WA99-0012 48.021 -122.859 Discovery Bay 7.79 111.478 WA99-003 N/A

WA99-0013 48.003 -122.843 Discovery Bay 7.79 111.478 WA99-003 N/A

WA99-0014 47.997 -122.874 Discovery Bay 7.79 111.478 WA99-003 N/A

WA99-0015 47.606 -124.373 KalalochCreek 0.86 8.363 WA99-001 N/A

WA99-0016 47.463 -124.339 Raft River 0.86 8.363 WA99-001 N/A

WA99-0017 47.347 -124.298 Quinault River 7.79 77.288 WA99-002 N/A

WA99-0018 * * Quinault River 7.79 77.288 WA99-002 N/A

WA99-0019 47.089 -124.176 Conner Creek 0.86 8.363 WA99-001 N/A

WA99-0020 47.004 -124.040 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0021 47.005 -124.000 Grass Creek 0.86 8.363 WA99-001 N/A

WA99-0022 46.966 -123.951 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0023 46.940 -124.104 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0024 46.935 -124.028 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0025 46.967 -123.858 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0026 46.921 -124.067 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0027 46.873 -124.034 Beardslee Slough 0.86 8.363 WA99-001 N/A

WA99-0028 46.870 -124.022 Beardslee Slough 0.86 8.363 WA99-001 N/A

WA99-0029 46.848 -124.032 Grays Harbor 36.58 562.230 WA99-004 N/A

WA99-0030 46.715 -124.045 Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0031 46.704 -123.887 Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0032 * * Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0033 46.650 -124.012 Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0034 46.567 -123.942 Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0035 46.539 -123.924 Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0036 46.418 -123.418 Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0037 * * Willapa Bay 36.58 562.230 WA99-004 N/A

WA99-0038 46.310 -124.009 Baker Bay 7.79 111.478 WA99-003 N/A

WA99-0039 46.301 -124.026 Baker Bay 7.79 111.478 WA99-003 N/A

WA99-0040 46.273 -123.973 Baker Bay 7.79 111.478 WA99-003 N/A

WA99-0041 * * Grays River 0.86 8.363 WA99-001 N/A

WA99-0042 46.263 -123.998 Baker Bay 7.79 111.478 WA99-003 N/A

WA99-0043 46.302 -123.711 Grays Bay 7.79 111.478 WA99-003 N/A

WA99-0044 46.300 -123.698 Grays Bay 7.79 111.478 WA99-003 N/A

WA99-0045 46.295 -123.703 Grays Bay 7.79 111.478 WA99-003 N/A

WA99-0046 46.287 -123.727 Grays Bay 7.79 111.478 WA99-003 N/A

WA99-0047 46.275 -123.717 Grays Bay 7.79 111.478 WA99-003 N/A

WA99-0048 46.095 -122.922 Cowlitz River 7.79 77.288 WA99-002 N/A

WA99-0049 46.085 -122.880 Carrolls Channel 7.79 77.288 WA99-002 N/A

WA99-0050 45.947 -122.786 Martin Slough 0.86 8.363 WA99-001 N/A

OR99-0001 46.188 -123.912 Youngs Bay 3.46 43.192 OR99-003 N/A

OR99-0002 46.211 -123.724 Cathlamet Bay 3.46 43.192 OR99-003 N/A

OR99-0003 46.180 -123.865 Youngs Bay 3.46 43.192 OR99-003 N/A

OR99-0004 46.217 -123.672 Cathlamet Bay 3.46 43.192 OR99-003 N/A

OR99-0005 46.167 -123.893 Youngs Bay 3.46 43.192 OR99-003 N/A

OR99-0006 46.208 -123.688 Cathlamet Bay 3.46 43.192 OR99-003 N/A

OR99-0007 46.169 -123.872 Youngs Bay 3.46 43.192 OR99-003 N/A

OR99-0008 46.226 -123.588 Marsh Island Creek 1.24 13.578 OR99-001 N/A

OR99-0009 46.190 -123.744 Cathlamet Bay 3.46 43.192 OR99-003 N/A

Table continued on next page
18

OR99-0010 46.189 -123.746 Cathlamet Bay 3.46 43.192 OR99-003 N/A

OR99-0011 46.186 -123.681 Cathlamet Bay 3.46 43.192 OR99-003 N/A

OR99-0012 46.149 -123.817 Youngs River 7.28 99.605 OR99-002 N/A

OR99-0013 46.187 -123.592 Knappa Slough 1.24 13.578 OR99-001 N/A

OR99-0014 46.170 -123.144 Bradbury Slough 7.28 99.605 OR99-002 N/A

OR99-0015 46.134 -123.272 Wallace Slough 7.28 99.605 OR99-002 N/A

OR99-0016 46.129 -123.226 Clatskanie River 1.24 13.578 OR99-001 N/A

OR99-0017 46.123 -123.036 Rinearson Slough 1.24 13.578 OR99-001 N/A

OR99-0018 45.691 -123.899 Nehalem River 7.28 99.605 OR99-002 N/A

OR99-0019 45.394 -123.953 Netarts Bay 7.28 99.605 OR99-002 N/A

OR99-0020 45.197 -123.961 Nestucca River 1.24 13.578 OR99-001 N/A

OR99-0021 45.166 -123.944 Little Nestucca River 1.24 13.578 OR99-001 N/A

OR99-0022 45.040 -123.994 Salmon River 1.24 13.578 OR99-001 N/A

OR99-0023 44.925 -124.018 Siletz Bay 7.28 99.605 OR99-002 N/A

OR99-0024 44.622 -124.034 Yaquina Bay 7.28 99.605 OR99-002 N/A

OR99-0025 44.599 -124.016 Yaquina River 7.28 99.605 OR99-002 N/A

OR99-0026 44.574 -123.963 Yaquina River 7.28 99.605 OR99-002 N/A

OR99-0027 44.414 -123.999 Alsea River 1.24 13.578 OR99-001 N/A

OR99-0028 44.305 -124.115 Yachats River 1.24 13.578 OR99-001 N/A

OR99-0029 44.188 -124.036 Rock Creek 1.24 13.578 OR99-001 N/A

OR99-0030 44.011 -124.126 Siuslaw River 7.28 99.605 OR99-002 N/A

OR99-0031 44.022 -123.881 Siuslaw River 7.28 99.605 OR99-002 N/A

OR99-0032 44.740 -124.136 Umpqua River 4.58 59.163 OR99-004 N/A

OR99-0033 43.762 -124.005 Smith River (OR) 7.28 99.605 OR99-002 N/A

OR99-0034 43.725 -124.146 Umpqua River 4.58 59.163 OR99-004 N/A

OR99-0035 44.772 -123.903 Smith River (OR) 7.28 99.605 OR99-002 N/A

OR99-0036 43.722 -124.124 Umpqua River 4.58 59.163 OR99-004 N/A

OR99-0037 43.693 -124.100 Scholfield Creek 1.24 13.578 OR99-001 N/A

OR99-0038 43.692 -124.065 Umpqua River 4.58 59.163 OR99-004 N/A

OR99-0039 43.423 -124.246 Coos Bay 4.58 59.163 OR99-004 N/A

OR99-0040 43.414 -124.207 Coos Bay 4.58 59.163 OR99-004 N/A

OR99-0041 43.406 -124.218 Coos Bay 4.58 59.163 OR99-004 N/A

OR99-0042 43.386 -124.292 Coos Bay 4.58 59.163 OR99-004 N/A

OR99-0043 43.404 -124.199 Coos Bay 4.58 59.163 OR99-004 N/A

OR99-0044 43.368 -124.304 Coos Bay 4.58 59.163 OR99-004 N/A

OR99-0045 43.341 -124.320 South Slough 7.28 99.605 OR99-002 N/A

OR99-0046 43.370 -124.148 Coos River 1.24 13.578 OR99-001 N/A

OR99-0047 43.377 -124.108 Coos River 1.24 13.578 OR99-001 N/A

OR99-0048 43.350 -124.169 Catching Slough 1.24 13.578 OR99-001 N/A

OR99-0049 43.321 -124.154 Catching Slough 1.24 13.578 OR99-001 N/A

OR99-0050 42.423 -124.419 Rogue River 7.28 99.605 OR99-002 N/A

OR99-0051 45.552 -123.929 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0052 45.547 -123.935 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0053 45.551 -123.912 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0054 45.534 -123.935 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0055 45.539 -123.923 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0056 45.536 -123.932 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0057 45.538 -123.906 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0058 45.528 -123.929 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0059 45.531 -123.912 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0060 45.524 -123.929 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0061 45.517 -123.934 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0062 45.524 -123.912 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0063 45.511 -123.921 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0064 45.517 -123.891 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0065 45.509 -123.933 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0066 45.515 -123.901 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0067 45.503 -123.933 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0068 45.509 -123.911 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0069 45.511 -123.891 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0070 45.498 -123.887 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0071 45.506 -123.895 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0072 45.498 -123.908 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0073 45.497 -123.891 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0074 45.491 -123.894 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0075 45.501 -123.869 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0076 45.495 -123.894 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0077 45.491 -123.900 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0078 45.481 -123.900 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0079 45.468 -123.885 Tillamook Bay 1.04 33.732 OR99-005 N/A

OR99-0080 45.441 -123.877 Tillamook River 1.04 33.732 OR99-005 N/A
19

CA99-0001 41.162 -124.118 Big Lagoon 7.79 102.651 CA99-002 N/A

CA99-0002 40.837 -124.117 Arcata Bay 12.5 268.504 CA99-001 N/A

CA99-0003 40.824 -124.142 Arcata Bay 12.5 268.504 CA99-001 N/A

CA99-0004 40.720 -124.238 Humboldt Bay 12.5 268.504 CA99-001 N/A

CA99-0005 40.703 -124.258 Humboldt Bay 12.5 268.504 CA99-001 N/A

CA99-0006 38.287 -123.028 Bodega Bay 12.5 268.504 CA99-001 N/A

CA99-0007 38.263 -123.012 Bodega Bay 12.5 268.504 CA99-001 N/A

CA99-0008 38.249 -122.978 Bodega Bay 12.5 268.504 CA99-001 N/A

CA99-0009 38.104 -122.848 Tomales Bay 12.5 268.504 CA99-001 N/A

CA99-0010 38.015 -122.917 Drakes Bay 12.5 268.504 CA99-001 N/A

CA99-0011 38.006 -122.910 Drakes Bay 12.5 268.504 CA99-001 N/A

CA99-0012 38.006 -122.873 Drakes Bay 12.5 268.504 CA99-001 N/A

CA99-0013 38.002 -122.865 Drakes Bay 12.5 268.504 CA99-001 N/A

CA99-0014 36.961 -122.019 Santa Cruz Harbor 7.79 102.651 CA99-002 N/A

CA99-0015 36.859 -121.801 Pajaro River 0.86 13.837 CA99-003 N/A

CA99-0016 36.633 -121.845 Monterey Harbor 7.79 102.651 CA99-002 N/A

CA99-0017 36.628 -121.853 Monterey Harbor 7.79 102.651 CA99-002 N/A

CA99-0018 36.537 -121.930 Carmel Bay 7.79 102.651 CA99-002 N/A

CA99-0019 36.525 -121.936 Carmel Bay 7.79 102.651 CA99-002 N/A

CA99-0020 35.346 -120.847 Morro Bay 7.79 102.651 CA99-002 N/A

CA99-0021 35.318 -120.858 Morro Bay 7.79 102.651 CA99-002 N/A

CA99-0022 35.171 -120.737 San Luis Obispo Bay 7.79 102.651 CA99-002 N/A

CA99-0023 35.173 -120.725 San Luis Obispo Bay 7.79 102.651 CA99-002 N/A

CA99-0024 35.161 -120.710 San Luis Obispo Bay 7.79 102.651 CA99-002 N/A

CA99-0025 34.692 -120.597 Santa Ynez River 0.86 13.837 CA99-003 N/A

CA99-0026 34.407 -119.693 Santa Barbara Harbor 0.86 13.837 CA99-003 N/A

CA99-0027 34.354 -119.309 Ventura River 0.86 13.837 CA99-003 N/A

CA99-0028 34.180 -119.230 Channel Islands Harbor 0.86 13.837 CA99-003 N/A

CA99-0029 34.167 -119.227 Channel Islands Harbor 0.86 13.837 CA99-003 N/A

CA99-0030 34.097 -119.079 Point Mugu Lagoon 0.86 13.837 CA99-003 N/A

CA99-0031 33.844 -118.395 King Harbor 0.86 13.837 CA99-003 N/A

CA99-0032 33.777 -118.242 Los Angeles River 0.86 13.837 CA99-003 N/A

CA99-0033 33.742 -118.252 Los Angeles Harbor 12.5 268.504 CA99-001 N/A

CA99-0034 33.755 -118.154 Long Beach Harbor 7.79 102.651 CA99-002 N/A

CA99-0035 33.741 -118.177 Long Beach Harbor 7.79 102.651 CA99-002 N/A

CA99-0036 33.730 -118.256 Los Angeles Harbor 12.5 268.504 CA99-001 N/A

CA99-0037 33.743 -118.140 Long Beach Harbor 7.79 102.651 CA99-002 N/A

CA99-0038 33.724 -118.214 Los Angeles Harbor 12.5 268.504 CA99-001 N/A

CA99-0039 33.719 -118.233 Los Angeles Harbor 12.5 268.504 CA99-001 N/A

CA99-0040 33.461 -117.702 Dana Point Harbor 0.86 13.837 CA99-003 N/A

CA99-0041 33.234 -117.412 Santa Margarita River 0.86 13.837 CA99-003 N/A

CA99-0042 33.145 -117.342 Agua Hedionda Creek 0.86 13.837 CA99-003 N/A

CA99-0043 33.143 -117.339 Agua Hedionda Creek 0.86 13.837 CA99-003 N/A

CA99-0044 32.772 -117.210 Mission Bay 7.79 102.651 CA99-002 N/A

CA99-0045 32.755 -117.248 San Diego River 0.86 13.837 CA99-003 N/A

CA99-0046 32.759 -117.219 San Diego River 0.86 13.837 CA99-003 N/A

CA99-0047 32.727 -117.215 San Diego Bay 12.5 268.504 CA99-001 N/A

CA99-0048 32.726 -117.180 San Diego Bay 12.5 268.504 CA99-001 N/A

CA99-0049 32.651 -117.129 San Diego Bay 12.5 268.504 CA99-001 N/A

CA99-0050 32.639 -117.138 San Diego Bay 12.5 268.504 CA99-001 N/A

CA99-0051 41.945 -124.201 Smith River (CA) 0.10 0.654 CA99-006 N

CA99-0052 41.947 -124.204 Smith River (CA) 0.106 0.654 CA99-006 N

CA99-0053 41.944 -124.197 Smith River (CA) 0.106 0.654 CA99-006 N

CA99-0054 41.941 -124.196 Smith River (CA) 0.106 0.654 CA99-006 N

CA99-0055 41.937 -124.196 Smith River (CA) 0.106 0.654 CA99-006 N

CA99-0056 41.606 -124.100 Wilson Creek 0.08 0.014 CA99-004 N

CA99-0057 41.605 -124.101 Wilson Creek 0.08 0.014 CA99-004 N

CA99-0058 41.547 -124.081 Klamath River 0.0346 0.309 CA99-009 Y

CA99-0059 41.546 -124.075 Klamath River 0.0346 0.309 CA99-009 Y

CA99-0060 41.541 -124.079 Klamath River 0.0346 0.309 CA99-009 Y

CA99-0061 41.028 -124.112 Little River 0.08 0.018 CA99-005 N

CA99-0062 41.027 -124.109 Little River 0.08 0.018 CA99-005 N

CA99-0063 40.644 -124.305 Eel River 0.0914 0.219 CA99-010 Y

CA99-0064 40.646 -124.304 Eel River 0.0914 0.219 CA99-010 Y

CA99-0065 40.475 -124.388 Bear River 0.08 0.018 CA99-005 N

CA99-0066 39.427 -123.808 Noyo River 0.0585 0.427 CA99-007 Y

CA99-0067 39.417 -123.812 Hare Creek 0.08 0.018 CA99-005 N

CA99-0068 39.418 -123.809 Hare Creek 0.08 0.018 CA99-005 N

CA99-0069 39.361 -123.815 Caspar Creek 0.08 0.014 CA99-004 N

CA99-0070 39.303 -123.794 Big River 0.0585 0.427 CA99-007 Y

Table continued on next page
20

CA99-0071 39.226 -123.770 Albion River 0.0914 0.219 CA99-010 Y

CA99-0072 39.225 -123.768 Albion River 0.0914 0.219 CA99-010 Y

CA99-0073 39.227 -123.764 Albion River 0.0914 0.219 CA99-010 Y

CA99-0074 39.103 -123.707 Elk Creek 0.08 0.014 CA99-004 N

CA99-0075 39.102 -123.705 Elk Creek 0.08 0.014 CA99-004 N

CA99-0076 38.954 -123.730 Garcia River 0.0585 0.427 CA99-007 Y

CA99-0077 38.451 -123.127 Russian River 0.0498 0.104 CA99-008 Y

CA99-0078 38.449 -123.125 Russian River 0.0498 0.104 CA99-008 Y

CA99-0079 38.307 -122.995 Estero Americano 0.0585 0.427 CA99-007 Y

CA99-0080 38.270 -122.976 Estero San Antonio 0.0585 0.427 CA99-007 Y
21

2.2 Data Analysis

Analysis of indicator data was conducted by calculation of cumulative distribution

functions (CDFs), an analysis approach that has been used extensively in other EMAP

coastal studies (Summers et al., 1993; Strobel et al.,1994; Hyland et al., 1996). The

CDFs describe the full distribution of indicator values in relation to their areal extent

across the sampling region of interest. The approximate 95% confidence intervals for

the CDFs also were computed based on estimates of variance. A detailed discussion of

methods for calculation of the CDFs used in EMAP analyses is provided in Diaz-Ramos

et al. (1996). 

