EPA/600/R-06/065F | December 2007 | www.epa.gov/ncea
United States
Environmental Protection
Agency
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, Washington, DC 20460
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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
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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 non-
insect 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.
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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
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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
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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, KB 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
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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 HilsenhoffBiotic 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
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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
vn
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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/).
Vlll
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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
312CancoRoad
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
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CONTRIBUTORS
Susan Cormierl
Jeff Dennis2
Melissa Evers2
Scott Freeman3
Chuck Lane l
Patricia Shaw-Allenl
Leon Tsomides2
WORKGROUP PARTICIPANTS
Jennie Bridge 4
Tom Danielson2
Susan Davies2
Mary-Ellen Dennis 2
Steve Fiske5
Alex Huryn 6
Dave Miller2
PaulMitnik2
U.S. EPA INTERNAL REVIEWERS
Suzanne Marcy l
Glenn W. Suter II1
Paul F. Wagner1
EXTERNAL REVIEWERS
Jerome M. Diamond 7
Alan T. Herlihy8
Stephen J. Klaine9
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
Oregon State University, Corvallis, OR
Clemson University, Clemson, SC
9
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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 urban-
related 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
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strength, various metals, and poly cyclic 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.
Xll
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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.
A
10
20
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 urban-
related 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
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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
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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
Land use
Urban / built up
Forest
Agriculture
Barren
Surface water
Percent of watershed area
Red Brook
19
61
10
8
2
Long Creek
40
26
8
26
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Source: Field (2005).
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.
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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 " [discharges... 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,
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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.
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Table 2. Project site description and classification
Stream
Long
Creek
Red
Brook
Site name3
LCM .380
LCM.910
LCM 2.270C
LCMn 2.274C
LCN.415C
LCS .369
LCD
(at Clark's Pond)
RB .071
RB 1.474
RB 3.961c'd
(reference site)
RBO
(at Clark's Pond)
Watershed size
acres
1,471
1,380
670
427
262
361
2,208
1,787
1,448
508
2,112
km2
6.0
5.6
2.7
1.7
1.1
1.5
8.9
7.2
5.9
2.1
8.5
% Impervious
area
13.5
10.1
7.1
14.3
32.6
47
no data
9.5
7.9
2.1
no data
Maine classification15
designation
C
C
B
B
C
C
no data
C
C
C
no data
attainment
C
C
C
N
N
C
no data
C
I
A
no data
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.
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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 sub-
sections: (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
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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-^im 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-^im 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
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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
RB 3.961
LCN .415
LCM 2.270
LCMn 2.274
EPT
richness
15
6
8
7
Percent
non-insects
7.8
35.6
16.0
1.4
HBI
4.2
6.6
6.6
6.2
Brook
trout
Present
Absent
Absent
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
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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 Stalls, 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 non-
insects (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
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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
Insecta
Insecta
Insecta
Insecta
Megaloptera
Diptera
Diptera
Trichoptera
Diptera
Sialidae
Chironomidae
Chironomidae
Odontoceridae
Chironomidae
Sialis
Tanytarsus
Micropsectra
Psilotreta
Stempellinella
4
6
7
0
5
Pr
C-F,G
C-G
Sc,C-G
C-G
B-Cb-Cg
Cb,Cg
Cb,Sp
Sp
Sp
sub-total
13
12
7
7
7
46
Site LCN .415 (total mean abundance = 62.7) c
Crustacea
Insecta
Gastropoda
Insecta
Insecta
Amphipoda
Diptera
Limnophila
Trichoptera
Trichoptera
Hyalellidae
Chironomidae
Physidae
Phryganeidae
Limnephilidae
Hyalella
Procladius
Physella
Ptilostomis
Limnephilus
8
9
8
5
3
Sh,G
Pr,C-G
Sc
Sh,Pr
Sh,C-G
Sw
Sp
Cg.Gl
Cb
Cb,Sp,Cg
sub-total
20
15
11
7
6
61
Site LCM 2.270 (total mean abundance = 386.0) c
Insecta
Insecta
Insecta
Pelecypoda
Crustacea
Coleoptera
Ephemeroptera
Diptera
Veneroida
Isopoda
Elmidae
Caenidae
Chironomidae
Sphaeriidae
Asellidae
Dubiraphia
Caenis
Clinotanypus
Sphaerium
Caecidotea
6
7
8
2
8
C-G,Sc
C-G,Sc
Pr
C-F
Sh
Cg,Cb
Sp,Cb
B
B
Sp
sub-total
41
16
9
5
4
75
Site LCMn 2.274 (total mean abundance = 97) c
Insecta
Insecta
Insecta
Insecta
Insecta
Coleoptera
Ephemeroptera
Diptera
Diptera
Diptera
Elmidae
Caenidae
Chironomidae
Chironomidae
Chironomidae
Dubiraphia
Caenis
Microtendipes
Procladius
Tanytarsus
6
7
6
9
6
C-G,Sc
C-G,Sc
C-F,G
Pr,C-G
C-F.G
Cg,Cb
Sp,Cb
Cg
Sp
Cb,Cg
sub-total
60
9
8
5
2
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 f of individuals from all three
rockbags divided by three samples.
14
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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 pond-
like 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
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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
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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
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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
U.S. EPA's rules for scoring types of evidence are reviewed at the beginning of each SOE scoring table.
18
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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 stormilows: 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 stormilows: total phosphorous, ortho-phosphorous, total Kjeldahl nitrogen, nitrate, & nitrite
water chemistry, 2000 baseilows: 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
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Table 6. Applicable types of evidence
Type of evidence
Concept
Project applicability
Analyzed for each specific
effect
Types of evidence that use data from the case:
Spatial/temporal co-
occurrence
Temporal sequence
Stressor-response
relationships from the field
Causal pathway
Evidence of exposure or
biological mechanism
Manipulation of exposure
Laboratory tests of site
media
Verified predictions
Symptoms
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.
The cause must precede the biological effect.
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.
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.
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.
Field experiments or management actions that increase or
decrease exposure to a cause must increase or decrease the
biological effect.
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.
Knowledge of a cause's mode of action permits prediction
and subsequent confirmation of previously unobserved
effects.
Biological measurements (often at lower levels of biological
organization than the effect) can be characteristic of one or a
few specific causes.
Site-specific data used
No evidence
Scatter plot analysis
applicable across all study
sites
Site-specific data used
No evidence
No evidence
Site-specific sediment
toxicity sample analysis for
2 of 3 impaired sites: LCN
.415 &LCMn2.274
No evidence
No evidence
No, generalized across all 4
endpoints
NA
Yes, 3 of 4 endpoints: EFT
richness, % non-insects, &
HBI
No, generalized across all 4
endpoints
NA
NA
Yes, 2 of 4 endpoints: EFT
richness & % non-insects
NA
NA
to
o
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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
Stressor-response
relationships from
laboratory studies
Stressor-response
relationships from other
field studies
Stressor-response
relationships from
ecological simulation
models
Analogous stressors
Manipulation of exposure at
other sites
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.
Within the case, the cause must be at levels associated with
related biological effects in laboratory studies.
At the impaired sites, the cause must be at levels sufficient to
cause similar biological effects in other field studies.
Within the case, the cause must be at levels associated with
effects in mathematical models simulating ecological
processes.
Agents similar to the causal agent at the impaired site should
lead to similar effects 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.
Site-specific data compared
to information from
elsewhere; majority of
analysis applicable across
all study sites
Site-specific data compared
to information from
elsewhere
Site-specific data compared
to information from
elsewhere
Ecological simulation
models were not used
No evidence
No evidence
Yes
Yes
Yes
NA
NA
NA
Evaluating multiple lines of evidence:
Consistency of evidence
Explanation of the evidence
Confidence in the argument for or against a candidate cause is
increased when many types of evidence consistently support
or weaken it.
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
Site-specific analysis
Yes
Yes
a Source: U.S. EPA CADDIS Web site (http://www.epa.gov/caddis/).
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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
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Table 7. Spatial/temporal co-occurrence data summary
a,b
Candidate
Cause
Increased
autochthony
Decreased
dissolved
oxygen
Altered flow
regime
Decreased
large woody
debris
Increased
sediment
Variable, units
dominant aquatic vegetation, approximate %
of local reach
chlorophyll a, mg/m2
dissolved oxygen, mg/L
baseflow discharge/watershed area, cfs/ac
storm event peak discharge/watershed area,
cfs/ac
storm event volume/watershed area, ac-ft/ac
storm event duration, hours
storm event time to peak discharge, hours
mean thalweg velocity, m/s
thalweg baseflow velocity measured at 2m
increments along 100m reach in site vicinity
LWD diameter >5cm, f of pieces
LWD diameter >10cm, f of pieces
baseflow TSS, mg/L
stormflow TSS, mg/L
muck-mud, %
RBPC epifaunal substrate, score & category
RBPC pool substrate, score & category
RBPC sediment deposition, score & category
RB 3.961
diatoms
25%
10.4
8.7 [3]
(8.0-9.5)
0.00073 [2]
(0.00071-0.00075)
0.0035
0.0041
25.4
9.4
0.10
highly variable
longitudinal velocity
and velocity normally
above zero
91
39
<10[3]
(<2 - <10)
<10-118[9]
60
13 sub-optimal
10 marginal
18 optimal
LCN .415
diatoms
25%
15.7
6.3 [3]
(5.3-7.8)
0.00055 [2]
(0.00035-0.00076)
0.1338
0.0276
5.5
2.3
no data
no data
<10[3]
(3- <10)
<10-271 [9]
40
13 sub-optimal
10 marginal
1 1 sub-optimal
LCM 2.270
rooted
submergents &
diatoms 25%
no data
5.3 [3]
(4.1-7.4)
no data
37
8
<10[3]
(1-<10)
no data
70
13 sub-optimal
10 marginal
18 optimal
LCMn 2.274
diatoms
20%
17.5
5.5 [3]
(4.4-6.2)
no data
0.03
low longitudinal
velocity variability
and velocity often
equal to zero
43
12
<10[3]
(4- <10)
no data
40
12 sub-optimal
8 marginal
18 optimal
to
OJ
-------
Table 7. Spatial/temporal co-occurrence data summary a b (continued)
Candidate
Cause
Increased
temperature
Variable, units
weekly minimum, °C
weekly maximum, °C
weekly mean, °C
RB 3.961
12. 9 [3]
(11.4-14.0)
21.1 [3]
(20.3-22.1)
16.7 [3]
(16.1-17.4)
LCN .415
16.3 [3]
(15.4-17.3)
22. 7 [3]
(21.6-24.2)
19.2 [3]
(18.6-20.0)
LCM 2.270
17.0
23.3
20.2
LCMn 2.274
13.2
21.8
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)
Ionic
strength
Cadmium
Copper
Lead
Nickel
Zinc
baseflow chloride
baseflow specific conductivity, uS/cm
baseflow
baseflow
baseflow
baseflow
baseflow
29 [3]
(26-30)
129 [3]
(79-155)
<0.0005 [3]
<0.002 [3]
<0.003 [3]
<0.004 [3]
<0.005 [3]
122 [3]
(91-141)
745 [3]
(659-796)
<0.0005 [3]
<0.002 [3]
<0.003 [3]
<0.004 [3]
0.014 [3]
(0.013-0.015)
99 [3]
(83-124)
568 [3]
(491-718)
<0.0005 [3]
<0.002 [3]
<0.003 [3]
<0.004 [3]
<0.005 [3]
66 [3]
(58-73)
459 [3]
(376-510)
<0.0005 [3]
0.0013 [3]
(<0.002-0.002)
< 0.003 [3]
< 0.004 [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
-------
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
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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 aztecd), 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
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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
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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
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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 non-
insects 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 site-
appropriate water hardness (18-60 mg CaC03/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
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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 site-
specific 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, stressor-
response 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
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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 sub-
surface 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 stressor-
response 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
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• 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.
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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.
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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
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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
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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 stressor-
36
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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 stressor-
response 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 stressor-
response 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
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600 -i
500 -
o 400 ~\
c
CO
T3
>i
E^
CO
300 -
200 -
100 -
0 -1
o
o
o
o
o
o
1
1
1
1
1
1
1
1
1
il _
i
^^^^H
1
O
O
0
'^^™ 1
] ^^™
1 1 1 1 1
0-30 30-60 60-100 100-200 >200
Specific Conductivity, uS/cm
Figure 6. Maine stream mayfly abundance versus specific conductivity.
Sample size = 175
Source: Analysis and presentation of data adapted from Davies et al. (unpublished).
38
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Table 8. Unique findings by candidate cause and site
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.
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.
Depositional "muck-mud" is higher at the
impaired site.
Depositional "muck-mud" is lower at the
impaired site.
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).
-------
Table 8. Unique findings by candidate cause and site a (continued)
Candidate
cause
LCN .415
LCM 2.270
LCMn 2.274
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.
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.
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
EFT 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
EFT & 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).
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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
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24%
18%
o
c
(0
•O
C
3
12%
c
(0
O)
6
o>
a>
6%
0%
Salt-tolerant:
A Amphipoda
O Isopoda
Salt-sensitive:
Baetidae
RB 3.961
A
LCN.415A
LCM 2.270
c
5
O
O
A
O
A
O
A
250 500 750
Specific Conductivity, (iS/cm
1000
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 salt-
sensitive, as defined by Kefford et al. (2003).
42
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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
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Table 9. Probable causes of impairment'
Impaired
site
Biological effect
Decreased EPT richness
Increased % non-
insects
Increased HBI
Brook trout absence
LCN
.415
increased ionic strength
altered flow regime
decreased dissolved oxygen
decreased large woody debris
increased ionic strength
altered 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 debris
altered flow regime
increased ionic strength
decreased dissolved oxygen
decreased dissolved oxygen
increased temperature
increased sediment
decreased large woody debris
altered flow regime
LCMn
2.274
decreased dissolved oxygen
increased temperature
increased ionic strength
decreased large woody debris
altered 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.
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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 Ambuhl, 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
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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.
O)
£
= 4
o>
O)
o>
I 2
(A
(A
5 1
Ecdyonurus venosus
0123456
Current velocity (cm/s)
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
andAmbuhl (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
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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.TC, 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
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10
o>
E
0)
o>
>
X
O
•o
I
o
I/)
I/)
G
I
H
F
E
Stu
dy 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
B
A
C
D
20 21 22 23
Temperature, weekly summer maximum °C
24
Figure 9. Dissolved oxygen versus temperature at project site.
12
O
I
O)
c"
0)
X
o
•o
I
o
I/)
I/)
10
ssalinity= 0
salinity =
sa
inity = 35,000 ppm
(~ ocean water)
10
14
18
Temperature, °C
22
26
30
Figure 10. Oxygen solubility versus temperature at various salinities.
Source: adapted from Stickney (1979).
48
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24
o
23
E
E
22
21
20
I
H
G
D
E
C
B
F
A
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 RB3.961
200 400 600 800
Specific Conductivity, u.S/cm
1000
1200
Figure 11. Temperature versus specific conductivity at project site.
10
o>
E
0)
o>
>
X
O
•o
I
o
I/)
I/)
I
G
H
E
D
Study S
ite Key
A LCS 369 D LCM ° 970 G PB 071
B LCM .380 E LCMn 2.274 H RB 1.474
C LCM .910 F LCN .415 I RB 3.961
C
B
F
A
200 400 600 800 1000
Specific Conductivity, u,S/cm
1200
Figure 12. Dissolved oxygen versus specific conductivity at project site.
49
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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
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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
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30
o 20
oT
s>
re
o
(A
10
•LCN .415
contributing watershed area: 260 acres
watershed impervious surface area: 33%
event runoff volume: 7.2 ac-ft
event runoff volume / watershed area: 0.0276 ac-ft/ac
•RB 1.694
contributing watershed area: 1350 acres
watershed impervious surface area: 6%
event runoff volume: 5.5 ac-ft
event runoff volume / watershed area: 0.0041 ac-ft/ac
0
0
10
25
15 20
Time, hr
Figure 13. Storm hydrographs on Long Creek and Red Brook, September 25, 2001.
30
35
40
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0.80
& 0.60 H
o
^ 0.40 H
0.20 -
0.00
LCM .603
gradient = 0.0012
LCM .910
gradient = no data
LCM 1.653
gradient = 0.0002
JfV
0.60 -
0.40 -
0.20 -
LCMn2.274
gradient = 0.0017
-AJL-JL-
AL
LCM 3.098
gradient = no data
RB .071
gradient = no data
0.80
f 0.60 -I
_o
, 0.40 -
0.20 -
0.00
RB 1.434
gradient = 0.0015
20
40 60
Distance, m
80 100 0
RB 2.119
gradient = 0.0012
20
40 60
Distance, m
80
100 0
RB 3.961
gradient = 0.0019
20
40 60
Distance, m
80
100
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).
-------
1200
1000
- 800
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600
400
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D LCI\
3 E LCI\
) F LCI\
G RB .071
H RB 1.474
I RB 3.961
0 10 20 30 40 50
Impervious Area, % of contributing watershed
Figure 15. Specific conductivity versus impervious area at project site.
1200
o
1
1000
600
o
O
£ 400
o
0)
Q.
200
I
E
G
H
F
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i
A LCS .369
B LCM .380
C LCM .910
A
Study Si
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E LCM
F LCN
eKey
2.270 G RB.071
n 2.274 H RB 1.474
.415 I RB3.961
50 100 150
Chloride, mg/L
200
250
Figure 16. Specific conductivity versus chloride at project site.
54
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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 urban-
related 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, stressor-
response relationships based on data from elsewhere, regional reference criteria, and/or
literature and information about candidate causes
55
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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 best-
case scenarios of brook trout habitat are for the case study region, taking into consideration
56
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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.
o
o
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24
23
22
= 21
us
I
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20
(
D
H
G
1
;
B
E
F
A
^^^^^^
I Study Site Key
1 A LCS .369 D LCM 2.270 G RB .071
| B LCM .380 E LCMn 2.274 H RB 1.474
I C LCM .910 F LCN.415 I RB 3.961
0 10 20 30 40 50
Impervious Area, % of contributing watershed
Figure 17. Temperature versus impervious area at project site.
57
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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 non-
insects 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
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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
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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
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Sources
Candidate
causes
ReSPOnSeS
sanding, salting
plowing
ing N
1
4
altered flow regime
\ toxic substances
J, dissolved oxygen
J, large woody debris
EPT = Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 1. Case study conceptual model elements.
-------
to
/ instream N / lawn care &N / riparian N
(impoundment 1 1 landscaping 1 1 devegetation 1
1 1 '
I water velocity f nutrients f light
1 1 1
i
f
1 j_ |eaf |jtter ^ ' | large woody debris !
f 1° producers
(algae and macrophytes)
v v
t autochthonous J, allochthonous T
food resources food resources
, ,
KEY ^
f X ' ^
f source ] additional step in
\_S causal pathway ^ X^EPT taxa\
proximate f I — ( t non-insect taxa J
stressor Qresponse^) | \^ f HBI score _/
I ^^^.^^^^ ^r^tlf^^
i , •*•
j rnnnRrtRrl . ....
