Effects of Urbanization on Stream Ecosystems in the 

Willamette River Basin and Surrounding Areas, 

Oregon and Washington

Scientific Investigations Report 2006–5101–D

U.S. Department of the Interior

U.S. Geological Survey

Chapter D of 

Effects of Urbanization on Stream Ecosystems in 

Six Metropolitan Areas of the United States

National Water-Quality Assessment Program
Front Cover – Starting lower left corner then clockwise: 

Oregon Department of Fish and Wildlife salmon spawning sign at Tickle Creek 

near Boring, Oregon. (photo by Andy Arnsberg, hydrologic technician, Portland 

Bureau of Environmental Services, Portland, Oregon, 2004.) 

Rainfall runoff along gutter of an impervious street surface, Beaverton. (photo by 

Hank Johnson, hydrologist, USGS, Portland, Oregon, 2007.) 

Urban debris in Johnson Creek at Circle Avenue, Oregon. (photo by Andy 

Arnsberg, hydrologic technician, Portland Bureau of Environmental Services, 

Portland, Oregon, 2004.)

Sediment barrier for urban development along Beaverton Creek. (photo by Hank 

Johnson, hydrologist, USGS, Portland, Oregon, 2008.)

Back Cover – Starting lower left clockwise:

Andy Arnsberg collecting water quality sample at N.F. Deep Creek at Barton, 

Oregon. (photo by Kurt Carpenter, biologist, USGS, Portland, Oregon, 2004.)

Ian Wigger collecting transducer data at Rock Creek near Vancouver, 

Washington. (photo by Mike Sarantou, hydrologic technician, USGS, Portland, 

Oregon, 2004.) 

Fanno Creek near Beaverton, Oregon, during a winter high flow event. (photo by 

Hank Johnson, hydrologist, USGS, Portland, Oregon, 2007.)

Claggett Creek at Keizer, Oregon during summer low flow. (photo by Andy 

Arnsberg, hydrologic technician, Portland Bureau of Environmental Services, 

Portland, Oregon, 2004.)
Effects of Urbanization on Stream 

Ecosystems in the Willamette River 

Basin and Surrounding Area, 

Oregon and Washington

By Ian R. Waite, Steven Sobieszczyk, Kurt D. Carpenter, Andrew J. Arnsberg, 

Henry M. Johnson, Curt A. Hughes, Michael J. Sarantou, and Frank A. Rinella

Chapter D of

Effects of Urbanization on Stream Ecosystems in 

Six Metropolitan Areas of the United States

National Water-Quality Assessment Program

Scientific Investigations Report 2006–5101–D

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2008

For product and ordering information:

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U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Waite, I.R., Sobieszczyk, Steven, Carpenter, K.D., Arnsberg, A.J., Johnson, H.M., Hughes, C.A., Sarantou, M.J., and 

Rinella, F.A., 2008, Effects of urbanization on stream ecosystems in the Willamette River basin and surrounding area, 

Oregon and Washington: U.S. Geological Survey Scientific Investigations Report 2006-5101-D, 62 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with accurate and timely 

scientific information that helps enhance and protect the overall quality of life and that facilitates 

effective management of water, biological, energy, and mineral resources (http://www.usgs.

gov/). Information on the quality of the Nation’s water resources is critical to assuring the long-term 

availability of water that is safe for drinking and recreation and suitable for industry, irrigation, and 

habitat for fish and wildlife. Population growth and increasing demands for multiple water uses make 

water availability, now measured in terms of quantity and quality, even more essential to the long-term 

sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support 

national, regional, and local information needs and decisions related to water-quality management 

and policy (http://water.usgs.gov/nawqa). Shaped by and coordinated with ongoing efforts of other 

Federal, State, and local agencies, the NAWQA Program is designed to answer: What is the condition 

of our Nation’s streams and ground-water? How are the conditions changing over time? How do natural 

features and human activities affect the quality of streams and ground-water, and where are those 

effects most pronounced? By combining information on water-chemistry, physical characteristics, stream 

habitat, and aquatic life, the NAWQA Program aims to provide science-based insights for current and 

emerging water issues and priorities. 

From 1991 to 2001, the NAWQA Program completed interdisciplinary assessments in 51 of the Nation’s 

major river basins and aquifer systems, referred to as Study Units (http://water.usgs.gov/nawqa/

studyu.html). Baseline conditions were established for comparison to future assessments, and longterm monitoring was initiated in many of the basins. During the next decade, 42 of the 51 Study Units 

will be reassessed so that 10 years of comparable monitoring data will be available to determine trends 

at many of the Nation’s streams and aquifers. The next 10 years of study also will fill in critical gaps 

in characterizing water-quality conditions, enhance understanding of factors that affect water quality, 

and establish links between sources of contaminants, the transport of those contaminants through the 

hydrologic system, and the potential effects of contaminants on humans and aquatic ecosystems.

The USGS aims to disseminate credible, timely, and relevant science information to inform practical and 

effective water-resource management and strategies that protect and restore water quality. We hope 

this NAWQA publication will provide you with insights and information to meet your needs, and will 

foster increased citizen awareness and involvement in the protection and restoration of our Nation’s 

waters. 

The USGS recognizes that a national assessment by a single program cannot address all water-resource 

issues of interest. External coordination at all levels is critical for a fully integrated understanding of 

watersheds and for cost-effective management, regulation, and conservation of our Nation’s water 

resources. The NAWQA Program, therefore, depends on advice and information from other agencies—

Federal, State, interstate, Tribal, and local—as well as nongovernmental organizations, industry, 

academia, and other stakeholder groups. Your assistance and suggestions are greatly appreciated.

 Robert M. Hirsch

Associate Director for Water
iv

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v

Contents

Foreword ........................................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................2

Study Area..............................................................................................................................................2

Methods...........................................................................................................................................................7

Site Selection.........................................................................................................................................7

Geospatial and Ecological Characteristics .............................................................................7

Gradient in Degree of Urbanization ..........................................................................................7

Site Accessibility..........................................................................................................................7

Urban Intensity Index...........................................................................................................................9

Data Collection...............................................................................................................................................9

Physical Characteristics......................................................................................................................9

Stream Hydrology ........................................................................................................................9

Stream Temperature....................................................................................................................9

Watershed and Stream Habitat...............................................................................................10

Chemical Characteristics ..................................................................................................................10

Discrete Samples.......................................................................................................................10

Semipermeable Membrane Devices......................................................................................10

Biological Characteristics.................................................................................................................11

Algal Assemblages....................................................................................................................11

Benthic Macroinvertebrate Assemblages ............................................................................11

Fish Assemblages......................................................................................................................11

Data Reduction and Analysis.....................................................................................................................12

Pesticide Toxicity Index Calculations..............................................................................................12

Explanatory Environmental Variables..............................................................................................12

Relating Biological Assemblages to Environmental Factors.......................................................13

Results. ...........................................................................................................................................................14

Physical Characteristics....................................................................................................................14

Geographic Setting....................................................................................................................14

Stream Hydrology ......................................................................................................................14

Water Temperature ...................................................................................................................16

Stream Habitat ...........................................................................................................................16

Chemical Characteristics ..................................................................................................................16

Pesticide Occurrence ...............................................................................................................16

Seasonal Variability..........................................................................................................18

Temporal Variability..........................................................................................................18

Pesticide Metrics in Relation to Urban Intensity Index..............................................18

Pesticide Toxicity Index in Relation to Urban Intensity Index ...................................21

Semipermeable Membrane Device Assays in Relation to Urban Intensity 

Index......................................................................................................................23

Nutrients and Field Parameters ..............................................................................................24
vi

Contents—Continued

Biological Characteristics.................................................................................................................26

Algae Assemblages...................................................................................................................26

Response in Algal Biomass to Urban Intensity Index.................................................27

Multivariate Analysis of Diatom Assemblages............................................................30

Response in Algal Metrics to Urban Intensity Index and Select Environmental 

Variables ...............................................................................................................32

Benthic Macroinvertebrate Assemblages ............................................................................33

Benthic Macroinvertebrate Metrics in Relation to Urban Intensity Index .............34

Multivariate Analysis of Benthic Macroinvertebrate Assemblages........................37

Fish Assemblages......................................................................................................................41

Fish Metrics in Relation to Urban Intensity Index .......................................................41

Multivariate Analysis of Fish Assemblages .................................................................44

Summary........................................................................................................................................................45

Acknowledgments.......................................................................................................................................46

References Cited..........................................................................................................................................46

Appendix A. Variable Definitions ...........................................................................................................51

Figures

Figure 1. Map showing location of the Willamette River basin and surrounding area,

Oregon and Washington .................................................................. 4

Figure 2. Map showing level III ecoregions of the Willamette River basin and surrounding

area, Oregon and Washington ............................................................ 5

Figure 3. Map showing national land cover data, Willamette River basin and surrounding

area, Oregon and Washington, 2001 ...................................................... 6

Figure 4. Map showing candidate and final watersheds selected for the urban gradient

study, Willamette River basin and surrounding area, Oregon and Washington ... 8

Figure 5. Graph showing relation between urban intensity index (UII) and number of falling

hydrologic events greater than or equal to 9 times the median, Willamette River

basin and surrounding area, Oregon and Washington ................................. 16

Figure 6. Graph showing percentage of riffle habitat in relation to summer dissolved

oxygen concentrations, Willamette River basin and surrounding area, Oregon

and Washington ........................................................................... 16

Figure 7. Boxplots showing pesticide concentrations and detection frequency for all

stream samples, Willamette River basin and surrounding area, Oregon and

Washington ................................................................................. 17

Figure 8. Graph showing urban intensity index (UII) and percentage of agricultural land for

all 28 sites, Willamette River basin and surrounding area, Oregon and Washington 21

Figure 9. Graph showing total pesticide concentration in relation to urban intensity index

(UII) for all 28 sites, Willamette River basin and surrounding area, Oregon and

Washington ................................................................................. 22
vii

Figures—Continued

Figure 10. Graph showing total insecticide concentration in relation to urban intensity

index (UII) for all 28 sites, Willamette River basin and surrounding area, Oregon

and Washington ........................................................................... 22

Figure 11. Graph showing relations between Pesticide Toxicity Index (PTI) and (A) urban

intensity index (UII) and (B) road density (ROADDEN), Willamette River basin

and surrounding area, Oregon and Washington ....................................... 23

Figure 12. Graph showing relation between the urban intensity index (UII) and

semipermeable membrane device results for the (A) toxic equivalent index

(TEQ) and (B) pyrene index ............................................................... 24

Figure 13. Graph showing relations between average total nitrogen concentrations and

(A) urban intensity index (UII) and (B) percentage of urban plus agricultural

land, Willamette River basin and surrounding area, Oregon and Washington ...... 25

Figure 14. Graph showing relation between the urban intensity index (UII) and (A)

chlorophyll-a and (B) ash-free dry mass, Willamette River basin and

surrounding area, Oregon and Washington ............................................. 30

Figure 15. Graph showing relations between ash-free dry mass and (A) nutrient index and

(B) concentrations of dissolved organic carbon, and (C) dissolved organic

carbon and concentrations of dissolved oxygen, Willamette River basin and

surrounding area, Oregon and Washington ............................................. 31

Figure 16. Graph showing relations between urban intensity index (UII) and (A)

percentage of algal taxa requiring high levels of dissolved oxygen, and (B)

relative density of eutrophic algae, Willamette River basin and surrounding

area, Oregon and Washington ............................................................ 32

Figure 17. Graph showing relation between urban intensity index (UII) and number of

benthic macroinvertebrate taxa (richness) in the Ephemeroptera, Plecoptera,

and Trichoptera orders (EPT), Willamette River basin and surrounding area,

Oregon and Washington .................................................................. 35

Figure 18. Graph showing benthic macroinvertebrate nonmetric dimensional scaling

ordination axis 1 scores in relation to (A) urban intensity index (UII), (B) summer

dissolved oxygen concentrations, (C) percentage of flat and low elevation land

in watershed and (D) and toxic equivalents from semipermeable membrane

devices, Willamette River basin and surrounding area, Oregon and Washington 40

Figure 19. Graph showing relation between urban intensity index (UII) and percent

dominance by single fish species at all 28 sites (highest relative abundance),

Willamette River basin and surrounding area, Oregon and Washington ............ 42

Figure 20. Graph showing relation between fish assemblages (nonmetric dimensional

scaling first axis ordination scores) and (A) urban intensity index (UII), (B) toxic

equivalents (TEQ) from semipermeable membrane devices, (C) summer

dissolved oxygen (DO) concentrations and (D) the number of falling hydrologic

events (PeriodF5), Willamette River basin and surrounding area, Oregon and

Washington ................................................................................. 44

Figure 21. Graph showing relation between midday summer dissolved oxygen (DO)

concentrations and percentage of salmonids, Willamette River basin and

surrounding area, Oregon and Washington ............................................. 45
viii

Tables

Table 1. Land cover and other watershed characteristics for 28 streams sampled during

the urbanization gradient study, Willamette River basin and surrounding area,

Oregon and Washington .................................................................. 3

Table 2. Correlations of urban indicator metrics and environmental setting metrics,

Willamette River basin and surrounding area, Oregon and Washington ............ 14

Table 3. Spearman’s rank correlations between urban indicator and water-chemistry

metrics and select environmental variables, Willamette River basin and

surrounding area, Oregon and Washington ............................................. 15

Table 4. Number of pesticide detections at each site by pesticide type for spring and

summer 2004, Willamette River basin and surrounding area, Oregon and

Washington ................................................................................. 19

Table 5. Summary statistics of pesticide concentrations collected during spring and

summer 2004, Willamette River basin and surrounding area, Oregon and

Washington ................................................................................. 20

Table 6. Spearman’s rank correlation coefficients (rho values) between urban indicator

and water-chemistry variables, Willamette River basin and surrounding area,

Oregon and Washington .................................................................. 22

Table 7. Most common algal taxa from the five major Divisions identified in Richest

Targeted Habitat samples, Willamette River basin and surrounding area, Oregon

and Washington ........................................................................... 26

Table 8. Dominant algal taxon (by cell density) at each site, dominant diatom taxon, and

diatom water-quality indicator classification, Willamette River basin and

surrounding area, Oregon and Washington ............................................. 28

Table 9. Spearman’s rank correlation coefficients (rho values) between diatom algal

metrics and the urban intensity index and select environmental variables,

Willamette River basin and surrounding area, Oregon and Washington ............ 33

Table 10. Number of benthic macroinvertebrate taxa and maximum abundance per insect

order or noninsect group, Willamette River basin and surrounding area, Oregon

and Washington ........................................................................... 34

Table 11. Commonly observed benthic macroinvertebrate taxa and tolerance values,

Willamette River basin and surrounding area, Oregon and Washington ............ 35

Table 12. Single dominant benthic macroinvertebrate taxon at each site, taxon name, U.S.

Environmental Protection Agency tolerance value, Ephemeroptera, Plecoptera,

and Trichoptera richness, and richness percentage per site, Willamette River

basin and surrounding area, Oregon and Washington ................................. 36

Table 13. Comparison of average benthic invertebrate abundance and richness metrics for

high- and low-urban streams, Willamette River basin and surrounding area,

Oregon and Washington .................................................................. 36

Table 14. Correlation between selected benthic macroinvertebrate metrics and

environmental variables, Willamette River basin and surrounding area, Oregon

and Washington ........................................................................... 38

Table 15. Fish species richness, total abundance, percentages of dominance (single

species), salmonids, and nonnative fish for 28 sites, Willamette River basin and

surrounding area, Oregon and Washington ............................................. 42

Table 16. Correlations of fish metrics and nonmetric dimensional scaling axis 1 ordination

scores with environmental variables, Willamette River basin and surrounding

area, Oregon and Washington ............................................................ 43
ix

Conversion Factors, Datums, and 

Abbreviations and Acronyms

Conversion Factors

Multiply By To obtain

centimeter (cm) 0.3937 inch (in.)

gram (g) 0.03527 ounce, avoirdupois (oz)

kilometer (km) 0.6214 mile (mi)

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 0.2642 gallon (gal)

meter (m) 3.281 foot (ft) 

millimeter (mm) 0.03937 inch (in.)

square centimeter (cm2

) 0.001076 square foot (ft2)

square kilometer (km2

) 0.3861 square mile (mi2)

square meter (m2

) 0.0002471 acre 

square meter (m2

) 10.76 square foot (ft2) 

square mile (mi2

) 2.590 square kilometer (km2

) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32.

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 

25°C).

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).

Datums

Vertical coordinate information is North American Vertical Datum of 1988 (NAVD 88).

Horizontal coordinate information is Universal Transverse Mercator (UTM), Zone 10, North 

American Datum of 1927 (NAD 27).

Elevation, as used in this report, refers to distance above the vertical datum.
x

Conversion Factors, Datums, and 

Abbreviations and Acronyms—Continued

Abbreviations and Acronyms

Abbreviations and 

Acronyms Meaning

ADAS Algal Data Analysis System

ADPS Automated Data Processing System

AFDM ash-free dry mass

AhR aryl hydrocarbon receptor

BOD biological oxygen demand

CVO Cascade Volcano Observatory

DIN dissolved inorganic nitrogen

DO dissolved oxygen

DOC dissolved organic carbon

EPT Ephemeroptera (mayflies), Plecoptera (stoneflies), Trichoptera (caddesflies)

EUSE Effects of Urbanization on Stream Ecosystems

H2S hydrogen sulfide

IDAS Invertebrate Data Analysis System

NAWQA National Water-Quality Assessment

NIST National Institute of Standards and Technology

nMDS nonmetric dimensional scaling

NWIS National Water Information System

NWQL National Water-Quality Laboratory

PAH polycyclic aromatic hydrocarbons

PCA principle component analysis

PCB polychlorinated biphenyls

PTI Pesticide Toxicity Index

QA quality assurance

QC quality control

QMH qualitative multihabitat

RGS reporter gene system

ROADDEN road density

RTH richest target habitat

SAS Statistical Analysis Software

SPMD semipermeable membrane device

SRP soluble reactive phosphorus

TEQ toxic equivalent

TN total nitrogen

TP total phosphorus

UII Urban intensity index

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey
Effects of Urbanization on Stream Ecosystems in the 

Willamette River Basin and Surrounding Area, 

Oregon and Washington

By Ian R. Waite, Steven Sobieszczyk, Kurt D. Carpenter, Andrew J. Arnsberg, Henry M. Johnson, 

Curt A. Hughes, Michael J. Sarantou, and Frank A. Rinella

Abstract

This report describes the effects of urbanization on 

physical, chemical, and biological characteristics of stream 

ecosystems in 28 watersheds along a gradient of urbanization 

in the Willamette River basin and surrounding area, Oregon 

and Washington, from 2003 through 2005. The study that 

generated the report is one of several urban-effects studies 

completed nationally by the U.S. Geological Survey National 

Water-Quality Assessment Program. Watersheds were selected 

to minimize natural variability caused by factors such as 

geology, elevation, and climate, and to maximize coverage 

of different stages of urban development among watersheds. 

Because land use or population density alone often are not a 

complete measure of urbanization, a combination of land use, 

land cover, infrastructure, and socioeconomic variables were 

integrated into a multimetric urban intensity index (UII) to 

represent the degree of urban development in each watershed. 

Physical characteristics studied include stream hydrology, 

stream temperature, and habitat; chemical characteristics 

studied include sulfate, chloride, nutrients, pesticides, 

dissolved and particulate organic and inorganic carbon, and 

suspended sediment; and biological characteristics studied 

include algal, macroinvertebrate, and fish assemblages. 

Semipermeable membrane devices, passive samplers that 

concentrate trace levels of hydrophobic organic contaminants 

such as polycyclic aromatic hydrocarbons and polychlorinated 

biphenyls, also were used. The objectives of the study were 

to (1) examine physical, chemical, and biological responses 

along the gradient of urbanization and (2) determine the major 

physical, chemical, and landscape variables affecting the 

structure of aquatic communities.

Common effects documented in the literature of 

urbanization on instream physical, chemical, and biological 

characteristics, such as increased contaminants, increased 

streamflow flashiness, increased concentrations of chemicals, 

and changes in aquatic community structure toward a 

more tolerant community associated with organically 

enriched conditions, generally were observed in this study. 

The strongest correlations to the UII and to many of the 

algal, macroinvertebrate, and fish assemblage metrics and 

community ordination involved water-chemistry metrics 

including the total pesticide concentration, toxic equivalents 

(extract assay from semipermeable membrane devices), and 

dissolved oxygen. Hydrologic variability metrics, such as 

flashiness, that normally are considered to be one of the main 

processes of urban disturbance had a strong association to 

the algal and fish assemblages in this study; however, the 

hydrologic variables for macroinvertebrates were secondary 

to the water-chemistry metrics mentioned above. Generally, 

the high urban intensity sites had high abundances of 

eutrophic and lower dissolved oxygen-indicating diatoms, 

high abundances of noninsects and tolerant insects, and 

high abundances of nonnative fish species. On the other 

hand, the low urban intensity sites had higher abundances of 

pollution sensitive diatoms, larger numbers of the sensitive 

macroinvertebrate EPT taxa (Ephemeroptera, Plecoptera 

and Trichoptera Orders), and fish assemblages with higher 

abundances of sensitive salmonids. The percent salmonid and 

macroinvertebrate EPT richness metrics plotted against the UII 

indicated a possible threshold response at about 25 on the UII, 

which is equivalent to an impervious surface value of about 

5 percent. However, due to the added agricultural land use 

at sites within the 25 to 60 UII range, this possible threshold 

probably is not solely due to urbanization, but a combination 

of urban and agricultural land use. The effects of agricultural 

and urban land use could not be distinguished from each 

other, yet combined they provide a good assessment of overall 

watershed disturbance.
2 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Introduction

Research has shown that stream ecosystems are 

increasingly degraded by urban development and human 

population growth (Booth and Jackson, 1997, Paul and 

Meyer, 2001; Walsh and others, 2005; Tate and others, 

2005). The growth of urban areas changes landscapes and 

increases stresses to freshwater systems by adversely altering 

water-quality, habitat, biodiversity, and ecosystem processes 

(McDonnell and Pickett, 1990; Sala and others, 2000; Paul 

and Meyer, 2001; Brown and others, 2005; Sprague and 

others, 2006). Urban growth, or urbanization, is defined 

as the development of rural, agricultural, or forested land 

into urban land, such as buildings and roads. Urbanization 

may be further defined by incorporating population density 

estimates, percentages of urban land use classification from 

remote sensing data (Brown and others, 2005; Tate and 

others, 2005), or percentage of impervious surface cover 

(Arnold and Gibbons, 1996). Regardless of how urbanization 

is characterized, it directly changes the physical habitat and 

stream hydrology of a river system (Sinokrot and Stefan, 

1993; LeBlanc and others, 1997). For example, encroachment 

of urban land into riparian areas decreases canopy cover, 

allowing more solar radiation to heat streams (Waite and 

Carpenter, 2000; Jacobson and others, 2001; Sprague and 

others, 2006). The expansion of urban land also introduces 

more industrial and human waste to rivers, which combines 

with more urban and agricultural pesticide applications that 

deteriorate water quality in streams. Additionally, urbanization 

brings increased development and more impervious surfaces. 

Impervious surfaces, such as roads, parking lots, and rooftops, 

increase surface runoff volumes and reduce the amount 

of water that infiltrates into the soil and ground water. As 

a result, the excess runoff modifies stream hydrology and 

channel morphology causing the degradation of aquatic 

habitats (Winterbourne and Townsend, 1991), the increase in 

sedimentation rates (Waite and Carpenter, 2000), and a greater 

fluctuation in frequency and magnitude of stormflows.

To investigate the effect of multiple urban stressors 

on stream ecosystems, the U.S. Geological Survey (USGS) 

National Water-Quality Assessment (NAWQA) Effects of 

Urbanization on Stream Ecosystems (EUSE) study examined 

the effects of varying degrees of urbanization among various 

watersheds in the Willamette River basin and surrounding 

area. The approach integrated multiple parameters, such as 

socioeconomic variables, population statistics, and land use 

metrics, into a single index measurement of urbanization 

intensity (Cuffney and others, 2000; Tate and others, 2005), 

and was based on a common design and sample collection 

technique (McMahon and Cuffney, 2000). Using this 

multimetric indicator of urban intensity, 28 watersheds in 

the study area were selected with increasing degrees of 

urbanization (table 1). The urban land use gradient ranged 

from minimal urban development to highly developed land, 

while limiting differences in natural features and local 

disturbances. The gradient was used to assess the effects of 

urbanization on stream water chemistry, habitat, and biological 

conditions (Walsh and others, 2001; Fitzpatrick and others, 

2004; Sprague and others, 2006).

Purpose and Scope

This report describes the physical (stream hydrology, 

water temperature, and stream habitat), chemical (nutrients 

and pesticides), and biological (algae, macroinvertebrate, and 

fish assemblages) characteristics of stream ecosystems in 28 

watersheds along a gradient of urbanization in the Willamette 

River basin and surrounding area of Oregon and southwestern 

Washington from 2003 through 2005. Watersheds were 

selected to minimize natural variability between sites due 

to watershed size, elevation, and climate, and to maximize 

coverage of different degrees of urban development. The 

objectives of the study were to (1) examine physical, chemical, 

and biological responses along a gradient of urbanization and 

(2) determine the major physical, chemical, and landscape 

variables associated with aquatic communities. 

Study Area

The Willamette River basin and surrounding area 

includes 35,000 km2 in northwestern Oregon and southwestern 

Washington (fig. 1). Although the Willamette River basin is in 

Oregon, the study area was extended into Washington because 

of similar socioeconomic, climatic, ecologic, and topographic 

settings. For example, 1,000 km2 of the Willamette ValleyLevel III ecoregion, as defined by Omernik (1987) extends 

across the Columbia River into Washington (fig. 2). An 

ecoregion—unlike a watershed, which delineates an area 

of convergent drainage—denotes an area of shared natural 

characteristics, such as soil types, elevation, and climate. The 

Willamette Valley ecoregion contains a mixture of rolling 

prairies, mixed forests, and extensive lowland valley wetlands.

Land cover in the basin (fig. 3) is predominately forest 

(66 percent), with moderate agriculture (29 percent) and 

minimal urban (3.5 percent) and surface water (1.5 percent) 

(U.S. Geological Survey, 2005). The valley plains and foothills 

primarily are used for cultivated crops, pasture, and grasslands, 

although minimally developed areas, such as Dundee, Oregon, 

to highly developed urban areas, such as Portland, Oregon, 

also are in the valley. Fertile soils and a temperate climate 
Introduction 3

Site 

identification 

No.