The Horvitz-Thompson ratio estimate of the CDF is given by the formula:

1

1

1 ( ) 1 () ;

( ) = estimated CDF (proportion) for indicator value 

n = number of samples

= the sample response for site i

= the k th CDF response indicator

1, ( )

i k

k

k k

i

k

i

i k

n

n i i

i i

ly x

Fx N

N

Fx x

y

x

y ly x

π

π

∧ ∧ =

∧

=

∧

≤

= =

≤

≤ =

∑

∑

0,

 = selection probability for site i

 = the estimated population size

k

i

x

otherwise

N

π

∧

⎧

⎨

⎩

The selection probability for a site is 1/area of the hexagon, e.g. the hexagon area of

California estuaries in the base study in the size class 5-25 km2

. When calculating the

mean for a variable, the same equation is used with Yi

 replacing the indicator function.
22

The Horvitz-Thompson unbiased estimate of the variance for the ratio estimate is given

by the formula:

2

2

2

1 11

1

11 1

[ ( )] ;

1 , ( ) ( ), ( ) ( )

( ) = estimated CDF (proportion) for indicator value 

1, ( ) 0,

k

i k k jk k

k k

i k

i k

k

n nn

i

i j

i ij i i j ij

n

i j i i

d d d

V Fx

N

N d ly x Fx d ly x Fx

Fx x

y x ly x otherwise

x

π ππ π

π

∧ ∧ = =≠

∧

∧ ∧∧

=

∧

⎛ ⎞

+ − ⎜ ⎟

⎝ ⎠ =

= = ≤− = ≤−

⎧ ≤

≤ = ⎨

⎩

∑ ∑∑

∑

th

th

th

= the k indicator level of interest

 = value of indicator for the i unit sampled

 = inclusion density evaluated at the location

 of the i sample point

 = joint inclusion density evaluat

i

i

ij

y

π

π

th th

ed at the locations

 of the i and j sample points

n = number of units sampled

The joint inclusion probabilities are given by

 π π

π − = ( 1) * i j

ij

n

n
23

When estimating the CDF across several strata, the above estimates for each stratum

must be combined. The equations are

∧ ∧

=

∧

∧

⎛ ⎞ = ⎜ ⎟ ⎝ ⎠ ∑

1

() ()

( ) = estimated CDF

( ) = estimated CDF for stratum i

 = area for stratum i

S = number of strata

A = total area of all strata

k k

k

k

s

i

i

i

i

i

A Fx Fx

A

F x

F x

A

and the variance estimate across strata is

∧ ∧

=

∧

∧

⎛ ⎞ = ⎜ ⎟ ⎝ ⎠ ∑

2

1

 = estimated variance for all strata

 = estimated variance for stratum i

 = area for stratum i

S = number of strata

A = total area of all strata

s

i

i

i

i

i

A V V

A

V

V

A
24

2.3 Indicators

The condition of West Coast estuarine resources was evaluated by collecting data for a

standard set of environmental parameters at all stations within the survey (Table 2-2). 

Field procedures followed methods outlined in the USEPA National Coastal Assessment

Field Operations Manual (USEPA, 2001b). The environmental indicators were similar to

those used in previous EMAP estuarine surveys in other regions of the country

(Weisberg et al., 1992; Macauley et al., 1994, 1995; Strobel et al., 1994, 1995; Hyland

et al., 1996, 1998). Indicators were divided into those representing general habitat

condition (Habitat Indicators), condition of benthic and demersal faunal resources (Biotic

Condition Indicators), and exposure to pollutants (Exposure Indicators). Habitat

indicators describe the general physical and chemical conditions at the study site, and

are often important in providing information used to interpret the results of biotic

condition indicators (e.g., salinity and sediment grain size with regard to benthic

community composition). Biotic condition indicators are measures of the status of the

benthic biological resources in response to site environmental conditions. The

Exposure indicators used in this survey quantify the amounts and types of pollutant

materials (metals, hydrocarbons, pesticides) that may be harmful to the biological

resources present. Some indicators may overlap the above categories. For example,

dissolved oxygen is clearly an indicator of habitat condition, but may also be considered

an exposure indicator because of the potentially harmful effects of low dissolved oxygen

levels to many members of the benthic community. 

In addition to the core set of indicators, a number of supplemental indicators were

conducted either by EMAP or by external collaborators during the EMAP Western

Coastal survey (Table 2-3). An additional sediment toxicity test was conducted for the

California stations composing the base study. The amphipod Eohaustorius estuarius

acute toxicity test was used in order to compare the sensitivity of this species with

Ampelisca abdita, which is the most commonly used amphipod bioassay species in the

EMAP program. Scientists with the USGS/BEST program conducted two sediment

porewater toxicity tests using the sea urchin Arbacia punctulata (fertilization toxicity test,

embryo development toxicity test) (USGS, 2000), and conducted the H4IIE bioassay

(bioassay-derived 2,3,7,8-tetrachlorodibenzo - p -dioxin equivalents (TCDD-EQ)) for

exposure of fish to planar halogenated hydrocarbons (USGS, 2001). Results of the sea

urchin bioassay tests are included in the present report, while the details of the H4IIe

bioassay are provided in USGS (2001). Results of the Eohaustorius toxicity test are not

presented here, since this test was done only with California sediments, but will be

provided in a separate statistical data report for the state of California.
25

Table 2-2. Core environmental indicators for the EMAP Western Coastal survey.

Habitat Indicators Benthic Condition Indicators

 Salinity Infaunal species composition

 Water depth Infaunal abundance

 pH Infaunal species richness and diversity

 Water temperature Demersal fish species composition

 Total suspended solids Demersal fish abundance

 Chlorophyll a concentration Demersal fish species richness and

diversity

 Nutrient concentrations (nitrates,

 nitrites, ammonia, & phosphate)

 External pathological anomalies in fish

 Percent light transmission Exposure Indicators

 Secchi depth Dissolved oxygen (DO) concentration

 Percent silt-clay of sediments Sediment contaminants

 Percent total organic carbon (TOC)

 in sediments

 Fish tissue contaminants

 Sediment toxicity (Ampelisca abdita

acute toxicity test)
26

Table 2-3. Environmental indicators under development or conducted by collaborators

during the EMAP Western Coastal survey.

Benthic Condition Indicators

West Coast benthic infaunal index - EMAP

Exposure Indicators

Sediment toxicity (amphipod Eohaustorius estuarius acute toxicity test) - EMAP

(California only)

Sediment porewater toxicity (sea urchin Arbacia punctulata fertilization toxicity test) -

USGS/BEST1

Sediment porewater toxicity (sea urchin Arbacia punctulata embryo development

toxicity test) - USGS/BEST1

H4IIE Bioassay-derived 2,3,7,8-tetrachlorodibenzo - p -dioxin equivalents (TCDD-EQ)

for exposure of fish to planar halogenated hydrocarbons - USGS/BEST2

1 USGS, 2000

2 USGS, 2001
27

2.3.1 Water Measurements

2.3.1.1 Hydrographic Profile

Water column profiles were performed at each site to measure dissolved oxygen (DO),

salinity, temperature, pH, and depth. Both secchi depth and a measurement of light

attenuation using photosynthetically active radiation (PAR) were made at each station. 

Methods and procedures used for hydrographic profiling follow guidance provided in the

NCA Quality Assurance Project Plan document (US EPA, 2001).

Basic water quality parameters were measured by different instruments in each state. 

Washington field crews used the Seabird SBE 19 CTD with data logging capability. In

Oregon there were two field crews. The Oregon Dept. of Environmental Quality field

crew used a YSI 6920 datasonde. The field crew provided by National Marine Fisheries

Service used a Hydrolab datasonde. California used a Hydrolab Datasonde 4a with a

cable connection to a deck display. Prior to conducting a CTD (Conductivity,

Temperature, Depth) cast, the instrument was allowed 2-3 minutes of warmup while

being maintained near the surface, after which the instrument was slowly lowered at the

rate of approximately 1 meter per second during the down cast. Individual

measurements were made at discrete intervals (with sufficient time for equilibration) as

follows:

Shallow sites (# 2 m) - 0.5-m intervals;

Typical depths (>2<10 m) - 0.5 m (near-surface) and every 1-m interval to nearbottom (0.5 m off-bottom);

Deep sites (>10 m) - 0.5 m (near-surface) and every 1-m interval to 10 m, then at

5-m intervals, thereafter, to near-bottom (0.5 m off-bottom).

Near-bottom conditions were measured at 0.5 m above the bottom by first ascertaining

whether the instrument was on the bottom (slack line/cable), and then pulling it up

approximately 0.5 m. A delay of 2-3 minutes was used to allow disturbed conditions to

settle before taking the near-bottom measurements. The profile was repeated on the

ascent and recorded for validation purposes, but only data from the descent were

reported in the final data. 

Measurements of light penetration were recorded using a hand-held LiCor LI-1400 light

meter for conditions at discrete depth intervals in a manner similar to that for profiling

water quality parameters with the hand-held water quality probes. The underwater

sensor was hand lowered according to the regime described above and at each discrete

interval, the deck reading and underwater reading were recorded. If the light

measurements became negative before reaching bottom, the measurement was

terminated at that depth. The profile was repeated on the ascent. As an indicator of

water column light conditions, the transmissivity at 1 m depth was calculated. 
28

The California field crew measured ambient light data in two ways. The Hydrolab

datasonde unit had a LiCor spherical irradiance sensor (LI -193SA) mounted to the

sensor package. For boat deployments, the deck sensor recording ambient light was a

cosine collector (LI-190SA)). However, many of the California sample locations were

too shallow to allow sampling from a boat, and required walking in to the sample site. At

these stations, the field crew took ambient irradiance with the spherical sensor in air,

and then took several subsurface readings with the same sensor. The difference in

geometry between the deck reference sensor and submerged sensor was corrected for

during the analysis of light transmission. An empirical comparison of similar LiCor

spherical and flat sensors, both calibrated for air measurements, was conducted. The

spherical sensor collected an average of two times the light measured by the flat

sensor. All ambient light measurements for California stations sampled by boat were

first corrected by this factor. The minimum depth where the first submerged light

reading was taken varied widely among stations, which made inter-station comparison

difficult. Therefore, the submerged and corresponding in air light measurements,

together with the depth of the measurement, were used to compute the light extinction

coefficient k, using the relationship k = (ln(I0) - ln(Id))/d , where I0 = in air measure of

light, Id = submerged light, and d = the depth of the first submerged light measurement.

The value of k that was computed was assumed to characterize the light attenuation

down to a depth of 1m, and light at a depth of 1 m (I1m) was then calculated as I1m = e(-

kd), where d = 1m. Percent light transmission at 1m was then computed as (I1m / I0) * 100. 

Secchi depth was determined by using a standard 20-cm diameter black and white

secchi disc. The disc was lowered to the depth at which it could no longer be discerned,

then was slowly retrieved until it just reappeared. The depth of reappearance was

recorded as secchi depth (rounded to the nearest 0.5 m).

2.3.1.2 Water Quality Indicators

The water column was sampled at each site for dissolved nutrients (N and P species),

chlorophyll a concentration, and total suspended solids (TSS). Sampling varied slightly

among the states but generally followed the guidance provided in the NCA Quality

Assurance Project Plan document (US EPA, 2001). At shallow sites (<2 m), water

samples were taken at 0.5 m (near-surface) and 0.5 m off-bottom. If the depth was so

shallow that the near-surface and near-bottom overlapped, then only a mid-depth

sample was taken. For sites deeper than 2 m, samples were taken at 0.5 m (nearsurface), mid-depth, and 0.5 m off-bottom.

For TSS analysis, 1 liter of unfiltered seawater was collected at the depths described

above. The samples were held in 1-L polypropylene bottles on wet ice in the field and

stored at 4°C until analyzed. 

For Washington samples, water used for nutrient, chlorophyll, and dissolved oxygen

samples was collected from discrete depths using 1.7-liter Nisken bottle and transferred

to two 66-ml plastic bottles. The chlorophyll samples were filtered by placing them in a
29

funnel containing a 0.7-:m GFF filter attached to a receiving bottle. A hand pump was

used to pull the seawater past the filter and into a receiving flask. The GFF filter was

then folded in half and placed in a labeled glass centrifuge tube containing 10 ml of 90

% acetone, and placed on ice until the tubes could be frozen at the end of the day. A

0.45-:m syringe filter was used with a pre-cleaned, 60-ml plastic syringe to filter

approximately 40 ml of water for nutrient analyses into 60-ml plastic bottles. 

In California, samples were obtained by using a Wildco 1.2-liter stainless steel

Kemmerer sampler. A second water sample was collected from each of the same

depths and an approximately 1-liter subsample was poured into a clean, wide-mouth

polycarbonate container for the chlorophyll and nutrient analyses. Two disposable,

graduated 50-cc polypropylene syringes fitted with a stainless steel or polypropylene

filtering assembly were used to filter the water sample through 0.7-:m GFF filters, and

the volume of water (up to 200 ml for each syringe) filtered was recorded. Both filters

were carefully removed using tweezers, folded once upon the pigment side, placed in a

prelabeled, disposable petri dish, and capped. The petri dish was wrapped in aluminum

foil, placed in a small styrofoam ice chest with several pounds of dry ice, and kept

frozen until analyzed. The syringe and filtering assembly were washed with deionized

water and stored in a clean compartment between sampling stations. For nutrients,

approximately 40 ml of filtrate from the chlorophyll filtration (surface water) were

collected into two prelabeled, clean 60-ml Nalgene screw-capped bottles, stored in the

dry ice chest, and kept frozen on dry ice until analyzed. 

Dissolved Oxygen was measured at Washington stations with a Beckman DO sensor

deployed on the Seabird CTD, at Oregon stations with a Yellow Springs Instruments

model 6562 DO sensor on the YSI datasonde, and at California stations with a Hydrolab

DO sensor on the Hydrolab datasonde. 

2.3.2 Sediment Toxicity Testing

2.3.2.1 Sediment Collection for Toxicity Testing, Chemical Analysis and Grain Size

Combined sediment for toxicity testing and chemical analysis was collected at all sites

from the top 2-3 centimeters of surficial sediment. Procedures for sediment collection

followed the guidance provided in the NCA Quality Assurance Project Plan document

(US EPA, 2001). Where possible, sediment grabs were taken with a 0.1-m2 van Veen

sampler. The top 2-3 centimeters of surficial sediment were scooped from each

individual grab, composited in a pre-cleaned container and homogenized within the

container by thorough stirring. Sediment from 2-9 grabs was composited to collect

approximately 6 liters of sediment. Where station depth precluded sampling with a boat

and van Veen grab, the sampling crew walked in to the sample site, and the top 2-3 cm

of sediment at the site was scooped from the sediment surface and processed similarly

to sediment collected by grab. This occurred at the following stations: 4 sites in

Washington: WA99-0015, WA99-0016, WA99-0017, WA99-0019; 33 sites in California: 
30

CA99-0001, CA99-0015, CA99-0021, CA99-0025, CA99-0030, CA99-0037, CA99-0041,

CA99-0045-46, CA99-0051-57, CA99-0059-65, CA99-0067-71, CA99-0073-74, CA99-

0076, CA99-0079-80. The composited sediment was held on ice and distributed to

individual containers for toxicity testing and chemical analyses either on board the

research vessel or at the laboratory. Aliquots of the homogenized sediment were

distributed to pre-cleaned containers for analysis of sediment organics, trace metals,

grain size and toxicity testing. Toxicity-test sediment was held at 4/C to await initiation of

toxicity testing within 7 days of collection. 

2.3.2.2 Laboratory Test Methods

2.3.2.2.1 Amphipod Toxicity Tests

The 10-day, solid-phase toxicity test with the marine amphipod Ampelisca abdita was

used to evaluate potential toxicity of sediments from all sites. Procedures followed the

general guidelines provided in ASTM Protocol E1367-92 (ASTM, 1991), the EPA

amphipod sediment toxicity test manual (USEPA,1994a) and the EMAP Laboratory

Methods Manual (USEPA,1994b). The Ampelisca test is a 10-d acute toxicity test which

measures the effect of sediment exposure on amphipod survival under static aerated

conditions. 

Approximately 3–3.5 L of surface sediments (composite of upper 2-3 cm from multiple

grabs) were collected from the sampling sites and stored in glass or polyethylene jars at

4 /C in the dark until testing. Toxicity tests were conducted with subsamples of the same

sediment on which the analysis of organic and trace metal contaminants and other

sediment characteristics was performed. 

Ampelisca abdita were collected from the Narrow (=Pettaquamscutt) River, Rhode

Island, by Eastern Aquatic Biosupply, or from San Pablo Bay in the San Francisco

Estuary by Brezina and Associates. Amphipods were shipped via overnight carrier to the

Marine Pollution Studies Laboratory at Granite Canyon, CA (CA and WA sediments),

Southern California Coastal Water Research Project (SCCWRP - CA sediments) or the 

Northwestern Aquatic Sciences, Inc., laboratory in Newport, Oregon (OR sediments),

where the Ampelisca tests were conducted. Amphipods were acclimated for 2-9 days

prior to testing. During the acclimation period, the amphipods were not fed (WA and CA)

or were fed a commercially available dried algal mix (OR). Healthy juvenile amphipods of

approximately the same size (0.5–1.0 mm) were used to initiate tests. The general health

of each batch of amphipods was evaluated in a reference toxicity test (i.e., “positive

control”), which was run for 96 h in a dilution series with seawater (no sediment phase)

and the reference toxicants cadmium chloride or sodium dodecyl sulfate (SDS). LC50

values for reference toxicants were computed for comparison with other reported toxicity

ranges for the same reference toxicant and test species. 
31

Treatments for the definitive tests with field samples consisted of five replicates of each

field sediment sample (100% sediment) and a negative control. A negative control was

run with each batch of field samples, which ranged from 4 to18 samples per batch.

Control sediment was ambient sediment from the amphipod collection sites. Twenty

amphipods were randomly distributed to each of five replicates per each treatment

including the control. Amphipods were not fed during the tests. All tests were

conducted under static conditions with aeration, and were monitored for water quality

(temperature, salinity, dissolved oxygen, pH, and total ammonia in the overlying water).

Target test temperature for A. abdita was 20 /C and target salinity was 28 psu.

The negative controls provided a basis of comparison for determining statistical

differences in survival in the field sediments. In addition, control survival provided a

measure of the acceptability of final test results. Test results with A. abdita were

considered valid if mean control survival (among the 5 replicates) was not less than

90% and survival in no single control replicate was less than 80%. Test batches where

these QA requirements were not met were not included in the CDF analysis. 

One-liter glass containers with covers were used as test chambers. Each chamber was

filled with 200 ml of sediment and 600–800 ml of filtered seawater. The sediment was

press-sieved, through either a 1.0-mm screen for control samples or a 2.0-mm screen

for field samples, to remove ambient fauna prior to placing the sediment in a test

chamber. Light was held constant during the 10-day test to inhibit amphipod emergence

from the sediment, thus maximizing exposure to the test sediment.

At the conclusion of a test, the sediment from each chamber was sieved through a 0.5-

mm screen to remove amphipods. The number of animals dead, alive, or missing was

recorded. Sediments with >10% missing animals were re-examined under a dissecting

microscope to ensure that no living specimens had been missed. Amphipods still

unaccounted for were considered to have died and decomposed in the sediment. 