• conceptual ! .S* ^v
! model ! f i brook trout J
1 — ' EPT - Ephemeroptera (
(stoneflies), and
HBI = Hilsenhoff Biotic
mayflies), Plecoptera
Trichoptera (caddisflies)
Index
CM Figure 2. Increased autochthony conceptual model.
-------
f instream \
[impoundment I
instream N f channel
impoundmentl I alteration
t temperature ]
KEY
additional step in
causa, pathway
lawn care &
landscaping
i r
1 ° producers
(algae and macrophyties
I photosynthesis/
respiration ratio
J, dissolved oxygen
(water column and/or interstitial)
proximate
stressor
• conceptual !
model i
C I brook trout j
EPT = Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 3. Decreased dissolved oxygen conceptual model.
-------
f riparian N
1 devegetation 1 .
\ / / r\\t
4 kj^
1 I large woody debris !
i '
1 J
f watershed N f impervious N
1 devegetation 1 1 surfaces 1
nnp| ^ 1 1 ( instrpam ^
^ I
t surface runoff .1.
1 ^ ^
1 | water velocity
J grni mdwarpr 1
t water velocity < | storm discharge recharge
>
I ^
,. , t evaporation and/or
1 ha^p rii^rharqp J r
t rate and/or >r
flow fluctuations j. btic habitat
f ^p ^^ ^^
t dislodgement j, water depth J, wetted channel
KEY
©additional step in
causal pathway
proximate s^1 "*x*
stressor f response J
i i i
1
*
XjEPT taxa\
i ( t non-insect taxa J
connected ! V V \^ T HBI score ^/
conceplual | ^*~~~ "— --x^ ^ — — ^^"^
llludel ! ^l brook trout ^
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 4. Altered flow regime conceptual model.
-------
KEY
additional step in
causal pathway
j connected
• conceptual !
model i
riparian
devegetation
I
X '
f channel
I alteration
! \ large woody debris \
I
wood substrate
I
C J, brook trout ^
EPT = Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 5. Decreased large woody debris conceptual model.
-------
X
/ watershed N
I devegetation I
('sanding, saltingN
f instream N
(impoundment I
f
ri- '
•y
J
I wa
I EPT taxa
f non-insect taxa
t HBI score
KEY
f source J
proximate
stressor
additional step in
causal pathway
f response j
j connected !
• conceptual !
model J
EPT = Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 6. Increased sediment, first half of conceptual model.
-------
EPT = Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 7. Increased sediment, second half of conceptual model.
-------
f detention^ p instream N ( impervious
1 basins 1 1 impoundment 1 /"
< -hinrH \\ / \ / f npa
^1 surfaces
\
X watershed N
Jevegetation 1
ilt-nti-n J ' ' l^devegetatiory ,
\ / 1
>r >r >K
1 water velocity f surface area
, - -
4, I \
( 1 \
\ evaporation and/or x
evapotranspiration
I J >lr >
f retention time
4r
I groundwater
recharge
V J
+ 1
f heated
surface runoff
>. J
1
^S V
^ r \ base discharc
1
— > -^
t l water depth
i
4?
1 terr
IfFY
iperature
©additional step in
causal pathway
proximate **•" ^v
stressor Q^response^
j connected . X 4*
i model 1 (i brook trout
xJL ^-
>lr
^^T ^^
f | non-insect taxa j
^v t HBI score J
c/^ / - cpnemc
Csfone/fr
HB/ =Hilsenh
je
iroptera (mayflies), Plecoptera
es), and Trichoptera (caddisflies)
off Biotic Index
CM Figure 8. Increased temperature conceptual model.
-------
S impervious N
I surfaces I
lawn care &
landscaping
industrial processes
('sanding, saltingN
I & plowing I
[ landfill leachate 1
f surface run-off
(airports)
>
f
f surface run-off
(roads, lots, stations)
1
KEY
additional step in
causal pathway
proximate
stressor
j connected .
• conceptual j
! model i
> f ^
( I brook trout ^
EPT = Ephemeroptera (mayflies), Plecoptera
(stoneflies), and Trichoptera (caddisflies)
HBI = Hilsenhoff Biotic Index
CM Figure 9. Increased toxic substances conceptual model.
-------
sediment
altered flow regime
large woody debris
temperature
dissolved oxygen
autochthony
toxic substances
CM Figure 10. Potential relationships among individual conceptual models.
-------
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
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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
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SOE Table 1. Spatial / temporal co-occurrence at LCN .415
Strength of evidence (SOE) scoring system for spatial / temporal co-occurrence
0 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 occur
NE No evidence.
Candidate Cause
Increased
autochthony
Decreased
dissolved
oxvaen
Altered flow
regime
Decreased
large woody
debris
Variable,
units
dominant aquatic
vegetation, estimated
% of local reach
chlorophyll a, mg/m2
dissolved oxygen, mg/L
baseflow discharge /
watershed area, cfs/ac
storm event peak
discharge / watershed
area, cfs/ac
storm event volume /
watershed area, ac-
ft/ac
storm event duration,
hours
storm event time to
peak discharge, hours
no
RB 3.961
diatoms
25%
10.4
8.7 [3]
(8.0 - 9.5)
0.00073 [2]
(0.00071 -
0.00075)
0.0035
0.0041
25.4
9.4
LWD data at
LCN .415
diatoms
25%
15.7
6.3 [3]
(5.3 - 7.8)
0.00055 [2]
(0.00035 -
0.00076)
0.1338
0.0276
5.5
2.3
impaired site
SOE
Difference score Comments
The higher chlorophyll a measurement at
0 LCN .415 was not considered strong
enouqh to merit a positive score, qiven the
51 % similarity in dominant aquatic vegetation.
-28% +
-25%
The baseflow data suggest that less
3716% groundwater recharge may be occurring at
the impaired site, although this is based on
+ 2 samples only. The 4 storm flow variables
578% indicate that the impaired site responds to
storm runoff with flashier discharge than the
0/ reference site (also see Figure 1 3).
-76%
NE
-------
Variable,
Candidate Cause units
Increased
sediment
Increased
temperature
baseflow TSS, mg/L
storm flow TSS, mg/L
muck-mud, %
RBP epifaunal
substrate, score &
category
RBP pool substrate,
score & category
RBP sediment
deposition, score &
category
weekly minimum, °C
weekly maximum, °C
weekly mean, °C
Increased toxic substances
Water column sampling (units in ppm or
Ionic strength
Cadmium
baseflow chloride
storm flow chloride
low flow calcium
low flow magnesium
baseflow specific
conductivity, uS/cm
baseflow
low flow
storm flow
RB 3.961
< 10 [3]
(< 2- < 10)
< 10- 118 [9]
60
13 sub-optimal
10 marginal
18 optimal
12. 9 [3]
(11.4-14.0)
21.1 [3]
(20.3-22.1)
16.7 [3]
(16.1 -17.4)
LCN .415
< 10 [3]
(3- < 10)
< 10-271 [9]
40
13 sub-optimal
10 marginal
1 1 sub-optimal
16. 3 [3]
(15.4- 17.3)
22.7 [3]
(21.6- 24.2)
19. 2 [3]
(18.6- 20.0)
mg/L, except specific conductivity
29 [3]
(26 - 30)
1 7 - 57 [9]
6.8
2.2
1 29 [3]
(79-155)
< 0.0005 [3]
< 0.0002
< 0.0005 [9]
122 [3]
(91 -141)
15 -296 [9]
67
17
745 [3]
(659 - 796)
< 0.0005 [3]
< 0.0002
< 0.0005 -
0.0007 [9]
Difference
= 0
130%
-33%
0
0
LCN .415
worse than
RB 3.961
27%
7%
15%
uS/cm):
324%
419%
885%
673%
476%
ND
ND
>0
SOE
score Comments
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.
+
+
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.
-------
Candidate Cause
Copper
Lead
Nickel
Zinc
Variable,
units
baseflow
low flow
storm flow
baseflow
low flow
storm flow
baseflow
low flow
storm flow
baseflow
low flow
storm flow
RB 3.961
< 0.002 [3]
LCN .415
< 0.002 [3]
contaminated sample
< 0.002 - 0.003
[9]
< 0.003 [3]
< 0.0002
< 0.003 - 0.004
[9]
< 0.004 [3]
0.00045
< 0.004 [9]
< 0.005 [3]
< 0.005
0.008 - 0.024 [9]
0.002 -0.01 8 [9]
< 0.003 [3]
< 0.0002
0.003 - 0.031 [9]
< 0.004 [3]
0.0032
< 0.004 -0.01 3
[9]
0.014 [3]
(0.013-0.015)
0.0064
0.043 -0.1 4 [9]
SOE
Difference score Comments
ND
NA
500%
ND
ND
675%
ND
611%
>0
>0
>0
483%
Aluminum
Antimony
Arsenic
Barium
Beryllium
Chromium
Cobalt
Iron
Manganese
Molybdenum
Selenium
Silver
Thallium
Vanadium
low flow
0.045
< 0.0005
< 0.0005
0.0054
< 0.0002
< 0.0005
0.00085
0.091
0.025
< 0.0005
< 0.001
< 0.0002
< 0.0005
0.0003
0.006
< 0.0005
0.00098
0.021
< 0.0002
0.0032
0.0029
0.14
0.37
0.00092
< 0.001
< 0.0002
< 0.0005
0.00082
-87%
ND
>0
289%
ND
>0
241%
54%
1380%
>0
ND
ND
ND
1 73%
_ _ _
0
+
+
0
+
+
+
+
+
0
0
0
+
-------
Candidate Cause
Variable,
units
RB 3.961
LCN .415
Difference
SOE
score
Comments
Polycyclic aromatic hydrocarbons (PAHs) water column sampling (ppm or mg/L):
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)
anthracene
Benzo(a) pyrene
Benzo(b)
fluoranthene
Benzo(ghi)
perylene
Benzo(k)
fluoranthene
Chrysene
Dibenzo(a.h)
anthracene
Fluoranthene
Fluorene
Indeno (1,2,3-cd)
pyrene
Naphthalene
Phenanthrene
Pyrene
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)
0.0001 &
< 0.0001
< 0.00005 &
< 0.0001
0.0002 &
< 0.0001
0.0001 &
0.00033
0.0001 &
0.00048
0.0002 &
0.00111
0.0001 & 0.0005
< 0.00005 &
0.00029
0.0002 & 0.0008
< 0.00005 &
0.00011 (note
that RL = 0.0002)
0.0005 & 0.001 6
0.0001 &
< 0.0001
0.0001 &
0.00056
0.0001 &
< 0.0001
0.00025 &
0.00067
0.0003 &
0.00115
>0&ND +
ND&ND 0
>0&ND +
> & >0 +
>0& >0 +
>0& >0 +
>0& >0 +
ND&>0 +
>0& >0 +
ND&ND 0
>0& >0 +
>0&ND +
>0& >0 +
>0&ND +
>0& >0 +
>0& >0 +
-------
Candidate Cause
Variable,
units
RB 3.961
LCN .415
SOE
Difference score
Comments
Sediment sampling (mg/kg):
Antimony
Arsenic
Barium
Beryllium
Cadmium
Chromium
Cobalt
Copper
Lead
Nickel
Selenium
Silver
Thallium
Vanadium
Zinc
one sediment sample
taken on 10/1 0/2003
< 10
< 20
43
< 1.0
< 3.0
6.3
5.5
3.2
14
< 6.0
< 10
< 3.0
< 20
9.2
32
< 10
< 20
41
< 1.0
< 3.0
18
8.2
6.3
13
10
< 10
<3.0
< 20
24
54
ND
ND
-5%
ND
ND
186%
49%
97%
-7%
>0
ND
ND
ND
161%
69%
0
0
0
0
+
+
+
+
0
0
0
+
+
Toxicity tests were conducted using these
sediment samples; for results and related
information, seethe Stressor- Response
analysis.
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 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
-------
SOE Table 2. Spatial / temporal co-occurrence at LCM 2.270
Strength of evidence (SOE) scoring system for spatial / temporal co-occurrence
0 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 occur
NE No evidence.
Candidate Cause
Increased
autochthony
Decreased
dissolved
oxvaen
Altered flow
regime
Decreased
large woody
debris
Increased
sediment
Variable,
units
dominant aquatic
vegetation, % of local
reach
baseflow, mg/L
no appropriate data
LWD diameter > 5cm,
# of pieces
LWD diameter > 10cm,
# of pieces
baseflow TSS, mg/L
muck-mud, %
RBP epifaunal
substrate, score, and
category
RBP pool substrate,
score and category
RBP sediment
deposition, score, and
category
RB 3.961
diatoms
25%
8.7 [3]
(8.0 - 9.5)
LCM 2.270
rooted
submergents
and diatoms
25%
5.3 [3]
(4.1 - 7.4)
Difference
0
-39%
to represent flow conditions at the impaired site
(e.g., velocity or discharge)
91
39
< 10 [3]
(<2- < 10)
60
13 sub-optimal
10 marginal
18 optimal
37
8
< 10 [3]
(1 - < 10)
70
13 sub-optimal
10 marginal
18 optimal
-59%
-79%
= 0
17%
0
0
0
SOE
score Comments
The minor reported difference in dominant
0 aquatic vegetation was not clear enough to
change the score from zero.
+
NE
+
The small difference in muck mud be\.M\ie>
the two sites does not provide enough
evidence over the other variables, which
0 are essentially equal at both sites;
therefore, this was scored zero. Note tha
some TSS data did not meet MEDEP
quality standards.
en
t
-------
Variable,
Candidate Cause units
Increa-ed weekly minimum< °c
. . weekly maximum, °C
weekly mean, C
RB 3.961
13.1
20.3
16.6
LCM 2.270
17.0
23.3
20.2
SOE
Difference score
29%
1 5% +
22%
Comments
Increased toxic substances
Water column sampling (units in ppm or mg/L, except specific conductivity uS/cm):
Ionic Strength
Cadmium
Copper
Lead
Nickel
Zinc
baseflow chloride
baseflow specific
conductivity, uS/cm
baseflow
baseflow
baseflow
baseflow
baseflow
29 [3]
(26 - 30)
1 29 [3]
(79-155)
< 0.0005 [3]
< 0.002 [3]
< 0.003 [3]
< 0.004 [3]
< 0.005 [3]
99 [3]
(83-124)
568 [3]
(491 -718)
< 0.0005 [3]
< 0.002 [3]
< 0.003 [3]
< 0.004 [3]
< 0.005 [3]
241%
340%
ND
ND
ND
ND
ND
+
0
0
0
0
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].
(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 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
-------
SOE Table 3. Spatial / temporal co-occurrence at LCMn 2.274
oo
o
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 occur
0 It is uncertain whether the candidate cause and the effect co-occur
NE No evidence.
Candidate Cause
Increased
autochthony
Decreased
dissolved
oxygen
Altered flow
regime
Decreased
large woody
debris
Variable,
units
dominant aquatic
vegetation, % of local
reach
chlorophyll a, mg/m2
baseflow, mg/L
mean thalweg velocity,
m/s
baseflow velocity
measured at 2m
increments along 100m
reach in site vicinity
LWD diameter > 5cm,
# of pieces
LWD diameter > 10cm,
# of pieces
RB 3.961
diatoms
25%
10.4
8.7 [3]
(8.0 - 9.5)
0.10
highly variable
longitudinal
channel velocity
and normally
above zero
91
39
LCMn 2.274
diatoms
20%
17.5
5.5 [3]
(4.4-6.2)
0.03
low longitudinal
velocity
variability and
often equal to
zero
43
12
Difference
-20%
68%
-37%
-73%
qualitative
support of
cause
-53%
-69%
SOE
score Comments
The higher diatom observation at the
reference site counteracts the higher
chlorophyll a measurement at the impaired
site; uncertainty yielded a score of zero.
Dissolved oxygen data were collected
approximately 10cm above the stream
+ bottom; therefore, these values may be
more applicable to fish habitat than benthic
invertebrate habitat.
Flow regime differences between the two
sites cannot be characterized by mean
+ velocity alone. Flow heterogeneity adds
support for a positive score (also see Figure
14).
+
-------
Variable,
Candidate Cause units
Increased
sediment
Increased
temperature
baseflow TSS, mg/L
muck mud, %
RBP epifaunal
substrate, score, and
category
RBP pool substrate,
score and category
RBP sediment
deposition, score, and
category
weekly minimum, °C
weekly maximum, °C
weekly mean, °C
Increased toxic substances
Water column sampling (units in ppm or
Ionic Strength
Cadmium
Copper
baseflow chloride
low flow calcium
low flow magnesium
baseflow specific
conductivity, uS/cm
baseflow
low flow
baseflow
low flow
RB 3.961
< 10 [3]
(< 2- < 10)
60
LCMn 2.274
< 10 [3]
(4- < 10)
40
1 3 sub-optimal 1 2 sub-optimal
10 marginal
18 optimal
13.1
20.3
16.6
8 marginal
18 optimal
13.2
21.8
16.5
mg/L, except specific conductivity
29 [3]
(26 - 30)
6.8
2.2
1 29 [3]
(79-155)
< 0.0005 [3]
< 0.0002
< 0.002 [3]
contaminated
66 [3]
(58 - 73)
31.5
11
459 [3]
(376-510)
< 0.0005 [3]
< 0.0002
0.001 3 [3]
0.002 - 0.002)
sample
Difference
= 0
-33%
0
0
0
0%
8%
0%
uS/cm):
1 28%
363%
400%
256%
ND
ND
ND
NA
SOE
score Comments
The difference in muck mud between the
two sites does not provide enough evidence
over the other variables, which are
0 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.