Site name USGS station No. Area 

(km2

)

Urban 

intensity 

index

Urban

(percent)

Agriculture

(percent)

Mean 

impervious 

surface

(percent)

1 Beaverton Creek near SW 216th Avenue, near 

Orenco, OR

14206435 96 100 83 1 40

2 Claggett Creek at Keizer, OR1 450022123012400 25 100 98 0 55

3 Fanno Creek at Durham, OR 14206950 81 96 84 1 39

4 Pringle Creek at Salem, OR1 445551123015800 25 88 89 6 42

5 Kellogg Creek at Milwaukie, OR1 452526122364400 34 88 81 2 39

6 Amazon Creek near Danebo Road, at Eugene, OR 440257123103200 50 77 62 8 29

7 Tryon Creek below Nettle Creek, near Lake Oswego, 

OR

14211315 17 72 60 0 23

8 Curtin Creek near Vancouver, WA 454321122352300 30 69 72 16 29

9 Johnson Creek at Circle Avenue, OR 452912122291200 56 59 42 24 17

10 Battle Creek near Turner, OR 445029122592600 30 58 33 40 13

11 Rock Creek at Quatama Road, near Hillsboro, OR 14206347 67 51 28 26 13

12 Whipple Creek near Salmon Creek, WA1 454510122424900 22 49 38 19 14

13 Chicken Creek near Sherwood, OR 14206750 40 45 22 36 9

14 North Fork Deep Creek at Barton, OR1 452337122243500 37 39 27 48 10

15 Oak Creek at Corvallis, OR 443326123165200 33 39 7 19 3

16 Tickle Creek near Boring, OR1 452414122213200 34 32 19 34 8

17 Chehalem Creek at Newberg, OR 451734122585400 98 29 9 44 3

18 Silk Creek near Cottage Grove, OR 434745123040200 42 24 3 11 1

19 Rock Creek near Battleground, WA1 455122122310600 26 23 8 7 2

20 Salmon Creek near Battleground, WA1 454549122295800 59 20 13 2 3

21 Deep Creek near Sandy, OR1 452231122200000 31 17 4 30 1

22 Nate Creek near Colton, OR 14199710 29 15 2 12 1

23 Milk Creek at Camp Adams, OR 450955122291200 104 12 2 9 1

24 South Scappoose Creek at Scappoose, OR 454543122524900 65 8 3 3 1

25 North Yamhill Creek near Yamhill, OR 452149123194900 66 8 1 0 0

26 Lost Creek near Dexter, OR 435212122483300 83 6 0 1 0

27 Iler Creek near Forest Grove, OR 453506123125700 13 4 0 5 0

28 East Fork Dairy Creek near Meacham Corner, OR1 14205400 88 0 1 1 0

1

 High frequency sampling sites, which spanned the full range of the UII, were used to determine whether the degree of urbanization affected the seasonality 

of water chemistry.

make the Willamette Valley a thriving agricultural region 

(Thorson and others, 2003). Land use in the forested Coastal 

Range and Cascades is a combination of timber harvesting, 

recreation, and development. Centered on the confluence of 

the Columbia and Willamette Rivers, Portland is the most 

populous city in Oregon, with 539,000 people in city limits 

and nearly 3 million people in the Portland/Salem/Vancouver 

metropolitan area (U.S. Census Bureau, 2000). The population 

in the metropolitan area increased almost 30 percent from 

1990 to 2000, with some suburban populations increasing 

more than 80 percent during the same period (U.S. Census 

Bureau, 2000).

With temperate, dry summers and cool, wet winters, the 

Willamette River basin and surrounding area is characteristic 

of Pacific Northwest climate. About 90 percent of the annual 

precipitation occurs during October through May (Uhrich 

and Wentz, 1999), falling as rain in the valley and snow in the 

mountains. The drainage network in the Willamette Valley 

combines natural dendritic tributaries, complex networks 

of canals in agricultural areas, and sewer piping in cities. 

Dams and reservoirs regulate most large rivers, such as the 

McKenzie, Santiam, and Willamette Rivers, which supply 

drinking water, power generation, and irrigation to different 

parts of the region.

Table 1. Land cover and other watershed characteristics for 28 streams sampled during the urbanization gradient study, Willamette 

River basin and surrounding area, Oregon and Washington.

[See figure 4 for site locations. Sites are sorted by urban intensity index (UII). Shading represents low, medium, high, and very high UII scores. 

Abbreviations: km2, square kilometer; USGS, U.S. Geological Survey; SW, southwest; OR, Oregon, WA, Washington]
4 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

or19-0168_fig01

LANE

LINN

DOUGLAS

WASCO

DESCHUTES

CLACKAMAS

MARION

POLK

JEFFERSON

KLAMATH

COOS

CLATSOP

LAKE

YAMHILL

LINCOLN

TILLAMOOK

BENTON

COLUMBIA

WASHINGTON

HOOD

MULTNOMAH RIVER

COWLITZ

SKAMANIA KLICKITAT

YAKIMA

CLARK

Portland

Salem

Eugene

Vancouver

WASHINGTON

OREGON

STUDY

AREA

City limits

Rivers

Study area

County boundary

EXPLANATION

Base map modified from USGS digital data (1:24,000). 

Projection: UTM, Zone 10, North American Datum 1927.

124° 123° 122° 121°

44°

45°

46°

0 25 50 75 KILOMETERS

0 25 50 75 MILES

PACIFIC OCEAN

 Columbia River

Willamette River

Figure 1. Location of the Willamette River basin and surrounding area, Oregon and Washington.
Introduction 5

or19-0168_fig02

LANE

LINN

DOUGLAS

WASCO

DESCHUTES

CLACKAMAS

MARION

POLK

JEFFERSON

KLAMATH

COOS

CLATSOP

LAKE

YAMHILL

LINCOLN

TILLAMOOK

BENTON

COLUMBIA

WASHINGTON

HOOD

MULTNOMAH RIVER

COWLITZ

SKAMANIA KLICKITAT

YAKIMA

CLARK

Portland

Salem

Eugene

Vancouver

WASHINGTON

OREGON

STUDY

AREA

Base map modified from USGS digital data (1:24,000),

USEPA Level III Ecoregion based on Omernick (1987). 

Projection: UTM, Zone 10, North American Datum 1927.

124° 123° 122° 121°

44°

45°

46°

Study Area

EXPLANATION

Level III Ecoregion

Blue Mountains

Cascades

Coast Range

Columbia Plateau

Eastern Cascades

Klamath Mountains

Northern Basin & Range

Puget Lowland

Willamette Valley

0 25 50 75 KILOMETERS

0 25 50 75 MILES

PACIFIC OCEAN

 Columbia River

Figure 2. Level III ecoregions of the Willamette River basin and surrounding area, Oregon and Washington.
6 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Figure 3. National land cover data, Willamette River basin and surrounding area, Oregon and Washington, 2001 

(U.S. Geological Survey, 2005).

or19-0168_fig03

LANE

LINN

DOUGLAS

WASCO

DESCHUTES

CLACKAMAS

MARION

POLK

JEFFERSON

KLAMATH

COOS

CLATSOP

LAKE

YAMHILL

LINCOLN

TILLAMOOK

BENTON

COLUMBIA

WASHINGTON

HOOD

MULTNOMAH RIVER

COWLITZ

SKAMANIA KLICKITAT

YAKIMA

CLARK

Portland

Salem

Eugene

Vancouver

WASHINGTON

OREGON

STUDY

AREA

Base map modified from USGS digital data (1:24,000),

USEPA Level III Ecoregion based on Omernick (1987). 

Projection: UTM, Zone 10, North American Datum 1927.

124° 123° 122° 121°

44°

45°

46°

0 25 50 75 KILOMETERS

0 25 50 75 MILES

PACIFIC OCEAN

 Columbia River

Study Area

EXPLANATION

Water

Urban

Barren

Forest

Shrub

Grass

Pasture

Agriculture

Wetland

Land cover
Methods 7

Methods

Methods used during this study followed guidelines 

established for the National EUSE Program (Cuffney and 

others, 2000; McMahon and Cuffney, 2000; Tate and others, 

2005). Site selection started with an initial 206 “candidate” 

streams and was eventually refined to 28 “final” streams. 

Data collection began in November 2003 and continued 

through March 2005, with the 28 final streams sampled for 

physical habitat, water chemistry, and aquatic biology. The 

final streams, and their associated watersheds, represented 

varying degrees of urbanization, yet shared similar geospatial 

and socioeconomic characteristics. During the study, 96 

water-quality samples were collected and stream habitat was 

evaluated at each site. In addition, the biological community 

(algae, benthic macroinvertebrates, and fish) in each stream 

was sampled during low-flow conditions. Stream stage and 

water temperature were monitored in each stream from March 

through November 2004. Semipermeable membrane devices 

were installed at each location for about one month.

Site Selection

Streams selected for this study represented a full gradient 

of urbanization, and met the predefined geospatial and 

ecological characteristics developed for the National EUSE 

Program defined below.

Geospatial and Ecological Characteristics

To limit natural variability between watersheds, certain 

geospatial and ecological constraints were required. The 

two primary site selection constraints were “watershed 

size” and “percent coverage in the Willamette Valley-Level 

III Ecoregion (Omernik, 1987)”. Watersheds could cover 

no less than 10 km2 and not exceed 130 km2. Additionally, 

all watersheds included a minimum of 20 percent of the 

Willamette Valley ecoregion. With these guidelines, site 

selection and watershed processing proceeded using 

Geographic Information Systems (GIS) and the USGS 

National Elevation Dataset (30-m resolution NED). An 

initial 206 candidate sites were identified and respective 

watersheds were delineated (fig. 4). Several GIS datasets 

were processed against the candidate watersheds, producing 

an assortment of land cover variables for each site. The GIS 

datasets included layers of socioeconomic (census variables), 

climatic (precipitation), ecologic (ecoregion), topographic 

(slope), hydrologic (hydrologic landscape regions), 

infrastructural (census road variables), and soil characteristics 

(erosion potential), which were calculated for (1) the entire 

basin, (2) the proximate segment of the upstream area, and 

(3) the adjacent riparian area (appendix A, table A1). For 

more detailed descriptions of techniques, conversions, and 

guidelines, as well as a complete list of geospatial variables 

and their descriptions, refer to Sprague and others (2006) and 

Falcone and others (2007).

Gradient in Degree of Urbanization

The main objective of this study was to examine 

the effect of different degrees of urbanization on stream 

ecosystems. Rather than investigate long-term temporal 

changes in one system, this study monitored a large number 

of sites at progressively higher levels of urbanization in a 

short timeframe. Theoretically, the relation of multiple sites 

at increasing degrees of urbanization should mimic similar 

development of one site over progressive years of increasing 

urbanization (Sprague and others, 2006). Therefore, selecting 

watersheds that represented a range in urbanization from 

minimum development to maximum development was 

paramount.

Classifying urbanization was more complicated than 

basing it solely on urban land use. For this study, watershed 

and riparian land cover, infrastructural, and demographic 

variables were integrated into a “candidate” urbanization 

intensity index (UII) (McMahon and Cuffney, 2000). 

This UII was calculated from data for all 206-candidate 

watersheds. Seventeen GIS variables with at least a 0.5 

Spearman’s correlation to population density and that were 

not correlated above 0.5 with watershed size were included 

in the calculation. After the UII was generated, 70 of the 206 

watersheds were selected for reconnaissance.

Site Accessibility

Each of the 70 remaining candidate sites were visited 

after their watersheds were delineated, characterized, and 

ranked with a UII. Field reconnaissance was used to verify 

GIS results and to evaluate accessibility and safety restrictions. 

Some sites were relocated upstream or downstream of 

the original location to obtain reaches with cobble or 

riffle substrate, or to avoid culverts or other undesirable 

obstacles. Some sites were excluded because the stream was 

ephemeral, watershed conditions were impossible to survey, or 

landowners would not permit access. Whenever possible, sites 

were selected to provide an even distribution along the UII.

Of the remaining candidate sites, a prerequisite 30 final 

sites were selected throughout the Willamette River basin 

and surrounding area. Initially, all 30 watersheds met the 

required geospatial and ecological characteristics. However, 

after adjustments for accessibility were incorporated into the 

drainage delineation, two sites did not fulfill the 20 percent 

coverage of the Level III ecoregion requirement—South 

Scappoose Creek in Oregon (6 percent) and Rock Creek in 
8 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

or19-0168_fig04

WASHINGTON

OREGON

STUDY

AREA

Level III Ecoregion

Candidate basin

Final basin and

 index number

EXPLANATION

Study area

23

Base map modified from USGS digital data (1:24,000),

USEPA Level III Ecoregion based on Omernick (1987). 

Projection: UTM, Zone 10, North American Datum 1927.

124° 123° 122° 121°

44°

45°

46°

0 25 50 75 KILOMETERS

0 25 50 75 MILES

1

28 24

3

11

23

17

26

25

12

20

9

22

6

5

18

21

16

15

8

7

13 14

10

19

4

2

27

Figure 4. Candidate and final watersheds selected for the urban gradient study, Willamette River basin and 

surrounding area, Oregon and Washington.
Data Collection 9

Washington (17 percent). The sites remained in the study 

after analysis of land cover, topographic, and hydrologic 

characteristics revealed that the watersheds shared similar 

characteristics with the other 28 sites and were necessary 

to fill vacancies in the urbanization gradient. Two other 

sites were eventually eliminated late in the study because 

conditions were not favorable for biological sampling in 

summer after water chemistry samples had been collected the 

previous winter. The final 28 sites and their basic watershed 

characteristics are listed in table 1.

Urban Intensity Index

A “final” UII was generated and applied to the 28 final 

sites based on the procedure developed by McMahon and 

Cuffney (2000). To calculate the final UII, a select group of 24 

input GIS variables (table A2) were normalized to watershed 

area and then sorted by ascending variable percentage. 

The sorted values then were ranked on a scale of 0 to 100. 

Variables that correlated with population density (according 

to a criterion of a Spearman’s rank correlation of greater or 

equal to 0.70) and remained uncorrelated with watershed area 

(absolute value of Spearman’s correlation less than or equal to 

0.50) were used as inputs for the UII. For each site, all ranked 

GIS variables that met these constraints were averaged to 

produce a raw UII. The averaged raw values then were scaled 

from 0 to 100. The resulting value represented the final urban 

intensity index value for each site. The final UII differed from 

the candidate UII because fewer sites were factored into the 

analysis, different GIS variables were incorporated into the 

UII calculation, and a higher Spearman’s rank correlation was 

used (increased from 0.50 from 0.70).

Data Collection

Physical Characteristics

Stream Hydrology

Stevens-Greenspan Model PS310 pressure transducers, 

each with an internal data logger, were used to measure 

stream-stage fluctuation during the study (Greenspan 

Technology, 2006). Transducers were placed instream in pools 

or runs to ensure consistent response of hydrologic stage 

and to minimize the potential for dewatering. The transducer 

model was not vented to the atmosphere; therefore, changes 

in recorded pressure reflected changes in stream level and 

atmospheric pressure. Data were corrected for fluctuations in 

atmospheric pressure using hourly barometric pressure data 

from nearby airports because continuous barometric pressure 

records were not available at the study sites. The stage data 

from the transducers had a precision of ±0.036 m, which 

did not meet USGS requirements for stage data precision 

(±0.003 m) (Sauer, 2002); however, it was deemed acceptable 

for the purposes of this study.

For logistical reasons, the pressure-transducer 

deployment periods varied among the sampling sites, with the 

most complete record obtained between March and November 

2004. This 9-month period included a number of “typical” 

spring and autumn rain events, and provided adequate 

data to characterize the hydrologic variability among sites. 

Hydrologic variables calculated from the stage data included 

more than 35 hydrologic variables. These variables included 

measures of stage variability (regularity in streamflow), 

estimates of streamflow magnitude (amount of water moving 

past a given point per unit of time), stream flashiness (how 

quickly streamflow changes from one magnitude to another), 

duration (length of time associated with specific streamflow 

conditions), and frequency (how often streamflows greater 

than or less than a certain magnitude recur). Calculations were 

based on equations outlined in McMahon and others (2003) 

using SAS version 8 (Delwiche and Slaughter, 1998).

Stream Temperature

Stevens-Greenspan Model PS310 pressure transducers 

also monitored continuous water temperature data 

(30-minute intervals) during the study. Twenty percent of 

the transducers were tested for accuracy (within ± 0.01°C, 

verified by comparing readings in a temperature bath with 

a traceable National Institute of Standards and Technology 

[NIS] thermometer prior to field deployment). Temperature 

data were stored in the Automated Data Processing System 

(ADAPS), a part of the National Water Information System 

(NWIS) (U.S. Geological Survey, 2003). Summary statistics 

for various water temperature measures included daily 

minimum, maximum, mean, range, and standard deviation, 

which were calculated for each stream using hourly data. 

Occasionally, short periods of temperature record were 

lost due to transducer failure or dewatering, such as when 

stream levels dropped during low flow in late summer. 

Temperature data for the missing intervals were reconstructed 

using an extraction-correlation technique, which used the 

30-minute data to extract daily mean values from March 

through November 2004 data. Sites then were correlated with 

each other. Linear regressions based on these correlations 

were used to estimate temperature values for days without a 

daily mean value. At sites with missing data, an average of the 

regressions was used to estimate missing values.
10 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Watershed and Stream Habitat

Watershed-level characterization of habitat provided 

information on the upstream geologic, climatic, hydrologic, 

morphologic, and biologic influences at a site. Watershedlevel habitat variables defined in this study included drainage 

area, drainage density, watershed length, mean watershed 

elevation, drainage shape, watershed relief, drainage texture, 

and cumulative perennial stream length. Other watershed-level 

information included land cover, surficial geology, soil, and 

riparian variables. Segment-level characterization of habitat 

provided information on finer scale influences in the relatively 

homogenous segment stream length. Actual segment length 

varies among streams depending on the distance between 

significant tributaries and/or point source inputs (Fitzpatrick 

and others, 1998). Segment-level variables determined in this 

study included sinuosity, slope segment length, and channel 

gradient. Watershed-level and segment-level characteristics 

were derived by GIS.

Reach-level characterization based on site visits was the 

principal means for describing local-scale influence within 

a segment (Fitzpatrick and others, 1998). Reach length was 

determined by multiplying the mean wetted channel width 

by 20 to ensure that all habitat types (pools, riffles, and runs), 

were represented within the reach. Reach-scale habitat data 

were collected during low-flow conditions in July and August 

2004. Stream depth, width, bed substrate, habitat cover, 

bank morphology, canopy closure, stream velocity, and bank 

vegetation were measured at 11 or 12 equally spaced transects 

along each reach (mesoscale characterization). At one site—

Curtin Creek—only nine transects were completed due to 

channel reach constraints. In addition, point velocity, substrate, 

and depth were measured where richest targeted habitat algae 

and benthic macroinvertebrate samples were collected (microscale characterization). A complete list of habitat variables 

used in this study is given in the appendix (tables A3 and A4). 

Detailed information on methods of habitat data collection and 

variables is available in Fitzpatrick and others (1998). 

 GIS variables, additional to those originally used in 

site selection and UII genesis, were gathered for analytical 

purposes. Hydrologic variables describing stream segment, 

riparian buffer, and road/stream intersection were examined, as 

well as associated dams, reservoirs, and waterway diversions. 

In addition, the program FRAGSTATS (McGarigal and others, 

2002) was run for each final watershed to evaluate spatial land 

use patterns. FRAGSTATS variables quantified the degree of 

fragmentation, such as size, configuration, and connectivity, of 

urban and nonurban areas in a watershed (Sprague and others, 

2006). As Alberti and Marzluff (2004) noted, this disruption 

of continuous land can affect ecosystem health by limiting or 

interrupting the natural movement of organisms. All additional 

GIS variables are available in Sprague and others (2006).

Chemical Characteristics

Discrete Samples

Water samples for chemical analysis were collected 

from all 28 sites twice during the study. Samples were 

collected from all sites in May 2004 (spring sampling) and 

in late August or early September 2004 (summer sampling) 

to bracket the biological sampling during July through 

September 2004. Water-chemistry conditions during these 

months were more likely to have a more direct effect on the 

biological communities in the streams than conditions earlier 

in the study. To document the seasonal variability in water 

chemistry, 10 of the 28 sites were sampled 4 additional times: 

November 2003, and January, March, and June 2004. These 10 

“high frequency” sampling sites spanned the full range of the 

UII to determine whether the degree of urbanization affected 

the seasonality of water chemistry (table 1).

Sulfate, chloride, nutrients, pesticides, dissolved and 

particulate organic and inorganic carbon, and suspended 

sediment samples were collected at all sites (table A7). Field 

measurements of water temperature, dissolved oxygen (DO), 

pH, specific conductance, and streamflow also were made 

during sampling. Samples were collected using standard 

protocols as outlined in the USGS National Field Manual 

(U.S. Geological Survey, variously dated). Nutrient and 

pesticide samples were analyzed at the USGS National 

Water-Quality Laboratory (NWQL) in Lakewood, Colorado, 

using methods developed by Fishman (1993) and Zaugg and 

others (1995). Suspended-sediment samples were analyzed 

at the USGS Cascade Volcano Observatory (CVO) sediment 

laboratory in Vancouver, Washington. Quality-control 

samples, including field blanks, replicates, and laboratory 

spikes were collected throughout the study and analyzed at 

the NWQL and CVO. About 10 percent of the total number of 

field samples was collected for quality assurance. All qualitycontrol, or quality-assurance, samples analyzed indicated that 

sample collection, processing, or laboratory analysis were 

acceptable.

Semipermeable Membrane Devices

Semipermeable membrane devices (SPMDs) are passive 

sampling cartridges that were deployed in each stream to 

sample and concentrate hydrophobic organic contaminants 

from the water (Huckins and others, 1993; Bryant and others, 

2007). In this study, SPMDs were designed to mimic the 

fatty tissues of fish, and used to indicate the potential for 

bioaccumulation of polychlorinated dioxins and furans, 

polycyclic aromatic hydrocarbons (PAHs), polychlorinated 

biphenyls (PCBs), and organochlorine and pyrethroid 

insecticides.
Data Collection 11

SPMDs were deployed in each of the 28 streams for 

about 4 weeks beginning in July 2004. At the end of the 

deployment period, they were removed and sent to multiple 

locations for analysis. Contaminant residues were recovered 

and separated at Environmental Sampling Technologies 

in St. Joseph, Missouri, as described in Huckins and 

others (1990). An ultraviolet fluorescence scan to quantify 

total PAHs (Johnson and others, 2004) and a Microtox® 

bioassay (Johnson, 1998) was run at the USGS Columbia 

Environmental Research Center in Columbia, Missouri. 

U.S. Army Corp of Engineers environmental laboratory in 

Vicksburg, Mississippi, ran an additional assay, the P450 RGS 

test that screens for aryl hydrocarbon receptor (AhR) type 

compounds that include PCBs, PAHs, dioxins, and furans 

(Murk and others, 1996).

Because SPMDs integrate chemical conditions over time 

and, sometimes, during variable flow conditions, they provide 

a more complete representation of chemical exposure than 

periodically collecting water samples (Huckins and others, 

1993). SPMDs also eliminated the problem of determining 

chemical exposure in aquatic organism tissue by eliminating 

concern whether organisms metabolized compounds or if 

organisms migrated from exposure sources. Limitations of the 

SPMDs include: 

1. The inner dialysis tubing (dialysate) was permeable only 

to nonionic compounds; and 

2. The accumulation rates may have been affected by 

the physicochemical properties of individual nonionic 

compounds, variations in water temperature, flow 

velocity, and biofouling on the exterior membrane surface 

(Huckins and others, 1993) and the exposure duration. 

All final data used in analysis were blank corrected/time 

normalized according to procedures outlined by Bryant and 

others (2007) to address these limitations and allow for better 

comparability of data among sites.

Biological Characteristics

Algal, benthic macroinvertebrate and fish assemblage 

samples were collected once during the study period in each of 

the 28 streams following protocols described in Moulton and 

others (2002). Algal and benthic macroinvertebrate samples were 

collected during September and October 2004, respectively, and 

fish communities were sampled in July and August 2004. 

Algal Assemblages

Quantitative algal samples were collected at each site 

from riffles at the richest targeted habitat (RTH) using methods 

described in Moulton and others (2002). RTH algal samples were 

collected from 5 to 15 representative rocks per site and combined 

into a single sample. Rocks were removed, and algal material was 

collected using the pipe-scribe top rock scrape method described 

in Carpenter (2003). A round plastic scribe (short length of PVC 

pipe) with an outside diameter ranging between 4 and 10.4 cm 

was placed on each rock, and algal material outside the scribe was 

removed with a plastic-bristle brush or scraped off with a knife, 

and discarded. The circular patch of algae remaining on the rock 

was scraped into a small washbasin, and rinsed into a 1-L sample 

bottle using stream water. Samples were briefly homogenized 

with an electric blender, and subsamples were collected 

for chlorophyll-a, ash-free dry mass (AFDM), and species 

identification. Chlorophyll-a and AFDM subsamples were 

collected on 45-micron glass-fiber filters, wrapped in foil, sealed, 

packed on dry ice, and shipped to the NWQL for fluorometric 

chlorophyll-a (Arar and Collins, 1997) and gravimetric AFDM 

analyses (Britton and Greeson, 1987). All algae water samples 

were preserved in 5 percent buffered formalin solution and 

shipped to the Academy of Natural Sciences of Philadelphia for 

taxa identification and enumeration following protocols described 

by Charles and others (2002).

Benthic Macroinvertebrate Assemblages

One semiquantitative RTH sample for benthic 

macroinvertebrates was collected from five riffle areas in 

each stream. Each of the five subsamples were collected 

using a 500-micron mesh Slack sampling net (modified 

Surber design), which was placed in the stream, and rocks 

were cleaned of benthic organisms from a 0.25 m2 sampling 

area into the net. The five subsamples were combined in the 

field at each site. Additionally, one qualitative multihabitat 

(QMH) sample was collected using a 500-micron mesh dip 

net, which was used to collect and composite organisms from 

a diversity of microhabitats present at each site (for example, 

riffles, runs, pools, grasses, woody debris) into a 19-L bucket. 

Microhabitats were sampled equally for a maximum of 1 hour. 

Both individual sample types underwent a field elutriation 

process to clean and remove large organic debris, excess rocks, 

and sand. The composited macroinvertebrate sample was 

transferred into a 1-L plastic bottle, preserved with 10 percent 

buffered formalin, and shipped to the NWQL for taxa 

identification and enumeration (Moulton and others, 2002).

Fish Assemblages

Fish were collected using a Smith-Root Model BP2 

backpack electro-shocker, with two separate upstream passes 

from the start to the end of the reach. Fish were caught using 

6 mm mesh nets and stored in aerated live wells. All fish were 

identified and enumerated in the field after each sampling 

pass. The first 30 fish of each species were weighed to the 

nearest 0.1 g, measured to the nearest millimeter, and checked 

for external anomalies (Moulton and others, 2002). The 

remaining individuals of each species were enumerated and 

checked for anomalies. Representative specimens of difficult 

to identify species were labeled and preserved in 10 percent 

buffered formalin solution and sent to the Department of Fish 

and Wildlife Ichthyology Museum at Oregon State University, 

Corvallis, Oregon, for identification verification. 
12 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Data Reduction and Analysis

Pesticide Toxicity Index Calculations

To supplement the spatial comparison of individual 

pesticides among sites, a pesticide toxicity index (PTI) was 

calculated for each stream water sample (Munn and Gilliom, 

2001). An additive model was used with the PTI to estimate 

potential toxicity of a water sample containing more than one 

pesticide. The toxicity was estimated by comparing stream 

concentrations to laboratory bioassay test endpoints such as 

the Lethal and Effect Concentrations for 50 percent of a test 

population (LC50 and EC50, respectively) for three taxonomic 

groups of aquatic organisms (fish, benthic invertebrates, and 

cladocerans [water flea]) (Munn and others, 2006). Although 

the PTI does not determine the actual toxicity of a sample, 

it can be used to estimate and rank the relative toxicity of 

samples containing one or more pesticides. The PTI value was 

computed for each sample by summing the toxicity quotients 

(the measured concentration of a pesticide in a stream sample 

divided by its median toxicity concentration from bioassay 

tests) for all pesticides detected in a sample. Some pesticide 

compounds had no toxicological data for some or all of the 

three taxonomic groups. To maximize the number of pesticides 

included in the PTI, a single overall PTI was calculated using 

the most sensitive or lowest median toxicity concentrations for 

fish, benthic macroinvertebrates, and cladocerans. Limitations 

of the PTI include: 

1. PTI was based on an additive model of pesticide toxicity 

(using combined toxicity-weighted concentrations 

of pesticides from multiple chemical classes without 

regard to mode of action), so the actual toxicity is not 

known because chemicals may act additively (3+2+1=6), 

independently (not additively, 1+1+1+1=1), or 

synergistically (3+2+1=9); 

2. PTI values were based on laboratory experiments 

(toxicity bioassays) of acute exposure that do not 

account for potential effects from repeated or chronic 

exposure. Environmental factors that may have affected 

bioavailability and toxicity, such as dissolved organic 

carbon (DOC) and temperature, were not incorporated 

into the PTI; 

3. PTI was calculated for pesticides in samples taken from 

the water column, which may underestimate the toxicity 

from pesticides that accumulate in benthic sediments. 