A variety of quality control procedures were incorporated to assure acceptability of

amphipod test results and comparability of the data with other studies. As described

above, these provisions included the use of standard ASTM and EMAP protocols,

positive controls run with a reference toxicant, negative “performance” controls run with

reference sediment from the amphipod collection site, and routine monitoring of water

quality variables to identify any departures from optimum tolerance ranges.

2.3.2.2.2 Sea Urchin Toxicity Tests

The Biomonitoring and Environmental Status and Trends Program (BEST) of the U.S.

Geological Survey obtained sediment samples collected by EMAP and conducted two

types of sea urchin toxicity tests. The fertilization and embryological development toxicity

tests were conducted with sediment porewater using gametes of the sea urchin Arbacia

punctulata. Methods and results are described in a technical report (USGS, 2000). 
32

Sediments for testing were held on ice or refrigerated at 4°C and shipped in insulated

coolers within 7 days to the BEST laboratory. Pore water was extracted from the test

sediments within 24 hours of receipt using a pneumatic device, centrifuged to remove

suspended particulate material, then stored frozen. Sediments that were received by the

BEST laboratory at temperatures exceeding acceptable temperature criteria were

excluded from the CDF analysis.

Sediment pore water was thawed two days prior to testing and stored at 4°C. Water

quality parameters (salinity, temperature, DO) were measured in the thawed pore water

and adjusted if necessary. Samples were tested at a temperature and salinity of 20 +

2°C and 30 + 1psu. Other water quality parameters that were measured included

dissolved oxygen, pH, sulfide, ammonia and dissolved organic carbon.

Toxicity was determined using percent fertilization and embryological development 

(percent normal pluteus stage) as endpoints with gametes of the sea urchin Arbacia

punctulata. A seawater dilution series (100, 50 and 25%) was used to determine the

toxicity of the sediment porewater samples. Filtered seawater and reconstituted brine

were used as dilution blanks. Reference pore water from an uncontaminated site in

Redfish Bay, TX, was included in each test as a negative control. A dilution series with

sodium dodecyl sulfate was used as a positive control. Toxicity was determined with

statistical comparisons among treatments using ANOVA and Dunnett’s one-tailed t-test

on the arcsine square root transformed data. 

2.3.3 Biotic Condition Indicators

2.3.3.1 Benthic Community Structure

Sediment samples to enumerate the benthic infauna were collected at all sampling sites

unless rocky bottom or other factors prohibited obtaining a benthic sample (see section

2.6). Procedures followed the guidance provided in the NCA Quality Assurance Project

Plan document (US EPA, 2001). The standard sampling gear for all three states was a

0.1-m2

 van Veen grab sampler. All Oregon sites were sampled using this gear. In both

Washington and California, some stations in shallow water required modified methods

when field crews walked into the site. In California, sites with a water depth less than

approximately 1 meter were sampled with hand-held cores. At these shallower areas, a

composite of sixteen 0.0065-m2

 cores was taken, for a total surface area of 0.1-m2. 

Eight of the base California stations and 23 of the Northern California intensive sites

were sampled with these cores. To evaluate the efficiency of smaller sample sizes, a

single 0.0065-m2

 core was taken from the van Veen grabs at 24 sites in Southern

California. For this analysis, the results from the sub-cores and the remainder of the

van Veen grab were combined. In Washington, four shallow-water sites (WA99-0015,

WA99-0016, WA99-0017, WA99-0019) were sampled using a 5-gallon bucket sampler

with an area of 0.049 m2

. Because of the difference in area, these four samples were

excluded from the analysis of benthic community structure.
33

The majority of the grab and core samples penetrated a minimum of 5 cm deep. The

eleven samples that penetrated 3-4 cm are included in the present analysis. After

collection, samples were sieved through nested 0.5-mm and 1.0-mm mesh screens. An

elutriation process was used to minimize damage to soft-bodied animals and the

material retained on the screens was relaxed in 1 kg of MgS04 per 20 L of seawater for

30 minutes. The residue was then preserved in the field in sodium borate-buffered 10%

formalin. 

The preserved samples were sent to analytical laboratories where they were transferred

to 70% ethanol within 2 weeks of field collection. The 1.0-mm mesh screen samples

were then sorted from the debris. The 0.5-mm mesh samples were not included as part

of EMAP West and were not sorted. The organisms were then identified to the lowest

practical taxonomic level (most often species), and counted by the primary taxonomists

(see Table 2-10). Secondary QA taxonomists ensured that uniform nomenclature was

used across the entire Western Coastal EMAP region; these recognized taxonomic

experts identified and resolved taxonomic discrepancies among the sets of primary

taxonomists. In the analyses for this report, all insect taxa were grouped as Insecta. 

Individual insect taxa will be identified in later versions of the database.

The benthic infaunal data were used to compute total numbers of individuals and total

number of species per 0.1-m2

 sample. The Shannon-Weaver information diversity

index Hr was calculated (log base 2) per 0.1-m2

 sample. Species were classified as

native, nonindigenous, cryptogenic, or indeterminate. Cryptogenic species are species

of uncertain geographic origin (Carlton, 1996), while indeterminate taxa are those taxa

not identified to a sufficiently low level to classify as native, nonindigenous, or

cryptogenic (Lee et al., in press). Species were classified using Cohen and Carlton

(1995) as the primary source and a report by TN and Associates (2001) for taxa not

classified by Cohen and Carlton. The TN and A report specifically classified the benthic

species collected by the 1999 EMAP survey as native, nonindigenous, or cryptogenic.

2.3.3.2 Fish Trawls

Fish trawls were conducted at each site, where possible, to collect fish/shellfish for

community structure and abundance estimates, collect target species for contaminant

analyses, and collect specimens for histopathological examination. In some cases, it

was necessary to use beach seines instead of trawls to collect fish for tissue analysis.

Only trawls were used to evaluate fish community structure because consistency

between beach seines was impossible to maintain. 

Trawls were conducted by using a 16-ft otter trawl with 1.5-inch mesh in the body and

wings and 1.25-inch mesh in the cod end. Community structure data (i.e, the fish data

on richness and abundance and individual lengths) were based on a trawl(s) of 10

minute duration. In open water, the trawl was conducted in a straight line with the site

location near center. Timing of the trawl began after the length of towline had been

payed out and the net began its plow. The speed over bottom was approximately 2
34

knots. When possible, trawling was conducted for the entire 10-minute period, after

which the ship’s transmission was placed in neutral and the trawl net retrieved and

brought aboard. In constrained areas where 10-minute trawls were not possible, two 5-

minute trawls were conducted. Contents of the bag were emptied into an appropriately

sized trough or livebox to await sorting, identifying, measuring, and sub-sampling. 

Trawling was the last field activity performed because of possible disturbance to

conditions at the site. Every effort was made to return any rare or endangered species

back to the water before they suffered undue stress.

In Oregon and Washington, fish for tissue and histopathological analysis were collected

with a 120-foot long beach seine where waters were too shallow to use the otter trawl. 

The seine had 1-inch mesh in the wings and 3/8-inch mesh in the bag end. In

California, a 100-foot seine with 1/8-inch mesh was used for fish collections in shallow

waters.

2.3.3.3 Fish Community Structure

Fish from a successful trawl (full time on bottom with no hangs or other interruptions)

were first sorted by species and identified to genus and species. Up to thirty individuals

per species were measured by using a fish measuring board to the nearest centimeter

(fork length when tail forked, otherwise overall length - snout to tip of caudal). The

lengths were recorded on a field form and a total count made for each species. All fish

not retained for histopathology or tissue chemistry were returned to the estuary. 

2.3.3.4 Fish Contaminant Sampling

Several species of demersal soles, flounders, and dabs were designated as target

species for the analyses of chemical contaminants in whole-body tissue. These flatfish

are common along the entire U.S. Pacific Coast and are intimately associated with the

sediments. Where the target flatfish species were not collected in sufficient numbers,

perchiform species were collected. These species live in the water column but feed

primarily or opportunistically on the benthos. In cases where neither flatfish species nor

perches were collected, other species that feed primarily or opportunistically on the

benthos were collected for tissue analysis. A total of 16 species were collected for

tissue analysis in the base study sites in all three states and a total of 17 species if the

intensive study stations are included. The species analyzed for tissue contaminants

were (species occurring in no or only one base study station are identified):

Pleuronectiformes

Citharichthys sordidus - Pacific sanddab

Citharichthys stigmaeus - speckled sanddab

Paralichthys californicus - California halibut

Platichthys stellatus - starry flounder

Pleuronectes isolepis - butter sole (1 base study station OR)
35

Pleuronectes vetulus - English sole

Psettichthys melanostictus - sand sole

Symphurus atricauda - California tonguefish (1 base study station CA)

Perciformes 

Cymatogaster aggregata - shiner perch

Embiotoca lateralis - stripped sea perch (1 base study station OR)

Gasterosteus aculeatus - threespine stickleback (1 base study and 

1 intensive study station CA)

Genyonemus lineatus - white croaker

Paralabrax maculatofasciatus - spotted sand bass (1 base study station CA)

Paralabrax nebulifer - barred sand bass 

Other

Atherinops affinis - topsmelt (1 base station CA)

Leptocottus armatus - Pacific staghorn sculpin 

Oligocottus rimensis - saddleback sculpin (2 Northern CA intensive study

stations) 

At sites where target species were captured in sufficient numbers, 3 to 30 individuals of

a species were combined into a composited sample. Due to their small size, up to 220

individual Gasterosteus aculeatus (threespine stickleback) were composited to obtain a

sufficient tissue sample at one of the intensive sites in California. In all cases, the fish

were first measured and recorded on the sampling form as chemistry fish. The fish were

then rinsed with site water, individually wrapped with heavy duty aluminum foil (with the

length of each individual fish printed on the foil wrap to facilitate the possible later

selection of specific individuals at the laboratory), and placed together in a plastic,

Ziploc bag labeled with the Station ID Code and a Species ID Code (e.g., the first four

letters of both the genus and species). The fish tissue chemistry samples were held on

wet ice in the field until they were transferred to shore and frozen to await laboratory

analysis. 

2.3.3.5 Fish Contaminant Chemistry Analyses

Neutral organic and metal contaminants were measured in the whole-body tissues of

the seventeen species of fish listed above (Section 2.4.3.4). Contaminant

concentrations were determined for each of the composited tissue samples. A total of

11 metals, 20 polychlorinated biphenyls (PCBs), DDT and its primary metabolites, and

an additional 13 pesticides were measured in the fish samples. Oregon measured PCB

110 and PCB77 as PCB 110/77. Compounds not measured in all three states (e.g.,

PCB187) are not reported here. PAHs were not measured in fish tissues because of

their rapid metabolism in vertebrates. The analytes measured in all three states in fish

and sediments are summarized in Table 2-4. Table 2-5 summarizes the sample

collection, preservation, and holding time requirements for sediment and tissue

samples. Table 2-6 summarizes the analytical methods used in the three states for
36

both sediments and tissues. For tissue chemistry analyses, the NCA Quality Assurance

Program Plan (EPA 2001) recommended that internal standards known as surrogates

be run, and suggested that reported concentrations for analytes be adjusted to correct

for recovery of surrogates. The state analytical laboratories generally used surrogates

only as an indication of whether a re-extraction of a sample was required. 

2.3.3.6 Fish Gross Pathology

Any fish pathologies (e.g., tumors) observed on fish collected in the trawls were

photographed, then excised and placed into labeled pathology containers, and put

immediately into Dietrich’s solution. Excised tissue included the entire pathology and

some adjacent healthy tissue. Pathology information, including cartridge number, fish

species, size, station ID, trawl number, pathology location, description, and sample

depth was recorded onto a Cumulative Fish Pathology Log. At the end of the field

collection, all samples were sent to Dr. Mark Meyers at NMFS/NOAA in Seattle for

analysis. A separate fish pathology report will be prepared by NOAA.

2.3.4 Sediment Chemistry

A total of 15 metals, 20 PCB congeners (PCBs), DDT and its primary metabolites, 12

pesticides, 21 polynuclear aromatic aromatics (PAHs), and total organic carbon (TOC)

were measured in sediments in all three states (Table 2-4). Oregon measured PCB 110

and PCB77 as PCB 110/77. Compounds not measured in all three states (e.g.,

hexaclorobenzene) are not reported here. With a few additions, this suite of

compounds is the same as measured in the NOAA NS&T Program.

Sediment for chemical analysis was collected from the top 2-3 centimeters in benthic

grabs and stored in pre-cleaned glass containers (see Table 2-5). Sediment samples

for chemical analysis were taken from the same sediment composite used for the

sediment toxicity tests. Approximately 250-300 ml of sediment was collected from each

station for analysis of the organic pollutants and another 250-300 ml for analysis of the

metals and TOC (Table 2-5). Table 2-6 lists the analytical methods used for each

compound. For sediment chemistry analyses, the NCA Quality Assurance Program

Plan (EPA 2001) recommended that internal standards known as surrogates be run,

and suggested that reported concentrations for analytes be adjusted to correct for

recovery of surrogates. The state analytical laboratories generally used surrogates only

as an indication of whether re-extraction of a sample was required. The exception was

the laboratory for the State of Washington which made surrogate recovery corrections

to the reported values for PAHs only.
Table 2-4. Compounds analyzed in all three states in sediments and fish tissues. PAHs and TOC were analyzed only in

sediments. Toxaphene was analyzed only in tissues. Oregon combined the analysis of PCB110 and PCB77 into a singlemeasurement of PCB 110/77. 

Polyaromatic Hydrocarbons

(PAHs)

PCB Congeners 

(Congener Number and

Compound)

DDT and Other

Chlorinated

Pesticides

Metals and Misc.

Low Molecular Weight PAHs (sediments only)

1-methylnaphthalene1-methylphenanthrene2-methylnaphthalene2,6-dimethylnaphthalene2,3,5-trimethylnaphthaleneAcenaphtheneAcenaphthyleneAnthraceneBiphenylFluoreneNaphthaleneHigh Molecular Weight PAHs (sediments only)

Benz(a)anthraceneBenzo(a)pyreneBenzo(b)fluorantheneBenzo(k)fluorantheneBenzo(g,h,i)peryleneChryseneDibenz(a,h)anthraceneFluorantheneIndeno(1,2,3-c,d)pyrenePyrene

8: 2,4'-dichlorobiphenyl

 18: 2,2',5-trichlorobiphenyl 28: 2,4,4'-trichlorobiphenyl 44: 2,2',3,5'-tetrachlorobiphenyl 52: 2,2',5,5'-tetrachlorobiphenyl 66: 2,3',4,4'-tetrachlorobiphenyl 77: 3,3',4,4'-tetrachlorobiphenyl101: 2,2',4,5,5'-pentachlorobiphenyl105: 2,3,3',4,4'-pentachlorobiphenyl110: 2,3,3',4',6-pentachlorobiphenyl118: 2,3',4,4',5-pentachlorobiphenyl126: 3,3',4,4',5-pentachlorobiphenyl128: 2,2',3,3',4,4'-hexachlorobiphenyl138: 2,2',3,4,4',5'-hexachlorobiphenyl153: 2,2',4,4',5,5'-hexachlorobiphenyl170: 2,2',3,3',4,4',5-heptachlorobiphenyl180: 2,2',3,4,4',5,5'-heptachlorobiphenyl195: 2,2',3,3',4,4',5,6-octachlorobiphenyl206: 2,2',3,3',4,4',5,5',6-nonachlorobiphenyl209: 2,2'3,3',4,4',5,5',6,6 '-decachlorobiphenyl

DDTs

2,4-DDD4,4'-DDD2,4'-DDE4,4'-DDE2,4'-DDT4,4'-DDTCyclopentadienes

AldrinDieldrinEndrinChlordanes

Alpha-ChlordaneHeptachlorHeptachlor EpoxideTrans-NonachlorOthersEndosulfan IEndosulfan IIEndosulfan SulfateLindane (gamma-BHC)MirexToxaphene (tissue only)

Metals

Aluminum Antimony (sediment only)ArsenicCadmiumChromiumCopperIron (sediment only)LeadManganese (sedimentonly)MercuryNickelSeleniumSilverTin (sediment only)ZincMiscellaneousTotal organic carbon (sediment only)

3

7
Table 2-5. Summary of EMAP-Coastal chemistry sample collection, preservation, and holding time requirements for

sediment and fish tissues. Modified from Table 5-3 (U.S. EPA, 2001a). 

Parameter Container Volume Sample Size Sample

Preservation

Max. SamplingHolding Time

Max. ExtractHolding Time

Sediment -Organics

500-ml precleaned glass 250 - 300 ml 300 g (approx.) Freeze (-18o C) 1 year 40 days

Sediment -Metals

125-ml HDPEwide-mouthbottle

100 - 150 ml 75 - 100 g

(approx.)

Freeze (-18oC)

1 year a

Sediment -TOC

Glass jar 100 - 150 ml 30 - 50 ml

(approx.)

Cool (4o C) 6 months a

Fish tissue Whole fish

individuallywrapped in Alfoil, thenplaced inwater-tightplastic bag.

NA NA Freeze (-18o

C)

1 year 40 days

a - No EPA criterion exists. Every effort should be made to analyze the sample as soon as possible following extractionor, in the case of metals, digestion.

3

8
39

Table 2-6. Methods used to analyze for contaminants in sediments and tissues. 

NA = not analyzed.

