EPA/600/R-06/065F 

 December 2007 

Causal Analysis of Biological Impairment 

in Long Creek: 

A Sandy-Bottomed Stream in Coastal 

Southern Maine 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 20460
DISCLAIMER 

This document has been reviewed in accordance with U.S. Environmental Protection 

Agency policy and approved for publication. Mention of trade names or commercial products 

does not constitute endorsement or recommendation for use. 

ABSTRACT 

This case study presents results from a complex causal assessment of a biologically 

impaired, urbanized coastal watershed located primarily in South Portland, Maine, USA—the 

Long Creek watershed. This assessment serves as an example implementation of U.S. 

Environmental Protection Agency Stressor Identification guidance. Four specific biological 

effects defining impairment and seven candidate causes of impairment were chosen and 

evaluated at three impaired sites along Long Creek. Biological effects include (1) decreased 

Ephemeroptera, Plecoptera, and Trichoptera (EPT) generic richness, (2) increased percent noninsect taxa individuals relative to total macroinvertebrate abundance, (3) increased Hilsenhoff 

Biotic Index (HBI) score, and (4) brook trout absence. Decreased dissolved oxygen, altered flow 

regime, decreased large woody debris, increased temperature, and increased toxicity due to ionic 

strength were identified as probable causes of impairment. The implications associated with 

interactions among probable causes are discussed in terms of this case study and causal 

assessment in general. 

ii 
TABLE OF CONTENTS 

LIST OF TABLES...........................................................................................................................v 

LIST OF FIGURES .........................................................................................................................v 

LIST OF ABBREVIATIONS AND ACRONYMS ...................................................................... vi 

FOREWARD..... ... ...................................................................................................................... vii 

PREFACE................................................................................................................................. viii 

AUTHORS, CONTRIBUTORS, AND REVIEWERS ................................................................. ix 

EXECUTIVE SUMMARY ........................................................................................................... xi 

1. INTRODUCTION .....................................................................................................................1 

 1.1. BACKGROUND.............................................................................................................2 

 1.1.1. Study Area Description .......................................................................................2 

 1.1.2. Historical Land Use.............................................................................................7 

 1.2. MAINE’S REGULATORY PROGRAM .......................................................................7 

 1.3. TRIGGER FOR CAUSAL ANALYSIS .........................................................................8 

 1.4. REPORT FORMAT ......................................................................................................10 

2. BIOLOGICAL IMPAIRMENT...............................................................................................11 

 2.1. ANALYSIS ...................................................................................................................11 

 2.1.1. Rockbag Sampling Data....................................................................................11 

 2.1.2. Maine’s Linear Discriminant Function Model..................................................12 

 2.2. SITE-SPECIFIC DESCRIPTIONS AND BIOLOGICAL CONSIDERATIONS ........13 

 2.2.1. RB 3.961 (reference site)...................................................................................13 

 2.2.2. LCN .415 (impaired site)...................................................................................13 

 2.2.3. LCM 2.270 (impaired site)................................................................................15 

 2.2.4. LCMn 2.274 (impaired site)..............................................................................15 

 2.3. APPLICATION TO CAUSAL ANALYSIS.................................................................15 

3. STRESSOR IDENTIFICATION.............................................................................................17 

 3.1. CANDIDATE CAUSES ...............................................................................................17 

 3.2. ANALYSIS OF CAUSES.............................................................................................18 

 3.2.1. Evidence that Uses Data from the Case ............................................................22 

 3.2.2. Evidence that Uses Data from Elsewhere .........................................................26 

 3.2.3. Evaluation of Multiple Types of Evidence........................................................31 

 3.2.4. Additional Evidence within the Case Study Watersheds ..................................32 

4. CONCLUSIONS......................................................................................................................34 

4.1. FINDINGS CONSISTENT ACROSS ALL THREE SITES ........................................34 

 4.2. FINDINGS PARTICULAR TO INDIVIDUAL SITES ...............................................37 

 4.3. ENDPOINT SPECIFIC FINDINGS .............................................................................41 

 4.4. SUMMARY CONCLUSIONS .....................................................................................43 

 

5. DISCUSSION..........................................................................................................................45 

5.1. INTERACTING URBAN STRESSORS & CAUSAL ASSESSMENT ......................45 

 5.1.1. Decreased Dissolved Oxygen and Altered Flow Regime .................................45 

 5.1.2. Increased Temperature and Decreased Dissolved Oxygen ...............................46 

iii 
TABLE OF CONTENTS (continued) 

5.1.3. Other Potential Interactions...............................................................................47 

 5.1.4. Negotiating Causal Interactions ........................................................................50 

5.2. CONFIDENCE IN CONCLUSIONS ...........................................................................55 

 5.2.1. Case-specific Data and Research Needs ...........................................................56 

 5.2.2. Research Needed to Understand Case-specific Data ........................................56 

6. LESSONS LEARNED.............................................................................................................58 

6.1. UNEVEN EVIDENCE — ADDRESS POTENTIAL BIASES....................................58 

6.2. BIOLOGICAL ENDPOINTS — CHOOSE SIMPLER MEASURES .........................58 

6.3. MULTI-STAGE CAUSAL ANALYSIS — STRATEGIZE IN ADVANCE ..............59 

CONCEPTUAL MODEL FIGURES ............................................................................................60 

STRENGTH-OF-EVIDENCE (SOE) TABLES............................................................................71 

APPENDIX A – HISTORIC MAPS...............................................................................................A 

APPENDIX B – MAINE’S WATER QUALITY CLASSIFICATION LAW...............................B 

APPENDIX C – MACROINVERTEBRATE ROCKBAG SAMPLING DATA ..........................C 

APPENDIX D – MAINE’S LINEAR DISCRIMINANT FUNCTION MODEL VARIABLES...D 

APPENDIX E – REGIONAL REFERENCE ANALYSIS ............................................................E 

APPENDIX F – CAUSAL DESCRIPTIONS, BASIC INTERACTIONS, AND SOURCES....... F 

APPENDIX G – MEASURED VARIABLES ...............................................................................G 

APPENDIX H – SCATTER PLOTS (S-R from the field).............................................................H 

APPENDIX I – SPECIES SENSITIVITY DISTRIBUTIONS (S-R from elsewhere).................... I 

APPENDIX J – SPECIFIC CONDUCTIVITY DATA FROM OTHER STATES ........................J 

REFERENCES ............................................................................................................................R 

iv 
LIST OF TABLES 

1. Watershed land use .................................................................................................................4 

2. Project site description and classification...............................................................................9 

3. Observed specific biological effects.....................................................................................12 

4. Dominant invertebrate taxa from rockbag samples ..............................................................14 

5. Measured variables relevant to each candidate cause...........................................................19 

6. Applicable types of evidence ................................................................................................20 

7. Spatial/temporal co-occurrence data summary.....................................................................23 

8. Unique findings by candidate cause and site ........................................................................39 

9. Probable causes of impairment .............................................................................................44

LIST OF FIGURES 

1. Project location map ...............................................................................................................1 

2. Elevation model of study watersheds .....................................................................................3 

3. Land use map ..........................................................................................................................5 

4. Impervious surface and project site locations.........................................................................6 

5. Caddisflies and large woody debris under water at reference site, RB 3.961 ......................28 

6. Maine stream mayfly abundance versus specific conductivity.............................................38 

7. Relative organism abundance versus specific conductivity at project site...........................42 

8. Impact of low dissolved oxygen and low current velocity on selected organisms...............46 

9. Dissolved oxygen versus temperature at project site............................................................48 

10. Oxygen solubility versus temperature at various salinities...................................................48 

11. Temperature versus specific conductivity at project site......................................................49 

12. Dissolved oxygen versus specific conductivity at project site..............................................49 

13. Storm hydrographs on Long Creek and Red Brook, September 25, 2001 ...........................52 

14. Baseflow thalweg velocity measurements throughout project site.......................................53 

15. Specific conductivity versus impervious area at project site ................................................54 

16. Specific conductivity versus chloride at project site.............................................................54 

17. Temperature versus impervious area at project site..............................................................57 

v 
LIST OF ABBREVIATIONS AND ACRONYMS 

CADDIS Causal Analysis/Diagnosis Decision Information System 

CCC criterion continuous concentration (chronic) 

CI confidence interval 

CMC criteria maximum concentration (acute) 

Cu copper 

CWA Clean Water Act 

ECOTOX ECOTOXicology database (U.S. EPA) 

EPT Ephemeroptera, Plecoptera, and Trichoptera 

FPOM fine particulate organic matter 

GIS geographic information system 

HBI Hilsenhoff Biotic Index 

LC50 lethal concentration, causing death in 50% of population 

LDF linear discriminant function 

LWD large woody debris 

MEDEP Maine Department of Environmental Protection 

N/A not applicable 

NCEA National Center for Environmental Assessment 

ND not detected 

NE no evidence 

NOAA National Oceanic and Atmospheric Administration 

ORD Office of Research and Development 

PAH polycyclic aromatic hydrocarbon 

Pb lead 

PCB polychlorinated biphenyl 

PPM parts per million 

PTIA percent total impervious surface area 

RBP Rapid Bioassessment Protocol 

RL reporting limit 

SOE strength-of-evidence 

S-R stressor-response 

SSD species sensitivity distribution 

ST see text 

TMDL Total Maximum Daily Load 

TSS total suspended solids 

USGS United States Geological Survey 

WQC water quality criteria 

WQS water quality standard 

vi 
FOREWORD 

The National Center for Environmental Assessment (NCEA) provides this case study as 

an example implementation of U.S. EPA’s Stressor Identification process, as presented online at 

the Causal Analysis / Diagnosis Decision Information System (CADDIS) Web site, 

http://www.epa.gov/caddis. The Long Creek case study provided U.S. EPA an opportunity to 

collaborate with the State of Maine and its Department of Environmental Protection. We hope 

this collaborative effort serves as a foundation for improving Long Creek’s ecological condition, 

and imparts a rudimentary understanding of EPA’s Stressor Identification process to Maine 

biologists and environmental managers. 

The work herein represents a rigorous adherence to EPA’s Stressor Identification 

guidance. Such a detailed approach may not be appropriate for all case studies; causal assessors 

should approach this type of analysis on a case by case basis. However, by pushing the bounds 

of EPA’s Stressor Identification guidance with this case study, two points are worth noting: 1), 

we have fine tuned the on-line version of the guidance found at the CADDIS Web site, and 2) 

this report presents a wide range of causal assessment issues and opportunities that may arise in 

any given case study. 

Michael Slimak 

Associate Director of Ecology 

National Center for Environmental Assessment, US EPA 

vii 
PREFACE

U.S. EPA’s National Center for Environmental Assessment, Maine Department of 

Environmental Protection, and Partnership for Environmental Technology Education authored 

this report jointly, with substantial contribution and constructive critique from U.S. EPA’s Office 

of Research and Development and external peer reviewers. The report is intended for risk 

assessors, field biologists, research scientists, and environmental managers interested in learning 

the process and potential of U.S. EPA’s Stressor Identification guidance 

(http://www.epa.gov/caddis/ and U.S. EPA, 2000a) by example. 

The report is a causal assessment case study of a biologically impaired, urbanized coastal 

watershed located in Maine, USA. In accordance with U.S. EPA’s Stressor Identification 

protocol, the report defines biological impairment, discusses candidate causes of impairment, and 

walks through a strength-of-evidence approach to identify probable causes. The last two 

chapters of the report discuss stressor interactions—in terms of general causal assessment and 

this case study specifically—and lessons learned upon case study completion that might be 

applied to future causal assessments. 

The Clean Water Act (CWA) requires states to develop TMDLs for waters when current 

pollution controls are not stringent enough to attain or maintain compliance with adopted water 

quality standards. Maine’s 1998 list of impaired water bodies includes Long Creek, the focus of 

the case study, and U.S. EPA chose the Long Creek watershed for study under CWA funding in 

early 1999. 

The case study project team completed the majority of literature review for this report in 

2005. Readers are encouraged to visit U.S. EPA’s CADDIS (Causal Analysis/Diagnosis 

Decision Information System) Web site for state of the art causal assessment information and 

references (http://www.epa.gov/caddis/). 

viii 
AUTHORS, CONTRIBUTORS, AND REVIEWERS 

This document was prepared by U.S. EPA’s Office of Research and Development, Maine 

Department of Environmental Protection, and Partnership for Environmental Technology 

Education. U.S. EPA’s National Center for Environmental Assessment was responsible for the 

publication of the document. Three U.S. EPA Office of Research and Development staff 

members conducted internal peer review of this report. The U.S. EPA contracted Eastern 

Research Group Inc., to facilitate external peer review of the document, which also included 

three reviewers. 

AUTHORS:

C. Richard Ziegler 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Center for Environmental Assessment 

1200 Pennsylvania Avenue, NW (mail code 8623-D) 

Washington, DC 20460 

Jeffrey T. Varricchione 

Maine Department of Environmental Protection 

312 Canco Road 

Portland, ME 04103 

Kate Schofield 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Center for Environmental Assessment 

1200 Pennsylvania Avenue, NW (mail code 8623-D) 

Washington, DC 20460 

Susan B. Norton 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Center for Environmental Assessment 

1200 Pennsylvania Avenue, NW (mail code 8623-D) 

Washington, DC 20460 

Susanne Meidel 

Maine Department of Environmental Protection 

17 State House Station 

Augusta, ME 04333 

and Partnership for Environmental Technology Education 

584 Main Street 

South Portland, ME 04106 

ix 
CONTRIBUTORS

Susan Cormier 1

Jeff Dennis 2

Melissa Evers 2

Scott Freeman 3

Chuck Lane 1

Patricia Shaw-Allen 1

Leon Tsomides 2 

WORKGROUP PARTICIPANTS

Jennie Bridge 4

Tom Danielson 2

Susan Davies 2

Mary-Ellen Dennis 2

Steve Fiske 5

Alex Huryn 6

Dave Miller 2

Paul Mitnik 2

U.S. EPA INTERNAL REVIEWERS

Suzanne Marcy 1

Glenn W. Suter II 1

Paul F. Wagner 1

EXTERNAL REVIEWERS

Jerome M. Diamond 7

Alan T. Herlihy 8

Stephen J. Klaine 9

1 U.S. Environmental Protection Agency, Office of Research and Development 

2 Maine Department of Environmental Protection, Augusta, ME 

3 CH2M HILL, Raleigh, NC 

4 U.S. EPA, Region One, Boston, MA 

5 Vermont Department of Environmental Conservation, Waterbury, VT 

6 University of Alabama, Tuscaloosa, AL 

7 Tetra Tech, Inc., Owings Mills, MD 

8 Oregon State University, Corvallis, OR 

9 Clemson University, Clemson, SC 

x 
EXECUTIVE SUMMARY 

This case study presents results from a complex causal assessment of a biologically 

impaired, urbanized coastal watershed located primarily in South Portland, Maine, USA—the 

Long Creek watershed. The project team conducted this assessment using U.S. Environmental 

Protection Agency (EPA) Stressor Identification guidance (http://www.epa.gov/caddis/ and U.S. 

EPA, 2000a), which provides a useful structure for organizing available evidence and helped 

identify several probable causes of biological impairment. 

The targeted audience for this report includes: Maine scientists and managers working to 

improve the environmental health of the Long Creek watershed through, for example, restoration 

efforts and Total Maximum Daily Load (TMDL) development; future causal assessors (scientists 

and managers) seeking to understand the process and potential of U.S. EPA’s Stressor 

Identification guidance; and the scientific community as it seeks to better understand urbanrelated stressor interactions at impaired sites throughout the world. The Long Creek causal 

analysis will serve as an example for the assessment of other coastal urban areas with similar 

problems. 

The Clean Water Act (CWA) requires states to develop TMDLs for waters when current 

pollution controls are not stringent enough to attain or maintain compliance with adopted water 

quality standards. Maine’s 1998 list of impaired water bodies includes Long Creek due to 

decreased dissolved oxygen and unspecified non-point source pollution. Long Creek’s listing 

partly triggered this case study. Ultimately, however, dissolved oxygen and non-point source 

pollution were identified among several candidate causes of impairment; causal analysis 

described in this report and efforts to restore the Long Creek ecosystem will likely focus on a 

variety of issues. The U.S. EPA chose Long Creek as an example urban watershed for study in 

early 1999. The project team, composed of Maine Department of Environmental Protection 

(MEDEP) and U.S. EPA personnel, partnered to conduct the causal analysis described herein. 

Results of the analysis are helping guide the MEDEP and other stakeholders in improving and 

managing the Long Creek watershed. 

The project team conducted a site-by-site causal analysis because different patterns of 

biological effects were observed at different sites throughout the Long Creek watershed. The 

team applied biological monitoring and water quality data to the U.S. EPA Stressor Identification 

process to establish strength-of-evidence by impaired site, biological endpoint, and candidate 

cause. The team chose four effects, or specific biological endpoints, defining impairment. The 

team chose seven candidate causes of impairment and evaluated each cause at each of three 

impaired sites within the Long Creek watershed. One of the candidate causes, increased toxic 

substances, might more accurately be considered a causal category rather than a single stressor, 

as this cause includes several stressors (or sub-groups) including increased toxicity due to ionic 

xi 
strength, various metals, and polycyclic aromatic hydrocarbons. Furthermore, the project team 

analyzed some causes in terms of acute exposure (short term duration or stormflow conditions) 

and chronic exposure (long term duration or baseflow conditions), based on data availability. 

While other stressor identification case studies may yield single, “smoking gun,” 

probable causes, the Long Creek case study results point to multiple probable causes of 

impairment—neither scenario necessarily reflects more or less success of the stressor 

identification process. The case study results indicate that probable causes vary by site and 

biological endpoint. In summary, of the seven potential causes listed and assessed, the project 

team promoted the following causes of impairment from “candidate” to “probable” status: 

decreased dissolved oxygen, altered flow regime, decreased large woody debris, increased 

temperature, and increased toxicity due to ionic strength. Results indicate that some stressors 

impact multiple biological endpoints and others do not. Episodic toxicity from metals in 

stormflows may contribute to impairment at one of the sites. Due to insufficient evidence, the 

project team was not able to rule out increased sediment as a cause. 

Urbanized watersheds are often subject to multiple, interacting causes of impairment. 

This is likely the case for Long Creek. This report details interacting causes of impairment in 

terms of general causal assessment methods and in terms of this case study. It may be beneficial 

to combine candidate and probable causes of impairment into groups at various points in the 

assessment process and to design remedial action by targeting sources of impairment common to 

multiple causes, such as impervious surface area. 

This report concludes with a lessons-learned section, in which the project team discusses 

three issues specific to this study and the causal assessment process in general: 

1. The project team acknowledges challenges associated with uneven evidence given 

data gaps and data availability. 

2. The project team addresses the benefits of choosing simplified measures of biological 

response. 

3. In terms of applying monitoring data to an assessment, the project team 

acknowledges the importance of forecasting data needs so that a sequential data 

collection plan, specific to the needs of the stressor identification process, might be 

implemented prior to beginning the causal assessment process. 

xii 
1. INTRODUCTION 

This report describes a case study of Long Creek, a biologically impaired stream located 

in southern coastal Maine, USA (Figure 1). Long Creek’s contributing watershed is urbanized: 

home to industrial, commercial, and residential land uses. The Long Creek watershed showcases 

a wide range of topics related to resource management including the environmental implications 

of urban land use for coastal regions and the interactions among multiple causes linked to 

biological impairment. 

Figure 1. Project location map. 

The scientific community continues to identify environmental impacts associated with 

urbanization (e.g.: Roy et al., 2003; Wang and Kanehl, 2003; Beach, 2002; Paul and Meyer, 

2001), and the Millennium Ecosystem Assessment (2005) emphasizes the current and future 

importance of ecologically healthy urban environments. However, the multitude of urbanrelated causes of watershed impairment confounds scientists and complicates resource 

management. According to Wang and Kanehl (2003), urban land use is the most important 

factor influencing assemblages of cold water macroinvertebrates in urbanizing watersheds. 

Adverse changes to these assemblages may be attributed to a wide range of causes, from toxic 

substances to altered stormwater flow. The challenge in this assessment is pinpointing specific 

1
causal relationships, thereby providing policy makers and stakeholders a foundation for 

improving an urban ecosystem. 

Identifying causes of urban-related biological impairment in coastal watersheds is a 

timely issue. Roughly 53% of U.S. residents live in coastal counties, which comprise only 17% 

of the country’s total land area (NOAA, 1998). The National Oceanic and Atmospheric 

Administration (NOAA) predicts that the ratio of coastal to inland residents will remain stable as 

population rises (NOAA, 1998). With more coastal urbanization comes more impervious surface 

area, which is becoming more problematic in terms of environmental impacts and growth 

management (Elvidge et al., 2004). The importance of accurate causal assessment is increasing 

for urbanizing coastal regions. 

The project team—composed of personnel from Maine Department of Environmental 

Protection (MEDEP), U.S. Environmental Protection Agency (EPA) Office of Research and 

Development (ORD), and Partnership for Environmental Technology Education—provides the 

following detailed causal analysis as an example for assessment of other coastal urban areas with 

similar problems in Maine and around the globe. 

1.1. BACKGROUND 

Portions of Long Creek have violated state of Maine standards for dissolved oxygen and 

aquatic life. The U.S. EPA chose Long Creek as an example urban watershed for study under 

Clean Water Act (CWA) funding (section 104-b-3, Water Quality Cooperative 

Agreements/Grants) in early 1999. Long Creek underwent the majority of existing commercial 

development approximately 35 to 40 years ago, and urban development of the area continues 

today. In comparison to other watersheds in the Portland, Maine area, Long Creek has a low 

number of landowners per acre due to more commercial development than residential areas. 

1.1.1. Study Area Description 

The study area for this assessment includes two watersheds: the Long Creek and Red 

Brook watersheds (Figure 2; Red Brook’s inclusion in this case study and its use as a reference 

stream is discussed below). Long Creek and Red Brook flow through the municipalities of South 

Portland, Scarborough, Westbrook, and a small portion of Portland, Maine, eventually draining 

into Clark’s Pond, the Fore River, Casco Bay, the Gulf of Maine, and the Atlantic Ocean. 

Clark’s Pond and everything upstream of Clark’s Pond, including Red Brook and Long Creek, 

are freshwater ecosystems, and the Fore River is estuarine, progressively becoming more saline 

until connecting to the Atlantic Ocean. Red Brook is located in a watershed adjacent to and 

immediately south of the Long Creek watershed. The upper reach of Red Brook provides a 

relatively unimpaired study site. The project team labels the upstream Red Brook site as the

2
Figure 2. Elevation model of study watersheds. 

Source: Map was generated using data obtained from Maine Office of Geographic Information Systems, at 

http://megis.maine.gov/, accessed on December 29, 2005; elevation based on USGS 1:24,000 map contours.

3
reference site, and the team compared conditions at Long Creek’s impaired sites to the Red 

Brook site. 

Long Creek and Red Brook are low-gradient, gently-sloped, freshwater streams, 

dominated primarily by very fine and medium-sized sand (i.e., 0.062-0.500 mm). Gravel and 

bedrock are present in isolated patches and not representative of the stream channels. The Long 

Creek watershed (approximately 8.9 km2

), located mainly in South Portland and Westbrook, 

includes an enclosed regional shopping mall (140 stores, 18 restaurants, and over 5,500 parking 

spaces), part of the Portland airport (Portland International Jetport, PWM), a golf course, two 

semiconductor manufacturing plants, office parks, residential areas, and forested areas. Long 

Creek was once named “Jackson Brook;” older documents and maps use this name. The Red 

Brook watershed (approximately 8.5 km2

), located primarily in Scarborough and South Portland, 

includes residential, retail, and forest land cover. Both watersheds include a stretch of the Maine 

Turnpike, a four-lane interstate highway, and a waste incinerator/landfill. Table 1 shows 

percentages of land use for each study watershed, Figure 3 shows various land use features, and 

Figure 4 shows the distribution of impervious surfaces throughout the study area. 

Table 1. Watershed land use 

Source: Field (2005). 

Percent of watershed area 

Land use Red Brook Long Creek 

Urban / built up 19 40 

Forest 61 26 

Agriculture 10 8 

Barren 8 26 

Surface water 2 <1 

4

Portions of both study streams are physically altered beyond the level of change expected 

from natural geomorphologic processes. Both streams include channelized sections, and 

regional documents kept by the Maine Department of Inland Fisheries and Wildlife suggest that 

portions of both streams were relocated to accommodate commercial development and road 

building. U.S. Geologic Survey (USGS) topographic maps indicate that upper reaches within 

both watersheds were subjected to gravel mining operations, and instream detention basins exist 

along the upper reaches of Long Creek. 
Figure 3. Land use map. 

Source: Map was generated using data obtained from Maine Office of Geographic Information Systems, at http://megis.maine.gov/, accessed on December 29, 2005. The aerial photograph (basemap) was taken in April, 2001. Landfill locations are approximate, based on MEDEP (2002a). Hazardous waste, air emissions, and water discharge site information are based on U.S. EPA Envirofacts, at http://www.epa.gov/enviro/, accessed on February 14, 2006; sites include, e.g., automobile service centers, department stores, gas stations, and manufacturing corporations). 

5
Figure 4. Impervious surface and project site locations. 

Source: Map was generated using data obtained from Maine Office of Geographic Information Systems, at http://megis.maine.gov/, accessed on December 29, 2005.

6
1.1.2. Historical Land Use 

The Long Creek and Red Brook watersheds were covered primarily by farmland and 

forest until the late 1960s (Seeley and Valle, 1983). Appendix A provides historic USGS maps 

of the project area, showing urban development as a function of time, from 1891 to 1980. Major 

commercial development and highway-building within the two watersheds began in the mid 

1900s, and contributed to erosion and pollution of Long Creek, Red Brook, and Clark’s Pond, 

located at the downstream confluence of the two streams (Seeley and Valle, 1983). Urban land 

cover of Long Creek watershed increased by 36% between 1952 and 1995, while Red Brook 

urban cover increased by 10% (Field, 2005). Long Creek watershed forest and agricultural land 

cover decreased by 10% and 34%, respectively, between 1952 and 1995, while those of Red 

Brook decreased by 2% and 11%, respectively (Field, 2005). Seeley and Valle (1983) note two 

major events leading to decreased water quality within the study watersheds and Clark’s Pond: 

(1) construction of Interstate 295, lasting “several years,” for which stabilized vegetation was 

removed from the Red Brook watershed and “huge amounts of fill” were relocated within the 

watershed and (2) construction of commercial facilities, including a regional shopping mall, 

industrial buildings and office buildings, with “little effort at erosion control.” 

Clark’s Pond, an approximately 16-acre impoundment at the base of Long Creek and Red 

Brook, apparently existed in the 1700s but was smaller. Between that time and 1920, the area 

surrounding the pond—presumably including Long Creek and Red Brook watersheds—was used 

agriculturally, to some degree (Seeley and Valle, 1983). Sometime before 1900, a dam was 

constructed at the downstream end of Clark’s Pond, thereby enlarging the pond, and the 

Cumberland County Ice Company began using the pond for harvesting ice. Ice-harvesting ended 

in the mid 1900s, just before the pond was stocked with trout and transformed into a sports 

fishery, which ceased in the 1960s, corresponding with decreased water quality (South Portland 

Engineering Department, 1994). 

1.2. MAINE’S REGULATORY PROGRAM 

The CWA requires states to adopt water quality standards (WQSs) that support 

designated uses for water bodies. Maine defines four surface water classes: AA, A, B, and C 

(MEDEP, 2002b). Each class is defined by standards describing conditions necessary to attain 

that class, such as minimum dissolved oxygen level. Class AA represents the highest level 

where “waters shall be as naturally occurs,” and Class C represents the lowest attainment level 

for which “[d]ischarges... may cause some changes to aquatic life...” (see Appendix B for 

detailed class descriptions). Furthermore, the MEDEP developed numeric criteria to support 

narrative descriptions for aquatic life criteria as found in the Water Quality Classification Law 

(Davies and Tsomides, 2002). The numeric criteria are based on statistical decision models, 

7
reliant on 30 quantitative measures reflecting various aspects of benthic macroinvertebrate 

community health. 

CWA section 303(d) requires states to develop TMDLs for waters when current pollution 

controls are not stringent enough to attain or maintain compliance with adopted water quality 

standards. Maine's 1998 303(d) list of impaired water bodies includes Long Creek because of 

decreased dissolved oxygen and unspecified non-point source pollution. This report focuses on 

determining causes of biological impairment, a necessary precursor for developing TMDLs. 

1.3. TRIGGER FOR CAUSAL ANALYSIS 

 The MEDEP studied in detail six sites along Long Creek and three along Red Brook 

(Figure 4) by collecting biological, chemical, and physical data at the nine total sites1

 (see 

MEDEP, 2002a for a detailed description of this effort). Table 2 shows Maine’s water quality 

class designations for the various sites and whether or not the class has been met. 

Macroinvertebrate data collected along the streams signal ecosystem degradation. The MEDEP 

found abundant numbers of brook trout in Red Brook at, and upstream of, RB 1.474 (including 

RB 3.961), but nowhere in Long Creek. Of the nine sites, three sites on Long Creek (LCN .415, 

LCM 2.270, and LCMn 2.274) did not attain their designated classes; one site on Red Brook, RB 

3.961, attained Class A, the second highest possible classification (MEDEP, 2002a). 

For stressor identification the project team selected the three sites not attaining designated 

class: LCN .415, LCM 2.270, and LCMn 2.274. The Class A site on Red Brook, RB 3.961, was 

used as a reference site for comparison to the three impaired Long Creek sites. All four study 

sites have low-gradients (less than 0.5 % slope), which is common throughout both watersheds 

(MEDEP, 2002a). The three non-attaining Long Creek sites represent different challenges facing 

parts of the Long Creek watershed and are the focus of this causal assessment. 

 

1

 Site names consist of the stream initials (“LC” for Long Creek and “RB” for Red Brook), a branch designation for 

Long Creek only (“N” for the northern branch, “M” for the main branch, “Mn” for the northern branch of the main 

branch, and “S” for the southern branch), and the river mile, which is measured upstream from the confluence with 

Clark’s Pond. 

8
Table 2. Project site description and classification 

Watershed size Maine classificationb

Stream Site namea

acres km2

% Impervious 

area designation attainment 

LCM .380 1,471 6.0 13.5 C C 

LCM .910 1,380 5.6 10.1 C C 

LCM 2.270c 670 2.7 7.1 B C 

LCMn 2.274c 427 1.7 14.3 B N 

LCN .415c 262 1.1 32.6 C N 

LCS .369 361 1.5 47 C C 

Long 

Creek 

LC 0 

(at Clark's Pond) 2,208 8.9 no data no data no data 

RB .071 1,787 7.2 9.5 C C 

RB 1.474 1,448 5.9 7.9 C I 

RB 3.961c,d 

(reference site) 508 2.1 2.1 C A 

Red 

Brook 

RB 0 

(at Clark's Pond) 2,112 8.5 no data no data no data 

a

 Site names consist of the stream’s initials (“LC” for Long Creek and “RB” for Red Brook), a branch designation 

for Long Creek only (“N” for the northern branch, “M” for the main branch, “Mn” for the northern branch of the 

main branch, and “S” for the southern branch), and the river mile, which is measured upstream from the confluence 

with Clark’s Pond. 

b

 Classes AA & A are the highest classifications (”natural” biological condition), C is the lowest class (represents 

the state's minimum environmental goals), N represents non-attainment of Class AA, A, B, or C (”degraded” 

biological condition), and I indicates that the class was indeterminate due to low abundance of organisms. c

 Highlighted sites are the focus of this case study. 

d

 RB 3.961 attained Class A and was designated a reference site. 

9
1.4. REPORT FORMAT 

This causal analysis adheres to U.S. EPA Stressor Identification guidance (see below). 

The remainder of this report addresses topics specific to that methodology, as follows: 

• Section 2 - Biological Impairment–This section describes the foundation of the causal 

analysis, the specific biological effects seen at the impaired sites and how those effects 

were quantified. 

• Section 3 - Stressor Identification–Section 3 describes potential stressors, assesses 

causal associations, and steps through strength-of-evidence (SOE) scoring for each 

stressor at each impaired site. 

• Section 4 - Conclusions–Causal assessment conclusions are broken into four subsections: (1) similarities among impaired sites by candidate cause, (2) findings unique to 

each site, (3) evidence for each specific biological endpoint, and (4) overall conclusions 

regarding Long Creek’s probable causes of impairment. 

• Section 5 - Discussion–This section addresses two key issues surrounding conclusions 

drawn in the previous section: (1) the significance of interacting stressors, both for this 

case study and causal assessment in general, and (2) the certainty of the conclusions. 

• Section 6 - Highlights and Lessons Learned–In this section, the team examines key 

lessons learned about the case study and overall stressor identification process. 

The target audience of this report ranges from managers with minimal technical training 

in causal assessment to scientists attempting to conduct similarly complex case studies. A 

rudimentary knowledge of U.S. EPA’s Stressor Identification guidance may assist readers. U.S. 

EPA’s CADDIS (Causal Analysis/Diagnosis Decision Information System) Web site, located at 

http://www.epa.gov/caddis/, provides causal assessors with the most recent stressor identification 

methodology, originally adapted from the Stressor Identification Guidance Document (U.S. 

EPA, 2000a). Additionally, the CADDIS Web site provides basic information for managers 

interested in learning about the capabilities of this process. 

To enhance this report’s readability, the project team sought to minimize repetition of 

information among text, tables, figures, and appendices, especially in terms of numeric data. 

Readers seeking detailed, numeric data not found in the text will find additional data in the tables 

and appendices. 

10
2. BIOLOGICAL IMPAIRMENT 

The project team characterized biological impairment at each of the three Long Creek 

sites that did not meet designated water quality classes. Specific effects were used to determine 

whether different causes or intensities of stress occurred at the different study sites. Evidence 

that similar responses occurred throughout Long Creek might suggest a common cause and 

support evaluating the three sites as a single group. Observed effects can suggest inclusion of 

certain candidate causes as discussed in Section 3. Furthermore, recognizing specific effects 

often makes it easier to identify and interpret relevant evidence from scientific literature and 

other field studies. 

2.1. ANALYSIS 

An early objective of this analysis is to identify a suite of biological variables on which to 

focus the causal analysis. The project team sought to identify biological variables with values 

greatly different between the impaired and reference sites. 

2.1.1. Rockbag Sampling Data 

MEDEP biologists conducted macroinvertebrate rockbag sampling throughout the study 

area beginning August 5-6, 1999, using standard MEDEP rockbag sampling protocol (Davies 

and Tsomides, 2002). They placed three rock bags (7.25-kg cobble substrate, enclosed in 2.54-

cm aperture mesh) in the stream channel at each site, in areas representative of the Long Creek 

and Red Brook watersheds and in sandy-runs with at least 79% shade from canopy cover. After 

a colonization period of 32 days, biologists placed a 600-μm mesh dip net downstream of each 

rockbag and pulled each bag into the net. The contents of each rockbag and dip net were then 

washed into a 600-μm sieve bucket. Biologists cleaned individual rocks by hand to ensure the 

capture of all sample organisms. Contents were transferred into labeled sample containers and 

preserved with ethyl alcohol. Rockbag sampling data are provided in Appendix C. 

The project team analyzed biological effects occurring at the three study sites as follows: 

• Variables contributing to Maine’s linear discriminant function (LDF) model (see 

description below) were examined to identify responses to study site conditions. 

• Species lists with associated life history attributes were examined to suggest additional 

variables for inclusion in the suite of specific biological effects. 

• Findings from the tasks stated above were used to determine whether biological 

responses were sufficiently similar to support grouping the three impaired study sites and 

to support development of a candidate cause list. 

11
2.1.2. Maine’s Linear Discriminant Function Model 

The MEDEP uses an LDF model to define attainment of WQSs. The model, an 

agglomerative index, incorporates approximately 30 variables associated with the invertebrate 

community at sampled sites (see Appendix D for variable descriptions). LDF variables include 

both indices and abundances of particular families or genera. 

The project team disaggregated the model into its 30 component variables to determine 

which variables were most influential at each of the three sites. LDF model values for each 

impaired site were compared to corresponding values for reference site RB 3.961, and to the 5th

and 95th percentile values observed at other high quality (i.e., Class A or AA), sandy-bottomed 

reference streams in Maine. Appendix E provides more information on the regional reference 

analysis and confirms the use of RB 3.961 as a reference site for this case study. 

Disaggregation of the LDF model revealed at least two major findings: (1) 

Ephemeroptera, Plecoptera, and Trichoptera (EPT) generic richness at the three impaired sites 

(LCN .415 = 6; LCM 2.270 = 8; LCMn 2.274 = 7) is roughly half that of the reference site (RB 

3.961 = 15) and (2) Hilsenhoff Biotic Index (HBI) scores are just above 6.0 across all three 

impaired sites compared with an HBI of 4.2 at the reference site (Table 3). 

Table 3. Observed specific biological effects 

Site 

EPT 

richness 

Percent 

non-insects HBI 

Brook 

trout 

RB 3.961 15 7.8 4.2 Present 

LCN .415 6 35.6 6.6 Absent 

LCM 2.270 8 16.0 6.6 Absent 

LCMn 2.274 7 1.4 6.2 Absent 

EPT richness is often used as an indicator of stream condition (see e.g.: Wallace et al., 

1996; Bednarek and Hart, 2005). While some individual taxa included under the EPT umbrella 

may be tolerant of particular stressors, EPT are generally more sensitive to common stressors 

and often provide a reasonable measure of stream condition—that is, greater EPT richness may 

indicate better conditions. HBI values often increase as certain aspects of stream condition 

decline. HBI was originally designed to assess low dissolved oxygen levels caused by organic 

loading in streams (Hilsenhoff, 1987), but the index often reflects the presence of other 

proximate stressors. 

12
2.2. SITE-SPECIFIC DESCRIPTIONS AND BIOLOGICAL CONSIDERATIONS 

The following site-specific observations are based on information from an earlier 

MEDEP report (2002a), lists of individual taxa observed at the four sites (Table 4; Appendix C), 

and expert knowledge of Maine ecosystems from authors of this document. 

2.2.1. RB 3.961 (reference site) 

Red Brook has a sinuous sandy-bottomed channel and an intact riparian corridor at river 

mile 3.961.2

 Impervious surface covers approximately 2% of the 508 acres upstream from this 

location. RB 3.961 was, at the time of observation, dominated by species typical of low 

gradient, sandy-bottomed streams in Maine. 

Unlike any sites along Long Creek, abundant brook trout were observed at RB 3.961. 

Several organisms characterized as less tolerant of human disturbance, including the mayfly 

Paraleptophlebia, were observed at this site. The alderfly Sialis, not recognized as an indicator 

organism (Mackie, 2001), was observed as the most abundant organism at the site, comprising 

13% of organisms collected. MEDEP notes, however, that no organisms stood out as dominant 

at this site, given that the most abundant organism observed accounted for only 13% of total 

abundance. 

2.2.2. LCN .415 (impaired site) 

The northern branch of Long Creek at river mile 0.415 is the most heavily urbanized of 

the three impaired study sites. Impervious surface covers approximately 33% of the 262 acres 

upstream of the study site. The contributing watershed includes a portion of Portland’s airport, a 

portion of two semiconductor manufacturing plants, major roadways, retail development, and a 

soft drink bottling plant. The study site has a sandy-bottomed substrate and an intact riparian 

corridor. 

 The community observed at LCN .415 includes organisms typical of flowing water, but 

MEDEP biologists did not observe sensitive taxa at this site that were present at the reference 

site. Biologists found fewer organisms than would be expected and a high percentage of noninsects (relative to total macroinvertebrates). A high abundance of hyalellid amphipods was 

found at the site. Amphipods have short generation times, which can increase their tolerance of 

unstable substrate and/or frequent disturbance. 

 

2

 River mile measurements refer to the length of channel upstream from the Clark’s Pond confluence, for both Long 

Creek and Red Brook. 

13
Table 4. Dominant invertebrate taxa from rockbag samples 

Class Order Family Genus HBI FFGa MOEb

% of total 

individuals 

at site 

Site RB 3.961 (total mean abundance = 120.3)c

Insecta Megaloptera Sialidae Sialis 4 Pr B-Cb-Cg 13 

Insecta Diptera Chironomidae Tanytarsus 6 C-F,G Cb,Cg 12 

Insecta Diptera Chironomidae Micropsectra 7 C-G Cb,Sp 7 

Insecta Trichoptera Odontoceridae Psilotreta 0 Sc,C-G Sp 7 

Insecta Diptera Chironomidae Stempellinella 5 C-G Sp 7 

sub-total 46 

Site LCN .415 (total mean abundance = 62.7) c

Crustacea Amphipoda Hyalellidae Hyalella 8 Sh,G Sw 20 

Insecta Diptera Chironomidae Procladius 9 Pr,C-G Sp 15 

Gastropoda Limnophila Physidae Physella 8 Sc Cg,Gl 11 

Insecta Trichoptera Phryganeidae Ptilostomis 5 Sh,Pr Cb 7 

Insecta Trichoptera Limnephilidae Limnephilus 3 Sh,C-G Cb,Sp,Cg 6 

sub-total 61 

Site LCM 2.270 (total mean abundance = 386.0) c

Insecta Coleoptera Elmidae Dubiraphia 6 C-G,Sc Cg,Cb 41 

Insecta Ephemeroptera Caenidae Caenis 7 C-G,Sc Sp,Cb 16 

Insecta Diptera Chironomidae Clinotanypus 8 Pr B 9 

Pelecypoda Veneroida Sphaeriidae Sphaerium 2 C-F B 5 

Crustacea Isopoda Asellidae Caecidotea 8 Sh Sp 4 

sub-total 75 

Site LCMn 2.274 (total mean abundance = 97) c

Insecta Coleoptera Elmidae Dubiraphia 6 C-G,Sc Cg,Cb 60 

Insecta Ephemeroptera Caenidae Caenis 7 C-G,Sc Sp,Cb 9 

Insecta Diptera Chironomidae Microtendipes 6 C-F,G Cg 8 

Insecta Diptera Chironomidae Procladius 9 Pr,C-G Sp 5 

Insecta Diptera Chironomidae Tanytarsus 6 C-F,G Cb,Cg 2 

sub-total 84 

a

 Functional feeding group (FFG): C=Collector; F=Filterer; G=Gatherer; Pr=Predator; Sc=Scraper; Sh=Shredder 

(classification based on Merritt and Cummins, 1996, and project team knowledge). 

b

 Mode of existence (MOE): B=Burrower; Cb=Climber; Cg=Clinger; Gl=Glider; Sp=Sprawler; Sw=Swimmer 

(classification based on Merritt and Cummins, 1996, and project team knowledge). 

c

 Organisms collected in three rockbags over 32 days. Total mean abundance = total # of individuals from all three 

rockbags divided by three samples. 

14
2.2.3. LCM 2.270 (impaired site) 

MEDEP staff describe Long Creek’s main branch at river mile 2.270 as a “wooded 

island” along this portion of the stream, implying that there is riparian vegetation in the vicinity 

of the site but less vegetation above and below the site. Impervious surface covers 

approximately 7% of the 670 acres upstream of the study site. The contributing watershed is 

primarily composed of a golf course and a major roadway. An instream dam and associated 

upstream detention area are located approximately 0.75 miles upstream of the site. 

 The dominant taxa found at LCM 2.270 are well adapted to low velocity, silty habitats. 

Taxa found here have adaptations that could potentially enable them to withstand unstable 

habitat conditions. The dominant organism observed was an elmid beetle of the genus 

Dubiraphia, which can cling to vegetation and woody debris and climb out of silt. They have a 

plastron, which may allow them to tolerate low dissolved oxygen levels. The site’s dominant 

mayfly, Caenis, is tolerant of silt, low velocity conditions, and high water temperature. A midge 

observed at this site, Clinotanypus, is often found in ponds or slow streams of variable size and 

quality; Clinotanypus lives within the sediment and prefers soft sediment and shallow, warm 

water. 

2.2.4. LCMn 2.274 (impaired site) 

Similar to LCM 2.270, site LCMn 2.274 is described as a narrow channel flowing 

through a “wooded island” refuge, with pond-like habitat and a predominance of fine sediments. 

Impervious surface (largely office parks and roadways) covers approximately 14% of the 427 

acres upstream of this site. 