This is especially true for hydrophobic compounds 

with moderate or high Koc values (for example, 

organophosphate insecticides or pyrethroid insecticides; 

4. In some cases, the toxicity endpoint was based on a few, 

or in some cases just 1 laboratory test (the number of tests 

for an individual pesticide and taxonomic group ranged 

from 1 to 165); and 

5. PTI values were calculated for just the three groups of 

aquatic organisms, not the full spectrum of aquatic life in 

these streams. 

Despite its limitations, the PTI proved to be a useful 

measure for assessing the potential cumulative effects of 

pesticide on aquatic ecosystems, and for examining the 

relative toxicity of pesticides that do not currently have 

aquatic-life benchmarks.

Explanatory Environmental Variables

Five distinct environmental data sets were compiled, 

which included hydrology, water temperature, stream habitat, 

water chemistry, and watershed characteristics. These data 

sets were used to explain differences in algae, benthic 

macroinvertebrates, and fish at the 28 sites. Generally, 

the number of variables in each data set greatly exceeded 

the number of sampling sites (n = 28); therefore, a large 

number of variables in each data set had to be eliminated 

with the remaining variables transformed and standardized 

to meet important statistical assumptions of normality and 

homogeneity of variance (Legendre and Legendre, 1998; 

Clarke and Gorley, 2006). The number of variables in each 

data set was reduced by analyzing the correlation matrix 

and scatter plots to eliminate strongly correlated, redundant 

variables. Appendixes in Sprague and others (2006) provide a 

complete list of all environmental variables sampled and used 

in our initial analyses.

After preliminary analysis with each environmental 

data set it became apparent that even with strong data 

transformations such as log(X + 1), each data set still 

contained extreme values that dominated and skewed the 

distributions and results. Subsequently, all analyses used rank 

transformations to eliminate the influence of these extreme 

values. The multivariate BIO-ENV (biology-environment 

relationship using the BEST statistics routine in PRIMER) 

procedure in PRIMER, version 6 (Clarke and Ainsworth, 

1993; Clarke and Gorley, 2006) was used to identify a subset 

of 5 to 10 variables in each data set that best explained the 

measured variation among the 28 sites from the initial larger 

number of variables in that data set. This procedure was 

completed separately for each data set, and then the final 

or “best of the explanatory environmental variables” were 

merged. The variables retained for each data set and detailed 

descriptions are listed in tables A3 to A8. 

In addition, a nutrient index was created by taking the 

first principle component (first axis) of a principle component 

analysis (PCA) on just the variables TN and TP, then 

converting the resulting axis scores to a scale from 0 to 100. 

The first PCA axis of TN and TP explains the largest amount 

of variation across the 28 sites and therefore so does the 

nutrient index.
Data Reduction and Analysis 13

The algal data was analyzed using multivariate statistics 

and algal water-chemistry metrics were calculated using Algal 

Data Analysis System (ADAS) software (Tom Cuffney, U.S. 

Geological Survey, written commun., 2007) that interfaced 

with an autecological compilation of water-quality indicator 

traits for more than 6,000 algal taxa (Porter, 2008). ADAS 

also created the diatom-only taxa-by-site data matrix used 

for the PRIMER analyses. Nearly all sites contained a high 

percentage of relatively small nondiatom taxa (mostly bluegreen and red algae) that overshadowed the signal from the 

diatoms. Much information is available on the tolerances and 

preferences of diatoms for several water chemistry parameters 

including nutrients, specific conductance, dissolved oxygen 

(DO), pH, temperature, amount of organic matter, and current 

velocity. Therefore, multivariate and algal metric analyses 

were performed only on diatom data, and all-taxa datasets 

were characterized by relative density (number of cells/cm2).

The Invertebrate Data Analysis System software 

(IDAS; Cuffney, 2003) was used to resolve taxa ambiguities 

for invertebrate data and to calculate about 140 benthic 

macroinvertebrate metrics commonly used in bioassessment 

(Davis and Simon, 1995; Barbour and others, 1999). Cuffney 

(2003) and Cuffney and others (2005) describe and discuss the 

issues of benthic macroinvertebrate taxa ambiguities that are 

beyond the scope of this report. The benthic macroinvertebrate 

metrics included measures of richness, percentage richness, 

density, percentage density, dominance, organism tolerance, 

and assemblage diversity. The tolerance metrics reported were 

based on the combination of regional tolerance values for the 

Pacific Northwest (B. Wisseman, Aquatic Biology Associates, 

Inc., written commun., 2003) or on professional judgment 

for taxa not covered in the Wisseman regional list. All 

tolerance values assigned to taxa followed the standard U.S. 

Environmental Protection Agency (USEPA) tolerance scoring 

of 0 to 10 from least to most tolerant (Barbour and others, 

1999, Cuffney, 2003). Tolerance values then were compared 

to national and Pacific Northwest regional values reported by 

Cuffney (2003) to assure consistency and appropriateness. 

Tolerance metrics were calculated based on richness and 

abundance (Cuffney, 2003). 

All invasive-fish counts were summed to create an 

aggregated nonnative “pseudospecies” to substitute for 

the individual nonnative counts (10) due to their limited 

individual occurrences among the sites. A fish index that 

summed the scores from four individual metrics also was 

computed: percentages of salmonids, reticulate sculpins, 

nonnative species and natives with reticulate and salmonids 

removed. Site values were given scores of 8, 4, 2, or 1 if the 

value fell within different quartiles (less than 25 percent, 26 

to 50 percent, 51 to 75 percent, or greater than 75 percent). 

Scores from the four metrics then were summed and converted 

to a 0 to 100 scale “fish index,” with higher values indicating 

a more natural fish assemblage. The two native ammocoete 

lamprey (Lampetra) species were combined into the single 

category. 

Biological data matrices commonly have numerous zero 

values and a few extreme values, resulting in a highly skewed 

distribution that requires some form of transformation to bring 

it closer to a normal distribution before statistical analyses 

can be completed (Legendre and Legendre, 1998; Clarke and 

Gorley, 2006). For all multivariate analyses, diatom density 

data was transformed using the square root function and 

benthic macroinvertebrate counts were converted to abundance 

values in number per square meter and log transformed (X + 

1). The abundance data for fish species were log transformed 

(X + 1) to create the site-species matrix for multivariate 

analysis.

Relating Biological Assemblages to 

Environmental Factors

Associations between the environmental and biological 

data (algae, benthic macroinvertebrates, and fish assemblages) 

were examined using Spearman rank correlations (SAS 

version 8: Delwiche and Slaughter, 1998) and PRIMER 

multivariate statistical analyses (ordinations). Nonmetric 

dimensional scaling (nMDS) ordinations of the full 

assemblage data (for fish and benthic invertebrates) or the 

diatoms-only assemblage (for algae) were generated using 

Bray-Curtis similarity matrices for each biological assemblage 

(PRIMER, version 6: Clarke and Gorley, 2006). This method 

reduces the complex multidimensional nature of ecological 

data (for example, multiple species across many sites) to a 

reduced set of axes (1–4) that attempts to capture as much 

strength and explained variation among sites as the original 

multidimensional data matrix (for more detailed information 

on multivariate ordinations see Legendre and Legendre 1998). 

The result is a 2-axis plot where samples (sites) are positioned 

according to degree of similarity in taxonomic composition 

with each other. The goal is to reduce the complex multivariate 

species data to two ordination axes, which then may be 

correlated with environmental factors that may influence the 

species composition. In addition, the environmental matrix 

(Euclidian distance similarity) was related directly to the 

ecological matrices using the BEST procedure in PRIMER to 

determine the final subset of the environmental variables that 

best describe the variation in the ecological species matrix 

(nMDS ordination) among the 28 sites. 

In this report, Spearman rank correlation coefficients (rho 

values) were considered strong when greater than or equal 

to 0.66 and moderate when between 0.66 and 0.50. All rho 

values greater than 0.50 were statistically significant at P less 

than 0.05. The different analytical techniques used, such as 

scatter plots, summary graphs, correlations, and multivariate 

analyses, although common and robust, do not prove direct 

cause and effect. They are useful, however, for providing 

insights into ecological processes, for revealing potential 

environmental pathways, and for generating hypotheses.
14 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Results

Physical Characteristics

Geographic Setting

Urban and agricultural watershed development in the 

Willamette River basin and surrounding area followed the 

prevailing natural regional topography: most development 

was in the flat valley lowlands rather than in the higher 

elevation foothills and mountains. This was evident by the 

strong correlation between the natural environmental setting 

metrics (mean and minimum watershed elevation) and the 

urban indicator metrics (UII, percentage impervious surface, 

POPDEN00, percentage urban + agriculture, and ROADDEN 

(table 2). Environmental setting affected the natural 

characteristics of streams through variations in precipitation, 

erosion, and instream habitat as mediated by natural channel 

geomorphology and geology. Therefore, even without human 

influence, there were minor to moderate differences from the 

higher gradient foothill streams to the low-gradient valley 

streams. However, many of the environmental setting metrics 

overemphasized these differences because some variables 

were calculated for the whole watershed and not just the 

local area surrounding the sampling site. A good example 

was mean watershed slope and watershed elevation. Because 

many streams in the Willamette River basin and surrounding 

area originated in the foothills or mountains, calculated 

watershed metrics included parts of the higher elevation and 

higher gradient reaches even though the characteristics of the 

stream at the sampling site reflected the location of the stream 

with a low-gradient valley. The environmental setting metrics 

were calculated this way to provide measures of watershed 

characteristics that were consistent nationally and simple 

to calculate. There was an effort to minimize the natural 

differences among sites by selecting stream sampling reaches 

that were within the low-gradient valley, even though a large 

part of the upper watershed may be in a different ecoregion. 

For example, 75 percent of the sites were within 80 m of 

the overall mean elevation of 220 m; sites ranged between 

50 m and 620 m in elevation. Correlation of minimum 

watershed elevation to the urban indicator metrics, although 

still moderately statistically significant, was somewhat lower 

than the correlation of mean watershed elevation to the urban 

indicator metrics (table 2).

Stream Hydrology

Increased flow variability, or stream “flashiness” in the 

form of frequent high peaks and low troughs, is considered 

a key effect of urbanization on streams (Paul and Meyer, 

2001; McMahon and others, 2003; Konrad and Booth, 2005; 

Roy and others, 2005). Konrad and Booth (2005), after 

reviewing the literature and analyzing a small number of sites 

with streamflow gaging stations from reference and urban 

dominated land use watersheds, determined that the frequency 

of “high-flow events as measured as the number of events 

three times above the median flow” and the “percent daily 

change” (flashiness) were the two most sensitive measures of 

changes in hydrographs due to urbanization. In their analysis, 

these two variables also were significantly correlated with 

algae, macroinvertebrates, and fish assemblage metrics. 

Data from this EUSE study corroborates these findings. For 

example, the four hydrologic variability metrics PeriodF5, 

PeriodF9, PeriodR5, and Richards-Baker Flashiness Index 

(Rb-flash), which related to rate in streamflow change, had 

Urban indicators Mean soil 

erodibility

Watershed elevation

Organic matter

(mean percent)

Annual 

precipitation

Water surface 

slope

(mean percent)

Water depth 

Mean Minimum (mean depth)

Urban indicator metrics

Urban intensity index (UII) 0.63 -0.87 -0.53 -0.61 -0.71 -0.81 -0.70

Percent impervious surface .57 -.90 -.59 -.64 -.67 -.85 -.68

POPDEN00 .60 -.88 -.55 -.62 -.70 -.81 -.69

Percent urban + agriculture .55 -.87 -.52 -.53 -.62 -.90 -.53

ROADDEN .52 -.81 -.48 -.54 -.66 -.76 -.65

Environmental setting metrics

Mean watershed elevation (m) -0.75 – 0.76 0.72 0.76 0.81 0.70

Minimum watershed elevation (m) -.71 0.76 – .59 .63 .40 .68

Table 2. Correlations of urban indicator metrics and environmental setting metrics, Willamette River basin and surrounding area, 

Oregon and Washington.

[See appendix A for variable definitions. Correlation coefficients were considered strong when ≥ 0.66 (bolded and shaded) and moderate when 0.66 > rho ≥ 0.5 

(bolded). Abbreviations: ROADDEN, road density; m, meter. Symbols: ≥, greater than or equal to; >, greater than; –, not applicable]
Results 15

significant correlation with the urban indicator metrics (table 

3). PeriodF5, PeriodF9 and PeriodR5 were metrics that 

summarized the frequency of periods of falling (F) or rising 

(R) stream-discharge events, where hourly stream-discharge 

change was greater than or equal to 5 or greater than or equal 

to 9 multiplied by the median decrease or increase over the 

period of record (table A5). For example, PeriodF5 referred 

to the number of hours when streamflow fell over the period 

of record by at least five times the median flow for that 

site. The Rb-flash characterizes the degree that streamflow 

changed relative to the daily median. PeriodF9, the metric 

that documented the number of falling hydrologic events 

greater than nine times the site median, had the strongest 

correlation values—rho 0.69 with the UII (fig. 5) and 0.71 

with road density (ROADDEN) (table 3). Associations among 

pairs of variables are shown as regression graphs (figs. 5 and 

6) with simple linear or curvilinear trend lines added to aid 

interpretation. 

Stream and reach-scale variables

Water-chemistry variables 

Summertime 

dissolved 

oxygen

Dissolved 

organic 

carbon

Total 

insecticides

Total 

pesticides

TEQ 

(SPMD)

Average 

specific 

conductance

Sulfate 

concentration

Total 

nitrogen 

concentration

Hydrologic variation metrics

Number of falling events > 5×median (PeriodF5) -0.45 0.71 0.71 0.50 0.70 0.42 0.56 0.40

Number of falling events > 9×median (PeriodF9) -.40 .62 .68 .48 .67 .49 .66 .43

Number of rising events > 5×median (PeriodR5) -.37 .60 .65 .45 .68 .34 .52 .40

Richards-Baker Flashiness Index (Rb-flash) -.40 .70 .62 .46 .63 .39 .53 .30

Water temperature metrics

Minimum temperature (95th percentile) -0.53 0.67 0.57 0.42 0.45 0.28 0.32 0.22

Habitat metrics

Mean embeddedness (riffle and runs) -0.66 0.46 0.36 0.39 0.41 0.69 0.55 0.52

Mean width/depth ration (riffle and runs) .50 -.34 -.26 -.10 -.24 -.59 -.50 -.35

Percent riffle habitat .84 -.60 -.39 -.33 -.49 -.61 -.57 -.46

Percent large substrate .48 -.21 -.12 -.06 -.00 -.36 -.14 -.05

Mean habitat heterogeneity -.61 .38 .29 .25 .18 .31 .14 -.05

Table 3. Spearman’s rank correlations between urban indicator and water-chemistry metrics and select environmental variables, 

Willamette River basin and surrounding area, Oregon and Washington.

[See appendix A for variable definitions. Correlation coefficients were considered strong when absolute value ≥ (bolded and shaded) and moderate when 0.66 > 

rho ≥ 0.5 (bolded). Abbreviations: ROADDEN, road density; TEQ, toxic equivalents; SPMD, semipermeable membrane device. Symbols: ≥, greater than or 

equal to; >, greater than]

Stream and reach-scale variables

Urban indicators

Urban 

intensity 

index (UII)

Impervious 

area

(percent)

POPDEN00

Urban + 

agriculture

(percent)

ROADDEN

Hydrologic variation metrics

Number of falling events > 5×median (PeriodF5) 0.69 0.64 0.68 0.52 0.70

Number of falling events > 9×median (PeriodF9) .69 .65 .67 .51 .71

Number of rising events > 5×median (PeriodR5) .65 .62 .65 .48 .68

Richards-Baker Flashiness Index (Rb-flash) .56 .49 .55 .41 .53

Water temperature metrics

Minimum temperature (95th percentile) 0.56 0.51 0.56 0.44 0.53

Habitat metrics

Mean embeddedness (riffle and runs) 0.59 0.58 0.57 0.57 0.49

Mean width/depth ration (riffle and runs) -.51 -.51 -.52 -.47 -.49

Percent riffle habitat -.63 -.61 -.63 -.57 -.55

Percent large substrate -.30 -.23 -.30 -.24 -.27

Mean habitat heterogeneity .30 .21 .29 .20 .28
16 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

PERCENT RIFFLE HABITAT

100

20

40

60

80

0

0 2 4 6 8 10 12

SUMMER DISSOLVED OXYGEN, IN MILLIGRAMS PER LITER

rho = 0.84

Figure 6. Percentage of riffle habitat in relation to summer dissolved oxygen 

concentrations, Willamette River basin and surrounding area, Oregon and 

Washington.

or19-0168_ fig05

Figure 5. Relationship between the Urban Intensity Index (UII) and the number of falling hydrologic events ≥ 9 tim

NUMBER OF FALLING EVENTS

≥ 9 TIMES THE MEDIAN (PERIOD F9)

rho = 0.69

100

10

1

0 20 40 60 80 100

URBAN INTENSITY INDEX

Figure 5. Relation between urban intensity index (UII) and number of falling 

hydrologic events greater than or equal to 9 times the median, Willamette 

River basin and surrounding area, Oregon and Washington.

Water Temperature

Water temperature metrics generally 

did not correlate strongly with any urban 

indicator metrics; however, the minimum 

water temperature metric (95th percentile) 

was positively correlated with the UII 

(0.56) (table 3) and negatively correlated 

with pollution sensitive diatoms (presented 

in the algae section, below). Because site 

selection was restricted to valley streams, 

the natural range in water temperature was 

narrow compared with the range in larger 

geographic areas or other ecosystems. 

Temperature data were lost during the 

hot summer months at three sites (Silk, 

Chehalem, and South Scappoose Creeks) 

due to transducer failure.

Stream Habitat

Stream habitat metrics did not have 

particularly strong correlation values with 

any urban indicator metrics; the strongest 

correlation was between percentage of 

riffle habitat and UII and POPDEN00, rho 

= -0.63 (table 3). The weak correlations 

among habitat metrics and urban indicator 

metrics likely were due to the study 

design; sites were selected to minimize 

natural differences to increase the chances 

of isolating the effects of urbanization 

(Short and others, 2005). Therefore, 

habitat measurements may have a better 

relation to changes in urbanization than 

was revealed in this study. Although not 

strongly correlated to urban indicators, 

certain habitat metrics did correspond 

well to water-chemistry metrics. For 

example, percentage of riffle habitat was 

strongly correlated with the summer DO 

concentrations (rho = 0.84; fig. 6).

Chemical Characteristics

Pesticide Occurrence

Ninety-six stream samples were analyzed for 64 

pesticides and degradation compounds. Among the samples, 

28 pesticides or degradates were detected including 12 

herbicides, 8 insecticides, 2 fungicides, and 6 degradates 

(fig. 7). At least one pesticide or degradation product was 

detected in 83 percent of the samples. Among all samples, the 

six most frequently detected pesticides were herbicides and 

herbicide degradates: atrazine, deethylatrazine (degradate of 

atrazine), simazine, hexazinone, prometon, and metolachlor. 

The highest frequency of occurrence was for atrazine, detected 

in 49 percent of all samples. Other pesticides with at least 10 

detections include 3,4-dichloroaniline (degradate of diuron, 

and other phenylurea herbicides), tebuthiuron, trifluralin, 

carbaryl, diazinon, chlorpyrifos, metalaxyl, and myclobutanil. 

Ten or more pesticides were detected at 7 sites in either the 

spring or summer sampling; North Fork Deep Creek had 10 or 

more detections in both samplings (table 4). 

Generally, individual pesticide concentrations were 

relatively low (fig. 7). The median concentration for any 

pesticide was 0.02 μg/L or less, and only seven pesticide 

concentrations exceeded 0.1 μg/L. The highest concentration 

of any sample was 1.72 μg/L for atrazine, and the highest 

combined pesticide concentration for a sample was 2.08 μg/L, 

occurring at Battle Creek during the spring 2004 sampling.
Results 17

or19-0168_ fig07

0.0001 0.001 0.01 0.1 1 10

0.0001 0.001 0.01 0.1 1 10

Atrazine

3,4-Dichloroaniline (D)

Deethylatrazine (D)

Simazine

Hexazinone

Prometon

Tebuthiuron

Trifluralin

Metribuzin

Terbuthylazine

Pendimethalin

DCPA

Metolachlor

Propyzamide

Carbaryl

Diazinon

Chlorpyrifos

1-Naphthol (D)

Dieldrin

Fipronil

Fonofos

Desulfinyl fipronil (D)

Fenamiphos

Fenamiphos sulfone (D)

Fenamiphos sulfoxide (D)

Malathion

Metalaxyl

Myclobutanil

HERBICIDES AND HERBICIDE DEGRADATES (D),

IN MICROGRAMS PER LITER

INSECTICIDES AND INSECTICIDE DEGRADATES (D),

IN MICROGRAMS PER LITER

FUNGICIDES,IN

MICROGRAMS

PER LITER

(49)

(47)

(37)

(35)

(32)

(29)

(19)

(14)

(4)

(4)

(2)

(1)

(1)

(25)

(21)

(13)

(6)

(2)

(2)

(2)

(2)

(2)

(2)

(2)

(1)

(23)

(46)

(10)

Figure 7. Pesticide concentrations and detection frequency for 

all stream samples, Willamette River basin and surrounding area, 

Oregon and Washington.Number in parentheses is equal to the 

total detections for that compound.
18 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Seasonal Variability

On average, there were more pesticide detections and 

higher pesticide concentrations during the spring sampling 

than during the summer (tables 4 and 5). For example, nearly 

twice as many pesticides were detected in spring, including 

116 herbicides (including 24 degradates), 27 insecticides 

(including 4 degradates) and 8 fungicides, compared to 

summer when 61 herbicides (including 16 degradates), 

16 insecticides (including 2 degradates) and 7 fungicides 

were detected (table 4). During spring sampling, 5 or more 

pesticides were detected at 16 sites, whereas during summer, 

at least 5 pesticides were detected at only 7 sites. Salmon 

Creek and Iler Creek, two minimally effected sites, were the 

only two streams with no pesticide detections in either spring 

or summer samplings. Most pesticide detections were in North 

Fork Deep Creek in both sampling periods likely because this 

area includes the highest amount of agricultural land use (48 

percent) of any of the watersheds (U.S. Geological Survey, 

2005). In addition to higher frequency of detections in the 

spring, total pesticide concentration for spring was more than 

3 times greater than in summer, although a large part of this 

difference was due to one large concentration at Battle Creek, 

Oregon, during the spring sampling (table 5). 

Herbicides were detected at 25 sites during the spring 

sampling and 19 sites in the summer (table 4). Atrazine, 

hexazinone, deethylatrazine, simazine, and prometon were 

the five most commonly detected herbicides in the spring, all 

with a detection frequency greater than 46 percent. During 

summer sampling the highest detection frequencies were for 

deethylatrazine, simazine, prometon, 3,4-dichloroaniline, 

and metolachlor, ranging between 25 and 43 percent, with 

prometon being the highest. Unlike atrazine, which primarily 

is used for agricultural purposes, and simazine, which is used 

in both urban and agricultural applications, prometon is used 

mostly for nonagricultural purposes, such as domestic and 

commercial applications to driveways, fence lines, lawns, and 

gardens. Prometon also can be used as an asphalt additive 

(Gilliom and others, 2006). Previous research documented a 

direct relation between urban land use and prometon detection 

frequency in surface water and ground water (Koplin and 

others, 1998), so it was not surprising to see such a high 

frequency of detection in our study. Where insecticides were 

detected, carbaryl and diazinon were predominant. Carbaryl, 

an agricultural and urban insecticide, was detected 39 percent 

of the time in spring and 18 percent in summer. Diazinon was 

detected slightly less than carbaryl in spring at 29 percent, 

yet slightly more in summer at 21 percent. Due to changes 

in pesticide regulations, residential uses of diazinon were 

cancelled in 2004, but use is still approved for agriculture.

Temporal Variability

During the 10 site “high frequency” sampling effort, 

pesticides were detected in all samples (6 sample times) for 

the 3 most highly-urbanized sites (Claggett, Pringle, and 

Kellogg Creeks) and in 2 mixed agricultural-urban sites 

(North Fork Deep and Tickle Creeks) (table 4). Pesticides 

were detected most frequently at North Fork Deep Creek, with 

at least eight pesticides detected in each sample. The fewest 

pesticides were detected in Salmon Creek, a predominantly 

forested watershed (UII = 20), with only one detection 

in March 2004. This relatively low pesticide detection 

frequency in Salmon Creek likely was due to the low amount 

of agricultural land in this watershed (2 percent). Three 

pesticides were detected in three of the six samplings (50 

percent) in the East Fork Dairy Creek watershed, even though 

it had only 1 percent combined urban plus agriculture land 

use (the site with the UII = 0). This probably was due to the 

close upstream proximity to the sampling site of a variety of 

agricultural activities (for example, Christmas tree plantations 

and nursery operations) even though they were of small 

acreage and therefore did not add significantly to the total of 

agricultural land use summarized as a percentage of the total 

watershed area.

Overall, 44 of the 60 samples collected contained 2 or 

more pesticides and 11 of the 60 samples contained 10 or 

more pesticides. On average, between 5 and 11 pesticides 

were detected at the 3 most highly-urban sites during the 

6 high frequency samplings, and between 1 to 3 pesticides 

were detected at the 3 lowest-urban sites. Streams draining 

predominantly urban watersheds have been shown to have 

higher detection frequencies and concentrations of some 

insecticides than other types of land uses (Anderson and 

others, 1997; Gilliom and others, 2006), and the results for 

this study followed this pattern. High frequency samples 

collected at the 3 most urban sites (UII ≥ 88) (table 1) had a 

detection of at least one insecticide in 58 percent of samples; 

whereas high frequency samples collected at the 3 least urban 

sites (UII ≤ 20) had insecticide detections in only 8 percent of 

samples. 

Pesticide Metrics in Relation to Urban Intensity Index

Relations between the UII and pesticide occurrence were 

strongest when considering the total number of pesticides 

and total concentration of all pesticides in a sample. For the 

spring and summer samplings a high UII was associated with 

a large number of pesticides detected in a sample. Comparison 

among groupings of sites based on the four levels of UII 

shaded in tables 4 and 5 (low: less than 10; medium: 10 to 25; 

high: 25 to 70; and very high: greater than 70) reveals some 
Results 19

Site name UII

Spring sampling Summer sampling Total 

detections Herbicide Insecticide Fungicide Total Herbicide Insecticide Fungicide Total

Beaverton Creek near SW 216th 

Avenue, near Orenco, OR

100 7 2 1 10 3 0 1 4 14

Claggett Creek at Keizer, OR 100 7 1 0 8 4 2 0 6 14

Fanno Creek at Durham, OR 96 8 2 0 10 1 2 1 4 14

Pringle Creek at Salem, OR 88 7 1 0 8 3 0 0 3 11

Kellogg Creek at Milwaukie, OR 88 7 0 0 7 6 1 0 7 14

Amazon Creek near Danebo Road, at 

Eugene, OR

77 2 2 0 4 0 3 0 3 7

Tryon Creek below Nettle Creek, near 

Lake Oswego, OR

72 2 3 0 5 5 3 0 8 13

Curtin Creek near Vancouver, WA 69 5 0 1 6 2 0 0 2 8

Johnson Creek at Circle Avenue, OR 59 8 1 1 10 4 1 1 6 16

Battle Creek near Turner, OR 58 8 2 0 10 6 0 0 6 16

Rock Creek at Quatama Road, near 

Hillsboro, OR

51 8 2 0 10 3 0 0 3 13

Whipple Creek near Salmon Creek, WA 49 2 1 0 3 0 0 0 0 3

Chicken Creek near Sherwood, OR 45 6 2 0 8 1 0 0 1 9

North Fork Deep Creek at Barton, OR 39 8 2 2 12 7 1 2 10 22

Oak Creek at Corvallis, OR 39 1 0 0 1 0 0 0 0 1

Tickle Creek near Boring, OR 32 6 1 1 8 7 2 1 10 18

Chehalem Creek at Newberg, OR 29 7 2 0 9 2 1 0 3 12

Silk Creek near Cottage Grove, OR 24 1 0 0 1 2 0 0 2 3

Rock Creek near Battleground, WA 23 1 3 1 5 0 0 1 1 6

Salmon Creek near Battleground, WA 20 0 0 0 0 0 0 0 0 0

Deep Creek near Sandy, OR 17 4 0 1 5 2 0 0 2 7

Nate Creek near Colton, OR 15 4 0 0 4 1 0 0 1 5

Milk Creek at Camp Adams, OR 12 2 0 0 2 1 0 0 1 3

South Scappose Creek at Scappose, OR 8 1 0 0 1 0 0 0 0 1

North Yamhill Creek near Yamhill, OR 8 0 0 0 0 1 0 0 1 1

Lost Creek near Dexter, OR 6 1 0 0 1 0 0 0 0 1

Iler Creek near Forest Grove, OR 4 0 0 0 0 0 0 0 0 0

East Fork Dairy Creek near Meacham 

Corner, OR

0 3 0 0 3 0 0 0 0 3

 Total 116 27 8 151 61 16 7 84 235

Urban intensity index Averages

UII ≥ 70 89 5.7 1.6 0.1 7.4 3.1 1.6 0.3 5.0 12

UII >25 – <70 47 5.9 1.3 .5 7.7 3.2 .5 .4 4.1 12

UII >10 – ≤ 25 19 2.0 .5 .3 2.8 1.0 0 .2 1.2 4

UII ≤ 10 5 1.0 0 0 1.0 .2 0 0 .2 1

Table 4. Number of pesticide detections at each site by pesticide type for spring and summer 2004, Willamette River basin and 

surrounding area, Oregon and Washington.