+
0
0
-------
Candidate Cause
Lead
Nickel
Zinc
Variable,
units
baseflow
low flow
baseflow
low flow
baseflow
low flow
RB 3.961
< 0.003 [3]
< 0.0002
< 0.004 [3]
0.00045
< 0.005
< 0.005
LCMn 2.274
< 0.003 [3]
< 0.0002
< 0.004 [3]
0.0019
0.0042 [3]
(< 0.005 - 0.005)
< 0.005
Difference
ND
ND
ND
322%
ND
ND
SOE
score Comments
0
+
0
Aluminum
Antimony
Arsenic
Barium
Beryllium
Chromium
Cobalt
Iron
Manganese
Molybdenum
Selenium
Silver
Thallium
Vanadium
low flow
0.045
< 0.0005
< 0.0005
0.0054
< 0.0002
< 0.0005
0.00085
0.091
0.025
< 0.0005
< 0.001
< 0.0002
< 0.0005
0.0003
0.019
< 0.0005
0.00235
0.011
< 0.0002
0.00205
0.000555
0.22
0.092
0.000385
< 0.001
< 0.0002
< 0.0005
0.000695
-58%
ND
>0
104%
ND
>0
-35%
142%
268%
ND
ND
ND
ND
132%
_ _ _
0
+
+
0
+
—
+
+
0
0
0
0
+
oo
to
-------
Candidate Cause
Variable,
units
RB 3.961
LCMn 2.274 Difference
SOE
score
Comments
Sediment sampling (mg/kg):
Antimony
Arsenic
Barium
Beryllium
Cadmium
Chromium
Cobalt
Copper
Lead
Nickel
Selenium
Silver
Thallium
Vanadium
Zinc
one sediment sample
taken on 10/1 0/2003
< 10
< 20
43
< 1.0
< 3.0
6.3
5.5
3.2
14
< 6.0
< 10
< 3.0
< 20
9.2
32
< 10
< 20
38
< 1.0
<3.0
16.5
6.95
6.25
7.5
10.5
< 10
<3.0
< 20
20
58.5
ND
ND
-1 2%
ND
ND
162%
26%
95%
-46%
>0
ND
ND
ND
1 1 7%
83%
0
0
0
0
+
+
+
+
0
0
0
+
+
Toxicity tests were conducted using these
sediment samples; for results and related
information, seethe Stressor- Response
analysis.
oo
OJ
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 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
-------
SOE Table 4. Stressor-response relationships from the field
Strength of evidence (SOE) scoring system for stressor-response relationship in 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.
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.
NE no evidence.
SOE score
Reasoning and Comments
Endpoint Score
Increased autochthony
Scatter plots for nutrients and aquatic vegetation were used to determine stressor-
response 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
increasing with increasing dissolved oxygen; the project team chooses to score
this zero (uncertain) but recognizes this as a borderline situation and that
additional data may add support to the correlation, thus supporting the case for
this cause.
EPT richness
% non-insects
HBI
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.
0
0
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.
Decreased large woody debris
Scatter plot data are sparse but support the case for this cause. EPT and large
woody debris are positively correlated. Additionally, HBI appears to decrease as
large woody debris increases.
EPT richness
% non-insects
HBI
EPT richness
% non-insects
HBI
NE
NE
NE
0
Increased sediment
EPT richness 0
% non-insects 0
HBI 0
84
-------
SOE score
Reasoning and Comments 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 „_ . .
..... -f. .... .. . . EPT richness +
appear to increase as chloride and specific conductivity increase, although the 0/
,„. ... . „ . . .. f ^.. .. . Im . J .. .. 3 . % non-insects +
relationship is weak-to-borderlme for chloride. HBI increases as chloride and
•r- ^ *• •* •
specific conductivity increase.
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
LCN .415
LCM 2.270
LCMn 2.274
Steps in causal pathway, units
RBP riparian vegetative zone width,
score and category
baseflow total phosphorus, ppm
baseflow ortho-phosphorus, ppm
baseflow total nitrogen, ppm
baseflow total kjeldahl nitrogen, ppm
baseflow nitrate + nitrite, ppm
storm flow total phosphorus, ppm
storm flow ortho-phosphorus, ppm
storm flow total nitrogen, ppm
storm flow total Kjeldahl nitrogen, ppm
storm flow nitrate + nitrite, ppm
LWD diameter > 5cm, # of pieces
LWD diameter > 10cm, # of pieces
mean thalweg velocity, m/s
shaded canopy, %
RB 3.961
10 optimal
0.009 [3]
(0.008-0.010)
0.003 [3]
(0.002 - 0.004)
0.310 [3]
(0.280 - 0.350)
0.1 67 [3]
(0.100-0.200)
0.1 43 [3]
(0.100-0.180)
0.011 -0.074
[9]
< 0.001 - 0.005
[9]
0.330 - 0.800
[9]
0.2 - 0.7 [9]
0.03 - 0.25 [9]
91
39
0.10
90.9
Value
6.5 sub-optimal
0.048 [3]
(0.040-0.061)
0.009 [3]
(0.004-0.017)
0.617 [3]
(0.610-0.620)
0.300 [3]
(0.300 - 0.300)
0.317 [3]
(0.310-0.320)
0.044 - 0.320
[9]
< 0.001 -0.015
[9]
0.520-1.670
[9]
0.4 - 1 .3 [9]
0.12-0.82 [9]
NE
NE
NE
88.1
Difference
<
433%
238%
99%
80%
121%
332%
200%
109%
86%
228%
NA
NA
NA
-3%
Value
4 marginal
0.025 [3]
(0.020 - 0.028)
0.008 [3]
(0.006-0.010)
0.51 3 [3]
(0.420 - 0.600)
0.467 [3]
(0.400 - 0.500)
< 0.047 [3]
(0.02 - < 0.20)
NE
NE
NE
NE
NE
37
8
NE
81.4
Difference
<
1 74%
200%
66%
1 80%
-67%
NA
NA
NA
NA
NA
-59%
-79%
NA
-10%
Value
7 sub-optimal
0.030 [3]
(0.024 - 0.035)
0.005 [3]
(0.002 - 0.007)
0.457 [3]
(0.330 - 0.540)
0.400 [3]
(0.300 - 0.500)
< 0.057 [3]
(0.03 - < 0.20)
NE
NE
NE
NE
NE
43
12
0.0273
90.8
Difference
<
230%
88%
47%
140%
-60%
NA
NA
NA
NA
NA
-53%
-69%
-73%
0%
Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range
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
[n].
-------
SOE Table 6. Causal pathway - Data - Decreased dissolved oxygen
LCN .415
LCM 2.270
LCMn 2.274
Steps in causal pathway, units
RBP channel alteration, score and
category
RBP riparian vegetative zone width,
score and category
baseflow total phosphorus, ppm
baseflow ortho-phosphorus, ppm
baseflow total nitrogen, ppm
baseflow total kjeldahl nitrogen, ppm
baseflow nitrate + nitrite, ppm
storm flow total phosphorus, ppm
storm flow ortho-phosphorus, ppm
storm flow total nitrogen, ppm
storm flow total Kjeldahl nitrogen, ppm
storm flow nitrate + nitrite, ppm
chlorophyll a, mg/m2
LWD diameter > 5cm, # of pieces
LWD diameter > 10cm, # of pieces
shaded canopy, %
RB 3.961
20 optimal
10 optimal
0.009 [3]
(0.008-0.010)
0.003 [3]
(0.002 - 0.004)
0.310 [3]
(0.280-0.350)
0.167 [3]
(0.100-0.200)
0.143 [3]
(0.100-0.180)
0.011 -0.074
[9]
< 0.001 -0.005
[9]
0.330-0.800
[9]
0.2-0.7 [9]
0.03-0.25(9]
10.4
91
39
90.9
Value
17 optimal
6.5 sub-optimal
0.048 [3]
(0.040-0.061)
0.009 [3]
(0.004-0.017)
0.617 [3]
(0.610-0.620)
0.300 [3]
(0.300 - 0.300)
0.317 [3]
(0.310-0.320)
0.044-0.320
[9]
< 0.001 -0.015
[9]
0.520-1.670
[9]
0.4-1.3 [9]
0.12-0.82(9]
15.7
NE
NE
88.1
Difference
= 0
<
433%
238%
99%
80%
121%
332%
200%
109%
86%
228%
51%
NA
NA
-3%
Value
14 sub-optimal
4 marginal
0.025 [3]
(0.020 - 0.028)
0.008 [3]
(0.006-0.010)
0.513 [3]
(0.420 - 0.600)
0.467 [3]
(0.400 - 0.500)
< 0.047 [3]
(0.02 - < 0.20)
NE
NE
NE
NE
NE
NE
37
8
81.4
Difference
<
<
1 74%
200%
66%
180%
-67%
NA
NA
NA
NA
NA
NA
-59%
-79%
-10%
Value
14 sub-optimal
7 sub-optimal
0.030 [3]
(0.024-0.035)
0.005 [3]
(0.002 - 0.007)
0.457 [3]
(0.330-0.540)
0.400 [3]
(0.300 - 0.500)
< 0.057 [3]
(0.03 - < 0.20)
NE
NE
NE
NE
NE
17.5
43
12
90.8
Difference
<
<
230%
88%
47%
140%
-60%
NA
NA
NA
NA
NA
68%
-53%
-69%
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 gualitative 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
-------
oo
oo
SOE Table 7. Causal pathway - Data - Altered flow regime
LCN .415
LCM 2.270
LCMn 2.274
Steps in causal pathway, units
RBP channel alteration, score, and
category
RBP channel sinuosity, score, and
category
RBP riparian vegetative zone width,
score, and category
LWD diameter > 5cm, # of pieces
LWD diameter > 10cm, # of pieces
percent impervious surface
RB 3.961
20 optimal
16 optimal
10 optimal
91
39
2.1
Value
17 optimal
9 marginal
6.5 sub-optimal
NE
NE
32.6
Difference
= 0
<
<
NA
NA
1452%
Value
14 sub-optimal
14 sub-optimal
4 marginal
37
8
7.1
Difference
<
<
<
-59%
-79%
238%
Value
14 sub-optimal
12 sub-optimal
7 sub-optimal
43
12
14.3
Difference
<
<
<
-53%
-69%
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 optimal
riparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal
-------
SOE Table 8. Causal pathway - Data - Decreased large woody debris
LCN .415
LCM 2.270
LCMn 2.274
Steps in causal pathway, units
RBP channel alteration, score, and
category
RBP channel sinuosity, score, and
category
RBP riparian vegetative zone width,
score, and category
RB 3.961
20 optimal
16 optimal
10 optimal
Value Difference
17 optimal =0
9 marginal <
6.5 sub-optimal <
Value Difference
14 sub-optimal <
14 sub-optimal <
4 marginal <
Value Difference
14 sub-optimal <
12 sub-optimal <
7 sub-optimal <
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 optimal
riparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal
-------
SOE Table 9. Causal pathway - Data - Increased sediment
LCN .415
LCM 2.270
LCMn 2.274
Steps in causal pathway, units
RBP channel alteration, score, and
category
RBP channel sinuosity, score, and
category
RBP riparian vegetative zone width,
score, and category
RBP bank vegetative protection, score,
and category
RBP bank stability, score, and category
Pfankuch, score
LWD diameter > 5cm, # of pieces
LWD diameter > 10cm, # of pieces
percent impervious surface
RB 3.961
20 optimal
16 optimal
10 optimal
10 optimal
9 optimal
93
91
39
2.1
Value
17 optimal
9 marginal
6.5 sub-optimal
10 optimal
7 sub-optimal
105
NE
NE
32.6
Difference
= 0
<
<
0
<
13%
NA
NA
1452%
Value
14 sub-optimal
14 sub-optimal
4 marginal
7 sub-optimal
8.5 optimal
NE
37
8
7.1
Difference
<
<
<
<
= 0
NA
-59%
-79%
238%
Value
14 sub-optimal
12 sub-optimal
7 sub-optimal
8 sub-optimal
9 optimal
111
43
12
14.3
Difference
<
<
<
<
= 0
19%
-53%
-69%
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
channel alteration
channel sinuosity
bank stability
bank vegetative protection
riparian vegetative zone width
Score and Condition Category
0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal
0-5 poor, 6-10 marginal, 11-15 sub-optimal, 16-20 optimal
0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal
0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal
0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal
-------
SOE Table 10. Causal pathway - Data - Increased temperature
LCN .415
LCM 2.270
LCMn 2.274
Steps in causal pathway, units
RBP channel alteration, score, and
category
RBP channel sinuosity, score, and
category
RBP riparian vegetative zone width,
score, and category
shaded canopy, %
percent impervious surface
RB 3.961
20 optimal
16 optimal
10 optimal
90.9
2.1
Value
17 optimal
9 marginal
6.5 sub-optimal
88.1
32.6
Difference
= 0
<
<
-3%
1452%
Value
14 sub-optimal
14 sub-optimal
4 marginal
81.4
7.1
Difference
<
<
<
-10%
238%
Value
14 sub-optimal
12 sub-optimal
7 sub-optimal
90.8
14.3
Difference
<
<
<
0%
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 optimal
riparian vegetative zone width 0-2 poor, 3-5 marginal, 6-8 sub-optimal, 9-10 optimal
-------
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%
to
-------
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.
SOE
Reasoning and Comments
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
SOE
Reasoning and Comments
score
SiteLCN .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
-------
SOE
Reasoning and Comments
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
SOE
Reasoning and Comments
score
SiteLCN .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 missinq step in each causal pathway
— Data show, with a high degree of certainty, that there is at least one missinq step in each causal pathway
SOE
Reasoning and Comments
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 missinq step in each causal pathway
— Data show, with a high degree of certainty, that there is at least one missinq step in each causal pathway
SOE
Reasoning and Comments
score
SiteLCN .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 sub-
optimal 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
-------
SOE
Reasoning and Comments
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 missinq step in each causal pathway
— Data show, with a high degree of certainty, that there is at least one missinq step in each causal pathway
SOE
Reasoning and Comments
score
SiteLCN .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
-------
SOE
Reasoning and Comments
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 missinq step in each causal pathway
— Data show, with a high degree of certainty, that there is at least one missinq step in each causal pathway
SOE
Reasoning and Comments
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
Organism
C. tentans
(chironomid)
H. azteca
(amphipod)
Lab
Control
87.5
100.0
RB
3.961
88.3
81.3
LCN
.415
87.1
85.0
LCM
2.270
NE
NE
LCMn
2.274
92.5
96.3
103
-------
SOE Table 20. Laboratory tests of site media (sediment toxicity) - Scores
Strength of evidence (SOE) scoring system for laboratory tests of site medic
+ + + 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.
Reasoning and Comments
SOE score
Endpoint Score
SiteLCN .415
The project team used the chironomid (C. tentans) and amphipod (H. azteca)
laboratory specimens as surrogates for EPT and non-insects, respectively.
Chironomid survivorship differences among the two impaired sites tested, the
reference site, and the laboratory control were not found to be statistically
significant; therefore, EPT was given a score of zero. Amphipod survival was
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
Sediment sampling laboratory tests were not conducted for this site.
EPT richness 0
% non-insects 0
HBI NE
brook trout N E
EPT richness NE
% non-insects NE
HBI NE
brook trout N E
Site LCN 2.274
The project team used the chironomid (C. tentans) laboratory specimen as a
surrogate for EPT. Chironomid survivorship differences among the two impaired
sites tested, the reference site, and the laboratory control were not found to be
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.
EPT richness
HBI
brook trout
0
NE
NE
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
gatherers
predators
scrapers
shredders
18.3
18.6
36.6
17.2
7.8
1.1
16.5
30.9
13.3
34.6
10.8
60.7
18.2
3.3
6.7
10.3
71.8
13.1
1.4
2.7
Mode of existence:
burrower-sprawlers
swimmers
clingers
climbers
57.9
5.3
6.4
27.7
38.3
22.9
5.9
18.6
33.9
2.9
47.6
3.5
19.2
2.1
70.1
7.6
105
-------
SOE Table 22. Stressor-response relationship from elsewhere - Data - Increased autochthony
Variable, units
chlorophyll a, mg/m2
baseflow total nitrogen,
ppm
baseflow total Kjeldahl
nitrogen, ppm
baseflow nitrate +
nitrite, ppm
baseflow total
phosphorus, ppm
Stressor-Response Benchmark
Description
reduced invertebrate diversity (Nordin, 1985)
eutrophy risk range (U.S. EPA, 2000b, summary
document)
EPA reference for ecoregion XIV, 59, northeastern
coastal zone (U.S. EPA, 2000c)
eutrophy risk range (U.S. EPA, 2000b, summary
document)
EPA reference for ecoregion XIV, 59, northeastern
coastal zone (U.S. EPA, 2000c)
EPA reference for ecoregion XIV, 59, northeastern
coastal zone (U.S. EPA, 2000c)
deleterious effects on fish communities (Miltner &
Rankin, 1998)
EPA reference for ecoregion XIV, 59, northeastern
coastal zone (U.S. EPA, 2000c)
eutrophy risk range (U.S. EPA, 2000b, summary
document)
Value
100
100-
200
0.57
1.5
0.30
0.31
0.06
0.024
0.035 -
0.075
RB 3.961
10.4
0.310 [3]
(0.280 -
0.350)
0.1 67 [3]
(0.100-
0.200)
0.1 43 [3]
(0.150-
< 0.20)
0.009 [3]
(0.008 -
0.010)
LCN .415
15.7
0.617 [3]
(0.610-
0.620)
0.300 [3]
(0.300 -
0.300)
0.317 [3]
(0.310-
0.320)
0.048 [3]
(0.040 -
0.061)
LCM 2.270
NE
0.51 3 [3]
(0.420-
0.600)
0.467 [3]
(0.400 -
0.500)
< 0.047 [3]
(0.02 -
< 0.20)
0.025 [3]
(0.020 -
0.028)
LCMn 2.274
17.5
0.457 [3]
(0.330 -
0.540)
0.400 [3]
(0.300 -
0.500)
< 0.057 [3]
(0.03 -
< 0.20)
0.030 [3]
(0.024 -
0.035)
Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].
-------
SOE Table 23. Stressor-response relationship from elsewhere - Data
Stressor-Response Benchmark
Variable, units
Description
Value
Decreased dissolved oxygen
RB 3.961 LCN.415 LCM 2.270 LCMn 2.274
minimum dissolved
oxygen, mg/L
U.S. EPA (1986a) fresh and cold water aquatic life
criteria
8.0
30-day LC50 values for four different EPT organisms 4.4 - 5.0
(Nebeker, 1972) [4]
optimum level for brook trout, where temperature is
above 15°C (Raleigh, 1982)
minimum acceptable temporary brook trout level
(Mills, 1971 as cited in Raleigh, 1982)
8.0 [3]
(8.0 - 9.5)
5.3 [3]
(5.3 - 7.8)
4.1 [3]
(4.1 - 7.4)
4.4 [3]
(4.4-6.2)
Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].