The dominant macroinvertebrate community observed at LCMn 2.274 reflects a pondlike community, tolerant of silt and sediment effects. Absence of passive filter feeders also 

suggests low or no flow velocity. Over 60% of the organisms found were Dubiraphia, indicating 

low site diversity. 

2.3. APPLICATION TO CAUSAL ANALYSIS 

The project team selected four biological endpoints for this causal assessment: 

• Decreased EPT generic richness (shown in this report as “decreased EPT richness”) 

• Increased percentage of non-insect taxa individuals, relative to total macroinvertebrate 

rockbag abundance, including both insects and non-insects (shown in this report as 

“increased percent non-insects”) 

• Increased HBI score 

• Absence of brook trout 

15
The EPT richness endpoint was chosen because, as described above, it is often used as an 

indicator of stream condition. Percent non-insects follows an opposite pattern; that is, as stream 

condition declines, the percentage of non-insect organisms increases. Usually, HBI values 

increase as stream health declines. Presence of brook trout (the fourth biological endpoint) was 

included because Maine stakeholders value this species, and there is a clear difference between 

what was observed at the reference site and the impaired sites (i.e., presence versus absence). 

Stakeholders consistently emphasize brook trout as a missing, yet important, component of the 

Long Creek ecosystem. 

Table 3 provides values for the selected biological endpoints. The project team evaluated 

each impaired site with respect to each endpoint with one exception; LCMn 2.274 did not show 

an increase in percent non-insects relative to the reference site, and, therefore, LCMn 2.274 was 

the only impaired site not assessed in terms of the non-insect biological endpoint. Observed 

macroinvertebrate communities were sufficiently different among the three impaired sites such 

that the project team chose to conduct a separate causal analysis for each site. 

Candidate causes of impairment may lead to reductions in abundance of sensitive taxa (i.e., 

EPT, insects relative to non-insects, pollution intolerant organisms, and brook trout) through, for 

example, increased mortality, decreased reproduction, increased emigration, decreased 

immigration, shifts in organism assemblage composition, or decreased ecosystem support of 

particular traits. Effects on focal taxa may result from direct or indirect impacts. For example, 

the taxon of concern may itself be adversely affected by a candidate cause, or it may be 

indirectly affected through impairment of other taxa, such as preferred prey. 

16
3. STRESSOR IDENTIFICATION 

3.1. CANDIDATE CAUSES 

This section describes candidate causes of biological impairments observed at the Long 

Creek study sites. The project team considered the following factors in developing the list of 

candidate causes: land use within the Long Creek and Red Brook watersheds, common causes of 

biological impairment in Maine stream ecosystems, and potential linkages between causes and 

biological endpoints discussed in the previous section. 

Observed biological effects were not specific enough to conclusively identify specific 

probable causes of impairment without further analysis. However, generalizations can be made 

to assist in developing a list of candidate causes of impairment. For example, absence of 

Plecoptera3

 and brook trout suggests that increased temperature might be included among 

candidate causes (e.g., Galli and Dubose, 1990). Presence of organisms with short life cycles 

suggests that flow alteration might be included as a candidate cause (e.g., Lytle and Poff, 2004). 

A panel at a Long Creek workshop in 2002 developed an initial candidate cause list 

(Augusta, ME, February 26-28, 2002), which was refined by the project team at subsequent 

meetings. Seven candidate causes of impairment were eventually chosen for this assessment 

(causes listed in no particular order): 

• increased autochthony (defined as increased on-site organic production) 

• decreased dissolved oxygen 

• altered flow regime (defined primarily as increased hydrologic flashiness, including 

decreased baseflow and increased peaks) 

• decreased large woody debris 

• increased sediment 

• increased temperature 

• increased toxic substances 

Each candidate cause is discussed in greater detail in Appendix F, and individual 

conceptual models for each cause are presented in the Conceptual Model (CM) figures section 

located after the main text (CM Figures 1-10). The project team identified several anthropogenic 

activities (also referred to as sources of stressors in the conceptual model figures, CM Figures 1-

 

3

 A total of three Plecopteran individuals were found in the study area, all located at reference site RB 3.961. This 

gives RB 3.961 a total mean plecopteran abundance at the low end of the project team’s regional reference analysis 

(see Appendix C). 

17
10) in the Long Creek watershed, which may contribute to at least one candidate cause. 

Appendix F describes candidate causes, basic causal interactions, and sources from a general

perspective; connections specific to Long Creek, among causes and effects, and probable causal 

interactions, are included in subsequent sections of the main text of this report. 

3.2. ANALYSIS OF CAUSES 

This section of the report describes how the project team used U.S. EPA’s Stressor 

Identification process, and its strength-of-evidence (SOE) approach, to link candidate causes 

with the specific effects described in Section 2. The team first considered types of evidence that 

use data only from the case. The team examined this evidence to see if it might refute a given 

candidate cause with sufficient confidence to eliminate that cause from consideration. Next, 

evidence that uses data from outside of the case (i.e., from elsewhere) was considered. The team 

then evaluated each candidate cause using all available types of evidence, scored in accordance 

with U.S. EPA’s Stressor Identification guidance.4

 Finally, the team identified additional 

evidence specific and important to the case study, which did not fit into the aforementioned 

framework. 

SOE scores revealed a combination of supporting and weakening evidence across 

impaired sites, candidate causes, and lines of evidence. The remaining part of Section 3 does not 

serve as a discussion of the scoring results. Rather, results are discussed in greater detail in 

Section 4 (Conclusions) in the context of determining which of the candidate causes should be 

classified as probable causes of impairment. 

MEDEP collected the majority of water chemistry and habitat quality data used to assess 

the candidate causes. Study-wide and site-specific data are available for watershed 

characteristics, baseflow and stormflow water chemistry, sediment toxicity, geomorphologic and 

hydrologic characteristics, and instream and riparian habitat conditions. Data collected by 

MEDEP, including collection and analysis techniques, can be found in MEDEP’s assessment 

report on Long Creek and Red Brook (MEDEP, 2002a). Table 5 lists measurements used to 

assess each candidate cause, and Appendix G describes available measurements. 

Availability of data and literature determined which types of evidence were considered. 

Table 6 describes the types of evidence that could be evaluated and whether endpoint-specific 

(EPT richness, percent non-insects, HBI, and brook trout) characterizations could be made. The 

project team was able to evaluate several types of evidence that use data from the case, 

including, spatial/temporal co-occurrence, stressor-response relationships from the field, causal 

pathway, and laboratory tests of site media. For types of evidence that use data from elsewhere, 

the team was able to evaluate mechanistically plausible cause and stressor-response relationships 

 

4

 U.S. EPA’s rules for scoring types of evidence are reviewed at the beginning of each SOE scoring table. 

18
Table 5. Measured variables relevant to each candidate cause 

Increased autochthony 

aquatic vegetation 

canopy shade 

chlorophyll a

RBP score: riparian vegetative zone width 

water chemistry, 2000 & 2001 stormflows: total phosphorous, ortho-phosphorous, total Kjeldahl nitrogen, nitrite, & nitrate 

water chemistry, 2000 baseflows: total phosphorous, ortho-phosphorous, total Kjeldahl nitrogen, nitrite, & nitrate 

Decreased dissolved oxygen 

canopy shade 

chlorophyll a

RBP scores: channel alteration & riparian vegetative zone width 

water chemistry, 2000 & 2001 stormflows: total phosphorous, ortho-phosphorous, total Kjeldahl nitrogen, nitrate, & nitrite 

water chemistry, 2000 baseflows: total phosphorous, ortho-phosphorous, total Kjeldahl nitrogen, nitrate, & nitrite 

water quality, 2000 baseflow: dissolved oxygen 

Altered flow regime 

 baseflow discharge 

baseflow thalweg velocity 

percent impervious surface 

RBP scores: channel alteration, channel sinuosity, & riparian vegetative zone width 

stormflow, 1994 event 

stormflow, 2001 event 

Decreased large woody debris (LWD) 

LWD count 

RBP scores: channel alteration, channel sinuosity, & riparian vegetative zone width 

Increased sediment 

chlorophyll a

muck mud 

Pfankuch rating (a measure of channel stability) 

percent impervious surface 

RBP scores: epifaunal substrate, pool substrate, sediment deposition, channel alteration, channel sinuosity, riparian 

vegetative zone width, bank vegetation protection, & bank stability 

sediment size 

water chemistry, 1994 stormflow: TSS 

 

water chemistry, 2000 & 2001 stormflows: TSS 

water chemistry, 2000 baseflows: TSS 

Increased temperature 

canopy shade 

percent impervious surface 

RBP scores: channel alteration, channel sinuosity, & riparian vegetative zone width 

temperature: weekly minimum, maximum, & mean 

Increased toxic substances 

sediment chemistry, 1993 

sediment chemistry, 2003 

sediment toxicity, 2003 

water chemistry, 1992 baseflow: copper, lead, & zinc 

water chemistry, 1994 stormflow: copper, lead, & zinc 

 water chemistry, 2000 & 2001 storm flows: cadmium, copper, lead, nickel, & zinc 

water chemistry, 2000 baseflows: cadmium, chloride, copper, lead, & nickel 

water chemistry, 2000 stormflow polycyclic aromatic hydrocarbons (PAHs) 

water chemistry, 2001 stormflow PAHs 

water chemistry, 2003 low flow: aluminum, antimony, arsenic, barium, beryllium, cadmium, calcium, chromium, cobalt, copper, iron, lead, magnesium, manganese, molybdenum, nickel, selenium, silver, thallium, vanadium, & zinc 

 water quality, 2000 baseflow: specific conductivity & salinity 

19
Table 6. Applicable types of evidence a

Type of evidence Concept Project applicability 

Analyzed for each specific 

effect 

Types of evidence that use data from the case: 

Spatial/temporal cooccurrence The biological effect must be observed where and when the cause is observed, and must not be observed where and when 

the cause is absent. 

Site-specific data used No, generalized across all 4 

endpoints 

Temporal sequence The cause must precede the biological effect. No evidence NA Stressor-response relationships from the field 

As exposure to the cause increases, intensity or frequency of the biological effect increases; as exposure to the cause decreases, intensity or frequency of the biological effect decreases. 

Scatter plot analysis applicable across all study sites 

Yes, 3 of 4 endpoints: EPT richness, % non-insects, & HBI 

Causal pathway Steps in the pathways linking sources to the cause can serve 

as supplementary or surrogate indicators that the cause and the biological effect are likely to have co-occurred. 

Site-specific data used No, generalized across all 4 

endpoints 

Evidence of exposure or biological mechanism 

Measurements of the biota show that relevant exposure to the cause has occurred, or that other biological mechanisms linking the cause to the effect have occurred. 

No evidence NA 

Manipulation of exposure Field experiments or management actions that increase or 

decrease exposure to a cause must increase or decrease the biological effect. 

No evidence NA 

Laboratory tests of site media 

Controlled exposure in laboratory tests to causes (usually toxic substances) present in site media should induce biological effects consistent with the effects observed in the field. 

Site-specific sediment toxicity sample analysis for 2 of 3 impaired sites: LCN .415 & LCMn 2.274 

Yes, 2 of 4 endpoints: EPT richness & % non-insects 

Verified predictions Knowledge of a cause's mode of action permits prediction 

and subsequent confirmation of previously unobserved effects. 

No evidence NA 

Symptoms Biological measurements (often at lower levels of biological 

organization than the effect) can be characteristic of one or a few specific causes. 

No evidence NA 

20
Table 6. Applicable types of evidence a (continued) 

Type of evidence Concept Project applicability 

Analyzed for each specific 

effect 

Types of evidence that use data from elsewhere: 

Mechanistically plausible cause 

The relationship between the cause and biological effect must be consistent with known principles of biology, chemistry and physics, as well as properties of the affected organisms and the receiving environment. 

Site-specific data compared to information from elsewhere; majority of analysis applicable across all study sites 

Yes 

Stressor-response relationships from laboratory studies 

Within the case, the cause must be at levels associated with related biological effects in laboratory studies. 

Site-specific data compared to information from elsewhere 

Yes 

Stressor-response relationships from other field studies 

At the impaired sites, the cause must be at levels sufficient to cause similar biological effects in other field studies. 

Site-specific data compared to information from elsewhere 

Yes 

Stressor-response relationships from ecological simulation models 

Within the case, the cause must be at levels associated with effects in mathematical models simulating ecological processes. 

Ecological simulation models were not used 

NA 

Analogous stressors Agents similar to the causal agent at the impaired site should 

lead to similar effects at other sites. 

No evidence NA 

Manipulation of exposure at other sites 

At similarly impacted locations outside the case sites, field experiments or management actions that increase or decrease exposure to a cause must increase or decrease the biological effect. 

No evidence NA 

Evaluating multiple lines of evidence: 

Consistency of evidence Confidence in the argument for or against a candidate cause is 

increased when many types of evidence consistently support or weaken it. 

Site-specific analysis Yes 

Explanation of the evidence Confidence in the argument for a candidate cause is increased 

when a post hoc mechanistic, conceptual, or mathematical model reasonably explains any inconsistent evidence. 

Site-specific analysis Yes 

a Source: U.S. EPA CADDIS Web site (http://www.epa.gov/caddis/). 

21
 

from laboratory and other field studies. Data are not available for several types of evidence (see 

Table 6), and those types of evidence will not be discussed further. Types of evidence for which 

data are available are discussed below and organized in detail in the SOE Tables section (SOE 

Tables 1-50).5

 

3.2.1. Evidence That Uses Data from the Case 

3.2.1.1. Spatial/Temporal Co-occurrence 

The project team compared data from each impaired site to reference site data for each 

candidate cause. Table 7 provides a summary of spatial/temporal co-occurrence data, and SOE 

Tables 1-3 provide the complete dataset for this line of evidence. Scores are located in SOE 

Tables 1-3. 

The project team made comparisons between samples collected on the same day and at 

similar times when possible; out of sync comparisons—for example, cross-year comparisons, 

were not used. If water quality samples taken at a biologically-impaired Long Creek site had 

higher lead (Pb) concentrations than corresponding samples at the Red Brook reference site 

taken on the same day and at a similar time, this would be considered supporting evidence for 

spatial/temporal co-occurrence at the Long Creek site, and Pb would be given a positive score in 

the appropriate table location. Only data directly representing proximate stressors (i.e., the 

candidate causes) were used as evidence for spatial/temporal co-occurrence. Data representing 

other steps in the causal pathway and surrogate measurements were considered under other types 

of evidence. The project team did not discriminate between small and large measured 

differences among data for the purposes of scoring spatial/temporal co-occurrence; even if the 

difference between the impaired sites and the reference site was small, the project team still 

considered this supporting evidence for the purpose of scoring. However, in some situations the 

team qualifies small and large differences either in the “General Comments” section of the SOE 

tables or within the text of this report. 

3.2.1.2. Stressor-Response Relationships from the Field 

The project team developed study-wide (Long Creek and Red Brook) scatter plots to 

assess stressor-response relationships, which might suggest that effects increase or decrease with 

increasing or decreasing exposure. Appendix G provides the scatter plots, which show 

biological impairment endpoints (EPT richness, percent non-insects, and HBI) as a function of 

stressor magnitude. The brook trout endpoint was not included in this analysis, as brook trout 

were assessed solely in terms of presence or absence. Nine sites along Long Creek and Red

5

 The project team attempted to convey SOE information across multiple impaired sites, candidate causes, and lines 

of evidence with the least amount of repetition. Nevertheless, the SOE tables included at the end of this report 

contain some repetition of information so that appropriate comparisons can be made for SOE-scoring purposes. 

22
Table 7. Spatial/temporal co-occurrence data summary a,b

Candidate 

Cause Variable, units RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 

dominant aquatic vegetation, approximate % of local reach 

diatoms 

25% 

diatoms 

25% 

rooted 

submergents & 

diatoms 25% 

diatoms 

20% 

Increased autochthony 

chlorophyll a, mg/m2 10.4 15.7 no data 17.5 

Decreased dissolved oxygen 

dissolved oxygen, mg/L 8.7 [3] 

(8.0-9.5) 

6.3 [3] 

(5.3-7.8) 

5.3 [3] 

(4.1-7.4) 

5.5 [3] 

(4.4-6.2) 

baseflow discharge/watershed area, cfs/ac 0.00073 [2] 

(0.00071-0.00075) 

0.00055 [2] 

(0.00035-0.00076) 

storm event peak discharge/watershed area, cfs/ac 

0.0035 0.1338 

storm event volume/watershed area, ac-ft/ac 0.0041 0.0276 storm event duration, hours 25.4 5.5 storm event time to peak discharge, hours 9.4 2.3 

no data 

mean thalweg velocity, m/s 0.10 0.03 

Altered flow regime 

thalweg baseflow velocity measured at 2m increments along 100m reach in site vicinity 

highly variable 

longitudinal velocity 

and velocity normally 

above zero 

no data 

no data 

low longitudinal 

velocity variability 

and velocity often 

equal to zero 

LWD diameter >5cm, # of pieces 91 37 43 Decreased 

large woody debris LWD diameter >10cm, # of pieces 39 

no data 

8 12 

baseflow TSS, mg/L <10 [3] 

(<2 - <10) 

<10 [3] 

(3- <10) 

<10 [3] 

(1- <10) 

<10 [3] 

(4- <10) 

stormflow TSS, mg/L <10-118 [9] <10-271 [9] no data no data muck-mud, % 60 40 70 40 RBPc epifaunal substrate, score & category 13 sub-optimal 13 sub-optimal 13 sub-optimal 12 sub-optimal RBPc pool substrate, score & category 10 marginal 10 marginal 10 marginal 8 marginal 

Increased sediment 

RBPc sediment deposition, score & category 18 optimal 11 sub-optimal 18 optimal 18 optimal 

23
Table 7. Spatial/temporal co-occurrence data summary a,b (continued) 

Candidate 

Cause Variable, units RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 

weekly minimum, °C 12.9 [3] 

(11.4-14.0) 

16.3 [3] 

(15.4-17.3) 

17.0 13.2 

weekly maximum, °C 21.1 [3] 

(20.3-22.1) 

22.7 [3] 

(21.6-24.2) 

23.3 21.8 

Increased temperature 

weekly mean, °C 16.7 [3] 

(16.1-17.4) 

19.2 [3] 

(18.6-20.0) 

20.2 16.5 

Increased toxic substances - water column samples, units in ppm or mg/L, except specific conductivity uS/cm:  (not all toxic substances data are shown here, rather only values for which all 4 sites have co-occurring data; SOE tables 1 - 3 show all collected data)

baseflow chloride 29 [3] 

(26-30) 

122 [3] 

(91-141) 

99 [3] 

(83-124) 

66 [3] 

(58-73) 

Ionic strength 

baseflow specific conductivity, uS/cm 129 [3] 

(79-155) 

745 [3] 

(659-796) 

568 [3] 

(491-718) 

459 [3] 

(376-510) 

Cadmium baseflow <0.0005 [3] <0.0005 [3] <0.0005 [3] <0.0005 [3] Copper baseflow <0.002 [3] <0.002 [3] <0.002 [3] 0.0013 [3] 

(<0.002-0.002) 

Lead baseflow <0.003 [3] <0.003 [3] <0.003 [3] < 0.003 [3] Nickel baseflow <0.004 [3] <0.004 [3] <0.004 [3] < 0.004 [3] Zinc baseflow <0.005 [3] 0.014 [3] 

(0.013-0.015) 

<0.005 [3] 0.0042 [3] 

(<0.005-0.005) 

a Baseflow values shown as mean [n] (range), where more than one value available, and stormflow values shown as range [n]. (note that a range is provided for 

baseflow only if a toxic substance was detected). 

b Lower thresholds of essential elements are not considered in this causal analysis. c Rapid Bioassessment Protocol (RBP): 

 Habitat Parameter: Score and Condition Category:

 epifaunal substrate / available cover 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal  pool substrate characterization 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal  sediment deposition 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

24
Brook, for which both endpoint and stressor data were collected, were used for this analysis; 

these sites include the three impaired sites and single reference site. The scatter plot analysis is 

not reported and scored on a site-by-site basis (see SOE Table 4), but is considered a 

characterization of the entire project area (both watersheds). With data from nine study sites 

throughout the project area, sample size is not sufficient to make judgments about individual 

sites or stream reaches. Rather, the project team sought only to characterize trends, if possible, 

across all nine sites. 

The project team interpreted the scatter plots by looking for linear and curvilinear trends 

in the data. The team supplemented visual interpretation with statistical correlation coefficients 

(Appendix H). Based on available data, at least one biological endpoint appeared to correlate 

with stressors associated with the following candidate causes: increased autochthony, decreased 

dissolved oxygen, decreased large woody debris, increased temperature, and increased toxic 

substances, specifically ionic strength (SOE Table 4 reports SOE scores by endpoint). 

Specific conductivity and chloride (often representative of ionic strength) were the only 

two variables for which the project team interpreted a correlation for all three assessed endpoints 

(EPT richness, percent non-insects, and HBI). As specific conductivity and chloride increase 

throughout the two study watersheds, EPT richness decreases while percent non-insects and HBI 

values increase. 

 The scatter plot analysis shows EPT richness decrease as a function of increasing percent 

impervious surface area. This information was not used for scoring this type of evidence. The 

project team uses impervious surface area as a surrogate measure for scoring the altered flow 

regime candidate cause for another type of evidence—specifically, stressor-response 

relationships from other studies (see Section 3.2.2). The team chose not to use surrogate 

measures for assessing types of evidence that only use data from the case study sites. Those 

types of evidence are generally considered stronger than those relying on information from 

outside the case study; likewise, surrogate measures are at least one step removed from the 

cause-and-effect relationship, and thus, introduce a weaker form of evidence. 

3.2.1.3. Causal Pathway

The project team found supporting evidence for some causal pathway steps across all 

candidate causes at all three impaired sites (SOE Tables 5-11). The conceptual models (CM 

Figures 1-10) show causal pathways for each candidate cause. The project team scored this 

association with a single plus in the SOE tables, not broken down by individual biological 

endpoint (SOE Tables 12-18). The team used increased percent impervious surface area as a 

causal step for all candidate causes except increased autochthony, and percent impervious 

surface area was often the strongest supporting evidence within a causal pathway (e.g., for 

increased toxic substances). 

25
3.2.1.4. Laboratory Tests of Site Media

Sediment samples were taken from the reference site and LCN .415 and LCMn 2.274 

(U.S. EPA, 2004a). The samples were tested in the laboratory for toxicity to chironomids 

(Chironomus tentans) and amphipods (Hyallela azteca), which the project team used as 

surrogates for EPT and non-insects, respectively. The sediment toxicity testing laboratory 

determined that chironomid survivorship differences among the two impaired sites tested, the 

reference site, and the laboratory control were not statistically significant under laboratory 

conditions (U.S. EPA, 2004a). Amphipod survival, under laboratory tests, was significantly 

lower at both the reference site and impaired site LCN .415 than under the laboratory control; 

survival at LCMn 2.274, however, was similar to the control. This offers conflicting 

information, considering more amphipods were found at LCN .415 than at the reference site. If 

sediment-related toxicity at the reference site is negatively impacting amphipods, the laboratory 

results indicate that the same effect might be observed at LCN .415 in the field, which is not the 

case. The project team scored this type of evidence zero (or uncertain) for the EPT richness and 

percent non-insects endpoints. SOE Tables 19 and 20 show data and scores for this type of 

evidence. 

Chironomids are generally thought to be more tolerant than EPT, and this was taken into 

consideration when scoring; had this dataset revealed a more significant correlation, the project 

team might have revisited the use of chironomids as surrogates for EPT and attempted to qualify 

conclusions. It should be noted that laboratory tests were conducted in controlled environments, 

unlike conditions found in the field, where more factors often interact and impact organism 

health. 

3.2.2. Evidence That Uses Data from Elsewhere 

3.2.2.1. Mechanistically Plausible Cause 

Scoring for mechanistically plausible cause was similar for all three sites and yielded 

supporting or neutral scores for each candidate cause.6

 Some mechanisms linking cause and 

effect are described earlier and in Appendix F, to which the following text often refers. 

The project team classified invertebrate taxa at each site according to functional feeding 

group and mode of existence (Merritt and Cummins, 1996). The project team then calculated 

relative site-specific abundance of each group (SOE Table 21). Values were compared across 

the reference site and impaired sites to determine if the data support increased autochthony 

and/or increased sediment as causes of impairment, under the mechanistically plausible cause 

 

6

 Unlike other types of evidence for which data are available, a separate table was not created for this type of 

evidence (i.e., mechanistically plausible cause); scoring is described in this section of the text for each candidate 

cause and each biological endpoint. 

26
type of evidence. Relative abundance of functional feeding and mode of existence groups varied 

widely across the three impaired sites. In some cases, variability resulted from dominance of one 

or a few taxa at some subset of these sites. For example, the coleopteran Dubiraphia (gatherer, 

clinger-climber) was absent from LCN .415, but comprised 41% and 60% of total invertebrate 

abundance at LCM 2.270 and LCMn 2.274, respectively. 

For increased autochthony, the project team expected to find food resource changes 

reflected by increases in scraping taxa and decreases in shredding taxa at impaired sites relative 

to the reference site. However, the data do not reflect this pattern: the highest relative abundance 

of scrapers is seen at the reference site, and the functional feeding group analysis does not show 

a clear pattern among the sites for percentage of shredders. Thus, the project team assigned a 

neutral score (zero; no mechanism is known) to the EPT richness endpoint across all three sites. 

Increased abundance of snails (non-insects) is often associated with increased autochthony, and 

data show that snails were found at LCN .415 and LCMn 2.274 but not at the reference site or 

LCM 2.270; therefore, for increased autochthony, the team scored the percent non-insects 

endpoint positive (single plus; plausible mechanism exists) for LCN .415 and LCMn 2.274 but 

neutral for LCM 2.270. HBI would be expected to increase, as it was originally designed to 

assess low dissolved oxygen caused by organic loading, and organic loading is often associated 

with increased autochthony (therefore, positive score for HBI across all three sites). The team 

did not find appropriate evidence to associate increased autochthony with changes in brook trout 

abundance. 

The project team scored mechanistically plausible cause for decreased dissolved oxygen

positive for all endpoints across all three sites. Low dissolved oxygen levels can cause 

asphyxiation for EPT taxa and brook trout and relative increases in tolerant non-insect taxa. HBI 

would be expected to increase, as it was originally designed to assess low dissolved oxygen 

caused by organic loading. 

Altered flow regime also was scored positively for all endpoints across all three 

impaired sites. The project team focused on lower day-to-day baseflow conditions (a component 

of hydrologic flashiness) as the specific candidate cause for this type of evidence. Appendix F 

describes mechanisms linking EPT richness and brook trout to running water habitats. Certain 

non-insect taxa (e.g., oligochaetes and snails) are tolerant of lentic conditions; similarly, several 

taxa with high HBI tolerance values (e.g., many chironomids and oligochaetes) are less reliant on 

fast-flowing habitats. 

Large woody debris provides habitat and cover for EPT taxa and brook trout (see 

Appendix F for more detailed information). A photograph taken upstream of RB 3.961 shows 

caddisflies attached to submerged large woody debris (Figure 5). Mechanistically plausible 

causes for changes in percent non-insects and HBI with respect to large woody debris are 

27
Figure 5. Caddisflies and large woody debris under water at reference site RB 3.961. 

Source: MEDEP staff; photograph taken in 2004. 

unknown. The project team scored EPT richness and brook trout endpoints positive and the 

percent non-insects and HBI endpoints neutral for large woody debris across all three sites. 

For increased sediment, the project team might expect to see increases in suspended 

sediment lead to decreases in abundance of filter-feeding taxa, many of which are trichopterans. 

This was observed, as filterer percentage was highest at the reference site, and therefore, the 

team scored the EPT richness endpoint positive across all three sites. Non-insect taxa like 

oligochaetes often increase in abundance with increasing fine sediments, and so this endpoint 

received a positive score. Zweig and Rabeni (2001) indicate that HBI may be insensitive to 

increases in deposited sediments, and that traits associated with susceptibility to organic 

enrichment (as related to HBI) are often not related to traits associated with sediment deposition. 

The HBI endpoint received a neutral score (zero) across all three sites. Mechanisms related to 

increased sediment and brook trout are discussed in Appendix F; the brook trout endpoint was 

assigned a positive score. 

 The project team scored mechanistically plausible cause for increased temperature

positive for the EPT richness and brook trout endpoints for all three sites (see Appendix F). The 

team could find no mechanistic information associating increased temperature with increases in 

percent non-insects or HBI values, so these endpoints were assigned neutral scores. 

28
The project team scored mechanistically plausible cause the same for all toxic 

substances: positive for EPT richness and brook trout but neutral for percent non-insects and 

HBI. The team assumes EPT richness and brook trout are likely to decline in the presence of 

increased toxic substances, but the team is uncertain whether percent non-insects and HBI taxa 

respond positively or negatively at similar toxic substance concentrations. Thus, percent noninsects and HBI endpoints were assigned neutral scores. 

3.2.2.2. Stressor-Response Relationships from Laboratory and Other Field Studies

SOE data and scores for stressor-response relationships from laboratory and other field 

studies7 used for this case study are shown in SOE Tables 22 through 37, with a separate table 

for polycyclic aromatic hydrocarbons (PAHs; SOE Table 38). 

Species sensitivity distributions (SSDs; Appendix I) were developed for those metals 

having adequate data in U.S. EPA’s public-access ECOTOX database 

(http://www.epa.gov/ecotox). SSDs are exposure-response relationships representing 

distribution of species sensitivities relative to exposure to individual metals in the water column. 

Because variance of sensitivities to chemicals among species is often more important to 

ecological risk assessment than variance among individuals, SSDs have become common in 

ecological effects analyses in the U.S., Europe, and elsewhere (Posthuma et al., 2002; see U.S. 

EPA, 2005 for additional information on the generation and utility of SSDs in causal 

assessment). 

Case study SSDs were generated using laboratory LC50 data. Since an LC50 is a 

concentration that kills half of the organisms in a test population, one would expect to observe a 

fish kill or a temporary reduction in the abundance of some species when water concentrations 

equal the LC50 for that species. Data used in generating SSDs do not represent specific species 

present at the study area. Toxicity data are generally not available for site-specific taxa due to 

the diversity of species occurring in the wild and the need to perform toxicity tests with well 

characterized organisms that can be successfully cultured in the laboratory. 

For each metal, the project team selected freshwater aquatic organism tests with siteappropriate water hardness (18-60 mg CaCO3/L), pH (6-8), and temperature (>15°C). It was 

necessary to generate SSDs with data for total metals because greater than 90% of freshwater 

metals data in ECOTOX are reported as total metals. Free ion or dissolved metal concentrations 

would be more appropriate indicators of actual toxic exposure and preferred for comparison with 

Long Creek dissolved metal data. However, the relative bioavailability of metals in unfiltered 

 

7

 U.S. EPA Stressor Identification guidance (U.S. EPA, 2000a) splits stressor-response relationships that use data 

from elsewhere into three categories: from laboratory studies, from other field studies, and from ecological 

simulation models. Laboratory and other field studies were combined into one table and one type of evidence for 

ease of presentation in this document. Ecological simulation models were not used in this case study. 

29
lab and natural waters differs because laboratory water contains little suspended matter. The 

project team did not generate SSDs for metals with sparse available toxicity data. 

Separate SSDs were generated for invertebrates and fish. In comparing SSDs for 

different species groups, invertebrates are generally more sensitive than fish. This difference 

may be due to the differing life spans of the two groups: a short (acute) exposure for relatively 

long-lived species such as brook trout may be equivalent to a long (chronic) exposure for 

relatively short-lived species such as caddisflies. Data were further subdivided to generate SSDs 

addressing potential effects at baseflow/low flow exposures (3-30 days) and at stormflow/pulsed 

exposures (<30 hours). Where possible, the project team superimposed site-specific data on SSD 

plots (i.e., the proportion of decreased EPT richness, relative to the reference site, and sitespecific observed metal concentrations). This was done to illustrate whether species reductions 

were plausible given site concentrations and whether the magnitude of effect observed at a given 

site is consistent with that suggested by the SSD. 

The project team chose to use impervious surface area as a surrogate measure for the 

altered flow regime candidate cause in the context of this type of evidence—that is, stressorresponse relationships from elsewhere. The use of impervious surface area, specifically increased 

hydrologic flashiness, allows the team to take advantage of endpoint-specific stressor-response 

data from other studies (see SOE Table 24). 

Impervious surface is often associated with the presence of other stressors and might be 

used as surrogate measure for those stressors; however, of the candidate causes identified in this 

case study, impervious surface is the least removed from altered flow regime. That is, from a 

causal pathway perspective, impervious surface directly alters flow with no interim steps. 

Specifically, precipitation falls and impervious surface alters a watershed’s hydrology. For 

impervious surface to increase toxic substances, for example, there must first be a source of toxic 

substances, the output of which may vary through time, and a mechanism by which the 

substances reach impervious surfaces, and then precipitation must mobilize the substances before 

they impair the watershed or stream. Unlike the link between impervious surface and altered 

flow regime, the link with increased toxic substances involves more steps. 

In the context of urban hydrology, flow regime may be governed principally by two 

factors: (1) a watershed’s contributing impervious surface area and (2) the efficiency with which 

water moves over land and into and through channels (e.g., Leopold, 1968). These two factors 

are also employed as major inputs for some hydrologic models (e.g., U.S. Army Corps of 

Engineers Hydrologic Engineering Center’s modeling products: 

http://www.hec.usace.army.mil/). Measures of percent impervious surface area contributing to 

each stream study site are available (Table 2). More qualitative evidence from the case can be 

used to characterize the second factor described above, that is, hydraulic efficiency. A recent 

aerial photograph of the project site (dated April 2001; Figure 3) shows significantly more 

30
urbanization in the vicinity of and adjacent to Long Creek in comparison to the area of Red 

Brook associated with the reference site (where forested land appears instead of urban land uses). 

Those urban areas in the Long Creek vicinity are associated with storm drain systems and a 

greater density of culverts, both likely corresponding with less flow resistance (concrete and 

metal channels generally have lower roughness values than vegetated channels), less channel 

sinuosity and shorter travel times (synthetic channels are often straightened), and less subsurface infiltration opportunities between areas of impervious surfaces and the stream channel 

(implications of impervious areas directly connected to streams are reviewed by Walsh et al., 

2005a, b). Given that the impaired site watersheds have greater stormflow hydraulic efficiency 

than the reference site watershed, and accepting the simplified two-factor flow regime premise 

stated above, it is permissible to use impervious surface area as a surrogate measure for altered 

flow regime, qualitatively and conservatively. 

3.2.3. Evaluation of Multiple Types of Evidence 

3.2.3.1. Consistency of Evidence

SOE Table 39 shows U.S. EPA’s scoring system for consistency of evidence. SOE 

Tables 40-42 provide summaries of case study scores, including consistency of evidence, with 

one table for each of the three impaired sites. SOE Table 43 provides only consistency of 

evidence scores so that the three sites can be compared. 

The project team determined scores for this type of evidence by isolating individual sites, 

causes, and endpoints, then assessing the overall body of evidence consisting of the six types of 

evidence previously scored. For example, beginning with site LCN .415, going to the “Increased 

autochthony” column of SOE Table 40, and reviewing the scores for the EPT richness endpoint, 

the spatial/temporal co-occurrence and causal pathway scores (0 and +, respectively) apply 

across all biological endpoints, including EPT richness. EPT richness scores for stressorresponse relationships from the field, mechanistically plausible cause, and stressor-response 

relationships from the laboratory and other field studies are 0, 0, and 0. There was no evidence 

to evaluate the remaining association, laboratory tests of site media, which applies only to the 

sediment toxicity sub-category of the increased toxic substances candidate cause. For this 

particular example, the evidence is ambiguous and inadequate; therefore, the team assigned a 

score of zero, neither supporting nor weakening the case for increased autochthony for the EPT 

richness endpoint. 

Not all consistency of evidence scoring scenarios are as clear-cut as the above example. 

The project team applied several general rules of thumb while attempting to score consistency of 

evidence: 

31
• NOT summing scores; for example, [0 and + and ++ and –] ≠ ++ or +2 

• Considering confidence of scores from other types of evidence individually; for example, 

the team might take into account sample size for a particular type of evidence, especially 

when a borderline positive or negative score was assigned 

• NOT considering all types of evidence with equal weight; there were exceptions, but in 

general, the following ranking held true for this case study (from strongest to weakest): 

 1. Spatial/temporal co-occurrence 

 2. Stressor-response relationships (from this case and from elsewhere) and 

laboratory tests of site media 

 3. Mechanistically plausible cause and causal pathway 

• NOT considering the overall body of evidence strong enough to assign +++ to any given 

endpoint; however, for situations where support was relatively strong, the team assigned 

++ 

• Viewing this exercise as a comparative analysis within the context of the overall case 

study; this part of the process provided us with an opportunity to highlight findings that 

merit additional emphasis8 

3.2.3.2. Explanation of Evidence

For the explanation of evidence association, the project team followed U.S. EPA’s 

Stressor Identification scoring system (see SOE Table 44). SOE Tables 45-48 show complete 

SOE scoring tables, including all candidate causes and all types of evidence. The team did not 

assign scores for many of the metals because of insufficient data. Inconsistency and ambiguity 

among types of evidence are discussed in Section 4. 

3.2.4. Additional Evidence Within the Case Study Watersheds 

A previous study of Long Creek and Red Brook (South Portland Engineering 

Department, 1994) and aerial photographs (see Appendix A) of the two watersheds provide 

additional evidence for the case study. However, the project team did not include or score this 

evidence as part of the SOE framework because data from the previous study was not gathered in 

the vicinity of the case study sites, and the team was unable to interpret the aerial photographs 

with confidence. 

3.2.4.1. Stream Discharge

The South Portland Engineering Department (1994) collected stream flow data during an 

August 18, 1994, storm. They took measurements on Long Creek and Red Brook, just upstream 

 

8

 U.S. EPA’s CADDIS Web site, http://www.epa.gov/caddis, and specifically “Step 5: Identify Probable Cause,” 

provides additional information and advice on the comparative process of bringing together multiple lines of 

evidence. 

32
of Clark’s Pond. South Portland Engineering Department (1994) noted that Red Brook 

stormflow “lags by a couple of hours” behind Long Creek and does not show “flow increase 

until over 0.75′′ of rain has fallen,” whereas Long Creek “immediately shows a flow increase.” 

The South Portland City Engineering Department developed a hydrograph for the storm, 

indicating that Long Creek has a flashier flow regime, marked by greater peak flow and greater 

runoff volume. The data lend support to the altered flow regime candidate cause but not 

specifically at the team’s study sites. 

3.2.4.2. Toxic Substances

South Portland Engineering Department (1994) conducted toxic substance sampling on 

Long Creek and Red Brook, just upstream of the confluence with Clark’s Pond. They took water 

column measurements on October 5, 1992, during baseflow conditions, and on August 18, 1994, 

during stormflow conditions. SOE Tables 49 and 50 provide comparisons between South 

Portland Engineering Department (1994) measurements and measurements taken by MEDEP 

(2002a). Baseflow concentrations measured by South Portland Engineering Department for 

copper (Cu) and Pb in Long Creek are close to stressor-response benchmarks (see SOE Tables 

49 and 50) and higher than those found in Red Brook. The data support the case for increased 

toxic substances as a cause of impairment on Long Creek but not specifically at study site 

locations. 

3.2.4.3. Aerial Photographs

Aerial photographs taken in 1940, 1952, 1976, 1995, 1998, and 2001 show the 

confluence of Long Creek and Red Brook with Clark’s Pond (Appendix A). Four of six 

photographs (1952, 1976, 1995, and 2001) appear to depict higher levels of suspended solid 

content originating from Long Creek than from Red Brook, just upstream of Clark’s Pond.9

 The 

project team cannot pinpoint the source of the suspended solids. Is the water column cloudiness 

normal for Long Creek due to surficial geology and/or soil type, a result of erosion due to 

stormflow runoff, or specific to some other unknown event or events, such as a construction 

project? The data lend questionable support to the increased sediment candidate cause. 

 

9

 The resolution and clarity of the historic aerial photographs shown in Appendix A do not allow speculation on the 

color difference between Long Creek and Red Brook for 1940 and 1998. 

33
4. CONCLUSIONS 

This section of the report documents conclusions of the stressor identification process 

based on SOE analysis. The conclusions are organized as follows: 

1. Similarities across all three impaired sites as described by candidate cause, providing a 

watershed perspective on broad-reaching probable causes 

2. Findings unique to each impaired site 

3. Summaries of evidence for each specific effect or biological endpoint 

4. Conclusions about the likelihood of each candidate cause contributing to Long Creek’s 

impairment 

All information found in the SOE tables (SOE Tables 1-50) is not covered in this section; 

rather, key points are highlighted. Further, the project team recognizes that some candidate 

causes have more complete supporting datasets than other causes; this represents a potential 

source of bias in the case study and will be discussed at the end of this report in Section 6. 

4.1. FINDINGS CONSISTENT ACROSS ALL THREE SITES 

4.1.1. Increased Autochthony—An Unlikely Cause 

Chlorophyll a concentrations recorded at four Long Creek sites are higher than at two 

Red Brook sites; however, none of the six measurements were taken at the exact locations of the 

three impaired sites or reference site; rather, the surrogate sites are open-canopy sections of the 

streams. Further, the level at which chlorophyll a concentrations indicate shifts in basal food 

resources, and the transition between autochthony and allochthony, is uncertain. Site 

reconnaissance suggests that all three impaired sites have dominant aquatic vegetation similar to 

the reference site. Scatter plots show that HBI values increase with increasing Kjeldahl nitrogen 

and total and ortho-phosphorus concentrations; relationships with other biological endpoints 

analyzed (EPT richness and percent non-insects) are ambiguous. The functional feeding group 

analysis does not support the increased autochthony hypothesis, because the relative abundance 

of scrapers and filterers decreases relative to the reference site. 

34
4.1.2. Decreased Dissolved Oxygen—A Probable Cause 

Pre-dawn dissolved oxygen measurements are lower at the impaired sites than at the 

reference site. Scatter plots indicate that HBI values increase as dissolved oxygen decreases; 

relationships with other biological endpoints analyzed (EPT richness and percent non-insects) 

are ambiguous. All dissolved oxygen measurements from the impaired sites fall below the U.S. 

EPA benchmark (see SOE Table 23), with expected implications for EPT richness and brook 

trout; all observed levels at the impaired sites also fall below the optimum brook trout level. 

Minimum dissolved oxygen concentrations at the impaired sites are below or close to 

documented EPT 30-day LC50 values. 

4.1.3. Altered Flow Regime—A Probable Cause 

Available evidence indicates that the impaired watershed is impacted by increased 

hydrologic flashiness, characterized by greater peak storm discharges, more frequent peak 

discharges, and lower between-storm baseflow. The majority of evidence specifically points to 

decreased baseflow as a probable cause of impairment. Site reconnaissance and thalweg velocity 

measurements throughout the Long Creek and Red Brook watersheds indicate that Long Creek 

has lower baseflow and less baseflow longitudinal heterogeneity relative to the reference site on 

Red Brook. 

The watersheds contributing to the impaired sites have higher impervious surface areas 

(33%, 14 %, and 7%) than the reference site (2%). If impervious surface area is used as a 

surrogate for altered flow regime in the stressor-response analysis that uses data from other 

studies (see Section 3.2.2.2), then, based on a study of Maine streams conducted by Morse et al. 

(2003), the project team would expect to see decreased EPT richness and brook trout, and 

increased percent non-insects at the impaired sites, which was indeed the case. 

4.1.4. Decreased Large Woody Debris—A Probable Cause 

Scatter plots show that EPT richness increases while percent non-insects and HBI values 

decrease with increasing large woody debris abundance. Evidence from the case was recorded 

as number of pieces of large woody debris along a 100-meter reach near each study site 

(excluding LCN .415). Evidence from other field studies indicates that large woody debris 

abundance is positively correlated with aquatic invertebrate abundance and diversity (Smock et 

al., 1989; Benke et al., 1984) and trout habitat (Neumann and Wildman, 2002; Flebbe, 1999). 

This evidence allowed the project team to make qualitative judgments regarding the case study 

data as part of the stressor-response analysis conducted for data from other studies. Thus, the 

project team assumes that greater abundance of large woody debris increases EPT richness and 

brook trout abundance while less large woody debris does the opposite. In a synthesis report on 

large woody debris, Benke and Wallace (2003) note that the significance of large woody debris 

35
for invertebrates has been documented, but that the quantitative role has not yet been 

determined; the team reached a similar conclusion while conducting this case study.