[Sites are sorted by urban intensity index (UII). Shading from light to dark represents low, medium, high, and very high UII scores. Abbreviations: OR, Oregon; 

WA, Washington. Symbols: ≥, greater than or equal to; >, greater than; <, less than; ≤, less than or equal to]
20 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Site name UII

Sum pesticide Sum pesticides (spring and summer)

Spring Summer Insecticide Herbicide Fungicide

Beaverton Creek near SW 216th Avenue near Orenco, OR 100 0.077 0.053 0.012 0.090 0.028

Claggett Creek at Keizer, OR 100 .100 .105 .042 .167 0

Fanno Creek at Durham, OR 96 .132 .055 .079 .094 .014

Pringle Creek at Salem, OR 88 .050 .037 .003 .084 0

Kellogg Creek at Milwaukie, OR 88 .064 .065 .006 .123 0

Amazon Creek near Danebo Road at Eugene, OR 77 .068 .062 .096 .034 0

Tryon Creek below Nettle Creek, near Lake Oswego, OR 72 .025 .066 .037 .054 0

Curtin Creek near Vancouver, WA 69 .026 .007 0 .029 .004

Johnson Creek at Circle Avenue, OR 59 .361 .225 .022 .498 .066

Battle Creek near Turner, OR 58 2.08 .158 .026 2.21 0

Rock Creek at Quatama Road near Hillsboro, OR 51 .214 .055 .054 .220 0

Whipple Creek near Salmon Creek, WA 49 .014 0 .002 .012 0

Chicken Creek near Sherwood, OR 45 .083 .035 .016 .102 0

North Fork Deep Creek at Barton, OR 39 .259 .161 .019 .354 .047

Oak Creek at Corvallis, OR 39 .008 0 0 .008 0

Tickle Creek near Boring, OR 32 .049 .058 .011 .071 .025

Chehalem Creek at Newberg, OR 29 .190 .057 .019 .232 0

Silk Creek near Cottage Grove, OR 24 .018 .038 0 .056 0

Rock Creek near Battleground, WA 23 .060 .015 .038 .002 .035

Salmon Creek near Battleground, WA 20 0 0 0 0 0

Deep Creek near Sandy, OR 17 .039 .018 0 .054 .003

Nate Creek near Colton, OR 15 .023 .002 0 .025 0

Milk Creek at Camp Adams, OR 12 .018 .005 0 .023 0

South Scappose Creek at Scappose, OR 8 .004 0 0 .004 0

North Yamhill Creek near Yamhill, OR 8 0 .010 0 .010 0

Lost Creek near Dexter, OR 6 .007 0 0 .007 0

Iler Creek near Forest Grove, OR 4 0 0 0 0 0

East Fork Dairy Creek near Meacham Corner, OR 0 .013 0 0 .013 0

 Total 3.99 1.29

 Urban intensity index Averages

UII ≥ 70 89 0.074 0.063 0.039 0.092 0.006

UII > 25 – < 70 47 .329 .076 .017 .374 .014

UII > 10 – ≤ 25 19 .026 .013 .006 .027 .006

UII ≤ 10 5 .005 .002 0 .007 0

interesting patterns. For example, when summed across the 

spring and summer samplings, an average of 12 pesticides 

were detected in both the high and very high UII groups 

(table 4). The number of detections dropped substantially, 

four pesticides detected on average, when only looking at 

medium UII sites and only one pesticide was detected on 

average in low UII sites (UII less than 10) (table 4). The 

pattern of herbicide concentrations varied from this, as average 

total herbicide concentrations were higher for high UII sites 

than when compared to very high UII sites (UII greater than 

70), even though the number of herbicide detections were 

the same between these two groups of sites. The higher 

herbicide concentrations of the high UII group compared 

to the very high UII group remained even after the extreme 

herbicide value from Battle Creek was removed. However, 

for insecticides, the average concentration was more than 2.5 

times greater in the very high UII group of sites than the high 

UII group.

Table 5. Summary statistics of pesticide concentrations collected during spring and summer 2004, Willamette River basin and 

surrounding area, Oregon and Washington.

[Pesticide concentrations are in micrograms per liter. Sites are sorted by urban intensity index (UII). Shading from light to dark represents low, medium, high, 

and very high UII scores. Abbreviations: OR, Oregon; WA, Washington; SW, southwest. Symbols: ≥, greater than or equal to; >, greater than; <, less than; ≤, 

less than or equal to]
Results 21

The fact that the high UII group averaged as many 

pesticide detections as the very high group, likely was due to 

the influence of agricultural land use in the watersheds. The 

amount of agricultural land in the watersheds in the high UII 

group ranged from 16 to 48 percent (an average of 31 percent), 

and the amount of urban ranged 7 to 72 percent (an average 

of 30 percent) (table 1; fig. 8). Therefore, many high category 

UII watersheds had about the same amount of influence 

from agricultural land use as urban land use. On the other 

hand, the very high UII category, which was dominated by 

urban land use (60–98 percent urban), had a relatively minor 

influence from agricultural land use (0–8 percent agriculture). 

In terms of the number of pesticides detected in streams, little 

difference was observed between agricultural and urban land; 

however, the composition of the pesticide mixture and the 

timing of delivery to the stream varied considerably between 

agricultural and urban sites in the study. These differences in 

pesticide detection frequency and types of pesticides between 

agriculture and urban land use are similar to those reported in 

the Willamette Valley by Anderson and others (1997) and in 

streams across the country by Gilliom and others (2006).

Among individual pesticides detected during this study, 

only prometon showed a significant correlation with UII 

(rho = 0.70), and then only during the spring sampling. Total 

pesticide and insecticide concentrations (log transformed 

due to extreme values that skew the distribution; log [X + 

0.0001] summed across spring and summer) were strongly 

correlated with the UII (rho = 0.68 and 0.69, respectively) 

(figs. 9, 10, and table 6). The correlation of log total pesticide 

concentration increased slightly when correlated to percentage 

urban plus agricultural land (rho = 0.72), yet the correlation 

decreased dramatically when related to only percent 

agricultural land (rho = 0.41). Conversely, the correlation of 

log total insecticide concentration decreased when related to 

urban plus agricultural land compared to its correlation to UII 

(rho = 0.63 and 0.69, respectively) (table 6). This suggests that 

many insecticide detections originated from applications in 

urban areas, not from the agricultural uses.

Pesticide Toxicity Index in Relation to Urban Intensity 

Index

PTI scores at the 28 sites typically were greater in spring 

than summer (18 greater, 8 less, 2 the same). The difference 

between most pairs of PTI scores was small, as 20 of the 28 

scores changed by one order of magnitude or less between the 

two samplings. The sum of the spring and summer PTI values 

was used to estimate the potential pesticide toxicity among 

sites and to follow our summary of actual pesticide detections 

and concentrations presented previously in this report. The 

sum of the PTI was significantly correlated with the UII (rho 

= 0.63, fig. 11A), yet had a stronger correlation to ROADDEN 

at rho = 0.69 (fig. 11B). The relation of PTI to ROADDEN 

was curvilinear and revealed two basic groups of sites with 

relatively high PTI values. One group of sites with the highest 

road density (ROADDEN greater than 10) also had the highest 

percentage of urban land use or highest UII values. Another 

group of sites with moderate road density had a combination 

of moderate percentage of urban land and substantial amounts 

of agricultural land (ROADDEN of 3.5 to 8.5 and PTI values 

greater than 4). This pattern followed the results of a number 

of pesticide detections stated above, such that high detection 

frequencies occurred at sites with high urban land use and at 

sites with lower amounts of urban land use but with moderate 

amounts of agricultural land.

Figure 8. Urban intensity index (UII) and percentage of agricultural land for all 28 sites, Willamette River basin and 

surrounding area, Oregon and Washington. 

0 0

87654321 9 1817

VERY HIGH

HIGH

MEDIUM

LOW

16151413121110 19 282726252423222120

WATERSHEDS, IN DECREASING ORDER OF URBAN INTENSITY INDEX

10

20

30

40

50

60

70

80

90

100

URBAN INTENSITY INDEX AND

PERCENT AGRICULTURAL LAND

Urban Intensity Index

Percent agricultural land
22 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

or19-0168_ fig09 Figure 9. Total pesticide concentration in relation to Urban Intensity Index (UII) for all 28 stream sites.

rho = 0.68

0

1

2

3

4

5

0 20 40 60 80 100

URBAN INTENSITY INDEX

LOG OF SUM OF TOTAL PESTICIDES,

IN MICROGRAMS PER LITER

Figure 10. Total insecticide concentration in relation to urban intensity index 

(UII) for all 28 sites, Willamette River basin and surrounding area, Oregon and 

Washington.

Figure 9. Total pesticide concentration in relation to urban intensity index 

(UII) for all 28 sites, Willamette River basin and surrounding area, Oregon and 

Washington.

rho = 0.69

0

0.02

0.04

0.06

0.08

0.10

20 40 60 80 100

URBAN INTENSITY INDEX

0

TOTAL INSECTICIDE CONCENTRATION,

IN MICRO GRAMS PER LITER

Urban indicators

Sum of spring + summer Water-chemistry variables

Insecticide Pesticide PTI TEQ Pyrene 

index

Summer 

DO DOC SO4 TN TP Nutrient 

index

Urban intensity index (UII) 0.69 0.68 0.63 0.81 0.67 -0.60 0.72 0.73 0.79 0.71 0.85

Percent impervious surface .65 .65 .61 .80 .64 -.56 .65 .72 .83 .71 .86

POPDEN00 .70 .68 .62 .81 .66 -.61 .70 .71 .81 .73 .85

Percent urban + agriculture .63 .72 .60 .73 .58 -.53 .60 .62 .86 .65 .84

ROADDEN .73 .67 .69 .75 .56 -.54 .69 .69 .75 .65 .79

Table 6. Spearman’s rank correlation coefficients (rho values) between urban indicator and water-chemistry variables, Willamette 

River basin and surrounding area, Oregon and Washington.

[Average dissolved organic carbon (DOC), sulfate (SO4), total nitrogen (TN), total phosphorus (TP) concentration values were used for the correlations. 

Correlation coefficients were considered strong when absolute value ≥ 0.66 (bolded and shaded) and moderate when 0.66 > rho ≥ 0.50 (bolded). Abbreviations:

PTI, Pesticide Toxicity Index; TEQ, toxic equivalents index; DO, dissolved oxygen; ROADDEN, road density. Symbol: ≥, greater than or equal to]
Results 23

OR19-0168_ fig11

0 10 20 30 40 50 60 70 80 90 100

rho = 0.63

A. Urban Intensity Index

0

1

2

3

4

5

6

7

0

1

2

3

4

5

6

7

0 2 4 6 8 10 12 14 16 18 20

ROAD DENSITY, IN SQUARE MILES

URBAN INTENSITY INDEX

LOG OF PESTICIDE TOXICITY INDEX

rho = 0.69

B. Road density

Semipermeable Membrane Device Assays in Relation to 

Urban Intensity Index

Of the three assays run on the SPMDs, the toxic 

equivalents (TEQ) index (P450 RGS assay for aryl 

hydrocarbon receptor agonists) and Pyrene Index (fluoroscan 

for total PAHs) provided consistent and reliable results. No 

interpretable results were achieved from the Microtox® assay 

and are not discussed (Bryant and others, 2007). The TEQ and 

Pyrene Index assays were correlated to the five urban indicator 

metrics, with TEQ having the strongest correlation to both 

UII and POPDEN00 at rho = 0.81 (table 6; fig. 12). Bryant 

and others (2007) determined similar strong correlations 

of the TEQ and Pyrene indices compared to the individual 

UIIs of other USGS EUSE studies in Atlanta, Georgia; 

Raleigh-Durham, North Carolina; Denver, Colorado; DallasFort Worth, Texas; and Milwaukee-Green Bay, Wisconsin. 

Figure 11. Relations between Pesticide Toxicity Index (PTI) and (A) urban 

intensity index (UII) and (B) road density (ROADDEN), Willamette River 

basin and surrounding area, Oregon and Washington.

They also concluded that the strong correlation of UII with 

pentachloroanisole and pyrogenic PAHs in the other study 

areas was evidence that these compounds were an important 

part of urbanization regardless of geographic location. 

Along with the three assays, part of each SPMD 

dialysate was analyzed for hydrophobic chemical compounds. 

Of the 141 compounds targeted for identification by gas 

chromatography and mass spectrometry analysis, 39 were 

detected in the Willamette River basin and surrounding area. 

In comparison, detection in the other 5 EUSE studies ranged 

from 49 compounds detected in Raleigh-Durham to 36 in 

Dallas-Fort Worth (Bryant and others, 2007). Only three 

PAH compounds detected in the Willamette River basin and 

surrounding area were significantly correlated to the UII, and 

this was the lowest number of significant correlations among 

the six EUSE studies (high of 21, Raleigh-Durham).
24 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

OR19-0168_ Relations between the Urban Intensity Index (UII) and semipermeable membrane device results

for toxic equivalents (TEQs) (A) and the Pyrene Index (B).

fig12

0

200

400

600

800

1,000

1,200

0 10 20 30 40 50 60 70 80 90 100

TOXIC EQUIVALENT INDEX

rho = 0.81

A. Toxic equivalent index

0

500

1,000

1,500

2,000

2,500

3,000

3,500

0 10 20 30 40 50 60 70 80 90 100

PYRENE INDEX

rho = 0.67

B. Pyrene index

URBAN INTENSITY INDEX

Figure 12. Relation between the urban intensity index 

(UII) and semipermeable membrane device results for the (A) toxic 

equivalent index (TEQ) and (B) pyrene index.

Nutrients and Field Parameters

For spring and summer samplings, total nitrogen (TN), 

total phosphorus (TP), and orthophosphorus (soluble reactive 

phosphorus; SRP) had positive correlations with the UII 

(table 6). The highest two TN concentrations of all sampling 

sites were in Curtin Creek during spring and summer (4.8 

and 3.9 mg/L, respectively). Curtin Creek was considered 

an outlier due to the relatively high TN values measured, 

which were probably caused by the large amount of groundwater inflow (ground-water that is high in DO and TN due 

to the natural coarse grain geology, which likely minimizes 

the amount of denitrification) just upstream of the sampling 

site. TN concentrations averaged for the spring and summer 

samplings and nutrient index were positively correlated to 

the UII (TN: rho = 0.79; fig. 13A) (nutrient index: rho = 0.85; 

table 6). The highest TP concentration (0.18 mg/L) was in 

Beaverton Creek in spring, and in Claggett Creek in summer 

(TP = 0.28 mg/L).

Some of the highest TN values were in the medium 

to high UII groups of sites (UII 25 to 70), likely due to the 

increased amount of agricultural land at these moderately 

urban sites (fig. 8). As a result, the correlation of TN increased 

further when percentage of agricultural land was included 

with percentage of urban land as the correlative variable 

(rho = 0.86; fig. 13B). Nevertheless, lower TN concentrations 

(generally less than 0.5 mg/L) were detected in sites with 

relatively low urban development (UII less than 25) , whereas 

relatively higher TN concentrations ranging from 0.7 to 

2.3 mg/L were commonly detected in higher UII sites (greater 

than 25), (not including the outlier value for Curtin Creek). 

The pattern for TP was not as consistent as shown for TN and 

its correlation decreased when the amount of agriculture was 

included (table 6), nevertheless, high UII sites generally had 

the highest TP concentrations ranging from 0.08 to 0.28 mg/L. 

Phosphorus concentrations (TP and SRP) in many 

stream sites increased from spring to summer as streamflow 

decreased towards base-flow. This likely was due to inputs 
Results 25

OR19-0168_ fig13

0 2010 30 40 50 60 70 80 90 100

URBAN INTENSITY INDEX

AVERAGE TOTAL NITROGEN, IN MILLIGRAMS PER LITER

0

1

2

3

4

5

0

1

2

3

4

5

0 0.20.1 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

URBAN PLUS AGRICULTURAL LAND, IN PERCENT

rho = 0.86

rho = 0.79

A. Urban intensity index

B. Urban plus agricultural land

Figure 13. Relations between average total nitrogen concentrations 

and (A) urban intensity index (UII) and (B) percentage of urban plus 

agricultural land, Willamette River basin and surrounding area, Oregon 

and Washington.

of phosphorus in ground water to streams, though other 

possible explanations include increased water use and 

increased influences of wastewater inputs from septic systems 

or treatment plants. Twenty-two of the 28 sites showed this 

pattern of increased SRP from summer to spring. Nitrogen 

concentrations, however, decreased from spring to summer and 

were more variable than phosphorus concentrations, possibly 

reflecting inputs from runoff of spring fertilizer applications 

in urban and agricultural land that may have subsided during 

the dry summer months. Most streams showed decreased 

concentrations of dissolved inorganic nitrogen (DIN) through 

the growing season, which may reflect the tendency for 

nitrogen to be in relatively short supply compared with 

phosphorus in some Northwest streams, particularly during 

summer (Carpenter, 2003). About one-third of the streams 

had DIN concentrations that were 0.5 to 1.7 mg/L lower 

during summer compared with spring. The greatest change in 

the DIN concentration from spring to summer was in North 

Fork Deep Creek, where nuisance levels of filamentous green 

algae (Cladophoraglomerata) contributed to relatively high 

chlorophyll-a levels (157 mg/m2). 

Among the water chemistry variables, strongest 

correlations to the UII (rho greater than 0.70) was for 

DOC and dissolved sulfate (SO4

; table 6) whereas, specific 

conductance, bicarbonate alkalinity, chloride, and summer 

dissolved oxygen (DO) (negative) also were correlated, but 

slightly less significantly (rho greater than 0.50). Sulfate 

sources include fertilizers, road pavement amendments, and 

certain algicides (copper sulfate, for example), and is often 

produced during combustion. Sulfate also is produced when 

bacteria in organic soils oxidize hydrogen sulfide (H2S). 

Potential sources of bicarbonate in urban areas include the 

slow erosion of concrete structures, sidewalks, and roadways, 

and calcium carbonate based lime products applied to lawns 

for pH control. 
26 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Class Order Number of 

taxa

Most common algal taxa

Scientific name

Maximum 

abundance 

(number of 

cells/cm2

)

Number of 

streams

(RTH)

Diatoms (Bacillariophyta)

Bacillariophyceae Pennales 214 Achnanthidium minutissimum 7.3E×105 27

Rhoicosphenia abbreviata 7.3E×105 25

Cocconeis placentula var. euglypta 1.6E×105 25

Planothidium lanceolatum 2.2E×105 22

Navicula minima 3.1E×105 21

Gomphonema kobayasii 2.5E×105 21

Sellaphora seminulum 1.4E×105 21

Achnanthes subhudsonis var. kraeuselii 1.7E×106 17

Bacillariophyceae Centrales 14 Melosira varians 2.5E×105 16

Blue-green algae (Cyanophyta)

Myxophyceae Oscillatoriales 10 Homoeothrix janthina 1.2E×107 21

Myxophyceae Chroococcales 4 Aphanocapsa sp. 3.8E×106 1

Myxophyceae Nostocales 1 Calothrix fusca 4.9E×104 1

Euglenoid algae (Euglenophyta)

Euglenophyceae Euglenales 1 Trachelomonas volvocina 5.9E×103 2

Green algae (Chlorophyta)

Chlorophyceae Oedogoniales 1 Oedogonium sp. 5.7E×104 6

Chlorophyceae Cladophorales 1 Cladophora glomerata 5.0E×104 2

Chlorophyceae Chlorococcales 4 Scenedesmus ecornis 3.0E×104 2

Chlorophyceae Chaetophorales 1 Stigeoclonium lubricum 2.1E×105 1

Chlorophyceae Volvocales 1 Pandorina morum 3.3E×104 1

Chlorophyceae Zygnematales 1 Spirogyra sp. 1.0E×104 1

Red algae (Rhodophyta)

(Undetermined) (Undetermined) 1 Unknown Rhodophyte Florideophycidae 

(chantransia stage) 

2.4E×106 25

Total number of taxa 254

DO is a critical parameter for aquatic life in streams, 

and is affected by a number of processes, including water 

temperature, atmospheric pressure, and the activity of bacteria, 

algae, and other aerobic organisms that consume DO, and 

processes that produce it (aeration in riffles, for example, and 

photosynthesis by algae). All DO data used in this report were 

instantaneous measurements collected during midday, and do 

not reflect the daily cycle of DO that often occurs in nutrientenriched streams with high algal production. It is likely that 

in many of these urban nutrient-enriched streams the DO may 

show large diurnal swings; very low DO in early morning after 

nighttime anerobic activity and super-saturated DO in late 

afternoon after photosynthesis by abundant algae.

Biological Characteristics

Algae Assemblages

Algal assemblages were dominated by pennate diatoms 

(Pennales Order), which comprised 214 of the 254 algal 

taxa identified in RTH (richest target habitat) riffle samples 

from the 28 sites (table 7; table A9). Based on biomass, 

however, Chlorphytes (green algae) were dominant, 

contributing on average about 70 percent of the total algal 

biovolume, whereas diatoms comprised 17 percent of the 

total algal biovolume. The most common diatoms in RTH 

samples were Achnanthidium minutissimum, Rhoicosphenia 

Table 7. Most common algal taxa from the five major Divisions identified in Richest Targeted Habitat samples, Willamette River basin 

and surrounding area, Oregon and Washington.

[Number of streams: One Richest Targeted Habitat (RTH) algal sample was collected from each of 28 streams. Abbreviation: cm2, square centimeter]
Results 27

abbreviata, Cocconeis placentula var. euglypta, Planothidium 

lanceolatum, Navicula minima, Gomphonema kobayasii, 

Sellaphora seminulum and Achnanthes subhudsonis var. 

kraeuselii (table 7).

Based on cell density (number of cells/cm2) blue-green 

and red algae were the dominant taxa at all but one site (Deep 

Creek), with the blue-green Homeothrix janthina dominating 

11 sites and unidentified red algae (vegetative “chantransia” 

stage) six sites (table 8). The red and blue-green algae have 

relatively small cells, and, therefore, tended to dominate cell 

densities. Many dominant diatoms, particularly at sites high 

on the UII, were high-nutrient (eutrophic) taxa, or preferred 

high TN concentrations, and were tolerant of moderate levels 

of DO (greater than 75 percent saturation) (table 8). Although 

many sites lower on the UII also were dominated by eutrophic 

diatom taxa, several were dominated by Achnanthes and

Achnanthidium species whose water-quality preferences have 

not yet been established. 

Sixty-seven percent of the total algal biovolume (for 

all RTH samples combined) was comprised of filamentous 

green algae, including Cladophora glomerata, Stigeoclonium, 

Odeogonium, and Spirogyra (table 7). The occurrence of these 

high-biomass forming filamentous green algae was sporadic 

along the UII, as they were detected at few sites despite 

relatively high nutrient levels. In addition to requiring high 

nutrients, these taxa also prefer relatively high light levels, 

which was limited in some streams where riparian vegetation 

or topographic relief provided shading. High sediment 

concentrations in some streams also may have limited light 

availability. Potapova and others (2005) determined that light 

conditions affected algal assemblages in streams around Salt 

Lake City, Utah, due to riparian vegetation, stream size, and 

suspended sediment. Carpenter and Waite (2000) determined 

filamentous blue-green algae, such as Oscillatoria, to be 

common in silt-laden agricultural streams in the Willamette 

Valley, possibly due to their ability to move and unbury 

themselves after siltation events, or from an inherent ability to 

grow under low light conditions.

Response in Algal Biomass to Urban Intensity Index

Benthic algal biomass was highly variable along the 

urban gradient, with chlorophyll-a values ranging from 5 to 

212 mg/m2

, and showed no obvious response to urbanization 

(fig. 14A). AFDM, a measure of the organic matter present, 

ranged from 2.4 to 70 g/m2, and was positively correlated 

with the UII (rho = 0.56; fig. 14B) and the nutrient index (rho 

= 0.72; fig. 15A). All but one site less than 25 on the UII had 

an AFDM value that indicated at least a moderate degree of 

organic enrichment, and many sites higher on the UII (greater 

than 25) exceeded the criterion to be considered organically 

enriched (fig. 15A; Biggs, 1996). Twelve of 28 streams had 

chlorophyll-a concentrations exceeding 50 mg/m2, a 

low-end threshold suggested to protect recreational and 

aesthetic qualities of streams (Biggs, 1996). The highest 

chlorophyll-a concentrations occurred in North Fork Deep and 

Amazon Creeks (157 and 212 mg/m2, respectively) due to high 

abundances of Cladophora glomerata, Oscillatoria princes, 

and Sellaphora seminulum (fig. 14A). The chlorophyll-a

concentrations in these streams also exceeded common 

nuisance indicator levels for benthic algae 100–150 mg/m2

(Horner and others, 1983; Welch and others, 1988, 1989; 

Biggs, 1996; Dodds and others, 1997, 1998). Proliferations 

of algae may develop quickly during periods of stable 

streamflow, especially in streams receiving nutrients. Newall 

and Walsh (2005) found that repeated rainfall events can 

stimulate algal growth in streams by providing pulses of 

nutrients, an effect that was enhanced by the amount of 

impervious surface and the degree of drainage connection 

within the storm-water network.

Although there was considerable variation between 

AFDM and DOC (fig. 15B), the highest AFDM values 

occurred when the DOC exceeded about 4 mg/L, and DOC 

was negatively correlated with DO concentrations (fig. 15C). 

Taken together, the relations among algal biomass, DOC, and 

DO indicate that algal biomass may be affecting DO levels 

through bacterial decomposition processes involving the 

production of DOC. DO also is affected, however, by water 

temperature and the amount of riffle habitat that aerates the 

water (fig. 6). Because diurnal fluctuations in DO and pH 

can occur from algal photosynthesis, however, the one-time 

instantaneous midday measurements collected for this study 

likely do not fully reflect the processes of photosynthesis and 

respiration that may occur in these streams.