Analyte CA

Sediment/Tissue

OR

Sediment/Tissue

WA

Sediment/Tissue

Aluminum ICPMS/ICPMS ICPAES/ICPAES ICPAES/ICPAES

Antimony ICPMS/ICPMS GFAA/NA ICPMS/NA

Arsenic ICPMS/ICPMS ICPAES/ICPAES AA/AA

Cadmium ICPMS/ICPMS GFAA/GFAA ICPMS/ICPMS

Chromium ICPMS/ICPMS ICPAES/ICPAES ICPAES/ICPMS

Copper ICPMS/ICPMS ICPAES/ICPAES ICPAES/ICPMS

Iron FAA/NA ICPAES/ICPAES ICPAES/ICPAES

Lead ICPMS/ICPMS ICPAES/GFAA ICPMS/ICPMS

Manganese ICPMS/ICPMS ICPAES/NA ICPAES/NA

Mercury FIMS/FIMS CVAA/CVAA CVAA/CVAA

Nickel ICPMS/ICPMS ICPAES/ICPAES ICPAES/ICPMS

Selenium HAA/ICPMS HAA/HAA AA/AA (FURNACE)

Silver GFAA/ICPMS GFAA/GFAA ICPMS/ICPMS

Tin ICPMS/NA ICPAES/ICPAES ICPMS/ICPMS

Zinc ICPMS/ICPMS ICPAES/ICPAES ICPAES/ICPMS

PCB congeners GCMS/GCMS GCECD/GCECD GCECD/GCECD

DDT, DDD, and

DDE

GCMS/GCMS GCECD/GCECD GCECD/GCECD

PAHs GCMS/NA GCMS/NA GCMS/NA

Aldrin GCMS/GCMS GCECD/GCECD GCECD/GCECD

Alpha-Chlordane GCMS/GCMS GCECD/GCECD GCECD/GCECD

Dieldrin GCMS/GCMS GCECD/GCECD GCECD/GCECD

Endosulfan I GCMS/GCMS GCECD/GCECD GCECD/GCECD

Endosulfan II GCMS/GCMS GCECD/GCECD GCECD/GCECD

Table continued on next page
40

Endosulfan

Sulfate

GCMS/GCMS GCECD/GCECD GCECD/GCECD

Endrin GCMS/GCMS GCECD/GCECD GCECD/GCECD

Heptachlor GCMS/GCMS GCECD/GCECD GCECD/GCECD

Heptachlor

Epoxide

GCMS/GCMS GCECD/GCECD GCECD/GCECD

Lindane

(gamma-BHC)

GCMS/GCMS GCECD/GCECD GCECD/GCECD

Mirex GCMS/GCMS GCECD/GCECD GCECD/GCECD

Trans-Nonachlor GCMS/GCMS GCECD/GCECD GCECD/GCECD

TOC MARPCN I/NA EPA415.1/NA PSEP-TOC/NA

Percent fines wet sieve/NA gravimetric/NA PSEP86/NA

Analytical Methods: CVAA = cold vapor atomic absorption, FAA = flame atomic

absorption, FIMS = flow injection mercury system, GCECD = gas chromatography with

electron capture detection, GCMS = gas chromatography/mass spectroscopy, GFAA =

graphite furnace atomic absorption spectrometry, ICPAES = inductively coupled

plasma/atomic emission spectrometry, ICPMS = inductively coupled plasma/mass

spectrometry , HAA = hydride atomic absorption, MARPCN I = high temperature

combustion method.
41

2.4 Quality Assurance/ Quality Control

The quality assurance/quality control (QA/QC) program for the Western Coastal EMAP

program is defined by the “Environmental Monitoring and Assessment Program

(EMAP): National Coastal Assessment Quality Assurance Project Plan 2001-2004" (US

EPA, 2001a). The NCA has established Data Quality Objectives (DQO) for estimates of

current status for indicators of condition which are stated as: "For each indicator of

condition, estimate the portion of the resource in degraded condition within ±10% for the

overall system and ±10% for subregions (i.e., states) with 90% confidence based on a

completed sampling regime." An assessment of this standard for the combined

1999/2000 data from the states of Washington, Oregon and California is presented in

the Quality Assurance Appendix of the National Coastal Condition Report II (EPA,

2004). The level of uncertainty for the combined west coast data set for all major

indicators was # 5%.

In general, the quality assurance elements for the EMAP Western Coastal program

included initial training workshops on all sampling and analysis requirements and initial

laboratory capability exercises, program-wide audits of field and laboratory operations,

documentation of chain-of-custody, and maintaining open lines of communication and

information exchange. Information management needs were demonstrated to all

participants by the Western Coastal EMAP information manager. Other quality control

measures were incorporated to assure data reliability and comparability and are

described in the NCA plan. These include the use of standard NCA protocols, routine

instrument calibrations, measures of analytical accuracy and precision (e.g., analysis of

standard reference materials, spiked samples, and field and laboratory replicates),

measures of the quality of test organisms and overall data acceptability in sediment

bioassays (e.g., use of positive and negative controls), range checks on the various

types of data, cross-checks between original data sheets (field or lab) and the various

computer-entered data sets, and participation in intercalibration exercises.

Accuracy is used to estimate systematic error (measured vs. true or expected), while

precision is used to determine random error (variability between individual

measurements). Collectively, they provide an estimate of the total error or uncertainty

associated with an individual measured value. Measurement quality objectives (MQO)

for all NCA field and laboratory parameters are expressed in terms of accuracy,

precision, and completeness goals in the NCA QA Project Plan (US EPA, 2001a, Table

A7-1). These MQOs were established from considerations of instrument manufacturers

specifications, scientific experience, and/or historical data. However, accuracy and

precision goals may not be definable for all parameters due to the nature of the

measurement type (e.g., fish pathology, no expected value).
42

2.4.1 QA of Chemical Analyses

Details of the quality assurance procedures used to generate chemical concentrations

within both sediments and tissue samples with acceptable levels of precision and

accuracy are given in U.S. EPA (2001a). Briefly, a performance-based approach was

used, which depending upon the compound included 1) continuous laboratory evaluation

through the use of Certified Reference Materials (CRMs) and/or Laboratory Control

Materials (LCMs), 2) laboratory spiked sample matrices, 3) laboratory reagent blanks, 

4) calibration standards, and 5) laboratory and field replicates. 

Control limit criteria for “relative accuracy” were based on comparing the laboratory’s

value to the true or “accepted” values in CRMs or LCMs (see U.S. EPA, 2001a for

details). The specific requirements for PAHs and PCBs/pesticides are that the “Lab’s

value should be within ±30% of true value on average for all analytes; not to exceed

±35% of true value for more than 30% of individual analytes.” (U.S. EPA 2001a). In

addition to evaluating the individual PAH and PCB analytes, relative accuracy for total

PAHs and PCBs was determined for each combined group of organic compounds. Metals

and other inorganic compounds were treated individually, and the laboratory's value for

each analyte should be within ±20% of the upper or lower 95% confidence limit of the

CRM or LCM. Because of inherent variability at low concentrations, these control limit

criteria were applied only to analytes having CRM or LCM values >10 times the MDL. 

To evaluate precision, each laboratory periodically analyzed CRM or LCM samples using

a control limit of 3 standard deviations of the mean (Taylor, 1987). Based on analysis of

all the samples in a given year, an overall relative standard deviation (RSD, or coefficient

of variation) of less than 30% was considered acceptable precision for analytes with

CRM concentrations > 10 times the MDL.

In order to evaluate the MQOs for precision, various analytical quality assurance/quality

control (QA/QC) samples were used, field measurement procedures were followed, and

field vouchers were collected. For analytical purposes, Method Detection Limits (MDL’s)

were calculated for the detection of each analyte at low levels distinguished above

background noise, taking into consideration the relative sensitivity of an analytical

method, based on the combined factors of instrument signal, sample size, and sample

processing steps. The MDL is defined as “the minimum concentration of a substance

that can be measured and reported with 99% confidence that the analyte concentration

is greater than zero and is determined from analysis of a sample in a given matrix

containing the analyte." (Code of Federal Regulations 40 CFR Part 136). Approved

laboratories were expected to perform in general accord with the target MDLs presented

for NCA analytes (US EPA, 2001a, Table A7-2). Because of analytical uncertainties

close to the MDL, there is greater confidence with concentrations above the Reporting

Limit (RL), which is the concentration of a substance in a matrix that can be reliably

quantified during routine laboratory operations. Typically, RLs are 3 to 5 times the MDL. 

Concentrations between the MDL and the RL were used in generating the CDF and
43

mean for the analyte. Values below the MDL were set to 0 and this value was used in

calculating both the CDFs and means.

Table 2-7 lists the units, method detection limits (MDL), and reporting limits (RL) for

each compound measured in sediment samples in all three states. The analytical

methods are those used in the NOAA NS&T Program (Lauenstein and Cantillo, 1993) or

documented in the EMAP-E Laboratory Methods Manual (U.S. EPA, 1993). The target

MDLs for the National Coastal Assessment (US EPA, 2001a) were achieved in almost

90% of sediment analytes across the three states (Table 2-7). Exceedances of the

target MDL could potentially affect the frequency with which a compound is detected,

but would have little effect on the shape of the CDF since such exceedances occur at

the low end of the concentration distribution.

Table 2-8 lists the units, method detection limits (MDL), and reporting limit (RL) for the

tissue analytes. The target MDLs for the National Coastal Assessment (US EPA,

2001a) were achieved in over 90% of tissue analytes across the three states (Table 2-

8). As mentioned for the sediments, exceedances of the target MDL could potentially

affect the frequency with which a compound is detected, but would have little effect on

the shape of the CDF since such exceedances occur at the low end of the concentration

distribution.

Prior to analysis of 1999 field samples, state laboratories participating in the NCA

program performed a demonstration of capability using SRMs provided by EPA. 

Results of this exercise are described in EPA (2004, Appendix A). In summary, results

were deemed acceptable for Washington and California and marginal for Oregon. 

A post-analysis assessment of the success of the analytical laboratories in meeting

NCA QA/QC guidelines was conducted by the QA officer of the Western Ecology

Division. These results are summarized in Table 2-9. Accuracy of results as assessed

by comparison to either an SRM, CRM, or LCM was within guidelines for all states for

analysis of metals in both sediment and tissues. For sediment PCBs and pesticides,

performance of the Oregon laboratory was less than the desired level, and the

performance of the California laboratories, while acceptable, was based on a limited

number of analytes in the LCM. For sediment PAHs, performance of the Oregon

laboratory was acceptable based on the LCM and less than desired based on the SRM. 

In several cases, accuracy could not be assessed for the field samples because

laboratories did not analyze reference tissue material for PCBs (Washington) or

pesticides (Washington, California), although ability to meet standards was

demonstrated in the initial lab capability exercise. 

The NCA analytical laboratory accuracy standards are based on the evaluation of

individual analytes (e.g. PCB congeners) while the NCA sediment condition indicators

are based on total sediment or tissue PAHs and PCBs. If the total PCB concentration in

the SRM is compared to the estimated total recovery of PCBs in sediments for all

congeners by the Oregon laboratory, the values are within 16% . A similar analysis for
Table 2-7. Units, method detection limits (MDL), and reporting limits (RL) for sediment chemistry for compounds

measured in all three states. The method detection limits and the reporting limits for Oregon and Washington are means

of all the reported sediment values, including non-detects. Target MDLs are from the National Coastal Assessment (US

EPA, 2001a). NR = not reported. NA = not applicable.

Analyte Units

(dry wt.)

Target

MDL

CA

MDL/RL

OR

MDL/RL

WA

MDL/RL

Aluminum :g/g 1500 0.05/0.15 1/4 20/100

Antimony :g/g 0.2 0.002/0.006 0.3/1 0.02/0.1Arsenic :g/g 1.5 0.1/0.3 0.3/1 0.2/0.3Cadmium :g/g 0.05 0.002/0.006 0.03/0.09 0.01/0.05Chromium :g/g 5.0 0.03/0.09 0.06/0.2 NR/0.5Copper :g/g 5.0 0.03/0.09 0.2/0.6 0.5/1Iron :g/g 500 2.0/6.0 0.8/2.5 20/100Lead :g/g 1.0 0.002/0.006 0.2/0.7 0.01/0.2Manganese :g/g 1.0 0.003/0.009 0.1/0.3 0.2/1Mercury :g/g 0.01 0.015/0.045 0.002/0.007 0.001/0.005

Nickel :g/g 1.0 0.006/0.018 0.3/1.0 1/1

Selenium :g/g 0.1 0.002/0.006 0.09/0.3 0.1/0.1Silver :g/g 0.05 0.008/0.024 0.0075/0.025 0.1/0.2Tin :g/g 0.1 0.002/0.006 0.3/0.9 0.02/0.1

4

4
Zinc :g/g 2.0 0.02/0.06 0.3/0.9 1/1

PCB congeners ng/g 1.0 1/5 0.87/1.10 0.06/0.59DDT, DDD, and DDE ng/g 1.0 1/5 0.01/0.92 0.06/0.61PAHs ng/g 10 5/13 2.65/30 1.1/1.1Aldrin ng/g 1.0 1/5 0.01/0.92 0.06/0.59Alpha-Chlordane ng/g 1.0 2/5 0.01/0.92 0.06/0.59Dieldrin ng/g 1.0 1/5 0.1/0.92 0.06/0.59Endosulfan I ng/g 1.0 5/10 0.1/0.92 0.06/0.59Endosulfan II ng/g 1.0 5/10 0.1/0.92 0.06/0.59Endosulfan Sulfate ng/g 1.0 5/10 0.02/1.70 0.06/0.59Endrin ng/g 1.0 5/10 0.1/0.92 0.06/0.59

Heptachlor ng/g 1.0 1/5 0.1/0.92 0.06/0.59Heptachlor Epoxide ng/g 1.0 1/5 0.1/0.92 0.06/0.60Lindane(gamma-BHC)

ng/g 1.0 2/5 0.1/0.92 0.060/0.63

Mirex ng/g 1.0 2/5 0.1/0.92 0.06/0.59Trans-Nonachlor ng/g 1.0 1/5 0.1/0.92 0.05/0.59TOC percent NA 0.01/0.01 0.0005/0.0005 0.1/0.1Percent fines percent NA NR 0.1/1 0.1/0.1

4

5
Table 2-8. Units, method detection limits (MDL), and reporting limits (RL) for tissue chemistry for compounds measured in

all three states. The reporting limits for Oregon and Washington are means of all the reported tissue values, includingnon-detects. The reporting limits for the PCBs in Oregon and Washington are mean of all the congeners. The PCBreporting limits in California are the range in individual congeners. Target MDLs are from the National Coastal

Assessment (US EPA, 2001a). NA = not applicable.

Analyte Units

(wet wt.)

Target 

MDL

CA

MDL/RL

OR

MDL/RL

WA

MDL

Aluminum :g/g 10.0 0.012/0.036 0.5/0.67 2/10

Arsenic :g/g 2.0 0.025/0.075 0.15/0.17 0.2/1.5

Cadmium :g/g 0.2 0.0005/0.0015 0.025/0.023 0.01/0.05Chromium :g/g 0.1 0.007/0.021 0.03/0.03 0.1/0.2Copper :g/g 5.0 0.007/0.021 0.1/0.10 0.5/0.5Lead :g/g 0.1 0.0005/0.0015 0.095/0.10 0.01/0.05Mercury :g/g 0.01 0.005/0.015 0.016/0.015 0.01/3Nickel :g/g 0.05 0.0015/0.0045 0.15/0.17 0.5/0.5Selenium :g/g 1.0 0.025/0.075 0.1/0.1 0.1/0.3Silver :g/g 0.5 0.002/0.006 0.0085/0.0083 0.01/0.01Zinc :g/g 50.0 0.005/0.015 0.15/0.17 1/1PCB congeners ng/g 2.0 1/ 2-5 0.2-4.9/1.14 0.1/0.41DDT, DDD, and DDE ng/g 2.0 1/2 0.01/1.14 0.1/0.51

4

6
Aldrin ng/g 2.0 1/2 0.01/1.14 0.1/0.47

Alpha-Chlordane ng/g 2.0 2/4 0.01/1.14 0.1/0.59Dieldrin ng/g 2.0 1/2 0.01/1.14 0.1/0.67Endosulfan I ng/g 2.0 1/2 0.01/1.14 0.1/0.66Endosulfan II ng/g 2.0 5/10 0.01/1.14 0.1/0.66Endosulfan Sulfate ng/g 2.0 2/4 0.02/2.25 0.1/0.80Endrin ng/g 2.0 5/10 0.01/1.14 0.1/0.66Heptachlor ng/g 2.0 2/4 0.01/1.14 0.1/0.37Heptachlor Epoxide ng/g 2.0 5/10 0.01/1.14 0.1/0.66Lindane (gamma-BHC) ng/g 2.0 2/4 0.01/1.14 0.1/0.66Mirex ng/g 2.0 5/10 0.01/1.14 0.1/0.38Toxaphene ng/g 2.0 10/20 0.01/11.4 0.1/13.3Trans-Nonachlor ng/g 2.0 1/5 0.01/1.14 0.1/0.36% Moisture percent NA NA NA NA

47
Table 2-9. Summary of performance of state analytical laboratories with regard to QA/QC criteria for analysis of reference

materials, matrix spike recoveries, and relative percent differences (RPD) of duplicates. MS = matrix spike, SRM =

Standard Reference Material, CRM = Certified Reference Material, LCM = Laboratory Reference Material, NA = not

analyzed. 

Analyte Material State Mean of all analytes

< ±30%

Less than 30% of analytes were within

35% of true value (% exceeding if >30%)

SRM/CRM/LCM

(# analytes reported / # of analytes in

SRM/CRM/LCM)

Matrix spike

recovery within

50%-150%

RPDs

MS / non-zero duplicate samples

average <30%

CA Yes Yes LCM (15/22) No MSs NA/Yes

PAHs Sediment OR No

Yes

No (44%) SRM 1944 (18/19) 

Yes LCM (22/22)

No No MS dups/Yes

WA Yes Yes SRM 1944 (19/19) No MSs NA/YesCA Yes Yes LCM (14/15) ? - no true

values**

Yes/No sample dups

Sediment OR Yes Yes LCM (15/15) Yes No MS dups/Yes

Metals

WA Yes Yes LCM (14/15) Yes Yes/YesCA Yes Yes LCM (11/13) ? - no true

values**

Yes/Yes

Tissue OR Yes Yes LCM (13/13) Yes No MS dups/Yes

WA Yes Yes LCM (12/13) Yes Yes/YesCA Yes Yes LCM (13/21) No MSs NA/no non-zeros

Sediment OR No No (76%) SRM 1944 (19/19) No MSs NA/No (low values)

PCBs WA Yes Yes SRM 1944 (17/19) Yes Yes/No (low values)

CA Yes* Yes CRM (8*/21) Yes Yes/Yes

4

8
Tissue OR Yes Yes LCM (21/21) Yes No MS dups/Yes

WA No no reference material used Yes Yes/YesCA Yes* Yes LCM (3*/20) No MSs NA/no non-zeros

Sediment OR No NO (140%) SRM 1944 (8/8) Yes No MS dups/Yes

Pesticides WA Yes Yes SRM 1944 (8/8) Yes Yes/No (low values)

CA No no reference material used Yes Yes/No (low values)

Tissue OR Yes Yes LCM (20/20) Yes No dups/Yes

WA No no reference material used Yes Yes/Yes

* Fewer than 50% of NCA analytes were present in LCM.** Duplicate values, but not true values, were reported for matrix spikes by the analytical laboratory.

94
50

 the recovery of total PAHs in sediments versus the SRM by the Oregon lab was within

24%. These values are within ± 30% of the true value and are considered adequate for

the purpose of inclusion of the Oregon total PCB and total PAH data in the computation

of a regional CDF. 

2.4.2 QA of Taxonomy

Quality control of taxonomic identifications involved the establishment of a network of

secondary QA/QC taxonomic specialists who confirmed identifications made by the

primary taxonomists (Table 2-10), and provided standardization of identifications among

the state participants.