4.1.5. Increased Sediment—A Possible Cause, but Conflicting Evidence 

Baseflow total suspended solids concentrations at the impaired sites are approximately 

the same as those taken at the reference site, and the values do not exceed levels reported to 

negatively affect aquatic invertebrates or brook trout. The percentages of burrowing and 

sprawling invertebrates, generally representative of higher deposited sediment levels, found at 

the impaired sites are not higher relative to the reference site, also weakening the case for this 

cause. Pfankuch and Rapid Bioassessment Protocol scores provide some support for this 

candidate cause across the impaired sites. Sediment at both the reference site and at the impaired 

sites is potentially fine enough to hinder brook trout egg survival, adding ambiguity to the case 

for this cause; if this were a primary cause of stress to brook trout, the project team would not 

expect to see brook trout at the reference site. Underlying differences in surficial geologies (see 

Appendix E) within the two case study watersheds may ultimately be responsible for differences 

in sediment behavior. The aerial photographs discussed in Section 3.2.4 provide weak support 

for this cause. Three of the five photographs appear to show a greater amount of suspended 

solids in Long Creek relative to Red Brook just upstream of Clark’s Pond. 

The project team acknowledges that the case study streams are sandy-bottomed 

(reference and impaired sites), and biological sampling data, as used by the project team, was 

gathered using MEDEP’s standard rockbag collection techniques. The rockbag sampling 

mechanism may have provided refuge for some organisms not naturally present at the sites, and 

consequently, impacted sampling results and SOE conclusions, specifically with respect to 

substrate and the increased sediment candidate cause. However, while not detailed in this report, 

MEDEP also conducted D-frame, kicknet, multihabitat sampling of sites, which removes (or 

alters) the potential substrate sampling bias. Based on cursory review by project team biologists, 

multihabitat sampling results reflect similar biological conditions and trends as determined by 

the rockbag results. Information on the multihabitat sampling data can be found in MEDEP 

(2002a). 

 The project team cannot rule out increased sediment as a potential cause, likely in the 

form of fine bedded sediments, but the degree to, and mechanisms by which it is acting are 

unclear. 

4.1.6. Increased Temperature—A Probable Cause 

Measured temperatures at the impaired sites are higher than those measured at the 

reference site. Scatter plots indicate that HBI values increase with increasing maximum 

temperature, but relationships with other invertebrate endpoints are ambiguous. The stressor36
response analysis based on data from other studies supports the case for this cause for the EPT 

richness and brook trout endpoints, to varying degrees among the impaired sites. 

4.1.7. Increased Toxic Substances—Ionic Strength is a Probable Cause 

Impervious surface area within the impaired watersheds is higher relative to the reference 

site, providing a potential means (that is, a step in the causal pathway) for increased stormwater 

concentrations of toxic substances to reach the impaired streams. 

The project team cannot rule out metals and PAHs for which field data and stressorresponse data, based on evidence from other studies, are sparse. 

Baseflow measurements of specific conductivity and chloride are higher at the impaired 

sites than at the reference site, supporting the case for toxicity due to increased ionic strength. 

Scatter plots indicate that EPT richness decreases while HBI values and percent non-insects 

increase with baseflow chloride and specific conductivity. Of the scatter plots used for stressorresponse relationships from the field, specific conductivity and chloride appear to show the 

strongest correlations, supporting the case for toxicity due to ionic strength. The observed 

relationship between EPT richness and specific conductivity within the study area is consistent 

with relationships observed throughout Maine (Figure 6) and in Florida and Kentucky 

(Appendix J). 

There is debate among scientists as to the mechanisms responsible for biological 

impairment associated with ionic strength. For example, disruption of osmotic regulation, 

decreased bioavailability of essential elements, increased availability of toxic metal ions, 

increases in other particularly harmful ions, ionic composition changes, or other as yet unknown 

mechanisms may all affect toxicity associated with ionic strength. The project team 

acknowledges that teasing apart proximate stressors and interacting stressors associated with 

ionic strength may not be possible at this point but the team recognizes that there is significant 

supporting evidence to promote ionic strength from candidate to probable cause of impairment. 

As a probable cause, increased ionic strength at the impaired sites may not be responsible for 

organism mortality, but rather a shift in community structure (also see Section 4.3.2). 

4.2. FINDINGS PARTICULAR TO INDIVIDUAL SITES 

Table 8 summarizes findings unique to one or common between two of the three 

impaired sites. Stakeholders involved with management decisions may benefit by addressing 

watershed-wide causes of impairment and causes of impairment unique to specific locations 

within the project area. 

37
Figure 6. Maine stream mayfly abundance versus specific conductivity. 

Sample size = 175 

Source: Analysis and presentation of data adapted from Davies et al. (unpublished). 

M

a

yfly A

bundanc

e

0

100

200

300

400

500

600

Specific Conductivity, uS/cm

0-30 30-60 60-100 100-200 >200

38
Table 8. Unique findings by candidate cause and site a

Candidate 

cause LCN .415 LCM 2.270 LCMn 2.274 

Increased autochthony 

Evidence for increased autochthony at LCN .415 is ambiguous; stressor-response relationships from laboratory or other field studies show that baseflow phosphorus levels might be causing effects, but other measures are at or below benchmark criteria. 

Evidence is sparse for these two sites. Stressor-response relationships from laboratory or other field studies weaken the case for this cause because measured nutrient values 

are at or below benchmark criteria. 

Altered flow regime 

A storm event hydrograph and related analysis show that this site's hydrology has been altered (greater and more frequent peak flows and lower baseflows). 

Detention upstream of this site may contribute to reduced baseflows. There is some evidence for channel alteration. Thalweg velocity measurements were not taken at the site, but those close to the site suggest that longitudinal flow heterogeneity and baseflow are low along this reach. 

Baseflow velocity was lower at LCMn 2.274 relative to the reference site, and thalweg velocity measurements were often equal to zero in the vicinity of the site. Longitudinal flow heterogeneity is low in the vicinity of this site compared to the reference site. There is evidence for channel alteration and decreased large woody debris, which may be indicative of altered flow. 

Decreased large woody debris 

For this site specifically, the majority of support rests with the scatter plot analysis as described in the text for all three impaired sites. 

Abundance measurements for large woody debris at these two impaired sites are lower than at the reference site. 

Depositional “muck-mud” is higher at the impaired site. 

Depositional “muck-mud” is lower at the impaired site. 

Increased sediment 

Stormflow total suspended solids (TSS) concentrations are higher at LCN .415 relative to the reference site, and potentially high enough to cause decreases to invertebrate populations. Depositional “muck-mud” is, however, lower at the impaired site. RBP sediment deposition scores are lower relative to the reference site (i.e., worse at the impaired site) although substrate scores are the same. Sediment sizes are slightly higher relative to the reference site, weakening the case that fine sediments may be hindering brook trout egg survival. 

Storm event total suspended solids (TSS) data are not available for these two sites. 

RBP substrate and deposition scores are approximately the same relative to the reference site. As mentioned in the text for all three impaired sites and the reference site, sediments are potentially fine enough to hinder brook trout egg survival; however, while sediments at the reference site are small, sediments at these two impaired sites (LCM 2.270 & LCMn 2.274) are especially small (i.e., greater than 90% of particles are between 0.062 & 0.13 mm at the impaired sites, as opposed to 53% at the reference site). 

39
Table 8. Unique findings by candidate cause and site a (continued) 

Candidate 

cause LCN .415 LCM 2.270 LCMn 2.274 

The upstream detention pond and riparian devegetation associated with the golf course may contribute to increased temperature. 

Temperatures recorded at this site did not conclusively exceed those observed at the reference site. Riparian devegetation associated with the upstream office park may contribute to increased temperature. 

Increased temperature 

Watershed impervious surface area is high at this location; the project team found some literature correlating temperature and impervious surface, additional research in this area may be helpful for understanding the impact of temperature and impervious surfaces, in the context of Long Creek. Rockbag sampling shows Caenis sp. (Ephemeroptera) as the second most abundant 

organism at these two sites but absent at the reference site and at LCN .415. While 

EPT taxa generally are more sensitive to ecosystem alterations, Caenis sp. is tolerant 

of high temperature (literature review by Galli and Dubose, 1990); however, this may be a deceptive indicator, as Caenis sp. is known to be tolerant of other stressors (e.g., low baseflow). 

Increased toxic substances 

Stormwater measurements for concentrations of 

lead, zinc, copper, chloride, and PAHs are high relative to the reference site, but nothing stands out except stormflow copper. Stressor-response relationships from other studies indicate that episodic toxicity from metals, such as copper in stormflows, may reach levels capable of impacting EPT & brook trout. Sediment toxicity tests showed no decreases in survival of amphipods or midges relative to the reference site. 

The stressor-response analysis does not support the case for toxicity due to metals (at least, for those sampled) in baseflow. 

Sediment toxicity tests showed no decreases in survival of amphipods or midges relative to the reference site. Stressor-response relationships from other studies do not support the case for toxicity due to metals (at least, for those sampled) in baseflow. 

a This table shows findings unique to one or two sites only; findings that are similar across all three impaired sites are discussed in the text (decreased dissolved 

oxygen is not shown here because findings were consistent across all three impaired sites). 

40
4.3. ENDPOINT SPECIFIC FINDINGS 

4.3.1. Decreased EPT Richness 

Available evidence supports decreased dissolved oxygen, toxicity due to ionic strength, 

altered flow regime, and decreased large woody debris as probable causes for decreases in EPT 

richness across all three impaired sites. The project team suspects decreased dissolved oxygen 

and altered flow regime (specifically decreased baseflow) act jointly to decrease EPT richness at 

the impaired sites (see Section 5.1). More detailed discussion of ionic strength and 

Ephemeroptera is included in Section 4.1. Increased temperature is a probable cause for 

decreased EPT richness at LCM 2.270 and LCMn 2.274.

4.3.2. Increased Percent Non-insects 

Increased ionic strength may be responsible for increases in percent non-insects at LCN 

.415 and LCM 2.270. (The project team did not analyze the third impaired site, LCMn 2.274, in 

terms of the percent non-insects endpoint; see Section 2.3.) 

In laboratory tests conducted to determine relative salinity tolerances of various 

freshwater macroinvertebrates, Kefford et al. (2003) observed that macrocrustaceans 

(specifically Decapoda, Amphipoda, and Isopoda) were the most salt-tolerant group tested. 

Conversely, baetid mayflies (Ephemeroptera: Baetidae) were the most salt-sensitive group 

(Kefford et al., 2003). An amphipod was the most abundant organism found at LCN .415, and 

an isopod was the fifth most abundant organism at LCM 2.270. Only one isopod individual was 

found at the reference site. Figure 7 shows relative organism abundance, broken down by 

Kefford et al.’s (2003) salt-sensitivity categories, from all nine monitored project sites as a 

function of specific conductivity. Relative organism abundances plotted in Figure 7 appear to 

peak at some optimal specific conductivity and then decrease as the stressor increases; albeit, the 

sample size of the team’s project site data is low. However, a similar trend can be seen 

throughout Maine (Figure 6). Figure 7 indicates that amphipods and isopods may be better 

suited to take advantage of higher conductivity (such as levels found at the impaired sites) than 

baetid mayflies. Overall, this evidence supports the case for increased ionic strength as a 

probable cause at the impaired sites. Non-insect, salt-tolerant organisms such as amphipods and 

isopods may be advantaged while salt-sensitive organisms are not, thereby causing overall 

invertebrate community shifts. Note that case study salinity levels are likely below mortality 

thresholds for sensitive taxa, but these levels may support certain biological preferences and/or 

adaptations, ultimately contributing to the observed biological conditions at the impaired sites. 

41
LCN .415

LCM 2.270

L

C

Mn 2.274

LCN .415

0%

6%

12%

18%

24%

0 250 500 750 1000

Specific Conductivity, μS/cm

R

elative Organism Abundance,

RB 3.961

Salt-tolerant:

 Amphipoda %

 Isopoda

Salt-sensitive:

 Baetidae

42

Figure 7. Relative organism abundance versus specific conductivity at project site. 

Specific conductivity measured at the nine project area sites (six on Long Creek, and 

three on Red Brook) as a function of organisms known to be salt-tolerant and saltsensitive, as defined by Kefford et al. (2003). 

conductivity measured at the nine project area sites (six on Long Creek, and 

three on Red Brook) as a function of organisms known to be salt-tolerant and saltsensitive, as defined by Kefford et al. (2003). 
4.3.3. Increased HBI Score 

Stressor-response relationships from the field (see Appendix H, scatter plots) indicate that 

HBI values may be responsive to a variety of variables, more so than for the EPT richness and 

percent non-insects endpoints. Based on available evidence, decreased dissolved oxygen is 

likely a primary cause for increased HBI values because HBI was designed to assess low 

dissolved oxygen caused by organic loading. Again, note that altered flow regime may be acting 

jointly with decreased dissolved oxygen (see Section 5.1). 

4.3.4. Absence of Brook Trout 

Decreased dissolved oxygen, altered flow regime, increased temperature, decreased large 

woody debris, and increased sediment are the probable causes linked to brook trout absence. 

According to the stressor-response analyses from other studies, temperatures are high enough 

and dissolved oxygen levels low enough at all three impaired sites to negatively affect brook 

trout. Lowered baseflow may create a situation whereby fish lack water volume and depth 

necessary for survival. In addition, sediment sizes at LCM 2.270 and LCMn 2.274 are 

potentially fine enough to hinder brook trout egg survival. 

4.4. SUMMARY CONCLUSIONS 

The project team did not find a single, primary cause of impairment for the Long Creek 

watershed or for an individual impaired site. Rather, the SOE analysis suggests several probable 

causes of impairment: 

• Decreased dissolved oxygen 

• Altered flow regime (specifically, decreased baseflow) 

• Decreased large woody debris 

• Increased temperature 

• Increased toxic substances (specifically increased ionic strength) 

These conclusions are presented by site and biological endpoint in Table 9. The 

importance of individual stressors varies among the impaired sites. The project team attempted 

to rank probable causes in order of importance for each site and endpoint in Table 9. 

Consistency of evidence scores (i.e., ++, +, 0, and -) weigh heavily in the team’s consideration 

for ordering the causes in Table 9, but it is within this table that the project team employed 

professional judgment, based on the entire SOE analysis and all available data. 

Results and analyses from this case study are helping guide the MEDEP and other 

stakeholders in improving and managing the Long Creek watershed.

43
Table 9. Probable causes of impairment a

Biological effect 

Impaired 

site Decreased EPT richness

Increased % noninsects Increased HBI Brook trout absence

LCN .415 

increased ionic strength altered flow regime decreased dissolved oxygen decreased large woody debris 

increased ionic strengthaltered flow regime 

altered flow regime decreased dissolved oxygen 

altered flow regime increased temperature decreased dissolved oxygen decreased large woody debris 

LCM 2.270 

decreased dissolved oxygen increased temperature increased ionic strength decreased large woody debrisaltered flow regime 

increased ionic strength decreased dissolved oxygen decreased dissolved oxygen 

increased temperature increased sediment decreased large woody debrisaltered flow regime 

LCMn 2.274 

decreased dissolved oxygen increased temperature increased ionic strength decreased large woody debrisaltered flow regime 

not evaluated altered flow regime 

decreased dissolved oxygen 

decreased dissolved oxygen altered flow regime increased sediment increased temperature decreased large woody debris 

a Probable causes are listed in order, from highest to lowest importance, as judged by the project team, within each cell.

44
5. DISCUSSION 

Two topics merit further discussion upon completing the Strength of Evidence (SOE) 

analysis. First, several candidate causes identified as probable causes are interrelated. 

Interactions are discussed from a general perspective in Appendix F, and that discussion is 

expanded upon here in terms of what the project team learned in the SOE analysis and in terms 

of implications for causal assessment in general. Second, the team discusses the certainty of its 

conclusions in the context of future data collection efforts that could be of value. 

5.1. INTERACTING URBAN STRESSORS AND CAUSAL ASSESSMENT 

Urbanized watersheds are often subject to multiple, interacting causes of impairment. 

Consider the following hypothetical example: decreased baseflow and water depth, two 

common manifestations of altered flow regime, may directly reduce suitable habitat for some 

organisms. Decreased baseflow may also reduce turbulence, thereby decreasing dissolved 

oxygen. Decreased water depth may facilitate increases in water temperature (the temperature of 

shallow water rises more quickly than that of deep water), thereby increasing metabolic rates in 

organisms. Subsequently, higher metabolic rates may increase demand for dissolved oxygen, 

while decreased turbulence decreases availability of dissolved oxygen. Dissolved oxygen is less 

soluble at both higher temperatures and higher salinity levels (or ionic strength), and when 

salinity climbs above favorable levels, sensitive species will spend more metabolic activity on 

osmoregulation, thereby limiting energy normally dedicated to other processes, such as that 

aimed at dealing with increased temperatures. These kinds of interactions may mislead and 

confound causal assessments, including the Long Creek case study. Note that in the above 

example, some agents, such as altered flow regime, stand alone as proximate stressors and serve 

as steps in the causal pathways of other proximate stressors. 

5.1.1. Decreased Dissolved Oxygen and Altered Flow Regime 

Decreased dissolved oxygen and altered flow regime, as two probable causes, may be 

acting as proximate stressors individually (see Section 4) at the Long Creek impaired sites. 

Additionally, decreased current velocity, a likely effect of decreased baseflow for Long Creek, 

serves as a potential step in a causal pathway leading to decreased dissolved oxygen (CM Figure 

3 and Appendix F). The two causes may also be acting jointly as follows. As dissolved oxygen 

decreases, sensitive invertebrates may need additional current velocity so that more oxygen 

flows over their gills. Others have acknowledged a similar relationship among flow-dependent 

EPT, flow regime, and dissolved oxygen concentration (Jaag and Ambühl, 1964; Bednarek and 

Hart, 2005). For example, the mayflies shown in Figure 8 (Rhithrogena and Baetis) can tolerate 

low dissolved oxygen so long as minimum current velocities are met. Given the low velocities 

45
and decreased dissolved oxygen at the impaired Long Creek sites, it is possible that these two 

stressors act in concert. Further, both causes frequently appear among the probable causes 

shown in Table 9. 

0

1

2

3

4

5

6

012345

Current velocity (cm/s)

Dissolved oxygen (mg/L)

Rhithrogena semicolorata

Baetis vernus

Ephemerella ignita

Ecdyonurus venosus

6

Figure 8. Impact of low dissolved oxygen & low current velocity on selected 

organisms. 

Organism lines represent various mayfly nymphs and the point at which survival is 

compromised by lack of oxygen and reduced flow velocity. Source: adapted from Jaag 

and Ambühl (1964). 

5.1.2. Increased Temperature and Decreased Dissolved Oxygen 

Similar to the above interaction, increased temperature and decreased dissolved oxygen 

are probable causes individually (see Section 4), increased temperature is a step in a causal 

pathway leading to decreased dissolved oxygen (CM Figure 3 and Appendix F), and the two 

stressors may work together as follows. When temperature increases, sensitive species require 

additional dissolved oxygen because higher temperatures increase many coldwater organisms’ 

investment in respiratory processes. Allan (1995) describes this connection and makes specific 

mention of caddisflies and stenothermic fish such as trout being susceptible to this joint 

interaction. The U.S. EPA ambient water quality criteria document for dissolved oxygen (U.S. 

EPA, 1986a) lends additional support, arguing that the two stressors may act additively or 

synergistically. Temperatures at Long Creek’s impaired sites are at levels described by Allan 

(1995) as problematic, and the sites have decreased dissolved oxygen levels. 

46
 Sites within the project area with high temperatures generally have low dissolved oxygen 

levels (Figure 9). Stressor-response relationships from other studies show approximately equal 

support for both temperature and dissolved oxygen as individual causes at the Long Creek 

impaired sites. Purely from a water chemistry perspective, oxygen is more soluble in water at 

lower temperatures; considering the range of temperatures in this case study (see SOE Table 27), 

for example, the weekly summer maximums for RB 3.961, 21.1°C, and LCM 2.270, 23.3°C, this 

translates to a difference in potential oxygen solubility of approximately 0.5 mg/L (transpose 

temperature values to Figure 10 in order to estimate this difference in potential oxygen 

solubility). Given these considerations, it may be difficult, if not impossible, to discern which 

among the following plays a more significant role at the impaired sites: 

• Increased temperature as an individual proximate stressor 

• Decreased dissolved oxygen as an individual proximate stressor 

- with increased temperature as a causal pathway step 

- without temperature as a causal pathway step 

• Increased temperature and decreased dissolved oxygen, working jointly 

5.1.3. Other Potential Interactions 

 Similar to the above mentioned interactions among dissolved oxygen, flow regime, and 

temperature, the following interactions may also be acting at the impaired Long Creek study 

sites. Decreased baseflow serves as a causal agent for temperature increases by increasing the 

amount of time water is exposed to sunlight, and shallower flows allow heat transfer to occur 

more rapidly. Decreased large woody debris can reduce turbulence and aeration, thereby 

decreasing dissolved oxygen. Decreased large woody debris may affect sediment distribution 

patterns along stream bottoms, decreasing habitat heterogeneity. 

Primarily based on water chemistry principles, the project team was able to limit support 

for two potential interactions as follows. Temperature could be presented as a causal pathway 

step for ionic strength because salt solubility increases as temperature increases. Figure 11 

shows that project area sites with high specific conductivity generally have high temperatures. 

However, a much greater temperature increase is needed to significantly raise the solubility of 

salt in water (Figure 10). Similarly, ionic strength could serve as a causal agent for dissolved 

oxygen (oxygen solubility in water varies with elevation, temperature, and salinity); within the 

project area, however, there does not appear to be a correlation between the two variables 

(Figure 12). Furthermore, salinity values observed at project sites (all less than 700 ppm, 

MEDEP, 2002a) are not at levels capable of significantly decreasing or increasing the solubility 

of oxygen in water (Figure 10; consider “salinity = 0” appropriate for all project sites). 

47
I

H

G

F

E

D

C

B

A

5

6

7

8

9

10

20 21 22 23 24

Temperature, weekly summer maximum °C

Dissolved Oxygen, mg/L

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

Figure 9. Dissolved oxygen versus temperature at project site. 

6

8

10

12

10 14 18 22 26 30

Temperature, °C

Dissolved oxygen, mg/L at saturation

salinity = 0

salinity = 5,000 ppm

salinity = 35,000 ppm

(~ ocean water)

Figure 10. Oxygen solubility versus temperature at various salinities. 

Source: adapted from Stickney (1979).

48
A

B

C

D

E F

G

H

I

20

21

22

23

24

0 200 400 600 800 1000 1200

Specific Conductivity, μS/cm

Temperature, weekly summer maximum °C

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

Figure 11. Temperature versus specific conductivity at project site. 

A

B

C

D

E

F

G

H

I

5

6

7

8

9

10

0 200 400 600 800 1000 1200

Specific Conductivity, μS/cm

Dissolved Oxygen, mg/L

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

Figure 12. Dissolved oxygen versus specific conductivity at project site. 

49
5.1.4. Negotiating Causal Interactions 

Interacting candidate causes present potential challenges for causal assessment. The 

discussion at the end of Section 5.1.2 illustrates the difficulty in ranking one probable cause 

above another if the two causes are suspected to interact. The project team now introduces a 

potential second challenge. Take for example, three candidate causes—X, Y, and Z—which are 

identified and analyzed using SOE associations as described herein. Upon completion of SOE 

scoring, neither X nor Y stands out as probable causes of impairment, and so attention shifts to 

candidate cause Z, which happens to have the most supporting evidence. As individual causes, 

X and Y are insignificant both in the field and as determined by this hypothetical causal analysis; 

however, a problem may arise if X and Y are allied stressors acting jointly to cause more damage 

than candidate cause Z. Aside from speculating on the significance of causal interactions upon 

completing SOE scoring, what could the hypothetical XYZ causal analysis team do differently to 

accommodate potential interacting causes of impairment within their SOE analysis? The Long 

Creek project team was lucky in that the X and Y equivalents do stand out individually as 

probable causes of impairment, and there is no single smoking gun, or Z equivalent, that draws 

attention away from potential X-Y interactions. 

To negotiate assessment of interacting causes, the combination of two or more causes 

could be analyzed separately. Along these lines, the new joint cause (e.g., “Candidate Cause #X: 

decreased dissolved oxygen allied with decreased baseflow”) could be added as a new column in 

scoring tables (e.g., see SOE Tables 40-42), and a new conceptual model could be developed for 

the new joint cause, representing a single proximate stressor (i.e., a single square box at the 

bottom of a new conceptual model). However, the Long Creek project team was challenged to 

find relevant stressor-response relationships from other studies for joint causes. Figure 8, the 

only three-dimensional stressor-response relationship from another field study found appropriate 

for use in this case study, shows a biological response as a function of two stressors—low 

dissolved oxygen and low current velocity. Joint or allied candidate causes may be significant 

causes of impairment for Long Creek, but quantifying joint risks in comparison to individual 

probable causes may not be feasible (see, for example, conclusions drawn in Section 5.1.2). 

Alternatively, it may be appropriate to de-emphasize ranking or comparison among 

individual causes and joint causes. Causes might be grouped to reduce effort spent on analyzing 

individual ones that ultimately cannot be prioritized due to confounding interactions. Allied 

stressors may also be added to candidate cause lists at the beginning of the stressor identification 

process. Given the complexity of interactions and potential joint impacts of candidate causes 

associated with this urban case study, the project team suggests that prudent remedial action 

target anthropogenic activities common to multiple probable causes. Impervious surface area, 

for example, is listed as one of the anthropogenic activity sources of all probable causes 

identified in this case study. Perhaps groups of causes could be combined according to common 

50
anthropogenic activities either at the beginning of the stressor identification process or during 

probable cause consideration. As more case studies are completed using U.S. EPA Stressor 

Identification guidance, it may be possible to begin new analyses with predetermined causal 

groups and to know specific causal interactions to watch out for, based on ecoregion (e.g., 

northeastern coastal zone) and general land use (e.g., urban and industrial). 

Impervious surface area upstream of an impaired site may be a suitable surrogate for 

general urban impairment. The three impaired sites have impervious surface areas of 7%, 14%, 

and 33%. Morse et al. (2003) found that insect communities in Maine streams show an abrupt 

decline in taxonomic richness as impervious surface area increases above 6%. All three 

impaired sites have impervious surface areas greater than 6%. The Morse et al. (2003) study 

mainly focuses on the negative impact of impervious surface area on EPT taxa. Maxted (1996) 

noted a shift toward tolerant taxa (represented by percent non-insects and HBI values at the Long 

Creek study sites) at impervious surface areas of 10 to 15%. Boward et al. (1999) were unable to 

find brook trout in Maryland watersheds with impervious surface area levels greater than 2%. 

However, Meidel and MEDEP (2005) found an exception to this general trend: 23 brook trout in 

a Maine stream with 13% impervious surface. MEDEP staff note that this may be an anomaly 

because of high groundwater input of cold water in the site’s vicinity, potentially creating a 

refuge where at least one criterion favoring brook trout is exceeded. Surrogate measures of 

impairment offer advantages to causal assessment, but caution must be taken to account for 

additional assumptions introduced by such measures. 

 The most immediate influences of increased impervious surface area (in northeast U.S. 

watersheds) may be alteration of hydrologic processes, a myriad of related impacts due to 

vegetation removal and increased application road salt in winter. The strongest direct evidence 

for altered flow regime are the single storm hydrograph for LCN .415 (Figure 13) and the 

thalweg flow velocities recorded along Long Creek and Red Brook (Figure 14), re-enforced by 

anecdotal feedback from MEDEP staff indicating that Long Creek seems to have lower baseflow 

relative to Red Brook during site visits. The SOE for road salt reaching the impaired sites is 

supported by spatial/temporal co-occurrence specific conductivity data. Figures 15 and 16 

indicate that increasing impervious surface area and chloride (a common road salt constituent), 

respectively, correlate with increasing specific conductivity throughout the project area. 

51
0

302010

0 5 10 15 20 25 30 35 40

Time, hr

Discharge, cfs

LCN .415contributing watershed area: 260 acreswatershed impervious surface area: 33%event runoff volume: 7.2 ac-ftevent runoff volume / watershed area: 0.0276 ac-ft/acRB 1.694contributing watershed area: 1350 acreswatershed impervious surface area: 6%event runoff volume: 5.5 ac-ftevent runoff volume / watershed area: 0.0041 ac-ft/ac

Figure 13. Storm hydrographs on Long Creek and Red Brook, September 25, 2001. 

52
0.80

0.600.400.200.00

0 20 40 60 80 10

0.800.600.400.200.00

0 20 40 60 80 100

0.800.600.400.200.00

0 20 40 60 80 100

Thalweg Velocity, m/s

0.800.600.400.200.00

0 20 40 60 80 10

0.800.600.400.200.00

0 20 40 60 80 100

0.800.600.400.200.00

0 20 40 60 80 10

Distance, m

0.800.600.400.200.00

0 20 40 60 80 100

Distance, m

0.800.600.400.200.00

0 20 40 60 80 100

Distance, m

Thalweg Velocity, m/s

LCM .603 gradient = 0.0012 

LCM .910 gradient = no data 

LCM 1.653 gradient = 0.0002 

LCM 3.098 gradient = no data 

RB .071 gradient = no data RB 3.961 gradient = 0.0019 

RB 2.119 gradient = 0.0012 

LCMn 2.274 gradient = 0.0017 RB 1.434 gradient = 0.0015 

0.800.600.400.200.00

0 20 40 60 80 100

Thalweg Velocity, m/s

0

00

Figure 14. Baseflow thalweg velocity measurements throughout project site. Measurements were taken at 2-m intervals in the vicinity of the site; gradients are expressed in feet/feet. 

Highlighted plots/sites are the focus of this case study. Source: MEDEP (2002a).

53
A

B

C

D

E

F

G

H

I

0

200

400

600

800

1000

1200

0 10 20 30 40 5

Impervious Area, % of contributing watershed

Specific Conductivity, 

μS/cm

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

0

Figure 15. Specific conductivity versus impervious area at project site. 

A

B

C

D

E

F

G

H

I

0

200

400

600

800

1000

1200

0 50 100 150 200 250

Chloride, mg/L

Specific Conductivity, 

μS/cm

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

Figure 16. Specific conductivity versus chloride at project site. 

54
5.2. CONFIDENCE IN CONCLUSIONS 

“All scientific work is incomplete—whether it be observational or experimental. 

All scientific work is liable to be upset or modified by advancing knowledge. That 

does not confer upon us a freedom to ignore the knowledge we already have, or to 

postpone the action that it appears to demand at a given time.” 

—Sir Bradford Hill, 1965 

The project team lists multiple probable causes of impairment in Section 4. Lack of 

evidence may have prevented promotion of one probable cause over another, in terms of 

significance for a particular study site. As discussed in Section 5.1, isolating individual urbanrelated candidate causes may not be possible or necessary. Unlike some other stressor 

identification case studies (refer to the CADDIS Web site, http://www.epa.gov/caddis, for 

examples), this report points to multiple candidate causes with little distinction among causes 

regarding significance to the project site. For the benefit of decision makers, however, the 

project team circumvents this issue by emphasizing anthropogenic activities or sources common 

to multiple stressors, such as impervious surface area, thereby empowering future efforts aimed 

at improving the Long Creek and Maine ecosystems. 

Ultimately, the project team is confident in the conclusions as they are. Some readers 

may prefer a single, “smoking gun” cause of impairment. This was not determined for the Long 

Creek case study, nor for any given Long Creek study site. This, however, does not reflect 

poorly on the stressor identification process as a tool in and of itself, nor implementation of the 

process for this particular case study. Rather, there are simply multiple probable causes of 

impairment at the case study sites. 

The project team concludes that some level of uncertainty is inherent to causal assessment, 

perhaps especially for urban ecosystems. That said, and in no way negating the high level of 

confidence in the conclusions already drawn, much of the remaining uncertainty for this case 

study may be explained by two factors: 

• Lack of sufficient case-specific data collected at the project’s reference and impaired 

sites, including measurements of biological conditions and/or stressors such as stormflow 

water quality observations 

• Lack of research needed to understand case-specific data including, for example, stressorresponse relationships based on data from elsewhere, regional reference criteria, and/or 

literature and information about candidate causes 

55
5.2.1. Case-Specific Data and Research Needs 

 The project team compiled a robust data set specific to the case study including both the 

impaired sites and other sites throughout the Long Creek and Red Brook watersheds; 

nevertheless, this causal analysis could have been strengthened by additional data including: 

• Flow regime or hydrology data – Historical stream flow time series data measured at 

the reference and impaired sites may have provided valuable information about the 

impacts of altered flow regime. 

• Total suspended solids measurements – Available baseflow suspended sediment data 

are sparse and some measurements may not meet MEDEP quality control criteria; 

additional stormflow suspended sediment data taken throughout the project area would 

have been desirable. 

• Pesticide measurements – The project team did not test for herbicides, fungicides, or 

insecticides; this may have been especially valuable downstream of intensive landscaping 

efforts such as in the vicinity of golf courses. 

• Stormflow metal concentrations – These data are limited to surrogate sites for LCN 

.415 and the reference site, and the data indicate that episodic toxicity from Cu is a 

possible cause of impairment. It might benefit the study to have stormflow metal 

concentration samples from more locations. 

5.2.2. Research Needed To Understand Case-Specific Data 

Large woody debris – Decreased large woody debris is listed as a probable cause of 

impairment. However, stressor-response relationships from elsewhere were used to support this 

cause directionally. Specifically, the project team was unable to compare large woody debris 

numbers or thresholds from the literature to those data collected at the study sites, and, therefore, 

the team supported the conclusions qualitatively by showing that more large woody debris would 

be helpful for EPT and brook trout at the impaired sites based on general research about the 

importance of large woody debris. A reasonable amount of site data exists but research needed 

to quantitatively understand the data does not. It would be helpful to have more quantitative 

stressor-response information related to specific mechanisms through which this proximate 

stressor impacts biological endpoints (e.g., large woody debris substrate for EPT taxa, cover for 

fish, and physical source of aeration/dissolved oxygen). Regional baseline data may also be of 

value. 

Brook trout habitat – Knowledge of historic brook trout habitat is limited for the case 

study area and the state of Maine; it would be valuable to know what the historic and/or bestcase scenarios of brook trout habitat are for the case study region, taking into consideration 

56
variables such as surficial geology and the life cycle of brook trout, both of which may be 

relevant to this case study. 

Relationship between stream temperature and impervious surface – There does not 

appear to be a clear correlation between temperature and impervious surface area within the 

project area (Figure 17). However, Morse (2001) discusses several causal pathways linking 

impervious surface and temperature in his literature review of the subject, specific to the 

northeastern U.S. Additional research regarding the mechanisms of this linkage may be valuable 

for this and other studies. 

Ionic strength and winter sanding, salting, and plowing – Recent studies in 

Northeastern U.S. show that road salting threatens freshwater ecosystems (Kaushal et al., 2005). 

The project team found supporting evidence for increased ionic strength as a candidate cause in 

the Long Creek watershed, and roads within the watershed are salted during winter, but data 

from outside the case study appears weak in this area. Considering the potentially contentious 

topic of decreasing winter road salt applications to minimize salinization of freshwater streams, 

more research on methods and impacts of winter road maintenance techniques may benefit 

causal assessments and help managers devise alternatives. 

I

H

G

F E

D

C

B

A

20

21

22

23

24

0 10 20 30 40 5

Impervious Area, % of contributing watershed

Temperature, weekly summer maximum °C

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

0

Figure 17. Temperature versus impervious area at project site. 

57
6. LESSONS LEARNED 

6.1. UNEVEN EVIDENCE—ADDRESS POTENTIAL BIASES 

Some candidate causes evaluated in this case study have more supporting data than 

others. For example, the project team does not have spatial/temporal co-occurrence data for 

altered flow regime and decreased large woody debris for all three impaired sites. The team 

discusses other specific data gaps in Section 5.2. Uneven data sets among candidate causes have 

the potential to impact Strength of Evidence (SOE) scoring; the U.S. EPA Stressor Identification 

consistency of evidence association scoring system (see SOE Table 39) differentiates +++ versus 

+, and - - - versus - indicating that a single + or - be assigned if “few” types of evidence are 

available. Caution should be taken where uneven evidence may impact SOE scores. 

The project team attempts to remove bias related to uneven evidence among causes by 

discussing the relative strengths and weaknesses of the data primarily when drawing conclusions 

about probable causes in Section 4. The team also acknowledges data gaps in Section 5.2, 

further qualifying the strength of the team’s results. SOE scores are not a final judgment; the 

scores must be put into context when conclusions are drawn, thereby providing causal 

assessment teams an opportunity to revisit potential causes, making sure causes are not 

overlooked simply because certain data were not collected. 

6.2. BIOLOGICAL ENDPOINTS—CHOOSE SIMPLER MEASURES 

The project team identified effects, or biological endpoints, representing a wide range of 

complexity. The brook trout endpoint is the simplest; the team relates the response as a binary 

variable, indicating presence or absence of a single species. The next simplest is the EPT 

richness endpoint, for which a generic count from three insect orders is used. The percent noninsects endpoint is more complicated because of its relativity to insect abundance; further, it is 

less descriptive in terms of not knowing which specific non-insects are relatively more or less 

abundant than specific insects or other non-insects. The HBI index is the most complicated 

variable. HBI is calculated by multiplying the abundance of observed organisms by assigned 

tolerance values, specific to organic pollution, summing the products, and dividing by the total 

number of individuals. 

Simplified specific effects may be of greater benefit to causal assessment than more 

complicated variables such as percentages and indices. The complexities and unknowns 

associated with the percent non-insects and HBI endpoints as mentioned above may have been 

avoided by identifying more specific endpoints. Furthermore, the project team’s endpoints 

overlap to some degree; for example, the project team may be double counting some organisms 

with the use of HBI and EPT. Consider also that a biotic index, such as HBI, may be responding 

to multiple stressors, not solely stress related to the index’s focus (i.e., organic pollution for 

58
HBI). This phenomenon appears to be demonstrated by the scatter plot analysis described earlier 

in the report (see HBI specific summary in Section 4). The team recommends future causal 

assessors select endpoint variables that are as specific as possible. 

6.3. MULTI-STAGE CAUSAL ANALYSIS—STRATEGIZE IN ADVANCE 

This causal assessment may have been conducted more efficiently and the results 

determined with more certainty if data collection had proceeded in two stages, with biological 

monitoring conducted first (perhaps as a scaled back effort), followed by thorough water quality, 

habitat, and biological monitoring at specific sites, rather than one large-scale data collection 

effort. The project team recognizes that this is not always possible; for the Long Creek case 

study, data were collected as part of a previous study and at sites that were not included in this 

causal assessment because the sites met class designations. U.S. EPA Stressor Identification 

guidance provides a basis for designing such a two-stage analysis. The guidance recommends 

determining biological impairments before causal analysis begins; actual causal analysis might 

proceed alongside and potentially guide water quality data collection efforts. 

Several steps aimed at increasing efficiency and certainty of results might be conducted 

between the two stages mentioned above. 

Choice of sites – Reference and impaired sites to be studied should be determined prior 

to stressor data collection. For the Long Creek case study, this may have helped to concentrate 

time spent in the field on sites of primary concern and avoid data gaps among candidate causes. 

If multiple potential study sites are appropriate for a particular case study but a limited number of 

sites will be studied, sites may be strategically chosen to take advantage of existing historical 

data. For example, if a watershed or site has historic stream gage and precipitation records 

associated with it or presently operating gages, this may be a good location to focus collection of 

stressor data. 

Analysis of biological monitoring data – Functional feeding group, mode of existence, 

and indicator species analyses may provide case study teams with clues about what is and is not 

happening in their study areas and help direct the types of stressor data to be collected at the 

study sites. 

Determination of specific biological effects or endpoints – It may be possible to group 

reference or impaired sites with similar attributes. Results from this causal assessment may have 

been strengthened with little additional effort if sites with similar types and levels of impairment 

had been grouped; grouped sites also may share other attributes, such as location within a 

watershed (e.g., elevation and contributing watershed size). Grouping sites may have 

strengthened stressor data if some values could be averaged among similar sites and compared 

collectively to a reference site value or an average value derived from a group of similar 

reference sites. 

59
CONCEPTUAL MODEL FIGURES 

CM 1. Case study conceptual model elements........................................................................61 

CM 2. Increased authochthony conceptual model ..................................................................62 

CM 3. Decreased dissolved oxygen conceptual model...........................................................63 

CM 4. Altered flow regime conceptual model........................................................................64 

CM 5. Decreased large woody debris conceptual model........................................................65 

CM 6. Increased sediment, first half of conceptual model .....................................................66 

CM 7. Increased sediment, second half of conceptual model.................................................67 

CM 8. Increased temperature conceptual model.....................................................................68 

CM 9. Increased toxic substances conceptual model..............................................................69 

CM 10. Potential relationships among individual conceptual models......................................70 

60
Sources

Candidate causesResponses

↑ toxic substances

↑ temperature

↑ autochthony ↑ sediment

↓ large woody debris ↓ dissolved oxygen

altered flow regime ↑ toxic substances

↑ temperature

↑ autochthony ↑ sediment

↓ large woody debris ↓ dissolved oxygen

altered flow regime

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

lawn care & 

landscaping

instream

impoundment

riparian 

devegetation

watershed 

devegetation

impervious 

surfaces

detention 

basins

channel 

alteration

sanding, salting 

& plowing

industrial 

processes

instream

deposits

landfill 

leachate

lawn care & 

landscaping

instream

impoundment

riparian 

devegetation

watershed 

devegetation

impervious 

surfaces

detention 

basins

channel 

alteration

sanding, salting 

& plowing

industrial 

processes

instream

deposits

landfill 

leachate

EPT = Ephemeroptera (mayflies), Plecoptera EPT = Ephemeroptera (mayflies), Plecoptera 

(stoneflies), and Trichoptera (caddisflies) 

HBI = Hilsenhoff Biotic Index 

CM Figure 1. Case study conceptual model elements. CM Figure 1.

61
EPT = Ephemeroptera (mayflies), Plecoptera EPT = Ephemeroptera (mayflies), Plecoptera 

(stoneflies), and Trichoptera (caddisflies) (stoneflies), and Trichoptera (caddisflies) 

HBI = Hilsenhoff Biotic Index 

source

proximate 

stressor response

KEY

additional step in 

causal pathway

connected 

conceptual 

model

riparian 

devegetation

↑ light

↑ autochthonous 

food resources

↓ leaf litter 

↓ allochthonous

food resources

↑ nutrients

↑ 1° producers 

(algae and macrophytes)

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ water velocity

lawn care & 

landscaping

instream

impoundment

↓ large woody debris

CM Figure 2. Increased autochthony conceptual model. 

62
EPT = Ephemeroptera (mayflies), Plecoptera EPT = Ephemeroptera (mayflies), Plecoptera

(stoneflies), and Trichoptera (caddisflies) 

HBI = Hilsenhoff Biotic Index 

source

proximate 

stressor response

KEY

additional step in 

causal pathway connected 

conceptual 

model

source

proximate 

stressor response

KEY

additional step in 

causal pathway connected 

conceptual 

model

↑ light

↑ temperature

↑ nutrients

↑ organic matter ↑ 1° producers (algae and macrophyties

↓ water velocity

↓ interstitial spaces

riparian 

devegetation

↓ photosynthesis/ 

respiration ratio ↓ aeration

↓ turbulence

↑ heterotrophs

↑ respiration ↓ dissolved oxygen 

(water column and/or interstitial) 

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

lawn care & 

landscaping

↑ sediment

↑ channel 

incision

channel 

alteration

instream

impoundment

↓ large woody debris

CM Figure 3. Decreased dissolved oxygen conceptual model. 