-------
SOE Table 24. Stressor-response relationship from elsewhere - Data - Altered flow regime
Variable, units
impervious surface
area, %
Stressor-Response Benchmark
Description Value
abrupt decline in taxonomic richness, specifically
EPT, and an increase in non-insects, specifically 6
gastropods (Morse et al., 2003)
shift to tolerant species (Maxted et al., 1 996) 10-15
brook trout not found (Boward et al., 1 999) 2
RB 3.961 LCN .415 LCM 2.270 LCMn 2.274
2.1 32.6 7.1 14.3
o
oo
-------
SOE Table 25. Stressor-response relationship from elsewhere - Data - Decreased large woody debris
Stressor-Response Benchmark
Variable, units
Description
Value
RB 3.961 LCN .415 LCM 2.270
LCMn
2.274
LWD diameter > 5 cm,
# of pieces
LWD diameter > 10cm,
# of pieces
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)
debris dam abundance positively correlated with
macroinvertebrate abundance and relative abundance
of shredders to biomass (Smock et al., 1989; applies
to EPT endpoint)
in high gradient mountain streams, trout nearly always
occupied pools with at least 2 pieces of woody debris
(Flebbe1999)
LWD contributes to wild trout habitat (Neumann and
Wildman, 2002)
re
0)
+J
o
3
•c
o
o
tn
'55
re
re
91
NE
37
43
39
NE
12
-------
SOE Table 26. Stressor-response relationship from elsewhere - Data - Increased sediment
Variable, units
baseflow TSS, mg/L
storm flow TSS, mg/L
sediment size, mm
Stressor-Response Benchmark
Description
exposure causing 40 - 60% aquatic invertebrate
mortality and severe habitat degradation at greater
than 1 ,000 hours duration (similar to baseflow
condition) (mean [n] (range), from literature review,
Newcombe and MacDonald, 1991)
exposure causing reduction in brook trout growth rate
at durations greater than 1 ,000 hours (similar to
baseflow condition) (mean [n] (range), from literature
review, Newcombe and MacDonald, 1991)
exposure causes decreased invertebrate population at
approximately 24 hours duration (similar to storm
event) (Gammon, 1970 as cited in Newcombe and
MacDonald, 1991)
sediment diameter potentially fine enough to hinder
brook trout egg survival and early development
(Argent and Flebbe, 1999)
Value
33 [4
studies]
(8 - 77)
45 [3
studies]
(12-100)
53-92
0.43-
0.85
RB 3.961
< 10 [3]
(< 2- < 10)
< 10- 118 [9]
53% of
particles @
0.062-0.13
& 35% @
0.25-0.5
LCN .415 LCM 2.270 LCMn 2.274
< 1 0 [3] < 1 0 [3] < 1 0 [3]
(^ ^ "\r\\ ("\ ^ "\r\\ (A ^ "\r\\
(j - < I V) ( I - < I V) (*t - < I V)
< 10 -271 [9] NE NE
45% of
particles© 100% of 92% of
0.062-0.13 particles© particles©
& 29% @ 0.062 - 0.1 3 0.062 - 0.1 3
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].
-------
SOE Table 27. Stressor-response relationship from elsewhere - Data
Stressor-Response Benchmark
Variable, units
Description
Value
Increased temperature
RB 3.961 LCN.415 LCM 2.270 LCMn 2.274
temperature, weekly
maximum, °C
severe stress to most cold-water organisms (literature
review by Galli and Dubose, 1990)
generalized optimum for EPT (literature review by
Galli and Dubose, 1990)
generalized physiological optimum for stenotherms
(trout and other coldwater fish) (literature review by
Galli and Dubose, 1990)
95th percentile brook trout tolerance limit (Eaton et al.
1995)
21
< 17
50% mortality for Baetis rhodani, Baetis tenax, and 21.1,
Caenis sp. (Ephemeroptera), respectively (literature 21.3, &
review by Galli and Dubose, 1990) 26.7
< 20.0
22.3
21.1 [3] 22.7 [3]
(20.3-22.1) (21.6-24.2)
23.3
21.8
Base and low flow values shown as mean [n] (range), where more than one value available, and storm flow values shown as range [n].
-------
SOE Table 28. Stressor-response relationship from elsewhere - Data - Increased toxic substances
Stressor-Response Benchmark
Variable
(ppm or mg/L) Flow
Description
Value
RB 3.961
LCN.415 LCM 2.270 LCMn 2.274
Ionic strength, water column sampling
calcium
chloride
magnesium
salinity
specific
conductivity,
low
base
storm
low
base
base
not available
EPA CCC
EPA CMC
230
860
not available
range of 48-hr LC50 values for various salt
combinations tested on Ceriodaphnia (Mount et al.,
1997)
EPT effects based on interpretation of statewide
data from Maine (Davies and MEDEP, 2005; Fig.
6), Florida (Florida Department of Environmental
Protection, 2005; Appendix J), and Kentucky (Pond,
2004; Appendix J)
presence of amphipods in place of EPT might be
indicative of higher conductivity, as amphipods are
more tolerant (Kefford et al., 2003)
250-
5700
100-200
NA
6.8
29 [3]
(26 - 30)
1 7 - 57 [9]
2.2
67 [3]
(0- 100)
1 29 [3]
(79-155)
67
122 [3]
(91 - 141)
15 -296 [9]
17
367 [3]
(300 - 400)
745 [3]
(659 - 796)
NE
99 [3]
(83-124)
NE
NE
267 [3]
(200 - 400)
568 [3]
(491 -718)
31.5
66 [3]
(58 - 73)
NE
11
200 [3]
459 [3]
(376-510)
Elements,
aluminum
arsenic
cadmium
water column sampling
low
low
base
low
storm
EPA CCC
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPA CCC
EPA CCC
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPA CMC
0.087
0.66
0.71
0.15
0.00025
0.032
0.35
0.002
0.045
< 0.0005
< 0.0005 [3]
< 0.0002
< 0.0005 [9]
0.006
0.00098
< 0.0005 [3]
< 0.0002
<• o nnns
0.0007 [9]
NE
NE
< 0.0005 [3]
NE
NE
0.019
0.00235
< 0.0005 [3]
< 0.0002
NE
-------
Variable
(ppm or mg/L)
chromium
copper
iron
lead
nickel
selenium
zinc
Flow
low
base
storm
low
base
low
storm
base
low
storm
low
base
low
storm
Stressor-Response Benchmark
Description
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPACCC
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPA CMC
EPACCC
EPA CCC
EPA CMC
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPA CCC
Value
0.17
7.3
0.008
0.015
0.009
0.013
0.061
0.013
1.0
0.0025
0.065
0.61
2.9
0.052
use baseflow S-R values immediately above
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPA CMC
EPA CCC
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPACCC
1.9
6.2
0.47
0.005
0.087
0.14
0.12
use baseflow S-R values immediately above
invertebrate SSD, LC50 for 10% of species
chordate SSD, LC50 for 10% of species
EPA CMC
0.45
1.9
0.12
RB 3.961
< 0.0005
< 0.002 [3]
-------
Variable
(ppm or mg/L) Flow
antimony
barium
beryllium
cobalt
manganese low
molybdenum
silver
thallium
vanadium
Stressor-Response Benchmark
Description Value
— see text —
RB 3.961
< 0.0005
0.0054
< 0.0002
0.00085
0.025
< 0.0005
< 0.0002
< 0.0005
0.0003
LCN .415
< 0.0005
0.021
< 0.0002
0.0029
0.37
0.00092
< 0.0002
< 0.0005
0.00082
LCM 2.270 LCMn 2.274
< 0.0005
0.011
< 0.0002
0.000555
NE 0.092
0.000385
< 0.0002
< 0.0005
0.000695
All values displayed in ppm or mg/L, unless otherwise noted.
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.)
EPA CCC and CMC from U.S. EPA, 2004b.
-------
SOE Table 29. Stressor-response relationship from elsewhere - Scores -
Increased autochthony
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 relationships in controllec
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.
SOE score
Reasoning and Comments
Endpoint Score
SiteLCN .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
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 relationship:
+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controllec
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.
SOE score
Reasoning and Comments
Endpoint Score
EPT richness +
% non-insects 0
HBI 0
brook trout +
SiteLCN .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.
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 mq/L) and optimum brook trout level (9 ,_„ . ,
EPT richness +
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.
116
-------
SOE Table 31. Stressor-response relationship from elsewhere - Scores - Altered
flow regime
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 relationships in controllec
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 ir
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
SiteLCN .415
Percent impervious surface is greater than all S-R benchmark values related to
multiple endpoints. (See text for discussion on percent impervious surface as a
conservative and qualitative surrogate for altered flow regime.)
EPT richness +
% non-insects +
HBI 0
brook trout +
Site LCM 2.270
Percent impervious surface is greater than all S-R benchmark values related to
multiple endpoints. (See text for discussion on percent impervious surface as a
conservative and qualitative surrogate for altered flow regime.)
EPT richness +
% non-insects +
HBI 0
brook trout +
Site LCMn 2.274
Percent impervious surface is greater than all S-R benchmark values related to
EPT and brook trout. (See text for discussion on percent impervious surface as a
conservative and qualitative surrogate for altered flow regime.)
EPT richness +
HBI 0
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 relationship:
+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controllec
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 ir
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
SiteLCN .415
EPT richness NE
...,_ . . . . „.. .,..- % non-insects NE
LWD was not measured at LCN .415. ,,„, .,._
HBI NE
brook trout N E
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
end points. 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 . .
. . t brook trout +
end points.
118
-------
SOE Table 33. Stressor-response relationship from elsewhere - Scores -
Increased sediment
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 relationships in controllec
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 ir
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
SiteLCN .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
TSS levels). Storm flow site measurements fall within the range of effects for
invertebrates, and sediment diameters are fine enough to impact early stages of
brook trout development, but note that reference site sediment sizes are similar.
The S-R data both weaken and support the case for this cause; therefore, zeros
were assigned to all scores, indicating ambiguity.
EPT richness 0
% non-insects 0
HBI 0
brook trout 0
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%
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 0
% non-insects 0
HBI 0
brook trout +
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 0
HBI 0
brook trout +
Note that some TSS data did not meet MEDEP quality standards (MEDEP, pens 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 relationship:
+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controllec
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 ir
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
SiteLCN .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.
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 relationship:
+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controllec
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 ir
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
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
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
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
evidence to the EPT and brook trout endpoints, but evidence for non-insects and HBI
HBI is unclear. brook trout
0
0
121
-------
SOE score
Reasoning and Comments Endpoint Score
zinc
All measured zinc values at the site fall below the 10% SSD thresholds. Baseflow
& low flow values fall below the EPA CCC. 1 of 9 storm event zinc samples
exceeds the EPA CMC value, and 1 of 9 equaled the CMC value. S-R evidence °
both weakens and supports the case for zinc as a cause; therefore, the project
. „ . . , , , brook trout 0
team scored all endpomts zero (unclear)
antimony, barium, beryllium, cobalt, manganese, molybdenum,
silver, thallium, and vanadium
EPT richness NE
M • r- r-, -_i i-i L_ i- -i L. • • L_ % non-insects NE
No appropriate S-R evidence could be applied to these remaining substances.
H D I IM t
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 relationship:
+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controllec
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 ir
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
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
zinc as causes. Note that we do not have storm flow data for copper at this site,
unlike LCN .415, where storm samples tested positive for copper levels above the
CCC and SSD 10% threshold but baseflow did not. Based on the data we do
have for the three substances, EPT and brook trout receive negative scores, and
impacts are unclear for non-insects and HBI.
EPT richness
% non-insects
HBI
brook trout
0
0
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 relationship:
+ + The observed relationship between exposure and effects in the case agrees quantitatively with stressor-response relationships in controllec
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 ir
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
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
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 +
HBI 0
brook trout 0
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
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
No appropriate S-R evidence could be applied to these remaining substances.
EPT richness NE
HBI NE
brook trout N E
124
-------
SOE Table 38. Stressor-response relationship from elsewhere - Increased PAH's 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 o
the quantitative differences are very large.
NE no evidence.
Polycyclic
Aromatic
Hydrocarbon
(PAH)
ALL units are
u,g/ml
Acenaph-
thene
Acenaph-
thylene
Anthracene
Benzo(a)
anthracene
Benzo(a)
pyrene
Benzo(b)
fluoranthene
Benzo(ghi)
perylene
Benzo(k)
fluoranthene
Chrysene
Storm, 10/18/00
1.1" over 21 hrs
LCN RB
.585 1.694 RL
0.10 nd 0.05
nd nd 0.05
0.20 nd 0.05
0.10 nd 0.05
0.10 nd 0.05
0.20 nd 0.05
0.10 nd 0.05
nd nd 0.05
0.20 nd 0.05
Storm, 9/25/01
1.7" over 24 hrs
LCN RB
.585 1.694 RL
nd nd 0.1
nd nd 0.1
nd nd 0.1
0.33 nd 0.1
0.48 nd 0.1
1.11 nd 0.1
0.5 nd 0.2
0.29 nd 0.1
0.8 nd 0.1
SOE
U.S. EPA, U.S. EPA, 1986b sub-
2004dA (Goldbook) Eisler, 1987 ECOTOX6 score
<=1,700&520
data for human acute and chronic ,. . „„„„, >
, . . not listed 1280 tox
consume only freshwater,
respectively
listed, but no .,-.,, .,-.,, .,-.,, ,,,-
not listed not listed not listed NE
data
data for human .,-.,, • . . .• . nr ,. \
not listed info not pertinent 95 (tox)
consume only
data for human .,-.,, LC87 (6mo) .,-.,,
. not listed . . ... * . ' „ not listed
consume only bluegill @ 1,000
. t , . LC50 (96hr)
data for human ... . A ,• _j
. not listed sandworm @ not listed
consume only ^ QQQ
data for human
consume only, info not pertinent,
but nps shows not listed but listed many not listed NE
300 marine times
acute LEG
, t . . t LC50 (96hr)
listed, but no ... . A ,• _j
. . not listed sandworm @ not listed
data >i,ooo
data for human
consume only,
but nps shows not listed not listed NE
300 marine
acute LEG
, . LC50 (96hr)
data for human ,. . ' ,.
. not listed sandworm @ not listed
consume only ^ OOQ
Canada,
2003
(fresh-
British water SOE
Columbia, aquatic sub-
1 993 life) score
6 chronic 5.8
not listed no data NE
4 chronic & 0.1 Q^2 +
phototox
0.1 chronic & +
phototox
0.01 chronic 0.015 +
not listed, but
pending ref to .
0.01 (NPS n°data +
1997)
not listed not listed NE
not listed, but
pending ref to .
0.01 (NPS n°data +
1997)
insufficient
. . no data N E
data
SOE
score
--
NE
0
0
0
0
0
0
0
-------
Polycyclic
Aromatic
Hydrocarbon
(PAH)
ALL units are
io.g/mi
Dibenzo(a,h)
anthracene
Fluoran-
thene
Fluorene
Indeno
(1,2,3-cd)
pvrene
Naphthalene
Phenan-
threne
Pyrene
Storm, 10/18/00
1.1" over 21 hrs
LCN RB
.585 1.694 RL
nd nd 0.05
0.50 nd 0.05
0.10 nd 0.05
0.10 nd 0.05
0.10 nd 0.05
0.25 nd 0.05
0.30 nd 0.05
Storm, 9/25/01
1.7" over 24 hrs
LCN RB
.585 1.694 RL
0.11 nd 0.2
1.6 nd 0.1
nd nd 0.1
0.56 nd 0.2
nd nd 0.1
0.67 nd 0.1
1.15 nd 0.1
SOE
U.S. EPA, U.S. EPA, 1986b sub-
2004dA (Goldbook) Eisler, 1987 ECOTOX6 score
. t , . LC50 (96hr)
data for human .,-.,, j A . r . j
. not listed sandworm @ not listed
consume only ^ QQQ
<= 3,980 acute
freshwater, and
data for human <= 40 and 16 LC50 (96hr) , .
consume only acute and chron, sandworm 500 , ^ ,
respectively,
saltwater
. , . LC50s (various
data for human .,-.,, nr.i. \ -,™ . r . j
not listed orqs, 96hr) 320 - not listed
consume only * 5^QQ
data for human .,-.,, . ,• . ^ ,,,-
. not listed not listed NE
consume only
LC50 (10d)
<= 2,300 and 620 copepod @ 50, (b^v\or)
listed, but no acute and chronic and LC50s
data freshwater, (various orgs, 24- , '
respectively 96 hr) 920 - (Pnysl01-
150,000 °9y)
LC50 (24hr) grass
listed, but no ,. . shrimp @ 370, _ ... , .
not listed . . !;r.. ,__. \ 340 tox
data and LC50 (96hr)
sandworm 600
data for human ,. , „ „_„ . .
not listed 1 ,020 tox
consume only
Canada,
2003
(fresh-
British water SOE
Columbia, aquatic sub-
1 993 life) score
not listed no data NE
4 chronic & 0.2
phototox
12 chronic 3.0
not listed no data NE
1 chronic 1.1
0.3 chronic 0.4 +
0.02 phototox 0.025 +
SOE
score
0
0
--
NE
--
0
0
Source (U.S. EPA, 2004d) lists only human health consumption criteria for some PAHs.
BECOTOX database (ECOTOXicology, located at: http://www.epa.gov/ecotox/).
-------
SOE Table 39. Consistency of evidence scoring system
Finding
Interpretation
Score
All available types of evidence support the case for the
candidate cause.
This finding convincingly supports the case for the candidate
cause.
All available types of evidence weaken the case for the
candidate cause.
This finding convincingly weakens the candidate cause.
All available types of evidence support the case for the
candidate cause, but few types are available.
All available types of evidence weaken the case for the
candidate cause, but few types are available.
This finding somewhat supports the case for the candidate
cause, but is not strongly supportive because coincidence and
errors may be responsible.
This finding somewhat weakens the case for the candidate
cause, but is not strongly weakening because coincidence and
errors may be responsible.
The evidence is ambiguous or inadequate.
This finding neither supports nor weakens the case for the
candidate cause.
Some available types of evidence support and some
weaken the case for the candidate cause.
This finding somewhat weakens the case for the candidate
cause but is not convincing because a few inconsistencies may
be explained.
Source: U.S. EPA CADDIS (http://www.epa.gov/caddis/).
-------
SOE Table 40. Strength of Evidence summary scoring at LCN .415
Biological endpoint
Candidate cause
Types of evidence that
use data from the case
"re
<- fll
2 <•>
Q- c
1 £
1! =
^ O
'•re ?
Q. o
V) 0
0)
^
0) £
= p
o t
« M
? !E
0 C
In -2
a* S "n
22 TO _
w £ c
re
^
ID
_^-
re
re
O
Types of evidence
that use data from
elsewhere
0)
.n
'35
3
re
Q.
"re
o
'E
re g)
0 3
^ 0
•c
0)
^
* C ai
w 5 ^
c P ^
O t O
9- >-
W Q. O
e f ^
0 C 2 (fl
V) O CO 0)
£ ™ E 3
8» e * «
0)
o
c
0)
;o
"^
LU
.
0
>»
O
c
0)
•4-1
'in
c
o
o
EPT richness
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
NE
0
0
NE
+
0
0
+
+
+
+
+
+
NE
0
0
+
+ +
+
+
% non-insects
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
00 +
+ 0 +
+ NE +
NE 0 +
+ 0 +
+ 0 +
+ + +
+ 0
+ 0
+ +
+ NE
+ 0
0 0
0 +
0
+
+ +
0
+
+
+ +
HBI
Increased autochthony 0 + +
Decreased dissolved oxygen + + +
Altered flow regime + NE +
Decreased large woody debris NE + +
Increased sediment + 0 +
Increased temperature + + +
Increased ionic strength + + +
+
+
+
+
0
0
0
0 +
0 +
0 +
NE +
0 +
0 +
0 +
Brook trout
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
NE
NE
NE
NE
NE
NE
NE
NE
0
+
+
+
+
+
+
NE
0
+
0
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
Biological endpoint
Candidate cause
Types of evidence that
use data from the case
"re
<- fll
2 <•>
Q- c
1 £
1! =
^ O
'•re ?