In order to assure uniform taxonomy and nomenclature among the primary taxonomists

for each group, and to avoid problems with data standardization at the end of the

project, progressive QA/QC and standardization were implemented. At frequent,

regular intervals (i.e., monthly), as primary taxonomy was completed, vouchers, voucher

sheets, and a portion of the QA samples were sent to the QA taxonomists. Immediate

feedback from the QA taxonomists to the primary taxonomists was used to correct work

and standardize between regional taxonomists. Each voucher was accompanied by a

voucher sheet listing the following information: major taxon (e.g., Annelida), family,

genus, species, sample from which the specimen was taken; references used in the

identification; and any characteristics of the specimen that differ from the original

description. Provisional species were described in detail on the voucher sheet.

As voucher specimens and bulk samples were processed by the QA taxonomist, any

differences in identifications or counts were discussed and resolved with the primary

taxonomist. The original data set remained with the primary taxonomist, and changes

agreed upon between the primary and QA taxonomists were made by the primary

taxonomist on a copy of the original data set. Changes to the data based on QA/QC

analysis were tracked in writing by both the primary and QA taxonomists. 
51

Table 2-10. Listing of primary and QA/QC taxonomists by taxon and region for the 1999

Western Coastal EMAP study. 

Organisms QA/QC

Taxonomist

Primary

Taxonomists

Region*

Annelida Gene Ruff John Oliver

Larry Lovell

Gene Ruff

Kathy Welch

NC

SC

WO

WO

Arthropoda Don Cadien Peter Slattery

Tony Phillips

Jeff Cordell

NC

SC

WO

Mollusca Don Cadien Peter Slattery

Kelvin Barwick

John Ljubenkov

Susan Weeks

NC

NC

SC

WO

Echinodermata Gordon Hendler Peter Slattery

Nancy Carder

Scott McEuen

NC

SC

WO

Miscellaneous taxa John Ljubenkov Peter Slattery

John Ljubenkov

Scott McEuen

NC

SC

WO

Freshwater fauna Rob Plotnikoff/

Chad Wiseman

Not Applicable

Not Applicable

Jeff Cordell

NC

SC

WO

*NC: Northern California, SC: Southern California, WO: Washington & Oregon
52

2.5 Data management

Data management for the West Coast stations sampled in 1999 is a component of the

overall EMAP Western Coastal Information Management Program. The Information

Management System is based on a centralized data storage model using standardized

data transfer protocols (SDTP) for data exchange among program participants. The

1999 data were submitted to the Information Manager (IM) located at the Southern

California Coastal Water Research Program (SCCWRP) for entry into the relational

database (Microsoft Access 2000). 

The data flow consists of interactions among four levels. Field crew leaders and

laboratory supervisors are responsible for compiling data generated by their

organizations and for entering the data into one or more of the SDTP tables. The State

IM Coordinator is responsible for compiling all data generated within a state into a unified

state database. The Western EMAP IM Coordinator (WIMC) is responsible for working

with State Coordinators to develop the SDTP, and for creation and management of the

centralized West Coast EMAP database. The EMAP IM Coordinator, located at the

Atlantic Ecology Division of EPA at Narragansett, Rhode Island, is responsible for

accepting data from Western EMAP, for placing it in the national EMAP database, and

for transferring it to other EPA databases, such as STORET.

Once all data tables of a particular data type (e.g., all tables containing fish data) were

certified by the WIMC, integrated multi-state data tables were provided to the Western

EMAP Quality Assurance Coordinator (QAC). The QAC reviewed the data with respect

to scientific content. Necessary corrections resulting from this review process were

returned to the Western EMAP IM Coordinator, who was responsible for working with the

State IM Coordinator to make necessary changes. 

Following certification of all portions of the data by the QAC, the WIMC submitted the

integrated multi-state data set to the EMAP IM Coordinator, who is the point of contact

for data requests about the integrated data set.

Details of the Western EMAP Information Management process are provided in Cooper

(2000). The structure of each of the relational database tables and supporting database

look-up tables used by the states to submit data to the WIMC are also provided in this

document (Cooper, 2000).

2.6 Unsamplable Area

In Washington, 6 stations (WA99-0005, Ozette River; WA99-0028, Beardslee Slough; 

WA99-0018, Quinault River; WA99-0032, WA99-0037, Willapa Bay; WA99-0041, Grays

River) proved to be inaccessible to sampling and were abandoned (Table 2-1). 

In Oregon, station OR99-0029 was abandoned prior to sampling because inspection

found that it fell too far upstream and was not visited. Station OR99-0075, part of the
53

Tillamook Bay intensification study, was not sampled because the station was located in

a marsh area. No sediment contaminant analyses were conducted at OR99-0044 or

OR99-0051 because of grab failures due to large amounts of rock and shell in the

substrate.

In California, all stations were visited. Among the base study stations, there were no grab

or trawl samples obtained at CA99-3019 (Carmel Bay) or CA99-3024 (San Luis Obispo

Bay) because of rocky substrate at the sites. Site CA99-3027, located in the Ventura

River, was not sampled because the station location was actually located on land and

the adjacent aquatic habitat could not be sampled because it consisted of a large

boulder substrate. Among the northern California intensification sites, no grab or trawl

samples were obtained at stations CA99-3058 (Klamath River), CA99-3066 (Noyo

River), CA99-3072 (Albion River), and CA99-3075 (Elk Creek) because of the presence

of rocky substrates. No trawl was obtained at station CA99-3056 (Wilson River)

because there was insufficient room to deploy gear.
54
55

3.0 Indicator Results

3.1 Habitat Indicators

3.1.1 Salinity

Salinity in the bottom water for the small estuaries of West Coast states ranged from 0

psu to 34.2 psu across the 201 stations where bottom salinities were collected. 

Approximately fifty percent of the area of the small estuaries had a salinity $ 30.9 psu

(Figure 3.1 -1). About 54% of the area of the West Coast states estuaries would be

classified as euhaline ($ 30 psu) based on the EMAP sampling. The extended left tail of

the CDF indicates that a number of samples were taken at low salinities, but that these

sites constituted a modest percentage of the total estuarine area. Approximately 19% of

the area of the small estuaries had salinities less than 20 psu, while only 11% of

estuarine area is represented by salinities less than 5 psu. The range of values for

surface salinity was identical to that in bottom water, and the CDF of surface salinity

values was very similar to that for bottom salinities. In interpreting these results, it is

important to recognize that salinity can vary both tidally and seasonally, as well as with

depth in the water column, and that these single measurements are "snapshots" during

the sampling events. 

3.1.2 Water Temperature

Temperature in the bottom water for the small estuaries of West Coast states ranged

from 8.5 °C to 32.1 °C across the 201 stations where bottom temperatures were

collected. The relatively wide range of bottom water temperature values reflects the two

biogeographic provinces which were sampled in West Coast states. The range of 

surface water temperatures was very similar to that for bottom water temperatures (9.3

°C to 32.1 °C). Approximately 13% of the area of the small estuaries had a temperature

at the bottom $ 20 °C, with about 19.6 % of area having bottom water temperatures #

11.1 °C (Figure 3.1 -2). These temperatures are representative of summer conditions in

the region. 

3.1.3 pH

The pH of bottom waters for the small estuaries of West Coast states had the

surprisingly wide range of from 5.1 to 10.2 across the 197 stations where bottom pH

measurements were collected. The range for pH in surface water samples was

identical to that for bottom waters. Approximately 91% of the area of the small estuaries

had a pH # 8.0 (Figure 3.1 -3). Values of pH $ 9 tended to be found at sites with low

salinity (# 7 psu), with the exception of the station from Point Mugu Lagoon, California,

where a pH of 9.3 and a salinity of 33.4 psu were recorded. Values of pH # 6.5 tended

to be found at sites with low salinity (# 1 psu).
56

3.1.4 Sediment Characteristics

The percent silt-clay of sediments ranged from 0 % to 96.4 % at the 190 stations from

which soft sediment samples could be obtained (Figure 3.1 -4). About 65% of the area

of the small estuaries had sediments composed of sands (< 20 % silt-clay), about 29.4

% was composed of intermediate muddy sands (20-80 % silt-clay), and only about 5.6

% was composed of muds (>80 % silt-clay). 

Percent total organic carbon (TOC) in sediments of small west coast estuaries ranged

from 0 % to 7.4 % at the 190 stations from which soft sediment samples could be

obtained (Figure 3.1 -5). About 84% of the area of the small estuaries had sediments

with TOC levels # 1.0 %. 

3.1.5 Water Quality Parameters

Water quality parameters are presented as water column mean values based on the

concentration averaged over the surface, mid-water, and bottom water samples. Water

depths during sampling ranged between 0.3 m and 30 m depth.

Chlorophyll a

The average water column concentration of chlorophyll a of small west coast estuaries

(Figure 3.1 -6) ranged from 0.4 to 47.6 :g L-1 across the 202 stations where chlorophyll

measurements were collected. Approximately 88% of total estuarine area was

characterized by average chlorophyll a concentrations # 7.9 :g L-1, while approximately

0.6 % of estuarine area had chlorophyll a values that exceeded concentrations of 15 :g

L-1. There was no geographic concentration of high chlorophyll values.

Nutrients

The average water column concentration of nitrate + nitrite of small west coast estuaries

(Figure 3.1 -7) ranged from 0 to 3472 :g L-1 across the 202 stations where nitrate +

nitrite measurements were collected. Approximately 95% of total estuarine area was

characterized by nitrate + nitrite concentrations # 263 :g L-1, while approximately 2.7 %

of estuarine area had nitrate + nitrite values that exceeded concentrations of 300 :g L-1. 

The average water column concentration of ammonium in small west coast estuaries

(Figure 3.1 -8) ranged from 0 to 580 :g L-1 across the 202 stations where ammonium

measurements were collected. Approximately 90% of total estuarine area was

characterized by ammonium concentrations # 125 :g L-1. 

The average water column concentration of total nitrogen (nitrate + nitrite + ammonium)

in small west coast estuaries (Figure 3.1 -9) ranged from 3.2 to 3519 :g L-1 across the

202 stations where total nitrogen measurements were collected. Approximately 90% of

total estuarine area was characterized by total nitrogen concentrations # 218 :g L-1. 
57

The average water column orthophosphate concentration of small west coast estuaries

(Figure 3.1 -10) ranged from 0 to 563.3 :g L-1 across the 202 stations where

orthophosphate measurements were collected. Approximately 95% of total estuarine

area was characterized by orthophosphate concentrations # 158 :g L-1.

The ratio of total nitrogen (nitrate + nitrite + ammonium) concentration to total

orthophosphate concentration was calculated as an indicator of which nutrient may be

controlling primary production in west coast small estuaries. A ratio above 16 is

generally considered indicative of phosphorus limitation, and a ratio below 16 is

indicative of nitrogen limitation (Geider and La Roche, 2002). The N/P ratio (Figure 3.1

-11) ranged from 0.16 to 393.5 across the 190 stations where sufficient measurements

were collected. Approximately 75% of estuarine area had N/P values # 16. The long

right tail of the CDF was due to four stations representing less than 1 % of estuarine

area with N/P ratios $ 100.

Total Suspended Solids

The average water column concentrations of total suspended solids (TSS) in the water

column of small west coast estuaries (Figure 3.1-12) ranged from 0 to 276.2 mg L-1

across the 201 stations where TSS measurements were collected. Approximately

95% of total estuarine area was characterized by TSS concentrations # 19.1 mg L-1.

Percent Light Transmission

The percent light transmission of the water column (adjusted to a reference sample

depth of 1 m) in small west coast estuaries (Figure 3.1 -13) ranged from 0 to 87.6% of

surface illumination. Approximately 21.3 % of total estuarine area showed a percent

light transmission of #10 %, and approximately 46.8 % of total estuarine area showed a

percent light transmission of #20 %.

3.1.6 Water Column Stratification

As an indicator of water column stratification, two indices were calculated for the 201

stations with temperature and salinity data. The first index was the simple difference

between bottom and surface salinities. The second index ()Ft

) was the difference

between the computed bottom and surface Ft

 values, where Ft is the density of a parcel

of water with a given salinity and tmperature relative to atmospheric pressure. Results

of the two indices were extremely similar. 

The simple stratification index ranged between -1.2 and 20.2 psu. Less than 4% of

estuarine area showed index values < 0, indicating bottom waters less saline than

surface waters (Figure 3.1 -14). Approximately 12% of estuarine area had index values

$ 2 psu, indicating strong stratification. The )Ft index had values ranging from -0.08 to

+16.2. Approximately 3% of estuarine area showed )Ft

 index values < 0, indicating
58

Bottom Salinity

West Coast Small Estuaries

0

20

40

60

80

100

0 5 10 15 20 25 30 35 40

Salinity (psu)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

bottom waters less saline than surface waters (Figure 3.1 -15). Approximately 12% of

estuarine area had )Ft

 index values $ 2, indicating strong stratification.

The limited indication of strong water column stratification within the small west coast

estuaries sampled is consistent with the large tidal amplitude across much of the region,

which should lead to a high degree of water column mixing. Additionally the sampling

period is during the summer period of low rainfall and low freshwater runoff which

should also reduce the extent of vertical stratification during the sample period.

Figure 3.1-1. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. salinity of bottom waters.
59

Bottom Temperature 

West Coast Small Estuaries

0

20

40

60

80

100

0 5 10 15 20 25 30 35

Temperature ( o C)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-2. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. temperature of bottom waters.
60

Bottom pH 

West Coast Small Estuaries

0

20

40

60

80

100

0 2 4 6 8 10 12

pH

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-3. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. pH in bottom waters.
61

Percent Sediment Silt-Clay 

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100

Silt-Clay (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-4. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. percent silt-clay of sediments.
62

Percent Sediment Total Organic Carbon 

West Coast Small Estuaries

0

20

40

60

80

100

012345678

Total Organic Carbon (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-5. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. percent total organic carbon of sediments.
63

Mean Chlorophyll a Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 10 20 30 40 50

Concentration (ug/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-6. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column mean concentration of chlorophyll a.
64

Mean Nitrate+Nitrite Nitrogen Concentration

 West Coast Small Estuaries

0

20

40

60

80

100

0 500 1000 1500 2000 2500 3000 3500 4000

Concentration (ug/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-7. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column mean nitrate + nitrite concentration.
65

Mean Ammonium Nitrogen Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 50 100 150 200 250 300 350 400

Concentration (ug/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-8. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column mean ammonium concentration.
66

Mean Total Dissolved Nitrogen Concentration

 West Coast Small Estuaries

0

20

40

60

80

100

0 500 1000 1500 2000 2500 3000 3500 4000

Concentration (ug/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-9. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column mean total nitrogen (nitrate + nitrite + ammonium) concentration.
67

Mean Orthophosphate Phosphorus Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 50 100 150 200 250

Concentration (ug/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-10. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column mean orthophosphate concentration.
68

Mean N:P Molar Ratio

West Coast Small Estuaries

0

20

40

60

80

100

0 50 100 150 200 250 300 350 400 450

Molar Ratio

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-11. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column mean ratio of total nitrogen (nitrate + nitrite + ammonium)

concentration to total orthophosphate concentration.
69

Mean Total Suspended Solids 

West Coast Small Estuaries 

0

20

40

60

80

100

0 50 100 150 200 250 300

Concentration (mg/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-12. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column total suspended solids concentration.
70

Percent Light Transmission at 1 m

West Coast Small Estuaries

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

Percent Light Transmission

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-13. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. percent light transmission estimated at a reference depth of 1 m in the water

column.
71

Stratification Index 

West Coast Small Estuaries

0

20

40

60

80

100

-5 0 5 10 15 20 25

Bottom Salinity Minus Surface Salinity

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-14. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. water column stratification index.
72

∆σt 

West Coast Small Estuaries

0

20

40

60

80

100

-2 0 2 4 6 8 10 12 14 16 18

(σt bottom - σt surface)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.1-15. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. )Ft

 stratification index.
73

3.2 Exposure Indicators

3.2.1 Dissolved Oxygen

Dissolved oxygen (DO) concentrations in the bottom water for the small estuaries of West

Coast states ranged from 3.75 mg L-1 to 16.3 mg L-1 across the 200 stations where

dissolved oxygen concentrations were measured. No observations were less than the

value of 2 mg L-1 considered indicative of anoxia, less than four percent of estuarine area

had a bottom DO concentration below 5 mg L-1, and approximately 92% of the area of

West Coast small estuaries had DO concentrations between 5 and 10 mg L-1 ( Fig. 3.2-1). 

The range of dissolved oxygen (DO) concentrations in the surface waters was very similar

to that for bottom waters (3.46 mg L-1 to 16.3 mg L-1) (Fig. 3.2-2). Approximately 83% of

the area of West Coast small estuaries had surface DO concentrations between 5 and 10

mg L-1, while nearly 11 % had DO concentrations > 10 mg/L-1. 

3.2.2 Sediment Contaminants

3.2.2.1 Sediment Metals

Concentrations of metals in sediment were measured at 190 stations, except antimony

and silver, which were measured at only 189 stations. The mean concentration of a metal

was calculated using all available samples with the non-detects set to 0. For comparative

purposes, mean concentrations of metals were also calculated using the subset of

samples in which the metals were detected (Table 3.2-1).

Arsenic

Arsenic was detected in 189 of the stations and had a mean concentration of 6.11 :g/g

(Table 3.2-1). The maximum concentration of 18.6 :g/g occurred in Grays Bay in the

Columbia River, Washington. The next two highest concentrations of 17.6 and 17.1 :g/g

occurred in Tillamook Bay, Oregon, and the Los Angeles Harbor, respectively. Fifty

percent of the area of the West Coast small estuaries had concentrations less than 5.53

:g/g, and 90% of the area had concentrations less than 8.75 :g/g (Figure 3.2-3). Arsenic

concentrations exceeded the ERL at 37 stations (14.8% of area), while no stations had

values exceeding the ERM (Table 3.2-1).

Cadmium

Cadmium was detected in 164 of the stations and had a mean concentration of 0.219

:g/g (Table 3.2-1). The maximum concentration of 4.30 :g/g occurred in the Los Angeles

Harbor. The only other value >1 :g/g was the 2.3 :g/g concentration in Discovery Bay,

which opens into the Strait of Juan de Fuca, Washington. Fifty percent of the area of the

West Coast small estuaries had cadmium concentrations less than 0.15 :g/g, and 90% of

the area had concentrations less than 0.44 :g/g (Figure 3.2-4). Cadmium concentrations

exceeded the ERL at only 2 stations (0.1% of area), while no stations had values

exceeding the ERM (Table 3.2-1).
74

Bottom Dissolved Oxygen 

West Coast Small Estuaries

0

20

40

60

80

100

0 2 4 6 8 10 12 14 16 18

Concentration (mg/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-1. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. dissolved oxygen of bottom waters.
75

Surface Dissolved Oxygen 

West Coast Small Estuaries

0

20

40

60

80

100

0 2 4 6 8 10 12 14 16 18

Concentration (mg/L)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-2. Percent area (and 95% C.I.) of small estuaries of the West Coast states

vs. dissolved oxygen of surface waters.
76

Chromium

Chromium was detected at all 190 stations and had a mean concentration of 128 :g/g

(Table 3.2-1). The two highest concentrations of 1770 and 1250 :g/g both occurred in

the Smith River, California. These were the only concentrations >1000 :g/g. Fifty

percent of the area of the West Coast small estuaries had concentrations less than 48.6

:g/g, and 90% of the area had concentrations less than 168 :g/g (Figure 3.2 -5). 