63
EPT = Ephemeroptera (mayflies), Plecoptera EPT = Ephemeroptera (mayflies), Plecoptera 

(stoneflies), and Trichoptera (caddisflies) (stoneflies), and Trichoptera (caddisflies) 

 HBI = Hilsenhoff Biotic Index 

source

proximate 

stressor response

KEY

additional step in 

causal pathway connected 

conceptual 

model

source

proximate 

stressor response

KEY

additional step in 

causal pathway connected 

conceptual 

model

↑ water velocity

riparian 

devegetation

↓ water velocity

impervious 

surfaces

↓ groundwater 

recharge ↑

↑

storm discharge

surface runoff

↑ dislodgement

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↑ evaporation and/or 

evapotranspiration

↓ water depth ↓ wetted channel

↓ lotic habitat

↑ rate and/or 

magnitude of 

flow fluctuations

↓ base discharge

channel 

alteration

watershed 

devegetation

instream

impoundment

↓ large woody debris

CM Figure 4. Altered flow regime conceptual model. 

64
 EPT = Ephemeroptera (mayflies), Plecoptera 

 (stoneflies), and Trichoptera (caddisflies)  HBI = Hilsenhoff Biotic Index 

riparian 

devegetation

↓ large woody debris

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

channel 

alteration

↓ cover ↓ wood substrate

riparian 

devegetation

↓ large woody debris

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

channel 

alteration

↓ cover ↓ wood substrate

source

proximate 

stressor response

KEY

additional step in 

causal pathway

connected 

conceptual 

model

CM Figure 5. Decreased large woody debris conceptual model.

65
 EPT = Ephemeroptera (mayflies), Plecoptera 

 (stoneflies), and Trichoptera (caddisflies)  HBI = Hilsenhoff Biotic Index 

riparian 

devegetation

↓ bank stability

impervious 

surfaces

watershed 

devegetation

↑ storm discharge

↑ channel and/or 

bank erosion

↓ large woody debris

↓ water velocity

↑ input of fine particles

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↑ deposited sediment

See second half of 

increased sediment 

conceptual model

↑ suspended sediment

instream

deposits channel alteration

sanding, salting 

& plowing

instream

impoundment

↑ terrestrial erosion

source

proximate 

stressor response

KEY

additional step in 

causal pathway

connected 

conceptual 

model

see CM Figure 7 

CM Figure 6. Increased sediment, first half of conceptual model. 

66
 EPT = Ephemeroptera (mayflies), Plecoptera 

 (stoneflies), and Trichoptera (caddisflies)  HBI = Hilsenhoff Biotic Index 

↓ substrate 

stability

↓ interstitial flow

↑ coverage 

of fines

↓ light 

(water column) ↓ water depth

↑ deposited sediment ↑ suspended sediment

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ dissolved oxygen

↑ temperature

↓ algae

↓ visibility

↑ dislodgement

↑ invertebrate drift

↑ embeddedness

↓ interstitial habitat

↑ burial of 

organisms

source

proximate 

stressor response

KEY

additional step in 

causal pathway

connected 

conceptual 

model

CM Figure 7. Increased sediment, second half of conceptual model. 

67
 EPT = Ephemeroptera (mayflies), Plecoptera 

 (stoneflies), and Trichoptera (caddisflies)  HBI = Hilsenhoff Biotic Index 

riparian 

devegetation

watershed 

devegetation

↑ light

↑ temperature

↑ heated 

surface runoff

↓ base discharge

impervious 

surfaces

↓ groundwater 

recharge

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ water depth

↓ water velocity

↑ retention time

detention 

basins

channel 

alteration

↑ evaporation and/or 

evapotranspiration

↑ surface area

instream

impoundment

source

proximate 

stressor response

KEY

additional step in 

causal pathway

connected 

conceptual 

model

CM Figure 8. Increased temperature conceptual model. 

68
 EPT = Ephemeroptera (mayflies), Plecoptera EPT = Ephemeroptera (mayflies), Plecoptera 

 (stoneflies), and Trichoptera (caddisflies)  HBI = Hilsenhoff Biotic Index 

↑ ionic content

landfill leachate industrial processes

impervious 

surfaces

↑ metals ↑ NH3 ↑ organics ↑ pesticides ↑ NaCl

↑ surface run-off 

(airports)

↑ surface run-off 

(roads, lots, stations)

↓ brook trout

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

↓ EPT taxa

↑ non-insect taxa

↑ HBI score

lawn care & 

landscaping

sanding, salting 

& plowing

source

proximate 

stressor response

KEY

additional step in 

causal pathway connected 

conceptual 

model

source

proximate 

stressor response

KEY

additional step in 

causal pathway connected 

conceptual 

model

CM Figure 9. Increased toxic substances conceptual model. 

69
↑ toxic substances

↑ temperature ↑ autochthony

↑ sediment

↓ large woody debris

↓ dissolved oxygen

altered flow regime

CM Figure 10. Potential relationships among individual conceptual models. M Figure 10.

70
STRENGTH-OF-EVIDENCE (SOE) TABLES 

SOE 1. Spatial / temporal co-occurrence at LCN .415 

SOE 2. Spatial / temporal co-occurrence at LCM 2.270 

SOE 3. Spatial / temporal co-occurrence at LCMn 2.274 

SOE 4. Stressor-response relationships from the field 

SOE 5. Causal pathway - Data - Increased autochthony 

SOE 6. Causal pathway - Data - Decreased dissolved oxygen 

SOE 7. Causal pathway - Data - Altered flow regime 

SOE 8. Causal pathway - Data - Decreased large woody debris 

SOE 9. Causal pathway - Data - Increased sediment 

SOE 10. Causal pathway - Data - Increased temperature 

SOE 11. Causal pathway - Data - Increased toxic substances 

SOE 12. Causal pathway - Scores - Increased autochthony 

SOE 13. Causal pathway - Scores - Decreased dissolved oxygen 

SOE 14. Causal pathway - Scores - Altered flow regime 

SOE 15. Causal pathway - Scores - Decreased large woody debris 

SOE 16. Causal pathway - Scores - Increased sediment 

SOE 17. Causal pathway - Scores - Increased temperature 

SOE 18. Causal pathway - Scores - Increased toxic substances 

SOE 19. Laboratory tests of site media (sediment toxicity) - Data 

SOE 20. Laboratory tests of site media (sediment toxicity) - Scores 

SOE 21. Mechanistically plausible cause (functional feeding & mode of existence groups) 

SOE 22. Stressor-response relationship from elsewhere - Data - Increased autochthony 

SOE 23. Stressor-response relationship from elsewhere - Data - Decreased dissolved oxygen 

SOE 24. Stressor-response relationship from elsewhere - Data - Altered flow regime 

SOE 25. Stressor-response relationship from elsewhere - Data - Decreased large woody debris 

SOE 26. Stressor-response relationship from elsewhere - Data - Increased sediment 

SOE 27. Stressor-response relationship from elsewhere - Data - Increased temperature 

SOE 28. Stressor-response relationship from elsewhere - Data - Increased toxic substances 

SOE 29. Stressor-response relationship from elsewhere - Scores - Increased autochthony 

SOE 30. Stressor-response relationship from elsewhere - Scores - Decreased dissolved oxygen 

SOE 31. Stressor-response relationship from elsewhere - Scores - Altered flow regime 

SOE 32. Stressor-response relationship from elsewhere - Scores - Decreased large woody debris 

SOE 33. Stressor-response relationship from elsewhere - Scores - Increased sediment 

SOE 34. Stressor-response relationship from elsewhere - Scores - Increased temperature 

SOE 35. Stressor-response relationship from elsewhere - Scores - Increased toxics at LCN .415 

SOE 36. Stressor-response relationship from elsewhere - Scores - Increased toxics at LCM 2.270 

SOE 37. Stressor-response relationship from elsewhere - Scores - Increased toxics at LCMn 2.274 

SOE 38. Stressor-response relationship from elsewhere - Increased PAH's at LCN .415 

71
SOE 39. Consistency of evidence scoring system 

SOE 40. Strength of evidence summary scoring at LCN .415 

SOE 41. Strength of evidence summary scoring at LCM 2.270 

SOE 42. Strength of evidence summary scoring at LCMn 2.274 

SOE 43. Consistency of evidence summary for all three impaired sites 

SOE 44. Explanation of evidence scoring system 

SOE 45. Strength of evidence complete scoring at LCN .415 

SOE 46. Strength of evidence complete scoring at LCM 2.270 

SOE 47. Strength of evidence complete scoring at LCMn 2.274 

SOE 48. Consistency of evidence complete scoring for all three impaired sites 

SOE 49. Water column metal observations study comparison - Low flow 

SOE 50. Water column metal observations study comparison - Stormflow

72
SOE Table 1. Spatial / temporal co-occurrence at LCN .415

Strength of evidence (SOE) scoring system for spatial / temporal co-occurrence

+ The effect occurs where or when the candidate cause occurs OR the effect does not occur where or when the candidate cause does not occur0 It is uncertain whether the candidate cause and the effect co-occur- - - The effect does not occur where or when the candidate cause occurs OR the effect occurs where or when the candidate cause does not occurR The effect does not occur where and when the candidate cause occurs OR the effect occurs where or when the candidate cause does not occur and the evidence is indisputableNE No evidence.

Variable, SOE

Candidate Cause units RB 3.961 LCN .415 Difference score Comments

dominant aquatic The higher chlorophyll 

a measurement at diatoms diatoms vegetation, estimated 

0 Increased LCN .415 was not considered strong 25% 25%

0 % of local reach autochthony enough to merit a positive score, given the 

chlorophyll 

a , mg/m2 10.4 15.7 51% similarity in dominant aquatic vegetation.

Decreased 8.7 [3] 6.3 [3] dissolved dissolved oxygen, mg/L -28% + (8.0 - 9.5) (5.3 - 7.8)oxygen

0.00073 [2] 0.00055 [2] baseflow discharge / (0.00071 - (0.00035 - -25% watershed area, cfs/ac 0.00075) 0.00076)

storm event peak The baseflow data suggest that less discharge / watershed 0.0035 0.1338 3716% groundwater recharge may be occurring at 

area, cfs/ac the impaired site, although this is based on Altered flow storm event volume / + 2 samples only. The 4 storm flow variables regime watershed area, ac- 0.0041 0.0276 578% indicate that the impaired site responds to 

ft/ac storm runoff with flashier discharge than the storm event duration, reference site (also see Figure 13). 25.4 5.5 -78% hours

storm event time to 9.4 2.3 -76% peak discharge, hours

Decreased large woody no LWD data at impaired site NEdebris

73
Candidate Cause

Variable,

units RB 3.961 LCN .415 Difference

SOE

score Comments

baseflow TSS, mg/L < 10 [3] (< 2 - < 10) < 10 [3] (3 - < 10)

≈ 0

storm flow TSS, mg/L < 10 - 118 [9] < 10 - 271 [9] 130%muck-mud, % 60 40 -33%

RBP epifaunal substrate, score & category

13 sub-optimal 13 sub-optimal 0

RBP pool substrate, score & category 10 marginal 10 marginal 0RBP sediment deposition, score & category

18 optimal 11 sub-optimal

LCN .415 

worse than 

RB 3.961

weekly minimum, °C 12.9 [3] (11.4 - 14.0) 16.3 [3] (15.4 - 17.3) 27%

weekly maximum, °C 21.1 [3] (20.3 - 22.1) 22.7 [3] (21.6 - 24.2) 7%

weekly mean, °C 16.7 [3] (16.1 - 17.4) 19.2 [3] (18.6 - 20.0) 15%

baseflow chloride 29 [3] (26 - 30) 122 [3] (91 - 141) 324%

storm flow chloride 17 - 57 [9] 15 - 296 [9] 419%low flow calcium 6.8 67 885%

low flow magnesium 2.2 17 673%

baseflow specific 

conductivity, uS/cm

129 [3]

(79 - 155)

745 [3]

(659 - 796) 476%

baseflow < 0.0005 [3] < 0.0005 [3] NDlow flow < 0.0002 < 0.0002 NDstorm flow < 0.0005 [9] < 0.0005 - 0.0007 [9] > 0

++

Increased toxic substances

Water column sampling (units in ppm or mg/L, except specific conductivity uS/cm):

+

The Cadmium positive score is considered borderline; due to ambiguity, this could have been scored zero. Only 1 of 9 storm samples at the impaired site registered positive for cadmium (0.0007 ppm), & cadmium was not detected in any other measurement.

Increased temperature

Ionic strength

Cadmium

The positive score is based on storm flow TSS and the RBP sediment deposition score. The project team recognizes that other variables listed indicate similarity between the two sites, and the muck mud variable indicates better conditions at the impaired site; as such, the positive score is borderline and, based on ambiguities, this cause could have been given a score of zero. Note that some TSS data did not meet MEDEP quality standards.

Increased sediment

+

74
Candidate Cause

Variable,

units RB 3.961 LCN .415 Difference

SOE

score Comments

baseflow < 0.002 [3] < 0.002 [3] NDlow flow NAstorm flow < 0.002 - 0.003 [9] 0.002 - 0.018 [9] 500%

baseflow < 0.003 [3] < 0.003 [3] NDlow flow < 0.0002 < 0.0002 NDstorm flow < 0.003 - 0.004 [9] 0.003 - 0.031 [9] 675%

baseflow < 0.004 [3] < 0.004 [3] NDlow flow 0.00045 0.0032 611%storm flow < 0.004 [9] < 0.004 - 0.013 [9] > 0baseflow < 0.005 [3] 0.014 [3] (0.013 - 0.015) > 0

low flow < 0.005 0.0064 > 0storm flow 0.008 - 0.024 [9] 0.043 - 0.14 [9] 483%

Aluminum 0.045 0.006 -87% - - -

Antimony < 0.0005 < 0.0005 ND 0

Arsenic < 0.0005 0.00098 > 0 +Barium 0.0054 0.021 289% +

Beryllium < 0.0002 < 0.0002 ND 0Chromium < 0.0005 0.0032 > 0 +

Cobalt 0.00085 0.0029 241% +

Iron 0.091 0.14 54% +

Manganese 0.025 0.37 1380% +Molybdenum < 0.0005 0.00092 > 0 +Selenium < 0.001 < 0.001 ND 0

Silver < 0.0002 < 0.0002 ND 0

Thallium < 0.0005 < 0.0005 ND 0

Vanadium 0.0003 0.00082 173% +

++

contaminated sample

low flow

CopperLeadNickelZinc

++

75
Candidate Cause

Variable,

units RB 3.961 LCN .415 Difference

SOE

score Comments

Acenaphthene 0.0001 & < 0.0001 > 0 & ND +Acenaphthylene < 0.00005 & < 0.0001 ND & ND 0Anthracene 0.0002 & < 0.0001 > 0 & ND +Benzo(a) anthracene

0.0001 & 0.00033 > & > 0 +

Benzo(a) pyrene 0.0001 & 0.00048 > 0 & > 0 +Benzo(b) fluoranthene

0.0002 & 0.00111 > 0 & > 0 +

Benzo(ghi) 

perylene 0.0001 & 0.0005 > 0 & > 0 +

Benzo(k) fluoranthene

< 0.00005 & 0.00029 ND & > 0 +

Chrysene 0.0002 & 0.0008 > 0 & > 0 +Dibenzo(a,h) anthracene

< 0.00005 & 0.00011 (note 

that RL = 0.0002)

ND & ND 0

Fluoranthene 0.0005 & 0.0016 > 0 & > 0 +Fluorene 0.0001 & < 0.0001 > 0 & ND +Indeno (1,2,3-cd) 

pyrene

0.0001 & 0.00056 > 0 & > 0 +

Naphthalene 0.0001 & < 0.0001 > 0 & ND +Phenanthrene 0.00025 & 0.00067 > 0 & > 0 +Pyrene 0.0003 & 0.00115 > 0 & > 0 +Polycyclic aromatic hydrocarbons (PAHs) water column sampling (ppm or mg/L):

storm flow PAH samples are from two 

events, occurring on 10/23/2000 and 

9/25/2001.

values and differences shown at right 

are separated by "&" to distinguish 

between the two storm events

PAHs were tested for but not detected 

for either storm event at the reference 

site (surrogate site RB 1.694)

76
Candidate Cause

Variable,

units RB 3.961 LCN .415 Difference

SOE

score Comments

Antimony < 10 < 10 ND 0

Arsenic < 20 < 20 ND 0Barium 43 41 -5% - - -

Beryllium < 1.0 < 1.0 ND 0Cadmium < 3.0 < 3.0 ND 0Chromium 6.3 18 186% +

Cobalt 5.5 8.2 49% +

Copper 3.2 6.3 97% +

Lead 14 13 -7% - - -

Nickel < 6.0 10 > 0 +Selenium < 10 < 10 ND 0

Silver < 3.0 < 3.0 ND 0

Thallium < 20 < 20 ND 0

Vanadium 9.2 24 161% +

Zinc 32 54 69% +

Toxicity tests were conducted using these sediment samples; for results and related information, see the Stressor-Response analysis.

Sediment sampling (mg/kg):

one sediment sample 

taken on 10/10/2003

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

(Note that a range is provided for baseflow only if a toxic substance is detected.)

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Lower thresholds of essential elements are not considered in this causal analysis.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

epifaunal substrate / available cover 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalpool substrate characterization 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

sediment deposition 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

77
SOE Table 2. Spatial / temporal co-occurrence at LCM 2.270

Strength of evidence (SOE) scoring system for spatial / temporal co-occurrence

+ The effect occurs where or when the candidate cause occurs OR the effect does not occur where or when the candidate cause does not occur0 It is uncertain whether the candidate cause and the effect co-occur- - - The effect does not occur where or when the candidate cause occurs OR the effect occurs where or when the candidate cause does not occurR The effect does not occur where and when the candidate cause occurs OR the effect occurs where or when the candidate cause does not occur and the evidence is indisputableNE No evidence.

Variable, SOE

Candidate Cause units RB 3.961 LCM 2.270 Difference score Comments

rooted dominant aquatic The minor reported difference in dominant Increased diatoms submergents vegetation, % of local 0 0 aquatic vegetation was not clear enough to autochthony 25% and diatoms reach change the score from zero. 25%

Decreased 8.7 [3] 5.3 [3] dissolved baseflow, mg/L -39% + (8.0 - 9.5) (4.1 - 7.4)oxygenAltered flow no appropriate data to represent flow conditions at the impaired site NEre

gime (e.g., velocity or discharge)

LWD diameter 

≥ 5cm, Decreased 91 37 -59% # of pieces large woody 

+ LWD diameter 

≥ 10cm, debris 39

8 -79% # of pieces

< 10 [3] < 10 [3] baseflow TSS, mg/L

≈ 0 (< 2 - < 10) (1 - < 10)

muck-mud, % 60 70 17% The small difference in muck mud between 

RBP epifaunal the two sites does not provide enough substrate, score, and 13 sub-optimal 13 sub-optimal 0 evidence over the other variables, which Increased 

category 0 are essentially equal at both sites; sediment RBP pool substrate, therefore, this was scored zero. Note that 10 marginal 10 marginal 0 score and category some TSS data did not meet MEDEP 

RBP sediment quality standards.deposition, score, and 18 optimal 18 optimal 0category

78
Candidate Cause

Variable,

units RB 3.961 LCM 2.270 Difference

SOE

score Comments

weekly minimum, °C 13.1 17.0 29%

weekly maximum, °C 20.3 23.3 15%

weekly mean, °C 16.6 20.2 22%

baseflow chloride 29 [3] (26 - 30) 99 [3] (83 - 124) 241%

baseflow specific 

conductivity, uS/cm

129 [3]

(79 - 155)

568 [3]

(491 - 718) 340%

Cadmium baseflow < 0.0005 [3] < 0.0005 [3] ND 0

Copper baseflow < 0.002 [3] < 0.002 [3] ND 0

Lead baseflow < 0.003 [3] < 0.003 [3] ND 0

Nickel baseflow < 0.004 [3] < 0.004 [3] ND 0

Zinc baseflow < 0.005 [3] < 0.005 [3] ND 0

Water column sampling (units in ppm or mg/L, except specific conductivity uS/cm):

+

Increased temperature

Ionic Strength +

Increased toxic substances

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

(Note that a range is provided for baseflow only if a toxic substance is detected.)

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Lower thresholds of essential elements are not considered in this causal analysis.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

epifaunal substrate / available cover 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalpool substrate characterization 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

sediment deposition 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

79
SOE Table 3. Spatial / temporal co-occurrence at LCMn 2.274

Strength of evidence (SOE) scoring system for spatial / temporal co-occurrence

+ The effect occurs where or when the candidate cause occurs OR the effect does not occur where or when the candidate cause does not occur0 It is uncertain whether the candidate cause and the effect co-occur- - - The effect does not occur where or when the candidate cause occurs OR the effect occurs where or when the candidate cause does not occurR The effect does not occur where and when the candidate cause occurs OR the effect occurs where or when the candidate cause does not occur, and the evidence is indisputableNE No evidence.

Variable, SOE

Candidate Cause units RB 3.961 LCMn 2.274 Difference score Comments

dominant aquatic diatoms diatoms The higher diatom observation at the vegetation, % of local -20% Increased 25% 20% reference site counteracts the higher reach

0 autochthony chlorophyll 

a measurement at the impaired 

site; uncertainty yielded a score of zero. chlorophyll 

a , mg/m2 10.4 17.5 68%

Dissolved oxygen data were collected 

Decreased approximately 10cm above the stream 8.7 [3] 5.5 [3] dissolved baseflow, mg/L -37% + bottom; therefore, these values may be (8.0 - 9.5) (4.4 - 6.2) more applicable to fish habitat than benthic oxygen

invertebrate habitat.

mean thalweg velocity, 0.10 0.03 -73% m/s Flow regime differences between the two 

highly variable low longitudinal sites cannot be characterized by mean Altered flow baseflow velocity longitudinal velocity qualitative + velocity alone. Flow heterogeneity adds regime measured at 2m channel velocity variability and support of support for a positive score (also see Figure increments along 100m and normally often equal to cause 14). reach in site vicinity above zero zero

LWD diameter 

≥ 5cm, Decreased 91 43 -53% # of pieces large woody 

+ LWD diameter 

≥ 10cm, debris 39 12 -69% # of pieces

80
Candidate Cause

Variable,

units RB 3.961 LCMn 2.274 Difference

SOE

score Comments

baseflow TSS, mg/L < 10 [3] (< 2 - < 10) < 10 [3] (4 - < 10) ≈ 0

muck mud, % 60 40 -33%

RBP epifaunal substrate, score, and category

13 sub-optimal 12 sub-optimal 0

RBP pool substrate, score and category 10 marginal 8 marginal 0RBP sediment deposition, score, and category

18 optimal 18 optimal 0

weekly minimum, °C 13.1 13.2 0%

weekly maximum, °C 20.3 21.8 8%

weekly mean, °C 16.6 16.5 0%baseflow chloride 29 [3] (26 - 30) 66 [3] (58 - 73) 128%

low flow calcium 6.8 31.5 363%low flow magnesium 2.2 11 400%

baseflow specific 

conductivity, uS/cm

129 [3]

(79 - 155)

459 [3]

(376 - 510) 256%

baseflow < 0.0005 [3] < 0.0005 [3] NDlow flow < 0.0002 < 0.0002 NDbaseflow < 0.002 [3] 0.0013 [3] (< 0.002 - 0.002) ND

low flow NA

Increased toxic substances

Water column sampling (units in ppm or mg/L, except specific conductivity uS/cm):

0 Increased sediment

The difference in muck mud between the two sites does not provide enough evidence over the other variables, which are essentially equal at both sites; therefore, this was scored zero. Note that some TSS data did not meet MEDEP quality standards.

+

The weekly maximum is higher, and this value may be more important that the others (see Stressor-Response analysis); therefore, while the minimum and mean values for the two sites are relatively similar, a positive score was still given.

Increased temperature

Ionic Strength +

contaminated sample

00

CadmiumCopper

81
Variable, SOE

Candidate Cause units RB 3.961 LCMn 2.274 Difference score Comments

baseflow < 0.003 [3] < 0.003 [3] ND Lead 0 low flow < 0.0002 < 0.0002 NDbaseflow < 0.004 [3] < 0.004 [3] ND Nickel + low flow 0.00045 0.0019 322%

0.0042 [3] baseflow < 0.005 ND Zinc (< 0.005 - 0.005) 0

low flow < 0.005 < 0.005 ND

Aluminum 0.045 0.019 -58% - - -

Antimony < 0.0005 < 0.0005 ND 0

Arsenic < 0.0005 0.00235 > 0 +Barium 0.0054 0.011 104% +Beryllium < 0.0002 < 0.0002 ND 0Chromium < 0.0005 0.00205 > 0 +Cobalt 0.00085 0.000555 -35% - - - low flow Iron 0.091 0.22 142% +

Manganese 0.025 0.092 268% +

Molybdenum < 0.0005 0.000385 ND 0Selenium < 0.001 < 0.001 ND 0Silver < 0.0002 < 0.0002 ND 0

Thallium < 0.0005 < 0.0005 ND 0

Vanadium 0.0003 0.000695 132% +

82
Candidate Cause

Variable,

units RB 3.961 LCMn 2.274 Difference

SOE

score Comments

Antimony < 10 < 10 ND 0

Arsenic < 20 < 20 ND 0Barium 43 38 -12% - - -Beryllium < 1.0 < 1.0 ND 0

Cadmium < 3.0 < 3.0 ND 0Chromium 6.3 16.5 162% +

Cobalt 5.5 6.95 26% +

Copper 3.2 6.25 95% +

Lead 14 7.5 -46% - - -

Nickel < 6.0 10.5 > 0 +

Selenium < 10 < 10 ND 0

Silver < 3.0 < 3.0 ND 0

Thallium < 20 < 20 ND 0

Vanadium 9.2 20 117% +

Zinc 32 58.5 83% +

Toxicity tests were conducted using these sediment samples; for results and related information, see the Stressor-Response analysis.

Sediment sampling (mg/kg):

one sediment sample 

taken on 10/10/2003

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

(Note that a range is provided for baseflow only if a toxic substance is detected.)

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Lower thresholds of essential elements are not considered in this causal analysis.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

epifaunal substrate / available cover 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalpool substrate characterization 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

sediment deposition 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

83
SOE Table 4. Stressor-response relationships from the field

+ + A strong effect gradient is observed relative to exposure to the candidate cause, at spatially linked sites, and the gradient is in the expected

direction.

+ A weak effect gradient is observed relative to exposure to the candidate cause, at spatially linked sites, OR a strong effect gradient is

observed relative to exposure to the candidate cause, at non-spatially linked sites, and the gradient is in the expected direction.

Strength of evidence (SOE) scoring system for stressor-response relationship in the field

NE no evidence.

0 An uncertain effect gradient is observed relative to exposure to the candidate cause

- An inconsistent effect gradient is observed relative to exposure to the candidate cause, at spatially linked sites, OR a strong effect gradient is 

observed relative to exposure to the candidate cause, at non-spatially linked sites, but the gradient is not in the expected direction.

- - A strong effect gradient is observed relative to exposure to the candidate cause, at spatially linked sites, but the relationship is not in the

expected direction.

Reasoning and Comments

SOE score

Endpoint Score

Increased autochthony

Scatter plots for nutrients and aquatic vegetation were used to determine stressorresponse relationships for autochthony. Weak positive gradients are seen EPT richness 0

between HBI and the following nutrients: total Kjeldahl nitrogen, total phosphorus, % non-insects 0

and ortho-phosphorus. Correlations for the other biological endpoints and other HBI +

variables remain uncertain.

Decreased dissolved oxygen

Scatter plots for dissolved oxygen (percent saturation and concentration) show 

weak correlation between decreasing HBI and increasing dissolved oxygen. 

Relationships for other biological endpoints are uncertain. However, EPT may be EPT richness 0

increasing with increasing dissolved oxygen; the project team chooses to score % non-insects 0

this zero (uncertain) but recognizes this as a borderline situation and that HBI +

additional data may add support to the correlation, thus supporting the case for 

this cause.

Altered flow regime

Appropriate stressor-response data from the project site are not available for 

direct analysis of this cause; therefore, NE scores were given.

EPT richness

% non-insects

HBI

NE

NE

NE

Decreased large woody debris

Scatter plot data are sparse but support the case for this cause. EPT and large EPT richness +

woody debris are positively correlated. Additionally, HBI appears to decrease as % non-insects 0

large woody debris increases. HBI +

Increased sediment

Substrate particle size, bank stability, and Rapid Bioassessment Protocol (RBP) 

variables were considered for this candidate cause. Noticeable relationships 

between the variables and biological endpoints were unclear. Weak correlations 

between RBP variables and biological endpoints did not merit positive scores.

EPT richness

% non-insects

HBI

0

0

0

84
Reasoning and Comments

SOE score

Endpoint Score

Increased temperature

Weekly minimum, maximum, and mean temperature and canopy shade variables 

are used for this candidate cause. EPT appears to decrease and HBI appears to EPT richness +

increase as weekly maximum temperature increases. There is a weak correlation % non-insects 0

between decreasing HBI and increasing canopy shade. Relationships between HBI +

remaining variables and biological endpoints remain uncertain. 

Increased toxic substances

ionic strength

EPT decreases as chloride and specific conductivity increase. Non-insects 

appear to increase as chloride and specific conductivity increase, although the 

relationship is weak-to-borderline for chloride. HBI increases as chloride and 

specific conductivity increase.

EPT richness

% non-insects

HBI

+

+

+

zinc

EPT richness 0

Scatter plot correlations between zinc and the biological endpoints are uncertain. % non-insects 0

HBI 0

85
SOE Table 5. Causal pathway - Data - Increased autochthony

LCMn 2.274 LCM 2.270 LCN .415

Steps in causal pathway, units RB 3.961 Value Difference Value Difference Value Difference

RBP riparian vegetative zone width, 10 optimal 6.5 sub-optimal < 4 marginal < 7 sub-optimal < score and category

0.009 [3] 0.048 [3] 0.025 [3] 0.030 [3] baseflow total phosphorus, ppm 433% 174% 230% (0.008 - 0.010) (0.040 - 0.061) (0.020 - 0.028) (0.024 - 0.035)

0.003 [3] 0.009 [3] 0.008 [3] 0.005 [3] baseflow ortho-phosphorus, ppm 238% 200% 88% (0.002 - 0.004) (0.004 - 0.017) (0.006 - 0.010) (0.002 - 0.007)

0.310 [3] 0.617 [3] 0.513 [3] 0.457 [3] baseflow total nitrogen, ppm 99% 66% 47% (0.280 - 0.350) (0.610 - 0.620) (0.420 - 0.600) (0.330 - 0.540)

0.167 [3] 0.300 [3] 0.467 [3] 0.400 [3] baseflow total kjeldahl nitrogen, ppm 80% 180% 140% (0.100 - 0.200) (0.300 - 0.300) (0.400 - 0.500) (0.300 - 0.500)

0.143 [3] 0.317 [3] < 0.047 [3] < 0.057 [3] baseflow nitrate + nitrite, ppm 121% -67% -60% (0.100 - 0.180) (0.310 - 0.320) (0.02 - < 0.20) (0.03 - < 0.20)

0.011 - 0.074 0.044 - 0.320 storm flow total phosphorus, ppm 332% NE NA NE NA [9] [9]

< 0.001 - 0.005 < 0.001 - 0.015 storm flow ortho-phosphorus, ppm 200% NE NA NE NA [9] [9]

0.330 - 0.800 0.520 - 1.670 storm flow total nitrogen, ppm 109% NE NA NE NA [9] [9]

storm flow total Kjeldahl nitrogen, ppm 0.2 - 0.7 [9] 0.4 - 1.3 [9] 86% NE NA NE NA

storm flow nitrate + nitrite, ppm 0.03 - 0.25 [9] 0.12 - 0.82 [9] 228% NE NA NE NA

LWD diameter ≥ 5cm, # of pieces 91 NE NA 37 -59% 43 -53%

LWD diameter ≥ 10cm, # of pieces 39 NE NA 8 -79% 12 -69%mean thalweg velocity, m/s 0.10 NE NA NE NA 0.0273 -73%shaded canopy, % 90.9 88.1 -3% 81.4 -10% 90.8 0%

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n]. 

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

riparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

86
SOE Table 6. Causal pathway - Data - Decreased dissolved oxygen

LCN .415 LCM 2.270 LCMn 2.274

Steps in causal pathway, units RB 3.961

Value Difference

Value Difference

Value Difference

RBP channel alteration, score and 20 optimal 17 optimal

≈ 0 14 sub-optimal < 14 sub-optimal < category

RBP riparian vegetative zone width, 10 optimal 6.5 sub-optimal < 4 marginal < 7 sub-optimal < score and category

0.009 [3] 0.048 [3] 0.025 [3] 0.030 [3] baseflow total phosphorus, ppm 433% 174% 230% (0.008 - 0.010) (0.040 - 0.061) (0.020 - 0.028) (0.024 - 0.035)

0.003 [3] 0.009 [3] 0.008 [3] 0.005 [3] baseflow ortho-phosphorus, ppm 238% 200% 88% (0.002 - 0.004) (0.004 - 0.017) (0.006 - 0.010) (0.002 - 0.007)

0.310 [3] 0.617 [3] 0.513 [3] 0.457 [3] baseflow total nitrogen, ppm 99% 66% 47% (0.280 - 0.350) (0.610 - 0.620) (0.420 - 0.600) (0.330 - 0.540)

0.167 [3] 0.300 [3] 0.467 [3] 0.400 [3] baseflow total kjeldahl nitrogen, ppm 80% 180% 140% (0.100 - 0.200) (0.300 - 0.300) (0.400 - 0.500) (0.300 - 0.500)

0.143 [3] 0.317 [3] < 0.047 [3] < 0.057 [3] baseflow nitrate + nitrite, ppm 121% -67% -60% (0.100 - 0.180) (0.310 - 0.320) (0.02 - < 0.20) (0.03 - < 0.20)

0.011 - 0.074 0.044 - 0.320 storm flow total phosphorus, ppm 332% NE NA NE NA [9] [9]

< 0.001 - 0.005 < 0.001 - 0.015 storm flow ortho-phosphorus, ppm 200% NE NA NE NA [9] [9]

0.330 - 0.800 0.520 - 1.670 storm flow total nitrogen, ppm 109% NE NA NE NA [9] [9]

storm flow total Kjeldahl nitrogen, ppm 0.2 - 0.7 [9] 0.4 - 1.3 [9] 86% NE NA NE NA

storm flow nitrate + nitrite, ppm 0.03 - 0.25 [9] 0.12 - 0.82 [9] 228% NE NA NE NAchlorophyll 

a , mg/m2 10.4 15.7 51% NE NA 17.5 68%

LWD diameter ≥ 5cm, # of pieces 91 NE NA 37 -59% 43 -53%

LWD diameter ≥ 10cm, # of pieces 39 NE NA 8 -79% 12 -69%

shaded canopy, % 90.9 88.1 -3% 81.4 -10% 90.8 0%

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n]. 

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

channel alteration 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

riparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

87
SOE Table 7. Causal pathway - Data - Altered flow regime

LCN .415 LCM 2.270 LCMn 2.274

Steps in causal pathway, units RB 3.961 Value Difference Value Difference Value Difference

RBP channel alteration, score, and 20 optimal 17 optimal ≈ 0 14 sub-optimal < 14 sub-optimal < category

RBP channel sinuosity, score, and 16 optimal 9 marginal < 14 sub-optimal < 12 sub-optimal < categoryRBP riparian vegetative zone width, 10 optimal 6.5 sub-optimal < 4 marginal < 7 sub-optimal < score, and categoryLWD diameter ≥ 5cm, # of pieces 91 NE NA 37 -59% 43 -53%

LWD diameter ≥ 10cm, # of pieces 39 NE NA 8 -79% 12 -69%percent impervious surface 2.1 32.6 1452% 7.1 238% 14.3 581%

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n]. 

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

channel alteration 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

channel sinuosity 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalriparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

88
SOE Table 8. Causal pathway - Data - Decreased large woody debris

LCN .415 LCM 2.270 LCMn 2.274

Steps in causal pathway, units RB 3.961 Value Difference Value Difference Value Difference

RBP channel alteration, score, and 20 optimal 17 optimal ≈ 0 14 sub-optimal < 14 sub-optimal < category

RBP channel sinuosity, score, and 16 optimal 9 marginal < 14 sub-optimal < 12 sub-optimal < categoryRBP riparian vegetative zone width, 10 optimal 6.5 sub-optimal < 4 marginal < 7 sub-optimal < score, and category

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n]. 

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

channel alteration 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

channel sinuosity 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalriparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

89
SOE Table 9. Causal pathway - Data - Increased sediment

LCN .415 LCM 2.270 LCMn 2.274

Steps in causal pathway, units RB 3.961 Value Difference Value Difference Value Difference

RBP channel alteration, score, and 20 optimal 17 optimal ≈ 0 14 sub-optimal < 14 sub-optimal < category

RBP channel sinuosity, score, and 16 optimal 9 marginal < 14 sub-optimal < 12 sub-optimal < categoryRBP riparian vegetative zone width, 10 optimal 6.5 sub-optimal < 4 marginal < 7 sub-optimal < score, and categoryRBP bank vegetative protection, score, 10 optimal 10 optimal 0 7 sub-optimal < 8 sub-optimal < and categoryRBP bank stability, score, and category 9 optimal 7 sub-optimal < 8.5 optimal ≈ 0 9 optimal ≈ 0

Pfankuch, score 93 105 13% NE NA 111 19%

LWD diameter ≥ 5cm, # of pieces 91 NE NA 37 -59% 43 -53%

LWD diameter ≥ 10cm, # of pieces 39 NE NA 8 -79% 12 -69%percent impervious surface 2.1 32.6 1452% 7.1 238% 14.3 581%

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n]. 

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

channel alteration 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

channel sinuosity 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalbank stability 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

bank vegetative protection 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimalriparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

90
SOE Table 10. Causal pathway - Data - Increased temperature

LCN .415 LCM 2.270 LCMn 2.274

Steps in causal pathway, units RB 3.961 Value Difference Value Difference Value Difference

RBP channel alteration, score, and 20 optimal 17 optimal ≈ 0 14 sub-optimal < 14 sub-optimal < category

RBP channel sinuosity, score, and 16 optimal 9 marginal < 14 sub-optimal < 12 sub-optimal < categoryRBP riparian vegetative zone width, 10 optimal 6.5 sub-optimal < 4 marginal < 7 sub-optimal < score, and categoryshaded canopy, % 90.9 88.1 -3% 81.4 -10% 90.8 0%

percent impervious surface 2.1 32.6 1452% 7.1 238% 14.3 581%

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n]. 

difference calculation

- the majority of differences are expressed as a percent = [ ( impaired value - reference value ) / reference value] * 100%;

- differences between Rapid Bioassessment Protocol (RBP) values are shown as greater or less than the reference value

based on RBP qualitative condition categories (see further below);

- differences between two ranges of values are calculated using the maximum values.

Rapid Bioassessment Protocol (RBP)

Habitat Parameter Score and Condition Category

channel alteration 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal

channel sinuosity 0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimalriparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal

91
SOE Table 11. Causal pathway - Data - Increased toxic substances

LCN .415 LCM 2.270 LCMn 2.274

Steps in causal pathway, units RB 3.961 Value Difference Value Difference Value Difference

percent impervious surface 2.1 32.6 1452% 7.1 238% 14.3 581%

92
SOE Table 12. Causal pathway - Scores - Increased autochthony

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present.

+ Data show that some steps in at least one causal pathway are present.

0 Data show that the presence of all steps in the causal pathway is uncertain.

- Data show that there is at least one missing step in each causal pathway.

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway.

Reasoning and Comments SOE 

score

 Site LCN .415

Evidence for some causal steps - All measured nutrients are greater at the impaired site than at 

the reference site, which could lead to increases in primary producers, thereby potentially 

increasing autochthony. Riparian devegetation, evidenced by the RBP riparian vegetation 

variable, could decrease allochthony, thereby increasing autochthony; however, there is no 

evidence for intermediate steps within that particular causal pathway.

+

Ambiguous evidence - Shaded canopy values at the impaired and reference sites are almost 

identical, which weakens the case for the increased light pathway.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

 Site LCM 2.270

Evidence for some causal steps - Most measured nutrients are greater at the impaired site than 

at the reference site, which could lead to increases in primary producers and potential increases 

in autochthony. Riparian devegetation, evidenced by the RBP riparian vegetation variable, leads 

to decreased LWD, for which there is evidence, thereby potentially decreasing allochthony and 

increasing autochthony; also, riparian devegetation could lead to increases in light, which is 

evidenced by the lower canopy shade percentage, thereby increasing primary producers and 

increasing autochthony. +

Ambiguous evidence - Measured nitrate plus nitrite at the site is lower than at the reference site; 

this contradicts the increased nutrients causal step.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

 Site LCMn 2.274

Evidence for some causal steps - Most measured nutrients are greater at the impaired site than 

at the reference site, which could lead to increases in primary producers and potential increases 

in autochthony. Riparian devegetation, evidenced by the RBP riparian vegetation variable, leads 

to decreased LWD, for which there is evidence, thereby potentially decreasing allochthony and 

increasing autochthony. There is evidence for decreased channel velocity at the site, which could 

increase primary producers.

+

Ambiguous evidence - Measured nitrate plus nitrite at the site is lower than at the reference site; 

this contradicts the increased nutrients causal step. Shaded canopy values at the impaired and 

reference sites are almost identical, which weakens the case for the increased light pathway.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

93
SOE Table 13. Causal pathway - Scores - Decreased dissolved oxygen

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present

+ Data show that some steps in at least one causal pathway are present

0 Data show that the presence of all steps in the causal pathway is uncertain

- Data show that there is at least one missing step in each causal pathway

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway

Reasoning and Comments SOE 

score

 Site LCN .415

Evidence for some causal steps - All measured nutrients are greater at the impaired site than at 

the reference site, which could lead to increases in primary producers, resultant disruptive shifts 

in the photosynthesis/respiration balance, and potential decreases in dissolved oxygen.

Ambiguous evidence - There is some evidence for riparian devegetation (lower RBP riparian 

vegetative zone width), but given the high shaded canopy value at the impaired site and its 

similarity to the reference condition, this causal pathway is probably not a factor.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

+

 Site LCM 2.270

Evidence for some causal steps - Most measured nutrients are greater at the impaired site than 

at the reference site, which could lead to increases in primary producers, resultant disruptive 

shifts in the photosynthesis/respiration balance, and potential decreases in dissolved oxygen. 

The low RBP riparian vegetation score lends evidence to increased riparian devegetation, 

leading to decreased LWD, for which there is also evidence, and this could reduce turbulence 

and aeration. The low RBP riparian vegetation score lends support to the increased light causal 

pathway, which is further supported by a lower shaded canopy percentage at the impaired site. 

Turbulence and aeration may also be reduced by channel alteration, as evidenced by the RBP +

scores.

Ambiguous evidence - Measured nitrate plus nitrite at the site is lower than at the reference site; 

this contradicts the increased nutrients causal step.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

94
Reasoning and Comments SOE 

score

 Site LCMn 2.274

Evidence for some causal steps - Most measured nutrients are greater at the impaired site than 

at the reference site, which could lead to increases in primary producers, resultant disruptive 

shifts in the photosynthesis/respiration balance, and potential decreases in dissolved oxygen. 

The low RBP riparian vegetation score lends support to increased riparian devegetation, leading 

to decreased LWD, for which there is also evidence, and this could reduce turbulence and 

aeration. Turbulence and aeration may also be reduced by channel alteration, as evidenced by 

the RBP scores. +

Ambiguous evidence - Measured nitrate plus nitrite at the site is lower than at the reference site; 

this contradicts the increased nutrients causal step. Shaded canopy values at the impaired and 

reference sites are almost identical, which weakens the case for the increased light pathway.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

95
SOE Table 14. Causal pathway - Scores - Altered flow regime

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present

+ Data show that some steps in at least one causal pathway are present

0 Data show that the presence of all steps in the causal pathway is uncertain

- Data show that there is at least one missing step in each causal pathway

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway

Reasoning and Comments SOE 

score

 Site LCN .415

Evidence for some causal steps - The high percent impervious surface within this watershed 

likely results in a more flashy hydrologic system—that is, a system with higher storm discharges 

and lower day-to-day base discharge—potentially leading to organism dislodgement and 

decreased base water depth and base wetted channel. Decreased channel sinuosity, a form of 

channel alteration evidenced by the RBP analysis, and riparian devegetation, evidenced by the 

RBP riparian vegetative zone width variable, could increase the potential for greater flow 

velocities and dislodgement of organisms.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

+

 Sites LCM 2.270 & LCMn 2.274

Potential pathways - Percent impervious surface within these watersheds likely results in more 

flashy hydrologic systems—that is, systems with higher storm discharges and lower day-to-day 

base discharge—potentially leading to organism dislodgement and decreased base water depth 

and base wetted channel. Riparian devegetation and channel alteration, evidenced by the RBP 

analysis and decreases in LWD, could increase the potential for greater flow velocities and +

dislodgement of organisms.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

96
SOE Table 15. Causal pathway - Scores - Decreased large woody debris

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present

+ Data show that some steps in at least one causal pathway are present

0 Data show that the presence of all steps in the causal pathway is uncertain

- Data show that there is at least one missing step in each causal pathway

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway

Reasoning and Comments SOE 

score

 Sites LCN .415, LCM 2.270, & LCMn 2.274

Evidence for some causal steps - The RBP analysis lends evidence to riparian devegetation, 

channel alteration, and decreased cover.