Elevated levels of dissolved nutrients can stimulate 

the growth of benthic and planktonic algae in streams. In 

some cases, high-biomass forming benthic algae such as 

filamentous Chlorophytes (green algae) may cover streams 

and foul substrates when high amounts of light are available 

for photosynthesis (Carpenter and Waite, 2000). In addition 

to the prolific growths of green algae described above, 

another high-nutrient indicator alga—Melosira varians—was 

detected at more than 50 percent of the sites (16 sites; table 7), 

making up about 10 percent of the total biovolume for all 

RTH samples. This eutrophic diatom is also a N-heterotroph 

because it may use organic forms of nitrogen for energy and 

growth. Melosira is considered a high quality food item for 

benthic macroinvertebrates because of its high nutrient and 

fatty acid content. This filamentous diatom has a morphology 

of relatively loosely connected cells that make it susceptible 

to removal by disturbance such as repeated scouring flows, 

high water velocity, or grazing by herbivorous benthic 

macroinvertebrates. Because of its tendency to fragment, 

Melosira does not tend to reach as high densities or biomass 

as other more resistant types (for example, Cladophora or 

Stigeoclonium) in disturbed habitats. 
28 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington Site name UII Dominant algal taxon Dominant diatom taxon Division Scientific name Scientific name Diatom water-quality indicator Beaverton Creek near SW 216th Avenue, near Orenco, OR 100 Red algae Unknown Rhodophyte Florideophycidae Gomphonema kobayasii Preference for high TN Claggett Creek at Keizer, OR 100 Red algae Unknown Rhodophyte Florideophycidae Gomphonema kobayasii Preference for high TN Fanno Creek at Durham, OR 96 Blue-green algae Leptolyngbya sp. Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Kellogg Creek at Milwaukie, OR 88 Blue-green algae Homoeothrix janthina Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Pringle Creek at Salem, OR 88 Blue-green algae Homoeothrix janthina Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Amazon Creek near Danebo Road, at Eugene, OR 77 Blue-green algae Leptolyngbya sp. Amphora pediculus Eutrophic/moderate DO (>75 percent) Tryon Creek below Nettle Creek, near Lake Oswego, OR 72 Blue-green algae Homoeothrix janthina Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Curtin Creek near Vancouver, WA 69 Blue-green algae Homoeothrix janthina Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Johnson Creek at Circle Avenue, OR 59 Red algae Unknown Rhodophyte Florideophycidae Gomphonema kobayasii Preference for high TN Battle Creek near Turner, OR 58 Blue-green algae Leptolyngbya sp. Preference for high DIN/ moderate DO (>75 percent) Rock Creek at Quatama Road, near Hillsboro, OR 51 Blue-green algae Phormidium autumnale Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Whipple Creek near Salmon Creek, WA 49 Red algae Unknown Rhodophyte Florideophycidae Cocconeis placentula var. lineata Eutrophic/low DO (>50 percent) Chicken Creek near Sherwood, OR 45 Red algae Unknown Rhodophyte Florideophycidae Nupela sp. Unknown North Fork Deep Creek at Barton, OR 39 Blue-green algae Porphyrosiphon martensianus Achnanthes subhudsonis var. kraeuselii Unknown Oak Creek at Corvallis, OR 39 Red algae Unknown Rhodophyte Florideophycidae Rhoicosphenia abbreviata Eutrophic/moderate DO (>75 percent) Table 8. Dominant algal taxon (by cell density) at each site, dominant diatom taxon, and diatom water-quality indicator classification, Willamette River basin and surrounding area, Oregon and Washington. [Sites are sorted by the urban intensity index (UII). Shading indicates sites with UII greater than 25. Water-quality indicator from Porter (2008). Abbreviations: TN, total nitrogen; DO, dissolved oxygen; SW, southwest; OR, Oregon, WA, Washington; DIN, dissolved inorganic nitrogen. Symbols: >, greater than]
Results 29

Site name UII

Dominant algal taxon Dominant diatom taxon

Division Scientific name Scientific name Diatom water-quality indicator

Tickle Creek near Boring, OR 32 Blue-green algae Homoeothrix janthina Achnanthes subhudsonis var. 

kraeuselii

Unknown

Chehalem Creek at Newberg, OR 29 Blue-green algae Homoeothrix janthina Rhoicosphenia abbreviata Eutrophic/moderate DO 

(>75 percent)

Silk Creek near Cottage Grove, OR 24 Blue-green algae Unknown Cyanophyte Rhoicosphenia abbreviata Eutrophic/moderate DO 

(>75 percent)

Rock Creek near Battleground, WA 23 Blue-green algae Aphanocapsa sp. Achnanthidium minutissimum Preference for high DIN/high 

DO (near 100 percent)

Salmon Creek near Battleground, WA 20 Blue-green algae Homoeothrix janthina Achnanthidium sp. 10 Unknown

Deep Creek near Sandy, OR 17 Diatom Achnanthes subhudsonis var. 

kraeuselii

Achnanthes subhudsonis var. 

kraeuselii

Unknown

Nate Creek near Colton, OR 15 Blue-green algae Homoeothrix janthina Achnanthidium sp. 10 Unknown

Milk Creek at Camp Adams, OR 12 Blue-green algae Phormidium autumnale Gomphonema sp. 2 Unknown

North Yamhill Creek near Yamhill, OR 8 Blue-green algae Unknown Cyanophyte Achnanthidium minutissimum Preference for high DIN/high 

DO (near 100 percent)

South Scappose Creek at Scappose, OR 8 Blue-green algae Homoeothrix janthina Gomphonema kobayasii Preference for high TN

Lost Creek near Dexter, OR 6 Blue-green algae Homoeothrix janthina Gomphonema rhombicum Unknown

Iler Creek near Forest Grove, OR 4 Blue-green algae Homoeothrix janthina Cocconeis placentula var. euglypta Eutrophic/low DO 

(>50 percent)

East Fork Dairy Creek near Meacham Corner, OR 0 Blue-green algae Unknown Cyanophyte Achnanthes subhudsonis var. 

kraeuselii 

Unknown

Table 8. Dominant algal taxon (by cell density) at each site, dominant diatom taxon, and diatom water-quality indicator classification, Willamette River basin and surrounding area, Oregon and Washington..—Continued[Sites are sorted by the urban intensity index (UII). Shading indicates sites with UII greater than 25. Water-quality indicator from Porter (2008). Abbreviations: TN, total nitrogen; DO, dissolved oxygen; SW, southwest; Ave., avenue; OR, Oregon, WA, Washington; DIN, dissolved inorganic nitrogen. Symbols: >, greater than]
30 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Multivariate Analysis of Diatom Assemblages

A number of environmental factors such as climate, 

geology, water-quality, habitat conditions, and anthropogenic 

disturbances (Biggs, 1990) can influence algal assemblages. 

In this study, diatom assemblage structure (axes scores 

from nMDS ordinations) were not significantly correlated 

(rho less than 0.2) to any of the urban indicators including 

road and population density, percentage of impervious 

area and urban land, or the UII. Additional multivariate 

analyses were conducted to identify which environmental 

variables (or combinations) explained the most variation in 

the diatom assemblage structure using the BEST routine in 

PRIMER. Variables included habitat parameters (water depth, 

velocity, and embeddedness), disturbance indicators (benthic 

macroinvertebrate grazers and a hydrologic variability index), 

light availability (open canopy), and water-quality measures 

(nutrients, DOC, pH, DO, and specific conductance). The best 

combination of variables—DOC, pH, Rb-flash and benthic 

macroinvertebrate scraper density—explained 68 percent of 

the variation in the diatom assemblage.

DOC, which was negatively correlated with DO 

(fig. 15), explained 44 percent of the variation in the diatoms 

assemblage structure among all sites. The highest individual 

rho values were those associated with habitat and channel 

hydraulics (percentage run habitat, Froude number, and 

maximum depth, rho = 0.47; average substrate embeddedness, 

rho = 0.32) and water chemistry (high-flow period specific 

conductance, rho =0.43; summer total phosphorus, rho = 

0.33; summer particulate nitrogen, rho = 0.33; summer 

minimum water temperature, rho = 0.33). Habitat and 

hydraulic conditions can alter the velocity regime for benthic 

algae, which can affect its overall growth form and profile 

(Hoagland and others, 1982), which is consistent with the 

influence of Froude number and Rb-flash on the diatom 

assemblage structure. In these streams, the higher amount 

of run habitat (and gradient) also might be contributing to 

higher sedimentation, leading to higher average substrate 

embeddedness. The water-quality variable with the highest rho 

value was specific conductance. Specific conductance often 

is used as a broad measure of anthropogenic influence, but 

is also affected by dilution (and watershed size), as well as 

OR19-0168_ fig14

rho = 0.31

0

50

100

150

200

250

0 10 20 30 40 50 60 70 80 90 100

A. Chlorophyll-a

rho = 0.56

0

10

20

30

40

50

60

70

80

0 10 20 30 40 50 60 70 80 90 100

URBAN INTENSITY INDEX

ASH-FREE DRY MASS, IN GRAMS

PER SQUARE METER

CHLORPHYLL-a, IN MILLIGRAMS

PER SQUARE METER

Battle Creek

Tryon

Creek

Pringle

Creek

B. Ash-free dry mass Fanno Creek

Amazon Creek

North Fork Deep Creek

Figure 14. Relation between the urban intensity index (UII) and (A) 

chlorophyll-a and (B) ash-free dry mass, Willamette River basin and 

surrounding area, Oregon and Washington. (Shading represents 

concentrations of chlorophyll-a greater than 100 mg/m2

).
Results 31

natural factors such as soil and geology. Specific conductance 

has been shown to correlate well with algal assemblages in 

other studies in Oregon (Walker and Pan, 2006), other EUSE 

study areas (Potapova and others, 2005), and in Australia 

(Newall and Walsh, 2005). Correlations between specific 

conductance and anthropogenic influences can be stronger 

than nitrogen and phosphorus concentrations in streams with 

significant algal growths because of the nutrient uptake effect, 

which can lower nutrient levels substantially during periods of 

active growth. 

Figure 15. Relations between ash-free dry mass and (A) nutrient index and (B) 

concentrations of dissolved organic carbon, and (C) dissolved organic carbon and 

concentrations of dissolved oxygen, Willamette River basin and surrounding area, 

Oregon and Washington.

or19-0168_ fig15

50

0

10

20

30

40

0 20 40 60 80 100

NUTRIENT INDEX, TOTAL NITROGEN AND TOTAL PHOSPHORUS

ALGAL BIOMASS, ASH-FREE DRY MASS, IN GRAMS PER SQUARE METER

Moderately enriched

Slightly enriched

Enriched

rho = 0.72

rho = 0.56

0

2

4

6

8

10

12

0 2 4 6 8 10 12

DISSOLVED OXYGEN CONCENTRATION, IN MILLIGRAMS PER LITER

DISSOLVED ORGANIC CARBON CONCENTRATION,

IN MILLIGRAMS PER LITER 

rho = – 0.68

0

20

40

60

80

100

0 2 4 6 8 10 12

DISSOLVED ORGANIC CARBON CONCENTRATION, IN MILLIGRAMS PER LITER

Fanno Creek

Amazon Creek

A. Nutrient index

B. Dissolved organic carbon

C. Dissolved oxygen
32 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Response in Algal Metrics to Urban Intensity Index and 

Select Environmental Variables

Two algal metrics were correlated to the UII, including 

percentage of diatoms requiring high DO concentrations 

(nearly saturated) and, to a lesser degree, percentage of 

eutrophic (high-nutrient indicator) algae (fig. 16). Algal 

metrics also indicate that nutrient and sediment enrichment 

have measurable effects on the diatom assemblage structure 

in these streams, with eight metrics having significant 

correlations with either the UII or other environmental variable 

(table 9). The highest correlation coefficients (rho values) 

occurred between algal metrics and water-quality variables, 

including nutrients, DOC, and DO, and measures of algal 

biomass, especially AFMD (table 9).

 The percentage of high-nutrient indicators (eutrophic 

diatoms) was strongly correlated to specific conductance 

(rho = 0.67) and moderately correlated to soluble reactive 

phosphorus (rho = 0.65), total phosphorus (rho = 0.55), and 

the nutrient index (rho = 0.52) (table 9). Another high-nutrient 

indicator metric (nitrogen heterotrophic taxa)—those that can 

use organic forms of nitrogen (organic nitrogen)—also were 

significantly correlated with concentrations of total nitrogen 

and total phosphorus (rho = 0.62 and 0.69, respectively) and 

algal biomass (AFDM: rho = 0.73; chlorophyll-a: rho = 0.69) 

(table 9). 

Algal metrics also showed the effects of depressed 

levels of DO in these streams that can result from bacterial 

respiration associated with decomposition of organic matter. 

For example, low-oxygen indicating taxa tolerant of depressed 

DO (10–30 percent saturation, or less [van Dam and others, 

1994]) were positively correlated with total phosphorus 

(rho = 0.62), DOC (rho = 0.69), and benthic algal biomass 

(AFDM, rho = 0.63) (table 9). In contrast, high oxygen 

indicator diatoms had negative correlations for most waterquality variables, particularly specific conductance and soluble 

reactive phosphorus (rho = -0.74 and -0.62, respectively). 

Additionally, the percentage of taxa associated with high 

levels of organic enrichment (a-mesosaprobic diatoms) 

was significantly correlated with concentrations of total 

phosphorus (organic nutrient: rho = 0.64) (table 9). These taxa 

tolerate depressed DO levels (10–70 percent saturation) and 

are associated with biological oxygen demand (BOD) levels of 

4–22 mg/L (van Dam and others, 1994).

The percentage of diatoms tolerant of nutrient 

and organic pollution (Bahls, 1993) were similarly 

positively correlated to total phosphorus and total 

nitrogen concentrations (tolerant taxa: rho = 0.67 and 

0.71, respectively) and algal biomass (AFDM: rho = 0.66; 

chlorophyll-a: rho = 0.62). The percentage of pollution 

sensitive diatoms, however, showed the opposite pattern 

and was negatively correlated with TP and TN (sensitive 

0

20

40

60

80

100

0 20 40 60 80 100

URBAN INTENSITY INDEX

PERCENTAGE OF HIGH NUTRIENT

(EUTROPHIC) ALGAE 

Chicken Creek

Battle Creek

rho = –0.46

rho = 0.46

0

20

40

60

80

100

RELATIVE DENSITY OF HIGH-DISSOLVED

OXYGEN REQUIRING DIATOMS 

A. Algal taxa

B. Eutrophic algae 

Battle Creek

Figure 16. Relations between urban intensity index (UII) and (A) 

percentage of algal taxa requiring high levels of dissolved oxygen, and (B) 

relative density of eutrophic algae, Willamette River basin and surrounding 

area, Oregon and Washington.
Results 33

Environmental variables

Diatom metric

High indicating taxa Oxygen indicating taxa Pollution

Silt 

Nutrient index

(eutrophic)

Organic 

enrichment

Organic 

nitrogen Low High Toleranttaxa 

Sensitive

taxa

Urban intensity index (UII) 0.46 0.52 0.38 0.33 -0.46 0.36 -0.45 0.40

Total nitrogen (TN) .37 .47 .62 .44 -.27 .71 -.62 .50

Nitrite+nitrate (NO2

+NO3) .28 .24 .41 .18 -.15 .63 -.47 .44

Total phosphorus (TP) .55 .64 .69 .62 -.57 .67 -.68 .70

Soluble reactive phosphorus (SRP) .65 .44 .57 .42 -.62 .59 -.51 .62

Nutrient index .52 .54 .65 .52 -.44 .70 -.63 nd

Specific conductance .67 .52 .51 .48 -.74 .50 -.50 .63

Summertime dissolved oxygen (DO) -.20 -.45 -.27 -.47 .28 -.36 .46 -.39

Summertime minimum water 

temperature

.41 .53 .51 .51 -.39 .51 -.61 .52

Sulfate (SO4

) .53 .45 .49 .35 -.52 .53 -.44 .60

Dissolved organic carbon (DOC) .25 .70 .56 .69 .50 -.61 .58

Chlorophyll-a .11 .44 .69 .40 -.08 .62 -.56 .54

Ash-free dry mass (AFDM) .29 .63 .73 .63 -.31 .66 -.69 .69

Table 9. Spearman’s rank correlation coefficients (rho values) between diatom algal metrics and the urban intensity index and select 

environmental variables, Willamette River basin and surrounding area, Oregon and Washington.

[See appendix A for definitions of environmental variables. Average concentrations were used for TN, NO2+NO3, total phosphorus, soluble reactive phosphorus, 

specific conductance, SO4, and DOC. Correlation coefficients were considered strong when absolute value ≥ 0.66 (bolded and shaded) and moderate when 0.66 

> rho ≥ 0.50 (bolded). Nutrient, nitrogen, and oxygen taxa: van Dam and others (1994). High nutrient indicating (eutrophic) taxa require high nutrient levels. 

Nitrogen heterotrophs–taxa may use organic nutrient forms. High organic taxa-α-meso/polysaprobous–taxa indicative of depressed dissolved oxygen levels 

(10–70 percent) and elevated biological oxygen demand (4–22 mg/L). Brackish water–taxa tolerate elevated levels of dissolved ions. Low oxygen–taxa tolerant 

of low dissolved oxygen levels. High oxygen–taxa require high dissolved oxygen levels. Pollution, Bahls (1993): tolerant–taxa generally tolerant of nutrient 

and organic enrichment; sensitive–taxa generally sensitive to nutrient and organic enrichment. Silt index: calculated by Sprouffske and others, 2006. Sum of 

motile Navicula and Nitzschia diatom taxa. Abbreviations: mg/L, milligram per liter; nd, no data]

taxa: rho values = -0.68; and -0.62, respectively) and algal 

biomass (AFDM: rho = -0.69; chlorophyll-a: rho = -0.56). 

Lastly, the Silt Index—the percentage of motile diatom genera 

Navicula and Nitzschia—was positively correlated with total 

phosphorus and AFDM (table 9). These organisms can thrive 

in streams affected by siltation because they can move out of 

the sediments to the surface where light levels are higher. 

Taken together, the algal data show that diatom 

assemblages are affected by variations in streamflow, grazing 

by herbivorous benthic invertebrates, and processes relating to 

DOC (organic matter formation from excessive nutrients and 

high water temperature and decomposition, and subsequent 

effects of algal and bacterial metabolism on concentrations of 

DO). The positive correlation between benthic organic matter 

(AFDM) and the UII indicate that urbanization increases 

the amount of algae and other organic matter in streams 

through nutrient and (or) organic enrichment. DO is an 

important factor for important fish such as trout and salmon, 

which require relatively high levels of DO for survival and 

reproduction.

Benthic Macroinvertebrate Assemblages

One-hundred thirty-nine unique benthic macroinvertebrate 

taxa were identified in the 28 RTH samples (table 10 and table 

A10). The most taxa (52) was for the insect order Diptera, 

with 37 from one dipteran family (Chironomidae), commonly 

known as midges. Diptera made up one-quarter of the total 

number of taxa collected, and had the highest taxa richness per 

family or order, by far. EPT orders—Ephemeroptera (mayflies), 

Plecoptera (stoneflies), and Trichoptera (caddisflies) had 13, 10, 

and 19 taxa per respective order. There were 12 taxa within the 

Coleoptera order (beetles), 2 taxa in Odonata (dragonflies and 

damselflies), and 1 each in Lepidoptera (butterflies and moths) 

and Megaloptera (dobsonflies). In addition to these insects, 29 

noninsect taxa were spread among 17 orders, including snails, 

clams, aquatic worms, amphipods, and mites (table 10). 

Only Simulium caadense (a dipteran blackfly) and 

Fluminicola (a gastropod snail) reached maximum singlesample abundances greater than 11,000 specimens per m2

. 
34 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Other major insect and noninsect orders had maximum 

abundances of between 1,300 and 4,100 specimens per 

sample. The noninsect Acari (Hydracarina, or water mites) 

and Simulium canadense (Diptera) were the most common 

taxa collected, occurring at 27 out of 28 sites (96 percentage 

occurrence; table 11), in addition, four of the top six most 

common taxa were other noninsects: Acari, Juga sp. (a 

snail), Dero sp. (Oligochaete worm), and Lumbriculidae 

(Oligochaete worm). Of the 22 taxa with at least 50 percent 

occurrence, 9 were noninsects, 6 were Diptera (5 chironomid 

midges and one blackfly, Simulium), 3 were Ephemeroptera, 

and 2 each were from Trichoptera and Coleoptera orders (table 

11). Eighteen of these 22 taxa were considered moderately to 

highly tolerant of poor water-quality conditions, although 4 

taxa (Paraleptophlebia sp., Zapada cinctipes, Rhithrogena sp., 

and Ceratopsyche cockerelli) were considered moderately to 

relatively sensitive.

Benthic Macroinvertebrate Metrics in Relation to Urban 

Intensity Index

The benthic macroinvertebrate metric “percent 

dominance” (percentage abundance of the maximum single 

taxon) has been considered a good bioindicator by some 

researchers (Barbour and others, 1999); however, in this and 

other recent studies, it does not correlate well with disturbance 

in this geographic region. In this study, percent dominance 

ranged from 14 percent to 67 percent, yet it only had a 

correlation to the UII of rho = 0.31. However, the tolerance 

values of the single dominant taxa did show a good relation 

to the UII. A list of sites, sorted by UII (table 12), showed 

that the dominant taxa of the 17 sites with a UII greater 

than 25 had tolerance values between 7 and 10 (average 8), 

as determined by the USEPA tolerance scale (least to most 

tolerant—0 to 10). Additionally, those sites with UII greater 

than 25 had, on average, EPT richness of 4 taxa totaling 15 

percent. On the other hand, sites with a UII less than 25 had 

tolerance values for their dominant taxa of between 3 and 8 

(average 5), with much greater numbers of EPT taxa (average 

of 15 EPT taxa or a percent EPT richness of 44 percent). As 

a result, although percent dominance as a metric by itself 

did not correlate well to disturbance, interpreting ecological 

characteristics of the single dominant taxa among sites, such 

as USEPA tolerance values and optima, was useful (table 12). 

Looking at all sites instead of just the end members, there also 

was a strong negative correlation between EPT richness and 

UII (rho = -0.75; fig. 17) that reflects this large decrease in 

EPT taxa from the low to high urban sites.

Cuffney and others (2005) compared benthic 

macroinvertebrate metrics from three urban studies for two 

site groupings with different urban intensities: (1) most highly 

urban sites sampled (UII ≥ 70) and (2) sites near reference 

condition (UII ≤ 10). They detected large differences between 

these two groupings in the richness and density of major 

benthic macroinvertebrate metrics including all taxa, EPT 

taxa only, Diptera, Chironomidae, and noninsects. Results 

from this study were similar, with an average increase of 

12 EPT taxa and 32 percent EPT richness from the high 

urban group to the near reference condition group (table 13). 

However, unlike Cuffney and others (2005), who showed a 

large increase in total richness (+25 taxa), we detected only 

a small increase in total taxa richness (an average increase 

of 5 taxa). In this study, the large increase in “EPT percent 

richness” was in addition to a large increase in average 

abundance of intolerant macroinvertebrates (+3,848) and 

Ephemeroptera (+3,111). There also was a large decrease in 

percentage of noninsect richness (-31 percent) and abundance 

of tolerant taxa (-48 percent). Plecoptera are one of the most 

sensitive aquatic insect orders and, on average, almost no 

Plecoptera were detected at the highly urbanized sites, yet on 

Insect order/

noninsect group

Number 

of unique 

taxa

Most 

abundant 

taxon

Maximum 

abundance 

(m2

)

Insects

Ephemeroptera 13 Baetis tricaudatus 3,082

Plecoptera 10 Zapada cinctipes 4,081

Trichoptera 19 Cheumatopsyche sp. 3,467

Diptera 52 Simulium canadense 12,306

Chironomidae1 37 Cricotopus 

bicinctus group

3,303

Coleoptera 12 Optioservus sp. 1,349

Lepidoptera 1 Lepidoptera 64

Megaloptera 1 Sialis sp. 40

Odonata 2 Gomphidae 113

Total insects 110

Noninsects

Amphipoda 3 Hyalella azteca 1,401

Oligochaeta 5 Tubificidae 2,129

Mollusca 10 Fluminicola sp. 11,419

Other non-insects 11 Acari 988

Total noninsects 29

Total number of taxa 139

1

The Chironomidae value is included in the Order Diptera and is not added 

for total insects.

Table 10. Number of benthic macroinvertebrate taxa and 

maximum abundance per insect order or noninsect group, 

Willamette River basin and surrounding area, Oregon and 

Washington.

[Abbreviation: m2, square meter]
Results 35

Insect order and 

noninsect group Taxa Number of streams

Percent of 

sites

PNW 

tolerance 

value

Noninsect (water mite) Acari 27 96 6

Diptera Simulium canadense 27 96 6

Noninsect (snail) Juga sp. 25 89 7

Ephemeroptera Baetis tricaudatus 23 82 7

Noninsect (worm) Dero sp. 22 79 10

Noninsect (worm) Lumbriculidae 20 71 8

Trichoptera Cheumatopsyche sp. 19 68 8

Ephemeroptera Paraleptophlebia sp. 19 68 5

Diptera (Chironomidae) Polypedilum sp. 19 68 6

Diptera (Chironomidae) Thienemannimyia group sp. 17 61 6

Diptera (Chironomidae) Rheotanytarsus sp. 16 57 6

Diptera (Chironomidae) Eukiefferiella sp. 16 57 8

Diptera (Chironomidae) Cricotopus bicinctus group 16 57 7

Coleoptera Optioservus sp. 16 57 9

Coleoptera Zapada cinctipes 16 57 4

Noninsect (snail) Ferrissia sp. 16 57 7

Noninsect (amphipod) Crangonyx sp. 15 54 8

Noninsect (worm) Tubificidae 15 54 10

Noninsect (crayfish) Pacifastacus leniusculus 15 54 7

Noninsect (snail) Fluminicola sp. 15 54 7

Ephemeroptera Rhithrogena sp. 15 54 3

Trichoptera Ceratopsyche cockerelli 14 50 5

Table 11. Commonly observed benthic macroinvertebrate taxa and tolerance values, Willamette 

River basin and surrounding area, Oregon and Washington.

[Taxa sorted in order of decreasing frequency of occurrence. Insect order and noninsect group: Taxa occurs in more 

than 50 percent of streams. Abbreviation: PNW, Pacific Northwest]

2

0

4

6

8

10

12

14

16

18

20

URBAN INTENSITY INDEX

EPHEMEROPTERA, PLECOPTERA, AND

TRICHOPTERA RICHNESS

South Scappoose Creek

Curtin Creek

rho = –0.75

0 20 40 60 80 100

Figure 17. Relation between urban intensity index (UII) and number 

of benthic macroinvertebrate taxa (richness) in the Ephemeroptera, 

Plecoptera, and Trichoptera orders (EPT), Willamette River basin and 

surrounding area, Oregon and Washington.
36 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Urban intensity 

index

Total taxa 

richness

EPEM 

abundance

PLECO 

percent 

abundance

EPT percent 

richness

EPT

richness

Noninsect 

percent 

richness

Intolerant 

abundance

Tolerant 

percent 

abundance

UII < = 10 30 3,622 14 43 15 16 3,891 25

UII > = 70 25 511 0 11 3 47 43 73

Difference 5 3,111 14 32 12 -31 3,848 -48

Table 13. Comparison of average benthic invertebrate abundance and richness metrics for high- and low-urban streams, Willamette 

River basin and surrounding area, Oregon and Washington.