Chromium concentrations exceeded the ERL at 68 stations (27% of area), while 10

stations (2.5% of area) had values exceeding the ERM (Table 3.2-1). 

Copper

Copper was detected at all 190 stations and had a mean concentration of 26.7 :g/g

(Table 3.2-1). The maximum concentration of 398 occurred in the Los Angeles Harbor. 

The only other value >100 :g/g was the 156 :g/g value in Santa Barbara Harbor,

California. Fifty percent of the area of the West Coast small estuaries had

concentrations less than 14.5 :g/g, and 90% had concentrations less than 55.2 :g/g

(Figure 3.2-6). Copper concentrations exceeded the ERL at 54 stations (21.2% of

area), while 1 stations (0.1% of area) had a value exceeding the ERM (Table 3.2-1). 

Lead

Lead was detected at all 190 stations and had mean concentration of 13.6 :g/g 

(Table 3.2-1). The maximum concentration of 293 :g/g occurred in the Los Angeles

Harbor, and the second highest value of 80 :g/g occurred in Santa Barbara Harbor,

California. Fifty percent of the area of the small estuaries had lead concentrations less

than 8.87 :g/g, and 90% of the area had concentrations less than 20.4 :g/g 

(Figure 3.2-7). Lead concentrations exceeded the ERL at only 5 stations (1.3% of

area), while 1 station (0.07% of area) had a value exceeding the ERM (Table 3.2-1).

Mercury

Mercury was detected at 180 of the stations and had a mean concentration of 0.113

:g/g (Table 3.2-1). The maximum concentration of 3.11 :g/g occurred in the Estero

Americano, California. The only other values >1 :g/g occurred in the Los Angeles

Harbor and the Albion River, California, which had concentrations of 2.33 and 1.37 :g/g,

respectively. Fifty percent of the area of the West Coast small estuaries had mercury

concentrations less than 0.03 :g/g, and 90% of the area had concentrations less than

0.16 :g/g (Figure 3.2-8). Mercury concentrations exceeded the ERL at 25 stations

(12.1% of area), while 3 stations (0.1% of area) had values exceeding the ERM (Table

3.2-1).

Nickel

Nickel was detected at all 190 stations and had a mean concentration of 47.6 :g/g

(Table 3.2-1). The two highest concentrations, 354 :g/g and 307 :g/g, both occurred in

the Smith River, California. Fifty percent of the area of the West Coast small estuaries

had nickel concentrations less than 18.6 :g/g, while 90% of the area had concentrations

less than 50.0 :g/g (Figure 3.2-9). Nickel concentrations exceeded the ERL at 116
77

stations (43.7% of area), while 45 stations (9.4% of area) had values exceeding the

ERM (Table 3.2-1). Nickel concentrations in relation to the published ERM values

should be interpreted cautiously since the ERM value has a low reliability (Long et al.,

1995). Because of its unreliability, nickel was excluded from a recent evaluation of

sediment quality in southern Puget Sound (Long et al., 2000). Additionally, a study of

metal concentrations in cores on the West Coast determined an historical background

concentration of nickel in the range of 35 - 70 ppm (Lauenstein et al., 2000), which

brackets the value of the ERM (51.6 ppm).

Selenium

Selenium was detected at 78 of the stations and had a mean concentration of 0.107

:g/g (Table 3.2-1). The maximum concentration of 1.6 :g/g occurred in the Los

Angeles Harbor. Of the seven other values >0.5 :g/g, six occurred in California and

one in Oregon. Approximately 71% of the area of the West Coast small estuaries had

non-detectable levels of selenium, and 90% had concentrations less than 0.25 :g/g

(Figure 3.2-10). No stations exceeded either the ERL or ERM for selenium.

Silver

Silver was detected at 178 of the stations and had a mean concentration of 0.16 :g/g

(Table 3.2-1). The maximum concentration of 1.13 :g/g occurred in the Los Angeles

Harbor. The second and third highest values of 0.98 and 0.92 :g/g were found in

Grays Bay, Washington, and San Diego Bay, respectively. Fifty percent of the area of

the West Coast small estuaries had a silver concentrations less than 0.21 :g/g, while

90% of the area had concentrations less than 0.48 :g/g (Figure 3.2-11). Silver

concentrations exceeded the ERL at only 1 station (0.1% of area) (Table 3.2-1), and no

stations exceeded the ERM.

Tin

Tin was detected at 130 stations and had a mean concentration of 1.24 :g/g 

(Table 3.2-1). The maximum concentration of 17.3 :g/g occurred in the Los Angeles

Harbor. The only other value greater than 10 :g/g was in the Albion River, California,

which had a concentration of 11.6 :g/g. Fifty percent of the area of the West Coast

small estuaries had a tin concentration less than 0.99 :g/g, while 90% of the area had

concentrations less than 2.67 :g/g (Figure 3.2-12).

Zinc

Zinc was detected at all 190 stations and had a mean concentration of 69.5 :g/g 

(Table 3.2-1). The maximum concentration of 538 :g/g occurred in the Los Angeles

Harbor, while the next highest value, 173 :g/g, was found in both the Santa Barbara

Harbor and San Diego Bay. Fifty percent of the area of the West Coast small estuaries

had zinc concentrations less than 49 :g/g, while 90% of the area had concentrations

less than 117 :g/g (Figure 3.2-13). Zinc concentrations exceeded the ERL at 4 stations

(1.2% of area), while 1 station (0.1% of area) had a value exceeding the ERM (Table

3.2-1).
78

Additional Metals

In addition to the 11 metals discussed above, aluminum, antimony, iron, and

manganese were measured in the sediments. The measured concentration and

frequency of detection for each of these metals are given in Table 3.2 -1. Each of these

four metals was detected at all of the stations, with the exception of antimony, which

was detected at 115 stations. Not unexpectedly, aluminum and iron were the two most

abundant metals, with mean concentrations of 44631 :g/g and 33642 :g/g,

respectively. 
Table 3.2-1. Summary statistics for sediment metal concentrations (

:g/g) for all stations from West Coast estuaries. The

overall mean and the overall standard deviation (SD) were calculated using all the data, including the non-detects whichwere set to 0. (N = 190, except 189 for antimony and silver). The “mean when present” was calculated using the sampleswhich had detectable concentrations of the compound. ERL and ERM values are from Long et al. (1995).

Metal Overall

Mean

Concentration

Overall 

SD

Mean 

Concen

-tration 

when

Present

Min Max Frequency

of

detection

ERL ERM >ERL

No.

Sites

>ERM

No.

Sites

>ERL

Area

>ERM

Area

Aluminum 44631 19837 44631 3030 78800 190Antimony 0.432 1.24 0.71 0 16.4 115Arsenic 6.11 3.05 6.14 0 18.6 189 8.2 70.0 37 0 14.8 0Cadmium 0.219 0.38 0.254 0 4.3 164 1.2 9.6 2 0 0.1 0Chromium 128 209 128 9.2 1770 190 81 370 68 10 27 2.5Copper 26.7 34.8 26.7 2.1 398 190 34 270 54 1 21.2 0.01Iron 33600 18600 33600 6000 87500 190Lead 13.6 22.7 13.6 3.0 293 190 46.7 218. 5 1 1.3 0.07Manganese 485 278 485 84.8 1390 190Mercury 0.113 0.302 0.120 0 3.11 180 0.15 0.71 25 3 12.1 0.1Nickel 47.6 55.4 47.6 3.3 354 190 20.9* 51.6* 116* 45* 43.7* 9.4*Selenium 0.107 0.209 0.261 0 1.60 78 2.0 25.0 0 0 0 0Silver 0.16 0.20 0.17 0 1.13 178 1.0 3.7 1 0 0.1 0Tin 1.24 1.86 1.81 0 17.3 130Zinc 69.5 52.0 69.5 7.9 538 190 150 410 4 1 1.2 0.1

* The ERL and ERM for nickel has low reliability for the West Coast. See text for discussion.

79
80

Sediment Arsenic Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 5 10 15 20

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-3. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of arsenic.
81

Sediment Cadmium Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

012345

Concentration (ug/g)

Cumulative Percent Area

Cumualtive Percent

95% Confidence Interval

Figure 3.2-4. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of cadmium.
82

Sediment Chromium Concentration

 West Coast Small Estuaries

0

20

40

60

80

100

0 500 1000 1500 2000

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-5. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of chromium.
83

Sediment Copper Concentration

 West Coast Small Estuaries

0

20

40

60

80

100

0 100 200 300 400 500

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-6. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of copper.
84

Sediment Lead Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 50 100 150 200 250 300 350

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-7. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of lead.
85

Sediment Total Mercury Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 0.5 1 1.5 2 2.5 3 3.5

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-8. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of mercury.
86

Sediment Nickel Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 50 100 150 200 250 300 350 400

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-9. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of nickel.
87

Sediment Selenium Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 0.5 1 1.5 2

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-10. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of selenium.
88

Sediment Silver Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 0.2 0.4 0.6 0.8 1 1.2

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-11. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of silver.
89

Sediment Tin Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 5 10 15 20

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-12. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of tin.
90

Sediment Zinc Concentration 

West Coast Small Estuaries

0

20

40

60

80

100

0 100 200 300 400 500 600

Concentration (ug/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-13. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of zinc.
91

3.2.2.2 Sediment Organics

An overall mean concentration was calculated for sediment organics using all the

samples (N=190) with the non-detects set to 0. “Mean concentrations when present”

were also calculated using the subset of samples in which the compounds were

detected (Table 3.2-2)

Total PAHs

PAHs were detected at 112 of the stations. One laboratory replicate from a sediment

sample from Martin Slough in the Columbia River had individual PAH concentrations 3

to 690 times greater than in the other three replicates from the same sample. Total

PAH concentration for this sample was 59,878 ng/g if the high laboratory replicate was

included, but 2427 ng/g if it was excluded. The order-of-magnitude higher

concentrations in this replicate could be due to a drop of creosote. Because the sample

appears to be an outlier relative to the other laboratory replicates at the station, this

sample was not included in the total PAH analysis.

Total PAHs had an overall mean concentration of 263 ng/g dry weight (Table 3.2-2). 

The highest concentration, 22,982 ng/g, occurred in the Los Angeles Harbor. The

compounds 2,6-Dimethylnaphthalene, 2,3,5-Trimethylnaphthalene, and

1-Methylphenanthrene constituted 61% of the total PAHs at the Los Angeles Harbor

site. Fifty percent of the area of the West Coast small estuaries had a total PAH

concentration less than 25 ng/g, and 90% of the area had a concentration less than 435

ng/g (Figure 3.2-14). On the average, low molecular weight (LMW) PAHs constituted

57 % of the total PAHs, while high molecular weight (HMW) PAHs constituted 43 % of

the total PAHs (Table 3.2-2). Four stations exceeded the ERL for both HMW (0.2 % of

area; Figure 3.2-15) and LMW PAHs (0.9 % of area; Figure 3.2-16), and two stations

exceeded the ERL (0.2 % of area) for total PAHs. The ERM was exceeded only for

LMW PAHs at two stations (Table 3.2-2).

Total PCBs

PCBs were detected at 78 of the stations, and total PCBs had an overall mean

concentration of 3.72 ng/g dry weight (Table 3.2-2). The maximum concentration of

86.5 ng/g dry weight occurred in San Diego Bay, while the second highest concentration

of 66.2 ng/g occurred in the Los Angeles Harbor. Seventy-three percent of the area of

the West Coast small estuaries had non-detectable levels of PCBs, while 90% of the

area had concentrations less than 7.5 ng/g (Figure 3.2-17). PCB18 was the most

abundant PCB conger and made up 18% of the total PCBs on average. The next most

abundant congener was PCB52, which made up 11% of the total PCBs. PCB18 and

PCB52 were also the most frequently detected PCB congeners, occurring in 69 and 68

of the stations, respectively. The ERL for total PCBs was exceeded at 7 stations (2.2%

of area), while no stations exceeded the ERM (Table 3.2-2).
92

Total DDT

DDT or one of its metabolites was detected at 28 of the stations, including 13 in

California, 3 in Oregon and 9 in Washington. Total DDT had an overall mean

concentration of 3.29 and a maximum concentration of 301 ng/g dry weight in the

Channel Island Harbor in Southern California (Table 3.2-2). The only two other values

>50 ng/g were the 99 and 50 ng/g concentrations in the Long Beach Harbor and the Los

Angeles Harbor, respectively. Eighty-eight percent of the area of the small estuaries

had non-detectable levels of DDTs, while 90% of the area had total DDT concentrations

less than 0.31 ng/g (Figure 3.2-18). The most abundant form was 4,4'-DDD,

constituting 77% of the total DDT on average (Table 3.2-2). The concentration of 4,4'-

DDD exceeded the ERL at 15 stations (6.1% of area), and exceeded the ERM at 3

stations (1.6% of area) (Table 3.2-2). The ERL for total DDT was exceeded at 17

stations (6.2% of area), while the ERM was exceeded at 3 stations (0.1% of area)

(Table 3.2-2). 

Additional Pesticides

Besides DDT, an additional 12 pesticides were measured in the sediments in all three

states (Table 3.2-2). Of these Dieldrin, Endosulfan II and Mirex were never detected at

any station. The other pesticides occurred in 3 to 11 of the 190 sediment samples. An

overall mean concentration was calculated for each of these pesticides using all the

samples (N=190) with the non-detects set to 0. Because of their low frequency of

detection, means were also calculated for these pesticides using just the samples in

which the pesticides were detected. Endrin had the highest concentrations, with an

overall mean concentration of 0.36 ng/g and a mean of 7.50 ng/g at the sites where it

was detected. All nine sites where endrin was detected had concentrations which

exceeded the ERL but not the ERM. Trans-nonachlor was the second most abundant of

the additional pesticides, with an overall mean of 0.21 ng/g and a mean of 5.70 ng/g

where detected. There was an insufficient number of detects to calculate CDFs for any

of the additional pesticides.
Table 3.2-2. Mean sediment concentrations (ng/g dry weight) and frequency of detection of the PAHs, PCBs and pesticides

measured in all three states. The overall mean and the overall standard deviation (SD) were calculated using all the data including

the non-detects, which were set to 0. The “mean when present” was calculated using the samples which had detectableconcentrations of the compound. N = 190. ERL and ERM values are from Long et al. (1995). NA - not analyzed, see text.

Analyte Overall mean

concentration

ng/g dry wt 

Overall 

SD 

Mean

concentration

 when

present

Min Max Frequency

of

detection

ERL ERM >ERL

No. Sites

>ERM

No. Sites

>ERL

Area %

>ERM

Area %

HMW PAHs 112 371.2 199 0 2918 107 1700 9600 4 0 0.2 0LMW PAHs 151 1460 398 0 20064 72 552 3160 4 2 0.9 0.1Total PAHs 263 1700 446 0 22982 112 4022 44792 2 0 0.2 0Total PCBs 3.72 9.57 9.05 0 86.5 78 22.7 180 7 0 2.2 02,4'-DDD 0.089 0.79 4.21 0 9.20 42,4'-DDE 0.183 1.20 4.97 0 13.6 72,4'-DDT 0.190 2.62 36.1 0 36.1 14,4'-DDD 0.285 2.12 5.42 0 26.7 104,4'-DDE 2.53 17.7 17.1 0 224 28 2.2 27.0 15 3 6.1 1.64,4'-DDT 0.015 0.20 2.80 0 2.80 1Total DDT 3.29 23.6 22.3 0 301 28 1.58 46.1 17 3 6.2 0.1Aldrin 0.022 0.22 1.38 0 2.90 3Alpha-chlordane 0.067 0.42 2.54 0 3.50 5Dieldrin 0.000 0.00 0.000 0 0.00 0 0.02 8 0 0 NA NAEndosulfan I 0.020 0.28 3.80 0 3.80 1Endosulfan II 0.000 0.00 0.00 0 0.00 0EndosulfanSulfate 0.053 0.40 2.54 0 3.60 4Endrin 0.355 1.60 7.50 0 7.50 9 0.02 45 9 0 NA NAHeptachlor 0.131 0.58 2.26 0 3.70 11HeptachlorEpoxide 0.053 0.54 5.00 0 6.70 2Lindane(gamma-BHC) 0.005 0.07 1.00 0 1.00 1Mirex 0.000 0.00 0.00 0 0.00 0Trans-nonachlor 0.210 1.31 5.70 0 12.7 7

9

3
94

Sediment Total PAHs 

West Coast Small Estuaries

0

20

40

60

80

100

0 5000 10000 15000 20000 25000

Concentration (ng/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-14. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of total PAHs.
95

Sediment High Molecular Weight PAHs 

West Coast Small Estuaries

0

20

40

60

80

100

0 500 1000 1500 2000 2500 3000 3500

Concentration (ng/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-15. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of high molecular weight PAHs.
96

Sediment Low Molecular Weight PAHs 

West Coast Small Estuaries

0

20

40

60

80

100

0 5000 10000 15000 20000 25000

Concentration (ng/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-16. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of low molecular weight PAHs.
97

Sediment Total PCBs 

West Coast Small Estuaries

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

Concentration (ng/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-17. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of total PCBs.
98

Sediment Total DDT Concentration

 West Coast Small Estuaries

0

20

40

60

80

100

0 50 100 150 200 250 300 350

Concentration (ng/g)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-18. Percent area (and 95% C.I.) of West Coast small estuaries vs. sediment

concentration of total DDT.
99

3.2.3 Sediment Toxicity

3.2.3.1 Ampelisca abdita

Sediment toxicity tests with the amphipod Ampelisca abdita were conducted on a total

of 190 sediment samples, 41 in Washington, 76 in Oregon, and 73 in California. Control

conditions for a successful toxicity test with this species require a mean of 90% survival

in the five replicates in control sediments, with no replicate less than 80%. If the

amphipods do not survive at acceptable levels in control replicates, it may be possible

that they were unduly stressed due to shipping or laboratory holding conditions and that

their response to test sediments may be compromised. The quality control requirements

were not met in 24 of the 190 samples, and these samples were excluded from the CDF

analysis, leaving 166 samples for analysis. The stations that were excluded included 7

in Washington, 6 in Oregon and 11 in California.