+

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

97
SOE Table 16. Causal pathway - Scores - Increased sediment

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present

+ Data show that some steps in at least one causal pathway are present

0 Data show that the presence of all steps in the causal pathway is uncertain

- Data show that there is at least one missing step in each causal pathway

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway

Reasoning and Comments SOE 

score

 Site LCN .415

Evidence for some causal steps - The high PTIA within this watershed could increase storm 

discharges, resulting in increased channel and/or bank erosion—thereby increasing potential 

sediment sources. Channel alteration and riparian devegetation, evidenced by the RBP 

qualitative scores for channel sinuosity and riparian vegetative width zone, may decrease bank 

stability, for which there is also evidence—specifically, a lower RBP bank stability qualitative 

score and a higher Pfankuch score—leading to increased bank erosion and potential sediment 

sources.

+

Ambiguous evidence - The RBP bank vegetative protection qualitative score is optimal for both 

sites, which weakens the case for increased riparian devegetation leading to erosion. The 

pathway including decreased velocity, allowing settling/deposition, is uncertain because the suboptimal score for RBP channel sinuosity may indicate increased flow velocity at the impaired site.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

 Site LCM 2.270

Evidence for some causal steps - The PTIA within this watershed could increase storm 

discharges, resulting in increased channel and/or bank erosion—thereby increasing potential 

sediment sources. Channel alteration and riparian devegetation, evidenced by the RBP 

qualitative scores for channel sinuosity and riparian vegetative width zone, may decrease bank 

stability, leading to increased bank erosion and potential sediment sources. Reduced riparian 

vegetation, evidenced by the RBP vegetative zone width and bank vegetative protection, may 

decrease LWD, which is lower at this site, thereby increasing erosion and further input of 

sediment.

+

Ambiguous evidence - The RBP bank stability qualitative score is optimal for both sites, which 

weakens the case for the causal pathway beginning with channel alteration and causing bank 

instability, leading to bank erosion. The pathway including decreased velocity allowing 

settling/deposition is uncertain because the sub-optimal score for RBP channel sinuosity may 

indicate increases in flow velocity at the impaired site.

SOE scoring - The project team did not eliminate any causal pathways, and there is

evidence for some steps.

98
Reasoning and Comments SOE 

score

 Site LCMn 2.274

Evidence for some causal steps - The PTIA within this watershed could increase storm 

discharges, resulting in increased channel and/or bank erosion—thereby increasing potential 

sediment sources. Channel alteration and riparian devegetation, evidenced by the RBP 

qualitative scores for channel sinuosity and riparian vegetative width zone, may decrease bank 

stability, leading to increased bank erosion and potential sediment sources. Reduced riparian 

vegetation, evidenced by the RBP vegetative zone width and bank vegetative protection, may 

decrease LWD, which is lower at the site, thereby increasing erosion and further input of 

sediment.

Ambiguous evidence - The RBP bank stability qualitative score is optimal for both sites, which +

weakens the case for the causal pathway beginning with channel alteration. Bank instability 

leading to bank erosion is not evident. However, the higher Pfankuch score at the impaired site 

supports decreased bank stability. The pathway including decreased velocity, allowing 

settling/deposition, is uncertain because the sub-optimal score for RBP channel sinuosity may 

indicate increases in flow velocity at the impaired site, while the actual velocity

measured at the site is lower than at the reference site.

SOE scoring - The project team did not eliminate any causal pathways, and there is

evidence for some steps.

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

99
SOE Table 17. Causal pathway - Scores - Increased temperature

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present

+ Data show that some steps in at least one causal pathway are present

0 Data show that the presence of all steps in the causal pathway is uncertain

- Data show that there is at least one missing step in each causal pathway

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway

Reasoning and Comments SOE 

score

 Site LCN .415

Evidence for some causal steps - The high PTIA within this watershed may hinder soil infiltration 

thereby decreasing groundwater recharge and base discharge and, in turn, keeping flow above 

ground exposed to light and ambient air temperature (warmer than underground) and lowering 

base flow water depths, which may increase the rate of water-warming on summer days.

Ambiguous evidence - The increased light pathway resulting from riparian devegetation is not 

supported by the relatively high shaded canopy value. The pathway including decreased velocity, +

allowing longer retention time, and/or evaporation/evapotranspiration, is uncertain because the 

sub-optimal score for RBP channel sinuosity may indicate increases in flow velocity at the 

impaired site.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

 Site LCM 2.270

Evidence for some causal steps - The PTIA within this watershed may hinder soil infiltration 

thereby decreasing groundwater recharge and base discharge and, in turn, keeping flow above 

ground exposed to light and ambient air temperature (warmer than underground) and lowering 

base flow water depths, which may increase the rate of water-warming on summer days. The 

shaded canopy percentage at the impaired site is lower than the reference and may be evidence 

for further temperature increases due to increased light exposure.

+

Ambiguous evidence - The pathway including decreased velocity, allowing longer retention time 

and/or evaporation/evapotranspiration, is uncertain because the sub-optimal score for RBP 

channel sinuosity may indicate increases in flow velocity at the impaired site.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

100
Reasoning and Comments SOE 

score

 Site LCMn 2.274

Evidence for some causal steps - The PTIA within this watershed may hinder soil infiltration 

thereby decreasing groundwater recharge and base discharge and, in turn, keeping flow above 

ground exposed to light and ambient air temperature (warmer than underground) and lowering 

base flow water depths, which may increase the rate of water-warming on summer days.

Ambiguous evidence - The increased light pathway resulting from riparian devegetation is not 

supported by the relatively high shaded canopy value. The pathway including decreased velocity, 

allowing longer retention time and/or evaporation/evapotranspiration, is uncertain because the 

sub-optimal score for RBP channel sinuosity may indicate increases in flow velocity at the 

impaired site; this is confounded, however, with the lower baseflow velocity measured at the 

impaired site.

SOE scoring - The project team did not eliminate any causal pathways, and there is evidence for 

some steps.

+

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

101
SOE Table 18. Causal pathway - Scores - Increased toxic substances

Strength of evidence (SOE) scoring system for causal pathway

++ Data show that all steps in at least one causal pathway are present

+ Data show that some steps in at least one causal pathway are present

0 Data show that the presence of all steps in the causal pathway is uncertain

- Data show that there is at least one missing step in each causal pathway

- - - Data show, with a high degree of certainty, that there is at least one missing step in each causal pathway

Reasoning and Comments SOE 

score

 Sites LCN .415, LCM 2.270, and LCMn 2.274

Evidence for some causal steps - Primary evidence consists of high watershed PTIA in 

conjunction with known industrial and commercial land uses.

SOE scoring - There is no evidence regarding specific surface run-off characteristics, pertaining +

to toxic substances (beyond that which was used for spatial co-occurrence evidence). The 

project team did not eliminate any causal pathways, and there is evidence for some steps 

(sources only).

Causal pathway tables are closely tied to the conceptual models developed for each candidate cause. Refer to 

conceptual model figures in the main report to see how relevant variables and comments for each candidate cause, 

as shown above, correspond to specific causal steps and pathways.

102
SOE Table 19. Laboratory tests of site media (sediment toxicity) - Data

Percent survival, after 10 days exposure to sediment

Lab RB LCN LCM LCMn

Organism Control 3.961 .415 2.270 2.274

C. tentans 87.5 88.3 87.1 NE 92.5 (chironomid)

H. azteca 100.0 81.3 85.0 NE 96.3 (amphipod)

103
SOE Table 20. Laboratory tests of site media (sediment toxicity) - Scores

Strength of evidence (SOE) scoring system for laboratory tests of site media

+ + + Laboratory tests with site media show clear biological effects that are closely related to the observed impairment

+ Laboratory tests with site media show ambiguous effects OR clear effects that are not closely related to the observed impairment

0 Laboratory tests with site media show uncertain effects

- Laboratory tests with site media show no toxic effects that can be related to the observed impairment

NE no evidence.

SOE score

Reasoning and Comments Endpoint Score

 Site LCN .415

The project team used the chironomid (C. tentans ) and amphipod (H. azteca ) 

laboratory specimens as surrogates for EPT and non-insects, respectively. EPT richness 0 Chironomid survivorship differences among the two impaired sites tested, the % non-insects 0 reference site, and the laboratory control were not found to be statistically HBI NE significant; therefore, EPT was given a score of zero. Amphipod survival was brook trout NE significantly lower at both the reference and impaired sites than under the 

laboratory control; therefore, the sediment's effect on amphipods is uncertain.

 Site LCM 2.270

EPT richness NE

% non-insects NE Sediment sampling laboratory tests were not conducted for this site. HBI NE

brook trout NE

 Site LCN 2.274

The project team used the chironomid (C. tentans ) laboratory specimen as a EPT richness 0 surrogate for EPT. Chironomid survivorship differences among the two impaired HBI NE sites tested, the reference site, and the laboratory control were not found to be brook trout NE statistically significant; therefore, EPT was given a score of zero. 

10-day laboratory exposure does not accurately represent site conditions, where longer term exposures to sediment 

are likely. 

104
SOE Table 21. Mechanistically plausible cause (functional feeding and 

mode of existence groups)

Group

Study Site Percent

RB 3.961 LCN .415 LCM 2.270 LCMn 2.274

Functional feeding:

filterers 18.3 1.1 10.8 10.3

gatherers 18.6 16.5 60.7 71.8

predators 36.6 30.9 18.2 13.1

scrapers 17.2 13.3 3.3 1.4

shredders 7.8 34.6 6.7 2.7

Mode of existence:

burrower-sprawlers 57.9 38.3 33.9 19.2

swimmers 5.3 22.9 2.9 2.1

clingers 6.4 5.9 47.6 70.1

climbers 27.7 18.6 3.5 7.6

105
SOE Table 22. Stressor-response relationship from elsewhere - Data - Increased autochthony

Stressor-Response Benchmark Variable, units RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 Description Value

reduced invertebrate diversity (Nordin, 1985) 100

chlorophyll 

a , mg/m2 eutrophy risk range (U.S. EPA, 2000b, summary 100 - 10.4 15.7 NE 17.5

document) 200EPA reference for ecoregion XIV, 59, northeastern 0.57 coastal zone (U.S. EPA, 2000c) 0.310 [3] 0.617 [3] 0.513 [3] 0.457 [3] baseflow total nitrogen, (0.280 - (0.610 - (0.420 - (0.330 - ppm eutrophy risk range (U.S. EPA, 2000b, summary 1.5 0.350) 0.620) 0.600) 0.540) document)

0.167 [3] 0.300 [3] 0.467 [3] 0.400 [3] baseflow total Kjeldahl EPA reference for ecoregion XIV, 59, northeastern 0.30 (0.100 - (0.300 - (0.400 - (0.300 - nitrogen, ppm coastal zone (U.S. EPA, 2000c) 0.200) 0.300) 0.500) 0.500)

0.143 [3] 0.317 [3] < 0.047 [3] < 0.057 [3] baseflow nitrate + EPA reference for ecoregion XIV, 59, northeastern 0.31 (0.150 - (0.310 - (0.02 - (0.03 - nitrite, ppm coastal zone (U.S. EPA, 2000c) < 0.20) 0.320) < 0.20) < 0.20)

deleterious effects on fish communities (Miltner & 0.06 Rankin, 1998) 0.009 [3] 0.048 [3] 0.025 [3] 0.030 [3] baseflow total EPA reference for ecoregion XIV, 59, northeastern 0.024 (0.008 - (0.040 - (0.020 - (0.024 - phosphorus, ppm coastal zone (U.S. EPA, 2000c) 0.010) 0.061) 0.028) 0.035) eutrophy risk range (U.S. EPA, 2000b, summary 0.035 -document) 0.075

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

106
SOE Table 23. Stressor-response relationship from elsewhere - Data - Decreased dissolved oxygen

Stressor-Response Benchmark Variable, units RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 Description Value

U.S. EPA (1986a) fresh and cold water aquatic life 8.0 criteria30-day LC50 values for four different EPT organisms 4.4 - 5.0(Nebeker, 1972) [4] minimum dissolved 8.0 [3] 5.3 [3] 4.1 [3] 4.4 [3]

oxygen, mg/L (8.0 - 9.5) (5.3 - 7.8) (4.1 - 7.4) (4.4 - 6.2) optimum level for brook trout, where temperature is 

9 above 15 ̊C (Raleigh, 1982)

minimum acceptable temporary brook trout level 

5 (Mills, 1971 as cited in Raleigh, 1982)

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

107
SOE Table 24. Stressor-response relationship from elsewhere - Data - Altered flow regime

Stressor-Response Benchmark Variable, units RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 Description Value

abrupt decline in taxonomic richness, specifically EPT, and an increase in non-insects, specifically 6

impervious surface gastropods (Morse et al., 2003) 2.1 32.6 7.1 14.3 area, % shift to tolerant species (Maxted et al., 1996) 10 - 15

brook trout not found (Boward et al., 1999)

2

108
SOE Table 25. Stressor-response relationship from elsewhere - Data - Decreased large woody debris

Stressor-Response Benchmark LCMn Variable, units RB 3.961 LCN .415 LCM 2.270 Description Value 2.274

aquatic invertebrate productivity 3 to 4 times higher for submerged wooden substrates or snags than for sandy or muddy benthic habitats (Benke et al., 1984; applies to EPT endpoint)

LWD diameter 

≥ 5 cm, 91 NE 37 43 debris dam abundance positively correlated with # of pieces macroinvertebrate abundance and relative abundance 

of shredders to biomass (Smock et al., 1989; applies ---------- ---------- ---------- ---------- ----------to EPT endpoint)

LWD diameter 

≥ 10cm, in high gradient mountain streams, trout nearly always # of pieces 39 NE 8 12 occupied pools with at least 2 pieces of woody debris 

(Flebbe 1999)LWD contributes to wild trout habitat (Neumann and Wildman, 2002)

N/A - analysis conducted qualitatively

109
SOE Table 26. Stressor-response relationship from elsewhere - Data - Increased sediment

Variable, units Stressor-Response Benchmark RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 Description Value

baseflow TSS, mg/L

exposure causing 40 - 60% aquatic invertebrate mortality and severe habitat degradation at greater 33 [4 than 1,000 hours duration (similar to baseflow studies]condition) (mean [n] (range), from literature review, (8 - 77)Newcombe and MacDonald, 1991) < 10 [3] < 10 [3] < 10 [3] < 10 [3]

(< 2 - < 10) (3 - < 10) (1 - < 10) (4 - < 10)

exposure causing reduction in brook trout growth rate 45 [3 at durations greater than 1,000 hours (similar to studies] baseflow condition) (mean [n] (range), from literature (12 - 100) review, Newcombe and MacDonald, 1991)

storm flow TSS, mg/L

exposure causes decreased invertebrate population at approximately 24 hours duration (similar to storm 53 - 92 event) (Gammon, 1970 as cited in Newcombe and 

MacDonald, 1991)

< 10 - 118 [9] < 10 - 271 [9] NE NE

sediment size, mm

sediment diameter potentially fine enough to hinder 0.43 - brook trout egg survival and early development 0.85 (Argent and Flebbe, 1999)

53% of 45% of 

particles @ particles @ 100% of 92% of 

0.062 - 0.13 0.062 - 0.13 particles @ particles @ 

& 35% @ & 29% @ 0.062 - 0.13 0.062 - 0.130.25 - 0.5 0.25 - 0.5

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

110
SOE Table 27. Stressor-response relationship from elsewhere - Data - Increased temperature

Stressor-Response Benchmark Variable, units RB 3.961 LCN .415 LCM 2.270 LCMn 2.274 Description Value

severe stress to most cold-water organisms (literature 21 review by Galli and Dubose, 1990)generalized optimum for EPT (literature review by < 17 Galli and Dubose, 1990)50% mortality for Baetis rhodani , Baetis tenax , and 21.1, temperature, weekly 21.1 [3] 22.7 [3] Caenis sp . (Ephemeroptera), respectively (literature 21.3, & 23.3 21.8 maximum, °C (20.3 - 22.1) (21.6 - 24.2) review by Galli and Dubose, 1990) 26.7generalized physiological optimum for stenotherms (trout and other coldwater fish) (literature review by < 20.0Galli and Dubose, 1990)95th percentile brook trout tolerance limit (Eaton et al., 22.3 1995)

Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].

111
SOE Table 28. Stressor-response relationship from elsewhere - Data - Increased toxic substances

Variable Stressor-Response Benchmark

(ppm or m

g/L) Flow Description

Value RB 3.961 LCN .415 LCM 2.270 LCMn 2.274

Ionic strength, water column sampling

calcium low not available 6.8 67 NE 31.5

29 [3] 122 [3] 99 [3] 66 [3] base EPA CCC 230 chloride (26 - 30) (91 - 141) (83 - 124) (58 - 73)

storm EPA CMC 860 17 - 57 [9] 15 - 296 [9] NE NE

ma

gnesium low not available 2.2 17 NE 11

range of 48-hr LC50 values for various salt 250 - 67 [3] 367 [3] 267 [3] salinity base combinations tested on Ceriodaphnia (Mount et al., 200 [3] 5700 (0 - 100) (300 - 400) (200 - 400) 1997)

EPT effects based on interpretation of statewide data from Maine (Davies and MEDEP, 2005; Fig. 6), Florida (Florida Department of Environmental 100 - 200 specific Protection, 2005; Appendix J), and Kentucky (Pond, 129 [3] 745 [3] 568 [3] 459 [3] conductivity, base 2004; Appendix J) (79 - 155) (659 - 796) (491 - 718) (376 - 510) uS/cm presence of amphipods in place of EPT might be 

indicative of higher conductivity, as amphipods are NAmore tolerant (Kefford et al., 2003)

Elements, water column sampling

aluminum low EPA CCC 0.087 0.045 0.006 NE 0.019

invertebrate SSD, LC50 for 10% of species 0.66

arsenic low chordate SSD, LC50 for 10% of species 0.71 < 0.0005 0.00098 NE 0.00235

EPA CCC 0.15

base < 0.0005 [3] < 0.0005 [3] < 0.0005 [3] < 0.0005 [3] EPA CCC 0.00025 low < 0.0002 < 0.0002 NE < 0.0002

cadmium invertebrate SSD, LC50 for 10% of species 0.032 < 0.0005 - storm chordate SSD, LC50 for 10% of species 0.35 < 0.0005 [9] NE NE 0.0007 [9] EPA CMC 0.002

112
Variable Stressor-Response Benchmark

(ppm or m

g/L) Flow Description

Value RB 3.961 LCN .415 LCM 2.270 LCMn 2.274

invertebrate SSD, LC50 for 10% of species 0.17 chromium low < 0.0005 0.0032 NE 0.00205 chordate SSD, LC50 for 10% of species 7.3

invertebrate SSD, LC50 for 10% of species 0.008 0.0013 [3]

base chordate SSD, LC50 for 10% of s

pecies 0.015 < 0.002 [3] < 0.002 [3] < 0.002 [3] (< 0.002 - 

EPA CCC 0.009 0.002) copper invertebrate SSD, LC50 for 10% of species 0.013 < 0.002 - 0.002 - 0.018 storm chordate SSD, LC50 for 10% of s

pecies 0.061 NE NE .003 [9] [9] EPA CMC 0.013

iron low EPA CCC 1.0 0.091 0.14 NE 0.22

base < 0.003 [3] < 0.003 [3] < 0.003 [3] < 0.003 [3] EPA CCC 0.0025 low < 0.0002 < 0.0002 NE < 0.0002 lead < 0.003 - 0.003 - 0.031 storm EPA CMC 0.065 NE NE .004 [9] [9]

invertebrate SSD, LC50 for 10% of species 0.61

base chordate SSD, LC50 for 10% of s

pecies 2.9 < 0.004 [3] < 0.004 [3] < 0.004 [3] < 0.004 [3]

EPA CCC 0.052

nickel low use baseflow S-R values immediately above 0.00045 0.0032 NE 0.0019

invertebrate SSD, LC50 for 10% of species 1.9 < 0.004 - storm chordate SSD, LC50 for 10% of s

pecies 6.2 < 0.004 [9] NE NE 0.013 [9] EPA CMC 0.47

selenium low EPA CCC 0.005 < 0.001 < 0.001 NE < 0.001

invertebrate SSD, LC50 for 10% of species 0.087 0.014 [3] 0.0042 [3]

base chordate SSD, LC50 for 10% of s

pecies 0.14 < 0.005 [3] (0.013 - < 0.005 [3] (< 0.005 - 

EPA CCC 0.12 0.015) 0.005)

zinc low use baseflow S-R values immediately above < 0.005 0.0064 NE < 0.005

invertebrate SSD, LC50 for 10% of species 0.45 .008 - .024 0.043 - 0.14 storm chordate SSD, LC50 for 10% of s

pecies 1.9 NE NE [9] [9] EPA CMC 0.12

113
Variable Stressor-Response Benchmark

(ppm or mg/L) Flow Description Value RB 3.961 LCN .415 LCM 2.270 LCMn 2.274

antimony < 0.0005 < 0.0005 < 0.0005

barium 0.0054 0.021 0.011beryllium < 0.0002 < 0.0002 < 0.0002

cobalt 0.00085 0.0029 0.000555manganese low --- see text --- 0.025 0.37 NE 0.092

molybdenum < 0.0005 0.00092 0.000385

silver < 0.0002 < 0.0002 < 0.0002

thallium < 0.0005 < 0.0005 < 0.0005vanadium 0.0003 0.00082 0.000695

.]n[e g , where more than one value available, and storm flow values shown as ran

) if a toxic substance is detected.

/L, unless otherwise noted.

y

)egran( ]n[

m or mg

rovided for baseflow onl pe is 

pped in 

g

ylap

Note that a ran

All values disBase and low flow values shown as mean 

(

EPA CCC and CMC from U.S. EPA, 2004b.

114
SOE Table 29. Stressor-response relationship from elsewhere - Scores - 

Increased autochthony

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not even qualitatively agree with stressor-response relationships

in controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

 Site LCN .415

The chlorophyll a site observation is approximately one order of magnitude less 

than benchmark values found in the literature. Total nitrogen levels at the 

impaired sites fall below the level for eutrophy risk, and all nitrogen measures are 

relatively close to the regional reference condition. While chlorophyll a and 

nitrogen values tend to weaken the case for increased autochthony, phosphorus 

values provide evidence for the cause. Specifically, baseflow total phosphorus is 

in the range where fish effects and/or eutrophication might be seen, and mean 

total site phosphorous was twice that of the regional reference value. S-R support 

for this cause is unclear, as the supporting evidence both weakens and supports.

EPT richness

% non-insects

HBI

brook trout

0

0

0

0

 Site LCM 2.270

Total nitrogen and phosphorus levels at the site fall under the level for eutrophy 

risk, and all nitrogen and phosphorus measures are relatively close to the regional 

reference condition values. Baseflow total phosphorus is below the range where 

fish effects might be seen. S-R data weaken the case for this cause. The project 

team score EPT and brook trout negatively because signs of increased 

autochthony are not significant; furthermore, a minor increase in autochthony 

would be expected to slightly benefit some organisms such as EPT and brook 

trout. HBI was also scored negatively because it was designed to reflect nutrient 

loading. Scoring for non-insects was unclear.

EPT richness

% non-insects

HBI

brook trout

-

0

-

-

 Site LCMn 2.274

The chlorophyll a site observation is approximately one order of magnitude less 

than benchmark values found in the literature. Total nitrogen and phosphorus site 

levels fall under the level for eutrophy risk, and all nitrogen and phosphorus 

measures are relatively close to the regional reference condition values. Baseflow 

total phosphorus is below the range where fish effects might be seen. S-R data 

refutes this cause. The project team scores EPT and brook trout negatively 

because signs of increased autochthony are not significant; furthermore, a minor 

increase in autochthony would be expected to slightly benefit some organisms 

such as EPT & brook trout. HBI was also scored negatively because it was 

designed to reflect nutrient loading.

EPT richness -

HBI -

brook trout -

115
SOE Table 30. Stressor-response relationship from elsewhere - Scores - 

Decreased dissolved oxygen

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not even qualitatively agree with stressor-response relationships

in controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

 Site LCN .415

The minimum measured dissolved oxygen value (5.3 mg/L) and the range of 

values are less than the EPA criteria (8.0 mg/L) and optimum brook trout level (9 

mg/L). We consider this supporting evidence for the case (positive score) for 

EPT taxa and brook trout, but it is unclear how non-insects and HBI would 

respond to these dissolved oxygen levels.

EPT richness

% non-insects

HBI

brook trout

+

0

0

+

 Site LCM 2.270

The minimum measured dissolved oxygen value (4.1 mg/L) and the range of 

values are less than the EPA criteria (8.0 mg/L) and optimum brook trout level (9 

mg/L). The range of observed values also dips into the 30-day LC50 range for 

EPT and goes below the temporary brook trout minimum (5 mg/L). We consider 

this supporting evidence for the case (positive score) for EPT taxa and brook 

trout, but it is unclear how non-insects and HBI would respond to these dissolved 

oxygen levels.

EPT richness

% non-insects

HBI

brook trout

+

0

0

+

 Site LCMn 2.274

The minimum measured dissolved oxygen value (4.4 mg/L) and the range of 

values are less than the EPA criteria (8.0 mg/L) and optimum brook trout level (9 

mg/L). The range of observed values also goes below the temporary brook trout 

minimum (5 mg/L). We consider this supporting evidence for the case (positive 

score) for EPT taxa and brook trout, but it is unclear how non-insects and HBI 

would respond to these dissolved oxygen levels.

EPT richness

HBI

brook trout

+

0

+

116
SOE Table 31. Stressor-response relationship from elsewhere - Scores - Altered 

flow regime

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

SOE score

Reasoning and Comments Endpoint Score

 Site LCN .415

EPT richness + Percent impervious surface is greater than all S-R benchmark values related to % non-insects + multiple endpoints. (See text for discussion on percent impervious surface as a HBI 0 conservative and qualitative surrogate for altered flow regime.) brook trout +

 Site LCM 2.270

EPT richness + Percent impervious surface is greater than all S-R benchmark values related to % non-insects + multiple endpoints. (See text for discussion on percent impervious surface as a HBI 0 conservative and qualitative surrogate for altered flow regime.) brook trout +

 Site LCMn 2.274

Percent impervious surface is greater than all S-R benchmark values related to EPT richness +

EPT and brook trout. (See text for discussion on percent impervious surface as a HBI 0

conservative and qualitative surrogate for altered flow regime.) brook trout +

117
SOE Table 32. Stressor-response relationship from elsewhere - Scores - 

Decreased large woody debris

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

 Site LCN .415

EPT richness NE

LWD was not measured at LCN .415. % non-insects

HBI

NE

NE

brook trout NE

 Site LCM 2.270

Relevant S-R data indicates that increased abundance or presence of LWD EPT richness +

supports macroinvertebrate and wild trout abundance. This evidence directionally % non-insects NE

and qualitatively supports the case for this cause for the EPT and brook trout HBI NE

endpoints. brook trout +

 Site LCMn 2.274

Relevant S-R data indicates that increased abundance or presence of LWD 

supports macroinvertebrate and wild trout abundance. This evidence directionally 

and qualitatively supports the case for this cause for the EPT and brook trout 

endpoints.

EPT richness

HBI

brook trout

+

NE

+

118
SOE Table 33. Stressor-response relationship from elsewhere - Scores - 

Increased sediment

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

 Site LCN .415

Baseflow TSS levels do not appear high enough to impact invertebrates or brook 

trout (note, however, that the invertebrate S-R value is based on 40-60% 

mortality; it's difficult to know what effects might be seen at the impaired site's EPT richness 0

TSS levels). Storm flow site measurements fall within the range of effects for % non-insects 0

invertebrates, and sediment diameters are fine enough to impact early stages of HBI 0

brook trout development, but note that reference site sediment sizes are similar. brook trout 0

The S-R data both weaken and support the case for this cause; therefore, zeros 

were assigned to all scores, indicating ambiguity.

 Site LCM 2.270

Baseflow TSS levels do not appear high enough to impact invertebrates or brook 

trout (note, however, that the invertebrate S-R value is based on 40-60% EPT richness 0

mortality; it's difficult to know what effects might be seen at the impaired site's % non-insects 0

TSS levels). Sediment diameters are fine enough to impact early stages of brook HBI 0

trout development, and so the brook trout endpoint was scored positive. Zeros brook trout +

were assigned to the other endpoint scores, indicating uncertainty.

 Site LCMn 2.274

Baseflow TSS levels do not appear high enough to impact invertebrates or brook 

trout (note, however, that the invertebrate S-R value is based on 40-60% 

mortality; it's difficult to know what effects might be seen at the impaired site's 

TSS levels). Sediment diameters are fine enough to impact early stages of brook 

trout development, and so the brook trout endpoint was scored positive. Zeros 

were assigned to the other endpoint scores, indicating uncertainty.

EPT richness

HBI

brook trout

0

0

+

Note that some TSS data did not meet MEDEP quality standards (MEDEP, pers comm, 2005).

119
SOE Table 34. Stressor-response relationship from elsewhere - Scores - 

Increased temperature

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

 Site LCN .415

The mean weekly maximum temperature exceeds most, and the range exceeds EPT richness +

all S-R benchmark values, except Caenis sp. LC50. The S-R evidence supports % non-insects 0

positive scores for EPT and brook trout, but it is unclear how non-insects and the HBI 0

HBI might respond to the site's temperatures. brook trout +

 Site LCM 2.270

The mean weekly maximum temperature exceeds all S-R benchmark values, 

except the Caenis sp. LC50. The site's second most dominant organism, Caenis EPT richness +

sp., is tolerant of high temperatures. In contrast, Caenidae were not found at the % non-insects 0

reference site. The S-R evidence supports positive scores for EPT and brook HBI 0

trout, but it is unclear how non-insects and the HBI might respond to the site's brook trout +

temperatures.

 Site LCMn 2.274

The mean weekly maximum temperature exceeds most of the S-R benchmark 

values listed. The site's second most dominant organism, Caenis sp., is tolerant 

of high temperatures. In contrast, Caenidae were not found at the reference site. 

The S-R evidence supports positive scores for EPT and brook trout, but it is 

unclear how non-insects and the HBI might respond to the site's high 

temperatures.

EPT richness

HBI

brook trout

+

0

+

120
SOE Table 35. Stressor-response relationship from elsewhere - Scores - 

Increased toxics at LCN .415

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

ionic strength

Chloride site values are below EPA CCC and CMC benchmarks. Salinity values 

are within the range of LC50 observations, and the specific conductivity range 

indicates effects to EPT for which we gave a positive score. Further supporting 

evidence comes from the most dominant species at LCN .415, an amphipod, a EPT richness +

salt tolerant non-insect (Kefford et al., 2003), and for this we also gave a positive % non-insects +

score. Evidence is unclear for HBI and brook trout. Note that salinity HBI 0

measurements were calculated using specific conductivity—internal to the YSI 85 brook trout 0

field data logger; therefore, as a secondary or indirect measure, salinity is not 

used in other SOE considerations but is used here only for comparison to 

literature.

aluminum, arsenic, chromium, iron, nickel, and selenium

All observed site values fall below EPA CCC and CMC values (applies to all but 

chromium). All measured values at the site fall below the 10% SSD thresholds 

(applies to arsenic, chromium, and nickel). This weakens the case for effects on 

EPT and brook trout, but evidence is unclear for non-insects and HBI, which could 

benefit from some level of these substances.

EPT richness

% non-insects

HBI

brook trout

-

0

0

-

cadmium and lead

Measured values at the site fall below the 10% SSD thresholds for cadmium. The 

baseflow reporting limits for cadmium and lead are greater than corresponding 

EPA CCC values; therefore, while cadmium and lead were not detected in 

baseflow samples, they could still exceed CCC values. 1 of 9 storm samples at 

the impaired site registered positive for cadmium (0.0007 ppm), and cadmium 

was not detected in any other measurement. For these two substances there is 

no supporting evidence, but neither can be ruled out.

EPT richness

% non-insects

HBI

brook trout

0

0

0

0

copper

1 of 9 storm event copper samples exceeded the invertebrate SSD 10% threshold # EPT taxa +

and the EPA CMC, and 1 of 9 equaled those two criteria; this adds supporting % non-insects 0

evidence to the EPT and brook trout endpoints, but evidence for non-insects and HBI 0

HBI is unclear. brook trout +

121
SOE score

Reasoning and Comments Endpoint Score

zinc

All measured zinc values at the site fall below the 10% SSD thresholds. Baseflow EPT richness 0 & low flow values fall below the EPA CCC. 1 of 9 storm event zinc samples % non-insects 0 exceeds the EPA CMC value, and 1 of 9 equaled the CMC value. S-R evidence HBI 0 both weakens and supports the case for zinc as a cause; therefore, the project brook trout 0 team scored all endpoints zero (unclear)

antimony, barium, beryllium, cobalt, manganese, molybdenum, 

silver, thallium, and vanadium

EPT richness NE

% non-insects NE No appropriate S-R evidence could be applied to these remaining substances. HBI NE

brook trout NE

122
SOE Table 36. Stressor-response relationship from elsewhere - Scores - 

Increased toxics at LCM 2.270

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

ionic strength

Baseflow chloride is below the EPA CCC. Salinity values are within the range of 

LC50 observations, and the specific conductivity range indicates effects to EPT 

for which we gave a positive score. Further supporting evidence comes from the 

fifth most dominant species at the site, an isopod, a salt tolerant non-insect 

(Kefford et al., 2003), and for this we also gave a positive score. Evidence is 

unclear for HBI and brook trout. Note that salinity measurements were calculated 

using specific conductivity—internal to the YSI 85 field data logger; therefore, as a 

secondary or indirect measure, salinity is not used in other SOE considerations 

but is used here only for comparison to literature.

EPT richness

% non-insects

HBI

brook trout

+

+

0

0

cadmium and lead

The baseflow reporting limits for cadmium and lead are greater than EPT richness 0

corresponding EPA CCC values; therefore, while cadmium and lead were not % non-insects 0

detected in baseflow samples, they could still exceed CCC values. For these two HBI 0

substances, there is no supporting evidence, but neither can be ruled out. brook trout 0

copper, nickel, and zinc

Copper, nickel, and zinc were not detected in baseflow samples, and the 

reporting limits fall below corresponding EPA CCC values and the 10% SSD 

thresholds; therefore, the S-R data weaken the case for copper, nickel, and/or EPT richness -

zinc as causes. Note that we do not have storm flow data for copper at this site, % non-insects 0

unlike LCN .415, where storm samples tested positive for copper levels above the HBI 0

CCC and SSD 10% threshold but baseflow did not. Based on the data we do brook trout -

have for the three substances, EPT and brook trout receive negative scores, and 

impacts are unclear for non-insects and HBI.

123
SOE Table 37. Stressor-response relationship from elsewhere - Scores - 

Increased toxics at LCMn 2.274

Strength of Evidence scoring system for plausible effect given stressor-response relationships

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships in controlled

laboratory experiments or from other field studies.

0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationships in

controlled laboratory experiments or from other field studies is ambiguous.

- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in controlled

laboratory experiments or from other field studies.

- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relationships in

controlled laboratory experiments or from other field studies or the quantitative differences are very large.

NE no evidence.

Reasoning and Comments

SOE score

Endpoint Score

ionic strength

Baseflow chloride is below the EPA CCC, and salinity is below the LC50 range. 

The specific conductivity range indicates effects to EPT for which we gave a 

positive score. Evidence is unclear for HBI and brook trout. Note that salinity EPT richness +

measurements were calculated using specific conductivity—internal to the YSI 85 HBI 0

field data logger; therefore, as a secondary or indirect measure, salinity is not brook trout 0

used in other SOE considerations but is used here only for comparison to 

literature.

aluminum, arsenic, chromium, copper, iron, nickel, selenium, and 

zinc

All observed site values fall below EPA CCC values (applies to all but chromium). 

All measured values at the site fall below the 10% SSD thresholds (applies to all 

but aluminum, iron, and selenium). Note that we do not have storm flow data for EPT richness -

copper at this site, unlike LCN .415, where storm samples tested positive for HBI 0

copper levels above the CCC and SSD 10% threshold but baseflow did not. brook trout -

Based on the data we do have for these substances, EPT and brook trout receive 

negative scores, and impacts are unclear for HBI.

cadmium and lead

The baseflow reporting limits for cadmium and lead are greater than 

corresponding EPA CCC values; therefore, while cadmium and lead were not 

detected in baseflow samples, they could still exceed CCC values. For these two 

substances, there is no supporting evidence, but neither can be ruled out.

EPT richness

HBI

brook trout

0

0

0

antimony, barium, beryllium, cobalt, manganese, molybdenum, 

silver, thallium, and vanadium

EPT richness NE

No appropriate S-R evidence could be applied to these remaining substances. HBI NE

brook trout NE

124
o

s

s ips in controlled laboratory experiments or from other field studie

s in controlled laboratory experiments or from other field studie

 in controlled laboratory experiments or from other field studies i

s

 from elsewhere - Increased PAH's at LCN .415

ntrolled laboratory experiments or from other field studie

ationships in controlled laboratory experiments or from other field studies 

s

onse relationship

p SOE Table 38. Stressor-res

Strength of Evidence scoring system for plausible effect given stressor-response relationship

+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationsh+ The observed relationship between exposure and effects in the case agrees qualitatively with stressor-response relationships0 The agreement between the observed relationship between exposure and effects in the case and stressor-response relationshipsambiguous.- The observed relationship between exposure and effects in the case does not agree with stressor-response relationships in co- - The observed relationship between exposure and effects in the case does not qualitatively agree with stressor-response relthe quantitative differences are very large.NE no evidence.

Polycyclic

Aromatic

Hydrocarbon

(PAH)

ALL units are 

μg/ml

Storm, 10/18/00

1.1" over 21 hrs

Storm, 9/25/01

1.7" over 24 hrs SOE 

U.S. EPA, U.S. EPA, 1986b sub2004dA (Goldbook) Eisler, 1987 ECOTOXB score

Canada, 

2003

(freshBritish water SOE 

Columbia, aquatic sub1993 life) score SOE score LCN RB .585 1.694 RL LCN RB .585 1.694 RL

Acenaphthene 0.10 nd 0.05 nd nd 0.1

<= 1,700 & 520 

data for human acute and chronic not listed 1280 (tox) - consume only freshwater, 

respectively

6 chronic 5.8 - - -

Acenaphthylene nd nd 0.05 nd nd 0.1 listed, but no not listed not listed not listed NE data not listed no data NE NEAnthracene 0.20 nd 0.05 nd nd 0.1 data for human not listed info not pertinent 95 (tox) - consume only 4 chronic & 0.1 0.012 + phototox 0Benzo(a)anthracene 0.10 nd 0.05 0.33 nd 0.1 data for human LC87 (6mo) not listed not listed - consume only bluegill @ 1,000 0.1 chronic & 0.018 + phototox 0Benzo(a)pyrene

0.10 nd 0.05 0.48 nd 0.1

LC50 (96hr) data for human not listed sandworm @ not listed - consume only >1,000 0.01 chronic 0.015 + 0

Benzo(b)fluoranthene 0.20 nd 0.05 1.11 nd 0.1

data for human 

consume only, info not pertinent, 

but nps shows not listed but listed many not listed NE

300 marine times

acute LEC

not listed, but 

pending ref to no data + 0.01 (NPS 

1997)

0

Benzo(ghi)perylene 0.10 nd 0.05 0.5 nd 0.2

LC50 (96hr) listed, but no not listed sandworm @ not listed - data >1,000 not listed not listed NE 0

Benzo(k)fluoranthene nd nd 0.05 0.29 nd 0.1

data for human 

consume only, 

but nps shows not listed not listed NE

300 marine 

acute LEC

not listed, but 

pending ref to no data + 0.01 (NPS 

1997)

0

Chrysene 0.20 nd 0.05 0.8 nd 0.1

LC50 (96hr) data for human not listed sandworm @ not listed - consume only >1,000 insufficient no data NE data 0

125
Polycyclic

Aromatic

Hydrocarbon

(PAH)

ALL units are 

μg/ml

Storm, 10/18/00

1.1" over 21 hrs

Storm, 9/25/01

1.7" over 24 hrs SOE 

U.S. EPA, U.S. EPA, 1986b sub2004dA (Goldbook) Eisler, 1987 ECOTOXB score

Canada, 

2003

(freshBritish water SOE 

Columbia, aquatic sub1993 life) score SOE score LCN RB .585 1.694 RL LCN RB .585 1.694 RL

Dibenzo(a,h)anthracene nd nd 0.05 0.11 nd 0.2

LC50 (96hr) data for human not listed sandworm @ not listed - consume only >1,000 not listed no data NE 0

Fluoranthene 0.50 nd 0.05 1.6 nd 0.1

<= 3,980 acute 

freshwater, and 38 data for human <= 40 and 16 LC50 (96hr) (feeding) - - consume only acute and chron, sandworm 500 200 (tox) respectively, 

saltwater

4 chronic & 0.2 0.04 + phototox 0

Fluorene 0.10 nd 0.05 nd nd 0.1

LC50s (various data for human not listed orgs, 96hr) 320 - not listed - consume only 5,600 12 chronic 3.0 - - -

Indeno(1,2,3-cd)pyrene

0.10 nd 0.05 0.56 nd 0.2 data for human not listed not listed NE consume only not listed no data NE NE

Naphthalene 0.10 nd 0.05 nd nd 0.1

LC50 (10d) 1,700 <= 2,300 and 620 copepod @ 50, (behavior) - listed, but no acute and chronic and LC50s 3,700 - data freshwater, (various orgs, 24- (physiol- respectively 96 hr) 920 - ogy) 150,000 1 chronic 1.1 - - -

Phenanthrene 0.25 nd 0.05 0.67 nd 0.1

LC50 (24hr) grass 

listed, but no shrimp @ 370, not listed 340 (tox) - data and LC50 (96hr) 

sandworm 600 

0.3 chronic 0.4 + 0

Pyrene 0.30 nd 0.05 1.15 nd 0.1 data for human not listed 1,020 (tox) - consume only 0.02 phototox 0.025 + 0

ASource (U.S. EPA, 2004d) lists only human health consumption criteria for some PAHs. BECOTOX database (ECOTOXicology, located at: http://www.epa.gov/ecotox/).

126
SOE Table 39. Consistency of evidence scoring system

Finding Interpretation Score

All available types of evidence support the case for the This finding convincingly supports the case for the candidate + + + candidate cause. cause.

All available types of evidence weaken the case for the This finding convincingly weakens the candidate cause. - - - candidate cause.

This finding somewhat supports the case for the candidate All available types of evidence support the case for the cause, but is not strongly supportive because coincidence and 

+ candidate cause, but few types are available. errors may be responsible.

This finding somewhat weakens the case for the candidate All available types of evidence weaken the case for the cause, but is not strongly weakening because coincidence and - candidate cause, but few types are available. errors may be responsible.

This finding neither supports nor weakens the case for the The evidence is ambiguous or inadequate.

0 candidate cause.

This finding somewhat weakens the case for the candidate Some available types of evidence support and some cause but is not convincing because a few inconsistencies may - weaken the case for the candidate cause. be explained.

Source: U.S. EPA CADDIS (http://www.epa.gov/caddis/).