Q. o
V) 0
0)
^
0) £
= p
o t
« M
? !E
0 C
In -2
a* S "n
22 TO _
w £ c
re
^
ID
_5"
re
re
O
Types of evidence
that use data from
elsewhere
0)
.n
'35
3
re
Q.
"re
o
'E
re g)
0 3
^ 0
•c
0)
^
* C ai
w 5 ^
c P ^
O t O
9- >-
W Q. O
e f ^
0 C 2 (fl
V) O CO 0)
£ ™ E 3
8» e * «
0)
o
c
0)
;o
"^
LU
.
0
>»
O
c
0)
•4-1
'in
c
o
o
EPT richness
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
0
NE
0 0
0
0
NE
0
+
+
+
+
+
+
+
+
+
0
+
+
+ +
+
+ +
0
+ +
+ +
% non-insects
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
0
+
NE
+
0
+
+
0 +
0 +
NE +
0 +
0 +
0 +
+ +
0
+
+
+
+
0
0
0
0
+
NE
0
0
+
0
+
+
+
0
+
+ +
HBI
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
0 + +
+ + +
NE NE +
+ + +
00 +
+ + +
+ + +
+
+
+
+
0
0
0
-
0
0
NE
0
0
0
0
+
0
+
0
+
+
Brook trout
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
0
+
NE
+
0
NE
NE
NE
NE
NE
NE
NE
0
+
+
+
+
+
+
+
+
+
+
+
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
Biological endpoint
Candidate cause
Types of evidence that
use data from the case
2
Q- c
£
k- (/) O
O C +S (/)
V) O CO 0)
g> re _§ ^
55 £ * %
0)
o
c
0)
;o
"^
LU
.
0
0
c
0)
(/)
'in
c
o
o
EPT richness
Increased autochthony 00+0
Decreased dissolved oxygen + 0 + + + + +
Altered flow regime + NE + + + +
Decreased large woody debris + + + + + + +
Increased sediment 00++ 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
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
Brook trout
Increased autochthony
Decreased dissolved oxygen
Altered flow regime
Decreased large woody debris
Increased sediment
Increased temperature
Increased ionic strength
0 + +
+ + +
+ NE +
+ + +
00 +
+ + +
+ + +
0 NE +
+ NE +
+ NE +
+ NE +
0 NE +
+ NE +
+ NE +
+
+ 0
+ 0
+ NE
0 0
0 0
0 0
0
+ +
+ +
+ +
+ +
+ +
+ 0
0
+
+
+
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
Impaired site
Biological endpoint LCN LCM LCMn
Candidate cause -415 2.270 2.274
EPT richness
Increased autochthony 0
Decreased dissolved oxygen + + + + +
Altered flow regime + + + +
Decreased large woody debris + + + + +
Increased sediment +00
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
o o S j *
d) CO
4- 4- (/) °- (/)
.£ "2 ^
+ + + c co 3)
0 + <= "g w
/-\ >S '5> o
+ 0 CD ° c
^— O (/)
+ + I- S |
•* 2
§ !.i
c £ ro
O oj o
CD a> •-
•K (?)
HBI
Increased autochthony + 0
Decreased dissolved oxygen + +
Altered flow regime + 0
Decreased large woody debris + +
Increased sediment + 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
inconsistencies or ambiguities in an otherwise positive body of
evidence that could make the body of evidence consistently
supporting.
This finding can save the case for a candidate cause that is
weakened by inconsistent evidence; however, without evidence
to support the explanation, the cause is barely strengthened.
There is no explanation for the inconsistencies or ambiguities
in the evidence.
This finding neither strengthens nor weakens the case for a
candidate cause.
OJ
to
There is a credible explanation for any positive
inconsistencies or ambiguities in an otherwise negative body
of evidence that could make the body of evidence consistently
weakening.
This finding further weakens an inconsistent case; however,
without evidence to support the explanation, the cause is barely
weakened.
Source: U.S. EPA CADDIS (http://www.epa.gov/caddis/)
-------
SOE Table 45. Strength of evidence complete scoring at LCN .415
Can
didate
use
Type
of
Evidence
.8-1
2 °-
CO 01
§ 0)
o-> P?
^ CD CO
>> S > ~ '*- 0)
^ T—I c_) °£ -7— i Q ^
-OO 0)"O ° 0)0) "O^ ~O ^
0)^ coo) 14— co~o CDC 0)":n
"E S^1 "°o> S5^ <" ^oroQ- •o5'">,^Sa)=tDo
<<M
CL
o
X
o
E
0)
13
0)
C/)
Types of evidence that use data from the case
Spatial/temporal
co-occurrence
Stressor-response
relationships from
the field
Causal pathway
Laboratory tests of
site media
NA
EPT richness
% non-insects
HBI
NA
EPT richness
% non-insects
0 + + NE + +
0 0 NE + 0 +
0 0 NE 0 0 0
+ + NE + 0 +
+ + + + + +
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 NE NE NE NE NE 0
NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0
NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0
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 NE NE NE NE NE NE NE NE NE NE NE
ST
NE
NE
NE
NE
NE
ST
NE
NE
NE
0
0
OJ
OJ
Types of evidence that use data from elsewhere
Mechanistically
plausible cause
Stressor-response
relationships from
laboratory or other
field studies
EPT
% non-insects
HBI
brook trout
EPT richness
% non-insects
HBI
brook trout
Multiple Lines of Evidence
Consistency of
evidence
Explanation of the
evidence
EPT richness
% non-insects
HBI
brook trout
% non-insects
HBI
brook trout
„
+ + + + + 0
+ + + + 00
0 + + NE 0 +
00 + NE 0 0
0 0 0 NE 0 0
0 + + NE 0 +
0
0
+
+
0
0
0000000000000000000
0000000000000000000
NE - NE NE 0 - NE + - 0 NE NE - - NE NE NE 0
0 NE 0 NE NE 0 0 NE 0 0 0 NE NE 0 0 NE NE NE 0
0 NE 0 NE NE 0 0 NE 0 0 0 NE NE 0 0 NE NE NE 0
NE - NE NE 0 - NE + - 0 NE NE - - NE NE NE 0
0
0
0
0
0
0
0
0
NE
NE
NE
NE
0 + + + + + +
0 + + + 0 + +
+ + + + + +
0 + + + + + +
0 ++ ++ ++ ++ ++
0 ++ ++ ++ ++ ++
0 ++ ++ ++ ++ ++
+ +
+ +
+
+
+ +
+ +
+ +
- 0-000-0 + -0 + 0- -000 +
00000000000 + 000000 +
00000000000 + 000000 +
- 0-000-0 + -0 + 0- -000 +
ST ST ST ST ST ST ST + + ST ST ST ST ST ST ST ST ST ST
ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST
ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST
ST ST ST ST ST ST ST + + ST ST ST ST ST ST ST ST ST ST
0
0
0
0
n
0
0
0
0
0
0
0
o
0
0
0
NE = No evidence; ST = See text
A Sediment toxicity laboratory results include individual metal concentrations found in the sediment samples; however, given lack of S-R information relevant to this type of data and given that the species
survivorship information does not indicate support for this cause, we do not break this column down by individual contaminants found in sediment samples.
-------
SOE Table 46. Strength of Evidence complete scoring at LCM 2.270
C a n d
date
Cause
flj +J
Type '5, |
of ° a.
Evidence 5 §j
^
-a o
Increase
autochth
c
03
0)
X
-D 0
03 -n
Decreas
dissolve
g
o
Altered f
regime
Increased toxic substances
p water column
to
-------
SOE Table 47. Strength of Evidence complete scoring at LCMn 2.274
Type
of
Evidence
re „
0 C
0)0
0 Q.
^ "O
m g
•o Increasedtoxicsubstances
% m water column S,
« E>
'S ^ jfl ^ ^ S"a a>c a> to
C/)-^ COC -Dm ^!>^ C/)CD (/)i-
cof= a>0 ^^ cD-Sp cop co0
cDg bg ™.i bo £•- £°-
cg Qo gS'ag cgj caj
D5
1
to
o
0
0 1
E >, FEE ^ 1 E E
.1 | -a E 1 | 1 ^ fe | | _ | ^ | |
|l|-le«ll5§:c^i>i<^SglSo
<<M
O
jdiment to
00
Types of evidence that use data from the case
Spatial/temporal
co-occurrence
Stressor-response
relationships from
the field
Causal Pathway
Laboratory tests of
site media
NA
EPT richness
HBI
NA
EPT richness
0 + + + 0 +
0 0 NE + 0 +
+ + NE + 0 +
+ + + + + +
NE NE NE NE NE NE
+
+
+
+
NE
— 0 + + 00+ — 0 + 0 + 0 + 000 + 0
NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0
NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0
NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE
ST
NE
NE
0
Types of evidence that use data from elsewhere
Mechanistically
plausible cause
Stressor-response
relationships from
laboratory or other
field studies
EPT richness
HBI
brook trout
EPT richness
HBI
brook trout
Multiple Lines of Evidence
Consistency of
evidence
Explanation of the
evidence
EPT richness
HBI
brook trout
EPT richness
HBI
brook trout
0 + + + + +
+ + + + 00
0 + + + + +
+ + + 0 +
0 0 NE 0 0
+ + + + +
+ + + ++ 0 + +
0 + + + 0 +
+ + + + + +
++ ++ ++ 0 ++
++ ++ ++ 0 ++
+ + ++ ++ ++ + +
0
+
+
0
0
+ +
+
+
+ +
+ +
+ +
0000000000000000000
NE - NE NE 0 - NE - - 0 NE NE - - NE NE NE -
0 NE 0 NE NE 0 0 NE 0 0 0 NE NE 0 0 NE NE NE 0
NE - NE NE 0 - NE - - 0 NE NE - - NE NE NE -
- 0-000-0- -0 + 0- -000-
00000000000 + 0000000
- 0-000-0- -0 + 0- -000-
ST ST ST ST ST ST ST - ST ST ST ST ST ST ST ST ST
ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST ST
ST ST ST ST ST ST ST - ST ST ST ST ST ST ST ST ST
+
0
+
NE
NE
NE
0
0
0
0
0
0
NE = No evidence; ST = See text
A Sediment toxicity laboratory results include individual metal concentrations found in the sediment samples; however, given lack of S-R information relevant to this type of data and given that the species
survivorship information does not indicate support for this cause, we do not break this column down by individual contaminants found in sediment samples.
-------
SOE Table 48. Consistency of evidence complete scoring for all three impaired sites
Candidate
use
Type
of
Evidence
LCN.415
Consistency of
Evidence
m o
EPT richness
% non-insects
HBI
brook trout
LCM 2.270
Consistency of
Evidence
EPT richness
% non-insects
HBI
brook trout
LCMn 2.274
Consistency of
Evidence
EPT richness
HBI
brook trout
5> CO co
c? 73 0 g ^ £ 2
73O 0)73 O 0)0) 73 .^ 73 ^
0) -C o> u_ C073 0) C 0) m
10 £ S— "OO) § >> "0) li
ii_ O o co .I* ._ o o ifi ~ ifi y~
o -^ o) co B o~> 0)0 o13 oE
eg 0^5 50) Qg cgj co)
0 + + + + + +
0 + + + 0 + +
+ + + + + +
0 + + + + + +
++ + ++ 0 ++
0 + + + 0 +
0 + 0 + 0 +
+ + + + + +
++ + ++ 0 ++
0 + + + 0 +
+ + + + + +
Increased toxic substances
water column
c
0)
to
o
'c
o
+ +
+ +
+
+
+ +
+ +
+
+
-
+
0) |
E >, E E | o> § E 1
Illllilllgillililia
<<M
- 0-000-0 + -0 + 0- -000 +
00000000000 + 000000 +
00000000000 + 000000 +
- 0-000-0 + -0 + 0- -000 +
NE NE NE NE NE 0 NE NE - NE 0 NE NE - NE NE NE NE
NE NE NE NE NE 0 NE NE 0 NE 0 NE NE 0 NE NE NE NE 0
NE NE NE NE NE 0 NE NE 0 NE 0 NE NE 0 NE NE NE NE 0
NE NE NE NE NE 0 NE NE - NE 0 NE NE - NE NE NE NE
- 0-000-0- -0 + 0- -000-
00000000000 + 0000000
- 0-000-0- -0 + 0- -000-
CO
i
Q_
0
0
0
0
NE
NE
NE
NE
NE
NE
NE
Sediment toxicity
0
0
0
0
NE
NE
NE
NE
0
0
0
NE = No evidence
A Sediment toxicity laboratory results include individual metal concentrations found in the sediment samples; however, given lack of S-R information relevant to this type of data and given that the species
survivorship information does not indicate support for this cause, we do not break this column down by individual contaminants found in sediment samples.
-------
SOE Table 49. Water column metal observations study comparison - Low flow
South Portland
Study
Metal
Copper, ppm
Lead, ppm
Zinc, ppm
Engineering
LCD
0.008
0.005
0.025
RBO
0.005
<0.001
0.025
LCN .585
<0.002
<0.003
0.015
LCM .595
<0.002
<0.003
<0.005
MEDEP
LCMn2.274
0.002
<0.003
0.005
LCS .186
0.002
<0.003
0.007
RB 1.694
<0.002
<0.003
0.009
Adapted from MEDEP (2002a) Table 4.1b.
-------
SOE Table 50. Water column metal observations study comparison - Stormflow
South Portland
Study Engineering MEDEP
Metal
Copper, ppm
Lead, ppm
Zinc, ppm
LCD
Aug-94
0.007
0.003
0.05
RBO
Aug-94
0.008
0.009
0.07
LCN
Mar-00
0.018
0.031
0.14
.585
Sep-01
0.013
0.015
0.12
LCM
Mar-00
0.021
0.052
0.2
.595
Sep-01
0.015
0.025
0.11
LCS
Mar-00
0.044
0.9
0.27
.186
Sep-01
0.007
0.007
0.062
RB1
Mar-00
<0.002
0.003
0.024
.694
Sep-01
0.003
0.004
0.023
Adapted from MEDEP (2002a) Table 4.1b.
OJ
oo
-------
APPENDICES
-------
APPENDIX A
HISTORIC MAPS
Figure A-l. 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.
3&^*&\ \$%z^>3/(y?%
fcfM \ j*r£%&z&rt"~$&.
r t1 j i-t.y •'.
sj \t
c - -, -. i - . . - -- •• ••
w ^i$f
V x^/. -- ^>4^^^^ \ ^ri^e^rTT^^
-
L^ C!*a
Figure A-4. Current USGS map - circa 1980s.
Dashed line is approximate location of superimposed case study watershed boundaries.
A-2
-------
** ' -1940
April, 2001'
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://ianus.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:
All copyrights and other rights to statutory text are reserved by the State of Maine. The text included in this publication
is current to the end of the 121st Legislature, which ended December 1, 2004, but is subject to change without notice. It is a
version that has not been officially certified by the Secretary of State. Refer to the Maine Revised Statutes Annotated and
supplements for certified text.
The Office of the Revisor of Statutes also requests that you send us one copy of any statutory publication you may
produce. Our goal is not to restrict publishing activity, but to keep track of who is publishing what, to identify any needless
duplication and to preserve the State's copyright rights.
PLEASE NOTE: The Reviser's Office cannot provide legal advice or
interpretation of Maine law. If you need such legal assistance, please contact a qualified
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
-------
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).
B-4
-------
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).