[Abbreviations: UII, urban intensity index; EPEM, Ephemeroptera; PLECO, Plecoptera; EPT, Ephemeroptera, Plecoptera, and Trichoptera. Symbols: >, 

greater than; <, less than]

Site name UII

Percent 

dominant 

taxon

Dominant taxon

USEPA 

tolerance 

value

EPT 

richness

EPT 

percent 

richness

Beaverton Creek near SW 216th Avenue, near Orenco, OR 100 27 Baetis tricaudatus 7 2 11

Claggett Creek at Keizer, OR 100 42 Tubificidae 10 0 0

Fanno Creek at Durham, OR 96 57 Cheumatopsyche sp. 8 3 11

Kellogg Creek at Milwaukie, OR 88 27 Cheumatopsyche sp. 8 7 21

Pringle Creek at Salem, OR 88 49 Simulium canadense 7 5 17

Amazon Creek near Danebo Road, at Eugene, OR 77 35 Cricotopus bicinctus group 7 1 4

Tryon Creek below Nettle Creek, near Lake Oswego, OR 72 30 Baetis tricaudatus 7 6 17

Curtin Creek near Vancouver, WA 69 16 Cheumatopsyche sp. 8 14 36

Johnson Creek at Circle Avenue, OR 59 29 Cheumatopsyche sp. 8 3 12

Battle Creek near Turner, OR 58 51 Cheumatopsyche sp. 8 3 14

Rock Creek at Quatama Road, near Hillsboro, OR 51 37 Cheumatopsyche sp. 8 3 10

Whipple Creek near Salmon Creek, WA 49 16 Optioservus sp. 9 9 27

Chicken Creek near Sherwood, OR 45 38 Cheumatopsyche sp. 8 6 24

North Fork Deep Creek at Barton, OR 39 34 Baetis tricaudatus 7 3 11

Oak Creek at Corvallis, OR 39 31 Ferrissia sp. 7 6 21

Tickle Creek near Boring, OR 32 67 Simulium canadense 7 2 11

Chehalem Creek at Newberg, OR 29 51 Fluminicola sp. 7 2 7

Silk Creek near Cottage Grove, OR 24 28 Simulium canadense 7 12 34

Rock Creek near Battleground, WA 23 14 Paratanytarsus sp. 6 15 36

Salmon Creek near Battleground, WA 20 27 Rhithrogena sp. 3 15 54

Deep Creek near Sandy, OR 17 23 Baetis tricaudatus 7 14 41

Nate Creek near Colton, OR 15 30 Rhithrogena sp. 3 14 50

Milk Creek at Camp Adams, OR 12 23 Cheumatopsyche sp. 8 18 56

North Yamhill Creek near Yamhill, OR 8 36 Ceratopsyche cockerelli 5 18 51

South Scappose Creek at Scappose, OR 8 20 Rhithrogena sp. 3 8 31

Lost Creek near Dexter, OR 6 30 Rhithrogena sp. 3 16 50

Iler Creek near Forest Grove, OR 4 26 Rhithrogena sp. 3 16 37

East Fork Dairy Creek near Meacham Corner, OR 0 18 Zapada cinctipes 4 18 47

 Average of sites greater than UII of 25 37 8 4 15

 Average of sites less than UII of 25 25 5 15 44

Table 12. Single dominant benthic macroinvertebrate taxon at each site, taxon name, U.S. Environmental Protection Agency tolerance 

value, Ephemeroptera, Plecoptera, and Trichoptera richness, and richness percentage per site, Willamette River basin and surrounding 

area, Oregon and Washington.

[Sites are sorted by the urban intensity index (UII). Shading indicates sites with UII greater than 25. Abbreviations: EPT, Ephemeroptera, Plecoptera, and 

Trichoptera; USEPA, U.S. Environmental Protection Agency; SW, southwest; OR, Oregon; WA, Washington]
Results 37

average, 14 percent abundance was detected at the sites near 

reference condition. Total taxa richness did not show a strong 

relation to urbanization in the Willamette Valley, even though 

richness of individual groups like EPT and noninsects had a 

strong relation to the UII. This indicates that there is specie 

replacement along the gradient, such that as sensitive EPT taxa 

drop out as urbanization increases noninsects and chironomid 

taxa take their place and total taxa richness remains relatively 

the same. Therefore, like the metric percent dominance 

mentioned previously, total taxa richness does not work well 

as a metric indicative of disturbance in this region even though 

it often is useful in other geographic regions.

Many benthic macroinvertebrate metrics had strong 

correlations to the UII. The three greatest rho values were 

for Ephemeroptera richness (negative), Plecoptera richness 

(negative), and the abundance of tolerant taxa (positive; 

table 14). Spearman correlation coefficients for these 

three benthic macroinvertebrate metrics and the five urban 

indicators were all greater than ±0.69, with the strongest 

positive correlation between tolerant taxa and the UII (0.79) 

and the strongest negative between EPEM richness and 

POPDEN00 (-0.79; table 14). Many benthic macroinvertebrate 

metrics also had relatively strong correlation values with 

selected environmental setting metrics, including measures of 

soil erosion potential, elevation, precipitation, watershed slope, 

and percentage of low elevation flat land in the watershed 

(table 14). Urban and agricultural land use development 

follows the natural topography in the Willamette Valley; 

a higher percentage of development is in the flatter lowelevation valley and less in the higher elevation foothills. 

Cuffney and others (2005) determined strong correlations 

for similar environmental setting variables with benthic 

macroinvertebrate metrics, but only for the more mountainous 

Salt Lake City region and not for the Boston or Birmingham 

areas. In the Willamette River basin and surrounding area, 

a number of benthic macroinvertebrate metrics had their 

strongest correlation coefficients to water-chemistry metrics, 

such as TP, total insecticide and total pesticide concentration, 

PTI, TEQ, and the Pyrene Index. Most Spearman correlation 

coefficients between benthic macroinvertebrate richness 

metrics and the aforementioned water-chemistry metrics were 

greater than 0.70 (table 14). The four strongest correlations 

were between percent Diptera richness (not including 

chironomid midges) and the Pyrene Index (rho = 0.88) and 

the TEQ (0.85), and between percent richness of tolerant taxa 

and the TEQ (0.87), and between the EPT: Chironomid ratio 

and the total insecticide concentration (-0.85; table 14). These 

strong correlation values between water-chemistry metrics 

and benthic macroinvertebrate metrics are similar to those 

published by Cuffney and others (2005), and indicate that one 

effect of pesticides and other potentially toxic compounds is 

a reduction in the number of sensitive insect taxa in favor of 

more tolerant chironomid midge larvae. 

A shift in the benthic macroinvertebrate assemblage 

toward less palatable organisms such as worms (Oligochaetes), 

or snails potentially could affect fish assemblages. Any 

reduction in EPT insect abundance or taxa richness could 

have implications for salmonids and other fish in this region 

because EPT taxa are important contributors to aquatic food 

webs, linking algae with fish. EPT taxa include herbivorous 

caddisflies and mayflies, which play an important role in 

food webs by grazing algae. The EPT taxa typically emerge 

into flying adults in a chronologic sequence that lasts nearly 

year-round, in a pattern predictable to the local angler and 

resident fish. Reductions in EPT taxa could, reduce food 

available for fish that may lead to reductions in production or 

changes in species composition indirectly, in addition, stream 

conditions such as temperature, DO, or other factors that affect 

macroinvertebrates may also directly affect the natural fish 

assemblage.

Multivariate Analysis of Benthic Macroinvertebrate 

Assemblages

Ordination analysis took advantage of the full species 

assemblage at each site to determine patterns among sites 

based on the biological data. This approach provided a 

more complete picture compared to analysis of individual 

benthic macroinvertebrate metrics, which examined selected 

components of the assemblage. The first nMDS ordination 

axis scores summarizes the major variation among sites as 

revealed by the full benthic macroinvertebrate species data 

(see Methods: Data Reduction and Analysis for explanation 

of ordinations), the scores reveal how the sites spread in a 

2-dimensional plot based on the species occurring at each 

site. Therefore, sites that plot close to each other are similar 

in species composition, whereas sites that plot far apart from 

one another are very different in species composition. The 

first ordination axis scores were negatively correlated to the 

UII with a consistent and fairly even distribution of points, 

whereas the percentage of low elevation flat land in the 

watershed, shown to have relatively high correlations only 

to a few invertebrate metrics, did not correlate as well (figs, 

18A and C), nor did the points spread consistently over the 

range of ordination scores. The ordination axis scores on the 

other hand, also had strong correlations to many of the same 

water-quality parameters as did the individual metrics (fig. 

18B) and the correlation values were within a similar range 

as the metrics (TEQ; rho = -0.87; fig. 18D). The PRIMER 

BEST routine identified six variables—TEQ, sum of total 

pesticides, average embeddedness, DO or percent riffle habitat 

(surrogates for each other), 7-day average water temperature, 

and the UII or percentage of urban plus agricultural land 

(surrogates for each other)—that explained about 65 percent 

of the variation in the benthic macroinvertebrate assemblages 

among all sites. 
38 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington Table 14. Correlation between selected benthic macroinvertebrate metrics and environmental variables, Willamette River basin and surrounding area, Oregon and Washington. [See appendix 

A for definitions of environmental variables. Correlation coefficients were considered strong when absolute value ≥ 0.66 (bolded and shaded) and moderate when 0.66 > rho ≥ 0.50 (bolded). 

Abbreviations: DO, dissolved oxygen; EPEM, Ephemeroptera; EPT, Ephemoroptera, Plecoptera, Trichoptera; PLECO, Plecoptera; ROADDEN, road density; SPMD, semipermeable membrane device; TEQ, toxic equivalent; nMDS + AFDM, nonmetric dimensional scaling + ash-free dry mass; mg/L, milligram per liter. Symbols: >, greater than; ≥, greater than or equal to]

Environmental variables

Invertebrate metrics

Ephemeroptera EPT Plecoptera

Nonchironomids Tolerant or intolerant metrics Noninsect metrics

Full 

invertebrate

assemblage

EPEM 

abundance

EPEM 

richness

EPT/

chironomid 

ratio

EPT 

richness

PLECO 

percent

PLECO 

richness

Nonmidge 

diptera percent 

richness

Intolerant 

abundance

Tolerant 

richness

Tolerant 

percent 

richness

Tolerant 

abundance Amphipod percent

Noninsect 

percent 

richness

Oligochaete 

percent 

richness

nMDS Axis1 

score

Urban indicator metrics

Urban intensity index (UII) -0.72 -0.78 -0.71 -0.75 -0.70 -0.77 0.75 -0.76 0.74 0.74 0.79 0.68 0.76 0.74 -0.83

Percent impervious surface -.66 -.76 -.70 -.72 -.67 -.75 .71 -.71 .71 .71 .75 .72 .72 .71 -.79POPDEN00 -.69 -.79 -.74 -.77 -.69 -.78 .74 -.76 .77 .76 .78 .67 .74 .74 -.83Percent urban and agriculture -.66 -.74 -.69 -.72 -.66 -.74 .70 -.73 .69 .67 .74 .68 .72 .68 -.80ROADDEN -.63 -.72 -.67 -.67 -.67 -.69 .67 -.71 .67 .67 .73 .60 .67 .70 -.76

Environmental setting metrics

Mean soil erodibility -0.63 -0.64 -0.55 -0.60 -0.44 -0.60 0.66 -0.51 0.69 0.66 0.75 0.58 0.66 0.67 -0.64

Minimum watershed elevation .42 .52 .49 .43 .53 -.48 .38 -.60 -.61 -.58 -.61 -.44 -.56 .45Percent flat and low elevation 

land in basin

-.72 -.60 -.52 -.55 -.44 -.53 .55 -.57 .52 .56 .51 .69 .62 .52 -.69

Annual precipitation .57 .57 .54 .57 .51 .59 -.62 .44 -.67 -.69 -.69 -.61 -.61 -.54 .63Mean percent watershed slope .45 .67 .58 .64 .63 .65 -.60 .63 -.55 -.49 -.61 -.69 -.65 -.55 .65

Hydrologic variation metrics

Number of falling events > 

5×median (PeriodF5)

-0.53 -0.55 -0.59 -0.55 -0.60 -0.56 0.62 -0.54 0.51 0.57 0.54 0.44 0.60 0.68 -0.62

Number of falling events > 

9×median (PeriodF9)

-.57 -.59 -.58 -.51 -.49 -.52 .62 -.59 .51 .59 .57 .36 .56 .67 -.59

Number of rising events > 

5×median (PeriodR5)

-.45 -.53 -.55 -.50 -.58 -.51 .57 -.51 .47 .53 .50 .39 .56 .60 -.56

Richards-Baker Flashiness Index 

(Rb-flash)

-.60 -.55 -.56 -.57 -.60 -.58 .58 -.64 .60 .55 .56 .35 .60 .52 -.64

Water temperature metrics

Minimum temperature (95th 

percentile)

-0.47 -0.48 -0.38 -0.44 -0.43 -0.38 0.54 -0.37 0.36 0.43 0.45 0.41 0.59 0.67 -0.53

Habitat metrics

Mean embeddedness (riffle and 

runs)

-0.60 -0.57 -0.47 -0.49 -0.37 -0.50 0.40 -0.46 0.55 0.46 0.67 0.55 0.43 0.42 -0.53

Mean width/depth ration (riffle 

and runs)

.37 .37 .24 .28 .09 .26 -.23 .25 -.44 -.37 -.39 -.47 -.26 -.41 .30

Percent riffle habitat .64 .55 .44 .46 .38 .47 -.41 .34 -.54 -.51 -.58 -.58 -.44 -.43 .58Percent large substrate .33 .21 .10 .22 -.03 .05 -.08 .13 -.24 -.18 -.22 -.11 -.11 -.16 .20

Mean habitat heterogeneity -.53 -.34 -.22 -.35 -.08 -.16 .25 -.25 .39 .35 .38 .10 .30 .29 -.38
Results 39

Environmental variables

Invertebrate metrics

Ephemeroptera EPT Plecoptera

Nonchironomids Tolerant or intolerant metrics Noninsect metrics

Full 

invertebrate

assemblage

EPEM 

abundance

EPEM 

richness

EPT/

chironomid 

ratio

EPT 

richness

PLECO 

percent

PLECO 

richness

Nonmidge 

diptera percent 

richness

Intolerant 

abundance

Tolerant 

richness

Tolerant 

percent 

richness

Tolerant 

abundance Amphipod percent

Noninsect 

percent 

richness

Oligochaete 

percent 

richness

nMDS Axis1 

score

Water-chemistry variables

Instantaneous summer DO (mg/L) 0.77 0.63 0.55 0.60 0.45 0.52 -0.58 0.41 -0.57 -0.56 -0.63 -0.44 -0.57 -0.46 0.69

Average dissolved organic carbon -.70 -.69 -.74 -.72 -.72 -.73 .71 -.63 .70 .64 .69 .59 .67 .62 -.79

Summer chlorophyll AFDM -.60 -.57 -.59 -.51 -.42 -.59 .47 -.54 .56 .55 .55 .52 .44 .33 -.57

Average total suspended sediment -.58 -.40 -.50 -.34 -.33 -.35 .43 -.25 .30 .28 .32 .25 .35 .30 -.48

Average sulfate concentration -.64 -.63 -.68 -.53 -.48 -.60 .58 -.58 .68 .66 .55 .74 .52 .56 -.62

Average total nitrogen (TN) -.51 -.73 -.75 -.69 -.67 -.76 .58 -.68 .66 .55 .62 .66 .57 .49 -.69

Average total phosphorus (TP) -.61 -.78 -.83 -.75 -.64 -.79 .65 -.64 .83 .74 .75 .72 .61 .56 -.72

Total of insecticides (spring + summer) -.67 -.77 -.85 -.75 -.75 -.74 .71 -.72 .75 .65 .67 .54 .69 .66 -.80

Total of pesticides (spring + summer) -.67 -.76 -.81 -.82 -.83 -.82 .78 -.75 .71 .65 .79 .47 .76 .56 -.85

Pesticide Toxicity Index (PTI; spring 

+ summer)

-.54 -.71 -.80 -.81 -.81 -.80 .70 -.76 .75 .70 .67 .42 .69 .51 -.79

TEQ (SPMD) -.77 -.80 -.77 -.79 -.69 -.81 .85 -.81 .80 .87 .79 .52 .83 .71 -.87

Pyrene Index (SPMD) -.63 -.73 -.70 -.76 -.65 -.77 .88 -.68 .73 .82 .69 .52 .82 .69 -.77

Table 14. Correlation between selected benthic macroinvertebrate metrics and environmental variables, Willamette River basin and surrounding area, Oregon and 

Washington.—Continued

[See appendix A for definitions of environmental variables. Correlation coefficients were considered strong when absolute value ≥ 0.66 (bolded and shaded) and moderate when 0.66 > rho ≥ 0.50 (bolded). Abbreviations: DO, dissolved oxygen; EPEM, Ephemeroptera; EPT, Ephemoroptera, Plecoptera, Trichoptera; PLECO, Plecoptera; ROADDEN, road density; SPMD, semipermeable membrane device; TEQ, toxic equivalent; nMDS + AFDM, nonmetric dimensional scaling + ash-free dry mass; mg/L, milligram per liter. Symbols: >, greater than; ≥, greater than or equal to]
40 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Although the first ordination axis used data from the 

complete benthic macroinvertebrate assemblage, the richness 

of EPT or Ephemeroptera metrics were strongly correlated 

with the nMDS axis score (rho greater than 0.90), which 

indicates that the first ordination axis largely described the 

same variation as the individual metrics, namely the change 

in richness of EPT or Ephemeroptera. This indicates that the 

disturbance gradient (UII) in the Willamette Valley was strong 

enough that differences among sites could be detected with 

only a part of the benthic macroinvertebrate assemblage. There 

is enough taxa diversity in the benthic macroinvertebrate data 

that part of the information is redundant. For example, EPT 

richness, a subset of the full species data set, could explain as 

much variation among sites as the full data (such as ordination 

axis). 

Most benthic macroinvertebrate metrics showed linear 

responses to urbanization with no apparent threshold except, 

possibly, for EPT richness. EPT richness plotted against the 

UII showed a strong negative trend as urbanization increased 

and may have exhibited a threshold response near UII = 25 

(fig. 17). All sites less than UII 25 had greater than 12 or more 

EPT taxa (average 15) except for South Scappoose Creek, 

whereas all sites greater than UII 25 had less than 9 EPT 

taxa (average 4), except for Curtin Creek (table 12). South 

Scappoose Creek likely has a lower EPT richness because 

it is a low gradient stream with minimal riffle habitat with 

potentially more urban influence than reflected by the UII 

score. Conversely, Curtin Creek had a greater abundance of 

EPT taxa than other streams greater than UII 25 because it had 

cold, clear summer flows due to a large amount of groundwater discharge upstream of the sampling site, thus offering 

better water quality habitat than what the UII would suggest. 

In addition, no insecticides were detected in Curtin Creek 

(table 4) and it had low TEQ and Pyrene Index values. As 

a result, Curtin Creek had remarkable numbers of EPT taxa 

and low percent taxa dominance even with little in-stream 

habitat. Cuffney and others (2005) determined that responses 

of benthic macroinvertebrate metrics in the pilot USGS EUSE 

study areas generally were linear and without thresholds, 

except for a few selected metrics for the Boston-area. No 

thresholds or initial resistance to the effects of urbanization for 

full assemblage measures or ordination axes were detected in 

or19-0168_ fig18 any region (Cuffney and others, 2005).

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 10 20 30 40 50 60 70 80 90 100

URBAN INTENSITY INDEX

rho = -0.83

A. Urban intensity index

0 10 20 30 40 50 60 70

PERCENT FLAT AND LOW ELEVATION LAND

rho = -0.69

B. Summer dissolved oxygen

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

32 4 5 6 7 8 9 10 11

MACROINVERTEBRATE NONMETRIC MULTIDIMENSIONAL SCALING AXIS 1 ORDINATION SCORE

SUMMER DISSOLVED OXYGEN, IN MILLIGRAMS PER LITER

rho = 0.69

C. Flat and low elevation land

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

100 300 500 700 900 1,100 1,300

TOXIC EQUIVALENTS, IN PICOGRAMS

rho = -0.87

D. Toxic equivlents

Figure 18. Benthic macroinvertebrate nonmetric dimensional scaling ordination axis 1 scores in relation to (A) urban 

intensity index (UII), (B) summer dissolved oxygen concentrations, (C) percentage of flat and low elevation land in 

watershed and (D) and toxic equivalents from semipermeable membrane devices, Willamette River basin and surrounding 

area, Oregon and Washington.
Results 41

Although there appeared to be a possible threshold 

in EPT richness at UII equal to 25, the apparent threshold 

was likely due to added agricultural land use in all sites 

greater than UII 25 than to any actual urban threshold. For 

example, at UII less than 25 the total percentage of urban plus 

agricultural land in the watershed was less than 16 percent 

(except for Deep Creek at 34 percent), yet immediately 

greater than a UII of 25, urban plus agricultural land 

increased markedly to between 53 and 98 percent (except 

for Oak Creek at 26 percent, table 1 and fig. 8). Therefore, 

any apparent threshold along the UII gradient was likely 

a threshold of the total of urban plus agricultural land use. 

However, the exact threshold is unknown because only two 

sites (Oak and Deep Creek) had urban plus agricultural land 

use percentages between 16 and 52 percent; therefore, there 

was not enough information in this data range to more fully 

evaluate thresholds. The plot of EPT richness and UII (fig. 17) 

indicates that if it exists, a threshold is at low values of urban 

plus agricultural land use, perhaps as low as 10 percent 

combined land use.

Although the streamflow, water temperature, and 

habitat measurements did not have as strong correlations 

as water-chemistry metrics to benthic macroinvertebrate 

metrics, they did have statistically significant values (greater 

than 0.60) for correlations of selected variables to a few 

metrics (table 14). The four hydrologic variables (PeriodF5, 

PeriodF9, PeriodR5 and Rb-flash) had correlations to a 

few benthic macroinvertebrate metrics greater than 0.60. 

For habitat measures, correlation values were this strong 

only for percentages of riffle and embeddedness correlated 

with Ephemeroptera abundance and tolerant abundance. 

Water temperature had only one correlation to benthic 

macroinvertebrate metrics greater than 0.60, with Oligochaete 

percent richness.

Fish Assemblages

Fish Metrics in Relation to Urban Intensity Index

Total fish richness ranged from 2 to 12 species, total 

abundance ranged from 52 to 672, and maximum relative 

abundance or percent dominance of any single species ranged 

from 20 to 98 percent among all sites (table 15). Sixty percent 

of the sites had six species or fewer, yet there was no strong 

correlation of number of fish species to total abundance. 

For example, the site with the highest number of species 

(12) had a total abundance of 163 (North Fork Deep Creek) 

and the site with the lowest numbers of species (2) had an 

abundance of 380 (Tyron Creek). Western streams naturally 

have relatively low fish species richness compared to streams 

east of the Rocky Mountains (Simon and Lyons, 1995; Meador 

and others, 2005), and as a result, fish species richness from 

western streams generally have not been a good bioindicator. 

For example, a poor relation of fish species richness to UII 

was determined in this study, yet Meador and others (2005) 

determined a strong relation between fish species richness 

and urbanization in the Boston and Birmingham areas. On the 

other hand, nonnative or invasive species are a more serious 

problem in western than eastern streams and nonnative fish 

were in approximately 50 percent of sites greater than a UII 

of 25, although only one occurrence was at a site less than 

25 (table 15). Amazon Creek, with a UII of 77, contained 

the most nonnative species (five species) and highest percent 

abundance of nonnatives (98 percent) of any site. Claggett 

Creek, with a UII of 100, was the next highest with four 

nonnative species (19 percent abundance).

Although total species richness was not different 

between low and high UII sites, percentage of salmonids and 

nonnatives were different. Salmonids were present at 10 of 11 

sites less than UII 25, whereas salmonids were present in only 

4 of 17 sites greater than UII 25. No sites with salmonids had 

any nonnatives except one site, North Fork Deep Creek with 

33 percent salmonids and 5 percent nonnatives. In this study, 

percent dominance (relative abundance) calculated from fish 

assemblage data had a strong curvilinear or possible threshold 

relation to the UII (rho = 0.67) where low urban sites (less 

than UII 25; table 15) had low percent dominance (average 

of 46 percent), although sites greater than UII 25 had average 

dominance values greater than 80 percent (fig. 19). The 

threshold for percent dominance at UII of 25 was equivalent to 

about 3–5 percent impervious surface, which was lower than 

most other thresholds previously reported for fish community 

metrics (Lyons and others, 1996; Wang and others, 2001). 

The apparent urban threshold likely was due to added 

agricultural land use in sites greater than UII 25 and therefore 

the threshold likely represents the effect from total watershed 

disturbance of urban plus agricultural land use and not just 

urbanization. 

The fish index, which combined individual metrics of 

percentages of salmonids, reticulate sculpins, nonnatives, 

and natives (with salmonids and reticulates removed), had 

high correlation values to urban indicators (UII: rho = -0.68; 

table 16). The fish index also was strongly correlated (rho 

greater than 0.60) to PeriodF5 hydrology, embeddedness, 

width-depth ratio, riffle percentage, summer DO, DOC, 

specific conductance, sulfate concentration, and TEQ 

(table 16). The highest correlation values were between 

percentage of salmonids and summer DO (rho = -0.81) and 

percentage of riffle (rho = -0.78). 
42 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

rho = 0.67

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100

URBAN INTENSITY INDEX

FISH DOMINANCE, IN PERCENT

Figure 19. Relation between urban intensity index (UII) and percent 

dominance by single fish species at all 28 sites (highest relative abundance), 

Willamette River basin and surrounding area, Oregon and Washington.

Site name UII Species 

richness

Total 

abundance

Percent

Dominance Salmonids Nonnatives

Beaverton Creek near SW 216th Avenue near Orenco, OR 100 6 361 97 0 1

Claggett Creek at Keizer, OR 100 8 325 79 0 19

Fanno Creek at Durham, OR 96 6 586 91 0 0

Kellogg Creek at Milwaukie, OR 88 4 541 90 0 0

Pringle Creek at Salem, OR 88 9 600 88 0 0

Amazon Creek near Danebo Road at Eugene, OR 77 8 597 90 0 98

Tryon Creek below Nettle Creek, near Lake Oswego, OR 72 2 380 98 2 0

Curtin Creek near Vancouver, WA 69 5 52 79 17 0

Johnson Creek at Circle Avenue, OR 59 8 278 47 0 1

Battle Creek near Turner, OR 58 5 281 75 0 8

Rock Creek at Quatama Road near Hillsboro, OR 51 5 251 98 2

Whipple Creek near Salmon Creek, WA 49 3 162 83 0 0

Chicken Creek near Sherwood, OR 45 4 344 83 0 0

North Fork Deep Creek at Barton, OR 39 12 163 20 33 5

Oak Creek at Corvallis, OR 39 4 394 97 0 0

Tickle Creek near Boring, OR 32 8 672 77 18 0

Chehalem Creek at Newberg, OR 29 6 456 88 0 1

Silk Creek near Cottage Grove, OR 24 7 217 70 2 0

Rock Creek near Battleground, WA 23 6 395 55 25 0

Salmon Creek near Battleground, WA 20 9 183 52 5 0

Deep Creek near Sandy, OR 17 8 220 36 25 0

Nate Creek near Colton, OR 15 4 148 91 7 0

Milk Creek at Camp Adams, OR 12 11 301 36 6 0

North Yamhill Creek near Yamhill, OR 8 6 189 28 38 0

South Scappoose Creek at Scappoose, OR 8 7 96 44 0 1

Lost Creek near Dexter, OR 6 9 253 26 5 0

Iler Creek near Forest Grove, OR 4 6 150 39 35 0

East Fork Dairy Creek near Meacham Corner, OR 0 8 639 32 38 0

Average of sites greater than UII of 25 6 379 81 4 8

Average of sites less than UII of 25 7 254 46 17 0

Table 15. Fish species richness, total abundance, percentages of dominance (single species), salmonids, and nonnative fish for 28 

sites, Willamette River basin and surrounding area, Oregon and Washington.

[Sites are sorted by urban intensity index (UII). Shading indicates sites with UII greater than 25. Abbreviations: SW, southwest; OR, Oregon; WA, Washington]
Results 43

Environmental variables FISH Index Percent 

salmonids

FISH nMDS 

Axis1

Urban indicator metrics

Urban intensity index (UII) -0.68 0.62 -0.76

Percent impervious surface -.63 .57 -.69

POPDEN00 -.68 .63 -.75

Percent urban + agriculture -.56 .49 -.68

ROADDEN -.57 .54 -.69

Hydrologic variation metrics

Number of falling events > 5×median (PeriodF5) -0.55 0.56 -0.72

Number of falling events > 9×median (PeriodF9) -.62 .53 -.63

Number of rising events > 5×median (PeriodR5) -.48 .48 -.66

Richards-Baker Flashiness Index (Rb-flash) -.53 .53 -.58

Habitat metrics

Mean embeddedness (riffle and runs) -0.64 0.58 -0.49

Mean width/depth ratio (riffle and runs) .61 -.53 .37

Percent riffle habitat .63 -.78 .67

Mean habitat heterogeneity -.50 .53 -.53

Water temperature metrics

Seven day average temperature -0.15 0.26 -0.52

Minimum temperature (95th percentile) -.50 .60 -.67

Water-chemistry variables

Summer dissolved oxygen (mg/L) 0.70 -0.81 0.77

Dissolved organic carbon -.68 .66 -.74

Specific conductance -.74 .60 -.53

Sulfate concentration -.69 .48 -.50

Sum of total insecticides (TN) -.59 .46 -.69

Sum of total pesticides (TP) -.52 .43 -.70

TEQ (SPMD) -.69 .70 .74

Table 16. Correlations of fish metrics and nonmetric dimensional scaling axis 1 ordination 

scores with environmental variables, Willamette River basin and surrounding area, Oregon and 

Washington.