127
SOE Table 40. Strength of Evidence summary scoring at LCN .415

Types of evidence 

Types of evidence that that use data from 

use data from the case elsewhere

Consistency of Evidence

Biological endpoint

Candidate cause

Spatial/temporalco-occurrenceStressor-response relationships from the fieldCausal pathwayMechanistically Plausible CauseStressor-response relationships from laboratory or other field studies

EPT richness

Increased autochthony 0 0 + 0 0 0

Decreased dissolved oxygen + 0 + + + +

Altered flow regime + NE + + + + +

Decreased large woody debris NE + + + NE +

Increased sediment + 0 + + 0 +

Increased temperature + + + + + +

Increased ionic strength + + + + + + +

% non-insects

Increased autochthony 0 0 + + 0 0

Decreased dissolved oxygen + 0 + + 0 +

Altered flow regime + NE + + + + +

Decreased large woody debris NE 0 + + NE 0

Increased sediment + 0 + + 0 +

Increased temperature + 0 + 0 0 +

Increased ionic strength + + + 0 + + +

HBI

Increased autochthony 0 + + + 0 +

Decreased dissolved oxygen + + + + 0 +

Altered flow regime + NE + + 0 +

Decreased large woody debris NE + + + NE +

Increased sediment + 0 + 0 0 +

Increased temperature + + + 0 0 +

Increased ionic strength + + + 0 0 +

Brook trout

Increased autochthony 0 NE + 0 0 0

Decreased dissolved oxygen + NE + + + +

Altered flow regime + NE + + + + +

Decreased large woody debris NE NE + + NE +

Increased sediment + NE + + 0 +

Increased temperature + NE + + + +

Increased ionic strength + NE + + 0 +

NE = No evidence

Complete summary tables, including toxic substances and all lines of evidence, are located in the appendices.

128
SOE Table 41. Strength of Evidence summary scoring at LCM 2.270

Types of evidence 

Types of evidence that that use data from 

use data from the case elsewhere

Consistency of Evidence

Biological endpoint

Candidate cause

Spatial/temporalco-occurrenceStressor-response relationships from the fieldCausal pathwayMechanistically Plausible CauseStressor-response relationships from laboratory or other field studies

EPT richness

Increased autochthony 0 0 + 0 - -

Decreased dissolved oxygen + 0 + + + + +

Altered flow regime NE NE + + + +

Decreased large woody debris + + + + + + +

Increased sediment 0 0 + + 0 0

Increased temperature + + + + + + +

Increased ionic strength + + + + + + +

% non-insects

Increased autochthony 0 0 + 0 0 0

Decreased dissolved oxygen + 0 + + 0 +

Altered flow regime NE NE + + + +

Decreased large woody debris + 0 + + NE +

Increased sediment 0 0 + + 0 0

Increased temperature + 0 + 0 0 +

Increased ionic strength + + + 0 + + +

HBI

Increased autochthony 0 + + + - 0

Decreased dissolved oxygen + + + + 0 +

Altered flow regime NE NE + + 0 0

Decreased large woody debris + + + + NE +

Increased sediment 0 0 + 0 0 0

Increased temperature + + + 0 0 +

Increased ionic strength + + + 0 0 +

Brook trout

Increased autochthony 0 NE + 0 - -

Decreased dissolved oxygen + NE + + + + +

Altered flow regime NE NE + + + +

Decreased large woody debris + NE + + + +

Increased sediment 0 NE + + + +

Increased temperature + NE + + + +

Increased ionic strength + NE + + 0 +

NE = No evidence

Complete summary tables, including toxic substances and all lines of evidence, are located in the appendices.

129
SOE Table 42. Strength of Evidence summary scoring at LCMn 2.274

Types of evidence 

Types of evidence that that use data from 

use data from the case elsewhere

Consistency of Evidence

Biological endpoint

Candidate cause

Spatial/temporalco-occurrenceStressor-response relationships from the fieldCausal pathwayMechanistically Plausible CauseStressor-response relationships from laboratory or other field studies

EPT richness

Increased autochthony 0 0 + 0 - -

Decreased dissolved oxygen + 0 + + + + +

Altered flow regime + NE + + + +

Decreased large woody debris + + + + + + +

Increased sediment 0 0 + + 0 0

Increased temperature + + + + + + +

Increased ionic strength + + + + + + +

% non-insects

Increased autochthony

Decreased dissolved oxygen

Altered flow regime

Decreased large woody debris

Increased sediment

Increased temperature

Increased ionic strength

The % non-insects biological endpoint

was not assessed at site LCMn 2.274.

See text for more information.

HBI

Increased autochthony 0 + + + - 0

Decreased dissolved oxygen + + + + 0 +

Altered flow regime + NE + + 0 +

Decreased large woody debris + + + + NE +

Increased sediment 0 0 + 0 0 0

Increased temperature + + + 0 0 +

Increased ionic strength + + + 0 0 +

Brook trout

Increased autochthony 0 NE + 0 - -

Decreased dissolved oxygen + NE + + + + +

Altered flow regime + NE + + + +

Decreased large woody debris + NE + + + +

Increased sediment 0 NE + + + +

Increased temperature + NE + + + +

Increased ionic strength + NE + + 0 +

NE = No evidence

Complete summary tables, including toxic substances and all lines of evidence, are located in the appendices.

130
SOE Table 43. Consistency of evidence summary for all three impaired sites 

Biological endpoint

Candidate cause

I m p a i r e d s i t e

LCN

.415

LCM

2.270

LCMn

2.274

EPT richness

Increased autochthony 0 - -

Decreased dissolved oxygen + + + + +

Altered flow regime + + + +

Decreased large woody debris + + + + +

Increased sediment + 0 0

Increased temperature + + + + +

Increased ionic strength + + + + + +

% non-insects

Increased autochthony 0 0

was not assessed at 

Decreased dissolved oxygen + +

Mn 2.274.

Altered flow regime + + +

biological endpoint

information.

Decreased large woody debris 0 +

Increased sediment + 0

Increased temperature + +

The % non-insects 

site LC

See text for more 

Increased ionic strength + + + +

HBI

Increased autochthony + 0 0

Decreased dissolved oxygen + + +

Altered flow regime + 0 +

Decreased large woody debris + + +

Increased sediment + 0 0

Increased temperature + + +

Increased ionic strength + + +

Brook trout

Increased autochthony 0 - -

Decreased dissolved oxygen + + + + +

Altered flow regime + + + +

Decreased large woody debris + + +

Increased sediment + + +

Increased temperature + + +

Increased ionic strength + + +

Complete summary tables are located in the appendices.

131
SOE Table 44. Explanation of evidence scoring system

Finding Interpretation Score

There is a credible explanation for any negative This finding can save the case for a candidate cause that is inconsistencies or ambiguities in an otherwise positive body of weakened by inconsistent evidence; however, without evidence + + evidence that could make the body of evidence consistently to support the explanation, the cause is barely strengthened.supporting.There is no explanation for the inconsistencies or ambiguities This finding neither strengthens nor weakens the case for a 

0 in the evidence. candidate cause.

There is a credible explanation for any positive This finding further weakens an inconsistent case; however, inconsistencies or ambiguities in an otherwise negative body without evidence to support the explanation, the cause is barely -of evidence that could make the body of evidence consistently weakened.weakening.

Source: U.S. EPA CADDIS (http://www.epa.gov/caddis/)

132
SOE Table 45. Strength of evidence complete scoring at LCN .415

C a n d i d a t e C a u s e

I n c r e a s e d t o x i c s u b s t a n c e s

w a t e r c o l u m n

Type

of

Biological Evidence

endpoint

Types of evidence that use data from the case

Spatial/temporal

Increased 

NA 0++ NE + + + - - - 0 + + 0 + + + + + + + + + 0 0 0 + + ST ST

co-occurrence

autochthony

Stressor-response EPT richness 0 0 NE + 0 ++ NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 NE NE

Decreased 

relationships from % non-insects 0 0 NE 0 0 0+ NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 NE NE

dissolved oxygen

the field HBI + + NE + 0 ++ NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 NE NECausal pathway NA + + + + + ++ ++++++++++++++++++++ +

Altered flow 

Laboratory tests of EPT richness NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0

regime

site media % non-insects NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0

Decreased large 

Types of evidence that use data from elsewhere

woody debris

EPT richness 0 + + + + ++ ++++++++++++++++++++ +

Mechanistically % non-insects + + + + + 00 00000000000000000000 0

Increased 

plausible cause HBI

sediment

+ + + + 0 00 00000000000000000000 0

brook trout 0 + + + + ++ ++++++++++++++++++++ +

Increased 

Stressor-response EPT richness 0++ NE 0 + +- NE - NE NE 0 - NE +-0 NE NE - - NE NE NE 0 0 NE

temperature

relationships from % non-insects 00+ NE 0 0 +0 NE 0 NE NE 0 0 NE 000 NE NE 0 0 NE NE NE 0 0 NElaboratory or other HBI 000 NE 0 0 00 NE 0 NE NE 0 0 NE 000 NE NE 0 0 NE NE NE 0 0 NE

Ionic strength

field studies brook trout 0++ NE 0 + 0- NE - NE NE 0 - NE +-0 NE NE - - NE NE NE 0 0 NE

Aluminum

Multiple Lines of Evidence

EPT richness 0 + + + + + + + + - 0 - 0 0 0 - 0 + - 0 + 0 - - 0 0 0 + 0 0

Antimony

Consistency of % non-insects 0 + + + 0 + + + + 0 0 0 0 0 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0

Arsenic

evidence HBI + + + + + ++ 00000000000+000000+0 0

brook trout 0 + + + + + + + - 0 - 0 0 0 - 0 + - 0 + 0 - - 0 0 0 + 0 0

Barium

EPT richness 0 + + + + + + + + + + + + - ST ST ST ST ST ST ST + + ST ST ST ST ST ST ST ST ST ST 0 0

Beryllium

Explanation of the % non-insects 0 + + + + + + + + + + + + ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST 0 0

evidence HBI 0 + + + + + + + + + + + + ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST 0 0

Cadmium

brook trout 0 + + + + + + + + + + + + - ST ST ST ST ST ST ST + + ST ST ST ST ST ST ST ST ST ST 0 0

Chromium

Cobalt

Copper

Iron

Lead

Manganese

Molybdenum

Nickel

Selenium

Silver

Thallium

Vanadium

Zinc

PAHs

A Sediment toxicity

k of S-R information relevant to this type of data and given that the species 

NE = No evidence; ST = See text

 Sediment toxicity laboratory results include individual metal concentrations found in the sediment samples; however, given lac

found in sediment samples.

Asurvivorship information does not indicate support for this cause, we do not break this column down by individual contaminants 

133
SOE Table 46. Strength of Evidence complete scoring at LCM 2.270

C a n d i d a t e C a u s e

Increased toxic substances

water column

Type

of

Evidence

Biological 

Types of evidence that use data from the case

endpoint

Spatial/temporal NA 0 + NE + 0 + +00000

co-occurrence

Increased 

Stressor-response EPT richness 0 0 NE + 0 ++ NE NE NE NE 0

autochthony

relationships from % non-insects 0 0 NE 0 0 0+ NE NE NE NE 0

the field HBI

+

Decreased 

+ NE + 0 ++ NE NE NE NE 0

Causal pathway NA + +

dissolved oxygen

+ + + + ++++++

Types of evidence that use data from elsewhere

Altered flow 

EPT richness 0 + + + + + ++++++

regime

Mechanistically % non-insects 0 + + + + 0 000000

plausible cause HBI ++++

Decreased large 

0 0 000000

brook trout 0+++

woody debris

+ + ++++++

Stressor-response EPT richness - + + + 0 + +0-0- -

relationships from % non-insects 00+ NE

Increased 

0 0 +00000

laboratory or other HBI -00 NE 0 0 000000

sediment

field studies brook trout - + + + + + 00-0- -

Increased 

Multiple Lines of Evidence

temperature

EPT richness - + + + + + 0 + + + + 0 - 0 - -

Consistency of % non-insects 0 + + + 0 + + + 0 0 0 0 0

Ionic 

evidence HBI 0 + 0 + 0 + +00000

strength

brook trout - + + + + + + + 0 - 0 - -

Cadmium

EPT richness - + + + + + + 0 + + + + ST - ST - -

Explanation of the % non-insects 0 + + + + + + 0 + + + + ST ST ST ST ST

Copper

evidence HBI - + + + + + + 0 + + + + ST ST ST ST ST

brook trout - + + + + + + + + + + + + ST - ST - -

Lead

Nickel

Zinc

NE = No evidence; ST = See text

134
SOE Table 47. Strength of Evidence complete scoring at LCMn 2.274

C a n d i d a t e C a u s e

I n c r e a s e d t o x i c s u b s t a n c e s

w a t e r c o l u m n

Type

Biological of

endpoint Evidence

Types of evidence that use data from the case

Increased 

Spatial/temporal

autochthony

NA 0 + + + 0 + + - - - 0 + + 0 0 + - - - 0 + 0 + 0 + 0 0 0 + 0 ST

co-occurrenceStressor-response EPT richness

Decreased dissolved 

0 0 NE + 0 ++ NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 NE

relationships from 

oxygen

HBI + + NE + 0 ++ NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 NE the field

Altered flow 

Causal Pathway NA + + + + + ++ +++++++++++++++++++ +

regime

Laboratory tests of EPT richness NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 site media

Decreased large 

woody debris

Types of evidence that use data from elsewhere

EPT richness 0 + + + + ++ +++++++++++++++++++ + Mechanistically 

Increased 

HBI + + + + 0 00 0000000000000000000 0 plausible cause

sediment

brook trout 0 + + + + ++ +++++++++++++++++++ +

Stressor-response EPT richness - + + + 0 + +- NE - NE NE 0 - NE --0 NE NE - - NE NE NE - NE

Increased 

relationships from HBI -00 NE 0 0 00 NE 0 NE NE 0 0 NE 000 NE NE 0 0 NE NE NE 0 NE

temperature

laboratory or other 

brook trout - + + + + + 0- NE - NE NE 0 - NE --0 NE NE - - NE NE NE - NE field studies

Ionic strength

Multiple Lines of Evidence

EPT richness - + + + + + 0 + + + + - 0 - 0 0 0 - 0 - - 0 + 0 - - 0 0 0 - 0

Aluminum

Consistency of HBI 0 + + + 0 + + 00000000000+0000000 0 evidence

Antimony

brook trout - + + + + + + + - 0 - 0 0 0 - 0 - - 0 + 0 - - 0 0 0 - 0

EPT richness - + + + + + + 0 + + + + - ST ST ST ST ST ST ST - ST ST ST ST ST ST ST ST ST - 0

Arsenic

Explanation of the HBI - + + + + + + 0 + + + + ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST 0 evidence

Barium

brook trout - + + + + + + + + + + + + - ST ST ST ST ST ST ST - ST ST ST ST ST ST ST ST ST - 0

Beryllium

Cadmium

Chromium

Cobalt

Copper

Iron

Lead

Manganese

Molybdenum

Nickel

Selenium

Silver

Thallium

Vanadium

Zinc

Sediment toxicityA

k of S-R information relevant to this type of data and given that the species 

t NE = No evidence; ST = See tex

A Sediment toxicity laboratory results include individual metal concentrations found in the sediment samples; however, given lac

found in sediment samples. survivorship information does not indicate support for this cause, we do not break this column down by individual contaminants 

135
SOE Table 48. Consistency of evidence complete scoring for all three impaired sites 

C a n d i d a t e C a u s e

I n c r e a s e d t o x i c s u b s t a n c e s

w a t e r c o l u m n

Type

of

Biological Evidence

endpoint

LCN .415

EPT richness

Increased 

0 + + + + + + + + - 0 - 0 0 0 - 0 + - 0 + 0 - - 0 0 0 + 0 0

Consistency of % non-insects 0 + + + 0 + + + + 0 0 0 0 0 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0

autochthony

Evidence HBI + + + + + ++ 00000000000+000000+0 0

Decreased 

brook trout 0 + + + + + + + - 0 - 0 0 0 - 0 + - 0 + 0 - - 0 0 0 + 0 0

dissolved oxygen

LCM 2.270

Altered flow 

EPT richness - + + + + + 0 + + + + NE NE NE NE NE 0 NE NE - NE 0 NE NE - NE NE NE NE - NE NE

regime

Consistency of % non-insects 0 + + + 0 + + + NE NE NE NE NE 0 NE NE 0 NE 0 NE NE 0 NE NE NE NE 0 NE NEEvidence HBI 0+0+

Decreased large 

0 ++ NE NE NE NE NE 0 NE NE 0 NE 0 NE NE 0 NE NE NE NE 0 NE NE

woody debris

brook trout - + + + + + + + NE NE NE NE NE 0 NE NE - NE 0 NE NE - NE NE NE NE - NE NE

LCMn 2.274

Increased 

sediment

EPT richness - + + + + + 0 + + + + - 0 - 0 0 0 - 0 - - 0 + 0 - - 0 0 0 - NE 0 Consistency of HBI 0 + + + 0 + + 00000000000+0000000 NE 0 Evidence

Increased 

brook trout - + + + + + + + - 0 - 0 0 0 - 0 - - 0 + 0 - - 0 0 0 - NE 0

temperature

Ionic strength

Aluminum

Antimony

Arsenic

Barium

Beryllium

Cadmium

Chromium

Cobalt

Copper

Iron

Lead

Manganese

Molybdenum

Nickel

Selenium

Silver

Thallium

Vanadium

Zinc

PAH's

Sediment toxicity

k of S-R information relevant to this type of data and given that the species 

NE = No evidence

 Sediment toxicity laboratory results include individual metal concentrations found in the sediment samples; however, given lac

found in sediment samples.

Asurvivorship information does not indicate support for this cause, we do not break this column down by individual contaminants 

136
SOE Table 49. Water column metal observations study comparison - Low flow

South Portland 

Study Engineering MEDEP

LC 0 RB 0 LCN .585 LCM .595 LCMn 2.274 LCS .186 RB 1.694 Metal

Copper, ppm 0.008 0.005 <0.002 <0.002 0.002 0.002 <0.002Lead, ppm 0.005 <0.001 <0.003 <0.003 <0.003 <0.003 <0.003Zinc, ppm 0.025 0.025 0.015 <0.005 0.005 0.007 0.009

Adapted from MEDEP (2002a) Table 4.1b.

137
SOE Table 50. Water column metal observations study comparison - Stormflow

South Portland 

Study Engineering MEDEP

LC 0 RB 0 LCN .585 LCM .595 LCS .186 RB 1.694

Aug-94 Aug-94 Mar-00 Sep-01 Mar-00 Sep-01 Mar-00 Sep-01 Mar-00 Sep-01 Metal

Copper, ppm 0.007 0.008 0.018 0.013 0.021 0.015 0.044 0.007 <0.002 0.003Lead, ppm 0.003 0.009 0.031 0.015 0.052 0.025 0.9 0.007 0.003 0.004Zinc, ppm 0.05 0.07 0.14 0.12 0.2 0.11 0.27 0.062 0.024 0.023

Adapted from MEDEP (2002a) Table 4.1b.

138
APPENDICES
APPENDIX A 

HISTORIC MAPS 

Figure A-1. Historic USGS map – 1891. 

Dashed line is approximate location of superimposed case study watershed boundaries. 

Figure A-2. Historic USGS map – 1916. 

Dashed line is approximate location of superimposed case study watershed boundaries. 

A - 1 
Figure A-3. Historic USGS map – 1957. 

Dashed line is approximate location of superimposed case study watershed boundaries. 

Figure A-4. Current USGS map – circa 1980s. 

Dashed line is approximate location of superimposed case study watershed boundaries. 

A - 2 
Figure A-5. Clark’s Pond – Confluence of Long Creek and Red Brook. 

Source: 1940 and 1952 aerial photographs from Field (2005); 1976 and 1995 aerial 

photographs from Greater Portland Council of Governments, at 

http://www.gpcog.org/, accessed in 2005; 1998 (USGS Digital Orthophoto 

Quadrangle) and 2001 aerial photographs from Maine Office of Geographic 

Information Systems, at http://megis.maine.gov/, accessed on December 29, 2005. 

A - 3 
APPENDIX B 

MAINE’S WATER QUALITY CLASSIFICATION LAW 

 The following is a copy of Maine’s water quality classification law: Title 38, Chapter 3, 

Article 4-A, Section 465, Standards for classification of fresh surface waters, last updated 

December 1, 2004. This documentation can be accessed at the Maine State Legislature Web site: 

http://janus.state.me.us/legis/

The State of Maine claims a copyright in its codified statutes. If you intend to republish this material, we do require that 

you include the following disclaimer in your publication: 

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attorney. 

 §465. Standards for classification of fresh surface waters (CONTAINS TEXT 

WITH VARYING EFFECTIVE DATES) 

The department shall have 4 standards for the classification of fresh surface waters which are not classified 

as great ponds. [1989, c. 890, Pt. A, §40 (aff); Pt. B, §61 (amd).] 

1. Class AA waters. Class AA shall be the highest classification and shall be applied to waters which are 

outstanding natural resources and which should be preserved because of their ecological, social, scenic or 

recreational importance. [2003, c. 574, §1 (amd).] 

A. (TEXT EFFECTIVE UNTIL CONTINGENCY: See Title 38, section 470-E) Class AA waters shall be 

of such quality that they are suitable for the designated uses of drinking water after disinfection, fishing, 

recreation in and on the water and navigation and as habitat for fish and other aquatic life. The habitat shall be 

characterized as free flowing and natural. 

 [1985, c. 698, §15 (new).] 

A. (TEXT EFFECTIVE ON CONTINGENCY: See Title 38, section 470-E) Class AA waters must be of 

such quality that they are suitable for the designated uses of drinking water after disinfection, fishing, 

agriculture, recreation in and on the water, navigation and as habitat for fish and other aquatic life. The habitat 

must be characterized as free-flowing and natural. 

 [2003, c. 227, §1 (amd); §9 (aff).] 

B. The aquatic life, dissolved oxygen and bacteria content of Class AA waters shall be as naturally occurs. 

 [1985, c. 698, §15 (new).] 

C. Except as provided in this paragraph, there may be no direct discharge of pollutants to Class AA waters. 

(1) Storm water discharges that are in compliance with state and local requirements are allowed. 

(2) A discharge to Class AA waters that are or once were populated by a distinct population 

segment of Atlantic salmon as determined pursuant to the United States Endangered Species Act of 1973, 

Public Law 93-205, as amended, is allowed if, in addition to satisfying all the requirements of this article, 

the applicant, prior to issuance of a discharge license, objectively demonstrates to the department's 

satisfaction that the discharge is necessary, that there are no other reasonable alternatives available and 

B - 1 
that the discharged effluent is for the purpose of and will assist in the restoration of Atlantic salmon and 

will return the waters to a state that is closer to historically natural chemical quality. 

(a) The department may issue no more than a total of 3 discharge licenses pursuant to this 

subparagraph and subsection 2, paragraph C, subparagraph (2). 

(b) A discharge license issued pursuant to this subparagraph may not be effective for more than 5 

years from the date of issuance. 

 [2003, c. 574, §1 (rpr).] 

2. Class A waters. Class A shall be the 2nd highest classification. [2003, c. 574, §2 (amd).] 

A. (TEXT EFFECTIVE UNTIL CONTINGENCY: See Title 38, section 470-E) Class A waters shall be of 

such quality that they are suitable for the designated uses of drinking water after disinfection; fishing; 

recreation in and on the water; industrial process and cooling water supply; hydroelectric power generation, 

except as prohibited under Title 12, section 403; and navigation; and as habitat for fish and other aquatic life. 

The habitat shall be characterized as natural. 

 [1985, c. 698, §15 (new).] 

A. (TEXT EFFECTIVE ON CONTINGENCY: See Title 38, section 470-E) Class A waters must be of 

such quality that they are suitable for the designated uses of drinking water after disinfection; fishing; 

agriculture; recreation in and on the water; industrial process and cooling water supply; hydroelectric power 

generation, except as prohibited under Title 12, section 403; navigation; and as habitat for fish and other 

aquatic life. The habitat must be characterized as natural. 

 [2003, c. 227, §2 (amd); §9 (aff).] 

B. The dissolved oxygen content of Class A waters shall be not less than 7 parts per million or 75% of 

saturation, whichever is higher. The aquatic life and bacteria content of Class A waters shall be as naturally 

occurs. 

 [1985, c. 698, §15 (new).] 

C. Except as provided in this paragraph, direct discharges to these waters licensed after January 1, 1986 are 

permitted only if, in addition to satisfying all the requirements of this article, the discharged effluent will be 

equal to or better than the existing water quality of the receiving waters. Prior to issuing a discharge license, the 

department shall require the applicant to objectively demonstrate to the department's satisfaction that the 

discharge is necessary and that there are no other reasonable alternatives available. Discharges into waters of 

this classification licensed prior to January 1, 1986 are allowed to continue only until practical alternatives 

exist. 

(1) This paragraph does not apply to a discharge of storm water that is in compliance with state 

and local requirements. 

(2) This paragraph does not apply to a discharge to Class A waters that are or once were populated 

by a distinct population segment of Atlantic salmon as determined pursuant to the United States 

Endangered Species Act of 1973, Public Law 93-205, as amended, if, in addition to satisfying all the 

requirements of this article, the applicant, prior to issuance of a discharge license, objectively 

demonstrates to the department's satisfaction that the discharge is necessary, that there are no other 

reasonable alternatives available and that the discharged effluent is for the purpose of and will assist in the 

restoration of Atlantic salmon and will return the waters to a state that is closer to historically natural 

chemical quality. 

(a) The department may issue no more than a total of 3 discharge licenses pursuant to this 

subparagraph and subsection 1, paragraph C, subparagraph (2). 

(b) A discharge license issued pursuant to this subparagraph may not be effective for more than 5 

years from the date of issuance. 

 [2003, c. 574, §2 (rpr).] 

D. Storm water discharges to Class A waters must be in compliance with state and local requirements. 

 [2003, c. 318, §4 (new).] 

E. Material may not be deposited on the banks of Class A waters in any manner that makes transfer of 

pollutants into the waters likely. 

B - 2 
 [2003, c. 318, §4 (new).] 

3. Class B waters. Class B shall be the 3rd highest classification. [1985, c. 698, §15 (new); 

2003, c. 227, §3 (amd); §9 (aff).] 

A. (TEXT EFFECTIVE UNTIL CONTINGENCY: See Title 38, section 470-E) Class B waters shall be of 

such quality that they are suitable for the designated uses of drinking water supply after treatment; fishing; 

recreation in and on the water; industrial process and cooling water supply; hydroelectric power generation, 

except as prohibited under Title 12, section 403; and navigation; and as habitat for fish and other aquatic life. 

The habitat shall be characterized as unimpaired. 

 [1985, c. 698, §15 (new).] 

A. (TEXT EFFECTIVE ON CONTINGENCY: See Title 38, section 470-E) Class B waters must be of 

such quality that they are suitable for the designated uses of drinking water supply after treatment; fishing; 

agriculture; recreation in and on the water; industrial process and cooling water supply; hydroelectric power 

generation, except as prohibited under Title 12, section 403; navigation; and as habitat for fish and other 

aquatic life. The habitat must be characterized as unimpaired. 

 [2003, c. 227, §3 (amd); §9 (aff).] 

B. The dissolved oxygen content of Class B waters shall be not less than 7 parts per million or 75% of 

saturation, whichever is higher, except that for the period from October 1st to May 14th, in order to ensure 

spawning and egg incubation of indigenous fish species, the 7-day mean dissolved oxygen concentration shall 

not be less than 9.5 parts per million and the 1-day minimum dissolved oxygen concentration shall not be less 

than 8.0 parts per million in identified fish spawning areas. Between May 15th and September 30th, the number 

of Escherichia coli bacteria of human origin in these waters may not exceed a geometric mean of 64 per 100 

milliliters or an instantaneous level of 427 per 100 milliliters. 

 [1985, c. 698, §15 (new).] 

C. Discharges to Class B waters shall not cause adverse impact to aquatic life in that the receiving waters 

shall be of sufficient quality to support all aquatic species indigenous to the receiving water without detrimental 

changes in the resident biological community. 

 [1985, c. 698, §15 (new).] 

4. Class C waters. Class C shall be the 4th highest classification. [2003, c. 664, §1 (amd).] 

A. (TEXT EFFECTIVE UNTIL CONTINGENCY: See Title 38, section 470-E) Class C waters shall be of 

such quality that they are suitable for the designated uses of drinking water supply after treatment; fishing; 

recreation in and on the water; industrial process and cooling water supply; hydroelectric power generation, 

except as prohibited under Title 12, section 403; and navigation; and as a habitat for fish and other aquatic life. 

 [1985, c. 698, §15 (new).] 

A. (TEXT EFFECTIVE ON CONTINGENCY: See Title 38, section 470-E) Class C waters must be of 

such quality that they are suitable for the designated uses of drinking water supply after treatment; fishing; 

agriculture; recreation in and on the water; industrial process and cooling water supply; hydroelectric power 

generation, except as prohibited under Title 12, section 403; navigation; and as a habitat for fish and other 

aquatic life. 

 [2003, c. 227, §4 (amd); §9 (aff).] 

B. The dissolved oxygen content of Class C water may be not less than 5 parts per million or 60% of 

saturation, whichever is higher, except that in identified salmonid spawning areas where water quality is 

sufficient to ensure spawning, egg incubation and survival of early life stages, that water quality sufficient for 

these purposes must be maintained. In addition, in order to provide additional protection for growth of 

indigenous fish, dischargers that were issued final discharge licenses or water quality certificates prior to March 

16, 2004 that are based on a 6.5 parts per million dissolved oxygen criterion must continue to be licensed using 

a temperature of 24 degrees centigrade or the ambient temperature of the water body, whichever is lower. Final 

discharge licenses and water quality certificates not based on a 6.5 parts per million dissolved oxygen criterion 

prior to March 16, 2004 must be based on a 6.5 parts per million dissolved oxygen criterion at a temperature of 

22 degrees centigrade or the ambient temperature of the water body, whichever is lower. Between May 15th 

and September 30th, the number of Escherichia coli bacteria of human origin in these waters may not exceed a 

geometric mean of 142 per 100 milliliters or an instantaneous level of 949 per 100 milliliters. The board shall 

adopt rules governing the procedure for designation of spawning areas. Those rules must include provision for 

B - 3 
B - 4 

periodic review of designated spawning areas and consultation with affected persons prior to designation of a 

stretch of water as a spawning area. 

 [2003, c. 664, §1 (amd).] 

C. Discharges to Class C waters may cause some changes to aquatic life, provided that the receiving waters 

shall be of sufficient quality to support all species of fish indigenous to the receiving waters and maintain the 

structure and function of the resident biological community. 

 [1985, c. 698, §15 (new).] 

PL 1985, Ch. 698, §15 (NEW). 

PL 1989, Ch. 890, §A40,B61-63 (AMD). 

PL 1999, Ch. 243, §8 (AMD). 

PL 2003, Ch. 227, §1-4 (AMD). 

PL 2003, Ch. 227, §9 (AFF). 

PL 2003, Ch. 318, §3,4 (AMD). 

PL 2003, Ch. 574, §1,2 (AMD). 

PL 2003, Ch. 664, §1 (AMD). 
APPENDIX C 

MACROINVERTEBRATE ROCKBAG SAMPLING DATA 

The following table provides rockbag sampling data for Long Creek and Red Brook. MEDEP biologists conducted sampling beginning

August 5-6, 1999, using three rockbags over a 32-day colonization period. See the main text for information on how the data was used in 

this analysis. For general information about the data, refer to MEDEP (2002a). 

Class Order Family Genus

Reference

site

RB

3.961

Impaired sites Other Long Creek & Red Brook sites

LCN LCM LCMn

.415 2.270 2.274

LCS LCM LCM RB RB

.369 .380 .910 .071 1.474

Non-Insects:

Arachnida Acari Hydrachnidae

Arachnida Acari Hygrobatidae Hygrobates

Arachnida Acari Lebertiidae FerrissiaCrustacea AmphipodaCrustacea Amphipoda Crangonyctidae Crangonyx

Crustacea Amphipoda Hyalellidae Hyalella

Crustacea CladoceraCrustacea Isopoda Asellidae Caecidotea

GastropodaGastropoda Limnophila Ancylidae Ferrissia

Gastropoda Limnophila Physidae Physa

Gastropoda Limnophila Physidae PhysellaGastropoda Limnophila Physidae

Gastropoda Limnophila PlanorbidaeGastropoda Mesogastropoda Valvatidae Valvata

Gastropoda Mollusca Planorbidae Gyraulus

Gastropoda Basommatophora Planorbidae Helisoma

Hirudinea Arhynchobdellida Erpobdellidae Erpobdella

Hirudinea Arhynchobdellida Erpobdellidae

Hirudinea Rhynchobdellida Rhynchobdellida

Hirudinea Rhynchobdellida Glossiphoniidae Glossiphonia

Hirudinea Rhynchobdellida Glossiphoniidae HelobdellaHirudinea Rhynchobdellida Glossiphoniidae PlacobdellaHydrozoa Hydroida

Oligochaeta Lumbriculida Lumbricidae

Oligochaeta Lumbriculida Lumbriculidae Stylodrilus

Oligochaeta Lumbriculida Lumbriculidae 

0

00

0

00

0

10

000

0

0

00

0

0

0

0

0400

0

4

0

000

000000

0 8 0

100

38 16 0

0 0 0

0 52 00 0 0

000003

21 0 0

100

0 0 0

000000

000

000

0 0 1

010

4100 26 0000000

0 1 0

000

0 0 0

00020

0001000400000000 73 52 0 0

60 23 65 0 0

00700

0 1 30 0 0

70000

0501000100

10 0 0 0 0

00010

00110

0042080000

30000

10000

0120007000

00601

00501

0010002200

000000200030000

C - 1
Class Order Family Genus

LCN

.415

LCM

2.270

LCMn

2.274

LCS

.369

LCM

.380

LCM

.910

RB

.071

RB

1.474

Oligochaeta Tubificida Enchytraeidae 0 10000000

Oligochaeta Tubificida Naididae Chaetogaster 2 00000000

Oligochaeta Tubificida Tubificidae Limnodrilus 0 03000000

Oligochaeta Tubificida Tubificidae 0 0 19 080000

Pelecypoda Veneroida Sphaeriidae Pisidium 14 1 0 0 18 0 0 0 0

Pelecypoda Veneroida Sphaeriidae 3 0 0030000Pelecypoda Veneroida Sphaeriidae Sphaerium 0 0 58 0 0 0 14 0 0

28 67 185 4 121 114 194 8 2

Insects:

Insecta Coleoptera Dytiscidae Deronectes 0 00023000

Insecta Coleoptera Dytiscidae Dytiscus 0 00100000

Insecta Coleoptera Elmidae Ancyronyx 0 00000200

Insecta Coleoptera Elmidae Dubiraphia 0 0 478 175 1 32 111 2 15

Insecta Coleoptera Elmidae 0 0 0000001Insecta Coleoptera Elmidae Macronychus 0 10002000

Insecta Coleoptera Elmidae Optioservus 0 0 0 1 0 0 37 0 0

Insecta Coleoptera Elmidae Oulimnius 0 00001000

Insecta Coleoptera Elmidae Promoresia 0 10020000

Insecta Coleoptera Elmidae Stenelmis 0 0 16 0 0 2 9 0 0

Insecta Coleoptera Haliplidae Haliplus 0 00000100

Insecta Coleoptera Psephenidae Ectopria 0 20000000

Insecta Collembola 0 00010000Insecta Diptera 0 00020000Insecta Diptera Ceratopogonidae Bezzia/Palpomyia 0 00010000

Insecta Diptera Ceratopogonidae Culicoides 0 01000000

Insecta Diptera Chironomidae Ablabesmyia 2 4 1 4 28 0 0 4 0

Insecta Diptera Chironomidae Apsectrotanypus 1 00000000

Insecta Diptera Chironomidae Brundiniella 3 00000000

Insecta Diptera Chironomidae Chironomus 0 0 2 0 15 0 0 0 0

Insecta Diptera Chironomidae Clinotanypus 0 0 104 0 0 0 0 0 0

Insecta Diptera Chironomidae Conchapelopia 3 00010000

Insecta Diptera Chironomidae Cricotopus 0 00000300

Insecta Diptera Chironomidae Cryptochironomus 0 00030000

Insecta Diptera Chironomidae Cryptotendipes 0 00000010Insecta Diptera Chironomidae Dicrotendipes 0 2 10 2 2 0 1 0 0

Insecta Diptera Chironomidae Heterotrissocladius 2 00000000

Insecta Diptera Chironomidae Hudsonimyia 0 00001000

Other Long Creek & Red Brook sites

Non-insect sub-total:

Reference

site

RB

3.961

Impaired sites

C - 2
Class Order Family Genus

Reference

site

RB

3.961

Impaired sites Other Long Creek & Red Brook sites

LCN LCM LCMn

.415 2.270 2.274

LCS LCM LCM RB RB

.369 .380 .910 .071 1.474

Insecta Diptera Chironomidae Kiefferulus

Insecta Diptera Chironomidae Labrundinia

Insecta Diptera Chironomidae MacropelopiaInsecta Diptera Chironomidae Meropelopia

Insecta Diptera Chironomidae MicropsectraInsecta Diptera Chironomidae Microtendipes

Insecta Diptera Chironomidae Natarsia

Insecta Diptera Chironomidae Parachironomus

Insecta Diptera Chironomidae Parakiefferiella

Insecta Diptera Chironomidae Paralauterborniella

Insecta Diptera Chironomidae Paramerina

Insecta Diptera Chironomidae Parametriocnemus

Insecta Diptera Chironomidae Phaenopsectra

Insecta Diptera Chironomidae Polypedilum

Insecta Diptera Chironomidae Procladius

Insecta Diptera Chironomidae Psectrotanypus

Insecta Diptera Chironomidae Rheotanytarsus

Insecta Diptera Chironomidae Stempellina

Insecta Diptera Chironomidae StempellinellaInsecta Diptera Chironomidae Tanytarsus

Insecta Diptera Chironomidae Thienemanniella

Insecta Diptera Chironomidae Thienemannimyia

Insecta Diptera Chironomidae Trissopelopia

Insecta Diptera Chironomidae Xylotopus

Insecta Diptera Chironomidae Zavrelia

Insecta Diptera Chironomidae Zavrelimyia

Insecta Diptera Chironomidae Nanocladius

Insecta Diptera Chironomidae Orthocladius

Insecta Diptera Chironomidae Paratanytarsus

Insecta Diptera Chironomidae Paratendipes

Insecta Diptera Culicidae Anopheles

Insecta Diptera EmpididaeInsecta Diptera Empididae Hemerodromia

Insecta Diptera Tabanidae Chrysops

Insecta Diptera TabanidaeInsecta Diptera Tipulidae Limnophila

Insecta Diptera Tipulidae Pilaria

Insecta Diptera Tipulidae Pseudolimnophila

0

1

18

2

27

0

1

0

2

4

3

6

0

13

8

03

0

26

42

03

2

0

0

9

0

0

0

0

0

1

0

3

0

0

1

1

000

100

000000

5000 37 22

3 11 0

000

000

000

612

000

100

010

29 21 14

100000

0 10 0

000

0 23 5902050

000

000

001

201

000

000

000

000

001

000

000

200

0 6 0

000

000

000

02000

00000

0000000000

00000

00197

34 3 0 1 0

01000

00000

00000

04110

10001

20 0 0 0 2

31 0 3 1 1

30011

0000008051

0 21 2 0 00 14 0 7 4

18 5 122 30 4

10000

12 32 0 0 4

00000

10000

00100

00000

10000

50000

70000

10000

00000

00000

10000

62000

0 53 0 0 0

00001

00000

00000

C - 3
Class Order Family Genus

LCN

.415

LCM

2.270

LCMn

2.274

LCS

.369

LCM

.380

LCM

.910

RB

.071

RB

1.474

Insecta Diptera Tipulidae Tipula 1 00003000

Insecta Ephemeroptera Baetidae Acerpenna 1 00000000

Insecta Ephemeroptera Baetidae 0 1 9100141Insecta Ephemeroptera Baetidae Cloeon 0 00200200

Insecta Ephemeroptera Caenidae Caenis 0 3 190 26 43 62 67 1 0

Insecta Ephemeroptera Ephemerellidae Eurylophella 0 00000040

Insecta Ephemeroptera Heptageniidae Heptageniidae 1 00000000

Insecta Ephemeroptera Heptageniidae Stenonema 8 00000002

Insecta Ephemeroptera Leptophlebiidae 6 0 0000000Insecta Ephemeroptera Leptophlebiidae Paraleptophlebia 12 0 0 0 0 0 0 57 10Insecta Hemiptera Gerridae Gerris 0 00100000

Insecta Hemiptera Veliidae Microvelia 0 30000000

Insecta Hemiptera Veliidae Veliidae 0 00000000

Insecta Megaloptera Corydalidae Nigronia 1 5 0 0 0 2 1 2 12

Insecta Megaloptera Sialidae Sialis 46 0 8 2 29 11 0 2 6

Insecta Odonata Aeshnidae Aeshna 0 30057000

Insecta Odonata Aeshnidae 0 0 0400400

Insecta Odonata Aeshnidae Boyeria 3 00411220

Insecta Odonata Calopterygidae 7 00000030

Insecta Odonata Calopterygidae Calopteryx 0 11004017

Insecta Odonata Coenagrionidae Argia 0 0 1 0 13 0 0 0 0

Insecta Odonata Coenagrionidae 0 03000200

Insecta Odonata Coenagrionidae Enallagma 0 00002000

Insecta Odonata Cordulegastridae Cordulegaster 5 00000000

Insecta Odonata Gomphidae Lanthus 1 00000000

Insecta Odonata Libellulidae Sympetrum 0 00100000

Insecta Plecoptera Leuctridae Leuctra 3 00000000

Insecta Trichoptera Calamoceratidae Heteroplectron 1 00000000

Insecta Trichoptera Dipseudopsidae Phylocentropus 1 0 7 2 16 4 0 3 7

Insecta Trichoptera Hydropsychidae Cheumatopsyche 0 00000002

Insecta Trichoptera Hydropsychidae Diplectrona 1 00000000

Insecta Trichoptera Hydropsychidae Hydropsyche 2 00010000

Insecta Trichoptera Hydroptilidae Oxyethira 0 00000020

Insecta Trichoptera Leptoceridae 0 0 1000000Insecta Trichoptera Leptoceridae Mystacides 0 9 0 0 0 11 9 40 0

Insecta Trichoptera Leptoceridae Oecetis 0 0 20 5 1 1 3 0 1

Insecta Trichoptera Limnephilidae Glyphopsyche 0 00001000

Insecta Trichoptera Limnephilidae 0 0 1000000Insecta Trichoptera Limnephilidae Limnephilus 3 12 0 5 1 0 0 0 2

Reference

site

RB

3.961

Impaired sites Other Long Creek & Red Brook sites

C - 4
Class Order Family Genus

Reference

site

RB

3.961

Impaired sites Other Long Creek & Red Brook sites

LCN LCM LCMn

.415 2.270 2.274

LCS LCM LCM RB RB

.369 .380 .910 .071 1.474

Insecta Trichoptera Limnephilidae Psychoglypha

Insecta Trichoptera Limnephilidae Pycnopsyche

Insecta Trichoptera Molannidae Molanna

Insecta Trichoptera Odontoceridae PsilotretaInsecta Trichoptera Phryganeidae Oligostomis

Insecta Trichoptera Phryganeidae

Insecta Trichoptera Phryganeidae Ptilostomis

Insecta Trichoptera Polycentropodidae

Insecta Trichoptera Polycentropodidae Polycentropus

Insecta Trichoptera Psychomyiidae Lype

56

0

27

5

0

0

0

00

000000

030

000

000

0 0 0

14 1 3

1 0 0

000000

0000000000

00101

0 16 0 0 0

0000010000

03203

000000006000020

Insect sub-total: 333 121 972 287 311 314 388 191 96

Total (non-insects + insects):

Total mean abundance (total / 3 samples):

% non insects:

361

120.3

7.8%

188 1157 291

62.7 385.7 97.0

35.6% 16.0% 1.4%

432 428 582 199 98

144.0 142.7 194.0 66.3 32.7

28.0% 26.6% 33.3% 4.0% 2.0%

C - 5
D - 1 

APPENDIX D 

MAINE’S LINEAR DISCRIMINANT FUNCTION MODEL VARIABLES

The following 30 linear discriminant function (LDF) model variable descriptions are 

copied directly from Davies and Tsomides (2002). Further information about the LDF model 

can be found in Davies and Tsomides (2002).
D - 2 
D - 3 
D - 4 
D - 5 
E - 1 

APPENDIX E 

REGIONAL REFERENCE ANALYSIS 

Red Brook site RB 3.961 was chosen as the reference site for this case study. The project 

team developed a regional reference library, as described in this appendix, to confirm that RB 

3.961 is a suitable reference site. 