o
Class Order
Non-Insects:
Arachnida Acari
Arachnida Acari
Arachnida Acari
Crustacea Amphipoda
Crustacea Amphipoda
Crustacea Amphipoda
Crustacea Cladocera
Crustacea Isopoda
Gastropoda
Gastropoda Limnophila
Gastropoda Limnophila
Gastropoda Limnophila
Gastropoda Limnophila
Gastropoda Limnophila
Gastropoda Mesogastropoda
Gastropoda Mollusca
Gastropoda Basommatophora
Hirudinea Arhynchobdellida
Hirudinea Arhynchobdellida
Hirudinea Rhynchobdellida
Hirudinea Rhynchobdellida
Hirudinea Rhynchobdellida
Hirudinea Rhynchobdellida
Hydrozoa Hydroida
Oligochaeta Lumbriculida
Oligochaeta Lumbriculida
Oligochaeta Lumbriculida
Family
Hydrachnidae
Hygrobatidae
Lebertiidae
Crangonyctidae
Hyalellidae
Asellidae
Ancylidae
Physidae
Physidae
Physidae
Planorbidae
Valvatidae
Planorbidae
Planorbidae
Erpobdellidae
Erpobdellidae
Glossiphoniidae
Glossiphoniidae
Glossiphoniidae
Lumbricidae
Lumbriculidae
Lumbriculidae
Genus
Hygrobates
Ferhssia
Crangonyx
Hyalella
Caecidotea
Ferhssia
Physa
Physella
Valvata
Gyraulus
Helisoma
Erpobdella
Rhynchobdellida
Glossiphonia
Helobdella
Placobdella
Stylodhlus
Reference
site
RB
3.961
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
0
4
0
Impaired
LCN
.415
0
0
0
0
1
38
0
0
0
0
0
21
1
0
0
0
0
0
0
0
4
0
0
0
0
0
0
sites
LCM LCMn
2.270 2.274
0
0
0
8
0
16
0
52
0
0
0
0
0
0
0
0
0
0
0
1
1
26
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
Other
LCS
.369
0
0
0
0
0
60
0
0
7
0
0
10
0
0
0
8
3
1
0
0
0
0
0
0
0
0
3
Long
LCM
.380
0
0
0
0
73
23
0
1
0
5
0
0
0
0
0
0
0
0
1
7
0
0
0
2
0
2
0
Creek & Red
LCM
.910
0
0
4
0
52
65
7
30
0
0
1
0
0
1
4
0
0
0
2
0
6
5
1
2
0
0
0
Brook
RB
071
2
1
0
0
0
0
0
0
0
1
0
0
1
1
2
0
0
0
0
0
0
0
0
0
0
0
0
sites
RB
1.474
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
-------
o
Class
Oligochaeta
Oligochaeta
Oligochaeta
Oligochaeta
Pelecypoda
Pelecypoda
Pelecypoda
Order
Tubificida
Tubificida
Tubificida
Tubificida
Veneroida
Veneroida
Veneroida
Family Genus
Enchytraeidae
Naididae Chaetogaster
Tubificidae Limnodrilus
Tubificidae
Sphaeriidae Pisidium
Sphaeriidae
Sphaeriidae Sphaerium
Non-insect sub-total:
Insects:
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Coleoptera
Collembola
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Dytiscidae Deronectes
Dytiscidae Dytiscus
Elmidae Ancyronyx
Elmidae Dubiraphia
Elmidae
Elmidae Macronychus
Elmidae Optioservus
Elmidae Oulimnius
Elmidae Promoresia
Elmidae Stenelmis
Haliplidae Haliplus
Psephenidae Ectopha
Ceratopogonidae Bezzia/Palpomyia
Ceratopogonidae Culicoides
Chironomidae Ablabesmyia
Chironomidae Apsectrotanypus
Chironomidae Brundiniella
Chironomidae Chironomus
Chironomidae Clinotanypus
Chironomidae Conchapelopia
Chironomidae Cricotopus
Chironomidae Cryptochironomus
Chironomidae Cryptotendipes
Chironomidae Dicrotendipes
Chironomidae Heterothssocladius
Chironomidae Hudsonimyia
Reference
site
RB
3.961
0
2
0
0
14
3
0
28
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
3
0
0
3
0
0
0
0
2
0
Impaired sites
LCN
.415
1
0
0
0
1
0
0
67
0
0
0
0
0
1
0
0
1
0
0
2
0
0
0
0
4
0
0
0
0
0
0
0
0
2
0
0
LCM
2.270
0
0
3
19
0
0
58
185
0
0
0
478
0
0
0
0
0
16
0
0
0
0
0
1
1
0
0
2
104
0
0
0
0
10
0
0
LCMn
2.274
0
0
0
0
0
0
0
4
0
1
0
175
0
0
1
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
0
0
2
0
0
Other
LCS
.369
0
0
0
8
18
3
0
121
2
0
0
1
0
0
0
0
2
0
0
0
1
2
1
0
28
0
0
15
0
1
0
3
0
2
0
0
Long
LCM
.380
0
0
0
0
0
0
0
114
3
0
0
32
0
2
0
1
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
Creek & Red
LCM
.910
0
0
0
0
0
0
14
194
0
0
2
111
0
0
37
0
0
9
1
0
0
0
0
0
0
0
0
0
0
0
3
0
0
1
0
0
Brook
RB
071
0
0
0
0
0
0
0
8
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
0
1
0
0
0
sites
RB
1.474
0
0
0
0
0
0
0
2
0
0
0
15
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
o
Class
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Order
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Diptera
Family
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Chironomidae
Culicidae
Empididae
Empididae
Tabanidae
Tabanidae
Tipulidae
Tipulidae
Tipulidae
Genus
Kiefferulus
Labrundinia
Macropelopia
Meropelopia
Micropsectra
Microtendipes
Natarsia
Parachironomus
Parakiefferiella
Paralauterborniella
Paramerina
Parametriocnemus
Phaenopsectra
Polypedilum
Procladius
Psectrotanypus
Rheotanytarsus
Stempellina
Stempellinella
Tanytarsus
Thienemanniella
Thienemannimyia
Trissopelopia
Xylotopus
Zavrelia
Zavrelimyia
Nanocladius
Orthocladius
Paratanytarsus
Paratendipes
Anopheles
Hemerodromia
Chrysops
Limnophila
Pilaria
Pseudolimnophila
Reference
site
RB
3.961
0
1
18
2
27
0
1
0
2
4
3
6
0
13
8
0
3
0
26
42
0
3
2
0
0
9
0
0
0
0
0
1
0
3
0
0
1
1
Impaired sites
LCN
.415
0
1
0
0
5
0
3
0
0
0
6
0
1
0
29
1
0
0
0
0
9
0
0
0
0
2
0
0
0
0
0
0
0
2
0
0
0
0
LCM
2.270
0
0
0
0
0
37
11
0
0
0
1
0
0
1
21
0
0
10
0
23
0
5
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
LCMn
2.274
0
0
0
0
0
22
0
0
0
0
2
0
0
0
14
0
0
0
0
5
2
0
0
0
1
1
0
0
0
0
1
0
0
0
0
0
0
0
Other
LCS
.369
0
0
0
0
0
0
34
0
0
0
0
1
20
31
3
0
0
0
0
18
1
12
0
1
0
0
1
5
7
1
0
0
1
6
0
0
0
0
Long
LCM
.380
2
0
0
0
0
0
3
1
0
0
4
0
0
0
0
0
8
21
14
5
0
32
0
0
0
0
0
0
0
0
0
0
0
2
53
0
0
0
Creek & Red
LCM
.910
0
0
0
0
0
1
0
0
0
0
1
0
0
3
0
0
0
2
0
122
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
Brook sites
RB RB
071 1.474
0 0
0 0
0 0
0 0
0 0
9 7
1 0
0 0
0 0
0 0
1 0
0 1
0 2
1 1
1 1
0 0
5 1
0 0
7 4
30 4
0 0
0 4
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 1
0 0
0 0
-------
o
Class
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Order
Diptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Ephemeroptera
Hemiptera
Hemiptera
Hemiptera
Megaloptera
Megaloptera
Odonata
Odonata
Odonata
Odonata
Odonata
Odonata
Odonata
Odonata
Odonata
Odonata
Odonata
Plecoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Family Genus
Tipulidae Tipula
Baetidae Acerpenna
Baetidae
Baetidae Cloeon
Caenidae Caenis
Ephemerellidae Eurylophella
Heptageniidae Heptageniidae
Heptageniidae Stenonema
Leptophlebiidae
Leptophlebiidae Paraleptophlebia
Gerridae Gerris
Veliidae Microvelia
Veliidae Veliidae
Corydalidae Nigronia
Sialidae S/a//s
Aeshnidae Aeshna
Aeshnidae
Aeshnidae Boyeria
Calopterygidae
Calopterygidae Calopteryx
Coenagrionidae Argia
Coenagrionidae
Coenagrionidae Enallagma
Cordulegastridae Cordulegaster
Gomphidae Lanthus
Libellulidae Sympetrum
Leuctridae Leuctra
Calamoceratidae Heteroplectron
Dipseudopsidae Phylocentropus
Hydropsychidae Cheumatopsyche
Hydropsychidae Diplectrona
Hydropsychidae Hydropsyche
Hydroptilidae Oxyethira
Leptoceridae
Leptoceridae Mystacides
Leptoceridae Oecetis
Limnephilidae Glyphopsyche
Limnephilidae
Limnephilidae Limnephilus
Reference
site
RB
3.961
1
1
0
0
0
0
1
8
6
12
0
0
0
1
46
0
0
3
7
0
0
0
0
5
1
0
3
1
1
0
1
2
0
0
0
0
0
0
3
Impaired sites
LCN
.415
0
0
1
0
3
0
0
0
0
0
0
3
0
5
0
3
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
9
0
0
0
12
LCM
2.270
0
0
9
0
190
0
0
0
0
0
0
0
0
0
8
0
0
0
0
1
1
3
0
0
0
0
0
0
7
0
0
0
0
1
0
20
0
1
0
LCMn
2.274
0
0
1
2
26
0
0
0
0
0
1
0
0
0
2
0
4
4
0
0
0
0
0
0
0
1
0
0
2
0
0
0
0
0
0
5
0
0
5
Other
LCS
.369
0
0
0
0
43
0
0
0
0
0
0
0
0
0
29
5
0
1
0
0
13
0
0
0
0
0
0
0
16
0
0
1
0
0
0
1
0
0
1
Long
LCM
.380
3
0
0
0
62
0
0
0
0
0
0
0
0
2
11
7
0
1
0
4
0
0
2
0
0
0
0
0
4
0
0
0
0
0
11
1
1
0
0
Creek & Red
LCM
.910
0
0
1
2
67
0
0
0
0
0
0
0
0
1
0
0
4
2
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
9
3
0
0
0
Brook
RB
071
0
0
4
0
1
4
0
0
0
57
0
0
0
2
2
0
0
2
3
1
0
0
0
0
0
0
0
0
3
0
0
0
2
0
40
0
0
0
0
sites
RB
1.474
0
0
1
0
0
0
0
2
0
10
0
0
0
12
6
0
0
0
0
7
0
0
0
0
0
0
0
0
7
2
0
0
0
0
0
1
0
0
2
-------
o
Class
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Insecta
Order
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Trichoptera
Family Genus
Limnephilidae Psychoglypha
Limnephilidae Pycnopsyche
Molannidae Molanna
Odontoceridae Psilotreta
Phryganeidae Oligostomis
Phryganeidae
Phryganeidae Ptilostomis
Polycentropodidae
Polycentropodidae Polycentropus
Psychomyiidae Lype
Insect sub-total:
Total mean
Total (non-insects + insects):
abundance (total / 3 samples):
% non insects:
Reference
site
RB
3.961
5
6
0
27
5
0
0
0
0
0
333
361
120.3
7.8%
Impaired sites
LCN
.415
0
0
0
0
0
0
14
1
0
0
121
188
62.7
35.6%
LCM
2.270
0
0
3
0
0
0
1
0
0
0
972
1157
385.7
16.0%
LCMn
2.274
0
0
0
0
0
0
3
0
0
0
287
291
97.0
1.4%
Other
LCS
.369
0
0
0
0
0
1
0
0
0
0
311
432
144.0
28.0%
Long Creek & Red Brook
LCM
.380
0
0
0
16
0
0
3
0
0
0
314
428
142.7
26.6%
LCM
.910
0
0
1
0
0
0
2
0
0
0
388
582
194.0
33.3%
RB
.071
0
0
0
0
0
0
0
0
6
2
191
199
66.3
4.0%
sites
RB
1.474
0
0
1
0
0
0
3
0
0
0
96
98
32.7
2.0%
-------
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).
1 Total Mean Abundance
Count all individuals in all replicate samples from one site and divide by the
number of replicates to yield mean number of individuals per sample.
2 Generic Richness
Count the number of different genera found in all replicates from one site.
Counting rules for Generic Richness:
a) All population counts at the species level will be aggregated to the generic
level.
b) A family level identification which includes no more than one taxon
identified to the generic level is counted as a separate taxon in generic
richness counts.
c) A family level identification with more than one taxon identified to generic
level is not counted towards generic richness. Counts are to be divided
proportionately among the genera that are present.
d) Higher level taxonomic identifications (Phylum, Class, Order) are not
counted toward generic richness unless they are the only representative.
e) Pupae are ignored in all calculations.
3 Plecoptera Mean Abundance
Count all individuals from the order Plecoptera in all replicate samplers from
one site and divide by the number of replicates to yield mean number of
Plecopteran individuals per sampler.
D-l
-------
Ephemeroptera Mean Abundance
Count all individuals from the order Ephemeroptera in all replicate samplers
from one site and divide by the number of replicates to yield mean number of
Ephemeropteran individuals per sampler.
Shannon-Wiener Generic Diversity (Shannon and Weaver, 1963)
After adjusting all counts to genus following counting rules in Variable 2:
d = -(Nlog10N-£n log,0 n )
where: d = Shannon-Wiener Diversity
c = 3.321928 (converts base 10 log to base 2)
N = Total abundance of individuals
n, = Total abundance of individuals in the ith taxon
Hilsenhoff Biotic Index (Hilsenhoff, 1987)
V —
^ N
where: HBI = Hilsenhoff Biotic Index
n, = number of individuals in the ith taxon
a, = tolerance value assigned to that taxon
N = total number of individuals in sample with tolerance values,
Relative Chironomidae Abundance
Calculate the mean number of individuals of the family Chironomidae,
following counting rules in Variable 4, and divide by total mean abundance
(Variable 1).
Relative Diptera Richness
Count the number of different genera from the Order Diptera, following
counting rules in Variable 2, and divide by generic richness (Variable 2).
Hydropsyche Mean Abundance
Count all individuals from the genus Hydropsyche in all replicate samplers
from one site, and divide by the number of replicates to yield mean number of
Hydropsyche individuals per sampler.
D-2
-------
10 Probability (A + B + C) from First Stage Model
Sum of probabilities for Classes A, B, and C from First Stage Model.
11 Cheumatopsyche Mean Abundance
Count all individuals from the genus Cheumatopsyche in all replicate
samplers from one site and divide by the number of replicates to yield mean
number of Cheumatopsyche individuals per sampler.
12 EPT - Diptera Richness Ratio
EPT Generic Richness (Variable 19) divided by the number of genera from
the order Diptera, following counting rules in Variable 2. If the number of
genera of Diptera in the sample is 0. a value of 1 is assigned to the
denominator.
13 Relative Oligochaeta Abundance
Calculate the mean number of individuals from the Order Oligochaeta,
following counting rules in Variable 4, and divide by total mean abundance
(Variable 1).
14 Probability (A + B) from First Stage Model
Sum of probabilities for Classes A and B from First Stage Model.
15 Perlidae Mean Abundance f Family Functional Group)
Count all individuals from the family Perlidae (Appendix C-3) in all replicate
samplers from one site and divide by the number of replicates to yield mean
number of Perlidae per sampler.
16 Tanypodinae Mean Abundance (Family Functional Group)
Count all individuals from the subfamily Tanypodinae (Appendix C-3) in all
replicate samplers from one site and divide by the number of replicates to
yield mean number of Tanypodinae per sampler.
17 Chlronomini Mean Abundance {Family Functional Group)
Count all individuals from the tribe Chironomini (Appendix C-3) in all replicate
samplers from one site and divide by the number of replicates to yield mean
number of Chironomini per sampler
D-3
-------
18 Relative Ephemeroptera Abundance
Variable 4 divided by Variable 1.
19 EPT Generic Richness
Count the number of different genera from the Order Ephemeroptera (E),
Plecoptera (P), and Trichoptera (T) in all replicate samplers, according to
counting rules in Variable 2, generic richness,
20 Variable Reserved
21 Sum of Mean Abundances of: Dicrotendipes, Micropsectra,
Parachironomus and HeSobdeila
Sum the abundance of the 4 genera and divide by the number of replicates (as
performed in Variable 4).
22 Probability of Class A from First Stage Model
Probability of Class A from First Stage Model.
23 Relative Piecoptera Richness
Count number of genera of Order Plecoptera, following counting rules in
Variable 2, and divide by generic richness (Variable 2).
24 Variable Reserved
25 Sum of Mean Abundances of Cheumatopsyche, Cricotopus, Tanytarsus
and Ablabesmyia
Sum the number of individuals in each genus in all replicate samplers and
divide by the number of replicates (as performed in Variable 4).
26 Sum of Mean Abundances of Acroneuria and Stenonema
Sum the number of individuals in each genus in all replicate samplers and
divide by the number of replicates (as performed in Variable 4).
27 Variable Reserved
D-4
-------
28 Ratio of EP Generic Richness
Count the number of different genera from the order Ephemeroptera (E), and
Plecoptera (P) in all replicate samplers, following counting rules in Variable 2,
and divide by 14 {maximum expected for Class A).
29 Variable Reserved
30 Ratio of Class A Indicator Taxa
Count the number of Class A indicator taxa as listed in Appendix C-2 that are
present in the community and divide by 7 (total possible number).
D-5
-------
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-l 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-l - 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 etal, 1997).
12 Ha, or Stream alluvium, consists of silt, sand, and gravel, comprising modern flood plains (Thompson et al.,
1997).
E-l
-------
graphically display information from Table C-l. 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.
E-2
-------
Table E-1. Regional reference and case study LDF model data
— 0)
•1 1
8. 1
Study site
Sf 1
o I «
0)
fl
1 2
"I
1
ofl
0) 0)
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= S
5 m
1
RB 3.961
LCN .415
LCM 2.270
LCMn 2.274
LCS .369
LCM .380
LCM .910
RB .071
RB 1.474
0)
re
~
re
>
o
E
LL
Q
5th %
25th %
50th %
75th %
95th %
Geology
Pmrs
Pp
Pp
Pp
Pmrs
Pp
Pp
Ha
Pmrs
QJ
1
TO
QJ
5
2
^
01
101.6
165.2
280.0
527.2
1354.2
121.0
62.7
386.0
97.0
144.3
143.0
194.0
66.3
33.0
QJ
."
£
C
QJ
U
02
23.6
44.0
56.0
68.0
74.9
54.0
32.0
36.0
27.0
44.0
40.0
38.0
31.0
26.0
QJ
1
C
|
S
TO
QJ
Q.
0
QJ
a
03
0.7
1.0
4.7
11.3
37.9
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
c
co
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c
co
QJ
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5.4
14.3
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23.3
22.0
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3.69
4.2
4.68
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2.49
4.52
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3.61
3.53
4.11
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3.14
3.80
4.3
4.70
5.32
4.22
6.64
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4.01
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0.27
0.40
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0.48
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0.2
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421.8
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0.0
0.0
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0.0
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fi
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0.36
0.51
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0.56
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=:
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QJ
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15
0.00
0.00
0.0
0.00
1.20
0.00
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0.0
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11.1
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39.6
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25.9
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2.3
1.7
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^
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0.0
2.2
5.0
14.4
27.5
15.3
47.7
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7.0
0.3
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^
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7.0
11.2
18.5
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=:
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0.0
5.7
27.5
68.4
180.5
5.6
1.0
16.9
8.0
24.2
3.7
1.7
3.7
3.5
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0.06
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0.19
0.24
0.08
0.02
0.17
0.10
0.10
0.14
0.12
0.33
0.13
tri
QJ
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19
11.0
13.5
19.0
22.5
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6.0
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9.0
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52 -32
p ^C
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0.03
0.03
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I
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a
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S £
-C .Q
O .co
o
-------
01 Total Mean Abundance
1600-1
1400-
1200
1000 -
800
600
400-
200
0-
— — —
||
P
Reg
Ref
— —
—
RB
3.961
— — —
LCS
.369
— — —
^^m
LCN
.415
— — —
LCM
.380
_____
—
LCM
.910
— — —
^_
LCMn
2.274
— — —
LCM
2.270
———————
^^m ^^^
RB RB
.071 1.474
120 •j^^^^^^^^^^^^^^^^-^^^^^^^^^^^^^^^^n
100
80
60
40
20
0
^~
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
W
80
70
60
50
40
30
20
10
0
02 Generic Richness
Reg
Ref
RB
3.961
LCS
.369
LCN
.415
LCM
.380
LCM
.910
LCMn LCM
2.274 2.270
RB
.071
RB
1.474
5 -
4 -
3
2
1 -
05 Shannon-Wiener Generic Diversity
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
03 Plecoptera Mean Abundance
40 -,
35 -
30 -
25 -
20 -
15 -
10 -
5 -
0 -
••
1
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
06 Hilsenhoff Biotic Index (HBI)
7 -
6
5 -
4 -
3
2
1 -
0 --
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
-------
07 Relative Chironomidae Abundance
08 Relative Diptera Richness
u.ou -
0.70 -
0.60-
0.50 -
0.40-
0.30
0.20
0.10 -
n on
u.uu -
|
^^^B ^^^^
^^H ^^^
. ^^^1 ^^^*
^^^1 ^^^_
1 ^^M ^^^
— ^— ^_ ^« ^~
\J. I\J ~
0.60 -
0.50 -
0.40-
0.30
0.20
0.10-
n nn
' r r r r 1 r r r r * \s.\s\s
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
^L ^_ ^_
^^^B
^^^ ^^^ ^^^ ^^^ ^^^
1 ^^^" ^^^^
^^^^ ^^^^
^^™
^^
1 1 1 1 1 1 1 1 1
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474 Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
07 Relative Chironomidae Abundance (Pp only)
09 Hydropsyche Mean Abundance
W
0.60 -
0.50 -
0.40 -
0.30
0.20
0.10 -
0.00 -
Reg RB
Ref 3.961
LCS LCN LCM LCM LCMn LCM RB RB
.369 .415 .380 .910 2.274 2.270 .071 1.474
400
350
300
250
200
150
100
50
.