The control-corrected survivorship of Ampelisca abdita in bioassays of sediments

collected in West Coast small estuaries (Figure 3.2 -19) ranged from 0 % to 109.9 %

across the 166 stations that were included in the analysis. Approximately 9.2 % of the

area of West Coast small estuaries (represented by 12 sites) had control-corrected

survivorship of Ampelisca abdita in sediment bioassays < 80%. Over 19 % of area had

control-corrected survivorship > 100 %, indicating better survival of amphipods in test

sediments than in controls.

Four stations in Washington, one in Oregon and seven stations in California had mean

survival in test sediments less than 80%. Only four stations had mean survival in test

sediments less than 60%; these included two sites in the Smith River, one site in the

Los Angeles River in California, and one site in Grays Bay, Washington. Of the 12 sites

with survival less than 80%, five sites showed evidence of high levels of sediment

contaminants. 

3.2.3.2 Arbacia punctulata

Sediment porewater toxicity tests with sea urchins, Arbacia punctulata, were conducted

on 41 sites in Washington, 36 base stations in Oregon, and 47 base stations in

California, for a total of 124 samples. No sediments from the intensification sites in

northern California or Tillamook Bay, Oregon, were tested with Arbacia. Five test

sediments from Oregon (OR99-0018,..20,..24,..25,..26) and thirteen from California

(CA99-0014,..15,..16,..17,..20, ..21,..22,..23,..25,..26,..28,..29,..30) arrived at the testing

laboratory at temperatures that exceeded the acceptable temperature criterion. Since it

is not known what effect the elevated temperatures may have on porewater toxicity, test

results from those sediment samples were excluded from the CDF analysis. As

described in Section 2.4.2.2.2, the designation of toxicity for Arbacia bioassays utilized

two statistical test criteria for individual samples, rather than using a single survival

standard as was done with the Ampelisca bioassays. The statistical test criteria in

practice translate to a control corrected standard of approximately 85% fertilization

success or embryonic survival in the CDF based analysis of data. 
100

The control corrected mean percent fertilization of A. punctulata eggs in the 100% of the

water quality adjusted (WQA) porewater treatment ranged from 0.2 % to 106 %, across

the 97 stations that were included in the analysis (Figure 3.2-20). Approximately 7.4 %

of the area of the West Coast small estuaries (12 sites) had control corrected mean

percent fertilization of < 86 %, and thus would be considered to have toxic sediments

based on this bioassay. For the 50 % of WQA porewater treatment, the range of mean

percent fertilization was 5 % to 106 %, while 2.3% of estuarine area (6 sites) had values

< 86% fertilization (Figure 3.2-21). For the 25 % of WQA porewater treatment, the

range of mean percent fertilization was 50 % to 106 %, while 0.8 % of estuarine area (4

sites) had values < 85% fertilization (Figure 3.2-22).

The control corrected mean percent successful development of A. punctulata embryos

in the 100 % of WQA porewater treatment ranged from 0 % to 103 %, across the 97

stations that were included in the analysis (Figure 3.2-23). Approximately 45 % of the

area of the West Coast small estuaries (52 sites) had control corrected mean percent

embryo development success of # 87 %, and thus would be considered to have toxic

sediments based on this bioassay. For the 50 % of WQA porewater treatment, the

range of mean percent embryo development success was 0 % to 103 %, while 19.7 %

of estuarine area (27 sites) had values < 85 % embryo development success (Figure

3.2-24). For the 25 % of WQA porewater treatment, the range of mean percent embryo

development success was 0 % to 103 %, while 2.5 % of estuarine area (6 sites) had

values < 86 % embryo development success (Figure 3.2-25).
101

Sediment Toxicity 

West Coast Small Estuaries

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140

Percent Survival Ampelisca abdita

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-19. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

control-corrected survivorship of Ampelisca abdita.
102

Percent Egg Fertilization Success

 of Arbacia punctulata - 100% of 

Water Quality Adjusted Porewater 

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100 120

Percent Egg Fertilization Success (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-20. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

fertilization of Arbacia punctulata eggs for the 100% water quality adjusted

porewater concentration.
103

Percent Egg Fertilization Success

 of Arbacia punctulata - 50% of 

Water Quality Adjusted Porewater 

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100 120

Percent Egg Fertilization Success (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-21. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

fertilization of Arbacia punctulata eggs for the 50% water quality adjusted

porewater concentration.
104

Percent Egg Fertilization Success

 of Arbacia punctulata - 25% of 

Water Quality Adjusted Porewater 

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100 120

Percent Egg Fertilization Success (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-22. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

fertilization of Arbacia punctulata eggs for the 25% water quality adjusted

porewater concentration.
105

Percent Embryonic Development Success

 of Arbacia punctulata - 100% of 

Water Quality Adjusted Porewater 

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100 120

Percent Embryonic Development Success (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-23. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

successful embryonic development of Arbacia punctulata for the 100% water

quality adjusted porewater concentration.
106

Percent Embryonic Development Success

 of Arbacia punctulata - 50% of 

Water Quality Adjusted Porewater

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100 120

Percent Embryonic Development Success (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-24. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

successful embryonic development of Arbacia punctulata for the 50% water

quality adjusted porewater concentration.
107

Percent Embryonic Development Success

 of Arbacia punctulata - 25% of 

Water Quality Adjusted Porewater

West Coast Small Estuaries

0

20

40

60

80

100

0 20 40 60 80 100 120

Percent Embryonic Development Success (%)

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.2-25. Percent area (and 95% C.I.) of West Coast small estuaries vs. percent

successful embryonic development of Arbacia punctulata for the 25% water

quality adjusted porewater concentration.
108

3.2.4 Tissue Contaminants

Residues of a suite of metals, PCBs, and pesticides were measured in the whole bodies

of fish (see Table 2-5 for list of compounds). Flatfish (pleuronectiformes) were the

designated target species, while various perch-like species (perciformes) were the

secondary target group when flatfish were not captured. If neither flatfish nor perch-like

species were present, whatever abundant species was captured at the site was utilized

as an “other” group. Twelve of the fifteen sites with residues measured on the “other”

species occurred in the Northern California intensive sites. The specific fish species in

each group and their relative abundance are given in Table 3.2-3. Combined across all

three states, fish residues were measured at 145 to 152 sites, depending upon the

analyte, with flatfish measured at 112 to 119 of these sites (Tables 3.2 -4 and 3.2 -5). 

Because it is not clear that the sites without any fish captured for residue analysis were

distributed randomly, and due to the uncertainties associated with mixing different guilds

of fish species, the fish residue data are presented as summary statistics rather than as

CDFs to estimate areas.

Fish tissue residues of the 11 metals measured in all three states are summarized for all

fish species combined and for each fish group in Table 3.2 -4. Aluminum, with an

average concentration of 122 :g/g for all fish species, had a residue about seven-times

greater than zinc, the metal with the second highest concentration. Silver, mercury,

cadmium, and lead had the lowest residues, with all four having a mean concentration

<0.1 :g/g when averaged for all species. The concentrations of the various metals

were generally similar among the three fish groups. The greatest difference was with

nickel, which had mean values of 0.38 :g/g and 0.11 :g/g in the flatfish and perches,

respectively, compared to an average of 2.07 :g/g in the “other” group. Though the

mean values were similar, the sample site location of the maximum tissue residues

varied for each of the metals. For example, all the mercury residues >0.05 :g/g

occurred in California, and the two residues >0.1 :g/g occurred in San Diego Bay and in

the Albion River in Northern California. In comparison, the two highest arsenic

concentrations occurred in Discovery Bay, Washington; the highest lead value occurred

in Willapa Bay, Washington; and the highest copper residues occurred in Tillamook Bay,

Oregon.

Fish tissue residues of total PCBs, total DDT, and other pesticides are summarized in

Table 3.2 -5. Total DDT had the highest residue of all the neutral organic contaminants,

averaging about 44.7 ng/g when averaged over all the fish species. 4,4'-DDE

constituted 83% to 91% of the total DDT in all three fish groups. In contrast to the

metals, total DDT showed a considerable difference among the fish groups, ranging

from 1.92 ng/g in the “other” group to 245 ng/g in the perciform species. Total PCBs

had the second highest residue of the neutral organics, averaging about 17 ng/g for all

fish species combined. PCB138 and PCB153 were the two most abundant PCB

congeners, making up 34% to 60% of the total PCBs in the three fish groups. As with

total DDT, total PCBs showed a considerable difference among the fish groups, ranging

from about 1 ng/g in the “other” group to 83 ng/g in the perciform species. It is possible

that these differences among fish groups are largely a result of where the different types
109

of fish species were collected rather than an inherent difference in bioaccumulation by

the fish groups. Genyonemus lineatus (white croaker) was the most abundant species

in the perciform group, and all the white croaker used for fish residues were obtained

from either the Los Angeles Harbor or the Long Beach Harbor. These two

industrialized harbors were the sites for the maximum fish residues for both total PCBs

and total DDT and had relatively high total PCB and total DDT sediment concentrations. 

In comparison, most of the individuals making up the “other” group were captured in the

non-industrialized, small, Northern California estuaries.

The residues of the thirteen additional pesticides were considerably lower than that of

total DDT (Table 3.2 -5). Endosulfan sulfate had the highest residue of the other

pesticides, with a concentration of 1.24 ng/g when averaged over all the fish species. 

No other pesticide was >1 ng/g when averaged over all the fish species, though Transnonachlor averaged 3.08 ng/g in the perciform species. Mirex and Toxaphene were

never detected in any fish. The three fish groups showed several differences in the

mean residues of these pesticides. None of the thirteen additional pesticides were

detected in the “other” fish group. The primary differences between the flatfish and

perch-like species were the absence of detectable levels of Endosulfan sulfate and the

higher residues of Trans-nonachlor in the perch-like species. As mentioned above,

differences in where the various species groups were collected may have contributed to

these among-group differences in residue patterns.

Tissue residues of certain organic pollutants (e.g., DDT and PCBs) and organometals

(e.g., mercury) tend to increase in larger organisms. It is not possible to directly

evaluate this effect using the EMAP data because different size fish were composited

into single analytical samples. It is possible, however, to assess whether there is any

relationship between the average size of the individuals in a composite and the

composite residue. Using mercury as the test compound, a significant positive linear

relationship was observed between average wet weight of the individuals and mercury

concentration when all fish species were combined as well as with Pleuronectes

vetulus. These preliminary results suggest that residues for the organic pollutants and

organometals would tend to be higher in larger fish in the small estuaries of the Pacific

Coast.
110

Table 3.2-3. The species composition and relative abundance of the three fish groups

used in the tissue residue analysis. The percent within a group is the relative

abundance of the species within the group in which it is included. The overall percent is

the relative abundance of the species when all the fish species are combined.

Fish Group Number Percent within

Group

Overall Percent

Pleuronectiformes

 Pleuronectes vetulus 47 37.0 29.4

 Platichthys stellatus 43 33.9 26.9

 Citharichthys stigmaeus 21 16.5 13.1

 Paralichthys californicus 10 7.87 6.25

 Psettichthys melanostictus 3 2.36 1.88

 Citharichthys sordidus 1 0.79 0.63

 Pleuronectes isolepis 1 0.79 0.63

 Symphurus atricauda 1 0.79 0.63

Perciformes

 Genyonemus lineatus 6 33.3 3.75

 Cymatogaster aggregata 5 27.8 3.13

 Paralabrax nebulifer 3 16.7 1.88

 Gasterosteus aculeatus 2 11.1 1.25

 Embiotoca lateralis 1 5.56 0.63

 Paralabrax maculatofasciatus 1 5.56 0.63

“Other”

 Leptocottus armatus 12 80.0 7.50

 Oligocottus rimensis 2 13.3 1.25

 Atherinops affinis 1 6.67 0.63
111

Table 3.2-4. Fish tissue residues of metals measured in all three states. The “All Fish”

group is the overall average combining all species. The species compositions of the

pleuronectiform, perciform, and “other” groups are given in Table 3.2 -3. 

Metal Mean

(:g/g wet)

SD Minimum Maximum Number

Samples 

All Fish

 Aluminum 122 110 3.36 569 145

 Arsenic 0.60 0.63 0.00 3.77 146

 Cadmium 0.03 0.04 0.00 0.31 145

 Chromium 1.11 3.48 0.07 36.5 145

 Copper 1.25 1.04 0.00 7.77 145

 Lead 0.06 0.10 0.00 0.84 145

 Mercury 0.02 0.02 0.00 0.11 149

 Nickel 0.52 1.74 0.00 15.1 145

 Selenium 0.37 0.14 0.00 0.83 147

 Silver 0.01 0.02 0.00 0.27 145

 Zinc 17.7 7.09 7.84 39.1 145

Pleuronectiformes

 Aluminum 116 110 3.36 568 112

 Arsenic 0.61 0.70 0 3.77 113

 Cadmium 0.03 0.05 0 0.31 112

 Chromium 1.00 3.47 0.07 36.5 112

 Copper 1.21 1.12 0 7.77 112

 Lead 0.05 0.10 0 0.84 112

 Mercury 0.02 0.02 0 0.09 116

 Nickel 0.38 1.30 0 13.2 112

 Selenium 0.35 0.13 0 0.63 114

 Silver 0.01 0.03 0 0.27 112

 Zinc 18.8 6.95 7.9 39.1 112

Perciformes

 Aluminum 117 82.2 15.2 266 18

 Arsenic 0.76 0.29 0.30 1.27 18

 Cadmium 0.01 0.01 0.00 0.04 18

 Chromium 0.46 0.59 0.12 2.66 18

 Copper 1.30 0.86 0.68 4.44 18

 Lead 0.10 0.10 0.00 0.37 18

 Mercury 0.05 0.02 0.01 0.11 18

 Nickel 0.11 0.16 0.00 0.53 18

 Selenium 0.52 0.17 0.17 0.83 18

 Silver 0.01 0.01 0.00 0.04 18

 Zinc 15.06 7.56 7.84 37.0 18

“Other”

 Aluminum 174 127 46.1 485 15

 Arsenic 0.33 0.08 0.23 0.50 15

 Cadmium 0.01 0.01 0.00 0.03 15

Table continued on next page
112

 Chromium 2.73 5.02 0.27 19.8 15

 Copper 1.51 0.42 1.01 2.39 15

 Lead 0.06 0.05 0.00 0.17 15

 Mercury 0.03 0.02 0.00 0.10 15

 Nickel 2.07 3.84 0.06 15.1 15

 Selenium 0.39 0.09 0.22 0.56 15

 Silver 0.01 0.00 0.00 0.01 15

 Zinc 13.0 4.73 9.46 29.0 15
113

Table 3.2-5. Fish tissue residues of total PCBs, total DDT and the additional pesticides

measured in all three states. The “All Fish” group is the overall average combining all

species. The species composition of the pleuronectiform, perciform, and “other” groups

are given in Table 3.2 -3. 

Compound Mean

(ng/g wet)

SD Minimum Maximum Number 

Samples

All Fish

 Total PCBs 17 47.9 0.00 331 152

 Aldrin 0.04 0.28 0.00 2.40 149

 Alpha-chlordane 0.18 1.07 0.00 11.5 149

 Total DDT 44.7 219 0.00 2509 148

 Dieldrin 0.05 0.24 0.00 1.40 149

 Endosulfan Sulfate 1.24 3.34 0.00 21.4 151

 Endosulfan I 0.10 0.63 0.00 5.17 150

 Endosulfan II 0.05 0.26 0.00 2.09 149

 Endrin 0.10 0.43 0.00 3.81 149

 Heptachlor 0.45 1.44 0.00 9.80 149

 Heptachlor Epoxide 0.02 0.16 0.00 1.26 149

 Lindane (gamma-BHC) 0.01 0.13 0.00 1.62 149

 Mirex 0.00 0.00 0.00 0.00 149

 Trans-nonachlor 0.58 2.60 0.00 27.1 149

 Toxaphene 0.00 0.00 0.00 0.00 149

Pleuronectiformes

 Total PCBs 8.89 21.5 0 133 119

 Aldrin 0.05 0.32 0 2.40 116

 Alpha-chlordane 0.08 0.38 0 3.55 116

 Total DDT 19.0 45.9 0 311 115

 Dieldrin 0.07 0.27 0 1.40 116

 Endosulfan Sulfate 1.59 3.71 0 21.4 118

 Endosulfan I 0.13 0.71 0 5.17 117

 Endosulfan II 0.05 0.26 0 2.09 116

 Endrin 0.12 0.48 0 3.81 116

 Heptachlor 0.58 1.61 0 9.80 116

 Heptachlor Epoxide 0.02 0.14 0 1.16 116

 Lindane (gamma-BHC) 0.01 0.15 0 1.62 116

 Mirex 0.00 0.00 0 0.00 116

 Trans-nonachlor 0.26 0.76 0 4.57 116

 Toxaphene 0.00 0.00 0 0.00 116

Perciformes

 Total PCBs 83.5 109 0.00 331 18

 Aldrin 0.00 0.00 0.00 0.00 18

 Alpha-chlordane 0.98 2.88 0.00 11.50 18

 Total DDT 245 593 0.00 2509 18

 Dieldrin 0.00 0.00 0.00 0.00 18

 Endosulfan Sulfate 0.00 0.00 0.00 0.00 18

Table continued on next page
114

 Endosulfan I 0.00 0.00 0.00 0.00 18

 Endosulfan II 0.08 0.36 0.00 1.51 18

 Endrin 0.06 0.24 0.00 1.01 18

 Heptachlor 0.00 0.00 0.00 0.00 18

 Heptachlor Epoxide 0.07 0.30 0.00 1.26 18

 Lindane (gamma-BHC) 0.00 0.00 0.00 0.00 18

 Mirex 0.00 0.00 0.00 0.00 18

 Trans-nonachlor 3.08 6.87 0.00 27.1 18

 Toxaphene 0.00 0.00 0.00 0.00 18

“Other”

 Total PCBs 1.08 1.89 0.00 4.70 15

 Aldrin 0.00 0.00 0.00 0.00 15

 Alpha-chlordane 0.00 0.00 0.00 0.00 15

 Total DDT 1.92 3.22 0.00 9.00 15

 Dieldrin 0.00 0.00 0.00 0.00 15

 Endosulfan Sulfate 0.00 0.00 0.00 0.00 15

 Endosulfan I 0.00 0.00 0.00 0.00 15

 Endosulfan II 0.00 0.00 0.00 0.00 15

 Endrin 0.00 0.00 0.00 0.00 15

 Heptachlor 0.00 0.00 0.00 0.00 15

 Heptachlor Epoxide 0.00 0.00 0.00 0.00 15

 Lindane (gamma-BHC) 0.00 0.00 0.00 0.00 15

 Mirex 0.00 0.00 0.00 0.00 15

 Trans-nonachlor 0.00 0.00 0.00 0.00 15

 Toxaphene 0.00 0.00 0.00 0.00 15
115

3.3 Biotic Condition Indicators

A total of 187 0.1-m2

 benthic samples (grabs or combined cores) were collected in the

three states: 47 in the base stations in California, 25 in the intensive stations in Northern

California, 49 in the base stations in Oregon, 29 in the intensive stations in Tillamook,

Oregon, and 37 in the base stations in Washington. Average penetration of the 187

samples was 10.3 cm, although five grabs and six core samples had a penetration less

than 5 cm. These eleven samples had an average benthic density about one-third

greater than the three-state average and so were included in the analysis.