[See appendix A for definitions of environmental variables. Correlation coefficients were considered strong when 

absolute value ≥ 0.66 (bolded and shaded) and moderate when 0.66 > rho ≥ 0.50 (bolded). Abbreviations: DO, 

dissolved oxygen; TEQ, toxic equivalent index; SPMD, semipermeable membrane device; TN, total nitrogen; TP, 

total phosphorus; mg/L, milligram per liter. Symbols: >, greater than]
44 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Multivariate Analysis of Fish Assemblages

Bioindicators, such as ordination axis scores and 

individual metrics, were correlated against individual 

environmental variables to gain insight into what was 

structuring or potentially affecting the fish assemblages. 

The full fish assemblage, as represented by the scores of 

the first nMDS ordination axis, was negatively correlated to 

the UII with no apparent threshold (rho = -0.76; fig. 20A). 

With the exception of the percentage of salmonids metric 

(which had some high rho correlation values; table 16), the 

nMDS ordination axes scores had stronger correlations to 

the environmental variables than the fish index or individual 

metrics. 

The relations between the ordination axis 1 scores and 

summer DO, TEQ, and PeriodF5 are shown in figures 20B–D. 

A strong linear response was noted in the fish assemblages 

along the UII and in response to DO concentrations. The 

response in the TEQ, however, may indicate a potential 

threshold between 300 and 500 picograms TEQ (fig. 20B). 

The axis 1 ordination scores also were strongly related to 

three hydrology variation metrics (PeriodF5; fig. 20D), 

percent riffle, minimum temperature, DOC, and sum of 

insecticides and pesticides (table 16). The BEST routine 

in PRIMER indicated that summer DO, percent riffles and 

PeriodF5 could explain about 60 percent of the variation in 

full fish assemblage data among the sites. The percentage of 

salmonids compared to the summer DO concentration may 

also be indicative of a possible threshold response (fig. 21). 

No salmonids were sampled at sites with midday summer 

DO concentrations less than 8 mg/L, except at Curtin Creek. 

Because salmonids require cool waters with high DO to thrive, 

few were observed during the summer in these Willamette 

Valley ecoregion streams that often can have high summer 

temperatures with low dissolved oxygen. The Oregon 

Department of Environmental Quality standard for DO is 

5.5 mg/L and 18 degrees Celsius (7-day moving average for 

the minimum summer water temperature). Curtin Creek was 

a unique site and although little high-quality fish habitat was 

within the sampled reach, it offered salmonids cold clear water 

during the summer with abundant instream habitat cover in the 

form of macrophytes and overhanging riparian vegetation. As 

a result, salmonids probably immigrated from nearby streams 

into Curtin Creek to take advantage of the cold water during 

summer.

URBAN INTENSITY INDEX

A. Urban intensity index

B. Toxic equivalents

SUMMER DISSOLVED OXYGEN, IN MILLIGRAMS PER LITER

C. Summer dissolved oxygen

TOXIC EQUIVALENTS, IN PICOGRAMS

D. Falling hydrologic events

0

0.5

1.0

1.5

2.0

2.5

3.0

4.0

3.5

0 20 40 60 80 100

rho = -0.76

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

0.5

1.0

1.5

2.0

2.5

3.0

4.0

3.5

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

100 300 500 700 900 1,100 1,300

rho = -0.74

2 3 4 5 6 7 8 9 10 11

rho = 0.77

rho = -0.72

0 10 20 30 40 50 60 70 80 90

NUMBER OF FALLING HYDROLOGIC EVENTS DURING PERIOD F5

FISH NONMETRIC MULTIDIMENSIONAL SCALING AXIS 1 SCORE

Figure 20. Relation between fish assemblages (nonmetric dimensional scaling first axis ordination scores) and (A) urban 

intensity index (UII), (B) toxic equivalents (TEQ) from semipermeable membrane devices, (C) summer dissolved oxygen (DO) 

concentrations and (D) the number of falling hydrologic events (PeriodF5), Willamette River basin and surrounding area, 

Oregon and Washington.
Summary 45

Summary

This study examined how urbanization affects stream 

ecosystems. Objectives of the study included an examination 

of physical, chemical, and biological responses to urbanization 

of small streams in the Willamette River basin and 

surrounding area, Oregon and Washington.

Hydrologic variable findings indicate that as urban 

intensity indicators increased (urban intensity index (UII), 

road density, percentage of impervious surface and population 

density), so did the stream flashiness. For example, the 

response of stream flashiness metrics to urbanization was 

moderate (0.66 > rho ≥ 0.50) to strong (rho ≥ 0.66) among the 

sites examined in this study. In addition, as urban indicators 

increased, minimum water temperature (95th percentile) also 

increased by a moderate response (0.56 ≥ rho ≥ 0.44). Other 

moderate responses to increased urbanization included an 

increase in average substrate embeddedness (riffles and runs), 

a decrease in average width-to-depth ratio (riffles and runs), 

and a decrease in the percentage of riffle habitat.

Physical data collected indicated that one of the strongest 

relations was detected between percentage of riffle habitat 

and summer dissolved oxygen concentrations (rho = 0.84). 

It was also discovered that there was a moderate to strong 

negative correlation of dissolved oxygen with minimum 

temperature, average substrate embeddedness, and mean 

habitat heterogeneity (measure of instream habitat diversity). 

There were other connections between physical and water 

chemistry, such as, streamflow flashiness metrics showed 

strong responses to select water-chemistry parameters, 

including dissolved organic carbon, sum of total pesticides, 

toxic equivalents (measure of water column contaminants 

obtained from semipermeable membrane devices), and sulfate 

concentration. Conversely, streamflow flashiness had a low 

correlation to nutrients, such as total nitrogen concentration 

(rho = 0.30).

Figure 21. Relation between midday summer dissolved oxygen (DO) 

concentrations and percentage of salmonids, Willamette River basin and 

surrounding area, Oregon and Washington.

or19-0168_ fig21 Relations between midday summertime dissolved oxygen concentrations and percent salmonids.

0

5

10

15

20

25

30

35

40

45

0 2 4 6 8 10 12

MIDDAY SUMMER DISSOLVED OXYGEN CONCENTRATION, IN MILLIGRAMS PER LITER

SALMONIDS, IN PERCENT

rho = 0.81

Most water-chemistry metrics, 

including sum total insecticide, sum total 

pesticide, pesticide toxicity index, toxic 

equivalents (TEQ), and Pyrene index, 

responded moderately to strongly to each 

increased urban indicator metric (0.83 ≥

rho ≥ 0.56). For example, the sum of total 

insecticides correlated strongly to road 

density, population density, and the urban 

intensity index (rho = 0.73, 0.70, and 

0.69, respectively). However, insecticides 

were slightly less correlated to percentage 

of impervious surface and urban plus 

agricultural land use (rho = 0.66 and 0.63, 

respectively). Sum of total pesticides 

was strongly related to each urban 

metric (rho ≥ 0.66), except percentage of 

impervious surface where it was moderate 

(rho = 0.65). The semipermeable membrane 

device assays correlated positively to urban 

indictors as well, with toxic equivalents strongly associated 

to all urban indicator metrics (0.81 ≥ rho ≥ 0.73). The Pyrene 

index increased moderately to strongly with the increasing 

urban metrics (0.67 ≥ rho ≥ 0.51). Total nitrogen and total 

phosphorus both correlated strongly to the urban intensity 

index (rho = 0.79 and 0.71, respectively). Total nitrogen 

also correlated positively with the percentage of urban plus 

agricultural land use. Other water-chemistry metrics with 

strong correlations that increased with increasing urbanization 

were specific conductance and dissolved sulfate, whereas 

dissolved organic carbon, alkalinity, chloride, and summer 

dissolved oxygen were moderately correlated. 

Algal assemblages responded to the nutrient and organic 

enrichment effects of urbanization (and agriculture at some 

sites), which included the development of nuisance green 

algae growths in some streams. For example, blue-green and 

red algae dominated the relative density in all but one stream, 

Deep Creek. High-nutrient indicator diatoms and other algal 

assemblages that tolerate moderate to high degrees of organic 

enrichment were positively correlated with the urban intensity 

index (rho = 0.52). 

Benthic algal chlorophyll-a was highly variable along the 

urban gradient, but the ash-free dry mass (measure of algal 

biomass used to indicate the degree of organic enrichment) 

was positively correlated with the urban intensity index (rho 

= 0.56). The ash-free dry mass was positively correlated with 

dissolved organic carbon concentrations, while dissolved 

oxygen was negatively correlated with dissolved organic 

carbon concentrations. These findings suggests that nutrient 

enrichment caused by urbanization increases the organic 

status of streams by stimulating algal growth and increasing 

ash-free dry mass. The organic matter eventually decomposes, 

which leads to the development of tolerant diatoms and 

heterotrophic algal taxa that make use of energy in the 

organic compounds. The use of such compounds by bacteria 

and other heterotrophic organisms consumes dissolved 
46 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

oxygen during respiration into carbon dioxide. Signs that 

this may be occurring in the more highly urbanized streams 

include the decrease in the relative abundance of diatom 

taxa requiring continuously high levels of dissolved oxygen. 

These sensitive taxa were most abundant at sites with a urban 

intensity index less than 25, and less abundant at sites higher 

on the urban gradient. In addition to nutrients and other 

effects of eutrophication such as organic enrichment, other 

environmental factors that were determined to be important in 

shaping the diatom assemblages included various measures of 

disturbance, such as streamflow flashiness, channel scour, and 

grazing benthic macroinvertebrates.

Benthic macroinvertebrate assemblages also showed a 

strong response to urbanization. From the most urbanized 

sites (urban intensity index greater than 70) to the least 

urbanized (urban intensity index less than 10), there was 

an average decrease of 12 Ephemeroptera, Plecoptera 

and Trichoptera taxa detected. In addition, there was a 

large increase in percentage of noninsects (31 percent) 

and percentage of abundance of tolerant taxa (48 percent) 

between the range of urbanization. At the sites across the full 

urban gradient, many macroinvertebrate metrics had strong 

correlations to urban indicators and water-quality variables. 

For example, Ephemeroptera, Plecoptera and Trichoptera 

taxa richness (rho = -0.75) and the nMDS ordination axis 

(rho = -0.83) were highly correlated to the urban intensity 

index. Macroinvertebrate metrics also had very strong 

correlations with total pesticide and insecticide concentrations, 

the pesticide toxicity index, contaminant measures from 

the semipermeable membrane device samples (TEQ and 

Pyrene Index), and summer dissolved oxygen. Although 

all four hydrologic variability and flashiness measures 

were moderately correlated to macroinvertebrate metrics, 

they represent less variation than any of the above waterquality variables. Therefore, although flashiness probably 

was an important issue in the urban areas of the Willamette 

River basin and surrounding areas, water chemistry issues 

including contaminants still are a dominant disturbance to 

macroinvertebrate assemblages followed by flashiness and 

sedimentation-substrate disturbance or habitat quality. 

Fish assemblages showed strong correlation to 

urbanization, as well. For example, on average, 4 percent 

salmonids (sensitive) and 8 percent nonnative fish (tolerant) 

were found at sites with an urban intensity index greater 

than 25. Conversely, 17 percent salmonids and less than 

1 percent nonnative fish were found at sites with an urban 

intensity index less than 25. All fish metrics, including fish 

index, salmonid percentage, and ordination axis 1 scores 

had strong correlations to the urban indicators and waterquality variables and moderate to strong correlation to 

the hydrologic variability, habitat, and water-temperature 

measures. Percentage of salmonids and macroinvertebrate 

Ephemeroptera, Plecoptera and Trichoptera taxa richness 

indicated a possible threshold response to urbanization at 

an urban intensity index of 25, which was equivalent to 

impervious surfaces of about 5 percent. However, due to 

the added agricultural land use element at sites with urban 

intensity index values between 25 and 60, this threshold may 

not be due to urbanization solely, but a combination of urban 

and agricultural land uses. The effects of agricultural and 

urban land use could not be distinguished from each other, 

yet combined provide a good assessment of overall watershed 

health.

Acknowledgments

The authors would like to thank the dedicated U.S. 

Geological Survey field crew for their tireless efforts during 

the extended field season. We also would like to thank 

the Washington County Watermaster and Clark County 

Public Works for their superior maintenance of stream gage 

equipment. We thank the organizations and landowners who 

permitted us access to sites that made this study possible. We 

would also like to give special thanks to Lori Sprague of the 

U.S. Geological Survey in Denver, Colorado, for her guidance 

and direction for this report. Lastly, we thank Dennis Wentz 

and Cathy Tate of the U.S. Geological Survey, Rick Hafele of 

the Oregon Department of Environmental Quality, and Chris 

Prescott of the City of Portland, Bureau of Environmental 

Services for their reviews, which greatly improved this report.

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50 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

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Open-File Report 95-181, 60 p.
Appendix A 51

Appendix A. Variable Definitions
52 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

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Appendix A 53

Basin 

characteristics GIS data theme Data theme source Reference or data source

Data used to delineate basins

Watershed 

boundaries

National Elevation Dataset (NED) U.S. Geological Survey U.S. Geological Survey, 1999, and U.S. Geological Survey Seamless Data Distribution System 

web site: http://seamless.usgs.gov; data extracted, 2002 and 2003.

Digital Raster Graphics (DRG) U.S. Geological Survey and 

Regional Ecosystem Office

Regional Ecosystem Office (REO) geographical information system (GIS) Data web site: http://

www.reo.gov/gis/data/DRG_Files/northwest.asp; data extracted, 2002–05.

National Hydrography Dataset (NHD) U.S. Geological Survey U.S. Geological Survey National Hydrography Dataset web site: http://nhd.usgs.gov/; data 

extracted 2005.

Data used as geographical information system (GIS) variables

Demography Census Blocks and Block Groups 2000, 

short (SF1) and long forms (SF3)

U.S. Census Bureau Geolytics Census 2000 Blocks short form CD and Census CD/DVD 2000 long form.

Infrastructure Census 2000 Topologically Integrated 

Geographic Encoding and Referencing system (TIGER) Line® files

U.S. Census Bureau Census TIGER web site: http://www.census.gov/geo/www/tiger/

National Pollutant Discharge Elimination 

System (NPDES)

U.S. Environmental 

Protection Agency

U.S. Environmental Protection Agency Envirofacts web site: http://www.epa.gov/enviro/index_

java.html; data extracted, 2002.

Toxics Release Inventory U.S. Environmental 

Protection Agency

U.S. Environmental Protection Agency Envirofacts web site: http://www.epa.gov/enviro/index_

java.html; data extracted, 2002.

Land use/land 

cover, including riparian buffer

National Land Cover Dataset (NLCD) 2001 U.S. Geological Survey U.S. Geological Survey, 2005; web site: http://www.mrlc.gov/mrlc2k_nlcd.asp; data extracted, 

2005.

National Hydrography Dataset (NHD) U.S. Geological Survey U.S. Geological Survey National Hydrography Dataset web site: http://nhd.usgs.gov/; data 

extracted 2005.

Soil State Soils Geographic (STATSGO) 

database

Natural Resources 

Conservation Service

National Resources Conservation Service web site: http://www.ncgc.nrcs.usda.gov/products/

datasets/statsgo/; data extracted, 2002.

Hydrologic soil groups Natural Resources 

Conservation Service

National Resources Conservation Service web site: http://www.ncgc.nrcs.usda.gov/products/

datasets/statsgo/; data extracted, 2002.

Hydrologic 

landscape regions

Hydrologic landscape regions U.S. Geological Survey U.S. Geological Survey web site: http://water.usgs.gov/GIS/metadata/usgswrd/XML/hlrus.xml; 

data extracted, 2002.

Ecoregion Ecoregions U.S. Environmental 

Protection Agency

U.S. Environmental Protection Agency web site: http://www.epa.gov/wed/pages/ecoregions/

level_iii.htm and http://www.epa.gov/wed/pages/ecoregions/level_iv.htm; data extracted, 2002 and 2005; Omernik (1987).

Topography National Elevation Dataset (NED) U.S. Geological Survey U.S. Geological Survey, 1999, and U.S. Geological Survey Seamless Data Distribution System 

web site: http://seamless.usgs.gov; data extracted, 2002 and 2005.

Climate Daymet Climatological Summaries for the 

Conterminous United States, 1980-97

University of Montana, Numerical 

Terradynamic Simulation Group and National Center for Atmospheric Research (NCAR)

Daymet web site: http://daymet.ntsg.umt.edu/data/data.htm; data extracted, 2005.

FRAGSTATS National Land Cover Dataset (NLCD) 2001 U.S. Geological Survey and 

National Oceanic and Atmospheric Administration

McGarigal, Kevin, and Marks, B.J., 1995, FRAGSTATS web site: http://www.umass.edu/landeco/

research/fragstats/fragstats.html; data extracted, 2005. Coastal Change and Analysis Program (C-CAP), 2006, web site: http://www.csc.noaa.gov/crs/lca/pacificcoast.html.

Table A1. Sources of geographical information system (GIS) and digital data used to derive study basins in the Willamette Valley ecoregion, Oregon and Washington.
54 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Variable code Definition

Spearmans’ rho 

correlation with 

population density

Census Variables

SEI_3 Socioeconomic Index 3: Principal component 3 for 63 socioeconomic variables (2000 census blockgroup based)0.92

HHDEN Household density (occupied housing units per square kilometer) (2000 census block-group based) .99

PPURBAN Proportion of population living in urban area (2000 census block-group based) .92

PP_SH95 Percentage of population living in same house as in 1995 (2000 census block-group based) -.80

PHUT Percentage of occupied housing units using utility gas (natural gas) as fuel (2000 census block-group 

based)

.78

PHLP Percentage of occupied housing units using liquid petroleum gas as fuel (2000 census block-group 

based)

-.78

PHWOOD Percentage of occupied housing units using wood as fuel (2000 census block-group based) -.90

HUDEN Density of housing units (housing units per square kilometer) (2000 cesnsus block-group based) .99

PPRURAL Proportion of population living in rural area (2000 census block-group based) -.92

PC_US Proportion of citizens born in United States (2000 census block-group based) -.81

PHU_G60 Proportion of housing units built prior to 1939 (2000 census block-group based) -.73

PPASIA Proportion of population of Asian ancestry (2000 census block-group based) .74

NLCD 2000 Land Cover/Land Use Variables

pNLCD1_2 Aggregated NLCD 2000 “level 1” category: developed (percentage of basin area) 0.98

pNLCD1_3 Aggregated NLCD 2000 “level 1” category: barren (includes all level 2 barren and unconsolidated 

categories) (percentage of basin area)

-.79

pNLCD1_4 Aggregated NLCD 2000 “level 1” category: forest (percentage of basin area) -.91

pNLCD1_5 Aggregated NLCD 2000 “level 1” category: shrubland (includes all level 2 shrub and scrub categories) 

(percentage of basin area)

-.85

NLCD_IS NLCD 2000 mean percent impervious surface .98

NLCD 2000 Riparian Buffer Variables

pNLCD1_B2 Buffer area in aggregated NLCD00 “level 1” category: developed (percentage of basin area) 0.97

pNLCD1_B3 Buffer area in aggregated NLCD 2000 “level 1” category: barren (includes all level 2 barren and 

unconsolidated categories) (percentage of basin area)

-.82

pNLCD1_B4 Buffer area in aggregated NLCD 2000 “level 1” category: forest (percentage of basin area) -.83

pNLCD1_B5 Buffer area in aggregated NLCD 2000 “level 1” category: shrubland (includes all level 2 shrub and 

scrub categories) (percentage of basin area)

-.87

NLCD_BIS NLCD 2000 mean percent impervious surface .97

Infrastructure Variables

ROADDEN Road density in watershed = [RDLENGTH (mi) / watershed area (mi2

)] 0.95

RDTRINDX Road traffic index in watershed (weighted miles): road traffic index i = SUM j (length ij * Veh_Traffic_

Wt ij) for watershed I and CFCC TIGER code j

.73

Table A2. Variables used to derive the final urban intensity index.

[Abbreviations: NLCD, National land cover data; mi, mile; mi2, square mile]
Appendix A 55

Description Variable code Definition

Urban intensity index UII See text of this report for defintion and full description

Percent impervious surface NLCD_IS NLCD 2001 mean percentage of impervious surface within watershed area (based on 

30 m resolution data)

POPDEN00 POPDEN00 2000 population density (people per square mile) (2000 census block based)

Percent urban + agriculture P_NLCD1_2+8 Aggregated P_NLCD 2001 level 1 category: developed (percentage of watershed) 

+ herbaceous planted/cultivated (percentage of watershed)

ROADDEN ROADDEN Road density in watershed = (RDLENGTH [kilometers] divided by watershed area 

[km2

])

Mean watershed elevation MEANELEV Mean watershed elevation (m)

Minimum watershed elevation MIN_ELEV Minimum watershed elevation (m)

Mean soil erodibility KFCAVE Mean soil erodibiity factor (K factor) including rock fragments (unitless)

Percent flat and low elevation 

land in basin

PFLATLOW Percentage of watershed area that is flat (slope less than 1 percent) and low (elevation 

less than midpoint)

Annual precipitation MAP Mean annual precipitation (based on 18 years of data) (cm)

Mean percent watershed slope SLOPE_X Mean watershed slope (percent)

Description Variable code Definition

Mean embeddedness 

(riffle and runs)

EmbedPctAvgRR Mean embeddedness (percent) for transects in riffle and run habitat only 

(excluding pool)

Mean width/depth ratio 

(riffle and runs)

WidthDepthAvgRR Mean wetted-channel width-depth ratio of transects in riffle and run habitat only 

(excluding pool)

Percent riffle habitat GCUTypeRiffPct Relative proportion of the total length of all geomorphic channel units that are 

comprised of riffles (percent)

Percent large substrate DomSub5-10Pct Percentage of occurrence of transect points where the dominant substrate 

consists of larger than coarse gravel particles (>16 mm)

Mean habitat heterogeneity stanRHH sumRHH = Reach Habitat Heterogeneity Index scaled to 0–10, sum of CV of 

Shape Index, CV velocity, and CV substrate

Description Variable code Definition

Number of falling events > 5×median 

(PeriodF5)

d_periodf5 Frequency of falling stream-discharge events, where hourly stream-discharge 

change is ≥5 multiplied by the median fall over POR (number of hourly 

periods)

Number of falling events > 9×median 

(PeriodF9)

d_periodf9 Frequency of falling stream-discharge events, where hourly stream-discharge 

change is ≥9 multiplied by the median fall over POR (number of hourly 

periods)

Number of rising events > 5×median 

(PeriodR5)

d_periodr5 Frequency of rising stream-discharge events, where hourly stream-discharge 

change is ≥5 multiplied by the median rise over POR (number of hourly 

periods)

Richards-Baker Flashiness Index 

(Rb-flash)

d_rb_flash Version of Richards-Baker Flashiness Index (Baker and others, 2004), 

calculated as the sum of the absolute value of the relative change in daily 

mean stream discharge, divided by the sum of the daily mean stream 

discharge for the POR (dimensionless)

Table A3. Watershed variables used in data analysis.

[See table A1 for data sources. Abbreviations: m, meter, km2, square kilometer; cm, centimeter]

Table A4. Reach-scale habitat variables.

[Abbreviations: mm, millimeter; CV, coefficient of variance. Symbol: >, greater than]

Table A5. Hydrologic variation metrics.

[Abbreviations: POR, period of record. Symbols: >, greater than; ≥, greater than or equal to]
56 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Description Variable code Definition

Seven day average temperature 7d_Ave_Temp Maximum of the 7 day moving average water temperature (ODEQ)

Minimum temperature

 (95th percentile)

t_pct_95n 95th-percentile stream-temperature value over period of record, divided by median streamtemperature value over period of record (dimensionless)

Description Variable code Definition

Instantaneous summer DO (mg/L) DISSOX Dissolved oxygen, water, unfiltered (mg/L)

Summer chlorophyll AFDM NAI National Water-Quality Assessment Program Autotrophic Index = chlorophyll a

(mg/m2

) divided by ash-free dry mass (g/m2)

Average dissolved organic carbon DISORGC Organic carbon, water, filtered (mg/L) average of spring and summer samplings

Specific conductance SPCOND Specific conductance, water, unfiltered (μS/cm)

Average total suspended sediment SUSSED Suspended sediment concentration (mg/L) average of spring and summer 

samplings

Average sulfate concentration SULFA Sulfate, water, filtered (mg/L) average of spring and summer samplings

Average total nitrogen TOTALN Total nitrogen, water, unfiltered (mg/L as N) average of spring and summer 

samplings

Average total phosphorus TOTALP Phosphorus, water, unfiltered (mg/L as P) average of spring and summer 

samplings

Total insecticides (spring + summer) NUMI Number of insecticides detected summed for spring and summer samplings

Total pesticides (spring + summer) NUMP Number of pesticides detected summed for spring and summer samplings

Pesticide Toxicity Index (spring + summer) PTIINV Pesticide Toxicity Index for benthic invertebrates summed for spring and summer 

samplings

TEQ (SPMD) SPMDTEQ SPMD toxicity, CYP1A1 production (toxic equivalents)

Pyrene Index (SPMD) SPMDUV SPMD toxicity, ultraviolet fluourescence (micrograms pyrene)

Description Variable code Definition

EPEM abundance EPEM Abundance of mayflies

EPEM richness EPEMR Richness composed of mayflies 

EPT/chironomid ratio EPT_CHR Ratio of EPT richness to midge richness

EPT richness EPTR Richness composed of mayflies, stoneflies, and caddisflies

PLECO percent PLECOp Percentage of total abundance composed of stoneflies

PLECO richness PLECOR Richness composed of stoneflies

Other diptera percent richness ODIPNIRp Percentage of total richness composed of non-midge Diptera and non-insects

Intolerant abundance Intol_abund Abundance-weighted USEPA tolerance value for intolerant taxa

Tolerant richness RICHTOL Average USEPA tolerance values for sample based on richness

Tolerant percent richness RICHTOLp Average USEPA tolerance values for sample based on percent richness

Tolerant abundance ABUNDTOL Abundence-weighted USEPA tolerance value for sample

Amphipod percent AMPHIp Percentage of total abundance composed of Amphipoda

Noninsect percent richness NONINSRp Percentage of total richness composed of noninsects

Oligochaet percent richness OLOGORp Percentage of total richness composed of Oligochaeta

nMDS Axis1 score nMDS axis 1 Axis 1 values from a bi-plot of 2-dimensional distribution based on multivariate similarities

Table A6. Stream temperature metrics.

[Abbreviation: ODEQ, Oregon Department of Environmental Quality]

Table A7. Water-chemistry variables.

[Abbreviations: DO, dissolved oxygen; N, nitrogen; P, phosphorus; SPMD, semipermeable membrane device; AFDM, ash-free dry mass; TEQ, toxic 

equivalent; mg/L, milligram per liter; mg/m2, milligram per square meter; μS/cm, microsiemens per centimeter at 25 degrees Celsius; g/mi2, gram per square 

meter]

Table A8. Invertebrate variables.