ll
Reg RB
Ref 3.961
LCS LCN LCM LCM LCMn LCM RB RB
.369 .415 .380 .910 2.274 2.270 .071 1.474
07 Relative Chironomidae Abundance (Pmrs only)
09 Hydropsyche Mean Abundance (Pp only)
0.70 -
0.60 -
0.50 -
0.40 -
0.30
0.20
0.10 -
0 00
_
1
^^m
^P ^~
-^^ ^~
^^^^
\ \ \ 1 \ \ \ \ \
bUU -
500
400
300
200
100
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
-
^
•
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474 Ref 3 961 36g 415 380 910 2 274 2 27Q Q71 -, 474
-------
W
20
15 --
10 -
5 --
09 Hydropsyche Mean Abundance (Pmrs)
13 Relative Oligochaeta Abundance
Reg
Ref
80 j-
70 --
60-
50-
40-
30-
20-
10-
0
Reg
Ref
2.50
0.00
RB LCS LCN LCM LCM LCMn LCM RB RB
3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
1 1 Cheumatopsyche Mean Abundance
RB LCS LCN LCM LCM LCMn LCM
3.961 .369 .415 .380 .910 2.274 2.270
12 EPT - Diptera Richness Ratio
RB
.071
RB
1.474
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
0.03 -
0.03 -
0.02 -
0.02 -
0.01 -
0.01 -
0.00 -
1.40-
1.20-
1.00 -
0.80-
0.60 -
0.40-
0.20
0.00-
60-
50
40
30
20
10
0 -
^
^— ^—
J
R£
Rt
1
;g RB LCS LCN LCM LCM LCMn LCM RB RB
=f 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
15 Perlidae Mean Abundance
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
16 Tanypodinae Mean Abundance
_
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
-------
16 Tanypodinae Mean Abundance (Pponly)
50 -
40 -
30 -
20 -
10 -
n
^^^^^ i i i i
Reg RB LCS LCN LCM
Ref 3.961 .369 .415 .380
^^^^^ I I I I
LCM LCMn LCM RB RB
.910 2.274 2.270 .071 1.474
0.35
18 Relative Ephemeroptera Abundance
w
16 Tanypodinae Mean Abundance (Pmrs only)
19 EPT Generic Richness
50
40
30
20
10
-
-
• __
H
^ —
^^m
25
20
15
10
5
n
•
1 —
^~ ^™ ^~ ^~ ^~
1 1 1 1 1 1 1 1 [ \ " i i i i i i i i i
Reg RB LCS LCN LCM LCM LCMn LCM RB RB Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474 Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
17 Chironomini Mean Abundance
£-\J\J
180 -
160
140 -
120
100 -
80
60
40
20
-
_
||
•
m — —
Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
21 Sum of Mean Abundances of Dicrotendipes,
Micropsectra, Parachironomus, & Helobdella
LCN
.415
LCM
.380
LCM
.910
LCMn
2.274
LCM
2.270
RB
.071
RB
1.474
-------
28 Ratio of EP Generic Richness
W
oo
0.09 -
0.08
0.07 -
0.06
0.05
0.04 -
0.03
0.02
0.01 -
+
^™
r
I .UU
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
n nn
I
^^i
J _
^^_
^^ ^^ ^^
ii i i i i i ii
Reg RB LCS LCN LCM LCM LCMn LCM RB RB Reg RB LCS LCN LCM LCM LCMn LCM RB RB
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474 Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
25 Sum of Mean Abundances Cheumatopsyche,
Cricotopus, Tanytarsus, & Ablabesmyia
30 Ratio of Class A Indicator Taxa
80
70
60
50
40
30
20
10 -
I
^^^B
Req RB LCS LCN LCM LCM LCMn LCM RB RB
0.45 -
0.40 -
0.35 -
0.30
0.25
0.20
0.15 -
0.10 -
005
0.00 -
^
B
^~ ^~
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474 Re9 ^ LCS LCN LCM LCM LCMn LCM m m
Ref 3.961 .369 .415 .380 .910 2.274 2.270 .071 1.474
26 Sum of Mean Abundances of Acroneuria & Stenonema
LCN
.415
LCM
.380
LCM
.910
LCMn
2.274
LCM
2.270
RB
.071
RB
1.474
Tricoptera Richness
-------
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-l
-------
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, 200 Ib). 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 (Backstrom 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 non-
insect 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
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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; Earth, 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
-------
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.
F-10
-------
APPENDIX G
MEASURED VARIABLES
Measured
Variable
aquatic
vegetation
baseflow
discharge
baseflow thalweg
velocity
canopy shade
chlorophyll a
large woody
debris count
muck mud
Pfankuch rating
percent
impervious
surface
Source
Citation Location
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
MEDEP,
2002a
Table 3.6. 3
Figure 3. 5. 10
Table 3.6.1
Table 3.6. 4
Figure 3. 2.1
Table 3.6. 9
Table 3.6. 4
Table 3. 7. 2
Table 3. 1.2
Applicable
Sites Description & Comments
LCN .415
LCM 2.270 dominant aquatic vegetation estimated visually as a percent of the reach in the
LCMn 2.274 vicinity of the site; observations made by MEDEP from 9/22/1999 to 9/26/1999
RB3.961
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
thalweg baseflow velocities taken at 2m intervals for 200m stretch of the reach in the
RR 3 961 vicinity °f the site; MEDEP estimated velocity by observing floating organic debris
during low flow or baseflow conditions 8/5/1 999 - 8/6/1 999
LCN .41 5 canopy shade was quantified as an average percent based on three visual estimates
LCM 2.270 of riparian zone condition-taken upstream, downstream, & mid-stream-in the vicinity
LCMn 2.274 of biological monitoring rockbag sample locations; observations made by MEDEP
RB 3.961 from 9/22/1 999 to 9/26/1 999
chlorophyll a measurements taken at surrogate sites LCN .585, LCMn 2.714, & RB
, ™« o4^, 2.790; these apply to sites LCN .415, LCMn 2.274, & RB 3.961, respectively;
LCMn 2 274
RB 3 961 surrogate sites represent open-canopy sections of the streams; MEDEP collected
data in June & July, 2000
LCM 2.270 woody debris pieces, categorized as above 5 cm and 10 cm in diameter, were
LCMn 2.274 counted for stream sites; surrogate site RB 3.500 was used to represent RB 3.961 ;
RB 3.961 MEDEP collected data between 11/19/2002 & 12/6/2002
LCN .415 muck mud (defjnec| as black, very fine organic, FPOM) was quantified as a percent of
? 974 the total orgar|ic substrate components at the site based on visual estimation;
RB3 961 observations made by MEDEP from 9/22/1999 to 9/26/1999
LCN .415
LCM 2.270 surrogate site LCN .404 was used to represent LCN .415; MEDEP collected data
LCMn 2.274 between 10/19/2000 & 11/3/2000
RB3.961
LCN .415
LCM 2.270 MEDEP estimated percent impervious surface using USGS topographic maps (circa
LCMn 2.274 1970's & 1980's) and 1995 aerial photographs
RB3.961
-------
o
to
Measured
Variable
Rapid
Bioassessment
Protocol (RBP)
scores
sediment
chemistry, 1 993
sediment
chemistry, 2003
sediment size
sediment toxicity,
2003
stormflow event,
1994
stormflow event,
2001
temperature:
weekly minimum,
maximum, &
mean
water chemistry,
1992(baseflow)
Source
Citation
MEDEP,
2002a
South
Portland
Engineering
Dept, 1994
U.S. EPA,
2004a
MEDEP,
2002a
US EPA,
2004a
South
Portland
Engineering
Dept, 1 994
MEDEP staff,
2005
MEDEP staff,
2005
South
Portland
Engineering
Dept, 1994
Location
Table 3.6. 8
Appendix C
laboratory
report
Appendix G
toxicity study
report text &
Appendix F
received as
spreadsheet
received as
spreadsheet
Appendix A
Applicable
Sites
LCN .415
LCM2.270
LCMn 2.274
RB3.961
NA
LCN .415
LCMn 2.274
RB3.961
LCN .415
LCMn 2.274
RB3.961
LCN .415
LCMn 2.274
RB3.961
NA
LCN .415
RB 3.961
LCN .415
LCM2.270
LCMn 2.274
RB3.961
NA
Description & Comments
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 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 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
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
2000
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
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
storm hydrograph produced by MEDEP for 9/25/2001 event; surrogate site RB 1 .694
was used to represent 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, & 8/21/1 999; RB 3.961, LCM 2.270, & LCMn 2.274 include 1 week of
simultaneous measurements ending 8/21/1999; all measurements made by MEDEP
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
-------
o
OJ
Measured
Variable
water chemistry,
1 994 (stormflow)
water chemistry,
2000 & 2001
(stormflow)
water chemistry,
2000 (baseflow)
water chemistry,
PAHs, 2000
(stormflow)
water chemistry,
PAHs, 2001
(stormflow)
water chemistry,
2003 (low flow)
water quality,
2000 (baseflow)
Source
Citation
South
Portland
Engineering
Dept, 1 994
MEDEP,
2002a
MEDEP,
2002a
U.S. EPA,
2000a
U.S. EPA,
2001
U.S. EPA,
2004a
MEDEP,
2002a
Location
Appendix E
Appendix C,
Tables 1a -
1c
Appendix C,
Tables 2a -
2c
laboratory
report
laboratory
report
laboratory
report
Appendix C,
Tables 3a &
3b
Applicable
Sites
NA
LCN .415
RB 3.961
LCN .415
LCM2.270
LCMn 2.274
RB3.961
LCN .415
RB3.961
LCN .415
RB3.961
LCN .415
LCMn 2.274
RB3.961
LCN .415
LCM2.270
LCMn 2.274
RB3.961
Description & Comments
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--!. e., this data was used to generalize differences
between the two study watersheds
stormflow sampling for cadmium, copper, lead, nickel, zinc, total phosphorous, ortho-
phosphorous, 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
baseflow sampling for cadmium, copper, lead, nickel, zinc, total phosphorous, ortho-
phosphorous, 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
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
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
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
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
-------
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-l 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-l 1 D50 substrate particle size
Figure H-12 Pfankuch bank stability
Figure H-l3 Temperature, weekly minimum
Figure H-l4 Temperature, weekly maximum HBI
Figure H-15 Temperature, weekly mean
Figure H-16 Canopy shade
Figure H-17 Zinc
Figure H-l8 Chloride EPT richness, % non-insects, HBI
Figure H-l9 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
H-l
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Figure H-l. 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
ffi
to
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Figure H-2. Nitrate + nitrite, mg/L
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1
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Figure H-3. Total phosphorus, 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
ffi
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0.002 0.004 0.006 0.008
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0.002 0.004 0.006 0.008
Figure H-4. Ortho phosphorus, mg/L
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(S)
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1 1 1 1 1 1 1 1 1 1 1 1 CO | | | | | |
20 22 24 26 28 30 20 22 24 26 28 30 20 22 24 26 28 30
Figure H-5. Aquatic vegetation, % of local reach (including diatoms)
A LCS .369
B LCM .380
C LCM .910
Study Site Key
D LCM 2.270
E LCMn 2.274
F LCN .415
G RB .071
H RB 1.474
I RB 3.961
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in
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0 5 10 15 20 25 30 05 10 15 20 25 30 05 10 15 20 25 30
Figure H-6. Aquatic vegetation, % of local reach (macroalgae & macrophytes only)
-------
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(S)
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Figure H-7. Dissolved oxygen saturation, %
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
„. _
| £ -
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Figure H-8. Dissolved oxygen concentration, mg/L
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30 40 50 60 70 80 90
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— LT) ~
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1
1 1 1 1 1 1 1
30 40 50 60 70 80 90
Figure H-9. Large woody debris, # of pieces with diameter > 5 cm
A LCS .369
B LCM .380
C LCM .910
Study Site Key
D LCM 2.270
E LCMn 2.274
F LCN .415
G RB .071
H RB 1.474
I RB 3.961
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10 15 20 25 30 35 40
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Figure H-10. Large woody debris, # of pieces with diameter > 10 cm
-------
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(S) r\\
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05 0.15 0.25
Figure H-ll. D50 substrate particle size, mm
Study Site Key
A LCS .369 D LCM 2.270 G RB .071
B LCM .380 E LCMn 2.274 H RB 1.474
•3- _
§ £ -
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B F A
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F LCN.415 I RB 3.961
n i r
95 100 105 110
n i i r
95 100 105 110
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95 100 105 110
Figure H-12. Pfankuch bank stability score
-------
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13 14 15 16 17 13 14 15 16 17 13 14 15 16 17
Figure H-13. Temperature, weekly minimum, C°
Study Site Key
A LCS.369 D LCM 2.270
B LCM .380 E LCMn 2.274
C LCM .910 F LCN.415
^
f CM
CD —
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20.5 21.5 22.5 23.5 20.5 21.5 22.5 23.5 | 20.5 21.5 22.5 23.5 |
G RB .071
H RB 1.474
I RB 3.961
Figure H-14. Temperature, weekly maximum, Cc
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1 1 1 1 1 1 1 1 CO 1 1 1 1
17 18 19 20 17 18 19 20 17 18 19 20
Figure H-15. Temperature, weekly mean, Cc
A LCS .369
B LCM .380
C LCM .910
Study Site Key
D LCM 2.270
E LCMn 2.274
F LCN .415
G RB .071
H RB 1.474
I RB 3.961
•3- _
CO
CD ^ -
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1 1 1 1 1 1 1 CO | | | | | | |
80 82 84 86 88 90 92
80 82 84 86 88 90 92
80 82 84 86 88 90 92
Figure H-16. Canopy shade, % cover
-------
1
G H
D
C E
R A F
1 1 1 1 1 1
0.004 0.008 0.012
8-
8
c o _
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0.004 0.008 0.012
Figure H-17. Zinc, mg/L
in
£ ~ -
c
o
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m co -
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H G
D
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RF A
I I I I
50 100 150 200
-
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£ o _
~ CM
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8? ° -
Fc
B A
D
I
HFG
l l l l
50 100 150 200
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
LO
CO
LO
— LO
CD
LO
LO
CO
A
1
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l l l l
50 100 150 200
Figure H-18. Chloride, mg/L
-------
^J.
CO
CO ~,
CD £! -
C
o
2 o _
1—
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m co -
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1
H G
D
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200 400 600 800 1000
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B A
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200 400 600 800 1000
LO
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— LO
CD
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D B F A
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200 400 600 800 1000
Figure H-19. Specific conductivity, \iS/cm
CO
§ ?! -
o
'OL 0 _
1—
CL
m co -
CD -
1
FG
D
C E
R FA
10 20 30 40
0 _
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
B A
D
1
HG F
1 1 1 1
10 20 30 40
LO
CO
LO
Si
1
LO
LO
CO
C LCM .910
DCB p A
E
1
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a.
i i i i
10 20 30 40
F LCN.415 I RB 3.961
Figure H-20. Impervious surface area, %
-------
o _
I I I
7 8 9 10
H G
D
E
_R F
I T
12
\
14
o _
A
1
7
B
D
1
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l l l l l l l
8 9 10 12 14
CD
I
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7
B R
C K
I
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l l l l l l l
8 9 10 12 14
Figure H-21. RBP epifaunal substrate / available cover
Study Site Key
1
B
D
E C
K F
1 1 1 1 1 1 1
8.0 8.5 9.0 9.5 10.5
i *-
c o _
~ CM
C
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s? ° -
LO —
c
D
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l l l l l l l
3.0 8.5 9.0 9.5 10.5
LO
CD
LO
LO
CD
1
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^
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CO
A LCS .369
B LCM .380
C LCM .910
• c "
1
H
l l l l l l l
8.0 8.5 9.0 9.5 10.5
D LCM 2.270 G RB .071
E LCMn 2.274 H RB 1.474
F LCN.415 I RB 3.961
i
i
i
i
i
i
i
i
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1
i
i
i
Figure H-22. RBP pool substrate characterization
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" Richness
10 12
l i
1 —
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co —
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1
G H
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A R
l l l l l l l
7 8 9 10 11 12 13
—
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C
A B
D
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7 8 9 10 11 12 13
5 ~
LO
IT)
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I
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D A I
H
r:
l l l l l l l
7 8 9 10 11 12 13
Figure H-23. RBP pool variability
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
B
A R F
1 1 1 1
1
D
C E
l l
_
o
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8
£ 0
•=f CM ~~
C
^ 0
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in -
F
C
A
B
D
1
Q
H F
1 1 1 1 1 1
8 10 12 14 16 18
8 10 12 14 16 18
A
l
8
B F D
h C
H
a.
i i i i i
10 12 14 16 18
Figure H-24. RBP sediment deposition
-------
^ _
in
o
2 0 _
CL
co —
CD -
1
1
H G
D
C E
F R A
—
(n
.E CM ~
c
o _
S? ° -
F
B A
D
1
H
LO
ID
LO
CD
z:
LO
LO
F B 6
E
1
H
1 1 1 1 1 1 1 1 1 1 1 1 1 1 CO | | | | | | |
6.0 17.0 18.0 19.0 16.0 17.0 18.0 19.0 16.0 17.0 18.0 19.0
Figure H-25. RBP channel flow Status
Study Site Key
A LCS .369 D LCM 2.270 G RB .071
B LCM .380 E LCMn 2.274 H RB 1.474
in
o
i2 o _
CL
CO —
CD -
I
G H
D
E C
A R F
I I I I I I I
0 _
CO
1
^ o
~ CM ~
C
O _
"!:
F c
A B
D
1
G H
1 1 1 1 1 1 1
LO
LO
m
LO
LO
C LCM .910
E
H
a.
i i i i i i i
F LCN.415 I RB 3.961
14 15 16 17 18 19 20
14 15 16 17 18 19 20
14 15 16 17 18 19 20
Figure H-26. RBP channel alteration
-------
I ^3"
*~
in
§ ~-
i .n
i O
1 2 ° -
CL
| m co -
! CD -
1
G H
D
E C
R F A
J
1 ~
I _
R -
in
$
B o _
~ CM
C
O _
^
^ ° -
in -
F
/\
B
D
1
F G H
LO
CD
—
LO
5
LO
^ ~
~
LO
A
F D
\j
1
H
r.
i 1 1 1 1 1 1 1 1 1 1 00 | | | | |
| 8 10 12 14 16 \ 8 10 12 14 16 8 10 12 14 16
Figure H-27. RBP channel sinuosity
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
in
~,
CD £! -
c
.n
o
2 ° -
CL
1 1 1
m CO -
CD -
1
H G
D
E
RAF
o _
CO
(/)
1
c o
.b CM
C
O _
^
**P o
° "~
LO -
F
B A
D
1
H F
LO
tb
LO
LTJ
CD
LO
^"
~
LO
B A F D
h C
1
H
a.