Methods

The regional reference library includes Maine streams with sandy-bottoms, Class A surface 

water quality designations, and surficial geology similar to that of the case study streams; this 

translates to 23 sites from 10 different streams. The project team compared each MEDEP Linear 

Discriminant Function (LDF; see Appendix B of this report and Tsomides and Davies, 2002) 

model variable distribution associated with the regional reference library to corresponding 

observed measurements from the three impaired Long Creek sites, the Red Brook reference site, 

and five additional sites also from the two watersheds (these nine total sites were not included in 

the regional reference library). 

A statistically significant relationship was found (Kruskal-Wallis test) between surficial geology 

and 3 of 23 LDF model variables: 07 Relative Chironomidae Abundance, 09 Hydropsyche Mean 

Abundance, and 16 Tanypodinae Mean Abundance. Therefore, for these three variables, the 

comparison with Long Creek and Red Brook sites is conducted by surficial geology type. Three 

surficial geology types are represented within the case study and regional reference library, 

primarily including Pp10 and Pmrs11 (type Ha12 is the third type, located only at site RB .071); 

therefore, variables 07, 09, and 16 were broken down into three different analyses—Pp sites, 

Pmrs sites, and the combination thereof. For the remaining 20 LDF variables, we do not 

distinguish on the basis of surficial geology type. 

Table C-1 compares 5th, 25th, 75th, and 95th percentiles of the regional reference library range to 

Long Creek and Red Brook site-specific values for each LDF variable. Percentiles were used for 

the comparison because reference stream data is not normally distributed, and many variables 

have a value of zero. Highlighted values fall outside the percentile range. Figures C-1 – C-30 

 

10 Pp, or Presumpscot Formation, consists of fine-grained silt and clay with minor marine fossils and dropstones 

deposited in deeper, quiet water during the marine submergence of the coastal zone (Thompson et al., 1997). 

11 Pmrs, or Marine regressive sand deposits, consists of sand deposited in marine waters during regression of the sea 

from the coastal zone. Sand is commonly interbedded with fine-grained sediments of the Presumscot Formation 

(Thompson et al., 1997). 

12 Ha, or Stream alluvium, consists of silt, sand, and gravel, comprising modern flood plains (Thompson et al., 

1997).
E - 2 

graphically display information from Table C-1. The table and the figures show 30 total 

comparisons, representing the 23 LDF model variables, three of which are further broken down 

by surficial geology type (Pp, Pmrs, and the combination of Pp and Pmrs). 

Results and discussion

For 15 of the LDF model variables, at least one case study site falls above the 95th percentile or 

below the 5th percentile. These variables are usually associated with overall low abundance (4 of 

the 8 non-reference sites), low abundance of Plecoptera (8 of 8 non-reference sites), or absence 

of Class A indicator taxa (8 of 8 non-reference sites). 

All sites in Long Creek have HBI values that are above the 95th percentile of the regional 

reference HBI value (and above the Red Brook sites). Four sites, LCN .415, LCMn 2.274, RB 

.071, and RB 1.474, have low total abundance. Three sites (including case study reference site 

RB 3.961) have Oligochaeta at a level significantly higher than the reference condition. Of the 

24 reference sites, six have oligochaetes present, so the presence does not prevent sites from 

attaining Class A. However, oligochaetes are not dominant at any of those reference sites. All 

sites except the reference site in this case study (RB 3.961) have low EPT richness and no 

Plecoptera individuals. However, in the reference streams there are sites showing 0.33 

Plecoptera (1 individual averaged over 3 rockbags). In the reference streams, there are some 

sites that attain Class A and have very low numbers of Plecoptera individuals per sample 

(Capisic 0.67, Frost Gulley 0.67, Cascade 0.67, and West Brook 0.33). Note that Plecoptera 

impacts multiple variables in the LDF model (12, 19, 23, 28, and minor influence on 30). 

RB 3.961 represents the regional reference sites quite well. Most LDF variable values for RB 

3.961 fall between the 25th and 75th percentiles of the regional reference condition. This regional 

reference analysis, on-site reconnaissance of the Red Brook and Long Creek watersheds, and 

general knowledge of the project team about Maine stream ecosystems and reference sites 

confirms RB 3.961 as a reasonable reference site for this case study.
Case Case study Other Long Creek & Red study impaired sites Brook sites reference 

Regional

reference

 L D F m o d e l v a r I a b l e

Total Mean Abundance

Generic Richness

Plecoptera Mean Abundance

01 02 03 04 05 06 07 07 07 08 09 09 09 11 12 13 15 16 16 16 17 18 19 21 23 25 26 28 30

Ephemeroptera Mean Abundance

5th % 101.6 23.6 0.7 5.4 3.04 3.14 0.10 0.08 0.41 0.27 0.0 0.0 0.0 0.0 0.36 0.00 0.00 0.0 0.0 7.0 0.0 0.03 11.0 0.0 0.03 0.0 0.0 0.36 0.14 3.3

25th % 165.2 44.0 1.0 14.3 3.69 3.80 0.34 0.19 0.48 0.40 0.2 8.0 0.0 0.0 0.51 0.00 0.00 4.2 2.2 11.2 5.7 0.06 13.5 2.2 0.03 3.2 0.5 0.43 0.29 8.5

Shannon-Wiener Generic Diversity

50th % 280.0 56.0 4.7 44.3 4.2 4.3 0.4 0.4 0.5 0.4 8.0 20.0 0.2 0.0 0.7 0.0 0.0 11.1 5.0 18.5 27.5 0.1 19.0 6.5 0.0 11.9 8.0 0.6 0.3 10.075th % 527.2 68.0 11.3 67.5 4.68 4.70 0.54 0.49 0.61 0.52 78.5 153.8 0.6 3.2 0.92 0.01 0.00 20.0 14.4 33.3 68.4 0.19 22.5 22.1 0.05 21.4 26.9 0.75 0.29 11.0

Hilsenhoff Biotic Index (HBI)

95th % 1354.2 74.9 37.9 97.8 4.92 5.32 0.67 0.62 0.70 0.63 421.8 531.1 17.5 68.9 2.07 0.01 1.20 39.6 27.5 50.2 180.5 0.24 24.0 50.9 0.09 79.4 61.0 0.93 0.43 13.9

Relative Chironomidae Abundance

Study site Geology

Relative Chironomidae Abundance (Pp)

RB 3.961 Pmrs 121.0 54.0 1.0 9.3 4.79 4.22 0.50 0.50 0.50 0.7 0.7 0.0 0.56 0.02 0.00 11.9 11.9 5.6 0.08 15.0 10.4 0.02 14.6 2.7 0.43 0.14 9.0

Relative Chironomidae Abundance (Pmrs)

LCN .415 Pp 62.7 32.0 0.0 1.3 4.00 6.64 0.34 0.34 0.38 0.0 0.0 0.0 0.50 0.01 0.00 15.3 15.3 1.0 0.02 6.0 2.3 0.00 1.3 0.0 0.14 0.00 4.0

Relative Diptera Richness

LCM 2.270 Pp 386.0 36.0 0.0 66.3 3.20 6.60 0.20 0.20 0.39 0.0 0.0 0.0 0.57 0.02 0.00 47.7 47.7 16.9 0.17 8.0 12.1 0.00 8.0 0.0 0.14 0.00 6.0

LCMn 2.274 Pp 97.0 27.0 0.0 9.7 2.49 6.16 0.18 0.18 0.37 0.0 0.0 0.0 0.70 0.00 0.00 7.0 7.0 8.0 0.10 7.0 0.7 0.00 3.0 0.0 0.21 0.00 4.1

 Mean Abundance Hydropsyche

 Mean Abundance (Pp) Hydropsyche

LCS .369 Pmrs 144.3 44.0 0.0 14.3 4.52 6.74 0.43 0.43 0.48 0.3 0.3 0.0 0.29 0.03 0.00 25.9 25.9 24.2 0.10 6.0 0.7 0.00 15.3 0.0 0.07 0.00 5.0

LCM .380 Pp 143.0 40.0 0.0 20.7 4.13 6.51 0.20 0.20 0.28 0.0 0.0 0.0 0.55 0.00 0.00 7.0 7.0 3.7 0.14 6.0 0.3 0.00 17.7 0.0 0.07 0.00 5.0

 Mean Abundance (Pmrs) Hydropsyche

LCM .910 Pp 194.0 38.0 0.0 23.3 3.61 6.38 0.23 0.23 0.21 0.0 0.0 0.0 0.88 0.00 0.00 0.3 0.3 1.7 0.12 7.0 2.0 0.00 41.7 0.0 0.21 0.00 4.1

 Mean Abundance Cheumatopsyche

RB .071 Ha 66.3 31.0 0.0 22.0 3.53 3.64 0.30 0.32 0.0 0.0 0.90 0.00 0.00 2.3 3.7 0.33 9.0 0.0 0.00 11.3 0.0 0.29 0.14 5.0

RB 1.474 Pmrs 33.0 26.0 0.0 4.3 4.11 4.01 0.26 0.26 0.38 0.0 0.0 0.7 0.90 0.00 0.00 1.7 1.7 3.5 0.13 9.0 0.3 0.00 2.1 0.7 0.21 0.00 6.0

EPT - Diptera Richness Ratio

Relative Oligochaeta Abundance

Perlidae Mean Abundance

Tanypodinae Mean Abundance

Tanypodinae Mean Abundance (Pp)

Tanypodinae Mean Abundance (Pmrs)

Chironomini Mean Abundance

Relative Ephemeroptera Abundance

EPT Generic Richness

Dicrotendipes, Sum of Mean Abundances of 

Micropsectra, Parachironomus, & Helobdella

Relative Plecoptera Richness

Cheumatopsyche, Sum of Mean Abundances of 

rsus, & Ablabesmyia Cricotopus, Tanyta

Acroneuria & Sum of Mean Abundances of 

Stenonema

Ratio of EP Generic Richness

Ratio of Class A Indicator Taxa

Tricoptera Richness

atl dadeo LDF m tudy ssend cae a l referenc . Regiona 1- EbleaT

e. gn raentileerc p th 95 de 5th andifall outslls ce hted g hli g Hi

E - 3
01 Total Mean Abundance

0

800600400200

1600140012001000

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

01 Total Mean Abundance

0

800600400200

1600140012001000

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

02 Generic Richness

0

8070605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

02 Generic Richness

0

8070605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

03 Plecoptera Mean Abundance

50

40353025201510

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

03 Plecoptera Mean Abundance

50

40353025201510

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

04 Ephemeroptera Mean Abundance

0

80604020

120100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

04 Ephemeroptera Mean Abundance

0

80604020

120100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

05 Shannon-Wiener Generic Diversity 6

543210

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

05 Shannon-Wiener Generic Diversity 6

543210

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

06 Hilsenhoff Biotic Index (HBI)

876543210

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

06 Hilsenhoff Biotic Index (HBI)

876543210

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

E - 4
07 Relative Chironomidae Abundance

0.800.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

07 Relative Chironomidae Abundance

0.800.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

07 Relative Chironomidae Abundance (Pp only) 0.70

0.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

07 Relative Chironomidae Abundance (Pp only) 0.70

0.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

07 Relative Chironomidae Abundance (Pmrs only)

0.800.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

07 Relative Chironomidae Abundance (Pmrs only)

0.800.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

08 Relative Diptera Richness

0.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

08 Relative Diptera Richness

0.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

09 Hydropsyche Mean Abundance

0

50

450400350300250200150100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

09 Hydropsyche Mean Abundance

0

50

450400350300250200150100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

09 Hydropsyche Mean Abundance (Pp only)

0

600500400300200100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

09 Hydropsyche Mean Abundance (Pp only)

0

600500400300200100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

E - 5
09 Hydropsyche Mean Abundance (Pmrs)

50

201510

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

09 Hydropsyche Mean Abundance (Pmrs)

50

201510

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

11 Cheumatopsyche Mean Abundance

0

8070605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

11 Cheumatopsyche Mean Abundance

0

8070605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

12 EPT - Diptera Richness Ratio 2.50

2.001.501.000.500.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

12 EPT - Diptera Richness Ratio 2.50

2.001.501.000.500.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

13 Relative Oligochaeta Abundance 0.04

0.030.030.020.020.010.010.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

13 Relative Oligochaeta Abundance 0.04

0.030.030.020.020.010.010.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

15 Perlidae Mean Abundance 1.40

1.201.000.800.600.400.200.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

15 Perlidae Mean Abundance 1.40

1.201.000.800.600.400.200.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

16 Tanypodinae Mean Abundance 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

16 Tanypodinae Mean Abundance 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

E - 6
16 Tanypodinae Mean Abundance (Pp only) 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

16 Tanypodinae Mean Abundance (Pp only) 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

16 Tanypodinae Mean Abundance (Pmrs only) 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

16 Tanypodinae Mean Abundance (Pmrs only) 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

17 Chironomini Mean Abundance

0

80604020

200180160140120100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

17 Chironomini Mean Abundance

0

80604020

200180160140120100

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

18 Relative Ephemeroptera Abundance 0.35

0.300.250.200.150.100.050.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

18 Relative Ephemeroptera Abundance 0.35

0.300.250.200.150.100.050.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

19 EPT Generic Richness 

50

3025201510

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

19 EPT Generic Richness 

50

3025201510

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

21 Sum of Mean Abundances of Dicrotendipes, 

M icropsectra, Parachironomus, & Helobdella 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

21 Sum of Mean Abundances of Dicrotendipes, 

M icropsectra, Parachironomus, & Helobdella 

0

605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

E - 7
23 Relative Plecoptera Richness 0.10

0.090.080.070.060.050.040.030.020.010.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

23 Relative Plecoptera Richness 0.10

0.090.080.070.060.050.040.030.020.010.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

25 Sum of Mean Abundances Cheumatopsyche, 

Cricotopus, Tanytarsus, & Ablabesmyia

0

908070605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

25 Sum of Mean Abundances Cheumatopsyche, 

Cricotopus, Tanytarsus, & Ablabesmyia

0

908070605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

26 Sum of Mean Abundances of Acroneuria & Stenonema 

0

70605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

26 Sum of Mean Abundances of Acroneuria & Stenonema 

0

70605040302010

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

28 Ratio of EP Generic Richness

1.000.900.800.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

28 Ratio of EP Generic Richness

1.000.900.800.700.600.500.400.300.200.100.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

30 Ratio of Class A Indicator Taxa

0.500.450.400.350.300.250.200.150.100.050.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

30 Ratio of Class A Indicator Taxa

0.500.450.400.350.300.250.200.150.100.050.00

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

Tricoptera Richness 

86420

16141210

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

Tricoptera Richness 

86420

16141210

Reg

Ref

RB

3.961

LCS

.369

LCN

.415

LCM.380

LCM.910

LCMn2.274

LCM

2.270

RB

.071

RB

1.474

E - 8
APPENDIX F 

CAUSAL DESCRIPTIONS, BASIC INTERACTIONS, AND SOURCES 

This appendix characterizes the candidate causes listed for this case study, potential 

interactions among causes, and sources (or anthropogenic activities) from a general perspective. 

The main text of this report discusses specific connections among candidate causes, including 

probable causal interactions occurring at the impaired study sites. This appendix frequently 

refers to the conceptual model figures (CM Figures 1 – 10), which precede the appendices. 

Candidate cause descriptions 

Candidate cause #1 – Increased autochthony (CM Figure 2)

Autochthony, or the production of organic matter within the stream itself, increases when 

conditions are favorable for primary producer growth. If nutrients, light, and other resources 

required by primary producers are abundant and physical conditions such as water velocity favor 

the establishment and accumulation of algae and macrophytes, then plant biomass or production 

is likely to increase (Mosisch et al., 2001; Biggs, 2000). Conditions favoring autochthonous 

production (e.g., riparian devegetation) are often simultaneously associated with reduced 

allochthonous inputs, or inputs of terrestrially-derived organic matter such as leaf litter and wood 

(Gregory et al., 1991). This shift in the dominance of autochthonous versus allochthonous 

organic matter may translate into a change in the basal food resources supporting stream 

communities. 

The abundance of EPT taxa requiring allochthonous coarse particulate organic matter 

(e.g., shredding stoneflies and caddisflies) may decrease if basal food resources are altered as 

described above (Wallace et al., 1997). Some EPT taxa feed on algae and associated fine 

particulate organic matter; therefore, loss of shredding EPT taxa may be offset by increases in 

scraping or filtering EPT taxa (Feminella and Hawkins, 1995). To more fully understand food 

resource effects, taxa should be considered either individually or according to functional feeding 

groups. Non-insect taxa feeding on algae and associated fine particles (e.g., snails) may also 

increase. Abundance of primary producers often increases in response to elevated nutrients. 

Thus, HBI, which was designed to reflect organic pollution, is likely to increase with increases in 

autochthony. Brook trout abundance may decrease due to increased autochthony indirectly 

through decreases in preferred prey. 

Anthropogenic activities contributing to increased autochthony for this case study include 

instream impoundment, lawn care and landscaping, and riparian devegetation. 

F - 1 
Candidate cause #2 – Decreased dissolved oxygen (CM Figure 3)

Four primary pathways most likely contribute to decreased water column and/or 

interstitial dissolved oxygen concentrations in Long Creek: increases in water temperature, 

decreases in water turbulence leading to decreased aeration, changes in the balance between 

primary producer photosynthesis and respiration, and increases in heterotrophic respiration. 

Increases in water temperature result in decreased dissolved oxygen concentrations because the 

solubility of oxygen decreases with increasing water temperature. In addition, organism 

metabolism (and thus oxygen consumption) increases with increasing water temperature (Allan, 

1995). Water turbulence increases aeration, which helps to incorporate atmospheric oxygen into 

the water column. Thus, factors reducing turbulent flow tend to reduce dissolved oxygen; these 

factors may include decreased large woody debris (Mutz, 2000) and decreased water velocity 

(Genkai-Kato et al., 2005). Increases in sediment deposition can cover and clog interstitial 

spaces, reducing the flow of oxygenated water into hyporheic areas (Argent and Flebbe, 1999). 

Increases in plant biomass and/or productivity, brought about by changing abiotic conditions 

(e.g., increased light and nutrients or decreased water velocity), may affect dissolved oxygen 

concentrations positively or negatively. Although stimulation of primary producers may lead to 

increased dissolved oxygen through increased photosynthesis, it also may increase dissolved 

oxygen consumption through increased plant respiration; this is especially true under low light 

conditions (i.e., on cloudy days or at night) when photosynthesis is limited (Allan, 1995). Dead 

plant matter also enters the organic matter pool, leading to increased heterotrophic respiration. 

Reductions in dissolved oxygen concentration can asphyxiate organisms, ultimately 

resulting in decreases in sensitive taxa, such as mayflies (Connolly et al., 2004), stoneflies, and 

salmonids (Barwick et al., 2004), and increases in tolerant non-insect taxa such as oligochaetes 

and pulmonate snails (Peckarsky et al., 1990). 

Anthropogenic activities contributing to decreased dissolved oxygen for this case study 

include channel alteration, instream impoundment, lawn care and landscaping, and riparian 

devegetation. 

Candidate cause #3 – Altered flow regime (CM Figure 4)

For the purposes of this case study, altered flow regime refers to several potential 

hydrologic modifications, including changes in water velocity, decreases in base discharge (or 

baseflow), and increases in storm discharge (or stormflow). Increased and decreased water 

velocity can affect aquatic biota. Increases in stream discharge and water velocity may increase 

shear force within the channel, dislodging biota from the stream bottom. Decreases in water 

velocity may convert lotic environments to more lentic habitats. Decreases in baseflow may 

result in decreased aquatic habitat availability in terms of wetted channel width or depth and 

decreased habitat quality in terms of flow heterogeneity. Baseflow reductions, coupled with 

F - 2 
increased stormflows, result in increased rates and/or magnitudes of flow fluctuations within 

stream channels (i.e., increased flashiness). Peak discharges may be higher, occur more rapidly 

and frequently, and return to base discharge levels more quickly, and base discharge levels may 

be lower than before the flow regime was altered. 

Some EPT taxa prefer running water habitats and are found on substrate surfaces in 

riffles. These epibenthic taxa may be more easily scoured than taxa that can burrow into 

sediments (e.g., oligochaetes), especially on unstable substrates (Holomuzki and Biggs, 2000). 

Conversion of higher water velocity areas into lower flow areas may eliminate lotic habitat. 

Brook trout may be impaired by decreased water velocity, as juvenile and adult salmonids 

require certain velocities for optimal foraging and growth (Baker and Coon, 1997). 

Anthropogenic activities contributing to altered flow regime for this case study include 

channel alteration, impervious surfaces, instream impoundment, riparian devegetation, and 

watershed devegetation. 

Candidate cause #4 – Decreased large woody debris (CM Figure 5)

Large woody debris provides habitat for aquatic insects and fish and creates turbulence 

which allows atmospheric oxygen to diffuse into the water column. Large woody debris 

provides stable substrate for aquatic organisms, which is especially important in low gradient 

systems with relatively unstable bottom sediments (Benke and Wallace, 2003; Smock et al., 

1989; Benke et al., 1984). Large woody debris also can retain macroinvertebrate food resources 

(e.g., leaves). Some EPT taxa, particularly clingers, require stable substrates for attachment 

(Merritt and Cummins, 1996). In sandy-bottomed streams, large woody debris is often the only 

stable substrate available and may be heavily colonized by epibenthic taxa (Benke et al., 1984). 

Benke and Wallace (2003; a synthesis manuscript describing the significance of wood for 

invertebrate communities in streams and rivers) provide diverse examples of macroinvertebrate 

use of large woody debris: some filtering caddisflies create habitat by gouging into woody 

debris; filtering invertebrates may use woody debris for net building; some caddisflies use pieces 

of woody debris to construct their cases; and some invertebrates use wood surfaces to climb out 

of the water as part of the emergence process. Debris dams may provide cover and create deep 

water habitats for fish (Neumann and Wildman, 2002; Flebbe, 1999), and decreases in large 

woody debris have been correlated with reduced trout numbers (Flebbe, 1999). 

Anthropogenic activities contributing to decreased large woody debris for this case study 

include channel alteration and riparian devegetation. 

Candidate cause #5 – Increased sediment (CM Figures 6 & 7)

Increased erosion of sediments from terrestrial environments or from stream channels and 

banks leads to increased input of fine (< 2 mm diameter) sediment particles to stream 

F - 3 
environments. Once in the stream, this sediment can either remain suspended in the water 

column or become deposited on the channel bottom, depending on whether flow conditions are 

sufficient for mobilization. Both suspended and deposited sediment can affect aquatic biota 

through direct and indirect pathways, as documented in numerous reviews (e.g., Wood and 

Armitage, 1997; Waters, 1995). High suspended sediment concentrations may decrease the 

ability of visual feeders, such as brook trout, to detect prey (Sweka and Hartman, 2001a), leading 

to increased foraging energy expenditure (Sweka and Hartman, 2001b). Suspended sediment 

may reduce light penetration, which can negatively impact primary producers; in addition, low 

light levels may stimulate downstream drift of invertebrates (Pearson and Franklin, 1968). As 

sediment is deposited and streambeds become increasingly embedded, interstitial spaces are 

eliminated. This can reduce interstitial flow, thereby creating hypoxic conditions (see dissolved 

oxygen discussion above), and eliminating benthic and hyporheic habitat for aquatic 

invertebrates and embryonic and larval fish. Several studies have shown negative effects of 

sediment on EPT taxa (e.g., McClelland and Brusven, 1980) and brook trout (e.g., Argent and 

Flebbe, 1999; Alexander and Hansen, 1986). In contrast, certain non-insect taxa such as 

oligochaetes are tolerant of sedimentation (Zweig and Rabeni, 2001). Sediment deposition also 

may lead to increased water temperatures as pool habitats fill with sediment and deeper, cooler 

water refuges are eliminated. As fine sediments deposit, bed particle size and stability tend to 

decrease. This reduction can lead to increased dislodgement of biota, especially during storms, 

and this loss of biota may be exacerbated by the loss of interstitial refugia associated with 

increased sedimentation (Borchardt and Statzner, 1990). Shifting substrates and layers of fine 

deposited sediment may also bury organisms. 

Anthropogenic activities contributing to increased sediment for this case study include 

channel alteration, impervious surfaces, instream deposits, instream impoundment, winter road 

sanding, salting, and plowing, riparian devegetation, and watershed devegetation. 

Candidate cause #6 – Increased temperature (CM Figure 8)

Stream water temperatures can increase through three major pathways: increased 

warming of water within the stream channel, decreased input of cold water, and/or increased 

input of warm water. When more light reaches the water surface as a result of riparian 

devegetation, heat energy transfer to the water column increases; decreases in water velocity may 

exacerbate this situation by increasing retention time and thus heat transfer to a given volume of 

water. Slower moving water also may allow increased water loss through evaporation and/or 

evapotranspiration. Decreases in baseflow reduce the volume of water that must be heated to 

raise water temperature, making it easier to warm the system. In addition, baseflow is often 

determined by groundwater inputs; because these inputs tend to be colder than surface waters 

during summer months, reductions in baseflow originating from subsurface water sources may 

F - 4 
translate into warmer summer water temperatures. Finally, increased inputs of heated surface 

runoff (e.g., from impervious surfaces) can raise stream water temperatures (Paul and Meyer, 

2001). 

Increases in stream temperature may lead to thermal stress for biotic assemblages, 

resulting in increases in warm-water tolerant taxa and decreases in taxa preferring colder waters, 

such as stoneflies and brook trout (Lessard and Hayes, 2003). Brook trout may be especially 

susceptible to warmer temperatures, as they prefer water temperatures below 20°C (Picard et al., 

2003; Galli and Dubose, 1990). 

Anthropogenic activities contributing to increased temperature for this case study include 

channel alteration, detention basins, impervious surfaces, instream impoundments, riparian 

devegetation, and watershed devegetation. 

Candidate cause #7 – Increased toxic substances (CM Figure 9)

Several types of toxic substances could cause the biological impairment observed in Long 

Creek, including metals, pesticides, organic contaminants, sodium chloride and/or ammonia. 

Increases in ionic strength may play a role, either directly (e.g., through osmoregulatory effects) 

or through effects on metal toxicity (Bäckström et al., 2004). Toxic inputs to Long Creek may 

be traced back to point and nonpoint sources (e.g., industrial effluent discharges and surface 

runoff from impervious surfaces, respectively). Adverse effects may include long-term chronic 

exposures to baseflow concentrations or more episodic acute exposures to stormflow 

concentrations. Stormflow concentrations may be more difficult to quantify given event 

frequency and variability. This candidate cause is especially complex, as organisms are likely to 

be exposed to multiple toxic substances simultaneously. 

Some EPT taxa are considered relatively intolerant of toxic substances, while some noninsect taxa (e.g., oligochaetes) are relatively pollution-tolerant. For example, Ephemeroptera 

richness has been found to be a sensitive indicator of both elevated metal concentrations and 

elevated conductivity (Yuan and Norton, 2003). 

Anthropogenic activities contributing to increased toxic substances for this case study 

include impervious surfaces, industrial processes, landfill leachate, lawn care and landscaping, 

and winter road sanding, salting, and plowing. 

Basic causal interactions 

Candidate causes do not act independently. Each candidate cause influences, and is 

influenced by, other candidate causes (CM Figure 10). In this section, we examine potential 

linkages among the seven candidate causes described above. 

Increased temperature relates directly to decreased dissolved oxygen concentrations, as 

oxygen solubility decreases at warmer water temperatures while metabolic activity—and thus 

F - 5 
oxygen consumption—increases (Allan, 1995). This increase in metabolic activity can also 

result in greater biological uptake of toxic substances. In addition, warmer temperatures result in 

decreased dissociation of ammonium hydroxide, which is highly toxic to many aquatic 

organisms, especially fish (Wetzel, 2001). A three-way interaction occurs as decreased 

dissolved oxygen levels in warm water change the redox potential of toxic substances, thereby 

influencing the biological availability of toxics such as heavy metals (Dodds, 2002). 

Increased autochthony can be linked to decreases in dissolved oxygen through the 

balance between photosynthesis and respiration in living plant tissue and the oxygen demand 

incurred from microbial respiration of decaying autochthonous plant material. Increased 

autochthony may also be linked to increased sediment and altered flow regimes at localized 

spatial scales; for example, algal mats and macrophytes can affect flow patterns by damping 

water velocities (Green, 2005), which can lead to increased sediment deposition and retention. 

This linkage goes both ways, however, as increased sediment and altered flow regime can 

influence primary producers. Increased sediment may attenuate light levels (thereby decreasing 

photosynthesis) and/or scour algae from stream bottoms. Additionally, increased water 

velocities and/or discharges frequently associated with altered flow regimes can cause increased 

scouring of algal mats. 

Decreases in large woody debris can be linked to altered flow regime, increased 

sediment, increased temperature, decreased dissolved oxygen, and increased autochthony. Large 

woody debris can decrease water velocity in some areas of the channel, resulting in greater flow 

heterogeneity and potentially mitigating negative impacts from peak discharges. Conversely, 

altered flow regime may lead to diminished large woody debris accumulation, as snag habitats 

may be washed out by higher and more frequent storm discharges. Large woody debris 

accumulations often result in the creation of pools within the stream channel. Deep water 

habitats can serve as cool water refuges in summer months, and the loss of such refuges can 

exacerbate the influence of increased water temperatures, especially for coldwater fish species. 

Large woody debris projecting above the stream bed generates turbulence, which can increase 

aeration of the water column and dissolved oxygen concentrations. Increased autochthony may 

be indirectly affected by decreased large woody debris, as retention of allochthonous resources 

tends to decrease in the absence of debris dams. 

Altered flow regime and increased sediment are often coupled, as flow regime may 

determine the extent to which fine sediments are suspended in the water column or deposited on 

the channel bottom. At high flows, more sediments and sediments of larger size are suspended 

and scoured from the stream bed; while at low flows, deposition may increase. Changes in flow 

regime can influence transport of toxic substances to and within the stream channel. For 

example, decreases in baseflow may result in decreased dilution of toxic effluents. Alteration of 

F - 6 
flow regime may result in decreased turbulence, leading to decreased dissolved oxygen 

concentrations. 

Increased sediment may be associated with increased toxic substances and/or increased 

autochthony, as both pollutants and nutrients (especially phosphorus) can adsorb to sediment 

particles (House, 2003; Laws, 1993). Adsorption may limit bioavailability of toxic substances 

and nutrients to water column taxa but may also result in higher exposures for sediment-dwelling 

taxa (Laws, 1993). Decreases in water depth associated with increased sediment deposition may 

result in warmer stream temperatures. Sediment clogging of interstitial spaces may reduce 

interstitial flow and contribute to hypoxic conditions in hyporheic areas (Greig et al., 2005). 

Sources or anthropogenic activities 

Channel alteration

Stream channel geomorphologic changes often occur in conjunction with factors 

affecting stream discharge and sediment supply (e.g., watershed infiltration rates, riparian 

devegetation, and watershed devegetation). Direct alteration of channel configuration can be a 

source of stress to aquatic systems. In this case study, human-induced channel alteration 

primarily takes the form of road culverts, floodplain fill, and stream relocation. Culverts and 

similar instream structures may create unfavorable and/or artificial instream transitions whereby 

piped, often confined, stream sections with low roughness lead to and from less altered sections 

of stream channel. As a result, high velocity flows exiting culverts may scour out pools. A 

culvert may also act as a check dam or grade control structure, creating pond-like conditions 

upstream. Upstream and downstream pond-like conditions may lead to increased water 

temperature. Culverts sized for maximum stormflows physically separate the channel from the 

original local floodplain. Culverts may also act as a physical barrier by way of elevated 

velocities or direct impediment of, for example, migrating fish. Artificial floodplain fill (e.g., 

carting in fill material for urban development on the floodplain) may restrict overbank flows, 

increase channel velocity, increase erosion (especially when inappropriate fill material is used or 

fill material is inadequately compacted), decrease floodplain habitat and wetted stream area, and 

lead to channel incision (i.e., narrowing and deepening of the stream channel). Water velocities 

in narrow, simplified channels may be increased (Sweeney et al., 2004), and high-energy 

stormflow may remain within incised channels, potentially causing increased erosion and 

reduced bank stability (Paul and Meyer, 2001). Large woody debris may also wash out of a 

simplified channel system more quickly. Stream relocation may increase erosion as banks are 

left unprotected and unsupported by vegetation. The physical act of relocating a stream (grading, 

construction, etc.) often increases sediment loading. After a stream is relocated, and often 

confined, the stream may attempt to meander, seeking more stable locations, causing additional 

sediment loading. 

F - 7 
Detention basins

For the purposes of this case study, the term “detention basins” refers to all water 

containment features, natural or engineered, offset from the original stream channel, regardless 

of outflow characteristics (that is, temporary or longer retention times). Detention basins are 

often designed to mitigate the impacts of peak stormflows, thereby altering flow regimes. 

Detention basins with extended retention times (commonly referred to as retention basins) may 

allow the opportunity for water temperatures to rise. Furthermore, basins designed for indefinite 

retention may withhold water from groundwater and subsurface flows, potentially altering 

baseflow dynamics. 

Impervious surfaces

Impervious surfaces (e.g., roads, parking lots, sidewalks, roofs, and compacted soils) 

impact watershed hydrology by altering runoff spatially and temporally (see Center for 

Watershed Protection, 2003 and Paul and Meyer, 2001 for reviews of impervious surface effects 

on aquatic systems). Impervious surfaces prevent precipitation from infiltrating soils, thereby 

increasing storm runoff volume and peak discharge. Impervious surfaces generally have higher 

thermal conductivity than surrounding areas and can elevate the temperature of surface runoff. 

Impervious surface runoff may contain higher concentrations of substances associated with 

vehicle use and related human activities (e.g., metals and polycyclic aromatic hydrocarbons), as 

these chemicals generally accumulate on impervious surfaces. Reduced infiltration resulting 

from increased impervious surface can lead to decreased groundwater recharge and decreased 

stream flow dependent on sub-surface inputs. 

Industrial processes

Waste products from industrial processes may contain a variety of toxic substances 

including heavy metals and organic compounds. Waste material may reach surface water 

through direct discharge or non-point sources, such as impervious surface runoff. 

Instream deposits

Sediment sources within the stream channel comprise potential instream sediment 

deposits. Instream sources can also serve as a source of downstream sediment deposition, often 

in association with impervious surface area and urbanization (Trimble, 1997). 

Instream impoundment

Instream impoundments generally decrease flow velocity, increase water residence time, 

and potentially transform lotic environments into lentic ecosystems. Impoundments may create 

F - 8 
low-lying saturated areas with altered vegetation, thereby decreasing the number of trees and 

associated canopy shade. Impoundment may increase water temperature and evaporation and 

evapotranspiration rates. 

Landfill leachate

Toxic compounds associated with waste deposited in landfills can be mobilized when 

surface or subsurface water percolates through landfill areas. Leachate can enter aquatic systems 

downstream of landfills, leading to contamination and biological impairment (Noaksson et al., 

2003; Dickman and Rygiel, 1998). 

Lawn care and landscaping

This activity refers to the care of golf courses, residential lawns, and similar 

vegetated/manicured areas demanding fertilizers, pesticides, and/or irrigation for continued 

upkeep. Fertilizer may reach streams through surface runoff or subsurface movement, and may 

introduce additional nutrients (e.g., phosphorus and nitrogen) to stream channels (Groffman et 

al., 2004; King et al., 2001; Barth, 1995). Pesticides enter surface water through similar 

pathways (Phillips et al., 2002; Crawford, 2001; Schueler, 1995). Irrigation may impact 

baseflow characteristics by increasing low flows between storms. 

Riparian devegetation

Removal of vegetation such as trees, bushes, and grasses from streamside areas impacts 

riparian ecosystems in several ways. Riparian devegetation reduces canopy cover over the 

stream channel, potentially increasing the amount of light reaching the stream and thus light 

levels and water temperatures (Ebersole et al., 2003; Poole and Berman, 2001). Allochthonous 

organic matter inputs to stream channels decrease (Angradi et al., 2004; Scarsbrook et al., 2001) 

as availability of leaf litter and large woody debris decrease due to removal of streamside 

vegetation. Riparian vegetation and its associated root network protect stream banks from 

collapse and erosion. Stream bank vegetation often absorbs the forces of erosive flows, further 

stabilizing banks. 

Watershed devegetation

Watershed devegetation refers to the removal of trees, bushes, and other plants from 

areas within the watershed not immediately adjacent to the stream channel. Watershed 

vegetation removal may result in several changes that affect aquatic systems. Devegetated soils 

are prone to compaction (see impervious surfaces above), leading to reduced infiltration and 

increased surface runoff during subsequent storms. Reduced vegetation can translate into less 

vegetative uptake of water, further increasing surface and subsurface runoff. Devegetated land 

F - 9 
F - 10 

surfaces absorb more heat, resulting in elevated surface runoff temperatures during storm events 

(Center for Watershed Protection, 2003). 

Winter sanding, salting, and plowing

Winter maintenance activities include sanding, salting, deicing, and snow plowing and 

disposal for areas such as roads, parking lots, and airport runways. Road sanding can result in 

direct inputs of sand into stream systems when applied sand is washed from roads with surface 

runoff. Road salting may similarly lead to direct inputs of sodium and calcium chloride and 

toxic substances associated with deicing chemicals or salt/abrasive mixtures (Anderson et al., 

2000). Snow plowed from impervious areas may include sand, salt, and other potentially toxic 

substances associated with impervious surfaces; subsequent disposal of plowed snow by direct 

dumping into streams or disposal in areas near stream banks may increase the potential for 

surface water contamination. 
APPENDIX G 

MEASURED VARIABLES 

Citation Location Description 

&

Comments

aquatic vegetation

MEDEP, 2002a Table 3.6.3

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

dominant aquatic vegetation estimated visually as a percent of the reach in the vicinity of the site; observations made by MEDEP from 9/22/1999 to 9/26/1999

baseflow discharge

MEDEP, 2002a Figure 3.5.10 LCN .415 RB 3.961 baseflow discharge was measured by MEDEP on 8/19/2000 & 9/18/2000, then divided by watershed area (cfs/ac); surrogate site LCN .585 was used to represent LCN .415

baseflow thalweg velocity

MEDEP, 2002a Table 3.6.1 LCMn 2.274 RB 3.961 thalweg baseflow velocities taken at 2m intervals for 200m stretch of the reach in the vicinity of the site; MEDEP estimated velocity by observing floating organic debris durin

g low flow or baseflow conditions 8/5/1999 - 8/6/1999

canopy shade MEDEP, 2002a Table 3.6.4

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

canopy shade was quantified as an average percent based on three visual estimates of riparian zone condition--taken upstream, downstream, & mid-stream--in the vicinity of biological monitoring rockbag sample locations; observations made by MEDEP from 9/22/1999 to 9/26/1999

chlorophyll 

a MEDEP, 2002a Figure 3.2.1 LCN .415 LCMn 2.274 RB 3.961 chlorophyll 

a measurements taken at surrogate sites LCN .585, LCMn 2.714, & RB 

2.790; these apply to sites LCN .415, LCMn 2.274, & RB 3.961, respectively; surrogate sites represent open-canopy sections of the streams; MEDEP collected data in June & Jul

y, 2000

large woody debris count

MEDEP, 2002a Table 3.6.9

LCM 2.270

LCMn 2.274

RB 3.961

woody debris pieces, categorized as above 5 cm and 10 cm in diameter, were counted for stream sites; surrogate site RB 3.500 was used to represent RB 3.961; MEDEP collected data between 11/19/2002 & 12/6/2002

muck mud MEDEP, 2002a Table 3.6.4

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

muck mud (defined as black, very fine organic, FPOM) was quantified as a percent of the total organic substrate components at the site based on visual estimation; observations made by MEDEP from 9/22/1999 to 9/26/1999

Pfankuch rating MEDEP, 2002a Table 3.7.2

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

surrogate site LCN .404 was used to represent LCN .415; MEDEP collected data between 10/19/2000 & 11/3/2000

percent impervious surface

MEDEP, 2002a Table 3.1.2

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

MEDEP estimated percent impervious surface using USGS topographic maps (circa 1970's & 1980's) and 1995 aerial photographs

Applicable 

Sites

Source Measured 

Variable

G - 1
Citation Location Description & Comments

Rapid Bioassessment Protocol (RBP) scores

MEDEP, 2002a Table 3.6.8

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

RBP scores taken by MEDEP on 10/11/1999 & 10/12/1999; numeric RBP scores converted to qualitative condition scores for use in analyses herein

sediment chemistry, 1993

South Portland Engineering Dept, 1994

Appendix C NA

sediment samples tested for cadmium, copper, lead, nickel, & zinc; samples collected by MEDEP on 10/31/1993; sampled at Long Creek & Red Brook just U/S of Clark's Pond; surrogate site representation not established--i.e., this data was used to generalize differences between the two study watersheds

sediment chemistry, 2003

U.S. EPA, 2004a

laboratory report

LCN .415

LCMn 2.274

RB 3.961

sediment samples tested for antimony, arsenic, barium, beryllium, cadmium, chromium, cobalt, copper, lead, nickel, selenium, silver, thallium, vanadium, & zinc; samples collected by MEDEP 10/10/2003 & analyzed by U.S. EPA 10/24/2003

sediment size MEDEP, 2002a Appendix G LCN .415 LCMn 2.274 RB 3.961 pebble counts conducted by size; surrogate sites LCN .595 & LCM 2.896 were used to represent LCN .415 & LCM 2.270, respectively; MEDEP collected data throughout 2000sediment toxicity, 2003 

US EPA, 2004a toxicity study

LCN .415

LCMn 2.274

RB 3.961

toxicity tests were conducted for stream site sediment samples (see above, U.S. EPA 2004a) on survival & growth of C. tentans (chironomid) & H. azteca (amphipod) 

10/24/2003

stormflow event, 1994

South Portland Engineering Dept, 1994

report text & Appendix F NA

precipitation & stream flow data for storm event on 8/18/1994, for locations on Long Creek & Red Brook just U/S of Clark's Pond; surrogate site representation not established--i.e., this data was used to generalize differences between the two study watersheds

stormflow event, 2001

MEDEP staff, 2005

received as spreadsheet

LCN .415

RB 3.961

storm hydrograph produced by MEDEP for 9/25/2001 event; surrogate site RB 1.694 was used to represent RB 3.961

temperature: weekly minimum, maximum, & mean

MEDEP staff, 2005

received as spreadsheet

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

weekly minimum, maximum, & mean from several weeks in August of 1999; RB 3.961 & LCN .415 include 3 simultaneous weeks of measurements ending 8/7/1999, 8/14/1999, & 8/21/1999; RB 3.961, LCM 2.270, & LCMn 2.274 include 1 week of simultaneous measurements ending 8/21/1999; all measurements made by MEDEP

water chemistry, 1992 (baseflow)

South Portland Engineering Dept, 1994

Appendix A NA

baseflow sampling for lead, copper, & zinc conducted on 10/5/1992; sampled at Long Creek & Red Brook just U/S of Clark's Pond; surrogate site representation not established--i.e., this data was used to generalize differences between the two study watersheds

Measured 

Variable

Source Applicable 

Sites

G - 2
Citation Location Description 

&

Comments

water chemistry, 1994 (stormflow)

South Portland Engineering Dept, 1994

Appendix E NA

stormflow sampling for copper, lead, zinc, & TSS; samples during storm event on 8/18/1994; sampled at Long Creek & Red Brook just U/S of Clark's Pond; surrogate site representation not established--i.e., this data was used to generalize differences between the two study watersheds

water chemistry, 2000 & 2001 (stormflow)

MEDEP, 2002a

Appendix C, Tables 1a - 1c

LCN .415

RB 3.961

stormflow sampling for cadmium, copper, lead, nickel, zinc, total phosphorous, orthophosphorous, total Kjeldahl nitrogen, nitrate (NO2), nitrite (NO3), chloride, & TSS; three samples were taken by MEDEP during each of three storm events (nine total) on 3/28/2000, 10/18/2000, & 9/25/2001; surrogate sites LCN .585 & RB 1.694 used to represent LCN .415 & RB 3.961, respectively

water chemistry, 2000 (baseflow)

MEDEP, 2002a

Appendix C, Tables 2a - 2c

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

baseflow sampling for cadmium, copper, lead, nickel, zinc, total phosphorous, orthophosphorous, total Kjeldahl nitrogen, nitrate (NO2), nitrite (NO3), chloride, & TSS, conducted by MEDEP on three days: 8/6/2000, 8/23/2000, & 9/19/2000; surrogate site LCN .585 was used to represent LCN .415

water chemistry, PAHs, 2000 (stormflow)

U.S. EPA, 2000a

laboratory report

LCN .415

RB 3.961

stormflow sampling for polycyclic aromatic hydrocarbons (PAHs); samples collected by MEDEP 10/23/2003 & analyzed by U.S. EPA 10/28/2003. surrogate sites LCN .585 & RB 1.694 used to represent LCN .415 & RB 3.961, respectively

water chemistry, PAHs, 2001 (stormflow)

U.S. EPA, 2001

laboratory report

LCN .415

RB 3.961

stormflow sampling for polycyclic aromatic hydrocarbons (PAHs); samples collected by MEDEP 9/25/2001 & analyzed by U.S. EPA 10/19/2003. surrogate sites LCN .585 & RB 1.694 used to represent LCN .415 & RB 3.961, respectively

water chemistry, 2003 (low flow)

U.S. EPA, 2004a

laboratory report

LCN .415

LCMn 2.274

RB 3.961

low flow water samples tested for aluminum, antimony, arsenic, barium, beryllium, cadmium, calcium, chromium, cobalt, copper, iron, lead, magnesium, manganese, molybdenum, nickel, selenium, silver, thallium, vanadium, & zinc; samples collected by MEDEP 10/10/2003 & analyzed by U.S. EPA 10/21/2003

water quality, 2000 (baseflow)

MEDEP, 2002a

Appendix C, Tables 3a & 3b

LCN .415

LCM 2.270

LCMn 2.274

RB 3.961

three early morning (5:00am - 7:00am) low flow, single point, water quality samples taken by MEDEP for dissolved oxygen, specific conductivity, & salinity on 6/15/2000, 9/1/2000, & 9/30/2000; measurements taken approximately 10 cm above stream bottom; note that the YSI model 85 field meter used to take measurements calculates salinity secondarily using measured conductivity; surrogate site LCN .585 was used to represent LCN .415

Measured 

Variable

Source Applicable 

Sites

G - 3
H - 1 

APPENDIX H 

SCATTER PLOTS (S-R FROM THE FIELD)

Scatter plots were developed using data presented in the MEDEP (2002a) Long Creek and Red 

Brook final report. The project team developed plots for variables with at least five study sites. 