[Abbreviations: EPT, ephemeroptera, plecoptera, trichoptera (mayflies, stonefiles, caddisflies); EPEM, Ephemeropera; USEPA, U.S. Environmental Protection 

Agency; PLECO, Plecoptera; nMDS, non-metric dimensional scaling an ordination technique]
Appendix A 57

Scientific name Algal 

division

Number 

of sites

Maximum abundance

Density 

(number of 

cells/cm2

)

Biovolume 

(μm3

/cm2)

Achnanthes conspicua D 9 174,558 9,316,189

Achnanthes lanceolata var. 

haynaldii

D 8 7,178 2,078,098

Achnanthes ricula D 2 1,196 1,786,041

Achnanthes sp. 1 D 2 5,692 400,668

Achnanthes subhudsonis

var. kraeuselii

D 17 1,714,946 87,217,271

Achnanthidium exiguum

var. heterovalvum

D 2 1,276 142,871

Achnanthidium 

minutissimum

D 27 731,894 29,102,105

Achnanthidium pyrenaicum D 2 805 66,995

Achnanthidium sp. 10 D 18 526,964 44,451,564

Adlafia bryophila D 4 22,770 1,077,659

Adlafia sp. 2 D 1 1,196 136,376

Amphora copulata D 4 1,196 2,109,603

Amphora inariensis D 3 89,606 16,001,306

Amphora pediculus D 13 352,026 35,385,789

Anorthoneis excentrica D 1 66 497,890

Aphanocapsa sp. BG 1 3,776,737 94,418,425

Asterionella formosa D 3 598 247,697

Aulacoseira ambigua D 2 2,951 1,058,304

Aulacoseira crenulata D 7 58,114 34,735,559

Aulacoseira distans D 1 360 127,017

Aulacoseira granulata D 5 31,906 15,312,909

Aulacoseira italica D 1 360 298,628

Aulacoseira muzzanensis D 1 719 2,292,481

Bacillaria paradoxa D 5 33,602 39,311,265

Caloneis amphisbaena D 1 360 2,919,321

Caloneis bacillum D 4 8,374 3,757,193

Caloneis hyalina D 8 8,401 2,974,192

Caloneis schumanniana D 1 719 583,193

Caloneis silicula D 2 268 368,071

Calothrix fusca BG 1 48,528 12,433,455

Cladophora glomerata G 2 50,004 51,340,971,926

Cocconeis pediculus D 1 58 202,379

Cocconeis placentula D 1 2,517 1,861,795

Cocconeis placentula var. 

euglypta

D 25 164,655 130,032,466

Cocconeis placentula var. 

lineata

D 18 121,015 130,040,130

Cocconeis placentula var. 

pseudolineata

D 1 215 381,612

Ctenophora pulchella var. 

lacerata

D 2 700 6,031,252

Cyclostephanos tholiformis D 3 15,953 3,094,622

Cyclotella meneghiniana D 4 28,002 23,428,779

Cyclotella pseudostelligera D 2 2,551 217,556

Cyclotella stelligera D 1 268 65,023

Cymbella cymbiformis D 1 1,290 2,664,683

Cymbella mesiana D 2 9,686 20,770,780

Cymbella mexicana D 2 4,879 217,210,927

Table A9. List of algal taxa identified in Richest Target Habitat samples, Willamette River basin and surrounding area, Oregon and 

Washington.

[Algal taxa from 28 Richest Targeted Habitat (RTH) samples. Abbreviations: cm2, square centimeter; μm3/cm2, cubic micron per square centimeter; sp., species; 

var., variety; D, diatom; BG, blue-green algae; G, green algae; E, euglenophyte; R, red algae; aff., affinis (similar to); cf., confer (compare with)]

Scientific name Algal 

division

Number 

of sites

Maximum abundance

Density 

(number of 

cells/cm2

)

Biovolume 

(μm3

/cm2)

Cymbella sp. 1 D 1 2,198 4,075,979

Cymbella tumida D 1 5,692 16,095,195

Denticula tenuis D 1 598 303,256

Diadesmis confervacea D 3 78,406 27,045,903

Diadesmis contenta D 3 9,686 340,549

Diatoma vulgaris D 2 95,718 286,082,017

Diploneis elliptica D 2 334 622,325

Diploneis parma D 2 8,728 12,167,326

Diploneis pseudovalis D 1 360 308,851

Encyonema minutum D 7 108,157 22,377,969

Encyonema prostratum D 1 15,953 29,576,818

Encyonema silesiacum D 11 267,546 91,228,617

Eunotia exigua D 4 1,543 258,799

Eunotia flexuosa D 3 4,843 14,241,971

Eunotia formica D 1 37 283,292

Eunotia incisa D 1 805 299,498

Eunotia minor D 6 24,510 12,949,517

Eunotia monodon D 1 719 1,575,396

Eunotia muscicola var. 

tridentula

D 1 268 150,230

Eunotia pectinalis var. 

undulata

D 1 9,686 28,244,330

Eunotia pirla D 1 5,692 18,099,135

Eunotia praerupta D 1 134 462,764

Fallacia tenera D 1 1,196 8,973,273

Fragilaria capucina var. 

gracilis

D 6 45,540 3,312,529

Fragilaria capucina var. 

rumpens

D 3 360 40,537

Fragilaria cf. crotonensis D 4 63,431 54,360,226

Fragilaria crotonensis D 1 117 49,676

Fragilaria nanana D 1 58 6,056

Fragilaria sp. 7 D 2 15,953 5,341,112

Fragilaria vaucheriae D 7 23,929 5,149,988

Fragilariforma bicapitata D 1 4,843 4,150,282

Fragilariforma virescens D 1 37 31,945

Frustulia amphipleuroides D 1 4,879 27,566,671

Frustulia crassinervia D 1 537 230,454

Frustulia rhomboides D 1 37 131,964

Frustulia vulgaris D 6 24,510 21,310,568

Frustulia weinholdii D 1 9,804 27,001,994

Geissleria acceptata D 3 5,819 4,579,240

Gomphoneis eriense var. 

variabilis

D 1 20,585 628,550,203

Gomphoneis herculeana D 1 430 2,884,920

Gomphoneis minuta D 1 9,501 290,100,101

Gomphonema aff. 

Kobayasii

D 19 222,006 1,585,057

Gomphonema affine D 5 22,770 28,562,881

Gomphonema 

americobtusatum

D 3 334 435,107

Gomphonema angustatum D 11 24,396 7,340,544
58 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Scientific name Algal 

division

Number 

of sites

Maximum abundance

Density 

(number of 

cells/cm2

)

Biovolume 

(μm3

/cm2)

Gomphonema bipunctatum D 1 360 468,093

Gomphonema 

drutelingense

D 1 1,609 2,095,005

Gomphonema gracile D 4 15,953 16,744,119

Gomphonema innocens D 3 56,925 32,754,489

Gomphonema kobayasii D 21 251,015 36,550,747

Gomphonema lagenula D 13 23,929 6,231,043

Gomphonema mexicanum D 2 2,682 2,889,033

Gomphonema micropus D 3 4,902 1,445,550

Gomphonema minutum D 3 2,909 509,968

Gomphonema parvulius D 1 5,600 7,291,720

Gomphonema parvulum D 5 31,906 7,953,419

Gomphonema parvulum 

var. saprophilum

D 1 719 936,186

Gomphonema patrickii D 1 537 143,654

Gomphonema pumilum D 1 2,683 598,872

Gomphonema rhombicum D 17 136,619 62,448,261

Gomphonema sp. 2 D 4 775,808 282,880,603

Gomphonema sp. 3 D 1 37 48,533

Gomphonema subclavatum D 1 360 239,466

Gomphosphenia 

lingulatiformis

D 1 22,729 10,921,783

Gyrosigma acuminatum D 1 202 1,418,469

Gyrosigma nodiferum D 1 4,843 18,880,003

Gyrosigma scalproides D 1 2,451 3,591,376

Hantzschia amphioxys D 3 598 664,160

Heteroleibleinia sp. BG 1 251,348 2,149,644

Hippodonta capitata D 4 9,804 3,297,494

Homoeothrix janthina BG 21 11,854,144 43,235,144

Homoeothrix juliana BG 4 979,535 51,670,281

Karayevia clevei D 2 360 58,612

Karayevia laterostrata D 1 771 1,151,596

Leptolyngbya sp. BG 9 9,510,686 30,054,496

Luticola goeppertiana D 1 16,801 12,950,671

Luticola mutica D 2 719 421,950

Mayamaea atomus D 2 15,953 514,641

Melosira varians D 16 250,469 1,231,832,428

Meridion circulare var. 

constrictum

D 4 5,600 1,492,472

Merismopedia glauca BG 1 643,866 12,034,106

Navicula absoluta D 1 4,187 998,760

Navicula antonii D 9 31,906 4,776,375

Navicula arvensis D 1 719 43,775

Navicula capitatoradiata D 2 1,196 672,127

Navicula concentrica D 8 55,835 34,511,814

Navicula constans var. 

symmetrica

D 1 360 386,180

Navicula cryptocephala D 10 34,314 11,320,621

Navicula cryptotenella D 17 68,310 16,471,200

Navicula germainii D 4 39,203 17,499,767

Navicula gregaria D 11 12,255 3,225,920

Navicula hintzii D 1 5,981 1,733,616

Scientific name Algal 

division

Number 

of sites

Maximum abundance

Density 

(number of 

cells/cm2

)

Biovolume 

(μm3

/cm2)

Navicula ingenua D 2 2,991 129,566

Navicula integra D 1 3,015 1,241,277

Navicula kotschyi D 1 268 62,799

Navicula lanceolata D 10 15,953 23,134,226

Navicula menisculus D 4 1,414 534,228

Navicula minima D 21 313,086 12,682,552

Navicula mobiliensis var. 

minor

D 1 7,353 15,569,915

Navicula peregrina D 1 101 346,236

Navicula pseudotenelloides D 1 22,402 1,201,442

Navicula radiosa D 1 37 41,391

Navicula recens D 1 1,543 777,048

Navicula reichardtiana D 1 1,720 207,842

Navicula reinhardtii D 1 112 297,952

Navicula rhynchocephala D 1 771 551,936

Navicula rostellata D 3 11,201 8,958,057

Navicula ruttnerii var. 

capitata

D 2 7,178 640,216

Navicula schroeteri var. 

escambia

D 12 66,177 48,109,997

Navicula sp. 44 D 1 3,167 3,042,572

Navicula sp. 47 D 1 6,334 334,297

Navicula subadnata D 1 133 995,781

Navicula subminuscula D 3 31,906 2,050,933

Navicula tenelloides D 6 9,686 1,218,147

Navicula tripunctata D 7 9,316 8,675,142

Navicula trivialis D 4 5,393 3,898,691

Navicula veneta D 2 1,196 200,083

Navicula viridulacalcis D 2 1,794 13,459,929

Navicula wallacei D 1 268 97,606

Nitzschia acidoclinata D 2 489 5,728,823

Nitzschia agnita D 1 15,953 1,459,116

Nitzschia amphibia D 18 624,722 121,686,962

Nitzschia angustata D 1 1,196 6,291,970

Nitzschia archibaldii D 1 15,953 997,034

Nitzschia brevissima D 1 805 337,018

Nitzschia capitellata D 5 9,804 3,673,000

Nitzschia dissipata D 17 239,295 59,895,837

Nitzschia filiformis D 1 2,800 2,172,325

Nitzschia fonticola D 16 199,412 18,979,964

Nitzschia fossilis D 1 2,393 28,026,405

Nitzschia gracilis D 2 1,196 432,220

Nitzschia heufleriana D 5 2,991 14,712,836

Nitzschia inconspicua D 17 311,083 9,212,723

Nitzschia intermedia D 2 1,196 828,511

Nitzschia liebethruthii D 1 1,276 114,439

Nitzschia linearis D 3 17,456 47,656,820

Nitzschia linearis var. 

subtilis

D 3 2,451 1,941,599

Nitzschia palea D 10 12,255 3,233,473

Nitzschia palea var. debilis D 6 19,517 2,887,687

Nitzschia perminuta D 1 101 9,803

Table A9. List of algal taxa identified in Richest Target Habitat samples, Willamette River basin and surrounding area, Oregon and 

Washington.—Continued

[Algal taxa from 28 Richest Targeted Habitat (RTH) samples. Abbreviations: cm2, square centimeter; μm3/cm2, cubic micron per square centimeter; sp., species; 

var., variety; D, diatom; BG, blue-green algae; G, green algae; E, euglenophyte; R, red algae; aff., affinis (similar to); cf., confer (compare with)]
Appendix A 59

Table A9. List of algal taxa identified in Richest Target Habitat samples, Willamette River basin and surrounding area, Oregon and 

Washington.—Continued

[Algal taxa from 28 Richest Targeted Habitat (RTH) samples. Abbreviations: cm2, square centimeter; μm3/cm2, cubic micron per square centimeter; sp., species; 

var., variety; D, diatom; BG, blue-green algae; G, green algae; E, euglenophyte; R, red algae; aff., affinis (similar to); cf., confer (compare with)]

Scientific name Algal 

division

Number 

of sites

Maximum abundance

Density 

(number of 

cells/cm2

)

Biovolume 

(μm3

/cm2)

Nitzschia radicula D 1 9,686 113,457,180

Nitzschia recta D 7 15,953 28,511,891

Nitzschia sigmoidea D 13 24,214 64,554,667

Nitzschia sociabilis D 6 39,216 8,558,069

Nitzschia solita D 1 5,600 1,066,901

Nitzschia tubicola D 1 1,276 288,948

Nitzschia vermicularis D 1 11,201 51,243,212

Nupela silvahercynia D 2 16,198 121,500,890

Nupela sp. 1 D 3 202,089 2,241,256

Nupela wellneri D 1 1,196 8,973,273

Oedogonium sp. G 6 56,756 1,132,047,129

Oscillatoria princeps BG 1 4,897,853 358,250,872

Pandorina morum G 1 32,885 2,795,192

Parlibellus protracta D 1 37 33,772

Phormidium autumnale BG 16 4,011,385 188,628,500

Phormidium retzii BG 3 150,011 22,207,813

Pinnularia divergens D 4 207 1,552,878

Pinnularia microstauron D 4 4,902 5,905,940

Pinnularia sudetica D 1 638 2,370,394

Pinnularia viridis D 1 1,079 5,906,620

Placoneis elginensis D 1 1,438 759,305

Planothidium delicatulum D 1 1,196 368,248

Planothidium 

frequentissimum

D 20 86,806 6,694,362

Planothidium lanceolatum D 22 215,365 53,446,394

Planothidium rostratum D 7 4,843 576,598

Porphyrosiphon luteus BG 1 1,029,009 25,725,232

Porphyrosiphon 

martensianus

BG 6 3,316,956 357,276,740

Psammothidium 

lauenburgianum

D 1 5,819 8,687,172

Pseudanabaena sp. BG 8 533,669 1,387,073

Reimeria sinuata D 18 91,080 15,338,294

Rhoicosphenia abbreviata D 25 726,420 307,435,607

Rhopalodia gibba D 1 1,196 7,244,122

Scenedesmus acutus G 1 13,354 432,707

Scenedesmus denticulatus G 1 49,219 1,000,115

Scenedesmus ecornis G 2 30,002 744,477

Scenedesmus quadricauda G 2 30,002 988,363

Sellaphora laevissima D 2 805 895,327

Sellaphora pupula D 8 16,801 7,770,995

Scientific name Algal 

division

Number 

of sites

Maximum abundance

Density 

(number of 

cells/cm2

)

Biovolume 

(μm3

/cm2)

Sellaphora seminulum D 21 143,577 486,913,494

Simonsenia delognei D 4 8,728 456,124

Spirogyra sp. G 1 10,016 808,152,137

Stauroneis kriegeri D 4 805 124,252

Stauroneis phoenicenteron D 1 207 11,516,940

Staurosira construens D 2 11,385 2,379,854

Staurosira construens var. 

binodis

D 2 137,210 68,470,231

Staurosira construens var. 

subsalina

D 1 11,201 3,170,875

Staurosira construens var. 

venter

D 4 106,542 9,569,688

Staurosira elliptica D 1 117 5,501

Staurosirella pinnata D 1 62,956 10,134,217

Stephanodiscus hantzschii D 1 360 115,171

Stephanodiscus minutulus D 1 202 58,697

Stigeoclonium lubricum G 1 213,468 84,043,977

Surirella amphioxys D 1 360 384,625,288

Surirella angusta D 6 5,600 6,141,920

Surirella biseriata D 2 5,600 89,695,680

Surirella brebissonii var. 

kuetzingii

D 4 11,637 11,901,456

Synedra acus D 2 2,909 4,921,361

Synedra parasitica D 6 52,367 4,721,265

Synedra parasitica var. 

subconstricta

D 2 1,276 126,279

Synedra ulna D 16 22,402 124,196,962

Tabellaria flocculosa D 1 268 121,629

Thalassiosira pseudonana D 3 15,953 763,341

Trachelomonas volvocina E 2 5,930 8,715,732

Tryblionella apiculata D 2 5,600 2,114,415

Tryblionella calida D 2 5,600 6,062,124

Tryblionella debilis D 1 4,902 1,807,780

Tryblionella victoriae D 1 268 3,142,500

Unknown Cyanophyte 

(colonial coccoid)

BG 8 113,512 143,431,520

Unknown Cyanophyte 

(colonial coccoid) 

BG 1 6,180,652 2,697,679,030

Unknown Rhodophyte 

Florideophycidae 

(chantransia) 

R 25 2,442,559 1,174,999,542
60 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Table A10. Macroinvertebrate species list sorted alphabetically by scientific name, order, number of sites collected (richest target 

habitat samples) and maxmum abundance among all 28 sites, Willamette River basin and surrounding area, Oregon and Washington.

[Abbreviation: sp., species]

Scientific name Order Number 

of sites

Maximum 

abundance

Ablabesmyia sp. Diptera 1 41

Acari Phylum Arthopoda 27 988

Acentrella turbida Ephemeroptera 8 1,455

Ampumixis dispar Coleoptera 1 54

Anisogammarus sp. Amphipoda 4 536

Anopheles sp. Diptera 1 20

Antocha sp. Diptera 4 141

Arctopsyche grandis Trichoptera 1 1

Argia sp. Odonata 5 90

Atherix pachypus Diptera 1 16

Baetis tricaudatus Ephemeroptera 23 3,082

Brillia sp. Diptera 11 86

Bryozoa Phylum 1 6

Caecidotea sp. Isopoda 8 877

Caenis sp. Ephemeroptera 1 64

Calineuria californica Plecoptera 11 228

Capniidae Plecoptera 1 31

Cardiocladius sp. Diptera 2 260

Ceratopogonidae Diptera 1 54

Ceratopsyche cockerelli Trichoptera 14 2,904

Chelifera/Metachela sp. Diptera 3 141

Cheumatopsyche sp. Trichoptera 19 3,467

Chironomus sp. Diptera 1 64

Cleptelmis addenda Coleoptera 5 323

Collembola Collembola 2 32

Corbicula sp. Veneroida 3 282

Corynoneura sp. Diptera 4 30

Crangonyx sp. Amphipoda 15 661

Cricotopus bicinctus 

group

Diptera 16 3,303

Cryptochironomus sp. Diptera 2 64

Cryptotendipes sp. Diptera 1 31

Culex sp. Diptera 1 64

Curculionidae Coleoptera 1 16

Dero sp. Tubificida 22 2,123

Dicosmoecus gilvipes Trichoptera 5 57

Dicranota sp. Diptera 2 27

Dicrotendipes sp. Diptera 3 153

Diphetor hageni Ephemeroptera 6 56

Diplocladius cultriger Diptera 2 387

Dixa sp. Diptera 1 32

Drunella doddsi Ephemeroptera 4 257

Drunella grandis Ephemeroptera 1 65

Enchytraeidae Enchytraeida 2 371

Epeorus sp. Ephemeroptera 1 556

Ephemerella sp. Ephemeroptera 1 23

Eukiefferiella sp. Diptera 16 864

Eukiefferiella/Tvetenia 

sp.

Diptera 1 23

Ferrissia sp. Basommatophora 16 790

Fluminicola sp. Mesogastropoda 15 11,419

Glossosoma sp. Trichoptera 5 484

Glyptotendipes sp. Diptera 1 64

Scientific name Order Number 

of sites

Maximum 

abundance

Gomphidae Odonata 2 113

Hemerodromia sp. Diptera 7 80

Hesperoperla pacifica Plecoptera 9 94

Heterlimnius sp. Coleoptera 1 17

Hexatoma sp. Diptera 1 32

Hyalella azteca Amphipoda 2 1,401

Hydra sp. Hydroida 1 32

Hydropsyche sp. Trichoptera 2 211

Hydroptila sp. Trichoptera 3 61

Ironodes sp. Ephemeroptera 4 145

Juga sp. Mesogastropoda 25 3,870

Lara sp. Coleoptera 9 147

Lepidoptera Lepidoptera 1 64

Lepidostoma sp. Trichoptera 5 78

Leptohyphidae Ephemeroptera 1 97

Leucotrichia pictipes Trichoptera 1 269

Limnophyes sp. Diptera 4 121

Lumbriculidae Lumbriculida 20 581

Malenka sp. Plecoptera 6 134

Margaritifera falcata Paleoheterodonta 4 2

Megadrile Class Oligochaeta 12 194

Menetus sp. Basommatophora 5 107

Micrasema sp. Trichoptera 4 134

Micropsectra sp. Diptera 8 311

Micropsectra/Tanytarsus 

sp.

Diptera 13 933

Microtendipes sp. Diptera 2 15

Nanocladius sp. Diptera 3 27

Narpus sp. Coleoptera 4 81

Nematoda Phylum 12 107

Nematomorpha Phylum 1 1

Neophylax sp. Trichoptera 2 2

Neoplasta sp. Diptera 2 80

Onocosmoecus sp. Trichoptera 1 1

Optioservus sp. Coleoptera 16 1,349

Ordobrevia nubifera Coleoptera 2 97

Pacifastacus leniusculus Decapoda 15 20

Parakiefferiella sp. Diptera 1 11

Paraleptophlebia sp. Ephemeroptera 19 672

Paramerina sp. Diptera 2 22

Parametriocnemus sp. Diptera 13 671

Paraphaenocladius sp. Diptera 1 13

Paratanytarsus sp. Diptera 9 541

Pericoma/Telmatoscopus 

sp.

Diptera 1 27

Perlinodes aureus Plecoptera 1 270

Phaenopsectra sp. Diptera 5 130

Physa sp. Basommatophora 5 82

Pisidium sp. Veneroida 12 222

Polypedilum sp. Diptera 19 307

Porifera Phylum 1 6

Prostoma sp. Hoplonemertea 9 40

Psephenus falli Coleoptera 1 1,322
Appendix A 61

Scientific name Order Number 

of sites

Maximum 

abundance

Pseudocloeon sp. Ephemeroptera 1 80

Psychomyia sp. Trichoptera 1 16

Pteronarcella sp. Plecoptera 1 27

Pteronarcys californica Plecoptera 4 33

Rheocricotopus sp. Diptera 5 32

Rheotanytarsus sp. Diptera 16 1,050

Rhithrogena sp. Ephemeroptera 15 3,057

Rhyacophila betteni 

group

Trichoptera 12 323

Rhyacophila hyalinata 

group

Trichoptera 1 188

Rhyacophila sibirica 

group

Trichoptera 1 105

Rhyacophila vedra Trichoptera 5 39

Sialis sp. Megaloptera 5 40

Simulium arcticum 

complex

Diptera 1 776

Simulium canadense Diptera 27 12,306

Skwala sp. Plecoptera 5 215

Sphaerium sp. Veneroida 1 484

Staphylinidae Coleoptera 1 16

Table A10. Macroinvertebrate species list sorted alphabetically by scientific name, order, number of sites collected (richest target 

habitat samples) and maximum abundance among all 28 sites, Willamette River basin and surrounding area, Oregon and Washington.—

Continued

[Abbreviation: sp., species]

Scientific name Order Number 

of sites

Maximum 

abundance

Stempellinella sp. Diptera 3 820

Stenochironomus sp. Diptera 2 23

Sublettea coffmani Diptera 2 315

Sweltsa sp. Plecoptera 13 501

Synorthocladius sp. Diptera 2 15

Tanytarsus sp. Diptera 7 113

Thienemanniella sp. Diptera 9 97

Thienemannimyia group Diptera 17 451

Tipula sp. Diptera 2 28

Tribelos sp. Diptera 1 8

Tubificidae Tubificida 15 2,129

Turbellaria Class 7 387

Tvetenia sp. Diptera 6 241

Unionacea Paleoheterodonta 1 23

Wormaldia gabriella Trichoptera 4 419

Xenochironomus 

xenolabis

Diptera 2 64

Zaitzevia parvula Coleoptera 12 885

Zaitzevia posthonia Coleoptera 2 101

Zapada cinctipes Plecoptera 16 4,081
62 Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington

Order Family Scientific 

name

Common 

name

Native or 

nonnative

Number 

of sites

Maximum 

abundance

Petromyzontiformes Petromyzontidae Lampetra richardsoni western brook lamprey Native 16 4

Petromyzontiformes Petromyzontidae Lampetra tridentata Pacific lamprey Native 2 1

Atheriniformes Poeciliidae Gambusia affinis western mosquitofish Nonnative 2 36

Cypriniformes Catostomidae Catostomus macrocheilus largescale sucker Native 10 13

Cypriniformes Cyprinidae Cyprinus carpio common carp Nonnative 1 8

Cypriniformes Cyprinidae Ptychocheilus oregonensis northern squawfish Native 6 5

Cypriniformes Cyprinidae Rhinichthys cataractae longnose dace Native 6 12

Cypriniformes Cyprinidae Rhinichthys osculus speckled dace Native 20 55

Cypriniformes Cyprinidae Richardsonius balteatus redside shiner Native 18 105

Gasterosteiformes Gasterosteidae Gasterosteus aculeatus threespine stickleback Native 1 1

Perciformes Centrarchidae Ambloplites rupestris rock bass Nonnative 1 1

Perciformes Centrarchidae Lepomis gibbosus pumpkinseed Nonnative 5 6

Perciformes Centrarchidae Lepomis macrochirus bluegill Nonnative 1 42

Perciformes Centrarchidae Micropterus salmoides largemouth bass Nonnative 4 536

Perciformes Centrarchidae Pomoxis annularis white crappie Nonnative 2 2

Percopsiformes Percopsidae Percopsis transmontana sand roller Native 2 4

Salmoniformes Salmonidae Oncorhynchus clarki cutthroat trout Native 14 47

Salmoniformes Salmonidae Oncorhynchus kisutch coho salmon Native 11 96

Salmoniformes Salmonidae Oncorhynchus mykiss rainbow trout Native 9 121

Scorpaeniformes Cottidae Cottus asper prickly sculpin Native 3 9

Scorpaeniformes Cottidae Cottus beldingi Paiute sculpin Native 3 51

Scorpaeniformes Cottidae Cottus perplexus reticulate sculpin Native 28 532

Scorpaeniformes Cottidae Cottus rhotheus torrent sculpin Native 15 157

Siluriformes Ictaluridae Ameiurus melas black bullhead Nonnative 1 1

Siluriformes Ictaluridae Ameiurus natalis yellow bullhead Nonnative 1 2

Siluriformes Ictaluridae Ameiurus nebulosus brown bullhead Nonnative 2 8

Table A11. Fish species list sorted by Order, Family, and scientific name, fish common name, native or nonnative species, number of 

sites collected and maximum abundance among all 28 sites, Willamette River basin and surrounding area, Oregon and Washington.
Manuscript approved for publication, July 1, 2008

Prepared by the USGS Publishing Network

Bill Gibbs 

Bob Crist

Debra Grillo

Bobbie Richey

Sharon Wahlstrom

For more information concerning the research in this report, contact the 

Director, Oregon Water Science Center

U.S. Geological Survey 

2130 SW 5th Avenue

Portland, Oregon 97201

http://oregon.usgs.gov/
Waite and others—Effects of Urbanization on Stream Ecosystems, Willamette River Basin, Oregon and Washington—Scientific Investigations Report 2006-5101-D