1 1 1 1 1 1 1 1 1 1 CO | | | | |
56789 56789 56789
Figure H-28. RBP bank stability
-------
<3- _
V)
o
[V O
*~
Q_
CO —
CD -
I
B
D
E C
R A F
O _
CO
1
(/) _
~ CM -
C
O _
^
S? ,_ -
in -
c"
A
B
D
1
p
i
LO
<6
_
LO
m
z:
LO
^"
~
LO
g A
5
E
1
H
r.
1 1 1 1 1 1 1 1 1 1 1 1 1 1 CO | | | | | | |
7.0 7.5 8.0 8.5 9.0 9.5 7.0 7.5 8.0 8.5 9.0 9.5 7.0 7.5 8.0 8.5 9.0 9.5
Figure H-29. RBP bank vegetative protection
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)
.c
o
'OL 0 -
1
CL
m co -
CD -
I
H G
D
C E
FAR
o
CO
*2
"o —
CD
I a-
c
O -
~z.
S? o -
LO —
c F
AB
D
1
G
H
LO
tb ~
LO
iri
CD
z:
LO
•^r
~
LO
D c FAB
1
H
r.
1 1 1 1 1 1 1 1 1 1 1 1 1 1 CO | | | | | | |
456789 10 456789 10 456789 10
Figure H-30. RBP riparian vegetative zone width
-------
Scatter plot statistical correlations
Total Kjeldahl nitrogen
Nitrate + nitrite
Total phosphorus
Ortho phosphorus
Aquatic veg. (including diatoms)
Aquatic veg. (macroalgae/phytes only)
Dissolved oxygen saturation
Dissolved oxygen concentration
LWD with diameter s 5 cm
LWD with diameter > 1 0 cm
D50 substrate particle size
Pfankuch bank stability
Temperature, weekly mean
Temperature, weekly minimum
Temperature, weekly maximum
Canopy shade
Zinc
Chloride
Specific conductivity
Impervious surface area
RBP epifaunal substrate/avail, cover
RBP pool substrate characterization
RBP pool variability
RBP sediment deposition
RBP channel flow status
RBP channel alteration
RBP channel sinuosity
RBP bank stability
RBP bank vegetative protection
RBP riparian vegetative zone width
EPT richness
Pearson's
-0.637
-0.011
-0.627
-0.451
0.000
-0.291
0.671
0.646
0.922
0.915
-0.343
-0.275
-0.532
-0.514
-0.622
0.251
-0.317
-0.658
-0.803
-0.600
0.391
0.481
0.348
0.444
0.149
0.691
0.653
0.532
0.339
0.610
Spearman's
-0.641
-0.030
-0.640
-0.568
0.000
-0.220
0.590
0.564
0.205
0.205
-0.427
0.296
-0.316
-0.162
-0.573
0.325
-0.210
-0.812
-0.864
-0.881
0.487
0.702
0.215
0.566
0.184
0.424
0.870
0.683
0.142
0.365
Kendall's
-0.509
-0.063
-0.607
-0.445
0.000
-0.201
0.449
0.389
0.105
0.105
-0.343
0.276
-0.210
-0.150
-0.449
0.210
-0.164
-0.688
-0.748
-0.748
0.419
0.600
0.167
0.459
0.144
0.349
0.750
0.525
0.141
0.250
Percent non-insects
Pearson's
0.504
0.124
0.668
0.542
0.574
0.457
-0.398
-0.382
-0.517
-0.434
0.326
-0.407
0.563
0.418
0.577
-0.570
0.315
0.677
0.821
0.572
-0.296
-0.386
0.045
-0.284
-0.278
0.004
-0.578
-0.542
0.310
-0.409
Spearman's
0.367
0.017
0.502
0.502
0.639
0.408
-0.183
-0.200
-0.500
-0.500
0.408
-0.548
0.650
0.200
0.483
-0.600
0.026
0.817
0.783
0.417
-0.077
-0.251
0.114
-0.380
-0.358
0.196
-0.407
-0.435
0.321
-0.424
Kendall's
0.222
-0.029
0.366
0.354
0.559
0.373
-0.111
-0.167
-0.400
-0.400
0.309
-0.357
0.444
0.222
0.278
-0.444
0.000
0.611
0.556
0.278
-0.090
-0.217
0.093
-0.304
-0.300
0.118
-0.319
-0.304
0.261
-0.261
HBI
Pearson's
0.798
-0.290
0.669
0.691
0.042
0.504
-0.891
-0.889
-0.941
-0.947
0.126
-0.267
0.384
0.164
0.774
-0.565
0.053
0.616
0.803
0.527
-0.397
-0.746
-0.346
0.006
0.103
-0.513
-0.656
-0.498
-0.126
-0.670
Spearman's
0.650
-0.253
0.335
0.570
0.091
0.398
-0.617
-0.650
-0.300
-0.300
0.259
-0.548
0.533
0.267
0.700
-0.500
-0.148
0.733
0.783
0.533
-0.504
-0.719
-0.332
-0.380
-0.055
-0.494
-0.627
-0.705
-0.330
-0.407
Kendall's
0.444
-0.203
0.254
0.471
0.043
0.298
-0.444
-0.500
-0.200
-0.200
0.206
-0.357
0.333
0.222
0.500
-0.333
-0.122
0.500
0.556
0.389
-0.389
-0.588
-0.217
-0.304
-0.033
-0.354
-0.493
-0.548
-0.196
-0.319
Cells have been flagged (highlighted) with values greater or less than 0.7.
-------
APPENDIX I
SPECIES SENSITIVITY DISTRIBUTIONS (S-R from elsewhere)
Figure 1-1. SSD - Baseflow - Invertebrate - Arsenic
Figure 1-2. SSD - Baseflow - Chordate - Arsenic
Figure 1-3. SSD - Stormflow - Invertebrate - Cadmium
Figure 1-4. SSD - Stormflow - Chordate - Cadmium
Figure 1-5. SSD - Baseflow - Invertebrate - Chromium
Figure 1-6. SSD - Baseflow - Chordate - Chromium
Figure 1-7. SSD - Stormflow - Invertebrate - Copper
Figure 1-8. SSD - Stormflow - Chordate - Copper
Figure 1-9. SSD - Baseflow - Invertebrate - Copper
Figure I-10. SSD - Baseflow - Chordate - Copper
Figure 1-11. SSD - Stormflow - Invertebrate - Nickel
Figure 1-12. SSD - Stormflow - Chordate - Nickel
Figure 1-13. SSD - Baseflow - Invertebrate - Nickel
Figure 1-14. SSD - Baseflow - Chordate - Nickel
Figure 1-15. SSD - Stormflow - Invertebrate - Zinc
Figure 1-16. SSD - Stormflow - Chordate - Zinc
Figure 1-17. SSD - Baseflow - Invertebrate - Zinc
Figure 1-18. SSD - Baseflow - Chordate - Zinc
Figure notes: CCC - criterion continuous concentration (chronic)
CMC - criteria maximum concentration (acute)
(CCC and CMC source: US EPA, 1986b)
1-1
-------
o
c
o
t
o
Q.
o
CJ
o
OJ
c
o
-D
OJ
OJ
o
sswwswggQ
SSD
0 LC50
§> LCMn 2. 274
d concentration
OJ
o
_C50c
.C509
.C509
Obsen
o
o
o
CL.
m
EPT impairment @ LCMn 2.274
EPT impairment® LCN .415
mtral tendancy
>% upper confidence interval
5% lower confidence interval
ation
Q x
/ 0 /
/ 0 /
0 ^ '
/'' ° ,-' 7
o
0.0001 0.001 0.01 0.1 1 10 100 10C
Concentration, mg/L
Figure 1-1. SSD - Baseflow - Invertebrate - Arsenic
to
Q)
Q.
'o
C
O
r
E
Q.
n -
^
CJ
i
CO
s
8
I
m
0
-———SSD LC
ccn i r
0 LC50 C
l@ LCMn 2. 274
>ed concentratio
0)
s
o
',50 cen
!50 959
50 959
bserva
o
o
o
LU
:ral tendency
> upper confidence interval
ion ,'
O
o
/ o * /
/ 0 / /
,' / 0 /
/ o /
/ ' 0 /
o ,
X v'
It , * -^
0.0001
0.001
0.01
0.1 1
Concentration, mg/L
10
100
1000
Figure 1-2. SSD - Baseflow - Chordate - Arsenic
1-2
-------
1
ft ft
u. o
to
0)
H OR
cu 0.6
5
c
o
r
o. 04
O
£
ft 9
U. L.
n
LO
CJ
c
o
CO
c
OJ
c
0
OJ
£
0
CJ
^
CJ
<
CL
LU
O
X' O s ' ^^^
X o, •' ^
/ *' c\
*'""- ^
/ ' fc^ /
/ 0 /
/ f*
/ o/
/ r" /
/ J /
EPT impairment @ LCN .415 / ° /
/ o /* V
/'' °X /7
/ OA;S / -"SSD LC50 central tendency
, ' / i>i>L) LU50 957o upper confidence interval
O , /
/ SSD LC50 95% lower confidence interval
-1° ^ O LC50 Observation
O
0.0001
0.001
0.01
0.1 1
Concentration, mg/L
10
Figure 1-3. SSD - Stormflow - Invertebrate - Cadmium
0.8
'!
o
c
o
t
o
Q.
o
0.6
0.4
0.2
0.0001
0.001
0.01
0.1 1
Concentration, mg/L
10
Figure 1-4. SSD - Stormflow - Chordate - Cadmium
100
1000
o
©
C
._§
0)
0
OJ
1
0
EPA CMC
O
O
0 LC50 Observation 0
0
o
0
0.*
* 0
o
o
vo
o
100
1000
1-3
-------
0.8
0.6
o
r
0.4
0.2
CNI
CNI
@LCMn
o
;oncentrat
OJ
1
0
EPT impairment @ LCMn 2
EPT impairment @ LCN .
LT>
LI
@LCN .
0
concentra
T3
OJ
OJ
O
274
(15
O
' ' s ^^
• SSD LC50 central tendency ' o ' /
SSD LC50 95% lower confidence interval / ° i "
O LC50 Observation / :••'
/ Qv
/ _.<:'•• o x
/ •' o
o /
x' » /
/ 1
^' O it /
-^ «:-"' /^
-^ o
0.0001
0.001
0.01
0.1 1
Concentration, mg/L
10
100
Figure 1-5. SSD - Baseflow - Invertebrate - Chromium
Concentration, mg/L
Figure 1-6. SSD - Baseflow - Chordate - Chromium
1000
to
,0)
(/)
M—
o
c
o
o
o
ol
CNI
C
CJ
c
.0
CO
OJ
o
o
I
0)
o
o
d concentration (
observe
O
6
o ,
, o i' ,
' 1
I l< I
1 * i
1 ok
; 1 /
•SSD LC50 central tendency / Q K 1
ccn i r-cr, nco/ f^ • t I ' •*" /
SSD LC50 95% lower confidence interval ' 0 '
O LC50 Observation , /
/ 0 '
/ /°
0.0001 0.001 0.01 0.1 1 10 100 10
1-4
-------
0.8
'I
O
c
o
r
o
Q.
o
0.6
0.4
0.2
to
CO
CO
a:
c
o
CO
c
OJ
c
0
T3
OJ
£
.a
0
EPT impairment @ LCN .41 5
/'
EPA CMC
'
0
CJ
©
ved concentratio
OJ
0
Q. 0.6-
'o
c
o
r
|0.4-
Q.
n 9
u.z ~
to
CT>
CD
a:
©
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0
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o
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0
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<
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5
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©
0
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O
0
o - -
,*
o
9^
/ /
^
*l 0
^ 0
,
O !
' o
0 /
9'
Q _/ -•""•""'- SSD LC50 central tendency
,' * ooU LOOU yo /o upper connoence interval
SSD LC50 95% lower confidence interval
o
O LC50 Observation
o
i i i i i i
0.0001 0.001 0.01 0.1 1 10 100 10
Concentration, mg/L
Figure 1-8. SSD - Stormflow - Chordate - Copper
1-5
-------
0.8
'I
(/)
•5
c
r
o
0.6
0.4
0.2
£
CNI
CNI
c
CJ
©
O
1
c
OJ
0
OJ
£
Si
_Q
0
EPT impairment @
CJ
CJ
CJ
CL
LU
LCMn 2.274
^
o
o
^
, -^ ,-"^
/ A>
,*' o /
/ t o
o /
0
1
o • /
/ o
-/ -0- -J ' /
'' 0 t /
/ ° /
/ ° • 'SSD LC50 central tendency
/ O / oon r*cf\ niro/ fj
/ SSD LC50 95 /o upper confidence interval
9'" / SSD LC50 95% lower confidence interval
,''o o LC50 Observation
' /
0
0.0001
0.001
0.01
0.1 1
Concentration, mg/L
10
100
1000
Figure 1-9. SSD - Baseflow - Invertebrate - Copper
1
0.8
t/)
0
I 0.6
'o
c
o
t
i. 04
o
n 9
u. z ~
r^.
i
o
©
O
CO
c
OJ
c
T3
OJ
OJ
^2
o
CJ
CJ
CJ
/ ,MaMama.o!55Q |_C50 central tendency
, "o
/ SSD LC50 95 /o upper confidence interval
^ SSD LC50 95% lower confidence interval
/:o O LC50 Observation
1 o x
o
i i i i i i
0.0001 0.001 0.01 0.1 1 10 100 10
Concentration, mg/L
Figure 1-10. SSD - Baseflow - Chordate - Copper
1-6
-------
0.8
w>
0)
1 °'6
0
c
o
§. 0.4
O
Q.
0.2
n -
s=
g
©
o
E
c
OJ
c
o
T3
^
OJ
1
EPT impairment @ LCN .41 5
'SSD LC50 central tend
SSD LC50 95% lower c
O LC50 Observation
o
E
O
CL
;ncy
onfidence interval
anfidence interval
O ,
o
6
t /
/ "
! h' i
1 J3 /
1 •£__/
-o '
/ ..o
6*
0.0001
0.001
0.01
0.1 1
Concentration, mg/L
10
100
1000
Figure 1-11. SSD - Stormflow - Invertebrate - Nickel
1
0 8
0)
£o.e-
•5
c
o
t
i. 04
o
0.2 -
£
§
.0
c
OJ
o
c
8
•a
£
(/I
o
"""""""-SSD LC50 central t
SSD LC50 95% upf
SSD LC50 95% low
O LC50 Observation
o
o
CL
LU
mdency
Der confidence interval
er confidence interval
0 X
/ 0 /
!"• /
1 ^
'OK /
/ £ /
I f '
1 a i
i // /
,' ° f 1
1 K I
1 1
/ O/ /
/ f
/
O '
/
/ J'J /
/ /
i i i i i
0.0001 0.001 0.01 0.1 1 10 100 10(
Concentration, mg/L
Figure 1-12. SSD - Stormflow - Chordate - Nickel
1-7
-------
'I
o
c
o
r
o
Q.
O
1
0
.o
c
.D
4
o
.L
to
o>
CO
CD
QL
©
o
2
c
OJ
c
0
-D
OJ
OJ
0
LT>
^
CJ
©
1
CO
c
s
i
s
9
tf>
_Q
O
:SSD LC
oor\ i /i
ooU l_<
SSD U
O LC50 (^
u
o
Q_
m
EPT impairment @
EPT impairment®
/- '
^50 central tendency / ' O .^
J50 95% upper confidence interval / ,/ /
?50 95% lower confidence interval / o /•
Observation xx ^ /
/ .^ /
/ O / /
/' f /
i -)b
/ .>' /
/ .>/"
,CMn 2.274 / ':;' ° /
LCN .415 /' ' /
/ '*~ ° /
/' // 0 '
I/
o ,-."•''" /
i i i i i i i
0.0001 0.001 0.01 0.1 1 10 100 10C
'I 0.6
Concentration, mg/L
Figure 1-13. SSD - Baseflow - Invertebrate - Nickel
1
Q
C
.D
4
2
CO
CD
c±
©
1
c
o
c
O
OJ
OJ
o
S
CJ
a
O
c
OJ
o
o
"D
>
OJ
_^
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LO
CJ
1
©
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CO
c
1
0
o
T3
OJ
OJ
Wl
o
CJ
CJ
CJ
CL
:::::::::::1SSD LC50 central
QQPl 1 ^Rfl QRO/ nn
ooU LL-oU yo /o Up
- - SSD LC50 95% lo\
O LC50 Observation
• .,
; /
O ,;< ;
T
/' Q-" ''
; ;' '
,' _} '
/ « /
/ /,;'
/ •'•'' /
/ l{i';' /
/ j"o
1 s '
/' / /
endency ' .v° /
/ ft 1
per confidence interval , if
\ier confidence interval O ," /
i i i i i i
0.0001 0.001 0.01 0.1 1 10 100 10
Concentration, mg/L
Figure 1-14. SSD - Baseflow - Chordate - Nickel
1-8
-------
w>
0)
S OR
s.
•5
c
o
r
Q. 04
O
£
CD
CL.
©
o
£
c
OJ
o
c
8
-a
OJ
OJ
1
EPT impairment @ LCN .41 5
LC50 central tendency
SSD LC50 95% lower confidenc
O LC50 Observation
EPA CMC
e interval
: interval
" O
© 0 '
1
§ ,° .
o j O
-Q
a; O
1 / °
0
0
o /
p
p '
p ,'
o
0
p
o
.•'o
p
0.0001 0.001 0.01 0.1 1 10 100 10C
Concentration, mg/L
Figure 1-15. SSD - Stormflow - Invertebrate - Zinc
w>
3>
Q. U'b
(/)
14-
o
c
o
t
o
o
£
5
0>
M
CD
cc
©
.1
i
c
OJ
£
8
•g
fe
5
O
LC50 central tendency
SSD LC50 95% lower confidenc
O LC50 Observation
EPA CMC
e interval
: interval
O
^ o
y /
© - <*
1 0 /
S I.I
a I O
1 / ^ /
S / f /'
/ /O /
/ /«/
/ /•' °/
/ /•/
/
• ° • /
°-'' 7
0
o
0.0001 0.001 0.01 0.1 1 10 100 10
Concentration, mg/L
Figure 1-16. SSD - Stormflow - Chordate - Zinc
1-9
-------
to
Q)
"5
c
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APPENDIX J
SPECIFIC CONDUCTIVITY DATA FROM OTHER STATES
Total taxa per sample
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Reference Sites
Figure J-2. Kentucky mined site Ephemeroptera (mayfly) abundance versus specific conductivity
Source: Pond (2004).
-------
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