3.3.1 Infaunal Species Richness and Diversity

A total of 841 benthic taxa, plus an additional 26 colonial species growing on hard

substrates (e.g., bryozoans on shell hash), were found in the 187 benthic samples. Due

to difficulties in standardizing the count of colonial species, such species were excluded

from the estimates of abundance and the count of number of species per sample.

Insects were included as a single taxon in the current analyses. Species richness

averaged 22.2 species per sample (0.1-m2

) in the three states, while average species

richness among the states ranged from a low of 14.3 species per sample in Oregon to a

high of 28.6 in California (Table 3.3-1). The Northern California intensive sites tended to

have a lower species richness, and without inclusion of these sites, the species richness

increased in the base California sites to an average of 38.2 species per sample. Across

the three states, species richness ranged from 1 to 157 species per grab (0.1-m2

). Of

the five benthic samples that only had one species, two occurred in California, two in

Oregon, and one in Washington. Four of these stations with low species richness

occurred at stations with bottom salinities <1 psu, while the fifth occurred at a station with

a bottom salinity of 13.9 psu. Of the three stations with >100 species per sample, two

occurred in Discovery Bay and the other in Freshwater Bay, both in the Strait of Juan de

Fuca, Washington. All these stations with high species richness had bottom salinities

>30 psu. 

On an areal basis, approximately 50% of the area of the West Coast small estuaries had

a species richness of # 17 species per sample, and 90% of the area had a species

richness less than 62 species per sample (Figure 3.3-1). Because of the small area of

the Northern California estuaries compared to rest of the coast, exclusion of the Northern

California intensive sites had an inconsequential effect on these areal estimates.

The diversity index Hr (log base 2 derived) averaged 2.33 in the three states and ranged

from 0 to 5.93 (Table 3.3-1). Across the states, average Hr ranged from a low of 1.88 in

Oregon to a high of 2.68 in California. Hr tended to be lower in small Northern California

estuaries, and for comparison, the exclusion of these intensive sites increased the

average for the California base station to 3.33. The stations with an Hr of 0 were the five

stations with a single species per sample mentioned above. The maximum Hr (5.93)

occurred in the Discovery Bay, Washington, sample that contained 147 species.
116

On an areal basis, 50% of the area of the West Coast small estuaries had an Hr less

than 2.80, and 90% of the area had an Hr less than 4.18 (Figure 3.2 -2). As with

species richness, exclusion of the Northern California stations had almost no effect on

these areal estimates.

3.3.2 Infaunal Abundance and Taxonomic Composition

Benthic density averaged 1378.9 individuals per sample in the three states and ranged

from 1 to 41,582 individuals per sample (Table 3.3-1). Average density across the

states ranged from a low of 482.5 individuals per sample in Washington to a high of

2620.7 individuals per sample in California (Table 3.3-1). Benthic density in the

Northern California intensive sites tended to be higher than the rest of the state, and if

these small estuarine systems are excluded, benthic density averaged 1033.0

individuals per sample in the base stations in California (Table 3.3-1). Across the three

states, six stations had densities <10 individuals/sample. Three of these low-density

stations occurred at sites with a salinity <0.5 psu, while the other three occurred at sites

with salinities ranging from about 1 to 9 psu. The two stations with the greatest benthic

densities, 41,582 and 32,285 individuals per sample, both occurred in the Smith River in

Northern California. The only other station with >20,000 individuals/sample occurred in

the Little River, also in Northern California. The amphipods Americorophium spinicorne

and A. salmonis constituted between 89% and 98% of the individuals at these stations. 

Salinity at these Smith River stations was 8-10 psu, while salinity at the Little River

station was 31.2 psu. 

On an areal basis, 50% of the area of the West Coast small estuaries had a benthic

density less than 151 individuals/sample, and 90% of the area had a density less than

1157 individuals/sample (Figure 3.3-3). As with species richness and Hr diversity,

exclusion of the Northern California stations had an inconsequential effect on the these

areal estimates.

 

The abundance, taxonomic grouping, and classification of the 10 most abundant benthic

species from the three states are given in Table 3.3-2. These ten numerically dominant

species made up 75% of the total fauna. The amphipods Americorophium spinicorne

and A. salmonis were the two most abundant species, making up 54% of the total

fauna. Oligochaetes were the third most abundant taxon, making up 7% of the total

fauna, as well as being the most frequently captured taxon. Of the remaining seven

numerically abundant species, six were polychaetes and one was an amphipod. The

maximum abundances of six of the numerically dominant species, including all three

amphipod species, occurred in the small estuaries of Northern California. With their

high densities and small area, the Northern California intensive sites have a

disproportionate impact on the three-state summary statistics. Therefore, the summary

statistics for the three states are also presented for the 10 most abundant benthic

species excluding the Northern California intensive sites (Table 3.3-3). Americorophium

spinicorne and A. salmonis were still the two most abundant species in the three states,

although their densities were only about 15% to 30% of their values when Northern

California was included. Another difference when the Northern California stations are

excluded is that the polychaete Owenia fusiformis and the amphipod Grandidierella

japonica were included among the numerically dominant species while Neanthes and

Eogammarus drop out.

Tables 3.3-2 and 3.3-3 list the classification of the numerically dominant species as

native, nonindigenous, cryptogenic, or indeterminate. Cryptogenic species are species

of uncertain geographic origin (Carlton, 1996), while indeterminate taxa are those taxa

not identified to a sufficiently low level to classify as native, nonindigenous, or
117

cryptogenic (Lee et al., 2003). Of the 10 numerically dominant species (Table 3.3-2),

five were native, two were indeterminate, two were nonindigenous, and one was

classified as cryptogenic. These three nonindigenous and cryptogenic species

constituted less than 6% of the total benthic abundance. When the Northern California

sites are excluded, the ten numerically dominant species in the three states are

composed of three natives, two indeterminate taxa, three nonindigenous species, and

two cryptogenic species (Table 3.3-3). The relative abundance of the combined,

numerically dominant nonindigenous and cryptogenic species was 15.3% (Table 3.3-3)

when the Northern California sites were excluded. This contribution to total abundance

was more than twice the relative abundance (5.7%, Table 3.3-2) calculated when the

Northern California sites were included.
118

Benthic Species Richness 

West Coast Small Estuaries 

0

20

40

60

80

100

0 20 40 60 80 100 120 140 160

Number of Species

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.3-1. Percent area (and 95% C.I.) of West Coast small estuaries vs. benthic

infaunal species richness.
119

Shannon-Weiner Diversity Index 

West Coast Small Estuaries 

0

20

40

60

80

100

01234567

H'

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.3-2. Percent area (and 95% C.I.) of West Coast small estuaries vs. benthic

infaunal Hr diversity.
120

Total Number of Benthic Organisms 

West Coast Small Estuaries 

0

20

40

60

80

100

0 5000 10000 15000 20000 25000 30000 35000 40000 45000

Number of Organisms

Cumulative Percent Area

Cumulative Percent

95% Confidence Interval

Figure 3.3-3. Percent area (and 95% C.I.) of West Coast small estuaries vs. benthic

infaunal total abundance.
Table 3.3-1. Summary statistics for benthic abundance, number of species per benthic sample, and Hr. All values are

calculated per 0.1 m2 benthic sample. The 3-State values include the base and intensive stations from California, Oregon

and Washington (N=187). The California values are calculated both for the base stations with the intensive stations in

Northern California included (N=72), and for the base stations without the California intensive sites (N=47). The Oregon

values are calculated for the base stations with the intensive stations in Tillamook Bay (N=78). The Washington values

are calculated for the base stations (N=37). 

Location:Parameter Mean SD Min Max

3-State: Individuals/sample 1378.9 4264.8 3 41,5823-State: Spp/sample 22.2 23.5 1 1473-State: Hr 2.33 1.26 0 5.93

CA: Individuals/sample 2620.7 6580.3 7 41,582CA: Spp/sample 28.6 23.7 1 95CA: Hr 2.68 1.35 0 5.24CA base wo/N. CA: Individuals/sample 1033.0 1442.3 12 7383CA base wo/N. CA: Spp/sample 38.2 23.6 5 95CA base wo/N. CA: Hr 3.33 1.13 1.34 5.24OR: Individuals/sample 657.7 1191.4 7 8118OR: Spp/sample 14.3 11.6 1 65OR: Hr 1.88 0.96 0 4.10WA: Individuals/sample 482.5 710.1 3 3106WA: Spp/sample 26.5 34.9 1 147WA: Hr 2.58 1.37 0 5.93

1

2

1
Table 3.3-2. Abundance, taxonomic grouping, and classification of the ten most abundant benthic species in the three

states including the intensification sites in Northern California and Tillamook, Oregon (N=187). * = maximum valueoccurred in the Northern California intensification sites. Taxonomic groupings: A = amphipod, O = oligochaete, P =

polychaete. Classification of the species: Native, NIS = nonindigenous, Crypto. = cryptogenic, Indeter. = indeterminatetaxa (see text for definitions).

Taxon Class Mean SD Max Min Percent

Abundance

Percent

Frequency

Americorophium spinicorne A Native 524.2 3389.8 39,700* 0 38.0 27.8Americorophium salmonis A Native 220.9 1257.7 14,728* 0 16.0 34.8Oligochaeta O Indeter. 96.7 343.1 3,219* 0 7.0 56.7Eogammarus confervicolusComplex

A Native 35.4 198.5 1953* 0 2.6 19.8

Streblospio benedicti P NIS 29.2 189.8 1889 0 2.1 13.9Mediomastus sp P Indeter. 28.0 86.3 668 0 2.0 39.6Mediomastus californiensis P Native 26.4 120.9 1162 0 1.9 22.5Pygospio elegans P Crypto. 25.9 202.5 1963 0 1.9 14.4Pseudopolydorapaucibranchiata

P NIS 23.4 216.3 2772 0 1.7 16.0

Neanthes limnicola P Native 19.7 94.7 1004* 0 1.4 29.4

122
Table 3.3-3. Abundance, taxonomic grouping, and classification of the ten most abundant benthic species in the three

states excluding the Northern California intensification stations (N=162). Taxonomic groupings: A = amphipod, O =

oligochaete, P = polychaete. Classification of the species: Native, NIS = nonindigenous, Crypto. = cryptogenic, Indeter. =indeterminate taxa (see text for definitions).

Taxon Class Mean SD Max Min Percent

Abundance

Percent

Frequency

Americorophium spinicorne A Native 77.4 515.5 6147 0 10.7 19.8Americorophium salmonis A Native 67.8 261.8 2598 0 9.3 34.0Oligochaeta O Indeter. 59.1 232.9 2393 0 8.1 53.1Mediomastus sp P Indeter. 32.3 92.0 668 0 4.4 45.1Mediomastus californiensis P Native 30.5 129.5 1162 0 4.2 24.7Pygospio elegans P Crytpo. 29.6 217.4 1963 0 4.1 13.6Pseudopolydorapaucibranchiata

P NIS 26.9 232.2 2772 0 3.7 16.7

Streblospio benedicti P NIS 25.2 174.2 1889 0 3.5 14.8Owenia fusiformis P Crypto. 16.0 154.7 1890 0 2.2 9.3Grandidierella japonica A NIS 13.2 69.3 637 0 1.82 24.7

1

2

3
124

3.3.3 Demersal Species Richness and Abundance

To measure abundance and composition, fish were sampled with 16-foot bottom otter

trawls in all three states. There was a total of 144 successful trawls of at least 5 minute

duration across the three states, with 37 in the base stations in California, 2 in the

intensive stations in Northern California, 43 in the base stations in Oregon, 28 in the

intensive stations in Tillamook, Oregon, and 34 in Washington. Trawls were pulled at

an average speed of 1.7 knots for an average duration of 9.9 minutes (Table 3.3-4). 

Due to the number of stations without successful trawls, the analysis of the fish trawl

data is limited to summary statistics and species composition, and no CDFs are

presented.

Table 3.3-5 shows the mean number of individuals and species captured per trawl for

the three states combined and in each of the individual states. The number of

individuals per trawl averaged 33.7 fish per trawl, with a low of 13.9 in Oregon and a

high of 68.0 in California. Species richness averaged 3.53 fish species per trawl, with a

low of 2.63 in Oregon and a high of 5.46 in California. A total of 77 fish species were

identified from the base stations in the three states, and no additional fish species were

collected from the additional trawls in the small Northern California estuaries and

Tillamook Bay. However, two additional species, Oligocottus maculosus and Salmo

clarkii, were captured in beach seines at a station in Washington that was too shallow to

pull the otter trawl. The results from these seines are not included in the summary

statistics.

The 10 most abundant fish species across the entire coast are given in Table 3.3-6.

These 10 numerically dominant species constituted 81% of the total fauna. 

Pleuronectes vetulus, the English sole, was both the most abundant and frequently

collected species along the West Coast. Citharichthys stigmaeus, the speckled

sanddab, was the second most abundant fish. These two flatfish made up more than

50% of the individuals captured in the three states and were among the top five most

abundant species in all three states (Table 3.3-7). Oregon and Washington had similar

species composition and shared four of the five numerically dominant species (Table

3.3-7). Two of the abundant species in California, Genyonemus lineatus and Seriphus

politus, were not found in the other states.
Table 3.3-4. Trawl duration and speed averaged across California, Oregon, and Washington (N=141) and in each

individual state. SD = standard deviation. Durations are given in minutes and fractions of minutes. Trawls with durationsless than 5 minutes were not use in the analysis and are not included in the table.

Location:Parameter Mean SD Maximum Minimum

3-State: Trawl duration (Min.) 9.9 1.18 15.0 5.03-State: Trawl speed (Knots) 1.7 0.41 3.1 0.9CA: Trawl duration (Min.) 9.8 1.06 12.0 5.0CA: Trawl speed (Knots) 2.0 0.27 3.1 1.0OR: Trawl duration (Min.) 9.8 1.25 13.0 5.0OR: Trawl speed (Knots) 1.6 0.39 2.4 0.9WA: Trawl duration (Min.) 10.0 1.20 15.0 7.0WA: Trawl speed (Knots) 1.3 0.17 1.6 1.0

1

2

5
Table 3.3-5. Mean number of fish captured per trawl and mean number of fish species per trawl averaged across

California, Oregon, and Washington (N=144) and for each individual state. SD = standard deviation. 

Location:Parameter Mean SD Minimum Maximum Percent

Frequency

(%)

3-State: Individuals/trawl 33.7 72.9 0 496 99.33-State: Species/trawl 3.53 2.68 0 17 99.3CA: Individuals/trawl 68.0 111.0 0 496 97.4CA: Species/trawl 5.46 3.77 0 17 97.4OR: Individuals/trawl 13.9 18.2 1 111 100OR: Species/trawl 2.63 1.38 1 6 100WA: Individuals/trawl 35.5 76.6 1 336 100WA: Species/trawl 3.18 2.10 1 10 100

1

2

6
Table 3.3-6. Ten numerically dominant fish species averaged across California, Oregon, and Washington, including both

the base and intensive stations (N=144). Relative abundance is the percentage the species makes up of the totalabundance. Frequency is the number (or percent) of trawls in which each species was captured in the three states.

Scientific Name Common Name Mean

Individuals/

Trawl

SD

Individuals/

Trawl

Max 

Individuals/

Trawl

Relative

Abundance

(%)

Frequency 

(% Frequency)

Pleuronectes vetulus English sole 10.40 34.63 256 30.9 67

(46.5%)

Citharichthys stigmaeus Speckled sanddab 6.75 23.96 194 20.0 46 

(31.9%)

Cymatogaster aggregata Shiner perch 2.83 17.08 193 8.4 35

(24.3%)

Platichthys stellatus Starry flounder 1.98 4.90 33 5.9 53

(36.8%)

Genyonemus lineatus White croaker 1.07 7.71 76 3.2 9 

(6.3%)

Microgadus proximus Pacific tomcod 0.90 8.72 104 2.7 7 

(4.9%)

Ophiodon elongatus Lingcod 0.89 4.66 40 2.6 13 

(9.0%)

Spirinchus thaleichthys Longfin smelt 0.88 7.55 79 2.6 4 

(2.8%)

Leptocottus armatus Pacific staghorn

sculpin

0.88 2.22 13 2.6 41

(28.5%)

Seriphus politus Queenfish 0.83 8.24 97 2.4 3 

(2.1%)

1

2

7
Table 3.3-7. Mean and standard deviation of the five most numerically abundant fish species in California, Oregon, and

Washington. The California and Oregon values include both the base and intensive stations. Frequency is the number(or percent) of trawls in which each species was captured within the state. N = 39 in California; N = 71 in Oregon; N = 34in Washington.

California

Species

California

Mean/Trawl

(SD)

California

Frequency

Oregon

Species

Oregon

Mean/Trawl

(SD)

Oregon

Frequency

Washington

Species

Washington

Mean/Trawl

(SD)

Washington

Frequency

Citharichthys

stigmaeus

19.3

(42.1)

17 

(43.6%)

Pleuronectes

vetulus

3.9

(6.6)

38 

(53.5%)

Pleuronectes

vetulus

16.6

(47.8)

18

(52.3%)

Pleuronectes

vetulus

16.9

(47.9)

11

 (28.2%)

Platichthys

stellatus

2.7

(5.1)

37

(52.1%)

Cymatogaster

aggregata

6.4

(33.0)

7

(21.3%)

Genyonemus

lineatus

3.9

(14.6)

9

 (23.1%)

Cymatogaster

aggregata

1.7

(4.9)

22

 (31.0%)

Citharichthys

stigmaeus

3.8

(12.5)

12 

(35.3%)

Ophiodonelongatus

3.1

(8.6)

9 

(23.1%)

Microgadus

proximus

1.6

(12.4)

2 

(2.8%)

Platichthys

stellatus

2.6

(6.6)

13

 (38.2%)

Seriphus

politus

3.1

(15.8)

3 

(7.7%)

Citharichthys

stigmaeus

1.3

(3.7)

17

 (23.9%)

Spirinchus

thaleichthys

1.3

(7.7)

1 

(2.9%)

1

2

8
129

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