All water quality and chemistry data represent water column baseflow averages. The following 

table shows the variables plotted and the project team’s interpretation—that is, whether the 

variables appear to correlate with any of three biological endpoints analyzed: EPT richness, 

percent non-insects, and/or HBI. Boxes were placed around scatter plots indicating a potential 

correlation, according to project team interpretation. A table of statistical correlation coefficients 

follows the scatter plot figures. Coefficients supplemented visual interpretation of the actual 

plots, when determining whether to list an endpoint correlation in the table immediately below. 

Scatter plot variable Correlation interpretation

Figure H-1 Total Kjeldahl nitrogen HBI

Figure H-2 Nitrate + nitrite

Figure H-3 Total phosphorus HBI

Figure H-4 Ortho phosphorus HBI

Figure H-5 Aquatic vegetation (including diatoms)

Figure H-6 Aquatic vegetation (macroalgae/phytes only)

Figure H-7 Dissolved oxygen saturation HBI

Figure H-8 Dissolved oxygen concentration HBI

Figure H-9 Large woody debris with diameter ≥ 5 cm EPT richness, HBI (low n)

Figure H-10 Large woody debris with diameter ≥ 10 cm EPT richness, HBI (low n)

Figure H-11 D50 substrate particle size

Figure H-12 Pfankuch bank stability

Figure H-13 Temperature, weekly minimum

Figure H-14 Temperature, weekly maximum HBI

Figure H-15 Temperature, weekly mean

Figure H-16 Canopy shade

Figure H-17 Zinc

Figure H-18 Chloride EPT richness, % non-insects, HBI

Figure H-19 Specific conductivity EPT richness, % non-insects, HBI

Figure H-20 Impervious surface area EPT richness

Figure H-21 RBP epifaunal substrate / available cover

Figure H-22 RBP pool substrate characterization HBI

Figure H-23 RBP pool variability

Figure H-24 RBP sediment deposition

Figure H-25 RBP channel flow status

Figure H-26 RBP channel alteration

Figure H-27 RBP channel sinuosity EPT richness

Figure H-28 RBP bank stability

Figure H-29 RBP bank vegetative protection

Figure H-30 RBP riparian vegetative zone width
A B

C

D

E

F

GH

I

0.20 0.30 0.40 0.50

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

0.20 0.30 0.40 0.50

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

0.20 0.30 0.40 0.50

3.5 4.5 5.5 6.5

HBI

Figure H-1. Total Kjeldahl nitrogen, mg/L

Study Site Key 

A LCS .369 D LCM 2.270 G RB .071 

B LCM .380 E LCMn 2.274 H RB 1.474 

C LCM .910 F LCN .415 I RB 3.961 

A

5

B

DCE

F

GH

I

0.05 0.15 0.25

6 8 10 12 14

EPT RichnessA B

CD

E

F

GH

I

0.05 0.15 0.25

5 10 20 30

% Non-insects

A BD

C

E

F

G

H

I

0.05 0.15 0.25

3.5 4.5 5.5 6.

HBI

Figure H-2. Nitrate + nitrite, mg/L 

H - 2
A B

C

D

E

F

GH

I

0.01 0.02 0.03 0.04

6 8 10 12 14

EPT RichnessA B

C

D

E

F

GH

I

0.01 0.02 0.03 0.04

5 10 20 30

% Non-insects

A B

C

D

E

F

H

G

I

0.01 0.02 0.03 0.04

3.5 4.5 5.5 6.5

HBI

Figure H-3. Total phosphorus, mg/L 

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

D

E

F

G H

I

0.002 0.004 0.006 0.008

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G

I

H

0.002 0.004 0.006 0.008

5 10 20 30

% Non-insects

A B

C

D

E

F

G

I

H

0.002 0.004 0.006 0.008

3.5 4.5 5.5 6.5

HBI

Figure H-4. Ortho phosphorus, mg/L 

H - 3
AB

C

D

E

I

GH

F

20 22 24 26 28 30

6 8 10 12 14

EPT RichnessAB

C

D

E

F

I

GH

20 22 24 26 28 30

5 10 20 30

% Non-insects

AB

C

D

E

F

I

H

G

20 22 24 26 28 30

3.5 4.5 5.5 6.5

HBI

g diatoms) local reach (includin Figure H-5. Aquatic vegetation, % of

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

C

D

I

GH

EA B F

302520151050

14121086 C BD

F

A

I

GHE

shnesci RTPE

302520151050

0 0 3 0 2 15 C

BD AF

E

I

H

G

stecnson-i N%

302520151050

5. 5 6 .55. 5 4 .3

IHB

Figure H-6. Aquatic vegetation, % of ophytes only) gae & macr ch (macroal l realoca

H - 4
A B

C

D

E

F

GH

I

55 60 65 70 75 80 85

6 8 10 12 14

EPT RichnessA

C

B

D

E

F

G H

I

55 60 65 70 75 80 85

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

55 60 65 70 75 80 85

3.5 4.5 5.5 6.5

HBI

Figure H-7. Dissolved oxygen saturation, %

474 

961 

071 RB .

RB 1.

RB 3.

GH

 I

Key 

274 

270 

 e

n 2.

415 

Study Sit

 2.CM

M

N .

C

C

L

L

L

D

 E

F 

369 

380 .

910 .

CS .

CM CM 

LLL

ABC

A B

C

D

E

F

GH

I

6789

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

6789

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

6789

3.5 4.5 5.5 6.5

HBI

n concentration, mg/L Figure H-8. Dissolved oxyge

H - 5
B

C

D

E

I

30 40 50 60 70 80 90

6 8 10 12 14

EPT RichnessB

C

D

E

I

30 40 50 60 70 80 90

5 10 20 30

% Non-insects

B

C

D

E

I

30 40 50 60 70 80 90

3.5 4.5 5.5 6.5

HBI

 5 cm ≥ th diameter oody debris, # of pieces wi Large w Figure H-9.

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

B

C

D

E

I

10 15 20 25 30 35 40

6 8 10 12 14

EPT RichnessB

C

D

E

I

10 15 20 25 30 35 40

5 10 20 30

% Non-insects

B

C

D

E

I

10 15 20 25 30 35 40

3.5 4.5 5.5 6.5

HBI

 10 cm th diameter ≥ i 0. Large woody debris, # of pieces w Figure H-1

H - 6
CE

A BF

H

I

6 8 10 12 14

0.05 0.15 0.25

EPT RichnessA B

C

E

F

H

I 5 10 20 30

0.05 0.15 0.25

% Non-insects

A BC

E

F

H

I

3.5 4.5 5.5 6.5

0.05 0.15 0.25

HBI

, mm trate particle size Figure H-11. D50 subs

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C E

F

G H

I

95 100 105 110

6 8 10 12 14

EPT RichnessA B

C

E

F

G H

I

95 100 105 110

5 10 20 30

% Non-insects

A B

C

E

F

G

H

I

95 100 105 110

3.5 4.5 5.5 6.5

HBI

Figure H-12. Pfankuch bank stability score 

H - 7
A B

C

D

E

F

GH

I

13 14 15 16 17

6 8 10 12 14

EPT RichnessA B

C

D

E

F

GH

I

13 14 15 16 17

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

13 14 15 16 17

3.5 4.5 5.5 6.5

HBI

m, C° eekly minimu 3. Temperature, w Figure H-1

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

AB

C

D

E

F

G H

I

20.5 21.5 22.5 23.5

6 8 10 12 14

EPT RichnessAB

C

D

E

F

G H

I

20.5 21.5 22.5 23.5

5 10 20 30

% Non-insects

AB

C

D

E

F

G

H

I

20.5 21.5 22.5 23.5

3.5 4.5 5.5 6.5

HBI

eekly maximum, C° Figure H-14. Temperature, w

H - 8
AB

C

D

E

F

G H

I

17 18 19 20

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

17 18 19 20

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

17 18 19 20

3.5 4.5 5.5 6.5

HBI

eekly mean, C° Figure H-15. Temperature, w

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

D

E

F

G H

I

80 82 84 86 88 90 92

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

80 82 84 86 88 90 92

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

80 82 84 86 88 90 92

3.5 4.5 5.5 6.5

HBI

over Figure H-16. Canopy shade, % c

H - 9
A

DCB

E

F

G H

I

0.004 0.008 0.012

6 8 10 12 14

EPT RichnessA

CBD

E

F

G H

I

0.004 0.008 0.012

5 10 20 30

% Non-insects

A BD

C

E

F

G

H

I

0.004 0.008 0.012

3.5 4.5 5.5 6.5

HBI

nc, mg/L Figure H-17. Zi

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

D

E

F

GH

I

50 100 150 200

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

50 100 150 200

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

50 100 150 200

3.5 4.5 5.5 6.5

HBI

Figure H-18. Chloride, mg/L 

H - 10
A B

C

D

E

F

GH

I

200 400 600 800 1000

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

200 400 600 800 1000

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

200 400 600 800 1000

3.5 4.5 5.5 6.5

HBI

S/cm Figure H-19. Specific conductivity, μ

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

D

E

F

GH

I

10 20 30 40

6 8 10 12 14

EPT RichnessA B

C

D

E

F

GH

I

10 20 30 40

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

10 20 30 40

3.5 4.5 5.5 6.5

HBI

Figure H-20. Impervious surface area, %

H - 11
A B

C

D

E

F

G H

I

7 8 9 10 12 14

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

7 8 9 10 12 14

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

7 8 9 10 12 14

3.5 4.5 5.5 6.5

HBI

ble cover substrate / availa Figure H-21. RBP epifaunal 

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

AB

C

D

E

F

GH

I

8.0 8.5 9.0 9.5 10.5

6 8 10 12 14

EPT RichnessAB

C

D

E

F

GH

I

8.0 8.5 9.0 9.5 10.5

5 10 20 30

% Non-insects

AB

C

D

E

F

H

G

I

8.0 8.5 9.0 9.5 10.5

3.5 4.5 5.5 6.5

HBI

Figure H-22. RBP pool substrate characterization 

H - 12
A B

C

D

E

F

G H

I

7 8 9 10 11 12 13

6 8 10 12 14

EPT RichnessA

CB

D

E

F

G H

I

7 8 9 10 11 12 13

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

7 8 9 10 11 12 13

3.5 4.5 5.5 6.5

HBI

Figure H-23. RBP pool variability 

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

DE

GH

F

I

8 10 12 14 16 18

6 8 10 12 14

EPT RichnessA B

C

DE

F

GH

I

8 10 12 14 16 18

5 10 20 30

% Non-insects

A B

C

DE

F

H

G

I

8 10 12 14 16 18

3.5 4.5 5.5 6.5

HBI

Figure H-24. RBP sediment deposition 

H - 13
A B

DC E

F

G H

I

16.0 17.0 18.0 19.0

6 8 10 12 14

EPT RichnessA B

CD

E

F

G H

I

16.0 17.0 18.0 19.0

5 10 20 30

% Non-insects

A B DC

E

F

G

H

I

16.0 17.0 18.0 19.0

3.5 4.5 5.5 6.5

HBI

Figure H-25. RBP channel flow Status 

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

DE

F

G H

I

14 15 16 17 18 19 20

6 8 10 12 14

EPT RichnessA B

C

DE

F

G H

I

14 15 16 17 18 19 20

5 10 20 30

% Non-insects

A B

C

DE

F

G

H

I

14 15 16 17 18 19 20

3.5 4.5 5.5 6.5

HBI

Figure H-26. RBP channel alteration 

H - 14
A B

DC E

F

G H

I

8 10 12 14 16

6 8 10 12 14

EPT RichnessA B

CD

E

F

G H

I

8 10 12 14 16

5 10 20 30

% Non-insects

A B D

C

E

F

G

H

I

8 10 12 14 16

3.5 4.5 5.5 6.5

HBI

Figure H-27. RBP channel sinuosity 

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

AB

C

D

E

F

I

GH

56789

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

56789

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

56789

3.5 4.5 5.5 6.5

HBI

Figure H-28. RBP bank stability 

H - 15
A B

C

D

E

F

GH

I

7.0 7.5 8.0 8.5 9.0 9.5

6 8 10 12 14

EPT RichnessA B

C

D

E

F

GH

I

7.0 7.5 8.0 8.5 9.0 9.5

5 10 20 30

% Non-insects

A B

C

D

E

F

H

G

I

7.0 7.5 8.0 8.5 9.0 9.5

3.5 4.5 5.5 6.5

HBI

Figure H-29. RBP bank vegetative protection 

071 RB .G

Key 

270 

 eStudy Sit

 2.CMLD 369 CS .LA

474 

961 

RB 1.

RB 3.

H

 I

274 n 2.

415 

M

N .

C

C

L

L

 E

F 

.380 

.910 

CM CM 

LL

BC

A B

C

D

E

F

G H

I

4 5 6 7 8 9 10

6 8 10 12 14

EPT RichnessA B

C

D

E

F

G H

I

4 5 6 7 8 9 10

5 10 20 30

% Non-insects

A B

C

D

E

F

G

H

I

4 5 6 7 8 9 10

3.5 4.5 5.5 6.5

HBI

dth i Figure H-30. RBP riparian vegetative zone w

H - 16
sion ical correlat atist stlotr pettSca

EPT richness Percent non-insects HBI

Pearson's Spearman's Kendall's Pearson's Spearman's Kendall's Pearson's Spearman's Kendall's

Total Kjeldahl nitrogen -0.637 -0.641 -0.509 0.504 0.367 0.222 0.798 0.650 0.444Nitrate + nitrite -0.011 -0.030 -0.063 0.124 0.017 -0.029 -0.290 -0.253 -0.203Total phosphorus -0.627 -0.640 -0.607 0.668 0.502 0.366 0.669 0.335 0.254Ortho phosphorus -0.451 -0.568 -0.445 0.542 0.502 0.354 0.691 0.570 0.471Aquatic veg. (including diatoms) 0.000 0.000 0.000 0.574 0.639 0.559 0.042 0.091 0.043Aquatic veg. (macroalgae/phytes only) -0.291 -0.220 -0.201 0.457 0.408 0.373 0.504 0.398 0.298Dissolved oxygen saturation 0.671 0.590 0.449 -0.398 -0.183 -0.111 -0.891 -0.617 -0.444Dissolved oxygen concentration 0.646 0.564 0.389 -0.382 -0.200 -0.167 -0.889 -0.650 -0.500LWD with diameter ≥ 5 cm 0.922 0.205 0.105 -0.517 -0.500 -0.400 -0.941 -0.300 -0.200LWD with diameter ≥ 10 cm 0.915 0.205 0.105 -0.434 -0.500 -0.400 -0.947 -0.300 -0.200

D50 substrate particle size -0.343 -0.427 -0.343 0.326 0.408 0.309 0.126 0.259 0.206Pfankuch bank stability -0.275 0.296 0.276 -0.407 -0.548 -0.357 -0.267 -0.548 -0.357Temperature, weekly mean -0.532 -0.316 -0.210 0.563 0.650 0.444 0.384 0.533 0.333Temperature, weekly minimum -0.514 -0.162 -0.150 0.418 0.200 0.222 0.164 0.267 0.222Temperature, weekly maximum -0.622 -0.573 -0.449 0.577 0.483 0.278 0.774 0.700 0.500Canopy shade 0.251 0.325 0.210 -0.570 -0.600 -0.444 -0.565 -0.500 -0.333Zinc -0.317 -0.210 -0.164 0.315 0.026 0.000 0.053 -0.148 -0.122Chloride -0.658 -0.812 -0.688 0.677 0.817 0.611 0.616 0.733 0.500Specific conductivity -0.803 -0.864 -0.748 0.821 0.783 0.556 0.803 0.783 0.556Impervious surface area -0.600 -0.881 -0.748 0.572 0.417 0.278 0.527 0.533 0.389RBP epifaunal substrate/avail. cover 0.391 0.487 0.419 -0.296 -0.077 -0.090 -0.397 -0.504 -0.389RBP pool substrate characterization 0.481 0.702 0.600 -0.386 -0.251 -0.217 -0.746 -0.719 -0.588RBP pool variability 0.348 0.215 0.167 0.045 0.114 0.093 -0.346 -0.332 -0.217RBP sediment deposition 0.444 0.566 0.459 -0.284 -0.380 -0.304 0.006 -0.380 -0.304RBP channel flow status 0.149 0.184 0.144 -0.278 -0.358 -0.300 0.103 -0.055 -0.033RBP channel alteration 0.691 0.424 0.349 0.004 0.196 0.118 -0.513 -0.494 -0.354RBP channel sinuosity 0.653 0.870 0.750 -0.578 -0.407 -0.319 -0.656 -0.627 -0.493RBP bank stability 0.532 0.683 0.525 -0.542 -0.435 -0.304 -0.498 -0.705 -0.548RBP bank vegetative protection 0.339 0.142 0.141 0.310 0.321 0.261 -0.126 -0.330 -0.196RBP riparian vegetative zone width 0.610 0.365 0.250 -0.409 -0.424 -0.261 -0.670 -0.407 -0.319

 than 0.7.s or les greater aluesth v highlighted) wi ed ( been flagg e havCells

H - 17
APPENDIX I 

SPECIES SENSITIVITY DISTRIBUTIONS (S-R from elsewhere) 

Figure I-1. SSD – Baseflow – Invertebrate – Arsenic 

Figure I-2. SSD – Baseflow – Chordate – Arsenic 

Figure I-3. SSD – Stormflow – Invertebrate – Cadmium 

Figure I-4. SSD – Stormflow – Chordate – Cadmium 

Figure I-5. SSD – Baseflow – Invertebrate – Chromium 

Figure I-6. SSD – Baseflow – Chordate – Chromium 

Figure I-7. SSD – Stormflow – Invertebrate – Copper 

Figure I-8. SSD – Stormflow – Chordate – Copper 

Figure I-9. SSD – Baseflow – Invertebrate – Copper 

Figure I-10. SSD – Baseflow – Chordate – Copper 

Figure I-11. SSD – Stormflow – Invertebrate – Nickel 

Figure I-12. SSD – Stormflow – Chordate – Nickel 

Figure I-13. SSD – Baseflow – Invertebrate – Nickel 

Figure I-14. SSD – Baseflow – Chordate – Nickel 

Figure I-15. SSD – Stormflow – Invertebrate – Zinc 

Figure I-16. SSD – Stormflow – Chordate – Zinc 

Figure I-17. SSD – Baseflow – Invertebrate – Zinc 

Figure I-18. SSD – Baseflow – Chordate – Zinc 

Figure notes: CCC - criterion continuous concentration (chronic) 

CMC - criteria maximum concentration (acute) 

 (CCC and CMC source: US EPA, 1986b) 

I - 1
EPT impairment @ LCN .415

EPA CCC

observed concentration @ LCMn 2.274

observed concentration @ LCN .415

EPT impairment @ LCMn 2.274

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendancy

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-1. SSD – Baseflow – Invertebrate – Arsenic EPA CCC observed concentration @ LCMn 2.274 observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-2. SSD – Baseflow – Chordate – Arsenic 

I - 2
EPT impairment @ LCN .415

EPA CMC

observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-3. SSD – Stormflow – Invertebrate – Cadmium EPA CMC observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-4. SSD – Stormflow – Chordate – Cadmium 

I - 3
EPT impairment @ LCMn 2.274 observed concentration @ LCMn 2.274 observed concentration @ LCN .415

EPT impairment @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-5. SSD – Baseflow – Invertebrate – Chromium observed concentration @ LCMn 2.274 observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-6. SSD – Baseflow – Chordate – Chromium 

I - 4
EPT impairment @ LCN .415

EPA CMC

observed concentration @ LCN .415

observed concentration @ RB 3.961

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-7. SSD – Stormflow – Invertebrate – Copper EPA CMC observed concentration @ RB 3.961 observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-8. SSD – Stormflow – Chordate – Copper 

I - 5
EPT impairment @ LCMn 2.274

EPA CCC

observed concentration @ LCMn 2.274

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-9. SSD – Baseflow – Invertebrate – Copper EPA CCC observed concentration @ LCMn 2.274

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-10. SSD – Baseflow – Chordate – Copper 

I - 6
EPT impairment @ LCN .415

EPA CMC

observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-11. SSD – Stormflow – Invertebrate – Nickel EPA CMC observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-12. SSD – Stormflow – Chordate – Nickel

I - 7
EPT impairment @ LCMn 2.274 EPA CCC

observed concentration @ LCMn 2.274

observed concentration @ RB 3.961

observed concentration @ LCN .415

EPT impairment @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-13. SSD – Baseflow – Invertebrate – Nickel EPA CCC observed concentration @ LCMn 2.274 observed concentration @ RB 3.961 observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-14. SSD – Baseflow – Chordate – Nickel

I - 8
EPT impairment @ LCN .415

EPA CMC

observed concentration @ RB 3.961

observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-15. SSD – Stormflow – Invertebrate – Zinc EPA CMC observed concentration @ RB 3.961 observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-16. SSD – Stormflow – Chordate – Zinc

I - 9
EPT impairment @ LCMn 2.274EPA CCC

observed concentration @ LCMn 2.274

observed concentration @ LCN .415

EPT impairment @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-17. SSD – Baseflow – Invertebrate – Zinc EPA CCC observed concentration @ LCMn 2.274 observed concentration @ LCN .415

0

0.2

0.4

0.6

0.8

1

0.0001 0.001 0.01 0.1 1 10 100 1000

Concentration, mg/L

Proportion of Species

SSD LC50 central tendency

SSD LC50 95% upper confidence interval

SSD LC50 95% lower confidence interval

LC50 Observation

Figure I-18. SSD – Baseflow – Chordate – Zinc

I - 10
APPENDIX J 

SPECIFIC CONDUCTIVITY DATA FROM OTHER STATES 

Figure J-1. Florida sensitive taxa at least disturbed sites versus specific conductivity Source: Florida Department of Environmental Protection (2005). 

J - 1
Figure J-2. Kentucky mined site Ephemeroptera (mayfly) abundance versus specific conductivity 

Source: Pond (2004). 

J - 2
REFERENCES 

Alexander, GR; Hansen, EA. (1986) Sand bed load in a brook trout stream. N Am J Fish Manage 6:9-23. 

Allan, JD. (1995) Stream ecology: structure and function of running waters. London, UK: Chapman and Hall 

Publishers. 

Anderson, J; Estabrooks, T; McDonnell, J. (2000) Duluth metropolitan area streams snowmelt runoff study. 

Minnesota Pollution Control Agency. 

Angradi, TR; Schweiger, EW; Bolgrien, DW; et al. (2004) Bank stabilization, riparian land use and the distribution 

of large woody debris in a regulated reach of the upper Missouri River, North Dakota, USA. River Res Appl 

20:829-846. 

Argent, DG; Flebbe, PA. (1999) Fine sediment effects on brook trout eggs in laboratory streams. Fish Res 

39:253-262. 

Baker, EA; Coon, TG. (1997) Development and evaluation of alternative habitat suitability criteria for brook trout. T 

Am Fish Soc 126:65-76. 

Barth, CA. (1995) Nutrient movement from the lawn to the stream? Watershed Protection Techniques 2:239-246. 

Barwick, DH; Foltz, JW; Rankin, DM. (2004) Summer habitat use by rainbow trout and brown trout in Jocassee 

Reservoir. N Am J Fish Manage 24:735-740. 

Bäckström, M; Karlsson, S; Bäckman, L; et al. (2004) Mobilisation of heavy metals by deicing salts in a roadside 

environment. Water Res 38:720-732. 

Beach, D. (2002) Coastal sprawl: the effects of urban design on aquatic ecosystems in the United States. Pew 

Oceans Commission, Arlington, VA. 

Benke, AC; Vanarsdall, TC; Gillespie, DM; et al. (1984) Invertebrate productivity in a sub-tropical blackwater river 

- the importance of habitat and life-history. Ecol Mono 54:25-63. 

Benke, AC; Wallace, JB. (2003) Influence of wood on invertebrate communities in streams and rivers. Am Fish Soc 

Sym 37:149-177. 

Biggs, BJF. (2000) Eutrophication of streams and rivers: dissolved nutrient-chlorophyll relationships for benthic 

algae. J N Am Benthol Soc 19:17-31. 

Borchardt, D; Statzner, B. (1990) Ecological impact of urban stormwater runoff studied in experimental flumes - 

population loss by drift and availability of refugial space. Aquat Sci 52:299-314. 

Boward, DM; Kazyak, PF; Stranko, SA; et al. (1999) From mountains to the sea: the state of Maryland’s freshwater 

streams. Maryland Department of Natural Resources, Monitoring and Nontidal Assessment Division, Annapolis, 

MD; EPA 903-R-99-023. 

British Columbia Ministry of Environment. (1993) Ambient water quality criteria for polycyclic aromatic 

hydrocarbons (PAHs). British Columbia Ministry of Environment. 

Connolly, NM; Crossland, MR; Pearson, RG. (2004) Effect of low dissolved oxygen on survival, emergence, and 

drift of tropical stream macroinvertebrates. J N Am Benthol Soc 23:251-270. 

Crawford, CG. (2001) Factors affecting pesticide occurrence and transport in a large midwestern river basin. J Am 

Water Res Assoc 37:1-15. 

R - 1 
CWP (Center for Watershed Protection). (2003) Impacts of Impervious Cover on Aquatic Systems. CWP, Ellicott 

City, MD. 

Davies, SP; Tsomides, DL. (2002) Methods for biological sampling and analysis of Maine's rivers and streams. 

Maine Department of Environmental Protection, Augusta, ME; DEPLW0387-B2002. 

Davies, SP; Drummond, FA; Courtemanch, DL; et al. Unpublished. Probabilistic models based on expert judgment 

protocols to assess attainment of tiered aquatic life uses in Maine rivers and streams. Maine Department of 

Environmental Protection, Augusta, ME. 

Dickman, M; Rygiel, G. (1998) Municipal landfill impacts on a natural stream located in an urban wetland in 

regional Niagara, Ontario. Canadian Field-Naturalist 112:619-630. 

Dodds, WK. (2002) Freshwater ecology: concepts and environmental applications. San Diego, CA: Academic Press. 

Eaton, JG; Mccormick, JH; Goodno, BE; et al. (1995) A field information-based system for estimating fish 

temperature tolerances. Fisheries 20:10-18. 

Ebersole, JL; Liss, WJ; Frissell, CA. (2003) Cold water patches in warm streams: Physicochemical characteristics 

and the influence of shading. J Am Water Res Assoc 39:355-368. 

Eisler, R. (1987) Polycyclic aromatic hydrocarbon hazards to fish, wildlife, and invertebrates: a synoptic review. 

U.S. Fish and Wildlife Service Biological Report. 

Elvidge, C; Milesi, C; Dietz, J; et al. (2004) U.S. constructed area approaches the size of Ohio. EOS Transactions, 

Am Geophys Union 85:233-240. 

Feminella, JW; Hawkins, CP. (1995) Interactions between stream herbivores and periphyton: a quantitative analysis 

of past experiments. J N Am Benthol Soc 14:465-509. 

Field, JJ. (2005) Fluvial geomorphologic assessment of Long Creek and Red Brook, South Portland, Maine. Field 

Geology Services, Farmington, ME. 

Flebbe, PA. (1999) Trout use of woody debris and habitat in Wine Spring Creek, North Carolina. Forest Ecol 

Manage 114:367-376. 

Florida Department of Environmental Protection. (2005) Statistical analysis of surface water quality specific 

conductance data. 

Galli, J; Dubose, R. (1990) Water temperature and freshwater biota: an overview. Department of Environmental 

Programs, Metropolitan Washington Council of Governments, Washington, DC. 

Genkai-Kato, M; Mitsuhashi, H; Kohmatsu, Y; et al. (2005) A seasonal change in the distribution of a streamdwelling stonefly nymph reflects oxygen supply and water flow. Ecol Res 20:223-226. 

Green, JC. (2005) Velocity and turbulence distribution around lotic macrophytes. Aqua Ecol 39:1-10. 

Gregory, SV; Swanson, FJ; McKee, WA; et al. (1991) An ecosystem perspective of riparian zones. Bioscience 

41:540-551. 

Greig, SM; Sear, DA; Carling, PA. (2005) The impact of fine sediment accumulation on the survival of incubating 

salmon progeny: implications for sediment management. Sci Total Environ 344:241-258. 

Groffman, PM; Law, NL; Belt, KT; et al. (2004) Nitrogen fluxes and retention in urban watershed ecosystems. 

Ecosystems 7:393-403. 

Hill, AB. (1965) The environment and disease: association or causation? Proc R Soc Med 58:295-300. 

R - 2 
Hilsenhoff, WL. (1987) An improved biotic index of organic stream pollution. Great Lakes Entomol 20:31-39. 

Holomuzki, JR; Biggs, BJF. (2000) Taxon-specific responses to high-flow disturbance in streams: implications for 

population persistence. J N Am Benthol Soc 19(4):670–679. 

House, WA. (2003) Geochemical cycling of phosphorus in rivers. Appl Geochem 18:739-748. 

Jaag, O; Ambühl, H. (1964) The effect of the current on the composition of biocoenoses in flowing water streams. 

Adv Water Pollut Res 1:39-49. 

Kaushal, SS; Groffman, PM; Likens, GE. (2005) Increased salinization of fresh water in the northeastern United 

States. Proc Nat Acad Sci US Am 102:13517-13520. 

Kefford, BJ; Papas, PJ; Nugegoda, D. (2003) Relative salinity tolerance of macroinvertebrates from the Barwon 

River, Victoria, Australia. Mar Freshwater Res 54:755-765. 

King, KW; Harmel, RD; Torbert, HA; et al. (2001) Impact of a turfgrass system on nutrient loadings to surface 

water. J Am Water Res Assoc 37:629-640. 

Laws, EA. (1993) Aquatic pollution. New York, NY: John Wiley & Sons, Inc. 

Leopold, LB. (1968) Hydrology for urban land planning - a guidebook on the hydrologic effects of urban land use. 

U.S. Geological Survey, National Center, Reston, VA. 

Lessard, JL; Hayes, DB. (2003) Effects of elevated water temperature on fish and macroinvertebrate communities 

below small dams. River Res Appl 19:721-732. 

Lytle, DA; Poff, NL. (2004) Adaptation of natural flow regimes. Trends Ecol Evol 19(2):94-100. 

MEDEP (Maine Department of Environmental Protection). (2002a) A biological, physical, and chemical assessment 

of two urban streams in southern Maine: Long Creek & Red Brook. Prepared by J.T. Varricchione. Maine 

Department of Environmental Protection, Augusta, ME; DEPLW0572. 

MEDEP (Maine Department of Environmental Protection). (2002b) River and stream biological monitoring 

program: frequently asked questions. Maine Department of Environmental Protection, Augusta, ME; DEPLW0561. 

Maxted, JR. (1996) The use of percent impervious cover to predict the ecological condition of wadeable nontidal 

streams in Delaware. Proceedings from A National Symposium, March 19-21, 1996, The Westin Hotel, Chicago, 

Illinois. 

McClelland, WT; Brusven, MA. (1980) Effects of sedimentation on the behavior and distribution of riffle insects in 

a laboratory stream. Aquat Insect 2:161-169. 

Meidel, S; MEDEP (Maine Department of Environmental Protection). (2005) Urban streams nonpoint source 

assessments in Maine: final report. Prepared by: Partnership for Environmental Technology Education (PETE), 

South Portland, ME and MEDEP, August, ME. DEPLW0699. 

Merritt, RW; Cummins, KW. (1996) An introduction to the aquatic insects of North America. Dubuque, Iowa: 

Kendall/Hunt Publishing Company. 

Millennium Ecosystem Assessment. (2005) Ecosystems and human well-being: Scenarios. In: Carpenter, SR; 

Pingali, PL; Bennett, EM, et al.; eds. Millennium ecosystem assessment, Vol. 2. Washington, DC: Island Press. 

Miltner, RJ; Rankin, ET. (1998) Primary nutrients and the biotic integrity of rivers and streams. Freshwater Biol 

40:145-158. 

R - 3 
Morse, CC. (2001) The response of first and second order streams to urban land-use in Maine, USA. Orono, Maine, 

University of Maine. 

Morse, CC; Huryn, AD; Cronan, C. (2003) Impervious surface area as a predictor of the effects of urbanization on 

stream insect communities in Maine, USA. Environ Monit Assess 89:95-127. 

Mosisch, TD; Bunn, SE; Davies, PM. (2001) The relative importance of shading and nutrients on algal production in 

subtropical streams. Freshwater Biol 46:1269-1278. 

Mount, DR; Gulley, DD; Hocket, JR; et al. (1997) Statistical models to predict the toxicity of major ions to 

Ceriodaphnia dubia, Daphnia magna and Pimephales promelas (fathead minnows). Environ Toxicol Chem 

16:2009-2019. 

Mutz, M. (2000) Influences of woody debris on flow patterns and channel morphology in a low energy, sand-bed 

stream reach. Int Rev Hydrobiol 85:107-121. 

Nebeker, AV. (1972) Effect of low oxygen concentration on survival and emergence of aquatic insects. T Am Fish 

Soc 4:675-679. 

Neumann, RM; Wildman, TL. (2002) Relationships between trout habitat use and woody debris in two southern 

New England streams. Ecol Freshw Fish 11:240-250. 

Newcombe, CP; MacDonald, DD. (1991) Effects of suspended sediments on aquatic ecosystems. N Am J Fish 

Manage 11:72-82. 

NOAA (National Oceanic and Atmospheric Administration). (1998) Population: Distribution, Density and Growth. 

by Thomas J. Culliton. NOAA's State of the Coast Report. Silver Spring, MD: NOAA. 

http://state_of_coast.noaa.gov/bulletins/html/pop_01/pop.html. 

Noaksson, E; Linderoth, M; Bosveld, ATC; et al. (2003) Endocrine disruption in brook trout (Salvelinus fontinalis) 

exposed to leachate from a public refuse dump. Sci Total Environ 305:87-103. 

Nordin, RN. (1985) Water Quality Criteria for Nutrients and Algae (Technical Appendix). British Columbia 

Ministry of the Environment, Victoria, British Columbia. 

Paul, MJ; Meyer, JL. (2001) Streams in the urban landscape. Ann Rev Ecol Syst 32:333-365. 

Pearson, WD; Franklin, DR. (1968) Some factors affecting drift rates of Baetis and Simuliidae in a large river. 

Ecology 49:75-81. 

Peckarsky, BL; Fraissinet, PR; Penton, M.A.; et al. (1990) Freshwater macroinvertebrates of northeastern North 

America. Ithaca, New York: Cornell University Press. 

Phillips, PJ; Eckhardt, DA; Freehafer, DA; et al. (2002) Regional patterns of pesticide concentrations in surface 

waters of New York in 1997. J Am Water Res Assoc 38:731-745. 

Picard, CR; Bozek, MA; Momot, WT. (2003) Effectiveness of using summer thermal indices to classify and protect 

brook trout streams in northern Ontario. N Am J Fish Manage 23:206-215. 

Pond, GJ. (2004) Effects of surface mining and residential land use on headwater stream biotic integrity in the 

eastern Kentucky coalfield region. Kentucky Department for Environmental Protection, Division of Water, 

Frankfurt, KY. 

Poole, GC; Berman, CH. (2001) An ecological perspective on in-stream temperature: Natural heat dynamics and 

mechanisms of human-caused thermal degradation. Environ Manage 27:787-802. 

R - 4 
Posthuma, L; Suter, GW II; Traas, TP. (2002) Species sensitivity distributions in ecotoxicology. Boca Raton, 

Florida: Lewis Publishers. 

Raleigh, RF. (1982) Habitat suitability index models: brook trout. U.S. Department of the Interior, Fish and Wildlife 

Service, Washington, DC; FWS/OBS-82/10.24. 

Roy, AH; Rosemond, AD; Paul, MJ; et al. (2003) Stream macroinvertebrate response to catchment urbanization 

(Georgia, USA). Freshwater Biol 48:329-346. 

Scarsbrook, MR; Quinn, JM; Halliday, J; et al. (2001) Factors controlling litter input dynamics in streams draining 

pasture, pine, and native forest catchments. New Zeal J Mar Fresh 35:751-762. 

Schueler, T. (1995) Urban pesticides: from the lawn to the stream. Watershed Protection Techniques 2:247-253. 

Seeley, RA; Valle, BD. (1983) Clark's Pond Study. South Portland Planning Department, South Portland, Maine. 

Shannon, CE; Weiner, W. (1963) The Mathematical Theory of Communication. University of Illinois Press, Urbana, 

Illinois, USA. 

Smock, LA; Metzler, GM; Gladden, JE. (1989) Role of debris dams in the structure and functioning of low-gradient 

headwater streams. Ecology 70:764-775. 

South Portland Engineering Department. (1994) Clark's Pond stormwater study: a case of wet pond treatment of 

stormwater. South Portland Engineering Department, South Portland, Maine. 

Stickney, RR. (1979) Principles of Warmwater Aquaculture. New York, NY: John Wiley and Sons. 

Sweeney, BW; Bott, TL; Jackson, JK; et al. (2004) Riparian deforestation, stream narrowing, and loss of stream 

ecosystem services. P Natl Acad Sci USA 101:14132-14137. 

Sweka, JA; Hartman, KJ. (2001a) Influence of turbidity on brook trout reactive distance and foraging success. T Am 

Fish Soc 130:138-146. 

Sweka, JA; Hartman, KJ. (2001b) Effects of turbidity on prey consumption and growth in brook trout and 

implications for bioenergetics modeling. Can J Fish Aquat Sci 58:386-393. 

Thompson, WB; Johnston, RA; Tucker, RD. (1997) Portland west quadrangle, Maine (surficial geology map). [97-

51]. Maine Geological Survey. 

Trimble, SW. (1997) Contribution of stream channel erosion to sediment yield from an urbanizing watershed. 

Science 278:1442-1444. 

U.S. EPA (Environmental Protection Agency). (1986a) Ambient water quality criteria for dissolved oxygen 

(freshwater). U.S. EPA Office of Research and Development, Environmental Research Laboratories, Duluth, 

Minnesota & Narragansett, Rhode Island; EPA 440/5-86-003. 

U.S. EPA (Environmental Protection Agency). (1986b) Quality criteria for water (Goldbook). U.S. EPA Office of 

Water, Regulations and Standards, Washington, DC; EPA 440/5-86-001. 

U.S. EPA (Environmental Protection Agency). (2000a) Stressor identification guidance document. U.S. EPA Office 

of Water, Office of Research and Development, Washington, DC; EPA-822-B-00-025. 

U.S. EPA (Environmental Protection Agency). (2000b) Nutrient criteria technical guidance manual: rivers and 

streams. U.S. EPA Office of Water, Office of Science and Technology, Washington, DC; EPA 822-B-00-002. 

U.S. EPA (Environmental Protection Agency). (2000c) Ambient water quality criteria recommendations - 

information supporting the development of state and tribal nutrient criteria: rivers and streams in nutrient ecoregion 

R - 5 
XIV. U.S. EPA Office of Water, Office of Science and Technology, Health and Ecological Criteria Division, 

Washington, DC; EPA 822-B-00-022. 

U.S. EPA (Environmental Protection Agency). (2000d) Polynuclear aromatic hydrocarbons (PAHs) analysis in 

aqueous samples - Casco Bay, ME. U.S. EPA Region 1, Office of Environmental Measurement & Evaluation, 

Lexington, MA; project number: 00100027. 

U.S. EPA (Environmental Protection Agency). (2001) Polynuclear aromatic hydrocarbons (PAHs) - Casco Bay, 

ME. U.S. EPA Office of Environmental Measurement & Evaluation, North Chelmsford, MA; project number: 

01090034. 

U.S. EPA (Environmental Protection Agency). (2004a) Long Creek sediment toxicity study 2003. U.S. EPA Region 

1, Office of Environmental Measurement & Evaluation, Ecosystems Assessment Group - Ecology Monitoring 

Team, Toxicity Testing Laboratory, N. Chelmsford, MA. 

U.S. EPA (Environmental Protection Agency). (2004b) National recommended water quality criteria. U.S. EPA 

Office of Water, Office of Science and Technology, Washington, DC. 

U.S. EPA (Environmental Protection Agency). (2005) Methods/indicators for determining when metals are the 

cause of biological impairments of rivers and streams: species sensitivity distributions and chronic exposureresponse relationships from laboratory data. U.S. EPA Office of Research and Development, National Center for 

Environmental Assessment, Cincinnati, OH; NCEA-C-1494. 

Wallace, JB; Eggert, SL; Meyer, JL; et al. (1997) Multiple trophic levels of a forest stream linked to terrestrial litter 

inputs. Science 277:102-104. 

Walsh, CJ; Roy, AH; Feminalla, JW; et al. (2005a) The urban stream syndrome: current knowledge and the search 

for a cure. J N Am Benthol Soc 24:706-723. 

Walsh, CJ; Fletcher, TD; Ladson, AR. (2005b) Stream restoration in urban catchments through redesigning 

stormwater systems: looking to the catchment to save the stream. J N Am Benthol Soc 24:690-705. 

Wang, LH; Kanehl, P. (2003) Influences of watershed urbanization and instream habitat on macroinvertebrates in 

cold water streams. J Am Water Res Assoc 39:1181-1196. 

Waters, TF. (1995) Sediment in streams: sources, biological effects and control. American Fisheries Society 

Monograph 7. 

Wetzel, RG. (2001) Limnology. San Diego, California: Academic Press. 

Wood, PJ; Armitage, PD. (1997) Biological effects of fine sediment in the lotic environment. Environ Manage 

21:203-217. 

Yuan, LL; Norton, SB. (2003) Comparing responses of macroinvertebrate metrics to increasing stress. J N Am 

Benthol Soc 22:308-322. 

Zweig, LD; Rabeni, CF. (2001) Biomonitoring for deposited sediment using benthic invertebrates: a test on 4 

Missouri streams. J N Am Benthol Soc 20:643-657. 

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